Diagnostics最新文献

{"title":"Deep Learning Image Processing Models in Dermatopathology.","authors":"Apoorva Mehta, Mateen Motavaf, Danyal Raza, Neil Jairath, Akshay Pulavarty, Ziyang Xu, Michael A Occidental, Alejandro A Gru, Alexandra Flamm","doi":"10.3390/diagnostics15192517","DOIUrl":"10.3390/diagnostics15192517","url":null,"abstract":"<p><p>Dermatopathology has rapidly advanced due to the implementation of deep learning models and artificial intelligence (AI). From convolutional neural networks (CNNs) to transformer-based foundation models, these systems are now capable of accurate whole-slide analysis and multimodal integration. This review synthesizes the most recent advents of deep-learning architecture and synthesizes its evolution from first-generation CNNs to hybrid CNN-transformer systems to large-scale foundational models such as Paige's PanDerm AI and Virchow. Herein, we examine performance benchmarks from real-world deployments of major dermatopathology deep learning models (DermAI, PathAssist Derm), as well as emerging next-generation models still under research and development. We assess barriers to clinical workflow adoption such as dataset bias, AI interpretability, and government regulation. Further, we discuss potential future research directions and emphasize the need for diverse, prospectively curated datasets, explainability frameworks for trust in AI, and rigorous compliance to Good Machine-Learning-Practice (GMLP) to achieve safe and scalable deep learning dermatopathology models that can fully integrate into clinical workflows.</p>","PeriodicalId":11225,"journal":{"name":"Diagnostics","volume":"15 19","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12523352/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145299097","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}

{"title":"Evaluation of the Effectiveness of Botulinum Therapy Based on the Anthropometric Characteristics of the Face Using Non-Invasive Thermal Imaging Data.","authors":"Olesya Kytko, Yuriy Vasil'ev, Ekaterina Emelyanova, Evgeniy Kutin, Ramin Sarmadian, Sofia Trofimova, Irina Kondrina, Alexander Moiseenko, Sergey Dydykin, Ekaterina Rebrova","doi":"10.3390/diagnostics15192519","DOIUrl":"10.3390/diagnostics15192519","url":null,"abstract":"<p><p><b>Objective</b>: The objective of this study was to clarify the connection between BTX-A injections and local changes in skin temperature and to assess the correlation between post-BTX-A injection facial vascular hyperthermia and subcutaneous adipose tissue thickness (SAT) in the frontal area using thermography. <b>Methods</b>: The study involved 30 patients (mean age 42 ± 0.5 years; 18 women, 12 men). Facial skin temperature was measured via thermography (Thermo GEAR G30) before, immediately after, and 20 min after subcutaneous injection of BTX-A with hemagglutinin complex, gelatin (6 mg), and maltose monohydrate (12 mg). SAT development was graded by combined visual-palpation assessment. Statistical analysis included Student's <i>t</i>-test and the Mann-Whitney U-test. <b>Results</b>: Biphasic thermal response: immediately post-injection: Significant decrease in min (-1.1 °C) and mean (-0.3 °C) facial temperatures (<i>p</i> < 0.05); 20 min post-injection: pronounced increase in mean (+1.5 °C), max (+1.3 °C), and min (+1.6 °C) temperatures (<i>p</i> < 0.001), attributed to BTX-A-induced vasodilation and local inflammation. Subjects with pronounced SAT exhibited significantly higher baseline temperatures (Me = 33.1 °C vs. 29.8 °C; <i>p</i> < 0.001) and more intense hyperthermic responses (+1.6 °C mean increase vs. +1.1 °C in low-SAT group; <i>p</i> < 0.001). Pronounced SAT was predominantly female (10/15; <i>p</i> < 0.05) and linked to higher BMI (33.3% overweight vs. 0% in low-SAT; *<i>p</i> = 0.036*). <b>Conclusions</b>: SAT thickness is a key determinant of post-BTX-A vascular hyperthermia, with pronounced SAT predicting stronger reactions. <b>Practical Recommendation</b>: Targeted local hypothermia (+4 °C to +8 °C for 5-7 min post-injection, adjustable by SAT thickness) mitigates hyperemia, edema, hematoma risk, and potential toxin diffusion, especially in high-SAT individuals.</p>","PeriodicalId":11225,"journal":{"name":"Diagnostics","volume":"15 19","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12524183/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145299101","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}

{"title":"Emerging Radioligands as Tools to Track Multi-Organ Senescence.","authors":"Anna Gagliardi, Silvia Migliari, Alessandra Guercio, Giorgio Baldari, Tiziano Graziani, Veronica Cervati, Livia Ruffini, Maura Scarlattei","doi":"10.3390/diagnostics15192518","DOIUrl":"10.3390/diagnostics15192518","url":null,"abstract":"<p><p>Senescence is a dynamic, multifaceted process implicated in tissue aging, organ dysfunction, and intricately associated with numerous chronic diseases. As senescent cells accumulate, they drive inflammation, fibrosis, and metabolic disruption through the senescence-associated secretory phenotype (SASP). Despite its clinical relevance, senescence remains challenging to detect non-invasively due to its heterogeneous nature and the lack of universal biomarkers. Recent advances in the development of specific imaging probes for positron emission tomography (PET) enable in vivo visualization of senescence-associated pathways across key organs, such as the lung, heart, kidney, and metabolic processes. For instance, [¹⁸F]FPyGal, a β-galactosidase-targeted tracer, has demonstrated selective accumulation in senescent cells in both preclinical and early clinical studies, while FAP-targeted radioligands are emerging as tools for imaging fibrotic remodeling in the lung, liver, kidney, and myocardium. This review examines a new generation of PET radioligands targeting hallmark features of senescence, with the potential to track and measure the process, the ability to be translated into clinical interventions for early diagnosis, and longitudinal monitoring of senescence-driven pathologies. By integrating organ-specific imaging biomarkers with molecular insights, PET probes are poised to transform our ability to manage and treat age-related diseases through personalized approaches.</p>","PeriodicalId":11225,"journal":{"name":"Diagnostics","volume":"15 19","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12523902/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145298895","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}

{"title":"The Predictive Power of Barotrauma from the Macklin Effect in the ARDS Population: A Comparison of COVID-19 and Non-COVID-19 ARDS-Could the Macklin Effect Serve as a Helpful Tool for Evaluating Transfer to ARDS Reference Centers?","authors":"Alberto Marabotti, Filippo Pelagatti, Gianluca Frezzetti, Marco Albanesi, Antonio Galluzzo, Alessandra Valletta, Laura Arianna Sorrentino, Andrea Cardoni, Giovanni Cianchi, Marco Ciapetti, Chiara Lazzeri, Adriano Peris, Manuela Bonizzoli","doi":"10.3390/diagnostics15192514","DOIUrl":"10.3390/diagnostics15192514","url":null,"abstract":"<p><p><b>Background:</b> The Macklin effect recently demonstrated a high positive predictive value for barotrauma in the COVID-19 ARDS population. However, there was less evidence available regarding the ARDS population without SARS-CoV-2 infection. We aim to analyze COVID-19 and non-COVID-19 ARDS subjects to assess the sensitivity and specificity of the Macklin effect in predicting the development of barotrauma in both groups. <b>Methods:</b> We retrospectively analyzed subjects with ARDS admitted to our center from January 2018 to November 2022. Experienced radiologists examined the presence of the Macklin effect on chest computed tomography scans. Subjects were then divided into two groups based on the presence or absence of the Macklin effect to assess its predictive power regarding barotrauma. Finally, we analyzed the impact of the Macklin effect and barotrauma on Intensive Care Unit and in-hospital mortality. <b>Results:</b> We analyzed 225 patients; the Macklin effect was observed in 44 subjects. In our cohort, the Macklin effect exhibited a sensitivity of 44.6% and a specificity of 90.6% in predicting barotrauma. After excluding the COVID-19 ARDS cases, the Macklin effect showed a sensitivity of 34.7% and a specificity of 93.6%. Nonetheless, in our population, the presence of the Macklin effect or the occurrence of barotrauma did not lead to increased ICU or in-hospital mortality. <b>Conclusions:</b> Our analysis highlighted that the Macklin effect demonstrates high specificity in predicting barotrauma but a low sensitivity; moreover, the development of barotrauma did not impact mortality, possibly due to the exclusion of mild to moderate ARDS and the inclusion of a significant number of ECMO recipients. Finally, the Macklin effect appears early during ARDS and may serve as an early indicator of lung frailty, potentially becoming an additional criterion for referral to centers for advanced ARDS treatment.</p>","PeriodicalId":11225,"journal":{"name":"Diagnostics","volume":"15 19","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12523701/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145299087","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}

{"title":"The Clinical Features and Prognosis of Idiopathic and Infection-Triggered Acute Exacerbation of Idiopathic Inflammatory Myopathy-Associated Interstitial Lung Disease: A Preliminary Study.","authors":"Jingping Zhang, Kai Yang, Lingfei Mo, Liyu He, Jiayin Tong, He Hei, Yuting Zhang, Yadan Sheng, Blessed Kondowe, Chenwang Jin","doi":"10.3390/diagnostics15192516","DOIUrl":"10.3390/diagnostics15192516","url":null,"abstract":"<p><p><b>Background</b>: Acute exacerbation (AE) of idiopathic inflammatory myopathy-associated interstitial lung disease (IIM-ILD) is fatal. Infection is one of the most important triggers of the AE of IIM-ILD. We evaluated the clinical features and prognosis of idiopathic (I-AE) and infection-triggered (iT-AE) acute exacerbation in IIM-ILD patients. <b>Methods</b>: We retrospectively reviewed 278 consecutive patients with IIM admitted to our hospital between January 2014 and December 2020. Among them, 69 patients experienced AE of IIM-ILD, including 34 with I-AE and 35 with iT-AE. Clinical features and short- and long-term outcomes were analyzed in this preliminary study. <b>Results</b>: Compared with I-AE, patients with iT-AE presented with lower hemoglobin and PaO₂/FiO₂ ratios but higher pulse, body temperature, white blood cell count, neutrophil percentage (NEU), C-reactive protein, erythrocyte sedimentation rates, lactate dehydrogenase, and hydroxybutyrate dehydrogenase levels. They also had more extensive ground-glass opacities (GGOs) on high-resolution computed tomography (all <i>p</i> < 0.05). Mortality was significantly higher in iT-AE than that in I-AE at 30 days (28.6% vs. 5.9%), 90 days (34.3% vs. 14.9%), and 1 year (54.3% vs. 17.6%; log-rank test, <i>p</i> = 0.002). Multivariate logistic regression showed that the combination of NEU and GGO extent could help discriminate iT-AE from I-AE (area under the receiver operating characteristic curve: 0.812; 95% confidence interval: 0.711-0.913; sensitivity: 71.4%, specificity: 73.5%, accuracy: 72.5%). <b>Conclusion</b>: This study found that iT-AE patients exhibited more severe hyperinflammation and markedly worse survival than I-AE patients. Combining NEU and GGO extent may assist in differentiating AE subtypes. Larger prospective studies are required to validate these findings.</p>","PeriodicalId":11225,"journal":{"name":"Diagnostics","volume":"15 19","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12523335/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145299150","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}

{"title":"EfficientNet-B3-Based Automated Deep Learning Framework for Multiclass Endoscopic Bladder Tissue Classification.","authors":"A A Abd El-Aziz, Mahmood A Mahmood, Sameh Abd El-Ghany","doi":"10.3390/diagnostics15192515","DOIUrl":"10.3390/diagnostics15192515","url":null,"abstract":"<p><p><b>Background:</b> Bladder cancer (BLCA) is a malignant growth that originates from the urothelial lining of the urinary bladder. Diagnosing BLCA is complex due to the variety of tumor features and its heterogeneous nature, which leads to significant morbidity and mortality. Understanding tumor histopathology is crucial for developing tailored therapies and improving patient outcomes. <b>Objectives:</b> Early diagnosis and treatment are essential to lower the mortality rate associated with bladder cancer. Manual classification of muscular tissues by pathologists is labor-intensive and relies heavily on experience, which can result in interobserver variability due to the similarities in cancerous cell morphology. Traditional methods for analyzing endoscopic images are often time-consuming and resource-intensive, making it difficult to efficiently identify tissue types. Therefore, there is a strong demand for a fully automated and reliable system for classifying smooth muscle images. <b>Methods:</b> This paper proposes a deep learning (DL) technique utilizing the EfficientNet-B3 model and a five-fold cross-validation method to assist in the early detection of BLCA. This model enables timely intervention and improved patient outcomes while streamlining the diagnostic process, ultimately reducing both time and costs for patients. We conducted experiments using the Endoscopic Bladder Tissue Classification (EBTC) dataset for multiclass classification tasks. The dataset was preprocessed using resizing and normalization methods to ensure consistent input. In-depth experiments were carried out utilizing the EBTC dataset, along with ablation studies to evaluate the best hyperparameters. A thorough statistical analysis and comparisons with five leading DL models-ConvNeXtBase, DenseNet-169, MobileNet, ResNet-101, and VGG-16-showed that the proposed model outperformed the others. <b>Conclusions:</b> The EfficientNet-B3 model achieved impressive results: accuracy of 99.03%, specificity of 99.30%, precision of 97.95%, recall of 96.85%, and an F1-score of 97.36%. These findings indicate that the EfficientNet-B3 model demonstrates significant potential in accurately and efficiently diagnosing BLCA. Its high performance and ability to reduce diagnostic time and cost make it a valuable tool for clinicians in the field of oncology and urology.</p>","PeriodicalId":11225,"journal":{"name":"Diagnostics","volume":"15 19","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12523409/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145298942","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}

{"title":"SarcoNet: A Pilot Study on Integrating Clinical and Kinematic Features for Sarcopenia Classification.","authors":"Muthamil Balakrishnan, Janardanan Kumar, Jaison Jacob Mathunny, Varshini Karthik, Ashok Kumar Devaraj","doi":"10.3390/diagnostics15192513","DOIUrl":"10.3390/diagnostics15192513","url":null,"abstract":"<p><p><b>Background and Objectives:</b> Sarcopenia is a progressive loss of skeletal muscle mass and function in elderly adults, posing a significant risk of frailty, falls, and morbidity. The current study designs and evaluates SarcoNet, a novel artificial neural network (ANN)-based classification framework developed in order to classify Sarcopenic from non-Sarcopenic subjects using a comprehensive real-time dataset. <b>Methods:</b> This pilot study involved 30 subjects, who were divided into Sarcopenic and non-Sarcopenic groups based on physician assessment. The collected dataset consists of thirty-one clinical parameters like skeletal muscle mass, which is collected using various equipment such as Body Composition Analyser, along with ten kinetic features which are derived from video-based gait analysis of joint angles obtained during walking on three terrain types such as slope, steps, and parallel path. The performance of the designed ANN-based SarcoNet was benchmarked against the traditional machine learning classifiers utilised including Support Vector Machine (SVM), k-Nearest Neighbours (k-NN), and Random Forest (RF), as well as hard and soft voting ensemble classifiers. <b>Results:</b> SarcoNet achieved the highest overall classification accuracy of about 94%, with a specificity and precision of about 100%, an F1-score of about 92.4%, and an AUC of 0.94, outperforming all other models. The incorporation of lower-limb joint kinetics such as knee flexion, extension, ankle plantarflexion and dorsiflexion significantly enhanced predictive capability of the model and thus reflecting the functional deterioration characteristic of muscles in Sarcopenia. <b>Conclusions:</b> SarcoNet provides a promising AI-driven solution in Sarcopenia diagnosis, especially in low-resource healthcare settings. Future work will focus on improving the dataset, validating the model across diverse populations, and incorporating explainable AI to improve clinical adoption.</p>","PeriodicalId":11225,"journal":{"name":"Diagnostics","volume":"15 19","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12523922/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145299200","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}

{"title":"Giant Bilateral Iliopsoas Abscesses, Secondary to Pott's Disease: Challenging Diagnostic-Therapeutic Protocol Management (Modern and Innovative Open Approach Technique Through J.L. Petit Triangle)-A Case Report and Literature Review.","authors":"Mihaela D Pîrvu, Cristian C Popa, Iulian Lupu, Cătălin N Grasa, Anca T Gheorghe, Vasile Sârbu","doi":"10.3390/diagnostics15192506","DOIUrl":"10.3390/diagnostics15192506","url":null,"abstract":"<p><p><b>Background and Clinical Significance:</b> Iliopsoas abscess has recently become a condition quite frequently present in our practice, arising through hematogenous or lymphatic dissemination (primary), or secondary to trauma or infectious-inflammatory vertebral, renal, or gastrointestinal diseases. It is often diagnosed with difficulty, due to the insidious and rather atypical symptomatology. The simultaneous relevance to neurosurgery, orthopedics, urology, rheumatology, and of course surgery, makes the iliopsoas abscess a real challenge in diagnosis and treatment for any of us, as well as collaboration between specialties. <b>Case Presentation</b>: The aim of this paper is to illustrate all this through a rare clinical case of vertebral tuberculosis, with giant abscesses of bilateral iliopsoas and comparison with data from the literature, through a review. <b>Conclusions</b>: The problems were related to the clinical-paraclinical, etiological diagnosis, surgical strategy, technique and tactics, surgical approach, treatment and immediate, and both long-term postoperative management. The ultimate goal is to reduce morbidity and mortality secondary to this often-disabling condition.</p>","PeriodicalId":11225,"journal":{"name":"Diagnostics","volume":"15 19","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12524242/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145299158","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}

{"title":"Significance of the Monitoring Right Ventricular Echocardiographic Parameters in Patients with Hypertrophic Cardiomyopathy Undergoing Alcohol Septal Ablation-A Single-Center Experience.","authors":"Tibor Poruban, Ingrid Schusterova, Dominik Pella, Jan Fedacko, Karolina Angela Sieradzka Uchnar, Barbora Sepesiova, Silvia Gurbalova","doi":"10.3390/diagnostics15192509","DOIUrl":"10.3390/diagnostics15192509","url":null,"abstract":"<p><p><b>Background/Objectives:</b> This study aimed to investigate the association between right ventricular (RV) structure and function and established markers of alcohol septal ablation (ASA) efficacy in patients with hypertrophic cardiomyopathy (HCM). We hypothesized that RV characteristics may serve as predictors of left ventricular outflow tract gradient (LVOT_G) in the early period following ASA. <b>Methods:</b> A retrospective analysis was performed in 50 HCM patients who underwent ASA. Correlations between echocardiographic RV parameters and standard indicators of ASA success were assessed at 3 months, 1 year, 3 years, and 5 years post-procedure. <b>Results:</b> Echocardiographic measurements of RV wall thickness (RVWT) at 3 months and 1 year after ASA showed significant correlations with maximum LVOT_G (<i>p</i> < 0.001), NYHA functional class, and left ventricular end-diastolic dimension (LV_D) (both <i>p</i> < 0.01). At 3 and 5 years, these correlations were no longer statistically significant (<i>p</i> = ns). No associations were observed for other parameters. <b>Conclusions:</b> Echocardiographic assessment of RVWT may serve as an early predictor of subsequent LVOT_G development as soon as 3 months after ASA. RVWT could therefore provide an estimate of long-term treatment effects. Further studies are needed to confirm these findings.</p>","PeriodicalId":11225,"journal":{"name":"Diagnostics","volume":"15 19","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12523401/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145298845","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}

{"title":"Echoes from Within: Mapping Gastrointestinal Obstruction with Ultrasound.","authors":"Lior Abramson, Rebecca G Theophanous, Brice Lefler, Lindsey Wu, Amber L Bowman, Jacqueline K Olive, Yuriy S Bronshteyn","doi":"10.3390/diagnostics15192511","DOIUrl":"10.3390/diagnostics15192511","url":null,"abstract":"<p><p>Patients presenting with abdominal pain and/or distension require rapid diagnostics to narrow the differential diagnosis from a long list of obstructive gastrointestinal (GI) pathologies that may appear clinically similar but warrant distinct management. While the workup of abdominal distension currently centers around computed tomography (CT), this modality is costly, requires radiation exposure, and necessitates patient transport, potentially delaying care. In contrast, point-of-care ultrasound (POCUS) avoids ionizing radiation and the need for patient transport while providing some insight into the gastrointestinal size and function. While POCUS cannot currently replace CT in the definitive diagnosis of GI obstructive pathologies, it remains a promising tool to help with the initial triage and monitoring responses to therapy for several causes of functional and/or mechanical GI obstruction, such as gastric dilation, ileus, and small bowel obstruction. Because the obstruction severity and features can evolve over time, POCUS enables serial examinations to monitor the progression or resolution. This manuscript reviews characteristic sonographic findings that help distinguish obstructive GI conditions and highlights practical techniques for integrating gastric and intestinal POCUS to improve diagnostic accuracy and expedite treatment.</p>","PeriodicalId":11225,"journal":{"name":"Diagnostics","volume":"15 19","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12523475/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145298907","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}