Abstract
Abstract Background: CDK 4/6 inhibitors (CDKI) with Endocrine therapy (ET) is mainstay treatment for hormone receptor-positive (HR+) Her2- metastatic breast cancer (MBC). Despite excellent efficacy, most patients develop resistance to CDKI limiting its utility. CDK4/6 are thought to act by upregulating VEGF causing tortuous angiogenesis and promoting cancer progression. Recent studies have shown aggressive tumors possess a higher density and tortuous vasculature. In this study, we evaluated if vascular radiomic features computationally extracted from liver CT scans pre- and post CDKI treatment could predict patient survival and treatment response. Method: From a registry of 350 patients on treatment with CDKI at institution 1(S1), 51 pts with HR+, Her2-, MBC patients with evidence of liver mets and disease progression (PFS) data were identified. 30 pts discontinued treatment due to progression or death, with a median time to progression of 195 days. Pre-treatment and first post-treatment CT exams were analyzed from 25 and 34 patients, respectively. Median time between scans was 128 days. To validate the prognostic value of our signature, a cohort of 29 patients with available OS data was identified from institution 2 (S2). A publicly available pre-trained deep learning model was applied to isolate liver metastases and vessels. Next, fast marching algorithm was applied to reduce vessels to their centerlines and divide the vasculature into constituent branches. 7 quantitative metrics were computed measuring vascularity of metastases and 3-D shape of hepatic vessels. First, the number (f1) and percentage (f2) of hepatic vessels arising from the tumor were computed. Vessel tortuosity - measuring the degree of twisting across a vessel - was computed separately for each branch. The mean (f3), standard deviation (f4), maximum (f5), skewness (f6), and kurtosis (f7) tortuosity values were calculated to summarize these measurements at patient level. The features were individually assessed at pre- and post-treatment for association with PFS at S1 in univariable Cox proportional hazards models. Features found to be associated in S1 were evaluated for association with OS in S2. Results: On the initial post-treatment scan, features of both tumor vascularization (f6 - HR=1.115 [1.039-1.196]; f7 - HR=10.646 [2.539-44.641]), as well as two features of vessel tortuosity (f3 - HR=0.011 [0.001-0.199]; f4 - HR=0.545 [0.313-0.949]) were significantly associated with PFS. Both tortuosity features were also significantly associated with OS in S2 (f3 - HR=0.085 [0.009-0.780]; f4 - HR=0.331 [0.130-0.842]). In addition the percentage (f7 - HR=6.445 [2.001-20.753]]),of vessels feeding the lesions was also significant in S2 while the number (f6 - HR=1.070 [0.966-1.184]), of vessels was not. No vessel metrics from the pre-treatment baseline exam were significantly associated with OS. Conclusions: Radiomic analysis of tumor vascularity and vessel tortuosity on CT scans post-CDK treatment was associated with patient survival and treatment response. Table 1.Association of vessel features with PFS in Institution 1(S1)and OS in Institution 2(S2)S1- Pretreatment CT (n=25)S1 - Post-Treatment CT (n=34)S2 - Post-treatment CT - Validation (n=29)f1Tortuosity - Mean0.9912702470.852294696–f2Tortuosity - St. Dev0.7563942230.273115373–f3Tortuosity - Max0.1387051870.0022517550.02931473f4Tortuosity - Skewness0.254463710.0318270370.02022882f5Tortuosity - Kurtosis0.3058266760.108967601–f6Number of vessels feeding lesions0.419096650.0025747910.19306052f7Percentage of vessels feeding lesions0.0517942660.0012205950.00179103 Citation Format: Vidya Sankar Viswanathan, Nathaniel Braman, Priyanka Reddy, Siddharth Kunte, Jame Abraham, Alberto J Montero, Anant Madabhushi. Post-treatment vascularity and vessel shape are associated with survival and response to CDK4/6 inhibitors in hormone receptor-positive metastatic breast cancer (MBC) [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P5-13-27.
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