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• W4285386077 abstract "Abstract The multicontrast EPImix sequence generates six contrasts, including a T 1 -weighted scan, in ~1 min. EPImix shows comparable diagnostic performance to conventional scans under qualitative clinical evaluation, and similarities in simple quantitative measures including contrast intensity. However, EPImix scans have not yet been compared to standard MRI scans using established quantitative measures. In this study, we compared conventional and EPImix-derived T 1 -weighted scans of 64 healthy participants using tissue volume estimates and predicted brain-age. All scans were pre-processed using the SPM12 DARTEL pipeline, generating measures of grey matter, white matter and cerebrospinal fluid volume. Brain-age was predicted using brainageR , a Gaussian Processes Regression model previously trained on a large sample of standard T 1 -weighted scans. Estimates of both global and voxel-wise tissue volume showed significantly similar results between standard and EPImix-derived T 1 -weighted scans. Brain-age estimates from both sequences were significantly correlated, although EPImix T 1 -weighted scans showed a systematic offset in predictions of chronological age. Supplementary analyses suggest that this is likely caused by the reduced field of view of EPImix scans, and the use of a brain-age model trained using conventional T 1 -weighted scans. However, this systematic error can be corrected using additional regression of T 1 -predicted brain-age onto EPImix-predicted brain-age. Finally, retest EPImix scans acquired for 10 participants demonstrated high test-retest reliability in all evaluated quantitative measurements. Quantitative analysis of EPImix scans has potential to reduce scanning time, increasing participant comfort and reducing cost, as well as to support automation of scanning, utilising active learning for faster and individually-tailored (neuro)imaging." @default.
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• W4285386077 date "2022-07-14" @default.
• W4285386077 modified "2023-09-24" @default.
• W4285386077 title "Tissue volume estimation and age prediction using rapid structural brain scans" @default.
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• W4285386077 doi "https://doi.org/10.1038/s41598-022-14904-5" @default.
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