Dataset Information

Radiomics for the detection of diffusely impaired myocardial perfusion: A proof-of-concept study using 13N-ammonia positron emission tomography.

ABSTRACT:

Aim

The current proof-of-concept study investigates the value of radiomic features from normal 13N-ammonia positron emission tomography (PET) myocardial retention images to identify patients with reduced global myocardial flow reserve (MFR).

Methods

Data from 100 patients with normal retention 13N-ammonia PET scans were divided into two groups, according to global MFR (i.e., < 2 and ≥ 2), as derived from quantitative PET analysis. We extracted radiomic features from retention images at each of five different gray-level (GL) discretization (8, 16, 32, 64, and 128 bins). Outcome independent and dependent feature selection and subsequent univariate and multivariate analyses was performed to identify image features predicting reduced global MFR.

Results

A total of 475 radiomic features were extracted per patient. Outcome independent and dependent feature selection resulted in a remainder of 35 features. Discretization at 16 bins (GL16) yielded the highest number of significant predictors of reduced MFR and was chosen for the final analysis. GLRLM_GLNU was the most robust parameter and at a cut-off of 948 yielded an accuracy, sensitivity, specificity, negative and positive predictive value of 67%, 74%, 58%, 64%, and 69%, respectively, to detect diffusely impaired myocardial perfusion.

Conclusion

A single radiomic feature (GLRLM_GLNU) extracted from visually normal 13N-ammonia PET retention images independently predicts reduced global MFR with moderate accuracy. This concept could potentially be applied to other myocardial perfusion imaging modalities based purely on relative distribution patterns to allow for better detection of diffuse disease.

SUBMITTER: Degtiarova G

PROVIDER: S-EPMC10371953 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature

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Publications

Radiomics for the detection of diffusely impaired myocardial perfusion: A proof-of-concept study using 13N-ammonia positron emission tomography.

Degtiarova Ganna G Garefa Chrysoula C Boehm Reto R Ciancone Domenico D Sepulcri Daniel D Gebhard Catherine C Giannopoulos Andreas A AA Pazhenkottil Aju P AP Kaufmann Philipp A PA Buechel Ronny R RR

Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology 20230105 4

<h4>Aim</h4>The current proof-of-concept study investigates the value of radiomic features from normal 13N-ammonia positron emission tomography (PET) myocardial retention images to identify patients with reduced global myocardial flow reserve (MFR).<h4>Methods</h4>Data from 100 patients with normal retention 13N-ammonia PET scans were divided into two groups, according to global MFR (i.e., < 2 and ≥ 2), as derived from quantitative PET analysis. We extracted radiomic features from retention imag ...[more]

PMID: 36600174

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Project description:BackgroundCoronary 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.MethodsEighty-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.ResultsMPI 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.ConclusionsThe 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.

Project description:BackgroundWe previously proposed a technique for quantitative measurement of rest and stress absolute myocardial blood flow (MBF) using a 2-injection single-scan imaging session. Recently, we validated the method in a pig model for the long-lived radiotracer 18F-Flurpiridaz with adenosine as a pharmacological stressor. The aim of the present work is to validate our technique for 13NH3.MethodsNine studies were performed in 6 pigs; 5 studies were done in the native state and 4 after infarction of the left anterior descending artery. Each study consisted of 3 dynamic scans: a 2-injection rest-rest single-scan acquisition (scan A), a 2-injection rest/stress single-scan acquisition (scan B), and a conventional 1-injection stress acquisition (scan C). Variable doses of adenosine combined with dobutamine were administered to induce a wide range of MBF. The 2-injection single-scan measurements were fitted with our nonstationary kinetic model (MGH2). In 4 studies, 13NH3 injections were paired with microsphere injections. MBF estimates obtained with our method were compared with those obtained with the standard method and with microspheres. We used a model-based method to generate separate rest and stress perfusion images.ResultsIn the absence of stress (scan A), the MBF values estimated by MGH2 were nearly the same for the 2-radiotracer injections (mean difference: 0.067±0.070 mL·min-1·cc-1, limits of agreement: [-0.070 to 0.204] mL·min-1·cc-1), showing good repeatability. Bland-Altman analyses demonstrated very good agreement with the conventional method for both rest (mean difference: -0.034±0.035 mL·min-1·cc-1, limits of agreement: [-0.103 to 0.035] mL·min-1·cc-1) and stress (mean difference: 0.057±0.361 mL·min-1·cc-1, limits of agreement: [-0.651 to 0.765] mL·min-1·cc-1) MBF measurements. Positron emission tomography and microsphere MBF measurements correlated closely. Very good quality perfusion images were obtained.ConclusionsThis study provides in vivo validation of our single-scan rest-stress method for 13NH3 measurements. The 13NH3 rest/stress myocardial perfusion imaging procedure can be compressed into a single positron emission tomography scan session lasting less than 15 minutes.

Dataset Information

Radiomics for the detection of diffusely impaired myocardial perfusion: A proof-of-concept study using 13N-ammonia positron emission tomography.

Aim

Methods

Results

Conclusion

Publications

Radiomics for the detection of diffusely impaired myocardial perfusion: A proof-of-concept study using 13N-ammonia positron emission tomography.

Similar Datasets

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