Literature DB >> 35782251

Practical methods for segmentation and calculation of brain volume and intracranial volume: a guide and comparison.

Thomas Harkey1, David Baker1, John Hagen1, Hayden Scott1, Viktoras Palys1.   

Abstract

Background: Accurate segmentation and calculation of total brain volume (BV) and intracranial volume (ICV) (further-volumetry) may serve various clinical tasks and research studies in neuroscience. Manual segmentation is extremely time consuming. There is a relative lack of published broad recommendations and comparisons of tools for automated volumetry, especially for users without expertise in computer science, for settings with limited resources, and when neuroimaging quality is suboptimal due to clinical circumstances. Our objective is to decrease the barrier to entry for research and clinical groups to perform volumetric cranial imaging analysis using free and reliable software tools.
Methods: Automated volumetry from computed tomography (CT)/magnetic resonance imaging (MRI) scans was accomplished using 3D Slicer (v. 4.11.0), FreeSurfer (v. 7.1.1), and volBrain (v. 1.0) in a cohort of 39 patients with ischemic middle cerebral artery territory brain infarcts in the acute stage. Visual inspection for accuracy was also performed. Statistical analysis included coefficient of determination (R2) and Bland-Altman (B-A) plots. A multifaceted comparison between 3D Slicer, FreeSurfer, and volBrain from practical user perspective was performed to compile a list of distinguishing features.
Results: BV: FreeSurfer, 3D Slicer, and volBrain provide similar estimations when high quality T1-MRI scans with 1 mm slices (3D scans) are available, whereas 3 mm and thicker slices (2D scans) introduce a dispersion in results. ICV: the most accurate volumetry is provided by 3D Slicer using CT scans. volBrain uses T1-MRIs and also provides good results which agree with 3D Slicer. Both of these methods may be more trustworthy than T1 MRI-derived FreeSurfer calculations. Conclusions: All three studied tools of automated intracranial and brain volumetry-3D Slicer, FreeSurfer, and volBrain-are free, reliable, require no complex programming, but still have certain limitations and significant differences. Based on our investigation findings, the readers should be able to select the right volumetry tool and neuroimaging study, and then follow provided step-by-step instructions to accomplish specific volumetry tasks. 2022 Quantitative Imaging in Medicine and Surgery. All rights reserved.

Entities:  

Keywords:  Brain volume (BV); computed tomography (CT); intracranial volume (ICV); magnetic resonance imaging (MRI); segmentation

Year:  2022        PMID: 35782251      PMCID: PMC9246750          DOI: 10.21037/qims-21-958

Source DB:  PubMed          Journal:  Quant Imaging Med Surg        ISSN: 2223-4306


  18 in total

1.  3D Slicer as an image computing platform for the Quantitative Imaging Network.

Authors:  Andriy Fedorov; Reinhard Beichel; Jayashree Kalpathy-Cramer; Julien Finet; Jean-Christophe Fillion-Robin; Sonia Pujol; Christian Bauer; Dominique Jennings; Fiona Fennessy; Milan Sonka; John Buatti; Stephen Aylward; James V Miller; Steve Pieper; Ron Kikinis
Journal:  Magn Reson Imaging       Date:  2012-07-06       Impact factor: 2.546

2.  Comparison of Automated Brain Volume Measures obtained with NeuroQuant and FreeSurfer.

Authors:  Alfred L Ochs; David E Ross; Megan D Zannoni; Tracy J Abildskov; Erin D Bigler
Journal:  J Neuroimaging       Date:  2015-02-26       Impact factor: 2.486

3.  Comparing Two Processing Pipelines to Measure Subcortical and Cortical Volumes in Patients with and without Mild Traumatic Brain Injury.

Authors:  Matthew W Reid; Nathan P Hannemann; Gerald E York; John L Ritter; Jonathan A Kini; Jeffrey D Lewis; Paul M Sherman; Carmen S Velez; Ann Marie Drennon; Jacob D Bolzenius; David F Tate
Journal:  J Neuroimaging       Date:  2017-02-14       Impact factor: 2.486

4.  Increasing the impact of medical image computing using community-based open-access hackathons: The NA-MIC and 3D Slicer experience.

Authors:  Tina Kapur; Steve Pieper; Andriy Fedorov; J-C Fillion-Robin; Michael Halle; Lauren O'Donnell; Andras Lasso; Tamas Ungi; Csaba Pinter; Julien Finet; Sonia Pujol; Jayender Jagadeesan; Junichi Tokuda; Isaiah Norton; Raul San Jose Estepar; David Gering; Hugo J W L Aerts; Marianna Jakab; Nobuhiko Hata; Luiz Ibanez; Daniel Blezek; Jim Miller; Stephen Aylward; W Eric L Grimson; Gabor Fichtinger; William M Wells; William E Lorensen; Will Schroeder; Ron Kikinis
Journal:  Med Image Anal       Date:  2016-07-07       Impact factor: 8.545

Review 5.  FreeSurfer.

Authors:  Bruce Fischl
Journal:  Neuroimage       Date:  2012-01-10       Impact factor: 6.556

6.  Within-subject template estimation for unbiased longitudinal image analysis.

Authors:  Martin Reuter; Nicholas J Schmansky; H Diana Rosas; Bruce Fischl
Journal:  Neuroimage       Date:  2012-03-10       Impact factor: 6.556

7.  Quantifying MRI geometric distortion in tissue.

Authors:  T Sumanaweera; G Glover; S Song; J Adler; S Napel
Journal:  Magn Reson Med       Date:  1994-01       Impact factor: 4.668

Review 8.  Decompressive craniectomy for malignant middle cerebral artery infarction: evidence and controversies.

Authors:  Reuben D Johnson; Nicholas F Maartens; Peter J Teddy
Journal:  J Clin Neurosci       Date:  2011-05-17       Impact factor: 1.961

9.  Surgical decompression for space-occupying cerebral infarction (the Hemicraniectomy After Middle Cerebral Artery infarction with Life-threatening Edema Trial [HAMLET]): a multicentre, open, randomised trial.

Authors:  Jeannette Hofmeijer; L Jaap Kappelle; Ale Algra; G Johan Amelink; Jan van Gijn; H Bart van der Worp
Journal:  Lancet Neurol       Date:  2009-03-05       Impact factor: 44.182

10.  Accurate automatic estimation of total intracranial volume: a nuisance variable with less nuisance.

Authors:  Ian B Malone; Kelvin K Leung; Shona Clegg; Josephine Barnes; Jennifer L Whitwell; John Ashburner; Nick C Fox; Gerard R Ridgway
Journal:  Neuroimage       Date:  2014-10-01       Impact factor: 6.556

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