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Altered gray matter morphometry in psychogenic erectile dysfunction patients: A Surface-based morphometry study

delete2025-08-06
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OA
AI
Z
Zilei Tian
Z
Ziyang Ma
B
Beihong Dou
X
Xiaopeng Huang
G
Guangsen Li
D
Degui Chang
T
Tao Yin *
P
Peihai Zhang *
DOI:10.1038/s41598-025-14706-5delete
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Abstract

Abstract

En 中文
Psychogenic erectile dysfunction (pED) is a prevalent male sexual dysfunction lacking organic etiology. Endeavors have been made in previous studies to disclose the brain pathological mechanisms of pED. However, the cortical morphological characteristics in pED patients remained largely unknown. This study enrolled 50 pED patients and 50 healthy controls (HC). The surface-based morphometry (SBM) analysis was conducted, and the between-group comparisons of the four cortical morphological parameters, including the cortical thickness, sulcus depth, gyrification index, and fractal dimension, were performed to investigate the cortical morphological alterations in pED patients, followed by correlation analysis between clinical data and SBM metrics. Furthermore, a classifier was developed based on a support vector classification algorithm and cortical morphological features to explore the feasibility of discriminating between pED patients and HC at an individual level. The results demonstrated that pED patients manifested consistent alteration in cortical morphology cross metrics in the orbitofrontal cortex, anterior and middle cingulate cortex, dorsolateral prefrontal cortex, and precentral gyrus, which were significantly correlated with the clinical symptoms in pED patients. Additionally, the classifier built based on 11 cortical morphological features achieved an accuracy of 82% in discriminating pED patients from HC. The current study provided new evidence of cortical morphological aberrations in pED patients, which deepened our understanding of the central pathology pattern of pED and was expected to facilitate the objective diagnosis of pED and the development of neuromodulation techniques targeting the alterations above.
Keywords:
Erectile dysfunction
MRI
Machine learning
Brain cortical thickness, cortical complexity
Reward system
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Scientific Reports cover
Scientific Reports
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