Diagnostics

29 pages, 1406 KiB

Open AccessArticle

Automated Lightweight Model for Asthma Detection Using Respiratory and Cough Sound Signals

by Shuting Xu, Ravinesh C. Deo, Oliver Faust, Prabal D. Barua, Jeffrey Soar and Rajendra Acharya

Diagnostics 2025, 15(9), 1155; https://doi.org/10.3390/diagnostics15091155 (registering DOI) - 1 May 2025

Abstract

Background and objective: Chronic respiratory diseases, such as asthma and COPD, pose significant challenges to human health and global healthcare systems. This pioneering study utilises AI analysis and modelling of cough and respiratory sound signals to classify and differentiate between asthma, COPD, [...] Read more.

Background and objective: Chronic respiratory diseases, such as asthma and COPD, pose significant challenges to human health and global healthcare systems. This pioneering study utilises AI analysis and modelling of cough and respiratory sound signals to classify and differentiate between asthma, COPD, and healthy subjects. The aim is to develop an AI-based diagnostic system capable of accurately distinguishing these conditions, thereby enhancing early detection and clinical management. Our study, therefore, presents the first AI system that leverages dual acoustic signals to enhance the diagnostic ACC of asthma using automated, lightweight deep learning models. Methods: To build an automated, lightweight model for asthma detection, tested separately with respiratory and cough sounds to assess their suitability for detecting asthma and COPD, the proposed AI models integrate the following ML algorithms: RF, SVM, DT, NN, and KNN, with an overall aim to demonstrate the efficacy of the proposed method for future clinical use. Model training and validation were performed using 5-fold cross-validation, wherein the dataset was randomly divided into five folds and the models were trained and tested iteratively to ensure robust performance. We evaluated the model outcomes with several performance metrics: ACC, precision, recall, F1 score, and area under the AUC. Additionally, a majority voting ensemble technique was employed to aggregate the predictions of the various classifiers for improved diagnostic reliability. We applied Gabor time–frequency transformation for feature extraction and NCA) for feature selection to optimise predictive accuracy. Independent comparative experiments were conducted, where cough-sound subsets were used to evaluate asthma detection capabilities, and respiratory-sound subsets were used to evaluate COPD detection capabilities, allowing for targeted model assessment. Results: The proposed ensemble approach, facilitated by a majority voting approach for model efficacy evaluation, achieved acceptable ACC values of 94.05% and 83.31% for differentiating between asthma and normal cases utilising separate respiratory sounds and cough sounds, respectively. The results highlight a substantial benefit in integrating multiple classifier models and sound modalities while demonstrating an unprecedented level of ACC and robustness for future diagnostic predictions of the disease. Conclusions: The present study sets a new benchmark in AI-based detection of respiratory diseases by integrating cough and respiratory sound signals for future diagnostics. The successful implementation of a dual-sound analysis approach promises advancements in the early detection and management of asthma and COPD. We conclude that the proposed model holds strong potential to transform asthma diagnostic practices and support clinicians in their respiratory healthcare practices. Full article

(This article belongs to the Special Issue Physiological Sound Processing for Medical Diagnostics: Innovations, Challenges, and Applications)

12 pages, 1137 KiB

Open AccessArticle

Evaluation of Adipokine Status and Leptin Receptor Gene Polymorphism in Patients with Severe Asthma

by Saule Maimysheva, Lyudmila Karazhanova, Andrey Orekhov, Assel Chinybayeva and Bolat Ashirov

Diagnostics 2025, 15(9), 1154; https://doi.org/10.3390/diagnostics15091154 (registering DOI) - 1 May 2025

Abstract

Background: Severe and difficult-to-control asthma occurs in 3–10% of patients in developed countries. The aim of our study was to investigate the association of the prognostic role of leptin and adiponectin, as well as the leptin receptor gene polymorphism Gln223Arg, in patients [...] Read more.

Background: Severe and difficult-to-control asthma occurs in 3–10% of patients in developed countries. The aim of our study was to investigate the association of the prognostic role of leptin and adiponectin, as well as the leptin receptor gene polymorphism Gln223Arg, in patients with difficult-to-control and severe asthma. Methods: The present study included 200 patients with asthma hospitalized in the Department of Pulmonology between January 2018 and December 2021. In all patients, in addition to routine clinical investigations, adiponectin, leptin and their ratio were analyzed, as well as levels of pro-inflammatory cytokines (IL-6, IL-8 and TNF-alpha). External respiratory function was also assessed. LEPR Gln223Arg single-nucleotide polymorphisms were genotyped by real-time PCR method. Results: Patients were randomized into two groups, depending on the severity of asthma: an uncontrolled asthma group and a controlled asthma group, according to the GINA criteria. Among patients with uncontrolled asthma, 101 subjects (74.3%) had metabolic syndrome (p < 0.001). There was an inverse association of the adiponectin/leptin ratio with the eosinophil count (B = −0.305, p < 0.001), IL-6 (B = −0.026, p < 0.001), IL-8 (B = −0.062, p < 0.001) and TNF-alpha (B = −0.047, p < 0.001) and a direct correlation with the level of FEV1 (B = 0.121, p < 0.001) and FVC (B = 0.104, p < 0.001). A probable association of homozygous A/A allele with increased risk of uncontrolled asthma was shown (p = 0.007). Conclusions: Leptin receptor polymorphism with A/A genotype may be associated with a higher probability of developing severe and difficult-to-control asthma. Full article

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

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21 pages, 683 KiB

Open AccessReview

Beyond X-Rays: Unveiling the Future of Dental Diagnosis with Dental Magnetic Resonance Imaging

by Anusha Vaddi, Pranav Parasher and Sonam Khurana

Diagnostics 2025, 15(9), 1153; https://doi.org/10.3390/diagnostics15091153 (registering DOI) - 1 May 2025

Abstract

Diagnostic imaging is fundamental in dentistry for disease detection, treatment planning, and outcome assessment. Traditional radiographic methods, such as periapical and panoramic radiographs, along with cone beam computed tomography (CBCT), utilize ionizing radiation and primarily focus on visualizing bony structures. Magnetic resonance imaging [...] Read more.

Diagnostic imaging is fundamental in dentistry for disease detection, treatment planning, and outcome assessment. Traditional radiographic methods, such as periapical and panoramic radiographs, along with cone beam computed tomography (CBCT), utilize ionizing radiation and primarily focus on visualizing bony structures. Magnetic resonance imaging (MRI) is emerging as a non-ionizing alternative that offers superior soft tissue contrast. However, standard MRI sequences face challenges visualizing mineralized tissues due to their short transverse relaxation times (T2), which results in rapid signal decay. Recent advancements exploring short T2 sequences, including Ultrashort Echo Time (UTE), Zero Echo Time (ZTE), and Sweep Imaging with Fourier Transformation (SWIFT), allow direct visualization of dental hard tissues. UTE captures signals from short T2 tissues using rapid pulse sequences, while ZTE employs encoding gradients before radiofrequency pulses to reduce signal loss. SWIFT enables near-simultaneous excitation and acquisition, improving ultrashort T2 detection. Additionally, customized intraoral and extraoral surface coils enhance the image resolution and signal-to-noise ratio (SNR), increasing MRI’s relevance in dentistry. Research highlights the potential of these short T2 sequences for early caries detection, pulp vitality assessment, and diagnosing jaw osseous pathology. While high-field MRI (3 T–7 T) improves resolution and increases susceptibility artifacts, low-field systems with specialized coils and short sequences offer promising alternatives. Despite obstacles such as cost and hardware constraints, ongoing studies refine protocols to enhance clinical applicability. Incorporating MRI in dentistry promises a safer, more comprehensive imaging methodology, potentially transforming diagnostics. This review emphasizes three types of short T2 sequences that have potential applications in the maxillofacial region. Full article

(This article belongs to the Special Issue Advances in Dental Imaging)

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19 pages, 691 KiB

Open AccessReview

Predictive Validity of Screening Tools and Role of Self-Esteem and Coping in Postpartum Depression Risk

by Nadica Motofelea, Alexandru Catalin Motofelea, Ionela Florica Tamasan, Teodora Hoinoiu, Jabri Tabrizi Madalina Ioana, Maja Vilibić, Antoniu Ionescu Cringu, Brenda Cristiana Bernad, Sorin Trinc and Dan-Bogdan Navolan

Diagnostics 2025, 15(9), 1152; https://doi.org/10.3390/diagnostics15091152 (registering DOI) - 30 Apr 2025

Abstract

Background/Objectives: Postpartum depression (PPD) is a prevalent mental health disorder affecting women after childbirth, with significant adverse effects on both maternal and infant outcomes. Early detection and intervention are critical to improving health trajectories. Material and Methods: This narrative review compares [...] Read more.

Background/Objectives: Postpartum depression (PPD) is a prevalent mental health disorder affecting women after childbirth, with significant adverse effects on both maternal and infant outcomes. Early detection and intervention are critical to improving health trajectories. Material and Methods: This narrative review compares the predictive validity of commonly used screening instruments for PPD, including the Edinburgh Postnatal Depression Scale (EPDS), Patient Health Questionnaire-9 (PHQ-9), and brief tools like PHQ-2 and PHQ-4. It also examines the role of self-esteem, assessed using the Rosenberg Self-Esteem Scale (RSES), and coping mechanisms, evaluated through the COPE Inventory, in moderating PPD risk. Results: Validation studies reveal variability in the performance of screening tools across different populations, emphasizing the need for contextual calibration. Low self-esteem and maladaptive coping strategies are consistently associated with higher PPD risk, with socioeconomic status (SES) further influencing these relationships. Interventions focusing on enhancing self-esteem and promoting adaptive coping, such as cognitive–behavioral therapy and psychoeducation, show promise in reducing PPD incidence. Conclusions: This review highlights gaps in existing research, particularly regarding screening during pregnancy, and calls for integrated predictive models incorporating psychosocial variables. Early, context-sensitive screening approaches are essential for effective PPD prevention and management. Full article

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

4 pages, 1015 KiB

Open AccessInteresting Images

Visualizing Aortic Inflammation by Diffusion-Weighted Whole-Body Imaging with Background Body Signal Suppression (DWIBS)

by Asuka Suzuki, Koji Hayashi, Mamiko Sato, Yuka Nakaya, Toyoaki Miura, Naoko Takaku, Toshiko Iwasaki and Yasutaka Kobayashi

Diagnostics 2025, 15(9), 1151; https://doi.org/10.3390/diagnostics15091151 (registering DOI) - 30 Apr 2025

Abstract

A 75-year-old man, with a history of descending thoracic aortic rupture and dissection treated with aortic stenting at 73 years old, was admitted for rehabilitation following recurrent cerebral ischemic attacks. Upon admission, blood tests revealed elevated inflammatory markers, including a C-reactive protein (CRP) [...] Read more.

A 75-year-old man, with a history of descending thoracic aortic rupture and dissection treated with aortic stenting at 73 years old, was admitted for rehabilitation following recurrent cerebral ischemic attacks. Upon admission, blood tests revealed elevated inflammatory markers, including a C-reactive protein (CRP) level of 10.75 mg/dL and a D-dimer level of 4.2 µg/mL, alongside microcytic anemia. Despite thorough evaluations using computed tomography (CT) and ultrasound, the origin of these abnormalities remained unidentified. Two months later, MRI using diffusion-weighted whole-body imaging with background body signal suppression (DWIBS) revealed hyperintensities in the thoracic aorta. He remained asymptomatic and progressed well during rehabilitation, prompting continued observation. However, three months after admission, he developed hemoptysis. Contrast-enhanced CT showed pneumonia, as well as enhanced lesions in the aortic wall, confirming aortic inflammation. Due to concerns about aortic stent ulceration, an emergency stent graft insertion extending to the superior mesenteric artery was performed. He recovered uneventfully and was discharged. DWIBS is an MRI-based tool that avoids exposure to radiation or contrast agents and is cost-effective. MRI using DWIBS demonstrated high signal accumulations in the aortic wall, indicative of inflammation. These findings suggest that DWIBS holds significant potential as a powerful imaging tool for detecting and assessing inflammation, particularly in the aorta. Full article

(This article belongs to the Special Issue New Trends in Cardiovascular Imaging)

26 pages, 714 KiB

Open AccessSystematic Review

Advanced Deep Learning Approaches in Detection Technologies for Comprehensive Breast Cancer Assessment Based on WSIs: A Systematic Literature Review

by Qiaoyi Xu, Afzan Adam, Azizi Abdullah and Nurkhairul Bariyah

Diagnostics 2025, 15(9), 1150; https://doi.org/10.3390/diagnostics15091150 (registering DOI) - 30 Apr 2025

Abstract

Background: Breast cancer is one of the leading causes of death among women worldwide. Accurate early detection of lymphocytes and molecular biomarkers is essential for improving diagnostic precision and patient prognosis. Whole slide images (WSIs) are central to digital pathology workflows in breast [...] Read more.

Background: Breast cancer is one of the leading causes of death among women worldwide. Accurate early detection of lymphocytes and molecular biomarkers is essential for improving diagnostic precision and patient prognosis. Whole slide images (WSIs) are central to digital pathology workflows in breast cancer assessment. However, applying deep learning techniques to WSIs presents persistent challenges, including variability in image quality, limited availability of high-quality annotations, poor model interpretability, high computational demands, and suboptimal processing efficiency. Methods: This systematic review, guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), examines deep learning-based detection methods for breast cancer published between 2020 and 2024. The analysis includes 39 peer-reviewed studies and 20 widely used WSI datasets. Results: To enhance clinical relevance and guide model development, this study introduces a five-dimensional evaluation framework covering accuracy and performance, robustness and generalization, interpretability, computational efficiency, and annotation quality. The framework facilitates a balanced and clinically aligned assessment of both established methods and recent innovations. Conclusions: This review offers a comprehensive analysis and proposes a practical roadmap for addressing core challenges in WSI-based breast cancer detection. It fills a critical gap in the literature and provides actionable guidance for researchers, clinicians, and developers seeking to optimize and translate WSI-based technologies into clinical workflows for comprehensive breast cancer assessment. Full article

(This article belongs to the Special Issue Artificial Intelligence for Health and Medicine)

21 pages, 764 KiB

Open AccessReview

Arrhythmic Risk Stratification in Patients with Arrhythmogenic Cardiomyopathy

by Marisa Varrenti, Eleonora Bonvicini, Leandro Fabrizio Milillo, Ilaria Garofani, Marco Carbonaro, Matteo Baroni, Lorenzo Gigli, Giulia Colombo, Federica Giordano, Raffaele Falco, Antonio Frontera, Roberto Menè, Alberto Preda, Sara Vargiu, Patrizio Mazzone and Fabrizio Guarracini

Diagnostics 2025, 15(9), 1149; https://doi.org/10.3390/diagnostics15091149 (registering DOI) - 30 Apr 2025

Abstract

Arrhythmogenic cardiomyopathy is a heart disease in which the heart muscle is replaced by scar tissue. This is the main substrate for the development of malignant ventricular arrhythmias. Sudden cardiac death is the most common manifestation and can often be the first sign [...] Read more.

Arrhythmogenic cardiomyopathy is a heart disease in which the heart muscle is replaced by scar tissue. This is the main substrate for the development of malignant ventricular arrhythmias. Sudden cardiac death is the most common manifestation and can often be the first sign of the disease, especially in young people. Correct stratification of arrhythmic risk is essential for the management of these patients but remains a challenge for the clinical cardiologist. In this context, the aim of our work was to review the literature and to analyse the most important studies and new developments with regard to the stratification of the risk of arrhythmia in patients suffering from arrhythmogenic cardiopathy. Full article

(This article belongs to the Special Issue The Cutting Edge of Cardiac Pacing, Electrophysiology and Diagnostic Techniques)

17 pages, 923 KiB

Open AccessArticle

Clinical Significance of Rotational Thromboelastometry (ROTEM) for Detection of Early Coagulopathy in Trauma Patients: A Retrospective Study

by Mohammad Asim, Ayman El-Menyar, Ruben Peralta, Suresh Arumugam, Bianca Wahlen, Khalid Ahmed, Naushad Ahmad Khan, Amani N. Alansari, Monira Mollazehi, Muhamed Ibnas, Ammar Al-Hassani, Ashok Parchani, Talat Chughtai, Sagar Galwankar, Hassan Al-Thani and Sandro Rizoli

Diagnostics 2025, 15(9), 1148; https://doi.org/10.3390/diagnostics15091148 (registering DOI) - 30 Apr 2025

Abstract

Background: We aimed to evaluate the clinical significance of abnormal rotational thromboelastometry (ROTEM) findings in trauma patients and investigate the relationships between FIBTEM-maximum clot firmness (MCF), fibrinogen concentration and patient outcomes. Methods: A retrospective cohort analysis was conducted on adult trauma [...] Read more.

Background: We aimed to evaluate the clinical significance of abnormal rotational thromboelastometry (ROTEM) findings in trauma patients and investigate the relationships between FIBTEM-maximum clot firmness (MCF), fibrinogen concentration and patient outcomes. Methods: A retrospective cohort analysis was conducted on adult trauma patients who underwent on-admission ROTEM testing between January 2020 and January 2021. Univariate analyses compared data based on injury severity, ROTEM findings (normal vs. abnormal), and initial fibrinogen concentration (normal vs. hypofibrinogenemia). ROC curve analysis was performed to determine the diagnostic performance of FIBTEM A10/MCF for its association with hypofibrinogenemia. Results: A total of 1488 patients were included in this study; the mean age was 36.4 ± 14.2 years and 92% were male. In total, 376 (25.3%) patients had ROTEM abnormalities. Severe injuries (ISS ≥ 16) were associated with a higher shock index, positive troponin T levels, standard coagulation abnormalities, hypofibrinogenemia, and abnormal ROTEM parameters (p < 0.05). These patients also had higher rates of massive transfusions and in-hospital mortality (p = 0.001). Coagulation alterations were significantly associated with higher injury severity score (ISS), shock index, head abbreviated injury score (AIS), hypofibrinogenemia, transfusion need, and mortality (p < 0.05). Hypofibrinogenemic patients were younger, sustained severe injuries, had higher shock indices and coagulation marker levels, required more intensive treatments, had longer hospital stays, and had higher mortality (p < 0.05). A significant positive correlation was found between plasma fibrinogen concentration and FIBTEM-MCF (r = 0.294; p = 0.001). Conclusions: Approximately one-fourth of the patients had early traumatic coagulopathy, as assessed by ROTEM. The FIBTEM A10/MCF may serves as a surrogate marker for plasma fibrinogen concentration. While prior studies have established the link between ROTEM and injury severity, our findings reinforce its relevance across varying trauma severity levels. However, prospective studies are warranted to validate its role within diverse trauma systems and evolving resuscitation protocols. Full article

(This article belongs to the Special Issue Advances in the Laboratory Diagnosis)

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12 pages, 1158 KiB

Open AccessArticle

Equation Built by Multiple Adaptive Regression Spline to Estimate Biological Age in Healthy Postmenopausal Women in Taiwan

by Chun-Feng Chang, Ta-Wei Chu, Chi-Hao Liu, Sheng-Tang Wu and Chung-Chi Yang

Diagnostics 2025, 15(9), 1147; https://doi.org/10.3390/diagnostics15091147 (registering DOI) - 30 Apr 2025

Abstract

Background: Biological age (BA) is a better representative of health status than chronological age (CA), as it uses different biological markers to quantify cellular and systemic change status. However, BA can be difficult to accurately estimate using current methods. This study uses multiple [...] Read more.

Background: Biological age (BA) is a better representative of health status than chronological age (CA), as it uses different biological markers to quantify cellular and systemic change status. However, BA can be difficult to accurately estimate using current methods. This study uses multiple adaptive regression spline (MARS) to build an equation to estimate BA among healthy postmenopausal women, thereby potentially improving the efficiency and accuracy of BA assessment. Methods: A total of 11,837 healthy women were enrolled (≥51 years old), excluding participants with metabolic syndrome variable values outside two standard deviations. MARS was applied, with the results compared to traditional multiple linear regression (MLR). The method with the smaller degree of estimation error was considered to be more accurate. The lower prediction errors yielded by MARS compared to the MLR method suggest that MARS performs better than MLR. Results: The equation derived from MARS is depicted. It could be noted that BA could be determined by marriage, systolic blood pressure (SBP), diastolic blood pressure (DBP), waist–hip ratio (WHR), alkaline phosphatase (ALP), lactate dehydrogenase (LDH), creatinine (Cr), carcinoembryonic antigen (CEA), bone mineral density (BMD), education level, and income. The MARS equation is generated. Conclusions: Using MARS, an equation was built to estimate biological age among healthy postmenopausal women in Taiwan. This equation could be used as a reference for calculating BA in general. Our equation showed that the most important factor was BMD, followed by WHR, Cr, marital status, education level, income, CEA, blood pressure, ALP, and LDH. Full article

(This article belongs to the Special Issue Application of Machine Learning in Disease Screening, Diagnosis and Prognosis)

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38 pages, 1484 KiB

Open AccessReview

Enhancing Radiologist Productivity with Artificial Intelligence in Magnetic Resonance Imaging (MRI): A Narrative Review

by Arun Nair, Wilson Ong, Aric Lee, Naomi Wenxin Leow, Andrew Makmur, Yong Han Ting, You Jun Lee, Shao Jin Ong, Jonathan Jiong Hao Tan, Naresh Kumar and James Thomas Patrick Decourcy Hallinan

Diagnostics 2025, 15(9), 1146; https://doi.org/10.3390/diagnostics15091146 (registering DOI) - 30 Apr 2025

Abstract

Artificial intelligence (AI) shows promise in streamlining MRI workflows by reducing radiologists’ workload and improving diagnostic accuracy. Despite MRI’s extensive clinical use, systematic evaluation of AI-driven productivity gains in MRI remains limited. This review addresses that gap by synthesizing evidence on how AI [...] Read more.

Artificial intelligence (AI) shows promise in streamlining MRI workflows by reducing radiologists’ workload and improving diagnostic accuracy. Despite MRI’s extensive clinical use, systematic evaluation of AI-driven productivity gains in MRI remains limited. This review addresses that gap by synthesizing evidence on how AI can shorten scanning and reading times, optimize worklist triage, and automate segmentation. On 15 November 2024, we searched PubMed, EMBASE, MEDLINE, Web of Science, Google Scholar, and Cochrane Library for English-language studies published between 2000 and 15 November 2024, focusing on AI applications in MRI. Additional searches of grey literature were conducted. After screening for relevance and full-text review, 67 studies met inclusion criteria. Extracted data included study design, AI techniques, and productivity-related outcomes such as time savings and diagnostic accuracy. The included studies were categorized into five themes: reducing scan times, automating segmentation, optimizing workflow, decreasing reading times, and general time-saving or workload reduction. Convolutional neural networks (CNNs), especially architectures like ResNet and U-Net, were commonly used for tasks ranging from segmentation to automated reporting. A few studies also explored machine learning-based automation software and, more recently, large language models. Although most demonstrated gains in efficiency and accuracy, limited external validation and dataset heterogeneity could reduce broader adoption. AI applications in MRI offer potential to enhance radiologist productivity, mainly through accelerated scans, automated segmentation, and streamlined workflows. Further research, including prospective validation and standardized metrics, is needed to enable safe, efficient, and equitable deployment of AI tools in clinical MRI practice. Full article

(This article belongs to the Special Issue Deep Learning in Medical Image Segmentation and Diagnosis)

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19 pages, 697 KiB

Open AccessArticle

Relationships Between Functional Impairment, Depressive Symptoms, and Ageing Attitudes in Older Adults

by Jessica Sawang, Katya Numbers, Ben C. P. Lam and Simone Reppermund

Diagnostics 2025, 15(9), 1145; https://doi.org/10.3390/diagnostics15091145 (registering DOI) - 30 Apr 2025

Abstract

Background/Objectives: Negative attitudes towards ageing, depressive symptoms, and impairment in instrumental activities of daily living (IADL) are associated with worse health outcomes in older adults, including increased risk of dementia. Little is known about the longitudinal impact of depressive symptoms and functional [...] Read more.

Background/Objectives: Negative attitudes towards ageing, depressive symptoms, and impairment in instrumental activities of daily living (IADL) are associated with worse health outcomes in older adults, including increased risk of dementia. Little is known about the longitudinal impact of depressive symptoms and functional impairment on ageing attitudes in older people. Identifying the relationships between these risk factors may help inform interventions targeting early dementia. The aim of this study was to determine whether depressive symptoms and functional impairment are associated with ageing attitudes over 6 years. Methods: Participants included 172 community-dwelling adults aged 76–96 years without dementia from the Sydney Memory and Ageing Study who were followed up over 6 years. Multiple linear regression models were used to examine prospective relationships between depressive symptoms, IADL (informant-reported or performance-based) and ageing attitudes. Results: After adjusting for potential confounding variables, more baseline depressive symptoms were associated with more negative ageing attitudes towards physical change (B = −0.10, 95%CI −0.18 to −0.02, p = 0.021) and psychological growth (B = −0.09, 95%CI −0.17 to −0.01, p = 0.037), and worse informant-reported IADL was associated with more negative ageing attitudes towards psychosocial change (B = −0.36, 95%CI −0.64 to −0.09, p = 0.010) over 6 years. Conclusions: The results highlight the importance of assessing and treating depressive symptoms and functional decline in older people, as they are significantly associated with negative attitudes about the ageing process, a known risk factor of worse health outcomes, including dementia. Full article

(This article belongs to the Special Issue Subjective Experiences of Decline and Dementia Risk: Cognitive, Functional, and Emotional Predictors of Cognitive Decline)

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11 pages, 1129 KiB

Open AccessArticle

Metabolic Syndrome and Hemorrhagic Stroke in Hispanic Elderly Patients with Cerebral Cavernous Malformations

by Alok K. Dwivedi, David Jang, Ofek Belkin, Justin Aickareth, Mellisa Renteria, Majd Hawwar, Jacob Croft, Ammar M. Kalas, Marc Zuckerman and Jun Zhang

Diagnostics 2025, 15(9), 1144; https://doi.org/10.3390/diagnostics15091144 (registering DOI) - 30 Apr 2025

Abstract

Background/Objectives: Cerebral cavernous malformations (CCMs) are neurological disorders that increase the risk of hemorrhagic stroke. The Mexican Hispanic population has a higher prevalence of both CCMs and metabolic syndrome (MetS), defined by the presence of three or more of the following: central obesity, [...] Read more.

Background/Objectives: Cerebral cavernous malformations (CCMs) are neurological disorders that increase the risk of hemorrhagic stroke. The Mexican Hispanic population has a higher prevalence of both CCMs and metabolic syndrome (MetS), defined by the presence of three or more of the following: central obesity, elevated triglycerides, low HDL, dyslipidemia, hypertension, or elevated fasting glucose. MetS is also associated with an increased risk of hemorrhagic stroke. However, the connection between MetS and hemorrhagic stroke in Hispanic CCM patients remains uncertain. Additionally, it is unclear if Hispanic CCM patients have different cardiometabolic profiles compared to controls. Methods: We analyzed a retrospective cohort of Mexican Hispanic adult CCM patients, including age- and gender-matched controls from the NHANES database. Fisher’s exact test or an unpaired Student’s t-test was used to compare risk factors between the CCM cohort and controls. Additionally, we conducted relative risk regression analysis to assess the adjusted association of MetS with hemorrhagic stroke. Results: The CCM cohort showed higher rates of epilepsy (24.6% vs. 1.6%, p < 0.001) and hemorrhagic stroke (36.6% vs. 3.6%, p < 0.001), but a lower prevalence of MetS (14% vs. 54.8%, p < 0.001) compared to age- and gender-matched Mexican Hispanic controls. The adjusted analysis revealed that among CCM patients in the older age group (age ≥ 50 years), MetS was associated with hemorrhagic stroke (RR = 2.38, 95%CI: 1.40–4.02, p = 0.001). Conclusions: This study reveals distinct features of CCMs in the Mexican Hispanic population, indicating a higher risk of hemorrhagic stroke and epilepsy compared to other ethnic groups. To mitigate the risk of hemorrhagic stroke, controlling blood pressure and managing comorbidities like metabolic syndrome (MetS) and epilepsy are essential, particularly in CCM patients aged 50 years and above. Full article

(This article belongs to the Special Issue Vascular Malformations: Diagnosis and Management)

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14 pages, 937 KiB

Open AccessArticle

Utility of Serum Biomarkers of Myocardial Fibrosis in High-Gradient Severe Aortic Stenosis: An Explorative Cardiovascular Magnetic Resonance Imaging-Based Study

by Megan R. Rajah, Erna Marais, Gerald J. Maarman, Emma Doubell, Anton F. Doubell and Philip G. Herbst

Diagnostics 2025, 15(9), 1143; https://doi.org/10.3390/diagnostics15091143 - 30 Apr 2025

Abstract

Background: Myocardial fibrosis in aortic stenosis (AS) is associated with a significant risk of poor clinical outcomes. Myocardial fibrosis can be evaluated using cardiovascular magnetic resonance (CMR) imaging and may be useful for risk-stratifying patients at high risk for poorer outcomes. A circulating [...] Read more.

Background: Myocardial fibrosis in aortic stenosis (AS) is associated with a significant risk of poor clinical outcomes. Myocardial fibrosis can be evaluated using cardiovascular magnetic resonance (CMR) imaging and may be useful for risk-stratifying patients at high risk for poorer outcomes. A circulating biomarker of fibrosis may be a cheaper, more accessible alternative to CMR in lower-to-middle-income countries. This study evaluated the correlation between serum biomarkers of myocardial fibrosis (TGF-β1, PICP, and PIIINP) with CMR markers of myocardial fibrosis (T1 mapping, extracellular volume fraction (ECV), and late gadolinium enhancement (LGE)). Methods: Twenty-one high-gradient (mean gradient ≥ 40 mmHg) severe AS (aortic valve area < 1.0 cm²) participants underwent T1 mapping and LGE imaging using CMR. Blood serum was collected for enzyme-linked immunosorbent assays of the listed biomarkers. Results: Serum TGF-β1 was associated significantly with the global T1 relaxation time on CMR (r = 0.46 with 95% CI 0.03 to 0.74, p = 0.04). In the high T1 time group (1056 vs. 1023 ms), trends toward elevated serum TGF-β1 concentration (13,044 vs. 10,341 pg/mL, p = 0.08) and ECV (26% vs. 24%, p = 0.07) were observed. The high T1 and trend towards elevated TGF-β1 concentration in this group tracked adverse LV remodeling and systolic dysfunction. There were no significant associations between PICP/PIIINP and T1 mapping or between the biomarkers and LGE quantity. Conclusions: Serum TGF-β1 is a potential surrogate for diffuse interstitial fibrosis measured by T1 mapping and ECV on CMR. Serum PICP and PIIINP may be less appropriate as surrogate markers of fibrosis in view of their temporal trends over the course of AS. Larger studies are needed to validate the utility of TGF-β1 as a marker of diffuse fibrosis and to evaluate the utility of serial PICP/PIIINP measurements to predict decompensation. Full article

(This article belongs to the Special Issue Cardiovascular Imaging)

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17 pages, 1071 KiB

Open AccessArticle

Ultrasound-Guided Versus Landmark-Based Extracorporeal Shock Wave Therapy for Calcific Shoulder Tendinopathy: An Interventional Clinical Trial

by Iosif Ilia, Caius Calin Miuta, Gyongyi Osser, Brigitte Osser, Csongor Toth, Manuela Simona Pop, Ramona Nicoleta Suciu, Veronica Huplea, Victor Niculescu and Laura Ioana Bondar

Diagnostics 2025, 15(9), 1142; https://doi.org/10.3390/diagnostics15091142 - 30 Apr 2025

Abstract

Background/Objectives: Calcific tendinopathy of the shoulder is a degenerative condition characterized by calcium deposits within the rotator cuff tendons, particularly the supraspinatus. It is a frequent cause of chronic shoulder pain and functional limitation, adversely affecting quality of life. While conservative treatments [...] Read more.

Background/Objectives: Calcific tendinopathy of the shoulder is a degenerative condition characterized by calcium deposits within the rotator cuff tendons, particularly the supraspinatus. It is a frequent cause of chronic shoulder pain and functional limitation, adversely affecting quality of life. While conservative treatments such as nonsteroidal anti-inflammatory drugs (NSAIDs), physiotherapy, and corticosteroid injections are commonly used, extracorporeal shock wave therapy (ESWT) has emerged as a promising non-invasive alternative. This interventional clinical trial compared the efficacy of ultrasound-guided versus landmark-based ESWT in treating calcific tendinopathy. Methods: Eighty-four patients with ultrasound-confirmed calcific tendinopathy were randomized into two groups. Group 1 received ultrasound-guided ESWT with real-time targeting of the deposit; Group 2 received landmark-based ESWT based on anatomical palpation. Both groups underwent three sessions (2000 impulses at 2.2 bars, energy level 5, 8 Hz). Clinical outcomes were assessed using the Constant–Murley score (CMS) at baseline, 12 weeks, and 6 months. Calcific deposit resorption was evaluated via ultrasound imaging. Results: The ultrasound-guided group showed a significant improvement in CMS from a median of 50 (range: 30–75) at baseline to 97 (52–100) at 6 months. The landmark-based group also improved, from 48 (32–74) to 79 (40–96). At 6 months post-treatment, 90.9% of patients in the ultrasound-guided group achieved successful outcomes (CMS ≥ 86), compared to 50% in the landmark-based group. Complete calcific resorption occurred in 65.9% of patients in Group 1, compared to 50% in Group 2; 15% of patients in Group 2 showed no resorption. Conclusions: Ultrasound-guided ESWT was significantly more effective than landmark-based ESWT in improving shoulder function, reducing pain, and promoting calcific deposit resorption. These findings support ultrasound guidance as a preferred approach for optimizing ESWT outcomes in patients with calcific tendinopathy of the shoulder. Full article

(This article belongs to the Special Issue Orthopedics and the Musculoskeletal System: Diagnosis, Prognosis, and Mechanisms)

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17 pages, 2082 KiB

Open AccessArticle

Comparing AI and Manual Segmentation of Prostate MRI: Towards AI-Driven 3D-Model-Guided Prostatectomy

by Thierry N. Boellaard, Roy van Erck, Sophia H. van der Graaf, Lisanne de Boer, Henk G. van der Poel, Laura S. Mertens, Pim J. van Leeuwen and Behdad Dashtbozorg

Diagnostics 2025, 15(9), 1141; https://doi.org/10.3390/diagnostics15091141 - 30 Apr 2025

Abstract

Background: Robot-assisted radical prostatectomy (RARP) is a common treatment option for prostate cancer. A 3D model for surgical guidance can improve surgical outcomes. Manual expert radiologist segmentation of the prostate and tumor in prostate MRI to create 3D models is labor-intensive and [...] Read more.

Background: Robot-assisted radical prostatectomy (RARP) is a common treatment option for prostate cancer. A 3D model for surgical guidance can improve surgical outcomes. Manual expert radiologist segmentation of the prostate and tumor in prostate MRI to create 3D models is labor-intensive and prone to inter-observer variability, highlighting the need for automated segmentation methods. Methods: This study evaluates the performance of the prostate and tumor segmentation using a commercially available AI tool without (fully automated) and with manual adjustment (AI-assisted) compared to manual segmentations on 120 patients, using several metrics, including Dice Coefficient and Hausdorff distance. Tumor detection rates were assessed with recall and precision. Results: For the prostate, both the fully automated AI model and AI-assisted model achieved a mean Dice score of 0.88, while AI-assisted had a lower Hausdorff distance (7.22 mm) compared to the fully automated (7.40 mm). For tumor segmentations, the Dice scores were 0.53 and 0.62, with Hausdorff distances of 9.53 mm and 6.62 mm obtained for fully automated AI and AI-assisted methods, respectively. The fully automated AI method had a recall of 0.74 and a precision of 0.76 in tumor detection, while the AI-assisted method achieved 0.95 recall and 0.94 precision. Fully automated segmentation required less than 1 min, while adjustments for the AI-assisted segmentation took an additional 81 s, and manual segmentation took approximately 15–30 min. Conclusions: The fully automated AI model shows promising results, offering high tumor detection rates and acceptable segmentation metrics. The AI-assisted strategy improved the relevant metrics with minimal additional time investment. Therefore, the AI-assisted segmentation method is promising for allowing 3D-model-guided surgery for all patients undergoing RARP. Full article

(This article belongs to the Special Issue Urologic Oncology: Biomarkers, Diagnosis, and Management)

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31 pages, 4669 KiB

Open AccessReview

Expanding Application of Optical Coherence Tomography Beyond the Clinic: A Narrative Review

by Tutut Nurjanah, Milin Patel, Jessica Mar, David Holden, Spencer C. Barrett and Nicolas A. Yannuzzi

Diagnostics 2025, 15(9), 1140; https://doi.org/10.3390/diagnostics15091140 - 29 Apr 2025

Abstract

Since its introduction, optical coherence tomography (OCT) has significantly progressed in addressing its limitations. By integrating artificial intelligence and multimodal imaging, OCT enhances both speed and image quality while reducing its size. OCT continues to advance, offering new possibilities beyond the in-office setting, [...] Read more.

Since its introduction, optical coherence tomography (OCT) has significantly progressed in addressing its limitations. By integrating artificial intelligence and multimodal imaging, OCT enhances both speed and image quality while reducing its size. OCT continues to advance, offering new possibilities beyond the in-office setting, including intraoperative applications. This review will explore the different types of home OCT and intraoperative OCT, as well as the uses of each device and their future potential in ophthalmology. Full article

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

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19 pages, 1406 KiB

Open AccessReview

Updates on the Prevalence, Quality of Life, and Management of Chronic Cough in Interstitial Lung Diseases

by Natalia V. Trushenko, Olga A. Suvorova, Anna E. Schmidt, Svetlana Y. Chikina, Iuliia A. Levina, Baina B. Lavginova and Sergey N. Avdeev

Diagnostics 2025, 15(9), 1139; https://doi.org/10.3390/diagnostics15091139 - 29 Apr 2025

Abstract

Background: Chronic cough is a common symptom in patients with interstitial lung diseases (ILDs), which significantly affects health-related quality of life (HRQoL). The prevalence of chronic cough varies from 30% to almost 90% in different ILDs, with the highest rate in patients with [...] Read more.

Background: Chronic cough is a common symptom in patients with interstitial lung diseases (ILDs), which significantly affects health-related quality of life (HRQoL). The prevalence of chronic cough varies from 30% to almost 90% in different ILDs, with the highest rate in patients with idiopathic pulmonary fibrosis. However, the pathophysiology of cough in ILDs remains poorly understood, with multiple proposed mechanisms contributing to its development. This knowledge gap complicates both clinical assessment and treatment, as current therapeutic strategies target general cough mechanisms rather than ILD-specific pathways. This review synthesizes existing data to clarify distinct cough mechanisms across ILD subtypes and identify opportunities for more targeted therapeutic strategies in this challenging patient population. Moreover, cough can be a clinical marker of disease severity and a predictor of ILD progression and transplant-free survival. Effective cough-specific therapeutic options that consider potential mechanisms, comorbidities, and individual effects on HRQoL are needed for cough associated with ILD. Therefore, the aim of this review was to analyze the prevalence, the impact on HRQoL, the pathophysiology, and the management of chronic cough in ILDs. Methods: We performed a comprehensive search in PubMed, MEDLINE, Embase, and the Cochrane Library. This review included randomized clinical trials, observational studies, systematic reviews, and meta-analyses in adults with chronic cough comparing ILD types. The following were excluded: commentaries, letters, case reports and case series, conference abstracts, and studies and publications lacking cough-specific outcomes. Results: Several approaches to reduce cough frequency and severity were described: antifibrotic agents, neuromodulators, opiates, inhaled local anesthetics, oxygen, speech therapy, and anti-reflux therapy. Some therapeutic approaches, such as oral corticosteroids and thalidomide, can cause significant side effects. Novel agents, such as P2X3 receptor antagonists, which are in phase III trials (COUGH-1/2), show promising results for refractory cough and may benefit ILD-related cough. Conclusions: Thus, a comprehensive assessment of cough is required for effective cough treatment in patients with ILDs considering possible mechanisms and individual impact on QoL. Full article

(This article belongs to the Special Issue Respiratory Diseases: Diagnosis and Management)

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11 pages, 2320 KiB

Open AccessArticle

Head and Neck Manifestations of Tularemia in Tyrol (Austria): A Case Series

by Roland Hartl, Matthias Santer, Wegene Borena, Charles Schmit, Hannes Thomas Fischer, Daniel Dejaco, Benedikt Gabriel Hofauer and Teresa Bernadette Steinbichler

Diagnostics 2025, 15(9), 1138; https://doi.org/10.3390/diagnostics15091138 - 29 Apr 2025

Abstract

Background: Tularemia is a rare zoonosis caused by the bacterium Francisella tularensis. In the head and neck region, it can manifest as cervical lymphadenopathy. Despite intensive therapy with various antibiotics, there is often a prolonged medical course. Methods: In this paper, all [...] Read more.

Background: Tularemia is a rare zoonosis caused by the bacterium Francisella tularensis. In the head and neck region, it can manifest as cervical lymphadenopathy. Despite intensive therapy with various antibiotics, there is often a prolonged medical course. Methods: In this paper, all documented cases of tularemia in the head and neck region at the Medical University of Innsbruck (Austria) are analyzed and the results compared with the literature. A retrospective analysis of all patients diagnosed with tularemia at the Department of Otorhinolaryngology-Head and Neck Surgery, Medical University of Innsbruck (Austria), was performed. Tularemia was diagnosed using a serologic agglutination antibody test. Results: Thirteen patients with tularemia presented at the Department of Otorhinolaryngology-Head and Neck Surgery, Medical University of Innsbruck (Austria), between 2010 and 2024. In 10 patients (10/13; 77%), animal contact or an insect bite was the suspected cause. The mean time from the onset of the first symptoms to diagnosis was 36 ± 15 days. The therapy took a mean of 5 ± 2 months until the last follow-up. On average, the patients were treated with 4 ± 1 different antibiotics. The median duration of hospital stay was 13 days (range: 0–36). In addition, a median of 9 (range: 2–20) further outpatient check-ups with several neck ultrasounds were carried out. Also, 10 patients (10/13; 77%) received a diagnostic and/or therapeutic surgical intervention. Conclusions: Tularemia is a rare infectious disease with a prolonged diagnostic and therapeutic course. Screening for tularemia should be performed in cases of cervical lymphadenopathy, especially if empirical antibiotic treatment has been ineffective or if there is a specific medical history. Full article

(This article belongs to the Special Issue Advances in Diagnosis and Treatment in Otolaryngology)

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13 pages, 1371 KiB

Open AccessArticle

Comparison of Automated Point-of-Care Gram Stainer (PoCGS^®) and Manual Staining

by Goh Ohji, Kenichiro Ohnuma, Kei Furui Ebisawa, Mari Kusuki, Shunkichi Ikegaki, Hiroaki Ozaki, Reiichi Ariizumi, Masakazu Nakajima and Makoto Taketani

Diagnostics 2025, 15(9), 1137; https://doi.org/10.3390/diagnostics15091137 - 29 Apr 2025

Abstract

Background/Objectives: Gram staining is an essential diagnostic technique used for the rapid identification of bacterial and fungal infections, playing a pivotal role in clinical decision-making, especially in point-of-care (POC) settings. Manual staining, while effective, is labor-intensive and prone to variability, relying heavily on [...] Read more.

Background/Objectives: Gram staining is an essential diagnostic technique used for the rapid identification of bacterial and fungal infections, playing a pivotal role in clinical decision-making, especially in point-of-care (POC) settings. Manual staining, while effective, is labor-intensive and prone to variability, relying heavily on the skill of laboratory personnel. Current automated Gram-staining systems are primarily designed for high-throughput laboratory environments, limiting their feasibility in decentralized healthcare settings such as emergency departments and rural clinics. This study aims to introduce and evaluate the Point-of-Care Gram Stainer (PoCGS^®), a compact, automated device engineered for single-slide processing, addressing challenges related to portability, standardization, and efficiency in POC applications. Methods: The PoCGS^® device was developed to emulate expert manual staining techniques through features such as methanol fixation and programmable reagent application. A comparative evaluation was performed using 40 urine samples, which included both clinical and artificial specimens. These samples were processed using PoCGS^®, manual staining by skilled experts, and manual staining by unskilled personnel. The outcomes were assessed based on microbial identification concordance, the staining uniformity, presence of artifacts, and agreement with the culture results. Statistical analyses, including agreement rates and quality scoring, were conducted to compare the performance of PoCGS^® against manual staining methods. Results: PoCGS^® achieved a 100% concordance rate with expert manual staining in terms of microbial identification, confirming its diagnostic accuracy. However, staining quality parameters such as the uniformity and presence of artifacts showed statistically significant differences when compared to skilled and unskilled personnel. Despite these limitations, PoCGS^® demonstrated a comparable performance regarding artifact reduction and agreement with the culture results, indicating its potential utility in POC environments. Challenges such as fixed processing times and limited adaptability to varying specimen characteristics were identified as areas for further improvement. Conclusions: The study findings suggest that PoCGS^® is a reliable and valuable tool for microbial identification in POC settings, with a performance comparable to skilled manual staining. Its compact design, automation, and ease of use make it particularly beneficial for resource-limited environments. Although improvements in staining uniformity and background clarity are required, PoCGS^® has the potential to standardize Gram staining protocols and improve diagnostic turnaround times. Future developments will focus on optimizing staining parameters and expanding its application to other clinical sample types, ensuring robustness and broader usability in diverse healthcare settings. Full article

(This article belongs to the Section Diagnostic Microbiology and Infectious Disease)

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