Comparison of Vendor-Provided Volumetry Software and NeuroQuant Using 3D T1-Weighted Images in Subjects with Cognitive Impairment: How Large is the Inter-Method Discrepancy?
2
조회
0
다운로드
2
인용
0
참고문헌
키워드
초록
Background: Determination of inter-method differences between clinically available volumetry methods are essential for the clinical application of brain volumetry in a wider context. Purpose: The purpose of this study was to examine the inter-method reliability and differences between the Siemens morphometry (SM) software and the NeuroQuant (NQ) software. Materials and Methods: MR images of 86 subjects with subjective or objective cognitive impairment were included in this retrospective study. For this study, 3D T1 volume images were obtained in all subjects using a 3T MR scanner (Skyra 3T, Siemens). Volumetric analysis of the 3D T1 volume images was performed using SM and NQ. To analyze the inter-method difference, correlation, and reliability, we used the paired t-test, Bland-Altman plot, Pearson’s correlation coefficient, intraclass correlation coefficient (ICC), and effect size (ES) using the MedCalc and SPSS software. Results: SM and NQ showed excellent reliability for cortical gray matter, cerebral white matter, and cerebrospinal fluid; and good reliability for intracranial volume, whole brain volume, both thalami, and both hippocampi. In contrast, poor reliability was observed for both basal ganglia including the caudate nucleus, putamen, and pallidum. Paired comparison revealed that while the mean volume of the right hippocampus was not different between the two software, the mean difference in the left hippocampus volume between the two methods was 0.17 ml (P < 0.001). The other brain regions showed significant differences in terms of measured volumes between the two software. Conclusion: SM and NQ provided good-to-excellent reliability in evaluating most brain structures, except for the basal ganglia in patients with cognitive impairment. Researchers and clinicians should be aware of the potential differences in the measured volumes when using these two different software interchangeably.
Abstract
Background: Determination of inter-method differences between clinically available volumetry methods are essential for the clinical application of brain volumetry in a wider context. Purpose: The purpose of this study was to examine the inter-method reliability and differences between the Siemens morphometry (SM) software and the NeuroQuant (NQ) software. Materials and Methods: MR images of 86 subjects with subjective or objective cognitive impairment were included in this retrospective study. For this study, 3D T1 volume images were obtained in all subjects using a 3T MR scanner (Skyra 3T, Siemens). Volumetric analysis of the 3D T1 volume images was performed using SM and NQ. To analyze the inter-method difference, correlation, and reliability, we used the paired t-test, Bland-Altman plot, Pearson’s correlation coefficient, intraclass correlation coefficient (ICC), and effect size (ES) using the MedCalc and SPSS software. Results: SM and NQ showed excellent reliability for cortical gray matter, cerebral white matter, and cerebrospinal fluid; and good reliability for intracranial volume, whole brain volume, both thalami, and both hippocampi. In contrast, poor reliability was observed for both basal ganglia including the caudate nucleus, putamen, and pallidum. Paired comparison revealed that while the mean volume of the right hippocampus was not different between the two software, the mean difference in the left hippocampus volume between the two methods was 0.17 ml (P < 0.001). The other brain regions showed significant differences in terms of measured volumes between the two software. Conclusion: SM and NQ provided good-to-excellent reliability in evaluating most brain structures, except for the basal ganglia in patients with cognitive impairment. Researchers and clinicians should be aware of the potential differences in the measured volumes when using these two different software interchangeably.
참고문헌 (32)
- 박미나, "Structural MR Imaging in the Diagnosis of Alzheimer’s Disease and Other Neurodegenerative Dementia: Current Imaging Approach and Future Perspectives", Korean Journal of Radiology, 17(6), pp.827~845 (2016), 대한영상의학회[DOI]
- Chetelat G, "Multimodal neuroimaging in Alzheimer's disease : early diagnosis, physiopathological mechanisms, and impact of lifestyle", J Alzheimers Dis, 64, pp.S199~S211 (2018)
- Groot C, "Differential effects of cognitive reserve and brain reserve on cognition in Alzheimer disease", Neurology, 90, pp.e149~e156 (2018)
- Min J, "Diagnostic efficacy of structural MRI in patients with mildto-moderate Alzheimer disease : automated volumetric assessment versus visual assessment", AJR Am J Roentgenol, 208, pp.617~623 (2017)
- Ross DE, "Man versus machine Part 2: Comparison of radiologists' interpretations and NeuroQuant measures of brain asymmetry and progressive atrophy in patients with traumatic brain injury", J Neuropsychiatry Clin Neurosci, 27, pp.147~152 (2015)
- Ross DE, "NeuroQuant®and NeuroGage® reveal effects of traumatic brain injury on brain volume", Brain Inj, 32, pp.1437~1441 (2018)
- Steenwijk MD, "Agreement of MSmetrix with established methods for measuring cross-sectional and longitudinal brain atrophy", Neuroimage Clin, 15, pp.843~853 (2017)
- 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)
- Tanpitukpongse TP, "Predictive utility of marketed volumetric software tools in subjects at risk for Alzheimer disease: do regions outside the hippocampus matter?", AJNR Am J Neuroradiol, 38, pp.546~552 (2017)
- Persson K, "Comparison of automated volumetry of the hippocampus using NeuroQuant® and visual assessment of the medial temporal lobe in Alzheimer's disease", Acta Radiol, 59, pp.997~1001 (2018)
- Niemantsverdriet E, "A Retrospective Belgian multi-center MRI biomarker study in Alzheimer's disease(REMEMBER)", J Alzheimers Dis, 63, pp.1509~1522 (2018)
- Ross DE, "High correlations between MRI brain volume measurements based on NeuroQuant®and FreeSurfer", Psychiatry Res Neuroimaging, 278, pp.69~76 (2018)
- Collins DL, "Towards accurate, automatic segmentation of the hippocampus and amygdala from MRI by augmenting ANIMAL with a template library and label fusion", Neuroimage, 52, pp.1355~1366 (2010)
- Petersen RC, "Mild cognitive impairment : clinical characterization and outcome", Arch Neurol, 56, pp.303~308 (1999)
- McKhann G, "Clinical diagnosis of Alzheimer's disease : report of the NINCDS-ADRDA Work Group under the auspices of Department of Health and Human Services Task Force on Alzheimer's Disease", Neurology, 34, pp.939~944 (1984)
- Roman GC, "Vascular dementia: diagnostic criteria for research studies. Report of the NINDS-AIREN International Workshop", Neurology, 43, pp.250~260 (1993)
- Ryu HJ, "Validation of the Korean version of the Lewy Body Composite Risk Score(K-LBCRS)", J Alzheimers Dis, 55, pp.1395~1401 (2017)
- Rascovsky K, "Sensitivity of revised diagnostic criteria for the behavioural variant of frontotemporal dementia", Brain, 134, pp.2456~2477 (2011)
- Poewe W, "Diagnosis and management of Parkinson's disease dementia", Int J Clin Pract, 62, pp.1581~1587 (2008)
- Koo TK, "A Guideline of selecting and reporting intraclass correlation coefficients for reliability research", J Chiropr Med, 15, pp.155~163 (2016)
- Olejnik S, "Measures of effect size for comparative studies: applications, interpretations, and limitations", Contemp Educ Psychol, 25, pp.241~286 (2000)
- Laubach M, "Size matters : grey matter brain reserve predicts executive functioning in the elderly", Neuropsychologia, 119, pp.172~181 (2018)
- Ochs AL, "Alzheimer's Disease Neuroimaging Initiative. Comparison of automated brain volume measures obtained with NeuroQuant® and FreeSurfer", J Neuroimaging, 25, pp.721~727 (2015)
- Reid MW, "Comparing two processing pipelines to measure subcortical and cortical volumes in patients with and without mild traumatic brain injury", J Neuroimaging, 27, pp.365~371 (2017)
- Jack CR Jr, "Prevalence of biologically vs clinically defined alzheimer spectrum entities using the national institute on aging-Alzheimer's association research framework", JAMA Neurol, 76, pp.1174~1183 (2019)
- Wang C, "Automated brain volumetrics in multiple sclerosis : a step closer to clinical application", J Neurol Neurosurg Psychiatry, 87, pp.754~757 (2016)
- Schmitter D, "An evaluation of volume-based morphometry for prediction of mild cognitive impairment and Alzheimer's disease", Neuroimage Clin, 7, pp.7~17 (2015)
- Roche A, "Assessing brain volumes using MorphoBox prototype", MAGNETOM Flash, 68, pp.33~37 (2017)
- Ogawa A, "Inferential reasoning by exclusion recruits parietal and prefrontal cortices", Neuroimage, 52, pp.1603~1610 (2010)
- Haller S, "Basic MR sequence parameters systematically bias automated brain volume estimation", Neuroradiology, 58, pp.1153~1160 (2016)
- Stelmokas J, "Translational MRI volumetry with NeuroQuant : effects of version and normative data on relationships with memory performance in healthy older adults and patients with mild cognitive impairment", J Alzheimers Dis, 60, pp.1499~1510 (2017)
- 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)
