Boccardi, Marina

AbstractIntroductionA harmonized protocol (HarP) for manual hippocampal segmentation on magnetic resonance imaging (MRI) has recently been developed by an international European Alzheimer's Disease Consortium–Alzheimer's Disease Neuroimaging Initiative project. We aimed at providing consensual certified HarP hippocampal labels in Montreal Neurological Institute (MNI) standard space to serve as reference in automated image analyses.MethodsManual HarP tracings on the high‐resolution MNI152 standard space template of four expert certified HarP tracers were combined to obtain consensual bilateral hippocampus labels. Utility and validity of these reference labels is demonstrated in a simple atlas‐based morphometry approach for automated calculation of HarP‐compliant hippocampal volumes within SPM software.ResultsIndividual tracings showed very high agreement among the four expert tracers (pairwise Jaccard indices 0.82–0.87). Automatically calculated hippocampal volumes were highly correlated (rL/R = 0.89/0.91) with gold standard volumes in the HarP benchmark data set (N = 135 MRIs), with a mean volume difference of 9% (standard deviation 7%).ConclusionThe consensual HarP hippocampus labels in the MNI152 template can serve as a reference standard for automated image analyses involving MNI standard space normalization.

AbstractBackgroundThe use of hippocampal volumetry as a biomarker for Alzheimer’s disease (AD) requires that tracers from different laboratories comply with the same segmentation method. Here we present a platform for training and qualifying new tracers to perform the manual segmentation of the hippocampus on magnetic resonance images (MRI) following the European Alzheimer's Disease Consortium and Alzheimer's Disease Neuroimaging Initiative (EADC‐ADNI) Harmonized Protocol (HarP). Our objective was to demonstrate that the training process embedded in the platform leads to increased compliance and qualification with the HarP.MethodThirteen new tracers' segmentations were compared with benchmark images with respect to: (a) absolute segmentation volume; (b) spatial overlap of contour with the reference using the Jaccard similarity index; and (c) spatial distance of contour with the reference. Point by point visual feedback was provided through three training phases on 10 MRI. Tracers were then tested on 10 different MRIs in the qualification phase.ResultsStatistical testing of training over three phases showed a significant increase of Jaccard (i.e. mean Jaccard overlap P < .001) between phases on average for all raters, demonstrating that training positively increased compliance with the HarP. Based on these results we defined qualification thresholds which all tracers were able to meet.ConclusionsThis platform is an adequate infrastructure allowing standardized training and evaluation of tracers' compliance with the HarP. This is a necessary step allowing the use of hippocampal volumetry as a biomarker for AD in clinical and research centers.