Detection of Alzheimer's Disease using cortical diffusion tensor imaging.

Mario Torso,Steven A Chance,Mark Jenkinson,Giovanna Zamboni,Marco Bozzali,For The Alzheimers Disease Neuroimage Initiative

doi:10.1002/hbm.25271

Abstract

The aim of this research was to test a novel in‐vivo brain MRI analysis method that could be used in clinical cohorts to investigate cortical architecture changes in patients with Alzheimer's Disease (AD). Three cohorts of patients with probable AD and healthy volunteers were used to assess the results of the method. The first group was used as the “Discovery” cohort, the second as the “Test” cohort and the last “ATN” (Amyloid, Tau, Neurodegeneration) cohort was used to test the method in an ADNI 3 cohort, comparing to amyloid and Tau PET. The method can detect altered quality of cortical grey matter in AD patients, providing an additional tool to assess AD, distinguishing between these and healthy controls with an accuracy range between good and excellent. These new measurements could be used within the “ATN” framework as an index of cortical microstructure quality and a marker of Neurodegeneration. Further development may aid diagnosis, patient selection, and quantification of the “Neurodegeneration” component in response to therapies in clinical trials.

Highlights

Data used in preparation of this article were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database
The present study aimed to provide the first preliminary in-vivo validation of these neuroimaging measurements in AD cohorts to demonstrate that they are sensitive to dementia-related microstructural changes
We considered as the “best discriminator” the feature with the highest area under the Receiver Operating Characteristics (ROC) curve (AUC)

Summary

Introduction

Data used in preparation of this article were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database (adni.loni.usc.edu). The investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report. A complete listing of ADNI investigators can be found at: http://adni.loni.usc.edu/wp-content/uploads/how_to_apply/ ADNI_Acknowledgement_List.pdf. 50% of dementia sufferers are thought to be undiagnosed, in the early stages of disease. Detection of Alzheimer's Disease (AD) presents a challenge for patient inclusion in drug trials, which may have contributed to trial failures costing pharmaceutical companies billions of dollars. The newly proposed Alzheimer's classification framework suggests a description based on a patient's biomarker profile (Jack Jr et al, 2018).

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