Evaluation of Reproducibility of Brain Volumetry between Commercial Software, Inbrain and Established Research Purpose Method, FreeSurfer
2
조회
0
다운로드
4
인용
0
참고문헌
키워드
초록
Background and Purpose We aimed to determine the intermethod reproducibility between the commercial software Inbrain (MIDAS IT) and the established research-purpose method FreeSurfer, as well as the effect of MRI resolution and the pathological condition of subjects on their intermethod reproducibility. Methods This study included 45 healthy volunteers and 85 patients with mild cognitive impairment (MCI). In 43 of the 85 patients with MCI, three-dimensional, T1-weighted MRI data were obtained at an in-plane resolution of 1.2 mm. The data of the remaining 42 patients with MCI and the healthy volunteers were obtained at an in-plane resolution of 1.0 mm. The within- subject coefficient of variation (CoV), intraclass correlation coefficient (ICC), and effect size were calculated, and means were compared using paired t-tests. The parameters obtained at 1.0-mm and 1.2-mm resolutions in patients with MCI were compared to evaluate the effect of the in-plane resolution on the intermethod reproducibility. The parameters obtained at a 1.0-mm in-plane resolution in patients with MCI and healthy volunteers were used to analyze the effect of subject condition on intermethod reproducibility. Results Overall the two methods showed excellent reproducibility across all regions of the brain (CoV=0.5–3.9, ICC=0.93 to >0.99). In the subgroup of healthy volunteers, the intermethod reliability was only good in some regions (frontal, temporal, cingulate, and insular). The intermethod reproducibility was better in the 1.0-mm group than the 1.2-mm group in all regions other than the nucleus accumbens. Conclusions Inbrain and FreeSurfer showed good-to-excellent intermethod reproducibility for volumetric measurements. Nevertheless, some noticeable differences were found based on subject condition, image resolution, and brain region.
Abstract
Background and Purpose We aimed to determine the intermethod reproducibility between the commercial software Inbrain (MIDAS IT) and the established research-purpose method FreeSurfer, as well as the effect of MRI resolution and the pathological condition of subjects on their intermethod reproducibility. Methods This study included 45 healthy volunteers and 85 patients with mild cognitive impairment (MCI). In 43 of the 85 patients with MCI, three-dimensional, T1-weighted MRI data were obtained at an in-plane resolution of 1.2 mm. The data of the remaining 42 patients with MCI and the healthy volunteers were obtained at an in-plane resolution of 1.0 mm. The within- subject coefficient of variation (CoV), intraclass correlation coefficient (ICC), and effect size were calculated, and means were compared using paired t-tests. The parameters obtained at 1.0-mm and 1.2-mm resolutions in patients with MCI were compared to evaluate the effect of the in-plane resolution on the intermethod reproducibility. The parameters obtained at a 1.0-mm in-plane resolution in patients with MCI and healthy volunteers were used to analyze the effect of subject condition on intermethod reproducibility. Results Overall the two methods showed excellent reproducibility across all regions of the brain (CoV=0.5–3.9, ICC=0.93 to >0.99). In the subgroup of healthy volunteers, the intermethod reliability was only good in some regions (frontal, temporal, cingulate, and insular). The intermethod reproducibility was better in the 1.0-mm group than the 1.2-mm group in all regions other than the nucleus accumbens. Conclusions Inbrain and FreeSurfer showed good-to-excellent intermethod reproducibility for volumetric measurements. Nevertheless, some noticeable differences were found based on subject condition, image resolution, and brain region.
참고문헌 (39)
- Marciniewicz E, "The role of MR volumetry in brain atrophy assessment in multiple sclerosis : a review of the literature", Adv Clin Exp Med, 28, pp.989~999 (2019)
- Galovic M, "Progressive cortical thinning in patients with focal epilepsy", JAMA Neurol, 76, pp.1230~1239 (2019)
- Bosco P, "The impact of automated hippocampal volumetry on diagnostic confidence in patients with suspected Alzheimer’s disease : a European Alzheimer’s Disease Consortium study", Alzheimers Dement, 13, pp.1013~1023 (2017)
- Giorgio A, "Clinical use of brain volumetry", J Magn Reson Imaging, 37, pp.1~14 (2013)
- Miskin N, "Diagnosis of normal-pressure hydrocephalus : use of traditional measures in the era of volumetric MR imaging", Radiology, 285, pp.197~205 (2017)
- Fischl B, "FreeSurfer", Neuroimage, 62, pp.774~781 (2012)
- Massat MB, "Artificial intelligence in radiology : hype or hope?", Appl Radiol, 47, pp.22~26 (2018)
- Ribbens A, "Assessment of brain atrophy in multiple sclerosis patients in clinical routine : a multi-center comparison study of radiological and quantitative reports(P4. 373)", Neurology, 88(16 Suppl), pp.P4~ (2017)
- Frisoni GB, "The EADC-ADNI harmonized protocol for manual hippocampal segmentation on magnetic resonance : evidence of validity", Alzheimers Dement, 11, pp.111~125 (2015)
- Kovacevic S, "High-throughput, fully automated volumetry for prediction of MMSE and CDR decline in mild cognitive impairment", Alzheimer Dis Assoc Disord, 23, pp.139~145 (2009)
- 김윤태, "Cohort Profile: Firefighter Research on the Enhancement of Safety and Health (FRESH), a Prospective Cohort Study on Korean Firefighters", Yonsei Medical Journal, 61(1), pp.103~109 (2020), 연세대학교의과대학[DOI]
- Jung NY, "Retinal microvasculature changes in amyloid-negative subcortical vascular cognitive impairment compared to amyloid-positive Alzheimer’s disease", J Neurol Sci, 396, pp.94~101 (2019)
- Lee JS, "Machine learning-based individual assessment of cortical atrophy pattern in Alzheimer’s disease spectrum : development of the classifier and longitudinal evaluation", Sci Rep, 8, pp.4161~ (2018)
- Zuo XN, "Harnessing reliability for neuroscience research", Nat Hum Behav, 3, pp.768~771 (2019)
- Petersen RC, "Current concepts in mild cognitive impairment", Arch Neurol, 58, pp.1985~1992 (2001)
- Cockrell JR, "Principles and practice of geriatric psychiatry", pp.140~141 (2002), John Wiley & Sons, Inc
- Morris JC, "Clinical Dementia Rating: a reliable and valid diagnostic and staging measure for dementia of the Alzheimer type", Int Psychogeriatr, 9(Suppl 1), pp.173~176 (1997)
- McKhann GM, "The diagnosis of dementia due to Alzheimer’s disease : recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease", Alzheimers Dement, 7, pp.263~269 (2011)
- Cho Y, "Individual subject classification for Alzheimer's disease based on incremental learning using a spatial frequency representation of cortical thickness data", Neuroimage, 59, pp.2217~2230 (2012)
- Lee Ji Young, "Clinically Available Software for Automatic Brain Volumetry: Comparisons of Volume Measurements and Validation of Intermethod Reliability", Korean Journal of Radiology, 22(3), pp.405~414 (2021), 대한영상의학회[DOI]
- 박지은, "Selection and Reporting of Statistical Methods to Assess Reliability of a Diagnostic Test: Conformity to Recommended Methods in a Peer-Reviewed Journal", Korean Journal of Radiology, 18(6), pp.888~897 (2017), 대한영상의학회[DOI]
- Sullivan DC, "Metrology standards for quantitative imaging biomarkers", Radiology, 277, pp.813~825 (2015)
- Hernaez R, "Reliability and agreement studies : a guide for clinical investigators", Gut, 64, pp.1018~1027 (2015)
- de Vet HC, "When to use agreement versus reliability measures", J Clin Epidemiol, 59, pp.1033~1039 (2006)
- Portney LG, "Foundations of clinical research: applications to practice", pp.2009, Pearson
- Cohen J, "Statistical power analysis for the social sciences" (1988), Lawrence Erlbaum Associates
- Ross DE, "High correlations between MRI brain volume measurements based on NeuroQuant® and FreeSurfer", Psychiatry Res Neuroimaging, 278, pp.69~76 (2018)
- Ochs AL, "Comparison of automated brain volume measures obtained with NeuroQuant and FreeSurfer", J Neuroimaging, 25, pp.721~727 (2015)
- Guo C, "Repeatability and reproducibility of FreeSurfer, FSL-SIENAX and SPM brain volumetric measurements and the effect of lesion filling in multiple sclerosis", Eur Radiol, 29, pp.1355~1364 (2019)
- Velasco-Annis C, "Reproducibility of brain MRI segmentation algorithms : empirical comparison of local MAP PSTAPLE, FreeSurfer, and FSL-FIRST", J Neuroimaging, 28, pp.162~172 (2018)
- Ross DE, "NeuroQuant® and Neu-roGage® reveal effects of traumatic brain injury on brain volume", Brain Inj, 32, pp.1437~1441 (2018)
- Storelli L, "Measurement of whole-brain and gray matter atrophy in multiple sclerosis : assessment with MR imaging", Radiology, 288, pp.554~564 (2018)
- Chung J, "Comparison of vendor-provided volumetry software and NeuroQuant using 3D T1-weighted images in subjects with cognitive impairment : how large is the intermethod discrepancy?", Investig Magn Reson Imaging, 24, pp.76~84 (2020)
- Sluimer JD, "Whole-brain atrophy rate and cognitive decline : longitudinal MR study of memory clinic patients", Radiology, 248, pp.590~598 (2008)
- Leung KK, "Automated cross-sectional and longitudinal hippocampal volume measurement in mild cognitive impairment and Alzheimer’s disease", Neuroimage, 51, pp.1345~1359 (2010)
- Wieshmann UC, "Image contrast and hippocampal volumetric measurements", Magn Reson Imaging, 16, pp.13~17 (1998)
- Neto LL, "The human nucleus accumbens: where is it? A stereotactic, anatomical and magnetic resonance imaging study", Neuromodulation, 11, pp.13~22 (2008)
- Droby A, "A human post-mortem brain model for the standardization of multi-centre MRI studies", Neuroimage, 110, pp.11~21 (2015)
- Desikan RS, "An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest", Neuroimage, 31, pp.968~980 (2006)