Individualized Prediction of Early Alzheimer's Disease Based on Magnetic Resonance Imaging Radiomics, Clinical, and Laboratory Examinations: A 60-Month Follow-Up Study.
J Magn Reson Imaging
; 54(5): 1647-1657, 2021 11.
Article
em En
| MEDLINE
| ID: mdl-33987915
ABSTRACT
BACKGROUND:
Accurately predicting whether and when mild cognitive impairment (MCI) will progress to Alzheimer's disease (AD) is of vital importance to help developing individualized treatment plans to defer the occurrence of irreversible dementia.PURPOSE:
To develop and validate radiomics models and multipredictor nomogram for predicting the time to progression (TTP) from MCI to AD. STUDY TYPE Retrospective. POPULATION One hundred sixty-two MCI patients (96 men and 66 women [median age, 72; age range, 56-88 years]) were included from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. FIELD STRENGTH/SEQUENCE T1 -weighted imaging and T2 -weighted fluid-attenuation inversion recovery imaging acquired at 3.0 T. ASSESSMENT During the 5-year follow-up, 68 patients converted to AD and 94 remained stable. Patients were randomly divided into the training (n = 112) and validation datasets (n = 50). Radiomic features were extracted from the whole cerebral cortex and subcortical nucleus of MR images. A radiomics model was established using least absolute shrinkage and selection operator (LASSO) Cox regression. The clinical-laboratory model and radiomics-clinical-laboratory model were developed by multivariate Cox proportional hazard model. The performance of each model was assessed by the concordance index (C-index). A multipredictor nomogram derived from the radiomics-clinical-laboratory model was constructed for individualized TTP estimation. STATISTICAL TESTS LASSO cox regression, univariate and multivariate Cox regression, Kaplan-Meier analysis and Student's t test were performed.RESULTS:
The C-index of the radiomics, clinical-laboratory and radiomics-clinical-laboratory models were 0.924 (95% confidence interval [CI] 0.894-0.952), 0.903 (0.868-0.938), 0.950 (0.929-0.971) in the training cohort and 0.811 (0.707-0.914), 0.901 (0824-0.977), 0.907 (0.836-0.979) in the validation cohort, respectively. A multipredictor nomogram with 15 predictors was established, which had high accuracy for individual TTP prediction with the C-index of 0.950 (0.929-0.971). DATACONCLUSION:
The prediction of individual TTP from MCI to AD could be accurately conducted using the radiomics-clinical-laboratory model and multipredictor nomogram. EVIDENCE LEVEL 3 TECHNICAL EFFICACY 2.Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Doença de Alzheimer
Tipo de estudo:
Observational_studies
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Prognostic_studies
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Risk_factors_studies
Limite:
Aged
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Aged80
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Female
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Humans
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Male
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Middle aged
Idioma:
En
Revista:
J Magn Reson Imaging
Assunto da revista:
DIAGNOSTICO POR IMAGEM
Ano de publicação:
2021
Tipo de documento:
Article
País de afiliação:
China
País de publicação:
EEUU
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ESTADOS UNIDOS
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ESTADOS UNIDOS DA AMERICA
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EUA
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UNITED STATES
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UNITED STATES OF AMERICA
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US
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USA