Voxel-wise quantification of myocardial blood flow with cardiovascular magnetic resonance: effect of variations in methodology and validation with positron emission ... View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2014-01-24

AUTHORS

Christopher A Miller, Josephine H Naish, Mark P Ainslie, Christine Tonge, Deborah Tout, Parthiban Arumugam, Anita Banerji, Robin M Egdell, David Clark, Peter Weale, Christopher D Steadman, Gerry P McCann, Simon G Ray, Geoffrey JM Parker, Matthias Schmitt

ABSTRACT

BackgroundQuantitative assessment of myocardial blood flow (MBF) from cardiovascular magnetic resonance (CMR) perfusion images appears to offer advantages over qualitative assessment. Currently however, clinical translation is lacking, at least in part due to considerable disparity in quantification methodology. The aim of this study was to evaluate the effect of common methodological differences in CMR voxel-wise measurement of MBF, using position emission tomography (PET) as external validation.MethodsEighteen subjects, including 9 with significant coronary artery disease (CAD) and 9 healthy volunteers prospectively underwent perfusion CMR. Comparison was made between MBF quantified using: 1. Calculated contrast agent concentration curves (to correct for signal saturation) versus raw signal intensity curves; 2. Mid-ventricular versus basal-ventricular short-axis arterial input function (AIF) extraction; 3. Three different deconvolution approaches; Fermi function parameterization, truncated singular value decomposition (TSVD) and first-order Tikhonov regularization with b-splines. CAD patients also prospectively underwent rubidium-82 PET (median interval 7 days).ResultsMBF was significantly higher when calculated using signal intensity compared to contrast agent concentration curves, and when the AIF was extracted from mid- compared to basal-ventricular images. MBF did not differ significantly between Fermi and Tikhonov, or between Fermi and TVSD deconvolution methods although there was a small difference between TSVD and Tikhonov (0.06 mL/min/g). Agreement between all deconvolution methods was high. MBF derived using each CMR deconvolution method showed a significant linear relationship (p < 0.001) with PET-derived MBF however each method underestimated MBF compared to PET (by 0.19 to 0.35 mL/min/g).ConclusionsVariations in more complex methodological factors such as deconvolution method have no greater effect on estimated MBF than simple factors such as AIF location and observer variability. Standardization of the quantification process will aid comparison between studies and may help CMR MBF quantification enter clinical use. More... »

PAGES

11

References to SciGraph publications

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URI

http://scigraph.springernature.com/pub.10.1186/1532-429x-16-11

DOI

http://dx.doi.org/10.1186/1532-429x-16-11

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1018694048

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/24460930


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29 schema:description BackgroundQuantitative assessment of myocardial blood flow (MBF) from cardiovascular magnetic resonance (CMR) perfusion images appears to offer advantages over qualitative assessment. Currently however, clinical translation is lacking, at least in part due to considerable disparity in quantification methodology. The aim of this study was to evaluate the effect of common methodological differences in CMR voxel-wise measurement of MBF, using position emission tomography (PET) as external validation.MethodsEighteen subjects, including 9 with significant coronary artery disease (CAD) and 9 healthy volunteers prospectively underwent perfusion CMR. Comparison was made between MBF quantified using: 1. Calculated contrast agent concentration curves (to correct for signal saturation) versus raw signal intensity curves; 2. Mid-ventricular versus basal-ventricular short-axis arterial input function (AIF) extraction; 3. Three different deconvolution approaches; Fermi function parameterization, truncated singular value decomposition (TSVD) and first-order Tikhonov regularization with b-splines. CAD patients also prospectively underwent rubidium-82 PET (median interval 7 days).ResultsMBF was significantly higher when calculated using signal intensity compared to contrast agent concentration curves, and when the AIF was extracted from mid- compared to basal-ventricular images. MBF did not differ significantly between Fermi and Tikhonov, or between Fermi and TVSD deconvolution methods although there was a small difference between TSVD and Tikhonov (0.06 mL/min/g). Agreement between all deconvolution methods was high. MBF derived using each CMR deconvolution method showed a significant linear relationship (p < 0.001) with PET-derived MBF however each method underestimated MBF compared to PET (by 0.19 to 0.35 mL/min/g).ConclusionsVariations in more complex methodological factors such as deconvolution method have no greater effect on estimated MBF than simple factors such as AIF location and observer variability. Standardization of the quantification process will aid comparison between studies and may help CMR MBF quantification enter clinical use.
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36 schema:keywords AIF
37 B-splines
38 CAD patients
39 CMR
40 ConclusionsVariation
41 Fermi
42 MBF quantification
43 MethodsEighteen subjects
44 TSVD
45 Tikhonov
46 Tikhonov regularization
47 advantages
48 agreement
49 aim
50 approach
51 artery disease
52 assessment
53 blood flow
54 cardiovascular magnetic resonance
55 clinical translation
56 clinical use
57 comparison
58 concentration curve
59 considerable disparity
60 contrast agent concentration curves
61 coronary artery disease
62 curves
63 decomposition
64 deconvolution approach
65 deconvolution method
66 differences
67 different deconvolution approaches
68 disease
69 disparities
70 effect
71 effect of variation
72 emission tomography
73 external validation
74 extraction
75 factors
76 first-order Tikhonov regularization
77 flow
78 function extraction
79 greater effect
80 healthy volunteers
81 images
82 intensity
83 intensity curves
84 linear relationship
85 location
86 magnetic resonance
87 magnetic resonance perfusion images
88 measurements
89 method
90 methodological differences
91 methodological factors
92 methodology
93 myocardial blood flow
94 observer variability
95 parameterization
96 part
97 patients
98 perfusion CMR
99 perfusion images
100 position emission tomography
101 positron emission tomography
102 process
103 qualitative assessment
104 quantification
105 quantification methodology
106 quantification process
107 regularization
108 relationship
109 resonance
110 signal intensity
111 signal intensity curves
112 significant coronary artery disease
113 significant linear relationship
114 simple factors
115 singular value decomposition
116 small differences
117 standardization
118 study
119 subjects
120 tomography
121 translation
122 use
123 validation
124 value decomposition
125 variability
126 variation
127 volunteers
128 voxel-wise measurements
129 voxel-wise quantification
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