Opportunistic deep learning powered calcium scoring in oncologic patients with very high coronary artery calcium (≥ 1000) undergoing 18F-FDG PET/CT

Our aim was to identify and quantify high coronary artery calcium (CAC) with deep learning (DL)-powered CAC scoring (CACS) in oncological patients with known very high CAC (≥ 1000) undergoing 18F-FDG-PET/CT for re-/staging. 100 patients were enrolled: 50 patients with Agatston scores ≥ 1000 (high CA...

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Veröffentlicht in:	Scientific reports 2022-11, Vol.12 (1), p.19191-19191, Article 19191
Hauptverfasser:	Sartoretti, Elisabeth, Gennari, Antonio G., Maurer, Alexander, Sartoretti, Thomas, Skawran, Stephan, Schwyzer, Moritz, Rossi, Alexia, Giannopoulos, Andreas A., Buechel, Ronny R., Gebhard, Catherine, Huellner, Martin W., Messerli, Michael
Format:	Artikel
Sprache:	eng
Schlagworte:	692/308 692/4019 692/4028 Arteriosclerosis Calcification (ectopic) Calcium Calcium, Dietary Computed tomography Coronary artery Coronary Artery Disease - diagnostic imaging Coronary vessels Coronary Vessels - diagnostic imaging Deep Learning EKG Fluorodeoxyglucose F18 Humanities and Social Sciences Humans Hypercalcemia Medical imaging multidisciplinary Positron emission tomography Positron Emission Tomography Computed Tomography Science Science (multidisciplinary) Single photon emission computed tomography
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Beschreibung
Zusammenfassung:	Our aim was to identify and quantify high coronary artery calcium (CAC) with deep learning (DL)-powered CAC scoring (CACS) in oncological patients with known very high CAC (≥ 1000) undergoing 18F-FDG-PET/CT for re-/staging. 100 patients were enrolled: 50 patients with Agatston scores ≥ 1000 (high CACS group), 50 patients with Agatston scores
ISSN:	2045-2322 2045-2322
DOI:	10.1038/s41598-022-20005-0