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Advanced Doppler Ultrasound Insights: A Multicenter Prospective Study on Healthy Skin.
IF 3 3区 医学 Q1 MEDICINE, GENERAL & INTERNAL Pub Date : 2025-02-26 DOI: 10.3390/diagnostics15050569
Priscila Giavedoni, Jorge Romaní, Francisco de Cabo, Francisco Javier García-Martínez, Mónica Quintana-Codina, Esther Roè-Crespo, Irene Fuertes de Vega, Xavier Soria-Gili, Rafael Aguayo-Ortiz, Patricia Garbayo-Salmons, Gonzalo Castillo, David Vidal-Sarró, Jordi Mollet, Laura Serra, Carlos Gonzalez, Emilio López-Trujillo, Miquel Just, Marc Combalia, Sebastian Podlipnik, Josep Malvehy, Ximena Wortsman

Background: There have been multiple studies on the use of Doppler ultrasound to define skin inflammation, but the visible vessels of healthy skin have yet to be described. Objective: This study aimed to evaluate the visible vessels of healthy skin using Doppler ultrasound. Methods: Prospective multicenter study using Doppler ultrasound to analyze healthy skin. The color percentage, flow velocity, and maximum vessel diameter were calculated. Results: 943 images from 152 patients were recorded. The most frequently used mode was color Doppler (40.6%), followed by power Doppler (30.4%). Visible vessels were detected in 18.23%; in positive Doppler images, color occupied less than 5%. The malar region exhibited the highest visible vessels. The 22 MHz probe detected smaller vessels with slower flows than the 18 MHz probe. Spectral Doppler showed peak systolic values of less than 10 cm/s and a vessel diameter of less than 1 mm. In most of the participating centers, the operators had less than 10 years of experience in performing skin ultrasound examinations. Sensitivity of the Doppler may vary according to the device. Conclusions: With the used ultrasound equipment, it was uncommon to visualize vessels in healthy skin. When seen, they covered less than 5% of the image with low flow and small size.

{"title":"Advanced Doppler Ultrasound Insights: A Multicenter Prospective Study on Healthy Skin.","authors":"Priscila Giavedoni, Jorge Romaní, Francisco de Cabo, Francisco Javier García-Martínez, Mónica Quintana-Codina, Esther Roè-Crespo, Irene Fuertes de Vega, Xavier Soria-Gili, Rafael Aguayo-Ortiz, Patricia Garbayo-Salmons, Gonzalo Castillo, David Vidal-Sarró, Jordi Mollet, Laura Serra, Carlos Gonzalez, Emilio López-Trujillo, Miquel Just, Marc Combalia, Sebastian Podlipnik, Josep Malvehy, Ximena Wortsman","doi":"10.3390/diagnostics15050569","DOIUrl":"10.3390/diagnostics15050569","url":null,"abstract":"<p><p><b>Background:</b> There have been multiple studies on the use of Doppler ultrasound to define skin inflammation, but the visible vessels of healthy skin have yet to be described. <b>Objective:</b> This study aimed to evaluate the visible vessels of healthy skin using Doppler ultrasound. <b>Methods:</b> Prospective multicenter study using Doppler ultrasound to analyze healthy skin. The color percentage, flow velocity, and maximum vessel diameter were calculated. <b>Results:</b> 943 images from 152 patients were recorded. The most frequently used mode was color Doppler (40.6%), followed by power Doppler (30.4%). Visible vessels were detected in 18.23%; in positive Doppler images, color occupied less than 5%. The malar region exhibited the highest visible vessels. The 22 MHz probe detected smaller vessels with slower flows than the 18 MHz probe. Spectral Doppler showed peak systolic values of less than 10 cm/s and a vessel diameter of less than 1 mm. In most of the participating centers, the operators had less than 10 years of experience in performing skin ultrasound examinations. Sensitivity of the Doppler may vary according to the device. <b>Conclusions:</b> With the used ultrasound equipment, it was uncommon to visualize vessels in healthy skin. When seen, they covered less than 5% of the image with low flow and small size.</p>","PeriodicalId":11225,"journal":{"name":"Diagnostics","volume":"15 5","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11899106/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143613857","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Editorial for the Special Issue "Imaging Diagnosis in the Abdomen"-A Step Forward in Diagnostic Precision.
IF 3 3区 医学 Q1 MEDICINE, GENERAL & INTERNAL Pub Date : 2025-02-25 DOI: 10.3390/diagnostics15050557
Piero Boraschi, Francescamaria Donati

Abdominal imaging has undergone a significant transformation in recent years, driven by the rapid evolution of diagnostic technologies and their integration into clinical practice [...].

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引用次数: 0
Detection of Gallbladder Disease Types Using a Feature Engineering-Based Developed CBIR System.
IF 3 3区 医学 Q1 MEDICINE, GENERAL & INTERNAL Pub Date : 2025-02-25 DOI: 10.3390/diagnostics15050552
Ahmet Bozdag, Muhammed Yildirim, Mucahit Karaduman, Hursit Burak Mutlu, Gulsah Karaduman, Aziz Aksoy

Background/Objectives: Early detection and diagnosis are important when treating gallbladder (GB) diseases. Poorer clinical outcomes and increased patient symptoms may result from any error or delay in diagnosis. Many signs and symptoms, especially those related to GB diseases with similar symptoms, may be unclear. Therefore, highly qualified medical professionals should interpret and understand ultrasound images. Considering that diagnosis via ultrasound imaging can be time- and labor-consuming, it may be challenging to finance and benefit from this service in remote locations. Methods: Today, artificial intelligence (AI) techniques ranging from machine learning (ML) to deep learning (DL), especially in large datasets, can help analysts using Content-Based Image Retrieval (CBIR) systems with the early diagnosis, treatment, and recognition of diseases, and then provide effective methods for a medical diagnosis. Results: The developed model is compared with two different textural and six different Convolutional Neural Network (CNN) models accepted in the literature-the developed model combines features obtained from three different pre-trained architectures for feature extraction. The cosine method was preferred as the similarity measurement metric. Conclusions: Our proposed CBIR model achieved successful results from six other different models. The AP value obtained in the proposed model is 0.94. This value shows that our CBIR-based model can be used to detect GB diseases.

{"title":"Detection of Gallbladder Disease Types Using a Feature Engineering-Based Developed CBIR System.","authors":"Ahmet Bozdag, Muhammed Yildirim, Mucahit Karaduman, Hursit Burak Mutlu, Gulsah Karaduman, Aziz Aksoy","doi":"10.3390/diagnostics15050552","DOIUrl":"10.3390/diagnostics15050552","url":null,"abstract":"<p><p><b>Background/Objectives:</b> Early detection and diagnosis are important when treating gallbladder (GB) diseases. Poorer clinical outcomes and increased patient symptoms may result from any error or delay in diagnosis. Many signs and symptoms, especially those related to GB diseases with similar symptoms, may be unclear. Therefore, highly qualified medical professionals should interpret and understand ultrasound images. Considering that diagnosis via ultrasound imaging can be time- and labor-consuming, it may be challenging to finance and benefit from this service in remote locations. <b>Methods:</b> Today, artificial intelligence (AI) techniques ranging from machine learning (ML) to deep learning (DL), especially in large datasets, can help analysts using Content-Based Image Retrieval (CBIR) systems with the early diagnosis, treatment, and recognition of diseases, and then provide effective methods for a medical diagnosis. <b>Results:</b> The developed model is compared with two different textural and six different Convolutional Neural Network (CNN) models accepted in the literature-the developed model combines features obtained from three different pre-trained architectures for feature extraction. The cosine method was preferred as the similarity measurement metric. <b>Conclusions:</b> Our proposed CBIR model achieved successful results from six other different models. The AP value obtained in the proposed model is 0.94. This value shows that our CBIR-based model can be used to detect GB diseases.</p>","PeriodicalId":11225,"journal":{"name":"Diagnostics","volume":"15 5","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11899127/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143613882","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
The Impact of SARS-CoV-2 Infection on Glucose Homeostasis in Hospitalized Patients with Pulmonary Impairment.
IF 3 3区 医学 Q1 MEDICINE, GENERAL & INTERNAL Pub Date : 2025-02-25 DOI: 10.3390/diagnostics15050554
Oana-Andreea Parlițeanu, Mara-Amalia Bălteanu, Dragoș Cosmin Zaharia, Tudor Constantinescu, Alexandra Maria Cristea, Ștefan Dumitrache-Rujinscki, Andra Elena Nica, Cristiana Voineag, Octavian Sabin Alexe, Emilia Tabacu, Alina Croitoru, Irina Strâmbu, Roxana Maria Nemeș, Beatrice Mahler

Background and Objectives: We conducted a retrospective observational study to evaluate the impact of elevated blood glucose levels in patients with SARS-CoV-2 infection and a prior diagnosis of diabetes mellitus (DM) or newly diagnosed hyperglycemia. Materials and Methods: This study analyzed 6065 patients admitted to the COVID-19 departments of the "Marius Nasta" National Institute of Pulmonology in Bucharest, Romania, between 26 October 2020 and 5 January 2023. Of these, 813 patients (13.40%) were selected for analysis due to either a pre-existing diagnosis of DM or hyperglycemia at the time of hospital admission. Results: The erythrocyte sedimentation rate (ESR) and C-reactive protein (CRP) levels were elevated in patients with blood glucose levels exceeding 300 mg/dL. These elevations correlated with the presence of respiratory failure and increased mortality rates. Additionally, oxygen requirements were significantly higher at elevated blood glucose levels (p < 0.001), with a direct relationship between glycemia and oxygen demand. This was accompanied by lower oxygen saturation levels (p < 0.001). Maximum blood glucose levels were associated with the severity of respiratory failure (AUC 0.6, 95% CI: 0.56-0.63, p < 0.001). We identified cut-off values for blood glucose at admission (217.5 mg/dL) and maximum blood glucose during hospitalization (257.5 mg/dL), both of which were associated with disease severity and identified as risk factors for increased mortality. Conclusions: High blood glucose levels, both at admission and during hospitalization, were identified as risk factors for poor prognosis and increased mortality in patients with SARS-CoV-2 infection, regardless of whether the hyperglycemia was due to a prior diagnosis of DM or was newly developed during the hospital stay. These findings underscore the importance of glycemic control in the management of hospitalized COVID-19 patients.

{"title":"The Impact of SARS-CoV-2 Infection on Glucose Homeostasis in Hospitalized Patients with Pulmonary Impairment.","authors":"Oana-Andreea Parlițeanu, Mara-Amalia Bălteanu, Dragoș Cosmin Zaharia, Tudor Constantinescu, Alexandra Maria Cristea, Ștefan Dumitrache-Rujinscki, Andra Elena Nica, Cristiana Voineag, Octavian Sabin Alexe, Emilia Tabacu, Alina Croitoru, Irina Strâmbu, Roxana Maria Nemeș, Beatrice Mahler","doi":"10.3390/diagnostics15050554","DOIUrl":"10.3390/diagnostics15050554","url":null,"abstract":"<p><p><b>Background and Objectives:</b> We conducted a retrospective observational study to evaluate the impact of elevated blood glucose levels in patients with SARS-CoV-2 infection and a prior diagnosis of diabetes mellitus (DM) or newly diagnosed hyperglycemia. <b>Materials and Methods:</b> This study analyzed 6065 patients admitted to the COVID-19 departments of the \"Marius Nasta\" National Institute of Pulmonology in Bucharest, Romania, between 26 October 2020 and 5 January 2023. Of these, 813 patients (13.40%) were selected for analysis due to either a pre-existing diagnosis of DM or hyperglycemia at the time of hospital admission. <b>Results:</b> The erythrocyte sedimentation rate (ESR) and C-reactive protein (CRP) levels were elevated in patients with blood glucose levels exceeding 300 mg/dL. These elevations correlated with the presence of respiratory failure and increased mortality rates. Additionally, oxygen requirements were significantly higher at elevated blood glucose levels (<i>p</i> < 0.001), with a direct relationship between glycemia and oxygen demand. This was accompanied by lower oxygen saturation levels (<i>p</i> < 0.001). Maximum blood glucose levels were associated with the severity of respiratory failure (AUC 0.6, 95% CI: 0.56-0.63, <i>p</i> < 0.001). We identified cut-off values for blood glucose at admission (217.5 mg/dL) and maximum blood glucose during hospitalization (257.5 mg/dL), both of which were associated with disease severity and identified as risk factors for increased mortality. <b>Conclusions:</b> High blood glucose levels, both at admission and during hospitalization, were identified as risk factors for poor prognosis and increased mortality in patients with SARS-CoV-2 infection, regardless of whether the hyperglycemia was due to a prior diagnosis of DM or was newly developed during the hospital stay. These findings underscore the importance of glycemic control in the management of hospitalized COVID-19 patients.</p>","PeriodicalId":11225,"journal":{"name":"Diagnostics","volume":"15 5","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11898410/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143613960","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
An Integrated Deep Learning Model with EfficientNet and ResNet for Accurate Multi-Class Skin Disease Classification.
IF 3 3区 医学 Q1 MEDICINE, GENERAL & INTERNAL Pub Date : 2025-02-25 DOI: 10.3390/diagnostics15050551
Madallah Alruwaili, Mahmood Mohamed

Background: Medical diagnosis for skin diseases, including leukemia, early skin cancer, benign neoplasms, and alternative disorders, becomes difficult because of external variations among groups of patients. A research goal is to create a fusion-level deep learning model that improves stability and skin disease classification performance. Methods: The model design merges three convolutional neural networks (CNNs): EfficientNet-B0, EfficientNet-B2, and ResNet50, which operate independently under distinct branches. The neural network model uses its capability to extract detailed features from multiple strong architectures to reach accurate results along with tight classification precision. A fusion mechanism completes its operation by transmitting extracted features to dense and dropout layers for generalization and reduced dimensionality. Analyses for this research utilized the 27,153-image Kaggle Skin Diseases Image Dataset, which distributed testing materials into training (80%), validation (10%), and testing (10%) portions for ten skin disorder classes. Results: Evaluation of the proposed model revealed 99.14% accuracy together with excellent precision, recall, and F1-score metrics. Conclusions: The proposed deep learning approach demonstrates strong potential as a starting point for dermatological diagnosis automation since it shows promise for clinical use in skin disease classification.

{"title":"An Integrated Deep Learning Model with EfficientNet and ResNet for Accurate Multi-Class Skin Disease Classification.","authors":"Madallah Alruwaili, Mahmood Mohamed","doi":"10.3390/diagnostics15050551","DOIUrl":"10.3390/diagnostics15050551","url":null,"abstract":"<p><p><b>Background:</b> Medical diagnosis for skin diseases, including leukemia, early skin cancer, benign neoplasms, and alternative disorders, becomes difficult because of external variations among groups of patients. A research goal is to create a fusion-level deep learning model that improves stability and skin disease classification performance. <b>Methods:</b> The model design merges three convolutional neural networks (CNNs): EfficientNet-B0, EfficientNet-B2, and ResNet50, which operate independently under distinct branches. The neural network model uses its capability to extract detailed features from multiple strong architectures to reach accurate results along with tight classification precision. A fusion mechanism completes its operation by transmitting extracted features to dense and dropout layers for generalization and reduced dimensionality. Analyses for this research utilized the 27,153-image Kaggle Skin Diseases Image Dataset, which distributed testing materials into training (80%), validation (10%), and testing (10%) portions for ten skin disorder classes. <b>Results:</b> Evaluation of the proposed model revealed 99.14% accuracy together with excellent precision, recall, and F1-score metrics. <b>Conclusions:</b> The proposed deep learning approach demonstrates strong potential as a starting point for dermatological diagnosis automation since it shows promise for clinical use in skin disease classification.</p>","PeriodicalId":11225,"journal":{"name":"Diagnostics","volume":"15 5","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11898587/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143613593","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Evaluation of Xpert® Carba-R Assay Performance from FecalSwab™ Samples.
IF 3 3区 医学 Q1 MEDICINE, GENERAL & INTERNAL Pub Date : 2025-02-25 DOI: 10.3390/diagnostics15050556
Nicla Giovacchini, Chiara Chilleri, Ilaria Baccani, Eleonora Riccobono, Gian Maria Rossolini, Alberto Antonelli

Background/Objectives: The emergence and spread of carbapenemase-producing Enterobacterales (CPE) represents a significant challenge prompting the need to optimize diagnostic tools to detect CPE carriers. The Xpert® Carba-R assay (Cepheid, Sunnyvale, CA, USA), a Real-Time PCR-based test, can detect the blaKPC, blaVIM, blaOXA-48, blaNDM and blaIMP carbapenemase genes directly from rectal swabs. This study assessed the performance of the Xpert® Carba-R assay using FecalSwab™ (Copan, Brescia, Italy), a liquid-based collection device. Methods: The first part of the study aimed to establish the FecalSwabTM volume which gave the most similar Ct values to those obtained by the Transystem™ double swab (Copan). The best volume was then used to assess the limit of detection (LoD) for each target and compare the accuracy of different FecalSwabTM storage conditions (room temperature or 4 °C after 16 h compared to T0). Results: The results indicated that using 200 µL of the FecalSwab™ medium provided reliable Ct values, with the lowest number of invalid samples compared to traditional methods. The average LoDs for different carbapenemases ranged from 4.7 × 103 to 6.8 × 103 CFU/mL. FecalSwab™ showed a better performance after 16 h at room temperature compared to storage at 4 °C. Conclusions: This study supports single sampling with the FecalSwab™ medium for both molecular and cultural methods, for the potential optimization of CPE screening.

{"title":"Evaluation of Xpert<sup>®</sup> Carba-R Assay Performance from FecalSwab™ Samples.","authors":"Nicla Giovacchini, Chiara Chilleri, Ilaria Baccani, Eleonora Riccobono, Gian Maria Rossolini, Alberto Antonelli","doi":"10.3390/diagnostics15050556","DOIUrl":"10.3390/diagnostics15050556","url":null,"abstract":"<p><p><b>Background/Objectives</b>: The emergence and spread of carbapenemase-producing <i>Enterobacterales</i> (CPE) represents a significant challenge prompting the need to optimize diagnostic tools to detect CPE carriers. The Xpert<sup>®</sup> Carba-R assay (Cepheid, Sunnyvale, CA, USA), a Real-Time PCR-based test, can detect the <i>bla</i><sub>KPC</sub>, <i>bla</i><sub>VIM</sub>, <i>bla</i><sub>OXA-48</sub>, <i>bla</i><sub>NDM</sub> and <i>bla</i><sub>IMP</sub> carbapenemase genes directly from rectal swabs. This study assessed the performance of the Xpert<sup>®</sup> Carba-R assay using FecalSwab™ (Copan, Brescia, Italy), a liquid-based collection device. <b>Methods</b>: The first part of the study aimed to establish the FecalSwab<sup>TM</sup> volume which gave the most similar Ct values to those obtained by the Transystem™ double swab (Copan). The best volume was then used to assess the limit of detection (LoD) for each target and compare the accuracy of different FecalSwab<sup>TM</sup> storage conditions (room temperature or 4 °C after 16 h compared to T<sub>0</sub>). <b>Results</b>: The results indicated that using 200 µL of the FecalSwab™ medium provided reliable Ct values, with the lowest number of invalid samples compared to traditional methods. The average LoDs for different carbapenemases ranged from 4.7 × 10<sup>3</sup> to 6.8 × 10<sup>3</sup> CFU/mL. FecalSwab™ showed a better performance after 16 h at room temperature compared to storage at 4 °C. <b>Conclusions</b>: This study supports single sampling with the FecalSwab™ medium for both molecular and cultural methods, for the potential optimization of CPE screening.</p>","PeriodicalId":11225,"journal":{"name":"Diagnostics","volume":"15 5","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11898457/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143613676","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Water Hammer Phenomenon in Coronary Arteries: Scientific Basis for Diagnostic and Predictive Modeling with Acoustic Action Mapping.
IF 3 3区 医学 Q1 MEDICINE, GENERAL & INTERNAL Pub Date : 2025-02-25 DOI: 10.3390/diagnostics15050553
Khiem D Ngo, Thach Nguyen, Huan Dat Pham, Hadrian Tran, Dat Q Ha, Truong S Dinh, Imran Mihas, Mihas Kodenchery, C Michael Gibson, Hien Q Nguyen, Thang Nguyen, Vu T Loc, Chinh D Nguyen, Hoang Anh Tien, Ernest Talarico, Marco Zuin, Gianluca Rigatelli, Aravinda Nanjundappa, Quynh T N Nguyen, The-Hung Nguyen

Background: In the study of coronary artery disease, the mechanisms underlying atherosclerosis initiation and progression or regression remain incompletely understood. Our research conceptualized the cardiovascular system as an integrated network of pumps and pipes, advocating for a paradigm shift from static imaging of coronary stenosis to dynamic assessments of coronary flow. Further review of fluid mechanics highlighted the water hammer phenomenon as a compelling analog for processes in coronary arteries. Methods: In this review, the analytical methodology employed a comprehensive, multifaceted approach that incorporated a review of fluid mechanics principles, in vitro acoustic experimentation, frame-by-frame visual angiographic assessments of in vivo coronary flow, and an artificial intelligence (AI) protocol designed to analyze the water hammer phenomenon within an acoustic framework. In the analysis of coronary flow, the angiograms were selected from patients with unstable angina if they had previously undergone one or more coronary angiograms, allowing for a longitudinal comparison of dynamic flow and phenomena. Results: The acoustic investigations pinpointed pockets of contrast concentrations, which might correspond to compression and rarefaction zones. Compression antinodes were correlated to severe stenosis, due to rapid shifts from low-pressure diastolic flow to high-pressure systolic surges, resulting in intimal injury. Rarefaction antinodes were correlated with milder lesions, due to de-escalating transitions from high systolic pressure to lower diastolic pressure. The areas of nodes remained without lesions. Based on the locations of antinodes and nodes, a coronary acoustic action map was constructed, enabling the identification of existing lesions, forecasting the progression of current lesions, and predicting the development of future lesions. Conclusions: The results suggested that intimal injury was likely induced by acoustic retrograde pressure waves from the water hammer phenomenon and developed new lesions at specifically exact locations.

{"title":"Water Hammer Phenomenon in Coronary Arteries: Scientific Basis for Diagnostic and Predictive Modeling with Acoustic Action Mapping.","authors":"Khiem D Ngo, Thach Nguyen, Huan Dat Pham, Hadrian Tran, Dat Q Ha, Truong S Dinh, Imran Mihas, Mihas Kodenchery, C Michael Gibson, Hien Q Nguyen, Thang Nguyen, Vu T Loc, Chinh D Nguyen, Hoang Anh Tien, Ernest Talarico, Marco Zuin, Gianluca Rigatelli, Aravinda Nanjundappa, Quynh T N Nguyen, The-Hung Nguyen","doi":"10.3390/diagnostics15050553","DOIUrl":"10.3390/diagnostics15050553","url":null,"abstract":"<p><p><b>Background:</b> In the study of coronary artery disease, the mechanisms underlying atherosclerosis initiation and progression or regression remain incompletely understood. Our research conceptualized the cardiovascular system as an integrated network of pumps and pipes, advocating for a paradigm shift from static imaging of coronary stenosis to dynamic assessments of coronary flow. Further review of fluid mechanics highlighted the water hammer phenomenon as a compelling analog for processes in coronary arteries. <b>Methods:</b> In this review, the analytical methodology employed a comprehensive, multifaceted approach that incorporated a review of fluid mechanics principles, in vitro acoustic experimentation, frame-by-frame visual angiographic assessments of in vivo coronary flow, and an artificial intelligence (AI) protocol designed to analyze the water hammer phenomenon within an acoustic framework. In the analysis of coronary flow, the angiograms were selected from patients with unstable angina if they had previously undergone one or more coronary angiograms, allowing for a longitudinal comparison of dynamic flow and phenomena. <b>Results:</b> The acoustic investigations pinpointed pockets of contrast concentrations, which might correspond to compression and rarefaction zones. Compression antinodes were correlated to severe stenosis, due to rapid shifts from low-pressure diastolic flow to high-pressure systolic surges, resulting in intimal injury. Rarefaction antinodes were correlated with milder lesions, due to de-escalating transitions from high systolic pressure to lower diastolic pressure. The areas of nodes remained without lesions. Based on the locations of antinodes and nodes, a coronary acoustic action map was constructed, enabling the identification of existing lesions, forecasting the progression of current lesions, and predicting the development of future lesions. <b>Conclusions:</b> The results suggested that intimal injury was likely induced by acoustic retrograde pressure waves from the water hammer phenomenon and developed new lesions at specifically exact locations.</p>","PeriodicalId":11225,"journal":{"name":"Diagnostics","volume":"15 5","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11899655/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143613922","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Digital Age and Medicine: Visualization and Evaluation of Foot Anatomy with Artificial Intelligence.
IF 3 3区 医学 Q1 MEDICINE, GENERAL & INTERNAL Pub Date : 2025-02-25 DOI: 10.3390/diagnostics15050550
Ferda Başgün, Tuba Altunbey, Sevinç Ay, Derya Öztürk Söylemez, Elif Emre, Nurseda Başgün

Background/Objectives: Artificial intelligence (AI) has attracted great interest due to its applicability in many fields. The adoption of visual illustration techniques produced by AI in the field of graphic design has further expanded the field of use of this technology. This study focuses on foot anatomy illustrations generated by Adobe Firefly and Microsoft Designer Image Creator applications, evaluating them based on detail, clarity, anatomical realism, accuracy, and aesthetic appeal. Methods: The illustrations were created using text-based scripts, and five anatomists compared them to traditional illustrations from the Sobotta Atlas of Human Anatomy. Results: Fleiss' Kappa statistic was used to analyze consistency among expert evaluations. For the four figures generated by both AI applications, Fleiss' Kappa agreement was high. Adobe Firefly performed slightly better in illustrating phalanx and ankle bones, but its anatomical accuracy was lower for tarsal and metatarsal bones. Microsoft Designer Image Creator excelled in illustrating metatarsal bones, while its tarsal and phalanx illustrations were less anatomically accurate than Adobe Firefly and the atlas drawings. Both programs showed average realism in ankle structures, while the tarsal bones had low realism. Conclusions: Artificial intelligence applications within the scope of the study showed fast performance. Aesthetic appeal is dominant at first glance in the resulting drawings. In general, both applications have struggled to reflect anatomical reality.

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引用次数: 0
Radiofrequency Echographic Multi Spectrometry-A Novel Tool in the Diagnosis of Osteoporosis and Prediction of Fragility Fractures: A Systematic Review.
IF 3 3区 医学 Q1 MEDICINE, GENERAL & INTERNAL Pub Date : 2025-02-25 DOI: 10.3390/diagnostics15050555
Elena Icătoiu, Andreea-Iulia Vlădulescu-Trandafir, Laura-Maria Groșeanu, Florian Berghea, Claudia-Oana Cobilinschi, Claudia-Gabriela Potcovaru, Andra-Rodica Bălănescu, Violeta-Claudia Bojincă

Background/Objectives: Given the significant economic and social burden of osteoporosis, there is growing interest in developing an efficient alternative to the traditional dual-energy X-ray absorptiometry (DXA). Radiofrequency Echographic Multi Spectrometry (REMS) is an innovative, non-ionizing imaging technique that recently emerged as a viable tool to diagnose osteoporosis and estimate the fragility fracture risk. Nevertheless, its clinical use is still limited due to its novelty and continuing uncertainty of long-term performance. Methods: In order to evaluate the accuracy of the REMS, a systematic review of the English-language literature was conducted. Three databases were searched for relevant publications from 1 January 2015 until 1 December 2024 using the keyword combinations "(radiofrequency echographic multi spectrometry OR REMS) AND (dual-energy X-ray absorptiometry OR DXA)". The initial search yielded 602 candidate articles. After screening the titles and abstracts following the eligibility criteria, 17 publications remained for full-text evaluation. Results: The reviewed studies demonstrated strong diagnostic agreement between REMS and DXA. Additionally, REMS showed enhanced diagnostic capabilities in cases where lumbar bone mineral density measurements by DXA were impaired by artifacts such as vertebral fractures, deformities, osteoarthritis, or vascular calcifications. REMS exhibited excellent intra-operator repeatability and precision, comparable to or exceeding the reported performance of DXA. The fragility score (FS), a parameter reflecting bone quality and structural integrity, effectively discriminated between fractured and non-fractured patients. Moreover, REMS proved to be a radiation-free option for bone health monitoring in radiation-sensitive populations or patients requiring frequent imaging to assess fracture risk. Conclusions: This current study underscores the robustness of REMS as a reliable method for diagnosing and monitoring osteoporosis and evaluating bone fragility via the FS. It also identifies critical knowledge gaps and emphasizes the need for further prospective studies to validate and expand the clinical applications of REMS across diverse patient populations.

背景/目标:鉴于骨质疏松症造成的巨大经济和社会负担,人们对开发传统双能 X 射线吸收测量法 (DXA) 的高效替代方法越来越感兴趣。射频回声多谱仪(REMS)是一种创新的非电离成像技术,最近已成为诊断骨质疏松症和估算脆性骨折风险的可行工具。然而,由于其新颖性和长期性能的不确定性,其临床应用仍然有限。方法:为了评估 REMS 的准确性,我们对英文文献进行了系统性回顾。使用关键词组合"(射频回波多谱勒或 REMS)和(双能 X 射线吸收测量或 DXA)"检索了三个数据库中 2015 年 1 月 1 日至 2024 年 12 月 1 日期间的相关出版物。初步搜索结果为 602 篇候选文章。按照资格标准对标题和摘要进行筛选后,剩下 17 篇文章进行全文评估。结果:经审查的研究表明,REMS 和 DXA 在诊断方面具有很强的一致性。此外,当 DXA 测量的腰椎骨矿物质密度受到椎体骨折、畸形、骨关节炎或血管钙化等伪影的影响时,REMS 显示出更强的诊断能力。REMS 显示出极佳的术者内可重复性和精确性,可媲美或超过已报道的 DXA 性能。脆性评分(FS)是反映骨骼质量和结构完整性的参数,它能有效区分骨折和非骨折患者。此外,对于辐射敏感人群或需要频繁进行成像以评估骨折风险的患者,REMS 被证明是一种无辐射的骨健康监测选择。结论:目前的这项研究强调了 REMS 作为诊断和监测骨质疏松症以及通过 FS 评估骨脆性的可靠方法的稳健性。研究还发现了一些关键的知识空白,并强调有必要进一步开展前瞻性研究,以验证和扩大 REMS 在不同患者群体中的临床应用。
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引用次数: 0
Breast Cancer Detection via Multi-Tiered Self-Contrastive Learning in Microwave Radiometric Imaging.
IF 3 3区 医学 Q1 MEDICINE, GENERAL & INTERNAL Pub Date : 2025-02-25 DOI: 10.3390/diagnostics15050549
Christoforos Galazis, Huiyi Wu, Igor Goryanin

Background: Early and accurate detection of breast cancer is crucial for improving treatment outcomes and survival rates. To achieve this, innovative imaging technologies such as microwave radiometry (MWR)-which measures internal tissue temperature-combined with advanced diagnostic methods like deep learning are essential. Methods: To address this need, we propose a hierarchical self-contrastive model for analyzing MWR data, called Joint-MWR (J-MWR). J-MWR focuses on comparing temperature variations within an individual by analyzing corresponding sub-regions of the two breasts, rather than across different samples. This approach enables the detection of subtle thermal abnormalities that may indicate potential issues. Results: We evaluated J-MWR on a dataset of 4932 patients, demonstrating improvements over existing MWR-based neural networks and conventional contrastive learning methods. The model achieved a Matthews correlation coefficient of 0.74 ± 0.02, reflecting its robust performance. Conclusions: These results emphasize the potential of intra-subject temperature comparison and the use of deep learning to replicate traditional feature extraction techniques, thereby improving accuracy while maintaining high generalizability.

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引用次数: 0
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Diagnostics
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