Identification of patients with and without minimal hepatic encephalopathy based on gray matter volumetry using a support vector machine learning algorithm

Autor:	Zhe-Ting Yang, Tian-Xiu Zou, Hua-Jun Chen, Qiu-Feng Chen
Jazyk:	angličtina
Rok vydání:	2020
Předmět:	Adult Male Support Vector Machine Lentiform nucleus Thalamus lcsh:Medicine computer.software_genre Article 030218 nuclear medicine & medical imaging Temporal lobe Learning and memory 03 medical and health sciences 0302 clinical medicine Text mining Voxel medicine Humans Gray Matter lcsh:Science Hepatic encephalopathy Multidisciplinary medicine.diagnostic_test business.industry lcsh:R Magnetic resonance imaging Cognitive neuroscience Middle Aged medicine.disease Magnetic Resonance Imaging Computational biology and bioinformatics Frontal lobe Neurology Hepatic Encephalopathy Computational neuroscience Female lcsh:Q business computer Algorithm human activities 030217 neurology & neurosurgery Neuroscience
Zdroj:	Scientific Reports, Vol 10, Iss 1, Pp 1-8 (2020) Scientific Reports
ISSN:	2045-2322
DOI:	10.1038/s41598-020-59433-1
Popis:	Minimal hepatic encephalopathy (MHE) is characterized by diffuse abnormalities in cerebral structure, such as reduced cortical thickness and altered brain parenchymal volume. This study tested the potential of gray matter (GM) volumetry to differentiate between cirrhotic patients with and without MHE using a support vector machine (SVM) learning method. High-resolution, T1-weighted magnetic resonance images were acquired from 24 cirrhotic patients with MHE and 29 cirrhotic patients without MHE (NHE). Voxel-based morphometry was conducted to evaluate the GM volume (GMV) for each subject. An SVM classifier was employed to explore the ability of the GMV measurement to diagnose MHE, and the leave-one-out cross-validation method was used to assess classification accuracy. The SVM algorithm based on GM volumetry achieved a classification accuracy of 83.02%, with a sensitivity of 83.33% and a specificity of 82.76%. The majority of the most discriminative GMVs were located in the bilateral frontal lobe, bilateral lentiform nucleus, bilateral thalamus, bilateral sensorimotor areas, bilateral visual regions, bilateral temporal lobe, bilateral cerebellum, left inferior parietal lobe, and right precuneus/posterior cingulate gyrus. Our results suggest that SVM analysis based on GM volumetry has the potential to help diagnose MHE in cirrhotic patients.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a6d83c1591d4c0c25c426639445cdaa1 http://link.springer.com/article/10.1038/s41598-020-59433-1 Zobrazit plný text záznamu Plný text ve formátu PDF Plný text ve formátu HTML
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