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Diagnostics
Volume 15
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Diagnostics, Volume 15, Issue 15 (August-1 2025) – 147 articles

Cover Story (view full-size image): Cardiac troponins are essential for the diagnosis of acute coronary syndromes, and the 99th percentile upper reference limit of troponin in the general population can be used to diagnose patients with myocardial injury. The Roche high-sensitivity troponin T assay is the only troponin T assay that has been recommended by the European Society of Cardiology for use in its rapid rule-out algorithms. In this paper, we report the performance of the new Sysmex high-sensitivity troponin T assay compared to the Roche troponin T assay and establish the high-sensitivity status of the Sysmex assay. In addition, we derived the 99th percentile upper reference limit for the Sysmex assay in both males and females in a healthy multi-ethnic population, and report the trends observed with increasing age and renal dysfunction. View this paper
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27 pages, 6083 KiB  
Article
Multidisciplinary, Clinical Assessment of Accelerated Deep-Learning MRI Protocols at 1.5 T and 3 T After Intracranial Tumor Surgery and Their Influence on Residual Tumor Perception
by Christer Ruff, Till-Karsten Hauser, Constantin Roder, Daniel Feucht, Paula Bombach, Leonie Zerweck, Deborah Staber, Frank Paulsen, Ulrike Ernemann and Georg Gohla
Diagnostics 2025, 15(15), 1982; https://doi.org/10.3390/diagnostics15151982 - 7 Aug 2025
Viewed by 330
Abstract
Background/Objectives: Postoperative MRI is crucial for detecting residual tumor, identifying complications, and planning subsequent therapy. This study evaluates accelerated deep learning reconstruction (DLR) versus standard clinical protocols for early postoperative MRI following tumor resection. Methods: This study uses a multidisciplinary approach [...] Read more.
Background/Objectives: Postoperative MRI is crucial for detecting residual tumor, identifying complications, and planning subsequent therapy. This study evaluates accelerated deep learning reconstruction (DLR) versus standard clinical protocols for early postoperative MRI following tumor resection. Methods: This study uses a multidisciplinary approach involving a neuroradiologist, neurosurgeon, neuro-oncologist, and radiotherapist to evaluate qualitative aspects using a 5-point Likert scale, the preferred reconstruction variant and potential residual tumor of DLR and conventional reconstruction (CR) of FLAIR, T1-weighted non-contrast and contrast-enhanced (T1), and coronal T2-weighted (T2) sequences for 1.5 and 3 T MRI. Quantitative analysis included the image quality metrics Structural Similarity Index (SSIM), Multi-Scale SSIM (MS-SSIM), Feature Similarity Index (FSIM), Noise Quality Metric (NQM), signal-to-noise ratio (SNR), and Peak SNR (PSNR) with CR as a reference. Results: All raters strongly preferred DLR over CR. This was most pronounced for FLAIR images at 1.5 and 3 T (91% at 1.5 T and 97% at 3 T) and least pronounced for T1 at 1.5 T (79% for non-contrast-enhanced and 84% for contrast-enhanced sequences) and for T2 at 3 T (69%). DLR demonstrated superior qualitative image quality for all sequences and field strengths (p < 0.001), except for T2 at 3 T, which was observed across all raters (p = 0.670). Diagnostic confidence was similar at 3 T with better but non-significant differences for T2 (p = 0.134) and at 1.5 T with better but non-significant differences for non-contrast-enhanced T1 (p = 0.083) and only marginally significant results for FLAIR (p = 0.033). Both the SSIM and MS-SSIM indicated near-perfect similarity between CR and DLR. FSIM performs worse in terms of consistency between CR and DLR. The image quality metrics NQM, SNR, and PSNR showed better results for DLR. Visual assessment of residual tumor was similar at 3 T but differed at 1.5 T, with more residual tumor detected with DLR, especially by the neurosurgeon (n = 4). Conclusions: An accelerated DLR protocol demonstrates clinical feasibility, enabling high-quality reconstructions in challenging postoperative MRIs. DLR sequences received strong multidisciplinary preference, underscoring their potential to improve neuro-oncologic decision making and suitability for clinical implementation. Full article
(This article belongs to the Special Issue Advanced Brain Tumor Imaging)
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20 pages, 2991 KiB  
Article
Data Analytics and Machine Learning Models on COVID-19 Medical Reports Enhanced with XAI for Usability
by Oliver Lohaj, Ján Paralič, Zuzana Paraličová, Daniela Javorská and Elena Zagorová
Diagnostics 2025, 15(15), 1981; https://doi.org/10.3390/diagnostics15151981 - 7 Aug 2025
Viewed by 307
Abstract
Objective—To identify effective data analytics and machine learning solutions that can help in the decision-making process in the medical domain and contribute to the understanding of COVID-19 disease. In this study, we analyze data from anonymized electronic medical records of 4711 patients [...] Read more.
Objective—To identify effective data analytics and machine learning solutions that can help in the decision-making process in the medical domain and contribute to the understanding of COVID-19 disease. In this study, we analyze data from anonymized electronic medical records of 4711 patients with COVID-19 disease admitted to hospital in Atlanta. Methods—We used random forest, LightGBM, XGBoost, CatBoost, KNN, SVM, logistic regression, and MLP neural network models in this work. The models are evaluated depending on the type of prediction by relevant metrics, especially accuracy, F1-score, and ROC AUC score. Another aim of the work was to find out which factors most affected severity and mortality risk among the patients. To identify the important features, different statistical methods were used, as well as LASSO regression, and explainable artificial intelligence (XAI) method SHAP values for model explainability. The best models were implemented in a web application and tested by medical experts. The model for prediction of mortality risk was tested on a validation cohort of 45 patients from the Department of Infectiology and Travel Medicine, L. Pasteur University Hospital in Košice (UNLP). Results—Our study shows that the best model for predicting COVID-19 disease severity was the LightGBM model with accuracy of 88.4% using all features and 89.5% using the eight most important features. The best model for predicting mortality risk was also the LightGBM model, which achieved a ROC AUC score of 83.7% and a classification accuracy of 81.2% using all features. Using a simplified model trained on the 15 most important features, the ROC AUC score was 83.6% and the classification accuracy was 80.5%. We deployed the simplified models for predicting COVID-19 disease severity and for predicting the risk of COVID-19-related death in a web-based application and tested them with medical experts. This test resulted in a ROC AUC score of 83.6% and an overall prediction accuracy of 73.3%. Full article
(This article belongs to the Special Issue Artificial Intelligence for Health and Medicine)
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12 pages, 588 KiB  
Article
Factors Affecting Thyroid Volume in Children Aged 4 to 18 Years
by Nevena Folić, Marko Folić, Miloš N. Milosavljević, Ana V. Pejčić, Slobodan Janković, Maja Vulović, Milos Stepovic, Isidora Mihajlović and Jovana Milosavljević
Diagnostics 2025, 15(15), 1980; https://doi.org/10.3390/diagnostics15151980 - 7 Aug 2025
Viewed by 322
Abstract
Background and Objectives: Ultrasound measurement of thyroid volume is not routinely performed in children without suspected thyroid disorders. However, pediatricians must be aware of the normal thyroid volume values in children in order to recognize and treat thyroid disorders in children on time. [...] Read more.
Background and Objectives: Ultrasound measurement of thyroid volume is not routinely performed in children without suspected thyroid disorders. However, pediatricians must be aware of the normal thyroid volume values in children in order to recognize and treat thyroid disorders in children on time. Therefore, this study aimed to explore factors that influence thyroid volume in children aged 4 to 18 years and to provide descriptive data on thyroid volume across this age range. Materials and Methods: This was a prospective, non-interventional cross-sectional study conducted on a population of children aged 4 to 18 years without confirmed thyroid disorders. We used validated formulas for calculating thyroid volume that integrate the linear dimensions of this organ, such as length, width, and depth, as well as the appropriate correction factor. The Spearman or Pearson correlation coefficient was calculated to assess the relationship between total thyroid volume and various continuous variables, while multiple linear regression analysis was used to evaluate the effect of potential predictors on the total thyroid volume. Results: The study included 100 children, predominantly girls (75.0%). Significant positive correlations with thyroid volume were found for age, height, weight, body mass index (BMI), body surface area, serum creatinine, birthweight, and number of comorbidities, while calcitonin was negatively correlated with children’s thyroid volume. We identified age, BMI, and serum creatinine as significant independent positive predictors of thyroid volume in children. Conclusions: Age, BMI, and serum creatinine emerged as significant independent positive predictors of thyroid volume and should be considered when interpreting pediatric thyroid ultrasound measurements. Full article
(This article belongs to the Special Issue Advances in the Diagnosis and Management of Head and Neck Disease)
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8 pages, 1090 KiB  
Interesting Images
A Rare and Atypical Manifestation of Intraosseous Hemangioma in the Zygomatic Bone
by Evagelos Kalfarentzos, Efthymios Mavrakos, Kamil Nelke, Andreas Kouroumalis, Gerasimos Moschonas, Argyro Mellou, Anastasia Therapontos and Christos Perisanidis
Diagnostics 2025, 15(15), 1979; https://doi.org/10.3390/diagnostics15151979 - 7 Aug 2025
Viewed by 305
Abstract
Intraosseous hemangiomas (IH) are rare intrabony lesions that represent less than 1% of intraosseous tumors. IH are mostly seen in the axial skeleton and skull. Most commonly, the frontal bone, zygomatic, sphenoid, maxilla, ethmoid, and lacrimal bone can manifest IH. Currently, IH is [...] Read more.
Intraosseous hemangiomas (IH) are rare intrabony lesions that represent less than 1% of intraosseous tumors. IH are mostly seen in the axial skeleton and skull. Most commonly, the frontal bone, zygomatic, sphenoid, maxilla, ethmoid, and lacrimal bone can manifest IH. Currently, IH is classified as a developmental condition of endothelial origin. According to WHO, the five histological types of IH are cavernous, capillary, epithelioid, histiocytoid, and sclerosing. IH of the zygoma is an extremely rare condition with female predominance. A systematic review recently estimated that there were 78 cases published in the literature until 2023. The lesion is usually asymptomatic and presents with a gradually deteriorating deformity of the malar area, and the patient might be able to recall a history of trauma. Numbness due to involvement of the infraorbital nerve might also be present; however, atypical skin and bone sensations might also occur. Other symptoms include painful swelling, bone asymmetry, skin irritation, sinus pressure, paresthesia, diplopia, enophthalmos, or atypical neuralgia. A bony lesion with a trabecular pattern in a radiating formation (sunburst pattern) or a multilocal lytic lesion pattern created by the multiple cavernous spaces (honeycomb pattern) is commonly observed during radiologic evaluation. We present a rare case of IH of the zygoma in a 65-year-old generally healthy woman. A cyst-like bone tumor was revealed from the CT scan, which made preoperative biopsy of the lesion problematic. A careful radiological diagnostic differentiation of the lesion should always be conducted in such cases to outline a safe surgical plan and possible alternatives if needed. The patient underwent total tumor resection in the operating room, and the defect was reconstructed with the use of a titanium mesh and a synthetic hydroxyapatite bone graft based on a 3D surgical guide printed model. Full article
(This article belongs to the Collection Interesting Images)
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17 pages, 5085 KiB  
Article
A Segmentation Network with Two Distinct Attention Modules for the Segmentation of Multiple Renal Structures in Ultrasound Images
by Youhe Zuo, Jing Li and Jing Tian
Diagnostics 2025, 15(15), 1978; https://doi.org/10.3390/diagnostics15151978 - 7 Aug 2025
Viewed by 302
Abstract
Background/Objectives: Ultrasound imaging is widely employed to assess kidney health and diagnose renal diseases. Accurate segmentation of renal structures in ultrasound images plays a critical role in the diagnosis and treatment of related kidney diseases. However, challenges such as speckle noise and [...] Read more.
Background/Objectives: Ultrasound imaging is widely employed to assess kidney health and diagnose renal diseases. Accurate segmentation of renal structures in ultrasound images plays a critical role in the diagnosis and treatment of related kidney diseases. However, challenges such as speckle noise and low contrast still hinder precise segmentation. Methods: In this work, we propose an encoder–decoder architecture, named MAT-UNet, which incorporates two distinct attention mechanisms to enhance segmentation accuracy. Specifically, the multi-convolution pixel-wise attention module utilizes the pixel-wise attention to enable the network to focus more effectively on important features at each stage. Furthermore, the triple-branch multi-head self-attention mechanism leverages the different convolution layers to obtain diverse receptive fields, capture global contextual information, compensate for the local receptive field limitations of convolution operations, and boost the segmentation performance. We evaluate the segmentation performance of the proposed MAT-UNet using the Open Kidney US Data Set (OKUD). Results: For renal capsule segmentation, MAT-UNet achieves a Dice Similarity Coefficient (DSC) of 93.83%, a 95% Hausdorff Distance (HD95) of 32.02 mm, an Average Surface Distance (ASD) of 9.80 mm, and an Intersection over Union (IOU) of 88.74%. Additionally, MAT-UNet achieves a DSC of 84.34%, HD95 of 35.79 mm, ASD of 11.17 mm, and IOU of 74.26% for central echo complex segmentation; a DSC of 66.34%, HD95 of 82.54 mm, ASD of 19.52 mm, and IOU of 51.78% for renal medulla segmentation; and a DSC of 58.93%, HD95 of 107.02 mm, ASD of 21.69 mm, and IOU of 43.61% for renal cortex segmentation. Conclusions: The experimental results demonstrate that our proposed MAT-UNet achieves superior performance in multiple renal structure segmentation in ultrasound images. Full article
(This article belongs to the Section Machine Learning and Artificial Intelligence in Diagnostics)
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4 pages, 179 KiB  
Editorial
Sports Radiology: A Key Driver of Clinical Decision-Making
by Francesco Feletti
Diagnostics 2025, 15(15), 1977; https://doi.org/10.3390/diagnostics15151977 - 7 Aug 2025
Viewed by 252
Abstract
In recent years, radiology has become a key factor in sports clinical decision-making, primarily due to two parallel trends: the need for timely imaging in elite sports and the increase in recreational and weekend exercise-related injuries among individuals who adopt a healthy lifestyle, [...] Read more.
In recent years, radiology has become a key factor in sports clinical decision-making, primarily due to two parallel trends: the need for timely imaging in elite sports and the increase in recreational and weekend exercise-related injuries among individuals who adopt a healthy lifestyle, often in outdoor settings and without structured physical preparation [...] Full article
(This article belongs to the Section Medical Imaging and Theranostics)
3 pages, 135 KiB  
Editorial
Exploring Gynecological Pathology and Imaging: A Crossroads of Technology, Biology, and Care
by Graziella Di Grezia
Diagnostics 2025, 15(15), 1976; https://doi.org/10.3390/diagnostics15151976 - 7 Aug 2025
Viewed by 282
Abstract
The field of gynecologic diagnostics is undergoing a profound transformation [...] Full article
(This article belongs to the Special Issue Exploring Gynecological Pathology and Imaging)
13 pages, 2759 KiB  
Article
A Novel Serum-Based Bioassay for Quantification of Cancer-Associated Transformation Activity: A Case–Control and Animal Study
by Aye Aye Khine, Hsuan-Shun Huang, Pao-Chu Chen, Chun-Shuo Hsu, Ying-Hsi Chen, Sung-Chao Chu and Tang-Yuan Chu
Diagnostics 2025, 15(15), 1975; https://doi.org/10.3390/diagnostics15151975 - 6 Aug 2025
Viewed by 370
Abstract
Background/Objectives: The detection of ovarian cancer remains challenging due to the lack of reliable serum biomarkers that reflect malignant transformation rather than mere tumor presence. We developed a novel biotest using an immortalized human fallopian tube epithelial cell line (TY), which exhibits [...] Read more.
Background/Objectives: The detection of ovarian cancer remains challenging due to the lack of reliable serum biomarkers that reflect malignant transformation rather than mere tumor presence. We developed a novel biotest using an immortalized human fallopian tube epithelial cell line (TY), which exhibits anchorage-independent growth (AIG) in response to cancer-associated serum factors. Methods: Sera from ovarian and breast cancer patients, non-cancer controls, and ID8 ovarian cancer-bearing mice were tested for AIG-promoting activity in TY cells. Results: TY cells (passage 96) effectively distinguished cancer sera from controls (68.50 ± 2.12 vs. 17.50 ± 3.54 colonies, p < 0.01) and correlated with serum CA125 levels (r = 0.73, p = 0.03) in ovarian cancer patients. Receiver operating characteristic (ROC) analysis showed high diagnostic accuracy (AUC = 0.85, cutoff: 23.75 colonies). The AIG-promoting activity was mediated by HGF/c-MET and IGF/IGF-1R signaling, as inhibition of these pathways reduced phosphorylation and AIG. In an ID8 mouse ovarian cancer model, TY-AIG colonies strongly correlated with tumor burden (r = 0.95, p < 0.01). Conclusions: Our findings demonstrate that the TY cell-based AIG assay is a sensitive and specific biotest for detecting ovarian cancer and potentially other malignancies, leveraging the fundamental hallmark of malignant transformation. Full article
(This article belongs to the Special Issue New Insights into the Diagnosis of Gynecological Diseases)
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16 pages, 2369 KiB  
Article
HMGB1 Deficiency Occurs in a Broad Range of Human Cancers and Is Often Associated with Unfavorable Tumor Phenotype
by Viktoria Chirico, Hena Sharifi, Maria Christina Tsourlakis, Seyma Büyücek, Clara Marie von Bargen, Katharina Möller, Florian Lutz, David Dum, Martina Kluth, Claudia Hube-Magg, Georgia Makrypidi-Fraune, Piero Caneve, Maximilian Lennartz, Morton Freytag, Sebastian Dwertmann Rico, Simon Kind, Viktor Reiswich, Eike Burandt, Till S. Clauditz, Patrick Lebok, Christoph Fraune, Till Krech, Sarah Minner, Andreas H. Marx, Waldemar Wilczak, Ronald Simon, Guido Sauter, Stefan Steurer and Kristina Jansenadd Show full author list remove Hide full author list
Diagnostics 2025, 15(15), 1974; https://doi.org/10.3390/diagnostics15151974 - 6 Aug 2025
Viewed by 360
Abstract
Background/Objectives: Aberrant expression of high-mobility group protein B1 (HMGB1) has been linked to cancer development and progression. Methods: To better comprehend the role of HMGB1 expression in cancer, a tissue microarray containing 14,966 samples from 134 different tumor entities and 608 [...] Read more.
Background/Objectives: Aberrant expression of high-mobility group protein B1 (HMGB1) has been linked to cancer development and progression. Methods: To better comprehend the role of HMGB1 expression in cancer, a tissue microarray containing 14,966 samples from 134 different tumor entities and 608 samples of 76 different normal tissue types was analyzed by immunohistochemistry. Results: Strong HMGB1 staining occurred in almost all normal cell types and in most cancers. Of 11,808 evaluable cancers, only 7.8% showed complete absence of HMGB1 staining (HMGB1 deficiency) while 9.9% showed 1+, 25.0% showed 2+, and 57.2% showed 3+ HMGB1 positivity. Absence of HMGB1 staining mostly occurred in pheochromocytoma (90.0%), seminoma (72.4%), gastrointestinal stromal tumor (28.6%), adrenal cortical carcinoma (25.0%), and Hodgkin’s lymphoma (25.0%). Low HMGB1 staining was linked to poor histologic grade (p < 0.0001), advanced pT stage (p < 0.0001), high UICC stage (p < 0.0001), and distant metastasis (p = 0.0413) in clear cell renal cell carcinoma, invasive tumor growth in urothelial carcinoma (pTa vs. pT2–4, p < 0.0001), mismatch repair deficiency (p = 0.0167) in colorectal cancers, and advanced pT stage in invasive breast carcinoma of no special type (p = 0.0038). Strong HMGB1 staining was linked to nodal metastases in high-grade serous ovarian carcinomas (p = 0.0213) and colorectal adenocarcinomas (p = 0.0137), as well as to poor histological grade in squamous cell carcinomas (p = 0.0010). Conclusions: HMGB1 deficiency and reduced HMGB1 expression occur in a broad range of different tumor entities. Low rather than strong HMGB1 staining is often linked to an aggressive tumor phenotype. Whether HMGB1 deficiency renders cells susceptible to specific drugs remains to be determined. Full article
(This article belongs to the Section Pathology and Molecular Diagnostics)
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18 pages, 7706 KiB  
Review
The Role of Imaging in Ventricular Tachycardia Ablation
by Pasquale Notarstefano, Michele Ciabatti, Carmine Marallo, Mirco Lazzeri, Aureliano Fraticelli, Valentina Tavanti, Giulio Zucchelli, Angelica La Camera and Leonardo Bolognese
Diagnostics 2025, 15(15), 1973; https://doi.org/10.3390/diagnostics15151973 - 6 Aug 2025
Viewed by 327
Abstract
Ventricular tachycardia (VT) remains a major cause of morbidity and mortality in patients with structural heart disease. While catheter ablation has become a cornerstone in VT management, recurrence rates remain substantial due to limitations in electroanatomic mapping (EAM), particularly in cases of deep [...] Read more.
Ventricular tachycardia (VT) remains a major cause of morbidity and mortality in patients with structural heart disease. While catheter ablation has become a cornerstone in VT management, recurrence rates remain substantial due to limitations in electroanatomic mapping (EAM), particularly in cases of deep or heterogeneous arrhythmogenic substrates. Cardiac imaging, especially when multimodal and integrated with mapping systems, has emerged as a critical adjunct to enhance procedural efficacy, safety, and individualized strategy. This comprehensive review explores the evolving role of various imaging modalities, including echocardiography, cardiac magnetic resonance (CMR), computed tomography (CT), positron emission tomography (PET), and intracardiac echocardiography (ICE), in the preprocedural and intraprocedural phases of VT ablation. We highlight their respective strengths in substrate identification, anatomical delineation, and real-time guidance. While limitations persist, including costs, availability, artifacts in device carriers, and lack of standardization, future advances are likely to redefine procedural workflows. Full article
(This article belongs to the Special Issue Advances in Diagnosis and Treatment of Cardiac Arrhythmias 2025)
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20 pages, 1388 KiB  
Article
Beyond Bone Mineral Density: Real-World Fracture Risk Profiles and Therapeutic Gaps in Postmenopausal Osteoporosis
by Anamaria Ardelean, Delia Mirela Tit, Roxana Furau, Oana Todut, Gabriela S. Bungau, Roxana Maria Sânziana Pavel, Bogdan Uivaraseanu, Diana Alina Bei and Cristian Furau
Diagnostics 2025, 15(15), 1972; https://doi.org/10.3390/diagnostics15151972 - 6 Aug 2025
Viewed by 385
Abstract
Background/Objectives: Osteoporosis remains a leading cause of morbidity in postmenopausal women, yet many high-risk individuals remain undiagnosed or untreated. This study aimed to assess the prevalence of osteoporosis and osteopenia, treatment patterns, and skeletal fragility indicators in a large cohort of postmenopausal [...] Read more.
Background/Objectives: Osteoporosis remains a leading cause of morbidity in postmenopausal women, yet many high-risk individuals remain undiagnosed or untreated. This study aimed to assess the prevalence of osteoporosis and osteopenia, treatment patterns, and skeletal fragility indicators in a large cohort of postmenopausal women undergoing DXA screening. Methods: We analyzed data from 1669 postmenopausal women aged 40–89 years who underwent DXA evaluation. BMD status was categorized as normal, osteopenia, or osteoporosis. Treatment status was classified based on active antiosteoporotic therapy, calcium/vitamin D supplementation, hormonal therapy (historical use), or no treatment. Logistic regression models were used to explore independent predictors of osteoporosis and treatment uptake. Results: A total of 45.0% of women had osteoporosis and 43.5% had osteopenia. Despite this, 58.5% of the population, over half of women with osteoporosis, were not receiving any active pharmacologic treatment. Bisphosphonates were the most prescribed therapy (17.9%), followed by calcium/vitamin D supplements (20.6%). A prior history of fragility fractures and radiological bone lesions were significantly associated with lower BMD (p < 0.05). Historical hormone replacement therapy (HRT) use was not associated with current BMD (p = 0.699), but women with HRT use reported significantly fewer fractures (p < 0.001). In multivariate analysis, later menopause age and low BMD status predicted higher odds of receiving active treatment. Conclusions: Our findings highlight a substantial care gap in osteoporosis management, with treatment primarily initiated reactively in more severe cases. Improved screening and earlier intervention strategies are urgently needed to prevent fractures and reduce the long-term burden of osteoporosis. Full article
(This article belongs to the Special Issue Diagnosis and Management of Osteoporosis)
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6 pages, 9206 KiB  
Interesting Images
“Single Coronary Artery” from Right Sinus—Uncommon Causes of Ischemia with Non-Obstructive Coronary Arteries
by Paweł Muszyński, Marlena Święcicka, Dominika Musiałowska, Dorota Pura, Małgorzata Kazberuk, Anna Kożuchowska-Eljasiewicz, Caroline Sasinowski, Urszula Bajda, Wiktoria Grądzka-Matys and Anna Tomaszuk-Kazberuk
Diagnostics 2025, 15(15), 1971; https://doi.org/10.3390/diagnostics15151971 - 6 Aug 2025
Viewed by 261
Abstract
Anomalies of coronary artery origins are rare but significant conditions that can range from benign to life-threatening. Early detection through imaging is crucial in preventing adverse outcomes. The treatment strategy varies depending on the type and severity of the anomaly, ranging from pharmacological [...] Read more.
Anomalies of coronary artery origins are rare but significant conditions that can range from benign to life-threatening. Early detection through imaging is crucial in preventing adverse outcomes. The treatment strategy varies depending on the type and severity of the anomaly, ranging from pharmacological treatment to surgery. A 22-year-old male patient, after syncope, after excluding other causes, had an exercise drill test, which was clinically negative and ECG-positive. Angio-CT revealed an undeveloped left main coronary artery (LMCA), and the circulation was supplied through the right coronary artery (RCA). The RCA provides the left anterior descending artery (LAD), and the LAD retrogradely supplies the left circumflex artery (LCX). The myocardial perfusion scintigraphy showed a slight lack of perfusion in the anterior wall (6% of total perfusion). The patient was qualified for further observation. A 77-year-old female underwent cardiac CT due to stenocardia. CT showed a lack of LMCA. The initial segment of the RCA gave rise to the left coronary artery (LCA), which encircled the aortic bulb posteriorly and bifurcated into branches resembling the LCX and LAD. After the Heart Team consultation, the patient was deemed eligible for conservative treatment. Angio-CT is a valuable tool for detecting coronary artery anomalies. Full article
(This article belongs to the Special Issue Novel Diagnostic Approaches and Treatment of Angina and Myocardial Ischemia)
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19 pages, 487 KiB  
Review
Smart Clothing and Medical Imaging Innovations for Real-Time Monitoring and Early Detection of Stroke: Bridging Technology and Patient Care
by David Sipos, Kata Vészi, Bence Bogár, Dániel Pető, Gábor Füredi, József Betlehem and Attila András Pandur
Diagnostics 2025, 15(15), 1970; https://doi.org/10.3390/diagnostics15151970 - 6 Aug 2025
Viewed by 502
Abstract
Stroke is a significant global health concern characterized by the abrupt disruption of cerebral blood flow, leading to neurological impairment. Accurate and timely diagnosis—enabled by imaging modalities such as computed tomography (CT) and magnetic resonance imaging (MRI)—is essential for differentiating stroke types and [...] Read more.
Stroke is a significant global health concern characterized by the abrupt disruption of cerebral blood flow, leading to neurological impairment. Accurate and timely diagnosis—enabled by imaging modalities such as computed tomography (CT) and magnetic resonance imaging (MRI)—is essential for differentiating stroke types and initiating interventions like thrombolysis, thrombectomy, or surgical management. In parallel, recent advancements in wearable technology, particularly smart clothing, offer new opportunities for stroke prevention, real-time monitoring, and rehabilitation. These garments integrate various sensors, including electrocardiogram (ECG) electrodes, electroencephalography (EEG) caps, electromyography (EMG) sensors, and motion or pressure sensors, to continuously track physiological and functional parameters. For example, ECG shirts monitor cardiac rhythm to detect atrial fibrillation, smart socks assess gait asymmetry for early mobility decline, and EEG caps provide data on neurocognitive recovery during rehabilitation. These technologies support personalized care across the stroke continuum, from early risk detection and acute event monitoring to long-term recovery. Integration with AI-driven analytics further enhances diagnostic accuracy and therapy optimization. This narrative review explores the application of smart clothing in conjunction with traditional imaging to improve stroke management and patient outcomes through a more proactive, connected, and patient-centered approach. Full article
(This article belongs to the Special Issue Novel Methods and Devices for Monitoring and Diagnosing in Critical Care)
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14 pages, 1517 KiB  
Article
Adverse Pathology After Radical Prostatectomy in Low- and Intermediate-Risk Prostate Cancer: A Propensity Score-Matched Analysis of Long-Term Health-Related Quality of Life
by Michael Chaloupka, Alexander Buchner, Marc Kidess, Benedikt Ebner, Yannic Volz, Nikolaos Pyrgidis, Stephan Timo Ledderose, Dirk-André Clevert, Julian Marcon, Philipp Weinhold, Christian G. Stief and Maria Apfelbeck
Diagnostics 2025, 15(15), 1969; https://doi.org/10.3390/diagnostics15151969 - 6 Aug 2025
Viewed by 453
Abstract
Background and Objective: Adverse pathology to high-risk prostate cancer (PCa) after radical prostatectomy (upgrading) poses a threat to risk stratification and treatment planning. The impact on sexual function, urinary continence, and health-related quality of life (HRQOL) remains unclear. Methods: From 2004 [...] Read more.
Background and Objective: Adverse pathology to high-risk prostate cancer (PCa) after radical prostatectomy (upgrading) poses a threat to risk stratification and treatment planning. The impact on sexual function, urinary continence, and health-related quality of life (HRQOL) remains unclear. Methods: From 2004 to 2024, 4189 patients with preop low-/intermediate-risk PCa (Gleason score 6 or 7a, PSA ≤ 20 ng/mL) underwent radical prostatectomy at our department and were analyzed. Primary endpoint was HRQOL, erectile function, and urinary continence. Secondary endpoint was rate of salvage therapies and biochemical-free survival. Propensity score matching was performed using “operative time”, “robot-assisted surgery”, “blood loss”, “nerve-sparing surgery”, “age”, and “BMI” to represent comparable surgical approach. Median follow-up was 39 months (Interquartile-range (IQR) 15–60). Key Findings and Limitations: Patients who were upgraded to high-risk PCa showed a higher rate of postoperative radiotherapy and androgen-deprivation therapy compared to patients who were not upgraded (21% vs. 7%, p < 0.001; 9% vs. 3%, p = 0.002). Five-year biochemical recurrence-free survival was 68% in the upgrading group vs. 84% in the no-upgrading group (p < 0.001). We saw no difference in patient-reported HRQOL, urinary continence, or erectile function. Multivariable analysis showed that postoperative upgrading was a significant risk for not achieving good overall HRQOL (OR: 0.77, 95% CI: 0.61–0.97, p = 0.028) during the follow-up. Conclusions and Clinical Implications: Although postoperative upgrading to high-risk PCa leads to worse oncologic outcomes and higher salvage therapy rates, this study indicates that its impact on health-related quality of life is minimal and should not deter a cautious approach to radical prostatectomy. Full article
(This article belongs to the Section Clinical Diagnosis and Prognosis)
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14 pages, 1848 KiB  
Article
RadiomiX for Radiomics Analysis: Automated Approaches to Overcome Challenges in Replicability
by Harel Kotler, Luca Bergamin, Fabio Aiolli, Elena Scagliori, Angela Grassi, Giulia Pasello, Alessandra Ferro, Francesca Caumo and Gisella Gennaro
Diagnostics 2025, 15(15), 1968; https://doi.org/10.3390/diagnostics15151968 - 5 Aug 2025
Viewed by 431
Abstract
Background/Objectives: To simplify the decision-making process in radiomics by employing RadiomiX, an algorithm designed to automatically identify the best model combination and validate them across multiple environments was developed, thus enhancing the reliability of results. Methods: RadiomiX systematically tests classifier and feature [...] Read more.
Background/Objectives: To simplify the decision-making process in radiomics by employing RadiomiX, an algorithm designed to automatically identify the best model combination and validate them across multiple environments was developed, thus enhancing the reliability of results. Methods: RadiomiX systematically tests classifier and feature selection method combinations known to be suitable for radiomic datasets to determine the best-performing configuration across multiple train–test splits and K-fold cross-validation. The framework was validated on four public retrospective radiomics datasets including lung nodules, metastatic breast cancer, and hepatic encephalopathy using CT, PET/CT, and MRI modalities. Model performance was assessed using the area under the receiver-operating-characteristic curve (AUC) and accuracy metrics. Results: RadiomiX achieved superior performance across four datasets: LLN (AUC = 0.850 and accuracy = 0.785), SLN (AUC = 0.845 and accuracy = 0.754), MBC (AUC = 0.889 and accuracy = 0.833), and CHE (AUC = 0.837 and accuracy = 0.730), significantly outperforming original published models (p < 0.001 for LLN/SLN and p = 0.023 for MBC accuracy). When original published models were re-evaluated using ten-fold cross-validation, their performance decreased substantially: LLN (AUC = 0.783 and accuracy = 0.731), SLN (AUC = 0.748 and accuracy = 0.714), MBC (AUC = 0.764 and accuracy = 0.711), and CHE (AUC = 0.755 and accuracy = 0.677), further highlighting RadiomiX’s methodological advantages. Conclusions: Systematically testing model combinations using RadiomiX has led to significant improvements in performance. This emphasizes the potential of automated ML as a step towards better-performing and more reliable radiomic models. Full article
(This article belongs to the Section Machine Learning and Artificial Intelligence in Diagnostics)
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10 pages, 1093 KiB  
Article
Diagnostic Accuracy of Shear Wave Elastography Versus Ultrasound in Plantar Fasciitis Among Patients with and Without Ankylosing Spondylitis
by Mahyar Daskareh, Mahsa Mehdipour Dalivand, Saeid Esmaeilian, Aseme Pourrajabi, Seyed Ali Moshtaghioon, Elham Rahmanipour, Ahmadreza Jamshidi, Majid Alikhani and Mohammad Ghorbani
Diagnostics 2025, 15(15), 1967; https://doi.org/10.3390/diagnostics15151967 - 5 Aug 2025
Viewed by 346
Abstract
Background: Plantar fasciitis (PF) is a common enthesopathy in patients with ankylosing spondylitis (AS). Shear wave elastography (SWE) and the Belgrade ultrasound enthesitis score (BUSES) may detect PF, but their comparative diagnostic performance is unclear. Objective: To compare SWE with the BUSES for [...] Read more.
Background: Plantar fasciitis (PF) is a common enthesopathy in patients with ankylosing spondylitis (AS). Shear wave elastography (SWE) and the Belgrade ultrasound enthesitis score (BUSES) may detect PF, but their comparative diagnostic performance is unclear. Objective: To compare SWE with the BUSES for identifying PF in individuals with and without AS. Methods: In this cross-sectional study, 96 participants were stratified into AS and non-AS populations, each further divided based on the presence or absence of clinical PF. Demographic data, the American Orthopedic Foot and Ankle Society Score (AOFAS), and the BASDAI score were recorded. All subjects underwent grayscale ultrasonography, the BUSES scoring, and SWE assessment of the plantar fascia. Logistic regression models were constructed for each population, controlling for age, body mass index (BMI), and fascia–skin distance. ROC curve analyses were performed to evaluate diagnostic accuracy. Results: In both AS and non-AS groups, SWE and the BUSES were significant predictors of PF (p < 0.05). SWE demonstrated slightly higher diagnostic accuracy, with area under the curve (AUC) values of 0.845 (AS) and 0.837 (non-AS), compared to the BUSES with AUCs of 0.785 and 0.831, respectively. SWE also showed stronger adjusted odds ratios in regression models. The interobserver agreement was good to excellent for both modalities. Conclusions: Both SWE and the BUSES are effective for PF detection, with SWE offering marginally superior diagnostic performance, particularly in AS patients. SWE may enhance the early identification of biomechanical changes in the plantar fascia. Full article
(This article belongs to the Special Issue Ultrasound Elastography in Musculoskeletal Disorders: From Bench to Bedside)
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27 pages, 11710 KiB  
Article
Assessing ResNeXt and RegNet Models for Diabetic Retinopathy Classification: A Comprehensive Comparative Study
by Samara Acosta-Jiménez, Valeria Maeda-Gutiérrez, Carlos E. Galván-Tejada, Miguel M. Mendoza-Mendoza, Luis C. Reveles-Gómez, José M. Celaya-Padilla, Jorge I. Galván-Tejada and Antonio García-Domínguez
Diagnostics 2025, 15(15), 1966; https://doi.org/10.3390/diagnostics15151966 - 5 Aug 2025
Viewed by 461
Abstract
Background/Objectives: Diabetic retinopathy is a leading cause of vision impairment worldwide, and the development of reliable automated classification systems is crucial for early diagnosis and clinical decision-making. This study presents a comprehensive comparative evaluation of two state-of-the-art deep learning families for the task [...] Read more.
Background/Objectives: Diabetic retinopathy is a leading cause of vision impairment worldwide, and the development of reliable automated classification systems is crucial for early diagnosis and clinical decision-making. This study presents a comprehensive comparative evaluation of two state-of-the-art deep learning families for the task of classifying diabetic retinopathy using retinal fundus images. Methods: The models were trained and tested in both binary and multi-class settings. The experimental design involved partitioning the data into training (70%), validation (20%), and testing (10%) sets. Model performance was assessed using standard metrics, including precision, sensitivity, specificity, F1-score, and the area under the receiver operating characteristic curve. Results: In binary classification, the ResNeXt101-64x4d model and RegNetY32GT model demonstrated outstanding performance, each achieving high sensitivity and precision. For multi-class classification, ResNeXt101-32x8d exhibited strong performance in early stages, while RegNetY16GT showed better balance across all stages, particularly in advanced diabetic retinopathy cases. To enhance transparency, SHapley Additive exPlanations were employed to visualize the pixel-level contributions for each model’s predictions. Conclusions: The findings suggest that while ResNeXt models are effective in detecting early signs, RegNet models offer more consistent performance in distinguishing between multiple stages of diabetic retinopathy severity. This dual approach combining quantitative evaluation and model interpretability supports the development of more robust and clinically trustworthy decision support systems for diabetic retinopathy screening. Full article
(This article belongs to the Special Issue Artificial Intelligence and Deep Learning in Clinical Classification and Prediction)
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16 pages, 390 KiB  
Review
The Role of Quantitative EEG in the Diagnosis of Alzheimer’s Disease
by Vasileios Papaliagkas
Diagnostics 2025, 15(15), 1965; https://doi.org/10.3390/diagnostics15151965 - 5 Aug 2025
Viewed by 1463
Abstract
Alzheimer’s disease is the most prevalent neurodegenerative disorder leading to progressive cognitive decline and functional impairment. Although advanced neuroimaging and cerebrospinal fluid biomarkers have improved early detection, their high costs, invasiveness, and limited accessibility restrict universal screening. Quantitative electroencephalography (qEEG) offers a non-invasive [...] Read more.
Alzheimer’s disease is the most prevalent neurodegenerative disorder leading to progressive cognitive decline and functional impairment. Although advanced neuroimaging and cerebrospinal fluid biomarkers have improved early detection, their high costs, invasiveness, and limited accessibility restrict universal screening. Quantitative electroencephalography (qEEG) offers a non-invasive and cost-effective alternative for assessing neurophysiological changes associated with AD. This review critically evaluates current evidence on EEG biomarkers, including spectral, connectivity, and complexity measures, discussing their pathophysiological basis, diagnostic accuracy, and clinical utility in AD. Limitations and future perspectives, especially in developing standardized protocols and integrating machine learning techniques, are also addressed. Full article
(This article belongs to the Special Issue EEG Analysis in Diagnostics)
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12 pages, 1549 KiB  
Article
Differentiating Main-Duct IPMN from Chronic Pancreatitis Using Next-Generation Sequencing of Main Pancreatic Duct Fluid: A Pilot Study
by Daniel Schmitz, Stefan Prax, Martin Kliment, Felix Gocke, Daniel Kazdal, Michael Allgäuer, Roland Penzel, Martina Kirchner, Olaf Neumann, Holger Sültmann, Jan Budczies, Peter Schirmacher, Frank Bergmann, Jörg-Peter Ritz, Raoul Hinze, Felix Grassmann, Jochen Rudi, Albrecht Stenzinger and Anna-Lena Volckmar
Diagnostics 2025, 15(15), 1964; https://doi.org/10.3390/diagnostics15151964 - 5 Aug 2025
Viewed by 359
Abstract
Background: A dilated main pancreatic duct (MPD) ≥ 5 mm can be observed in main-duct IPMNs (MD-IPMN) and chronic pancreatitis (CP); however, distinguishing between the two differently treated diseases can be difficult. Cell-free (cf) DNA in MPD fluid obtained by EUS-guided FNA [...] Read more.
Background: A dilated main pancreatic duct (MPD) ≥ 5 mm can be observed in main-duct IPMNs (MD-IPMN) and chronic pancreatitis (CP); however, distinguishing between the two differently treated diseases can be difficult. Cell-free (cf) DNA in MPD fluid obtained by EUS-guided FNA might help to distinguish MD-IPMN from CP. Methods: All patients with a dilated MPD ≥ 5 mm on EUS during the period of 1 June 2017 to 30 April 2024 were prospectively analysed in this single-centre study, with EUS-guided MPD fluid aspiration performed for suspected MD-IPMN or CP in patients who were suitable for surgery. Twenty-two known gastrointestinal cancer genes, including GNAS and KRAS, were analysed by deep targeted (dt) NGS. The results were correlated with resected tissue, biopsy, and long-term follow-up. Results: A total of 164 patients with a dilated MPD were identified, of which 30 (18.3%) underwent EUS-guided FNA, with 1 patient having a minor complication (3.3%). Twenty-two patients (mean MPD diameter of 12.4 (7–31) mm) with a definitive, mostly surgically confirmed diagnosis were included in the analysis. Only a fish-mouth papilla, which was present in 3 of 12 (25%) MD-IPMNs, could reliably differentiate between the two diseases, with history, symptoms, diffuse or segmental MPD dilation, presence of calcifications on imaging, cytology, and CEA in the ductal fluid failing to achieve differentiation. However, GNAS mutations were found exclusively in 11 of the 12 (91.6%) patients with MD-IPMN (p < 0.01), whereas KRAS mutations were identified in both diseases. Conclusions: GNAS testing by dtNGS in aspirated fluid from dilated MPD obtained by EUS-guided FNA may help differentiate MD-IPMN from CP for surgical resection. Full article
(This article belongs to the Special Issue Advances in Endoscopy)
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13 pages, 2232 KiB  
Article
Artificial Intelligence-Assisted Lung Perfusion Quantification from Spectral CT Iodine Map in Pulmonary Embolism
by Reza Piri, Parisa Seyedhosseini, Samir Jawad, Emilie Sonne-Holm, Camilla Stedstrup Mosgaard, Ekim Seven, Kristian Eskesen, Ole Peter Kristiansen, Søren Fanø, Mathias Greve Lindholm, Lia E. Bang, Jørn Carlsen, Anna Kalhauge, Lars Lönn, Jesper Kjærgaard and Peter Sommer Ulriksen
Diagnostics 2025, 15(15), 1963; https://doi.org/10.3390/diagnostics15151963 - 5 Aug 2025
Viewed by 391
Abstract
Introduction: This study evaluated the performance of automated dual-energy computed tomography (DECT)-based quantification of perfusion defects (PDs) in acute pulmonary embolism and examined its correlation with clinical parameters. Methods: We retrospectively analyzed data from 171 patients treated for moderate-to-severe acute pulmonary [...] Read more.
Introduction: This study evaluated the performance of automated dual-energy computed tomography (DECT)-based quantification of perfusion defects (PDs) in acute pulmonary embolism and examined its correlation with clinical parameters. Methods: We retrospectively analyzed data from 171 patients treated for moderate-to-severe acute pulmonary embolism, who underwent DECT imaging at two separate time points. PDs were quantified using a fully automated AI-based segmentation method that relied exclusively on iodine perfusion maps. This was compared with a semi-automatic clinician-guided segmentation, where radiologists manually adjusted thresholds to eliminate artifacts. Clinical variables including the Miller obstruction score, right-to-left ventricular diameter ratio, oxygen saturation, and patient-reported symptoms were also collected. Results: The semiautomatic method demonstrated stronger correlations with embolic burden (Miller score; r = 0.4, p < 0.001 at follow-up) and a negative correlation with oxygen saturation (r = −0.2, p = 0.04). In contrast, the fully automated AI-based quantification consistently produced lower PD values and demonstrated weaker associations with clinical parameters. Conclusions: Semiautomatic quantification of PDs currently provides superior accuracy and clinical relevance for evaluating lung PDs in acute pulmonary embolism. Future multimodal AI models that incorporate both anatomical and clinical data may further enhance diagnostic precision. Full article
(This article belongs to the Section Machine Learning and Artificial Intelligence in Diagnostics)
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10 pages, 1047 KiB  
Article
The Effect of Obesity and General Anaesthesia Mode on the Frontal QRS-T Angle During Laparoscopic Surgery
by Harun Tolga Duran, Bülent Meriç Çam, Ahmet Salih Tüzen, Muhammet Aydın Akdoğan and Suat Evirgen
Diagnostics 2025, 15(15), 1962; https://doi.org/10.3390/diagnostics15151962 - 5 Aug 2025
Viewed by 291
Abstract
Background/Objectives: Obesity is a major cause of repolarisation defects of the heart. The frontal QRS-T angle is a new parameter used for cardiac evaluation. This study aimed to evaluate the effects of a laparoscopic cholecystectomy and anaesthetic agents on the frontal QRS-T [...] Read more.
Background/Objectives: Obesity is a major cause of repolarisation defects of the heart. The frontal QRS-T angle is a new parameter used for cardiac evaluation. This study aimed to evaluate the effects of a laparoscopic cholecystectomy and anaesthetic agents on the frontal QRS-T angle in individuals with obesity. Methods: A total of 91 patients who underwent a laparoscopic cholecystectomy surgery were included in this study. The patients were divided into two groups according to body mass index (BMI) < 30 (n = 68) and ≥30 (n = 23). The frontal QRS-T angle (FQRST), QT interval (QT), corrected QT, and other electrocardiography (ECG) findings were recorded at different time points. Results: In the BMI ≥ 30 group, the frontal QRS-T angle and QT interval measured during the intraoperative period were statistically higher than those of the BMI < 30 group (p < 0.001, p < 0.001). Additionally, the frontal QRS-T angle value was statistically higher in all patients postoperatively compared with the preoperative and intraoperative periods (p < 0.001). Furthermore, there was a positive correlation between the BMI and the frontal QRS-T angle. Our study found that the QRS-T angle and the QT interval duration measured during surgery in the BMI ≥ 30 group who underwent a laparoscopic cholecystectomy were significantly higher than in the BMI < 30 group. Conclusions: We recommend close haemodynamic monitoring during and after surgery for patients with obesity undergoing a laparoscopic cholecystectomy. Full article
(This article belongs to the Section Clinical Diagnosis and Prognosis)
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20 pages, 2316 KiB  
Article
Detection of Dental Anomalies in Digital Panoramic Images Using YOLO: A Next Generation Approach Based on Single Stage Detection Models
by Uğur Şevik and Onur Mutlu
Diagnostics 2025, 15(15), 1961; https://doi.org/10.3390/diagnostics15151961 - 5 Aug 2025
Viewed by 528
Abstract
Background/Objectives: The diagnosis of pediatric dental conditions from panoramic radiographs is uniquely challenging due to the dynamic nature of the mixed dentition phase, which can lead to subjective and inconsistent interpretations. This study aims to develop and rigorously validate an advanced deep [...] Read more.
Background/Objectives: The diagnosis of pediatric dental conditions from panoramic radiographs is uniquely challenging due to the dynamic nature of the mixed dentition phase, which can lead to subjective and inconsistent interpretations. This study aims to develop and rigorously validate an advanced deep learning model to enhance diagnostic accuracy and efficiency in pediatric dentistry, providing an objective tool to support clinical decision-making. Methods: An initial comparative study of four state-of-the-art YOLO variants (YOLOv8, v9, v10, and v11) was conducted to identify the optimal architecture for detecting four common findings: Dental Caries, Deciduous Tooth, Root Canal Treatment, and Pulpotomy. A stringent two-tiered validation strategy was employed: a primary public dataset (n = 644 images) was used for training and model selection, while a completely independent external dataset (n = 150 images) was used for final testing. All annotations were validated by a dual-expert team comprising a board-certified pediatric dentist and an experienced oral and maxillofacial radiologist. Results: Based on its leading performance on the internal validation set, YOLOv11x was selected as the optimal model, achieving a mean Average Precision (mAP50) of 0.91. When evaluated on the independent external test set, the model demonstrated robust generalization, achieving an overall F1-Score of 0.81 and a mAP50 of 0.82. It yielded clinically valuable recall rates for therapeutic interventions (Root Canal Treatment: 88%; Pulpotomy: 86%) and other conditions (Deciduous Tooth: 84%; Dental Caries: 79%). Conclusions: Validated through a rigorous dual-dataset and dual-expert process, the YOLOv11x model demonstrates its potential as an accurate and reliable tool for automated detection in pediatric panoramic radiographs. This work suggests that such AI-driven systems can serve as valuable assistive tools for clinicians by supporting diagnostic workflows and contributing to the consistent detection of common dental findings in pediatric patients. Full article
(This article belongs to the Special Issue Artificial Intelligence in the Diagnostics of Dental Diseases, 2nd Edition)
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19 pages, 2363 KiB  
Article
Can Biomarkers Predict Kidney Function Recovery and Mortality in Patients with Critical COVID-19 and Acute Kidney Injury?
by Noemí Del Toro-Cisneros, José C. Páez-Franco, Miguel A. Martínez-Rojas, Isaac González-Soria, Juan Antonio Ortega-Trejo, Hilda Sánchez-Vidal, Norma A. Bobadilla, Alfredo Ulloa-Aguirre and Olynka Vega-Vega
Diagnostics 2025, 15(15), 1960; https://doi.org/10.3390/diagnostics15151960 - 5 Aug 2025
Viewed by 375
Abstract
Background/Objectives: COVID-19 is a systemic viral infection that may lead to serious complications including acute kidney injury that requires kidney replacement therapy. The primary aim of this study was to evaluate urinary SerpinA3 (uSerpinA3) excretion as a biomarker of kidney recovery at [...] Read more.
Background/Objectives: COVID-19 is a systemic viral infection that may lead to serious complications including acute kidney injury that requires kidney replacement therapy. The primary aim of this study was to evaluate urinary SerpinA3 (uSerpinA3) excretion as a biomarker of kidney recovery at 90 days, and the mortality in patients with critical COVID-19 and AKI requiring kidney replacement therapy (KRT). Methods: The study included patients with critical COVID-19 on invasive mechanical ventilation (IMV) requiring KRT. Blood and urine samples were obtained when KRT was initiated (day zero), and thereafter on days 1, 3, 7, and 14 post-replacement. uSerpinA3, kidney injury molecule-1 (uKIM-1), and neutrophil gelatinase-associated lipocalin (uNGAL) were measured in urine, and interleukin-6 (IL-6), interleukin-10 (IL-10), and tumor necrosis factor alpha (TNF-α) in peripheral blood. In addition, metabolomics in sample days zero and 3, and in the survivors on sample day 90 was performed by employing gas chromatography coupled with mass spectrometry. Results: A total of 60 patients were recruited, of whom 29 (48%) survived hospitalization and recovered kidney function by day 90. In the survivors, 79% presented complete recovery (CRR) and the remaining (21%) recovered partially (PRR). In terms of uSerpinA3, levels on days 7 and 14 predicted CRR, with AUC values of 0.68 (p = 0.041) and 0.71 (p = 0.030), respectively, as well as mortality, with AUC values of 0.75 (p = 0.007) and 0.76 (p = 0.015), respectively. Among the other biomarkers, the excretion of uKIM-1 on day zero of KRT had a superior performance as a CRR predictor [(AUC, 0.71 (p = 0.017)], and as a mortality predictor [AUC, 0.68 (p = 0.028)]. In the metabolomics analysis, we identified four distinct profiles; the metabolite that maintained statistical significance in predicting mortality was p-cresol glucuronide. Conclusions: This study strongly suggests that uSerpinA3 and uKIM-1 can predict CRR and mortality in patients with critical COVID-19 and AKI requiring KRT. Metabolic analysis appears promising for identifying affected pathways and their clinical impact in this population. Full article
(This article belongs to the Special Issue Acute Kidney Injury and Chronic Kidney Disease: From Pathogenesis to Diagnostics)
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12 pages, 472 KiB  
Communication
LAMPOX: A Portable and Rapid Molecular Diagnostic Assay for the Epidemic Clade IIb Mpox Virus Detection
by Anna Rosa Garbuglia, Mallory Draye, Silvia Pauciullo, Daniele Lapa, Eliana Specchiarello, Florence Nazé and Pascal Mertens
Diagnostics 2025, 15(15), 1959; https://doi.org/10.3390/diagnostics15151959 - 4 Aug 2025
Viewed by 436
Abstract
The global spread of Mpox virus (MPXV) underscores the urgent need for rapid, field-deployable diagnostic tools, especially in low-resource settings. We evaluated a loop-mediated isothermal amplification (LAMP) assay, termed LAMPOX, developed by Coris BioConcept. The assay was tested in three formats—two liquid versions [...] Read more.
The global spread of Mpox virus (MPXV) underscores the urgent need for rapid, field-deployable diagnostic tools, especially in low-resource settings. We evaluated a loop-mediated isothermal amplification (LAMP) assay, termed LAMPOX, developed by Coris BioConcept. The assay was tested in three formats—two liquid versions and a dried, ready-to-use version—targeting only the ORF F3L (Liquid V1) or both the ORF F3L and N4R (Liquid V2 and dried) genomic regions. Analytical sensitivity and specificity were assessed using 60 clinical samples from confirmed MPXV-positive patients. Sensitivity on clinical samples was 81.7% for Liquid V1 and 88.3% for Liquid V2. The dried LAMPOX assay demonstrated a sensitivity of 88.3% and a specificity of 100% in a panel of 112 negative controls, with most positive samples detected in under 7 min. Additionally, a simplified sample lysis protocol was developed to facilitate point-of-care use. While this method showed slightly reduced sensitivity compared to standard DNA extraction, it proved effective for samples with higher viral loads. The dried format offers key advantages, including ambient-temperature stability and minimal equipment needs, making it suitable for point-of-care testing. These findings support LAMPOX as a promising tool for rapid MPXV detection during outbreaks, especially in resource-limited settings where traditional PCR is impractical. Full article
(This article belongs to the Special Issue Diagnostics in Focus: Accelerating Access for Priority Diseases in Africa)
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20 pages, 4576 KiB  
Article
Enhanced HoVerNet Optimization for Precise Nuclei Segmentation in Diffuse Large B-Cell Lymphoma
by Gei Ki Tang, Chee Chin Lim, Faezahtul Arbaeyah Hussain, Qi Wei Oung, Aidy Irman Yajid, Sumayyah Mohammad Azmi and Yen Fook Chong
Diagnostics 2025, 15(15), 1958; https://doi.org/10.3390/diagnostics15151958 - 4 Aug 2025
Viewed by 398
Abstract
Background/Objectives: Diffuse Large B-Cell Lymphoma (DLBCL) is the most common subtype of non-Hodgkin lymphoma and demands precise segmentation and classification of nuclei for effective diagnosis and disease severity assessment. This study aims to evaluate the performance of HoVerNet, a deep learning model, [...] Read more.
Background/Objectives: Diffuse Large B-Cell Lymphoma (DLBCL) is the most common subtype of non-Hodgkin lymphoma and demands precise segmentation and classification of nuclei for effective diagnosis and disease severity assessment. This study aims to evaluate the performance of HoVerNet, a deep learning model, for nuclei segmentation and classification in CMYC-stained whole slide images and to assess its integration into a user-friendly diagnostic tool. Methods: A dataset of 122 CMYC-stained whole slide images (WSIs) was used. Pre-processing steps, including stain normalization and patch extraction, were applied to improve input consistency. HoVerNet, a multi-branch neural network, was used for both nuclei segmentation and classification, particularly focusing on its ability to manage overlapping nuclei and complex morphological variations. Model performance was validated using metrics such as accuracy, precision, recall, and F1 score. Additionally, a graphic user interface (GUI) was developed to incorporate automated segmentation, cell counting, and severity assessment functionalities. Results: HoVerNet achieved a validation accuracy of 82.5%, with a precision of 85.3%, recall of 82.6%, and an F1 score of 83.9%. The model showed powerful performance in differentiating overlapping and morphologically complex nuclei. The developed GUI enabled real-time visualization and diagnostic support, enhancing the efficiency and usability of DLBCL histopathological analysis. Conclusions: HoVerNet, combined with an integrated GUI, presents a promising approach for streamlining DLBCL diagnostics through accurate segmentation and real-time visualization. Future work will focus on incorporating Vision Transformers and additional staining protocols to improve generalizability and clinical utility. Full article
(This article belongs to the Special Issue Artificial Intelligence-Driven Radiomics in Medical Diagnosis)
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7 pages, 1853 KiB  
Interesting Images
Mucinous Carcinoma, Mucinous Borderline Tumor and Pseudomyxoma Ovarii in a Cystic Teratoma: A Histological Conundrum
by Cinzia Giacometti, Mariateresa Mirandola, Camillo Aliberti, Filippo Molinari, Lisa Marcolini, Daniele Mautone and Guido Martignoni
Diagnostics 2025, 15(15), 1957; https://doi.org/10.3390/diagnostics15151957 - 4 Aug 2025
Viewed by 408
Abstract
Mature teratomas account for approximately 20% of all ovarian tumors identified in pathological studies. Benign or malignant somatic neoplasms developing within teratomas can arise from any tissue in up to 2% of mature cystic teratomas, including low-grade malignant mucinous neoplasms. This report presents [...] Read more.
Mature teratomas account for approximately 20% of all ovarian tumors identified in pathological studies. Benign or malignant somatic neoplasms developing within teratomas can arise from any tissue in up to 2% of mature cystic teratomas, including low-grade malignant mucinous neoplasms. This report presents the case of a 34-year-old woman with no previous gynecological or general health issues, who was admitted to our Hospital after an asymptomatic pelvic mass was detected during a routine exam. A transvaginal ultrasound revealed a unilateral pelvic mass in the left adnexal region, measuring 8 cm. The CT scan showed a cystic-appearing formation measuring nearly 12 cm, which indented the bladder dome. Final diagnosis indicated a mucinous carcinoma arising from a mucinous borderline lesion within the context of a mature ovarian teratoma. No other involvement or lymphadenopathies were detected on 18FDG-PET CT scan, and the patient is now well and free of recurrences. Full article
(This article belongs to the Special Issue Pathology and Diagnosis of Gynecologic Diseases, 3rd Edition)
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11 pages, 3222 KiB  
Article
Cervical Ectopic Pregnancies—Imaging and Endovascular Treatment
by Maciej Szmygin, Bartosz Kłobuszewski, Karolina Nieoczym, Weronika Dymara-Konopka, Sławomir Woźniak, Hanna Szmygin, Łukasz Światłowski and Krzysztof Pyra
Diagnostics 2025, 15(15), 1956; https://doi.org/10.3390/diagnostics15151956 - 4 Aug 2025
Viewed by 276
Abstract
Objective: Cervical pregnancy (CP) accounts for less than 1% of all ectopic pregnancies. The standard of management for CP is still under detailed investigation; however, among the known treatment methods, super-selective uterine artery embolization (UAE) and the use of methotrexate (MTX) have [...] Read more.
Objective: Cervical pregnancy (CP) accounts for less than 1% of all ectopic pregnancies. The standard of management for CP is still under detailed investigation; however, among the known treatment methods, super-selective uterine artery embolization (UAE) and the use of methotrexate (MTX) have emerged as effective and minimally invasive options in recent years. Our aim is to present our center’s experience and provide available evidence evaluating the efficacy of UAE in the treatment of CP. Materials and Methods: This single-center and retrospective study evaluated the procedural and clinical outcomes of patients with CP who underwent endovascular uterine embolization with MTX between 2017 and 2024. Both procedural and clinical efficacy and safety, as well as the rate of complications and long-term outcomes, were noted. Results: A total of nine patients were diagnosed with CP (imaging examination included transvaginal ultrasound and/or magnetic resonance imaging) and referred for endovascular treatment. The mean age of the patients was 36.7 years, and the mean gestational age on admission was 9 weeks. In all cases, selective catheterization of supplying vessels and subsequent embolization with a mixture of methotrexate and gel sponge was carried out. The technical success rate was 100% with no complications. Follow-up ultrasound confirmed the disappearance of the flow signal around the intracervical gestational sac in all cases. Conclusions: In conclusion, this retrospective study demonstrated the procedural and clinical safety and efficacy of uterine artery embolization in patients with cervical pregnancy. This is why endovascular therapy should be proposed to these individuals and be included in treatment options discussed during multidisciplinary boards. Full article
(This article belongs to the Special Issue Advancements in Interventional Radiology Techniques in Vascular and Extravascular Diseases)
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19 pages, 3739 KiB  
Article
Disturbances in Resting State Functional Connectivity in Schizophrenia: A Study of Hippocampal Subregions, the Parahippocampal Gyrus and Functional Brain Networks
by Raghad M. Makhdoum and Adnan A. S. Alahmadi
Diagnostics 2025, 15(15), 1955; https://doi.org/10.3390/diagnostics15151955 - 4 Aug 2025
Viewed by 350
Abstract
Background/Objectives: Schizophrenia exhibits symptoms linked to the hippocampus and parahippocampal gyrus. This includes the entorhinal cortex (ERC) and perirhinal cortex (PRC) as anterior parts, along with the posterior segment known as the parahippocampal cortex (PHC). However, recent research has detailed atlases based on [...] Read more.
Background/Objectives: Schizophrenia exhibits symptoms linked to the hippocampus and parahippocampal gyrus. This includes the entorhinal cortex (ERC) and perirhinal cortex (PRC) as anterior parts, along with the posterior segment known as the parahippocampal cortex (PHC). However, recent research has detailed atlases based on cytoarchitectural characteristics and the hippocampus divided into four subregions: cornu ammonis (CA), dentate gyrus (DG), subiculum (SUB), and hippocampal–amygdaloid transition (HATA). This study aimed to explore the functional connectivity (FC) changes between these hippocampal subregions and the parahippocampal gyrus structures (ERC, PRC, and PHC) as well as between hippocampal subregions and various functional brain networks in schizophrenia. Methods: In total, 50 individuals with schizophrenia and 50 matched healthy subjects were examined using resting state functional magnetic resonance imaging (rs-fMRI). Results: The results showed alterations characterized by increases and decreases in the strength of the positive connectivity between the parahippocampal gyrus structures and the four hippocampal subregions when comparing patients with schizophrenia with healthy subjects. Alterations were observed among the hippocampal subregions and functional brain networks, as well as the formation of new connections and absence of connections. Conclusions: There is strong evidence that the different subregions of the hippocampus have unique functions and their connectivity with the parahippocampal cortices and brain networks are affected by schizophrenia. Full article
(This article belongs to the Section Medical Imaging and Theranostics)
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23 pages, 470 KiB  
Systematic Review
Current Understanding and Future Research Direction for Estimating the Postmortem Interval: A Systematic Review
by Gabriela Strete, Andreea Sălcudean, Adina-Alexandra Cozma and Carmen-Corina Radu
Diagnostics 2025, 15(15), 1954; https://doi.org/10.3390/diagnostics15151954 - 4 Aug 2025
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Abstract
Background: Accurate estimation of the postmortem interval (PMI) is critical in forensic death investigations. Traditional signs of death—algor mortis, livor mortis, and rigor mortis—are generally reliable only within the first two to three days after death, with their accuracy decreasing as decomposition [...] Read more.
Background: Accurate estimation of the postmortem interval (PMI) is critical in forensic death investigations. Traditional signs of death—algor mortis, livor mortis, and rigor mortis—are generally reliable only within the first two to three days after death, with their accuracy decreasing as decomposition progresses. This paper presents a systematic review conducted in accordance with PRISMA guidelines, aiming to evaluate and compare current methods for estimating the PMI. Specifically, the study identifies both traditional and modern techniques, analyzes their advantages, limitations, and applicable timeframes, critically synthesizes the literature, and highlights the importance of combining multiple approaches to improve accuracy. Methods: A systematic search was conducted in the PubMed, Scopus, and Web of Science databases, following the PRISMA guidelines. The review included original articles and reviews that evaluated PMI estimation methods (through thanatological signs, entomology, microbial succession, molecular, imaging, and omics approaches). Extracted data included study design, methodology, PMI range, and accuracy information. Out of the 1245 identified records, 50 studies met the inclusion criteria for qualitative synthesis. Results: Emerging methods, such as molecular markers, microbial succession, omics technologies, and advanced imaging show improved accuracy across extended postmortem intervals. RNA degradation methods demonstrated higher accuracy within the first 72 h, while entomology and microbial analysis are more applicable during intermediate and late decomposition stages. Although no single method is universally reliable, combining traditional and modern approaches tailored to case-specific factors improves overall PMI estimation accuracy. Conclusions: This study supports the use of an integrative, multidisciplinary, and evidence-based approach to improve time-since-death estimation. Such a strategy enhances forensic outcomes by enabling more precise PMI estimates in complex or delayed cases, increasing legal reliability, and supporting court-admissible expert testimony based on validated, multi-method protocols. Full article
(This article belongs to the Section Pathology and Molecular Diagnostics)
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Review
Molar Pregnancy: Early Diagnosis, Clinical Management, and the Role of Referral Centers
by Antônio Braga, Lohayne Coutinho, Marcela Chagas, Juliana Pereira Soares, Gustavo Yano Callado, Raphael Alevato, Consuelo Lozoya, Sue Yazaki Sun, Edward Araujo Júnior and Jorge Rezende-Filho
Diagnostics 2025, 15(15), 1953; https://doi.org/10.3390/diagnostics15151953 - 4 Aug 2025
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Abstract
Molar pregnancy (MP) is a gestational disorder resulting from abnormal fertilization, leading to atypical trophoblastic proliferation and the formation of a complete or partial hydatidiform mole. This condition represents the most common form of gestational trophoblastic disease (GTD) and carries a significant risk [...] Read more.
Molar pregnancy (MP) is a gestational disorder resulting from abnormal fertilization, leading to atypical trophoblastic proliferation and the formation of a complete or partial hydatidiform mole. This condition represents the most common form of gestational trophoblastic disease (GTD) and carries a significant risk of progression to gestational trophoblastic neoplasia (GTN). Although rare in high-income countries, MP remains up to ten times more prevalent in low-income and developing countries, contributing to preventable maternal morbidity and mortality. This narrative review provides an updated, practical overview of the clinical presentation, diagnosis, treatment, and follow-up of MP. A key focus is the challenge of early diagnosis, particularly given the increasing frequency of first-trimester detection, where classical histopathological criteria may be subtle, leading to diagnostic errors. The review innovates by integrating advanced diagnostic methods—combining histopathology, immunohistochemistry using p57Kip2, Ki-67, and p53 markers, along with cytogenetic analysis—to improve diagnostic accuracy in early gestation. The central role of referral centers is also emphasized, not only in facilitating timely treatment and access to chemotherapy, but also in implementing standardized post-molar follow-up protocols that reduce progression to GTN and maternal mortality. By focusing on both advanced diagnostic strategies and the organization of care through referral centers, this review offers a comprehensive, practice-oriented perspective to optimize patient outcomes in GTD and address persistent care gaps in high-burden regions. Full article
(This article belongs to the Special Issue New Insights into the Diagnosis of Gynecological Diseases)
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