Category Ranking
98%
Total Visits
921
Avg Visit Duration
2 minutes
Citations
20
Article Abstract
Hirsutism is a relatively common disorder which affects approximately 5% to 15% of women. It is defined by excessive growth of terminal hair in women, which primarily affects areas dependent on androgens, such as the face, abdomen, buttocks, and thighs. Hirsutism can be caused by a variety of etiologies, which are most often not lifethreatening. However, in some cases, hirsutism can be an indicator of more serious underlying pathology, such as a neoplasm, which may require further elucidation with imaging. Within the abdomen and pelvis, adrenal and ovarian pathologies are the primary consideration. The goal of this manuscript is to review the etiologies and imaging features of various intra-abdominal and intra-pelvic causes of hirsutism.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11213803 | PMC |
| http://dx.doi.org/10.1007/s00261-024-04189-9 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
A novel multimodal framework combining habitat radiomics, deep learning, and conventional radiomics for predicting MGMT gene promoter methylation in Glioma: Superior performance of integrated models.
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.
Clinicopathological features of dermal clear cell sarcoma: A series of 13 cases.
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 PDFLeveraging GPT-4o for Automated Extraction and Categorization of CAD-RADS Features From Free-Text Coronary CT Angiography Reports: Diagnostic Study.
JMIR 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.
Multimodal Deep Learning for Predicting Postoperative Vault and Selecting ICL Sizes Using AS-OCT and UBM Images.
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.
Morphological features of the great saphenous vein in patients with chronic venous disease of the lower extremities undergoing the most common endovenous treatment techniques.
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.