Vessel Specific Coronary Artery Calcium Scoring

Shahzad, Rahil; Walsum, Theo van; Schaap, Michiel; Rossi, Alexia; Klein, Stefan; Weustink, Annick C.; Feyter, Pim J. de; Vliet, Lucas J. van; Niessen, Wiro J.

doi:10.1016/j.acra.2012.07.018

Cited by 72 publications

(59 citation statements)

References 24 publications

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“…Interestingly, several recent studies have reported that the pattern and progression of calcification in individual coronary arteries are more valuable compared to total heart calcium measurements for risk stratification and prediction of adverse cardiovascular outcomes (20,21). An additional finding of the present study was the observed significant correlation between high ARC and coronary calcified plaques.…”

Section: Discussionmentioning

confidence: 50%

Correlations Between Aortic Root Calcification and Coronary Artery Atherosclerotic Markers Assessed Using Multidetector Computed Tomography

et al. 2015

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Section: Discussionmentioning

confidence: 50%

Correlations Between Aortic Root Calcification and Coronary Artery Atherosclerotic Markers Assessed Using Multidetector Computed Tomography

et al. 2015

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“…In their recent publications, Shahzad et al (47) and Isgum et al (48) demonstrated that automated computerized calcium scoring of coronary vessel territories and total heart calcium in low-dose MDCT is feasible and reproducible. We propose that a quick, visual analysis of calcium load may provide similar information.…”

Section: Discussionmentioning

confidence: 98%

Extracoronary Thoracic and Coronary Artery Calcifications on Chest CT for Lung Cancer Screening

et al. 2015

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“…They all follow the same general framework: first, a region of interest (ROI) around the heart is located, either using anatomy-based approaches 5 , atlas-based location strategies 6 or 2.5 D object detection strategies. 7,8 Second, CACs are found in the ROI and categorized as relevant or not using their relative position in the image 9 , their texture and size features 10 or a combination of both 11,12 . The latest works of Ref.…”

Section: Introductionmentioning

confidence: 99%

Automated Agatston score computation in non-ECG gated CT scans using deep learning

Cano-Espinosa¹,

González

Washko

et al. 2018

Medical Imaging 2018: Image Processing

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Introduction: The Agatston score is a well-established metric of cardiovascular disease related to clinical outcomes. It is computed from CT scans by a) measuring the volume and intensity of the atherosclerotic plaques and b) aggregating such information in an index. Objective: To generate a convolutional neural network that inputs a non-contrast chest CT scan and outputs the Agatston score associated with it directly, without a prior segmentation of Coronary Artery Calcifications (CAC). Materials and methods: We use a database of 5973 non-contrast non-ECG gated chest CT scans where the Agatston score has been manually computed. The heart of each scan is cropped automatically using an object detector. The database is split in 4973 cases for training and 1000 for testing. We train a 3D deep convolutional neural network to regress the Agatston score directly from the extracted hearts. Results: The proposed method yields a Pearson correlation coefficient of r = 0.93; p ≤ 0.0001 against manual reference standard in the 1000 test cases. It further stratifies correctly 72.6% of the cases with respect to standard risk groups. This compares to more complex state-of-the-art methods based on prior segmentations of the CACs, which achieve r = 0.94 in ECG-gated pulmonary CT. Conclusions: A convolutional neural network can regress the Agatston score from the image of the heart directly, without a prior segmentation of the CACs. This is a new and simpler paradigm in the Agatston score computation that yields similar results to the state-of-the-art literature.

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Vessel Specific Coronary Artery Calcium Scoring

Cited by 72 publications

References 24 publications

Correlations Between Aortic Root Calcification and Coronary Artery Atherosclerotic Markers Assessed Using Multidetector Computed Tomography

Correlations Between Aortic Root Calcification and Coronary Artery Atherosclerotic Markers Assessed Using Multidetector Computed Tomography

Extracoronary Thoracic and Coronary Artery Calcifications on Chest CT for Lung Cancer Screening

Automated Agatston score computation in non-ECG gated CT scans using deep learning

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