Integration of coronary artery calcium scoring from CT attenuation scans by machine learning improves prediction of adverse cardiovascular events in patients undergoing SPECT/CT myocardial perfusion imaging.
J Nucl Cardiol
; 30(2): 590-603, 2023 04.
Article
en En
| MEDLINE
| ID: mdl-36195826
ABSTRACT
BACKGROUND:
Machine learning (ML) has been previously applied for prognostication in patients undergoing SPECT myocardial perfusion imaging (MPI). We evaluated whether including attenuation CT coronary artery calcification (CAC) scoring improves ML prediction of major adverse cardiovascular events (MACE) in patients undergoing SPECT/CT MPI.METHODS:
From the REFINE SPECT Registry 4770 patients with SPECT/CT performed at a single center were included (age 64 ± 12 years, 45% female). ML algorithm (XGBoost) inputs were clinical risk factors, stress variables, SPECT imaging parameters, and expert-observer CAC scoring using CT attenuation correction scans performed to obtain CT attenuation maps. The ML model was trained and validated using tenfold hold-out validation. Receiver Operator Characteristics (ROC) curves were analyzed for prediction of MACE. MACE-free survival was evaluated with standard survival analyses.RESULTS:
During a median follow-up of 24.1 months, 475 patients (10%) experienced MACE. Higher area under the ROC curve for MACE was observed with ML when CAC scoring was included (CAC-ML score, 0.77, 95% confidence interval [CI] 0.75-0.79) compared to ML without CAC (ML score, 0.75, 95% CI 0.73-0.77, P = .005) and when compared to CAC score alone (0.71, 95% CI 0.68-0.73, P < .001). Among clinical, imaging, and stress parameters, CAC score had highest variable importance for ML. On survival analysis patients with high CAC-ML score (> 0.091) had higher event rate when compared to patients with low CAC-ML score (hazard ratio 5.3, 95% CI 4.3-6.5, P < .001).CONCLUSION:
Integration of attenuation CT CAC scoring improves the predictive value of ML risk score for MACE prediction in patients undergoing SPECT MPI.Palabras clave
Texto completo:
1
Colección:
01-internacional
Banco de datos:
MEDLINE
Asunto principal:
Enfermedad de la Arteria Coronaria
/
Imagen de Perfusión Miocárdica
Tipo de estudio:
Prognostic_studies
/
Risk_factors_studies
Límite:
Aged
/
Female
/
Humans
/
Male
/
Middle aged
Idioma:
En
Revista:
J Nucl Cardiol
Asunto de la revista:
CARDIOLOGIA
Año:
2023
Tipo del documento:
Article
País de afiliación:
Estados Unidos