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Volume 14
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Diagnostics, Volume 14, Issue 12 (June-2 2024) – 80 articles

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14 pages, 2022 KiB  
Article
Comparative Analysis of Lymphocyte Populations in Post-COVID-19 Condition and COVID-19 Convalescent Individuals
by Luisa Berger, Johannes Wolf, Sven Kalbitz, Nils Kellner, Christoph Lübbert and Stephan Borte
Diagnostics 2024, 14(12), 1286; https://0-doi-org.brum.beds.ac.uk/10.3390/diagnostics14121286 - 18 Jun 2024
Abstract
Reduced lymphocyte counts in peripheral blood are one of the most common observations in acute phases of viral infections. Although many studies have already examined the impact of immune (dys)regulation during SARS-CoV-2 infection, there are still uncertainties about the long-term consequences for lymphocyte [...] Read more.
Reduced lymphocyte counts in peripheral blood are one of the most common observations in acute phases of viral infections. Although many studies have already examined the impact of immune (dys)regulation during SARS-CoV-2 infection, there are still uncertainties about the long-term consequences for lymphocyte homeostasis. Furthermore, as persistent cellular aberrations have been described following other viral infections, patients with “Post-COVID-19 Condition” (PCC) may present similarly. In order to investigate cellular changes in the adaptive immune system, we performed a retrospective analysis of flow cytometric data from lymphocyte subpopulations in 106 patients with confirmed SARS-CoV-2 infection who received medical care at our institution. The patients were divided into three groups according to the follow-up date; laboratory analyses of COVID-19 patients were compared with 28 unexposed healthy controls. Regarding B lymphocyte subsets, levels of IgA + CD27+, IgG + CD27+, IgM + CD27− and switched B cells were significantly reduced at the last follow-up compared to unexposed healthy controls (UHC). Of the 106 COVID-19 patients, 56 were clinically classified as featuring PCC. Significant differences between PCC and COVID-19 convalescents compared to UHC were observed in T helper cells and class-switched B cells. However, we did not detect specific or long-lasting immune cellular changes in PCC compared to the non-post-COVID-19 condition. Full article
(This article belongs to the Topic Post COVID-19: Latest Advances, Challenges and Methodologies)
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16 pages, 7286 KiB  
Article
Glaucoma Detection through a Novel Hyperspectral Imaging Band Selection and Vision Transformer Integration
by Ching-Yu Wang, Hong-Thai Nguyen, Wen-Shuang Fan, Jiann-Hwa Lue, Penchun Saenprasarn, Meei-Maan Chen, Shuan-Yu Huang, Fen-Chi Lin and Hsiang-Chen Wang
Diagnostics 2024, 14(12), 1285; https://0-doi-org.brum.beds.ac.uk/10.3390/diagnostics14121285 - 18 Jun 2024
Abstract
Conventional diagnostic methods for glaucoma primarily rely on non-dynamic fundus images and often analyze features such as the optic cup-to-disc ratio and abnormalities in specific retinal locations like the macula and fovea. However, hyperspectral imaging techniques focus on detecting alterations in oxygen saturation [...] Read more.
Conventional diagnostic methods for glaucoma primarily rely on non-dynamic fundus images and often analyze features such as the optic cup-to-disc ratio and abnormalities in specific retinal locations like the macula and fovea. However, hyperspectral imaging techniques focus on detecting alterations in oxygen saturation within retinal vessels, offering a potentially more comprehensive approach to diagnosis. This study explores the diagnostic potential of hyperspectral imaging for glaucoma by introducing a novel hyperspectral imaging conversion technique. Digital fundus images are transformed into hyperspectral representations, allowing for a detailed analysis of spectral variations. Spectral regions exhibiting differences are identified through spectral analysis, and images are reconstructed from these specific regions. The Vision Transformer (ViT) algorithm is then employed for classification and comparison across selected spectral bands. Fundus images are used to identify differences in lesions, utilizing a dataset of 1291 images. This study evaluates the classification performance of models using various spectral bands, revealing that the 610–780 nm band outperforms others with an accuracy, precision, recall, F1-score, and AUC-ROC all approximately at 0.9007, indicating its superior effectiveness for the task. The RGB model also shows strong performance, while other bands exhibit lower recall and overall metrics. This research highlights the disparities between machine learning algorithms and traditional clinical approaches in fundus image analysis. The findings suggest that hyperspectral imaging, coupled with advanced computational techniques such as the ViT algorithm, could significantly enhance glaucoma diagnosis. This understanding offers insights into the potential transformation of glaucoma diagnostics through the integration of hyperspectral imaging and innovative computational methodologies. Full article
(This article belongs to the Special Issue Artificial Intelligence in Eye Disease—3rd Edition)
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16 pages, 4238 KiB  
Article
A Machine Learning Model for the Prediction of COVID-19 Severity Using RNA-Seq, Clinical, and Co-Morbidity Data
by Sahil Sethi, Sushil Shakyawar, Athreya S. Reddy, Jai Chand Patel and Chittibabu Guda
Diagnostics 2024, 14(12), 1284; https://0-doi-org.brum.beds.ac.uk/10.3390/diagnostics14121284 - 18 Jun 2024
Abstract
The premise for this study emanated from the need to understand SARS-CoV-2 infections at the molecular level and to develop predictive tools for managing COVID-19 severity. With the varied clinical outcomes observed among infected individuals, creating a reliable machine learning (ML) model for [...] Read more.
The premise for this study emanated from the need to understand SARS-CoV-2 infections at the molecular level and to develop predictive tools for managing COVID-19 severity. With the varied clinical outcomes observed among infected individuals, creating a reliable machine learning (ML) model for predicting the severity of COVID-19 became paramount. Despite the availability of large-scale genomic and clinical data, previous studies have not effectively utilized multi-modality data for disease severity prediction using data-driven approaches. Our primary goal is to predict COVID-19 severity using a machine-learning model trained on a combination of patients’ gene expression, clinical features, and co-morbidity data. Employing various ML algorithms, including Logistic Regression (LR), XGBoost (XG), Naïve Bayes (NB), and Support Vector Machine (SVM), alongside feature selection methods, we sought to identify the best-performing model for disease severity prediction. The results highlighted XG as the superior classifier, with 95% accuracy and a 0.99 AUC (Area Under the Curve), for distinguishing severity groups. Additionally, the SHAP analysis revealed vital features contributing to prediction, including several genes such as COX14, LAMB2, DOLK, SDCBP2, RHBDL1, and IER3-AS1. Notably, two clinical features, the absolute neutrophil count and Viremia Categories, emerged as top contributors. Integrating multiple data modalities has significantly improved the accuracy of disease severity prediction compared to using any single modality. The identified features could serve as biomarkers for COVID-19 prognosis and patient care, allowing clinicians to optimize treatment strategies and refine clinical decision-making processes for enhanced patient outcomes. Full article
(This article belongs to the Special Issue Artificial Intelligence in Clinical Decision Support)
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11 pages, 1238 KiB  
Article
Diagnostic Performance of Plasma SP-D, KL-6, and CC16 in Acutely Hospitalised Patients Suspected of Having Community-Acquired Pneumonia—A Diagnostic Accuracy Study
by Anne Heltborg, Christian B. Mogensen, Eline S. Andersen, Mariana B. Cartuliares, Eva R. B. Petersen, Thor A. Skovsted, Stefan Posth, Ole Graumann, Morten J. Lorentzen, Mathias A. Hertz, Claus L. Brasen and Helene Skjøt-Arkil
Diagnostics 2024, 14(12), 1283; https://0-doi-org.brum.beds.ac.uk/10.3390/diagnostics14121283 - 17 Jun 2024
Abstract
Community-acquired pneumonia is a common cause of acute hospitalisation. Identifying patients with community-acquired pneumonia among patients suspected of having the disease can be a challenge, which causes unnecessary antibiotic treatment. We investigated whether the circulatory pulmonary injury markers surfactant protein D (SP-D), Krebs [...] Read more.
Community-acquired pneumonia is a common cause of acute hospitalisation. Identifying patients with community-acquired pneumonia among patients suspected of having the disease can be a challenge, which causes unnecessary antibiotic treatment. We investigated whether the circulatory pulmonary injury markers surfactant protein D (SP-D), Krebs von den Lungen-6 (KL-6), and Club cell protein 16 (CC16) could help identify patients with community-acquired pneumonia upon acute admission. In this multi-centre diagnostic accuracy study, SP-D, KL-6, and CC16 were quantified in plasma samples from acutely hospitalised patients with provisional diagnoses of community-acquired pneumonia. The area under the receiver operator characteristics curve (AUC) was calculated for each marker against the following outcomes: patients’ final diagnoses regarding community-acquired pneumonia assigned by an expert panel, and pneumonic findings on chest CTs. Plasma samples from 339 patients were analysed. The prevalence of community-acquired pneumonia was 63%. AUCs for each marker against both final diagnoses and chest CT diagnoses ranged between 0.50 and 0.56. Thus, SP-D, KL-6, and CC16 demonstrated poor diagnostic performance for community-acquired pneumonia in acutely hospitalised patients. Our findings indicate that the markers cannot readily assist physicians in confirming or ruling out community-acquired pneumonia. Full article
(This article belongs to the Special Issue Laboratory Diagnosis of Infectious Diseases)
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23 pages, 5580 KiB  
Hypothesis
Introducing a New Innovative Technique for the Recording and Interpretation of Dynamic Coronary Angiography
by Thach Nguyen, Khiem Ngo, Tri Loc Vu, Hien Q. Nguyen, Dat H. Pham, Mihas Kodenchery, Marco Zuin, Gianluca Rigatelli, Aravinda Nanjundappa and Michael Gibson
Diagnostics 2024, 14(12), 1282; https://0-doi-org.brum.beds.ac.uk/10.3390/diagnostics14121282 - 17 Jun 2024
Abstract
In the study of coronary artery disease (CAD), the mechanism of plaque formation and development is still an important subject for investigation. A limitation of current coronary angiography (CAG) is that it can only show static images of the narrowing of arterial channels [...] Read more.
In the study of coronary artery disease (CAD), the mechanism of plaque formation and development is still an important subject for investigation. A limitation of current coronary angiography (CAG) is that it can only show static images of the narrowing of arterial channels without identifying the mechanism of the disease or predicting its progression or regression. To address this limitation, the CAG technique has been modified. The new approach emphasizes identifying and analyzing blood flow patterns, employing methodologies akin to those used by hydraulic engineers for fluid or gas movement through domestic or industrial pipes and pumps. With the new technique, various flow patterns and arterial phenomena—such as laminar, turbulent, antegrade, retrograde, and recirculating flow and potentially water hammer shock and vortex formation—are identified, recorded, and classified. These phenomena are then correlated with the presence of lesions at different locations within the coronary vasculature. The formation and growth of these lesions are explained from the perspective of fluid mechanics. As the pathophysiology of CAD and other cardiovascular conditions becomes clearer, new medical, surgical, and interventional treatments could be developed to reverse abnormal coronary flow dynamics and restore laminar flow, leading to improved clinical outcomes. Full article
(This article belongs to the Special Issue Angiography: Diagnostic Imaging in Clinical Diseases)
25 pages, 1733 KiB  
Review
Deep Learning for Alzheimer’s Disease Prediction: A Comprehensive Review
by Isra Malik, Ahmed Iqbal, Yeong Hyeon Gu and Mugahed A. Al-antari
Diagnostics 2024, 14(12), 1281; https://0-doi-org.brum.beds.ac.uk/10.3390/diagnostics14121281 - 17 Jun 2024
Abstract
Alzheimer’s disease (AD) is a neurological disorder that significantly impairs cognitive function, leading to memory loss and eventually death. AD progresses through three stages: early stage, mild cognitive impairment (MCI) (middle stage), and dementia. Early diagnosis of Alzheimer’s disease is crucial and can [...] Read more.
Alzheimer’s disease (AD) is a neurological disorder that significantly impairs cognitive function, leading to memory loss and eventually death. AD progresses through three stages: early stage, mild cognitive impairment (MCI) (middle stage), and dementia. Early diagnosis of Alzheimer’s disease is crucial and can improve survival rates among patients. Traditional methods for diagnosing AD through regular checkups and manual examinations are challenging. Advances in computer-aided diagnosis systems (CADs) have led to the development of various artificial intelligence and deep learning-based methods for rapid AD detection. This survey aims to explore the different modalities, feature extraction methods, datasets, machine learning techniques, and validation methods used in AD detection. We reviewed 116 relevant papers from repositories including Elsevier (45), IEEE (25), Springer (19), Wiley (6), PLOS One (5), MDPI (3), World Scientific (3), Frontiers (3), PeerJ (2), Hindawi (2), IO Press (1), and other multiple sources (2). The review is presented in tables for ease of reference, allowing readers to quickly grasp the key findings of each study. Additionally, this review addresses the challenges in the current literature and emphasizes the importance of interpretability and explainability in understanding deep learning model predictions. The primary goal is to assess existing techniques for AD identification and highlight obstacles to guide future research. Full article
(This article belongs to the Special Issue Deep Learning in Medical and Biomedical Image Processing)
14 pages, 1740 KiB  
Article
The Impact of AI on Metal Artifacts in CBCT Oral Cavity Imaging
by Róża Wajer, Adrian Wajer, Natalia Kazimierczak, Justyna Wilamowska and Zbigniew Serafin
Diagnostics 2024, 14(12), 1280; https://0-doi-org.brum.beds.ac.uk/10.3390/diagnostics14121280 - 17 Jun 2024
Abstract
Objective: This study aimed to assess the impact of artificial intelligence (AI)-driven noise reduction algorithms on metal artifacts and image quality parameters in cone-beam computed tomography (CBCT) images of the oral cavity. Materials and Methods: This retrospective study included 70 patients, 61 of [...] Read more.
Objective: This study aimed to assess the impact of artificial intelligence (AI)-driven noise reduction algorithms on metal artifacts and image quality parameters in cone-beam computed tomography (CBCT) images of the oral cavity. Materials and Methods: This retrospective study included 70 patients, 61 of whom were analyzed after excluding those with severe motion artifacts. CBCT scans, performed using a Hyperion X9 PRO 13 × 10 CBCT machine, included images with dental implants, amalgam fillings, orthodontic appliances, root canal fillings, and crowns. Images were processed with the ClariCT.AI deep learning model (DLM) for noise reduction. Objective image quality was assessed using metrics such as the differentiation between voxel values (ΔVVs), the artifact index (AIx), and the contrast-to-noise ratio (CNR). Subjective assessments were performed by two experienced readers, who rated overall image quality and artifact intensity on predefined scales. Results: Compared with native images, DLM reconstructions significantly reduced the AIx and increased the CNR (p < 0.001), indicating improved image clarity and artifact reduction. Subjective assessments also favored DLM images, with higher ratings for overall image quality and lower artifact intensity (p < 0.001). However, the ΔVV values were similar between the native and DLM images, indicating that while the DLM reduced noise, it maintained the overall density distribution. Orthodontic appliances produced the most pronounced artifacts, while implants generated the least. Conclusions: AI-based noise reduction using ClariCT.AI significantly enhances CBCT image quality by reducing noise and metal artifacts, thereby improving diagnostic accuracy and treatment planning. Further research with larger, multicenter cohorts is recommended to validate these findings. Full article
(This article belongs to the Special Issue Advances in Oral and Maxillofacial Radiology)
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5 pages, 8233 KiB  
Case Report
Whole-Exome Sequencing Revealed a Pathogenic Germline Variant in the Fumarate Hydratase Gene, Leading to the Diagnosis of Hereditary Leiomyomatosis and Renal Cell Cancer
by Akari Nagashima, Sohshi Morimura, Toshihisa Hamada, Takayuki Shiomi, Ichiro Mori, Naoko Sato, Junko Nomoto, Masaki Tanaka, Shoji Tsuji and Makoto Sugaya
Diagnostics 2024, 14(12), 1279; https://0-doi-org.brum.beds.ac.uk/10.3390/diagnostics14121279 - 17 Jun 2024
Abstract
The diagnosis of hereditary skin tumors is difficult for “old” diagnostic tools such as immunohistochemistry. Whole-exome sequencing analysis as a “new” diagnostic tool enables us to make a final diagnosis in spite of unknown hereditary diseases in the past. Hereditary leiomyomatosis and renal [...] Read more.
The diagnosis of hereditary skin tumors is difficult for “old” diagnostic tools such as immunohistochemistry. Whole-exome sequencing analysis as a “new” diagnostic tool enables us to make a final diagnosis in spite of unknown hereditary diseases in the past. Hereditary leiomyomatosis and renal cell cancer are autosomal dominant hereditary cancer syndromes characterized by uterine myomas, cutaneous leiomyomas, and aggressive renal cell cancer. The syndrome is associated with pathogenic germline variants in the fumarate hydratase gene. Herein, we demonstrate a pathogenic germline variant of the fumarate hydratase gene in a 60-year-old woman with multiple cutaneous leiomyomas, leading to the diagnosis of hereditary leiomyomatosis and renal cell cancer. Whole-exome sequencing analysis using genomic DNA extracted from peripheral blood leukocytes revealed one germline variant in the FH gene on chromosome 1 (c.290G>A, p.Gly97Asp). She received total hysterectomy due to uterine myoma, which strongly supported the diagnosis. No tumor was detected in her kidney by computed tomography and ultrasound examination. Genetic examination for the mutation of the fumarate hydratase gene is important in order to reach the correct diagnosis and to detect renal cancer at its early stage. Full article
(This article belongs to the Special Issue Advances in Diagnosis of Skin and Superficial Tissues Disorders—“Old and Emerging” Diagnostic Tools)
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14 pages, 930 KiB  
Article
Non-Invasive Prediction of Choledocholithiasis Using 1D Convolutional Neural Networks and Clinical Data
by Enrique Mena-Camilo, Sebastián Salazar-Colores, Marco Antonio Aceves-Fernández, Edgard Efrén Lozada-Hernández and Juan Manuel Ramos-Arreguín
Diagnostics 2024, 14(12), 1278; https://0-doi-org.brum.beds.ac.uk/10.3390/diagnostics14121278 - 17 Jun 2024
Abstract
This paper introduces a novel one-dimensional convolutional neural network that utilizes clinical data to accurately detect choledocholithiasis, where gallstones obstruct the common bile duct. Swift and precise detection of this condition is critical to preventing severe complications, such as biliary colic, jaundice, and [...] Read more.
This paper introduces a novel one-dimensional convolutional neural network that utilizes clinical data to accurately detect choledocholithiasis, where gallstones obstruct the common bile duct. Swift and precise detection of this condition is critical to preventing severe complications, such as biliary colic, jaundice, and pancreatitis. This cutting-edge model was rigorously compared with other machine learning methods commonly used in similar problems, such as logistic regression, linear discriminant analysis, and a state-of-the-art random forest, using a dataset derived from endoscopic retrograde cholangiopancreatography scans performed at Olive View–University of California, Los Angeles Medical Center. The one-dimensional convolutional neural network model demonstrated exceptional performance, achieving 90.77% accuracy and 92.86% specificity, with an area under the curve of 0.9270. While the paper acknowledges potential areas for improvement, it emphasizes the effectiveness of the one-dimensional convolutional neural network architecture. The results suggest that this one-dimensional convolutional neural network approach could serve as a plausible alternative to endoscopic retrograde cholangiopancreatography, considering its disadvantages, such as the need for specialized equipment and skilled personnel and the risk of postoperative complications. The potential of the one-dimensional convolutional neural network model to significantly advance the clinical diagnosis of this gallstone-related condition is notable, offering a less invasive, potentially safer, and more accessible alternative. Full article
(This article belongs to the Special Issue Pathology of Hepatobiliary Diseases)
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11 pages, 2170 KiB  
Article
Morphological Characteristics of the Double Mental Foramen and Its Relevance in Clinical Practice: An Observational Study
by Alejandro Bruna-Mejias, Pablo Nova-Baeza, Florencia Torres-Riquelme, Maria Fernanda Delgado-Retamal, Mathias Orellana-Donoso, Alejandra Suazo-Santibañez, Walter Sepulveda-Loyola, Iván Valdés-Orrego, Juan Sanchis-Gimeno and Juan José Valenzuela-Fuenzalida
Diagnostics 2024, 14(12), 1277; https://0-doi-org.brum.beds.ac.uk/10.3390/diagnostics14121277 - 17 Jun 2024
Abstract
The mental foramen (MF) is an opening found bilaterally on the anterolateral aspect of the mandible; it can be round or oval and have different diameters. One of the anatomical variants of the jaw is the presence of an accessory mental foramen (AMF). [...] Read more.
The mental foramen (MF) is an opening found bilaterally on the anterolateral aspect of the mandible; it can be round or oval and have different diameters. One of the anatomical variants of the jaw is the presence of an accessory mental foramen (AMF). These are usually smaller than the MF and can be located above, below, or to the sides of the main MF. The objective of this study was to recognize the presence of AMF in dry jaws of the Chilean population and collect information about its clinical relevance reported in the literature. In this descriptive observational study, we have collected dried jaws obtained from three higher education institutions in Santiago de Chile, from the Department of Morphology of the Andrés Bello University, the Normal Human Anatomy Unit of the University of Santiago, and the Human Anatomy pavilion from the Faculty of Medicine of the Finis Terrae University. The samples for this research were obtained by convenience, and the observation of the jaws was carried out in the human anatomy laboratories of each institution by three evaluators independently, and a fourth evaluator was included to validate that each evaluation was correct. The sample for this research came from 260 dry jaws, showing the following findings from the total jaws studied, and to classify as an accessory MF, it will be examined and measured so that it complies with what is declared in the literature as the presence of AMF, which is between 0.74 mm. and 0.89 mm. There were 17 studies included with a sample that fluctuated between 1 and 4000, with a cumulative total of 7946 and an average number of jaws analyzed from the studies of 467.4, showing statistically significant differences between the means with the sample analyzed in this study; p = 0.095. For the cumulative prevalence of the presence of AMF, this was 3.07 in this study, and in the compared studies, the average of AMF was 8.01%, which did not present a statistically significant difference; p = 0.158. Regarding the presence of variants of unilateral AMF, this occurred in five jaws, which is equivalent to 1.84% in the sample of this study, while in previous studies, it was 7.5%, being higher on the left side than on the right. The presence of AMF is a variant with high prevalence if we compare it with other variants of the jaw. Knowledge of the anatomy and position of the AMF is crucial to analyze different scenarios in the face of surgical procedures or conservative treatments of the lower anterior dental region. Full article
(This article belongs to the Special Issue Head and Neck Surgery: Diagnosis and Management)
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11 pages, 551 KiB  
Article
Anxiety and Mood Disruption in Collegiate Athletes Acutely Following Mild Traumatic Brain Injury
by Rachel Zhang, Michael Martyna, Jordan Cornwell, Masaru Teramoto, Mollie Selfridge, Amanda Brown, Jamshid Ghajar and Angela Lumba-Brown
Diagnostics 2024, 14(12), 1276; https://0-doi-org.brum.beds.ac.uk/10.3390/diagnostics14121276 - 17 Jun 2024
Abstract
Objective: To report the symptom burden of anxiety and mood-related indicators following mTBI in collegiate student-athletes. Study Design: Retrospective cohort study of varsity collegiate athletes. Setting: University sports medicine at a tertiary care center. Patients: Division I college varsity athletes diagnosed with mTBI [...] Read more.
Objective: To report the symptom burden of anxiety and mood-related indicators following mTBI in collegiate student-athletes. Study Design: Retrospective cohort study of varsity collegiate athletes. Setting: University sports medicine at a tertiary care center. Patients: Division I college varsity athletes diagnosed with mTBI at a single institution between 2016 and 2019. Independent Variables: Pre- and post-injury. Main Outcome Measures: Comparisons between baseline testing and post-mTBI symptom scale assessments were made to determine changes in scores at the individual and group levels. The primary outcome was the prevalence of post-mTBI symptoms from within 72 h of injury through return to play. Associations with sport, sex, age, and return-to-play time were included. Results: Compared to baseline, mood and anxiety symptom scores were significantly higher acutely following mTBI (2.1 ± 3.3 vs. 14.3 ± 12.2; p < 0.001). A family history of migraine was significantly associated with higher mood and anxiety symptom scores (20.0 ± 14.9 with history vs. 13.3 ± 11.3 without history; p = 0.042). Mood and anxiety symptom scores were highly correlated with non-mood and anxiety symptom scores for all athletes, including the subgroup with prolonged symptoms (r = 0.769; p < 0.001). Conclusions: Symptoms of anxiety or mood disruption are common during the acute period post-injury in varsity college athletes. Risk factors for higher symptom reports immediately following mTBI and for prolonged symptoms (>10 days) included female sex, those with a family history of migraine, and those with an overall higher symptom burden post-injury. Full article
(This article belongs to the Special Issue The Assessment, Diagnosis, and Management of Sport-Related Concussion in Childhood and Adolescence)
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14 pages, 406 KiB  
Article
Topographic and Surgical Risk Factors for Early Myopic Regression between Small Incision Lenticule Extraction and Laser In Situ Keratomileusis
by Chia-Yi Lee, Yu-Ting Jeng, Shun-Fa Yang, Chin-Te Huang, Chen-Cheng Chao, Ie-Bin Lian, Jing-Yang Huang and Chao-Kai Chang
Diagnostics 2024, 14(12), 1275; https://0-doi-org.brum.beds.ac.uk/10.3390/diagnostics14121275 - 17 Jun 2024
Viewed by 118
Abstract
Our objective was to evaluate the topographic and surgical factors of early myopic regression between laser in situ keratomileusis (LASIK) and small-incision lenticule extraction (SMILE). A retrospective case–control study was conducted, and 368 and 92 eyes were enrolled in the LASIK and SMILE [...] Read more.
Our objective was to evaluate the topographic and surgical factors of early myopic regression between laser in situ keratomileusis (LASIK) and small-incision lenticule extraction (SMILE). A retrospective case–control study was conducted, and 368 and 92 eyes were enrolled in the LASIK and SMILE groups via propensity score matching (PSM). Visual acuity, refractive status, axial length, and topographic/surgical parameters were collected. Multiple linear regression was applied to the yield coefficient and the 95% confidence interval (CI) of the parameters. The cumulative incidence of early myopic regression was higher in the LASIK group (p < 0.001). In the SMILE group, a lower central corneal thickness (CCT) thinnest value and a higher corneal cylinder associated with early myopic regression were observed; meanwhile, in the LASIK group, a lower CCT thinnest value, a higher steep corneal curvature, a larger optic zone, and a lower flap thickness related to early myopic regression were observed (all p < 0.05). In the SMILE group, a higher CCT difference correlated with early myopic regression was observed compared to the LASIK group (p = 0.030), and higher steep corneal curvature and lower cap/flap thickness (both p < 0.05) correlated with early myopic regression were observed in the LASIK group compared to the SMILE group. In conclusion, CCT differences significantly influence early myopic regression in the SMILE group; meanwhile, corneal curvature and flap thickness affect early myopic regression principally in the LASIK group. Full article
(This article belongs to the Special Issue New Perspectives in Diagnosis and Management of Eye Diseases)
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11 pages, 770 KiB  
Article
Inoculum Size and False-Positive Detection of NDM- and OXA-48-Type Carbapenemases Using Two Multiplex Lateral Flow Assays
by Chung-Ho Lee, Huiluo Cao, Shuo Jiang, Tammy Ting-Yan Wong, Cindy Wing-Sze Tse and Pak-Leung Ho
Diagnostics 2024, 14(12), 1274; https://0-doi-org.brum.beds.ac.uk/10.3390/diagnostics14121274 - 17 Jun 2024
Viewed by 121
Abstract
The NG-Test CARBA 5 and Carbapenem-resistant K.N.I.V.O. Detection K-Set are lateral flow assays (LFAs) that rapidly detect five carbapenemases (KPC, NDM, IMP, VIM and OXA-48-like). We evaluated the effect of inoculum size on the performance of these two assays using 27 Enterobacterales isolates. [...] Read more.
The NG-Test CARBA 5 and Carbapenem-resistant K.N.I.V.O. Detection K-Set are lateral flow assays (LFAs) that rapidly detect five carbapenemases (KPC, NDM, IMP, VIM and OXA-48-like). We evaluated the effect of inoculum size on the performance of these two assays using 27 Enterobacterales isolates. Whole-genome sequencing (WGS) was used as the reference method. Using the NG-Test CARBA 5, eight Serratia spp. and six M. morganii isolates showed false-positive NDM results with a high inoculum. Using the Carbapenem-resistant K.N.I.V.O. Detection K-Set, eight M. morganii, four Serratia spp. and one K. pneumoniae isolates showed false-positive NDM and/or OXA-48-like bands at large inoculum sizes, while the other two M. morganii isolates demonstrated false-positive NDM and OXA-48-like results at all inoculum sizes. The false-positive bands varied in intensity. WGS confirmed that no carbapenemase gene was present. No protein sequence with a ≥50% identity to NDM or OXA-48-like enzymes was found. This study emphasizes the importance of assessing inoculum size in the diagnostic evaluation of LFAs. Full article
(This article belongs to the Section Point-of-Care Diagnostics and Devices)
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14 pages, 1835 KiB  
Article
Early Detection of Inflammation and Malnutrition and Prediction of Acute Events in Hemodialysis Patients through PINI (Prognostic Inflammatory and Nutritional Index)
by Monica Cordos, Maria-Alexandra Martu, Cristiana-Elena Vlad, Vasilica Toma, Alin Dumitru Ciubotaru, Minerva Codruta Badescu, Ancuta Goriuc and Liliana Foia
Diagnostics 2024, 14(12), 1273; https://0-doi-org.brum.beds.ac.uk/10.3390/diagnostics14121273 - 17 Jun 2024
Viewed by 172
Abstract
Protein-energy wasting and inflammation are major risk factors for complications in hemodialysis patients. As these risk factors are triggered by a pro-inflammatory state, oxidative stress and hemodynamic dysfunction, which overlap in hemodialyzed subjects, we aimed to assess the efficacy of a cost-effective and [...] Read more.
Protein-energy wasting and inflammation are major risk factors for complications in hemodialysis patients. As these risk factors are triggered by a pro-inflammatory state, oxidative stress and hemodynamic dysfunction, which overlap in hemodialyzed subjects, we aimed to assess the efficacy of a cost-effective and straightforward screening tool, the Prognostic Inflammatory and Nutritional Index (PINI), in regularly screening maintenance hemodialysis (MHD) patients, to detect early signs of inflammation and malnutrition. A 12-month follow-up was carried out on a cohort of 102 adult patients undergoing maintenance dialysis, during which the Prognostic Inflammatory and Nutritional Index (PINI) was calculated using the formula alpha1-Acid Glycoprotein (AGP) × C-reactive protein (CRP)/albumin (ALB) × transthyretin (TTR). A PINI score < 1 was considered normal. The patients were stratified based on their PINI score: 66 patients (64.70%) had a normal score, below 1, while 36 patients (35.30%) had a PINI score ≥ 1. Despite the absence of clinical evidence of inflammation at enrollment, the latter group exhibited higher levels of CRP. During the follow-up period, all patients with a PINI score ≥ 1 experienced at least one acute event, compared to only 6% of patients with a normal PINI score, which presented COVID-19 infection as an acute event. The evaluation of the PINI can effectively identify the silent malnutrition–inflammation syndrome and predict the risk of acute events. This straightforward test appears to be a rapid tool that is independent of the examiner’s experience and subjectivity, thereby potentially reducing hospitalization costs. Full article
(This article belongs to the Special Issue Signatures Underlying Inflammation in the Pathogenesis and Evolution of Chronic Diseases)
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7 pages, 1122 KiB  
Case Report
A Case of Refractory Vernal Keratoconjunctivitis Showing Improvement after the Administration of Upadacitinib for the Treatment of Atopic Dermatitis
by Yoshihito Mima, Eri Tsutsumi, Tsutomu Ohtsuka, Ippei Ebato, Yukihiro Nakata, Taro Kubota and Yuta Norimatsu
Diagnostics 2024, 14(12), 1272; https://0-doi-org.brum.beds.ac.uk/10.3390/diagnostics14121272 - 17 Jun 2024
Viewed by 169
Abstract
Vernal keratoconjunctivitis is a persistent allergic ocular disease predominantly mediated by the T-helper 2 lymphocyte-associated immune response. The standard therapeutic approaches for vernal keratoconjunctivitis include topical corticosteroids and immunosuppressive eye drops. However, managing vernal keratoconjunctivitis with only topical treatments becomes challenging during seasonally [...] Read more.
Vernal keratoconjunctivitis is a persistent allergic ocular disease predominantly mediated by the T-helper 2 lymphocyte-associated immune response. The standard therapeutic approaches for vernal keratoconjunctivitis include topical corticosteroids and immunosuppressive eye drops. However, managing vernal keratoconjunctivitis with only topical treatments becomes challenging during seasonally exacerbated periods. Systemic treatments such as oral corticosteroids or cyclosporine may be alternative options. Recently, dupilumab’s efficacy in refractory vernal keratoconjunctivitis treatment has been documented. Here, we report a case of refractory vernal keratoconjunctivitis coexisting with atopic dermatitis that rapidly improved after upadacitinib administration. An 18-year-old Japanese woman presented with atopic dermatitis, vernal keratoconjunctivitis, and hay fever. In winter, the patient experienced widespread erythema and escalated itching, leading to significant discomfort and insomnia. Owing to the difficulty in maintaining her current regimen, upadacitinib (15 mg), a Janus kinase inhibitor was initiated. After upadacitinib administration, the treatment-resistant vernal keratoconjunctivitis and erythema improved. Upadacitinib is beneficial in severe cases of atopic dermatitis. Consequently, in our case, upadacitinib may offer therapeutic benefits for refractory vernal conjunctivitis by improving the T-helper 1/2 type immune response, autoimmunity, and oxidative stress. To our knowledge, this is the first report suggesting the potential utility of upadacitinib in managing severe vernal conjunctivitis. Full article
(This article belongs to the Special Issue Eye Diseases: Diagnosis and Management—Volume 2)
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17 pages, 10539 KiB  
Review
Uterine Tumor Resembling Ovarian Sex-Cord Tumor (UTROSCT): A Rare Polyphenotypic Neoplasm
by Giovanna Giordano, Debora Guareschi and Elena Thai
Diagnostics 2024, 14(12), 1271; https://0-doi-org.brum.beds.ac.uk/10.3390/diagnostics14121271 - 17 Jun 2024
Viewed by 200
Abstract
Uterine tumor resembling ovarian sex-cord tumor (UTROSCT) is a rare form of uterine mesenchymal neoplasm. Although UTROSCT generally exhibits benign behavior with a favorable prognosis, this neoplasm is nevertheless classified as being of uncertain malignant potential, given its low rate of recurrence and [...] Read more.
Uterine tumor resembling ovarian sex-cord tumor (UTROSCT) is a rare form of uterine mesenchymal neoplasm. Although UTROSCT generally exhibits benign behavior with a favorable prognosis, this neoplasm is nevertheless classified as being of uncertain malignant potential, given its low rate of recurrence and the fact that it rarely produces metastases (e.g., in the lymph nodes, epiploic appendix, omentum, small bowel, subcutaneous tissue, lungs). Its histogenesis is also uncertain. Typically, UTROSCT occurs in peri-menopausal or menopausal women, but it can sometimes be observed in young women. Usually, this neoplasm can be found in the uterine corpus as a nodular intramural lesion, while it is less frequently submucosal, subserosal, or polypoid/intracavitary. UTROSCT can cause abnormal bleeding, pelvic pain, enlarged uterus, and mass sensation, but sometimes it is found purely by chance. This neoplasm can be considered polyphenotypic on morphological, immunohistochemical, and genetic analyses. Generally, upon microscopic examination, UTROSCT shows a predominant pattern of the cords, nests, and trabeculae typical of sex-cord tumors of the ovary, while immunohistochemically it is characterized by a coexpression of epithelial, smooth muscle, and sex-cord markers. The aim of this review is to report clinical and pathological data and genetic alterations to establish their impact on the prognosis and management of patients affected by this rare entity. Full article
(This article belongs to the Special Issue Diagnosis and Management of Uterine Lesions)
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16 pages, 4225 KiB  
Review
Left Ventricular Papillary Muscle: Anatomy, Pathophysiology, and Multimodal Evaluation
by Shiying Li, Zhen Wang, Wenpei Fu, Fangya Li, Hui Gu, Nan Cui, Yixia Lin, Mingxing Xie and Yali Yang
Diagnostics 2024, 14(12), 1270; https://0-doi-org.brum.beds.ac.uk/10.3390/diagnostics14121270 - 16 Jun 2024
Viewed by 218
Abstract
As an integral part of the mitral valve apparatus, the left ventricle papillary muscle (PM) controls mitral valve closure during systole and participates in the ejection process during left ventricular systole. Mitral regurgitation (MR) is the most immediate and predominant result when the [...] Read more.
As an integral part of the mitral valve apparatus, the left ventricle papillary muscle (PM) controls mitral valve closure during systole and participates in the ejection process during left ventricular systole. Mitral regurgitation (MR) is the most immediate and predominant result when the PM is structurally or functionally abnormal. However, dysfunction of the PM is easily underestimated or overlooked in clinical interventions for MR-related diseases. Therefore, adequate recognition of PM dysfunction and PM-derived MR is critical. In this review, we systematically describe the normal anatomical variations in the PM and the pathophysiology of PM dysfunction-related diseases and summarize the commonly used parameters and the advantages and disadvantages of various noninvasive imaging modalities for the structural and functional assessment of the PM. Full article
(This article belongs to the Section Medical Imaging and Theranostics)
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19 pages, 10228 KiB  
Article
Community-Based View on Diagnostic Imaging at the End of COVID-19 Pandemic: Online Survey-Assisted Study
by Nina D. Anfinogenova, Aleksandra S. Maksimova, Tatiana A. Shelkovnikova, Nadezhda I. Ryumshina, Alina D. Kuznetsova, Nazary P. Chesalov, Rostislav S. Karpov, Wladimir Y. Ussov and Alexey N. Repin
Diagnostics 2024, 14(12), 1269; https://doi.org/10.3390/diagnostics14121269 - 15 Jun 2024
Viewed by 380
Abstract
(1) Background: An online survey-based observational cross-sectional study aimed at elucidating the experience and attitudes of an unstructured population regarding diagnostic imaging. (2) Methods: Invitations to participate were distributed using mixed-mode design to deidentified residents aged 18 years and older. Main outcome measures [...] Read more.
(1) Background: An online survey-based observational cross-sectional study aimed at elucidating the experience and attitudes of an unstructured population regarding diagnostic imaging. (2) Methods: Invitations to participate were distributed using mixed-mode design to deidentified residents aged 18 years and older. Main outcome measures included morbidity structure and incidence of diagnostic imaging administrations. (3) Results: Respondents (n = 1069) aged 44.3 ± 14.4 years; 32.8% suffered from cardiovascular diseases (CVD); 9.5% had chronic respiratory pathology; 28.9% considered themselves healthy. Respondents with COVID-19 history (49.7%) reported higher rates of computed tomography (CT) (p < 0.0001), magnetic resonance imaging (MRI) (p < 0.001), and ultrasound (p < 0.05). COVID-19 history in CVD respondents shifted imaging administrations towards CT and MRI (p < 0.05). Every tenth respondent received MRI, CT, and ultrasound on a paid basis; 29.0% could not pay for diagnostic procedures; 13.1% reported unavailable MRI. Professional status significantly affected the pattern of diagnostic modalities (p < 0.05). MRI and CT availability differed between respondents in urban and rural areas (p < 0.0001). History of technogenic events predisposed responders to overestimate diagnostic value of fluorography (p < 0.05). (4) Conclusions: Preparedness to future pandemics requires the development of community-based outreach programs focusing on people’s awareness regarding medical imaging safety and diagnostic value. Full article
(This article belongs to the Special Issue AI and Big Data in Healthcare)
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24 pages, 2359 KiB  
Article
Predicting Tumor Dynamics Post-Staged GKRS: Machine Learning Models in Brain Metastases Prognosis
by Ana-Maria Trofin, Călin Gh. Buzea, Răzvan Buga, Maricel Agop, Lăcrămioara Ochiuz, Dragos Teodor Iancu and Lucian Eva
Diagnostics 2024, 14(12), 1268; https://0-doi-org.brum.beds.ac.uk/10.3390/diagnostics14121268 - 15 Jun 2024
Viewed by 146
Abstract
This study assesses the predictive performance of six machine learning models and a 1D Convolutional Neural Network (CNN) in forecasting tumor dynamics within three months following Gamma Knife radiosurgery (GKRS) in 77 brain metastasis (BM) patients. The analysis meticulously evaluates each model before [...] Read more.
This study assesses the predictive performance of six machine learning models and a 1D Convolutional Neural Network (CNN) in forecasting tumor dynamics within three months following Gamma Knife radiosurgery (GKRS) in 77 brain metastasis (BM) patients. The analysis meticulously evaluates each model before and after hyperparameter tuning, utilizing accuracy, AUC, and other metrics derived from confusion matrices. The CNN model showcased notable performance with an accuracy of 98% and an AUC of 0.97, effectively complementing the broader model analysis. Initial findings highlighted that XGBoost significantly outperformed other models with an accuracy of 0.95 and an AUC of 0.95 before tuning. Post-tuning, the Support Vector Machine (SVM) demonstrated the most substantial improvement, achieving an accuracy of 0.98 and an AUC of 0.98. Conversely, XGBoost showed a decline in performance after tuning, indicating potential overfitting. The study also explores feature importance across models, noting that features like “control at one year”, “age of the patient”, and “beam-on time for volume V1 treated” were consistently influential across various models, albeit their impacts were interpreted differently depending on the model’s underlying mechanics. This comprehensive evaluation not only underscores the importance of model selection and hyperparameter tuning but also highlights the practical implications in medical diagnostic scenarios, where the accuracy of positive predictions can be crucial. Our research explores the effects of staged Gamma Knife radiosurgery (GKRS) on larger tumors, revealing no significant outcome differences across protocols. It uniquely considers the impact of beam-on time and fraction intervals on treatment efficacy. However, the investigation is limited by a small patient cohort and data from a single institution, suggesting the need for future multicenter research. Full article
(This article belongs to the Special Issue Lesion Detection and Analysis Using Artificial Intelligence—2nd Edition)
15 pages, 2546 KiB  
Article
CT Angiography-Guided Needle Insertion for Interstitial Brachytherapy in Locally Advanced Cervical Cancer
by Alexandra Timea Kirsch-Mangu, Diana Cristina Pop, Alexandru Tipcu, Alexandra Ioana Andries, Gina Iulia Pasca, Zsolt Fekete, Andrei Roman, Alexandru Irimie and Claudia Ordeanu
Diagnostics 2024, 14(12), 1267; https://0-doi-org.brum.beds.ac.uk/10.3390/diagnostics14121267 - 15 Jun 2024
Viewed by 223
Abstract
CT angiography might be a suitable procedure to avoid arterial puncture in combined intracavitary and interstitial brachytherapy for cervical cancer curatively treated with combined chemoradiation and brachytherapy boost. Data in the literature about this technique are scarce. We introduced this method and collected [...] Read more.
CT angiography might be a suitable procedure to avoid arterial puncture in combined intracavitary and interstitial brachytherapy for cervical cancer curatively treated with combined chemoradiation and brachytherapy boost. Data in the literature about this technique are scarce. We introduced this method and collected brachytherapy data from patients treated in our department between May 2021 and April 2024. We analyzed the applicator subtype, needle insertion (planned versus implanted), implanted depth and the role of CT angiography in selecting needle trajectories and insertion depths. None of the patients managed through this protocol experienced atrial puncture and consequent hemorrhage. Needle positions were accurately selected with the aid of CT angiography with proper coverage of brachytherapy targets and avoidance of organs at risk. CT angiography is a promising method for guiding needle insertion during interstitial brachytherapy. Full article
(This article belongs to the Special Issue Imaging for the Diagnosis of Obstetric and Gynecological Diseases)
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13 pages, 585 KiB  
Article
Side- and Sinus-Specific Relationships between Chronic Rhinosinusitis and Ischemic Stroke Using Imaging Analyses
by Eun Hyun Cho, Kyung Hoon Park, Ji Hee Kim, Heejin Kim, Hyo-Jeong Lee and Jee Hye Wee
Diagnostics 2024, 14(12), 1266; https://0-doi-org.brum.beds.ac.uk/10.3390/diagnostics14121266 - 15 Jun 2024
Viewed by 224
Abstract
Recent studies have reported chronic rhinosinusitis (CRS) as an independent risk factor for stroke. However, the association with stroke depending on the affected sinuses has not been explored. This study aimed to elucidate the side- and sinus-specific relationship between CRS and ischemic stroke [...] Read more.
Recent studies have reported chronic rhinosinusitis (CRS) as an independent risk factor for stroke. However, the association with stroke depending on the affected sinuses has not been explored. This study aimed to elucidate the side- and sinus-specific relationship between CRS and ischemic stroke through imaging analyses. We retrospectively reviewed the medical records of patients who were diagnosed with ischemic stroke at a tertiary center. CRS was defined as having a total score of greater than or equal to 4, according to the Lund–Mackay scoring system, through brain magnetic resonance imaging or computed tomography. We investigated the side- and sinus-specific correlation between CRS and ischemic stroke. Subgroup analyses were performed for different age groups. CRS prevalence in patients with ischemic stroke was 18.4%, which was higher than the previously reported prevalence in the general population. Overall, there was no correlation between the directions of the CRS and ischemic stroke (p > 0.05). When each sinus was analyzed, the frontal (Cramer’s V = 0.479, p < 0.001), anterior (Cramer’s V = 0.396, p < 0.001)/posterior (Cramer’s V = 0.300, p = 0.008) ethmoid, and sphenoid (Cramer’s V = 0.383, p = 0.005) sinuses showed a statistically significant correlation with the side of stroke, but the maxillary sinus (Cramer’s V = 0.138, p = 0.208) did not. In subgroup analyses, a significant right-side correlation between the two diseases was observed in the older-age subgroup (≥65 years old, Cramer’s V = 0.142, p = 0.040). Diabetes mellitus (odds ratio = 1.596, 95% confidence interval = 1.204–2.116) was identified as an independent risk factor for having CRS in patients with ischemic stroke. CRS of the frontal, anterior/posterior ethmoid, and sphenoid sinuses has a directional relationship with ischemic stroke. Our results on which sinuses correlate with stroke advocate for the active surveillance of CRS in patients at high risk of ischemic stroke. Full article
(This article belongs to the Special Issue Advances in Diagnosis and Treatment in Otolaryngology)
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6 pages, 181 KiB  
Editorial
Advancements in Artificial Intelligence for Medical Computer-Aided Diagnosis
by Mugahed A. Al-antari
Diagnostics 2024, 14(12), 1265; https://0-doi-org.brum.beds.ac.uk/10.3390/diagnostics14121265 - 15 Jun 2024
Viewed by 219
Abstract
Rapid advancements in artificial intelligence (AI) and machine learning (ML) are currently transforming the field of diagnostics, enabling unprecedented accuracy and efficiency in disease detection, classification, and treatment planning. This Special Issue, entitled “Artificial Intelligence Advances for Medical Computer-Aided Diagnosis”, presents a curated [...] Read more.
Rapid advancements in artificial intelligence (AI) and machine learning (ML) are currently transforming the field of diagnostics, enabling unprecedented accuracy and efficiency in disease detection, classification, and treatment planning. This Special Issue, entitled “Artificial Intelligence Advances for Medical Computer-Aided Diagnosis”, presents a curated collection of cutting-edge research that explores the integration of AI and ML technologies into various diagnostic modalities. The contributions presented here highlight innovative algorithms, models, and applications that pave the way for improved diagnostic capabilities across a range of medical fields, including radiology, pathology, genomics, and personalized medicine. By showcasing both theoretical advancements and practical implementations, this Special Issue aims to provide a comprehensive overview of current trends and future directions in AI-driven diagnostics, fostering further research and collaboration in this dynamic and impactful area of healthcare. We have published a total of 12 research articles in this Special Issue, all collected between March 2023 and December 2023, comprising 1 Editorial cover letter, 9 regular research articles, 1 review article, and 1 article categorized as “other”. Full article
(This article belongs to the Special Issue Artificial Intelligence Advances for Medical Computer-Aided Diagnosis)
11 pages, 4795 KiB  
Article
ML Models Built Using Clinical Parameters and Radiomic Features Extracted from 18F-Choline PET/CT for the Prediction of Biochemical Recurrence after Metastasis-Directed Therapy in Patients with Oligometastatic Prostate Cancer
by Luca Urso, Corrado Cittanti, Luigi Manco, Naima Ortolan, Francesca Borgia, Antonio Malorgio, Giovanni Scribano, Edoardo Mastella, Massimo Guidoboni, Antonio Stefanelli, Alessandro Turra and Mirco Bartolomei
Diagnostics 2024, 14(12), 1264; https://0-doi-org.brum.beds.ac.uk/10.3390/diagnostics14121264 - 15 Jun 2024
Viewed by 238
Abstract
Oligometastatic patients at [18F]F-Fluorocholine (18F-choline) PET/CT may be treated with metastasis-directed therapy (MDT). The aim of this study was to combine radiomic parameters extracted from 18F-choline PET/CT and clinical data to build machine learning (ML) models able to [...] Read more.
Oligometastatic patients at [18F]F-Fluorocholine (18F-choline) PET/CT may be treated with metastasis-directed therapy (MDT). The aim of this study was to combine radiomic parameters extracted from 18F-choline PET/CT and clinical data to build machine learning (ML) models able to predict MDT efficacy. Methods: Oligorecurrent patients (≤5 lesions) at 18F-choline PET/CT and treated with MDT were collected. A per-patient and per-lesion analysis was performed, using 2-year biochemical recurrence (BCR) after MDT as the standard of reference. Clinical parameters and radiomic features (RFts) extracted from 18F-choline PET/CT were used for training five ML Models for both CT and PET images. The performance metrics were calculated (i.e., Area Under the Curve—AUC; Classification Accuracy—CA). Results: A total of 46 metastases were selected and segmented in 29 patients. BCR after MDT occurred in 20 (69%) patients after 2 years of follow-up. In total, 73 and 33 robust RFTs were selected from CT and PET datasets, respectively. PET ML Models showed better performances than CT Models for discriminating BCR after MDT, with Stochastic Gradient Descent (SGD) being the best model (AUC = 0.95; CA = 0.90). Conclusion: ML Models built using clinical parameters and CT and PET RFts extracted via 18F-choline PET/CT can accurately predict BCR after MDT in oligorecurrent PCa patients. If validated externally, ML Models could improve the selection of oligorecurrent PCa patients for treatment with MDT. Full article
(This article belongs to the Special Issue Artificial Intelligence in Clinical Medical Imaging: Volume 2)
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13 pages, 2848 KiB  
Article
Deep Learning-Based Prediction Model for the Cobb Angle in Adolescent Idiopathic Scoliosis Patients
by Chun-Sing (Elvis) Chui, Zhong He, Tsz-Ping Lam, Ka-Kwan (Kyle) Mak, Hin-Ting (Randy) Ng, Chun-Hai (Ericsson) Fung, Mei-Shuen Chan, Sheung-Wai Law, Yuk-Wai (Wayne) Lee, Lik-Hang (Alec) Hung, Chiu-Wing (Winnie) Chu, Sze-Yi (Sibyl) Mak, Wing-Fung (Edmond) Yau, Zhen Liu, Wu-Jun Li, Zezhang Zhu, Man Yeung (Ronald) Wong, Chun-Yiu (Jack) Cheng, Yong Qiu and Shu-Hang (Patrick) Yung
Diagnostics 2024, 14(12), 1263; https://0-doi-org.brum.beds.ac.uk/10.3390/diagnostics14121263 - 14 Jun 2024
Viewed by 144
Abstract
Scoliosis, characterized by spine deformity, is most common in adolescent idiopathic scoliosis (AIS). Manual Cobb angle measurement limitations underscore the need for automated tools. This study employed a vertebral landmark extraction method and Feedforward Neural Network (FNN) to predict scoliosis progression in 79 [...] Read more.
Scoliosis, characterized by spine deformity, is most common in adolescent idiopathic scoliosis (AIS). Manual Cobb angle measurement limitations underscore the need for automated tools. This study employed a vertebral landmark extraction method and Feedforward Neural Network (FNN) to predict scoliosis progression in 79 AIS patients. The novel intervertebral angles matrix format showcased results. The mean absolute error for the intervertebral angle progression was 1.5 degrees, while the Pearson correlation of the predicted Cobb angles was 0.86. The accuracy in classifying Cobb angles (<15°, 15–25°, 25–35°, 35–45°, >45°) was 0.85, with 0.65 sensitivity and 0.91 specificity. The FNN demonstrated superior accuracy, sensitivity, and specificity, aiding in tailored treatments for potential scoliosis progression. Addressing FNNs’ over-fitting issue through strategies like “dropout” or regularization could further enhance their performance. This study presents a promising step towards automated scoliosis diagnosis and prognosis. Full article
(This article belongs to the Section Machine Learning and Artificial Intelligence in Diagnostics)
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18 pages, 1091 KiB  
Article
An Image-Based Prior Knowledge-Free Approach for a Multi-Material Decomposition in Photon-Counting Computed Tomography
by Jonas Neumann, Tristan Nowak, Bernhard Schmidt and Joachim von Zanthier
Diagnostics 2024, 14(12), 1262; https://0-doi-org.brum.beds.ac.uk/10.3390/diagnostics14121262 - 14 Jun 2024
Viewed by 207
Abstract
Photon-counting CT systems generally allow for acquiring multiple spectral datasets and thus for decomposing CT images into multiple materials. We introduce a prior knowledge-free deterministic material decomposition approach for quantifying three material concentrations on a commercial photon-counting CT system based on a single [...] Read more.
Photon-counting CT systems generally allow for acquiring multiple spectral datasets and thus for decomposing CT images into multiple materials. We introduce a prior knowledge-free deterministic material decomposition approach for quantifying three material concentrations on a commercial photon-counting CT system based on a single CT scan. We acquired two phantom measurement series: one to calibrate and one to test the algorithm. For evaluation, we used an anthropomorphic abdominal phantom with inserts of either aqueous iodine solution, aqueous tungsten solution, or water. Material CT numbers were predicted based on a polynomial in the following parameters: Water-equivalent object diameter, object center-to-isocenter distance, voxel-to-isocenter distance, voxel-to-object center distance, and X-ray tube current. The material decomposition was performed as a generalized least-squares estimation. The algorithm provided material maps of iodine, tungsten, and water with average estimation errors of 4% in the contrast agent maps and 1% in the water map with respect to the material concentrations in the inserts. The contrast-to-noise ratio in the iodine and tungsten map was 36% and 16% compared to the noise-minimal threshold image. We were able to decompose four spectral images into iodine, tungsten, and water. Full article
(This article belongs to the Special Issue Applications of CT Scans to Quantitative Imaging and Precision Medicine)
10 pages, 227 KiB  
Article
Hypothyroidism and Heart Rate Variability: Implications for Cardiac Autonomic Regulation
by Carina Bogdan, Viviana Mihaela Ivan, Adrian Apostol, Oana Elena Sandu, Felix-Mihai Maralescu and Daniel Florin Lighezan
Diagnostics 2024, 14(12), 1261; https://0-doi-org.brum.beds.ac.uk/10.3390/diagnostics14121261 - 14 Jun 2024
Viewed by 186
Abstract
Thyroid hormones have a pivotal role in controlling metabolic processes, cardiovascular function, and autonomic nervous system activity. Hypothyroidism, a prevalent endocrine illness marked by inadequate production of thyroid hormone, has been linked to different cardiovascular abnormalities, including alterations in heart rate variability (HRV). [...] Read more.
Thyroid hormones have a pivotal role in controlling metabolic processes, cardiovascular function, and autonomic nervous system activity. Hypothyroidism, a prevalent endocrine illness marked by inadequate production of thyroid hormone, has been linked to different cardiovascular abnormalities, including alterations in heart rate variability (HRV). The study included 110 patients with hypothyroid disorder. Participants underwent clinical assessments, including thyroid function tests and HRV analysis. HRV, a measure of the variation in time intervals between heartbeats, serves as an indicator of autonomic nervous system activity and cardiovascular health. The HRV values were acquired using continuous 24-h electrocardiogram (ECG) monitoring in individuals with hypothyroidism, as well as after a treatment period of 3 months. All patients exhibited cardiovascular symptoms like palpitations or fatigue but showed no discernible cardiac pathology or other conditions associated with cardiac disease. The findings of our study demonstrate associations between hypothyroidism and alterations in heart rate variability (HRV) parameters. These results illustrate the possible influence of thyroid dysfunction on the regulation of cardiac autonomic function. Full article
(This article belongs to the Special Issue Diagnosis and Prognosis of Heart Disease)
23 pages, 515 KiB  
Review
Empowering Modern Dentistry: The Impact of Artificial Intelligence on Patient Care and Clinical Decision Making
by Zeliha Merve Semerci and Selmi Yardımcı
Diagnostics 2024, 14(12), 1260; https://0-doi-org.brum.beds.ac.uk/10.3390/diagnostics14121260 - 14 Jun 2024
Viewed by 192
Abstract
Advancements in artificial intelligence (AI) are poised to catalyze a transformative shift across diverse dental disciplines including endodontics, oral radiology, orthodontics, pediatric dentistry, periodontology, prosthodontics, and restorative dentistry. This narrative review delineates the burgeoning role of AI in enhancing diagnostic precision, streamlining treatment [...] Read more.
Advancements in artificial intelligence (AI) are poised to catalyze a transformative shift across diverse dental disciplines including endodontics, oral radiology, orthodontics, pediatric dentistry, periodontology, prosthodontics, and restorative dentistry. This narrative review delineates the burgeoning role of AI in enhancing diagnostic precision, streamlining treatment planning, and potentially unveiling innovative therapeutic modalities, thereby elevating patient care standards. Recent analyses corroborate the superiority of AI-assisted methodologies over conventional techniques, affirming their capacity for personalization, accuracy, and efficiency in dental care. Central to these AI applications are convolutional neural networks and deep learning models, which have demonstrated efficacy in diagnosis, prognosis, and therapeutic decision making, in some instances surpassing traditional methods in complex cases. Despite these advancements, the integration of AI into clinical practice is accompanied by challenges, such as data security concerns, the demand for transparency in AI-generated outcomes, and the imperative for ongoing validation to establish the reliability and applicability of AI tools. This review underscores the prospective benefits of AI in dental practice, envisioning AI not as a replacement for dental professionals but as an adjunctive tool that fortifies the dental profession. While AI heralds improvements in diagnostics, treatment planning, and personalized care, ethical and practical considerations must be meticulously navigated to ensure responsible development of AI in dentistry. Full article
(This article belongs to the Section Machine Learning and Artificial Intelligence in Diagnostics)
12 pages, 864 KiB  
Article
Surgical Therapy of Infective Prosthesis Endocarditis following TAVI: A Single Center’s Experience
by Alexander Weymann, Ali Saad Merzah, Arian Arjomandi Rad, Lukman Amanov, Thanos Athanasiou, Bastian Schmack, Aron-Frederik Popov, Arjang Ruhparwar and Alina Zubarevich
Diagnostics 2024, 14(12), 1259; https://0-doi-org.brum.beds.ac.uk/10.3390/diagnostics14121259 - 14 Jun 2024
Viewed by 183
Abstract
Background/Objectives: Infective prosthesis endocarditis (IE) following transcatheter aortic valve implantation (TAVI) presents significant management challenges, marked by high mortality rates. This study reviews our center’s experience with surgical interventions for IE in patients post-TAVI, focusing on outcomes, challenges, and procedural complexities, and providing [...] Read more.
Background/Objectives: Infective prosthesis endocarditis (IE) following transcatheter aortic valve implantation (TAVI) presents significant management challenges, marked by high mortality rates. This study reviews our center’s experience with surgical interventions for IE in patients post-TAVI, focusing on outcomes, challenges, and procedural complexities, and providing an overview of the limited literature surrounding this subject. Methods: This study was executed as a comprehensive retrospective analysis, targeting the clinical outcomes of surgical treatment in patients presenting with PVE following TAVI procedures at our institution. From July 2017 to July 2022, we identified five patients who had previously undergone transfemoral transcatheter aortic valve implantation and were later diagnosed with PVE needing surgery, strictly adhering to the modified Duke criteria. Results: All surgical procedures were reported successful with no intra- or postoperative mortality. Patients were predominantly male (80%), with an average age of 76 ± 8.6 years, presenting mostly with dyspnea (NYHA Class II). The mean follow-up was between 121 and 1973 days, with outcomes showing no occurrences of stroke, myocardial infarction, or major bleeding. One patient expired from unrelated causes 3.7 years post-surgery. The operative and postoperative protocols demonstrated effective disease management with enhanced survival and minimal complications. Conclusions: The surgical treatment of IE following TAVI, though challenging, can be successfully achieved with careful patient selection and a multidisciplinary approach. The favorable outcomes suggest that surgical intervention remains a viable option for managing this high-risk patient group. Our study also highlights the scarce literature available on this topic, suggesting an urgent need for more comprehensive research to enhance understanding and improve treatment strategies. Future studies with larger cohorts are needed to further validate these findings and refine surgical strategies for this growing patient population. Full article
(This article belongs to the Section Pathology and Molecular Diagnostics)
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10 pages, 1355 KiB  
Article
Comparison of Magnetic Resonance Imaging with Electrodiagnosis in the Evaluation of Clinical Suspicion of Lumbosacral Radiculopathy
by Alberto Montaner-Cuello, Santos Caudevilla-Polo, Diego Rodríguez-Mena, Gianluca Ciuffreda, Pilar Pardos-Aguilella, Isabel Albarova-Corral, Jorge Pérez-Rey and Elena Bueno-Gracia
Diagnostics 2024, 14(12), 1258; https://0-doi-org.brum.beds.ac.uk/10.3390/diagnostics14121258 - 14 Jun 2024
Viewed by 238
Abstract
(1) Background: The diagnosis of lumbosacral radiculopathy involves anamnesis, an assessment of sensitivity and strength, diagnostic imaging—usually magnetic resonance imaging (MRI)—and electrodiagnostic testing (EDX), typically electromyography (EMG), and electroneurography (ENG). MRI evaluates the structures supporting the spinal cord, while EDX evaluates root functionality. [...] Read more.
(1) Background: The diagnosis of lumbosacral radiculopathy involves anamnesis, an assessment of sensitivity and strength, diagnostic imaging—usually magnetic resonance imaging (MRI)—and electrodiagnostic testing (EDX), typically electromyography (EMG), and electroneurography (ENG). MRI evaluates the structures supporting the spinal cord, while EDX evaluates root functionality. The present study aimed to analyze the concordance of MRI and EDX findings in patients with clinically suspected radiculopathy. Additionally, we investigated the comparison between these two reference tests and various clinical variables and questionnaires. (2) Methods: We designed a prospective epidemiological study of consecutive cases with an observational, descriptive, cross-sectional, and double-blind nature following the STROBE guidelines, encompassing 142 patients with clinical suspicion of lumbosacral radiculopathy. (3) Results: Of the sample, 58.5% tested positive for radiculopathy using EDX as the reference test, while 45.8% tested positive using MRI. The comparison between MRI and EDX in the diagnosis of radiculopathy in patients with clinical suspicion was not significant; the overall agreement was 40.8%. Only the years with symptoms were comparatively significant between the positive and negative radiculopathy groups as determined by EDX. (4) Conclusion: The comparison between lumbar radiculopathy diagnoses in patients with clinically suspected pathology using MRI and EDX as diagnostic modalities did not yield statistically significant findings. MRI and EDX are complementary tests assessing different aspects in patients with suspected radiculopathy; degeneration of the structures supporting the spinal cord does not necessarily imply root dysfunction. Full article
(This article belongs to the Section Medical Imaging and Theranostics)
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Article
GETNet: Group Normalization Shuffle and Enhanced Channel Self-Attention Network Based on VT-UNet for Brain Tumor Segmentation
by Bin Guo, Ning Cao, Ruihao Zhang and Peng Yang
Diagnostics 2024, 14(12), 1257; https://0-doi-org.brum.beds.ac.uk/10.3390/diagnostics14121257 - 14 Jun 2024
Viewed by 231
Abstract
Currently, brain tumors are extremely harmful and prevalent. Deep learning technologies, including CNNs, UNet, and Transformer, have been applied in brain tumor segmentation for many years and have achieved some success. However, traditional CNNs and UNet capture insufficient global information, and Transformer cannot [...] Read more.
Currently, brain tumors are extremely harmful and prevalent. Deep learning technologies, including CNNs, UNet, and Transformer, have been applied in brain tumor segmentation for many years and have achieved some success. However, traditional CNNs and UNet capture insufficient global information, and Transformer cannot provide sufficient local information. Fusing the global information from Transformer with the local information of convolutions is an important step toward improving brain tumor segmentation. We propose the Group Normalization Shuffle and Enhanced Channel Self-Attention Network (GETNet), a network combining the pure Transformer structure with convolution operations based on VT-UNet, which considers both global and local information. The network includes the proposed group normalization shuffle block (GNS) and enhanced channel self-attention block (ECSA). The GNS is used after the VT Encoder Block and before the downsampling block to improve information extraction. An ECSA module is added to the bottleneck layer to utilize the characteristics of the detailed features in the bottom layer effectively. We also conducted experiments on the BraTS2021 dataset to demonstrate the performance of our network. The Dice coefficient (Dice) score results show that the values for the regions of the whole tumor (WT), tumor core (TC), and enhancing tumor (ET) were 91.77, 86.03, and 83.64, respectively. The results show that the proposed model achieves state-of-the-art performance compared with more than eleven benchmarks. Full article
(This article belongs to the Special Issue Recent Advances in Artificial Intelligence-Based Medical Image Analysis)
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