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- Macfarlane, M. D., et al.
(författare)
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Shape abnormalities of the caudate nucleus correlate with poorer gait and balance: Results from a subset of the ladis study
- 2015
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Ingår i: The American journal of geriatric psychiatry. - : Elsevier BV. - 1064-7481. ; 23:1, s. 59-U90
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Tidskriftsartikel (refereegranskat)abstract
- Objective Functional deficits seen in several neurodegenerative disorders have been linked with dysfunction in frontostriatal circuits and with associated shape alterations in striatal structures. The severity of visible white matter hyperintensities (WMHs) on magnetic resonance imaging has been found to correlate with poorer performance on measures of gait and balance. This study aimed to determine whether striatal volume and shape changes were correlated with gait dysfunction. Methods Magnetic resonance imaging scans and clinical gait/balance data (scores from the Short Physical Performance Battery [SPPB]) were sourced from 66 subjects in the previously published LADIS trial, performed in nondisabled individuals older than age 65 years with WMHs at study entry. Data were obtained at study entry and at 3-year follow-up. Caudate nuclei and putamina were manually traced using a previously published method and volumes calculated. The relationships between volume and physical performance on the SPPB were investigated with shape analysis using the spherical harmonic shape description toolkit. Results There was no correlation between the severity of WMHs and striatal volumes. Caudate nuclei volume correlated with performance on the SPPB at baseline but not at follow-up, with subsequent shape analysis showing left caudate changes occurred in areas corresponding to inputs of the dorsolateral prefrontal, premotor, and motor cortex. There was no correlation between putamen volumes and performance on the SPPB. Conclusion Disruption in frontostriatal circuits may play a role in mediating poorer physical performance in individuals with WMHs. Striatal volume and shape changes may be suitable biomarkers for functional changes in this population. © 2015 American Association for Geriatric Psychiatry.
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| 2. |
- Schaap, M., et al.
(författare)
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Standardized evaluation methodology and reference database for evaluating coronary artery centerline extraction algorithms
- 2009
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Ingår i: Medical Image Analysis. - : Elsevier. - 1361-8415 .- 1361-8423. ; 13:5, s. 701-714
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Tidskriftsartikel (refereegranskat)abstract
- Efficiently obtaining a reliable coronary artery centerline from computed tomography angiography data is relevant in clinical practice. Whereas numerous methods have been presented for this purpose, up to now no standardized evaluation methodology has been published to reliably evaluate and compare the performance of the existing or newly developed coronary artery centerline extraction algorithms. This paper describes a standardized evaluation methodology and reference database for the quantitative evaluation of coronary artery centerline extraction algorithms. The contribution of this work is fourfold: (1) a method is described to create a consensus centerline with multiple observers, (2) well-defined measures are presented for the evaluation of coronary artery centerline extraction algorithms, (3) a database containing 32 cardiac CTA datasets with corresponding reference standard is described and made available, and (4) 13 coronary artery centerline extraction algorithms, implemented by different research groups, are quantitatively evaluated and compared. The presented evaluation framework is made available to the medical imaging community for benchmarking existing or newly developed coronary centerline extraction algorithms.
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| 5. |
- Commowick, Olivier, et al.
(författare)
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Objective Evaluation of Multiple Sclerosis Lesion Segmentation using a Data Management and Processing Infrastructure
- 2018
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Ingår i: Scientific Reports. - : Nature Publishing Group. - 2045-2322. ; 8
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Tidskriftsartikel (refereegranskat)abstract
- We present a study of multiple sclerosis segmentation algorithms conducted at the international MICCAI 2016 challenge. This challenge was operated using a new open-science computing infrastructure. This allowed for the automatic and independent evaluation of a large range of algorithms in a fair and completely automatic manner. This computing infrastructure was used to evaluate thirteen methods of MS lesions segmentation, exploring a broad range of state-of-theart algorithms, against a high-quality database of 53 MS cases coming from four centers following a common definition of the acquisition protocol. Each case was annotated manually by an unprecedented number of seven different experts. Results of the challenge highlighted that automatic algorithms, including the recent machine learning methods (random forests, deep learning,.), are still trailing human expertise on both detection and delineation criteria. In addition, we demonstrate that computing a statistically robust consensus of the algorithms performs closer to human expertise on one score (segmentation) although still trailing on detection scores.
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| 6. |
- Looi, Jeffrey C. L., et al.
(författare)
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The Australian, US, Scandinavian Imaging Exchange (AUSSIE): an innovative, virtually-integrated health research network embedded in health care
- 2014
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Ingår i: Australasian Psychiatry. - : SAGE Publications. - 1039-8562 .- 1440-1665. ; 22:3, s. 260-265
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Tidskriftsartikel (refereegranskat)abstract
- Objective: To describe the development, design and function of an innovative international clinical research network for neuroimaging research, based in Australia, within a joint state health service/medical school. This Australian, US, Scandinavian Imaging Exchange (AUSSIE) network focuses upon identifying neuroimaging biomarkers for neuropsychiatric and neurodegenerative disease. Methods: We describe a case study of the iterative development of the network, identifying characteristic features and methods which may serve as potential models for virtual clinical research networks. This network was established to analyse clinically-derived neuroimaging data relevant to neuropsychiatric and neurodegenerative disease, specifically in relation to subcortical brain structures. Results: The AUSSIE network has harnessed synergies from the individual expertise of the component groups, primarily clinical neuroscience researchers, to analyse a variety of clinical data. Conclusion: AUSSIE is an active virtual clinical research network, analogous to a connectome, which is embedded in health care and has produced significant research, advancing our understanding of neuropsychiatric and neurodegenerative disease through the lens of neuroimaging.
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