The combination of multiparemetric imaging with cutting-edge image processing has gained momentum for pre-surgical treatment planning. Anatomy based therapy planning for suspected and verified tumors has been recently supplemented with information on tumor metabolism or specific tumor markers, such as PSMA in case of prostate cancer. Furthermore, additional tissue characteristics like cell density and blood flow augment the analysis and planning before surgery.
Beyond these features, supplementary methods for in-depth image analysis were recently introduced to combine and capture textural features (Radiomics) with additional information form MRI and PET-imaging (mpRadiomics). Machine learning approaches with big data are applied to derive prognostic relevant information for future patient care. These topics are currently of high research interest.
Biopsy planning for suspected prostate-cancer
The combination of multiparametric MRI (mpMRI) with ultrasound for trans-rectal ultrasound guided (TRUS) biopsy has been established in recent years. Additional relevant information for biopsy planning can be collected by combining mpMRI and prostate specific membrane antigen (PSMA)-PET-imaging (mpPET/MRI), especially in complex cases or after negative biopsy but high clinical suspicion for the presence of prostate cancer. These examinations add information on PSMA-expression on prostate cancer cells and takes only marginally longer than mpMRI alone.
Combining multiparametric MRI (mpMRI) and information on glucose metabolism from FDG-PET can add relevant information in urinary bladder cancer on aggressive tumor parts and infiltration of deep muscle layers. This combined examination can be offered for specific cases in pre-operative planning. The multiparametric analysis can be conducted on a voxel- level (smallest unit of information).