Development of quantitative and continuous measure for severity degree of Alzheimer’s disease evaluated from MRI images of 761 human brains
Abstract Background Alzheimer’s disease affects profoundly the quality of human behavior and cognition. The very broad distribution of its severity across various human subjects requires the quantitative diagnose of Alzheimer’s disease beyond the conventional tripartite classification of cohorts suc...
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| Format: | Article |
| Language: | English |
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BMC
2022-08-01
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| Series: | BMC Bioinformatics |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12859-022-04903-8 |
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| author | Sangyeol Kim Seongjun Park Iksoo Chang the Alzheimer’s Disease Neuroimaging Initiative |
| author_facet | Sangyeol Kim Seongjun Park Iksoo Chang the Alzheimer’s Disease Neuroimaging Initiative |
| author_sort | Sangyeol Kim |
| collection | DOAJ |
| description | Abstract Background Alzheimer’s disease affects profoundly the quality of human behavior and cognition. The very broad distribution of its severity across various human subjects requires the quantitative diagnose of Alzheimer’s disease beyond the conventional tripartite classification of cohorts such as cognitively normal (CN), mild cognitive impairment (MCI), Alzheimer’s disease (AD). The unfolding of such broad distributions by the quantitative and continuous degree of AD severity is necessary for the precise diagnose in the cross-sectional study of different stages in AD. Results We conducted the massive reanalysis on MRI images of 761 human brains based on the accumulated bigdata of Alzheimer’s Disease Neuroimaging Initiative. The score matrix of cortical thickness profile at cortex points of subjects was constructed by statistically learning the cortical thickness data of 761 human brains. We also developed a new and simple algebraic predictor which provides the quantitative and continuous degree of AD severity of subjects along the scale from 0 for fully CN to 1 for fully AD state. The mathematical measure of a new predictor for the degree of AD severity is presented based on a covariance correlation matrix of cortical thickness profile between human subjects. One can remove the uncertainty in the determination of different stages in AD by the quantitative degree of AD severity and thus go far beyond the tripartite classification of cohorts. Conclusions We unfold the nature of broad distribution of AD severity of subjects even within a given cohort by the scale from 0 for fully CN to 1 for fully AD state. The quantitative and continuous degree of AD severity developed in this study would be a good practical measure for diagnosing the different stages in AD severity. |
| first_indexed | 2024-04-11T20:12:58Z |
| format | Article |
| id | doaj.art-c5f8a59c7c334c498c2b7e64c316f4a2 |
| institution | Directory Open Access Journal |
| issn | 1471-2105 |
| language | English |
| last_indexed | 2024-04-11T20:12:58Z |
| publishDate | 2022-08-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Bioinformatics |
| spelling | doaj.art-c5f8a59c7c334c498c2b7e64c316f4a22022-12-22T04:05:03ZengBMCBMC Bioinformatics1471-21052022-08-0123111710.1186/s12859-022-04903-8Development of quantitative and continuous measure for severity degree of Alzheimer’s disease evaluated from MRI images of 761 human brainsSangyeol Kim0Seongjun Park1Iksoo Chang2the Alzheimer’s Disease Neuroimaging InitiativeDepartment of Brain Sciences, Daegu Gyeongbuk Institute of Science and TechnologyDepartment of Emerging Materials Science, Daegu Gyeongbuk Institute of Science and TechnologyDepartment of Brain Sciences, Daegu Gyeongbuk Institute of Science and TechnologyAbstract Background Alzheimer’s disease affects profoundly the quality of human behavior and cognition. The very broad distribution of its severity across various human subjects requires the quantitative diagnose of Alzheimer’s disease beyond the conventional tripartite classification of cohorts such as cognitively normal (CN), mild cognitive impairment (MCI), Alzheimer’s disease (AD). The unfolding of such broad distributions by the quantitative and continuous degree of AD severity is necessary for the precise diagnose in the cross-sectional study of different stages in AD. Results We conducted the massive reanalysis on MRI images of 761 human brains based on the accumulated bigdata of Alzheimer’s Disease Neuroimaging Initiative. The score matrix of cortical thickness profile at cortex points of subjects was constructed by statistically learning the cortical thickness data of 761 human brains. We also developed a new and simple algebraic predictor which provides the quantitative and continuous degree of AD severity of subjects along the scale from 0 for fully CN to 1 for fully AD state. The mathematical measure of a new predictor for the degree of AD severity is presented based on a covariance correlation matrix of cortical thickness profile between human subjects. One can remove the uncertainty in the determination of different stages in AD by the quantitative degree of AD severity and thus go far beyond the tripartite classification of cohorts. Conclusions We unfold the nature of broad distribution of AD severity of subjects even within a given cohort by the scale from 0 for fully CN to 1 for fully AD state. The quantitative and continuous degree of AD severity developed in this study would be a good practical measure for diagnosing the different stages in AD severity.https://doi.org/10.1186/s12859-022-04903-8Alzheimer’s diseaseMild cognitive impairmentMRICortical thicknessBigdata |
| spellingShingle | Sangyeol Kim Seongjun Park Iksoo Chang the Alzheimer’s Disease Neuroimaging Initiative Development of quantitative and continuous measure for severity degree of Alzheimer’s disease evaluated from MRI images of 761 human brains BMC Bioinformatics Alzheimer’s disease Mild cognitive impairment MRI Cortical thickness Bigdata |
| title | Development of quantitative and continuous measure for severity degree of Alzheimer’s disease evaluated from MRI images of 761 human brains |
| title_full | Development of quantitative and continuous measure for severity degree of Alzheimer’s disease evaluated from MRI images of 761 human brains |
| title_fullStr | Development of quantitative and continuous measure for severity degree of Alzheimer’s disease evaluated from MRI images of 761 human brains |
| title_full_unstemmed | Development of quantitative and continuous measure for severity degree of Alzheimer’s disease evaluated from MRI images of 761 human brains |
| title_short | Development of quantitative and continuous measure for severity degree of Alzheimer’s disease evaluated from MRI images of 761 human brains |
| title_sort | development of quantitative and continuous measure for severity degree of alzheimer s disease evaluated from mri images of 761 human brains |
| topic | Alzheimer’s disease Mild cognitive impairment MRI Cortical thickness Bigdata |
| url | https://doi.org/10.1186/s12859-022-04903-8 |
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