Innovative analytic methods in the imaging of upper tract urothelial carcinoma: Radiomics, Radiogenomics and creation of a new prognostic tool for systemic therapies of UTUC

• Applicant: Dr. Lennert Eismann
• Subject Area: Reproductive Medicine, Urology
• Term: from 2022 to 2023
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 503318851

Upper tract urothelial carcinoma (UTUC) are rare malignant tumors arising from the urothel of the ureter and renal pelvis. Small and superficial lesions can be treated by minimal-invasive kidney sparing surgery. At the time of diagnosis about 60% of UTUC are invasive and require radical surgery. In locally advanced and metastatic disease systemic therapy is recommended. Current diagnostic work-up using CT scan, ureteroscopy with cytology and biopsy is reported with an accuracy of up to 74%. Despite significant advances in diagnostic tools, staging of UTUC is still in need of improvement in regards of grading and invasiveness which is crucial to initiate adequate treatment. Radiomics is a promising imaging-based technique with potential to fill the gap in preoperative work-up. Radiomics extracts data from standard imaging and converts them to clinical useful information. In contrast to conventional analysis of imaging radiomics analyses texture fields, extended shape modeling based on single data points, called voxels. These information are histogram-based statistics and follow the hypothesis to mirror tumor characteristics. Radiomics holds immense potential to predict tumor characteristics such as invasiveness, grading and mutational burden. Consequently, radiomics might allow most accurate staging, prognosticate response to systemic therapy and evaluate risk of progression.The objective of my fellowship is to convert standard radiological information from staging images into more widely useful clinical parameters. The Department of Urology at Memorial Sloan-Kettering Cancer Center (MSKCC) holds a vast database of UTUC patients including clinical and genomic information and corresponding imaging. The collaboration of Urology and Radiology at MSKCC has specialized on radiomics in genitourinary malignanciCes. In the first step I attempt to develop a method of risk stratifying UTUC by using radiomics. Therefore features of the images will be extracted to identify aggressive and infiltrative UTUC. The knowledge of tumor grading and infiltration are crucial to offer either kidney sparing or radical surgery. Secondly, imaging features will be correlated with genomic alterations to identify a genomic footprint of UTUC. Various genetic alterations have been identified to correlate with tumor grading, invasiveness and risk of progression. Therefore, I plan to develop a nomogram to identify low-risk and high-risk patients using radiogenomics. In the third step I will be focusing on imaging-based prediction of response rates to systemic therapy. Therefore, imaging features will be used to develop a risk score to predict treatment response, including relevant clinical information and genetic mutations assessed. According to the risk score probability of treatment response might be predictable. In line with the current literature and first preliminary results radiomics holds high potential to introduce imaging-adapted medicine in clinical practice of UTUC.

• DFG Programme: WBP Fellowship
• International Connection: USA
• Host: Dr. A. Ari Hakimi