Huanjun Wang

To assess the association between prenatal ultrasonography and intrauterine Cytomegalovirus (CMV) infection and to elucidate its clinical characteristics.

Background: Intraductal carcinoma (IDC) and invasive cribriform (Cr) histologic patterns are important adverse morphologies in prostate cancer (PCa) and may influence pretreatment risk stratification. This study evaluated the feasibility of time-dependent diffusion magnetic resonance imaging (t_d-dMRI)-based microstructural mapping for preoperative characterization of these aggressive morphologies. Methods: This retrospective study included 95 men with pathologically confirmed PCa on radical prostatectomy specimens from March 2023 to March 2025. T_d-dMRI was performed using pulsed and oscillating gradient diffusion sequences. Microstructural parameters, including extracellular diffusivity (D_ex), cell diameter (d), intracellular volume fraction (f_in), cellularity, and diffusivities at 0, 17, and 33 Hz (ADC_0Hz, ADC_17Hz, and ADC_33Hz), were estimated using a two-compartment model. Conventional apparent diffusion coefficient (ADC_DWI) values were obtained from standard diffusion-weighted imaging. Parameters were compared between tumors with and without Cr/IDC patterns, and diagnostic performance was assessed using receiver operating characteristic analysis. Pairwise comparisons of AUCs were performed using the DeLong test. Results: Among 95 participants, 62 (65.3%) had Cr/IDC patterns. Compared with Cr/IDC-negative tumors, Cr/IDC-positive tumors showed higher f_in and cellularity (both p < 0.001) and lower ADC_DWI, ADC_0Hz, ADC_17Hz, and ADC_33Hz values (all p < 0.05). D_ex and d did not differ significantly between groups. Among t_d-dMRI-derived parameters, f_in showed the highest diagnostic performance (AUC = 0.757; 95% CI, 0.654–0.860). Conclusions: T_d-dMRI-based microstructural mapping demonstrates promise for characterizing the Cr/IDC morphologies in PCa.

Background: The Vesical Imaging-Reporting and Data System (VI-RADS) has limited diagnostic accuracy in distinguishing non-muscle-invasive bladder cancer (NMIBC) within VI-RADS categories 2 and 3, despite its value for overall NMIBC assessment. Dynamic contrast-enhanced MRI (DCE-MRI), which reflects tumor vascularity, holds promise for improving these challenging cases but remains underutilized due to unexploited spatiotemporal information. Methods: We developed a deep learning model to comprehensively quantify spatiotemporal features from multiphase DCE-MRI in 184 patients with VI-RADS 2 or 3 (training: n = 115, validation: n = 20, testing: n = 49). The model integrated multiscale feature extraction and contextual attention mechanisms to enhance diagnostic performance. Results: The model outperformed established benchmarks (e.g., VGG, ResNet) and the conventional VI-RADS ≤ 2 threshold (sensitivity: 0.67 for NMIBC), achieving a sensitivity of 0.90 (95% CI: 0.81–0.96) for NMIBC and an area under the curve (AUC) of 0.82 (95% CI: 0.75–0.89) for overall classification. Visualizations confirmed its ability to identify key spatiotemporal patterns linked to muscle invasion. Conclusions: By leveraging comprehensive spatiotemporal information from DCE-MRI, our deep learning model significantly improves NMIBC diagnosis in VI-RADS 2/3 cases, offering a clinically valuable tool to address the limitations of current VI-RADS assessment.

Deuterium metabolic imaging (DMI) is a promising noninvasive technique for assessing tumor metabolism, yet its application in bladder cancer (BCa) remains unexplored. This study presents the first demonstration of DMI for evaluating therapeutic response in BCa through in vitro and in vivo experiments. Two types of deuterium‐labeled glucose tracers, [6,6′‐ ² H ₂ ]‐D‐glucose and [2,3,4,6,6′‐ ² H ₅ ]‐D‐glucose, are systematically compared for their efficacy in capturing glycolytic activity and treatment‐induced metabolic changes in BCa models. In subcutaneous tumors, deuterium magnetic resonance spectroscopy and spectroscopic imaging reveal pronounced suppression of glycolytic flux following chemotherapy, underscoring the potential of DMI for early therapeutic response assessment in BCa treatment. Both tracers consistently detect these chemotherapy‐related metabolism shifts in both vitro and in vivo experiments, indicating the translational advantage of [2,3,4,6,6′‐ ² H ₅ ]‐D‐glucose as a cost‐effective alternative to [6,6′‐ ² H ₂ ]‐D‐glucose. Notably, subcutaneous administration yields metabolic profiles comparable to intravenous delivery. Finally, the optimized lower‐dose, subcutaneous [2,3,4,6,6′‐ ² H ₅ ]‐D‐glucose protocol is successfully validated in orthotopic BCa models. These results demonstrate DMI as a reliable tool for non‐invasive monitoring of therapeutic response in BCa, with practical potential for future clinical translation.

Background: Bladder cancer (BCa) with variant histology (VH) is aggressive, leading to poor prognosis and resistance to neoadjuvant treatment (NAT). Preoperative identification of VH may be important for informing treatment options. Purpose: To develop and validate a multiparametric MRI‐based ensemble model to identify VH in BCa and explore its association with disease‐free survival (DFS) and NAT response. Study Type: Retrospective. Subjects: Six hundred twenty patients with pathologically confirmed BCa (median age, 65 years [IQR: 56, 73], 145 female) from four centers who underwent preoperative MRI, were divided into a training ( n = 311), internal validation ( n = 54) from Center 1, and three external validation datasets ( n = 85, 68, and 102, respectively). Two additional cohorts, DFS ( n = 75) and NAT ( n = 69) cohorts, were collected from Center 1 to evaluate prognosis. Field Strength/Sequence: 3T, non‐fat suppressed T2‐weighted imaging using fast spin echo, diffusion‐weighted imaging using single‐shot echo planar imaging, and T1‐weighted dynamic contrast‐enhanced sequence using 3D gradient echo sequence. Assessment: Habitat, radiomic, clinical, clinical‐radiomic based, and the VHRisk Score (VHRiS) models were constructed for evaluating VH. The prognostic value of VHRiS for DFS and pathological complete response (pCR) rate was further evaluated. Statistical Tests: Mann–Whitney U test, t ‐test, ROC analysis (AUC), Kaplan–Meier curves, log‐rank test, and SHapley Additive exPlanations (SHAP) analysis. Results: The VHRiS model demonstrated favorable accuracy (AUCs: training, 0.971; internal validation, 0.895; external validation, 0.898–0.974). Low‐risk patients (VHRiS ≥ 0.863) exhibited significantly longer DFS than high‐risk patients (4.20 months vs. 3.08 months) in the DFS cohort (median follow‐up period: 13.19 months [IQR: 6.54, 31.91]). They also showed a higher pCR rate than high‐risk patients (64% vs. 33%) in the NAT cohort. Data Conclusions: The VHRiS model may be a robust tool for identifying VH, and may offer a potential method for risk stratification and prognosis prediction in patients with BCa. Levels of Evidence: 4. Technical Efficacy Stage: 2.

Objective To evaluate the clinical utility of multiparametric MRI in differentiating pathological stages (ypT0 vs ypT1–4) in patients with muscle-invasive bladder cancer (MIBCa) following neoadjuvant therapy (NAT). Materials and methods In this double-center cohort study, post-NAT multiparametric MRI in all consecutive patients who underwent surgery after NAT was analyzed. Two experienced radiologists independently evaluated the MRI features obtained after NAT. The post-NAT yT stage was assigned based on T2-weighted diffusion-weighted imaging (T2DWI) and on contrast-enhanced MRI scans. The diagnostic accuracies for distinguishing post-NAT ypT0 from ypT1–4 tumors with the two protocols were evaluated. Cohen’s kappa (κ) statistics were used to evaluate the consistency between readers for the post-NAT yT stage. Results A total of 149 patients (mean age, 62 years ± 10 [SD]; 131 men) from two institutions were enrolled. The area under the receiver operating characteristic curve of the contrast-enhanced MRI protocol in predicting post-NAT ypT0 stage was 0.84 (95% CI: 0.77, 0.91), which was better than that of the T2DWI protocol (0.75; 95% CI: 0.67, 0.81; p = 0.002). The interobserver agreement was excellent for both the T2DWI protocol (κ = 0.89) and the contrast-enhanced MRI protocol (κ = 0.85). Conclusions Multiparametric MRI, particularly contrast-enhanced MRI, demonstrated superior accuracy in identifying ypT0 status following NAT in MIBCa, establishing it as an essential diagnostic tool for guiding bladder preservation in clinical decision-making. Key Points Question Accurately identifying pathological complete response (ypT0) after NAT is essential for selecting bladder-preservation strategies, yet remains clinically challenging. Findings Post-treatment contrast-enhanced MRI accurately identified ypT0 status with an AUC of 0.84 and excellent inter-reader agreement, outperforming T2DWI. Clinical relevance Contrast-enhanced MRI is a reliable, non-invasive method for detecting complete tumor response after NAT, enabling better patient selection for bladder-sparing approaches and potentially improving quality of life. Graphical Abstract

Purpose: To construct diagnostic models that distinguish renal oncocytoma (RO) from chromophobe renal cell carcinoma (CRCC) using intratumoral and peritumoral radiomic features from the corticomedullary phase (CMP) and nephrographic phase (NP) of computed tomography, and compare model results with manual and radiological results.Methods: The RO and CRCC cases from five centers were split into a training set (70%) and a validation set (30%). CMP and NP intratumoral and peritumoral (1–3 mm) radiomic features were extracted. Segmentation was performed by radiologists and software. Features with high intraclass correlation coefficients (ICC>0.75) were selected through univariate analysis, followed by the LASSO method to determine the final features for the SVM model. All images were assessed by two radiologists, and radiological reports were also examined. The diagnostic performances of the different methods were compared using several statistical methods.Results: The training set had 65 cases (29 RO, 36 CRCC) and the validation set had 27 cases (12 RO, 15 CRCC). All the training models had excellent performance (area under the curve [AUC]: 0.828–0.942); the AUC values of the validation models ranged from 0.900 (Model 4) to 0.600 (Model 2). CMP models (AUC: 0.811–0.900) generally outperformed NP and fusion models (AUC: 0.728–0.756). SVM models (sensitivity: 62.50–88.89%; specificity: 63.16–77.78%; accuracy: 62.96–81.48%) outperformed manual diagnosis (sensitivity: 46.74–70.59%; specificity: 41.67–46.34%; accuracy: 52.27–59.78%). The clinical reports alone had no diagnostic value.Conclusion: CMP intratumoral and peritumoral radiomics models reliably distinguished RO from CRCC.

Background: The detection of prostate cancer (PCa) via conventional magnetic resonance imaging (MRI) in patients with prostate-specific antigen (PSA) levels within the grey zone remains challenging. Whether synthetic MRI can provide supplementary benefits for the accurate diagnosis of PCa in this specific population is still unknown. This study aims to investigate the diagnostic performance of synthetic MRI for differentiating PCa lesions from noncancerous lesions in patients with PSA levels within the grey zone (4–10 ng/mL). Methods: Clinical and MRI data, including synthetic MRI data of patients suspected of having PCa between August 2020 and August 2022, were retrospectively collected from The First Affiliated Hospital of Sun Yat-sen University and Sun Yat-sen University Cancer Center. Patients with PSA levels ranging from 4–10 ng/mL were enrolled. Pathology was obtained either from transrectal ultrasound-guided biopsy or radical prostatectomy. Regions of interest were manually drawn by two independent radiologists, and the values of quantitative parameters, including longitudinal relaxation time (T1), transverse relaxation time (T2), proton density (PD), and apparent diffusion coefficient (ADC), were separately measured. Interobserver agreement was evaluated using the interclass correlation coefficient (ICC). The differences in quantitative parameter values between PCa and noncancerous lesions were assessed using an independent sample t-test or the Mann-Whitney U test. Receiver operating characteristic curve analysis was performed to evaluate the diagnostic performance of each parameter (T1, T2, PD, and ADC values), as well as their combination. PResults: A total of 130 patients were enrolled in this study, with a mean age of 67.32±8.87 years. The interobserver agreement of all the T1, T2, PD, and ADC values was classified as good or above (ICC =0.60–1.00). The means of the T1, T2, PD, and ADC values were significantly different between PCa and noncancerous lesions (P=0.022, PConclusions: Quantitative parameters, including T1, T2, and PD, derived from synthetic MRI can be applied to differentiate PCa lesions from noncancerous lesions in patients with PSA levels within the grey zone. However, when these parameters were combined with the ADC, the diagnostic performance did not improve compared to that with the ADC value alone.