Diagnostics

12 pages, 432 KB

Open AccessArticle

Long-Term Evolution of Skeletal Muscle Quantity and Quality After Curative-Intent Colon Cancer Surgery: A Retrospective Cohort Study

by Argyri Papadimitriou, Michael Schneider, Salim Zenkhri, Dieter Hahnloser, David Martin, He Ayu Xu, Damien Maier, Fabio Becce, Fabian Grass and Martin Hübner

Diagnostics 2025, 15(23), 3092; https://doi.org/10.3390/diagnostics15233092 - 4 Dec 2025

Viewed by 452

Abstract

Background: Computed tomography (CT)-based sarcopenia is a promising predictor of postoperative complications and recovery. However, studies on the longitudinal evolution of skeletal muscle markers are lacking and findings regarding its correlation with survival are still not clear. Methods: We conducted a [...] Read more.

Background: Computed tomography (CT)-based sarcopenia is a promising predictor of postoperative complications and recovery. However, studies on the longitudinal evolution of skeletal muscle markers are lacking and findings regarding its correlation with survival are still not clear. Methods: We conducted a retrospective single-center cohort study of consecutive patients undergoing curative-intent colon cancer surgery. Skeletal muscle area (SMA), skeletal muscle index (SMI), skeletal muscle radiation attenuation (SMRA), and intermuscular adipose tissue (IMAT) area and index (IMATI) were measured on a single axial CT slice at the third lumbar vertebral level before surgery and at 6, 12, and 24 months after. Descriptive statistics were used to report the evolution over time of CT-based sarcopenia markers. Their correlation with overall survival was analyzed using Cox’s proportional hazards regression analysis. Results: The final cohort included 102 patients (65.7% males) with a mean age of 66 ± 13 years. Eighty-five (86.7%) patients were alive at 24 months, and forty-five (45.9%) underwent a CT scan at all time points. CT-based sarcopenia markers remained statistically stable over 2 years. Age (HR 1.07, 95% CI 1.00–1.14) and ASA score (HR 2.4, 95% CI 1.00–5.7) were negative independent predictive factors. Patients with larger differences (

Δ

) of IMAT area and IMATI at 12 months, HR 0.79 (95% CI 0.67–0.93) and 0.49 (95% CI 0.30–0.80), respectively, had a lower mortality. Conclusions: CT-based markers of skeletal muscle quantity (SMA, SMI) and quality (IMAT area, IMATI) remained statistically stable after curative-intent colon cancer surgery. No preoperative CT-based sarcopenia markers were predictive of overall survival. Larger cohorts are needed to generalize these initial findings. Full article

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

► Show Figures

Figure 1

21 pages, 6152 KB

Open AccessArticle

Structural Retinal Analysis in Toxoplasmic Retinochoroiditis: OCT Follow-Up with Three-Dimensional Reconstruction

by Ioana Damian, Adrian Pop, Adrian Groza, Elisabetta Miserocchi and Simona Delia Nicoară

Diagnostics 2025, 15(23), 3091; https://doi.org/10.3390/diagnostics15233091 - 4 Dec 2025

Viewed by 395

Abstract

Background: Ocular toxoplasmosis remains the leading cause of posterior uveitis worldwide. Optical coherence tomography (OCT) provides valuable insights into the structural alterations associated with this condition. The present study aimed to characterize the vitreous, retinal, and choroidal morphological changes observed during both [...] Read more.

Background: Ocular toxoplasmosis remains the leading cause of posterior uveitis worldwide. Optical coherence tomography (OCT) provides valuable insights into the structural alterations associated with this condition. The present study aimed to characterize the vitreous, retinal, and choroidal morphological changes observed during both the active and scarred stages of ocular toxoplasmosis using OCT imaging. A secondary objective was to evaluate the added value of three-dimensional reconstruction in the assessment of retinal lesions. Methods: A retrospective study was conducted on 12 eyes belonging to 12 patients diagnosed with toxoplasmosis retinochoroiditis (TRC). Optical coherence tomography (OCT) scans centered on the active lesions were qualitatively analyzed at baseline and follow-up. Additionally, a ResUNet model was trained to generate a full volumetric reconstruction of the retinochoroidal lesions in selected cases. Results: Twelve eyes were analyzed at a mean of 16.2 days from symptom onset. The mean follow-up duration was 144 days (range: 12–490 days). OCT imaging revealed characteristic alterations in the retina, choroid, and vitreous body, which were documented both at baseline and at follow-up. Representative cases were selected for three-dimensional reconstruction to illustrate the extent of retinal architectural involvement. Conclusions: OCT analysis refines our understanding of the structural damage associated with ocular toxoplasmosis, while three-dimensional reconstruction enhances our ability to visualize and interpret these alterations on a larger scale. Full article

(This article belongs to the Special Issue Optical Coherence Tomography in Diagnosis of Ophthalmology Disease)

► Show Figures

Figure 1

17 pages, 1724 KB

Open AccessArticle

Evaluation of Model Performance and Clinical Usefulness in Automated Rectal Segmentation in CT for Prostate and Cervical Cancer

by Paria Naseri, Daryoush Shahbazi-Gahrouei and Saeed Rajaei-Nejad

Diagnostics 2025, 15(23), 3090; https://doi.org/10.3390/diagnostics15233090 - 4 Dec 2025

Viewed by 404

Abstract

Background: Precise delineation of the rectum is crucial in treatment planning for cancers in the pelvic region, such as prostate and cervical cancers. Manual segmentation is also still time-consuming and suffers from inter-observer variability. Since there are meaningful differences in rectal anatomy between [...] Read more.

Background: Precise delineation of the rectum is crucial in treatment planning for cancers in the pelvic region, such as prostate and cervical cancers. Manual segmentation is also still time-consuming and suffers from inter-observer variability. Since there are meaningful differences in rectal anatomy between males and females, incorporating sex-specific anatomical patterns can be used to enhance the performance of segmentations. Furthermore, recent deep learning advancements have provided promising solutions for automatically classifying patient sex from CT scans and leveraging this information for enhancing the accuracy of rectal segmentation. However, their clinical utility requires comprehensive validation against real-world standards. Methods: In this study, a two-stage deep learning pipeline was developed using CT scans from 186 patients with either prostate or cervical cancer. First, a CNN model automatically classified the patient’s biological sex from CT images in order to capture anatomical variations dependent on sex. Second, a sex-aware U-Net model performed automated rectal segmentation, allowing the network to adjust its feature representation based on the anatomical differences identified in stage one. The internal validation had an 80/20 train–test split, and 15% of the training portion was held out for validation to ensure balanced distribution regarding sex and diagnosis. Model performance was evaluated using spatial similarity metrics, including the Dice Similarity Coefficient (DSC), Hausdorff Distance, and Average Surface Distance. Additionally, a radiation oncologist conducted a retrospective clinical evaluation using a 3-point Likert scale. Statistical significance was examined using Wilcoxon signed-rank tests, Welch’s t-tests, and Mann–Whitney U test. Results: The sex-classification model attained an accuracy of 94.6% (AUC = 0.98, 95% CI: 0.96–0.99). Incorporation of predicted sex into the segmentation pipeline improved anatomical consistency of U-Net outputs. Mean DSC values were 0.91 (95% CI: 0.89–0.92) for prostate cases and 0.89 (95% CI: 0.87–0.91) for cervical cases, with no significant difference between groups (p = 0.12). Surface distance metrics calculated on resampled isotropic voxels showed mean HD values of 3.4 ± 0.8 mm and ASD of 1.2 ± 0.3 mm, consistent with clinically acceptable accuracy. On clinical evaluation, 89.2% of contours were rated as excellent, while 9.1% required only minor adjustments. Automated segmentation reduced the average contouring time from 12.7 ± 2.3 min manually to 4.3 ± 0.9 min. Conclusions: The proposed sex-aware deep learning framework offers accurate, robust segmentation of the rectum in pelvic CT imaging by explicitly modeling sex-specific differences in anatomical characteristics. This physiologically informed approach enhances segmentation performance and supports reliable integration of AI-based delineation into radiotherapy workflows to improve both contouring efficiency and clinical consistency. Full article

(This article belongs to the Special Issue Medical Images Segmentation and Diagnosis)

► Show Figures

Figure 1

20 pages, 3151 KB

Open AccessArticle

MMDD: A Multimodal Multitask Dynamic Disentanglement Framework for Robust Major Depressive Disorder Diagnosis Across Neuroimaging Sites

by Qiongpu Chen, Peishan Dai, Kaineng Huang, Ting Hu and Shenghui Liao

Diagnostics 2025, 15(23), 3089; https://doi.org/10.3390/diagnostics15233089 - 4 Dec 2025

Viewed by 517

Abstract

Background/Objectives: Major Depressive Disorder (MDD) is a severe psychiatric disorder, and effective, efficient automated diagnostic approaches are urgently needed. Traditional methods for assessing MDD face three key challenges: reliance on predefined features, inadequate handling of multi-site data heterogeneity, and suboptimal feature fusion. To [...] Read more.

Background/Objectives: Major Depressive Disorder (MDD) is a severe psychiatric disorder, and effective, efficient automated diagnostic approaches are urgently needed. Traditional methods for assessing MDD face three key challenges: reliance on predefined features, inadequate handling of multi-site data heterogeneity, and suboptimal feature fusion. To address these issues, this study proposes the Multimodal Multitask Dynamic Disentanglement (MMDD) Framework. Methods: The MMDD Framework has three core innovations. First, it adopts a dual-pathway feature extraction architecture combining a 3D ResNet for modeling gray matter volume (GMV) data and an LSTM–Transformer for processing time series data. Second, it includes a Bidirectional Cross-Attention Fusion (BCAF) mechanism for dynamic feature alignment and complementary integration. Third, it uses a Gradient Reversal Layer-based Multitask Learning (GRL-MTL) strategy for enhancing the model’s domain generalization capability. Results: MMDD achieved 77.76% classification accuracy on the REST-meta-MDD dataset. Ablation studies confirmed that both the BCAF mechanism and GRL-MTL strategy played critical roles: the former optimized multimodal fusion, while the latter effectively mitigated site-related heterogeneity. Through interpretability analysis, we identified distinct neurobiological patterns: time series were primarily localized to subcortical hubs and the cerebellum, whereas GMV mainly involved higher-order cognitive and emotion-regulation cortices. Notably, the middle cingulate gyrus showed consistent abnormalities across both imaging modalities. Conclusions: This study makes two major contributions. First, we develop a robust and generalizable computational framework for objective MDD diagnosis by effectively leveraging multimodal data. Second, we provide data-driven insights into MDD’s distinct neuropathological processes, thereby advancing our understanding of the disorder. Full article

(This article belongs to the Special Issue Artificial Intelligence and Pattern Recognition Methods for the Automatic Detection and Evaluation of Neurological Disorders, 2nd Edition)

► Show Figures

Figure 1

24 pages, 2238 KB

Open AccessArticle

Heart Morphometry in Standard Second Trimester Scan

by Alexandru-Cristian Comănescu, Dragoș-Ovidiu Alexandru, Maria-Cristina Comănescu, Agnesa Preda and Mar Bennasar

Diagnostics 2025, 15(23), 3088; https://doi.org/10.3390/diagnostics15233088 - 4 Dec 2025

Viewed by 270

Abstract

Introduction: Routine second trimester anomaly scans include standard cardiac planes, yet detailed cardiac morphometry is not part of current practice. We hypothesized that a comprehensive set of cardiac measurements could be obtained from these standard views without prolonging examination time and with clinically [...] Read more.

Introduction: Routine second trimester anomaly scans include standard cardiac planes, yet detailed cardiac morphometry is not part of current practice. We hypothesized that a comprehensive set of cardiac measurements could be obtained from these standard views without prolonging examination time and with clinically meaningful reproducibility. Methods: We conducted a prospective study involving ninety-two uncomplicated singleton pregnancies undergoing routine second trimester anomaly scans. Cardiac measurements were obtained using standard ISUOG/SRUOG planes, both during the examination and offline. Feasibility, reproducibility, and the impact on scanning time were evaluated, and results were compared with established reference ranges. Results: All morphometric measurements were successfully obtained in 100% of included cases. Mean “screen time” increased only minimally from 35.45 min (95% CI 32.9–38.0) to 38.75 min (95% CI 36.1–41.4), with a non-significant mean difference of 3.30 min (p = 0.063). Most z-scores fell within ±2 SD. Intra-observer reproducibility ranged from fair to excellent, with strong correlations for major cardiac dimensions (r > 0.80 for multiple parameters). Conclusions: Comprehensive fetal cardiac morphometry can be integrated into the routine second trimester anomaly scan using standard imaging planes, without prolonging the examination. This approach may support earlier recognition of atypical growth patterns or cardiac remodeling. Full article

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

► Show Figures

Figure 1

15 pages, 1875 KB

Open AccessArticle

MS-Detector: A Hierarchical Deep Learning Method to Detect Muscle Strain Using Bilateral Symmetric Ultrasound Images of the Body

by Le Zhu, Yifu Xiong, Huachao Wu, Li Zhu, Zihan Tang, Wenbin Pei, Jing Zhou and Zhidong Xue

Diagnostics 2025, 15(23), 3087; https://doi.org/10.3390/diagnostics15233087 - 4 Dec 2025

Viewed by 350

Abstract

Background/Objectives: Muscle strain impairs mobility and quality of life, yet ultrasound diagnosis remains dependent on subjective expert interpretation, which can lead to variability in lesion detection. This study aimed to develop and evaluate MS-detector, a symmetry-aware, two-stage deep learning model that leverages bilateral [...] Read more.

Background/Objectives: Muscle strain impairs mobility and quality of life, yet ultrasound diagnosis remains dependent on subjective expert interpretation, which can lead to variability in lesion detection. This study aimed to develop and evaluate MS-detector, a symmetry-aware, two-stage deep learning model that leverages bilateral B-mode ultrasound images to automatically detect muscle strain and provide clinicians with a consistent second-reader decision-support tool in routine practice. Methods: A YOLOv5-based detector proposes candidate regions, and a Siamese convolutional neural network (CNN) compares contralateral regions to filter false positives. The dataset comprised 559 bilateral pairs from 86 patients with consensus labels. All splits were enforced at the patient level. A fixed, independent hold-out test set of 32 pairs was never used for training, tuning, or threshold selection. Five-fold cross-validation (CV) on the remaining development set was used for model selection. The operating point was pre-specified at T1 = 0.01 and T2 = 0.20. Results: The detector achieved mAP = 0.4006 (five-fold CV mean). On the hold-out set at the pre-specified operating point, MS-detector attained recall = 0.826 and precision = 0.486, improving F1/F2 over the YOLOv5 baseline by increasing precision with an acceptable recall trade-off. A representative figure illustrates the reduction in low-confidence false positives after filtering; this example is illustrative rather than aggregate. Conclusions: Leveraging contralateral symmetry in a hierarchical scheme improves detection precision while maintaining clinically acceptable recall, supporting MS-detector as a decision-support tool. Future work will evaluate generalizability across scanners and centers and assess calibrated probabilistic fusion and lesion grading. Full article

(This article belongs to the Special Issue 3rd Edition: AI/ML-Based Medical Image Processing and Analysis)

► Show Figures

Figure 1

30 pages, 1289 KB

Open AccessReview

Omics Sciences in Dentistry: A Narrative Review on Diagnostic and Therapeutic Applications for Prevalent Oral Diseases

by Marco Lollobrigida, Giulia Mazzucchi and Alberto De Biase

Diagnostics 2025, 15(23), 3086; https://doi.org/10.3390/diagnostics15233086 - 4 Dec 2025

Viewed by 591

Abstract

Omics sciences are revolutionizing the field of biomedical and dental research by allowing for an integrated understanding of the molecular basis of health and disease. This narrative review analyzes the role of these novel technologies supporting the diagnosis, prognosis, and treatment of the [...] Read more.

Omics sciences are revolutionizing the field of biomedical and dental research by allowing for an integrated understanding of the molecular basis of health and disease. This narrative review analyzes the role of these novel technologies supporting the diagnosis, prognosis, and treatment of the most noteworthy oral diseases, such as dental caries, periodontitis, and oral squamous cell carcinoma. The review discusses the characterization of disease-associated genetic variations and polygenic risk scores as evidenced by genomic studies. It further examines how transcriptomic analyses can identify diagnostic gene expression signatures of immune dysregulation and tumor heterogeneity. The contribution of proteomics and metabolomics studies to the discovery of diagnostic and prognostic protein and metabolites biomarkers is also analyzed. Finally, the integration of different omics datasets within multi-omics frameworks is discussed as a key approach for a holistic interpretation of oral pathogenesis and data-driven precision dentistry. The review also addresses current limitations in the clinical translation of omics sciences into tools for early diagnosis, personalized prevention, and targeted therapy. Full article

(This article belongs to the Special Issue Recent Updates on the Diagnosis of Dental and Oral Diseases, Second Edition)

► Show Figures

Figure 1

19 pages, 1107 KB

Open AccessArticle

Liver Tissue Mapping in Transfusion-Dependent β-Thalassemia: Reproducibility and Clinical Insights from Multiparametric MRI

by Antonella Meloni, Riccardo Bisi, Vincenzo Positano, Aldo Carnevale, Nicola Pegoraro, Laura Pistoia, Anna Spasiano, Elisabetta Corigliano, Antonella Cossu, Emanuela De Marco, Ilaria Fotzi, Petra Keilberg, Alberto Clemente and Alberto Cossu

Diagnostics 2025, 15(23), 3085; https://doi.org/10.3390/diagnostics15233085 - 4 Dec 2025

Viewed by 349

Abstract

Background/Objectives: We measured hepatic T2*, T1, and T2 values in N = 81 transfusion-dependent thalassemia (TDT) patients to assess and compare their reproducibility, evaluate their correlations with demographics and clinical parameters, and explore their association with disease-related complications. Methods: All TDT patients [...] Read more.

Background/Objectives: We measured hepatic T2*, T1, and T2 values in N = 81 transfusion-dependent thalassemia (TDT) patients to assess and compare their reproducibility, evaluate their correlations with demographics and clinical parameters, and explore their association with disease-related complications. Methods: All TDT patients (52 females, 38.13 ± 10.79 years), were enrolled in the Extension-Myocardial Iron Overload in Thalassaemia Network. The magnetic resonance imaging protocol (1.5 T) included: multi-echo gradient echo sequences for T2* relaxometry, modified look-locker inversion recovery (MOLLI) sequences for T1 mapping, and multi-echo fast-spin-echo (MEFSE) sequences for T2 mapping. Results: All three relaxation times demonstrated good intra- and inter-observer reproducibility and were significantly correlated with each other. Of the 59 patients with reduced T2*, 45 (76.3%) also had reduced T1, and 42 (71.2%) had reduced T2 values. Among 22 patients with normal T2*, 3 (13.6%) exhibited reduced T1. No patients showed increased T1, and only one had elevated T2. Liver relaxation times were not associated with gender or splenectomy status. All relaxation times inversely correlated with serum ferritin levels, while T2 and T2* inversely correlated with mean alanine aminotransferase levels. Cirrhosis and glucose metabolism alterations were associated with lower relaxation times. All three relaxation times effectively discriminated between the absence and presence of cirrhosis [areas under the curve (AUCs) with 95% confidence intervals (CIs): 0.85 (0.75–0.92) for T2*, 0.78 (0.68–0.87) for T1, and 0.92 (0.84–0.97) for T2]. T2* showed comparable accuracy to T1 and T2, while a significant difference was observed between T1 and T2 values. All liver relaxation times demonstrated similar diagnostic performance in identifying glucose metabolism alterations [AUCs with 95% CIs: 0.67 (0.55–0.77) for T2*, 0.69 (0.57–0.79) for T1, and 0.67 (0.56–0.77) for T2]. Conclusions: In TDT, a comprehensive assessment of hepatic relaxation times may enhance clinical monitoring and management of iron overload and its related complications. Full article

(This article belongs to the Special Issue Diagnostic and Clinical Application of Magnetic Resonance Imaging—2nd Edition)

► Show Figures

Figure 1

15 pages, 3861 KB

Open AccessArticle

Segmental Non-Mass Enhancement Features in Breast Magnetic Resonance Imaging: A Multicenter Retrospective Study of Histopathologic Correlations

by Hale Aydin, Cansu Bozkurt, Serhat Hayme, Almila Coskun Bilge, Pelin Seher Oztekin, Aydan Avdan Aslan, Irem Ozcan, Serap Gultekin, Abdulkadir Eren and Irmak Durur Subası

Diagnostics 2025, 15(23), 3084; https://doi.org/10.3390/diagnostics15233084 - 4 Dec 2025

Viewed by 585

Abstract

Background/Objectives: Segmental non-mass enhancement (NME) is the breast MRI distribution pattern with the highest positive predictive value (PPV) for malignancy. Despite its diagnostic relevance, its imaging characteristics have rarely been examined in isolation, leaving uncertainty in clinical practice. This multicenter retrospective cohort [...] Read more.

Background/Objectives: Segmental non-mass enhancement (NME) is the breast MRI distribution pattern with the highest positive predictive value (PPV) for malignancy. Despite its diagnostic relevance, its imaging characteristics have rarely been examined in isolation, leaving uncertainty in clinical practice. This multicenter retrospective cohort study aimed to evaluate multiparametric MRI features—including internal enhancement pattern, dynamic contrast-enhanced (DCE) kinetics, and diffusion restriction—in segmental NME to identify malignancy predictors. Methods: This retrospective cohort review included 14,834 breast MRI reports from five institutions (September 2017–February 2024), identifying 103 women (mean age, 44.4 ± 9.9 years) with segmental NME (70 malignant, 33 benign). MRI was performed at 1.5 T or 3 T using standardized protocols. Two breast radiologists, blinded to pathology, assessed internal enhancement, DCE kinetics, diffusion restriction, and short tau inversion recovery (STIR) features according to BI-RADS. Statistical analyses included chi-square/Fisher’s tests and logistic regression. Results: Clustered ring enhancement (CRE) was significantly associated with malignancy (p = 0.004). Fast initial-phase enhancement (p < 0.001) and delayed-phase washout (p = 0.011) also correlated with malignancy. On multivariate analysis, fast initial-phase enhancement remained an independent predictor (odds ratio [OR] = 5.133, p = 0.031), whereas slow enhancement predicted benignity (OR = 0.194, p = 0.020). Histologies included ductal carcinoma in situ, invasive ductal carcinoma, granulomatous mastitis, and benign hyperplastic lesions. Conclusions: This study, focusing exclusively on segmental NME, identifies CRE, fast initial-phase enhancement, and washout kinetics as reliable imaging biomarkers. Incorporating these features into breast MRI interpretation may improve diagnostic accuracy, risk stratification, and management decisions. Full article

(This article belongs to the Special Issue Diagnosis, Prognosis and Management of Breast Cancer)

► Show Figures

Figure 1

16 pages, 4428 KB

Open AccessArticle

Depth-Resolved OCT of Root Canal Walls After Diode-Laser Irradiation: A Descriptive Ex Vivo Study Following a Stereomicroscopy Report

by Adrian Ştefan Stănuşi, Oana Andreea Diaconu, Andreea Stănuşi, Eugen Osiac, Mihaela Roxana Brătoiu, Gabriel-Sebastian Petrescu, Adelina Smaranda Bugălă, Bogdan Dimitriu and Mihaela Jana Ţuculină

Diagnostics 2025, 15(23), 3083; https://doi.org/10.3390/diagnostics15233083 - 4 Dec 2025

Viewed by 356

Abstract

Background/Objectives: Diode lasers are used as adjuncts for endodontic disinfection, but their depth-resolved effects on root dentin are insufficiently described. This ex vivo study used optical coherence tomography (OCT) to qualitatively document laser-related morphological signatures on canal walls. Methods: Palatal roots [...] Read more.

Background/Objectives: Diode lasers are used as adjuncts for endodontic disinfection, but their depth-resolved effects on root dentin are insufficiently described. This ex vivo study used optical coherence tomography (OCT) to qualitatively document laser-related morphological signatures on canal walls. Methods: Palatal roots from extracted maxillary first molars were standardized and hemisectioned to create specimens allocated to a conventional diode-laser protocol, a higher-power protocol, or control. A 940-nm diode laser with endodontic tips was applied per group. Swept-source OCT acquired serial B-scans along the root length. Two endodontists reviewed images for thermally induced morphological alterations (TIMAs). Reporting is descriptive. Results: OCT revealed laser-related hyper-reflective linear/radial signatures extending from the canal lumen toward the external root surface in laser-treated specimens. Qualitatively, signatures appeared more conspicuous and extended deeper with the higher-power protocol than with the conventional protocol. Findings were most evident in the coronal/middle thirds. Control specimens served to contextualize background appearances from preparation and sectioning. Representative B-scans illustrate typical patterns. The novelty of the present study results from the identification of areas of morphological alteration through the OCT examination of the walls of the root canals. Conclusions: Depth-resolved OCT can visualize dentinal alterations associated with diode-laser irradiation in an ex vivo model. These observations support careful parameter selection and motivate in situ studies with concurrent temperature monitoring and histologic correlation. Full article

(This article belongs to the Special Issue Advances in Optical Coherence Tomography in 2025)

► Show Figures

Figure 1

17 pages, 700 KB

Open AccessSystematic Review

Trochlear Nerve Palsy: A Systematic Review of Etiologies and Diagnostic Insights

by Areti Alexandrou, Nicholas Georgiou, George G. Botis, Ioannis Vezakis, George Triantafyllou, Eirini Christodoulaki, Harris Pishiaras, Alexandros Samolis, Nikiforos Christakos, Theodosis Kalamatianos, Ioannis Lamprianidis, Ioannis Kakkos, George K. Matsopoulos, George Tsakotos, Ourania Tzortzi and Maria Piagkou

Diagnostics 2025, 15(23), 3082; https://doi.org/10.3390/diagnostics15233082 - 3 Dec 2025

Viewed by 757

Abstract

Background/Objectives: Trochlear nerve palsy (TNP) is a clinically significant neuro-ophthalmic disorder with a broad and heterogeneous etiologic spectrum. Due to the trochlear nerve (TN)’s long intracranial course and its proximity to key neurosurgical corridors, it is particularly susceptible to injury. This systematic review [...] Read more.

Background/Objectives: Trochlear nerve palsy (TNP) is a clinically significant neuro-ophthalmic disorder with a broad and heterogeneous etiologic spectrum. Due to the trochlear nerve (TN)’s long intracranial course and its proximity to key neurosurgical corridors, it is particularly susceptible to injury. This systematic review aimed to synthesize contemporary evidence on TNP etiologies and highlight diagnostic considerations. Methods: Following PRISMA 2020 guidelines (PROSPERO registration: CRD420251150614), we systematically searched PubMed through July 2025 for studies reporting TNP etiologies. Given substantial heterogeneity in study populations and methodologies, a qualitative synthesis was performed examining study characteristics, patient demographics, etiological distribution, and clinical outcomes. Results: Thirty-three studies (n = 5785) met the inclusion criteria. Reported etiologies clustered into seven categories: congenital, vascular/ischemic, infectious/inflammatory, structural, traumatic, iatrogenic, and idiopathic. Congenital cases frequently demonstrated absence of the TN or superior oblique hypoplasia. Microvascular ischemia predominated in older adults with vascular risk factors and typically exhibited spontaneous recovery. Structural lesions (e.g., tumors, aneurysms) and trauma were major acquired causes, often associated with more persistent deficits. Iatrogenic palsy predominantly followed skull base and petroclival procedures; most cases resolved, although lasting dysfunction occurred after complex or radiosurgical interventions. A proportion of cases remained idiopathic, and many resolved spontaneously. Conclusions: TNP displays a broad etiologic spectrum with distinct clinical profiles and prognostic trajectories. Accurate etiologic classifications supported by targeted neuroimaging and focused clinical evaluation are essential for optimizing management and informing neurosurgical decision-making. Full article

(This article belongs to the Special Issue Imaging and Diagnosis in Neurosurgery)

► Show Figures

Figure 1

25 pages, 9160 KB

Open AccessArticle

Diagnosis of Schizophrenia Using Multimodal Data and Classification Using the EEGNet Framework

by Nandini Manickam, Vijayakumar Ponnusamy and Arul Saravanan

Diagnostics 2025, 15(23), 3081; https://doi.org/10.3390/diagnostics15233081 - 3 Dec 2025

Viewed by 577

Abstract

Background/Objectives: In recent years, people have been facing a lot of difficulties in handling stress, emotions, social, and behavioral issues, which have led to severe mental disorders. Schizophrenia is one disorder that requires more attention. This disorder is characterized by positive or [...] Read more.

Background/Objectives: In recent years, people have been facing a lot of difficulties in handling stress, emotions, social, and behavioral issues, which have led to severe mental disorders. Schizophrenia is one disorder that requires more attention. This disorder is characterized by positive or psychotic symptoms, negative symptoms, and cognitive symptoms, which makes diagnosis and treatment complicated. The main objective is to identify the degree of severity of symptoms through multimodal data and classify them using the EEGNet framework. Methods: Multimodal data are collected. To identify the severity of symptoms of schizophrenia, initial screening is performed through assessment tools such as the Positive and Negative Symptoms Scale (PANSS), Brief Negative Symptom Scale (BNSS), Scale for Assessment of Negative Symptoms (NSA-16), and Scale for Assessment of Positive Symptoms (SAPS). Designed photo elicitation and VR box video stimuli are used for data collection. The patients are asked to express their thoughts upon viewing photos shown through a photo elicitation task. The patients are given Virtual Reality (VR) stimuli where videos will be played in a VR box and patients are asked to express their thoughts. Patients’ facial expressions and speech signals are captured through webcam while performing these tasks. Finally, the electrical activities of the patients are assessed through a 14-channel EEG headset. A novel method of fusing and embedding of normalized multimodality features into the EEGNet architecture is carried out that enables combined utilization of electrophysiological information from EEG and complementary behavioral–affective cues from other modalities, thereby enhancing classification performance while retaining the architectural efficiency of EEGNet. Results: The reliability and validity of the questionnaire are statistically analyzed and found to be α = 0.761. The sum of variance of PANSS is about 27.08, SAPS is about 28.61, and BNSS is about 29.92 with p < 0.05. This EEGNet model displays an accuracy of 0.99, precision of 0.99, recall of 0.98, and F1-score of 0.99 for healthy and a precision of 0.98, recall of 0.99, and F1-score of 0.99 for schizophrenia-affected patients and ROC AUC of about 0.9989. Conclusions: This system proves to be a promising method for the diagnosis of schizophrenia and thereby enhances the performance of the system. Full article

(This article belongs to the Special Issue The Future of Diagnostics: Exploring the Role of Artificial Intelligence in Medicine)

► Show Figures

Figure 1

14 pages, 3540 KB

Open AccessCase Report

Digitally Guided Modified Intentional Replantation for a Tooth with Hopeless Periodontal Prognosis: A Case Report

by Raul Cuesta Román, Ángel Arturo López-González, Joan Obrador de Hevia, Sebastiana Arroyo Bote, Hernán Paublini Oliveira and Pere Riutord-Sbert

Diagnostics 2025, 15(23), 3080; https://doi.org/10.3390/diagnostics15233080 - 3 Dec 2025

Viewed by 539

Abstract

Background and Clinical Significance: Advanced periodontitis with severe vertical bone loss and grade III mobility is usually managed by extraction and implant placement. Digital workflows and modern regenerative techniques have opened the possibility of preserving teeth that would traditionally be considered for extraction. [...] Read more.

Background and Clinical Significance: Advanced periodontitis with severe vertical bone loss and grade III mobility is usually managed by extraction and implant placement. Digital workflows and modern regenerative techniques have opened the possibility of preserving teeth that would traditionally be considered for extraction. This report describes a digitally guided modified intentional replantation (MIR) protocol applied to a maxillary tooth with severe periodontal involvement and unfavourable prognosis. Case Presentation: A 68-year-old male, non-smoker, with a history of heart transplantation under stable medical control, presented with generalized Stage IV, Grade C periodontitis. Tooth 21 showed >75% vertical bone loss, probing depths ≥ 9 mm, bleeding on probing, and grade III mobility. After non-surgical therapy and periodontal stabilization, a CAD/CAM-assisted MIR procedure was planned. Cone-beam computed tomography (CBCT) and a 3D-printed tooth replica were used to design a surgical guide for a new recipient socket. The tooth was atraumatically extracted, stored in chilled sterile saline, and managed extraorally for approximately 10 min. Apicoectomy and retrograde sealing with Biodentine^® were performed, followed by immediate replantation into the digitally prepared socket, semi-rigid splinting, and guided tissue regeneration using autologous bone chips, xenograft (Bio-Oss^®), enamel matrix derivative (Emdogain^®), and a collagen membrane (Bio-Gide^®). A conventional orthograde root canal treatment was completed within the first month. At 12 months, tooth 21 exhibited grade 0 mobility, probing depths of 3–4 mm without bleeding on probing, and stable soft tissues. Standardized periapical radiographs and CBCT showed radiographic bone fill within the previous defect and a continuous periodontal ligament-like space, with no signs of ankylosis or root resorption. The tooth was fully functional and asymptomatic. Conclusions: In this medically complex patient, digitally guided MIR allowed preservation of a tooth with severe periodontal involvement and poor prognosis, achieving favourable short-term clinical and radiographic outcomes. While long-term data and larger series are needed, MIR may be considered a tooth-preserving option in carefully selected cases as an alternative to immediate extraction and implant placement. Full article

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

► Show Figures

Figure 1

9 pages, 1176 KB

Open AccessArticle

Long-Term (>10 Years) Effects of Medical and Surgical Airway Obstruction Treatment on Dentofacial Morphology

by Anthony T. Macari, Annie Babakhanian, Ingrid Karam and Joseph G. Ghafari

Diagnostics 2025, 15(23), 3079; https://doi.org/10.3390/diagnostics15233079 - 3 Dec 2025

Viewed by 333

Abstract

Airway obstruction may lead to dentofacial dysmorphogenesis, with severity influenced by age, duration, and extent of obstruction. Aims: to evaluate long-term craniofacial changes in children with a history of mouth breathing, comparing outcomes between those treated with lymphoid tissue removal or with medication, [...] Read more.

Airway obstruction may lead to dentofacial dysmorphogenesis, with severity influenced by age, duration, and extent of obstruction. Aims: to evaluate long-term craniofacial changes in children with a history of mouth breathing, comparing outcomes between those treated with lymphoid tissue removal or with medication, and considering treatment age. Materials and Methods: Fifty-seven patients with a mean age of 19.09 years (range: 15.1–25.2 years) who had been evaluated in an earlier study (T1) were recalled at an average of 13 years follow-up (T2) and classified into a surgical group (n = 34), who had an adenoidectomy, and a non-surgical group (n = 23) treated with medication. Lateral cephalograms were obtained and compared with the original pre-treatment records. Control groups were included, matching the subjects in both groups for age and sex. Statistical analyses included group comparisons and associations among variables. Results: Significant improvement in both treatment groups were observed for the gonial angle (Ar-Go-Me), facial convexity (S-N-Me) and facial height (N-Gn), but T2-T1 changes in the surgical group were statistically significantly greater than in the medical therapy group. The palatal plane inclination to the horizontal (PP/H) and the mandibular plane inclination (MP/H) and to cranial base (MP/SN) were significantly improved in both groups (0.001 < p < 0.01). Conclusions: Both surgical and medical treatment of airway obstruction resulted in the reversal of the harmful effect of the obstruction. However, adenoidectomy was associated with greater improvements, possibly because the original obstruction was more severe and longer-standing. The results underline the importance of early recognition and management of airway obstruction to mitigate developmental orofacial dysmorphology. Full article

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

► Show Figures

Figure 1

20 pages, 652 KB

Open AccessReview

The Evolving Role of Cine MRI in Crohn’s Disease: From Functional Motility Analysis to Precision Management: A Review of the Last 10 Years

by Ali S. Alyami

Diagnostics 2025, 15(23), 3078; https://doi.org/10.3390/diagnostics15233078 - 3 Dec 2025

Viewed by 400

Abstract

Cine (dynamic) MRI is a non-invasive MRI technique that captures moving images and can be valuable in evaluating inflammatory bowel disease (IBD). This sequence shows emerging potential in providing functional data to assess bowel motility patterns, to aid in the differentiation between predominantly [...] Read more.

Cine (dynamic) MRI is a non-invasive MRI technique that captures moving images and can be valuable in evaluating inflammatory bowel disease (IBD). This sequence shows emerging potential in providing functional data to assess bowel motility patterns, to aid in the differentiation between predominantly inflammatory (showing reduced peristalsis) and fibrotic strictures (rigid, non-motile segments) and detecting functional obstructions in Crohn’s disease (CD). Unlike static MRI, cine MRI enables clinicians to observe peristaltic movements, aiding in disease characterization and treatment monitoring. Its non-invasive nature and lack of ionizing radiation make it especially useful for repeated assessments in CD. Studies indicate it improves diagnostic accuracy when used with conventional MRI sequences, providing a complementary, functional dimension to the comprehensive management of this chronic condition. While the functional assessment offered by cine MRI presents a significant advantage over conventional static imaging, its clinical translation is currently challenged by high technical variability. Specifically, there is a distinct lack of standardized acquisition protocols (such as field strength, sequence parameters), post-processing software, and universally validated quantitative motility metrics (such as motility index). Therefore, a primary objective of this review is not only to summarize the evolving diagnostic and monitoring applications of cine MRI but also to critically address the methodological inconsistencies and reproducibility hurdles that must be overcome before this technique can be fully integrated into clinical guidelines for precision management of CD. Full article

(This article belongs to the Special Issue Advancements in the Diagnosis and Treatment of Inflammatory Bowel Diseases)

► Show Figures

Figure 1

7 pages, 2641 KB

Open AccessCase Report

Fever of Unknown Origin and Penetrating Aortic Ulcer Successfully Treated with Thoracic Endovascular Aortic Repair—A Case Report

by Tomislav Jakljević, Franka Kunovac, Tatjana Zekić and Vjekoslav Tomulić

Diagnostics 2025, 15(23), 3077; https://doi.org/10.3390/diagnostics15233077 - 3 Dec 2025

Viewed by 372

Abstract

Background and Clinical Significance: Fever of undetermined origin (FUO is a diagnostic challenge. It is essential to exclude infections, paraneoplastic syndromes, and large-vessel vasculitis (LVV). Case presentation: We describe a 59-year-old female with FUO and no apparent signs of infection. Laboratory [...] Read more.

Background and Clinical Significance: Fever of undetermined origin (FUO is a diagnostic challenge. It is essential to exclude infections, paraneoplastic syndromes, and large-vessel vasculitis (LVV). Case presentation: We describe a 59-year-old female with FUO and no apparent signs of infection. Laboratory results were consistent with inflammation (ESR 83, CRP 203 (ref. value (RV) < 5 mg/dl), ferritin 311 (RV < 120 µg/L), microcytic anemia, thrombocytosis. With administration of both ceftriaxone and levofloxacin, a decrease in CRP was monitored (51 mg/L). HRCT of the chest, abdomen, and pelvis revealed a saccular aneurysm of the descending thoracic aorta and an ectatic right common iliac artery. Due to suspicion of LVV, CT angiography was performed to exclude inflammatory changes in the blood vessels. Diffuse atherosclerosis with a 30 mm penetrating thoracic aortic ulcer (PAU) was found. PET-CT and leukocyte scintigraphy were used to rule out vasculitis and infection. The patient was successfully treated with Thoracic Endovascular Aortic Repair (TEVAR). Conclusions: As sophisticated imaging techniques become more widely used, more PAUs are being detected as incidental abnormalities in individuals without acute aortic syndrome. With adequate management, many people with PAU can live a stable and healthy life without experiencing significant consequences. Full article

(This article belongs to the Special Issue Insights into Imaging Diagnosis of Heart Disease)

► Show Figures

Figure 1

9 pages, 231 KB

Open AccessReview

AI-Driven Advances in Women’s Health Diagnostics: Current Applications and Future Directions

by Christian Macedonia

Diagnostics 2025, 15(23), 3076; https://doi.org/10.3390/diagnostics15233076 - 3 Dec 2025

Viewed by 891

Abstract

Background: Women’s health has historically served as an incubator for major medical innovations yet often faces relative neglect in sustained funding and implementation. The rise of artificial intelligence (AI) and machine learning (ML) presents both opportunities and risks for diagnostics in obstetrics and [...] Read more.

Background: Women’s health has historically served as an incubator for major medical innovations yet often faces relative neglect in sustained funding and implementation. The rise of artificial intelligence (AI) and machine learning (ML) presents both opportunities and risks for diagnostics in obstetrics and gynecology (OB/GYN). Methods: A narrative review (January 2018–August 2025) integrating peer-reviewed literature and clinical exemplars was conducted. OB/GYN relevance, clinical validation/scale, near-term outcome impact, and domain diversity were prioritized in selection. Results: We highlight ten promising AI applications across imaging, laboratory diagnostics, patient monitoring/digital biomarkers, and decision support, including AI-enhanced fetal ultrasound, cervical screening, preeclampsia prediction with cell-free RNA, noninvasive endometriosis testing, remote maternal–fetal monitoring, and reinforcement-learning decision support in gynecologic oncology. Conclusions: AI shows transformative potential for women’s health diagnostics but requires attention to bias, privacy, regulatory evolution, reimbursement, and workflow integration. Equity-focused development and diverse datasets are essential to ensure benefits accrue broadly. Full article

(This article belongs to the Special Issue Game-Changing Concepts in Reproductive Health)

12 pages, 510 KB

Open AccessArticle

Association Between Pneumoconiosis and Pleural Empyema: A Retrospective Cohort Study

by Khay-Seng Soh, Cheng-Li Lin, Wei-Ming Lee and Der-Yang Cho

Diagnostics 2025, 15(23), 3075; https://doi.org/10.3390/diagnostics15233075 - 3 Dec 2025

Viewed by 437

Abstract

Background: Pneumoconiosis is associated with chronic pulmonary and systemic complications, yet its relationship with pleural empyema remains insufficiently defined. This study evaluated the risk of pleural empyema among individuals with pneumoconiosis using a nationwide population-based cohort. Methods: Using Taiwan’s National Health Insurance database, [...] Read more.

Background: Pneumoconiosis is associated with chronic pulmonary and systemic complications, yet its relationship with pleural empyema remains insufficiently defined. This study evaluated the risk of pleural empyema among individuals with pneumoconiosis using a nationwide population-based cohort. Methods: Using Taiwan’s National Health Insurance database, we identified 14,441 patients with newly diagnosed pneumoconiosis and 57,764 matched controls by age, sex, and index year. Pleural empyema was ascertained using ICD-based definitions. Cox proportional hazards models, stratified and cluster-adjusted to account for matched design, were used to estimate hazard ratios (HRs). Competing-risk models, propensity score matching, E-value estimation, and mediation analysis were performed to evaluate robustness and residual confounding. Results: During follow-up, the incidence of pleural empyema was significantly higher in the pneumoconiosis cohort than in controls (2.33 vs. 1.02 per 1000 person-years). Pneumoconiosis was associated with an increased risk of pleural empyema (adjusted HR = 1.79, 95% CI: 1.47–2.18), consistent across subgroup analyses and competing-risk models. The strongest associations were observed among younger individuals and those without comorbidities. Sensitivity analyses, including 1:1 propensity score matching, yielded similar effect estimates. The E-value suggested that only a strong unmeasured confounder could fully explain the observed association. Conclusions: Patients with pneumoconiosis face a substantially elevated risk of developing pleural empyema, independent of demographic factors, comorbidities, corticosteroid use, and healthcare utilization. Intensified monitoring for pleural complications in pneumoconiosis patients who develop respiratory infections may lead to earlier diagnosis and a reduction in the negative outcomes associated with pleural empyema. Full article

(This article belongs to the Special Issue Advances in Pulmonary and Critical Care Medicine: Diagnosis and Management)

► Show Figures

Figure 1

3 pages, 483 KB

Open AccessInteresting Images

Zolpidem-Associated Dermatitis Artefacta—An Unusual Cause of Cicatricial Alopecia

by Martyna Sławińska, Krzysztof Sadko, Beata Zagórska and Małgorzata Sokołowska-Wojdyło

Diagnostics 2025, 15(23), 3074; https://doi.org/10.3390/diagnostics15233074 - 3 Dec 2025

Viewed by 333

Abstract

We present the case of a 95-year-old female patient who presented with erosions and scarring of the scalp, accompanied by long-term hair loss. Due to multiple comorbidities, she was treated with several medications, including zolpidem for insomnia. Clinical examination revealed scars and ulcers [...] Read more.

We present the case of a 95-year-old female patient who presented with erosions and scarring of the scalp, accompanied by long-term hair loss. Due to multiple comorbidities, she was treated with several medications, including zolpidem for insomnia. Clinical examination revealed scars and ulcers in the parietal region, along with diffuse age-related hair thinning. Histopathological analysis demonstrated scarring alopecia with features of local trauma. This case illustrates a rare instance of secondary cicatricial alopecia associated with zolpidem-induced complex sleep-related amnestic behavior. Detailed information on the patient’s medication history was crucial for establishing the correct diagnosis. Full article

(This article belongs to the Special Issue Advances in Diagnosis and Management of Skin Diseases)

► Show Figures

Figure 1

13 pages, 242 KB

Open AccessArticle

Increased Worry Associated with Self-Reported, but Not Informant-Reported, Subjective Cognitive Decline Predicts Increased Risk of Incident Dementia

by Katya T. Numbers, Ben C. P. Lam, Suraj Samtani, Russell J. Chander, Ashleigh S. Vella, Perminder S. Sachdev and Henry Brodaty

Diagnostics 2025, 15(23), 3073; https://doi.org/10.3390/diagnostics15233073 - 3 Dec 2025

Viewed by 388

Abstract

Background: Subjective cognitive complaints (SCC) have emerged as an important predictor of future dementia, with the SCD-plus framework emphasizing the prognostic value of cognitive concern and informant corroboration. Most research has focused on the presence or persistence of concern rather than examining [...] Read more.

Background: Subjective cognitive complaints (SCC) have emerged as an important predictor of future dementia, with the SCD-plus framework emphasizing the prognostic value of cognitive concern and informant corroboration. Most research has focused on the presence or persistence of concern rather than examining trajectories of change over time. Objective: To determine if baseline levels and longitudinal trajectories of SCC concern from both participants and informants independently predict incident dementia over 10 years. Methods: Data were from 873 community-dwelling older adults (mean age 78.65 years) in the Sydney Memory and Ageing Study. Employing latent growth curve modelling, we analyzed binary SCC and concern variables. Cox proportional hazards models examined the association between concern trajectories and incident dementia over a 10-year follow-up, controlling for demographic and clinical factors. Results: Both participant-reported (Hazard Ratio [HR] = 1.21) and informant-reported (HR = 1.32) SCC concern at baseline independently predicted dementia risk. Notably, increasing participant SCC concern over time conferred substantial additional risk (HR = 10.23), while changes in informant concern did not significantly improve dementia risk prediction. Conclusions: Both participant and informant reports of SCC concern provide valuable but distinct prognostic information for dementia risk. The substantial predictive value of increasing participant concern over time highlights the importance of monitoring subjective cognitive experiences longitudinally. These findings support the clinical utility of tracking concern trajectories and suggest that the patient’s evolving perspective may be particularly sensitive to underlying pathological processes. Full article

(This article belongs to the Special Issue Neurodiagnostics in Public Health: Cognitive Decline, Mental Health, and Emerging Technologies)

14 pages, 1101 KB

Open AccessArticle

Morphological Analysis of the Cavernous Segment of the Internal Carotid Artery: A Retrospective, Single Center Study of Its Clinical Significance

by Kristian Bechev, Nina Yotova, Marin Kanarev, Anelia Petrova, Kostadin Kostadinov, Galabin Markov and Daniel Markov

Diagnostics 2025, 15(23), 3072; https://doi.org/10.3390/diagnostics15233072 - 3 Dec 2025

Viewed by 448

Abstract

Background/Objectives: The cavernous segment of the internal carotid artery (ICA) is a critical neurovascular structure with complex cranial nerve relationships. Understanding its morphometric variability is essential for safe microsurgical and endovascular procedures. This study aimed to characterize the morphometry of the cavernous ICA [...] Read more.

Background/Objectives: The cavernous segment of the internal carotid artery (ICA) is a critical neurovascular structure with complex cranial nerve relationships. Understanding its morphometric variability is essential for safe microsurgical and endovascular procedures. This study aimed to characterize the morphometry of the cavernous ICA using Magnetic resonance imaging (MRI) and assess associations with demographic variables. Methods: A retrospective observational study was conducted on 135 MRI scans of adult patients, distributed among 79 women and 56 men with an average age of 50.8 years, without cerebrovascular pathology, performed between March 2023 and January 2025. The diameters of the left and right cavernous ICA and the intercarotid distance were measured using RadiAnt DICOM Viewer. Statistical analyses included descriptive statistics, t-tests, correlations, and multivariate regression models adjusted for age and sex. Principal component and cluster analyses were applied to identify morphometric patterns. Results: The mean left and right ICA diameters were both 5.09 ± 0.65 mm, with a mean intercarotid distance of 17.4 ± 4.22 mm. No age-related associations were found (p > 0.05). Male patients showed significantly larger right ICA diameters (p = 0.008). Bilateral symmetry was confirmed (p > 0.05). Two morphometric clusters were identified: Morphotype 1 (larger ICA caliber and narrower spacing) and Morphotype 2 (smaller caliber and wider spacing), showing a significant sex distribution difference (p = 0.012). Conclusions: The cavernous ICA demonstrates stable bilateral symmetry with minor sex-dependent differences. Morphometric characterization supports safer planning of transsphenoidal, endovascular, and skull-base surgeries by reducing the risk of iatrogenic neurovascular injury. Full article

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

► Show Figures

Figure 1

24 pages, 557 KB

Open AccessReview

A Comprehensive Review Comparing Artificial Intelligence and Clinical Diagnostic Approaches for Dry Eye Disease

by Manal El Harti, Said Jai Andaloussi and Ouail Ouchetto

Diagnostics 2025, 15(23), 3071; https://doi.org/10.3390/diagnostics15233071 - 2 Dec 2025

Viewed by 619

Abstract

This paper provides an overview of artificial intelligence (AI) applications in ophthalmology, with a focus on diagnosing dry eye disease (DED). We aim to synthesize studies that explicitly compare AI-based diagnostic models with clinical tests employed by ophthalmologists, examine results obtained using similar [...] Read more.

This paper provides an overview of artificial intelligence (AI) applications in ophthalmology, with a focus on diagnosing dry eye disease (DED). We aim to synthesize studies that explicitly compare AI-based diagnostic models with clinical tests employed by ophthalmologists, examine results obtained using similar imaging modalities, and identify recurring limitations to propose recommendations for future work. We conducted a systematic literature search following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines across four databases: Google Scholar, PubMed, ScienceDirect, and the Cochrane Library. We targeted studies published between 2020 and 2025 and applied predefined inclusion criteria to select 30 original peer-reviewed articles. We then analyzed each study based on the AI models used, development strategies, diagnostic performance, correlation with clinical parameters, and reported limitations. The imaging modalities covered include videokeratography, smartphone-based imaging, tear film interferometry, anterior segment optical coherence tomography, infrared meibography, in vivo confocal microscopy, and slit-lamp photography. Across modalities, deep learning models (e.g., U-shaped Convolutional Network (U-Net), Residual Network (ResNet), Densely Connected Convolutional Network (DenseNet), Generative Adversarial Networks (GANs), transformers) demonstrated promising performance, often matching or surpassing clinical assessments, with reported accuracies ranging from 82% to 99%. However, few studies performed external validations or addressed inter-expert variability. The findings confirm AI’s potential in DED diagnosis, but emphasize gaps in data diversity, clinical use, and reproducibility. It offers practical recommendations for future research to bridge these gaps and support AI deployment in routine eye care. Full article

(This article belongs to the Special Issue New Perspectives in Ophthalmic Imaging)

► Show Figures

Figure 1

20 pages, 2479 KB

Open AccessArticle

Predictors of Unfavorable Outcomes in Diabetic Foot Ulcers

by Renata Pauliukienė, Kristina Šutienė, Aistė Čemerkaitė and Jonas Čeponis

Diagnostics 2025, 15(23), 3070; https://doi.org/10.3390/diagnostics15233070 - 2 Dec 2025

Viewed by 1536

Abstract

Background/Objectives: The aim of this study was to identify systemic, metabolic, and host-related prognostic factors for long-term outcomes in patients with a diabetic foot ulcer (DFU). Methods: One hundred patients were selected from a high-risk cohort of 426 individuals with a [...] Read more.

Background/Objectives: The aim of this study was to identify systemic, metabolic, and host-related prognostic factors for long-term outcomes in patients with a diabetic foot ulcer (DFU). Methods: One hundred patients were selected from a high-risk cohort of 426 individuals with a DFU (January 2021–January 2023) based on predefined inclusion and exclusion criteria. Clinical, laboratory, and imaging data were collected. Outcomes were categorized as favorable (healing) or unfavorable (non-healing, re-ulceration, amputation, or death). Prognostic factors were analyzed using random forest and categorical boosting models, with SHAP values to determine the importance of individual predictors. Results: The median age of participants was 65 years (interquartile range [IQR], 57–69.25), and the median duration of diabetes was 18 years (IQR, 12–26). Over a mean 2.1-year follow-up, unfavorable outcomes occurred in 53% of the whole cohort and in 36% of survivors. The strongest predictors of poor prognosis were prior amputation, elevated inflammatory markers, reduced eGFR, and dyslipidemia. Triglycerides showed a U-shaped association with outcomes. A lower BMI and shorter diabetes duration paradoxically were also linked to poorer prognosis. Glycemic control, comorbidities, and local foot characteristics had limited predictive value. Conclusions: Long-term DFU prognosis is driven mainly by systemic and host-related factors rather than by ulcer characteristics alone. Inflammation, renal dysfunction, dyslipidemia—particularly triglycerides—and prior amputation were the strongest predictors of unfavorable outcomes. Full article

(This article belongs to the Special Issue Chronic Wounds: Diagnosis and Management)

► Show Figures

Figure 1

11 pages, 224 KB

Open AccessArticle

Exome-Based Identification of Candidate Genes in Sporadic Adenomyosis Cases

by Feyza Nur Tuncer, Nimet Eser Ma, Sevcan Aydin, Nura Fitnat Topbas Selcuki, Ipek Yildiz Ozaydin and Engin Oral

Diagnostics 2025, 15(23), 3069; https://doi.org/10.3390/diagnostics15233069 - 2 Dec 2025

Viewed by 374

Abstract

Background: Adenomyosis is a benign uterine disorder defined by the invagination of ectopic endometrial-like tissue into the myometrium, causing heavy menstrual bleeding and pain. While its pathogenesis remains unclear, shared-symptomology with endometriosis suggests a common mechanism. Adenomyosis is often diagnosed after age [...] Read more.

Background: Adenomyosis is a benign uterine disorder defined by the invagination of ectopic endometrial-like tissue into the myometrium, causing heavy menstrual bleeding and pain. While its pathogenesis remains unclear, shared-symptomology with endometriosis suggests a common mechanism. Adenomyosis is often diagnosed after age 40 due to its complex presentation and the need for histopathological confirmation, underscoring the need for non-invasive markers. Methods: Ten unrelated women with histopathological diagnosis of adenomyosis were recruited. All recruits completed the WERF-EPHect questionnaire and were additionally questioned about any comorbidities. Genomic DNA isolated from peripheral blood was subjected to whole exome sequencing (WES) on Illumina NovaSeq 6000 and was analyzed using the Pairend NGS Cloud platform. Variants were filtered for MAF < 1% and were prioritized based on functional relevance and impact determined by in silico prediction tools. Variant selection adhered to stringent quality metrics to identify candidate variants associated with adenomyosis. Results: WES analysis did not reveal any variant common to the cohort. A total of eight pathogenic and two likely pathogenic novel variants were identified. Moreover, novel variants of p.(Val331Ile) in EFHB and p.(Phe14Val) in MEIS1 were the most frequently shared genetic variants in the cohort. Conclusions: Our findings suggest novel candidate genes for adenomyosis that warrant validation and functional investigation in larger, independent cohorts. Full article

(This article belongs to the Special Issue Diagnosis and Prognosis of Gynecological and Obstetric Diseases)

20 pages, 1477 KB

Open AccessReview

Mechanisms and Impact of Cognitive Reserve in Normal Aging and Alzheimer’s Disease

by Chanda Simfukwe, Seong Soo A. An and Young Chul Youn

Diagnostics 2025, 15(23), 3068; https://doi.org/10.3390/diagnostics15233068 - 2 Dec 2025

Viewed by 1179

Abstract

Age-related cognitive decline and individual differences in dementia susceptibility are increasingly explained through the concept of cognitive reserve (CR). CR reflected the brain’s adaptive capacity to sustain cognitive performance despite Alzheimer’s disease (AD)-related pathology, extending beyond traditional biomarkers that captured the molecular or [...] Read more.

Age-related cognitive decline and individual differences in dementia susceptibility are increasingly explained through the concept of cognitive reserve (CR). CR reflected the brain’s adaptive capacity to sustain cognitive performance despite Alzheimer’s disease (AD)-related pathology, extending beyond traditional biomarkers that captured the molecular or structural changes, but often failed to account for clinical heterogeneity. This review provided a comprehensive synthesis of how CR was operationalized through three major methodological approaches: sociobehavioral proxies, residual variance frameworks, and neurobiological indicators within the context of longitudinal study designs. The review included evidences from a structured PubMed and Scopus search restricted to English-language studies examining the incidence of mild cognitive impairment (MCI) or AD. Findings consistently demonstrated that higher CR, most commonly estimated through sociobehavioral proxies, such as educational level, occupational complexity, bilingualism, and engagement in cognitively stimulating activities, was associated with a delayed onset of impairment, lower dementia risk, and better clinical outcomes, despite a comparable neuropathological burden. Residual variance approaches provided complementary insights by quantifying cognitive performance that exceeded the predicted levels from underlying pathology, thereby capturing unexplained variance by structural or molecular disease markers. These residual-based methods extend CR concept beyond life-course experiences, offering statistical evidence of resilience within longitudinal trajectories of aging and disease. Additional evidence from electrophysiological and genetic investigations further suggested that CR enhanced the neural efficiency, flexibility, and the recruitment of compensatory networks. Finally, neuroimaging studies provided the mechanistic evidence that CR was supported by alterations in brain structure, functional connectivity, and activation patterns, though findings on long-term trajectories remained inconsistent. Overall, CR emerged as a multidimensional and modifiable construct that enhanced resilience to aging and dementia. Future research should prioritize the integrative longitudinal designs, combining sociobehavioral, residual variance, genetic, electrophysiological, and neuroimaging approaches to clarify mechanisms, establishing robust measurement frameworks and advance clinical translation. Full article

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

► Show Figures

Figure 1

14 pages, 1955 KB

Open AccessCase Report

Different Patterns of Cortical Electrical Activity by Tactile, Acoustic and Visual Stimuli in Infants: An EEG Exploratory Study

by Rocío Llamas-Ramos, Jorge Juan Alvarado-Omenat, Juan Luis Sánchez-González, Ismael Sanz-Esteban, J. Ignacio Serrano and Inés Llamas-Ramos

Diagnostics 2025, 15(23), 3067; https://doi.org/10.3390/diagnostics15233067 - 2 Dec 2025

Viewed by 381

Abstract

Background and Clinical Significance: Understanding early brain development in infants is essential as identifying an abnormal pattern could accelerate the start of early interventions. There is still limited evidence on how external stimuli (such as tactile, auditory, and visual inputs) influence cortical electrical [...] Read more.

Background and Clinical Significance: Understanding early brain development in infants is essential as identifying an abnormal pattern could accelerate the start of early interventions. There is still limited evidence on how external stimuli (such as tactile, auditory, and visual inputs) influence cortical electrical activity, underscoring the need for integrative studies comparing these modalities in the first months of life. The objective of this paper is to determine the effects of different stimuli (tactile, auditory, and visual) in cortical electrical activity to take advantage of its use in individualized protocols and treatments. Case Presentation: An 8-channel electroencephalography cap was placed on the infant’s head to analyze 10 different conditions depending on the selected stimuli: Kangaroo Care with mother and father, rest, tactile stimuli, visual stimuli, acoustic stimuli, and sleep for 5 min. The environment was the same in all conditions to ensure comparison. All conditions have been able to modify the cortical electrical activity presenting different patterns of electrical activity. Tactile stimuli (massage) showed increased activity in the left parietal region. Acoustic stimuli showed increased activity in the frontal region. Visual stimuli presented different patterns, but with a higher occurrence of artifacts due to baby’s movement. Conclusions: Acoustic stimuli with music increased cortical electrical activity in frontal region, while tactile stimuli increased the left cerebral hemisphere activity. Future studies are needed to support these exploratory results to establish early interventions in pathological conditions. Full article

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

► Show Figures

Graphical abstract

22 pages, 3756 KB

Open AccessArticle

Browser-Based Multi-Cancer Classification Framework Using Depthwise Separable Convolutions for Precision Diagnostics

by Divine Sebukpor, Ikenna Odezuligbo, Maimuna Nagey, Michael Chukwuka, Oluwamayowa Akinsuyi and Blessing Ndubuisi

Diagnostics 2025, 15(23), 3066; https://doi.org/10.3390/diagnostics15233066 - 1 Dec 2025

Viewed by 470

Abstract

Background: Early and accurate cancer detection remains a critical challenge in global healthcare. Deep learning has shown strong diagnostic potential, yet widespread adoption is limited by dependence on high-performance hardware, centralized servers, and data-privacy risks. Methods: This study introduces a browser-based [...] Read more.

Background: Early and accurate cancer detection remains a critical challenge in global healthcare. Deep learning has shown strong diagnostic potential, yet widespread adoption is limited by dependence on high-performance hardware, centralized servers, and data-privacy risks. Methods: This study introduces a browser-based multi-cancer classification framework that performs real-time, client-side inference using TensorFlow.js—eliminating the need for external servers or specialized GPUs. The proposed model fine-tunes the Xception architecture, leveraging depthwise separable convolutions for efficient feature extraction, on a large multi-cancer dataset of over 130,000 histopathological and cytological images spanning 26 cancer types. It was benchmarked against VGG16, ResNet50, EfficientNet-B0, and Vision Transformer. Results: The model achieved a Top-1 accuracy of 99.85% and Top-5 accuracy of 100%, surpassing all comparators while maintaining lightweight computational requirements. Grad-CAM visualizations confirmed that predictions were guided by histopathologically relevant regions, reinforcing interpretability and clinical trust. Conclusions: This work represents the first fully browser-deployable, privacy-preserving deep learning framework for multi-cancer diagnosis, demonstrating that high-accuracy AI can be achieved without infrastructure overhead. It establishes a practical pathway for equitable, cost-effective global deployment of medical AI tools. Full article

(This article belongs to the Special Issue Artificial Intelligence-Driven Radiomics in Medical Diagnosis)

► Show Figures

Figure 1

12 pages, 567 KB

Open AccessArticle

Heart Failure Alert Duration and Time at Risk of Heart Failure as Potential Modifier Factors of the TriageHF Algorithm in Remote Monitoring of Heart Failure: A Cohort Study

by David Ledesma Oloriz, Daniel García Iglesias, Rodrigo Ariel di Massa, Álvaro Lorente Ros, Fernando López Iglesias, Vanesa Alonso Fernández and José Manuel Rubín López

Diagnostics 2025, 15(23), 3065; https://doi.org/10.3390/diagnostics15233065 - 1 Dec 2025

Viewed by 333

Abstract

Background: The TriageHF algorithm provides remote monitoring for heart failure (HF), but its clinical implementation is limited by a high rate of false positive alerts. Objective: To assess whether incorporating alarm duration and individual time at risk can improve the diagnostic [...] Read more.

Background: The TriageHF algorithm provides remote monitoring for heart failure (HF), but its clinical implementation is limited by a high rate of false positive alerts. Objective: To assess whether incorporating alarm duration and individual time at risk can improve the diagnostic performance of the TriageHF algorithm. Methods: This was a single-center prospective cohort study in which 37 patients with Medtronic ICDs implanted between January 2020 and June 2022 were enrolled. HF events were defined as episodes requiring intravenous diuretics or hospitalization. A total of 609 TriageHF alerts were analyzed. Two strategies were analyzed: a standard approach (high-risk and moderate-risk alerts > 7 days considered positive) and a modified approach (high-risk and moderate-risk alerts > 15 days considered positive). The relationship between time spent in a low-risk state and the algorithm’s positive predictive value (PPV) was also assessed. Results: In the standard configuration, sensitivity was 96.7% and specificity was 76.4%, with 81.9% of false positives. The modified approach showed improved specificity (85.6%) and PPV (24.3%), with minimal impact on sensitivity (87%) and negative predictive value (99.1%). There was a significant inverse correlation between time spent at low-risk and individual PPV (R² = 0.64, p = 0.018). Conclusions: Using a ≥15-day threshold improved the specificity and PPV of the TriageHF algorithm. Incorporating individual time at risk may further refine risk stratification and enhance cost-effectiveness in HF remote monitoring strategies. Full article

(This article belongs to the Special Issue Cardiovascular Diseases: Advances in Diagnosis and Management)

► Show Figures

Figure 1

11 pages, 1364 KB

Open AccessArticle

Prevalence-Guided Anti-HCV and Reflex HCV Ag Testing in the Detection of Patients with Chronic Hepatitis C in Hepatitis C Endemic Areas

by Sheng-Hsueh Chen, Yuan-Jie Ding, Nien-Tzu Hsu, Te-Sheng Chang, Yu-Chen Lin, Wen-Hua Chao and Sheng-Nan Lu

Diagnostics 2025, 15(23), 3064; https://doi.org/10.3390/diagnostics15233064 - 1 Dec 2025

Viewed by 374

Abstract

Background/Objectives: Chronic hepatitis C virus (HCV) remains a major public health concern in Taiwan, particularly in southern regions with high endemicity. While HCV elimination is a national priority, resources are often limited. Relying solely on broad, township-level prevalence rates is inefficient, as [...] Read more.

Background/Objectives: Chronic hepatitis C virus (HCV) remains a major public health concern in Taiwan, particularly in southern regions with high endemicity. While HCV elimination is a national priority, resources are often limited. Relying solely on broad, township-level prevalence rates is inefficient, as the true disease burden can vary dramatically at the village level. Therefore, identifying local hotspots through fine-scale mapping is critical for efficient resource allocation and targeted intervention. This study aimed to validate village-level prevalence estimates and evaluate the efficiency of a community-based, targeted screening approach utilizing this detailed prevalence data in Chiayi County. Methods: We integrated data from the Chiayi Health Bureau and Chiayi Chang Gung Memorial Hospital (2000–2015) to generate village-level risk maps for five townships: Lioujiao (LJ), Yijhu (YH), Dongshih (DS), Taibao (TB), and Lucao (LC). Between 2018 and 2021, we conducted door-to-door community screening using anti-HCV testing with reflex HCV antigen (Ag) testing. Anti-HCV/HCV Ag prevalence, number needed to test (NNT), and linkage-to-care rates were calculated to validate prevalence estimates and assess screening efficiency. Results: Among 3910 participants, anti-HCV prevalence ranged from 5.4% (TB) to 8.7% (DS). Estimated and observed village-level prevalence showed moderate-to-strong correlation (r = 0.696–0.830, p < 0.001). Screening efficiency was highest in DS (NNT = 21) and lowest in TB (NNT = 42). Of 132 antigen-positive individuals, 131 (99.2%) initiated direct-acting antiviral therapy. Conclusions: The village-level risk maps accurately predicted local HCV burden, enabling targeted screening with high diagnostic yield and near-complete treatment uptake. This approach maximizes resource efficiency and may serve as a scalable model for advancing Taiwan and the WHO’s 2030 HCV elimination goals. Full article

(This article belongs to the Special Issue Advances in Diagnosis and Management of Liver Diseases)

► Show Figures

Figure 1

20 pages, 856 KB

Open AccessSystematic Review

Postmortem Diagnosis of Dilated Cardiomyopathy: A Systematic Review Revisiting Fundamentals

by Simona Calabrese, Vincenzo Cianci, Daniela Sapienza, Alessandro Nicolosi, Beatrice Spadaro, Antonio Ieni, Desirèe Speranza, Patrizia Gualniera, Alessio Asmundo and Cristina Mondello

Diagnostics 2025, 15(23), 3063; https://doi.org/10.3390/diagnostics15233063 - 1 Dec 2025

Viewed by 651

Abstract

Background: Dilated cardiomyopathy (DCM) is a myocardial disorder characterized by structural and functional abnormalities, in particular left or biventricular chamber dilatation and systolic dysfunction, occurring without evidence of coronary artery disease, hypertension, valvular disease, or congenital heart defects. It is a significant cause [...] Read more.

Background: Dilated cardiomyopathy (DCM) is a myocardial disorder characterized by structural and functional abnormalities, in particular left or biventricular chamber dilatation and systolic dysfunction, occurring without evidence of coronary artery disease, hypertension, valvular disease, or congenital heart defects. It is a significant cause of sudden cardiac death, particularly in young individuals, often remaining undiagnosed until autopsy. Methods: A systematic review of the literature was conducted following PRISMA guidelines to revisit the main postmortem findings (gross, microscopic, and genetic) useful to perform the postmortem diagnosis of DCM. Scientific databases (PubMed and Scopus) were searched for articles published up to February 2025 describing postmortem findings in individuals diagnosed with DCM. Inclusion criteria were focused on studies reporting macroscopic cardiac findings, and microscopic and genetic variants identified postmortem or in related familial studies. Data were extracted and categorized to identify consistent diagnostic markers and to assess the frequency and relevance of genetic findings in autopsy-confirmed DCM cases. From 2081 initial records, 30 studies met inclusion criteria. Two reviewers independently performed study selection and data extraction, and methodological limitations of the included studies were considered qualitatively to inform the synthesis. Results: Common macroscopic features included increased heart weight (often > 350 g), dilated left or biventricular chambers, and thinning of the ventricular walls. Histologically, the most consistent findings were diffuse interstitial fibrosis, myocyte hypertrophy, and nuclear atypia. Particular attention was given to morphological features essential to distinguish between genetic and nongenetic forms of DCM and, thus, useful to perform a differential diagnosis with disease having a DCM-like pattern. Notably, truncating variants in genes such as TTN, FLNC, DSP, PKP2, and MYH7 were frequently reported, particularly in young decedents with no significant history of cardiac disease. However, only about half of reviewed studies included any form of genetic analysis, reflecting a significant gap in current practice for forensic pathologists. Conclusions: DCM may cause sudden death without prior symptoms, making genetic testing essential to uncover the diagnosis, especially in cases with a negative phenotype. Therefore, molecular autopsy combined with careful macroscopic and microscopic analysis can strengthen the forensic assessment. Full article

(This article belongs to the Special Issue Advances in Pathology for Forensic Diagnosis)

► Show Figures

Figure 1

Journal Menu

Journal Browser

Diagnostics, Volume 15, Issue 23 (December-1 2025) – 156 articles

Further Information

Guidelines

MDPI Initiatives

Follow MDPI