@article{64ffb0c5682c4f24ad1802ded8f2d9d2,
title = "Automated quantitative MRI volumetry reports support diagnostic interpretation in dementia: a multi-rater, clinical accuracy study",
abstract = "Objectives: We examined whether providing a quantitative report (QReport) of regional brain volumes improves radiologists{\textquoteright} accuracy and confidence in detecting volume loss, and in differentiating Alzheimer{\textquoteright}s disease (AD) and frontotemporal dementia (FTD), compared with visual assessment alone. Methods: Our forced-choice multi-rater clinical accuracy study used MRI from 16 AD patients, 14 FTD patients, and 15 healthy controls; age range 52–81. Our QReport was presented to raters with regional grey matter volumes plotted as percentiles against data from a normative population (n = 461). Nine raters with varying radiological experience (3 each: consultants, registrars, {\textquoteleft}non-clinical image analysts{\textquoteright}) assessed each case twice (with and without the QReport). Raters were blinded to clinical and demographic information; they classified scans as {\textquoteleft}normal{\textquoteright} or {\textquoteleft}abnormal{\textquoteright} and if {\textquoteleft}abnormal{\textquoteright} as {\textquoteleft}AD{\textquoteright} or {\textquoteleft}FTD{\textquoteright}. Results: The QReport improved sensitivity for detecting volume loss and AD across all raters combined (p = 0.015* and p = 0.002*, respectively). Only the consultant group{\textquoteright}s accuracy increased significantly when using the QReport (p = 0.02*). Overall, raters{\textquoteright} agreement (Cohen{\textquoteright}s κ) with the {\textquoteleft}gold standard{\textquoteright} was not significantly affected by the QReport; only the consultant group improved significantly (κs 0.41➔0.55, p = 0.04*). Cronbach{\textquoteright}s alpha for interrater agreement improved from 0.886 to 0.925, corresponding to an improvement from {\textquoteleft}good{\textquoteright} to {\textquoteleft}excellent{\textquoteright}. Conclusion: Our QReport referencing single-subject results to normative data alongside visual assessment improved sensitivity, accuracy, and interrater agreement for detecting volume loss. The QReport was most effective in the consultants, suggesting that experience is needed to fully benefit from the additional information provided by quantitative analyses. Key Points: • The use of quantitative report alongside routine visual MRI assessment improves sensitivity and accuracy for detecting volume loss and AD vs visual assessment alone. • Consultant neuroradiologists{\textquoteright} assessment accuracy and agreement (kappa scores) significantly improved with the use of quantitative atrophy reports. • First multi-rater radiological clinical evaluation of visual quantitative MRI atrophy report for use as a diagnostic aid in dementia.",
keywords = "Alzheimer{\textquoteright}s disease, Atrophy, Frontotemporal dementia, Magnetic resonance imaging, Radiologists",
author = "{for the Alzheimer{\textquoteright}s Disease Neuroimaging Initiative} and Pemberton, {Hugh G.} and Olivia Goodkin and Ferran Prados and Das, {Ravi K.} and Vos, {Sjoerd B.} and James Moggridge and William Coath and Elizabeth Gordon and Ryan Barrett and Anne Schmitt and Hefina Whiteley-Jones and Christian Burd and Wattjes, {Mike P.} and Sven Haller and Vernooij, {Meike W.} and Lorna Harper and Fox, {Nick C.} and Paterson, {Ross W.} and Schott, {Jonathan M.} and Sotirios Bisdas and Mark White and Sebastien Ourselin and Thornton, {John S.} and Yousry, {Tarek A.} and Cardoso, {M. Jorge} and Frederik Barkhof",
note = "Funding Information: The authors would like to thank all the study participants. We would also like to thank Rachel Scahill and Sarah Tabrizi for use of their TRACK-HD data. Data used in the preparation of this article were obtained in part from the Alzheimer?s Disease Neuroimaging Initiative (ADNI) database (adni.loni.usc.edu). Data collection and sharing for this project were funded by the Alzheimer?s Disease Neuroimaging Initiative (ADNI) (National Institutes of Health Grant U01 AG024904) and DOD ADNI (Department of Defense award number W81XWH-12-2-0012). The ADNI was launched in 2003 as a public-private partnership, led by Principal Investigator Michael W. Weiner, MD. The primary goal of ADNI has been to test whether serial magnetic resonance imaging (MRI), positron emission tomography (PET), other biological markers, and clinical and neuropsychological assessment can be combined to measure the progression of mild cognitive impairment (MCI) and early Alzheimer?s disease (AD). ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following: AbbVie, Alzheimer?s Association; Alzheimer?s Drug Discovery Foundation; Araclon Biotech; BioClinica, Inc.; Biogen; Bristol-Myers Squibb Company; CereSpir, Inc.; Cogstate; Eisai Inc.; Elan Pharmaceuticals, Inc.; Eli Lilly and Company; EuroImmun; F. Hoffmann-La Roche Ltd. and its affiliated company Genentech, Inc.; Fujirebio; GE Healthcare; IXICO Ltd.; Janssen Alzheimer Immunotherapy Research & Development, LLC.; Johnson & Johnson Pharmaceutical Research & Development LLC.; Lumosity; Lundbeck; Merck & Co., Inc.; Meso Scale Diagnostics, LLC.; NeuroRx Research; Neurotrack Technologies; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Piramal Imaging; Servier; Takeda Pharmaceutical Company; and Transition Therapeutics. The Canadian Institutes of Health Research is providing funds to support ADNI clinical sites in Canada. Private sector contributions are facilitated by the Foundation for the National Institutes of Health (www.fnih.org). The grantee organisation is the Northern California Institute for Research and Education, and the study is coordinated by the Alzheimer?s Therapeutic Research Institute at the University of Southern California. ADNI data are disseminated by the Laboratory for Neuro Imaging at the University of Southern California. Publisher Copyright: {\textcopyright} 2021, The Author(s). Copyright: Copyright 2021 Elsevier B.V., All rights reserved.",
year = "2021",
month = jul,
doi = "10.1007/s00330-020-07455-8",
language = "English",
volume = "31",
pages = "5312--5323",
journal = "European Radiology",
issn = "0938-7994",
publisher = "Springer Verlag",
number = "7",
}