Search

Objectives: To develop a radiomics model using preoperative multiphasic CT for predicting distant metastasis after surgical resection in patients with localized clear cell renal cell carcinoma (ccRCC) and to identify key biological pathways underlying the predictive radiomics features using RNA sequencing data. Methods: In this multi-institutional retrospective study, a CT radiomics metastasis score (RMS) was developed from a radiomics analysis cohort (n = 184) for distant metastasis prediction. Using a gene expression analysis cohort (n = 326), radiomics-associated gene modules were identified. Based on a radiogenomics discovery cohort (n = 42), key biological pathways were enriched from the gene modules. Furthermore, a multigene signature associated with RMS was constructed and validated on an independent radiogenomics validation cohort (n = 37). Results: The 9-feature-based RMS predicted distant metastasis with an AUC of 0.861 in validation set and was independent with clinical factors (p < 0.001). A gene module comprising 114 genes was identified to be associated with all nine radiomics features (p < 0.05). Four enriched pathways were identified, including ECM-receptor interaction, focal adhesion, protein digestion and absorption, and PI3K-Akt pathways. Most of them play important roles in tumor progression and metastasis. A 19-gene signature was constructed from the radiomics-associated gene module and predicted metastasis with an AUC of 0.843 in the radiogenomics validation cohort. Conclusions: CT radiomics features can predict distant metastasis after surgical resection of localized ccRCC while the predictive radiomics phenotypes may be driven by key biological pathways related to cancer progression and metastasis. Key Points: • Radiomics features from primary tumor in preoperative CT predicted distant metastasis after surgical resection in patients with localized ccRCC. • CT radiomics features predictive of distant metastasis were associated with key signaling pathways related to tumor progression and metastasis. • Gene signature associated with radiomics metastasis score predicted distant metastasis in localized ccRCC. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate the utility of MR R2*-mapping and the optimal time-point for assessing the response of pulmonary metastatic renal cell carcinoma (mRCC) to anti-angiogenic targeted therapy (aATT).Materials and Methods: The exploration-sample group and the validation-sample group consisted of 22 and 16 patients. The parameters of MR R2*-mapping, including the R2* value at each time-point (R2*base, R2*1cyc and R2*2cyc) and change between different time-points (R2*(1cyc-base)/base, R2*(2cyc-base)/base and R2*(2cyc-1cyc)/1cyc), were evaluated with a receiver-operating-characteristic analysis, and a cut-off value derived from the clinical outcome was applied to the Kaplan-Meier method to assess the value of R2* mapping and Response-Evaluation-Criteria in Solid Tumours (RECIST) during treatment evaluation.Results: The inter-, intra-observer agreements and inter-scan consistency were excellent (p > 0.80). For the exploration-sample group, the areas under the curve for the parameters of MR R2* mapping were 0.55, 0.60, 0.83, 0.64, 0.88 and 0.83 for R2*base, R2*1cyc, R2*2cyc, R2*(1cyc-base)/base, R2*(2cyc-base)/base and R2*(2cyc-1cyc)/1cyc. For the validation-sample, R2*(2cyc-base)/base better predicted progression-free survival (p = 0.03) than RECIST and other R2* mapping parameters with a lower p value.Conclusion: Assessing aATT outcome based on changes in the R2* value between baseline and second treatment is more accurate than assessment at other time-points and assessment based on the RECIST.Key Points: • The inter-scan consistency of R2*-mapping in pulmonary mRCC are excellent. • The intra-/inter-observer agreement of R2* mapping in pulmonary mRCC are excellent. • Using changes in R2* value between baseline/after second-treatment is better than RECIST. • The choice of baseline/after second treatment is better than other time-points. [ABSTRACT FROM AUTHOR]