Dataset Information

COVID-CT-MD, COVID-19 computed tomography scan dataset applicable in machine learning and deep learning.

ABSTRACT: Novel Coronavirus (COVID-19) has drastically overwhelmed more than 200 countries affecting millions and claiming almost 2 million lives, since its emergence in late 2019. This highly contagious disease can easily spread, and if not controlled in a timely fashion, can rapidly incapacitate healthcare systems. The current standard diagnosis method, the Reverse Transcription Polymerase Chain Reaction (RT- PCR), is time consuming, and subject to low sensitivity. Chest Radiograph (CXR), the first imaging modality to be used, is readily available and gives immediate results. However, it has notoriously lower sensitivity than Computed Tomography (CT), which can be used efficiently to complement other diagnostic methods. This paper introduces a new COVID-19 CT scan dataset, referred to as COVID-CT-MD, consisting of not only COVID-19 cases, but also healthy and participants infected by Community Acquired Pneumonia (CAP). COVID-CT-MD dataset, which is accompanied with lobe-level, slice-level and patient-level labels, has the potential to facilitate the COVID-19 research, in particular COVID-CT-MD can assist in development of advanced Machine Learning (ML) and Deep Neural Network (DNN) based solutions.

SUBMITTER: Afshar P

PROVIDER: S-EPMC8085195 | biostudies-literature | 2021 Apr

REPOSITORIES: biostudies-literature

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COVID-CT-MD, COVID-19 computed tomography scan dataset applicable in machine learning and deep learning.

Afshar Parnian P Heidarian Shahin S Enshaei Nastaran N Naderkhani Farnoosh F Rafiee Moezedin Javad MJ Oikonomou Anastasia A Fard Faranak Babaki FB Samimi Kaveh K Plataniotis Konstantinos N KN Mohammadi Arash A

Scientific data 20210429 1

Novel Coronavirus (COVID-19) has drastically overwhelmed more than 200 countries affecting millions and claiming almost 2 million lives, since its emergence in late 2019. This highly contagious disease can easily spread, and if not controlled in a timely fashion, can rapidly incapacitate healthcare systems. The current standard diagnosis method, the Reverse Transcription Polymerase Chain Reaction (RT- PCR), is time consuming, and subject to low sensitivity. Chest Radiograph (CXR), the first imag ...[more]

PMID: 33927208

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Project description:BackgroundNitroglycerin administration prior to examination improves stenosis assessment of coronary computed tomography (CT) angiography (CCTA). However, whether nitroglycerin influences CT-derived fractional flow reserve (FFR, CT-FFR) evaluation remains unclear. This study aimed to investigate the effect of nitroglycerin on diagnostic performance of CT-FFR.MethodsIn this single-center retrospective study, 107 consecutive patients suspected of coronary artery disease (CAD) with nitroglycerin administration prior to CCTA in 2019 were matched to 107 patients without nitroglycerin in 2016 from Fuwai Hospital. All patients underwent CCTA and invasive FFR in a month. Vessel-based and patient-based accuracy and diagnostic performance of CT-FFR were compared between the two groups, as well as image quality, coronary artery diameter and evaluability. Quantitative variables were compared by Kruskal-Wallis H test. Categorical variables and rates were compared by χ2 test or Fisher exact test.ResultsA total of 214 patients (56.1±8.9 years, 155 male) with 237 target lesion vessels were analyzed, including 120 vessels in nitroglycerin and 117 vessels in non-nitroglycerin group. Per-vessel based accuracy of CT-FFR was higher in nitroglycerin group {80.0% [95% confidence interval (CI): 71.7-86.7%] vs. 68.4% (59.1-76.7%), P=0.041}. On a per-patient basis, nitroglycerin administration improved the accuracy [83.2% (74.7-89.7%) vs. 68.2% (58.5-76.9%), P=0.01], specificity [82.7% (69.7-91.8%) vs. 61.9% (48.8-73.9%), P=0.01], positive predictive value (PPV) [83.6% (73.6-90.4%) vs. 58.6% (50.0-66.9%), P=0.004], and area under the curve (AUC) [0.83 (0.75-0.89) vs. 0.71 (0.61-0.79), P=0.03] of CT-FFR. Vessel diameters (left main arteries: 4.3 vs. 3.8 mm, P<0.001; left anterior descending arteries: 3.1 vs. 2.9 mm, P=0.001; left circumflex arteries: 2.9 vs. 2.7 mm, P=0.01; right coronary arteries: 3.7 vs. 3.4 mm, P=0.001) and number of evaluable coronary arteries (11.0 vs. 8.0, P<0.001) were larger in nitroglycerin group.ConclusionsNitroglycerin administration prior to CCTA has positive effects on diagnostic performance of CT-FFR.

Dataset Information

COVID-CT-MD, COVID-19 computed tomography scan dataset applicable in machine learning and deep learning.

Publications

COVID-CT-MD, COVID-19 computed tomography scan dataset applicable in machine learning and deep learning.

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