MP45-17 CORRELATION BETWEEN CTC COUNTS AND RADIOMIC METRICS FROM MULTIPLE OSSEOUS METASTATIC LESIONS IN METASTATIC PROSTATE CANCER

Abstract

You have accessJournal of UrologyCME1 May 2022MP45-17 CORRELATION BETWEEN CTC COUNTS AND RADIOMIC METRICS FROM MULTIPLE OSSEOUS METASTATIC LESIONS IN METASTATIC PROSTATE CANCER Bino Varghese, Steven Cen, Gareth Morrison, Jonathan Buckley, Dejerianne Ostrow, David Quinn, Timothy Triche, Amir Goldkorn, and Vinay Duddalwar Bino VargheseBino Varghese More articles by this author , Steven CenSteven Cen More articles by this author , Gareth MorrisonGareth Morrison More articles by this author , Jonathan BuckleyJonathan Buckley More articles by this author , Dejerianne OstrowDejerianne Ostrow More articles by this author , David QuinnDavid Quinn More articles by this author , Timothy TricheTimothy Triche More articles by this author , Amir GoldkornAmir Goldkorn More articles by this author , and Vinay DuddalwarVinay Duddalwar More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000002611.17AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Identify CT radiomic correlates for liquid biopsy metrics such as circulating tumor cells (CTC) counts in patients with metastatic prostate cancer (PC). Together, CT radiomics and liquid biopsy could detect clonal heterogeneity and aid in improved patient management. METHODS: Under IRB-approved informed consent, blood was collected from 22 patients with metastatic castrate resistant PC (mCRPC). CTC counts were enumerated using CellSearch platforms. Five osseous metastatic lesions were manually segmented from CT scans in the same patients using ITK-SNAP by an experienced radiologist. Cancer imaging phenomics toolkit (CaPTk) was used for radiomics analysis. A panel of 6 metrics representing first-order statistical measures: Intensity and second-order statistical measures: Greylevel cooccurrence matrix (GLCM) were calculated from each segmented lesion per patient. Mixed model correlation was used to examine correlation between weighted average of radiomic features from the five bone lesions per patient and their CTC counts. Benjamini-Hochberg Procedure was used to control false discovery rate from multiple comparisons. RESULTS: The distribution of CTC counts was 102±198 (min: 0, max: 692). Among the 69 texture features extracted from the bone lesions, the weighted average of Intensity-based inter-quartile-range and GLCM-based kurtosis, variance and standard-deviation extracted from the 5 bone lesions per patient showed statistically significant correlation with CellSearch enumerated CTC counts ranged between 0.71 to 0.79 with adjusted p-value < 0.01). Radiomics and liquid biopsy have theoretically comparable advantages: they are both noninvasive, can be quantified and followed serially to evaluate disease progression. While their exact role in clinical practice is yet to be established, we conducted a preliminary integrative assessment of the two, within a small cohort. We show that the weighted average of select radiomic metrics extracted from multiple bone lesions (N=5) provide strong correlates for CTC counts. CONCLUSIONS: Post validation in larger cohorts, radiomic corelates of liquid biopsy parameters such as CTC counts may provide surrogates for assessment of the likelihood of recurrence and metastasis in PC. With the widespread applicability of artificial intelligence in healthcare, diverse information about tumor behavior based on its genotype and phenotype decoded via imaging, may predict treatment failures earlier than with conventional methods. Source of Funding: NCI: 1R01CA257610-01 © 2022 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 207Issue Supplement 5May 2022Page: e769 Advertisement Copyright & Permissions© 2022 by American Urological Association Education and Research, Inc.MetricsAuthor Information Bino Varghese More articles by this author Steven Cen More articles by this author Gareth Morrison More articles by this author Jonathan Buckley More articles by this author Dejerianne Ostrow More articles by this author David Quinn More articles by this author Timothy Triche More articles by this author Amir Goldkorn More articles by this author Vinay Duddalwar More articles by this author Expand All Advertisement PDF DownloadLoading ...