## 3 Imaging Evaluation of Therapy Response in Metastatic RCC  
In oncology, imaging is widely employed to assess treatment response and guide patient management [16]. CT represents an accurate imaging modality for this purpose,often preferred to MRI because its total-body acquisition allows to detect potential distant metastases. Usually, the imaging assessment of treatment response or disease progression in cancer patients is performed by dimensional evaluation of tumor burden in consecutive scans; in particular, Response Evaluation Criteria in Solid Tumors (RECIST) have been embraced for this purpose and also applied in patients with metastatic RCC [17]. Of note, these criteria have been proposed to standardize and objectively assess solid tumor measurements both in adult and pediatric cancer clinical trials where tumor response is required. As a consequence, in daily clinical practice many oncologists have adopted these criteria to evaluate imaging studies during the follow-up, but physicians make decisions about treatment strategies also considering clinical criteria. In detail, RECIST identifies measurable and non-measurable tumor lesions with the former including lesions having a longest diameter of \(\geq\)10 mm and the latter including small lesions (\(\leq\)10 mm), skeletal metastases, leptomeningeal disease, ascites, pleural and pericardial effusions. Hence, for the assessment of treatment response target and non-target lesions are usually identified with the former represented by measurable lesions, up to a maximum of five total lesions as well as a maximum of two lesions per organ, and the latter including all tumor lesions not chosen as target lesions. On the basis of dimensional lesion changes during the follow-up, the disease is classified as stable, in progression, with partial or complete response. Nowadays, the introduction of innovative drugs with predominant cytostatic effect makes RECIST, dimensional criteria, insufficient to get an adequate response imaging evaluation. First of all, they do not include early indicators of tumor response; of note, the anatomic assessment may take more time to detect any shrinkage unlike use of functional hybrid imaging exams, that may show tumor changes earlier. Secondly, RECIST do not have a clinical validation to be used in the response assessment to novel agents; surprisingly, a low response rate has been reported for many patients with metastatic RCC, despite a higher numbers of cases with prolonged stable disease and improved survival compared to conventional treatment protocols [10]. Hence, RECIST might underestimate the tumor response to these innovative drugs as well as the RECIST system does not include recent advanced imaging techniques, frequently considered in clinical trials, able to assess tumor micro-environment and atypical tumor response patterns which may occur using antiangiogenic agents and/or ICIs [18]. Therefore, considering these aforementioned limitations of RECIST, the widespread of advanced targeted therapies and the need to answer to specific clinical issues, new imaging criteria are needed. Moreover, going beyond the visual image evaluation, the emergence of radiomics has shown the potential to further increase the value of CT and MRI for treatment response assessment [19]. Radiomics is a complex multi-step process that aims to extract a large number of quantitative features from digital medical images, allowing to quantitatively explore tumor heterogeneity which reflects its underlying pathophysiology. Radiomic features integrated or not with clinical data can be used to build machine learning models which can potentially aid the physicians in clinical practice by improving diagnostic, prognostic, and predictive accuracy [19]. In particular, texture analysis features assess the spatial distribution of pixel intensity levels within an image, the obtained quantitative data reflect the image heterogeneity.