Rescue Protocol to Improve the Image Quality of 18F-FDG PET/CT Myocardial Metabolic Imaging

Development and evaluation of a radiomics model of resting 13N-ammonia positron emission tomography myocardial perfusion imaging to predict coronary artery stenosis in patients with suspected coronary heart disease

BACKGROUND

Coronary angiography (CAG) is usually performed in patients with coronary heart disease (CHD) to evaluate the coronary artery stenosis. However, patients with iodine allergy and renal dysfunction are not suitable for CAG. We try to develop a radiomics machine learning model based on rest 13N-ammonia (13N-NH3) positron emission tomography (PET) myocardial perfusion imaging (MPI) to predict coronary stenosis.

METHODS

Eighty-four patients were included with the inclusion criteria: adult patients; suspected CHD; resting MPI and CAG were performed; and complete data. Coronary artery stenosis >75% were considered to be significant stenosis. Patients were randomly divided into a training group and a testing group with a ratio of 1:1. Myocardial blood flow (MBF), perfusion defect extent (EXT), total perfusion deficit (TPD), and summed rest score (SRS) were obtained. Myocardial static images of the left ventricular (LV) coronary segments were segmented, and radiomics features were extracted. In the training set, the conventional parameter (MPI model) and radiomics (Rad model) models were constructed using the machine learning method and were combined to construct a nomogram. The models' performance was evaluated by area under the curve (AUC), accuracy, sensitivity, specificity, decision analysis curve (DCA), and calibration curves. Testing and subgroup analysis were performed.

RESULTS

MPI model was composed of MBF and EXT, and Rad model was composed of 12 radiomics features. In the training set, the AUC/accuracy/sensitivity/specificity of the MPI model, Rad model, and the nomogram were 0.795/0.778/0.937/0.511, 0.912/0.825/0.760/0.936 and 0.911/0.865/0.924/0.766 respectively. In the testing set, the AUC/accuracy/sensitivity/specificity of the MPI model, Rad model, and the nomogram were 0.798/0.722/0.659/0.841, 0.887/0.810/0.744/0.932 and 0.900/0.849/0.854/0.841 respectively. The AUC of Rad model and nomogram were significantly higher than that of MPI model. The DCA curve also showed that the clinical net benefit of the Rad model and nomogram was similar but greater than that of MPI model. The calibration curve showed good agreement between the observed and predicted values of the Rad model. In the subgroup analysis of Rad model, there was no significant difference in AUC between subgroups.

CONCLUSIONS

The Rad model is more accurate than the MPI model in predicting coronary stenosis. This noninvasive technique could help improve risk stratification and had good generalization ability.

Intravenous insulin injection supplemented with subsequent milk consumption is a safer formulation for cardiac viability 18F-FDG imaging

BACKGROUND

The safety and efficacy of intravenous insulin injection coupled with subsequent milk consumption was evaluated for high-quality cardiac viability F-18-fluorodeoxyglucose (18F-FDG) images.

METHODS AND RESULTS

A total of 328 patients with known/suspected coronary artery disease received intravenous insulin injection with or without subsequent milk consumption for cardiac 18F-FDG imaging. When blood glucose levels had decreased by ≥ 20%, 18F-FDG was injected. Patients were scored for hypoglycemic symptoms using a 10-point scale (discomfort: 0, none; 1 to 3, mild; 4 to 6, moderate; 7 to 9, severe). An insulin-related hypoglycemic event was defined as an increased symptomatic score following insulin injection. The number of hypoglycemic events was significantly lower in the milk consumption group than in the group that did not (24/164 vs. 51/164, P < .01). Maximal and averaged standardized uptake value of the left ventricular myocardium (MyoSUVmax and MyoSUVmean) were also measured. The milk and control groups had similar mean hypoglycemic symptom scores (4.2 ± 4.0 vs. 3.3 ± 3.1, respectively), MyoSUVmax, and MyoSUVmean (11.1 ± 4.8, 7.3 ± 3.2 vs. 11.4 ± 4.5, 7.4 ± 3.2, respectively).

CONCLUSION

Intravenous insulin injection supplemented with subsequent milk consumption is a safer formulation for cardiac viability 18F-FDG imaging without impairing image quality.