Individual subject classification of mixed dementia from pure subcortical vascular dementia based on subcortical shape analysis.
Subcortical vascular dementia (SVaD), one of common causes of dementia, has concomitant Alzheimer's disease (AD) pathology in over 30%, termed "mixed dementia". Identifying mixed dementia from SVaD is important because potential amyloid-targeted therapies may be effective for treatmen...
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oai:doaj.org-article:b197b49a297f44d796b45631f1c4939a2021-11-18T08:51:40ZIndividual subject classification of mixed dementia from pure subcortical vascular dementia based on subcortical shape analysis.1932-620310.1371/journal.pone.0075602https://doaj.org/article/b197b49a297f44d796b45631f1c4939a2013-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/24130724/pdf/?tool=EBIhttps://doaj.org/toc/1932-6203Subcortical vascular dementia (SVaD), one of common causes of dementia, has concomitant Alzheimer's disease (AD) pathology in over 30%, termed "mixed dementia". Identifying mixed dementia from SVaD is important because potential amyloid-targeted therapies may be effective for treatment in mixed dementia. The purpose of this study was to discriminate mixed dementia from pure SVaD using magnetic resonance imaging (MRI). We measured brain amyloid deposition using the 11C-Pittsburgh compound B positron emission tomography (PiB-PET) in 68 patients with SVaD. A PiB retention ratio greater than 1.5 was considered PiB(+). Hippocampal and amygdalar shape were used in the incremental learning method to discriminate mixed dementia from pure SVaD because these structures are known to be prominently involved by AD pathologies. Among 68 patients, 23 (33.8%) patients were positive for PiB binding. With use of hippocampal shape analysis alone, PiB(+) SVaD could be discriminated from PiB(-) SVaD with 77.9% accuracy (95.7% sensitivity and 68.9% specificity). With use of amygdalar shape, the discrimination accuracy was 75.0% (87.0% sensitivity and 68.9% specificity). When hippocampal and amygdalar shape were analyzed together, accuracy increased to 82.4% (95.7% sensitivity and 75.6% specificity). An incremental learning method using hippocampal and amygdalar shape distinguishes mixed dementia from pure SVaD. Furthermore, our results suggest that amyloid pathology and vascular pathology have different effects on the shape of the hippocampus and amygdala.Hee Jin KimJeonghun KimHanna ChoByoung Seok YeCindy W YoonYoung NohGeon Ha KimJae Hong LeeJae Seung KimYearn Seong ChoeKyung-Han LeeChang-Hun KimSang Won SeoMichael W WeinerDuk L NaJoon-Kyung SeongPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 8, Iss 10, p e75602 (2013) |
| institution |
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| collection |
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| language |
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| topic |
Medicine R Science Q |
| spellingShingle |
Medicine R Science Q Hee Jin Kim Jeonghun Kim Hanna Cho Byoung Seok Ye Cindy W Yoon Young Noh Geon Ha Kim Jae Hong Lee Jae Seung Kim Yearn Seong Choe Kyung-Han Lee Chang-Hun Kim Sang Won Seo Michael W Weiner Duk L Na Joon-Kyung Seong Individual subject classification of mixed dementia from pure subcortical vascular dementia based on subcortical shape analysis. |
| description |
Subcortical vascular dementia (SVaD), one of common causes of dementia, has concomitant Alzheimer's disease (AD) pathology in over 30%, termed "mixed dementia". Identifying mixed dementia from SVaD is important because potential amyloid-targeted therapies may be effective for treatment in mixed dementia. The purpose of this study was to discriminate mixed dementia from pure SVaD using magnetic resonance imaging (MRI). We measured brain amyloid deposition using the 11C-Pittsburgh compound B positron emission tomography (PiB-PET) in 68 patients with SVaD. A PiB retention ratio greater than 1.5 was considered PiB(+). Hippocampal and amygdalar shape were used in the incremental learning method to discriminate mixed dementia from pure SVaD because these structures are known to be prominently involved by AD pathologies. Among 68 patients, 23 (33.8%) patients were positive for PiB binding. With use of hippocampal shape analysis alone, PiB(+) SVaD could be discriminated from PiB(-) SVaD with 77.9% accuracy (95.7% sensitivity and 68.9% specificity). With use of amygdalar shape, the discrimination accuracy was 75.0% (87.0% sensitivity and 68.9% specificity). When hippocampal and amygdalar shape were analyzed together, accuracy increased to 82.4% (95.7% sensitivity and 75.6% specificity). An incremental learning method using hippocampal and amygdalar shape distinguishes mixed dementia from pure SVaD. Furthermore, our results suggest that amyloid pathology and vascular pathology have different effects on the shape of the hippocampus and amygdala. |
| format |
article |
| author |
Hee Jin Kim Jeonghun Kim Hanna Cho Byoung Seok Ye Cindy W Yoon Young Noh Geon Ha Kim Jae Hong Lee Jae Seung Kim Yearn Seong Choe Kyung-Han Lee Chang-Hun Kim Sang Won Seo Michael W Weiner Duk L Na Joon-Kyung Seong |
| author_facet |
Hee Jin Kim Jeonghun Kim Hanna Cho Byoung Seok Ye Cindy W Yoon Young Noh Geon Ha Kim Jae Hong Lee Jae Seung Kim Yearn Seong Choe Kyung-Han Lee Chang-Hun Kim Sang Won Seo Michael W Weiner Duk L Na Joon-Kyung Seong |
| author_sort |
Hee Jin Kim |
| title |
Individual subject classification of mixed dementia from pure subcortical vascular dementia based on subcortical shape analysis. |
| title_short |
Individual subject classification of mixed dementia from pure subcortical vascular dementia based on subcortical shape analysis. |
| title_full |
Individual subject classification of mixed dementia from pure subcortical vascular dementia based on subcortical shape analysis. |
| title_fullStr |
Individual subject classification of mixed dementia from pure subcortical vascular dementia based on subcortical shape analysis. |
| title_full_unstemmed |
Individual subject classification of mixed dementia from pure subcortical vascular dementia based on subcortical shape analysis. |
| title_sort |
individual subject classification of mixed dementia from pure subcortical vascular dementia based on subcortical shape analysis. |
| publisher |
Public Library of Science (PLoS) |
| publishDate |
2013 |
| url |
https://doaj.org/article/b197b49a297f44d796b45631f1c4939a |
| work_keys_str_mv |
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