Purpose

To test and compare the repeatability and diagnostic accuracy of different academic and commercial brain volumetry solutions with different methodologies with and without DeepLearning (DL).

Materials & Methods

Brain volumetry measurements were carried out with the open-source software packages FreeSurfer (v6.0.0) and SPM (v12) and were compared against a commercially available software solution mdbrain (v4.4) based on DeepLearning algorithms. The MIRIAD study including 45 patients with confirmed Alzheimer’s disease and 23 healthy controls being followed over 2y served as data set. Furthermore, back-to-back scans (n=178) carried out on the same day were included. Images were acquired on a 1.5T MR-scanner using standard 3D-T1w images. Brain volumetry was performed for several regions incl. whole brain, grey & white matter, all lobes, hippocampus and all ventricles. All systems were compared in terms repeatability and performance. The performance was quantified using ROC-analysis by calculating the corresponding AUCs.

Results

For the repeatability tests, the DL-based mdbrain showed a significantly better stability as compared to FreeSurfer and SPM for all analyzed regions (e.g. mean deviations to reference for whole brain 0.06+/-0.09% vs. 0.43+/-0.87% vs 0.12+-0.06%). Performance analysis also yielded higher AUC values for mdbrain and SPM (mean value whole brain 0.96 & 0.95) vs. FreeSurfer (0.77).

Discussion

As compared to FreeSurfer & SPM mdbrain showed sign. better repeatability for all of the evaluated regions. This is reflected by the improved mean values and a lower overall error. Taking into account the shorter evaluation time of <5min for the DL-based product vs. ~10h for FreeSurfer and ~30min for SPM, mdbrain appears to be a valuable tool to enable the routine application of brain volumetry in clinical practice.

All authors are employees of the mediaire GmbH.