5 research outputs found
Comparison of quality control methods for automated diffusion tensor imaging analysis pipelines
© 2019 Haddad et al. The processing of brain diffusion tensor imaging (DTI) data for large cohort studies requires fully automatic pipelines to perform quality control (QC) and artifact/outlier removal procedures on the raw DTI data prior to calculation of diffusion parameters. In this study, three automatic DTI processing pipelines, each complying with the general ENIGMA framework, were designed by uniquely combining multiple image processing software tools. Different QC procedures based on the RESTORE algorithm, the DTIPrep protocol, and a combination of both methods were compared using simulated ground truth and artifact containing DTI datasets modeling eddy current induced distortions, various levels of motion artifacts, and thermal noise. Variability was also examined in 20 DTI datasets acquired in subjects with vascular cognitive impairment (VCI) from the multi-site Ontario Neurodegenerative Disease Research Initiative (ONDRI). The mean fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) were calculated in global brain grey matter (GM) and white matter (WM) regions. For the simulated DTI datasets, the measure used to evaluate the performance of the pipelines was the normalized difference between the mean DTI metrics measured in GM and WM regions and the corresponding ground truth DTI value. The performance of the proposed pipelines was very similar, particularly in FA measurements. However, the pipeline based on the RESTORE algorithm was the most accurate when analyzing the artifact containing DTI datasets. The pipeline that combined the DTIPrep protocol and the RESTORE algorithm produced the lowest standard deviation in FA measurements in normal appearing WM across subjects. We concluded that this pipeline was the most robust and is preferred for automated analysis of multisite brain DTI data
Comparison of Diffusion Tensor Imaging Metrics in Normal-Appearing White Matter to Cerebrovascular Lesions and Correlation with Cerebrovascular Disease Risk Factors and Severity
Alterations in tissue microstructure in normal-appearing white matter (NAWM), specifically measured by diffusion tensor imaging (DTI) fractional anisotropy (FA), have been associated with cognitive outcomes following stroke. The purpose of this study was to comprehensively compare conventional DTI measures of tissue microstructure in NAWM to diverse vascular brain lesions in people with cerebrovascular disease (CVD) and to examine associations between FA in NAWM and cerebrovascular risk factors. DTI metrics including fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) were measured in cerebral tissues and cerebrovascular anomalies from 152 people with CVD participating in the Ontario Neurodegenerative Disease Research Initiative (ONDRI). Ten cerebral tissue types were segmented including NAWM, and vascular lesions including stroke, periventricular and deep white matter hyperintensities, periventricular and deep lacunar infarcts, and perivascular spaces (PVS) using T1-weighted, proton density-weighted, T2-weighted, and fluid attenuated inversion recovery MRI scans. Mean DTI metrics were measured in each tissue region using a previously developed DTI processing pipeline and compared between tissues using multivariate analysis of covariance. Associations between FA in NAWM and several CVD risk factors were also examined. DTI metrics in vascular lesions differed significantly from healthy tissue. Specifically, all tissue types had significantly different MD values, while FA was also found to be different in most tissue types. FA in NAWM was inversely related to hypertension and modified Rankin scale (mRS). This study demonstrated the differences between conventional DTI metrics, FA, MD, AD, and RD, in cerebral vascular lesions and healthy tissue types. Therefore, incorporating DTI to characterize the integrity of the tissue microstructure could help to define the extent and severity of various brain vascular anomalies. The association between FA within NAWM and clinical evaluation of hypertension and disability provides further evidence that white matter microstructural integrity is impacted by cerebrovascular function
Table_2_Retinal nerve fiber layer in frontotemporal lobar degeneration and amyotrophic lateral sclerosis.DOCX
PurposeTauopathy and transactive response DNA binding protein 43 (TDP-43) proteinopathy are associated with neurodegenerative diseases. These proteinopathies are difficult to detect in vivo. This study examined if spectral-domain optical coherence tomography (SD-OCT) can differentiate in vivo the difference in peripapillary retinal nerve fibre layer (pRNFL) thickness and macular retinal thickness between participants with presumed tauopathy (progressive supranuclear palsy) and those with presumed TDP-43 proteinopathy (amyotrophic lateral sclerosis and semantic variant primary progressive aphasia).Study designProspective, multi-centre, observational study.Materials and methodspRNFL and macular SD-OCT images were acquired in both eyes of each participant using Heidelberg Spectralis SD-OCT. Global and pRNFL thickness in 6 sectors were analyzed, as well as macular thickness in a central 1 mm diameter zone and 4 surrounding sectors. Linear mixed model methods adjusting for baseline differences between groups were used to compare the two groups with respect to pRNFL and macular thickness.ResultsA significant difference was found in mean pRNFL thickness between groups, with the TDP-43 group (n = 28 eyes) having a significantly thinner pRNFL in the temporal sector than the tauopathy group (n = 9 eyes; mean difference = 15.46 μm, SE = 6.98, p = 0.046), which was not significant after adjusting for multiple comparisons. No other significant differences were found between groups for pRNFL or macular thickness.ConclusionThe finding that the temporal pRNFL in the TDP-43 group was on average 15.46 μm thinner could potentially have clinical significance. Future work with larger sample sizes, longitudinal studies, and at the level of retinal sublayers will help to determine the utility of SD-OCT to differentiate between these two proteinopathies.</p
Table_1_Retinal nerve fiber layer in frontotemporal lobar degeneration and amyotrophic lateral sclerosis.DOCX
PurposeTauopathy and transactive response DNA binding protein 43 (TDP-43) proteinopathy are associated with neurodegenerative diseases. These proteinopathies are difficult to detect in vivo. This study examined if spectral-domain optical coherence tomography (SD-OCT) can differentiate in vivo the difference in peripapillary retinal nerve fibre layer (pRNFL) thickness and macular retinal thickness between participants with presumed tauopathy (progressive supranuclear palsy) and those with presumed TDP-43 proteinopathy (amyotrophic lateral sclerosis and semantic variant primary progressive aphasia).Study designProspective, multi-centre, observational study.Materials and methodspRNFL and macular SD-OCT images were acquired in both eyes of each participant using Heidelberg Spectralis SD-OCT. Global and pRNFL thickness in 6 sectors were analyzed, as well as macular thickness in a central 1 mm diameter zone and 4 surrounding sectors. Linear mixed model methods adjusting for baseline differences between groups were used to compare the two groups with respect to pRNFL and macular thickness.ResultsA significant difference was found in mean pRNFL thickness between groups, with the TDP-43 group (n = 28 eyes) having a significantly thinner pRNFL in the temporal sector than the tauopathy group (n = 9 eyes; mean difference = 15.46 μm, SE = 6.98, p = 0.046), which was not significant after adjusting for multiple comparisons. No other significant differences were found between groups for pRNFL or macular thickness.ConclusionThe finding that the temporal pRNFL in the TDP-43 group was on average 15.46 μm thinner could potentially have clinical significance. Future work with larger sample sizes, longitudinal studies, and at the level of retinal sublayers will help to determine the utility of SD-OCT to differentiate between these two proteinopathies.</p
White matter hyperintensities and smaller cortical thickness are associated with neuropsychiatric symptoms in neurodegenerative and cerebrovascular diseases
Abstract Background Neuropsychiatric symptoms (NPS) are a core feature of most neurodegenerative and cerebrovascular diseases. White matter hyperintensities and brain atrophy have been implicated in NPS. We aimed to investigate the relative contribution of white matter hyperintensities and cortical thickness to NPS in participants across neurodegenerative and cerebrovascular diseases. Methods Five hundred thirteen participants with one of these conditions, i.e. Alzheimer’s Disease/Mild Cognitive Impairment, Amyotrophic Lateral Sclerosis, Frontotemporal Dementia, Parkinson’s Disease, or Cerebrovascular Disease, were included in the study. NPS were assessed using the Neuropsychiatric Inventory – Questionnaire and grouped into hyperactivity, psychotic, affective, and apathy subsyndromes. White matter hyperintensities were quantified using a semi-automatic segmentation technique and FreeSurfer cortical thickness was used to measure regional grey matter loss. Results Although NPS were frequent across the five disease groups, participants with frontotemporal dementia had the highest frequency of hyperactivity, apathy, and affective subsyndromes compared to other groups, whilst psychotic subsyndrome was high in both frontotemporal dementia and Parkinson’s disease. Results from univariate and multivariate results showed that various predictors were associated with neuropsychiatric subsyndromes, especially cortical thickness in the inferior frontal, cingulate, and insula regions, sex(female), global cognition, and basal ganglia-thalamus white matter hyperintensities. Conclusions In participants with neurodegenerative and cerebrovascular diseases, our results suggest that smaller cortical thickness and white matter hyperintensity burden in several cortical-subcortical structures may contribute to the development of NPS. Further studies investigating the mechanisms that determine the progression of NPS in various neurodegenerative and cerebrovascular diseases are needed