BACKGROUND:To compare image quality between integrated slice-specific dynamic shimming diffusion-weighted imaging (iShim-DWI) and conventional single-shot echo-planar (SS-EPI) DWI in the upper abdomen, and to evaluate performance differences within iShim-DWI using high (800 s/mm2) versus ultra-high (1600 s/mm2) b-values. METHODS:A cohort of 162 consecutive participants was included. Among them, 110 underwent both iShim-DWI (b = 800 s/mm2) and SS-EPI-DWI (b = 800 s/mm2), while the remaining 52 received iShim-DWI at both b = 800 s/mm2 and b = 1600 s/mm2. Qualitative assessment focused on image quality features including fat suppression, distortion, artifacts, overall image quality and lesion confidence score. Lesion detection efficiency was compared. Quantitative evaluation included signal intensity (SI), signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and ADC-related parameters of normal upper abdominal organs and lesions. RESULTS:iShim-DWI received significantly higher scores in artifact reduction overall image quality and lesion confidence score compared with SS-EPI-DWI (all P < 0.0001). Fat suppression did not differ significantly between the two sequences (P = 0.0703). Five additional lesions were detected by iShim-DWI that were not visible on SS-EPI-DWI. iShim-DWI yielded significantly higher SNR and CNR for both normal organs (P < 0.001) and lesions (P = 0.0023; 0.0024), along with higher ΔADC and lower ADC variability (SD) compared with SS-EPI-DWI (both P < 0.05). Within iShim-DWI, the b = 800 s/mm2 protocol provided significantly higher lesion SNR (P = 0.0231) and CNR (P = 0.0438) than b = 1600 s/mm2, while lesion confidence scores were similarly high (P > 0.9999). CONCLUSIONS:iShim-DWI provides substantially improved image quality, more stable ADC measurements, and better lesion detection and visualization in the upper abdomen compared with SS-EPI-DWI. In our cohort, iShim-DWI at b = 800 s/mm2 achieves a favorable balance between lesion contrast and SNR, and may serve as a preferred routine clinical option. Further validation in larger cohorts is warranted.

IntroductionThis study aimed to evaluate the impact of varying slice thickness on quantitative values using the Magnetic Resonance Image Compilation (MAGiC) sequence. MethodsIn this retrospective study, 23 healthy subjects underwent the MAGiC sequence (at 3.0 T) with three slice thicknesses: 3 mm (TH3), 4 mm (TH4), and 5 mm (TH5). The T1, T2, and PD values were measured in various knee joint cartilage regions by two experienced radiologists, including the lateral femoral condyle (LFC), lateral tibial plateau (LTP), medial femoral condyle (MFC), medial tibial plateau (MTP), patella (PAT), and trochlea (TRO). The effects of varying slice thicknesses (TH4 vs. TH3 and TH5 vs. TH3) were analyzed using paired t-tests or Wilcoxon signed rank tests, with statistical significance set at P < 0.025. Intra-rater and inter-rater reliability were also assessed. ResultsMeasurements of T1, T2, and PD values demonstrated high intra- and inter-rater reliability. Minimal differences were observed across slice thicknesses for T1WI, T2WI, and PDWI images. T2 and PD values showed little variation, while T1 mapping revealed significant differences. T2 values were consistent across regions, except for the LFC. DiscussionTH4 and TH5 can replace TH3 for knee joint scanning while reducing scan time, with minimal differences in anatomical depiction across sequences. MAGiC technology significantly improves efficiency by acquiring quantitative data in a single scan, demonstrating stable T2 values unaffected by slice thickness, though T1 and PD values are thickness-dependent. This technique holds clinical value for cartilage injury assessment but requires further research on the applicability of multiplanar imaging. ConclusionT2 values obtained with the MAGiC sequence are stable across TH3, TH4, and TH5, allowing for reliable cartilage T2 quantification using TH5 to reduce patient scan time.

Purpose: The objective of this research was to formulate and corroborate a predictive model intended to identify myocardial fibrosis in individuals suffering from coronary artery disease (CAD). This objective was accomplished by integrating radiomic features extracted from cardiac magnetic resonance (CMR) T1 mapping alongside multiple clinical and functional parameters. Methods: In this multicenter retrospective analysis, a total of 240 participants diagnosed with CAD who had undergone CMR imaging inclusive of T1 mapping were examined. The cohort was categorized into a training set which included patients from the first center (n = 168), and an independent external validation set, comprising patients from a second center (n = 72). Myocardial fibrosis was identified utilizing the late gadolinium enhancement (LGE) technique. Radiomic features were derived from the T1 mapping images, while pertinent clinical, functional, and tissue characteristics were also gathered. Least absolute shrinkage and selection operator regression method was utilized for feature selection. Subsequently, a multivariate logistic regression model was developed, and its effectiveness was gauged through area under the curve (AUC), decision curve analysis and calibration curves. Results: Key independent predictors identified in the training cohort included left ventricular ejection fraction end-diastolic and end-systolic volume indices, myocardial mass index, post-contrast T1, and extracellular volume fraction (all P < 0.05). The integrated model exhibited strong discriminative performance, with an AUC of 0.955 in the training set and 0.972 in the validation set. Calibration and decision curve analyses further confirmed its clinical applicability. Conclusion: The CMR-based integrated model effectively predicts myocardial fibrosis in CAD patients, offering a non-invasive tool for improved risk stratification and personalized management.

BackgroundCardiac involvement in dystrophinopathy progresses from diffuse myocardial remodeling to overt systolic failure. Multiparametric cardiac magnetic resonance (CMR) offers simultaneous insights into myocardial mechanics and tissue characterization, yet the optimal diagnostic parameters for tracking disease severity remain to be fully characterized.ObjectiveTo objectively evaluate the descriptive and discriminative performance of integrating strain and quantitative T1 mapping parameters for identifying myocardial fibrosis burden and stratifying systolic dysfunction in patients with dystrophinopathy.Materials and methodsThis retrospective study analyzed 55 patients with genetically confirmed dystrophinopathy and 30 healthy controls who underwent CMR between January 2020 and December 2024. Patients were sequentially stratified by late gadolinium enhancement (LGE) status (Group A: LGE-negative, n = 16; Group B: LGE-positive, n = 39), and further sub-stratified by left ventricular ejection fraction (LVEF) (Group C: LVEF ≥ 50%, n = 23; Group D: LVEF < 50%, n = 16). Least absolute shrinkage and selection operator (LASSO) regression with 10-fold cross-validation was applied for non-zero feature selection, followed by the construction of multivariable Firth penalized logistic regression models. Model comparisons were made using the non-parametric DeLong test.ResultsCompared with Group A, Group B exhibited significant differences in LVEF (p < .001), mid-ventricular circumferential strain (CS_Mid, p < .001), and native T1 in segment 11 (T1map_seg11, mid-inferolateral, p = .004). In single-parameter ROC analysis, CS_Mid, LVEF, and T1map_seg11 exhibited an area under the curve (AUC) of 0.842 [95% confidence interval (CI): 0.735–0.949], 0.828 (95% CI: 0.714–0.942), and 0.715 (95% CI: 0.549–0.880), respectively. The combined model of CS_Mid and T1map_seg11 achieved the AUC of 0.888 (95% CI: 0.793–0.983). Compared Group C with Group D, CS_Global and T1map_seg5 models yielded AUCs of 0.921 (95% CI: 0.822–1.000) and 0.823 (95% CI: 0.694–0.953). The combined model (CS_Global + T1map_seg5) achieved the AUC of 0.951 (95% CI, 0.864–1.000, DeLong p = .567 vs T1map_seg5, DeLong p = .101 vs. T1map_seg5).ConclusionsIn dystrophinopathy, multiparametric CMR enables structural and functional assessment of myocardial remodeling. Segmental native T1, particularly in the basal and mid-inferolateral segments, provides complementary information on regional myocardial tissue abnormalities. In contrast, CS accounts for most of the discrimination of disease severity. These findings suggest that the distinctive contribution of CMR may lie in regional myocardial tissue characterization rather than conventional functional assessment.

Gallbladder cancer is recognized as one of the most aggressive malignancies within the biliary system. Usually, the substantial part of patients are diagnosed at advanced stages, often with metastases to distant organs. In cases of metastatic gallbladder adenocarcinoma, the potential benefit of primary tumor resection (PTR) in improving patient prognosis remains an unresolved issue that warrants further investigation. We collected data to identify patients diagnosed with gallbladder cancer and concurrent metastases to the liver, lungs, bones, brain, or distant lymph nodes between 2004 and 2021 from the Surveillance, Epidemiology, and End Results (SEER) database. The impact of primary tumor resection (PTR) on overall survival (OS) and cancer-specific survival (CSS) was evaluated using the Cox proportional hazards model. Kaplan-Meier survival curves were generated for additional clarity. Subgroup analyses were also conducted to identify patient groups that might have a longer survival period from PTR. A total of 1968 patients diagnosed with metastatic gallbladder adenocarcinoma at the time of initial presentation between 2004 and 2021 were included in the analysis. Among these, liver metastasis was the most frequent site of metastasis (n = 1695, 86.12

Solitary fibrous tumor of liver (SFTL) is a rare mesenchymal neoplasm. Due to its low incidence and atypical clinical presentation, preoperative diagnosis is often challenging, making imaging features critical for its identification. Contrast-enhanced ultrasound (CEUS), a dynamic imaging technique, has been demonstrated to provide high diagnostic accuracy for hepatic lesions. This study reports the CEUS characteristics of a percutaneous biopsy-confirmed SFTL in an adult patient. The findings included peripheral hyperenhancement during the arterial phase, progressive centripetal filling with partial perfusion defects, and early washout commencing in the portal venous phase, which became more pronounced in the delayed phase.

OBJECTIVE:Occupational asbestos exposure remains a major public health concern in Southeast Asia (SEA), where use persists and comprehensive assessments are limited. METHODS:GBD 2023 data were used to estimate deaths and DALYs attributable to occupational asbestos exposure in SEA and 13 countries. Trends were analyzed by EAPC and Joinpoint, stratified by sex, age, and cause. RESULTS:Deaths increased markedly from 1990 to 2023, with rising ASMR. Males had substantially higher rates than females. Trends showed periods of increase, with continuous rises among females. Most countries showed increasing burden. Tracheal, bronchus, and lung cancer was the leading cause, followed by mesothelioma, with highest burden in older adults. CONCLUSIONS:Occupational asbestos exposure burden in SEA has increased with clear sex, age, and regional disparities, highlighting the need for strengthened control and prevention strategies.

Primary cardiac spindle cell sarcoma is extremely rare, with atypical clinical manifestations and imaging features. This case report details a 54-year-old female patient with a primary cardiac spindle cell sarcoma of the left atrium, initially thought to represent a recurrent cardiac myxoma. Despite utilizing multiple imaging techniques, the patient's complex clinical history complicated the diagnostic process, and the correct diagnosis was established after surgical resection and pathological evaluation. This case highlights the diagnostic pitfalls associated with presumed recurrent cardiac myxomas and underscores the importance of careful pathological assessment and long-term surveillance, even in tumors with low-grade malignant features.

BACKGROUND:Lumbar disc herniation (LDH) causes compositional alterations within compressed nerve roots, resulting in low back pain (LBP). The ultrashort echo time magnetization transfer technique (UTE-MT) facilitates assessment of macromolecular changes in collagen- or myelin-rich tissues in nerve roots. PURPOSE:To assess lumbar nerve root composition in LDH using UTE-MT. STUDY TYPE:Prospective. POPULATION:One hundred and seventy-six participants (age range, 20-89; 72 females) with LDH. FIELD STRENGTH/SEQUENCE:3T/UTE-MT, Carr-Purcell-Meiboom-Gill (CPMG). ASSESSMENT:UTE-MT ratio (UTE-MTR) and T2 value in compressed nerve roots (determined on axial T2) were evaluated by UTE-MT and CPMG in LDH patients (L4/5-L5/S1). Additionally, pain and functionality were evaluated using the visual analog scale (VAS) and Oswestry Disability Index (ODI). STATISTICAL TESTS:Linear regression and Bland-Altman assessed UTE-MT reproducibility. One-way ANOVA assessed the statistical significance of UTE-MTR and T2 measures between compressed and intact nerve roots. ROC and DCA evaluated diagnostic performance and clinical value of UTE-MTR and T2 in discriminating between compressed and intact nerve roots. Linear regression correlated UTE-MTR and T2 with pain and functionality scores. The p value < 0.05 was considered significant. RESULTS:Significant increases in UTE-MTR and decreases in T2 values in compressed nerve roots compared to intact ones. High AUC values for UTE-MTR (0.912 at L4/5 and 0.900 at L5/S1) highlighted its superior ability to distinguish between compressed and intact nerve roots, outperforming T2 (AUCs of 0.840 and 0.790, respectively) in cohort discrimination. Strong significant positive correlations were found between UTE-MTR and VAS (R 2 = 0.63) and ODI (R 2 = 0.62), while T2 values showed moderate significant negative correlations with VAS (R 2 = 0.32) and ODI (R 2 = 0.32) for the measurement of the most severely compressed nerve roots (determined on axial T2). DATA CONCLUSION:UTE-MT technique can detect macromolecular alterations in the compressed nerve roots of patients diagnosed with LDH. LEVEL OF EVIDENCE: 1: TECHNICAL EFFICACY:Stage 2.

Cardiac ultrasound image segmentation is a crucial task in medical image analysis. It provides efficient and accurate support for early disease screening and treatment plans. Among current deep learning methods, images acquired by different devices exhibit differences in resolution and contrast, resulting in uneven image quality and increasing the difficulty of accurate segmentation. Furthermore, Convolutional Neural Networks (CNNs) excel at local feature extraction but lack global dependencies, and Transformers capture global context yet lack fine-grained spatial information, leading to coarse upsampled segmentation. To address these limitations, this paper proposes the bit plane enhanced fusion network (BPEFNet), a segmentation method for cardiac ultrasound images. This method integrates the grayscale information of the original image and the binary image information from the 3 MSB planes. First, dual-information feature extraction (DIFE) is employed to extract both local and global information from the original image and the bit plane. Second, by leveraging the tri-branch attention cooperative interaction (TBACI) to fuse local and global features, it enhances the ability to integrate multiscale and multispatial information. The final features are obtained by fusing through the hierarchical context multi-scale aggregation (HCMSA) module. Experiments on the CAMUS dataset show that the overall Dice coefficient of BPEFNet reaches 0.9364 and 0.9196 for end-diastole (ED) and end-systole (ES) phases, respectively. The EchoNet-Dynamic dataset shows that the overall Dice coefficient of BPEFNet reaches 0.9350 and 0.9127 for ED and ES phases, respectively. Compared with other methods, it performs the best in both subjective visualization results and objective quantitative metrics, enabling accurate segmentation of cardiac structures. Our model exhibits good segmentation capability and demonstrates potential in clinical applications.

BACKGROUND:Ankle cartilage is prone to degeneration due to overuse. Developing a non-invasive MRI technique to detect early running-induced lesions enables timely intervention. PURPOSE:To evaluate the value of the ultrashort echo time magnetization transfer (UTE-MT) sequence in monitoring tibiotalar cartilage changes in amateur marathon runners before and after a marathon. STUDY TYPE:Prospective. SUBJECTS:Thirty amateur marathon runners (25 males, 5 females; range: 24-50 years). SEQUENCE:3D UTE-MT (gradient-echo), 3D UTE-T2* (gradient-echo). ASSESSMENT:MRI scans at three time points: 1 week pre-marathon, 2 days post-marathon, and 4 weeks post-marathon. Medial and lateral tibiotalar cartilage was subdivided into 12 subregions, consisting of anterior, middle, and posterior segments for the tibial and talus parts on each side. The UTE-MTR and UTE-T2* values were measured per subregion at each time point. STATISTICAL TESTS:Repeated measures one-way ANOVA and the Tukey test. p < 0.05 was considered statistically significant. RESULTS:Most cartilage subregions showed decreased UTE-MTR values 2 days post-marathon and increased after 4 weeks. Significant differences in UTE-MTR over time were observed in 9 subregions, including the medial and lateral anterior, middle, and posterior tibial cartilage (MTiA, MTiM, MTiP, LTiA, LTiM, LTiP), the medial and lateral posterior talus regions (MTaP, LTaP), and the medial middle talus cartilage (MTaM). Post hoc tests revealed significant UTE-MTR decreases 2 days post-marathon in all 9 regions (Rate: MTiA: -3.9%; MTiM: -2.8%; MTiP: -3.0%; MTaP: -4.5%; MTaM: -4.2%; LTiA: -3.5%; LTiM: -4.7%; LTiP: -5.8%; LTaP: -6.8%), with significant increases in MTiA (3.7%) and MTaM (4.4%) at 4 weeks. UTE-T2* values rose in most cartilage regions at 2 days post-marathon and continued increasing at 4 weeks. Only MTiP, LTiM, and LTaM showed significant changes. DATA CONCLUSION:This study demonstrates that the UTE-MT sequence enables the quantitative assessment of dynamic changes in tibiotalar joint cartilage after a marathon. LEVEL OF EVIDENCE: 2: TECHNICAL EFFICACY:Stage 1.

Assessing left ventricular (LV) systolic function is critical for diagnosis, treatment, and prognosis. Current methods like LV ejection fraction (LVEF) and global longitudinal strain (GLS) are time-consuming and image-quality-dependent. This study aimed to evaluate the prognostic value of Tissue Motion Annular Displacement (TMAD) in patients with CAD and develop a stable, reproducible LVEF estimation model for rapid cardiac dysfunction screening. In this prospective, multicentre study we characterised LVEF and TMAD, calculated AUROCs to predict MACE and reduced systolic function, and performed Cox modelling for MACE risk. A rapid LVEF evaluation method was developed using the best-fit model and applied in CAD patients. TMAD, especially nTMADmid, showed significant correlations with GLS (r = 0.850, P < 0.001) and LVEF (r = 0.608, P < 0.001). Moreover, TMAD demonstrated high diagnostic efficacy for identifying MACE (AUC = 0.880, P<0.001) and reduced LV systolic function (AUC = 0.903, P = 0.008). The multivariate Cox proportional hazards model revealed that TMAD was the only independent risk factor for MACE. Power equations (highest F-value) were selected to build the model, showing minimal bias between observed and estimated LVEF across validation sets. Furthermore, TMAD exhibited high intra- and inter-observer reproducibility, was independent of view selection and image quality, and required significantly shorter time-consuming than both LVEF and GLS. TMAD is a valuable tool for assessing LV systolic function and providing incremental prognostic information. The TMAD-based predictive model enables rapid LVEF prediction and rapid detection of myocardial damage. Its simplicity and independence from image quality make it particularly useful in challenging imaging scenarios. TMAD demonstrates significant correlations with both GLS and LVEF, and exhibits superior diagnostic efficacy in identifying patients with reduced LV systolic function (AUC = 0.903, P < 0.001) and major adverse cardiovascular events (AUC = 0.880, P<0.001). The LVEF-TMAD model enables rapid LVEF calculation and is effective for patients with and without coronary artery disease. TMAD, as an independent risk factor for major adverse cardiovascular events, provides incremental prognostic information.

OBJECTIVE:Given the high hypoenhancement prevalence of hepatic hemangiomas (HHs) during the transitional phase and Kupffer phase (KP) of Sonazoid contrast-enhanced ultrasound (CEUS), this study aimed to investigate the hypoenhancement phenomenon pattern and its influencing factors. METHODS:This was a prospective multicenter study. A total of 136 patients with HHs were enrolled from 26 medical centers, including 76 cases in the KP hypoenhancement group and 60 cases in the KP non-hypoenhancement group. Enhancement characteristics and patterns at different time points during the transitional phase were analyzed between the two groups. Statistical analyses included Mann-Whitney U test for two independent samples, chi-square test or Fisher's exact test for categorical variables and Spearman's rank correlation analysis for the relationship between hypoenhancement prevalence and time points. Survival analysis was used to compare differences in the start time of hypoenhancement among HHs with different characteristics. Multivariate Cox regression analysis was performed to identify the influencing factors of KP hypoenhancement. RESULTS:The hypoenhancement prevalence of HHs in the KP was 55.9% (76/136). The proportions of hyperenhancement, isohyperenhancement, mild hypoenhancement and marked hypoenhancement were 5.9% (8/136), 38.2% (52/136), 41.9% (57/136) and 14.0% (19/136), respectively. There was a significant positive correlation between the hypoenhancement prevalence and time points (rs = 0.993, p < 0.001). The main start time of hypoenhancement was 4 min (p < 0.001). The median hypoenhancement time in the KP hypoenhancement group was 5.5 min. Two-dimensional ultrasound (2-D-US) echo type and maximum diameter were independent influencing factors for Sonazoid KP hypoenhancement: hypoechoic lesions were more likely to present hypoenhancement compared with hyperechoic ones (HR = 1.80, 95% CI: 1.10-2.95, p = 0.020); both lesions ≥5 cm and those between 2 and 5 cm had a higher likelihood of hypoenhancement compared with lesions <2 cm, with HR = 2.58 (95% CI: 1.18-5.65, p = 0.018) and HR = 2.32 (95% CI: 1.35-3.97, p = 0.002), respectively. CONCLUSION:More than half of HHs show hypoenhancement in the KP of Sonazoid CEUS, and mild hypoenhancement is the main enhancement pattern among hypoenhancement cases. Hypoenhancement mostly occurs after 4 min, and the hypoenhancement prevalence gradually increases over time. The independent influencing factor for KP hypoenhancement is 2-D-US hypoechogenicity and maximum diameter greater than 2 cm.

Background: CT is limited for local staging of bladder cancer due to insufficient soft-tissue contrast. Photon-counting detector (PCD) CT with low-keV virtual monoenergetic images (VMIs) provides greater lesion contrast with acceptable image noise and high resolution and may aid assessment for muscle invasion. Objective: To compare the performance of low-keV VMIs and conventional polychromatic images for diagnosing muscle invasion on PCD CT in patients with bladder cancer. Methods: This prospective study included patients with pathologically confirmed bladder cancer who underwent preoperative PCD CT between August 2025 and March 2026. VMIs at 40, 50, 60, and 70 keV and T3D images (representing conventional polychromatic images) were reconstructed from portal venous-phase acquisitions. Two radiologists assessed objective and subjective image quality measures to identify an optimal VMI reconstruction. Three radiologists independently reviewed the optimal VMI and T3D reconstructions to assess muscle invasion using an algorithm based on bladder wall continuity at the lesion base, incorporating ancillary features (stalk, inner-layer enhancement, tumor size ≤1 cm) in equivocal cases. Diagnostic performance was assessed using transurethral resection or cystectomy as the reference. Results: The analysis included 110 patients (81 male, 29 female; median age, 63 years); 27 had muscle-invasive disease. Among VMI reconstructions, 40 keV was selected as the optimal energy level based on highest tumor SNR, tumor CNR, subjective tumor conspicuity, and subjective tumor-bladder wall interface delineation. Accuracy, sensitivity, and specificity for muscle invasion for reader 1 were 86.4%, 96.3%, and 83.1% for 40-keV VMIs and 66.4%, 96.3%, and 56.6% for T3D; for reader 2 were 87.3%, 88.9%, and 86.7% for 40-keV VMIs and 71.8%, 85.2%, and 67.5% for T3D; and for reader 3 were 80.9%, 88.9%, and 78.3% for 40-keV VMIs and 65.5%, 85.2%, and 59.0% for T3D. For all readers, accuracy and specificity were higher for 40-keV VMIs than for T3D (p<.001), whereas sensitivity was not significantly different (p>.99). Conclusion: In patients with bladder cancer undergoing PCD CT, diagnostic performance for muscle invasion was greater for 40-keV VMIs than for conventional polychromatic images. Clinical Impact: PCD CT with low-keV VMIs may have a complementary role for preoperative local staging of bladder cancer.

To evaluate whether coronal reduced field-of-view (r-FOV) diffusion-weighted imaging (DWI) improves image quality and local T staging of upper tract urothelial carcinoma (UTUC) compared with conventional axial full field-of-view (f-FOV) DWI. In this retrospective single-center study, 60 patients with pathologically confirmed UTUC who underwent preoperative magnetic resonance urography (MRU) were included. The imaging protocol comprised both axial f-FOV DWI and coronal r-FOV DWI acquired on a 3.0-T scanner. Two radiologists independently assessed subjective image quality (sharpness, distortion, artifacts, and lesion conspicuity). Tumor contrast and apparent diffusion coefficient (ADC) values were measured. Local T staging was performed using each DWI sequence, with particular focus on identifying locally advanced disease (≥ T3). Histopathology from radical nephroureterectomy served as the reference standard. Coronal r-FOV DWI demonstrated significantly higher image quality scores across all subjective parameters than axial f-FOV DWI (all p ≤ 0.003). Tumor contrast was higher on r-FOV DWI (p < 0.001), and ADC values measured on r-FOV DWI were significantly lower than those on f-FOV DWI (p < 0.001), with a strong correlation between the two techniques (r = 0.765). High-grade UTUC showed significantly lower ADC values than low-grade tumors on both sequences (p < 0.05). For detecting locally advanced disease (≥ T3), coronal r-FOV DWI achieved higher sensitivity (91.7

Background:Existing studies provide limited knowledge of the metastatic pattern, survival rate, and prognosis of primary gastrointestinal melanoma (PGM). This study aimed to investigate the metastatic patterns, prognostic factors, and conduct deep learning model of PGM. Methods:The Surveillance, Epidemiology, and End Results (SEER) database was analysed to determine survival time, survival rates, and metastatic patterns in PGM. Cox regression analysis identified prognostic factors associated with overall survival (OS) and cancer-specific survival (CSS). Patients were divided into discovery (80%) and validation cohorts (20%) to develop and validate deep learning-based models for predicting OS and CSS of PGMs. The area under the receiver operating characteristic curve (AUC) was used to evaluate model performance. Results:The median OS was 18 months [95% confidence interval (CI): 15-21] and 22 months (95% CI: 19-26) at CSS. OS rates were 60% (95% CI: 56-64%), 32% (95% CI: 28-36%), and 22% (95% CI: 18-26%) at 1, 3, and 5 years. The most common metastasis sites were the liver (19%), lungs (16%), bones (5%), and brain (4%). Older age, involvement of other sites, regional or distant stage disease, and two distant metastases were associated with worse OS or CSS, whereas systemic therapy was a protective factor. The deep learning models demonstrated performance in predicting OS (AUC: 0.7757-0.8366 at 1 year and 0.8046-0.8177 at 3 years) and CSS (0.7870-0.8169 AUC at 1 year and 0.7314-0.7720 at 3 years). Conclusions:The prognosis of PGM varies significantly among subtypes, and the models developed in this study provide accurate predictions of OS and CSS, offering potentials for clinical utility.

Objective: Recent clinical evidence indicates that persistent reservoirs of SARS-CoV-2 in human brain tissue are associated with various neurologic symptoms. While brain tumors have unique vascular abnormalities and immunosuppressive environments, it is unclear whether SARS-CoV-2 can infect brain tumors. Methods: Brain tumor samples were collected from a cohort of 72 COVID-19 patients during the SARS-CoV-2 BA.5 wave in Guangzhou. SARS-CoV-2 infection was confirmed by quantitative reverse-transcription polymerase chain reaction (qRT-PCR) and immunohistochemical (IHC) staining. Immune cell infiltration within the tumor tissues was assessed using IHC. RNA-sequencing was performed to investigate virus-host interactions in the brain tumors. Results: Brain tumor samples from 72 COVID-19 patients were examined and SARS-CoV-2 RNA was detected in 11% of the samples, which included samples from craniopharyngiomas, pituitary neuroendocrine tumors (PitNETs), meningiomas, and gliomas. SARS-CoV-2 infection was present in tumor and endothelial cells within these brain tumors. SARS-CoV-2-positive tumors had greater immune cell infiltration, particularly an increase in CD8+ T cells in gliomas and pituitary PitNETs, along with the activation of innate signaling pathways. The transcriptomic analysis revealed that activation of the complement cascade within tumors may drive changes in the immune microenvironment of SARS-CoV-2-positive tumors. Conclusions: These findings provided evidence of SARS-CoV-2 infection in brain tumors and suggested a role in altering the tumor immunosuppressive microenvironment.

IMPORTANCE:Electrical impedance tomography (EIT) offers a noninvasive, radiation-free imaging alternative, but its perfusion evaluation capability in children is understudied. Hypertonic saline-enhanced EIT may address this gap, enabling real-time guidance for individualized respiratory support. OBJECTIVES:This study aims to systematically assess the safety and efficacy of hypertonic saline-enhanced bedside EIT in evaluating pulmonary perfusion in pediatric patients with acute respiratory distress syndrome (ARDS). DESIGN:Single-center prospective observational study. SETTING AND PARTICIPANTS:Pediatric ARDS patients undergoing invasive mechanical ventilation were enrolled at the PICU of the Capital Center for Children's Health, Capital Medical University, China, from December 29, 2024, to August 7, 2025. MAIN OUTCOMES AND MEASURES:Each participant received a central venous bolus of 0.2 mL/kg (up to a maximum of 10 mL) of a 10% hypertonic saline. EIT data were collected from 2 minutes before the injection to 1-2 minutes following it. Key parameters, including dead space ventilation fraction, intrapulmonary shunt fraction, and ventilation/perfusion (V/Q) matching percentage, were analyzed to evaluate lung pathophysiology and inform therapeutic strategies. The study monitored eight patients (four males, four females; ages ranging from 4 mo to 11 yr). RESULTS:All procedures were well-tolerated, with no adverse events, including hypernatremia. In five patients who also underwent contrast-enhanced CT, EIT findings were consistent with CT results. Seven patients demonstrated matched V/Q ratios (74.97-80.39%), while one patient with pulmonary embolism exhibited increased dead space ventilation (37.03%) and decreased V/Q matching (60.71%). CONCLUSIONS AND RELEVANCE:Hypertonic saline-enhanced EIT is a safe, effective, and feasible bedside method for evaluating pulmonary perfusion in mechanically ventilated children with ARDS. These findings implied potential associations with the CT outcomes, indicating its significant potential for guiding targeted respiratory management. Although promising, these results stem from a small sample size, necessitating further validation in larger studies.

Background:Patellofemoral osteoarthritis (PFOA) is a common cause of anterior knee pain but is frequently overlooked on routine radiographic assessment. This study aimed to develop and internally validate a radiomics-based nomogram for diagnosing PFOA using lateral knee radiographs combined with clinical features. Methods:This retrospective multicenter study included 1,742 patients with 2,197 knees who underwent knee radiography between July 2017 and July 2020. During screening, 13 patients (15 knees) were excluded because of poor positioning or unqualified image quality, leaving 1,729 patients (2,182 knees) for analysis. PFOA was identified on lateral radiographs according to the Framingham criteria. Radiomic features were extracted from manually delineated rectangular regions of interest (ROIs) on lateral knee radiographs. The dataset was randomly divided into training and internal test sets at a ratio of 7:3. After feature selection, logistic regression (LR), k-nearest neighbors (KNN), and random forest (RF) models were developed and compared. A radiomics-clinical nomogram was subsequently constructed and internally validated. Results:Twenty-five radiomic features were ultimately selected for model construction. In the internal test set, the LR model achieved the best performance, with an area under the curve (AUC) of 0.773. Age was identified as an independent risk factor for PFOA. The nomogram integrating radiomic features, age, and sex showed improved diagnostic performance, with an AUC of 0.842, and demonstrated good calibration and clinical utility. External test set further demonstrated acceptable diagnostic performance of the LR model, with an AUC of 0.751. Conclusions:A radiomics-based nomogram integrating lateral knee radiographs with clinical factors showed good diagnostic performance for PFOA and may serve as a practical tool for radiographic assessment.

Objective This study examines the epidemiology and influencing factors of chronic cough in adults in the Chengdu-Chongqing region, providing a basis for its prevention and management and serving as a reference for broader research to improve respiratory health in the area. Methods 1. Questionnaire Design: The questionnaire was developed based on a literature review on chronic cough, identifying common causes, potential influencing factors, and impacts on patients. It includes demographic information, lifestyle history, medical history, cough presence and clinical characteristics, and its impact on patients. 2.Data Collection: From May 2023 to February 2024, surveys were conducted among residents aged 18 to 85 who had lived in the Chengdu or Chongqing regions for at least one year. Questionnaires were completed in communities, parks, and online using both electronic and paper formats. 3. Data Analysis: Data were entered into Questionnaire Star and analyzed using SPSS 26.0. Results A total of 4,820 questionnaires were collected, of which 4 were deemed invalid, resulting in 4,816 valid responses. Among these, 3,012 were from Chengdu, Sichuan, and 1,804 were from Chongqing. Chronic cough was present in 402 individuals, accounting for 8.35% (402/4,816) of the total population, with the majority of cases occurring in the 18-29 age group (18.66%). Chi-square tests revealed that gender, age group, education level, occupation, smoking history, alcohol consumption history, BMI categories, residential area, and history of chronic diseases were all significantly associated with chronic cough (P < 0.001). After adjusting for confounding factors through multivariate logistic regression, smoking history, alcohol consumption history, age group, history of chronic diseases, and urban residency were identified as significant risk factors for chronic cough. Conclusions The prevalence of chronic cough among adults in the Chengdu and Chongqing area is 8.35%. Factors significantly associated with chronic cough include gender, age group, occupation, education level, residential area, smoking history, alcohol consumption history, BMI categories, and history of chronic diseases. Smoking history, alcohol consumption history, age group, history of chronic diseases, and urban residency were identified as important risk factors for chronic cough. Keywords Chengdu-Chongqing Region, Chronic Cough, Epidemiological Survey, Influencing Factors