Dataset Information

Annotated computed tomography coronary angiogram images and associated data of normal and diseased arteries.

ABSTRACT: Computed Tomography Coronary Angiography (CTCA) is a non-invasive method to evaluate coronary artery anatomy and disease. CTCA is ideal for geometry reconstruction to create virtual models of coronary arteries. To our knowledge there is no public dataset that includes centrelines and segmentation of the full coronary tree. We provide anonymized CTCA images, voxel-wise annotations and associated data in the form of centrelines, calcification scores and meshes of the coronary lumen in 20 normal and 20 diseased cases. Images were obtained along with patient information with informed, written consent as part of the Coronary Atlas. Cases were classified as normal (zero calcium score with no signs of stenosis) or diseased (confirmed coronary artery disease). Manual voxel-wise segmentations by three experts were combined using majority voting to generate the final annotations. Provided data can be used for a variety of research purposes, such as 3D printing patient-specific models, development and validation of segmentation algorithms, education and training of medical personnel and in-silico analyses such as testing of medical devices.

SUBMITTER: Gharleghi R

PROVIDER: S-EPMC10006074 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature

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Annotated computed tomography coronary angiogram images and associated data of normal and diseased arteries.

Gharleghi R R Adikari D D Ellenberger K K Webster M M Ellis C C Sowmya A A Ooi S S Beier S S

Scientific data 20230310 1

Computed Tomography Coronary Angiography (CTCA) is a non-invasive method to evaluate coronary artery anatomy and disease. CTCA is ideal for geometry reconstruction to create virtual models of coronary arteries. To our knowledge there is no public dataset that includes centrelines and segmentation of the full coronary tree. We provide anonymized CTCA images, voxel-wise annotations and associated data in the form of centrelines, calcification scores and meshes of the coronary lumen in 20 normal an ...[more]

PMID: 36899014

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Project description:Thin-cap fibroatheroma (TCFA) and plaque rupture have been recognized as the most frequent risk factor for thrombosis and acute coronary syndrome. Intravascular optical coherence tomography (IVOCT) can identify TCFA and assess cap thickness, which provides an opportunity to assess plaque vulnerability. We developed an automated method that can detect lipidous plaque and assess fibrous cap thickness in IVOCT images. This study analyzed a total of 4360 IVOCT image frames of 77 lesions among 41 patients. Expert cardiologists manually labeled lipidous plaque based on established criteria. To improve segmentation performance, preprocessing included lumen segmentation, pixel-shifting, and noise filtering on the raw polar (r, θ) IVOCT images. We used the DeepLab-v3 plus deep learning model to classify lipidous plaque pixels. After lipid detection, we automatically detected the outer border of the fibrous cap using a special dynamic programming algorithm and assessed the cap thickness. Our method provided excellent discriminability of lipid plaque with a sensitivity of 85.8% and A-line Dice coefficient of 0.837. By comparing lipid angle measurements between two analysts following editing of our automated software, we found good agreement by Bland-Altman analysis (difference 6.7° ± 17°; mean ~ 196°). Our method accurately detected the fibrous cap from the detected lipid plaque. Automated analysis required a significant modification for only 5.5% frames. Furthermore, our method showed a good agreement of fibrous cap thickness between two analysts with Bland-Altman analysis (4.2 ± 14.6 µm; mean ~ 175 µm), indicating little bias between users and good reproducibility of the measurement. We developed a fully automated method for fibrous cap quantification in IVOCT images, resulting in good agreement with determinations by analysts. The method has great potential to enable highly automated, repeatable, and comprehensive evaluations of TCFAs.

Project description:BackgroundCoronary computed tomography angiogram (CCTA) has the characteristics of non-invasive, high resolution, and can accurately determine the characteristics of tubular wall plaques. The non-calcified plaque loading of the coronary arteries is unstable and prone to shedding, leading to adverse cardiovascular events. However, few studies focused on the predictive value of non-calcified plaque loading for adverse cardiovascular events in patients with unstable coronary heart disease (CHD). The present study was conducted to investigate the association of coronary non-calcified plaque loading based on CCTA and adverse cardiovascular events in patients with unstable CHD.MethodsA total of 206 patients with unstable CHD were collected and followed up for 1 year. The patients were divided into an observation group (n=56) and a control group (n=150) according to whether adverse cardiovascular events occurred or not. We analyzed the predictive value of coronary artery non-calcified plaque loading for adverse cardiovascular events in unstable CHD using receiver operating characteristic and multivariate logistics regression analysis.ResultsCompared with the control group, the non-calcified plaque volume in the observation group was increased (160.10±44.02 vs. 128.06±42.22 mm3, P=0.000); non-calcified plaque loading increased (26.93%±7.98% vs. 21.46%±7.62%, P=0.000); carotid intima-media thickness increased (1.49±0.17 vs. 1.40%±0.18 mm, P=0.001); and left ventricular ejection fraction (LVEF) was significantly reduced (53.28%±7.39% vs. 58.02%±7.91%, P=0.000). Non-calcified plaque volume and non-calcified plaque loading have certain diagnostic value for recurrence of adverse cardiovascular events within 1 year (P<0.05). A non-calcified plaque volume >145.58 mm3 is a risk factor for recurrence of adverse cardiovascular events (P<0.05).ConclusionsIncreased non-calcified plaque volume in patients with unstable CHD is associated with the development of adverse cardiovascular events in patients with unstable CHD.

Dataset Information

Annotated computed tomography coronary angiogram images and associated data of normal and diseased arteries.

Publications

Annotated computed tomography coronary angiogram images and associated data of normal and diseased arteries.

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