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Purpose: Gait improvement following high-volume lumbar puncture (HVLP) and continuous lumbar drain (cLD) is widely used to predict shunt response in patients with suspected normal pressure hydrocephalus (NPH). Here, we investigate differences in MRI volumetric and traditional measures between HVLP/cLD responders and non-responders to identify imaging features that may help predict HVLP/cLD response.
Methods: Eighty-two patients with suspected NPH were studied retrospectively. Gait testing was performed before and immediately/24 h/72 h after HVLP/cLD. A positive response was defined as improvement in gait post-procedure. Thirty-six responders (26 men; mean age 79.3 ± 6.3) and 46 non-responders (25 men; mean age 77.2 ± 6.1) underwent pre-procedure brain MRI including a 3D T1-weighted sequence. Subcortical regional volumes were segmented using FreeSurfer. After normalizing for total intracranial volume, two-way type III ANCOVA test and chi-square test were used to characterize statistical group differences. Evans' index, callosal angle (CA), and disproportionately enlarged subarachnoid space hydrocephalus were assessed. Multivariable logistic regression models were tested using Akaike information criterion to determine which combination of metrics most accurately predicts HVLP/cLD response.
Results: Responders and non-responders demonstrated no differences in total ventricular and white/gray matter volumes. CA (men only) and third and fourth ventricular volumes were smaller; and hippocampal volume was larger in responders (p < 0.05). Temporal horns volume correlated with degree of improvement in gait velocity in responders (p = 0.0006). The regression model was 76.8% accurate for HVLP/cLD response.
Conclusion: CA and third and fourth ventricular volumes and hippocampal volume may serve as potentially useful imaging features that may help predict spinal tap response and hence potentially shunt response.
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http://dx.doi.org/10.1007/s00234-021-02782-z | DOI Listing |
Eur J Radiol
September 2025
Department of Radiology, Affiliated Hospital of Hebei University, Baoding 071000, China. Electronic address:
Purpose: The present study aimed to develop a noninvasive predictive framework that integrates clinical data, conventional radiomics, habitat imaging, and deep learning for the preoperative stratification of MGMT gene promoter methylation in glioma.
Materials And Methods: This retrospective study included 410 patients from the University of California, San Francisco, USA, and 102 patients from our hospital. Seven models were constructed using preoperative contrast-enhanced T1-weighted MRI with gadobenate dimeglumine as the contrast agent.
Pathol Res Pract
September 2025
Department of Pathology, Xijing Hospital and School of Basic Medicine, Fourth Military Medical University, Xi'an, China. Electronic address:
Background: Dermal clear cell sarcoma (DCCS) is a rare malignant mesenchymal neoplasm. Owing to the overlaps in its morphological and immunophenotypic profiles with a broad spectrum of tumors exhibiting melanocytic differentiation, it is frequently misdiagnosed as other tumor entities in clinical practice. By systematically analyzing the clinicopathological characteristics, immunophenotypic features, and molecular biological properties of DCCS, this study intends to further enhance pathologists' understanding of this disease and provide a valuable reference for its accurate diagnosis.
View Article and Find Full Text PDFJMIR Med Inform
September 2025
Departments of Radiology, The Third Affiliated Hospital, Sun Yat-Sen University, 600 Tianhe Road, Guangzhou, Guangdong, 510630, China, 86 18922109279, 86 20852523108.
Background: Despite the Coronary Artery Reporting and Data System (CAD-RADS) providing a standardized approach, radiologists continue to favor free-text reports. This preference creates significant challenges for data extraction and analysis in longitudinal studies, potentially limiting large-scale research and quality assessment initiatives.
Objective: To evaluate the ability of the generative pre-trained transformer (GPT)-4o model to convert real-world coronary computed tomography angiography (CCTA) free-text reports into structured data and automatically identify CAD-RADS categories and P categories.
J Cataract Refract Surg
July 2025
Department of Ophthalmology, West China Hospital of Sichuan University, Chengdu City, Sichuan Province, China.
Purpose: To develop and validate a multimodal deep-learning model for predicting postoperative vault height and selecting implantable collamer lens (ICL) sizes using Anterior Segment Optical Coherence Tomography (AS-OCT) and Ultrasound Biomicroscope (UBM) images combined with clinical features.
Setting: West China Hospital of Sichuan University, China.
Design: Deep-learning study.
Pol Merkur Lekarski
September 2025
Kharkiv Clinical Hospital on Railway Transport No. 1 ≪Health Care Center≫ of Joint-Stock Company «Ukrainian Railways», Kharkiv, Ukraine.
Objective: Aim: The purpose was to identify the morphological features of the great saphenous vein in patients with chronic venous disease of the lower extremities undergoing treatment with endovenous high-frequency electric welding in automatic mode, endovenous laser ablation, and ultrasound-guided microfoam sclerotherapy.
Patients And Methods: Materials and Methods: The material for the comprehensive morphological study consisted of fragments of the great saphenous vein obtained from 32 patients with chronic venous disease of the lower extremities. The material was divided into three groups according to the endovenous treatment techniques applied.