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Chapter 11 trial, where patients with primary prostate cancer (non-metastatic on PET) are treated based on predictions from clinical nomograms versus predictions from machine learning-based radiomics analysis (Figure 11.1). Such a trial (aimed at proving non-inferiority) would need to utilize a hard clinical endpoint, such as time to biochemical recurrence, and/or time to castration-resistant disease. In mCRPC, the main current role seems to be selection of patients amenable to PSMA-radioligand therapy (177Lu or 225Ac) and follow-up imaging during and after these treatments (45,64). Response assessment is especially promising, since the repeatability of whole body quantitative PET parameters is very high as we show in Chapter 5. For other treatments, such as taxane chemotherapy and androgen-axis inhibitors, the benefit of quantitative PSMA PET-CT for response assessment over basic measures such as PSA remains to be shown (46,65). This needs to include a more elaborate investigation of the flare phenomenon that maybe present during AR-targeted therapy (66,67). Also, the superiority in assessment of treatment response using PSMA PET-CT versus standard imaging modalities (bone scintigraphy and diagnostic CT) has not yet been established. Finally, we may briefly speculate about the use of PSMA PET-CT in development of drugs that target PSMA, such as the PMPA-2 PSMA inhibitor (53). Pre-clinical data have shown that inhibiting PSMA has a therapeutic effect, but these drugs have not yet been clinically tested (53). If phase I trials are to be performed, they should use PSMA PET-CT to evaluate treatment targeting, preferably using quantitative analysis to assess heterogeneity of drug targeting between (or even within) lesions. The treatment paradigm for mCRPC has shifted toward androgen receptor (AR) axis-targeted treatments. As [18F]FDHT specifically targets the AR, it has been shown to be very prognostic and may also be predictive for these treatments(24). For [18F]FDHT PET-CT, response assessment in mCPRC is mostly limited to abiraterone as this drug does not directly bind the AR (68). Prognostication, on the other hand, can be performed for all treatment types. Especially for AR-targeted treatments, [18F]FDHT PET biomarkers will be useful as it can be used to assess intrapatient heterogeneity of AR-expression, potentially identifying AR-mutant lesions, or lesions harboring AR-splice variants (69,70). A limitation of [18F]FDHT PET is its poor biodistribution, presence of metabolites, and the need for dynamic imaging; all rendering routine clinical use unlikely (10). We recommend that [18F]FDHT PET quantification should be used as a tool in clinical trials aiming to identify AR-mutant lesions for biopsy targeting to identify novel molecular prostate cancer subtypes. 218