BACKGROUND:
Frontotemporal dementia (FTD) is a neurodegenerative disease which causes grey matter atrophy within the frontal and/or temporal lobes of the brain. Using novel Wave-CAIPI technology, rapid MRI sequences could reduce costs and save time, being 70% faster than classical T1 scans. This project investigated rapid T1 MRI scans’ potential to dissociate presymptomatic and symptomatic participants with FTD from controls in comparison to classical scans.
METHODS:
Classical T1 (5 mins) and rapid T1 (1 min) scans were acquired on a SIEMENS Prisma scanner for 28 participants, including carriers of mutations causal of FTD (3 symptomatic carriers and 21 presymptomatic carriers) and 4 mutation-negative controls. Data was preprocessed using FreeSurfer with grey matter volumes and thickness extracted for the frontal and temporal lobes. For each brain region and metric, we correlated the volume and thickness values for rapid and classical scans across all participants. For each sequence, we performed receiver-operating characteristic (ROC) analyses assessing the sensitivity and specificity of frontal and temporal lobe volumes and thickness for distinguishing all carriers from controls, symptomatic carriers from controls and presymptomatic carriers from controls. We compared area under the curve (AUC) for each sequence using DeLong’s test.
RESULTS:
Temporal, frontal and frontotemporal brain volumes and thickness were highly correlated between rapid and classical T1 scans. R 2 values ranged from 0.82 to 0.94 for thickness and 0.92 to 0.98 for volumes, with temporal lobe volume showing the highest correlation and frontal lobe thickness the lowest. Though AUCs dissociating presymptomatic carriers from controls remained modest, these did not significantly differ between rapid and classical scans.
CONCLUSION:
Rapid T1 scans offer a compelling alternative, demonstrating comparability to classical even at the presymptomatic disease stage. By substantially reducing scan time and cost while preserving data quality and clinical relevance, this approach holds strong promise for broad application across research and clinical settings.