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Impact of social media use in static and dynamic functional network connectivity of social anxiety disorder

2026-04-14T07:23:12Z

Title: Impact of social media use in static and dynamic functional network connectivity of social anxiety disorder Authors: Kim, Hesun Erin; Kim, Byung-Hoon; Cho, Yesol; Ko, Yujin; Kim, Jae-Jin Abstract: Although social media use patterns are related to social anxiety disorder (SAD), their modulatory relationship with functional network connectivity (FNC) change remains unexplored. This study aims to address this question by utilizing static and dynamic FNC analyses. Using resting-state fMRI data from 45 SAD patients and 43 healthy controls (HC) across two acquisition timepoints (baseline, 2-month follow-up), we examined static and dynamic FNC. Standard region-of-interest (ROI)-to-ROI analysis was performed for static FNC. Dynamic FNC was analyzed using sliding-window and kmeans clustering approach. Social media usage was differentiated between messaging (MSG) and social platform (SP) across four time-of-day segments. Influences of digital social behavior were assessed through correlation analysis. Patients showed decreased static connectivity within cognitive control networks, particularly involving the default mode network. Dynamic FNC analysis identified four brain states, with SAD showing altered temporal dynamics. Specifically, patients exhibited abnormalities in the temporal properties of State 1, characterized as an internally focused state linked to self-referential processing. Lowered State 1 occurrence at follow-up was associated with higher social media use-MSG use in HC and SP use in SAD. Greater SP use was related to increased engagements of an externally vigilant state (State 3) in SAD. Aberrant temporal properties in SAD illustrate difficulties disengaging from maladaptive self-referential processing and a propensity toward heightened sensory vigilance. Furthermore, social media use, particularly content-based SP, may modulate brain dynamics related to introspection and external processing among patients. The findings underscore comprehensive neurobiological underpinnings of SAD and impacts of digital social behavior.

A Novel Radiomics-based Interpretable Model for Bladder Cancer Grade Prediction Using White-Light Cystoscopy Images

2026-05-12T08:35:44Z

Title: A Novel Radiomics-based Interpretable Model for Bladder Cancer Grade Prediction Using White-Light Cystoscopy Images Authors: Choi, Yewon; Cho, Sang Wouk; Hong, Junho; Lee, Jongsoo; Kim, Hwiyoung; Lee, Kwang Suk Abstract: Background and objective: White-light cystoscopy (WLC) is the standard diagnostic modality for bladder cancer, but preoperative grading remains inaccurate. We developed a multichannel radiomics model to predict tumour grade (low-grade [LG] vs high-grade [HG]) from WLC and to identify imaging biomarkers. Methods: WLC images were retrospectively collected from 423 patients across two centres. A total of 2624 tumour regions were segmented for training, with 584 and 358 regions for internal and external validation, respectively. Radiomic features were extracted from the greyscale and red-green-blue channels. Feature selection was performed using coefficient thresholding and the least absolute shrinkage and selection operator. Five machine-learning classifiers were trained. Model performance was assessed using discrimination, calibration, and decision curve analysis (DCA). Interpretability was assessed using SHapley Additive exPlanations (SHAP) and feature visualisation. Key findings and limitations: The support vector machine model achieved robust performance, with an area under the receiver operating characteristic curve of 0.87 (95% confidence interval [CI] = 0.84-0.89) for internal validation and 0.79 (95% CI = 0.73-0.85) for external validation. SHAP analysis revealed distinct radiomic patterns differentiating LG from HG tumours. Limitations include retrospective design, manual segmentation, and a small, imbalanced external set, so validation reflects preliminary transportability rather than robustness or generalisability. Although calibration was acceptable and net benefit appeared at thresholds >= 0.30, external data constraints warrant caution. Conclusions and clinical implications: The proposed multichannel radiomics model supports grade prediction from WLC images and identifies a green channel. This approach provides a basis for developing real-time, filter-based tools for intraoperative risk stratification. (c) 2026 The Author(s). Published by Elsevier B.V. on behalf of European Association of Urology. This is an open access article under the CC BY license (http://creativecommons. org/licenses/by/4.0/).

Ultrasound Imaging Features Associated With Neoplastic Gallbladder Polyps: A Systematic Review and Meta-Analysis

2026-04-07T02:08:19Z

Title: Ultrasound Imaging Features Associated With Neoplastic Gallbladder Polyps: A Systematic Review and Meta-Analysis Authors: Lee, Sunyoung; Chang, Won; Kim, Yeun-Yoon; Park, Jin Young; Jeon, Sun Kyung; Lee, Jeong Eun; Yoo, Jeongin; Han, Seungchul; Park, So Hyun; Kim, Jae Hyun; Park, Hyo Jung; Zhang, Hyun-Soo; Yoon, Jeong Hee Abstract: Objective: Although most gallbladder polyps are benign, some neoplastic polyps may be malignant or may serve as precursors to malignancy. Distinguishing neoplastic and non-neoplastic polyps using imaging examinations remains a major challenge. This meta-analysis aimed to identify the ultrasound (US) features that are significantly associated with neoplastic polyps. Materials and Methods: The MEDLINE, EMBASE, Cochrane, and KoreaMed databases were searched for articles published up to August 31, 2025. Bivariate random-effects models were used to calculate the meta-analytic pooled diagnostic odds ratios (DORs), sensitivities, and specificities, along with their 95% confidence intervals (CIs), for each US imaging feature in the diagnosis of neoplastic polyps. Results: Thirty studies evaluating 8,953 patients, including 1,216 (13.6%) patients with neoplastic polyps, were included. Among the nine evaluated US imaging features, namely, size >= 10 mm, sessile morphology, single polyp, coexisting gallstones, hypoechogenicity, heterogeneous echogenicity, gallbladder wall thickening (GBWT), absence of hyperechoic spot, and vascularity, eight were significantly associated with neoplastic polyps: size >= 10 mm (DOR: 6.23 [95% CI: 1.86-20.90]), sessile morphology (DOR: 3.54 [1.93-5.97]), single polyp (DOR: 2.21 [1.76-2.74]), coexisting gallstones (DOR: 1.86 [1.29-2.60]), hypoechogenicity (DOR: 3.55 [1.47-7.30]), GBWT (DOR: 9.38 [1.47-32.20]), absence of hyperechoic spots (DOR: 4.23 [2.46-6.83]), and vascularity (DOR: 9.72 [5.81-15.30]). Of these, size >= 10 mm demonstrated the highest pooled sensitivity (0.79 [95% CI: 0.68-0.87]), whereas hypoechogenicity showed the highest pooled specificity (0.93 [95% CI: 0.82-0.98]). Conclusion: Eight US imaging features (size >= 10 mm, sessile morphology, single polyp, coexisting gallstones, hypoechogenicity, GBWT, absence of hyperechoic spots, and vascularity) were significantly associated with the presence of neoplastic polyps. These features may facilitate the management of gallbladder polyps.

Association of T2-Weighted Imaging Features in Invasive Breast Cancer With Clinicopathologic Features and Neoadjuvant Treatment Outcomes

2026-04-07T02:08:16Z

Title: Association of T2-Weighted Imaging Features in Invasive Breast Cancer With Clinicopathologic Features and Neoadjuvant Treatment Outcomes Authors: Youn, Inyoung; Roh, Yun Ho; Kim, Min Jung; Yoon, Jung Hyun; Kwon, Mi-ri; Park, Vivian Youngjean Abstract: Objective: To investigate the associations between T2-weighted imaging (T2WI) features and clinicopathologic characteristics in invasive breast cancer, as well as their relationship with treatment response to neoadjuvant chemotherapy (NAC). Materials and Methods: This retrospective study included 179 women with invasive breast cancer who underwent preoperative 3T breast MRI between November 2020 and February 2021. Intratumoral T2 signal intensity (SI) and peritumoral edema were graded on T2WI, and T2 relaxation times were calculated both including and excluding necrotic or cystic areas. T2 relaxation times were compared across T2 SI grades using the Kruskal-Wallis test. Associations between T2 features and clinicopathologic factors were assessed using chi-square tests and logistic regression analyses. In patients who received NAC (n = 68), associations between T2 features and NAC outcomes were also evaluated. Results: Higher intratumoral T2 SI and peritumoral edema grades were significantly associated with longer T2 relaxation times (P < 0.001). Intratumoral T2 SI grades were associated with higher clinical T category, axillary lymph node metastasis, and tumor multiplicity (all P < 0.05). Longer intratumoral T2 relaxation times were associated with higher clinical T category, hormone receptor (HR) negativity, and the triple-negative subtype (all P < 0.05), even after excluding necrotic or cystic areas. Higher peritumoral edema grades were associated with advanced clinical T category, HR negativity, and the triple-negative subtype (all P < 0.05). T2 relaxation times of peritumoral edema showed no significant associations, except with higher clinical T category (P = 0.005) and estrogen receptor status (P = 0.030). In the NAC subgroup, higher intratumoral T2 SI grades and longer T2 relaxation times were significantly associated with disease progression during NAC (P < 0.05), but not with non-pathologic complete response. Peritumoral edema showed no significant association with NAC outcomes (P > 0.05). Conclusion: T2-weighted MRI features were associated with clinicopathologic factors, including clinical T category, HR status, triple-negative subtype, and disease progression during NAC.