Ultrasound in Medicine and Biology最新文献

{"title":"SPACE: Subregion Perfusion Analysis for Comprehensive Evaluation of Breast Tumor Using Contrast-Enhanced Ultrasound-A Retrospective and Prospective Multicenter Cohort Study.","authors":"Yuhan Fu, Jifan Chen, Yijie Chen, Zimei Lin, Lei Ye, Dequan Ye, Fei Gao, Chaoxue Zhang, Pintong Huang","doi":"10.1016/j.ultrasmedbio.2025.05.008","DOIUrl":"https://doi.org/10.1016/j.ultrasmedbio.2025.05.008","url":null,"abstract":"<p><strong>Objective: </strong>To develop a dynamic contrast-enhanced ultrasound (CEUS)-based method for segmenting tumor perfusion subregions, quantifying tumor heterogeneity, and constructing models for distinguishing benign from malignant breast tumors.</p><p><strong>Methods: </strong>This retrospective-prospective cohort study analyzed CEUS videos of patients with breast tumors from four academic medical centers between September 2015 and October 2024. Pixel-based time-intensity curve (TIC) perfusion variables were extracted, followed by the generation of perfusion heterogeneity maps through cluster analysis. A combined diagnostic model incorporating clinical variables, subregion percentages, and radiomics scores was developed, and subsequently, a nomogram based on this model was constructed for clinical application.</p><p><strong>Results: </strong>A total of 339 participants were included in this bidirectional study. Retrospective data included 233 tumors divided into training and test sets. The prospective data comprised 106 tumors as an independent test set. Subregion analysis revealed Subregion 2 dominated benign tumors, while Subregion 3 was prevalent in malignant tumors. Among 59 machine-learning models, Elastic Net (ENET) (α = 0.7) performed best. Age and subregion radiomics scores were independent risk factors. The combined model achieved area under the curve (AUC) values of 0.93, 0.82, and 0.90 in the training, retrospective, and prospective test sets, respectively.</p><p><strong>Conclusion: </strong>The proposed CEUS-based method enhances visualization and quantification of tumor perfusion dynamics, significantly improving the diagnostic accuracy for breast tumors.</p>","PeriodicalId":49399,"journal":{"name":"Ultrasound in Medicine and Biology","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144561731","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correcting for Diffraction and Quantifying Volumetric Scatterer Concentration Using First-order Speckle Statistics.","authors":"Alexandra Christensen, Timothy J Hall, Helen Feltovich, Ivan Rosado-Mendez","doi":"10.1016/j.ultrasmedbio.2025.06.006","DOIUrl":"10.1016/j.ultrasmedbio.2025.06.006","url":null,"abstract":"<p><strong>Purpose: </strong>Speckle statistics are fundamentally related to the resolution of an ultrasound image. Existing models for speckle statistics do not account for changes in resolution with imaging depth, a reality of clinical pulse-echo ultrasound, thereby posing challenges to interpretation. The purpose of this work is to evaluate and address this shortfall in first-order speckle statistics analysis.</p><p><strong>Methods: </strong>Simulated ultrasonic speckle from a low scatterer density medium was created with known acquisition parameters, and speckle statistics of the Nakagami and homodyned K distributions were estimated with and without compensating for the expected change in the resolution cell size, defined by the ultrasound pulse volume, over the field of view. Compensation methods using resolution estimates from the predicted acoustic field, image autocorrelation, or spectral analysis were compared. The absolute number of scatterers per cubic millimeter was also calculated from corrected speckle statistics estimates. The results were validated with experiments in a low scatterer density phantom using a clinical scanner, and in in vivo rhesus macaque cervix and human Achilles tendon images.</p><p><strong>Results: </strong>It was shown in both simulations and phantoms that, when no compensation was applied, the expansion of the resolution cell size caused a saturation of Nakagami m and homodyned K parameter estimates at depths beyond the focal distance, even when scatterer concentration was constant throughout the depth of the phantoms. This confounding factor was reduced by compensating for the changing resolution cell size, resulting in a decrease in the normalized root mean squared errors between estimates at focus and estimates at all depths (7.8 ± 0.3% to 5.1 ± 0.3% in m, 68 ± 2% to 9.1 ± 0.3% in α, and 40 ± 1% to 6.8 ± 0.3% in k in simulated acquisitions; 21.5 ± 0.4% to 15.4 ± 0.4% in m, 291 ± 15% to 76 ± 12% in α, and 39 ± 1% to 21 ± 1% in k in phantom acquisitions). Images from in vivo analysis before and after compensation resulted in an increase in median contrast-to-noise ratio between the cervix and background and the Achilles tendon and background.</p><p><strong>Conclusion: </strong>Compensation for changes in ultrasonic resolution with depth prevents saturation in speckle statistics estimates, thus providing more relevant information about tissue properties. The methods described in this work reduce the system dependence of speckle statistics analysis, thus addressing a barrier to the clinical application and adoption of speckle statistics.</p>","PeriodicalId":49399,"journal":{"name":"Ultrasound in Medicine and Biology","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12233144/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144555533","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":"Transperineal Ultrasound Enhance Accuracy of Bowel Ultrasound in Assessing Disease Activity in Pediatric Ulcerative Colitis Patients.","authors":"Fulvia Terracciano, Antonella Marra, Fabrizio Bossa, Cristina Bucci, Angelica Dirodi, Francesco Esposito, Maria Rosa Pastore, Antonio Marseglia, Maria Rosa Valvano, Sonia Carparelli, Antonio Massimo Ippolito, Veronica Nassisi, Dolores Ferrara, Francesco Perri","doi":"10.1016/j.ultrasmedbio.2025.05.030","DOIUrl":"https://doi.org/10.1016/j.ultrasmedbio.2025.05.030","url":null,"abstract":"<p><strong>Objective: </strong>Ulcerative colitis (UC) is an inflammatory bowel disease involving the rectum and colon. Transabdominal bowel ultrasound (TBUS) is a noninvasive technique evaluating inflamed colonic segments. Previous studies showed optimal concordance between TBUS and endoscopy in the colon, but suboptimal in the rectum. Transperineal ultrasound (TPUS) of the rectum achieved high agreement with endoscopy in adult UC patients. This study aimed to assess the accuracy of ultrasound in evaluating disease activity in pediatric UC patients through TBUS and TPUS examinations.</p><p><strong>Methods: </strong>All pediatric UC patients who underwent endoscopy were consecutively enrolled. Disease activity was determined using the PUCAI score and the Mayo Endoscopic Score for each segment. Remission was defined as Mayo≤1 at endoscopy and bowel wall thickness ≤3 mm in the colon and ≤4 mm in the rectum at ultrasound examination. A concordance analysis comparing endoscopy and the US was performed overall and for each segment.</p><p><strong>Results: </strong>Twenty-six patients were enrolled. Ten patients had an endoscopic remission/inactive disease; 16 had moderate-severe colitis, of whom 6 had an isolated rectal involvement, and 10 had an active disease involving segments proximal to the rectum. We showed a good performance of TBUS for all colonic segments and for the rectum, when visible; the TPUS was a feasible technique with a good concordance with endoscopic findings (Cohen κ-value 0.77).</p><p><strong>Conclusion: </strong>In our pediatric population, both TBUS and TPUS showed an overall good correlation with endoscopy results and may represent a good surrogate of endoscopy, when not advisable.</p>","PeriodicalId":49399,"journal":{"name":"Ultrasound in Medicine and Biology","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144530694","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhanced Ultrasound Image Formation With Computationally Efficient Cross-Angular Delay Multiply and Sum Beamforming.","authors":"Cameron A B Smith, Matthieu Toulemonde, Marcelo Lerendegui, Kai Riemer, Dina Malounda, Peter D Weinberg, Mikhail G Shapiro, Meng-Xing Tang","doi":"10.1016/j.ultrasmedbio.2025.05.023","DOIUrl":"10.1016/j.ultrasmedbio.2025.05.023","url":null,"abstract":"<p><strong>Objective: </strong>Ultrasound imaging as a clinical tool is commonly achieved using the delay and sum (DAS) beamforming algorithm, which has limited resolution and suffers from high side lobes. Recently nonlinear processing has proven to be an effective way to enhance image quality. In this work, we describe a new beamforming algorithm called Cross-Angular Delay Multiply and Sum (CADMAS).</p><p><strong>Methods: </strong>CADMAS takes advantage of nonlinear compounding across planewave steering angles to enhance image contrast. This is then implemented with a mathematical reformulation to produce images at a low computational cost. We tested CADMAS in both conventional B-Mode and amplitude modulation imaging across in vitro and in vivo datasets, and for microbubbles and gas vesicles. We compared the results to DAS and two other nonlinear beamformers, frame multiply and sum (FMAS) and delay multiply and sum (DMAS), as well as the combination of the two.</p><p><strong>Results: </strong>Our results show on average across our datasets a 7.6 to 40 dB improvement in image contrast over DAS and a 4.8 to 20 dB improvement over DMAS. The computation time of CADMAS is between 1 and 2 times that of DAS; in our implementation we experienced a less than 6% increase in computation time.</p><p><strong>Conclusion: </strong>Our results show a robust improvement in contrast across multiple datasets both in vitro and in vivo, demonstrating its potential for biological and clinical applications.</p>","PeriodicalId":49399,"journal":{"name":"Ultrasound in Medicine and Biology","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144530691","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Novel Artificial Intelligence-Driven Infant Meningitis Screening From High-Resolution Ultrasound Imaging.","authors":"Hassan Ahmed Sial, Francesc Carandell, Sara Ajanovic, Javier Jiménez, Rita Quesada, Fabião Santos, W Chris Buck, Muhammad Sidat, Quique Bassat, Beatrice Jobst, Paula Petrone","doi":"10.1016/j.ultrasmedbio.2025.04.009","DOIUrl":"https://doi.org/10.1016/j.ultrasmedbio.2025.04.009","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Infant meningitis can be a life-threatening disease and requires prompt and accurate diagnosis to prevent severe outcomes or death. Gold-standard diagnosis requires lumbar puncture (LP) to obtain and analyze cerebrospinal fluid (CSF). Despite being standard practice, LPs are invasive, pose risks for the patient and often yield negative results, either due to contamination with red blood cells from the puncture itself or because LPs are routinely performed to rule out a life-threatening infection, despite the disease's relatively low incidence. Furthermore, in low-income settings where incidence is the highest, LPs and CSF exams are rarely feasible, and suspected meningitis cases are generally treated empirically. There is a growing need for non-invasive, accurate diagnostic methods.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methodology: &lt;/strong&gt;We developed a three-stage deep learning framework using Neosonics ultrasound technology for 30 infants with suspected meningitis and a permeable fontanelle at three Spanish University Hospitals (from 2021 to 2023). In stage 1, 2194 images were processed for quality control using a vessel/non-vessel model, with a focus on vessel identification and manual removal of images exhibiting artifacts such as poor coupling and clutter. This refinement process resulted in a final cohort comprising 16 patients-6 cases (336 images) and 10 controls (445 images), yielding 781 images for the second stage. The second stage involved the use of a deep learning model to classify images based on a white blood cell count threshold (set at 30 cells/mm&lt;sup&gt;3&lt;/sup&gt;) into control or meningitis categories. The third stage integrated explainable artificial intelligence (XAI) methods, such as Grad-CAM visualizations, alongside image statistical analysis, to provide transparency and interpretability of the model's decision-making process in our artificial intelligence-driven screening tool.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Our approach achieved 96% accuracy in quality control and 93% precision and 92% accuracy in image-level meningitis detection, with an overall patient-level accuracy of 94%. It identified 6 meningitis cases and 10 controls with 100% sensitivity and 90% specificity, demonstrating only a single misclassification. The use of gradient-weighted class activation mapping-based XAI significantly enhanced diagnostic interpretability, and to further refine our insights we incorporated a statistics-based XAI approach. By analyzing image metrics such as entropy and standard deviation, we identified texture variations in the images attributable to the presence of cells, which improved the interpretability of our diagnostic tool.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusion: &lt;/strong&gt;This study supports the efficacy of a multi-stage deep learning model for non-invasive screening of infant meningitis and its potential to guide the need for LPs. It also highlights the transformative potential of artificial intelligence in medical diagnostic screeni","PeriodicalId":49399,"journal":{"name":"Ultrasound in Medicine and Biology","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144530693","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deep Learning-Based Automated Detection of the Middle Cerebral Artery in Transcranial Doppler Ultrasound Examinations.","authors":"HyeonWoo Lee, William Shi, Rashid Al Mukaddim, Elizabeth Brunelle, Abhinav Palisetti, Syed M Imaduddin, Phavalan Rajendram, Diego Incontri, Vasileios-Arsenios Lioutas, Thomas Heldt, Balasundar I Raju","doi":"10.1016/j.ultrasmedbio.2025.05.028","DOIUrl":"https://doi.org/10.1016/j.ultrasmedbio.2025.05.028","url":null,"abstract":"<p><strong>Objective: </strong>Transcranial Doppler (TCD) ultrasound has significant clinical value for assessing cerebral hemodynamics, but its reliance on operator expertise limits broader clinical adoption. In this work, we present a lightweight real-time deep learning-based approach capable of automatically identifying the middle cerebral artery (MCA) in TCD Color Doppler images.</p><p><strong>Methods: </strong>Two state-of-the-art object detection models, YOLOv10 and Real-Time Detection Transformers (RT-DETR), were investigated for automated MCA detection in real-time. TCD Color Doppler data (41 subjects; 365 videos; 61,611 frames) were collected from neurologically healthy individuals (n = 31) and stroke patients (n = 10). MCA bounding box annotations were performed by clinical experts on all frames. Model training consisted of pretraining utilizing a large abdominal ultrasound dataset followed by subsequent fine-tuning on acquired TCD data. Detection performance at the instance and frame levels, and inference speed were assessed through four-fold cross-validation. Inter-rater agreement between model and two human expert readers was assessed using distance between bounding boxes and inter-rater variability was quantified using the individual equivalence coefficient (IEC) metric.</p><p><strong>Results: </strong>Both YOLOv10 and RT-DETR models showed comparable frame level accuracy for MCA presence, with F1 scores of 0.884 ± 0.023 and 0.884 ± 0.019 respectively. YOLOv10 outperformed RT-DETR for instance-level localization accuracy (AP: 0.817 vs. 0.780) and had considerably faster inference speed on a desktop CPU (11.6 ms vs. 91.14 ms). Furthermore, YOLOv10 showed an average inference time of 36 ms per frame on a tablet device. The IEC was -1.08 with 95 % confidence interval: [-1.45, -0.19], showing that the AI predictions deviated less from each reader than the readers' annotations deviated from each other.</p><p><strong>Conclusion: </strong>Real-time automated detection of the MCA is feasible and can be implemented on mobile platforms, potentially enabling wider clinical adoption by less-trained operators in point-of-care settings.</p>","PeriodicalId":49399,"journal":{"name":"Ultrasound in Medicine and Biology","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144530690","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of Contrast-Enhanced Ultrasound on Hepatic Two-Dimensional Shear Wave Elastography: Does Elastography Need to be Performed Before Contrast Administration?","authors":"Jiayao Huang, Qingyu Wu, Bowen Zhuang, Baoxian Liu, Lu Yao, Haiyi Long, Xian Zhong, Xiaoyan Xie, Liya Su, Manxia Lin","doi":"10.1016/j.ultrasmedbio.2025.05.029","DOIUrl":"https://doi.org/10.1016/j.ultrasmedbio.2025.05.029","url":null,"abstract":"<p><strong>Objective: </strong>The present study aims to explore the dynamic impact of contrast-enhanced ultrasound (CEUS) on hepatic two-dimensional shear wave elastography (2D-SWE), especially in its assessment of liver fibrosis, and to analyze the pathological and biological basis of this impact.</p><p><strong>Methods: </strong>From August 2023 to August 2024, 220 participants were prospectively enrolled, among which 111 underwent liver histopathological examination. The 2D-SWE examinations were conducted at the pre-CEUS phase, CEUS phase (5-6 min after the injection of SonoVue), early post-CEUS phase (8-10 min after the injection), and late post-CEUS phase (25-30 min after the injection), respectively. Analysis of variance compared the indexes across different phases. Multivariate linear regression analyses identified the factors influencing the difference in 2D-SWE measurement values (Emean) between pre-CEUS and CEUS phases.</p><p><strong>Results: </strong>Emean at the CEUS phase and early post-CEUS phase was significantly lower than the pre-CEUS levels [the mean difference was 1.70 kPa and 0.90 kPa, respectively, both p < 0.001]. At the late post-CEUS phase, the Emean returned to the pre-CEUS levels (p = 0.078). Compared to the pre-CEUS phase, the percentage of the downgrade of significant fibrosis at the CEUS, early post-CEUS, and late post-CEUS phase was 55.3%, 35.3%, and 6.0%, respectively; while the downgrade of cirrhosis was 37.8%, 18.3%, and 2.4%, respectively. Liver inflammatory activity (p = 0.008, β = 0.88, 95% CI = 0.24-1.52) independently influenced the differences between the pre-CEUS and CEUS phase Emean. The higher the inflammatory activity grade, the greater the differences in Emean.</p><p><strong>Conclusion: </strong>Following CEUS, 2D-SWE measurement values initially decrease and subsequently return to baseline levels. This transient decrease can lead to a downgraded assessment of liver fibrosis. Furthermore, the liver inflammatory activity is an independent factor influencing the magnitude of the reduction in 2D-SWE measurement values after CEUS.</p>","PeriodicalId":49399,"journal":{"name":"Ultrasound in Medicine and Biology","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144530692","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Study of Confounding Factors in Shear Wave Elastography of the Diaphragm.","authors":"Izzati Mohammad Munir, Sook Sam Leong, Anis Shafina Mahfudz, Li Shyan Ch'ng, Jeannie Hsiu Ding Wong, Anushya Vijayananthan, Chee Kuan Wong","doi":"10.1016/j.ultrasmedbio.2025.05.027","DOIUrl":"https://doi.org/10.1016/j.ultrasmedbio.2025.05.027","url":null,"abstract":"<p><strong>Objective: </strong>Changes in diaphragmatic stiffness are associated with pathological conditions, including severe pneumonia, and the application of shear wave elastography (SWE) in evaluating diaphragmatic stiffness has been studied. This study investigates confounding factors in diaphragmatic SWE to facilitate the development of a standard protocol that may be used in a clinical setting.</p><p><strong>Methods: </strong>A total of 84 healthy volunteers were subjected to SWE to determine the shear wave velocity (SWV) and coefficient of variation (CV) of their diaphragms. The effects of transducer frequency, respiration, scanning sides, body positioning and region of interest (ROI) were investigated. 20 volunteers from the recruited volunteers were re-scanned by a second observer.</p><p><strong>Results: </strong>No significant differences were observed in median SWV for transducer frequencies, scanning sides and ROI locations. For respiration, median SWV was higher during inspiration than during expiration (p < 0.001). There was also a significant difference in diaphragm CV between the former and the latter (p = 0.038). The median SWV for body position was significantly higher when sitting compared with lying in the supine position (p < 0.001). Regarding CVs, these were lower for the L10-2 transducer, inspiration, left side, supine position, and at inferior ROI locations, although most were not significant except for respiration. Inter-observer reliability appeared to have a low error rate, as indicated by the intra-class correlation coefficient of 0.911.</p><p><strong>Conclusion: </strong>We recommend a protocol that uses a higher frequency L18-5 transducer. Imaging should be taken in the supine position during inspiration at the right middle hemi diaphragm area.</p>","PeriodicalId":49399,"journal":{"name":"Ultrasound in Medicine and Biology","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144498987","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cavitation threshold in the porcine crystalline lens.","authors":"Clement Foullounoux, Frederic Mascarelli, Philippe Gain, Gilles Thuret, Cyril Lafon, Maxime Lafond","doi":"10.1016/j.ultrasmedbio.2025.05.018","DOIUrl":"10.1016/j.ultrasmedbio.2025.05.018","url":null,"abstract":"<p><strong>Objective: </strong>To evaluate ultrasonic cavitation thresholds in young (6 months) and old (2-6 years) porcine crystalline lenses using a 2 MHz transducer.</p><p><strong>Methods: </strong>For cavitation threshold estimation, five to nine samples were exposed to bursts of different peak negative pressures from 20.6 to 36.1 MPa with duty cycles (DCs) of 0.025%, 0.05%, 0.1% and subsequently 0.000006% at maximum output. Cavitation signals were recorded and their energies were calculated. The cavitation events percentage was estimated through the detection of energy values outside 5 standard deviations from the mean value.</p><p><strong>Results: </strong>Cavitation thresholds were estimated at -31.7 MPa for a 0.1% DC but severe cataracts were observed. In order to determine a therapeutic application, a more suitable ultrasound scheme using an ultra-low DC (0.6e^-5%, 12 cycles at 1 Hz PRF) was used and a cavitation threshold was determined at -36.1 MPa. In that case, no cataract was observed on a macroscopic scale. Nevertheless, important variations in cavitation thresholds between samples and the two tested populations were observed, most likely due to variations in viscoelastic properties, water content distribution, temperature increases and age disparity.</p><p><strong>Conclusion: </strong>The results show a trend toward higher cavitation probability while increasing the negative pressure at that focus. However, no significant differences in cavitation events percentage could be observed due to the limited sample size. Ultra-low DC results show the feasibility of cavitation nucleation while reducing heat deposition. The safety aspect needs to be explored further.</p>","PeriodicalId":49399,"journal":{"name":"Ultrasound in Medicine and Biology","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144369420","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development of Radiomics-Based Risk Prediction Models for Stages of Hashimoto's Thyroiditis Using Ultrasound, Clinical, and Laboratory Factors.","authors":"Jia-Hui Chen, Kai Kang, Xin-Yue Wang, Jian-Ning Chi, Xue-Meng Gao, Yong Xin Li, Ying Huang","doi":"10.1016/j.ultrasmedbio.2025.05.025","DOIUrl":"10.1016/j.ultrasmedbio.2025.05.025","url":null,"abstract":"<p><strong>Objectives: </strong>To develop a radiomics risk-predictive model for differentiating the different stages of Hashimoto's thyroiditis (HT).</p><p><strong>Methods: </strong>Data from patients with HT who underwent definitive surgical pathology between January 2018 and December 2023 were retrospectively collected and categorized into early HT (HT patients with simple positive antibodies or simultaneously accompanied by elevated thyroid hormones) and late HT (HT patients with positive antibodies and beginning to present subclinical hypothyroidism or developing hypothyroidism). Ultrasound images and five clinical and 12 laboratory indicators were obtained. Six classifiers were used to construct radiomics models. The gradient boosting decision tree (GBDT) classifier was used to screen for the best features to explore the main risk factors for differentiating early HT. The performance of each model was evaluated by receiver operating characteristic (ROC) curve. The model was validated using one internal and two external test cohorts.</p><p><strong>Results: </strong>A total of 785 patients were enrolled. Extreme gradient boosting (XGBOOST) showed best performance in the training cohort, with an AUC of 0.999 (0.998, 1), and AUC values of 0.993 (0.98, 1), 0.947 (0.866, 1), and 0.98 (0.939, 1), respectively, in the internal test, first external, and second external cohorts. Ultrasound radiomic features contributed to 78.6% (11/14) of the model. The first-order feature of traverse section of thyroid ultrasound image, texture feature gray-level run length matrix (GLRLM) of longitudinal section of thyroid ultrasound image and free thyroxine showed the greatest contributions in the model.</p><p><strong>Conclusion: </strong>Our study developed and tested a risk-predictive model that effectively differentiated HT stages to more precisely and actively manage patients with HT at an earlier stage.</p>","PeriodicalId":49399,"journal":{"name":"Ultrasound in Medicine and Biology","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144369422","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}