Dataset Information

Machine learning-based automatic estimation of cortical atrophy using brain computed tomography images.

ABSTRACT: Cortical atrophy is measured clinically according to established visual rating scales based on magnetic resonance imaging (MRI). Although brain MRI is the primary imaging marker for neurodegeneration, computed tomography (CT) is also widely used for the early detection and diagnosis of dementia. However, they are seldom investigated. Therefore, we developed a machine learning algorithm for the automatic estimation of cortical atrophy on brain CT. Brain CT images (259 Alzheimer's dementia and 55 cognitively normal subjects) were visually rated by three neurologists and used for training. We constructed an algorithm by combining the convolutional neural network and regularized logistic regression (RLR). Model performance was then compared with that of neurologists, and feature importance was measured. RLR provided fast and reliable automatic estimations of frontal atrophy (75.2% accuracy, 93.6% sensitivity, 67.2% specificity, and 0.87 area under the curve [AUC]), posterior atrophy (79.6% accuracy, 87.2% sensitivity, 75.9% specificity, and 0.88 AUC), right medial temporal atrophy (81.2% accuracy, 84.7% sensitivity, 79.6% specificity, and 0.88 AUC), and left medial temporal atrophy (77.7% accuracy, 91.1% sensitivity, 72.3% specificity, and 0.90 AUC). We concluded that RLR-based automatic estimation of brain CT provided a comprehensive rating of atrophy that can potentially support physicians in real clinical settings.

SUBMITTER: Jang JW

PROVIDER: S-EPMC9427760 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature

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Machine learning-based automatic estimation of cortical atrophy using brain computed tomography images.

Jang Jae-Won JW Kim Jeonghun J Park Sang-Won SW Kasani Payam Hosseinzadeh PH Kim Yeshin Y Kim Seongheon S Kim Soo-Jong SJ Na Duk L DL Moon Seung Hwan SH Seo Sang Won SW Seong Joon-Kyung JK

Scientific reports 20220830 1

Cortical atrophy is measured clinically according to established visual rating scales based on magnetic resonance imaging (MRI). Although brain MRI is the primary imaging marker for neurodegeneration, computed tomography (CT) is also widely used for the early detection and diagnosis of dementia. However, they are seldom investigated. Therefore, we developed a machine learning algorithm for the automatic estimation of cortical atrophy on brain CT. Brain CT images (259 Alzheimer's dementia and 55 ...[more]

PMID: 36042322

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Dataset Information

Machine learning-based automatic estimation of cortical atrophy using brain computed tomography images.

Publications

Machine learning-based automatic estimation of cortical atrophy using brain computed tomography images.

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