Algebraic T2 estimation improves detection of right temporal lobe epilepsy by MR T2 relaxometry

Seizure related abnormalities may be detected with T2 relaxometry, which involves quantitative estimation of T2 values. Accounting for the partial-volume effect of cerebrospinal fluid (CSF) is important, especially for voxel-based relaxometry, VBR. With a mono-exponential decay model, this can be accomplished by including a baseline constant. An algebraic calculation, which accommodates this constant, offers improved T2 estimation speed over the commonly used non-linear fitting approach. Our objective was to compare the algebraic approach against three fitting approaches for the detection of seizure related abnormalities. We tested the performance of the four methods in the presence of noise using simulated data as well as real data acquired at 3 T with a Carr-Purcell-Meiboom-Gill sequence from 45 healthy subjects and 24 patients with confirmed right temporal lobe epilepsy. A quantitative analysis was performed on spatially normalized data by measuring T2 in various regions and with a whole brain tissue segmentation analysis. The detection rate of hippocampal T2 changes in patients was assessed by comparing the regional T2 measurements from each patient against the control data with a z-score threshold of 2.33. The algebraic method yielded high sensitivity for detection of hippocampal abnormalities in the epileptic patients in regional assessment and in follow-up single-subject VBR. This can be attributed to the relatively small variance across healthy subjects and improved precision in the presence of CSF and noise in simulation. In conclusion, the algebraic method is better than fitting based on faster calculation speed and better sensitivity for detecting seizure-related T2 changes.