Manual Hippocampal Segmentation Research Articles

The EADC-ADNI harmonized protocol for hippocampal segmentation: A validation study

Recently, a group of major international experts have completed a comprehensive effort to efficiently define a harmonized protocol for manual hippocampal segmentation that is optimized for Alzheimer's research (known as the EADC-ADNI Harmonized Protocol (the HarP)). This study compares the HarP with one of the widely used hippocampal segmentation protocols (Pruessner, 2000), based on a single automatic segmentation method trained separately with libraries made from each manual segmentation protocol. The automatic segmentation conformity with the corresponding manual segmentation and the ability to capture Alzheimer's disease related hippocampal atrophy on large datasets are measured to compare the manual protocols. In addition to the possibility of harmonizing different procedures of hippocampal segmentation, our results show that using the HarP, the automatic segmentation conformity with manual segmentation is also preserved (Dice's κ=0.88,κ=0.87 for Pruessner and HarP respectively (p = 0.726 for common training library)). Furthermore, the results show that the HarP can capture the Alzheimer's disease related hippocampal volume differences in large datasets. The HarP-derived segmentation shows large effect size (Cohen's d = 1.5883) in separating Alzheimer's Disease patients versus normal controls (AD:NC) and medium effect size (Cohen's d = 0.5747) in separating stable versus progressive Mild Cognitively Impaired patients (sMCI:pMCI). Furthermore, the area under the ROC curve for a LDA classifier trained based on age, sex and HarP-derived hippocampal volume is 0.8858 for AD:NC, and for 0.6677 sMCI:pMCI. These results show that the harmonized protocol-derived labels can be widely used in clinic and research, as a sensitive and accurate way of delineating the hippocampus.

Reference standard space hippocampus labels according to the European Alzheimer's Disease Consortium–Alzheimer's Disease Neuroimaging Initiative harmonized protocol: Utility in automated volumetry

A 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. Manual 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. Individual 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%). The consensual HarP hippocampus labels in the MNI152 template can serve as a reference standard for automated image analyses involving MNI standard space normalization.

Quantitative Neuroimaging Software for Clinical Assessment of Hippocampal Volumes on MR Imaging.

Background:Multiple neurological disorders including Alzheimer’s disease (AD), mesial temporal sclerosis, and mild traumatic brain injury manifest with volume loss on brain MRI. Subtle volume loss is particularly seen early in AD. While prior research has demonstrated the value of this additional information from quantitative neuroimaging, very few applications have been approved for clinical use. Here we describe a US FDA cleared software program, NeuroreaderTM, for assessment of clinical hippocampal volume on brain MRI.Objective:To present the validation of hippocampal volumetrics on a clinical software program.Method:Subjects were drawn (n = 99) from the Alzheimer Disease Neuroimaging Initiative study. Volumetric brain MR imaging was acquired in both 1.5 T (n = 59) and 3.0 T (n = 40) scanners in participants with manual hippocampal segmentation. Fully automated hippocampal segmentation and measurement was done using a multiple atlas approach. The Dice Similarity Coefficient (DSC) measured the level of spatial overlap between NeuroreaderTM and gold standard manual segmentation from 0 to 1 with 0 denoting no overlap and 1 representing complete agreement. DSC comparisons between 1.5 T and 3.0 T scanners were done using standard independent samples T-tests.Results:In the bilateral hippocampus, mean DSC was 0.87 with a range of 0.78–0.91 (right hippocampus) and 0.76–0.91 (left hippocampus). Automated segmentation agreement with manual segmentation was essentially equivalent at 1.5 T (DSC = 0.879) versus 3.0 T (DSC = 0.872).Conclusion:This work provides a description and validation of a software program that can be applied in measuring hippocampal volume, a biomarker that is frequently abnormal in AD and other neurological disorders.

A quantitative comparison between two manual hippocampal segmentation protocols

A quantitative comparison between two manual hippocampal segmentation protocols

A quantitative comparison between two manual hippocampal segmentation protocols

A quantitative comparison between two manual hippocampal segmentation protocols

Training labels for hippocampal segmentation based on the EADC-ADNI harmonized hippocampal protocol

The 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. Sixty-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. Hippocampal volumes (mm(3)) 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 (mm(3)) 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. This 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.

Harmonized benchmark labels of the hippocampus on magnetic resonance: The EADC-ADNI project

A 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. Five 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. Two hundred labels have been provided for the 20 magnetic resonance images. Intra- and interrater ICCs were >0.94, and mean similarity coefficients were 1.5T, 0.73 (95% confidence interval [CI], 0.71-0.75); 3T, 0.75 (95% CI, 0.74-0.76). Certified benchmark labels have been produced based on the HarP to be used for tracers' training and qualification.

Delphi definition of the EADC-ADNI Harmonized Protocol for hippocampal segmentation on magnetic resonance

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. 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. 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. Consensus was achieved among international experts with respect to hippocampal segmentation using MR resulting in a harmonized segmentation protocol.

Automated versus manual hippocampal segmentation in preoperative and postoperative patients with epilepsy.

To compare manual and automated preoperative and postoperative hippocampal volume measurements in patients with intractable epilepsy. We studied 34 patients referred to the Clinical Epilepsy Section, National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH) for evaluation of intractable epilepsy and 21 normal volunteers who received 1.5 or 3 T GE Signa magnetic resonance imaging (MRI) scans. Hippocampal volumes were traced manually on each slice and assembled into three-dimensional volumes by investigators who were blinded to other data. Automated volumetric measurements were obtained using FreeSurfer. Statistical analysis was performed with GraphPad Prism. Automated hippocampal volumes were larger than manual volumes in both patients and normal volunteers (p < 0.05). Right to left hemisphere hippocampal ratio and percent of hippocampus resected did not differ significantly by segmentation method. It was not possible to obtain accurate total resection volumes with the automated method. Values such as side-to-side ratio and percent resected may be more directly translatable between manual and automated methods than absolute measures of volume. Accurate determination of resection volumes is important for studies of the effects of surgery on both seizure control and postoperative neuropsychological deficits. Our preliminary data suggest that FreeSurfer may provide an accurate and simple method for quantitating hippocampal resections. However, it may be less valuable for large or extratemporal resections, or when distortions of normal anatomy are present. A PowerPoint slide summarizing this article is available for download in the Supporting Information section here.

Automated hippocampal segmentation in patients with epilepsy: Available free online

PurposeHippocampal sclerosis, a common cause of refractory focal epilepsy, requires hippocampal volumetry for accurate diagnosis and surgical planning. Manual segmentation is time-consuming and subject to interrater/intrarater variability. Automated algorithms perform poorly in patients with temporal lobe epilepsy. We validate and make freely available online a novel automated method.MethodsManual hippocampal segmentation was performed on 876, 3T MRI scans and 202, 1.5T scans. A template database of 400 high-quality manual segmentations was used to perform automated segmentation of all scans with a multi-atlas–based segmentation propagation method adapted to perform label fusion based on local similarity to ensure accurate segmentation regardless of pathology. Agreement between manual and automated segmentations was assessed by degree of overlap (Dice coefficient) and comparison of hippocampal volumes.Key FindingsThe automated segmentation algorithm provided robust delineation of the hippocampi on 3T scans with no more variability than that seen between different human raters (Dice coefficients: interrater 0.832, manual vs. automated 0.847). In addition, the algorithm provided excellent results with the 1.5T scans (Dice coefficient 0.827), and automated segmentation remained accurate even in small sclerotic hippocampi. There was a strong correlation between manual and automated hippocampal volumes (Pearson correlation coefficient 0.929 on the left and 0.941 on the right in 3T scans).SignificanceWe demonstrate reliable identification of hippocampal atrophy in patients with hippocampal sclerosis, which is crucial for clinical management of epilepsy, particularly if surgical treatment is being contemplated. We provide a free online Web-based service to enable hippocampal volumetry to be available globally, with consequent greatly improved evaluation of those with epilepsy.

Hippocampal volume and memory and learning outcomes at 7 years in children born very preterm.

Using magnetic resonance imaging, this study compared hippocampal volume between 145 very preterm children and 34 children born full-term at 7 years of age. The relationship between hippocampal volume and memory and learning impairments at 7 years was also investigated. Manual hippocampal segmentation and subsequent three-dimensional volumetric analysis revealed reduced hippocampal volumes in very preterm children compared with term peers. However, this relationship did not remain after correcting for whole brain volume and neonatal brain abnormality. Contrary to expectations, hippocampal volume in the very preterm cohort was not related to memory and learning outcomes. Further research investigating the effects of very preterm birth on more extensive networks in the brain that support memory and learning in middle childhood is needed.

Training for manual hippocampal segmentation based on the EADC-ADNI harmonized protocol

Training for manual hippocampal segmentation based on the EADC-ADNI harmonized protocol

Validation of the EADC-ADNI Harmonized Protocol for Manual Hippocampal Segmentation: Preliminary Results

Validation of the EADC-ADNI Harmonized Protocol for Manual Hippocampal Segmentation: Preliminary Results

Training for manual hippocampal segmentation based on the EADC-ADNI harmonized protocol

Training for manual hippocampal segmentation based on the EADC-ADNI harmonized protocol

Automated and Manual Hippocampal Segmentation Techniques: A Comparison of Results and Reproducibility (P06.053)

Automated and Manual Hippocampal Segmentation Techniques: A Comparison of Results and Reproducibility (P06.053)

Comparison of Automated and Manual Hippocampal Segmentation (P03.101)

Comparison of Automated and Manual Hippocampal Segmentation (P03.101)

Delphi Consensus on Landmarks for the Manual Segmentation of the Hippocampus on MRI: Preliminary Results from the EADC-ADNI Harmonized Protocol Working Group (S04.003)

Objective: To define a harmonized protocol for manual hippocampal segmentation from magnetic resonance scans. Background Heterogeneity of landmarks among protocols leads to different volume estimates, hampering comparison of studies and clinical use. Landmark differences among the 12 most common protocols were extracted, operationalized, and quantitatively investigated. The results were presented to the Delphi panel, consisting of seventeen researchers with substantial expertise in hippocampal segmentation, to reach an evidence-based consensus on segmentation landmarks. Design/Methods: The Delphi panel participated in recursive anonymous voting sessions where feedback from previous rounds was utilized to progressively facilitate panelists9 agreement. Panelists were presented with tracing alternatives, each associated with quantitative data relating: (i) reliability, (ii) impact on whole hippocampal volume, and (iii) correlation with AD pathology. Panelists were asked to choose among alternatives and provide justification and comments. Anonymous votes and comments, and voting statistics of the first round were fed into the second Delphi round. Exact probability on binomial test of the choice was computed. At the time of writing, two Delphi rounds were completed. Results: Sixteen panelists completed both Delphi rounds. Agreement was significant on inclusion of alveus and fimbria (81%, p=0.021), of the whole visible hippocampal tail (75%, p=0.035), and approached significance for the segmentation of the medial border of the body following visible morphology (69%, p=0.057). Agreement on including the minimum hippocampus, alveus, morphological subiculum, whole hippocampal tail in the final hippocampal tracing protocol was significant (88%, p=0.001). Based on the previous quantitative investigation of landmark differences, the hippocampus so defined covers 100% of hippocampal tissue, captures 100% of AD-related atrophy, and has good intra-rater (0.99) and inter-rater (0.94) reliability measured on volume statistics. Conclusions: The most “inclusive” landmarks were preferred by Delphi panelists. Further rounds will be run to seek statistically significant agreement for all aspects. Supported by: Alzheimer9s Association. Lilly International. Wyeth International (Pfizer Group). Disclosure: Dr. Boccardi has nothing to disclose. Dr. Bocchetta has nothing to disclose. Dr. Apostolova has nothing to disclose. Dr. Barnes has nothing to disclose. Dr. Bartzokis has received personal compensation for activities with Bristol-Myers Squibb Company and Novartis. Dr. Bartzokis has received research support from Novartis and Janssen Pharmaceutica. Dr. Corbetta has nothing to disclose. Dr. DeCarli has received personal compensation for activities wtih Merck Pharmaceutical, Avanir, Bayer Pharmaceuticals, and Pfizer as a consultant.Dr. DeCarli has received personal compensation in an editorial capacity for Alzheimer9s Disease and Associated Disorders.Dr. DeCarli has received research support from Merck. Dr. DeToledo-Morrell has nothing to disclose. Dr. Firbank has nothing to disclose. Dr. Ganzola has nothing to disclose. Dr. Gerritsen has nothing to disclose. Dr. Henneman has nothing to disclose. Dr. Killiany has received personal compensation for activities with Sunovion Pharmaceuticals Inc as a consultant. Dr. Killiany has received research support from The MRI Centers of New England and a clinical affiliation with Essex Neurological Associates. Dr. Malykhin has nothing to disclose. Dr. Pasqualetti has nothing to disclose. Dr. Pruessner has nothing to disclose. Dr. Redolfi has nothing to disclose. Dr. Robitaille has nothing to disclose. Dr. Soininen has received personal compensation for activities with ACImmune. Dr. Tolomeo has nothing to disclose. Dr. Wang has nothing to disclose. Dr. Watson has nothing to disclose. Dr. Wolf has nothing to disclose. Dr. Duchesne has received (royalty or license fee or contractual rights) payments from Screen Inc.Dr. Duchesne has received research support from Afga Healthcare Inc. Dr. Jack has received personal compensation for activities with Janssen Pharmaceutica, Eisai Inc, General Electric, Johnson and Johnson, and Eli Lilly & Company as a consultant.Dr. Jack has received research support from Pfizer Inc, Allon, and Baxter, Inc. Dr. Frisoni has received personal compensation for activities Eli Lilly & Company, Bristol-Myers Squibb Company, Bayer Healthcare, Lundbeck Research USA, Inc., Elan Corporation, AstraZeneca Pharmaceuticals, Pfizer Inc, Baxter, Taurx, and Wyeth Pharmaceuticals. Dr. Frisoni has received personal compensation in an editorial capacity for Lancet Neurology, Aging Clinical & Experimental Research, Neurobiology of Aging, Alzheimer9s Diseases and Associated Disorders, and Neurogenerative Diseases. Dr. Frisoni has received research support from Wyeth Corporation, Eli Lilly & Company, Lundbeck Research USA, Inc.

Survey of protocols for the manual segmentation of the hippocampus: preparatory steps towards a joint EADC-ADNI harmonized protocol.

Manual segmentation from magnetic resonance imaging (MR) is the gold standard for evaluating hippocampal atrophy in Alzheimer's disease (AD). Nonetheless, different segmentation protocols provide up to 2.5-fold volume differences. Here we surveyed the most frequently used segmentation protocols in the AD literature as a preliminary step for international harmonization. The anatomical landmarks (anteriormost and posteriormost slices, superior, inferior, medial, and lateral borders) were identified from 12 published protocols for hippocampal manual segmentation ([Abbreviation] first author, publication year: [B] Bartzokis, 1998; [C] Convit, 1997; [dTM] deToledo-Morrell, 2004; [H] Haller, 1997; [J] Jack, 1994; [K] Killiany, 1993; [L] Lehericy, 1994; [M] Malykhin, 2007; [Pa] Pantel, 2000; [Pr] Pruessner, 2000; [S] Soininen, 1994; [W] Watson, 1992). The hippocampi of one healthy control and one AD patient taken from the 1.5T MR ADNI database were segmented by a single rater according to each protocol. The accuracy of the protocols' interpretation and translation into practice was checked with lead authors of protocols through individual interactive web conferences. Semantically harmonized landmarks and differences were then extracted, regarding: (a) the posteriormost slice, protocol [B] being the most restrictive, and [H, M, Pa, Pr, S] the most inclusive; (b) inclusion [C, dTM, J, L, M, Pr, W] or exclusion [B, H, K, Pa, S] of alveus/fimbria; (c) separation from the parahippocampal gyrus, [C] being the most restrictive, [B, dTM, H, J, Pa, S] the most inclusive. There were no substantial differences in the definition of the anteriormost slice. This survey will allow us to operationalize differences among protocols into tracing units, measure their impact on the repeatability and diagnostic accuracy of manual hippocampal segmentation, and finally develop a harmonized protocol.

No effect of 5HTTLPR or BDNF Val66Met polymorphism on hippocampal morphology in major depression

Neuroimaging research implicates the hippocampus in the aetiology of major depressive disorder (MDD). Imaging genetics studies have investigated the influence of the serotonin transporter-linked polymorphic region (5HTTLPR) and brain-derived neurotrophic factor (BDNF) Val66Met polymorphism on the hippocampus in healthy individuals and patients with depression (MDD). However, conflicting results have led to inconclusive evidence about the effect of 5HTTLPR or BDNF on hippocampal volume (HCV). We hypothesized that analysis methods based on three-dimensional (3D) hippocampal shape mapping could offer improved sensitivity to clarify these effects. Magnetic resonance imaging data were collected in parallel samples of 111 healthy individuals and 84 MDD patients. Manual hippocampal segmentation was conducted and the resulting data used to investigate the influence of 5HTTLPR and BDNF Val66Met genotypes on HCV and 3D shape within each sample. Hippocampal volume normalized by intracranial volume (ICV) showed no significant difference between 5HTTLPR S allele carriers and L/L homozygotes or between BDNF Met allele carriers and Val/Val homozygotes in the group of healthy individuals. Moreover, there was no significant difference in normalized HCV between 5HTTLPR diallelic and triallelic classifications or between the BDNF Val66Met genotypes in MDD patients, although there was a relationship between BDNF Val66Met and ICV. Shape analysis detected dispersed between-group differences, but these effects did not survive multiple testing correction. In this study, there was no evidence of a genetic effect for 5HTTLPR or BDNF Val66Met on hippocampal morphology in either healthy individuals or MDD patients despite the relatively large sample sizes and sensitive methodology.

Estimating the impact of differences among protocols for manual hippocampal segmentation on Alzheimer's disease-related atrophy: Preparatory phase for a harmonized protocol

Estimating the impact of differences among protocols for manual hippocampal segmentation on Alzheimer's disease-related atrophy: Preparatory phase for a harmonized protocol