Duchesne, Simon

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.

AbstractBackgroundThe European Alzheimer's Disease Consortium and Alzheimer's Disease Neuroimaging Initiative (ADNI) Harmonized Protocol (HarP) is a Delphi definition of manual hippocampal segmentation from magnetic resonance imaging (MRI) that can be used as the standard of truth to train new tracers, and to validate automated segmentation algorithms. Training requires large and representative data sets of segmented hippocampi. This work aims to produce a set of HarP labels for the proper training and certification of tracers and algorithms.MethodsSixty‐eight 1.5 T and 67 3 T volumetric structural ADNI scans from different subjects, balanced by age, medial temporal atrophy, and scanner manufacturer, were segmented by five qualified HarP tracers whose absolute interrater intraclass correlation coefficients were 0.953 and 0.975 (left and right). Labels were validated as HarP compliant through centralized quality check and correction.ResultsHippocampal volumes (mm3) were as follows: controls: left = 3060 (standard deviation [SD], 502), right = 3120 (SD, 897); mild cognitive impairment (MCI): left = 2596 (SD, 447), right = 2686 (SD, 473); and Alzheimer’s disease (AD): left = 2301 (SD, 492), right = 2445 (SD, 525). Volumes significantly correlated with atrophy severity at Scheltens' scale (Spearman's ρ = <−0.468, P = <.0005).Cerebrospinal fluid spaces (mm3) were as follows: controls: left = 23 (32), right = 25 (25); MCI: left = 15 (13), right = 22 (16); and AD: left = 11 (13), right = 20 (25). Five subjects (3.7%) presented with unusual anatomy.ConclusionsThis work provides reference hippocampal labels for the training and certification of automated segmentation algorithms. The publicly released labels will allow the widespread implementation of the standard segmentation protocol.

Abstract Background An international Delphi panel has defined a harmonized protocol (HarP) for the manual segmentation of the hippocampus on MR. The aim of this study is to study the concurrent validity of the HarP toward local protocols, and its major sources of variance. Methods Fourteen tracers segmented 10 Alzheimer's Disease Neuroimaging Initiative (ADNI) cases scanned at 1.5 T and 3T following local protocols, qualified for segmentation based on the HarP through a standard web‐platform and resegmented following the HarP. The five most accurate tracers followed the HarP to segment 15 ADNI cases acquired at three time points on both 1.5 T and 3T. Results The agreement among tracers was relatively low with the local protocols (absolute left/right ICC 0.44/0.43) and much higher with the HarP (absolute left/right ICC 0.88/0.89). On the larger set of 15 cases, the HarP agreement within (left/right ICC range: 0.94/0.95 to 0.99/0.99) and among tracers (left/right ICC range: 0.89/0.90) was very high. The volume variance due to different tracers was 0.9% of the total, comparing favorably to variance due to scanner manufacturer (1.2), atrophy rates (3.5), hemispheric asymmetry (3.7), field strength (4.4), and significantly smaller than the variance due to atrophy (33.5%, P < .001), and physiological variability (49.2%, P < .001). Conclusions The HarP has high measurement stability compared with local segmentation protocols, and good reproducibility within and among human tracers. Hippocampi segmented with the HarP can be used as a reference for the qualification of human tracers and automated segmentation algorithms.

AbstractBackgroundA globally harmonized protocol (HarP) for manual hippocampal segmentation based on magnetic resonance has been recently developed by a task force from European Alzheimer's Disease Consortium (EADC) and Alzheimer's Disease Neuroimaging Initiative (ADNI). Our aim was to produce benchmark labels based on the HarP for manual segmentation.MethodsFive experts of manual hippocampal segmentation underwent specific training on the HarP and segmented 40 right and left hippocampi from 10 ADNI subjects on both 1.5 T and 3 T scans. An independent expert visually checked segmentations for compliance with the HarP. Descriptive measures of agreement between tracers were intraclass correlation coefficients (ICCs) of crude volumes and similarity coefficients of three‐dimensional volumes.ResultsTwo hundred labels have been provided for the 20 magnetic resonance images. Intra‐ and interrater ICCs were >0.94, and mean similarity coefficients were 1.5 T, 0.73 (95% confidence interval [CI], 0.71–0.75); 3 T, 0.75 (95% CI, 0.74–0.76).ConclusionCertified benchmark labels have been produced based on the HarP to be used for tracers' training and qualification.

Abstract Background This study aimed to have international experts converge on a harmonized definition of whole hippocampus boundaries and segmentation procedures, to define standard operating procedures for magnetic resonance (MR)‐based manual hippocampal segmentation. Methods The panel received a questionnaire regarding whole hippocampus boundaries and segmentation procedures. Quantitative information was supplied to allow evidence‐based answers. A recursive and anonymous Delphi procedure was used to achieve convergence. Significance of agreement among panelists was assessed by exact probability on Fisher's and binomial tests. Results Agreement was significant on the inclusion of alveus/fimbria ( P = .021), whole hippocampal tail ( P = .013), medial border of the body according to visible morphology ( P = .0006), and on this combined set of features ( P = .001). This definition captures 100% of hippocampal tissue, 100% of Alzheimer’s disease‐related atrophy, and demonstrated good reliability on preliminary intrarater (0.98) and inter‐rater (0.94) estimates. Discussion Consensus was achieved among international experts with respect to hippocampal segmentation using MR resulting in a harmonized segmentation protocol.

ABSTRACTBACKGROUND AND PURPOSEAn effort to define and validate a Harmonized Protocol for standard hippocampal segmentation is being carried out. We wished to estimate the effect of magnetic resonance image (MRI) spatial orientation on manual hippocampal segmentations to define optimal standard orientation of MRIs for hippocampal volumetry.METHODSThree expert tracers segmented twice the hippocampi of 10 ADNI subjects on MRI slices oriented perpendicular to the anterior‐posterior commissure (AC‐PC) line and the long hippocampal axes plane, following internationally harmonized landmarks. We computed intra and interrater reliability figures for total volumes and similarity coefficients.RESULTSTotal volume reliability was similar for both orientations. Similarity coefficients were significantly higher for the AC‐PC orientation (exact P = 0.002).DISCUSSIONThese data show that AC‐PC orientation is slightly more reliable for manual segmentations, possibly due to better visualization of the cerebrospinal fluid spaces separating hippocampal head and amygdala. A Delphi panel of experts has used these data to decide on the optimal orientation for a Harmonized Protocol for hippocampal segmentation.