Diagnostics

18 pages, 2030 KiB

Open AccessArticle

Health Outcomes and Resource Consumption Analysis of Radioembolization with Y90 Glass Microspheres (TARE-Y90) Versus Transarterial Chemoembolization with Irinotecan (DEBIRI) in Patients with Liver Metastases from Colorectal Cancer in Spain

by Juan José Ciampi-Dopazo, Gonzalo Ruiz Villaverde, Juan José Espejo, Raúl García Marcos, Daniel Pérez Enguix, Serena Pisoni, José J. Martínez-Rodrigo, Pablo Navarro Vergara, Pedro Pardo Moreno and Antonio Rodríguez-Fernández

Diagnostics 2025, 15(7), 796; https://doi.org/10.3390/diagnostics15070796 (registering DOI) - 21 Mar 2025

Abstract

Background: The present study aims to investigate the superiority of TARE-Y90 in the treatment of liver metastases from colorectal cancer in comparison to DEBIRI and perform a parallel resource consumption study to demonstrate a possible favorable cost-effectiveness balance. Methods: The number [...] Read more.

Background: The present study aims to investigate the superiority of TARE-Y90 in the treatment of liver metastases from colorectal cancer in comparison to DEBIRI and perform a parallel resource consumption study to demonstrate a possible favorable cost-effectiveness balance. Methods: The number of subjects included in this study was 46 for TARE-Y90 and 56 in the DEBIRI group. The variables of interest in this study were collected for all selected subjects. Time-to-endpoint outcomes (overall survival, time to progression and time to extra-hepatic progression) were calculated by Kaplan–Meier analysis, reported as medians with 95% confidence intervals and compared between groups by log-rank testing. Values for median time-to-event and 95% confidence intervals were calculated using bootstrapping. Results: Categorization into overall response (OR) and no overall response (NOR) revealed a higher percentage of overall responses in the DEBIRI group (52%) compared to TARE-Y90 (24%). The numerical differences observed in certain response categories did not reach statistical significance, indicating a comparable overall response to treatment between the two cohorts based on the m-RECIST criteria. Median overall survival for the TARE-Y90 cohort was 11.3 (95% CI 10.9–18.6) months and 15.8 (95% CI 14.8–22.7) months for the DEBIRI cohort. Log-rank testing showed no statistically significant differences (p = 0.53). Median time to hepatic disease progression for the TARE-Y90 cohort was 3.5 (95% CI 3.4–8.1) months and 3.8 (95% CI 3.7–11.1) months for the DEBIRI cohort. Log-rank testing showed no statistically significant differences (p = 0.82). An important result of the resource utilization analysis is that TARE-Y90 patients had 1.33 treatments on average per patient, while DEBIRI patients had 3.16 treatments per patient. TARE-Y90 patients also needed fewer days of hospitalization than those in the DEBIRI group. The consequence is that the overall use of resources was higher for DEBIRI in comparison to TARE-Y90. Conclusions: Our analysis of the TARE-Y90 and DEBIRI treatments for CRC liver metastases contributes valuable insights into their comparative effectiveness, revealing no significant differences in radiological responses and overall survival. TARE-Y90 showed higher resource utilization, and its potential advantages in patient comfort and average resource consumption per patient warrant consideration. Full article

(This article belongs to the Special Issue Advances in Diagnostic and Interventional Radiology in Oncology)

► Show Figures

Figure 1

17 pages, 2888 KiB

Open AccessArticle

Investigating the Influence of Body Mass Index on Organs at Risk Doses for Adjuvant High-Dose-Rate Vaginal Cuff Brachytherapy in Patients with Early-Stage Endometrial Carcinoma: A Single-Center Experience

by Alexandra Timea Kirsch-Mangu, Diana Cristina Pop, Alexandru Țipcu, Andrei-Rareș Avasi, Claudia Ordeanu, Ovidiu Florin Coza and Alexandru Irimie

Diagnostics 2025, 15(7), 795; https://doi.org/10.3390/diagnostics15070795 (registering DOI) - 21 Mar 2025

Abstract

Background: Endometrial cancer is the most common gynecologic malignancy in developed countries, with obesity recognized as a major risk factor contributing to its incidence. The rising prevalence of obesity has significant implications for treatment planning, particularly in radiation therapy approaches such as [...] Read more.

Background: Endometrial cancer is the most common gynecologic malignancy in developed countries, with obesity recognized as a major risk factor contributing to its incidence. The rising prevalence of obesity has significant implications for treatment planning, particularly in radiation therapy approaches such as high-dose-rate (HDR) vaginal cuff brachytherapy, which is commonly used as adjuvant therapy in early-stage endometrial carcinoma. Body Mass Index (BMI) is a key factor in brachytherapy, as increased adiposity may alter dosimetric parameters, affecting radiation distribution and doses received by organs at risk (OARs). Understanding the correlation between BMI and radiation dose to OARs is essential for optimizing treatment planning and minimizing adverse effects. Identifying dose variations across different BMI categories may help refine patient-specific brachytherapy approaches to ensure both efficacy and safety. Objectives: This study aims to investigate the influence of Body Mass Index (BMI) on the doses received by organs at risk (OAR) during high-dose-rate (HDR) vaginal cuff brachytherapy in patients diagnosed with early-stage endometrial carcinoma. Understanding the relationship between BMI and OAR doses could enhance treatment planning and minimize complications. Methods: We collected brachytherapy data for 242 endometrial cancer patients treated with adjuvant HDR vaginal cuff brachytherapy. The patients were categorized based on their BMI into normal weight, overweight, and obese groups. Dosimetric data were collected for OARs, including the bladder, rectum, and sigmoid colon, and also for dose fractionation, D90%, and the active length of the brachytherapy cylinder. The analysis included comparing the doses received by each organ across different BMI categories using appropriate statistical methods. Results: Preliminary findings indicated a significant variation in the doses to OARs correlating with BMI classifications. Obese patients exhibited slightly higher mean doses to the rectum and sigmoid compared to those with a normal BMI. The statistical analysis demonstrated that as BMI increased, the dose to these organs at risk also tended to increase, suggesting a need for adjusted treatment planning strategies in this population. Conclusions: Obesity is a key concern in endometrial cancer patients, with higher BMI linked to slightly increased doses to the rectum and sigmoid, though treatment remained homogeneously delivered. Future prospective clinical studies are essential to explore the relationship between these dosimetric findings, specifically the correlation between higher BMI, increased doses to organs at risk (OARs), and late treatment-related toxicities. This research is needed to better understand the long-term implications and to optimize therapeutic outcomes. Full article

(This article belongs to the Special Issue Advances in Diagnosis of Gynecological Cancers)

► Show Figures

Figure 1

11 pages, 2813 KiB

Open AccessArticle

Perspectives on Reducing Barriers to the Adoption of Digital and Computational Pathology Technology by Clinical Labs

by Jeffrey L. Bessen, Melissa Alexander, Olivia Foroughi, Roderick Brathwaite, Emre Baser, Liam C. Lee, Omar Perez and Gary Gustavsen

Diagnostics 2025, 15(7), 794; https://doi.org/10.3390/diagnostics15070794 (registering DOI) - 21 Mar 2025

Abstract

Background/Objectives: Digital and computational pathology (DP/CP) tools have the potential to improve the efficiency and accuracy of the anatomic pathology workflow; however, current adoption among US hospital and reference labs remains low. Methods: To better understand the current utilization of DP/CP technology and [...] Read more.

Background/Objectives: Digital and computational pathology (DP/CP) tools have the potential to improve the efficiency and accuracy of the anatomic pathology workflow; however, current adoption among US hospital and reference labs remains low. Methods: To better understand the current utilization of DP/CP technology and barriers to widespread adoption, we conducted a survey among 63 anatomic pathologists and lab directors within the US health system. Results: The survey results indicated that current use cases for DP/CP involve streamlining traditional manual pathology and that labs would have substantial difficulty providing AI-guided image analysis if it were required by physicians today. Among potential catalysts for the broader adoption of DP/CP, pathologists identified clinical guidelines as a key resource for anatomic pathology, whose endorsement of DP/CP would be highly impactful for reducing current barriers. Conclusions: Expanded access to DP/CP may ultimately benefit all major stakeholders—patients, physicians, clinical laboratory professionals, care settings, and payers—and will therefore require collaboration across these groups. Full article

(This article belongs to the Special Issue Latest News in Digital Pathology)

► Show Figures

Figure 1

24 pages, 2731 KiB

Open AccessArticle

Pneumocystis Jirovecii Pneumonia: The Potential of KEX1, MSG1, and MSG2 as Key Antigens in Cytokine Release Assays

by F. A. Ottilie Neumann, Markus Müller, Gregor Mattert, Sven Liebig, Victor Herbst, Dorinja Zapf, Til R. Kiderlen, Christian Linke, Franziska Arp, P. Markus Deckert, Stefan Lüth, Sandra Schwarzlose-Schwarck, Werner Dammermann and Mark Reinwald

Diagnostics 2025, 15(7), 793; https://doi.org/10.3390/diagnostics15070793 (registering DOI) - 21 Mar 2025

Abstract

Background/Objectives: Pneumocystis jirovecii pneumonia (PJP) is the most frequently diagnosed AIDS-defining illness in Europe, with especially high mortality in HIV-negative patients caused by delayed diagnosis and low awareness. This study aims to evaluate cytokine release assays (CRA) to facilitate a less invasive [...] Read more.

Background/Objectives: Pneumocystis jirovecii pneumonia (PJP) is the most frequently diagnosed AIDS-defining illness in Europe, with especially high mortality in HIV-negative patients caused by delayed diagnosis and low awareness. This study aims to evaluate cytokine release assays (CRA) to facilitate a less invasive and resource-efficient PJP specific diagnostic test. We focus on the P. jirovecii antigens Kexin 1 (KEX1), MSG1, and MSG2, which were identified in prior studies as immunologically relevant. Methods: Whole blood samples from 50 participants—22 healthy individuals and 28 immunocompromised individuals, including 8 with proven PJP—were stimulated in vitro with full-length and partial KEX1, MSG1, MSG2, and a combination of all three antigens (PJ-MIX). Following 24 h incubation at 37 °C, cytokine levels of IL-2, IFN-γ, IL-17A, and IL-17F were measured. Results: Stimulation with full-length KEX1, MSG1, MSG2, and PJ-MIX antigens induced higher IL-2 concentrations in the healthy control group compared to the groups IL-2 baseline levels and to the group of proven PJP cases. Similarly, stimulation with full-length KEX1, MSG1, and PJ-MIX elevated IFN-γ levels in the healthy control group compared to baseline IFN-γ levels. Conclusions: Our findings highlight the potential of IL-2 and IFN-γ release following stimulation with PJ antigens, with PJ-MIX eliciting the strongest and most significant responses, suggesting a cumulative antigen effect. This pilot study establishes a foundation for a PJP-specific CRA, deepening our knowledge of T-cell immunity against PJP. Clinically, such a test could, among other applications, evaluate at-risk patients who should receive prophylaxis and may consequently reduce PJP-related morbidity and mortality. Full article

(This article belongs to the Special Issue Advances in Fungal Infections: Special Issue in Diagnostics Journal, 3rd Edition)

► Show Figures

Figure 1

15 pages, 1017 KiB

Open AccessSystematic Review

Clinicopathological Comparison Between GREB1- and ESR1-Rearranged Uterine Tumors Resembling Ovarian Sex Cord Tumors (UTROSCTs): A Systematic Review

by Livia Maccio, Damiano Arciuolo, Angela Santoro, Antonio Raffone, Diego Raimondo, Susanna Ronchi, Nicoletta D’Alessandris, Giulia Scaglione, Michele Valente, Belen Padial Urtueta, Francesca Addante, Nadine Narducci, Emma Bragantini, Jvan Casarin, Giuseppe Angelico, Stefano La Rosa, Gian Franco Zannoni and Antonio Travaglino

Diagnostics 2025, 15(6), 792; https://doi.org/10.3390/diagnostics15060792 (registering DOI) - 20 Mar 2025

Abstract

Introduction: Among uterine tumors resembling ovarian sex cord tumors (UTROSCTs), it has been suggested that GREB1-rearranged cases are biologically distinct from ESR1-rearranged cases and might be considered as a separate entity. Objectives: The aim of this systematic review was to assess [...] Read more.

Introduction: Among uterine tumors resembling ovarian sex cord tumors (UTROSCTs), it has been suggested that GREB1-rearranged cases are biologically distinct from ESR1-rearranged cases and might be considered as a separate entity. Objectives: The aim of this systematic review was to assess the difference between GREB1- and ESR1-rearranged UTROSCTs with regard to several clinico-pathological parameters. Methods: Three electronic databases were searched from their inception to February 2025 for all studies assessing the presence of GREB1 and ESR1 rearrangements in UTROSCTs. Exclusion criteria comprised overlapping patient data, case reports, and reviews. Statistical analysis was performed to compare clinicopathological variables between GREB1- and ESR1-rearranged UTROSCTs. Dichotomous variables were compared by using Fisher’s exact test; continuous variables were compared by using Student’s t-test. A p-value < 0.05 was considered significant. Results: Six studies with 88 molecularly classified UTROSCTs were included. A total of 36 cases were GREB1-rearranged, and 52 cases were ESR1-rearranged. GREB1-rearranged UTROSCTs showed a significantly older age (p < 0.001), larger tumor size (p = 0.002), less common submucosal/polypoid growth (p = 0.005), higher mitotic index (p = 0.010), more common LVSI (p = 0.049), and higher likelihood to undergo hysterectomy (p = 0.008) compared to ESR1-rearranged cases. No significant differences were detected with regard to margins, cytological atypia, necrosis, retiform pattern, and rhabdoid cells. No significant differences were found in the immunohistochemical expression of any of the assessed markers (wide-spectrum cytokeratins, α-inhibin, calretinin, WT1, CD10, CD56, CD99, smooth muscle actin, desmin, h-caldesmon, Melan-A/MART1, SF1, or Ki67). GREB1-rearranged UTROSCTs showed significantly lower disease-free survival compared to ESR1-rearranged UTROSTCs (p = 0.049). Conclusions: In conclusion, GREB1-rearranged UTROSCTs occur at an older age, are less likely to display a submucosal/polypoid growth, and exhibit larger size, a higher mitotic index, more common lymphovascular space invasion, and lower disease-free survival compared to ESR1-rearranged UTROSCTs. Nonetheless, the similar immunophenotype suggests that they belong to the same tumor family. Further studies are necessary to confirm this point. Full article

(This article belongs to the Special Issue Molecular Pathology and Diagnostic Biomarkers of Gynaecological Cancers)

► Show Figures

Figure 1

20 pages, 2305 KiB

Open AccessArticle

Comparison of 46 Cytokines in Peripheral Blood Between Patients with Papillary Thyroid Cancer and Healthy Individuals with AI-Driven Analysis to Distinguish Between the Two Groups

by Kyung-Jin Bae, Jun-Hyung Bae, Ae-Chin Oh and Chi-Hyun Cho

Diagnostics 2025, 15(6), 791; https://doi.org/10.3390/diagnostics15060791 (registering DOI) - 20 Mar 2025

Abstract

Background: Recent studies have analyzed some cytokines in patients with papillary thyroid carcinoma (PTC), but simultaneous analysis of multiple cytokines remains rare. Nonetheless, the simultaneous assessment of multiple cytokines is increasingly recognized as crucial for understanding the cytokine characteristics and developmental mechanisms [...] Read more.

Background: Recent studies have analyzed some cytokines in patients with papillary thyroid carcinoma (PTC), but simultaneous analysis of multiple cytokines remains rare. Nonetheless, the simultaneous assessment of multiple cytokines is increasingly recognized as crucial for understanding the cytokine characteristics and developmental mechanisms in PTC. In addition, studies applying artificial intelligence (AI) to discriminate patients with PTC based on serum multiple cytokine data have been performed rarely. Here, we measured and compared 46 cytokines in patients with PTC and healthy individuals, applying AI algorithms to classify the two groups. Methods: Blood serum was isolated from 63 patients with PTC and 63 control individuals. Forty-six cytokines were analyzed simultaneously using Luminex assay Human XL Cytokine Panel. Several laboratory findings were identified from electronic medical records. Student’s t-test or the Mann–Whitney U test were performed to analyze the difference between the two groups. As AI classification algorithms to categorize patients with PTC, K-nearest neighbor function, Naïve Bayes classifier, logistic regression, support vector machine, and eXtreme Gradient Boosting (XGBoost) were employed. The SHAP analysis assessed how individual parameters influence the classification of patients with PTC. Results: Cytokine levels, including GM-CSF, IFN-γ, IL-1ra, IL-7, IL-10, IL-12p40, IL-15, CCL20/MIP-α, CCL5/RANTES, and TNF-α, were significantly higher in PTC than in controls. Conversely, CD40 Ligand, EGF, IL-1β, PDGF-AA, and TGF-α exhibited significantly lower concentrations in PTC compared to controls. Among the five classification algorithms evaluated, XGBoost demonstrated superior performance in terms of accuracy, precision, sensitivity (recall), specificity, F1-score, and ROC-AUC score. Notably, EGF and IL-10 were identified as critical cytokines that significantly contributed to the differentiation of patients with PTC. Conclusions: A total of 5 cytokines showed lower levels in the PTC group than in the control, while 10 cytokines showed higher levels. While XGBoost demonstrated the best performance in discriminating between the PTC group and the control group, EGF and IL-10 were considered to be closely associated with PTC. Full article

(This article belongs to the Section Clinical Laboratory Medicine)

► Show Figures

Figure 1

14 pages, 3652 KiB

Open AccessArticle

Improving Diagnostic Performance for Head and Neck Tumors with Simple Diffusion Kurtosis Imaging and Machine Learning Bi-Parameter Analysis

by Suzuka Yoshida, Masahiro Kuroda, Yoshihide Nakamura, Yuka Fukumura, Yuki Nakamitsu, Wlla E. Al-Hammad, Kazuhiro Kuroda, Yudai Shimizu, Yoshinori Tanabe, Masataka Oita, Irfan Sugianto, Majd Barham, Nouha Tekiki, Nurul N. Kamaruddin, Miki Hisatomi, Yoshinobu Yanagi and Junichi Asaumi

Diagnostics 2025, 15(6), 790; https://doi.org/10.3390/diagnostics15060790 (registering DOI) - 20 Mar 2025

Abstract

Background/Objectives: Mean kurtosis (MK) values in simple diffusion kurtosis imaging (SDI)—a type of diffusion kurtosis imaging (DKI)—have been reported to be useful in the diagnosis of head and neck malignancies, for which pre-processing with smoothing filters has been reported to improve the diagnostic [...] Read more.

Background/Objectives: Mean kurtosis (MK) values in simple diffusion kurtosis imaging (SDI)—a type of diffusion kurtosis imaging (DKI)—have been reported to be useful in the diagnosis of head and neck malignancies, for which pre-processing with smoothing filters has been reported to improve the diagnostic accuracy. Multi-parameter analysis using DKI in combination with other image types has recently been reported to improve the diagnostic performance. The purpose of this study was to evaluate the usefulness of machine learning (ML)-based multi-parameter analysis using the MK and apparent diffusion coefficient (ADC) values—which can be acquired simultaneously through SDI—for the differential diagnosis of benign and malignant head and neck tumors, which is important for determining the treatment strategy, as well as examining the usefulness of filter pre-processing. Methods: A total of 32 pathologically diagnosed head and neck tumors were included in the study, and a Gaussian filter was used for image pre-processing. MK and ADC values were extracted from pixels within the tumor area and used as explanatory variables. Five ML algorithms were used to create models for the prediction of tumor status (benign or malignant), which were evaluated through ROC analysis. Results: Bi-parameter analysis with gradient boosting achieved the best diagnostic performance, with an AUC of 0.81. Conclusions: The usefulness of bi-parameter analysis with ML methods for the differential diagnosis of benign and malignant head and neck tumors using SDI data were demonstrated. Full article

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

► Show Figures

Figure 1

36 pages, 10750 KiB

Open AccessArticle

A Novel Diagnostic Framework with an Optimized Ensemble of Vision Transformers and Convolutional Neural Networks for Enhanced Alzheimer’s Disease Detection in Medical Imaging

by Joy Chakra Bortty, Gouri Shankar Chakraborty, Inshad Rahman Noman, Salil Batra, Joy Das, Kanchon Kumar Bishnu, Md Tanvir Rahman Tarafder and Araf Islam

Diagnostics 2025, 15(6), 789; https://doi.org/10.3390/diagnostics15060789 (registering DOI) - 20 Mar 2025

Abstract

Background/Objectives: Alzheimer’s disease (AD) is a progressive, neurodegenerative disorder, which causes memory loss and loss of cognitive functioning, along with behavioral changes. Early detection is important to delay disease progression, timely intervention and to increase patients’ and caregivers’ quality of life (QoL). One [...] Read more.

Background/Objectives: Alzheimer’s disease (AD) is a progressive, neurodegenerative disorder, which causes memory loss and loss of cognitive functioning, along with behavioral changes. Early detection is important to delay disease progression, timely intervention and to increase patients’ and caregivers’ quality of life (QoL). One of the major and primary challenges for preventing any disease is to identify the disease at the initial stage through a quick and reliable detection process. Different researchers across the world are still working relentlessly, coming up with significant solutions. Artificial intelligence-based solutions are putting great importance on identifying the disease efficiently, where deep learning with medical imaging is highly being utilized to develop disease detection frameworks. In this work, a novel and optimized detection framework has been proposed that comes with remarkable performance that can classify the level of Alzheimer’s accurately and efficiently. Methods: A powerful vision transformer model (ViT-B16) with three efficient Convolutional Neural Network (CNN) models (VGG19, ResNet152V2, and EfficientNetV2B3) has been trained with a benchmark dataset, ‘OASIS’, that comes with a high volume of brain Magnetic Resonance Images (MRI). Results: A weighted average ensemble technique with a Grasshopper optimization algorithm has been designed and utilized to ensure maximum performance with high accuracy of 97.31%, precision of 97.32, recall of 97.35, and F1 score of 0.97. Conclusions: The work has been compared with other existing state-of-the-art techniques, where it comes with high efficiency, sensitivity, and reliability. The framework can be utilized in IoMT infrastructure where one can access smart and remote diagnosis services. Full article

(This article belongs to the Special Issue Artificial Intelligence in Brain Diseases)

► Show Figures

Figure 1

9 pages, 1066 KiB

Open AccessArticle

MRI Detection of Unknown Primary Tumours in the Head and Neck: What Is the Expected Normal Asymmetry in the Size of the Palatine Tonsils?

by Kaijing Mao, Qi Yong H. Ai, Kuo Feng Hung, Irene O. L. Tse, Ho Sang Leung, Yannis Yan Liang, Yu Chen, Lun M. Wong, W. K. Jacky Lam and Ann D. King

Diagnostics 2025, 15(6), 788; https://doi.org/10.3390/diagnostics15060788 (registering DOI) - 20 Mar 2025

Abstract

Background/Objectives: The detection of unknown primary tumours in the palatine tonsils (PTs) on imaging relies heavily on asymmetry in size between the right and left sides, but the expected normal range in asymmetry is not well documented. This study aimed to document the [...] Read more.

Background/Objectives: The detection of unknown primary tumours in the palatine tonsils (PTs) on imaging relies heavily on asymmetry in size between the right and left sides, but the expected normal range in asymmetry is not well documented. This study aimed to document the expected range of asymmetry in the size of the PTs in adults without cancer. Methods: This retrospective study evaluated 250 pairs of normal PTs on MRIs of adults without head and neck cancer. The size (volume, V) of the PTs on the left and right sides were measured, and the percentage difference in volume (ΔV%) between the two sides was calculated. An additional analysis of PT volumes in 29 patients with ipsilateral early-stage palatine tonsillar cancer (PTCs) was performed. Results: In patients without PTC, the normal PTs had a mean volume of 3.0 ± 1.7 cm³, and there was a difference in size between the left and right PTs, showing a median ΔV% of 11.6% (range: 0.1–79.0%); most patients had a ΔV% of ≤40% (95%) for PTs. In patients with ipsilateral PTC, the normal PT had a smaller size compared with PTC (p < 0.01), showing a median ΔV% of 132.9% (range: 8.5–863.2%). Compared with patients without PTC, those with PTC showed a greater ΔV% (p < 0.01). An optimal ΔV% threshold of >39.6% achieved the best accuracy of 95% for identifying PTC. Conclusions: PTs are asymmetrical in size in adults without PTC. An additional analysis involving patients with PTC confirmed a threshold of ΔV% of 40% for PTs, which may be clinically valuable to help detect pathology using MRI. Full article

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

► Show Figures

Figure 1

28 pages, 1031 KiB

Open AccessReview

AI and Smart Devices in Cardio-Oncology: Advancements in Cardiotoxicity Prediction and Cardiovascular Monitoring

by Luiza Camelia Nechita, Dana Tutunaru, Aurel Nechita, Andreea Elena Voipan, Daniel Voipan, Ancuta Elena Tupu and Carmina Liana Musat

Diagnostics 2025, 15(6), 787; https://doi.org/10.3390/diagnostics15060787 (registering DOI) - 20 Mar 2025

Abstract

The increasing prevalence of cardiovascular complications in cancer patients due to cardiotoxic treatments has necessitated advanced monitoring and predictive solutions. Cardio-oncology is an evolving interdisciplinary field that addresses these challenges by integrating artificial intelligence (AI) and smart cardiac devices. This comprehensive review explores [...] Read more.

The increasing prevalence of cardiovascular complications in cancer patients due to cardiotoxic treatments has necessitated advanced monitoring and predictive solutions. Cardio-oncology is an evolving interdisciplinary field that addresses these challenges by integrating artificial intelligence (AI) and smart cardiac devices. This comprehensive review explores the integration of artificial intelligence (AI) and smart cardiac devices in cardio-oncology, highlighting their role in improving cardiovascular risk assessment and the early detection and real-time monitoring of cardiotoxicity. AI-driven techniques, including machine learning (ML) and deep learning (DL), enhance risk stratification, optimize treatment decisions, and support personalized care for oncology patients at cardiovascular risk. Wearable ECG patches, biosensors, and AI-integrated implantable devices enable continuous cardiac surveillance and predictive analytics. While these advancements offer significant potential, challenges such as data standardization, regulatory approvals, and equitable access must be addressed. Further research, clinical validation, and multidisciplinary collaboration are essential to fully integrate AI-driven solutions into cardio-oncology practices and improve patient outcomes. Full article

(This article belongs to the Special Issue AI-Assisted Diagnostics in Telemedicine and Digital Health)

► Show Figures

Figure 1

10 pages, 1842 KiB

Open AccessArticle

Do We Need to Add the Type of Treatment Planning System, Dose Calculation Grid Size, and CT Density Curve to Predictive Models?

by Reza Reiazi, Surendra Prajapati, Leonardo Che Fru, Dongyeon Lee and Mohammad Salehpour

Diagnostics 2025, 15(6), 786; https://doi.org/10.3390/diagnostics15060786 (registering DOI) - 20 Mar 2025

Abstract

Background: Generalizability and domain dependency are critical challenges in developing predictive models for healthcare, particularly in medical diagnostics and radiation oncology. Predictive models designed to assess tumor recurrence rely on comprehensive and high-quality datasets, encompassing treatment planning parameters, imaging protocols, and patient-specific data. [...] Read more.

Background: Generalizability and domain dependency are critical challenges in developing predictive models for healthcare, particularly in medical diagnostics and radiation oncology. Predictive models designed to assess tumor recurrence rely on comprehensive and high-quality datasets, encompassing treatment planning parameters, imaging protocols, and patient-specific data. However, domain dependency, arising from variations in dose calculation algorithms, computed tomography (CT) density conversion curves, imaging modalities, and institutional protocols, can significantly undermine model reliability and clinical utility. Methods: This study evaluated dose calculation differences in the head and neck cancer treatment plans of 19 patients using two treatment planning systems, Pinnacle 9.10 and RayStation 11, with similar dose calculation algorithms. Variations in the dose grid size and CT density conversion curves were assessed for their impact on domain dependency. Results: Results showed that dose grid size differences had a more significant influence within RayStation than Pinnacle, while CT curve variations introduced potential domain discrepancies. The findings underscore the critical role of precise and standardized treatment planning in enhancing the reliability of predictive modeling for tumor recurrence assessment. Conclusions: Incorporating treatment planning parameters, such as dose distribution and target volumes, as explicit features in model training can mitigate the impact of domain dependency and enhance prediction accuracy. Solutions such as multi-institutional data harmonization and domain adaptation techniques are essential to improve model generalizability and robustness. These strategies support the better integration of predictive modeling into clinical workflows, ultimately optimizing patient outcomes and personalized treatment strategies. Full article

(This article belongs to the Special Issue Artificial Intelligence in Clinical Decision Support—2nd Edition)

► Show Figures

Figure 1

22 pages, 7900 KiB

Open AccessSystematic Review

What the Radiologist Needs to Know About Sport Hernias: A Systematic Review of the Current Literature

by Gian Nicola Bisciotti, Andrea Bisciotti, Alessandro Bisciotti and Alessio Auci

Diagnostics 2025, 15(6), 785; https://doi.org/10.3390/diagnostics15060785 - 20 Mar 2025

Abstract

Introduction: The sports hernia (SH) is one of the most important causes of groin pain syndrome (GPS). However, despite its importance in GPS etiopathogenesis, SH is one of the least understood and poorly defined clinical conditions in sports medicine. The aim of this [...] Read more.

Introduction: The sports hernia (SH) is one of the most important causes of groin pain syndrome (GPS). However, despite its importance in GPS etiopathogenesis, SH is one of the least understood and poorly defined clinical conditions in sports medicine. The aim of this systematic review is to clearly define SH from a radiological point of view and to clarify the relationship between the radiological presentation of SH and its clinical manifestation. Methods: The PubMed/MEDLINE, Scopus, ISI, Cochrane Database of Systematic Reviews, and PEDro databases were consulted for systematic reviews on the role of SH in the onset of GPS. The inclusion and exclusion criteria were based on PICO tool. Results: After screening 560 articles, 81 studies were included and summarized in this systematic review. All studies were checked to identify any potential conflict of interest. The quality assessment of each individual study considered was performed in agreement with the Joanna Briggs Institute quantitative critical appraisal tools. Conclusions: The correct definition of SH is “weakness of the posterior wall of the inguinal canal”, which, in response to a Valsalva maneuver, forms a bulging that compresses the nerves passing along the inguinal canal. Thus, from an anatomical point of view, SH represents a direct inguinal hernia “in fieri”. Furthermore, an excessive dilation of the external inguinal ring represents an indirect sign of possible posterior inguinal canal wall weakness. Full article

(This article belongs to the Special Issue Imaging Diagnosis in Abdomen, 2nd Edition)

► Show Figures

Figure 1

13 pages, 2033 KiB

Open AccessArticle

Relationship Between Sigmoid Volvulus Subtypes, Clinical Course, and Imaging Findings

by Kemal Bugra Memis and Sonay Aydin

Diagnostics 2025, 15(6), 784; https://doi.org/10.3390/diagnostics15060784 - 20 Mar 2025

Abstract

Background: Recent studies indicate that the organo-axial subtype of a sigmoid volvulus is more prevalent than the conventional mesentero-axial subtype. Our study aimed to assess the clinical and radiological findings that differentiate between these two subtypes, as well as to ascertain treatment outcomes [...] Read more.

Background: Recent studies indicate that the organo-axial subtype of a sigmoid volvulus is more prevalent than the conventional mesentero-axial subtype. Our study aimed to assess the clinical and radiological findings that differentiate between these two subtypes, as well as to ascertain treatment outcomes and prognostic characteristics. Methods: A retrospective review included 54 patients, during which abdominal plain radiographs and computed tomography images were analyzed by two radiologists, and data on recurrence, mortality, and treatment outcomes were documented. Results: The mesentero-axial subtype comprised 40 cases (74%). No distinct radiographic findings were observed to differentiate between the two groups. In computed tomography, the sole significant parameter for differentiation was the number of transition zones. The diameter of the segment exhibiting a volvulus was greater in instances of the mesentero-axial subtype. The endoscopic detorsion treatment proved ineffective in five patients within the mesentero-axial sigmoid volvulus cohort. Conclusions: Identifying these two types of SV on CT images is essential because of their distinct prognoses and therapeutic results. Full article

(This article belongs to the Special Issue Diagnostic Imaging in Gastrointestinal and Liver Diseases)

► Show Figures

Figure 1

16 pages, 2180 KiB

Open AccessArticle

Machine Learning Based Multi-Parameter Modeling for Prediction of Post-Inflammatory Lung Changes

by Gerlig Widmann, Anna Katharina Luger, Thomas Sonnweber, Christoph Schwabl, Katharina Cima, Anna Katharina Gerstner, Alex Pizzini, Sabina Sahanic, Anna Boehm, Maxmilian Coen, Ewald Wöll, Günter Weiss, Rudolf Kirchmair, Leonhard Gruber, Gudrun M. Feuchtner, Ivan Tancevski, Judith Löffler-Ragg and Piotr Tymoszuk

Diagnostics 2025, 15(6), 783; https://doi.org/10.3390/diagnostics15060783 - 20 Mar 2025

Abstract

Objectives: Prediction of lung function deficits following pulmonary infection is challenging and suffers from inaccuracy. We sought to develop machine-learning models for prediction of post-inflammatory lung changes based on COVID-19 recovery data. Methods: In the prospective CovILD study (n = [...] Read more.

Objectives: Prediction of lung function deficits following pulmonary infection is challenging and suffers from inaccuracy. We sought to develop machine-learning models for prediction of post-inflammatory lung changes based on COVID-19 recovery data. Methods: In the prospective CovILD study (n = 420 longitudinal observations from n = 140 COVID-19 survivors), data on lung function testing (LFT), chest CT including severity scoring by a human radiologist and density measurement by artificial intelligence, demography, and persistent symptoms were collected. This information was used to develop models of numeric readouts and abnormalities of LFT with four machine learning algorithms (Random Forest, gradient boosted machines, neural network, and support vector machines). Results: Reduced DLCO (diffusion capacity for carbon monoxide <80% of reference) was found in 94 (22%) observations. Those observations were modeled with a cross-validated accuracy of 82–85%, AUC of 0.87–0.9, and Cohen’s κ of 0.45–0.5. No reliable models could be established for FEV1 or FVC. For DLCO as a continuous variable, three machine learning algorithms yielded meaningful models with cross-validated mean absolute errors of 11.6–12.5% and R² of 0.26–0.34. CT-derived features such as opacity, high opacity, and CT severity score were among the most influential predictors of DLCO impairment. Conclusions: Multi-parameter machine learning trained with demographic, clinical, and artificial intelligence chest CT data reliably and reproducibly predicts LFT deficits and outperforms single markers of lung pathology and human radiologist’s assessment. It may improve diagnostic and foster personalized treatment. Full article

(This article belongs to the Special Issue Artificial Intelligence in Lung Diseases: 3rd Edition)

► Show Figures

Figure 1

14 pages, 5303 KiB

Open AccessArticle

The Zucker Diabetic Fatty Rat as a Model for Vascular Changes in Diabetic Kidney Disease: Characterising Hydronephrosis

by Amy McDermott, Nathalie Sarup Panduro, Iman Taghavi, Hans Martin Kjer, Stinne Byrholdt Søgaard, Michael Bachmann Nielsen, Jørgen Arendt Jensen and Charlotte Mehlin Sørensen

Diagnostics 2025, 15(6), 782; https://doi.org/10.3390/diagnostics15060782 - 20 Mar 2025

Abstract

Background/Objectives: Diabetic kidney disease (DKD) is a significant concern for global healthcare, particularly in individuals with diabetes. The Zucker rat strain is a commonly used model of type 2 diabetes, despite awareness that this animal can develop hydronephrosis. In this study, we present [...] Read more.

Background/Objectives: Diabetic kidney disease (DKD) is a significant concern for global healthcare, particularly in individuals with diabetes. The Zucker rat strain is a commonly used model of type 2 diabetes, despite awareness that this animal can develop hydronephrosis. In this study, we present novel imaging data evaluating the accuracy of this animal model in replicating the vascular aspects of human DKD while examining the impact of hydronephrosis on its validity as a disease model. Methods: This study reused data from a population of male Zucker Diabetic Fatty (ZDF; n = 22) rats and Zucker Lean (ZL) rats (n = 22) aged 12 to approximately 40 weeks. Vascular casting was performed to enable visualisation of the renal vasculature. Anatomical regional volumes and vascular density data were obtained from μCT scans using image thresholding and manual analysis. The effects of hydronephrosis were evaluated using renal functional parameters and histological examination. Results: A significantly lower cortical vascular density, as well as lower total renal vascular density, was seen in ZDF rats compared to ZL rats, independent of age. We identified that hydronephrosis affected 92% of ZDF rats and 69% of ZL rats. Hydronephrosis cavity size was significantly correlated with the degree of hyperglycaemia and rate of diuresis but had no other detected impact on renal function, vascularity, or tissue histological architecture. Conclusions: These findings support using the Zucker rat strain as a model for vascular changes in DKD. Despite identifying severe hydronephrosis in this population, it had minimal quantifiable impact on renal function or diabetes modelling. Full article

(This article belongs to the Special Issue Current Issues on Kidney Diseases Diagnosis and Management 2025)

► Show Figures

Figure 1

11 pages, 6299 KiB

Open AccessCase Report

Cladosporium species novum Invasive Pulmonary Infection in a Patient with Post-COVID-19 Syndrome and AIDS

by Milorad Bijelović, Nikola Gardić, Aleksandra Lovrenski, Danijela Petrović, Gordana Kozoderović, Vesna Lalošević, Vuk Vračar and Dušan Lalošević

Diagnostics 2025, 15(6), 781; https://doi.org/10.3390/diagnostics15060781 - 20 Mar 2025

Abstract

Background and Clinical Significance: Since the prevalence of fungal lung infections is increasing, certain agents, such as Cladosporium spp., have emerged as unexpected causes. Cladosporium spp. fungi are ubiquitous in environments such as soil, fruits, and wine corks; they are a part of [...] Read more.

Background and Clinical Significance: Since the prevalence of fungal lung infections is increasing, certain agents, such as Cladosporium spp., have emerged as unexpected causes. Cladosporium spp. fungi are ubiquitous in environments such as soil, fruits, and wine corks; they are a part of the normal human skin flora; and they are known respiratory allergens. Case Presentation: A patient with a history of post-COVID-19 syndrome and AIDS presented with lung pathology indicative of an invasive fungal infection. The initial histopathological examination revealed numerous yeast-like cells with narrow-based budding, which led to a mistaken diagnosis of cryptococcosis. However, further detailed examination revealed sparse hyphae in the lung tissue, suggesting a more complex fungal infection. Molecular analyses and sequence BLAST alignment were performed, ultimately identifying the infectious agent as “Cladosporium species novum”, a rare cause of invasive pulmonary cladosporiasis. Conclusions: Invasive pulmonary cladosporiasis is a rare condition, and the morphological features of the fungus alone were insufficient to establish a correct diagnosis. A comprehensive pathohistological and molecular approach with bioinformatics tools is essential for the correct identification of rare and potentially life-threatening fungal pathogens in immunocompromised patients. Full article

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

► Show Figures

Figure 1

4 pages, 5140 KiB

Open AccessInteresting Images

Orbital Neurolymphomatosis in Patient with CNS Lymphoma

by Tara Shooshani, Michael Han, Jeremiah P. Tao, Samuel J. Spiegel and Maria Del Valle Estopinal

Diagnostics 2025, 15(6), 780; https://doi.org/10.3390/diagnostics15060780 - 20 Mar 2025

Abstract

Neurolymphomatosis (NL) is a rare manifestation of hematologic malignancies, characterized by a neoplastic infiltration of the peripheral nervous system and cranial nerves (CNs). Non-Hodgkin lymphomas (NHLs) account for 90% of NL cases, while acute leukemia represents 10% of the cases. NL can occur [...] Read more.

Neurolymphomatosis (NL) is a rare manifestation of hematologic malignancies, characterized by a neoplastic infiltration of the peripheral nervous system and cranial nerves (CNs). Non-Hodgkin lymphomas (NHLs) account for 90% of NL cases, while acute leukemia represents 10% of the cases. NL can occur as the first manifestation of a malignancy (primary), or as a relapse or progression of a previously treated disease (secondary). Herein, we report a unique case of NL involving the orbits and CNs in a 74-year-old female with primary central nervous system (CNS) diffuse large B-cell lymphoma (DLBCL). Our patient developed secondary neurolymphomatosis involving the orbits and CNs II, III, V, and VI, supported by clinical, radiologic, and histologic findings. The lacrimal gland enhancement was histopathologically proven to be caused by the direct spread of CNS DLBCL to the lacrimal nerve, a branch of CN V, identifying NL as one of the conditions that can affect this organ. The lacrimal gland could be considered as a more accessible biopsy site when the involvement of CN V is suspected. Full article

(This article belongs to the Special Issue Pathology and Diagnosis of Head and Neck Diseases)

► Show Figures

Figure 1

14 pages, 2871 KiB

Open AccessArticle

The Association of Heart Failure and Liver T1 Mapping in Cardiac Magnetic Resonance Imaging

by Adrian T. Huber, Joanna Bartkowiak, Robin Seitz, Benedikt Bernhard, Martina Boscolo Berto, Giancarlo Spano, Benedikt Wagner, Verena C. Obmann, Lukas Ebner, Inga A. S. Todorski, Michael P. Brönnimann, Kady Fischer, Dominik P. Guensch, Andreas Christe, Annalisa Berzigotti, Lorenz Räber, Tobias Reichlin, Thomas Pilgrim, Fabien Praz, Christoph Gräni, Nicholas Brugger and Alan A. Peters Show full author list Hide full author list

Diagnostics 2025, 15(6), 779; https://doi.org/10.3390/diagnostics15060779 - 20 Mar 2025

Abstract

Background/Objectives: The objective of this study was to investigate the association between congestive heart failure (CHF) and T1 mapping in both liver lobes using cardiac MRI. Methods: This retrospective study included patients who underwent cardiac MRI with T1 mapping sequences on a 1.5 [...] Read more.

Background/Objectives: The objective of this study was to investigate the association between congestive heart failure (CHF) and T1 mapping in both liver lobes using cardiac MRI. Methods: This retrospective study included patients who underwent cardiac MRI with T1 mapping sequences on a 1.5 T scanner. The liver T1 values were measured in four hepatic regions, utilizing cardiac short axis and four-chamber views. Echocardiographic and laboratory data were collected within 90 days of the cardiac MRI. Comparisons of the liver T1 values and echocardiographic parameters between patients with and without elevated NT-proBNP levels (>125 pg/mL) were conducted using the Mann–Whitney U test. Logistic regression models were employed to adjust for confounding factors. Results: A total of 397 patients were included (with a median age of 56 years; 127 females), of whom 35% (n = 138) exhibited elevated NT-proBNP levels. The patients with elevated NT-proBNP levels showed a larger end-diastolic volume (EDV: 92 vs. 81 mL/m², p < 0.001) and a lower LVEF level (50% vs. 60%, p < 0.001). The liver T1 was significantly higher in the right liver lobe (670 vs. 596 ms, p < 0.001) and the caudate lobe (664 vs. 598 ms, p < 0.001), but not in the left lobe (571 vs. 568 ms, p = 0.068) or the dome (590 vs. 560 ms, p = 0.1). T1 mapping in the caudate (OR 1.013, 95% CI 1.004–1.023, p = 0.005) and right liver lobes (OR 1.012, 95% CI 1.003–1.021, p = 0.009) remained independently predictive in the logistic regression analysis. Conclusions: Elevated T1 values in the caudate and right liver lobes assessed by cardiac MRI were independently associated with CHF and outperformed T1 measurements in the left liver lobe in predicting disease. Full article

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

► Show Figures

Figure 1

18 pages, 9445 KiB

Open AccessReview

The Role of Autopsy in Diagnosing Fatal Chest Injuries in Road Traffic Accidents: A Literature Review

by Matteo Antonio Sacco, Maria Cristina Verrina, Saverio Gualtieri, Agostinho Santos, Bárbara Ferreira Mendes, Alessandro Pasquale Tarallo, Aurora Princi, Stefano Lombardo, Pietrantonio Ricci and Isabella Aquila

Diagnostics 2025, 15(6), 778; https://doi.org/10.3390/diagnostics15060778 - 19 Mar 2025

Abstract

Road accidents are one of the leading causes of death worldwide, with significant repercussions on public health and the global economy. Fatal accidents can cause injuries in various anatomical areas with different dynamics. The thorax is one of the main sites involved in [...] Read more.

Road accidents are one of the leading causes of death worldwide, with significant repercussions on public health and the global economy. Fatal accidents can cause injuries in various anatomical areas with different dynamics. The thorax is one of the main sites involved in fatal accidents, due to the presence of vital organs such as the heart and lungs. Protective devices, such as seatbelts and airbags, also play a fundamental role in preventing chest injuries. However, external examination is often insufficient to determine the extent of internal trauma, resulting in significant difficulties in reconstructing the accident dynamics. In particular, in the absence of an autopsy, it is difficult to determine whether the driver or passengers were wearing protective devices, such as seatbelts, at the time of the accident. Diagnosing injuries secondary to protective devices, such as airbags, can also be complex without this assessment. Through a review of the literature, this work analyzes the different types of thoracic trauma that can be found at autopsy, providing indications to the forensic pathologist for the examination of these injuries. This review highlights the importance of the autopsy examination as a gold-standard investigation in the analysis of thoracic trauma from road accidents, in order to evaluate with certainty the injuries that caused death, and to facilitate the reconstruction of the dynamics for judicial purposes. Finally, an analysis of postmortem radiological investigations and of the role of protective measures in these events, such as the seatbelt and airbag, is provided. Full article

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

► Show Figures

Figure 1

Journal Description

Diagnostics

Latest Articles

Journal Menu

Journal Browser

Highly Accessed Articles

Latest Books

E-Mail Alert

News

Topics

Conferences

Special Issues

Topical Collections

Further Information

Guidelines

MDPI Initiatives

Follow MDPI