FLAIR MRI biomarkers of the normal appearing brain matter are related to cognition

被引:15
作者
Bahsoun, M-A [1 ]
Khan, M. U. [1 ]
Mitha, S. [1 ]
Ghazvanchahi, A. [1 ]
Khosravani, H. [2 ]
Maralani, P. Jabehdar [3 ]
Tardif, J-C [4 ,5 ]
Moody, A. R. [3 ]
Tyrrell, P. N. [3 ,6 ,7 ]
Khademi, A. [1 ,8 ,9 ]
机构
[1] Ryerson Univ, Elect Comp & Biomed Engn Dept, Toronto, ON, Canada
[2] Univ Toronto, Dept Med, Hurvitz Brain Sci Program, Div Neurol, Toronto, ON, Canada
[3] Univ Toronto, Dept Med Imaging, Toronto, ON, Canada
[4] Montreal Heart Inst, Montreal, PQ, Canada
[5] Univ Montreal, Dept Med, Montreal, PQ, Canada
[6] Univ Toronto, Dept Stat Sci, Toronto, ON, Canada
[7] Univ Toronto, Inst Med Sci, Toronto, ON, Canada
[8] Unity Hlth Network, Keenan Res Ctr Biomed Sci, St Michaels Hosp, Toronto, ON, Canada
[9] Inst Biomed Engn Sci & Technol iBEST, Toronto, ON, Canada
基金
美国国家卫生研究院; 加拿大创新基金会; 加拿大健康研究院; 加拿大自然科学与工程研究理事会;
关键词
FLAIR; Texture analysis; Biomarkers; Normal-appearing brain matter (NABM); Alzheimer's disease; Neurodegeneration; WHITE-MATTER; VASCULAR CONTRIBUTIONS; TEXTURE MEASURES; IMPAIRMENT; DEMENTIA; DISEASE; HYPERINTENSITIES; CLASSIFICATION; STANDARDS; RISK;
D O I
10.1016/j.nicl.2022.102955
中图分类号
R445 [影像诊断学];
学科分类号
100207 ;
摘要
A novel biomarker panel was proposed to quantify macro and microstructural biomarkers from the normal-appearing brain matter (NABM) in multicentre fluid-attenuation inversion recovery (FLAIR) MRI. The NABM is composed of the white and gray matter regions of the brain, with the lesions and cerebrospinal fluid removed. The primary hypothesis was that NABM biomarkers from FLAIR MRI are related to cognitive outcome as determined by MoCA score. There were three groups of features designed for this task based on 1) texture: microstructural integrity (MII), macrostructural damage (MAD), microstructural damage (MID), 2) intensity: median, skewness, kurtosis and 3) volume: NABM to ICV volume ratio. Biomarkers were extracted from over 1400 imaging volumes from more than 87 centres and unadjusted ANOVA analysis revealed significant differences in means of the MII, MAD, and NABM volume biomarkers across all cognitive groups. In an adjusted ANCOVA model, a significant relationship between MoCA categories was found that was dependent on subject age for MII, MAD, intensity, kurtosis and NABM volume biomarkers. These results demonstrate that structural brain changes in the NABM are related to cognitive outcome (with different relationships depending on the age of the subjects). Therefore these biomarkers have high potential for clinical translation. As a secondary hypothesis, we investigated whether texture features from FLAIR MRI can quantify microstructural changes related to how "structured" or "damaged" the tissue is. Based on correlation analysis with diffusion weighted MRI (dMRI), it was shown that FLAIR MRI texture biomarkers (MII and MAD) had strong correlations to mean diffusivity (MD) which is related to tissue degeneration in the GM and WM regions. As FLAIR MRI is routinely collected for clinical neurological examinations, novel biomarkers from FLAIR MRI could be used to supplement current clinical biomarkers and for monitoring disease progression. Biomarkers could also be used to stratify patients into homogeneous disease subgroups for clinical trials, or to learn more about mechanistic development of dementia disease.
引用
收藏
页数:21
相关论文
共 68 条
[1]   Detection of brain tumor in 3D MRI images using local binary patterns and histogram orientation gradient [J].
Abbasi, Solmaz ;
Tajeripour, Farshad .
NEUROCOMPUTING, 2017, 219 :526-535
[2]   A method of computing the effectiveness of an insecticide [J].
Abbott, WS .
JOURNAL OF ECONOMIC ENTOMOLOGY, 1925, 18 :265-267
[3]   Alzheimer's Disease Neuroimaging Initiative 2 Clinical Core: Progress and plans [J].
Aisen, Paul S. ;
Petersen, Ronald C. ;
Donohue, Michael ;
Weiner, Michael W. .
ALZHEIMERS & DEMENTIA, 2015, 11 (07) :734-739
[4]   White matter hyperintensities in vascular contributions to cognitive impairment and dementia (VCID): Knowledge gaps and opportunities [J].
Alber, Jessica ;
Alladi, Suvarna ;
Bae, Hee-Joon ;
Barton, David A. ;
Beckett, Laurel A. ;
Bell, Joanne M. ;
Berman, Sara E. ;
Biessels, Geert Jan ;
Black, Sandra E. ;
Bos, Isabelle ;
Bowman, Gene L. ;
Brai, Emanuele ;
Brickman, Adam M. ;
Callahan, Brandy L. ;
Corriveau, Roderick A. ;
Fossati, Silvia ;
Gottesman, Rebecca F. ;
Gustafson, Deborah R. ;
Hachinski, Vladimir ;
Hayden, Kathleen M. ;
Helman, Alex M. ;
Hughes, Timothy M. ;
Isaacs, Jeremy D. ;
Jefferson, Angela L. ;
Johnson, Sterling C. ;
Kapasi, Alifiya ;
Kern, Silke ;
Kwon, Jay C. ;
Kukolja, Juraj ;
Lee, Athene ;
Lockhart, Samuel N. ;
Murray, Anne ;
Osborn, Katie E. ;
Power, Melinda C. ;
Price, Brittani R. ;
Rhodius-Meester, Hanneke F. M. ;
Rondeau, Jacqueline A. ;
Rosen, Allyson C. ;
Rosene, Douglas L. ;
Schneider, Julie A. ;
Scholtzova, Henrieta ;
Shaaban, C. Elizabeth ;
Silva, Narlon C. B. S. ;
Snyder, Heather M. ;
Swardfager, Walter ;
Troen, Aron M. ;
van Veluw, Susanne J. ;
Vemuri, Prashanthi ;
Wallin, Anders ;
Wellington, Cheryl .
ALZHEIMERS & DEMENTIA-TRANSLATIONAL RESEARCH & CLINICAL INTERVENTIONS, 2019, 5 (01) :107-117
[5]   Diffusion tensor imaging of the brain [J].
Alexander, Andrew L. ;
Lee, Jee Eun ;
Lazar, Mariana ;
Field, Aaron S. .
NEUROTHERAPEUTICS, 2007, 4 (03) :316-329
[6]  
Alves Gilberto Sousa, 2012, Dement. neuropsychol., V6, P158
[7]  
Alzheimer's Disease Neuroimaging Initiative (ADNI2), 2008, DEF ALZH DIS PROC MA
[8]  
[Anonymous], FDA's Decision to Approve New Treatment for Alzheimer's Disease | FDA
[9]   Cerebrovascular pathology in Alzheimer's disease: Hopes and gaps [J].
Badji, Atef ;
Westman, Eric .
PSYCHIATRY RESEARCH-NEUROIMAGING, 2020, 306
[10]   Understanding White Matter Disease Imaging-Pathological Correlations in Vascular Cognitive Impairment [J].
Black, Sandra ;
Gao, FuQiang ;
Bilbao, Juan .
STROKE, 2009, 40 (03) :S48-S52