Multimodal Hippocampal Subfield Grading For Alzheimer’s Disease Classification
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Abstract
Numerous studies have proposed biomarkers based on magnetic resonance imaging (MRI) to detect and predict the risk of evolution toward Alzheimer’s disease (AD). Most of these methods have focused on the hippocampus, which is known to be one of the earliest structures impacted by the disease. To date, patch-based grading approaches provide among the best biomarkers based on the hippocampus. However, this structure is complex and is divided into different subfields, not equally impacted by AD. Former in - vivo imaging studies mainly investigated structural alterations of these subfields using volumetric measurements and microstructural modifications with mean diffusivity measurements. The aim of our work is to improve the current classification performances based on the hippocampus with a new multimodal patch-based framework combining structural and diffusivity MRI. The combination of these two MRI modalities enables the capture of subtle structural and microstructural alterations. Moreover, we propose to study the efficiency of this new framework applied to the hippocampal subfields. To this end, we compare the classification accuracy provided by the different hippocampal subfields using volume, mean diffusivity, and our novel multimodal patch-based grading framework combining structural and diffusion MRI. The experiments conducted in this work show that our new multimodal patch-based method applied to the whole hippocampus provides the most discriminating biomarker for advanced AD detection while our new framework applied into subiculum obtains the best results for AD prediction, improving by two percentage points the accuracy compared to the whole hippocampus.
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EC and hippocampus are two key vulnerable brain regions in AD, becoming affected in the early stages of AD.
“The EC and hippocampus are two key vulnerable brain regions in AD, becoming affected in the early stages of AD (Mak et al., 2017, Hett et al., 2019).”
From Disrupted structural connectivity in ArcAβ mouse model of Aβ amyloidosis (2020) · cites this paper as Hett et al., 2019
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Adaptive fusion of texture-based grading for Alzheimer's disease classification
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Alzheimer's disease with asymmetric parietal lobe atrophy: a case report.
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Self-citationDiscriminative analysis of multivariate features from structural MRI and diffusion tensor images
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Self-citationPatch-Based DTI Grading: Application to Alzheimer’s Disease Classification
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Self-citationNICE: Non-local Intracranial Cavity Extraction
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Self-citationAltered hippocampal subfield volumes in major depressive disorder with and without anhedonia
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Self-citationA novel deep learning based hippocampus subfield segmentation method
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Self-citationMultimodal hippocampal and amygdala subfield volumetry in polygenic risk for Alzheimer's disease
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Self-citationDeep neural network CSES-NET and multi-channel feature fusion for Alzheimer's disease diagnosis
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Electroacupuncture improves vascular cognitive impairment no dementia: A Randomized Clinical Trial
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Combining Nonlinear Features of EEG and MRI to Diagnose Alzheimer’s Disease
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Predicting Mental Decline Rates in Mild Cognitive Impairment From Baseline MRI Volumetric Data
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Ex-Vivo Hippocampus Segmentation Using Diffusion-Weighted MRI
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Self-citationVolumetric changes within hippocampal subfields in Alzheimer’s disease continuum
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Self-citationDeepHIPS: A novel Deep Learning based Hippocampus Subfield Segmentation methodPreprint
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Self-citationPatch-Based Abnormality Maps for Improved Deep Learning-Based Classification of Huntington’s Disease
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Self-citationDisrupted structural connectivity in ArcAβ mouse model of Aβ amyloidosis
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“The EC and hippocampus are two key vulnerable brain regions in AD, becoming affected in the early stages of AD (Mak et al., 2017, Hett et al., 2019).”
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Self-citationVoxel-Level fMRI Analysis by Representation Learning and Deep Clustering for Alzheimer’s Disease
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An Image Feature extraction technique Alzheimer’s disease using inductive learning
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Vision Sensors - Recent Advances
Gallegos-Funes, F. J. (2022) · IntechOpen eBooks · doi:10.5772/intechopen.100738 · Cited by 1 · see citing works
EEG and MRI Processing for Alzheimer’s Diseases
Rad, E. M. (2022) · IntechOpen eBooks · doi:10.5772/intechopen.107162 · Cited by 1 · see citing works
Predicting MCI and Alzheimer’s disease on structural brain integrity with machine learningPreprint
Mieling, M., Yousuf, M., & Bunzeck, N. (2023) · doi:10.31219/osf.io/8dtcm
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Ding, S., Johns, E., Orlichenko, A., Fredericks, C. A., & Zhao, Y. (2026) · The Annals of Applied Statistics · doi:10.1214/26-aoas2154
Moslehi, M., Sharma, R., Khorasani, A., & NeuroimagingInitiative, F. T. A. D. (2026) · Journal of Imaging Informatics in Medicine · doi:10.1007/s10278-026-02181-x
- Authors
- Hett, K., Ta, V.-T., Catheline, G., Tourdias, T., Manjón, J. V., Coupé, P., Initiative, A. D. N., Weiner, M. W., Aisen, P., Petersen, R., Jack, C. R., Jagust, W., Trojanowki, J. Q., Toga, A. W., Beckett, L., Green, R. C., Saykin, A. J., Morris, J., Shaw, L. M., Khachaturian, Z., Sorensen, G., Carrillo, M., Kuller, L., Raichle, M., Paul, S., Davies, P., Fillit, H., Hefti, F., Holtzman, D., Mesulam, M. M., Potter, W., Snyder, P., Montine, T., Thomas, R. G., Donohue, M., Walter, S., Sather, T., Jiminez, G., Balasubramanian, A. B., Mason, J., Sim, I., Harvey, D., Bernstein, M., Fox, N., Thompson, P., Schuff, N., DeCArli, C., Borowski, B., Gunter, J., Senjem, M., Vemuri, P., Jones, D., Kantarci, K., Ward, C., Koeppe, R. A., Foster, N., Reiman, E. M., Chen, K., Mathis, C., Landau, S., Cairns, N. J., Householder, E., Taylor-Reinwald, L., Lee, V., Korecka, M., Figurski, M., Crawford, K., Neu, S., Foroud, T. M., Potkin, S., Shen, L., Faber, K., Kim, S., Nho, K., Thal, L., Frank, R., Hsiao, J., Kaye, J., Quinn, J., Silbert, L., Lind, B., Carter, R., Dolen, S., Ances, B., Carroll, M., Creech, M. L., Franklin, E., Mintun, M. A., Schneider, S., Oliver, A., Schneider, L. S., Pawluczyk, S., Beccera, M., Teodoro, L., Spann, B. M., Brewer, J., Vanderswag, H., Fleisher, A., Marson, D., Griffith, R., Clark, D., Geldmacher, D., Brockington, J., Roberson, E., Love, M. N., Heidebrink, J. L., Lord, J. L., Mason, S. S., Albers, C. S., Knopman, D., Johnson, K., Grossman, H., Mitsis, E., Shah, R. C., deToledo-Morrell, L., Doody, R. S., Villanueva-Meyer, J., Chowdhury, M., Rountree, S., Dang, M., Duara, R., Varon, D., Greig, M. T., Roberts, P., Stern, Y., Honig, L. S., Bell, K. L., Albert, M., Onyike, C., D’Agostino, D., Kielb, S., Galvin, J. E., Cerbone, B., Michel, C. A., Pogorelec, D. M., Rusinek, H., de Leon, M. J., Glodzik, L., De Santi, S., Womack, K., Mathews, D., Quiceno, M., Doraiswamy, P. M., Petrella, J. R., Borges-Neto, S., Wong, T. Z., Coleman, E., Levey, A. I., Lah, J. J., Cella, J. S., Burns, J. M., Swerdlow, R. H., Brooks, W. M., Arnold, S. E., Karlawish, J. H., Wolk, D., Clark, C. M., Apostolova, L., Tingus, K., Woo, E., Silverman, D. H. S., Lu, P. H., Bartzokis, G., Smith, C. D., Jicha, G., Hardy, P., Sinha, P., Oates, E., Conrad, G., Graff-Radford, N. R., Parfitt, F., Kendall, T., Johnson, H., Lopez, O. L., Oakley, M., Simpson, D. M., Farlow, M. R., Hake, A. M., Matthews, B. R., Brosch, J. R., Herring, S., Hunt, C., Porsteinsson, A. P., Goldstein, B. S., Martin, K., Makino, K. M., Ismail, M. S., Brand, C., Mulnard, R. A., Thai, G., Mc-Adams-Ortiz, C., van Dyck, C. H., Carson, R. E., MacAvoy, M. G., Varma, P., Chertkow, H., Bergman, H., Hosein, C., Black, S., Stefanovic, B., Caldwell, C., Hsiung, G.-Y. R., Feldman, H., Mudge, B., Assaly, M., Finger, E., Pasternack, S., Rachisky, I., Trost, D., Kertesz, A., Bernick, C., Munic, D., Lipowski, K., Weintraub, M. A. S., Bonakdarpour, B., Kerwin, D., Wu, C.-K., Johnson, N., Sadowsky, C., Villena, T., Turner, R. S., Johnson, K., Reynolds, B., Sperling, R. A., Johnson, K. A., Marshall, G., Yesavage, J., Taylor, J. L., Lane, B., Rosen, A., Tinklenberg, J., Sabbagh, M. N., Belden, C. M., Jacobson, S. A., Sirrel, S. A., Kowall, N., Killiany, R., Budson, A. E., Norbash, A., Johnson, P. L., Obisesan, T. O., Wolday, S., Allard, J., Lerner, A., Ogrocki, P., Tatsuoka, C., Fatica, P., Fletcher, E., Maillard, P., Olichney, J., Carmichael, O., Kittur, S., Borrie, M., Lee, T.-Y., Bartha, R., Johnson, S., Asthana, S., Carlsson, C. M., Preda, A., Nguyen, D., Tariot, P., Burke, A., Trncic, N., Fleisher, A., Reeder, S., Bates, V., Capote, H., Rainka, M., Scharre, D. W., Kataki, M., Adeli, A., Zimmerman, E. A., Celmins, D., Brown, A. D., Pearlson, G. D., Blank, K., Anderson, K., Flashman, L. A., Seltzer, M., Hynes, M. L., Santulli, R. B., Sink, K. M., Gordineer, L., Williamson, J. D., Garg, P., Watkins, F., Ott, B. R., Querfurth, H., Tremont, G., Salloway, S., Malloy, P., Correia, S., Rosen, H. J., Miller, B. L., Perry, D., Mintzer, J., Spicer, K., Bachman, D., Finger, E., Pasternak, S., Rachinsky, I., Rogers, J., Drost, D., Pomara, N., Hernando, R., Sarrael, A., Schultz, S. K., Boles Ponto, L. L., Shim, H., Smith, K. E., Relkin, N., Chaing, G., Lin, M., Ravdin, L., Smith, A., Raj, B. A., & Fargher, K.
- Affiliations
- Centre National de la Recherche Scientifique (FR)
- Université de Bordeaux (FR)
- Universitat Politècnica de València (ES)
- University of California, San Francisco (US)
- University of California San Diego (US)
- Mayo Clinic (US)
- University of California, Berkeley (US)
- University of Pennsylvania (US)
- University of Southern California (US)
- University of California, Davis (US)
- Brigham and Women's Hospital (US)
- Indiana University Bloomington (US)
- Washington University in St. Louis (US)
- Prevent Alzheimer’s Disease 2020 (US)
- Siemens (Germany) (DE)
- Alzheimer's Association (US)
- Cornell University (US)
- Albert Einstein College of Medicine (US)
- Alzheimer's Drug Discovery Foundation (US)
- Acumen Pharmaceuticals (United States) (US)
- Northwestern University (US)
- National Institute of Mental Health (US)
- Brown University (US)
- University of Washington (US)
- University of California, Los Angeles (US)
- University of Michigan (US)
- University of Utah (US)
- Banner Alzheimer’s Institute (US)
- University of Pittsburgh (US)
- University of California, Irvine (US)
- National Institute on Aging (US)
- Oregon Health & Science University (US)
- University of Alabama at Birmingham (US)
- Icahn School of Medicine at Mount Sinai (US)
- Rush University Medical Center (US)
- Baylor College of Medicine (US)
- Columbia University Irving Medical Center (US)
- Johns Hopkins University (US)
- New York University (US)
- Duke Medical Center (US)
- Emory University (US)
- University of Kansas Medical Center (US)
- University of Kentucky (US)
- University of Rochester Medicine (US)
- Yale University (US)
- Jewish General Hospital (CA)
- Sunnybrook Health Science Centre (CA)
- University of British Columbia (CA)
- St. Joseph's Hospital (CA)
- Cleveland Clinic (US)
- Palm Beach Neurology (US)
- Georgetown University Medical Center (US)
- Stanford University (US)
- Boston University (US)
- Howard University (US)
- Case Western Reserve University (US)
- St Joseph's Health Care (CA)
- Dent Neurologic Institute (US)
- The Ohio State University (US)
- Albany Medical College (US)
- Hartford Hospital (US)
- Dartmouth–Hitchcock Medical Center (US)
- Wake Forest University Health Sciences (US)
- Medical University of South Carolina (US)
- Nathan Kline Institute for Psychiatric Research (US)
- University of Iowa (US)
- University of South Florida (US)
- Corresponding author
- Hett, Kilian
- ORCID
- Hett, Kilian
- Ta, Vinh-Thong
- Tourdias, Thomas
- Manjón, José V.
- Weiner, Michael W.
- Aisen, Paul
- Petersen, Ronald
- Jack, Clifford R.
- Jagust, William
- Toga, Arthur W.
- Beckett, Laurel
- Green, Robert C.
- Saykin, Andrew J.
- Morris, John
- Shaw, Leslie M.
- Paul, Steven
- Davies, Peter
- Fillit, Howard
- Hefti, Franz
- Mesulam, M. Marcel
- Snyder, Peter
- Thomas, Ronald G.
- Donohue, Michael
- Walter, Sarah
- Balasubramanian, Archana B.
- Fox, Nick
- Thompson, Paul
- DeCArli, Charles
- Vemuri, Prashanthi
- Jones, David
- Kantarci, Kejal
- Koeppe, Robert A.
- Reiman, Eric M.
- Chen, Kewei
- Landau, Susan
- Cairns, Nigel J.
- Korecka, Magdalena
- Crawford, Karen
- Foroud, Tatiana M.
- Potkin, Steven
- Shen, Li
- Faber, Kelley
- Kim, Sungeun
- Nho, Kwangsik
- Hsiao, John
- Kaye, Jeffrey
- Quinn, Joseph
- Silbert, Lisa
- Ances, Beau
- Carroll, Maria
- Franklin, Erin
- Oliver, Angela
- Schneider, Lon S.
- Marson, Daniel
- Clark, David
- Geldmacher, David
- Roberson, Erik
- Love, Marissa Natelson
- Heidebrink, Judith L.
- Lord, Joanne L.
- Knopman, David
- Johnson, Kris
- Shah, Raj C.
- Duara, Ranjan
- Stern, Yaakov
- Honig, Lawrence S.
- Bell, Karen L.
- Albert, Marilyn
- Onyike, Chiadi
- D’Agostino, Daniel
- Kielb, Stephanie
- Galvin, James E.
- Cerbone, Brittany
- Rusinek, Henry
- Glodzik, Lidia
- Womack, Kyle
- Quiceno, Mary
- Doraiswamy, P. Murali
- Petrella, Jeffrey R.
- Wong, Terence Z.
- Levey, Allan I.
- Lah, James J.
- Burns, Jeffrey M.
- Swerdlow, Russell H.
- Brooks, William M.
- Arnold, Steven E.
- Karlawish, Jason H.
- Wolk, David
- Clark, Christopher M.
- Apostolova, Liana
- Silverman, Daniel H. S.
- Lu, Po H.
- Smith, Charles D.
- Hardy, Peter
- Sinha, Partha
- Johnson, Heather
- Farlow, Martin R.
- Hake, Ann Marie
- Brosch, Jared R.
- Porsteinsson, Anton P.
- Ismail, M. Saleem
- Thai, Gaby
- Carson, Richard E.
- Chertkow, Howard
- Bergman, Howard
- Stefanovic, Bojana
- Hsiung, Ging-Yuek Robin
- Feldman, Howard
- Bernick, Charles
- Bonakdarpour, Borna
- Kerwin, Diana
- Johnson, Nancy
- Turner, Raymond Scott
- Sperling, Reisa A.
- Johnson, Keith A.
- Marshall, Gad
- Yesavage, Jerome
- Taylor, Joy L.
- Lane, Barton
- Rosen, Allyson
- Sabbagh, Marwan N.
- Belden, Christine M.
- Jacobson, Sandra A.
- Kowall, Neil
- Killiany, Ronald
- Budson, Andrew E.
- Norbash, Alexander
- Obisesan, Thomas O.
- Lerner, Alan
- Tatsuoka, Curtis
- Fletcher, Evan
- Maillard, Pauline
- Olichney, John
- Carmichael, Owen
- Johnson, Sterling
- Asthana, Sanjay
- Carlsson, Cynthia M.
- Preda, Adrian
- Nguyen, Dana
- Tariot, Pierre
- Burke, Anna
- Scharre, Douglas W.
- Kataki, Maria
- Pearlson, Godfrey D.
- Flashman, Laura A.
- Hynes, Mary L.
- Santulli, Robert B.
- Sink, Kaycee M.
- Williamson, Jeff D.
- Garg, Pradeep
- Ott, Brian R.
- Tremont, Geoffrey
- Salloway, Stephen
- Correia, Stephen
- Miller, Bruce L.
- Mintzer, Jacobo
- Bachman, David
- Pasternak, Stephen
- Pomara, Nunzio
- Schultz, Susan K.
- Shim, Hyungsub
- Relkin, Norman
- Ravdin, Lisa
- Smith, Amanda
- Venue
- Scientific Reports
- Published
- 2019-09-25
- Volume
- 9
- Issue
- 1
- Pages
- 13845-13845
- ISSN
- 2045-2322 (ISSN-L)
- PMC
- PMC6761169
- OpenAlex
- W2975235655
- Cited by
- 49
- References
- 106
- Citations by year
- 2026: 3 · 2025: 2 · 2024: 5 · 2023: 7 · 2022: 13 · 2021: 5 · 2020: 13 · 2019: 1
- FWCI
- 6.37
- Type
- journal article
- Language
- en
- Update notices
- correction (2020-06-30)
- Open access
- gold
- doi.org
- Locations
- Scientific Reports (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- eScholarship (California Digital Library) (submittedVersion, cc-by)
- HAL (submittedVersion, other-oa)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- UCL Discovery (University College London) (submittedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Scholarship@Western (Western University) (submittedVersion)
- RiuNet (Universitat Politècnica de València) (submittedVersion, cc-by-nc-nd)
- Funders
- Foundation for the National Institutes of Health (U01AG024904, Grant U01 AG024904, AG024904)
- Eli Lilly and Company (U01 AG024904, AG024904)
- Pfizer (AG024904, U01 AG024904)
- Biogen (U01 AG024904, AG024904)
- University of Southern California (U01 AG024904)
- F. Hoffmann-La Roche (AG024904, U01 AG024904)
- Alzheimer's Disease Neuroimaging Initiative (U01AG024904, AG024904)
- Novartis Pharmaceuticals Corporation (U01 AG024904, AG024904)
- Agence Nationale de la Recherche (ANR- 10-IDEX-03-02, 10‐IDEX‐03‐02, 10-LABX-57, ANR18, ANR-10-IDEX, ANR-10LABX-57, ANR-18-CE45-0013, ANR-10, IDEX-03-02, ANR-10-LABX, HL-MRI ANR-10-IDEX-03-02, HR-DTI ANR-10-LABX-57)
- Eisai (U01 AG024904, AG024904)
- Centre National de la Recherche Scientifique (ANR-10-IDEX-03-02)
- Servier (AG024904, U01 AG024904)
- IXICO (AG024904, U01 AG024904)
- National Institutes of Health (5u01ag024904-10, U01-AG024904, Grant U01 AG024904, AG024904)
- Genentech (AG024904, U01 AG024904)
- National Institute on Aging (U01-AG-024904, AG 024904)
- National Institute of Biomedical Imaging and Bioengineering (U01 AG024904, AG024904)
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Medical Image Segmentation Techniques
- Keywords
- Alzheimer's disease, hippocampal subfields, subiculum, multimodal MRI, diffusion MRI, mean diffusivity, structural MRI, biomarkers, Alzheimer's disease classification, early detection of Alzheimer's disease
- MeSH terms
- Aged, Aged, 80 and over, Alzheimer Disease, Female, Hippocampus, Humans, Male, Radiographic Image Interpretation, Computer-Assisted, Diffusion Magnetic Resonance Imaging, Diffusion Tensor Imaging, Multimodal Imaging
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