Cronkhite–Canada syndrome is a rare, non-hereditary polyposis syndrome characterized by non-specific gastrointestinal symptoms accompanied by alopecia, cutaneous hyperpigmentation, and nail dystrophy. Characteristic endoscopic findings are diffuse sessile polypoid lesions with edematous mucosa. We report a case of a 44-year-old woman in whom intestinal ultrasound and CT revealed diffuse mucosal thickening and an ileocecal intussusception—findings that may not be pathognomonic but are highly unusual in adults. These imaging features served as critical red flags that directed the clinical suspicion toward Cronkhite–Canada syndrome and prompted timely endoscopic confirmation.

Breast ultrasound (BUS) is an essential tool for diagnosing breast lesions, with millions of examinations per year. However, publicly available high-quality BUS benchmarks for AI development are limited in data scale and annotation richness. In this work, we present BUS-CoT, a BUS dataset for chain-of-thought (CoT) reasoning analysis, which contains 11,439 ultrasound images from 11,850 lesions and 4,838 patients, covering all 99 WHO-defined histopathology categories. For model training and evaluation, we provide a curated high-quality subset of 5,163 lesion-focused images annotated by experienced radiologists. To facilitate research on incentivizing CoT reasoning, we construct the reasoning processes based on observation, feature, diagnosis and pathology labels, annotated and verified by experienced experts. Moreover, by covering lesions of all histopathology types, we aim to facilitate robust AI systems in rare cases, which can be error-prone in clinical practice. The data and code are publicly available at https://doi.org/10.6084/m9.figshare.30838715.

Objective To evaluate the application value of the Peyton four-step teaching method in the standardized training of intestinal ultrasound and compare it with traditional teaching methods,so as to provide an optimized approach for clinical ultrasound training.Methods Participants from the Department of Ultra-sound at Peking Union Medical College Hospital between September 2024 and March 2025 were randomly as-signed to either the traditional group or Peyton group.The traditional group followed the conventional"lecture-demonstration-practice"model,while the Peyton group implemented the standardized"demonstration-decon-struction-comprehension-execution"four-step approach.All training focused on standard intestinal ultrasound scanning techniques.After the training,the operational skills were independently evaluated by the instructors.To verify the reproducibility of the teaching method,the participants in traditional teaching group received addi-tional Peyton method training after the initial assessment and underwent a second evaluation.Results A total of 18 participants were included in this study,with 9 in the traditional teaching group and 9 in the Peyton teach-ing group.Participants in the Peyton group demonstrated significantly higher scores than those in the traditional group at every anatomical site assessed(all P＜0.05),including the terminal ileum[7.3(6.5,8)vs.(3.1±1.4)],ileocecal region[7(6,8)vs.(3.7±1.3)],appendix[8(7,8.3)vs.(5.3±0.8)],colon[7(6.5,7.7)vs.5.3(2.8,5.3)]and small intestine[(7.3±0.5)vs.(3.7±1.2)].The overall score was also significantly higher in the Peyton group[(7.2±0.9)vs.(3.7±1.0),P＜0.001].After receiving supplemental Peyton method training,the traditional group showed significant improvement in all anatomical site scores,with the overall score increasing to[(7.5±0.4),P=0.008].Conclusions The Peyton four-step method is significantly more effective than traditional teaching in improving residents'intestinal ultrasound skills,demonstrating its suitability as the preferred approach for standardized training programs.

OBJECTIVE:Ultrasound-based viscoelastic imaging enables the real-time characterization of tissue properties. In this study, we aimed to investigate the correlation between viscoelastic mechanical properties and tumor proliferation in invasive ductal breast cancer (IDC). METHODS:This prospective study consecutively enrolled patients with IDC during October 2024 and January 2025. All patients underwent preoperative shear-wave elastography (SWE) and ultrasound-based viscoelastic imaging. The viscoelastic mechanical properties (viscosity coefficients [Vmax and Vmean] and dispersion coefficients [Dmax and Dmean]) and SWE (Emax) were measured within the tumor and in a 1-mm peritumoral region (Vtmax, Vtmean, et al.). Patients were stratified into high (Ki-67 ≥ 14%) and low (Ki-67 < 14%) proliferation groups. Viscoelastic mechanical properties and SWE between groups were compared. RESULTS:Among the 124 female patients with IDC, 94 exhibited high Ki-67 expression while 30 had low Ki-67 expression. No significant differences were observed in SWE-based elasticity between the two groups (p > 0.05). Vmean and Vtmean were lower in the high Ki-67 group (1.1 [0.7-1.7] vs. 1.5 [1.0-2.3], p = 0.020; 1.3 [0.8-1.8] vs. 1.7 [1.1-2.4], p = 0.026, respectively). Using Vmean ≤ 1.2 Pa·s as cutoff value, a significantly higher proportion of high Ki-67 expression was found (64.9% vs. 35.1%, p = 0.016). CONCLUSION:Viscoelastic mechanical properties, rather than traditional SWE elasticity, correlated with Ki-67 expression in IDC. A lower Vmean may be correlated with higher proliferative activity, potentially serving as a non-invasive imaging biomarker. These findings support further exploration of ultrasound-based viscoelastic imaging for the assessment of tumor microenvironment heterogeneity.

Foundation models have emerged as powerful tools for addressing various tasks in clinical settings. However, their potential development for breast ultrasound analysis remains untapped. Here we present BUSGen, the first foundation generative model designed for breast ultrasound image analysis. Pretrained on over 3.5 million breast ultrasound images, BUSGen has acquired extensive knowledge of breast structures, pathological features and clinical variations. With few-shot adaptation, BUSGen can generate repositories of realistic and informative task-specific data, facilitating the development of models for a wide range of downstream tasks. Extensive experiments highlight BUSGen's exceptional adaptability, significantly exceeding real-data-trained foundation models in breast cancer screening, diagnosis and prognosis. In breast cancer early diagnosis, our approach outperformed all board-certified radiologists (n = 9), achieving an average sensitivity improvement of 16.5% (P < 0.0001). In addition, we characterized the scaling effect of using synthetic data. Finally, BUSGen enabled de-identified data sharing, making progress forward in secure medical data utilization.

Intestinal stricture is a severe complication of Crohn's disease (CD), and the accurate differentiation of fibrotic strictures holds significant clinical value for guiding therapeutic decision-making. Due to the frequent difficulty in endoscopic passage caused by luminal narrowing, the assessment of lesions and tissue biopsy are often limited. In contrast, cross-sectional imaging techniques not only provide a comprehensive evaluation of intestinal lesions but also reveal extraintestinal changes, offering critical evidence for clinical decisions. With the rapid advancement of imaging technology, various novel radiological methods have emerged, providing new approaches for the assessment of intestinal fibrosis in CD strictures. Through a literature review, this article summarizes the latest research progress in advanced imaging techniques, including ultrasound elastography, magnetic resonance imaging(MRI) diffusion-weighted imaging, magnetization transfer MRI, and fibroblast activation protein inhibitor (FAPI)- positron emission computed tomography(PET). Additionally, it explores the potential applications and future directions of artificial intelligence and radiomics in the detection and grading of CD-associated fibrosis.

Background/Aims:This study aimed to investigate the prognostic value of early post-induction intestinal ultrasound (IUS) findings in predicting long-term clinical outcomes among patients with moderate-to-severe ulcerative colitis (UC). Methods:This retrospective, single-center study consecutively enrolled patients with moderate-to-severe, left-sided or extensive UC. Clinical endpoints were assessed at the end of follow-up or 1 year after induction therapy (for patients with at least 1 year of follow-up) and categorized as clinical remission (Short Clinical Colitis Activity Index [SCCAI] ≤ 2) or non-remission (SCCAI > 2). Patients who experienced a negative disease course before the evaluation point were classified as clinical non-remission. Results:A total of 56 patients were included. The bowel wall thickness (BWT; 5.1 ± 1.7 mm vs. 6.0 ±1.4 mm; P= 0.032) and Milan ultrasound criteria (MUC; 8.3 ± 3.2 vs. 9.9 ± 2.2; P= 0.029) evaluated at early follow-up IUS were lower for patients reaching longterm clinical remission. Patients with BWT < 5 mm on early follow-up IUS (83% vs. 45%; P= 0.006) or MUC < 6.2 (100% vs. 45%; P< 0.001) had a significantly higher rate of long-term clinical remission. Kaplan-Meier analysis revealed a lower cumulative probability of a negative disease course in patients with BWT < 5 mm (P= 0.025) or MUC < 6.2 (P= 0.025). Cox regression analysis identified BWT ≥ 5 mm as an independent predictor of a negative disease course. Conclusions:BWT <5 mm and MUC < 6.2 may serve as intermediate targets for IUS-guided "treat-to-target" strategy, offering a practical approach to improve longterm clinical remission in patients with moderate-to-severe UC.

Axillary lymph node (ALN) metastasis is a critical factor influencing prognosis and treatment strategies in breast cancer patients. However, traditional methodsu2014ranging from physical examination to ultrasoundu2014often lack the precision required for clinical decision-making. In recent years, ultrasound radiomics and deep learning have emerged as promising solutions, leveraging high-throughput quantitative features from ultrasound images to enhance detection accuracy. This review explores the development and application of radiomics and deep learning across multiple ultrasound modalities (grayscale, elastography, and contrast-enhanced ultrasound), as well as in multimodal imaging approaches that integrate ultrasound with MRI and PET/CT, underscoring the benefits of incorporating clinicopathological variables to boost predictive performance. These studies provide a vital foundation for personalized treatment and precision medicine in breast cancer management.

To determine a direct method for diagnosing axillary lymph node (ALN) tumor burden preoperatively in cT1-2N0 breast cancer patients, we developed and validated a deep learning (DL) model based on ultrasound (US) images of sentinel lymph nodes (SLNs) detected by contrast-enhanced lymphatic ultrasound (CEUS). Women with cT1-T2N0 breast cancer who received CEUS were enrolled prospectively from Peking Union Medical College Hospital between April 2020 and July 2021 and from Sichuan Cancer Hospital between April 2022 and July 2022. Heavy ALN tumor burden was defined as > 2 metastatic lymph nodes according to the Z0011 criteria. We developed a DL model, the modality-adaptive network with clinicopathological information (MAN + C), using grayscale or color Doppler US images and radioclinicopathological information to predict heavy tumor burden. A total of 595 SLNs from 374 patients met the inclusion criteria. The areas under the receiver operating characteristic curve (AUCs) were calculated to evaluate the predictive performance of the model, yielding values of 0.91[95

Breast contrast-enhanced ultrasound (CEUS)has been used in clinical practice for nearly two decades. CEUS provides real-time assessment of microvascular perfusion, offering valuable functional information complementary to conventional ultrasound. Nonetheless, the lack of standardization in relevant techniques has hindered the widespread adoption and further development of this technology. As a specialized committee, Superficial Organs and Peripheral Vessels Committee of Chinese Association of Ultrasound in Medicine and Engineering has always been committed to standardizing the clinical application of ultrasound. This expert consensus aims to standardize examination procedures, image interpretation, and reporting for diagnostic settings. It outlines key indications and provides recommendations on acquisition techniques, qualitative and quantitative analysis of enhancement patterns, and standardized lexicon for reporting.

To investigate the pathological diagnostic features of non-esophageal eosinophilic gastrointestinal disorders (non-EoE EGIDs) and establish site-specific pathological diagnostic workflows. A retrospective case-control study was conducted on 444 biopsy specimens from 70 non-EoE EGIDs patients (2012–2023, Peking Union Medical College Hospital). Controls groups included 200 specimens from 155 chronic active gastroenteritis patients and 282 specimens from 134 patients with Crohn’s disease, Behçet’s disease and chronic active colitis of unexplained etiology. Pathological features were compared using chi-square tests, Bonferroni post-hoc tests, and modified Poisson regression analyses. The features assessed included eosinophil counts, infiltration sites, villous blunting, intraepithelial neutrophil infiltration/cryptitis, lamina propria neutrophilic infiltration, edema, and the degree of lymphoplasmacytic infiltration. In the stomach, no significant differences were observed in any pathological features between non-EoE EGIDs and controls. In the duodenum, small bowel, and colon, significant differences were observed in eosinophil counts, infiltration sites, and the other morphological indicators. Multivariable modified Poisson regression identified independent pathological predictors in these three segments. High-density eosinophil patterns and intraepithelial eosinophil infiltration are key diagnostic features of non-EoE EGIDs. Other morphological indicators serve as important auxiliary diagnostic criteria.

Large language models (LLMs) are increasingly being evaluated for radiology reporting. However, the incremental value of adding report-embedded key images to report text for breast ultrasound report auditing remains unclear. This retrospective study included 818 breast ultrasound examinations with pathology- or follow-up-based reference standards. A workflow-error-enriched 300-report subset was constructed, comprising 240 reports with 329 inserted errors and 60 error-free reports. GPT-5.5 and Gemini 3.1 Pro Preview were evaluated under two input settings: report text alone and multimodal input; the latter additionally included report-embedded key images. A physician reader provided a human benchmark. In the full cohort, GPT-5.5 was evaluated with key-image input versus physician-interpreted findings input for malignancy and BI-RADS risk classification. Multimodal input increased report-level sensitivity from 77.5

BACKGROUND/AIMS:The awareness, accessibility, and utilization of transabdominal intestinal ultrasound (IUS) in inflammatory bowel disease (IBD) management from both physicians' and patients' perspectives remains unclear in China. This nationwide cross-sectional survey aimed to gauge the current utilization of IUS, physician and patient perceptions and knowledge gap in IBD management across China. METHODS:A structured questionnaire, developed by the China IUS Group, was distributed to 612 physicians (69.8% of gastroenterologists, 28.0% of radiologists) from 38 tertiary hospitals and 1,154 IBD patients. RESULTS:A total of 91.7% of physicians expressed an intention to incorporate IUS into future clinical practice. However, while 69.3% of physicians reported IUS availability at their institutions, its utilization varied widely. Only 16.5% of physicians applied IUS to more than 75% of their IBD patients. Additionally, 27.1% of physicians reported receiving IUS training. Radiologists were more likely than gastroenterologists to consider IUS as a sensitive tool for evaluating treatment efficacy (48.3% vs. 19.4%, P< 0.001), intestinal wall fibrosis (33.7% vs. 27.4%, P< 0.001), intestinal fistula (27.9% vs. 11.2%, P< 0.001), abdominal abscesses (49.4% vs. 28.6%, P< 0.001), and disease severity (30.2% vs. 11.0%, P< 0.001). Patients expressed high satisfaction with IUS (76.1%), yet 39.2% had safety concerns. CONCLUSIONS:Despite growing recognition of IUS in China, its wide utilization in IBD management requires further promotion. The notable disparity between gastroenterologists and radiologists regarding IUS underscores the need for targeted, specialty-specific training. Strengthening patient education efforts is essential to further enhance patient acceptance of IUS.

Crohn's disease (CD) is frequently complicated by intestinal strictures, which substantially affect patients quality of life and long-term outcomes. Accurate classification of strictures-as inflammatory, fibrotic, or mixed-is critical for selecting optimal therapeutic strategies. In clinical practice, multidisciplinary team (MDT) consultation is often employed to assess stricture characteristics. However, the accuracy and inter-specialty consistency of stricture evaluation within MDTs remain inadequately characterized. This study aimed to assess the intra-disciplinary consistency and accuracy of decision-making for CD-related strictures, evaluate the accuracy of post MDT decisions, and propose recommendations for stricture nature assessment and MDT workflow optimization. A mixed-methods study was conducted at Peking Union Medical College Hospital involving 42 patients with CD and intestinal strictures. MDT participants-including specialists from gastroenterology, surgery, ultrasound, and MDT meeting chairs-were involved in evaluating intra-disciplinary decision consistency and accuracy. Semi-structured qualitative interviews were also conducted to explore factors influencing clinical decision-making. Gastroenterologists demonstrated the highest intra-team consistency (PABAK = 0.75) and diagnostic accuracy (89.3%). Ultrasound specialists showed improved consistency following targeted training (from 0.46 to 0.93). The overall accuracy of historical MDT decisions was 92.9%. Key factors influencing stricture nature judgment included clinical presentation, laboratory findings, imaging features, and endoscopic evaluation. Seven core components were identified to improve MDT workflow: expert selection, team building, training, pre-meeting preparation, in-meeting procedures, post-meeting actions, and continuous quality improvement. This study reveals variability in decision-making for CD-related strictures across different specialties. To improve diagnostic accuracy and treatment planning, we propose clear stricture classification criteria and a structured MDT workflow to standardize and enhance multidisciplinary management of CD.

The 70-gene signature (70-GS; MammaPrint) assay is useful for prognosis assessment in HR+/HER2- early breast cancer, but limited accessibility motivates development of noninvasive alternatives. We retrospectively enrolled 219 women with preoperative grayscale ultrasound and 70-GS results, including a development cohort (n = 125), an internal validation cohort (n = 53), and a temporally independent validation cohort (n = 41). Radiomic features were extracted from manually delineated ROIs using PyRadiomics, and a radiomics score was derived after LASSO selection. Candidate radiomics-only, clinicopathologic-only, and full clinicoradiomic models were explored. To reduce overfitting, we selected a parsimonious model combining the radiomics score and Ki67 as the primary model. The simplified model achieved AUCs of 0.878, 0.816, and 0.831 in the development, internal validation, and temporally independent validation cohorts, respectively. In 1000 bootstrap resamples, the optimism-corrected AUC was 0.872 and the corrected calibration slope was 0.953. Adding the radiomics score to a Ki67-only model significantly improved model fit (likelihood-ratio chi-square = 17.14, df = 1, p < 0.001). An ultrasound radiomics and Ki67 model may provide a noninvasive reference for estimating MammaPrint risk categorization, but it should be considered only as a supportive adjunct and not as a replacement for genomic testing.

Objectives: To propose a multimodal deep learning method for the classification of benign and malignant breast non-mass lesions (NMLs) using grayscale and color Doppler ultrasound and to compare the performance of multi-modality and single-modality breast ultrasound (BUS) models. Methods: This retrospective study collected 248 pathologically confirmed NMLs from 241 female patients comprising grayscale and color Doppler BUS images from March 2018 to November 2024. Three types of convolutional neural networks (CNNs), including ResNet50, ResNet18, and VGG16, were evaluated as single-modality (grayscale or color Doppler) models via five-fold cross-validations. The optimal model for each single-modality approach was chosen as the backbone network for multimodal deep learning. Features extracted from grayscale and color Doppler BUS images were then concatenated to predict the probabilities of benignity and malignancy. The diagnostic efficacy of the multi-modality BUS models was comparatively evaluated against single-modality counterparts. Results: The single-modality VGG16 models outperformed the other two CNN types for both grayscale and color Doppler BUS using five-fold cross-validations. Additionally, single-modality grayscale models outperformed single-modality color Doppler models. With a mean accuracy of 91.54%, sensitivity of 94.15%, specificity of 87.30%, F1 score of 0.93, and area under the receiver operating characteristic curve (AUC) of 0.96, the multimodal VGG16 models performed better than single-modality counterparts. Conclusions: VGG 16-based multimodal ultrasound deep learning showed excellent diagnostic efficacy in distinguishing between benign and malignant NMLs, indicating therapeutic potential to help radiologists assess NMLs.

BACKGROUND:Strictures in ulcerative colitis (UC) are relatively uncommon but are associated with increased risk of malignancy and complications. Until recently, fibrogenesis and strictures have remained largely unexplored in UC. AIM:To investigate the incidence, long-term prognosis and risk factors of colorectal strictures in a large cohort of UC patients. METHODS:A total of 938 hospitalized UC patients at Peking Union Medical College Hospital were included from 2014 to 2024. Stricture was defined as a fixed localized narrowing of the colorectal lumen. Risk factors for stricture formation were identified by multivariable Cox regression. Prognosis was analyzed using the Kaplan-Meier or Fine-Gray method. Sensitivity analysis excluded malignant strictures due to their distinct pathophysiology. RESULTS:The overall incidence of stricture was 12.4% over a median follow-up of 8.70 years, with a 10-year cumulative probability of 11.3%. Malignancy occurred in 8.6% of stricture cases. UC patients with strictures were at higher risk for intestinal complications, surgery and malignancy (P < 0.05). The 10-year cumulative probabilities of surgery and all-cause mortality were 37.6% and 1.6%, respectively. Age ≥ 40 years at diagnosis [hazard ratio (HR) = 2.197, 95% confidence interval (CI): 1.487-3.242] and extraintestinal manifestations (HR = 2.072, 95%CI: 1.326-3.239) were associated with higher stricture risk, while the use of biological agents such as vedolizumab (HR = 0.382, 95%CI: 0.203-0.720) was protective against strictures (P < 0.05). Sensitivity analysis on benign strictures showed consistent findings, with similar risk factors and worse long-term outcomes. CONCLUSION:UC patients with strictures had worse long-term prognostic outcomes. Earlier endoscopic surveillance and biologic treatment should be considered in patients ≥ 40 years or those with extraintestinal manifestations.

Background:Ultrasound (US) is the preferred imaging modality for preoperative localization of primary hyperparathyroidism (PHPT). Parathyroid adenomas may be confused with normal lymph nodes on conventional US. This study aimed to explore the usefulness of microvascular flow imaging (MVFI) in differentiating parathyroid adenomas from normal lymph nodes and compare it with color Doppler flow imaging (CDFI). Methods:A total of 34 parathyroid adenomas that appeared peripherally hypoechoic and internally hyperechoic mimicking normal lymph nodes were identified in 34 patients with PHPT, and 34 cervical level III normal lymph nodes from 34 healthy controls were selected for comparison. The ability of CDFI and MVFI to detect the vascular characteristics of parathyroid adenomas were compared. Results:On CDFI, the detection rates of polar vessels, hilar vessels, and rich vascular in parathyroid adenomas were 44.1%, 8.8%, and 52.9%, respectively. These characteristics in normal lymph nodes showed detection rates of 2.9%, 38.2%, and 8.8%, respectively. On MVFI, the detection rates of polar vessels, hilar vessels, and rich vascular in parathyroid adenomas were 82.4%, 5.9%, and 94.1%, respectively. For normal lymph nodes, the detection rates of these characteristics were 5.9%, 76.5%, and 11.8%, respectively. Compared with CDFI, MVFI detected a significantly higher rate of polar vessels and rich vascularity in parathyroid adenomas (82.4% vs. 44.1% and 94.1% vs. 52.9%, P=0.034 and P<0.001), as well as hilar vessels in normal lymph nodes (76.5% vs. 38.2%, P<0.001). Conclusions:MVFI more frequently identified polar vessels and rich vascularity in parathyroid adenomas, as well as hilar vessels in lymph nodes, compared to CDFI. This suggests that MVFI may play a better role in differentiating parathyroid adenomas from lymph nodes, contributing to surgical planning in PHPT cases.