Repeatability of 18F-FDG PET Radiomic Features in Cervical Cancer
| Autor: | Richard L. Wahl, Tyler J. Fraum, Min-Young Lee, John Crandall, Linda Jiang, Perry W. Grigsby |
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| Rok vydání: | 2020 |
| Předmět: |
Cervical cancer
Matrix difference equation business.industry Pattern recognition Repeatability computer.software_genre medicine.disease 030218 nuclear medicine & medical imaging 18f fdg pet 03 medical and health sciences 0302 clinical medicine Concordance correlation coefficient Voxel Feature (computer vision) 030220 oncology & carcinogenesis Expectation–maximization algorithm medicine Radiology Nuclear Medicine and imaging Artificial intelligence business computer Mathematics |
| Zdroj: | Journal of Nuclear Medicine. 62:707-715 |
| ISSN: | 2159-662X 0161-5505 |
| Popis: | Knowledge of the intrinsic variability of radiomic features is essential to the proper interpretation of changes in these features over time. The primary aim of this study was to assess the test–retest repeatability of radiomic features extracted from 18F-FDG PET images of cervical tumors. The impact of different image preprocessing methods was also explored. Methods: Patients with cervical cancer underwent baseline and repeat 18F-FDG PET/CT imaging within 7 d. PET images were reconstructed using 2 methods: ordered-subset expectation maximization (PETOSEM) or ordered-subset expectation maximization with point-spread function (PETPSF). Tumors were segmented to produce whole-tumor volumes of interest (VOIWT) and 40% isocontours (VOI40). Voxels were either left at the default size or resampled to 3-mm isotropic voxels. SUV was discretized to a fixed number of bins (32, 64, or 128). Radiomic features were extracted from both VOIs, and repeatability was then assessed using the Lin concordance correlation coefficient (CCC). Results: Eleven patients were enrolled and completed the test–retest PET/CT imaging protocol. Shape, neighborhood gray-level difference matrix, and gray-level cooccurrence matrix features were repeatable, with a mean CCC value of 0.81. Radiomic features extracted from PETOSEM images showed significantly better repeatability than features extracted from PETPSF images (P 0.96) when extracted from VOI40. Conclusion: Shape, gray-level cooccurrence matrix, and neighborhood gray-level difference matrix radiomic features were consistently repeatable, whereas gray-level run length matrix and gray-level zone length matrix features were highly variable. Radiomic features extracted from VOI40 were more repeatable than features extracted from VOIWT. Changes in voxel size or SUV discretization parameters typically resulted in relatively small differences in feature value, though several features were highly sensitive to these changes. |
| Databáze: | OpenAIRE |
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