Journal Description
Diagnostics
Diagnostics
is an international, peer-reviewed, open access journal on medical diagnosis published semimonthly online by MDPI. The British Neuro-Oncology Society (BNOS), the International Society for Infectious Diseases in Obstetrics and Gynaecology (ISIDOG) and the Swiss Union of Laboratory Medicine (SULM) are affiliated with Diagnostics and their members receive a discount on the article processing charges.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, SCIE (Web of Science), PubMed, PMC, Embase, Inspec, CAPlus / SciFinder, and other databases.
- Journal Rank: JCR - Q1 (Medicine, General and Internal) / CiteScore - Q2 (Internal Medicine)
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 20.5 days after submission; acceptance to publication is undertaken in 2.7 days (median values for papers published in this journal in the first half of 2024).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
- Companion journal: LabMed.
Impact Factor:
3.0 (2023);
5-Year Impact Factor:
3.1 (2023)
Latest Articles
An Innovative Hybrid Model for Automatic Detection of White Blood Cells in Clinical Laboratories
Diagnostics 2024, 14(18), 2093; https://doi.org/10.3390/diagnostics14182093 (registering DOI) - 22 Sep 2024
Abstract
Background: Microscopic examination of peripheral blood is a standard practice in clinical medicine. Although manual examination is considered the gold standard, it presents several disadvantages, such as interobserver variability, being quite time-consuming, and requiring well-trained professionals. New automatic digital algorithms have been developed
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Background: Microscopic examination of peripheral blood is a standard practice in clinical medicine. Although manual examination is considered the gold standard, it presents several disadvantages, such as interobserver variability, being quite time-consuming, and requiring well-trained professionals. New automatic digital algorithms have been developed to eliminate the disadvantages of manual examination and improve the workload of clinical laboratories. Objectives: Regular analysis of peripheral blood cells and careful interpretation of their results are critical for protecting individual health and early diagnosis of diseases. Because many diseases can occur due to this, this study aims to detect white blood cells automatically. Methods: A hybrid model has been developed for this purpose. In the developed model, feature extraction has been performed with MobileNetV2 and EfficientNetb0 architectures. In the next step, the neighborhood component analysis (NCA) method eliminated unnecessary features in the feature maps so that the model could work faster. Then, different features of the same image were combined, and the extracted features were combined to increase the model’s performance. Results: The optimized feature map was classified into different classifiers in the last step. The proposed model obtained a competitive accuracy value of 95.6%. Conclusions: The results obtained in the proposed model show that the proposed model can be used in the detection of white blood cells.
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(This article belongs to the Special Issue Artificial Intelligence and Deep Learning in Clinical Classification and Prediction)
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The Development of a Yolov8-Based Model for the Measurement of Critical Shoulder Angle (CSA), Lateral Acromion Angle (LAA), and Acromion Index (AI) from Shoulder X-ray Images
by
Turab Selçuk
Diagnostics 2024, 14(18), 2092; https://doi.org/10.3390/diagnostics14182092 (registering DOI) - 22 Sep 2024
Abstract
Background:The accurate and effective evaluation of parameters such as critical shoulder angle, lateral acromion angle, and acromion index from shoulder X-ray images is crucial for identifying pathological changes and assessing disease risk in the shoulder joint. Methods: In this study, a
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Background:The accurate and effective evaluation of parameters such as critical shoulder angle, lateral acromion angle, and acromion index from shoulder X-ray images is crucial for identifying pathological changes and assessing disease risk in the shoulder joint. Methods: In this study, a YOLOv8-based model was developed to automatically measure these three parameters together, contributing to the existing literature. Initially, YOLOv8 was used to segment the acromion, glenoid, and humerus regions, after which the CSA, LAA angles, and AI between these regions were calculated. The MURA dataset was employed in this study. Results: Segmentation performance was evaluated with the Dice and Jaccard similarity indices, both exceeding 0.9. Statistical analyses of the measurement performance, including Pearson correlation coefficient, RMSE, and ICC values demonstrated that the proposed model exhibits high consistency and similarity with manual measurements. Conclusion: The results indicate that automatic measurement methods align with manual measurements with high accuracy and offer an effective alternative for clinical applications. This study provides valuable insights for the early diagnosis and management of shoulder diseases and makes a significant contribution to existing measurement methods.
Full article
(This article belongs to the Special Issue Recent Advances in Bone and Joint Imaging—2nd Edition)
Open AccessArticle
Comparative Performance of Autoencoders and Traditional Machine Learning Algorithms in Clinical Data Analysis for Predicting Post-Staged GKRS Tumor Dynamics
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Simona Ruxandra Volovăț, Tudor Ovidiu Popa, Dragoș Rusu, Lăcrămioara Ochiuz, Decebal Vasincu, Maricel Agop, Călin Gheorghe Buzea and Cristian Constantin Volovăț
Diagnostics 2024, 14(18), 2091; https://doi.org/10.3390/diagnostics14182091 (registering DOI) - 21 Sep 2024
Abstract
Introduction: Accurate prediction of tumor dynamics following Gamma Knife radiosurgery (GKRS) is critical for optimizing treatment strategies for patients with brain metastases (BMs). Traditional machine learning (ML) algorithms have been widely used for this purpose; however, recent advancements in deep learning, such
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Introduction: Accurate prediction of tumor dynamics following Gamma Knife radiosurgery (GKRS) is critical for optimizing treatment strategies for patients with brain metastases (BMs). Traditional machine learning (ML) algorithms have been widely used for this purpose; however, recent advancements in deep learning, such as autoencoders, offer the potential to enhance predictive accuracy. This study aims to evaluate the efficacy of autoencoders compared to traditional ML models in predicting tumor progression or regression after GKRS. Objectives: The primary objective of this study is to assess whether integrating autoencoder-derived features into traditional ML models can improve their performance in predicting tumor dynamics three months post-GKRS in patients with brain metastases. Methods: This retrospective analysis utilized clinical data from 77 patients treated at the “Prof. Dr. Nicolae Oblu” Emergency Clinic Hospital-Iasi. Twelve variables, including socio-demographic, clinical, treatment, and radiosurgery-related factors, were considered. Tumor progression or regression within three months post-GKRS was the primary outcome, with 71 cases of regression and 6 cases of progression. Traditional ML models, such as Logistic Regression, Support Vector Machine (SVM), K-Nearest Neighbors (KNN), Extra Trees, Random Forest, and XGBoost, were trained and evaluated. The study further explored the impact of incorporating features derived from autoencoders, particularly focusing on the effect of compression in the bottleneck layer on model performance. Results: Traditional ML models achieved accuracy rates ranging from 0.91 (KNN) to 1.00 (Extra Trees). Integrating autoencoder-derived features generally enhanced model performance. Logistic Regression saw an accuracy increase from 0.91 to 0.94, and SVM improved from 0.85 to 0.96. XGBoost maintained consistent performance with an accuracy of 0.94 and an AUC of 0.98, regardless of the feature set used. These results demonstrate that hybrid models combining deep learning and traditional ML techniques can improve predictive accuracy. Conclusions: The study highlights the potential of hybrid models incorporating autoencoder-derived features to enhance the predictive accuracy and robustness of traditional ML models in forecasting tumor dynamics post-GKRS. These advancements could significantly contribute to personalized medicine, enabling more precise and individualized treatment planning based on refined predictive insights, ultimately improving patient outcomes.
Full article
(This article belongs to the Special Issue Integrative Approaches in Head and Neck Cancer Imaging)
Open AccessArticle
Application of the 5th WHO Guidelines for the Diagnosis of Lung Carcinoma in Small Lung Biopsies in a Tertiary Care Center: Is Insecurity of Pathologists for the Accurate Diagnosis Justified?
by
Manuela Beckert, Christian Meyer, Thomas Papadopoulos and Georgia Levidou
Diagnostics 2024, 14(18), 2090; https://doi.org/10.3390/diagnostics14182090 (registering DOI) - 21 Sep 2024
Abstract
Background/Objectives: The diagnosis of lung carcinoma (LC) is currently performed in small biopsies and according to the WHO classification by using limited stains to spare tissue for molecular testing. This procedure, however, often causes diagnostic uncertainty among pathologists. Methods: In this retrospective analysis,
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Background/Objectives: The diagnosis of lung carcinoma (LC) is currently performed in small biopsies and according to the WHO classification by using limited stains to spare tissue for molecular testing. This procedure, however, often causes diagnostic uncertainty among pathologists. Methods: In this retrospective analysis, we compared the diagnosis made by these guidelines in 288 lung biopsies with that using more stains, as retrieved from our archive. We also compared the results of p63 and p40 immunoexpression and investigated the diagnostic role of p53/Rb1. Results: In our investigation, we reached a definite diagnosis with a mean number of one stain compared with six stains in the original diagnostic procedure, with a 97.3% concordance rate. Only in the case of metastases, a clear advantage is proven in the use of more stains, especially in the absence of clinical information. We also found a comparable utility of p40 and p63 for the diagnosis of squamous cell carcinoma, despite the higher p63 expression in other histological types. Moreover, normal p53/Rb1 expression could be utilized for the exclusion of small-cell LC. Conclusions: Our study confirms the diagnostic certainty achieved by the suggestions of the WHO classification and justifies the potential insecurity in the absence of adequate communication with the treating clinician.
Full article
(This article belongs to the Special Issue Histopathology in Cancer Diagnosis and Prognosis)
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Open AccessReview
Review of In Situ Hybridization (ISH) Stain Images Using Computational Techniques
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Zaka Ur Rehman, Mohammad Faizal Ahmad Fauzi, Wan Siti Halimatul Munirah Wan Ahmad, Fazly Salleh Abas, Phaik Leng Cheah, Seow Fan Chiew and Lai-Meng Looi
Diagnostics 2024, 14(18), 2089; https://doi.org/10.3390/diagnostics14182089 (registering DOI) - 21 Sep 2024
Abstract
Recent advancements in medical imaging have greatly enhanced the application of computational techniques in digital pathology, particularly for the classification of breast cancer using in situ hybridization (ISH) imaging. HER2 amplification, a key prognostic marker in 20–25% of breast cancers, can be assessed
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Recent advancements in medical imaging have greatly enhanced the application of computational techniques in digital pathology, particularly for the classification of breast cancer using in situ hybridization (ISH) imaging. HER2 amplification, a key prognostic marker in 20–25% of breast cancers, can be assessed through alterations in gene copy number or protein expression. However, challenges persist due to the heterogeneity of nuclear regions and complexities in cancer biomarker detection. This review examines semi-automated and fully automated computational methods for analyzing ISH images with a focus on HER2 gene amplification. Literature from 1997 to 2023 is analyzed, emphasizing silver-enhanced in situ hybridization (SISH) and its integration with image processing and machine learning techniques. Both conventional machine learning approaches and recent advances in deep learning are compared. The review reveals that automated ISH analysis in combination with bright-field microscopy provides a cost-effective and scalable solution for routine pathology. The integration of deep learning techniques shows promise in improving accuracy over conventional methods, although there are limitations related to data variability and computational demands. Automated ISH analysis can reduce manual labor and increase diagnostic accuracy. Future research should focus on refining these computational methods, particularly in handling the complex nature of HER2 status evaluation, and integrate best practices to further enhance clinical adoption of these techniques.
Full article
(This article belongs to the Special Issue Advances in Machine Learning for Computer-Aided Diagnosis in Biomedical Imaging—2nd Edition)
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Open AccessInteresting Images
Atraumatic Hepatic Laceration with Hemoperitoneum
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Gaetano Maria Russo, Evangelia Zoi, Imma D’Iglio and Maria Luisa Mangoni di Santo Stefano
Diagnostics 2024, 14(18), 2088; https://doi.org/10.3390/diagnostics14182088 (registering DOI) - 21 Sep 2024
Abstract
Introduction: A rare case of atraumatic liver laceration associated with hemoperitoneum is presented in a patient with amyloidosis who came to the hospital for abdominal pain. Case Presentation: The imaging findings reveal significant hepatomegaly with finely heterogeneous hepatic density and subcapsular hypo-dense streaks
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Introduction: A rare case of atraumatic liver laceration associated with hemoperitoneum is presented in a patient with amyloidosis who came to the hospital for abdominal pain. Case Presentation: The imaging findings reveal significant hepatomegaly with finely heterogeneous hepatic density and subcapsular hypo-dense streaks in segments VI and VII, likely representing lesions. Post-contrast enhancement shows a punctiform contrast medium extravasation within the subhepatic fluid collection, visible from the arterial phase and intensifying in subsequent study phases. Discussion: These imaging findings suggest an atraumatic hepatic laceration, a diagnosis confirmed by the presence of hemoperitoneum distributed bilaterally under the diaphragm, in the paracolic gutters, along the mesentery root, and predominantly in the peri-hepatic region. Conclusion: The detailed imaging analysis provided critical insights into the diagnosis and management of this rare clinical presentation.
Full article
(This article belongs to the Special Issue Diagnosis and Management of Liver Diseases—2nd Edition)
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Open AccessArticle
The Effectiveness of Ultrasound-Guided Infiltrations Combined with Early Rehabilitation in the Management of Low Back Pain: A Retrospective Observational Study
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Danilo Donati, Fabio Vita, Vincenza Amoruso, Flavio Origlio, Roberto Tedeschi, Francesco Castagnini, Salvatore Massimo Stella, Marco Miceli, Cesare Faldini and Stefano Galletti
Diagnostics 2024, 14(18), 2087; https://doi.org/10.3390/diagnostics14182087 (registering DOI) - 20 Sep 2024
Abstract
Background and Aims: Low back pain is a prevalent condition affecting 60–85% of individuals during their lifetime. Despite various proposed mechanisms, the etiology of low back pain remains unclear. This study aims to evaluate the effectiveness of combining ultrasound-guided infiltrations with early rehabilitation
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Background and Aims: Low back pain is a prevalent condition affecting 60–85% of individuals during their lifetime. Despite various proposed mechanisms, the etiology of low back pain remains unclear. This study aims to evaluate the effectiveness of combining ultrasound-guided infiltrations with early rehabilitation in reducing pain and improving functional limitations in patients with chronic nonspecific low back pain. Methods: A retrospective observational study was conducted, reviewing data from January to April 2024 involving 40 patients with chronic nonspecific low back pain. Each patient received two cycles of ultrasound-guided lidocaine and corticosteroid infiltrations at the level of the posterior lower iliac spine, followed by 10 rehabilitation sessions. Patients were assessed at baseline (T0), after the first treatment cycle (T1), and after the second cycle (T2) using the Oswestry Disability Index, Quebec Back Pain Disability Scale, Roland Disability Questionnaire, and Numeric Rating Scale. Results: Significant improvements were observed across all assessment scales. The ODI scores decreased from 33.5 at baseline to 3.5 after treatment (p < 0.001). Similar reductions were noted in the QBPDS (from 61.5 to 10.3), RDQ (from 18 to 3.4), and NRS (from 7.4 to 1.3). The combination of ultrasound-guided infiltrations and early rehabilitation resulted in a significant reduction in pain and disability, with the most notable improvements occurring after the second treatment cycle. Conclusions: The integration of ultrasound-guided infiltrations with early rehabilitation is highly effective in managing chronic nonspecific low back pain, significantly reducing both pain and functional limitations.
Full article
(This article belongs to the Special Issue Current Perspectives and Advances in Ultrasound Imaging)
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Open AccessReview
Endoscopic Ultrasound and Intraductal Ultrasound in the Diagnosis of Biliary Tract Diseases: A Narrative Review
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Akiya Nakahata, Yasunobu Yamashita and Masayuki Kitano
Diagnostics 2024, 14(18), 2086; https://doi.org/10.3390/diagnostics14182086 (registering DOI) - 20 Sep 2024
Abstract
Endoscopic ultrasound (EUS) and intraductal ultrasound (IDUS) play very important roles in the field of biliary tract disease. Because of their excellent spatial resolution, the detection of small lesions and T- or N-staging of tumors have become possible. Additionally, contrast-enhanced EUS and the
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Endoscopic ultrasound (EUS) and intraductal ultrasound (IDUS) play very important roles in the field of biliary tract disease. Because of their excellent spatial resolution, the detection of small lesions and T- or N-staging of tumors have become possible. Additionally, contrast-enhanced EUS and the new imaging technique of detective flow imaging are reported to be useful for differential diagnosis. Furthermore, EUS-guided tissue acquisition is used not only for pathological diagnosis but also to collect tissue samples for cancer genome profiling. This review provides an overview of diagnosis utilizing the features and techniques of EUS and IDUS.
Full article
(This article belongs to the Special Issue Ultrasound Technologies in Clinical Medicine: Recent Advances in Gastroenterology)
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Open AccessReview
Osteosarcoma Metastasis to the Thorax: A Pictorial Review of Chest Computed Tomography Findings
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Khalid Abdulaziz Alduraibi, Jawaher Ali Towhari, Hatim Abdullah Alebdi, Bader Zaid Alfadhel, Ghazi S. Alotaibi, Subha Ghosh and Mnahi Bin Saeedan
Diagnostics 2024, 14(18), 2085; https://doi.org/10.3390/diagnostics14182085 (registering DOI) - 20 Sep 2024
Abstract
Background: Osteosarcoma, a primary bone malignancy in children and adolescents, frequently metastasizes to the lungs, contributing significantly to morbidity and mortality. Lung Metastases: At diagnosis, 15–20% of patients present with detectable lung metastases. Chest computed tomography (CT) is vital for the early detection
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Background: Osteosarcoma, a primary bone malignancy in children and adolescents, frequently metastasizes to the lungs, contributing significantly to morbidity and mortality. Lung Metastases: At diagnosis, 15–20% of patients present with detectable lung metastases. Chest computed tomography (CT) is vital for the early detection and monitoring of these metastases. Lung involvement typically presents as multiple nodules of varying sizes and can include atypical features such as cavitation, cystic lesions, ground-glass halos, intravascular tumor thrombi, and endobronchial disease. Additional Findings: Pleural metastasis often occurs alongside pulmonary disease, and complications like spontaneous pneumothorax may arise. Additional findings may include thoracic lymphadenopathy, cardiac tumor thrombus, and chest wall deposits. Conclusion: Familiarity with these imaging patterns is essential for radiologists to ensure timely diagnosis and effective management. This review highlights the critical role of chest CT in detecting and characterizing osteosarcoma metastasis.
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(This article belongs to the Special Issue Recent Developments and Future Trends in Thoracic Imaging)
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Open AccessCase Report
“Lazarus Response” When Feto-Maternal Microchimerism Kicks in: Spontaneous Remission in Refractory Primary Mediastinal B Cell Lymphoma Following Twin Pregnancy
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Radu Andrei Tomai, Sabina Iluta, Adrian Bogdan Tigu, Madalina Nistor, Anamaria Bancos, Diana Cenariu, Ciprian Jitaru, Sergiu Patcas, Delia Dima, David Kegyes, Sanda Buruiana, Mihnea Zdrenghea, Alina Daniela Tanase, Ciprian Tomuleasa and Romeo Micu
Diagnostics 2024, 14(18), 2084; https://doi.org/10.3390/diagnostics14182084 (registering DOI) - 20 Sep 2024
Abstract
Background: Spontaneous remission of cancer is a rare and poorly understood phenomenon characterized by complete or partial remission of a malignancy in the absence of or with inadequate treatment. The underlying mechanism for such occurrences is poorly understood, however, immune mechanisms seem
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Background: Spontaneous remission of cancer is a rare and poorly understood phenomenon characterized by complete or partial remission of a malignancy in the absence of or with inadequate treatment. The underlying mechanism for such occurrences is poorly understood, however, immune mechanisms seem to play an important role in such cases. In recent years increasingly more data have become available in favor of the clinical benefit of low levels of chimerism in hematologic malignancies. One such instance of naturally occurring low-level chimerism is feto-maternal microchimerism which has been shown to influence cancer progression and, in some instances, to be a protective factor against malignancy. Case report: We report a case of a young female patient with aggressive primary mediastinal large B cell lymphoma refractory to two lines of chemo-immunotherapy achieving sustained complete metabolic remission of tumor while pregnant with twins. Results: A focus on feto-maternal microchimerism during and after pregnancy revealed transient levels of feto-maternal microchimerism in the peripheral blood of the patient as measured by quantifying the Y-chromosome-linked SRY gene. Conclusions: Microchimerism presents significant potential for enhancing our comprehension of disease mechanisms, uncovering novel therapeutic targets, and refining diagnostic and treatment approaches, especially concerning cancer.
Full article
(This article belongs to the Special Issue Imaging of Fetal and Maternal Diseases in Pregnancy: 3rd Edition)
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Open AccessArticle
Optical Coherence Tomography as a Diagnosis-Assisted Tool for Guiding the Treatment of Melasma: A Case Series Study
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Chin-Yi Yang, Ja-Hon Lin and Chien-Ming Chen
Diagnostics 2024, 14(18), 2083; https://doi.org/10.3390/diagnostics14182083 (registering DOI) - 20 Sep 2024
Abstract
Background/Objectives: Multiple underlying pathomechanisms may lead to melasma, but there has been no report on the use of optical coherence tomography (OCT) to reveal specific pathomechanisms in individual patients and provide individualized treatments accordingly. Using real-time OCT images, we studied the pathomechanisms of
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Background/Objectives: Multiple underlying pathomechanisms may lead to melasma, but there has been no report on the use of optical coherence tomography (OCT) to reveal specific pathomechanisms in individual patients and provide individualized treatments accordingly. Using real-time OCT images, we studied the pathomechanisms of melasma in 12 female patients and the effects of individualized treatments. Methods: Patients were divided into good and bad improved groups according to the improvement in hyperpigmentation at month 4. Results: In the bad improved group, all melanin or confetti melanin had significantly decreased at month 2 or month 4 while granular melanin ratio at month or month 4 significantly increased, the most parameters of dendritic-sharped cells (DCs) before and after treatment were not significantly different, the collagen area or collagen density at month 4 significantly decreased. In the good improved group, there was slightly low all melanin/confetti melanin at month 4 and high granular melanin at month 4 in comparison to the bad improved group. Moreover, most of the parameters in the DCs at month 4 significantly increased while most parameters in collagen at month 4 significantly decreased. Conclusions: OCT is useful in revealing the involved pathomechanisms of melasma in individualized patients. Positive treatment results can be achieved through individualized therapy regimen targeting the pathomechanisms.
Full article
(This article belongs to the Special Issue Dermatology: Diagnosis and Management)
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Open AccessArticle
A Rapid Increase in Serum Lactate Levels after Cardiovascular Surgery Is Associated with Postoperative Serious Adverse Events: A Single Center Retrospective Study
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Kenichiro Kikuchi, Satoshi Kazuma and Yoshiki Masuda
Diagnostics 2024, 14(18), 2082; https://doi.org/10.3390/diagnostics14182082 - 20 Sep 2024
Abstract
Background/Objectives: Hyperlactatemia is a common predictive factor for poor post-cardiovascular surgery outcomes. However, it is not well understood whether the rapid postoperative lactate level elevation in a short period of time is associated with patient outcomes. Herein, we investigated the relationship between the
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Background/Objectives: Hyperlactatemia is a common predictive factor for poor post-cardiovascular surgery outcomes. However, it is not well understood whether the rapid postoperative lactate level elevation in a short period of time is associated with patient outcomes. Herein, we investigated the relationship between the degree of change in serum lactate levels and postoperative serious adverse events (PSAEs), including mortality, within 24 h of cardiovascular surgery. Methods: In this retrospective study, we evaluated the relationship between a rapid serum lactate level increase and PSAEs after open-heart and major vascular surgery. We divided the patients into those with and without PSAEs. Univariate and multivariate analyses were performed to evaluate the association between PSAEs and rapid lactate level increases. Results: We enrolled 445 patients; 16% (n = 71) had PSAEs. The peak lactate levels during the first 24 h of intensive care unit (ICU) stay were higher in patients with PSAEs than in those without. The maximum change in lactate levels between two consecutive lactate measurements during the first 24 h after ICU admission was higher in patients with PSAEs than in those without. A multivariate logistic regression analysis revealed that changes in lactate levels of 2 mmol/L or more between two consecutive lactate measurements were associated with PSAEs. ICU peak lactate levels of 3 mmol/L or more were not associated with PSAEs. Conclusions: Rapid serum lactate level increases of 2 mmol/L or more during the first 24 h of ICU admission post-cardiovascular surgery are associated with PSAEs.
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(This article belongs to the Section Clinical Laboratory Medicine)
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Distal Transradial Access Optimization: A Prospective Trial of Ultrasound-Guided Radial Artery Characterization for the Anatomical Snuffbox
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Łukasz Koziński, Zbigniew Orzałkiewicz, Paweł Zagożdżon and Alicja Dąbrowska-Kugacka
Diagnostics 2024, 14(18), 2081; https://doi.org/10.3390/diagnostics14182081 - 20 Sep 2024
Abstract
Background/Objectives: The distal transradial approach (dTRA) is increasingly used in interventional cardiology. Doppler Ultrasound (DUS) effectively assesses radial artery (RA) characteristics. This study aims to identify specific RA DUS characteristics in patients undergoing coronary procedures via dTRA. Methods: Participants from the ANTARES
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Background/Objectives: The distal transradial approach (dTRA) is increasingly used in interventional cardiology. Doppler Ultrasound (DUS) effectively assesses radial artery (RA) characteristics. This study aims to identify specific RA DUS characteristics in patients undergoing coronary procedures via dTRA. Methods: Participants from the ANTARES trial who completed the intervention per-protocol and retained RA patency were included. DUS was performed at baseline, 1 day, and 60 days post-procedure. Results: Among 400 participants, 348 had either dTRA (n = 169) or conventional transradial access (cTRA) (n = 179). Distal RA lumen diameter was 12% smaller than that of the proximal RA (p < 0.001). Men had a 14% larger distal RA diameter than women (2.33 ± 0.31 mm vs. 2.04 ± 0.27 mm, p < 0.0001), similar to the proximal RA relationship. Peak flow velocities were similar between the sexes. Univariate linear regression showed that height, weight, body mass index, and body surface area (BSA) predicted arterial size, with BSA remaining significant in multivariate analysis (beta coefficient 0.62; confidence interval 0.49–0.75; p < 0.0001). Distal RA diameter correlated positively with palpable pulse at the snuffbox and wrist. The dTRA resulted in an immediate 14% and 11% increase in distal and proximal RA diameter, respectively (both p < 0.05). Sixty days after dTRA, the distal RA remained slightly dilated (p < 0.05), while the proximal RA returned to baseline. Conclusions: Distal RA diameter is significantly associated with sex, measuring smaller than the forearm segment. A strong palpable pulse correlates with larger distal RA size. The dTRA induces RA lumen expansion. A thorough understanding of distal RA anatomy is essential for optimizing patient selection and refining techniques for transradial procedures.
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(This article belongs to the Special Issue New Trends and Advances in Cardiac Imaging)
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Open AccessArticle
Optimal Training Positive Sample Size Determination for Deep Learning with a Validation on CBCT Image Caries Recognition
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Yanlin Wang, Gang Li, Xinyue Zhang, Yue Wang, Zhenhao Zhang, Jupeng Li, Junqi Ma and Linghang Wang
Diagnostics 2024, 14(18), 2080; https://doi.org/10.3390/diagnostics14182080 - 20 Sep 2024
Abstract
Objectives: During deep learning model training, it is essential to consider the balance among the effects of sample size, actual resources, and time constraints. Single-arm objective performance criteria (OPC) was proposed to determine the optimal positive sample size for training deep learning
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Objectives: During deep learning model training, it is essential to consider the balance among the effects of sample size, actual resources, and time constraints. Single-arm objective performance criteria (OPC) was proposed to determine the optimal positive sample size for training deep learning models in caries recognition. Methods: An expected sensitivity (PT) of 0.6 and a clinically acceptable sensitivity (P0) of 0.5 were applied to the single-arm OPC calculation formula, yielding an optimal training set comprising 263 carious teeth. U-Net, YOLOv5n, and CariesDetectNet were trained and validated using clinically self-collected cone-beam computed tomography (CBCT) images that included varying quantities of carious teeth. To assess performance, an additional dataset was utilized to evaluate the accuracy of caries detection by both the models and two dental radiologists. Results: When the number of carious teeth reached approximately 250, the models reached the optimal performance levels. U-Net demonstrated superior performance, achieving accuracy, sensitivity, specificity, F1-Score, and Dice similarity coefficients of 0.9929, 0.9307, 0.9989, 0.9590, and 0.9435, respectively. The three models exhibited greater accuracy in caries recognition compared to dental radiologists. Conclusions: This study demonstrated that the positive sample size of CBCT images containing caries was predictable and could be calculated using single-arm OPC.
Full article
(This article belongs to the Special Issue Applications of Dentomaxillofacial Diagnostic Imaging in Different Specialties)
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Open AccessArticle
Influence of Right Atrial Pressure on the Prognosis of Patients with Rheumatic Mitral Stenosis Undergoing Percutaneous Mitral Balloon Valvuloplasty
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Daniella Cian Nazzetta, Larissa Christine Gomes de Sousa, Vitor Emer Egypto Rosa, Fernanda Castiglioni Tessari, Carlos M. Campos, Maria Antonieta Albanez Medeiros Lopes, Carlos Viana Poyares Jardim, Luís Gustavo Mapa, Layara Fernanda Vicente Pereira Lipari, Mariana Pezzute Lopes, João Ricardo Cordeiro Fernandes, Antonio de Santis, Lucas José Neves Tachotti Pires, Roney Orismar Sampaio and Flávio Tarasoutchi
Diagnostics 2024, 14(18), 2079; https://doi.org/10.3390/diagnostics14182079 - 19 Sep 2024
Abstract
Background: Pulmonary hypertension (PH) often complicates mitral stenosis (MS). The prognostic impact of pulmonary vascular resistance (PVR) in MS patients remains unclear. Previous study has demonstrated the prognostic impact of right atrial pressure (RAP) in patients with primary PH. We aim to determine
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Background: Pulmonary hypertension (PH) often complicates mitral stenosis (MS). The prognostic impact of pulmonary vascular resistance (PVR) in MS patients remains unclear. Previous study has demonstrated the prognostic impact of right atrial pressure (RAP) in patients with primary PH. We aim to determine the prognostic impact of PVR and RAP in patients with rheumatic MS undergoing percutaneous mitral balloon valvuloplasty (PMBV). Methods: A total of 58 patients with symptomatic severe rheumatic MS who underwent PMBV between 2016 and 2020 were included. Patients were divided into two groups: PVR ≤ 2WU (N = 26) and PVR > 2WU (N = 32). The composite endpoint included death, reintervention or persistent NYHA functional class III-IV during follow-up. Results: The median age was 50 (42–60) years, with 82.8% being female. Median pulmonary artery systolic pressure (PASP) was 42 (35–50.5) mmHg. Patients with PVR ≤ 2WU had lower PASP on both echocardiogram and catheterization. The PMBV success rate was 75.9%. Multivariate analysis, adjusted for PVR, showed RAP as the only independent predictor of the composite endpoint (HR:1.507, 95% CI:1.015–2.237, p = 0.042). The optimal RAP cutoff was 9.5 mmHg (HR:3.481, 95% CI:1.041–11.641; p = 0.043). Conclusions: RAP was an independent predictor of adverse outcomes in patients with rheumatic MS undergoing PMBV, while PVR did not show prognostic significance. These findings suggest that the prognostic value of PVR may be lower than expected.
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(This article belongs to the Special Issue Rheumatic Diseases: Diagnosis and Management)
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Open AccessArticle
Glucose and Lipid Metabolism Disorders in Adults with Spinal Muscular Atrophy Type 3
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Marija Miletić, Zorica Stević, Svetlana Vujović, Jelena Rakočević, Ana Tomić, Milina Tančić Gajić, Miloš Stojanović, Aleksa Palibrk and Miloš Žarković
Diagnostics 2024, 14(18), 2078; https://doi.org/10.3390/diagnostics14182078 - 19 Sep 2024
Abstract
Background: Spinal muscular atrophy type 3 (juvenile SMA, Kugelberg–Welander disease) is a genetic disease caused by changes in the survival motor neuron 1 (SMN) gene. However, there is increasing evidence of metabolic abnormalities in SMA patients, such as altered fatty acid metabolism, impaired
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Background: Spinal muscular atrophy type 3 (juvenile SMA, Kugelberg–Welander disease) is a genetic disease caused by changes in the survival motor neuron 1 (SMN) gene. However, there is increasing evidence of metabolic abnormalities in SMA patients, such as altered fatty acid metabolism, impaired glucose tolerance, and defects in the functioning of muscle mitochondria. Given that data in the literature are scarce regarding this subject, the purpose of this study was to estimate the prevalence of glucose and lipid metabolism disorders in adult patients with SMA type 3. Methods: We conducted a cross-sectional study of 23 adult patients with SMA type 3 who underwent a comprehensive evaluation, including a physical examination, biochemical analysis, and an oral glucose tolerance test during 2020–2023. Results: At least one lipid abnormality was observed in 60.8% of patients. All four lipid parameters were atypical in 4.3% of patients, three lipid parameters were abnormal in 21.7% of patients, and two lipid parameters were altered in 8.7% patients. A total of 91.3% of SMA3 patients met the HOMA-IR criteria for insulin resistance, with 30.43% having impaired glucose tolerance. None of the patients met the criteria for a diagnosis of overt DM2. Conclusions: The prevalence of dyslipidemia and altered glucose metabolism in our study sets apart the adult population with SMA3 from the general population, confirming a significant interplay between muscle, liver, and adipose tissue. Ensuring metabolic care for aging patients with SMA 3 is crucial, as they are vulnerable to metabolic derangements and cardiovascular risks.
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(This article belongs to the Special Issue Diagnosis, Biomarkers, and Treatment of Metabolic Disorders)
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Open AccessArticle
Combining Signals for EEG-Free Arousal Detection during Home Sleep Testing: A Retrospective Study
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Safa Boudabous, Juliette Millet and Emmanuel Bacry
Diagnostics 2024, 14(18), 2077; https://doi.org/10.3390/diagnostics14182077 - 19 Sep 2024
Abstract
Introduction: Accurately detecting arousal events during sleep is essential for evaluating sleep quality and diagnosing sleep disorders, such as sleep apnea/hypopnea syndrome. While the American Academy of Sleep Medicine guidelines associate arousal events with electroencephalogram (EEG) signal variations, EEGs are often not recorded
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Introduction: Accurately detecting arousal events during sleep is essential for evaluating sleep quality and diagnosing sleep disorders, such as sleep apnea/hypopnea syndrome. While the American Academy of Sleep Medicine guidelines associate arousal events with electroencephalogram (EEG) signal variations, EEGs are often not recorded during home sleep testing (HST) using wearable devices or smartphone applications. Objectives: The primary objective of this study was to explore the potential of alternatively relying on combinations of easily measurable physiological signals during HST for arousal detection where EEGs are not recorded. Methods: We conducted a data-driven retrospective study following an incremental device-agnostic analysis approach, where we simulated a limited-channel setting using polysomnography data and used deep learning to automate the detection task. During the analysis, we tested multiple signal combinations to evaluate their potential effectiveness. We trained and evaluated the model on the Multi-Ethnic Study of Atherosclerosis dataset. Results: The results demonstrated that combining multiple signals significantly improved performance compared with single-input signal models. Notably, combining thoracic effort, heart rate, and a wake/sleep indicator signal achieved competitive performance compared with the state-of-the-art DeepCAD model using electrocardiogram as input with an average precision of 61.59% and an average recall of 56.46% across the test records. Conclusions: This study demonstrated the potential of combining easy-to-record HST signals to characterize the autonomic markers of arousal better. It provides valuable insights to HST device designers on signals that improve EEG-free arousal detection.
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(This article belongs to the Special Issue Diagnosis of Sleep Disorders Using Machine Learning Approaches)
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Open AccessArticle
Diagnostic and Prognostic Utilities of Pancreatic Stone Protein in Patients with Suspected Sepsis
by
Gun-Hyuk Lee, Hanah Kim, Hee-Won Moon, Yeo-Min Yun, Mikyoung Park, Seungho Lee and Mina Hur
Diagnostics 2024, 14(18), 2076; https://doi.org/10.3390/diagnostics14182076 - 19 Sep 2024
Abstract
Background/Objectives: Pancreatic stone protein (PSP) is an emerging biomarker of sepsis that is secreted from pancreas sensing remote organ damages. We explored the diagnostic and prognostic utilities of PSP in patients with suspected sepsis. Methods: In a total of 285 patients (suspected sepsis,
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Background/Objectives: Pancreatic stone protein (PSP) is an emerging biomarker of sepsis that is secreted from pancreas sensing remote organ damages. We explored the diagnostic and prognostic utilities of PSP in patients with suspected sepsis. Methods: In a total of 285 patients (suspected sepsis, n = 148; sepsis, n = 137), we compared PSP with procalcitonin (PCT) and sequential organ failure assessment (SOFA) score. Sepsis diagnoses were explored using receiver operating characteristic curve analyses with area under the curves (AUCs). Clinical outcomes (in-hospital mortality, 30-day mortality, and kidney replacement therapy [KRT]) were explored using the Kaplan–Meier method and a multivariate analysis with hazard ratio (HR). Results: PCT and PSP were comparable for sepsis diagnosis (AUC = 0.71–0.72, p < 0.001). The sepsis proportion was significantly higher when both biomarkers increased than when either one or both biomarkers did not increase (89.0% vs. 21.3–47.7%, p < 0.001). Each biomarker quartile (Q1–Q4) differed significantly according to their SOFA score (all p < 0.001). Compared with Q1, the Q2–Q4 groups showed worse clinical outcomes (p = 0.002–0.041). Both biomarkers added to the SOFA score showed higher HRs than the SOFA score alone (3.3–9.6 vs. 2.8–4.2, p < 0.001–0.011), with nearly 2.5-fold higher HR (9.6 vs. 4.2) for predicting KRT. Conclusions: Although PCT and PSP did not independently predict clinical outcomes in the multivariate analysis, PSP demonstrated diagnostic and prognostic utilities in patients with suspected sepsis, especially for predicting kidney dysfunction. PSP, alone or in combination with PCT, would be a valuable tool that can be added to clinical assessments.
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(This article belongs to the Special Issue Advances in Laboratory Markers of Human Disease)
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Estimating the Extraction Time of an Upper Third Molar: Proposal and Validation of Results
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Belén Lima-Sánchez, Paula Hermida-Cabrera, Vanessa Montoya-Salazar, Luis-Guillermo Oliveros-López, Pedro Alomar-Velasco, Maria-Angeles Serrera-Figallo, Daniel Torres-Lagares and María Baus-Domínguez
Diagnostics 2024, 14(18), 2075; https://doi.org/10.3390/diagnostics14182075 - 19 Sep 2024
Abstract
Background: Numerous studies in the literature have aimed to evaluate the difficulty level of removing third molars. However, most of these studies have focused on the lower third molars, which can lead to complications. There is a lack of a method to determine
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Background: Numerous studies in the literature have aimed to evaluate the difficulty level of removing third molars. However, most of these studies have focused on the lower third molars, which can lead to complications. There is a lack of a method to determine the complexity of upper third molar extraction. Therefore, this study’s objective was to develop an equation using multiple linear regression to estimate the extraction time of an upper third molar based on its complexity. Methods: This study involved patients enrolled in the Master of Oral Surgery program at the University of Seville. To determine their relationship with surgical time, the researchers analyzed various factors, such as depth, root morphology, and the need for odontosection. They then validated their findings by studying patients treated at Palmaplanas Hospital in Mallorca. Results: The cohort analysis from the University of Seville revealed significant associations between surgical time and the identified factors. A regression equation design was performed to predict the total duration of surgical intervention for wisdom teeth extraction. This equation incorporates several independent variables, represented by Xi, together with a constant term, C, and the corresponding coefficients, Bi, which weight the impact of each variable on the intervention time. The results are as follows: −0.312 (spatial relationship), 0.651 (depth), −0.443 (bone and mucosa integrity), 0.214 (roots), −0.745 (ostectomy), 0.713 (odontosection), and −0.426 (suture). Upon application of the statistical methodology to the Palmaplanas Hospital cohort, a regression coefficient of 0.770 was determined. This indicates a strong correlation between the input data and the estimated surgical time. Conclusions: In conclusion, the proposed formula demonstrates notable validity in predicting the surgical time required to extract upper third molars.
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(This article belongs to the Section Medical Imaging and Theranostics)
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The Use of Artificial Intelligence in Predicting Chemotherapy-Induced Toxicities in Metastatic Colorectal Cancer: A Data-Driven Approach for Personalized Oncology
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Eliza-Maria Froicu, Oriana-Maria Oniciuc, Vlad-Adrian Afrăsânie, Mihai-Vasile Marinca, Silvia Riondino, Elena Adriana Dumitrescu, Teodora Alexa-Stratulat, Iulian Radu, Lucian Miron, Gema Bacoanu, Vladimir Poroch and Bogdan Gafton
Diagnostics 2024, 14(18), 2074; https://doi.org/10.3390/diagnostics14182074 - 19 Sep 2024
Abstract
Background: Machine learning models learn about general behavior from data by finding the relationships between features. Our purpose was to develop a predictive model to identify and predict which subset of colorectal cancer patients are more likely to experience chemotherapy-induced toxicity and to
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Background: Machine learning models learn about general behavior from data by finding the relationships between features. Our purpose was to develop a predictive model to identify and predict which subset of colorectal cancer patients are more likely to experience chemotherapy-induced toxicity and to determine the specific attributes that influence the presence of treatment-related side effects. Methods: The predictor was general toxicity, and for the construction of our data training, we selected 95 characteristics that represent the health state of 74 patients prior to their first round of chemotherapy. After the data were processed, Random Forest models were trained to offer an optimal balance between accuracy and interpretability. Results: We constructed a machine learning predictor with an emphasis on assessing the importance of numerical and categorical variables in relation to toxicity. Conclusions: The incorporation of artificial intelligence in personalizing colorectal cancer management by anticipating and overseeing toxicities more effectively illustrates a pivotal shift towards more personalized and precise medical care.
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(This article belongs to the Special Issue Artificial Intelligence in Cancers—2nd Edition)
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