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Marina Boccardi

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5 papers

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YNICL Journal 2019 Journal Article

A comparison of automated segmentation and manual tracing in estimating hippocampal volume in ischemic stroke and healthy control participants

Mohamed Salah Khlif
Natalia Egorova
Emilio Werden
Alberto Redolfi
Marina Boccardi
Charles S. DeCarli
Evan Fletcher
Baljeet Singh

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.

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YNICL Journal 2019 Journal Article

Assessment of longitudinal hippocampal atrophy in the first year after ischemic stroke using automatic segmentation techniques

Mohamed Salah Khlif
Emilio Werden
Natalia Egorova
Marina Boccardi
Alberto Redolfi
Laura Bird
Amy Brodtmann

We assessed first-year hippocampal atrophy in stroke patients and healthy controls using manual and automated segmentations: AdaBoost, FIRST (fsl/v5.0.8), FreeSurfer/v5.3 and v6.0, and Subfields (in FreeSurfer/v6.0). We estimated hippocampal volumes in 39 healthy controls and 124 stroke participants at three months, and 38 controls and 113 stroke participants at one year. We used intra-class correlation, concordance, and reduced major axis regression to assess agreement between automated and 'Manual' estimations. A linear mixed-effect model was used to characterize hippocampal atrophy. Overall, hippocampal volumes were reduced by 3.9% in first-ever stroke and 9.2% in recurrent stroke at three months post-stroke, with comparable ipsi-and contra-lesional reductions in first-ever stroke. Mean atrophy rates between time points were 0.5% for controls and 1.0% for stroke patients (0.6% contra-lesionally, 1.4% ipsi-lesionally). Atrophy rates in left and right-hemisphere strokes were comparable. All methods revealed significant volume change in first-ever and ipsi-lesional stroke (p < 0.001). Hippocampal volume estimation was not impacted by hemisphere, study group, or scan time point, but rather, by the interaction between the automated segmentation method and hippocampal size. Compared to Manual, Subfields and FIRST recorded the lowest bias. FreeSurfer/v5.3 overestimated volumes the most for large hippocampi, while FIRST was the most accurate in estimating small volumes. AdaBoost performance was average. Our findings suggest that first-year ipsi-lesional hippocampal atrophy rate especially in first-ever stroke, is greater than atrophy rates in healthy controls and contra-lesional stroke. Subfields and FIRST can complementarily be effective in characterizing the hippocampal atrophy in healthy and stroke cohorts.

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YNICL Journal 2019 Journal Article

Medial temporal lobe atrophy and posterior atrophy scales normative values

Matteo Cotta Ramusino
Daniele Altomare
Ruggero Bacchin
Silvia Ingala
Claudio Bnà
Matteo Bonetti
Alfredo Costa
Frederik Barkhof

OBJECTIVES: The medial temporal lobe atrophy (MTA) and the posterior atrophy (PA) scales allow to assess the degree hippocampal and parietal atrophy from magnetic resonance imaging (MRI) scans. Despite reliable, easy and widespread employment, appropriate normative values are still missing. We aim to provide norms for the Italian population. METHODS: Two independent raters assigned the highest MTA and PA score between hemispheres, based on 3D T1-weighted MRI of 936 Italian Brain Normative Archive subjects (age: mean ± SD: 50.2 ± 14.7, range: 20-84; MMSE>26 or CDR = 0). The inter-rater agreement was assessed with the absolute intraclass correlation coefficient (aICC). We assessed the association between MTA and PA scores and sociodemographic features and APOE status, and normative data were established by age decade based on percentile distributions. RESULTS: Raters agreed in 90% of cases for MTA (aICC = 0.86; 95% CI = 0.69-0.98) and in 86% for PA (aICC = 0.82; 95% CI = 0.58-0.98). For both rating scales, score distribution was skewed, with MTA = 0 in 38% of the population and PA = 0 in 52%, while a score ≥ 2 was only observed in 12% for MTA and in 10% for PA. Median denoted overall hippocampal (MTA: median = 1, IQR = 0-1) and parietal (PA: median = 0, IQR = 0-1) integrity. The 90th percentile of the age-specific distributions increased from 1 (at age 20-59) for both scales, to 2 for PA over age 60, and up to 4 for MTA over age 80. Gender, education and APOE status did not significantly affect the percentile distributions in the whole sample, nor in the subset over age 60. CONCLUSIONS: Our normative data for the MTA and PA scales are consistent with previous studies and overcome their main limitations (in particular uneven representation of ages and missing percentile distributions), defining the age-specific norms to be considered for proper brain atrophy assessment.

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YNIMG Journal 2016 Journal Article

Integrating longitudinal information in hippocampal volume measurements for the early detection of Alzheimer's disease

Andrea Chincarini
Francesco Sensi
Luca Rei
Gianluca Gemme
Sandro Squarcia
Renata Longo
Francesco Brun
Sabina Tangaro

Background Structural MRI measures for monitoring Alzheimer's Disease (AD) progression are becoming instrumental in the clinical practice, and more so in the context of longitudinal studies. This investigation addresses the impact of four image analysis approaches on the longitudinal performance of the hippocampal volume. Methods We present a hippocampal segmentation algorithm and validate it on a gold-standard manual tracing database. We segmented 460 subjects from ADNI, each subject having been scanned twice at baseline, 12-month and 24month follow-up scan (1. 5T, T1 MRI). We used the bilateral hippocampal volume v and its variation, measured as the annualized volume change Λ= δv/year(mm 3/y). Four processing approaches with different complexity are compared to maximize the longitudinal information, and they are tested for cohort discrimination ability. Reference cohorts are Controls vs. Alzheimer's Disease (CTRL/AD) and CTRL vs. Mild Cognitive Impairment who subsequently progressed to AD dementia (CTRL/MCI-co). We discuss the conditions on v and the added value of Λ in discriminating subjects. Results The age-corrected bilateral annualized atrophy rate (%/year) were: −1. 6 (0. 6) for CTRL, −2. 2 (1. 0) for MCI-nc, −3. 2 (1. 2) for MCI-co and −4. 0 (1. 5) for AD. Combined (v, Λ) discrimination ability gave an Area under the ROC curve (auc)=0. 93 for CTRL vs AD and auc =0. 88 for CTRL vs MCI-co. Conclusions Longitudinal volume measurements can provide meaningful clinical insight and added value with respect to the baseline provided the analysis procedure embeds the longitudinal information.

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YNIMG Journal 2015 Journal Article

Quantitative comparison of 21 protocols for labeling hippocampal subfields and parahippocampal subregions in in vivo MRI: Towards a harmonized segmentation protocol

Paul A. Yushkevich
Robert S.C. Amaral
Jean C. Augustinack
Andrew R. Bender
Jeffrey D. Bernstein
Marina Boccardi
Martina Bocchetta
Alison C. Burggren

Objective An increasing number of human in vivo magnetic resonance imaging (MRI) studies have focused on examining the structure and function of the subfields of the hippocampal formation (the dentate gyrus, CA fields 1−3, and the subiculum) and subregions of the parahippocampal gyrus (entorhinal, perirhinal, and parahippocampal cortices). The ability to interpret the results of such studies and to relate them to each other would be improved if a common standard existed for labeling hippocampal subfields and parahippocampal subregions. Currently, research groups label different subsets of structures and use different rules, landmarks, and cues to define their anatomical extents. This paper characterizes, both qualitatively and quantitatively, the variability in the existing manual segmentation protocols for labeling hippocampal and parahippocampal substructures in MRI, with the goal of guiding subsequent work on developing a harmonized substructure segmentation protocol. Method MRI scans of a single healthy adult human subject were acquired both at 3T and 7T. Representatives from 21 research groups applied their respective manual segmentation protocols to the MRI modalities of their choice. The resulting set of 21 segmentations was analyzed in a common anatomical space to quantify similarity and identify areas of agreement. Results The differences between the 21 protocols include the region within which segmentation is performed, the set of anatomical labels used, and the extents of specific anatomical labels. The greatest overall disagreement among the protocols is at the CA1/subiculum boundary, and disagreement across all structures is greatest in the anterior portion of the hippocampal formation relative to the body and tail. Conclusions The combined examination of the 21 protocols in the same dataset suggests possible strategies towards developing a harmonized subfield segmentation protocol and facilitates comparison between published studies.

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