TY - JOUR
T1 - Performance of visual, manual, and automatic coronary calcium scoring of cardiac 13N-ammonia PET/low dose CT
AU - Dobrolinska, Magdalena M.
AU - Lazarenko, Sergiy V.
AU - van der Zant, Friso M.
AU - Does, Lonneke
AU - van der Werf, Niels
AU - Prakken, Niek H.J.
AU - Greuter, Marcel J.W.
AU - Slart, Riemer H.J.A.
AU - Knol, Remco J.J.
N1 - Funding Information:
M.M.D. received the “EACVI Research Grant 2020” and “Specialised Research Fellowship 2019 Grant from “Club 30” and Polish Cardiac Society”.
Publisher Copyright:
© 2022, The Author(s).
PY - 2023/2
Y1 - 2023/2
N2 - Background: Coronary artery calcium is a well-known predictor of major adverse cardiac events and is usually scored manually from dedicated, ECG-triggered calcium scoring CT (CSCT) scans. In clinical practice, a myocardial perfusion PET scan is accompanied by a non-ECG triggered low dose CT (LDCT) scan. In this study, we investigated the accuracy of patients’ cardiovascular risk categorisation based on manual, visual, and automatic AI calcium scoring using the LDCT scan. Methods: We retrospectively enrolled 213 patients. Each patient received a 13N-ammonia PET scan, an LDCT scan, and a CSCT scan as the gold standard. All LDCT and CSCT scans were scored manually, visually, and automatically. For the manual scoring, we used vendor recommended software (Syngo.via, Siemens). For visual scoring a 6-points risk scale was used (0; 1-10; 11-100; 101-400; 401-100; > 1 000 Agatston score). The automatic scoring was performed with deep learning software (Syngo.via, Siemens). All manual and automatic Agatston scores were converted to the 6-point risk scale. Manual CSCT scoring was used as a reference. Results: The agreement of manual and automatic LDCT scoring with the reference was low [weighted kappa 0.59 (95% CI 0.53-0.65); 0.50 (95% CI 0.44-0.56), respectively], but the agreement of visual LDCT scoring was strong [0.82 (95% CI 0.77-0.86)]. Conclusions: Compared with the gold standard manual CSCT scoring, visual LDCT scoring outperformed manual LDCT and automatic LDCT scoring.
AB - Background: Coronary artery calcium is a well-known predictor of major adverse cardiac events and is usually scored manually from dedicated, ECG-triggered calcium scoring CT (CSCT) scans. In clinical practice, a myocardial perfusion PET scan is accompanied by a non-ECG triggered low dose CT (LDCT) scan. In this study, we investigated the accuracy of patients’ cardiovascular risk categorisation based on manual, visual, and automatic AI calcium scoring using the LDCT scan. Methods: We retrospectively enrolled 213 patients. Each patient received a 13N-ammonia PET scan, an LDCT scan, and a CSCT scan as the gold standard. All LDCT and CSCT scans were scored manually, visually, and automatically. For the manual scoring, we used vendor recommended software (Syngo.via, Siemens). For visual scoring a 6-points risk scale was used (0; 1-10; 11-100; 101-400; 401-100; > 1 000 Agatston score). The automatic scoring was performed with deep learning software (Syngo.via, Siemens). All manual and automatic Agatston scores were converted to the 6-point risk scale. Manual CSCT scoring was used as a reference. Results: The agreement of manual and automatic LDCT scoring with the reference was low [weighted kappa 0.59 (95% CI 0.53-0.65); 0.50 (95% CI 0.44-0.56), respectively], but the agreement of visual LDCT scoring was strong [0.82 (95% CI 0.77-0.86)]. Conclusions: Compared with the gold standard manual CSCT scoring, visual LDCT scoring outperformed manual LDCT and automatic LDCT scoring.
UR - http://www.scopus.com/inward/record.url?scp=85132136368&partnerID=8YFLogxK
U2 - 10.1007/s12350-022-03018-0
DO - 10.1007/s12350-022-03018-0
M3 - Article
C2 - 35708853
AN - SCOPUS:85132136368
SN - 1071-3581
VL - 30
SP - 239
EP - 250
JO - Journal of Nuclear Cardiology
JF - Journal of Nuclear Cardiology
IS - 1
ER -