Background: This systematic review investigates the integration of automatic segmentation techniques of magnetic resonance imaging (MRI) with neuropsychological assessments for early diagnosis and prognosis of Alzheimer's Disease (AD). Objectives: Focus on studies that utilise automated MRI segmentation and neuropsychological evaluations across the AD spectrum. Data sources: A literature search was conducted on the PubMed database on 7 November 2024, using key terms related to MRI, segmentation, brain structures, AD, and cognitive decline. Study eligibility criteria: Studies including individuals with AD, mild cognitive impairment (MCI), or subjective cognitive decline (SCD), utilising structural MRI, focusing on grey matter and automatic segmentation, and reporting cognitive assessments were included. Study appraisal and synthesis methods: Data were extracted and synthesised focusing on associations between MRI measures and cognitive tests, and discriminative values for diagnosis or prognosis. Results: Seven studies were included, showing a significant association between structural changes in the medial temporal lobe and cognitive decline. The combination of MRI volumetric measures and neuropsychological scores enhanced diagnostic accuracy. Neuropsychological measures demonstrated superiority in the identification of patients with MCI and mild AD in comparison to MRI measures alone. Limitations: Heterogeneity across studies, selection and measurement bias, and lack of non-response data were noted. Conclusions and implications: This review emphasises the necessity of integrating automated MRI segmentation with neuropsychological assessments for the diagnosis and prognosis of AD. While MRI is valuable, neuropsychological testing remains essential for early detection. Future studies should focus on developing integrated predictive models and refining neuroimaging techniques.
Integration of automatic MRI segmentation techniques with neuropsychological assessments for early diagnosis and prognosis of Alzheimer’s disease. A systematic review
Sabrina Bonarota;Federico Giove;
2025-01-01
Abstract
Background: This systematic review investigates the integration of automatic segmentation techniques of magnetic resonance imaging (MRI) with neuropsychological assessments for early diagnosis and prognosis of Alzheimer's Disease (AD). Objectives: Focus on studies that utilise automated MRI segmentation and neuropsychological evaluations across the AD spectrum. Data sources: A literature search was conducted on the PubMed database on 7 November 2024, using key terms related to MRI, segmentation, brain structures, AD, and cognitive decline. Study eligibility criteria: Studies including individuals with AD, mild cognitive impairment (MCI), or subjective cognitive decline (SCD), utilising structural MRI, focusing on grey matter and automatic segmentation, and reporting cognitive assessments were included. Study appraisal and synthesis methods: Data were extracted and synthesised focusing on associations between MRI measures and cognitive tests, and discriminative values for diagnosis or prognosis. Results: Seven studies were included, showing a significant association between structural changes in the medial temporal lobe and cognitive decline. The combination of MRI volumetric measures and neuropsychological scores enhanced diagnostic accuracy. Neuropsychological measures demonstrated superiority in the identification of patients with MCI and mild AD in comparison to MRI measures alone. Limitations: Heterogeneity across studies, selection and measurement bias, and lack of non-response data were noted. Conclusions and implications: This review emphasises the necessity of integrating automated MRI segmentation with neuropsychological assessments for the diagnosis and prognosis of AD. While MRI is valuable, neuropsychological testing remains essential for early detection. Future studies should focus on developing integrated predictive models and refining neuroimaging techniques.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
