Diagnostics

13 pages, 1492 KB

Open AccessArticle

Association Between Systemic Inflammatory Response Biomarkers and Disease Activity in Systemic Lupus Erythematosus: A Multi-Center Retrospective Study

by Tao Ma, Jiale Zhang, Jie Kong, Hua Wei, Huaixia Hu, Yinshan Zang, Hongjun He, Wenwen Wang, Xiaoxiang Chen and Yingying Gao

Diagnostics 2026, 16(12), 1944; https://doi.org/10.3390/diagnostics16121944 - 22 Jun 2026

Viewed by 221

Abstract

Objective: To evaluate the association of routine complete blood count (CBC)-derived inflammatory biomarkers, including neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), platelet-to-lymphocyte ratio (PLR), and systemic inflammation response index (SIRI), with disease activity and exploratory neuropsychiatric risk stratification in patients with systemic lupus [...] Read more.

Objective: To evaluate the association of routine complete blood count (CBC)-derived inflammatory biomarkers, including neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), platelet-to-lymphocyte ratio (PLR), and systemic inflammation response index (SIRI), with disease activity and exploratory neuropsychiatric risk stratification in patients with systemic lupus erythematosus (SLE). Methods: In this multi-center retrospective study, 579 SLE patients and 282 healthy controls (HCs) were recruited from five clinical centers between 2018 and 2025. NLR, MLR, PLR, and SIRI were calculated from routine CBC parameters. Disease activity was assessed using the SLE Disease Activity Index 2000 (SLEDAI-2K), with high activity defined as SLEDAI-2K ≥ 10. The comparison between SLE patients and HCs was performed as an exploratory descriptive analysis to characterize systemic inflammatory profiles, whereas the primary analyses focused on associations with disease activity and NPSLE-related risk stratification. Results: SLE patients exhibited significantly higher levels of SIRI, NLR, PLR, and MLR compared to HCs (all p < 0.001). In this exploratory comparison, MLR showed the largest area under the curve for distinguishing SLE patients from HCs (AUC: 0.849, Cut-off: 0.263). In regression analyses, MLR, NLR, PLR, and SIRI were positively associated with SLEDAI-2K score. In multivariable linear regression analysis, MLR was associated with a higher SLEDAI-2K score (B = 4.600, 95% CI: 2.039–7.160, p < 0.001). In patients with available neuropsychiatric data, MLR, NLR, and SIRI were higher in patients with NPSLE than in those with non-NPSLE, whereas PLR showed no significant difference. SIRI showed modest exploratory discriminatory ability for NPSLE and may provide auxiliary information for NPSLE risk stratification (AUC: 0.710, p < 0.001, Cut-off: 1.438). Conclusions: Routine CBC-derived inflammatory biomarkers, particularly MLR, NLR, and SIRI, are associated with SLE disease activity and may serve as accessible, low-cost adjunctive tools for rapid clinical assessment. SIRI may provide additional auxiliary information for identifying patients at higher risk of neuropsychiatric involvement. However, these biomarkers should be interpreted as complementary screening or risk-stratification tools rather than substitutes for established disease activity indices or organ-specific evaluations. Further prospective studies are warranted to validate their clinical utility. Full article

(This article belongs to the Section Clinical Diagnosis and Prognosis)

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15 pages, 1776 KB

Open AccessReview

Vertebrogenic Low Back Pain and Basivertebral Nerve Ablation: A Review of Mechanisms, Imaging-Driven Selection, and Clinical Outcomes

by Daniele G. Romano, Ludovica Liguori, Giulia Pacella, Raffaele Natella, Federico Bruno, Francesco Arrigoni, Michela Bruno, Stefano Piemonte, Michele Fischetti, Mario Brunese and Marcello Zappia

Diagnostics 2026, 16(12), 1943; https://doi.org/10.3390/diagnostics16121943 - 22 Jun 2026

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Abstract

Background: Vertebrogenic low back pain (LBP) is a distinct subtype of chronic LBP (cLBP) arising from nociceptive sensitization of the basivertebral nerve (BVN) within pathologically altered vertebral endplates. Modic type 1 and type 2 changes on MRI are primary imaging biomarkers for patient [...] Read more.

Background: Vertebrogenic low back pain (LBP) is a distinct subtype of chronic LBP (cLBP) arising from nociceptive sensitization of the basivertebral nerve (BVN) within pathologically altered vertebral endplates. Modic type 1 and type 2 changes on MRI are primary imaging biomarkers for patient selection. Basivertebral nerve ablation (BVNA), a minimally invasive intraosseous radiofrequency procedure, has emerged as a targeted treatment for this condition. This narrative review aims to synthesize current evidence on the pathophysiology of vertebrogenic LBP, patient selection criteria, procedural outcomes, safety profile, and cost-effectiveness of BVNA. Methods: We conducted this narrative review of the literature, encompassing randomized controlled trials (including the SMART and INTRACEPT studies), prospective registries, and real-world cohort studies evaluating BVNA for vertebrogenic LBP. Clinical and imaging-based selection criteria, procedural techniques, outcome measures, adverse events, opioid utilization, and healthcare utilization data were examined. Results: Evidence demonstrates consistent and durable reductions in pain and disability following BVNA, with a favorable safety profile. Complication rates are low, with vertebral compression fracture and procedure-related radicular pain reported as the most frequent adverse events. BVNA is associated with reduced opioid consumption and decreased overall healthcare utilization. Moreover, emerging data suggest efficacy beyond originally defined inclusion criteria, including cases of osteoporosis, multilevel Modic changes, adult spinal deformity, and complex comorbid presentations. Conclusions: BVNA represents an effective and safe treatment option within the multimodal management of vertebrogenic LBP. Current evidence supports a gradual expansion of procedural indications, with implications for healthcare resource optimization and opioid stewardship. Full article

(This article belongs to the Special Issue Advances in the Diagnosis and Management of Low-Back Pain)

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14 pages, 2025 KB

Open AccessCase Report

Multivalvular Carcinoid Heart Disease: The Role of Echocardiography in Diagnosis and Selection for Heterotopic Bicaval Valve Implantation

by Bianca Corrêa Rocha de Mello, Ana Clara Pierote Rodrigues Vasconcelos, Mariana Ubaldo Barbosa Paiva, Mateus Veloso e Silva, Nattália de Oliveira Maciel, Priscila Ribeiro de Andrade, Rodolfo Deusdará and Maria Estefânia Bosco Otto

Diagnostics 2026, 16(12), 1942; https://doi.org/10.3390/diagnostics16121942 - 22 Jun 2026

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Abstract

Background and Clinical Significance: Carcinoid heart disease (CHD) is an uncommon valvular manifestation of neuroendocrine tumours, usually affecting right-sided cardiac valves. Left-sided involvement is rare and is generally associated with bronchopulmonary carcinoid, right-to-left shunting, or markedly elevated circulating vasoactive substances. Therapeutic decision-making [...] Read more.

Background and Clinical Significance: Carcinoid heart disease (CHD) is an uncommon valvular manifestation of neuroendocrine tumours, usually affecting right-sided cardiac valves. Left-sided involvement is rare and is generally associated with bronchopulmonary carcinoid, right-to-left shunting, or markedly elevated circulating vasoactive substances. Therapeutic decision-making is particularly challenging in advanced disease when severe tricuspid regurgitation occurs in patients at prohibitive surgical risk. Case Presentation: We report the case of a 61-year-old male patient with progressive dyspnoea, abdominal distension, lower-limb oedema, facial flushing, and 15 kg of unintentional weight loss. Transthoracic and transoesophageal echocardiography demonstrated torrential tricuspid regurgitation caused by thickened, retracted, and immobile leaflets, with additional mitral and aortic valve involvement, raising strong suspicion of CHD. An agitated-saline contrast study demonstrated delayed right-to-left shunting without patent foramen ovale, suggesting an extracardiac, likely intrapulmonary, shunt. Somatostatin receptor PET/CT identified a pancreatic lesion with metastatic disease, and bone marrow biopsy confirmed neuroendocrine tumour infiltration. Owing to prohibitive surgical risk, as reflected by a Tricuspid Regurgitation Impact Score (TRI-SCORE) with an estimated in-hospital mortality of 65%, unfavourable tricuspid anatomy for repair, and refractory venous congestion, heterotopic bicaval valve implantation was performed (TricValve system -P&F). Discussion: This case highlights the role of echocardiography in recognising the characteristic phenotype of CHD, detecting occult right-to-left shunting, and supporting selection of a palliative transcatheter intervention. It also illustrates the value of a multimodality diagnostic strategy integrating echocardiography, functional oncological imaging, and histopathology in tumour-related cardiac disease. Conclusions: In selected inoperable patients with advanced carcinoid-related tricuspid regurgitation, heterotopic bicaval valve implantation may represent a feasible strategy for reducing venous congestion and improving functional status. Full article

(This article belongs to the Special Issue Innovations in Diagnosis and Management of Cardiovascular Diseases)

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25 pages, 4672 KB

Open AccessArticle

Data-Efficient and Explainable Multimodal Survival Prediction in NSCLC Using Deep Image Embeddings, Clinical Variables, and Gradient-Boosted Trees

by Sevim Sahin and Adil Gursel Karacor

Diagnostics 2026, 16(12), 1941; https://doi.org/10.3390/diagnostics16121941 - 22 Jun 2026

Viewed by 302

Abstract

Background/Objectives: Survival prediction in non-small cell lung cancer (NSCLC) remains challenging, particularly in limited-sample settings where end-to-end deep learning models may suffer from limited generalization. This study aimed to develop a data-efficient, multimodal, and explainable framework integrating computed tomography (CT)-derived imaging information with [...] Read more.

Background/Objectives: Survival prediction in non-small cell lung cancer (NSCLC) remains challenging, particularly in limited-sample settings where end-to-end deep learning models may suffer from limited generalization. This study aimed to develop a data-efficient, multimodal, and explainable framework integrating computed tomography (CT)-derived imaging information with clinical variables for NSCLC survival prediction. Methods: CT images, tumor segmentations, and clinical data from the publicly available NSCLC Radiomics (LUNG1) dataset (377 patients) were used. Tumor-focused regions were extracted using segmentation masks, and pretrained RadImageNet-InceptionV3 embeddings were obtained from the largest tumor-containing slice and neighboring-slice summaries. Deep imaging embeddings, engineered imaging features, and clinical variables were fused into a unified tabular representation. To improve robustness under limited-sample conditions, feature blocks were compressed using principal component analysis. CatBoost, XGBoost, and LightGBM models were trained on a development set and evaluated on a strictly held-out final validation set. Results: In three-class survival stratification, assigning censored/non-event patients to the upper survival group produced the strongest ordinal prognostic performance. Under the EX_PLUS_NON_EX_TOP setting, CatBoost achieved the best holdout score-based class C-index of 0.655. In continuous survival regression, LightGBM achieved the best holdout event-patient C-index of 0.576. Clinical variables provided the dominant prognostic signal, while compact deep image embeddings contributed complementary information, particularly in separating short- and long-survival groups. SHAP analysis confirmed contributions from both clinical and image-derived features. Conclusions: The proposed framework provides a proof-of-concept demonstration of a data-efficient and explainable image-to-tabular approach for NSCLC survival prediction under strict internal holdout validation. The results suggest that pretrained CT embeddings, clinical variables, gradient-boosted trees, and SHAP-based interpretation can be combined in a feasible, limited-sample survival modeling pipeline, while external validation remains necessary before clinical translation. Full article

(This article belongs to the Section Machine Learning and Artificial Intelligence in Diagnostics)

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4 pages, 2338 KB

Open AccessInteresting Images

Anomalous Left Coronary Artery from the Pulmonary Artery: Cinematic Volume Rendering Technique for Enhanced Anatomic Visualization

by Shuo Liang, Kun Zhang and Hong Zhang

Diagnostics 2026, 16(12), 1940; https://doi.org/10.3390/diagnostics16121940 - 22 Jun 2026

Viewed by 190

Abstract

Anomalous left coronary artery from the pulmonary artery (ALCAPA) is a rare congenital anomaly with exceptional survival into adulthood. We present a 66-year-old woman with chest and back pain in whom ALCAPA was diagnosed using coronary computed tomography angiography (CCTA) with curved planar [...] Read more.

Anomalous left coronary artery from the pulmonary artery (ALCAPA) is a rare congenital anomaly with exceptional survival into adulthood. We present a 66-year-old woman with chest and back pain in whom ALCAPA was diagnosed using coronary computed tomography angiography (CCTA) with curved planar reformation and cinematic volume rendering technique (cVRT). Photorealistic three-dimensional reconstruction provided complementary three-dimensional visualization that may facilitate anatomic understanding and communication of the anomalous origin. Conservative management was adopted given the patient’s age and well-developed collateral circulation. This case underscores the value of advanced CCTA visualization in diagnosing rare coronary anomalies in elderly patients. Full article

(This article belongs to the Section Medical Imaging and Theranostics)

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31 pages, 5802 KB

Open AccessArticle

Automated Aqueductal CSF Flow Analysis in Spontaneous Intracranial Hypotension: Hemodynamic Quantification and Exploratory Waveform Morphology Assessment Using Cine PC-MRI

by Yi-Jhe Huang, Wen-Hsien Chen, Hung-Chieh Chen and Da-Chuan Cheng

Diagnostics 2026, 16(12), 1939; https://doi.org/10.3390/diagnostics16121939 - 22 Jun 2026

Viewed by 257

Abstract

Background/Objectives: Spontaneous intracranial hypotension (SIH) is caused by spinal cerebrospinal fluid (CSF) leakage and is typically diagnosed by clinical presentation and characteristic MRI signs; however, objective tools for monitoring physiological changes and treatment response remain limited. Cine phase-contrast MRI (PC-MRI) enables noninvasive quantification [...] Read more.

Background/Objectives: Spontaneous intracranial hypotension (SIH) is caused by spinal cerebrospinal fluid (CSF) leakage and is typically diagnosed by clinical presentation and characteristic MRI signs; however, objective tools for monitoring physiological changes and treatment response remain limited. Cine phase-contrast MRI (PC-MRI) enables noninvasive quantification of aqueductal CSF dynamics, yet reliable analysis is challenging since the cerebral aqueduct is extremely small and susceptible to low contrast, partial volume effects, and ROI-dependent measurement variability—particularly in SIH where CSF pulsatility is often reduced. Methods: We propose an end-to-end automated framework that integrates (1) a cascade localization–segmentation strategy, consisting of Tiny YOLOv4 detection followed by MultiResUNet segmentation on a YOLOv4-derived cropped ROI; (2) physiology-informed pulsatility-based segmentation (PUBS) to refine anatomical masks into functional flow ROIs; and (3) one-dimensional convolutional neural networks (1D-CNNs) to extract exploratory waveform morphology features from 32-phase cardiac-cycle velocity waveforms. The study includes 39 participants, yielding 59 cine PC-MRI examinations: 11 controls, 28 Pre-treatment SIH scans and 20 Post-treatment Recovery scans. Results: The cascade model significantly improves segmentation robustness compared with a full-image baseline, achieving higher Dice scores and markedly lower boundary errors across cohorts (e.g., Pre-treatment SIH HD95: 1.66 ± 0.74 px vs. 15.37 ± 44.98 px). PUBS refinement reduces quantification deviation from expert manual references in SIH (mean relative error: 7.4% to 5.6%) and improves diagnostic performance for multiple hemodynamic parameters (e.g., downward mean flow AUC: 0.747 to 0.792). For waveform morphology analysis, the end-to-end 1D-CNN classifier was evaluated using repeated-seed participant-level grouped LOOCV. The repeated-seed ensemble prediction showed modest out-of-sample discrimination between Normal controls and Pre-treatment SIH scans, with an AUC of 0.646, a bootstrap 95% confidence interval of 0.455–0.826, and a permutation-test p-value of 0.072. Separately, exploratory analysis of the final baseline-trained 1D-CNN latent space showed marked, apparent Normal-versus-SIH separability and an intermediate recovery distribution in PCA space, suggesting that aqueductal waveform morphology may encode SIH-related physiological information. Conclusions: These findings suggest that SIH-related information may be reflected not only in flow magnitude but also in aqueductal CSF waveform morphology. However, the modest and statistically non-significant out-of-sample performance of the end-to-end 1D-CNN classifier indicates that morphology-based AI features should currently be regarded as exploratory biomarker candidates rather than validated stand-alone diagnostic tools. Larger independent cohorts are required to confirm their reproducibility, physiological meaning, and clinical utility. Full article

(This article belongs to the Special Issue Imaging of the Future: From the Standardisation of Diagnostic Processes to Artificial Intelligence)

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21 pages, 1302 KB

Open AccessArticle

Simplification of a Three-Constant Intraocular Lens Calculation Formula to a Single-Constant Approach: The Haigis Formula

by Achim Langenbucher, Nóra Szentmáry, Alan Cayless, Benjamin Fassbind, Iwan Bolzern, Peter Hoffmann and Jascha Armin Wendelstein

Diagnostics 2026, 16(12), 1938; https://doi.org/10.3390/diagnostics16121938 - 22 Jun 2026

Viewed by 235

Abstract

Background/Objectives: To derive and validate a simplified modification of the Haigis intraocular lens (IOL) power calculation formula by reducing the three-constant effective lens position (ELP) model to a single constant while introducing an optimized keratometer index and axial length correction. Methods: In this [...] Read more.

Background/Objectives: To derive and validate a simplified modification of the Haigis intraocular lens (IOL) power calculation formula by reducing the three-constant effective lens position (ELP) model to a single constant while introducing an optimized keratometer index and axial length correction. Methods: In this retrospective study, a large multicentric dataset (Dataset 1; 22,466 eyes, 113 IOL models) was used to optimize the Haigis constant triplet and keratometer index using nonlinear programming with Cooke’s axial length correction. A second independent dataset (Dataset 2; 3181 eyes, six IOL models) was used for cross-validation. Three approaches were compared: classical Haigis, modified triplet, and two single-constant models acting on IOL power (H1) or ELP (H2). Results: The optimized keratometer index (1.3296 ± 0.0003) was significantly lower than the classical value, indicating systematic overestimation of corneal power. Modified triplet and single-constant approaches achieved comparable or slightly lower prediction errors than the classical formula. The H1 approach showed marginally superior performance. Bootstrapping confirmed parameter stability. Conclusions: A single-constant modification of the Haigis formula incorporating an optimized keratometer index and axial length correction maintains prediction accuracy while simplifying clinical implementation. Full article

(This article belongs to the Special Issue Eye Disease: Diagnosis, Management, and Prognosis—2nd Edition)

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25 pages, 2353 KB

Open AccessArticle

A Multitask Time–Frequency Deep Learning Approach for Anesthesia Depth Monitoring and Transition Prediction

by Saliha Kevser Kavuncu, Mehmet Yalvac and Alper Basturk

Diagnostics 2026, 16(12), 1937; https://doi.org/10.3390/diagnostics16121937 - 22 Jun 2026

Viewed by 247

Abstract

Background: Electroencephalography (EEG) signals are widely used for monitoring anesthesia depth during surgery. Current commercial indicators are largely closed-source and may reflect dynamic changes with some delay. Methods: This study proposes a multitask deep learning model for continuous Bispectral Index (BIS) estimation, binary [...] Read more.

Background: Electroencephalography (EEG) signals are widely used for monitoring anesthesia depth during surgery. Current commercial indicators are largely closed-source and may reflect dynamic changes with some delay. Methods: This study proposes a multitask deep learning model for continuous Bispectral Index (BIS) estimation, binary anesthesia-state classification, and prediction of transitions toward light anesthesia at different time intervals. Dual-channel EEG signals from 5471 surgical cases in the VitalDB dataset were divided into 60 s windows. Short-Time Fourier Transform (STFT) captured instantaneous frequency changes to transform the signal into a two-dimensional map. A ResNet-SE architecture incorporating Squeeze-and-Excitation blocks was used to identify EEG features associated with anesthesia depth. Results: A Mean Absolute Error of 3.27 and a Root Mean Square Error of 5.48 were obtained in anesthesia depth estimation. Light anesthesia classification achieved an AUC of 0.99 on the internal test set. Conclusions: The proposed multitask model enables the assessment of anesthesia depth and transitions toward light anesthesia using EEG signals. Full article

(This article belongs to the Section Machine Learning and Artificial Intelligence in Diagnostics)

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17 pages, 2302 KB

Open AccessReview

Early Rectal Cancer: Diagnostic Challenges and the Role of Endoscopic Intermuscular Dissection Within the Therapeutic Algorithm

by Rossella Maresca, Giulio Calabrese, Franziska Deutschbein, Valentina Blasi, Tommaso Schepis, Daniele Salvi, Silvia Pecere, Paola Cesaro, Cristiano Spada, Sandro Sferrazza and Federico Barbaro

Diagnostics 2026, 16(12), 1936; https://doi.org/10.3390/diagnostics16121936 - 22 Jun 2026

Viewed by 449

Abstract

Early rectal cancer represents a challenging setting in which accurate locoregional staging is essential to guide appropriate treatment. Current diagnostic strategies primarily include magnetic resonance imaging (MRI) and endoscopic ultrasound (EUS). However, both modalities show significant limitations in early-stage disease, particularly in T [...] Read more.

Early rectal cancer represents a challenging setting in which accurate locoregional staging is essential to guide appropriate treatment. Current diagnostic strategies primarily include magnetic resonance imaging (MRI) and endoscopic ultrasound (EUS). However, both modalities show significant limitations in early-stage disease, particularly in T staging. This diagnostic gap impacts therapeutic decision-making, particularly in patients with lesions suggestive of deep submucosal invasion. In these cases, endoscopic submucosal dissection (ESD) may be insufficient to achieve adequate vertical negative margins, whereas radical surgery is associated with considerable morbidity and potential impairment of quality of life. In this gray zone, endoscopic intermuscular dissection (EID) has recently emerged as a novel therapeutic approach designed to overcome the limitations of standard endoscopic resection. By enabling dissection within the deeper intermuscular plane, it can achieve curative resections while preserving rectal wall integrity. This narrative review aims to explore the current diagnostic gaps in early rectal cancer and to define the potential role of EID within the current therapeutic algorithm. Full article

(This article belongs to the Special Issue Advances in Gastrointestinal Endoscopy: From Diagnosis to Therapy)

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15 pages, 8052 KB

Open AccessInteresting Images

Oncocytic Adrenocortical Carcinoma with Somatic Pathogenic Variants of NF1 and TP53 Genes in a Young Adult Harboring a Germline Likely Pathogenic Variant in CEL Gene: From Hyperandrogenemia of Dual (Adrenal–Ovarian) Cause to Oocyte Preservation and Mitotane Initiation

by Mara Carsote, Augustin Dima, Oana-Claudia Sima, Ana-Maria Gheorghe, Mihai Costachescu, Elena-Emanuela Braha, Sorina Violeta Schipor, Dana Manda, Andrei Muresan, Anda Dumitrascu, Adrian Ciuche, Laura Dracea, Teodor Ionut Constantin and Dana Terzea

Diagnostics 2026, 16(12), 1935; https://doi.org/10.3390/diagnostics16121935 - 22 Jun 2026

Viewed by 247

Abstract

The oncocytic variant of adrenocortical carcinoma (OACC) represents an exceptional type of adrenal malignancy, with heterogenous presentation. Currently, the genetic and molecular spectrum remains an open matter. A 20-year-old adult was accidentally found with a 7.2 cm adrenal tumor and underwent an open [...] Read more.

The oncocytic variant of adrenocortical carcinoma (OACC) represents an exceptional type of adrenal malignancy, with heterogenous presentation. Currently, the genetic and molecular spectrum remains an open matter. A 20-year-old adult was accidentally found with a 7.2 cm adrenal tumor and underwent an open right adrenalectomy with OACC confirmation. Post-adrenalectomy positron emission tomography/computed tomography was negative. Immunohistochemistry was positive for calretin, inhibin, steroidogenic factor 1; Ki67 of 20%. Microsatellite instability was 7.61. Lin–Weiss–Bisceglia score showed 2 major criteria [mitoses 6/50 HPF + positive atypical mitoses], the reticuline algorithm (disrupted reticuline network + mitoses 6/50 HPF) was consistent for a malignant behavior, the Helsinki score was of 48. Next generation sequencing identified a likely pathogenic variant of CEL gene (heterozygote, c.539-2A>G) in peripheral blood and two pathogenic variants in the tumor: exon 48, NF1 gene [c.7159_7164del p.(N2387_F2388del)] and exon 6, TP53 gene [c.596delG p.(G199Efs*48)]. Polycystic ovary syndrome type A has been diagnosed as teenager with no phenotype change before the tumor detection. After surgery, oocyte retrieval and cryopreservation upon ovarian stimulation protocol (OSP) was performed before starting mitotane therapy. To the best of our knowledge, this is a novel genetic configuration in OACC with an impact on prognosis to be determined. Hyperandrogenemia stands on a dual source (potential CEL-driven insulin resistance for the ovary and OACC-originating for the adrenal glands). Also, this is the first case to receive OSP in OACC, noting that a tailored multidisciplinary management is mandatory. Full article

(This article belongs to the Special Issue State of the Art in the Diagnosis and Management of Endocrine Tumors)

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16 pages, 6673 KB

Open AccessArticle

Automated Segmentation of Diffuse and Multifocal Nerve Enlargement in Immune-Mediated Neuropathy Using Temporal Deep Learning on Continuous Ultrasound Scans

by Miho Akaza, Ryo Maeda, Tai Otani, Hirokazu Natsui, Tadashi Kanouchi and Yuki Sumi

Diagnostics 2026, 16(12), 1934; https://doi.org/10.3390/diagnostics16121934 - 22 Jun 2026

Viewed by 204

Abstract

Objectives: Peripheral nerve ultrasound is used to evaluate nerve enlargement in immune-mediated neuropathies; however, assessment can be challenging because the distribution and severity of nerve enlargement vary among patients and are often accompanied by indistinct nerve boundaries and heterogeneous echogenicity. Although deep [...] Read more.

Objectives: Peripheral nerve ultrasound is used to evaluate nerve enlargement in immune-mediated neuropathies; however, assessment can be challenging because the distribution and severity of nerve enlargement vary among patients and are often accompanied by indistinct nerve boundaries and heterogeneous echogenicity. Although deep learning-based segmentation has been reported, most studies have focused on limited regions or single anatomical sites, primarily in compressive neuropathies. This study aimed to evaluate the performance of temporal deep learning-based segmentation for assessing diffuse or focal nerve enlargement in immune-mediated neuropathies using continuous ultrasound scans. Methods: Twenty-five healthy participants and five patients with immune-mediated neuropathy and nerve enlargement were included. Continuous ultrasound scanning from the wrist to below the elbow was performed. A static DeepLabV3+ model and temporal models incorporating convolutional long short-term memory (ConvLSTM) or Temporal Mamba were constructed and compared. Results: In healthy participants, segmentation performance was comparable across models. In contrast, in patients with nerve enlargement, temporal models demonstrated higher Dice coefficients and reduced frame-to-frame variability. The ConvLSTM-based model showed the highest performance, with mean Dice coefficients ranging from 0.87 to 0.92. Conclusions: Temporal deep learning showed potential for nerve segmentation in selected cases with nerve enlargement associated with immune-mediated neuropathies. Temporal models achieved improved segmentation performance and reduced frame-to-frame variability in these preliminary cases. This approach may facilitate more consistent quantitative ultrasound evaluation and warrants further validation in larger cohorts. Full article

(This article belongs to the Section Machine Learning and Artificial Intelligence in Diagnostics)

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17 pages, 5066 KB

Open AccessArticle

BAP1 and PBRM1 Loss Is Associated with Aggressive Clinicopathological Features in Clear Cell Renal Cell Carcinoma: Prognostic Implications in a 10-Year Surgical Cohort

by Mario Daniel Tapia-Tapia, Daniel Sánchez-Zalabardo, Jorge Caño-Velasco, Marcos Torres-Roca, Sara Esparza-Alamanzón, María Rodríguez-Gómez, Eduardo Miraval-Wong, Jaione García-Martínez, Vanesa Ocon-Cruz, Felipe Villacampa-Aubá, Carmina Alejandra Muñoz-Bastidas, Daniel González-Padilla, Julián Sanz-Ortega and Bernardino Miñana-López

Diagnostics 2026, 16(12), 1933; https://doi.org/10.3390/diagnostics16121933 - 22 Jun 2026

Viewed by 233

Abstract

Background/Objectives: Clear cell renal cell carcinoma (ccRCC) is a biologically heterogeneous disease. Beyond VHL inactivation, alterations in chromatin remodeling genes BAP1 and PBRM1 define distinct tumor phenotypes with prognostic implications. We sought to characterize the clinicopathological features and oncological outcomes associated with [...] Read more.

Background/Objectives: Clear cell renal cell carcinoma (ccRCC) is a biologically heterogeneous disease. Beyond VHL inactivation, alterations in chromatin remodeling genes BAP1 and PBRM1 define distinct tumor phenotypes with prognostic implications. We sought to characterize the clinicopathological features and oncological outcomes associated with IHC-defined loss of these markers in a contemporary surgical cohort. Methods: We retrospectively analyzed 214 patients undergoing partial or radical nephrectomy for ccRCC (2010–2021). Loss of BAP1 and PBRM1 expression was assessed by automated immunohistochemistry. Tumors with retained expression were classified as wild-type and compared with those showing loss of at least one marker. Survival outcomes were evaluated using Kaplan–Meier analysis, multivariable Cox models, and Restricted Mean Survival Time (RMST). Results: IHC-defined loss was identified in 19 patients (8.9%): BAP1 in 12 (5.6%) and PBRM1 in 7 (3.3%). Tumors with IHC-defined loss showed more aggressive features, including larger size (7.7 vs. 4.7 cm; p = 0.009), higher necrosis (36.8% vs. 18.5%; p = 0.050), and more advanced stage (pT3–pT4: 47.4% vs. 16.4%; p < 0.001). Kaplan–Meier analysis demonstrated significantly worse survival outcomes in the IHC-loss group across all endpoints (p ≤ 0.011). RMST analysis at 60 months confirmed significantly worse outcomes across all endpoints (p ≤ 0.005). Conclusions: Loss of BAP1 or PBRM1 identifies a biologically aggressive ccRCC subset with worse oncological outcomes. IHC-based molecular profiling is a practical and accessible tool for risk stratification in surgically treated ccRCC. Full article

(This article belongs to the Special Issue Precision Diagnostics in Kidney Cancer)

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37 pages, 11390 KB

Open AccessReview

Human Papillomavirus Infection Across the Immunological Spectrum: Clinical Expression, Colposcopic Challenges, and Therapeutic Implications

by Antonio Braga, Gustavo Ribeiro Lima, Karine Mello Duvivier, Edward Araujo Júnior, Caroline Alves de Oliveira Martins, Isabel Cristina Chulvis do Val Guimarães and Susana Cristina Aidé Viviani Fialho

Diagnostics 2026, 16(12), 1932; https://doi.org/10.3390/diagnostics16121932 - 22 Jun 2026

Viewed by 606

Abstract

Human papillomavirus (HPV) infection is a major driver of anogenital disease and virus-related carcinogenesis. Although most infections resolve spontaneously, persistent infection with high-risk genotypes may progress to high-grade squamous intraepithelial lesions (HSILs) and cancer, particularly in the setting of impaired immune surveillance. Unlike [...] Read more.

Human papillomavirus (HPV) infection is a major driver of anogenital disease and virus-related carcinogenesis. Although most infections resolve spontaneously, persistent infection with high-risk genotypes may progress to high-grade squamous intraepithelial lesions (HSILs) and cancer, particularly in the setting of impaired immune surveillance. Unlike previous HPV-related reviews focused primarily on cervical disease, vaccination, or isolated immunosuppressed populations, this narrative review comparatively examines the clinical expression, colposcopic findings, screening strategies, and therapeutic implications of HPV-related disease across the immunological spectrum. This narrative review provides an integrative synthesis of HPV-related disease in the female lower genital tract across the immunological spectrum. A structured, non-systematic search of PubMed/MEDLINE, Scopus, and Web of Science was conducted using terms related to “human papillomavirus”, “HPV”, “cervical intraepithelial neoplasia”, “colposcopy”, “immunosuppression”, “HIV”, and “vaccination”. Immunosuppressed populations, including individuals living with HIV, transplant recipients, and patients receiving immunosuppressive therapy, exhibit higher rates of persistent infection, multifocal disease, recurrence, and progression to HSIL and invasive malignancy. These patients also present greater diagnostic complexity, broader anatomical involvement, and reduced response to conventional treatment. Rather than representing a uniform condition, HPV-related disease reflects a biologically dynamic spectrum shaped by host immune competence. This review highlights the distinct clinical, colposcopic, and therapeutic challenges observed in immunosuppressed populations and reinforces the need for individualized, risk-adapted strategies integrating contemporary advances in screening, vaccination, and HPV-related disease management. Full article

(This article belongs to the Special Issue Advances in Diagnosis and Treatment of Gynecological Infections)

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18 pages, 4314 KB

Open AccessArticle

Optimizing a Multimodal Large Language Model for Ultrasound-Based Thyroid Nodule Malignancy Classification: A Comparative Study of Few-Shot Learning, Prompt Engineering, and Fine-Tuning

by Yu-Hsuan Li, Yu-Cheng Cheng, Chih-Yun Chang and I-Te Lee

Diagnostics 2026, 16(12), 1931; https://doi.org/10.3390/diagnostics16121931 - 22 Jun 2026

Viewed by 254

Abstract

Objectives: Multimodal large language models (MLLMs) have shown potential for medical image classification. We evaluated four optimization strategies in two MLLMs—GPT-4o (gpt-4o-2024-08-06) and Gemini 2.5 Flash-Lite—for ultrasound-based thyroid nodule malignancy classification using two public datasets and a clinical cohort of nodules with atypia [...] Read more.

Objectives: Multimodal large language models (MLLMs) have shown potential for medical image classification. We evaluated four optimization strategies in two MLLMs—GPT-4o (gpt-4o-2024-08-06) and Gemini 2.5 Flash-Lite—for ultrasound-based thyroid nodule malignancy classification using two public datasets and a clinical cohort of nodules with atypia of undetermined significance (AUS) cytology. Methods: Text prompting, few-shot learning, fine-tuning, and a hybrid strategy combining fine-tuning with few-shot learning were evaluated for each model. Performance was assessed using the Digital Database of Thyroid Images (DDTI; n = 80), a 1000-image test subset of TN5000, and an institutional AUS cohort with surgical pathology (n = 84). In the AUS cohort, the best-performing strategy was compared with the consensus classification of three endocrinologists and the American Thyroid Association (ATA) ultrasound risk stratification. Results: For GPT-4o, the hybrid strategy achieved the highest area under the receiver operating characteristic curve (AUC) in DDTI (0.866), TN5000 (0.689), and the AUS cohort (0.836). In the AUS cohort, its specificity was higher than that of endocrinologist consensus and ATA risk stratification when only high-suspicion nodules were classified as malignant (95.1% vs. 70.7% and 70.7%; p = 0.002 and p = 0.001, respectively), while sensitivity did not differ significantly (72.1% vs. 74.4% and 79.1%, respectively; both p > 0.05). However, the hybrid model misclassified 12 of 43 malignant nodules, corresponding to a false-negative rate of 27.9%. When high- and intermediate-suspicion ATA categories were classified as malignant, ATA sensitivity increased to 83.7% and specificity decreased to 56.1%; the hybrid model had a higher AUC than ATA risk stratification (0.836 vs. 0.749; p = 0.017). For Gemini 2.5 Flash-Lite, few-shot learning, fine-tuning, and the hybrid strategy did not improve AUC relative to text prompting in any dataset. Conclusions: The hybrid strategy produced the most consistent performance gains for GPT-4o across the three datasets but did not improve Gemini 2.5 Flash-Lite. The optimized GPT-4o model achieved high specificity in the diagnostically challenging AUS cohort, although its false-negative rate limits its use as a stand-alone diagnostic tool. Further validation in larger, prospective multicenter cohorts is required before clinical use. Full article

(This article belongs to the Section Machine Learning and Artificial Intelligence in Diagnostics)

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36 pages, 2071 KB

Open AccessSystematic Review

Diagnostic Performance of the MeMed BV Test to Distinguish Between Bacterial and Viral or Other Non-Bacterial Causes Amongst ED and Urgent Care Patients: A Systematic Review with Meta-Analysis

by Sandeep Moola, Enitan D. Carrol, Richard Rothman, Hasik PN, Andrey Maslov and Oleg Borisenko

Diagnostics 2026, 16(12), 1930; https://doi.org/10.3390/diagnostics16121930 - 22 Jun 2026

Viewed by 460

Abstract

Background/Objectives: Respiratory tract symptoms, urinary symptoms, and acute fevers frequently prompt emergency urgent care visits. Distinguishing bacterial from viral or non-bacterial etiology remains difficult because clinical features overlap and laboratory microbiological tests are often non-specific or delayed. The MeMed BV^® test [...] Read more.

Background/Objectives: Respiratory tract symptoms, urinary symptoms, and acute fevers frequently prompt emergency urgent care visits. Distinguishing bacterial from viral or non-bacterial etiology remains difficult because clinical features overlap and laboratory microbiological tests are often non-specific or delayed. The MeMed BV^® test is a rapid host-response assay that combines TRAIL, IP-10, and CRP into a composite score to differentiate between bacterial and viral/non-bacterial infections within 15 min. The objective of this systematic review and meta-analysis was to evaluate the diagnostic accuracy and clinical utility of the MeMed BV test in adults and children with suspected respiratory tract infections, urinary tract infections, and undifferentiated fever. Methods: The review followed PRISMA-DTA guidelines. Medline, Embase, CINAHL, and the Cochrane Library databases were searched. The risk of bias was assessed using the QUADAS-2, Cochrane RoB 2.0, ROBINS-I, and JBI tools. Where appropriate, meta-analyses were performed using a bivariate random-effects or HSROC model. Results: Sixteen studies (12 diagnostic test accuracy (DTA) studies and four non-DTA studies) were included. The pooled sensitivity was 91% (95% CI: 86–94%), and specificity was 92% (95% CI: 91–93%), with consistent accuracy in adults (Sensitivity 93%/Specificity 91%) and children (Sensitivity 88%/Specificity 93%). The non-DTA studies demonstrated that MeMed BV-guided management improved antibiotic stewardship: antibiotics were prescribed in 20.6% of viral versus 73.2% of bacterial cases, and clinician adherence to MeMed BV results reached 75–80%. Conclusions: The MeMed BV test demonstrates consistently high diagnostic accuracy and is associated with improved antibiotic decision-making, supporting its integration into clinical workflows. Full article

(This article belongs to the Special Issue Recent Advances in Epidemiological Diagnostics: Detecting and Controlling Infectious Diseases, 2nd Edition)

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22 pages, 3544 KB

Open AccessArticle

Radiographic Angle-Based Machine Learning Models for the Diagnosis of Pes Planus and Pes Cavus: A Large-Scale Study Using Weight-Bearing Lateral Foot Radiographs

by Rabia Taşdemir, Mustafa Işık, Ahmet Hakan İnce, Ebru Sena Poyraz, Şule Baysal, Ramazan Parıldar and Nevzat Gönder

Diagnostics 2026, 16(12), 1929; https://doi.org/10.3390/diagnostics16121929 - 22 Jun 2026

Viewed by 248

Abstract

Background/Objectives: Pes planus and pes cavus are common foot deformities, which may lead to pain, functional limitations, and impairment of foot biomechanics. While calcaneal pitch, talar declination, and Meary angles, commonly used in diagnosis, provide objective information, their lack of a gold [...] Read more.

Background/Objectives: Pes planus and pes cavus are common foot deformities, which may lead to pain, functional limitations, and impairment of foot biomechanics. While calcaneal pitch, talar declination, and Meary angles, commonly used in diagnosis, provide objective information, their lack of a gold standard and the observer’s dependence on manual measurements limit their reliability. Therefore, in this study, these angles obtained from weight-bearing lateral foot radiographs were evaluated according to literature references, and the aim was to determine the model that provides the most accurate prediction in the diagnosis of pes planus using machine learning algorithms. It should be emphasized that, because the diagnostic labels were derived from literature-based thresholds of these same angles, the machine-learning task addressed here is the automated reproduction and standardization of expert, angle-threshold-based classification, rather than an independent clinical diagnosis from raw images. Methods: This retrospective study was conducted using weight-bearing lateral foot radiographs of 697 male patients obtained from the archives of public hospitals in Gaziantep. Calcaneal pitch, Meary angle, and talar declination angles were evaluated in both feet, and the data were labeled as normal, pes planus, and pes cavus. The dataset, consisting of a total of 1394 feet, was divided into training and test groups and analyzed using Random Forest, XGBoost, Logistic Regression, Support Vector Machine (SVM), and K-Nearest Neighbors (KNN) algorithms; the diagnostic performance of the models was compared using measures such as accuracy, F1 score, sensitivity, and specificity. Results: A total of 1394 feet from 697 male patients (mean age 24.8 ± 5.57 years) were analyzed using five machine learning algorithms with calcaneal pitch angle (CPA), Meary angle (MA), and talar declination angle (TDA) as reference labels. Ensemble-based methods showed superior performance, with XGBoost achieving perfect classification (Accuracy = 1.000) under all three labels for the left foot and 0.996–1.000 for the right foot, while Random Forest reached 0.986–1.000 across all experiments. Logistic Regression and SVM yielded moderate accuracies (0.905–0.973), whereas KNN consistently performed the weakest (0.905–0.964), particularly in the pes cavus subgroup. The near-perfect accuracy obtained when the labeling angle was itself included among the predictors reflects, at least in part, the algebraic reconstruction of the threshold rule from a same-source variable rather than genuine diagnostic generalization; results should therefore be interpreted with this in mind. Conclusions: This study demonstrates that machine learning, particularly ensemble methods such as XGBoost and Random Forest, provides high accuracy and consistency in diagnosing foot arch deformities based on radiographic angle measurements. Traditional models, such as Logistic Regression, still hold value in terms of clinical interpretability despite their lower performance. The findings suggest that machine learning-based approaches can offer objective, rapid, and reliable decision support tools for diagnosing pes planus and pes cavus, but external validation studies are necessary for clinical generalizability. Full article

(This article belongs to the Special Issue Musculoskeletal Imaging in Clinical Practice: From Qualitative Diagnosis to Quantitative Analysis)

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16 pages, 1520 KB

Open AccessArticle

Paranasal Sinus Morphometry for Forensic Sex Estimation: A Computed Tomography Study of 499 Individuals with a Cross-Validated, Transparently Reported Machine Learning Model

by Muhammet Can, Cihangir Işık and Burcu Düzel Asıg

Diagnostics 2026, 16(12), 1928; https://doi.org/10.3390/diagnostics16121928 - 22 Jun 2026

Viewed by 648

Abstract

Background/Objectives: Paranasal sinus morphometry on computed tomography (CT) is of interest for forensic sex estimation, but many published predictive models rely on in-sample formulas without cross-validation, external testing, or release of model parameters. We aimed to characterize sex differences, pneumatization patterns, asymmetry, and [...] Read more.

Background/Objectives: Paranasal sinus morphometry on computed tomography (CT) is of interest for forensic sex estimation, but many published predictive models rely on in-sample formulas without cross-validation, external testing, or release of model parameters. We aimed to characterize sex differences, pneumatization patterns, asymmetry, and age relationships of the paranasal sinuses in a Turkish adult population, and to develop, cross-validate, and transparently report a predictive model for sex estimation, explicitly benchmarked against the single best morphometric feature. Methods: In this single-center, STROBE-compliant retrospective cross-sectional study, maxillary, frontal, and sphenoid sinus volumes were measured by semi-automated active-contour segmentation in ITK-SNAP on CT scans of 499 adults (282 male, 217 female; 18–65 years). Between-sex differences were tested with the Mann–Whitney U test with Bonferroni correction; effect sizes used Cliff’s delta and the probability of superiority. L1-regularized logistic regression, random forest, and gradient boosting were trained with 10-fold stratified cross-validation and a held-out 20% test set, and compared with a univariate frontal-volume benchmark. Results: All three sinus volumes were larger in males (all Bonferroni-adjusted p < 0.001), with the largest effect among the individual sinuses for the frontal sinus (Cliff’s delta = 0.53; probability of male superiority = 0.77). The best classifier was L1-regularized logistic regression (10-fold cross-validated AUC 0.79 ± 0.07; held-out test AUC 0.80; accuracy 70%). Because the area under the ROC curve of a single continuous marker equals its probability of superiority, frontal volume alone reached an AUC of approximately 0.77; the multivariable model therefore added little beyond this single feature. Age could not be reliably estimated (test mean absolute error ≈ 10.8 years; R² ≈ 0). Conclusions: Paranasal sinus volumes show robust sex dimorphism, concentrated in the frontal sinus, but provide only moderate sex discrimination—appropriate as one corroborating input in a forensic identification workflow rather than a stand-alone determinant. Age cannot be reliably estimated from sinus morphometry in this cohort. Full model coefficients are reported to permit independent replication. Full article

(This article belongs to the Section Forensic Diagnostics)

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10 pages, 971 KB

Open AccessArticle

Selective Inhibition of Insulin-Degrading Enzyme Eliminates Hemolysis Interference in Serum Insulin Measurements

by María Rodríguez-García, Bernardino González de la Presa, Aleix B. Fabregat-Bolufer, Naira Rico, Helena Castella, Alejandro Calvera-Rayo, Marga Giménez, Felicia A. Hanzu, Manuel Morales-Ruiz and Gregori Casals

Diagnostics 2026, 16(12), 1927; https://doi.org/10.3390/diagnostics16121927 - 22 Jun 2026

Viewed by 197

Abstract

Objectives. Hemolysis significantly interferes with insulin measurements in clinical settings, leading to inaccurate results. Although the activity of insulin-degrading enzyme (IDE) is assumed to be the primary mechanism, the potential involvement of additional mechanisms remains unclear. This study aims to determine if [...] Read more.

Objectives. Hemolysis significantly interferes with insulin measurements in clinical settings, leading to inaccurate results. Although the activity of insulin-degrading enzyme (IDE) is assumed to be the primary mechanism, the potential involvement of additional mechanisms remains unclear. This study aims to determine if IDE is the sole cause of this interference by using a selective IDE inhibitor, 6bK, and to explore whether this inhibition can completely prevent hemolysis-related inaccuracies in insulin assays. Methods. The effects of 6bK on insulin degradation were evaluated in hemolyzed and non-hemolyzed serum samples at room temperature, following the CLSI guidelines EP07-A2 and C56-A. Insulin levels were measured using chemiluminescent immunoassays. Additional assessments included the impact of 6bK on serum C-peptide, proinsulin, and standard biochemical parameters. The effects of 6bK were also evaluated at 4 °C and after 21 days of storage at room temperature prior to use. Results. Hemolysis caused a significant decrease in insulin concentrations, dependent on hemolysate levels and incubation time. The addition of 10 µM 6bK completely reversed hemolysis-induced insulin degradation in serum across a broad range of insulin baseline concentrations and degrees of hemolysis. Furthermore, 6bK did not affect insulin levels in non-hemolyzed samples or alter the quantification of C-peptide, proinsulin, or standard biochemical parameters. Conclusions. The decrease in serum insulin concentration due to hemolysis is exclusively attributed to the action of IDE. Selective inhibition of IDE by 6bK effectively eliminates hemolysis-induced interference in insulin measurements, providing a novel and reliable solution for accurate insulin quantification in hemolyzed clinical samples. Full article

(This article belongs to the Special Issue Advances in Laboratory Analysis and Diagnostics)

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22 pages, 1879 KB

Open AccessCase Report

Pediatric Sjögren’s Disease: Literature Review and Diagnostic Challenges in an Uncommon Case

by Otilia Elena Frăsinariu, Dragoș Florin Teșoi, Anca Cardoneanu, Ileana Katerina Ioniuc, Ana Maria Scurtu, Elena Cojocaru, Larisa Ioana Teșoi, Ionut Daniel Iancu, Anamaria Laura Buga and Ingrith Crenguța Miron

Diagnostics 2026, 16(12), 1926; https://doi.org/10.3390/diagnostics16121926 - 22 Jun 2026

Viewed by 184

Abstract

Background and Clinical Significance: Childhood-onset Sjögren’s disease (cSjD) is a rare autoimmune disorder that remains challenging to diagnose because of its heterogeneous clinical presentation and the frequent absence of classic sicca symptoms at disease onset. Recurrent parotitis and systemic manifestations often predominate in [...] Read more.

Background and Clinical Significance: Childhood-onset Sjögren’s disease (cSjD) is a rare autoimmune disorder that remains challenging to diagnose because of its heterogeneous clinical presentation and the frequent absence of classic sicca symptoms at disease onset. Recurrent parotitis and systemic manifestations often predominate in pediatric patients, contributing to diagnostic delay and potential irreversible glandular damage. Early recognition is essential to prevent complications and improve long-term outcomes. Case Presentation: We report the case of a 17-year-old female diagnosed with primary Sjögren’s disease following a prolonged history of recurrent parotid involvement and progressive glandular dysfunction. Comprehensive evaluation revealed positive anti-SSA antibodies, hypergammaglobulinemia, characteristic salivary gland ultrasonography abnormalities, and a positive minor salivary gland biopsy, resulting in fulfillment of all domains of the 2016 ACR/EULAR classification criteria. The patient also exhibited unusual vascular findings, including carotid atheromatous calcifications in the absence of traditional cardiovascular risk factors. Conclusion: This case highlights the diagnostic complexity of cSjD and underscores the value of a multimodal diagnostic approach integrating clinical assessment, serology, imaging, and histopathology. The presence of early vascular abnormalities broadens the spectrum of potential extraglandular manifestations and emphasizes the need for comprehensive evaluation and long-term monitoring in affected patients. Full article

(This article belongs to the Special Issue Trends and Diagnosis of Autoimmune Diseases)

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23 pages, 1148 KB

Open AccessReview

Metastasis of Breast Lobular Carcinoma to the Uterine Cervix: A Narrative Review

by Mahmoud Rezk Abdelwahed Hussein and Toka Mahmoud Rezk Abdelwahed Hussein

Diagnostics 2026, 16(12), 1925; https://doi.org/10.3390/diagnostics16121925 - 21 Jun 2026

Viewed by 275

Abstract

Background: Metastases to the uterine cervix from extragenital malignancies represent uncommon clinical events, with breast invasive lobular carcinoma (ILC) documented as the predominant primary source in reported literature. Objectives/Aim: To characterize the clinicopathologic features of ILCs metastatic to the uterine cervix. Methods: We [...] Read more.

Background: Metastases to the uterine cervix from extragenital malignancies represent uncommon clinical events, with breast invasive lobular carcinoma (ILC) documented as the predominant primary source in reported literature. Objectives/Aim: To characterize the clinicopathologic features of ILCs metastatic to the uterine cervix. Methods: We performed a PubMed search using several keywords. Results: A total of 29 studies were included in the final analysis. The mean age at presentation of cervical metastasis was 56.8 ± 2.0 years. The mean interval between the initial diagnosis of ILC and the detection of cervical metastasis was 55.6 ± 8.2 months. Clinical presentations included vaginal bleeding, pelvic pain, and unhealthy enlarged, indurated uterine cervix on local examination. The diagnosis was established via tissue biopsy and immunohistochemical stains (positive reactivity for CK7, ER, PR, E-Cadherin, GATA3, GCDP-15 and mammaglobin). There are no consensus treatment protocols, and therapy should be tailored individually based on the extent of disease. Combined surgical and systemic therapy was the most commonly used modality. Conclusions: Metastasis of breast ILCs to the uterine cervix poses a significant diagnostic challenge. A high index of clinical suspicion and detailed clinical history are essential for accurate diagnosis. Full article

(This article belongs to the Section Pathology and Molecular Diagnostics)

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18 pages, 4111 KB

Open AccessReview

Operational Validity in Decentralized Molecular Point-of-Care Diagnostics: A Human Factors Engineering Perspective

by Moustafa Kardjadj

Diagnostics 2026, 16(12), 1924; https://doi.org/10.3390/diagnostics16121924 - 21 Jun 2026

Viewed by 543

Abstract

The rapid expansion of molecular point-of-care (POC) diagnostics into decentralized settings, including emergency departments, retail pharmacies, and home environments, has shifted the burden of diagnostic performance from laboratory professionals to heterogeneous, often non-expert users. While traditional evaluation frameworks focus on analytical and clinical [...] Read more.

The rapid expansion of molecular point-of-care (POC) diagnostics into decentralized settings, including emergency departments, retail pharmacies, and home environments, has shifted the burden of diagnostic performance from laboratory professionals to heterogeneous, often non-expert users. While traditional evaluation frameworks focus on analytical and clinical validity, they often overlook the impact of human-system interactions on real-world reliability. This review introduces the concept of Operational Validity: the ability of a diagnostic system to preserve its intended performance when operated by intended users within the constraints of real-world workflows and environments. To establish a rigorous foundation for this concept, this study provides a critical comparative analysis contrasting Operational Validity against traditional clinical evaluation dimensions (analytical validity, clinical validity, and clinical utility) and post-market metrics. While existing literature outlines isolated usability principles, the significance of this study lies in its synthesis of these fragmented concepts into a formalized, lifecycle-based “Operational Validity” framework that explicitly maps the causal mechanisms connecting initial user interaction directly to downstream clinical outcomes. By synthesizing international standards (IEC 62366-1) alongside the newly finalized May 2026 U.S. Food and Drug Administration (FDA) guidance on the Content of Human Factors Information in Medical Device Marketing Submissions, we examine how human factors engineering (HFE) and usability engineering serve as the methodological foundation for operational validity. We analyze the specific complexities of molecular workflows, identify key parameters of use-related failure modes in pre-analytical and interpretation stages, and detail the mandatory role of iterative formative and final summative usability testing in mitigating these risks. Finally, we propose a lifecycle-based approach to HFE that integrates design, simulated-use validation, and post-market surveillance. Establishing operational validity is essential to ensure that the high analytical sensitivity of molecular POC platforms translates into consistent clinical utility across the full spectrum of decentralized care. Full article

(This article belongs to the Section Point-of-Care Diagnostics and Devices)

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10 pages, 6845 KB

Open AccessCase Report

Subacute Left Ventricular Free-Wall Rupture After Thrombolysis: From Concealed Rupture on CT to Successful Surgical Patch Repair

by Mohamed Ghaleb, Omar Elsayed, Mahmoud F. Elshahat, Ahmed Goha, Ibrahim ALshaghdali, Nawwaf M. ALAnazi, Mohamed E. Abdeldayem, Sulieman B. Haddadin and Naif S. ALGhasab

Diagnostics 2026, 16(12), 1923; https://doi.org/10.3390/diagnostics16121923 - 21 Jun 2026

Viewed by 328

Abstract

Background and Clinical Significance: Left ventricular free-wall rupture (LVFWR) is a rare but devastating mechanical complication of acute myocardial infarction (AMI), with reported in-hospital mortality approaching 90% without surgical intervention. Although its incidence has declined in the contemporary primary percutaneous coronary intervention [...] Read more.

Background and Clinical Significance: Left ventricular free-wall rupture (LVFWR) is a rare but devastating mechanical complication of acute myocardial infarction (AMI), with reported in-hospital mortality approaching 90% without surgical intervention. Although its incidence has declined in the contemporary primary percutaneous coronary intervention (PCI) era, LVFWR remains an important cause of early post-infarction death, particularly after delayed reperfusion or fibrinolytic therapy. Subacute or contained “oozing” ruptures pose a unique diagnostic challenge because hemodynamic stability and nonspecific symptoms can mask the underlying catastrophe, and standard transthoracic echocardiography may fail to visualize a sealed defect. Contrast-enhanced cardiac computed tomography (CT) has emerged as a valuable adjunct in this setting, enabling early recognition and surgical planning. Case Presentation: We report a case of a 51-year-old male, a heavy smoker, with acute lateral ST-segment elevation myocardial infarction (STEMI) treated with thrombolysis at a referring hospital, followed by percutaneous coronary intervention (PCI) to the obtuse marginal branch. Despite reperfusion, he developed persistent pleuritic chest pain and a small pericardial effusion. Cardiac computed tomography (CT) demonstrated a contained (sealed) lateral-wall oozing-type left ventricular free-wall rupture (LVFWR) with thrombus sealing the defect. A multidisciplinary heart team initially opted for diligent observation with frequent echocardiography. Within the first 24 h, the pericardial effusion increased, and echocardiography showed circumferential effusion with lateral wall thickening and hematoma, prompting emergent sternotomy. Intraoperatively, a large posterolateral infarct with an oozing-type LV free-wall rupture was identified. Surgical repair was performed using interrupted pledgeted sutures, native pericardial patch, BioGlue, and an overlying Teflon patch, with intra-aortic balloon pump (IABP) support. This case demonstrates the complementary diagnostic value of multimodality imaging—echocardiography for serial monitoring of the pericardial effusion and regional wall changes, and cardiac CT for direct characterization of the contained (sealed) defect—and the timely transition from conservative to surgical management in oozing-type rupture. The patient recovered uneventfully and was discharged in stable condition. Conclusions: This case highlights the diagnostic value of multimodality imaging—particularly cardiac CT—in detecting contained (sealed) LVFWR when echocardiography is inconclusive. Early recognition and prompt surgical intervention enabled a successful outcome in this otherwise frequently fatal complication. Full article

(This article belongs to the Special Issue Innovations in Diagnostic and Interventional Cardiology: Bridging Imaging, Physiology, and Therapy)

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16 pages, 845 KB

Open AccessArticle

Association Between Triglyceride/High-Density Lipoprotein Ratio and Premature Coronary Artery Disease in Young Saudi Population: A Case–Control Study

by Thamir Al-khlaiwi, Ayman Alsaleh, Hessah Alshammari, Sara Abou Al-Saud, Manan Alhakbany, Abdulmalik Alqahtani, Aliah Alshanwani, Sarah Mazi and Muhammad Iqbal

Diagnostics 2026, 16(12), 1922; https://doi.org/10.3390/diagnostics16121922 - 21 Jun 2026

Viewed by 238

Abstract

Background/Objectives: Limited research has evaluated the association between the triglyceride-to-high-density lipoprotein (TG/HDL) ratio and premature coronary artery disease (PCAD), particularly in Saudi Arabia. Therefore, this study aimed to investigate the association of the TG/HDL ratio with PCAD and to assess its sensitivity [...] Read more.

Background/Objectives: Limited research has evaluated the association between the triglyceride-to-high-density lipoprotein (TG/HDL) ratio and premature coronary artery disease (PCAD), particularly in Saudi Arabia. Therefore, this study aimed to investigate the association of the TG/HDL ratio with PCAD and to assess its sensitivity and specificity in a young Saudi population. Methods: This comparative retrospective case–control study utilized data collected from patients’ electronic medical records at King Saud University Medical City (KSUMC) between 2015 and 2023. The vessel score and Gensini score were used to evaluate the severity of coronary occlusion. The study population was divided into two groups: (1) a healthy control group consisting of blood bank donors, selected to exclude individuals with chronic diseases such as metabolic disorders and hypertension, with no evidence of coronary artery disease and aged ≤50 years (as confirmed by a cardiologist to rule out cardiovascular disease); and (2) patients with PCAD, aged ≤51 years, who underwent selective coronary angiography using the standard hospital procedure (right femoral artery approach). Coronary angiographic images were evaluated using right and left oblique views with cranial and caudal angulations. Results: A total of 898 subjects were included in the study, comprising 440 healthy controls and 458 patients with PCAD. Higher HbA1c levels were significantly associated with PCAD (adjusted OR = 13.03, 95% CI [7.32, 23.18], p < 0.001). Importantly, the TG/HDL ratio, the primary biomarker of interest, remained significantly associated with PCAD after full adjustment. Each unit increase in the TG/HDL ratio was associated with more than a threefold increase in the odds of PCAD (adjusted OR = 3.39, 95% CI [2.22, 5.16], p < 0.001), independent of age, sex, BMI, HbA1c, smoking, and total cholesterol levels. Among females, the TG/HDL ratio demonstrated an area under the curve (AUC) of 0.796, with an optimal cut-off value of 0.91, yielding 77.8% sensitivity and 71.4% specificity. Among males, the TG/HDL ratio yielded an AUC of 0.786, with a higher optimal cut-off value of 1.09 providing 73.4% sensitivity and 65.4% specificity. Conclusions: Our study indicates that the TG/HDL ratio and HbA1c are significantly associated with PCAD in young Saudi male and female populations, demonstrating good sensitivity and specificity. Females exhibited a lower cut-off value than males. Smoking and elevated cholesterol levels were also identified as prominent risk factors. However, the TG/HDL ratio did not distinguish between moderate and severe coronary stenosis, as assessed by the Gensini score. Full article

(This article belongs to the Section Clinical Laboratory Medicine)

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19 pages, 538 KB

Open AccessReview

Artificial Intelligence in Cardiac Point-of-Care Ultrasound: A Narrative Review

by Evan Avraham Alpert, Toby Kwartz, Barry Hahn, Waid Abdulghani, Ahmad Nama and Ziv Dadon

Diagnostics 2026, 16(12), 1921; https://doi.org/10.3390/diagnostics16121921 - 21 Jun 2026

Viewed by 446

Abstract

Background: Cardiac point-of-care ultrasound (POCUS) is widely used in emergency and acute care settings. Still, broader use remains limited by operator dependence and variability in image acquisition and interpretation. Artificial intelligence (AI), including machine learning and deep learning methods, has been applied [...] Read more.

Background: Cardiac point-of-care ultrasound (POCUS) is widely used in emergency and acute care settings. Still, broader use remains limited by operator dependence and variability in image acquisition and interpretation. Artificial intelligence (AI), including machine learning and deep learning methods, has been applied to cardiac POCUS to support image acquisition, automate quantitative measurements, and assist interpretation. Methods: We performed a narrative review of current applications of AI-assisted cardiac POCUS. A targeted literature search of PubMed and Google Scholar from 2018 to 2026 was conducted using terms related to AI, machine learning, deep learning, and cardiac ultrasound. Studies evaluating AI-assisted cardiac ultrasound in clinical, educational, or image-acquisition settings were included, with emphasis on recent, clinically relevant applications. Results: The most developed application of AI-assisted cardiac POCUS is an automated assessment of left ventricular systolic function, particularly the left ventricular ejection fraction (LVEF), where multiple studies report agreement with expert interpretation or formal echocardiography and improved performance among novice users. AI-assisted tools have also been evaluated for pericardial effusion detection, guidance for image acquisition, and education. More complex applications, including diastolic function assessment and hemodynamic measurements such as LVOT-VTI, remain less well validated and more dependent on image quality. Across studies, performance is closely linked to image acquisition quality and has often been evaluated under controlled rather than real-world conditions. Conclusions: Current evidence supports AI-assisted cardiac POCUS primarily as a decision-support tool, with the strongest data for automated assessment of LVEF. Other applications remain investigational. Full article

(This article belongs to the Special Issue Clinical Diagnosis and Management in Emergency and Hospital Medicine–2nd Edition)

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16 pages, 1398 KB

Open AccessArticle

Endometrial Microbiome Profiles in Women Evaluated for Infertility or Recurrent Miscarriage: A Single-Center Descriptive Study

by Argyro Papadopoulou, Sofoklis Stavros, Anastasios Potiris, Panagiota Tsoplou, Kyriaki Dioikitopoulou, Vasiliki Plastourgou, Christodoulos Papanikopoulos, Georgios Tournas, Efthalia Moustakli, Athanasios Zikopoulos, Sofia Anysiadou, Anastasia Maria Daskalaki, Panagiotis Antsaklis, Georgios Daskalakis and Ekaterini Domali

Diagnostics 2026, 16(12), 1920; https://doi.org/10.3390/diagnostics16121920 - 21 Jun 2026

Viewed by 276

Abstract

Background/Objectives: The role of the endometrial microbiome in reproductive failure remains incompletely understood. This study aimed to describe the composition of the endometrial microbiome in women evaluated for infertility or recurrent miscarriage. Methods: In this single-center descriptive study, endometrial samples were collected from [...] Read more.

Background/Objectives: The role of the endometrial microbiome in reproductive failure remains incompletely understood. This study aimed to describe the composition of the endometrial microbiome in women evaluated for infertility or recurrent miscarriage. Methods: In this single-center descriptive study, endometrial samples were collected from women evaluated for infertility or recurrent miscarriage. Microbiome profiling was performed using 16S rRNA gene next-generation sequencing. Samples were classified as Lactobacillus-dominant when Lactobacillus spp. accounted for ≥90% of the total bacterial community. Alpha diversity was assessed using the Shannon and Simpson indices, while beta diversity was evaluated using Bray–Curtis dissimilarity, principal coordinates analysis (PCoA), PERMANOVA, and PERMDISP. Results: Of the 60 samples, 20 (33.3%) were Lactobacillus-dominant and 40 (66.7%) were non-Lactobacillus-dominant. Across all samples, Firmicutes was the predominant phylum (76.6%). Non-Lactobacillus-dominant samples showed significantly higher alpha diversity than Lactobacillus-dominant samples for both the Shannon and Simpson indices (p = 1.19 × 10⁻⁶ and p = 1.51 × 10⁻⁶, respectively), as well as higher observed taxa richness (p = 0.000017). PCoA based on Bray–Curtis dissimilarity demonstrated clear separation between microbiome profiles, supported by PERMANOVA (pseudo-F = 13.87, R² = 0.193, p = 0.001). PERMDISP showed significantly greater dispersion among non-Lactobacillus-dominant samples (F = 566.94, p < 0.001). Non-Lactobacillus-dominant samples showed greater representation of Enterococcus and Prevotella. Conclusions: In this cohort non-Lactobacillus-dominant communities were more frequent with greater diversity, richness, and compositional heterogeneity than Lactobacillus-dominant communities. These findings highlight the need for larger, standardized studies with appropriate control populations to clarify their clinical significance. Full article

(This article belongs to the Special Issue Advances in Diagnostic Pathways for Pregnancy Complications and Gynecologic Disease)

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17 pages, 1410 KB

Open AccessArticle

Preoperative OCT Biomarkers as Predictors of Postoperative Functional Outcome Assessed by Microperimetry After Inverted ILM Flap Surgery

by Ovidiu Samoilă, Anca Mădălina Sere, Lăcrămioara Samoilă and Daniel-Corneliu Leucuța

Diagnostics 2026, 16(12), 1919; https://doi.org/10.3390/diagnostics16121919 - 20 Jun 2026

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Abstract

Background/Objectives: A macular hole represents a significant surgical condition in an increasingly aging population. Advances in surgical techniques, particularly pars plana vitrectomy with inverted internal limiting membrane (ILM) flap, have established high anatomical closure rates exceeding 90%. The prognostic factors influencing visual [...] Read more.

Background/Objectives: A macular hole represents a significant surgical condition in an increasingly aging population. Advances in surgical techniques, particularly pars plana vitrectomy with inverted internal limiting membrane (ILM) flap, have established high anatomical closure rates exceeding 90%. The prognostic factors influencing visual recovery remain incompletely understood, and it is unclear which patients can be expected to achieve optimal functional outcomes. Methods: This retrospective longitudinal study included 35 eyes of 32 patients followed for 3–12 months. Preoperative OCT parameters (minimum linear diameter, basal diameter, and hole height) and derived indices were correlated with functional outcomes, including best-corrected visual acuity (BCVA) and microperimetry, stratified as central macular sensitivity (CMS) and sensitivity at 4° and 20°. Postoperative ellipsoid zone (EZ) and external limiting membrane (ELM) integrity were also analyzed. Predictive performance was assessed using root mean square error (RMSE) and coefficient of determination (R²). A linear regression model based on BCVA served as baseline, while Extreme Gradient Boosting (XGBoost) models incorporating OCT features were developed. Feature importance was evaluated using Shapley Additive Explanations (SHAP). Results: Overall closure rate was 100%, including 91.4% Type 1 and 8.6% Type 2 closure. Models incorporating OCT parameters outperformed BCVA-based models (lower RMSE, and higher R²). Minimum linear diameter and hole height were the strongest predictors of postoperative outcomes. Microperimetry detected functional improvement beyond BCVA and correlated with EZ and ELM restoration. Conclusions: Preoperative macular hole morphology represents a key determinant of postoperative functional recovery. These structural parameters provide meaningful prognostic value beyond visual acuity alone, supporting the role of combined OCT and microperimetric assessment in predicting surgical outcomes. Full article

(This article belongs to the Special Issue Clinical Prognostic and Predictive Biomarkers, 4th Edition)

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17 pages, 1202 KB

Open AccessReview

Current State and Future of Artificial Intelligence in Pediatric Interventional Radiology: A Narrative Review

by Abdulaziz Mohammad Al-Sharydah

Diagnostics 2026, 16(12), 1918; https://doi.org/10.3390/diagnostics16121918 - 20 Jun 2026

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Abstract

Artificial intelligence (AI) is reshaping the field of diagnostic radiology; however, its applications in interventional radiology and pediatric interventional radiology (PIR) remain limited despite clear clinical needs and the rich multimodal data environment characteristic of pediatric procedural care. In this narrative review, I [...] Read more.

Artificial intelligence (AI) is reshaping the field of diagnostic radiology; however, its applications in interventional radiology and pediatric interventional radiology (PIR) remain limited despite clear clinical needs and the rich multimodal data environment characteristic of pediatric procedural care. In this narrative review, I summarize the current state of AI technologies relevant to PIR and outline future perspectives for their clinical integration. Peer-reviewed literature and position statements identified through MEDLINE/PubMed, Embase, Scopus, and major society publications up to the first quarter of 2026 are synthesized, focusing on AI applications across the PIR care pathway, including dose-sparing image acquisition and reconstruction, automated image interpretation and computer-aided diagnosis, data-driven procedural planning and navigation, and post-procedural risk prediction and monitoring. After briefly introducing core machine learning and deep learning concepts, pediatric-specific challenges are discussed, including radiation sensitivity, growth-related anatomical variability, regulatory constraints, and the scarcity of large, annotated datasets, as well as existing and emerging applications along the PIR care pathway: AI-assisted dose reduction and image reconstruction, automated image interpretation, segmentation, and computer-aided diagnosis; data-driven procedural planning, including three-dimensional modelling, augmented reality, AI-enabled/AI-adjacent robotics, and AI-directed procedural navigation; and post-procedural risk prediction and outcome monitoring. Finally, emerging paradigms, including explainable AI, federated learning, and multimodal integration, are highlighted, and research priorities, collaborative frameworks, and governance principles required to ensure safe, equitable, and effective AI deployment in PIR are outlined. In doing so, this review delineates the current evidence gaps and priority directions for clinically meaningful AI adoption in PIR. Although AI has the potential to improve patient care, it has not yet been specifically designed, validated, or deployed in children. Existing work demonstrates feasibility across the PIR workflow, but most tools remain weakly linked to pediatric clinical endpoints. Full article

(This article belongs to the Section Machine Learning and Artificial Intelligence in Diagnostics)

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14 pages, 2593 KB

Open AccessArticle

Digital and Manual Assessment of Intrafollicular Ki-67, MYC, and p53 in Classic Follicular Lymphoma

by George C. de Castro, Morgan L. Shannon, Ruth Zhang, Kunwar Singh, Robert S. Ohgami and Kwun Wah Wen

Diagnostics 2026, 16(12), 1917; https://doi.org/10.3390/diagnostics16121917 - 20 Jun 2026

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Abstract

Background/Objectives: There remains a need for additional prognostic markers in classic follicular lymphoma (cFL) to identify aggressive disease. Immunohistochemical stains such as Ki-67, MYC, and p53 have shown variable associations with histologic grade and adverse outcomes. In this study, we aimed to [...] Read more.

Background/Objectives: There remains a need for additional prognostic markers in classic follicular lymphoma (cFL) to identify aggressive disease. Immunohistochemical stains such as Ki-67, MYC, and p53 have shown variable associations with histologic grade and adverse outcomes. In this study, we aimed to assess intrafollicular Ki-67, MYC, and p53 expression in cFL via immunohistochemistry, quantified by both manual and digital methods, and evaluate their relation to histologic grade and clinical outcomes. Methods: We evaluated 37 cases of cFL from 2000 to 2019 and performed immunohistochemistry for Ki-67, MYC, and p53 on tumor microarray tissue. Stains were assessed within follicles by digital pathology means on QuPath software and via manual low-power estimates. Results:MYC expression was greater in FL3A compared to FL1–2 across all digital and manual scoring methods (all p < 0.05). Ki-67 and p53 expression did not differ by histologic grade group. No biomarker showed a significant association with adverse clinicopathologic features or outcomes, including FLIPI risk group, bulky disease, clinical stage, event-free survival, or overall survival. Manual and digital scores demonstrated strong correlations for all markers (ρ = 0.71–0.89, all p < 0.001). Conclusions: In our cohort, MYC expression was increased in FL3A compared to FL1–2, while no intrafollicular biomarker measurement was associated with adverse clinicopathologic features or clinical outcomes in exploratory analyses. These findings should be interpreted with caution in light of our limited cohort size. Strong concordance between manual and digital scoring supports the feasibility of digital IHC quantification in cFL. Full article

(This article belongs to the Section Pathology and Molecular Diagnostics)

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13 pages, 3329 KB

Open AccessArticle

Surgical Outcomes of Nonmelanoma Skin Cancer Managed with Systematic Preoperative Reflectance Confocal Microscopy-Guided Margin Assessment: A Retrospective Cohort Study Comparing Wide Local Excision and Mohs Micrographic Surgery

by Federico Venturi, Elisabetta Mazzotti, Carlotta Baraldi, Biagio Scotti, Camilla Reggiani, Barbara Corti, Elisabetta Magnaterra, Daniela Tassone and Emi Dika

Diagnostics 2026, 16(12), 1916; https://doi.org/10.3390/diagnostics16121916 - 20 Jun 2026

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Abstract

Background: Reflectance confocal microscopy (RCM) enables noninvasive, high-resolution visualization of skin tumors and may improve preoperative margin assessment in nonmelanoma skin cancer (NMSC). However, its impact on surgical outcomes in routine clinical practice remains incompletely defined. Objective: To evaluate surgical outcomes of NMSC [...] Read more.

Background: Reflectance confocal microscopy (RCM) enables noninvasive, high-resolution visualization of skin tumors and may improve preoperative margin assessment in nonmelanoma skin cancer (NMSC). However, its impact on surgical outcomes in routine clinical practice remains incompletely defined. Objective: To evaluate surgical outcomes of NMSC managed with systematic preoperative RCM-guided margin assessment, comparing wide local excision (WLE) and Mohs micrographic surgery (MMS). Methods: We conducted a retrospective study of 71 consecutive NMSC treated at a tertiary dermatologic oncology center. All tumors underwent RCM evaluation for diagnosis and preoperative margin mapping. Outcomes included positive margins after WLE, local recurrence, recurrence-free survival, and the number of Mohs stages. Associations were analyzed using Fisher’s exact tests and Firth penalized logistic regression. Results: Among 47 tumors treated with WLE, positive margins occurred in 10.6%. Among 24 MMS cases, 70.8% were cleared in a single stage. Local recurrence occurred in 14.9% of WLE-treated tumors and in none of the MMS-treated tumors (p = 0.087). All recurrences occurred in tumors initially demonstrated positive margins after WLE, despite subsequent re-excision and histologic clearance. In multivariable Firth regression, MMS was associated with a lower risk of recurrence (OR 0.13; 95% CI, 0.008–2.10). Conclusions: In this RCM-guided cohort, low margin positivity after WLE and high single-stage clearance in MMS suggest improved surgical accuracy and efficiency. Recurrence was confined to margin-positive tumors, supporting a margin-driven model of tumor control and highlighting RCM as a potential preoperative margin-control strategy. Full article

(This article belongs to the Special Issue Novel Advances in the Diagnosis of Dermatology)

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13 pages, 2222 KB

Open AccessArticle

Hydrogel-Coated Clips Are Associated with a Higher Risk of Dislocation After Ultrasound-Guided Breast Biopsy

by Michael Swoboda, Johannes Deeg, Mark Panczel, Birgit Amort, Silke Haushammer, Valentin Ladenhauf, Malik Galijasevic, Pietro G. Lacaita, Daniel Egle, Afschin Soleiman, Michaela Kluckner and Leonhard Gruber

Diagnostics 2026, 16(12), 1915; https://doi.org/10.3390/diagnostics16121915 - 20 Jun 2026

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Abstract

Background: Breast clip marker movement after ultrasound-guided biopsy can negatively affect lesion re-localisation rates and surgical outcomes, underscoring the need for improved understanding of the factors influencing clip displacement. Thus, this study aimed to compare four different breast clip markers and identify [...] Read more.

Background: Breast clip marker movement after ultrasound-guided biopsy can negatively affect lesion re-localisation rates and surgical outcomes, underscoring the need for improved understanding of the factors influencing clip displacement. Thus, this study aimed to compare four different breast clip markers and identify risk factors for clip migration and dislocation after ultrasound-guided placement. Methods: This retrospective study included 350 patients who underwent ultrasound-guided biopsy of a newly diagnosed breast lesion with placement of one of four types of breast clips (UltraClip Dual Trigger Biodur 108 Coil Marker [UC], TUMARK Professional [TP], TUMARK Vision [TV] and HydroMARK Breast Biopsy Site Marker [HM]). Clip migration and dislocation were assessed immediately after placement and during follow-up imaging for at least 3 months. A binary logistic regression analysis was performed to identify predictors of clip dislocation including lesional, perilesional and procedural parameters. Results: Clip migration rates were 26.0%, 18.0%, 10.0% and 25.0% and clip dislocation rates were 14.0%, 20.0%, 9.0% and 38.0% for UC, TP, TV and HM, respectively. Features significantly associated with clip dislocation included predominantly fatty surrounding tissue (p = 0.046) with low perilesional shear wave velocities (p = 0.054), smooth lesion contours (p = 0.041), soft lesion strain elastography (p =0.001), low clip-to-lesion-surface distance (p = 0.002) and the use of an HM breast clip (p = 0.032). Conclusions: The type of breast clip-marker, as well as perilesional and lesional characteristics, influence the likelihood of clip dislocation. Notably, the hydrogel-coated clip (HM) exhibited the highest rate of dislocation. Full article

(This article belongs to the Special Issue Diagnostic Radiology for Breast Cancer)

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Diagnostics, Volume 16, Issue 12 (June-2 2026) – 195 articles

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