Cardiac SPECT Radiomics Features Repeatability and Reproducibility: A Multi Scanner Phantom Study

TL;DR

This study evaluates the robustness of cardiac SPECT radiomics features across various imaging settings using multiple scanners and identifies the most reproducible features for potential clinical application.

Contribution

It systematically assesses the repeatability and reproducibility of a wide range of radiomics features under different imaging parameters in a multi-scanner phantom study.

Findings

IDMN and IDN features are highly reproducible (COV < 5) across settings.

Matrix size significantly impacts feature variability, with over 82% showing high variability (COV > 20).

Certain features like IDMN, IDN, RP, ZE, and DE are consistently reproducible.

Abstract

Background: The aim of this study was to assess the robustness of cardiac SPECT radiomics features against changes in imaging settings including acquisition and reconstruction settings. Methods: Four scanners were used to acquire SPECT scans of a cardiac phantom with 5mCi of 99mTc. The effects of different image acquisition and reconstruction settings including the Number of View, View Matrix Size, attenuation correction, image reconstruction algorithm, number of iterations, number of subsets, type of filter, full width at half maximum (FWHM) of Gaussian filter, Butterworth filter order, and Butterworth filter cut-off were studied. In total 5263 different images were reconstructed. Eighty-seven radiomic features including first, second, and high order textures were extracted from images. To assess reproducibility and repeatability the coefficient of variation (COV) was used for each image feature over the different imaging settings. Result: IDMN and IDN features from GLCM, RP from GLRLM, ZE from GLSZM, and DE from GLDM feature sets were the only features that were the most reproducible (COV < 5) against changes in all imaging settings. In addition, the IDMN feature from GLCM, LALGLE, SALGLE and LGLZE from GLSZM, and SDLGLE from GLDM feature sets were the features that were less reproducible (COV>20 ) against changes in all imaging settings. Matrix size has the greatest impact on feature variability as most of features are not repeatable and 82.76 of them had (COV>20 ). Conclusion: Repeatability and reproducibility of SPECT radiomics texture features in different imaging settings is feature-dependent, and different image acquisitions and reconstructions have different effects on radiomics texture features. Low COV radiomics features could be consider for further clinical studies. Keywords: SPECT, Radiomics, Cardiac, Repeatability, Reproducibility