Subin Lee, BSc; Hyunna Lee, PhD; Ki Woong Kim, MD, PhD; for the Alzheimer’s Disease Neuroimaging Initiative
Background: Early identification of people at risk of imminent progression to dementia due to Alzheimer disease is crucial for timely intervention and treatment. We investigated whether the texture of MRI brain scans could predict the progression of mild cognitive impairment (MCI) to Alzheimer disease earlier than volume.
Methods: We constructed a development data set (121 people who were cognitively normal and 145 who had mild Alzheimer disease) and a validation data set (113 patients with stable MCI who did not progress to Alzheimer disease for 3 years; 40 with early MCI who progressed to Alzheimer disease after 12–36 months; and 41 with late MCI who progressed to Alzheimer disease within 12 months) from the Alzheimer’s Disease Neuroimaging Initiative. We analyzed the texture of the hippocampus, precuneus and posterior cingulate cortex using a grey-level co-occurrence matrix. We constructed texture and volume indices from the development data set using logistic regression. Using area under the curve (AUC) of receiver operator characteristics, we compared the accuracy of hippocampal volume, hippocampal texture and the composite texture of the hippocampus, precuneus and posterior cingulate cortex in predicting conversion from MCI to Alzheimer disease in the validation data set.
Results: Compared with hippocampal volume, hippocampal texture (0.790 v. 0.739, p = 0.047) and composite texture (0.811 v. 0.739, p = 0.007) showed larger AUCs for conversion to Alzheimer disease from both early and late MCI. Hippocampal texture showed a marginally larger AUC than hippocampal volume in early MCI (0.795 v. 0.726, p = 0.060). Composite texture showed a larger AUC for conversion to Alzheimer disease than hippocampal volume in both early (0.817 v. 0.726, p = 0.027) and late MCI (0.805 v. 0.753, p = 0.019).
Limitations: This study was limited by the absence of histological data, and the pathology reflected by the texture measures remains to be validated.
Conclusion: Textures of the hippocampus, precuneus and posterior cingulate cortex predicted conversion from MCI to Alzheimer disease at an earlier time point and with higher accuracy than hippocampal volume.
Submitted Sep. 23, 2018; Revised Dec. 17, 2018; Revised Jan. 25, 2019; Revised Mar. 5, 2019; Accepted Mar. 8, 2019; Published online June 21, 2019
Acknowledgements: The authors thank Nick C. Fox for comments on the manuscript, and Da-Yea Song for assistance in collection of data. This study was supported by a grant from the Korean Health Technology R&D Project, Ministry of Health, Welfare, Republic of Korea (grant no. HI09C1379 [A092077]). 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). 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 provides 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 organization 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.
Affiliations: From the Department of Brain & Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, Korea (S. Lee, Kim); the Health Innovation Big Data Center, Asan Institute for Life Sciences, Asan Medical Center, Seoul, Korea (H. Lee); the Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, Korea (Kim); and the Department of Psychiatry, Seoul National University College of Medicine, Seoul, Korea (Kim).
Competing interests: H. Lee declares no competing interests. S. Lee and K.W. Kim have a patent relating to the content of this manuscript.
Contributors: All authors designed the study. S. Lee acquired and analyzed the data, which K.W. Kim also analyzed. S. Lee and K.W. Kim wrote the article, which all authors reviewed. All authors approved the final version to be published and can certify that no other individuals not listed as authors have made substantial contributions to the paper.
Alzheimer’s Disease Neuroimaging Initiative investigators: 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. Data used in preparation of this article were obtained from the ADNI database (adni.loni.usc.edu). As such, the ADNI investigators contributed to the design and implementation of ADNI and/ or provided data, but did not participate in analysis or writing of this report.
Correspondence to: K.W. Kim, Department of Neuropsychiatry, Seoul National University Bundang Hospital, 82 Gumi-ro 173 beon-gil, Bundang-gu, Seongnam-si, Gyeonggi-do, 13620, Republic of Korea; firstname.lastname@example.org