Diagnostics

28 pages, 1015 KB

Open AccessReview

How Does ACR BI-RADS^® v2025 Change the Radiologist’s Approach? A Practical Guide Across Mammography, Ultrasound, and MRI: A Narrative Review

by Ela Kaplan and Ahmet Burak Aydemir

Diagnostics 2026, 16(13), 2135; https://doi.org/10.3390/diagnostics16132135 (registering DOI) - 7 Jul 2026

Abstract

Twelve years after the 2013 fifth edition, the American College of Radiology has released BI-RADS^® v2025, with substantial revisions across mammography, ultrasonography, MRI, and the newly independent contrast-enhanced mammography (CEM) section. This review compares the two editions and reads the main changes [...] Read more.

Twelve years after the 2013 fifth edition, the American College of Radiology has released BI-RADS^® v2025, with substantial revisions across mammography, ultrasonography, MRI, and the newly independent contrast-enhanced mammography (CEM) section. This review compares the two editions and reads the main changes against the available evidence on diagnostic performance and reader agreement, rather than only cataloguing them. Examples featuring digital breast tomosynthesis, synthetic mammography, and automated whole-breast ultrasonography now appear throughout the modality sections. “Lobulated” has been added as a shape descriptor across all modalities, while “microlobulated” was dropped from the mammography margin list. Calcification terms shifted from etiology to morphology: “milk of calcium” became “layering,” “punctate” was folded into “round,” and “dystrophic” moved under “coarse.” Ultrasonography gained two new entries, “non-mass lesion” and “echogenic rind,” and on MRI, “initial phase” was renamed “early phase.” Category 6 was rewritten; therefore, surgical excision is recognized as one of several definitive local treatments, and an “uncoupled” principle now separates assessment from management. The auditing section folds Category 3 follow-up into basic auditing and adds a Method of Detection data field. Most supporting data, however, predate v2025, and reader agreement remains lower for newer descriptors such as non-mass enhancement; whether the revisions measurably improve reproducibility is still unproven. Integrating every high-sensitivity tool also brings more false positives, overdiagnosis, and cost; artificial intelligence and radiomics may help close the reproducibility gap, but resource-stratified, equitable implementation will be essential. With v2025, BI-RADS becomes a multimodality framework rather than a reporting lexicon alone. Full article

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

26 pages, 9972 KB

Open AccessArticle

Ultrasonographic Knee Abnormalities and Their Association with Pain in Young Male Handball and Basketball Athletes: A Cross-Sectional Study

by Nicoleta Anamaria Pascalau, Alexandru Bogdan Ilieș, Brigitte Osser, Csongor Toth, Gyongyi Osser, Laura Ioana Bondar, Gheorghe Codruț Bulz, Anca Maria Sabău, Mihaela Gavrila-Ardelean and Corina Dalia Toderescu

Diagnostics 2026, 16(13), 2134; https://doi.org/10.3390/diagnostics16132134 (registering DOI) - 7 Jul 2026

Abstract

Background/Objectives: Knee injuries and overuse-related disorders are common among athletes participating in jumping sports such as handball and basketball. Musculoskeletal ultrasonography is increasingly used for the assessment of knee pathology; however, evidence regarding the prevalence and clinical relevance of ultrasonographic abnormalities in young [...] Read more.

Background/Objectives: Knee injuries and overuse-related disorders are common among athletes participating in jumping sports such as handball and basketball. Musculoskeletal ultrasonography is increasingly used for the assessment of knee pathology; however, evidence regarding the prevalence and clinical relevance of ultrasonographic abnormalities in young athletes remains limited. The aim of this study was to investigate the prevalence of ultrasonographic knee abnormalities in young male handball and basketball athletes and to examine their association with pain intensity. Methods: A cross-sectional observational study was conducted between June 2025 and June 2026 and included 69 competitive male athletes (35 handball players and 34 basketball players). All participants underwent bilateral knee ultrasonographic examination using a standardized assessment protocol and completed a questionnaire regarding demographic and training characteristics. Knee pain intensity was evaluated using the Visual Analogue Scale (VAS). Comparisons between sports were performed using χ² and t-tests, while associations between participant-level ultrasonographic findings and pain were evaluated using independent-samples t-tests (or Mann–Whitney U tests, as appropriate), with Cohen’s d effect sizes and exploratory multivariable linear regression. Sensitivity analyses stratified by sport were additionally performed. Results: Patellar tendinopathy was the most prevalent ultrasonographic abnormality (21.0%), followed by medial meniscal abnormality (15.9%) and infrapatellar bursitis (13.0%). Athletes with patellar tendinopathy, medial meniscal abnormality, or infrapatellar bursitis had significantly higher VAS pain scores than athletes without the corresponding ultrasonographic abnormality. Patellar tendinopathy demonstrated the strongest association with participant-reported pain (VAS: 4.1 ± 1.3; Cohen’s d = 1.24; p < 0.001). Handball athletes exhibited a significantly higher prevalence of patellar tendinopathy than basketball athletes (34.3% vs. 11.8%; OR = 3.90, 95% CI: 1.09–13.95; p = 0.027). In multivariable regression analysis adjusted for age, BMI, sport type, previous knee injury, and weekly training volume, patellar tendinopathy (β = 1.34, p < 0.001), medial meniscal abnormality (β = 0.70, p = 0.017), and infrapatellar bursitis (β = 0.54, p = 0.046) remained independently associated with higher pain scores. The regression model explained 39% of the variance in VAS pain scores (R² = 0.39). Conclusions: Ultrasonographic knee abnormalities are common among young male handball and basketball athletes and are significantly associated with pain intensity. Because ultrasonography has limited ability to characterize intra-articular pathology, particularly the menisci, the ultrasonographic abnormalities identified in this study should not be interpreted as definitive diagnoses, and MRI remains the reference imaging modality when comprehensive evaluation of intra-articular pathology is clinically indicated. Patellar tendinopathy was the most prevalent ultrasonographic abnormality and was most strongly associated with pain intensity. These findings support the use of musculoskeletal ultrasonography as a complementary imaging modality alongside clinical assessment in the evaluation of symptomatic athletes. However, prospective longitudinal studies are required to determine whether these ultrasonographic abnormalities have prognostic value for future pain, functional limitation, or time-loss injury. Full article

(This article belongs to the Special Issue Ultrasound Diagnosis and Guided Intervention of Musculoskeletal/Neuromuscular Pathology, Second Edition)

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39 pages, 963 KB

Open AccessReview

Current Landscape of Molecular Diagnostic Tests and Emerging Tools for Tuberculosis and Drug Resistance

by Safaa El Kassimi, Rkia Eddabra, Bouchra Belkadi, Abdelkarim Filali-Maltouf and Hassan Ait Benhassou

Diagnostics 2026, 16(13), 2133; https://doi.org/10.3390/diagnostics16132133 (registering DOI) - 7 Jul 2026

Abstract

This review synthesizes recent advances in WHO-endorsed NAATs for TB diagnosis and drug resistance detection. We examine the principles, genetic targets, diagnostic performance, implementation settings, and programmatic role of assays across the spectrum of technological complexity, from cartridge-based platforms to line probe assays [...] Read more.

This review synthesizes recent advances in WHO-endorsed NAATs for TB diagnosis and drug resistance detection. We examine the principles, genetic targets, diagnostic performance, implementation settings, and programmatic role of assays across the spectrum of technological complexity, from cartridge-based platforms to line probe assays and sequencing-based technologies. In addition, we highlight emerging molecular tools that show promise for future WHO endorsement and may further strengthen decentralized and near-patient testing. Low- and moderate-complexity assays such as Xpert^® MTB/RIF, Xpert^® Ultra, and Truenat^TM MTB/MTB Plus have emerged as essential frontline tools for TB diagnosis and rifampicin resistance detection, especially in decentralized settings. LPAs, including GenoType^® MTBDRplus and MTBDRsl, extend resistance profiling to isoniazid, fluoroquinolones, and second-line injectables, and remain valuable in intermediate and central laboratories. More recent developments, including Xpert^® XDR, Deeplex^® Myc-TB, AmPORE-TB^®, and TBseq^®, enable broader resistance detection and, in the case of targeted sequencing assays, comprehensive characterization of multidrug-resistant and extensively drug-resistant TB (MDR/XDR-TB). Emerging diagnostic innovations—such as CRISPR-based detection systems, streamlined isothermal amplification assays, and portable sequencing technologies—further expand the landscape and may complement existing WHO-endorsed platforms. Importantly, these technologies reduce delays in regimen selection, improve patient outcomes, and provide critical data for surveillance. Nevertheless, performance gaps for rare mutations, limited sensitivity in paucibacillary or extrapulmonary disease, infrastructure requirements, and cost remain barriers to universal adoption. The evolution of TB molecular diagnostics demonstrates a clear shift toward more rapid, accurate, and comprehensive resistance detection. No single assay is universally optimal, yet the combined portfolio, spanning rapid cartridge-based NAATs, LPAs, and next-generation sequencing, forms a complementary framework for improving diagnosis, optimizing treatment, and supporting global TB elimination strategies. Full article

(This article belongs to the Special Issue Bacterial Infections and Antimicrobial Resistance: Diagnosis and Management)

17 pages, 5186 KB

Open AccessArticle

Inflammatory Signatures of Graves’ Orbitopathy: Linking Thyroid Autoimmunity, Disease Activity, and Novel Hematological Biomarkers

by Sadettin Ozturk and Elif Melis Baloğlu Akyol

Diagnostics 2026, 16(13), 2132; https://doi.org/10.3390/diagnostics16132132 - 7 Jul 2026

Abstract

Background: Graves’ disease is an autoimmune thyroid disorder that may be accompanied by systemic inflammation and Graves’ orbitopathy. This study evaluated the relationship between readily available hematological inflammatory markers and orbitopathy in patients with Graves’ disease. Methods: This retrospective observational study [...] Read more.

Background: Graves’ disease is an autoimmune thyroid disorder that may be accompanied by systemic inflammation and Graves’ orbitopathy. This study evaluated the relationship between readily available hematological inflammatory markers and orbitopathy in patients with Graves’ disease. Methods: This retrospective observational study included 178 adult patients with Graves’ disease. Demographic, clinical, ophthalmological, and laboratory data were analyzed. Neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), systemic immune-inflammation index (SII), monocyte-to-HDL cholesterol ratio (MHR), and C-reactive protein-to-albumin ratio (CAR) were calculated. Correlation, logistic regression, and ROC analyses were performed. Results: Among the 178 patients, 63 (35.4%) had Graves’ orbitopathy. Patients with orbitopathy had significantly higher NLR, PLR, SII, MHR, and CAR values than those without orbitopathy (all p < 0.001). Thyrotropin receptor antibody (TRAb) and thyroid-stimulating immunoglobulin (TSI) levels were positively correlated with all inflammatory markers. In multivariable logistic regression analysis, current smoking (OR 2.31, p = 0.047), TRAb (OR 1.08, p = 0.009), TSI (OR 1.06, p = 0.041), NLR (OR 1.63, p = 0.034), SII (OR 1.01, p = 0.018), MHR (OR 2.91, p = 0.012), and CAR (OR 3.84, p = 0.008) remained independently associated with Graves’ orbitopathy. Among the individual biomarkers, MHR showed the highest discriminative performance (AUC 0.818, 95% CI 0.754–0.882), while the combined inflammatory model achieved an AUC of 0.891 (95% CI 0.842–0.940), with an optimal predicted probability cut-off ≥ 0.43. Conclusions: Hematological inflammatory markers are associated with thyroid autoimmunity, disease activity, and Graves’ orbitopathy. These inexpensive and easily accessible markers may support clinical risk assessment in patients with Graves’ disease. Full article

(This article belongs to the Special Issue Thyroid Disorders: New Clinical Diagnosis and Management)

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14 pages, 1238 KB

Open AccessArticle

Benchmarking Multimodal Large Language Models for Cardiopulmonary Findings on Chest Radiographs: Sex-Stratified Discrimination and Operating Characteristics

by Matteo Haupt, Arne Bischoff, Myriam Atoubi, Rohit Philip Thomas and Martin H. Maurer

Diagnostics 2026, 16(13), 2131; https://doi.org/10.3390/diagnostics16132131 (registering DOI) - 7 Jul 2026

Abstract

Background/Objectives: To characterize the zero-shot diagnostic behavior of three commercial multimodal large language models (MLLMs) on cardiopulmonary chest radiograph findings and to assess sex-stratified performance differences. Methods: GPT-5.4, Claude Opus 4.5, and Gemini 2.5 Pro were evaluated in 4500 pathology-specific radiograph [...] Read more.

Background/Objectives: To characterize the zero-shot diagnostic behavior of three commercial multimodal large language models (MLLMs) on cardiopulmonary chest radiograph findings and to assess sex-stratified performance differences. Methods: GPT-5.4, Claude Opus 4.5, and Gemini 2.5 Pro were evaluated in 4500 pathology-specific radiograph evaluations based on frontal chest radiographs from the publicly available CheXpert dataset. Three balanced cohorts of 1500 images each were constructed for cardiomegaly, pulmonary edema, and pleural effusion (375 per sex-by-label subgroup). All models received identical zero-shot prompts requesting binary classification. The primary outcome was area under the receiver operating characteristic curve (AUC-ROC) with 95% bootstrap confidence intervals. Secondary outcomes were sensitivity and specificity. Results: A total of 4500 pathology-specific radiograph evaluations were performed across the three cohorts (2250 male and 2250 female cohort entries; mean age 58.4 ± 18.0 years). GPT-5.4 achieved the highest discrimination (AUC-ROC 0.836–0.883) but showed very low sensitivity (0.043–0.424) with near-perfect specificity (0.977–0.997). Claude Opus 4.5 showed moderate discrimination (AUC-ROC 0.698–0.761) with balanced sensitivity (0.396–0.876) and specificity (0.461–0.863). Gemini 2.5 Pro showed moderate discrimination (AUC-ROC 0.745–0.770) but favored sensitivity (0.673–0.973) at the expense of specificity (0.241–0.804). Sex-stratified analyses showed consistently higher AUC point estimates in male patients for cardiomegaly and pulmonary edema, but smaller and less directional differences for pleural effusion. Conclusions: Commercial MLLMs differ considerably in operating profiles, ranging from ultraconservative to aggressive detection, so that strong aggregate discrimination can mask sensitivity too low for reliable detection. None of the evaluated models are currently suitable for autonomous chest radiograph interpretation. Sex-stratified differences were modest but non-uniform, supporting subgroup-aware reporting rather than reliance on pooled metrics alone. Full article

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

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17 pages, 890 KB

Open AccessArticle

Malignancy as a Predictor and Potential Modifier of Laboratory Biomarker Prognostic Value in Acute Pulmonary Embolism

by Sonja Salinger, Aleksandra Kozic, Stefan Ilic, Boris Dzudovic, Bojana Subotic, Jovan Matijasevic, Marija Benic, Tamara Kovacevic Preradovic, Ana Kovacevic-Kuzmanovic, Irena Mitevska, Vladimir Miloradovic, Ema Jevtic, Aleksandar Neskovic and Slobodan Obradovic

Diagnostics 2026, 16(13), 2130; https://doi.org/10.3390/diagnostics16132130 - 7 Jul 2026

Abstract

Background/Objectives: Acute pulmonary embolism (PE) is a major cause of cardiovascular mortality, with prognosis influenced by hemodynamic status, comorbidities, and biomarker profiles. Although several laboratory markers have demonstrated prognostic relevance in PE, it remains unclear whether their predictive performance differs in patients with [...] Read more.

Background/Objectives: Acute pulmonary embolism (PE) is a major cause of cardiovascular mortality, with prognosis influenced by hemodynamic status, comorbidities, and biomarker profiles. Although several laboratory markers have demonstrated prognostic relevance in PE, it remains unclear whether their predictive performance differs in patients with active malignancy. This study aimed to identify laboratory predictors of in-hospital mortality in acute PE and evaluate the modifying effect of malignancy on biomarker-based prognostic stratification. Methods: This retrospective multicenter cohort study included 2803 consecutive patients with confirmed acute PE enrolled in the Regional Pulmonary Embolism Registry (REPER) between January 2015 and April 2026. Univariate and multivariable logistic regression analyses were performed to identify predictors of in-hospital mortality in the overall cohort and subgroups stratified by malignancy status. Interaction analyses were used to formally assess effect modification by malignancy. Results: Active malignancy was present in 14.02% of patients, and overall in-hospital mortality was 11.10%. Multivariable analysis identified malignancy, CRP, glucose, creatinine clearance (CrCl), platelet count, and ESC risk category as independent predictors of in-hospital mortality. In-hospital mortality was significantly higher in patients with malignancy compared with those without (16.54% vs. 10.21%, p < 0.001). In the malignant subgroup, CRP and glucose remained independent predictors, whereas in non-malignant patients, CRP, glucose, CrCl, and ESC risk category were independently associated with outcome. Significant interactions between malignancy status and CrCl, age, glucose, and total leukocyte count suggest that the prognostic contribution of these variables may differ according to cancer status. Conclusions: Active malignancy is an independent predictor of in-hospital mortality in acute PE and appears to be associated with a more severe presentation. Our findings suggest that malignancy may also modify the prognostic performance of certain biomarkers. These observations suggest that conventional risk stratification tools may require cautious, malignancy-aware interpretation and that prospective studies validating malignancy-adapted prognostic frameworks are warranted. Full article

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15 pages, 4388 KB

Open AccessArticle

Pancreatic Stone Protein in Burns: Clinical Value of Bedside Testing—A Prospective Pilot Study

by Moritz Billner, Philipp von Imhoff, Konrad Karcz, Vadym Burchak, Maximilian C. Stumpfe, Celena A. Soergel and Denis Ehrl

Diagnostics 2026, 16(13), 2129; https://doi.org/10.3390/diagnostics16132129 - 7 Jul 2026

Abstract

Background: Early detection of severe infections in burn patients is difficult due to confounding sterile inflammation. Previous research has shown that Pancreatic Stone Protein (PSP) is less affected by trauma and surgery. Therefore, this study investigated whether longitudinal PSP trends can distinguish sterile [...] Read more.

Background: Early detection of severe infections in burn patients is difficult due to confounding sterile inflammation. Previous research has shown that Pancreatic Stone Protein (PSP) is less affected by trauma and surgery. Therefore, this study investigated whether longitudinal PSP trends can distinguish sterile post-burn inflammation from clinically relevant infections and indicate response to antimicrobial therapy. Methods: This prospective pilot cohort study included 10 consecutive adult patients with moderate to severe burn injuries admitted to a specialized burn intensive care unit. PSP levels were measured using bedside testing (abioSCOPE^®) daily over a 14-day observation period. Clinical parameters, burn severity as assessed by the Abbreviated Burn Severity Index (ABSI), and the occurrence of severe infectious complications, including pneumonia and bacteremia, were systematically recorded. PSP measurements were not used to guide clinical decision-making. Results: Patients who developed severe infectious complications (pneumonia and/or bacteremia; mean ABSI 8.5) showed a consistent and characteristic increase in PSP levels (>350 ng/mL) over time, with elevations preceding the clinical diagnosis of infection (24–120 h). In contrast, patients without pneumonia or bacteremia (mean ABSI 6) exhibited low and stable PSP (<150 ng/mL) concentrations throughout the observation period, despite the presence of burn-related injury and the expected sterile inflammatory response. Conclusions: In this exploratory cohort study distinct PSP trajectory patterns, with persistently low levels in non-infected patients and rising levels preceding clinically diagnosed infection in several cases, were observed. These preliminary findings suggest that longitudinal PSP monitoring may provide potential utility for infection surveillance in burn ICU patients. However, due to the exploratory design and very limited sample size, the findings should be interpreted cautiously and require validation in larger prospective multicenter studies before conclusions regarding clinical decision-making or patient outcomes can be drawn. Full article

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

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13 pages, 261 KB

Open AccessPerspective

Tracking Bone Loss in GLP-1RA Therapy: The Potential of the Deoxypyridinoline Urine Test

by Angeliki Margoni, Efthimia K. Basdra and Athanasios G. Papavassiliou

Diagnostics 2026, 16(13), 2128; https://doi.org/10.3390/diagnostics16132128 - 7 Jul 2026

Abstract

Skeletal safety of glucagon-like peptide-1 receptor agonists (GLP-1RAs) remains uncharted, with emerging evidence suggesting a divergence between mono- and dual-agonist therapies. GLP-1RA monotherapy appears bone-neutral, with modest or no adverse effects on bone mineral density (BMD), whilst dual agonists may confer a relatively [...] Read more.

Skeletal safety of glucagon-like peptide-1 receptor agonists (GLP-1RAs) remains uncharted, with emerging evidence suggesting a divergence between mono- and dual-agonist therapies. GLP-1RA monotherapy appears bone-neutral, with modest or no adverse effects on bone mineral density (BMD), whilst dual agonists may confer a relatively higher risk of osteoporosis and fractures, plausibly mediated by greater weight loss magnitude and concomitant reductions in lean body mass (LBM) rather than direct osteotoxicity. Intensified surveillance is warranted in susceptible phenotypes, including older adults and postmenopausal women with low baseline BMD under conditions of rapid weight loss. Osteoporosis risk is further amplified by pre-existing osteopenia, nutritional deficiencies, and concomitant exposure to bone-active agents. Given the limitations of serial dual-energy X-ray absorptiometry (DXA), including cumulative radiation exposure and limited sensitivity to early remodeling changes, biochemical markers potentially depict bone turnover more dynamically. Measurement of dynamic bone resorption markers enables early identification of skeletal disturbances, supporting proactive adjustment of therapeutic strategy, dosing, and duration. Specifically, deoxypyridinoline (DPD), a bone-specific collagen crosslink, is a highly sensitive and rapidly responsive urine biomarker of osteoclastic activity. Incorporating DPD urine testing into monitoring frameworks potentially facilitates individualized therapeutic modulation, optimizing the metabolic efficacy of GLP-1RAs while safeguarding skeletal integrity. Full article

(This article belongs to the Section Clinical Laboratory Medicine)

15 pages, 853 KB

Open AccessArticle

Baseline Inflammatory Biomarkers and Disease Burden for Predicting Response to Stapokibart in CRSwNP

by Yuzhe Hao, Xiangning Cheng, Yuxuan Liu, Shazhou Li, Bingyue Huo, Ziyi Long, Qianxue Hu, Tianjian Xie, Lijun Du, Bo Liu, Xuan Jiao, Shan Chen, Tao Zhou, Liuqing Zhou, Yue Zhou and Jianjun Chen

Diagnostics 2026, 16(13), 2127; https://doi.org/10.3390/diagnostics16132127 - 7 Jul 2026

Abstract

Background: Stapokibart is a novel biologic for chronic rhinosinusitis with nasal polyps (CRSwNP). We aimed to identify baseline biomarkers predicting early (4-week) and mid-term (16-week) responses to stapokibart in CRSwNP. Methods: A total of 57 patients were prospectively enrolled. Baseline clinical data [...] Read more.

Background: Stapokibart is a novel biologic for chronic rhinosinusitis with nasal polyps (CRSwNP). We aimed to identify baseline biomarkers predicting early (4-week) and mid-term (16-week) responses to stapokibart in CRSwNP. Methods: A total of 57 patients were prospectively enrolled. Baseline clinical data and complete blood count (CBC) parameters were collected, and derived inflammatory indices were calculated. Patients were classified as responders or non-responders at week 4 and 16 based on achieving either a ≥8.9-point reduction in SNOT-22 or a ≥1-point decrease in Nasal Polyp Score (NPS). Results: Stapokibart significantly improved SNOT-22, VAS, and NPS at both week 4 and week 16 (all p < 0.001). At week 4, 80.7% achieved an early response. Responders showed significantly higher baseline eosinophil count and eosinophil percentage and lower neutrophil-to-eosinophil ratio (N/E) (all p < 0.05). Univariate analysis identified N/E, comorbid asthma, eosinophil count, and aggregate index of systemic inflammation (AISI) as predictors of early response (all p < 0.05). Multivariate analysis identified N/E as an independent predictor (OR = 0.943, p = 0.011; AUC = 0.756). At week 16, 75.4% of patients achieved a mid-term response. Responders had significantly higher baseline SNOT-22 scores and NPS (p < 0.05). Multivariate analysis showed that baseline NPS and SNOT-22 scores were independently associated with mid-term response, and their combined model showed good predictive performance (AUC = 0.832, 95% CI: 0.716–0.948). Conclusions: Peripheral blood inflammatory biomarkers, particularly N/E, may predict early response to stapokibart in CRSwNP, whereas mid-term response appears more strongly associated with baseline disease severity. These findings support biomarker-driven stratification for individualized treatment strategies in CRSwNP. Full article

(This article belongs to the Special Issue Novel Biomarkers for Clinical Diagnosis and Prognosis)

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15 pages, 972 KB

Open AccessArticle

Prognostic Impact of Immune-Inflammatory and Nutritional Indices in Metastatic Hormone-Sensitive Prostate Cancer

by Mehmet Nuri Baser, Ahmet Baklaci, Ahmet Unlu, Asim Armagan Aydin, Zeynel Umut Alpsoy, Suleyman Utku Uzun and Bilgin Demir

Diagnostics 2026, 16(13), 2126; https://doi.org/10.3390/diagnostics16132126 - 7 Jul 2026

Abstract

Background/Objectives: Systemic inflammation and nutritional status influence cancer progression and prognosis. The C-reactive protein–albumin–lymphocyte (CALLY) index is a novel biomarker reflecting inflammation, immune response, and nutritional status; however, its prognostic value in metastatic hormone-sensitive prostate cancer (mHSPC) remains unclear. Methods: This [...] Read more.

Background/Objectives: Systemic inflammation and nutritional status influence cancer progression and prognosis. The C-reactive protein–albumin–lymphocyte (CALLY) index is a novel biomarker reflecting inflammation, immune response, and nutritional status; however, its prognostic value in metastatic hormone-sensitive prostate cancer (mHSPC) remains unclear. Methods: This retrospective multicenter cohort study included 159 patients with de novo mHSPC diagnosed between January 2018 and April 2025. Baseline CALLY, neutrophil-to-lymphocyte ratio (NLR), systemic immune-inflammation index (SII), and systemic inflammation response index (SIRI) were calculated. Results: The optimal CALLY cut-off was 0.58. A low CALLY was associated with significantly shorter progression-free survival (PFS) and overall survival (OS). It correlated with higher tumor burden, higher Gleason grade, elevated prostate-specific antigen levels, and poorer performance status. In univariate analysis, a low CALLY predicted worse OS (HR 5.20; p = 0.021), although this effect was attenuated in multivariate analysis (HR 2.15; 95% CI 0.52–8.90; p = 0.290), and its absolute discriminatory performance in receiver operating characteristic analysis remained modest (AUC = 0.558). Complete response rates differed significantly (high-CALLY 41.7% vs. low-CALLY 5.9%, p < 0.001), suggesting a potential link between baseline CALLY and treatment response. Conclusions: Among the indices evaluated, CALLY demonstrated the highest, though still modest, discriminatory ability for overall survival (AUC 0.558), and was the only marker to reach statistical significance in survival analysis. Its prognostic effect was attenuated in multivariable analysis, suggesting that CALLY reflects, rather than independently drives, the systemic consequences of high-burden disease. These findings are exploratory, and prospective validation in larger cohorts is required to determine its potential clinical utility. Full article

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

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24 pages, 1241 KB

Open AccessArticle

Associations Between Delayed Cerebral Ischemia in Spontaneous Subarachnoid Hemorrhage and Dysfunction of Autonomic Cardiovascular Modulation Compared to Transcranial Doppler Ultrasound Findings

by Matthias C. Borutta, Chiara Vetter, Florian Kraemer, Stefan T. Gerner, Kosmas Macha, Ludwig Singer, Tobias Engelhorn, Arnd Doerfler, Stefan Schwab and Julia Koehn

Diagnostics 2026, 16(13), 2125; https://doi.org/10.3390/diagnostics16132125 - 7 Jul 2026

Abstract

Background: This study aims to assess associations between occurrence of delayed cerebral ischemia (DCI) in spontaneous subarachnoid hemorrhage (SAH) and possible dysfunction of autonomic cardiovascular modulation compared to transcranial Doppler ultrasound (TCD). Methods: In this prospective observational study, 53 patients with [...] Read more.

Background: This study aims to assess associations between occurrence of delayed cerebral ischemia (DCI) in spontaneous subarachnoid hemorrhage (SAH) and possible dysfunction of autonomic cardiovascular modulation compared to transcranial Doppler ultrasound (TCD). Methods: In this prospective observational study, 53 patients with spontaneous SAH were enrolled, and 17 patients met DCI criteria, i.e., new cerebral infarction > 72 h after SAH onset on follow-up CT scans. Autonomic modulation as well as TCD-frequencies were monitored within 24 h after SAH onset and then daily until day 10. From 5 min time-series of R–R-interval (RRI) and blood-pressure (BP) recordings, parameters of sympathetic, parasympathetic and total autonomic cardiovascular modulation were calculated, including time- and frequency-domain parameters. Data were compared between patients with and without DCI. Further subgroup analyses were performed according to functional outcome after 3 to 6 months (i.e., favorable outcome, modified Rankin Scale (mRS) ≤ 3 vs. unfavorable outcome, mRS > 3) regardless of DCI. Results: RRI and BP values as well as TCD frequencies did not differ between patients with and without DCI. Compared to No DCI patients, the cohort of DCI patients had significantly lower values of sympathetic modulation (RRI-LF powers, SBP-LF powers) on days 5 and 9 after SAH, significantly lower values of total autonomic modulation (RRI-SD, RRI-CV, RRI-total powers) and insignificantly lower values of parasympathetic modulation (RMSSDs, RRI-HF powers) on day 5 after SAH. Parameters of sympathetic, parasympathetic, and total autonomic modulation did not differ significantly between patients with favorable and unfavorable outcomes, but showed slightly lower values in the unfavorable outcome group. Yet, additionally calculated value of normalized RRI-LF and normalized RRI-HF powers, as well as LF/HF ratios were significantly different in the unfavorable outcome cohort. Conclusions: Not only within the acute phase, but also during the first days after disease onset, spontaneous SAH induces a decrease in sympathetic, parasympathetic and total autonomic cardiovascular modulation. In contrast to standard diagnostic evaluation for detecting clinically relevant vasospasms—i.e., TCD—autonomic dysfunction was associated with development of DCI and poor clinical outcome. Thus, assessment of heart rate variability may predict augmented risk of cardiovascular complications and may represent a promising adjunctive marker within multimodal neuromonitoring in SAH patients. Full article

(This article belongs to the Special Issue Cerebrovascular Lesions: Diagnosis and Management, 2nd Edition)

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9 pages, 6182 KB

Open AccessCase Report

Autopsy-Confirmed Non-Paraneoplastic Lambert–Eaton Myasthenic Syndrome with Cerebellar Degeneration: A Case Report

by Hajime Iwata, Jun Ikezawa, Masayuki Honda, Ryo Morishima, Yuta Amagasaki, Tomonari Seki, Takahiro Kiriu, Keisuke Ishizawa, Kazushi Takahashi and Haruka Okada

Diagnostics 2026, 16(13), 2124; https://doi.org/10.3390/diagnostics16132124 - 7 Jul 2026

Abstract

Background and Clinical Significance: Lambert–Eaton myasthenic syndrome (LEMS) is mediated by antibodies against P/Q-type voltage-gated calcium channels (VGCCs) and is classified as paraneoplastic (T-LEMS) or non-paraneoplastic (NT-LEMS). Cerebellar degeneration is recognized in T-LEMS, but pathological confirmation in NT-LEMS has not been reported. [...] Read more.

Background and Clinical Significance: Lambert–Eaton myasthenic syndrome (LEMS) is mediated by antibodies against P/Q-type voltage-gated calcium channels (VGCCs) and is classified as paraneoplastic (T-LEMS) or non-paraneoplastic (NT-LEMS). Cerebellar degeneration is recognized in T-LEMS, but pathological confirmation in NT-LEMS has not been reported. Case Presentation: A 79-year-old man developed progressive ataxic gait and dysarthria at age 76 and was diagnosed with LEMS based on repetitive nerve stimulation findings and anti-P/Q-type VGCC antibodies. No malignancy was identified during more than 40 months of surveillance, and comprehensive autopsy revealed no occult tumor. After hospitalization for erythroderma and pneumonia, he died of respiratory failure. Postmortem examination revealed severe Purkinje cell loss with Bergmann gliosis in the anterior lobe and tuber vermis, accompanied by torpedoes and empty baskets, without significant inflammation. These findings indicate that NT-LEMS can reach the same VGCC-associated Purkinje cell endpoint previously documented only in paraneoplastic LEMS, despite different upstream triggers. Conclusions: This first autopsy-confirmed case of NT-LEMS with cerebellar degeneration supports a shared, non-inflammatory VGCC-mediated pathway of Purkinje cell injury across LEMS subtypes. Full article

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

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15 pages, 1330 KB

Open AccessArticle

Comparative Evaluation of Hybrid Attention-CNN and Vision Transformer Models for Multi-Class Classification of Third–Second Molar Relationships on CBCT

by Hazal Karslıoğlu, Jale Bektaş, Lutfiye Sal, Mert Durukan and Mehmet Ozgur Ozemre

Diagnostics 2026, 16(13), 2123; https://doi.org/10.3390/diagnostics16132123 - 7 Jul 2026

Abstract

Background/Objectives: Impacted third molars may adversely affect adjacent second molars, leading to pathological conditions such as external root resorption and dental caries. Accurate assessment of these interactions is important for treatment planning and clinical decision-making. Although cone-beam computed tomography (CBCT) provides detailed [...] Read more.

Background/Objectives: Impacted third molars may adversely affect adjacent second molars, leading to pathological conditions such as external root resorption and dental caries. Accurate assessment of these interactions is important for treatment planning and clinical decision-making. Although cone-beam computed tomography (CBCT) provides detailed three-dimensional imaging, image interpretation remains challenging. Recent advances in artificial intelligence have enabled automated radiographic analysis using deep learning methods. Methods: This retrospective study included 162 CBCT scans obtained from patients aged 18–75 years. A total of 306 third molar–second molar units were evaluated. Based on radiographic findings, interactions were categorized as independent, contact, or resorption. Several deep learning architectures were developed and evaluated, including conventional convolutional neural networks (CNNs), attention-based CNNs, and Vision Transformer (ViT) models. Performance was assessed using standard classification metrics, and an ensemble approach was applied to improve predictive stability. Results: Attention-based and Transformer-based models generally outperformed conventional CNN architectures. These models achieved better discrimination among the defined classes and demonstrated superior overall performance. The ensemble model produced the most reliable results, achieving the highest macro-area under the curve (macro-AUC) values. Distinguishing contact cases from independent cases was the most challenging task, whereas resorption cases were identified more consistently across different models. Conclusions: Transformer-based deep learning models showed promising performance for CBCT-based assessment of third molar–second molar interactions. Ensemble learning further improved classification reliability and robustness. These findings suggest that artificial intelligence-assisted systems may support early detection of third molar-related pathological changes and contribute to more accurate radiological evaluation and clinical decision-making. 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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17 pages, 5508 KB

Open AccessTechnical Note

Meridian-Dependent Geometric Planning for Pars Plana Scleral Fixation: An Orientation-Adjusted Analytical Model

by Goran Marić, Danny A. Mammo, Damir Godec, Milan Pešić and Zoran Vatavuk

Diagnostics 2026, 16(13), 2122; https://doi.org/10.3390/diagnostics16132122 - 7 Jul 2026

Abstract

To establish a geometric framework for scleral fixation planning in secondary intraocular lens (IOL) implantation that accounts for corneal ellipticity and meridional orientation, and to analyze the limitations of fixed limbus-distance marking. The limbal boundary was modeled as an ellipse defined by the [...] Read more.

To establish a geometric framework for scleral fixation planning in secondary intraocular lens (IOL) implantation that accounts for corneal ellipticity and meridional orientation, and to analyze the limitations of fixed limbus-distance marking. The limbal boundary was modeled as an ellipse defined by the horizontal and vertical white-to-white (WTW) diameters. A target circumferential scleral locus is defined concentrically relative to an anatomical reference center. Fixation points are determined as a function of the meridional orientation θ using an explicit radial model of the elliptical limbus and an orientation-dependent limbal offset. The framework is analyzed for two-, three-, and four-point fixation configurations, including the effect of uniform circumferential displacement. A constant limbus-distance strategy implicitly assumes rotational invariance of limbal geometry. When the cornea is elliptical, this assumption produces predictable meridional deviations from the intended circumferential scleral locus for vertical and oblique fixation. An orientation-dependent limbal offset preserves geometric symmetry across all meridians and maintains fixation points on a consistent target locus, independent of angular configuration. Under representative biometric conditions, the maximal geometric deviation from the intended scleral locus approached approximately 0.58 mm when a constant limbus-distance strategy was applied. Scleral fixation planning can be formalized as a geometric problem governed by limbal ellipticity and meridional orientation. An explicit orientation-dependent model provides a technique-independent basis for reproducible fixation planning and reduces reliance on fixed-distance heuristics. Full article

(This article belongs to the Special Issue Emerging Technologies and Diagnostic Innovations in Optometry and Vision Science)

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20 pages, 13973 KB

Open AccessArticle

An End-to-End Deep Learning System for Gastrointestinal Bleeding Detection and Quantification in Wireless Capsule Endoscopy

by Mujeeb Rahman Kanhira Kadavath, Aman Kitaz, Nour El Houda Benyahia and Shatha Hussein

Diagnostics 2026, 16(13), 2121; https://doi.org/10.3390/diagnostics16132121 - 7 Jul 2026

Abstract

Background/Objectives: Gastrointestinal bleeding is a critical finding in wireless capsule endoscopy (WCE), but manual examination of thousands of image frames is labor-intensive, time-consuming, and susceptible to missed lesions. This study aimed to develop and evaluate a comprehensive deep-learning framework for automated bleeding [...] Read more.

Background/Objectives: Gastrointestinal bleeding is a critical finding in wireless capsule endoscopy (WCE), but manual examination of thousands of image frames is labor-intensive, time-consuming, and susceptible to missed lesions. This study aimed to develop and evaluate a comprehensive deep-learning framework for automated bleeding detection, localization, and quantitative assessment in WCE images. Methods: The proposed framework integrates three complementary deep-learning models: (i) a custom two-dimensional convolutional neural network (2D-CNN) for frame-level bleeding classification, (ii) a three-dimensional convolutional neural network (3D-CNN) for sequence-level analysis by exploiting temporal information from consecutive frames, and (iii) a U-Net architecture for pixel-level segmentation and bleeding-area quantification. The models were trained and evaluated using expert-annotated WCE datasets with pixel-level ground-truth masks. Results: The proposed 2D-CNN and 3D-CNN achieved excellent classification performance, with areas under the receiver operating characteristic curve (AUCs) of 0.9986 and 0.9971, respectively. The U-Net model achieved a Dice similarity coefficient of 0.93, an intersection-over-union (IoU) of 0.8677, and an overall segmentation accuracy of 97.25%. The integrated framework outperformed previously reported methods, demonstrating robust performance for bleeding detection, localization, and quantitative assessment. Conclusions: The proposed end-to-end deep-learning framework enables accurate automated bleeding detection, localization, and severity quantification in WCE images. By reducing the burden of manual image review, improving diagnostic consistency, and providing objective bleeding assessment, the framework has strong potential to support clinical decision-making and enhance gastrointestinal diagnostic workflows. Full article

(This article belongs to the Special Issue AI and Computational Tools in Gastrointestinal Diagnostics: Shaping the Future of Clinical Practice)

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22 pages, 3975 KB

Open AccessArticle

When Brownian Motion Meets Clinical Laboratory Automation: A DLS-Inspired Autocorrelation Function for Characterizing Workflow Performance in Sample Processing

by Claudia Spoliti, Raimondo De Cristofaro and Enrico Di Stasio

Diagnostics 2026, 16(13), 2120; https://doi.org/10.3390/diagnostics16132120 - 7 Jul 2026

Abstract

Background/Objectives: Laboratory automation is a key strategy for increasing productivity and reducing sample turnaround time (TAT), a common indicator of laboratory performance. However, owing to the statistical distribution of TAT values, conventional descriptors such as mean, standard deviation, and percentiles cannot capture [...] Read more.

Background/Objectives: Laboratory automation is a key strategy for increasing productivity and reducing sample turnaround time (TAT), a common indicator of laboratory performance. However, owing to the statistical distribution of TAT values, conventional descriptors such as mean, standard deviation, and percentiles cannot capture the processing history of individual samples. In this study, sample flow within a highly automated laboratory system was analyzed by analogy with the Brownian motion of molecules in solution, using an ad hoc modified Dynamic Light Scattering (DLS) correlation function. Methods: Seven processing histories, each consisting of 1000 samples and representing different TAT scenarios, were generated, and the corresponding correlation functions were calculated. Each sample was assumed to remain correlated with its initial state (value = 1) until its TAT was reached; thereafter, once the result was produced, the sample was considered uncorrelated and its status value became 0. The correlation function was defined as the normalized progressive sum, over time, of the status values of all analyzed samples at each time point. Results: The DLS-inspired autocorrelation function enabled the derivation of parameters describing both overall system performance and sample processing status. These parameters provide quantitative indicators for near-real-time monitoring of automation chain efficiency and reveal system features that are not accessible through conventional TAT statistics. Conclusions: This approach allows the definition of measurable metrics describing the system’s capacity to buffer and mitigate operational disruptions at both the global and individual-sample levels. The proposed framework provides a novel tool for evaluating, monitoring, and comparing the performance of laboratory automation systems. Full article

(This article belongs to the Special Issue Advances in the Laboratory Diagnosis—2nd Edition)

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10 pages, 3518 KB

Open AccessArticle

Tumor Heterogeneity of RCCs Assessed by mpMRI with Direct Radiological–Histopathological Correlation

by Antonia M. Pausch, Viktoria S. Hadnagy, Toni Rabadi, Daniel Eberli, Niels J. Rupp and Andreas M. Hötker

Diagnostics 2026, 16(13), 2119; https://doi.org/10.3390/diagnostics16132119 - 7 Jul 2026

Abstract

Background/Objectives: The heterogenous nature of renal cell carcinomas (RCCs) is increasingly recognized. The purpose of this proof-of-concept pilot study was to evaluate correlations between multiparametric MRI (mpMRI)-derived and histopathological parameters in RCCs from spatially matched regions on both MRI and pathological examination to [...] Read more.

Background/Objectives: The heterogenous nature of renal cell carcinomas (RCCs) is increasingly recognized. The purpose of this proof-of-concept pilot study was to evaluate correlations between multiparametric MRI (mpMRI)-derived and histopathological parameters in RCCs from spatially matched regions on both MRI and pathological examination to support targeted biopsy planning. Methods: In this prospective single-center pilot study, patients with solid renal tumors ≥2 cm undergoing nephrectomy were prospectively enrolled. Each patient underwent preoperative 3.0T-mpMRI including T2-weighted and pre-/post-contrast T1-weighted sequences, chemical-shift imaging, IVIM-DWI, and T1/T2*/R2 mapping. Tumor regions were defined jointly by a pathologist and radiologist, and identical regions of interest were assessed for each tumor region across all sequences to gain quantitative mpMRI-derived parameters. Histopathology provided quantitative regional fractions of viable tumor, fibrosis, hemorrhage, and cystic/necrotic components. Spearman’s rank correlations and univariable linear regression assessed associations between mpMRI and histopathological parameters on a regional level. Results: Across 49 tumor regions in eight patients (65.3% clear cell, 34.7% papillary RCCs), the mean viable tumor fraction was 80.9% (SD 17.6). The viable tumor fraction showed inverse correlations with nephrographic and delayed phase signal intensity changes (rho = −0.59/rho = −0.51), T1 values (rho = −0.56), true diffusion coefficient D (rho = −0.47), and ADC (rho = −0.45), and a positive correlation with R² times (rho = 0.55). Delayed and nephrographic phase signal intensity changes (R² = 0.41/R² = 0.39) were the strongest single exploratory imaging correlates of viable tumor fraction. Conclusions: These findings support the feasibility of quantitative mpMRI parameters to capture regional intratumoral heterogeneity in RCCs, thereby highlighting regions with high viable tumor burden, which may help to refine the imaging-based assessment of RCCs in the future. Full article

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

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22 pages, 1683 KB

Open AccessArticle

Machine Learning-Based Prediction of Masaoka–Koga Stage and WHO Histological Risk Group in Thymic Epithelial Tumors Using Biomarker Combinations

by Konstantinos Kitrou, Georgios Mandrakis, Georgios Tsirogiannis, Stamatios Theocharis, Constantinos Halkiopoulos and Yannis Stamatiou

Diagnostics 2026, 16(13), 2118; https://doi.org/10.3390/diagnostics16132118 - 7 Jul 2026

Abstract

Background: Thymic epithelial tumors (TETs) are the most common primary neoplasms of the anterior mediastinum and present a dual classification challenge, namely anatomical staging according to the Masaoka–Koga system and histological risk stratification according to the World Health Organization (WHO) classification. Both tasks [...] Read more.

Background: Thymic epithelial tumors (TETs) are the most common primary neoplasms of the anterior mediastinum and present a dual classification challenge, namely anatomical staging according to the Masaoka–Koga system and histological risk stratification according to the World Health Organization (WHO) classification. Both tasks rely on expert pathological assessment and may be affected by interobserver variability. This study applied supervised machine learning (ML) to quantitative immunohistochemical (IHC) H-score profiles to predict Masaoka–Koga stage and WHO risk group in TETs. Methods: Logistic regression (LR) and XGBoost were applied to 19 biomarkers, including cellular localization, across two parallel analyses. Masaoka–Koga stage prediction was performed in 81 patients, including 59 early-stage and 22 advanced-stage cases, using the Synthetic Minority Oversampling Technique (SMOTE) across 100 train/test splits. WHO risk group prediction was performed in 89 patients, including 45 low-risk and 44 high-risk tumors, without oversampling. A cross-endpoint analysis applied the optimal Masaoka–Koga model to the WHO endpoint. Results: LR consistently outperformed XGBoost. The optimal Masaoka–Koga model combined Eph receptor A6 (EphA6) membranous, Yes-associated protein (YAP) nuclear, and histone deacetylase 4 (HDAC4) cytoplasmic H-scores, achieving an area under the curve (AUC) of 0.756. The optimal WHO model combined transcriptional coactivator with PDZ-binding motif (TAZ) cytoplasmic, EphA6 membranous, and YAP nuclear H-scores, achieving an AUC of 0.936. The Masaoka–Koga triad predicted WHO risk group with an AUC of 0.901. No tetrad improved trivariate performance. Conclusions: IHC H-score profiling combined with supervised ML identifies biologically interpretable candidate signatures for TET classification, although prospective external validation is required before clinical application. Full article

(This article belongs to the Special Issue A New Era in Diagnosis: From Biomarkers to Artificial Intelligence, 2nd Edition)

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8 pages, 625 KB

Open AccessEditorial

Advances in Nephrology

by Marijn M. Speeckaert

Diagnostics 2026, 16(13), 2117; https://doi.org/10.3390/diagnostics16132117 - 6 Jul 2026

Abstract

Nephrology is experiencing an ongoing shift toward an era in which kidney diseases are differentiated by their intrinsic biology, rather than by clinical manifestations, histopathology, or changes in kidney function [...] Full article

(This article belongs to the Special Issue Advances in Nephrology)

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28 pages, 1304 KB

Open AccessReview

Endocrine Disruptors and Gynecological Malignancies

by Dimitris Baroutis, Eleni Katsianou, Konstantinos Koukoumpanis, Ioannis Fragiskos, Nikolaos Sindos, Michael Sindos and George Daskalakis

Diagnostics 2026, 16(13), 2116; https://doi.org/10.3390/diagnostics16132116 - 6 Jul 2026

Abstract

Background/Objectives: Endocrine-disrupting chemicals (EDCs) interfere with hormonal homeostasis and have been implicated in gynecological malignancy pathogenesis. This narrative review synthesizes current evidence regarding EDC exposure and breast, endometrial, ovarian, and cervical cancers, examining molecular mechanisms, epidemiology, and diagnostic and clinical implications. Methods: We [...] Read more.

Background/Objectives: Endocrine-disrupting chemicals (EDCs) interfere with hormonal homeostasis and have been implicated in gynecological malignancy pathogenesis. This narrative review synthesizes current evidence regarding EDC exposure and breast, endometrial, ovarian, and cervical cancers, examining molecular mechanisms, epidemiology, and diagnostic and clinical implications. Methods: We conducted a literature review using PubMed/MEDLINE, Embase, Scopus, and Cochrane databases through April 2026, including systematic reviews, meta-analyses, prospective cohorts, case-control studies, and mechanistic investigations examining EDC-cancer associations. Methodological quality was appraised using the Newcastle-Ottawa Scale and AMSTAR-2, with overall certainty of evidence rated using the GRADE framework. Results: Major EDC classes—bisphenol compounds, phthalates, polychlorinated biphenyls, organochlorine pesticides, and per- and polyfluoroalkyl substances—demonstrate carcinogenic potential through estrogen receptor modulation, epigenetic alterations, oxidative stress, and oncogenic signaling disruption. Breast cancer shows the strongest evidence, with prenatal and early-life DDT/DDE exposure associated with up to a 3.7-fold increased risk. Endometrial cancer demonstrates associations with xenoestrogen mixtures exhibiting non-monotonic dose-responses, whereas ovarian and cervical cancers show emerging but limited associations. Common mechanisms include receptor crosstalk, epigenetic dysregulation with transgenerational effects, oxidative genomic instability, metabolic reprogramming, and cancer stem cell enrichment. Conclusions: Evidence supports EDC contributions to gynecological malignancy through convergent pathways, though causal inference remains constrained by observational epidemiology, long latency periods, and challenges in characterizing real-world mixture exposures. Diagnostic and prevention strategies should integrate EDC exposure into risk-prediction models, leverage multi-omics biomarkers for early detection, and emphasize exposure reduction during critical developmental windows alongside regulatory reform. Full article

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

13 pages, 422 KB

Open AccessArticle

Genetic Testing Yield for Dilated Cardiomyopathy in a Single Lithuanian Center

by Marius Šukys, Eglė Ereminienė, Kristina Aleknavičienė, Rimvydas Jonikas, Karolina Mėlinytė-Ankudavičė, Paulius Bučius and Rasa Ugenskienė

Diagnostics 2026, 16(13), 2115; https://doi.org/10.3390/diagnostics16132115 - 6 Jul 2026

Abstract

Background/Objectives: Dilated cardiomyopathy is a heterogeneous disorder with a substantial genetic contribution from a variety of pathogenic variants. Hereditary isolated DCM is often caused by variants in genes encoding sarcomere proteins, as well as proteins involved in desmosomes or other cardiac cell [...] Read more.

Background/Objectives: Dilated cardiomyopathy is a heterogeneous disorder with a substantial genetic contribution from a variety of pathogenic variants. Hereditary isolated DCM is often caused by variants in genes encoding sarcomere proteins, as well as proteins involved in desmosomes or other cardiac cell functions. Identifying genetic causes improves our understanding of DCM pathophysiology, facilitates prognostic assessment, and enables more personalized disease management. Methods: We retrospectively analyzed genetic data from adult patients with a clinical diagnosis of isolated DCM evaluated at a Lithuanian tertiary university hospital between 2019 and 2024. All patients were tested with a next-generation sequencing cardiovascular gene panel. Results: We gathered 169 patients and initially reached a 16.0% (n = 27) genetic testing diagnostic yield. We performed all genetic variant reanalyses with the most current classification guidelines, and we found an additional eight positive cases. Our final diagnostic yield was 20.7% (n = 35). TTN was the most frequently affected gene (n = 30), whereas variants in BAG3 (n = 2), DSP (n = 1), LMNA (n = 1), and FLNC (n = 1) were rare. In total, 15 variants were novel—not described in the literature or databases. We did not observe significant clinical differences between patients with pathogenic variants and those without pathogenic variants. We expected a different clinical course with variants in genes like BAG3 or LMNA, but there were only a few cases. Conclusions: Genetic testing remains an important tool for confirming complex DCM cases and allows earlier disease management for relatives at risk. Full article

(This article belongs to the Special Issue From Clinical Diagnosis to Effective Treatment of Cardiomyopathy)

16 pages, 927 KB

Open AccessArticle

Footprints as Morphometric Evidence for Somatic Prediction and Body Proportion Reconstruction in Forensic Medicine

by Fatma Çam Aygün, Serdar Babacan, Tuğçe Koca Yavuz and Kenan Kaya

Diagnostics 2026, 16(13), 2114; https://doi.org/10.3390/diagnostics16132114 - 6 Jul 2026

Abstract

Background/Objectives: This study aimed to apply morphometric and multivariate analytical techniques to footprint evidence for forensic identity determination, focusing on sex estimation and the reconstruction of body proportions as components of the biological profile. By integrating detailed footprint metrics with body measurements, [...] Read more.

Background/Objectives: This study aimed to apply morphometric and multivariate analytical techniques to footprint evidence for forensic identity determination, focusing on sex estimation and the reconstruction of body proportions as components of the biological profile. By integrating detailed footprint metrics with body measurements, the research sought to develop discriminant and regression models to evaluate the predictive value of footprint metrics for sex estimation and selected somatic dimensions. Methods: Static bilateral footprints were obtained using charcoal powder impressions and digitized using ImageJ. Eleven footprint parameters (F1–F11) and eleven body measurements (B1–B11) were recorded. Sex-based differences were examined using appropriate parametric or non-parametric tests with effect sizes. Sex estimation was evaluated using discriminant function analysis and internally validated using leave-one-out and stratified 10-fold cross-validation. Regression models for stature and body dimension estimation were assessed with multicollinearity diagnostics and repeated 10-fold cross-validation, including RMSE, MAE, and cross-validated R². Results: The apparent discriminant classification accuracies were 74.0% for the right foot and 71.0% for the left foot. After internal validation, classification performance decreased to approximately 64–67%, indicating moderate discriminative ability. Reduced regression models showed the most stable validated performance for stature and arm span, although cross-validated R² values remained weak. Conclusions: Static footprint morphometry may provide supportive information for sex estimation and selected somatic dimensions in this Turkish adult sample. However, the validated performance indicates that these models should be interpreted as ancillary and exploratory tools rather than standalone forensic identification methods. Full article

(This article belongs to the Section Forensic Diagnostics)

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17 pages, 782 KB

Open AccessArticle

Renal Function and Serum Neurofilament Light Chain in Acute Ischemic Stroke: An Observational Cohort Study

by Federica Ferrari, Nicola Davide Loizzo, Federico Mazzacane, Beatrice Del Bello, Salvatore Console, Silvia Scaranzin, Chiara Morandi, Matteo Gastaldi, Alessandra Persico and Anna Cavallini

Diagnostics 2026, 16(13), 2113; https://doi.org/10.3390/diagnostics16132113 - 6 Jul 2026

Abstract

Background/Objectives. Neurofilament light chain (NfL) is a biomarker of axonal injury with prognostic value in acute ischemic stroke and a promising surrogate outcome marker. This study evaluated whether serum NfL concentrations in ischemic stroke were modified by varying degrees of renal function. [...] Read more.

Background/Objectives. Neurofilament light chain (NfL) is a biomarker of axonal injury with prognostic value in acute ischemic stroke and a promising surrogate outcome marker. This study evaluated whether serum NfL concentrations in ischemic stroke were modified by varying degrees of renal function. Methods. In this prospective, single-center observational study, patients aged 18–80 y admitted to the IRCCS Mondino Foundation—Stroke Unit between May 2022 and August 2024 were enrolled. Inclusion criteria were: radiologically confirmed ischemic stroke within 24 h of onset, NIHSS ≥ 1 at admission, pre-stroke mRS < 2, no other neurological comorbidities, and eGFR > 30 mL/min/1.73 m². Serum creatinine was measured on admission, and eGFR was calculated using the CKD-EPI equation. Serum NfL was measured by Ella™ immunoassay at T0 (≤24 h), T1 (5 ± 3 d), and T2 (7 ± 3 d). Factors associated with serum NfL concentrations were assessed using linear mixed-effects models, and prognostic associations were evaluated by multivariate logistic regression. Results. Ninety-seven patients were included (median age 68.3 y; 39.2% female). Higher NfL levels were independently associated with lower eGFR (−2.4% per mL/min/1.73 m² increase; 95% CI −3.2% to −1.6%; p < 0.001), and higher NIHSS at admission (+3.5% per point; 95% CI 0.7% to 6.4%; p = 0.014). Time from stroke onset was also associated with NfL (p < 0.001). Among patients with 3-month follow-up and T2 measurement (n = 62), the main effects of log10-transformed NfL at T2 and eGFR were not independently associated with unfavorable outcomes. However, a significant log10 NfL × eGFR interaction was observed (OR 0.22; 95% CI 0.07–0.73; p = 0.014), indicating that the prognostic association of NfL varied according to renal function. Conclusions. Renal function affects serum NfL after ischemic stroke and appears to modify its prognostic association with 3-month outcomes. Full article

(This article belongs to the Special Issue New Advances in Cerebrovascular Disease: Clinical Diagnosis, Treatment, and Prognosis)

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20 pages, 1108 KB

Open AccessArticle

Patient-Reported Experiences in Chronic Dermatological Conditions: Validation of the Romanian PSPSQ 2.0 Within Contemporary Dermatologic Care Pathways

by Nicoleta Cirstea, Delia Mirela Tit, Mirela Marioara Toma, Anamaria Lavinia Purza, Ada Radu, Gabriela S. Bungau, Ruxandra-Cristina Marin, Călin Muntean, Georgiana Iris Tit and Radu Dumitru Moleriu

Diagnostics 2026, 16(13), 2112; https://doi.org/10.3390/diagnostics16132112 - 6 Jul 2026

Abstract

Background/Objectives: Chronic dermatological conditions increasingly require complex and patient-centered therapeutic management, including biologic therapies, injectable treatments, and multidisciplinary care. In this context, patient-reported experience measures (PREMs) may provide valuable insight into the quality and effectiveness of pharmacist-delivered care. This study aims to [...] Read more.

Background/Objectives: Chronic dermatological conditions increasingly require complex and patient-centered therapeutic management, including biologic therapies, injectable treatments, and multidisciplinary care. In this context, patient-reported experience measures (PREMs) may provide valuable insight into the quality and effectiveness of pharmacist-delivered care. This study aims to translate, culturally adapt, and evaluate the psychometric performance of the Patient Satisfaction with Pharmacist Services Questionnaire (PSPSQ 2.0) as a patient-reported experience measure in Romanian patients with chronic dermatological conditions. Methods: A cross-sectional validation study was conducted in community pharmacies across Romania (N = 220). The questionnaire was translated using a structured forward-translation and expert review process, in accordance with ISPOR and COSMIN recommendations. Internal consistency was assessed using Cronbach’s alpha and item-level statistics. Construct validity was examined using exploratory factor analysis (EFA), confirmatory factor analysis (CFA), and bifactor modeling. Known-groups validity and floor and ceiling effects were also evaluated. Results: The Romanian PSPSQ 2.0 demonstrated excellent internal consistency (α = 0.978; subscales α = 0.961–0.969). EFA indicated a dominant single-factor structure, explaining 84.0% of the variance. In CFA, the original three-factor model showed excellent relative fit (CFI = 0.999, TLI = 0.999), although RMSEA indicated some model misfit (0.109). Bifactor analysis revealed a strong general satisfaction factor, with consistently high loadings (0.80–0.99), suggesting that most item variance is attributable to a global patient satisfaction construct. These findings support the use of the instrument as a global measure of patient experience within contemporary dermatologic care pathways. Conclusions: The Romanian version of the PSPSQ 2.0 demonstrates excellent reliability and acceptable construct validity as a PREM for assessing patient satisfaction with pharmacist services. The findings support the use of total scores as a robust indicator of patient experience, while domain-level interpretation should be approached with caution due to substantial overlap between dimensions. This instrument may support the integration of patient-reported measures into routine evaluation of pharmaceutical care. Full article

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

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14 pages, 2938 KB

Open AccessArticle

Towards Automated Quality Assurance: Integrating Deep Learning and Classical ML into the Digital Radiography Pipeline

by Hsuan-Yu Chen, Cheng-Fu Chou, Sheng-Hung Liao, Meng-Hsun Wu, Kuan-Yi Chen, Ta-Wei Yang, Jungwei Wilfred Fan and Chih-Hao Chang

Diagnostics 2026, 16(13), 2111; https://doi.org/10.3390/diagnostics16132111 - 6 Jul 2026

Abstract

Background/Objectives: To develop and evaluate a deep learning-based quality control system for Lumbar Spinal Digital Radiographs (LSDR), designed to automate and improve their evaluation and reduce reliance on manual reviews. Methods: This retrospective study utilized a deep learning workflow comprising image segmentation, feature [...] Read more.

Background/Objectives: To develop and evaluate a deep learning-based quality control system for Lumbar Spinal Digital Radiographs (LSDR), designed to automate and improve their evaluation and reduce reliance on manual reviews. Methods: This retrospective study utilized a deep learning workflow comprising image segmentation, feature extraction, and a classification model. The dataset, including anteroposterior (AP) and lateral (LAT) X-ray images, was expanded through data augmentation techniques. Four U-Net-based models were assessed: standard U-Net, Swin-UNet, Attention U-Net, and Attention U-Net with the weight map, with the latter selected for its superior performance. Extracted features, such as brightness, contrast, and anatomical positioning, were used in an XGBoost classifier, which was evaluated using mean intersection over union (mIoU), accuracy, sensitivity, specificity, and AUC. Results: The Attention U-Net with weighted attention outperformed the other models, achieving high mIoU scores in both AP and LAT views. The XGBoost classifier achieved the best performance in classifying images as “qualified” or “unqualified,” with an AUC of approximately 0.9, high accuracy, and balanced sensitivity and specificity. This approach effectively addressed class imbalances and improved model accuracy compared to traditional machine learning models such as MLP and SVM. Conclusions: The developed automated quality control system demonstrated potential for enhancing image quality, enhancing diagnostic reliability, and optimizing clinical workflow efficiency. Full article

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

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14 pages, 488 KB

Open AccessArticle

Complete Blood Count-Derived Inflammatory Indices in Catatonia: A Retrospective Matched Case–Control Study

by Octavia Căpățînă, Adela Hanga, Sonia Tivadar, Andrei Hopulele-Petri, Denis Paval and Mihaela Fadgyas Stanculete

Diagnostics 2026, 16(13), 2110; https://doi.org/10.3390/diagnostics16132110 - 6 Jul 2026

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Abstract

Background/Objectives: Catatonia is a severe transdiagnostic neuropsychiatric syndrome for which accessible biological correlates remain insufficiently characterized. This study explored whether complete blood count (CBC)-derived inflammatory indices differ between psychiatric inpatients with catatonia and matched psychiatric controls without catatonia. Methods: This retrospective [...] Read more.

Background/Objectives: Catatonia is a severe transdiagnostic neuropsychiatric syndrome for which accessible biological correlates remain insufficiently characterized. This study explored whether complete blood count (CBC)-derived inflammatory indices differ between psychiatric inpatients with catatonia and matched psychiatric controls without catatonia. Methods: This retrospective matched case–control study included 46 patients with catatonia and 46 psychiatric controls selected from the same clinical setting and study period. Controls were frequency-matched by sex, age distribution, and broad psychiatric diagnosis. CBC parameters obtained within the first 24 h of admission were used to calculate the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), systemic immune–inflammation index (SII), and systemic inflammation response index (SIRI). Group comparisons, adjusted log–linear regression models, Spearman correlations with documented catatonic signs, and exploratory receiver operating characteristic analyses were performed. Results: SII was higher in patients with catatonia than in controls and remained significant after Bonferroni correction (median 584 [IQR 468–823] vs. 476 [IQR 339–619], Bonferroni-adjusted p = 0.032). In secondary adjusted models, catatonia was associated with higher SII and SIRI after adjustment for body mass index, smoking, antipsychotic exposure, diabetes mellitus, and arterial hypertension. No inflammatory index correlated significantly with the number of documented catatonic signs after correction. Exploratory discrimination was poor to fair, with SII showing the highest AUC (0.665, 95% CI 0.550–0.773). Conclusions: CBC-derived indices, particularly SII, may reflect systemic inflammatory or physiological stress burden in catatonia, but they should be interpreted as exploratory markers rather than diagnostic biomarkers. Full article

(This article belongs to the Special Issue Advances in Mental Health Diagnosis and Screening, 2nd Edition)

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16 pages, 377 KB

Open AccessArticle

Urological Malformations Identify the High-Burden Phenotype Among Children Hospitalized for Presumed Urinary Tract Infection: A Retrospective Cohort

by Ana C. Espíritu-Mojarro, Gustavo A. Hernández-Fuentes, Gabriela E. Pedroza-Orozco, José Guzmán-Esquivel, Jesús Venegas-Ramírez, Ileana Y. Ceja-Claro, Daniel A. Montes-Galindo, Carmen A. Sánchez-Ramírez, Mercedes Fuentes-Murguia, Fabian Rojas-Larios, Karmina Sánchez-Meza, Gabriel Ceja-Espíritu, Mario Del-Toro-Equihua and Iván Delgado-Enciso

Diagnostics 2026, 16(13), 2109; https://doi.org/10.3390/diagnostics16132109 - 6 Jul 2026

Viewed by 125

Abstract

Background/Objectives: The clinical utility of renal ultrasound after pediatric urinary tract infection (UTI) remains controversial, particularly because not all ultrasonographic abnormalities have the same prognostic significance. This study aimed to determine whether nephrourological malformations identify the phenotype associated with greater subsequent clinical burden [...] Read more.

Background/Objectives: The clinical utility of renal ultrasound after pediatric urinary tract infection (UTI) remains controversial, particularly because not all ultrasonographic abnormalities have the same prognostic significance. This study aimed to determine whether nephrourological malformations identify the phenotype associated with greater subsequent clinical burden among children hospitalized with presumed UTI and interpretable renal ultrasound findings, and to differentiate this phenotype from non-malformative ultrasound abnormalities. Methods: A retrospective single-center hospital-based cohort study was conducted in children aged 2 months to 17 years hospitalized with a clinical diagnosis of UTI at a general hospital of the Mexican Social Security Institute between 2020 and 2025. The cohort included both microbiologically confirmed UTI cases and probable clinical/microbiologically unconfirmed UTI cases. Of 182 registered patients, 130 with interpretable renal ultrasound were included. The primary exposure was the presence of adjudicated nephrourological malformation. As a secondary exposure, within the subgroup without malformation, abnormal non-malformative ultrasound findings were compared with normal ultrasound findings. Outcomes included outpatient follow-up, subspecialty referral, and hospital readmission. Crude associations were expressed as relative risks (RR), and adjusted analyses were estimated using modified Poisson regression with HC3 robust errors. Results: Twenty-nine of 130 patients (22.31%) were classified as having nephrourological malformations, and 31 (23.85%) had abnormal non-malformative ultrasound findings. Malformations were associated with higher outpatient follow-up (79.31% vs. 44.55%; RR 1.78, 95% CI 1.34–2.37), greater subspecialty referral (79.31% vs. 49.50%; RR 1.60, 95% CI 1.22–2.10), and increased readmission (44.83% vs. 13.86%; RR 3.23, 95% CI 1.72–6.08). In adjusted models, malformations remained associated with follow-up (aRR 1.72, 95% CI 1.25–2.37), referral (aRR 1.59, 95% CI 1.17–2.16), and readmission (aRR 3.38, 95% CI 1.58–7.23). In contrast, abnormal non-malformative ultrasound findings showed no significant adjusted associations. Microbiologically confirmed UTI was present in 47/130 patients (36.15%), and malformations were more frequent in this subgroup than in probable/non-confirmed clinical UTI (34.04% vs. 15.66%; p = 0.027). Conclusions: In this single-center hospital-based cohort, subsequent clinical burden was concentrated in the nephrourological malformation phenotype rather than in the broader category of “abnormal ultrasound”. These findings suggest that renal ultrasound may serve as a useful prognostic stratification tool beyond its role as a nonspecific detector of abnormalities following pediatric UTI. Given the observational design, these associations should be confirmed in larger prospective studies. Full article

(This article belongs to the Special Issue Optimization of Clinical Imaging: From Diagnosis to Prognosis, 2nd Edition)

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13 pages, 963 KB

Open AccessReview

Choline PET/CT in the PSMA Era: Clinical Repositioning, Biological Perspectives, and Emerging Applications

by Virginia Rossetti, Lorenzo Fantini, Irene Marini, Monica Celli, Ilaria Grassi, Maddalena Sansovini, Silvia Nicolini, Federica Matteucci and Paola Caroli

Diagnostics 2026, 16(13), 2108; https://doi.org/10.3390/diagnostics16132108 - 6 Jul 2026

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Abstract

The widespread adoption of prostate-specific membrane antigen (PSMA)-targeted PET/CT has profoundly reshaped molecular imaging in prostate cancer and has substantially reduced the routine use of radiolabeled choline tracers. However, the transition from choline to PSMA imaging should not be interpreted simply as the [...] Read more.

The widespread adoption of prostate-specific membrane antigen (PSMA)-targeted PET/CT has profoundly reshaped molecular imaging in prostate cancer and has substantially reduced the routine use of radiolabeled choline tracers. However, the transition from choline to PSMA imaging should not be interpreted simply as the replacement of one radiopharmaceutical by another, but rather as part of a broader evolution from metabolism-based imaging toward receptor-targeted and biology-driven imaging strategies. This narrative review critically reassesses the residual and emerging role of choline PET/CT in the PSMA era, with particular attention to the biological rationale of choline uptake, selected prostate cancer scenarios, and extra-prostatic applications. In prostate cancer, PSMA PET/CT remains the dominant imaging modality because of its superior diagnostic performance, particularly in biochemical recurrence; nevertheless, choline PET/CT may provide complementary metabolic information in highly selected settings, including PSMA-low or heterogeneous disease, aggressive or dedifferentiated variants, neuroendocrine transformation, equivocal PSMA findings, and limited PSMA availability. These prostate cancer applications, however, are supported mainly by biological rationale, indirect evidence, and limited clinical data and should therefore be regarded as exploratory rather than established indications. By contrast, ¹⁸F-fluorocholine PET/CT has emerged as a clinically established imaging modality in primary hyperparathyroidism, particularly after negative or inconclusive conventional imaging, with prospective studies and meta-analyses demonstrating high detection rates and superior performance compared with conventional scintigraphic techniques. Additional applications in hepatocellular carcinoma and selected neuro-oncologic settings remain exploratory and require further validation. Overall, choline PET/CT should not be considered obsolete in the PSMA era, but selectively repositioned within biology-driven and multiparametric imaging strategies, with its strongest evidence currently supporting primary hyperparathyroidism and its other applications requiring cautious interpretation and further prospective validation. Full article

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

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26 pages, 4327 KB

Open AccessArticle

A Comparative Analysis of EWT and EMD Techniques in the Diagnosis of Major Depressive Disorder Using EEG: Asymmetry Features and Explainability via SHAP

by Nadide Gulsah Gulenc, Gokce Koc and Mahmut Ozturk

Diagnostics 2026, 16(13), 2107; https://doi.org/10.3390/diagnostics16132107 - 5 Jul 2026

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Abstract

Background/Objectives: Major Depressive Disorder is a serious mental disorder that negatively affects an individual’s health and quality of life. The diagnosis of this disease is based on clinical interviews, questionnaires, and the patient’s self-reports. The objective of this study is to develop [...] Read more.

Background/Objectives: Major Depressive Disorder is a serious mental disorder that negatively affects an individual’s health and quality of life. The diagnosis of this disease is based on clinical interviews, questionnaires, and the patient’s self-reports. The objective of this study is to develop a biological diagnostic system based on the analysis of EEG signals and brain regions, rather than relying on self-reports. Methods: In this study, the EEG signals in the Multimodal Open Mental Disorder Analysis (MODMA) dataset were divided into six anatomical regions: prefrontal, frontal, central, parietal, temporal, and occipital. Empirical Wavelet Transform and Empirical Mode Decomposition methods were applied separately to the channels in each region, resulting in three IMF components. A total of 23 features, including statistical, nonlinear, spectral, and model-based (AR) features, were extracted from each IMF component. In addition to these features, asymmetry features between the left and right hemispheres were also included. Feature dimensions ranging from 10 to 40 were selected via the mRMR method, and the extracted feature sets were classified using SVM, k-NN, RUSBoost, Random Forest, and Meta-Ensemble machine learning models with Leave-One-Subject-Out (LOSO) validation. Results: According to the analysis results, the highest accuracy rate in Major Depressive Disorder (MDD) diagnosis was achieved by classifying features extracted from the frontal and prefrontal regions. The EMD signal processing method demonstrated superior performance compared to the EWT method. An accuracy rate of 98.11% was achieved using Random Forest and Meta-Ensemble models. Conclusions: In the proposed method, Explainable Artificial Intelligence (XAI) based SHAP analysis was applied to provide reliable and interpretable features for MDD diagnosis based on brain regional analysis. Full article

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

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20 pages, 1351 KB

Open AccessArticle

Ultrasound-Guided 5% Dextrose Hydrodissection Procedures for Persistent and Recurrent Post-Surgical Carpal Tunnel Syndrome: A Prospective Single-Center Cohort Study

by Marius Nicolae Popescu, Claudiu Căpeț, Simona Elena Săvulescu, Cristina Popescu and Mihai Berteanu

Diagnostics 2026, 16(13), 2106; https://doi.org/10.3390/diagnostics16132106 - 5 Jul 2026

Viewed by 174

Abstract

Background/Objectives: Persistent and recurrent symptoms after carpal tunnel release remain challenging, and non-surgical options for post-surgical carpal tunnel syndrome (CTS) are poorly defined. This study evaluated 6-month treatment success after ultrasound-guided 5% dextrose in water (D5W) hydrodissection in persistent or recurrent post-surgical [...] Read more.

Background/Objectives: Persistent and recurrent symptoms after carpal tunnel release remain challenging, and non-surgical options for post-surgical carpal tunnel syndrome (CTS) are poorly defined. This study evaluated 6-month treatment success after ultrasound-guided 5% dextrose in water (D5W) hydrodissection in persistent or recurrent post-surgical CTS and compared outcomes between subgroups. Methods: In this prospective single-center interventional cohort study, 100 patients with post-surgical CTS were enrolled: 50 with persistent disease and 50 with recurrent disease. All underwent 1–4 treatments with ultrasound-guided D5W hydrodissection using a standardized protocol. Treatment success at 6 months was defined as Patient Global Impression of Change (PGIC) scores of 6–7 together with clinically meaningful improvement in at least two of three domains: ≥30% reduction in 0–10 VAS pain, ≥0.8-point reduction in BCTQ-SSS, and ≥0.5-point reduction in BCTQ-FSS. Secondary outcomes included 12-month durability; longitudinal clinical, ultrasonographic, and electrodiagnostic changes; predictors of treatment success; treatment exposure; and safety. Results: Treatment success at 6 months occurred in 58 of 100 patients (58.0%) and was more frequent in recurrent than persistent CTS (70.0% vs. 46.0%, p = 0.015). At 12 months, treatment success persisted in 52.0% of the cohort (64.0% vs. 40.0%, p = 0.017). Clinical and ultrasonographic outcomes improved significantly over time, with greater improvement in recurrent CTS. Electrodiagnostic improvement was more modest. Recurrent CTS independently predicted success (adjusted OR 2.58, 95% CI 1.10–6.03), whereas severe electrodiagnostic involvement and greater baseline median nerve cross-sectional area were associated with lower odds of success. No serious treatment-related adverse events occurred. Conclusions: Ultrasound-guided D5W hydrodissection was associated with meaningful improvement in post-surgical CTS, particularly recurrent disease. Full article

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

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Diagnostics, Volume 16, Issue 13 (July-1 2026) – 191 articles

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