Keywords: Radiomics, Prostate, Repeatability, Optimization
Motivation: Radiomic feature extraction techniques may be combined with reduced k-space data acquisition, if their repeatability and clinical performance would stay in the same levels as with full data acquisition.
Goal(s): We evaluate radiomics for their potential to be used in keyhole imaging acquiring k-space only partially.
Approach: We utilized 78 patients with prostate cancer who underwent short-term test-retest prostate MRI examination. We calculated ADC parameter map with different portions of k-space, simulating keyhole acquisitions. We extracted radiomics, evaluating intra-class correlation coefficient ICC(3,1) changes and area under ROC curve (AUC).
Results: Repeatability and classification performance stayed in acceptable limits for some of the radiomics.
Impact: The technique is relative easy to implement, and thus may benefit clinical MR examinations in the near future.
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