Assessment of white matter hyperintensity severity using multimodal magnetic resonance imaging
Authors: Parent Olivier , Bussy Aurélie , Devenyi Gabriel Allan , Dai Alyssa , Costantino Manuela , Tullo Stephanie , Salaciak Alyssa , Bedford Saashi , Farzin Sarah , Béland Marie-Lise , Valiquette Vanessa , Villeneuve Sylvia , Poirier Judes , Tardif Christine Lucas , Dadar Mahsa ,   the PREVENT-AD Research Group, Tam Angela , Labonté Anne , Binette Alexa Pichet , Faubert Anne-Marie , Mathieu Axel , Madjar Cécile , Carrier Charles Edouard , Dansereau Christian , Kazazian Christina , Lepage Claude , Picard Cynthia , Maillet David , Michaud Diane , Couture Doris , Dea Doris , Cuello Claudio , Barkun Alan , Evans Alan , Courcot Blandine , Tardif Christine , Debacker Clément , Jack Clifford R , Fontaine David , Knopman David S , Multhaup Gerhard , Near Jamie , Leoutsakos Jeannie-Marie , Maltais Jean-Robert , Brandt Jason , Pruessner Jens , Morris John C , Breitner John C S , Poirier Judes , Cheewakriengkrai Laksanun , MÃ¼nter Lisa-Marie , Collins Louis , Chakravarty Mallar , Sager Mark A , Dauar-Tedeschi Marina , Eisenberg Mark , Rajah Natasha , Aisen Paul , Toussaint Paule-Joanne , Rosa-Neto Pedro , Bellec Pierre , Kostopoulos Penelope , Etienne Pierre , Tariot Pierre N , Orban Pierre , Sperling Reisa A , Hoge Rick , Thomas Ronald G , Gauthier Serge , Craft Suzanne , Villeneuve Sylvia , Montine Thomas J , Nair Vasavan , Bohbot Véronique , Venugopalan Vinod , Fonov Vladimir , Ituria-Medina Yasser , Khachaturian Zaven S , Teigner Eduard , Anthal Elena , Yu Elsa , Ferdinand Fabiola , Pogossova Galina , Mayrand Ginette , Duclair Guerda , Gagné Guylaine , Newbold-Fox Holly , Leppert Illana , Vallée Isabelle , Vogel Jacob , Tremblay-Mercier Jennifer , Frenette Joanne , Frappier Josée , Kat Justin , Miron Justin , Wan Karen , Mahar Laura , Carmo Leopoldina , Théroux Louise , Dadar Mahsa , Dufour Marianne , Lafaille-Magnan Marie-Elyse , Appleby Melissa , Savard Mélissa , Tuwaig Miranda , Petkova Mirela , Rioux Pierre , Meyer Pierre-FranÃ§ois , El-Khoury Rana , Gordon Renee , Giles Renuka , Das Samir , Wang Seqian , Tabrizi Shirin , Mathotaarachchi Sulantha , Dubuc Sylvie , Lee Tanya , Beaudry Thomas , Gervais Valérie , Pagé Véronique , Gonneaud Julie , Ayranci GÃ¼lebru , Pascoal Tharick A , Desautels René , Benbouhoud Fatiha , Saint-Fort Eunice Farah , Verfaillie Sander C J , Farzin Sarah , Salaciak Alyssa , Tullo Stephanie , Vachon-Presseau Etienne , Daoust Leslie-Ann , KÃ¶be Theresa , Spreng Nathan , McSweeney Melissa , Nilsson Nathalie , Pishnamazi Morteza , Bedetti Christophe , Hudon Louise , Greco Claudia , Soucy Jean-Paul , Chakravarty M Mallar 
Published: October 2023

White matter hyperintensities are radiological abnormalities reflecting cerebrovascular dysfunction detectable using MRI. White matter hyperintensities are often present in individuals at the later stages of the lifespan and in prodromal stages in the Alzheimer’s disease spectrum. Tissue alterations underlying white matter hyperintensities may include demyelination, inflammation and oedema, but these are highly variable by neuroanatomical location and between individuals. There is a crucial need to characterize these white matter hyperintensity tissue alterations in vivo to improve prognosis and, potentially, treatment outcomes. How different MRI measure(s) of tissue microstructure capture clinically-relevant white matter hyperintensity tissue damage is currently unknown. Here, we compared six MRI signal measures sampled within white matter hyperintensities and their associations with multiple clinically-relevant outcomes, consisting of global and cortical brain morphometry, cognitive function, diagnostic and demographic differences and cardiovascular risk factors. We used cross-sectional data from 118 participants: healthy controls (n = 30), individuals at high risk for Alzheimer’s disease due to familial history (n = 47), mild cognitive impairment (n = 32) and clinical Alzheimer’s disease dementia (n = 9). We sampled the median signal within white matter hyperintensities on weighted MRI images [T1-weighted (T1w), T2-weighted (T2w), T1w/T2w ratio, fluid-attenuated inversion recovery (FLAIR)] as well as the relaxation times from quantitative T1 (qT1) and T2* (qT2*) images. qT2* and fluid-attenuated inversion recovery signals within white matter hyperintensities displayed different age- and disease-related trends compared to normal-appearing white matter signals, suggesting sensitivity to white matter hyperintensity-specific tissue deterioration. Further, white matter hyperintensity qT2*, particularly in periventricular and occipital white matter regions, was consistently associated with all types of clinically-relevant outcomes in both univariate and multivariate analyses and across two parcellation schemes. qT1 and fluid-attenuated inversion recovery measures showed consistent clinical relationships in multivariate but not univariate analyses, while T1w, T2w and T1w/T2w ratio measures were not consistently associated with clinical variables. We observed that the qT2* signal was sensitive to clinically-relevant microstructural tissue alterations specific to white matter hyperintensities. Our results suggest that combining volumetric and signal measures of white matter hyperintensity should be considered to fully characterize the severity of white matter hyperintensities in vivo. These findings may have implications in determining the reversibility of white matter hyperintensities and the potential efficacy of cardio- and cerebrovascular treatments.