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This is enabled by leveraging high\u2010resolution quantitative blood oxygenation level dependent (qBOLD) analysis of magnitude images obtained from a multi\u2010echo gradient\u2010echo MRI (mGRE) scan performed on a 3.0 Tesla scanner.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>Achieving superior spatial resolution in qBOLD necessitates the utilization of an mGRE scan with only four echoes, which in turn limits the number of measurements compared to the parameters within the qBOLD model. Consequently, it becomes imperative to discard non\u2010essential parameters to facilitate further analysis. This process entails transforming the qBOLD model into a format suitable for fitting the log\u2010magnitude difference (L\u2010MDif) profiles of the four echo magnitudes present in each brain voxel. In order to bolster spatial specificity, the log\u2010difference qBOLD model undergoes refinement into a representative form, termed as r\u2010qBOLD, particularly when applied to class\u2010averaged L\u2010MDif signals derived through k\u2010means clustering of L\u2010MDif signals from all brain voxels into a predetermined number of clusters. The agreement between parameters estimated using r\u2010qBOLD for different cluster sizes is validated using Bland\u2013Altman analysis, and the model's goodness\u2010of\u2010fit is evaluated using a \u2010test. Retrospective MRI data of Alzheimer's disease (AD), mild cognitive impairment (MCI), and non\u2010demented patients without neuropathological disorders, pacemakers, other implants, or psychiatric disorders, who completed a minimum of three visits prior to MRI enrolment, are utilized for the study.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Utilizing a cohort comprising 30 demented patients aged 65\u201383 years in stages 4\u20136 representing mild, moderate, and severe stages according to the clinical dementia rating (CDR), matched with an age\u2010matched non\u2010demented control group of 18 individuals, we conducted joint observations of OEF and DoHb levels estimated using r\u2010qBOLD. The observations elucidate metabolic signatures in dementia based on OEF and DoHb levels in each voxel. Our principal findings highlight the significance of spatial patterns of metabolic profiles (metabolic patterns) within two distinct regimes: OEF levels exceeding the normal range (S1\u2010regime), and OEF levels below the normal range (S2\u2010regime). The S1\u2010regime, accompanied by low DoHb levels, predominantly manifests in fronto\u2010parietal and perivascular regions with increase in dementia severity. Conversely, the S2\u2010regime, accompanied by low DoHb levels, is observed in medial temporal (MTL) regions. Other regions with abnormal metabolic patterns included the orbitofrontal cortex (OFC), medial\u2010orbital prefrontal cortex (MOPFC), hypothalamus, ventro\u2010medial prefrontal cortex (VMPFC), and retrosplenial cortex (RSP). Dysfunction in the OFC and MOPFC indicated cognitive and emotional impairment, while hypothalamic involvement potentially indicated preclinical dementia. Reduced metabolic activity in the RSP suggested early\u2010stage AD related functional abnormalities.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>Integrated analysis of OEF and DoHb levels using r\u2010qBOLD reveals distinct metabolic signatures across dementia phases, highlighting regions susceptible to neuronal loss, vascular involvement, and preclinical indicators.<\/jats:p><\/jats:sec>","DOI":"10.1002\/mp.17173","type":"journal-article","created":{"date-parts":[[2024,6,18]],"date-time":"2024-06-18T07:34:52Z","timestamp":1718696092000},"page":"6002-6019","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Unveiling metabolic patterns in dementia: Insights from high\u2010resolution quantitative blood\u2010oxygenation\u2010level\u2010dependent MRI"],"prefix":"10.1002","volume":"51","author":[{"given":"Arun Raj","family":"T.","sequence":"first","affiliation":[{"name":"Division of Medical Informatics School of Informatics Kerala University of Digital Sciences Innovation &amp; Technology (DUK)  Trivandrum Kerala India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Karthik","family":"K.","sequence":"additional","affiliation":[{"name":"Department of Neuroimaging &amp; Interventional Radiology National Institute of Mental Health and Neuro\u2010Sciences (NIMHANS)  Bengaluru Karnataka India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Joseph Suresh","family":"Paul","sequence":"additional","affiliation":[{"name":"Division of Medical Informatics School of Informatics Kerala University of Digital Sciences Innovation &amp; Technology (DUK)  Trivandrum Kerala India"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2024,6,18]]},"reference":[{"key":"e_1_2_8_2_1","doi-asserted-by":"publisher","DOI":"10.1002\/trc2.12179"},{"key":"e_1_2_8_3_1","doi-asserted-by":"publisher","DOI":"10.1038\/nrdp.2015.56"},{"key":"e_1_2_8_4_1","doi-asserted-by":"publisher","DOI":"10.3233\/JAD-131868"},{"key":"e_1_2_8_5_1","doi-asserted-by":"publisher","DOI":"10.1212\/01.wnl.0000244749.20056.d4"},{"key":"e_1_2_8_6_1","doi-asserted-by":"publisher","DOI":"10.1177\/0271678X16658662"},{"key":"e_1_2_8_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/S1474-4422(02)00190-4"},{"key":"e_1_2_8_8_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2004.07.013"},{"key":"e_1_2_8_9_1","doi-asserted-by":"publisher","DOI":"10.1002\/jmri.27264"},{"key":"e_1_2_8_10_1","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.28410"},{"key":"e_1_2_8_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2020.117136"},{"key":"e_1_2_8_12_1","doi-asserted-by":"publisher","DOI":"10.1177\/0271678X20973951"},{"key":"e_1_2_8_13_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2023.120189"},{"key":"e_1_2_8_14_1","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.29272"},{"key":"e_1_2_8_15_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2011.12.017"},{"key":"e_1_2_8_16_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2012.07.065"},{"key":"e_1_2_8_17_1","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.21108"},{"key":"e_1_2_8_18_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2016.11.057"},{"key":"e_1_2_8_19_1","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.21627"},{"key":"e_1_2_8_20_1","doi-asserted-by":"publisher","DOI":"10.1097\/00004647-199912000-00001"},{"key":"e_1_2_8_21_1","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.25463"},{"key":"e_1_2_8_22_1","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.26253"},{"issue":"5","key":"e_1_2_8_23_1","first-page":"862","article-title":"Measurement of cerebral blood flow in chronic carotid occlusive disease: comparison of dynamic susceptibility contrast perfusion MR imaging with positron emission tomography","volume":"24","author":"Mukherjee P","year":"2003","journal-title":"Am J Neuroradiol"},{"key":"e_1_2_8_24_1","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.24918"},{"key":"e_1_2_8_25_1","doi-asserted-by":"publisher","DOI":"10.4329\/wjr.v5.i4.156"},{"key":"e_1_2_8_26_1","doi-asserted-by":"publisher","DOI":"10.3389\/fnins.2020.570848"},{"key":"e_1_2_8_27_1","doi-asserted-by":"publisher","DOI":"10.1101\/cshperspect.a006189"},{"key":"e_1_2_8_28_1","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.1910320610"},{"key":"e_1_2_8_29_1","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.27135"},{"key":"e_1_2_8_30_1","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.25358"},{"key":"e_1_2_8_31_1","first-page":"204","article-title":"Gradient echo plural contrast imaging (GEPCI)\u2010New fast magnetic resonance imaging technique for simultaneous acquisition of T2, T1 (or spin density) and T2*\u2010weighted images. 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