{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,31]],"date-time":"2026-03-31T15:15:24Z","timestamp":1774970124979,"version":"3.50.1"},"reference-count":26,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2026,3,31]],"date-time":"2026-03-31T00:00:00Z","timestamp":1774915200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Riset Kolaborasi Indonesia (RKI) or Indonesian Research Collaboration Program"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Diagnostics"],"abstract":"<jats:p>Background\/Objectives: Alzheimer\u2019s disease (AD) is a leading cause of dementia globally, yet standard diagnostic markers like cerebrospinal fluid (CSF) analysis and molecular imaging are invasive and resource-intensive. While artificial intelligence (AI)-based volumetric magnetic resonance imaging (MRI) offers a scalable and non-invasive alternative, data correlating these structural metrics with fluid biomarkers and cognitive status in Southeast Asian populations are scarce. This study addresses this critical gap by examining the within-cohort relationship between CSF biomarkers and regional brain volumes derived from AI-assisted MRI in Indonesian patients with clinically diagnosed AD, providing novel data for an underrepresented population. Methods: Twenty-one AD patients from three national referral hospitals in Indonesia underwent lumbar puncture for CSF biomarker analysis and 3 Tesla structural brain MRI. Brain volumes were analyzed using United Imaging Intelligence software, focusing on AD-relevant regions (hippocampus, entorhinal cortex, parahippocampus, precuneus, and posterior cingulate cortex [PCC]). Results: Spearman\u2019s correlation revealed significant positive associations between CSF A\u03b242 levels and several brain regions. Strong correlations were found with the right entorhinal volume indexed to intracranial volume (VICV) (r = 0.601, p = 0.004), right PCC VICV (r = 0.603, p = 0.004), right entorhinal volume (r = 0.533, p = 0.013), and right hippocampus VICV (r = 0.503, p = 0.020). Furthermore, MoCA-InA scores demonstrated highly significant positive correlations with CSF A\u03b242 concentrations (r = 0.720, p &lt; 0.001), right Hippocampus VICV (r = 0.703, p &lt; 0.001), and right PCC VICV (r = 0.695, p &lt; 0.001). No significant correlations were found between CSF pTau or the pTau\/A\u03b242 ratio and regional volumes. Conclusions: These results highlight the entorhinal cortex and PCC as early affected regions where CSF A\u03b242 correlates with preserved volume, supporting their role as structural markers in early AD. The absence of pTau associations may reflect early-stage pathology or limitations of cross-sectional volumetry. In resource-limited settings, AI-assisted volumetric MRI demonstrates potential utility as a non-invasive tool for stratifying amyloid-associated brain atrophy and staging disease severity.<\/jats:p>","DOI":"10.3390\/diagnostics16071050","type":"journal-article","created":{"date-parts":[[2026,3,31]],"date-time":"2026-03-31T13:23:17Z","timestamp":1774963397000},"page":"1050","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Artificial Intelligence-Assisted Volumetric Brain Analysis Correlated with CSF Biomarkers in Alzheimer\u2019s Disease: A Pilot Study"],"prefix":"10.3390","volume":"16","author":[{"given":"Pukovisa","family":"Prawiroharjo","sequence":"first","affiliation":[{"name":"Department of Neurology, Faculty of Medicine, Universitas Indonesia, Jakarta 10430, Indonesia"},{"name":"Department of Neurology, RSUPN Dr. Cipto Mangunkusumo, Jakarta 10320, Indonesia"},{"name":"Department of Neurology, Rumah Sakit Universitas Indonesia, Depok 16424, Indonesia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2741-2983","authenticated-orcid":false,"given":"Amelia Nur","family":"Vidyanti","sequence":"additional","affiliation":[{"name":"Department of Neurology, Faculty of Medicine, Public Health, and Nursing, Universitas Gadjah Mada, Yogyakarta 55281, Indonesia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuliarni","family":"Syafrita","sequence":"additional","affiliation":[{"name":"Department of Neurology, Faculty of Medicine, Universitas Andalas, West Sumatra 25127, Indonesia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9046-6303","authenticated-orcid":false,"given":"Reyhan Eddy","family":"Yunus","sequence":"additional","affiliation":[{"name":"Department of Radiology, Faculty of Medicine, Universitas Indonesia, Jakarta 10430, Indonesia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-6659-6600","authenticated-orcid":false,"given":"Aldithya","family":"Fakhri","sequence":"additional","affiliation":[{"name":"Faculty of Medicine, Universitas Indonesia, Jakarta 10430, Indonesia"},{"name":"Brainz Research and Innovation Center, Jakarta 12310, Indonesia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8710-1370","authenticated-orcid":false,"given":"Violine","family":"Martalia","sequence":"additional","affiliation":[{"name":"Faculty of Medicine, Universitas Indonesia, Jakarta 10430, Indonesia"},{"name":"Brainz Research and Innovation Center, Jakarta 12310, Indonesia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3346-7534","authenticated-orcid":false,"given":"Aileen","family":"Gabrielle","sequence":"additional","affiliation":[{"name":"Brainz Research and Innovation Center, Jakarta 12310, Indonesia"},{"name":"Faculty of Medicine, Universitas Hang Tuah, Surabaya 60241, Indonesia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sarah Alya","family":"Rahmayani","sequence":"additional","affiliation":[{"name":"Brainz Research and Innovation Center, Jakarta 12310, Indonesia"},{"name":"Faculty of Medicine, Universitas Sebelas Maret, Surakarta 57126, Indonesia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-7601-3872","authenticated-orcid":false,"given":"Gamael","family":"Marcel","sequence":"additional","affiliation":[{"name":"Department of Radiology, Faculty of Medicine, Universitas Indonesia, Jakarta 10430, Indonesia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Vidya Gani","family":"Wijaya","sequence":"additional","affiliation":[{"name":"Brainz Research and Innovation Center, Jakarta 12310, Indonesia"},{"name":"School of Medicine and Health Sciences, Atma Jaya Catholic University of Indonesia, Jakarta 14440, Indonesia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0453-3408","authenticated-orcid":false,"given":"Alya Ayu","family":"Tazkia","sequence":"additional","affiliation":[{"name":"Brainz Research and Innovation Center, Jakarta 12310, Indonesia"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2026,3,31]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"263","DOI":"10.1016\/j.jalz.2011.03.005","article-title":"The diagnosis of dementia due to Alzheimer\u2019s disease: Recommendations from the National Institute on Aging-Alzheimer\u2019s Association workgroups on diagnostic guidelines for Alzheimer\u2019s disease","volume":"7","author":"McKhann","year":"2011","journal-title":"Alzheimer\u2019s Dement."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"e76","DOI":"10.1192\/bjo.2023.76","article-title":"Comprehensive measurement of the prevalence of dementia in low- and middle-income countries: STRiDE methodology and its application in Indonesia and South Africa","volume":"9","author":"Farina","year":"2023","journal-title":"BJPsych Open"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"908915","DOI":"10.1155\/2014\/908915","article-title":"Global epidemiology of dementia: Alzheimer\u2019s and vascular types","volume":"2014","author":"Rizzi","year":"2014","journal-title":"Biomed. Res. Int."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"He, Z., Zhang, H., Hu, G., Qiao, Y., Yin, C., Li, J., Lin, H., Wu, A., Qin, D., and Law, B.Y.-K. (2025). The current status, trends, and challenges of Alzheimer\u2019s disease and other dementias in Asia (1990\u20132036). Front. Public Health, 13.","DOI":"10.3389\/fpubh.2025.1583339"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"020701","DOI":"10.7189\/jogh.10.020701","article-title":"Systematic review estimating the burden of dementia in the WHO Southeast Asia Region using Bayesian and frequentist approaches","volume":"10","author":"Poon","year":"2020","journal-title":"J. Glob. Health"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1016\/S0197-4580(03)00086-1","article-title":"Neurochemical diagnosis of Alzheimer\u2019s dementia by CSF A\u03b242, A\u03b242\/A\u03b240 ratio and total tau","volume":"25","author":"Lewczuk","year":"2004","journal-title":"Neurobiol. Aging"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"3035","DOI":"10.1093\/brain\/awl269","article-title":"CSF phosphorylated tau protein correlates with neocortical neurofibrillary pathology in Alzheimer\u2019s disease","volume":"129","author":"Buerger","year":"2006","journal-title":"Brain"},{"key":"ref_8","first-page":"e70037","article-title":"Artificial intelligence\u2013based rapid brain volumetry substantially improves differential diagnosis in dementia","volume":"16","author":"Rudolph","year":"2024","journal-title":"Alzheimer\u2019s Dement. Diagn. Assess. Dis. Monit."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"102","DOI":"10.1016\/j.zemedi.2018.11.002","article-title":"An overview of deep learning in medical imaging focusing on MRI","volume":"29","author":"Lundervold","year":"2019","journal-title":"Z. Med. Phys."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"584","DOI":"10.1002\/ird3.108","article-title":"An investigation into the applicability of rapid artificial intelligence-assisted compressed sensing in brain magnetic resonance imaging performed at 5 Tesla field strength","volume":"2","author":"Zhou","year":"2024","journal-title":"iRADIOLOGY"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"379","DOI":"10.2147\/IJGM.S499950","article-title":"AI-Assisted Compressed Sensing Enables Faster Brain MRI for the Elderly: Image Quality and Diagnostic Equivalence with Conventional Imaging","volume":"18","author":"Gu","year":"2025","journal-title":"Int. J. Gen. Med."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"487","DOI":"10.1007\/s00234-024-03280-8","article-title":"Towards validation in clinical routine: A comparative analysis of visual MTA ratings versus the automated ratio between inferior lateral ventricle and hippocampal volumes in Alzheimer\u2019s disease diagnosis","volume":"66","author":"Wittens","year":"2024","journal-title":"Neuroradiology"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"535","DOI":"10.1016\/j.jalz.2018.02.018","article-title":"NIA-AA Research Framework: Toward a biological definition of Alzheimer\u2019s disease","volume":"14","author":"Jack","year":"2018","journal-title":"Alzheimer\u2019s Dement."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"American Psychiatric Association (2013). Diagnostic and Statistical Manual of Mental Disorders, American Psychiatric Publishing. [5th ed.].","DOI":"10.1176\/appi.books.9780890425596"},{"key":"ref_15","unstructured":"Husein, N., Lumempouw, S., Ramli, Y. (2010). Montreal Cognitive Assessment versi Indonesia (MoCA-InA) untuk skrining gangguan fungsi kognitif. Neurona, 27."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Dorey, A., Perret-Liaudet, A., Tholance, Y., Fourier, A., and Quadrio, I. (2015). Cerebrospinal fluid A\u03b240 improves the interpretation of A\u03b242 concentration for diagnosing Alzheimer\u2019s disease. Front. Neurol., 6.","DOI":"10.3389\/fneur.2015.00247"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Libowitz, M., Wei, K., Tran, T., Chu, K., Moncrieffe, K., Harrington, M.G., and King, K. (2021). Regional brain volumes relate to Alzheimer\u2019s disease cerebrospinal fluid biomarkers and neuropsychometry: A cross-sectional, observational study. PLoS ONE, 16.","DOI":"10.1371\/journal.pone.0254332"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"70","DOI":"10.1016\/j.neurobiolaging.2024.01.014","article-title":"The spatial distribution of coupling between tau and neurodegeneration in amyloid-\u03b2 positive mild cognitive impairment","volume":"136","author":"Robinson","year":"2024","journal-title":"Neurobiol. Aging"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"202","DOI":"10.1016\/j.neurobiolaging.2015.12.009","article-title":"Age-related cortical thinning in cognitively healthy individuals in their 60s: The PATH Through Life study","volume":"39","author":"Shaw","year":"2016","journal-title":"Neurobiol. Aging"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Li, Q., Wang, J., Liu, J., Wang, Y., and Li, K. (2021). Magnetic Resonance Imaging Measurement of Entorhinal Cortex in the Diagnosis and Differential Diagnosis of Mild Cognitive Impairment and Alzheimer\u2019s Disease. Brain Sci., 11.","DOI":"10.21203\/rs.3.rs-502523\/v1"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"124","DOI":"10.1016\/j.tins.2022.11.006","article-title":"Entorhinal cortex dysfunction in Alzheimer\u2019s disease","volume":"46","author":"Igarashi","year":"2022","journal-title":"Trends Neurosci."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"632","DOI":"10.1001\/archneurol.2009.59","article-title":"Preclinical Evidence of Alzheimer Changes: Convergent Cerebrospinal Fluid Biomarker and Fluorodeoxyglucose Positron Emission Tomography Findings","volume":"66","author":"Petrie","year":"2009","journal-title":"Arch. Neurol."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"2750","DOI":"10.1002\/alz.13011","article-title":"Cortical tau is associated with microstructural imaging biomarkers of neurite density and dendritic complexity in Alzheimer\u2019s disease","volume":"19","author":"Weston","year":"2023","journal-title":"Alzheimer\u2019s Dement."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Li, C., Chen, T., Chiu, M., Yen, R.-F., Shih, M.-C., and Lin, C.-H. (2021). Integrated 18F-T807 Tau PET, Structural MRI, and Plasma Tau in Tauopathy Neurodegenerative Disorders. Front. Aging Neurosci., 13.","DOI":"10.3389\/fnagi.2021.646440"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"7686","DOI":"10.1007\/s00330-023-09742-6","article-title":"AI-assisted compressed sensing and parallel imaging sequences for MRI of patients with nasopharyngeal carcinoma: Comparison of their capabilities in terms of examination time and image quality","volume":"33","author":"Liu","year":"2023","journal-title":"Eur. Radiol."},{"key":"ref_26","first-page":"e12556","article-title":"Association of CSF biomarkers with MRI brain changes in Alzheimer\u2019s disease","volume":"16","author":"Seidu","year":"2024","journal-title":"Alzheimer\u2019s Dement."}],"container-title":["Diagnostics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2075-4418\/16\/7\/1050\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,31]],"date-time":"2026-03-31T13:43:06Z","timestamp":1774964586000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2075-4418\/16\/7\/1050"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,3,31]]},"references-count":26,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2026,4]]}},"alternative-id":["diagnostics16071050"],"URL":"https:\/\/doi.org\/10.3390\/diagnostics16071050","relation":{},"ISSN":["2075-4418"],"issn-type":[{"value":"2075-4418","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,3,31]]}}}