journal article·2021-07-28Open access

Current Imaging Evaluation of Tumor Response to Advanced Medical Treatment in Metastatic Renal-Cell Carcinoma: Clinical Implications

Martina Caruso, Valeria Romeo, Arnaldo Stanzione, Carlo Buonerba, Giuseppe Di Lorenzo, Simone Maurea

Applied Sciences· Volume 11· Issue 15

Abstract

The present review is focused on the role of diagnostic tomographic imaging such as computed tomography and magnetic resonance imaging to assess and predict tumor response to advanced medical treatments in metastatic renal cell carcinoma (RCC) patients. In this regard, antiangiogenic agents and immune checkpoint inhibitors (ICIs) have developed as advanced treatment options replacing the conventional therapy based on interferon-alpha and interleuchin-2 which had unfavorable toxicity profile and low response rates. In clinical practice, the imaging evaluation of treatment response in cancer patients is based on dimensional changes of tumor lesions in sequential scans; in particular, Response Evaluation Criteria in Solid Tumors (RECIST) have been defined for this purpose and also applied in patients with metastatic RCC. However, these new drugs with predominant cytostatic effect make RECIST insufficient to realize an adequate response imaging evaluation. Therefore, new imaging criteria (mCHOI and iRECIST) have been proposed to assess tumor response to advanced medical treatments of metastatic RCC, they correlate better than RECIST with the progression-free survival and overall survival. Finally, a potential role of radiomics and machine learning models has been suggested to predict tumor response.
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Research context

OpenAlex topics: Radiomics and Machine Learning in Medical Imaging · Renal cell carcinoma treatment · Advanced X-ray and CT Imaging

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Advanced Biomedical Sciences, University of Naples “Federico II”, Via S. Pansini, 5, 80131 Naples, Italy

Regional Reference Center for Rare Tumors, Department of Oncology and Hematology, AOU “Federico II” of Naples, Via S. Pansini, 5, 80131 Naples, Italy

Oncology Unit, Andrea Tortora Hospital, ASL Salerno, 84016 Pagani, Italy

Vincenzo Tiberio, Department of Medicine & Health Sciences, University of Molise, 86100 Campobasso, Italy

References (42)

Show source-provided references
1. Epidemiology of renal cell carcinoma10.14740/wjon1279 ↗
2. Management of the incidental renal mass 110.1148/radiol.2491070783 ↗
3. Renal cell carcinoma10.1038/nrdp.2017.9 ↗
4. Surveillance after radical or partial nephrectomy for localized renal cell carcinoma and management of recurrent disease10.1016/S0094-0143(03)00056-9 ↗
5. Metastatic renal cell carcinoma: Radiologic findings and assessment of response to targeted antiangiogenic therapy by using multidetector CT10.1148/rg.336125110 ↗
6. An update on targeted therapy in metastatic renal cell carcinoma
7. Lenvatinib, everolimus, and the combination in patients with metastatic renal cell carcinoma: A randomised, phase 2, open-label, multicentre trial10.1016/S1470-2045(15)00290-9 ↗
8. Tumor angiogenesis: Pathophysiology and implications for contrast-enhanced MRI and CT assessment10.1007/s00261-005-0386-5 ↗
9. Jonasch, E., Gao, J., and Rathmell, W.K. (2014). Renal cell carcinoma. BMJ, 349.10.1136/bmj.g4797 ↗
10. Advanced renal cell carcinoma: Role of the radiologist in the era of precision medicine10.1148/radiol.2017160343 ↗
11. Pembrolizumab plus axitinib versus sunitinib for advanced renal-cell carcinoma10.1056/NEJMoa1816714 ↗
12. Sequencing and combination of systemic therapy in metastatic renal cell carcinoma10.1016/j.euo.2019.06.022 ↗
13. Imaging of tumour response to immunotherapy10.1186/s41747-019-0134-1 ↗
14. T cell memory against colon carcinoma is long-lived in the absence of antigen10.4049/jimmunol.163.7.3676 ↗
15. Nivolumab versus everolimus in advanced renal-cell carcinoma10.1056/NEJMoa1510665 ↗
16. Imaging for metastatic renal cell carcinoma10.1016/j.ucl.2020.04.005 ↗
17. New response evaluation criteria in solid tumours: Revised RECIST guideline (version 1.1)10.1016/j.ejca.2008.10.026 ↗
18. The role of response evaluation criteria in solid tumour in anticancer treatment evaluation: Results of a survey in the oncology community10.1016/j.ejca.2013.10.011 ↗
19. Radiomics: Images are more than pictures, they are data10.1148/radiol.2015151169 ↗
20. MRI radiomics for the prediction of fuhrman grade in clear cell renal cell carcinoma: A machine learning exploratory study10.1007/s10278-020-00336-y ↗
21. Khene, Z.-E., Mathieu, R., Peyronnet, B., Kokorian, R., Gasmi, A., Khene, F., Rioux-Leclercq, N., Kammerer-Jacquet, S.F., Shariat, S., and Laguerre, B. (2020). Radiomics can predict tumour response in patients treated with Nivolumab for a metastatic renal cell carcinoma: An artificial intelligence concept. World J. Urol., 3–5.10.1007/s00345-020-03334-5 ↗
22. Pretreatment assessment of tumor enhancement on contrast-enhanced computed tomography as a potential predictor of treatment outcome in metastatic renal cell carcinoma patients receiving antiangiogenic therapy10.1002/cncr.25019 ↗
23. Pathological evidence of necrosis in recurrent renal mass following treatment with sunitinib10.1111/j.1442-2042.2007.01902.x ↗
24. Assessing tumor response and detecting recurrence in metastatic renal cell carcinoma on targeted therapy: Importance of size and attenuation on contrast-enhanced CT10.2214/AJR.09.2941 ↗
25. Correlation of computed tomography and positron emission tomography in patients with metastatic gastrointestinal stromal tumor treated at a single institution with imatinib mesylate: Proposal of new computed tomography response criteria10.1200/JCO.2006.07.3049 ↗
26. Revised choi imaging criteria correlate with clinical outcomes in patients with metastatic renal cell carcinoma treated with sunitinib10.1148/radiol.14132702 ↗
27. Perfusion MDCT enables early detection of therapeutic response to antiangiogenic therapy10.2214/AJR.07.2848 ↗
28. Computed tomography perfusion imaging for therapeutic assessment: Has it come of age as a biomarker in oncology?10.1097/RLI.0b013e318229ff3e ↗
29. Guidelines for the evaluation of immune therapy activity in solid tumors: Immune-related response criteria10.1158/1078-0432.CCR-09-1624 ↗
30. Pseudoprogression in previously treated patients with non–small cell lung cancer who received nivolumab monotherapy10.1016/j.jtho.2018.10.167 ↗
31. Hyperprogressive disease in patients with advanced non-small cell lung cancer treated with PD-1/PD-L1 inhibitors or with single-agent chemotherapy10.1001/jamaoncol.2018.3676 ↗
32. Hyperprogressive disease is a new pattern of progression in cancer patients treated by anti-PD-1/PD-L110.1158/1078-0432.CCR-16-1741 ↗
33. Developing a common language for tumor response to immunotherapy: Immune-related response criteria using unidimensional measurements10.1158/1078-0432.CCR-13-0895 ↗
34. iRECIST: Guidelines for response criteria for use in trials testing immunotherapeutics10.1016/S1470-2045(17)30074-8 ↗
35. Which criteria should we use to evaluate the efficacy of immune-checkpoint inhibitors?10.21037/atm.2018.04.17 ↗
36. Avelumab plus axitinib versus sunitinib for advanced renal-cell carcinoma10.1056/NEJMoa1816047 ↗
37. Metastatic renal carcinoma: Evaluation of antiangiogenic therapy with dynamic contrast-enhanced CT10.1148/radiol.10091362 ↗
38. Pilot study of DCE-MRI to predict progression-free survival with sorafenib therapy in renal cell carcinoma10.4161/cbt.7.4.5624 ↗
39. Nathan, P.D., Vinayan, A., Stott, D., Juttla, J., and Goh, V. (2010). CT response assessment combining reduction in both size and arterial phase density correlates with time to progression in metastatic renal cancer patients treated with targeted therapies. Cancer Biol. Ther., 9.10.4161/cbt.9.1.10340 ↗
40. Assessment of response to tyrosine kinase inhibitors in metastatic renal cell cancer: CT texture as a predictive biomarker10.1148/radiol.11110264 ↗
41. Romagnoli, G., Wiedermann, M., Hübner, F., Wenners, A., Mathiak, M., Röcken, C., Maass, N., Klapper, W., and Alkatout, I. (2017). Morphological evaluation of tumor-infiltrating lymphocytes (TILs) to investigate invasive breast cancer immunogenicity, reveal lymphocytic networks and help relapse prediction: A retrospective study. Int. J. Mol. Sci., 18.10.3390/ijms18091936 ↗
42. A radiomics approach to assess tumour-infiltrating CD8 cells and response to anti-PD-1 or anti-PD-L1 immunotherapy: An imaging biomarker, retrospective multicohort study10.1016/S1470-2045(18)30413-3 ↗