Quantification of the myocardial area at risk using coronary CT angiography and Voronoi algorithm-based myocardial segmentation

Kurata, Akira; Kono, Atsushi K.; Sakamoto, T.; Kido, Teruhiko; Mochizuki, Takashi; Hara, Hiroshi; Abe, Mitsunori; Coenen, Adriaan; Saru-Chelu, Raluca; Feyter, Pim J. de; Krestin, Gabriël P.; Nieman, Koen

doi:10.1007/s00330-014-3388-2

Cited by 57 publications

(41 citation statements)

References 24 publications

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“…A recent study has demonstrated the high reprodu-cibility of CTA-based LV myocardial territory and the good correlation of CTbased MAAR with SPECT-based MAAR [10]. SPECT has been established as a clinical standard because of the substantial evidence supporting its use in the diagnosis and management of CAD [5] [20] [23].…”

Section: Discussionmentioning

confidence: 99%

“…In diagnostic imaging, a previous study has shown the usefulness of this algorithm for liver segmentation, based on CT portal venography [9], and a recent study has reported that ICA-based stenosis-related CT myocardial territory correlates with the SPECT-based myocardial area at risk (MAAR) [10]. Coronary CTA stenosis-related CT myocardial territory is an assumption of the maximum MAAR that is obtained from a resting coronary CTA dataset.…”

Section: Introductionmentioning

confidence: 99%

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Myocardial Segmentation of Area at Risk Based on Coronary Computed Tomography Angiography and Voronoi Diagram in Comparison with Magnetic Resonance Perfusion Imaging

Fukuyama¹,

Kurata²,

Tanabe³

et al. 2017

OJRad

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Purpose: To assess the clinical feasibility of automated segmentation of the myocardial area at risk (MAAR) using coronary computed tomography angiography (CT-MAAR), as compared to stress magnetic resonance myocardial perfusion imaging (MR-MPI). Materials and Methods: Thirty patients who underwent coronary computed tomography angiography (CTA) and stress MR-MPI were retrospectively evaluated. The myocardial territory of the left ventricle (LV) distal to coronary artery stenosis (≥50% or ≥70% stenosis on coronary CTA) was three-dimensionally quantified using a Voronoi diagram. The ratio of all stenosis-related territories to the LV volume was defined as CT-MAAR (%-LV volume). The proportion of segments with perfusion defects in stress MR-MPI to the total of 16 segments (range: 0% -100%; with a 6.3%-interval scale) was defined as the reference. Correlation was assessed using Spearman's test. The capability of CT-MAAR to predict the ischemic burden was assessed. Results: Stress MR-MPI depicted a median ischemic burden of 25.2% (range: 18.9% -44.1%) in 30 patients without myocardial infarction. When CTA stenosis criteria of ≥50% (n = 30) and ≥70% (n = 27) were applied to estimate CT-MAAR, the median CT-MAAR values were 48.2% (31.6% -64.3%) and 32.5% (23.7% -51.9%), respectively. The correlations between the CT-MAAR values and the MR-based ischemic burden were significant (0.73 and 0.97 for ≥50% and ≥70% stenosis, respectively). CT-MAAR predicted the MR-based ischemic burden within ±1 segment of %-LV (6.3%) in 40% (12/30) of patients with ≥50% stenosis, and in 81.5% (22/27) of How to cite this paper: Fukuyama, N., Kido, T., Kurata, A., Tanabe, Y., Kido, T., Yokoi, T., Ogawa, R., Nishiyama, H., Uetani, T. and Mochizuki, T. 10patients with ≥70% stenosis. Conclusions: Comprehensive assessment of resting coronary CTA combined with Voronoi diagram-based myocardial segmentation may help predict the myocardial ischemic burden in patients with severe coronary CTA stenosis.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Myocardial Segmentation of Area at Risk Based on Coronary Computed Tomography Angiography and Voronoi Diagram in Comparison with Magnetic Resonance Perfusion Imaging

Fukuyama¹,

Kurata²,

Tanabe³

et al. 2017

OJRad

Self Cite

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“…Furthermore, because there are variations in the myocardial area at risk in each patient, vascular territory misinterpretation on PET corresponding to the culprit or reference vessel can occur. 33 Therefore, quantitative PET and coronary CTA may be complementary for better non-invasive diagnosis.…”

Section: Future Directionsmentioning

confidence: 99%

Clinical Usefulness of Coronary Flow Reserve Ratio for the Detection of Significant Coronary Artery Disease on <sup>13</sup>N-Ammonia Positron Emission Tomography

Kawaguchi

Okayama

Kito

et al. 2018

Circ J

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Background: This study aimed to evaluate the diagnostic performance of coronary flow reserve (CFR), hyperemic myocardial blood flow (hMBF), and CFR ratio for detecting significant coronary artery disease (CAD) on 13 N-ammonia positron emission tomography (PET). Methods and Results:We analyzed 63 patients (mean age, 71±9 years; 43 males) with suspected CAD who underwent both pharmacological stress/rest 13 N-ammonia PET and coronary angiography. CFR and hMBF for PET were calculated automatically using quantitative PET software, and the CFR ratio was defined as the ratio of per-vessel CFR to maximum CFR in a standard 17-segment model. We compared the diagnostic performance among the 3 quantitative values. In the per-vessel analysis, 55 vessels were diagnosed as significant CAD (≥70% stenosis and/or fraction flow reserve ≤0.8). CFR, hMBF, and CFR ratio of significant CAD were significantly lower than for non-significant CAD (1.85±0.69 vs. 2.38±0.69; P<0.01, 1.67±0.54 vs. 2.19±0.52 mL · min −1 · g −1 ; P<0.01, and 0.66±0.15 vs. 0.82±0.09; P<0.01, respectively). In the receiver-operating characteristic curve analysis, CFR, hMBF, and CFR ratio had areas under the curve of 0.71, 0.75, and 0.85 respectively, and the CFR ratio was significantly higher than CFR and hMBF (P<0.05). The sensitivity, specificity, and accuracy of the CFR ratio with an optimal cutoff value of 0.75 were 75%, 85%, and 82%, respectively. Conclusions:Clinically, the CFR ratio in 13 N-ammonia PET was more effective in detecting significant CAD.

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“…There have been several studies of patient‐specific bull's‐eye maps of the LV 8 , 9 , 10 , 11 . These studies reported patient‐specific mappings between each of the 17 segments and LV territories using CMR, adapting the 17‐segment model using patient‐specific anatomy.…”

Section: Introductionmentioning

confidence: 99%

“…There have been several studies of patient-specific bull's-eye maps of the LV. (8)(9)(10)(11) These studies reported patient-specific mappings between each of the 17 segments and LV territories using CMR, adapting the 17-segment model using patient-specific anatomy. The studies' approach achieved better correspondence between the 17 segments and coronary arterial territories, but could not provide a precise mapping between segments and the AHA recommended nomenclature.…”

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confidence: 99%

Patient‐specific 17‐segment myocardial modeling on a bull's‐eye map

Jung

Kim

et al. 2016

J Applied Clin Med Phys

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The purpose of this study was to develop and validate cardiac computed tomography (CT) quantitative analysis software with a patient‐specific, 17‐segment myocardial model that uses electrocardiogram (ECG)‐gated cardiac CT images to differentiate between normal controls and severe aortic stenosis (AS) patients. ECG‐gated cardiac CT images from 35 normal controls and 144 AS patients were semiautomatically segmented to create a patient‐specific, 17‐segment myocardial model. Two experts then manually determined the anterior and posterior interventricular grooves to be boundaries between the 1st and 2nd segments and between the 3rd and 4th segments, respectively, to correct the model. Each segment was automatically identified as follows. The outer angle of two boundaries was divided to differentiate the 1st, 4th, 5th, and 6th segments in the basal plane, whereas the inner angle divided the 2nd and 3rd segments. The segments of the midplane were similarly divided. Segmental area distributions were quantitatively evaluated on the bull's‐eye map on the basis of the morphological boundaries by measuring the area of each segment. Segmental areas of severe AS patients and normal controls were significantly different (t‐test, all p‐values<0.011) in the proposed model because the septal regions of the severe AS patients were smaller than those of normal controls and the difference was enough to divide the two groups. The capabilities of the 2D segmental areas (p<0.011) may be equivalent to those of 3D segmental analysis (all p‐values<0.001) for differentiating the two groups (t‐test, all p‐values<0.001). The proposed method is superior to the conventional 17‐segment in relation to reflection of patient‐specific morphological variation and allows to obtain a more precise mapping between segments and the AHA recommended nomenclature. It can be used to differentiate severer AS patients and normal controls and also helps to understand the left ventricular morphology at a glance.PACS number(s): 87.57.N‐, 87.57.R‐, 87.57.qp

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Quantification of the myocardial area at risk using coronary CT angiography and Voronoi algorithm-based myocardial segmentation

Abstract: • Voronoi algorithm allows for three-dimensional myocardial segmentation of coronary CT angiography • Stenosis-related CT myocardial territories correlate to SPECT based area at risk • CT angiography myocardial segmentation may assist in clinical decision-making.

Cited by 57 publications

References 24 publications

Myocardial Segmentation of Area at Risk Based on Coronary Computed Tomography Angiography and Voronoi Diagram in Comparison with Magnetic Resonance Perfusion Imaging

Myocardial Segmentation of Area at Risk Based on Coronary Computed Tomography Angiography and Voronoi Diagram in Comparison with Magnetic Resonance Perfusion Imaging

Clinical Usefulness of Coronary Flow Reserve Ratio for the Detection of Significant Coronary Artery Disease on <sup>13</sup>N-Ammonia Positron Emission Tomography

Patient‐specific 17‐segment myocardial modeling on a bull's‐eye map

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