Dataset Information

A comparison of automated segmentation and manual tracing for quantifying hippocampal and amygdala volumes.

ABSTRACT: Large databases of high-resolution structural MR images are being assembled to quantitatively examine the relationships between brain anatomy, disease progression, treatment regimens, and genetic influences upon brain structure. Quantifying brain structures in such large databases cannot be practically accomplished by expert neuroanatomists using hand-tracing. Rather, this research will depend upon automated methods that reliably and accurately segment and quantify dozens of brain regions. At present, there is little guidance available to help clinical research groups in choosing such tools. Thus, our goal was to compare the performance of two popular and fully automated tools, FSL/FIRST and FreeSurfer, to expert hand tracing in the measurement of the hippocampus and amygdala. Volumes derived from each automated measurement were compared to hand tracing for percent volume overlap, percent volume difference, across-sample correlation, and 3-D group-level shape analysis. In addition, sample size estimates for conducting between-group studies were computed for a range of effect sizes. Compared to hand tracing, hippocampal measurements with FreeSurfer exhibited greater volume overlap, smaller volume difference, and higher correlation than FIRST, and sample size estimates with FreeSurfer were closer to hand tracing. Amygdala measurement with FreeSurfer was also more highly correlated to hand tracing than FIRST, but exhibited a greater volume difference than FIRST. Both techniques had comparable volume overlap and similar sample size estimates. Compared to hand tracing, a 3-D shape analysis of the hippocampus showed FreeSurfer was more accurate than FIRST, particularly in the head and tail. However, FIRST more accurately represented the amygdala shape than FreeSurfer, which inflated its anterior and posterior surfaces.

SUBMITTER: Morey RA

PROVIDER: S-EPMC2714773 | biostudies-literature | 2009 Apr

REPOSITORIES: biostudies-literature

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A comparison of automated segmentation and manual tracing for quantifying hippocampal and amygdala volumes.

Morey Rajendra A RA Petty Christopher M CM Xu Yuan Y Hayes Jasmeet Pannu JP Wagner H Ryan HR Lewis Darrell V DV LaBar Kevin S KS Styner Martin M McCarthy Gregory G

NeuroImage 20081230 3

Large databases of high-resolution structural MR images are being assembled to quantitatively examine the relationships between brain anatomy, disease progression, treatment regimens, and genetic influences upon brain structure. Quantifying brain structures in such large databases cannot be practically accomplished by expert neuroanatomists using hand-tracing. Rather, this research will depend upon automated methods that reliably and accurately segment and quantify dozens of brain regions. At pr ...[more]

PMID: 19162198

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Project description:Manual quantification of the hippocampal atrophy state and rate is time consuming and prone to poor reproducibility, even when performed by neuroanatomical experts. The automation of hippocampal segmentation has been investigated in normal aging, epilepsy, and in Alzheimer's disease. Our first goal was to compare manual and automated hippocampal segmentation in ischemic stroke and to, secondly, study the impact of stroke lesion presence on hippocampal volume estimation. We used eight automated methods to segment T1-weighted MR images from 105 ischemic stroke patients and 39 age-matched controls sampled from the Cognition And Neocortical Volume After Stroke (CANVAS) study. The methods were: AdaBoost, Atlas-based Hippocampal Segmentation (ABHS) from the IDeALab, Computational Anatomy Toolbox (CAT) using 3 atlas variants (Hammers, LPBA40 and Neuromorphometics), FIRST, FreeSurfer v5.3, and FreeSurfer v6.0-Subfields. A number of these methods were employed to re-segment the T1 images for the stroke group after the stroke lesions were masked (i.e., removed). The automated methods were assessed on eight measures: process yield (i.e. segmentation success rate), correlation (Pearson's R and Shrout's ICC), concordance (Lin's RC and Kandall's W), slope 'a' of best-fit line from correlation plots, percentage of outliers from Bland-Altman plots, and significance of control-stroke difference. We eliminated the redundant measures after analysing between-measure correlations using Spearman's rank correlation. We ranked the automated methods based on the sum of the remaining non-redundant measures where each measure ranged between 0 and 1. Subfields attained an overall score of 96.3%, followed by AdaBoost (95.0%) and FIRST (94.7%). CAT using the LPBA40 atlas inflated hippocampal volumes the most, while the Hammers atlas returned the smallest volumes overall. FIRST (p = 0.014), FreeSurfer v5.3 (p = 0.007), manual tracing (p = 0.049), and CAT using the Neuromorphometics atlas (p = 0.017) all showed a significantly reduced hippocampal volume mean for the stroke group compared to control at three months. Moreover, masking of the stroke lesions prior to segmentation resulted in hippocampal volumes which agreed less with manual tracing. These findings recommend an automated segmentation without lesion masking as a more reliable procedure for the estimation of hippocampal volume in ischemic stroke.

Project description:BackgroundInfants with congenital Zika syndrome (CZS) are known to exhibit characteristic brain abnormalities. However, the brain anatomy of Zika virus (ZIKV)-exposed infants, born to ZIKV-positive pregnant mothers, who have normal-appearing head characteristics at birth, has not been evaluated in detail. The aim of this prospective study is, therefore, to compare the cortical and subcortical brain structural volume measures of ZIKV-exposed normocephalic infants to age-matched healthy controls.Methods and findingsWe acquired T2-MRI of the whole brain of 18 ZIKV-exposed infants and 8 normal controls on a 3T MRI scanner. The MR images were auto-segmented into eight tissue types and anatomical regions including the white matter, cortical grey matter, deep nuclear grey matter, corticospinal fluid, amygdala, hippocampus, cerebellum, and brainstem. We determined the volumes of these regions and calculated the total intracranial volume (TICV) and head circumference (HC). We compared these measurements between the two groups, controlling for infant age at scan, by first comparing results for all subjects in each group and secondly performing a subgroup analysis for subjects below 8 weeks of postnatal age at scan. ZIKV-exposed infants demonstrated a significant decrease in amygdala volume compared to the control group in both the group and subgroup comparisons (p<0.05, corrected for multiple comparisons using FDR). No significant volume differences were observed in TICV, HC, or any specific brain tissue structures or regions. Study limitations include small sample size, which was due to abrupt cessation of extramural funding as the ZIKV epidemic waned.ConclusionZIKV-exposed infants exhibited smaller volumes in the amygdala, a brain region primarily involved in emotional and behavioral processing. This brain MRI finding may lead to poorer behavioral outcomes and warrants long-term monitoring of pediatric cases of infants with gestational exposure to Zika virus as well as other neurotropic viruses.

Project description:PurposePrecise and reproducible hippocampus outlining is important to quantify hippocampal atrophy caused by neurodegenerative diseases and to spare the hippocampus in whole brain radiation therapy when performing prophylactic cranial irradiation or treating brain metastases. This study aimed to quantify systematic differences between methods by comparing regional volume and outline reproducibility of manual, FSL-FIRST and FreeSurfer hippocampus segmentations.Materials and methodsThis study used a dataset from ADNI (Alzheimer's Disease Neuroimaging Initiative), including 20 healthy controls, 40 patients with mild cognitive impairment (MCI), and 20 patients with Alzheimer's disease (AD). For each subject back-to-back (BTB) T1-weighted 3D MPRAGE images were acquired at time-point baseline (BL) and 12 months later (M12). Hippocampi segmentations of all methods were converted into triangulated meshes, regional volumes were extracted and regional Jaccard indices were computed between the hippocampi meshes of paired BTB scans to evaluate reproducibility. Regional volumes and Jaccard indices were modelled as a function of group (G), method (M), hemisphere (H), time-point (T), region (R) and interactions.ResultsFor the volume data the model selection procedure yielded the following significant main effects G, M, H, T and R and interaction effects G-R and M-R. The same model was found for the BTB scans. For all methods volumes reduces with the severity of disease. Significant fixed effects for the regional Jaccard index data were M, R and the interaction M-R. For all methods the middle region was most reproducible, independent of diagnostic group. FSL-FIRST was most and FreeSurfer least reproducible.Discussion/conclusionA novel method to perform detailed analysis of subtle differences in hippocampus segmentation is proposed. The method showed that hippocampal segmentation reproducibility was best for FSL-FIRST and worst for Freesurfer. We also found systematic regional differences in hippocampal segmentation between different methods reinforcing the need of adopting harmonized protocols.

Dataset Information

A comparison of automated segmentation and manual tracing for quantifying hippocampal and amygdala volumes.

Publications

A comparison of automated segmentation and manual tracing for quantifying hippocampal and amygdala volumes.

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