Revised diagnostic criteria for Alzheimer disease (AD) acknowledge a key role of imaging biomarkers for early diagnosis. Diagnostic accuracy depends on which marker (i.e., amyloid imaging, ¹⁸F-fluorodeoxyglucose [FDG]-PET, SPECT, MRI) as well as how it is measured ("metric": visual, manual, semiautomated, or automated segmentation/computation). We evaluated diagnostic accuracy of marker vs metric in separating AD from healthy and prognostic accuracy to predict progression in mild cognitive impairment. The outcome measure was positive (negative) likelihood ratio, LR+ (LR-), defined as the ratio between the probability of positive (negative) test outcome in patients and the probability of positive (negative) test outcome in healthy controls. Diagnostic LR+ of markers was between 4.4 and 9.4 and LR- between 0.25 and 0.08, whereas prognostic LR+ and LR- were between 1.7 and 7.5, and 0.50 and 0.11, respectively. Within metrics, LRs varied up to 100-fold: LR+ from approximately 1 to 100; LR- from approximately 1.00 to 0.01. Markers accounted for 11% and 18% of diagnostic and prognostic variance of LR+ and 16% and 24% of LR-. Across all markers, metrics accounted for an equal or larger amount of variance than markers: 13% and 62% of diagnostic and prognostic variance of LR+, and 29% and 18% of LR-. Within markers, the largest proportion of diagnostic LR+ and LR- variability was within ¹⁸F-FDG-PET and MRI metrics, respectively. Diagnostic and prognostic accuracy of imaging AD biomarkers is at least as dependent on how the biomarker is measured as on the biomarker itself. Standard operating procedures are key to biomarker use in the clinical routine and drug trials.

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.

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.