A novel MRI‐compatible brain ventricle phantom for validation of segmentation and volumetry methods

Khan, Amanda Farah; Drozd, John; Moreland, Robert; Ta, Robert; Borrie, Michael; Bartha, Robert

doi:10.1002/jmri.23612

Cited by 11 publications

(12 citation statements)

References 22 publications

(24 reference statements)

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“…Firstly, a large voxel size can blur the boundary of an object due to partial volume effects, leading to a seeming boundary outward shift and thus volume overestimation. This is a well-known phenomenon that has been observed in previous QA studies [20, 21]. Here, stroke sequences “c” and “d” had the thickest slices and led to the two largest differences between measured and predicted volumes amongst centers, with “d” characterized by both the largest overall voxel size and largest difference.…”

Section: Discussionsupporting

confidence: 68%

Multicenter Evaluation of Geometric Accuracy of MRI Protocols Used in Experimental Stroke

et al. 2016

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It has recently been suggested that multicenter preclinical stroke studies should be carried out to improve translation from bench to bedside, but the accuracy of magnetic resonance imaging (MRI) scanners routinely used in experimental stroke has not yet been evaluated. We aimed to assess and compare geometric accuracy of preclinical scanners and examine the longitudinal stability of one scanner using a simple quality assurance (QA) protocol. Six 7 Tesla animal scanners across six different preclinical imaging centers throughout Europe were used to scan a small structural phantom and estimate linear scaling errors in all orthogonal directions and volumetric errors. Between-scanner imaging consisted of a standard sequence and each center’s preferred sequence for the assessment of infarct size in rat models of stroke. The standard sequence was also used to evaluate the drift in accuracy of the worst performing scanner over a period of six months following basic gradient calibration. Scaling and volumetric errors using the standard sequence were less variable than corresponding errors using different stroke sequences. The errors for one scanner, estimated using the standard sequence, were very high (above 4% scaling errors for each orthogonal direction, 18.73% volumetric error). Calibration of the gradient coils in this system reduced scaling errors to within ±1.0%; these remained stable during the subsequent 6-month assessment. In conclusion, despite decades of use in experimental studies, preclinical MRI still suffers from poor and variable geometric accuracy, influenced by the use of miscalibrated systems and various types of sequences for the same purpose. For effective pooling of data in multicenter studies, centers should adopt standardized procedures for system QA and in vivo imaging.

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Section: Discussionsupporting

confidence: 68%

Multicenter Evaluation of Geometric Accuracy of MRI Protocols Used in Experimental Stroke

et al. 2016

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“…Accurate ventricular segmentation also has an important role in estimating disease progression. Khan et al [358] described the construction and testing of a physical brain ventricle phantom constructed to accurately simulate brain tissue T1 relaxation times. The phantom proved suitable for the validation of ventricular segmentation algorithms as it was life size, easy to fabricate, inexpensive, and accurately mimicked brain tissue.…”

Section: Methods Papersmentioning

confidence: 99%

2014 Update of the Alzheimer's Disease Neuroimaging Initiative: A review of papers published since its inception

Weiner

Veitch

Aisen

et al. 2015

Alzheimer's & Dementia

273

224

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The Alzheimer’s Disease Neuroimaging Initiative (ADNI) is an ongoing, longitudinal, multicenter study designed to develop clinical, imaging, genetic, and biochemical biomarkers for the early detection and tracking of Alzheimer’s disease (AD). The initial study, ADNI-1, enrolled 400 subjects with early mild cognitive impairment (MCI), 200 with early AD, and 200 cognitively normal elderly controls. ADNI-1 was extended by a 2-year Grand Opportunities grant in 2009 and by a competitive renewal, ADNI-2, which enrolled an additional 550 participants and will run until 2015. This article reviews all papers published since the inception of the initiative and summarizes the results to the end of 2013. The major accomplishments of ADNI have been as follows: (1) the development of standardized methods for clinical tests, magnetic resonance imaging (MRI), positron emission tomography (PET), and cerebrospinal fluid (CSF) biomarkers in a multicenter setting; (2) elucidation of the patterns and rates of change of imaging and CSF biomarker measurements in control subjects, MCI patients, and AD patients. CSF biomarkers are largely consistent with disease trajectories predicted by β-amyloid cascade (Hardy, J Alzheimer’s Dis 2006;9(Suppl 3):151–3) and tau-mediated neurodegeneration hypotheses for AD, whereas brain atrophy and hypometabolism levels show predicted patterns but exhibit differing rates of change depending on region and disease severity; (3) the assessment of alternative methods of diagnostic categorization. Currently, the best classifiers select and combine optimum features from multiple modalities, including MRI, [18F]-fluorodeoxyglucose-PET, amyloid PET, CSF biomarkers, and clinical tests; (4) the development of blood biomarkers for AD as potentially noninvasive and low-cost alternatives to CSF biomarkers for AD diagnosis and the assessment of α-syn as an additional biomarker; (5) the development of methods for the early detection of AD. CSF biomarkers, β-amyloid 42 and tau, as well as amyloid PET may reflect the earliest steps in AD pathology in mildly symptomatic or even nonsymptomatic subjects and are leading candidates for the detection of AD in its preclinical stages; (6) the improvement of clinical trial efficiency through the identification of subjects most likely to undergo imminent future clinical decline and the use of more sensitive outcome measures to reduce sample sizes. Multimodal methods incorporating APOE status and longitudinal MRI proved most highly predictive of future decline. Refinements of clinical tests used as outcome measures such as clinical dementia rating-sum of boxes further reduced sample sizes; (7) the pioneering of genome-wide association studies that leverage quantitative imaging and biomarker phenotypes, including longitudinal data, to confirm recently identified loci, CR1, CLU, and PICALM and to identify novel AD risk loci; (8) worldwide impact through the establishment of ADNI-like programs in Japan, Australia, Argentina, Taiwan, China, Korea, Europe, and Italy; (9) understanding ...

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“…Other phantoms include that used by participants in the Alzheimer's Disease Neuroimaging Initiative (ADNI) to assess scanner performance for multicenter trials and the fBIRN phantom, which is widely used for characterizing MR scanner performance specific to functional MRI studies. Special‐purpose phantoms have been employed for other QC applications, for example, to assess imaging methods such as diffusion MRI, to assess image‐processing tools, and to evaluate image distortion or artifact . The ACR phantom itself is also used for QC programs other than those mandated under the ACR accreditation program …”

Section: Discussionmentioning

confidence: 99%

On replacing the manual measurement of ACR phantom images performed by MRI technologists with an automated measurement approach

Panych

Chiou

Qin

et al. 2015

J. Magn. Reson. Imaging

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A novel MRI‐compatible brain ventricle phantom for validation of segmentation and volumetry methods

Cited by 11 publications

References 22 publications

Multicenter Evaluation of Geometric Accuracy of MRI Protocols Used in Experimental Stroke

Multicenter Evaluation of Geometric Accuracy of MRI Protocols Used in Experimental Stroke

2014 Update of the Alzheimer's Disease Neuroimaging Initiative: A review of papers published since its inception

On replacing the manual measurement of ACR phantom images performed by MRI technologists with an automated measurement approach

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