Sign in
NeurosciencebioRxiv
Preprint

A novel technology for objective, accurate and non-invasive early diagnosis and monitoring of Alzheimer’s disease in clinics and clinical trials

Kaveh Vejdani, Thomas Liebmann, Nicolas Adrien PannetieriD, Elham Khosravi, Mohsen YousefnezhadiD, Pavan Krishnamurthy, Nima Farzan, Cameron Bahar, Ahmad SalehiiD, Hesaam Esfandyarpour, Padideh Kamali‐Zare

Abstract

We have developed a novel medical image processing technology for objective, accurate, and non-invasive diagnosis, prognosis, and monitoring of Alzheimers disease using standard clinical brain MRI (magnetic resonance imaging) and basic clinical cognitive assessment. The technology is a robust, highly accurate, fully automated, high-throughput, cloud-based platform, which operates in a fully integrated and controlled environment. In diagnosis mode, our technology performs with 91% balanced accuracy on blind testing to diagnose the current neurocognitive status, and in prognosis mode or early detection at mild cognitive impairment (MCI) stage with 88% balanced accuracy on blind testing to predict progression from MCI to Alzheimers dementia (AD) within 5 years. Such prognostic capability is currently non-existent, even in specialty clinics and hospitals, a major factor in Alzheimers clinical trial failures. The algorithms diagnostic certainty precisely mirrors the diagnostic confidence of an expert cognitive neurologist for both MCI (Spearmans Rho = 1) and AD (Rho = 1). In addition to widespread clinical applications, this novel technology can enable correct patient selection and therapeutic effect monitoring in clinical trials of Alzheimers disease, the crucial elements to finding a cure.

PDFDOI

02 /Specification & Classification

Click any tag to browse matching papers

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISGrassi '19Tam '19Qiu '20Zandifar '19Satone '20Abrol '19
69% semantic matchNeuroscience
Massimiliano Grassi, Nadine Rouleaux, Daniela Caldirola+5 more·Frontiers in Neurology·Jul 16, 2019· 126 citations