Molecular Imaging of Newly Diagnosed Prostate Cancer

Detecting localised prostate cancer using radiomic features in PSMA PET and multiparametric MRI for biologically targeted radiation therapy

BACKGROUND

Prostate-Specific Membrane Antigen (PSMA) PET/CT and multiparametric MRI (mpMRI) are well-established modalities for identifying intra-prostatic lesions (IPLs) in localised prostate cancer. This study aimed to investigate the use of PSMA PET/CT and mpMRI for biologically targeted radiation therapy treatment planning by: (1) analysing the relationship between imaging parameters at a voxel-wise level and (2) assessing the performance of radiomic-based machine learning models to predict tumour location and grade.

METHODS

PSMA PET/CT and mpMRI data from 19 prostate cancer patients were co-registered with whole-mount histopathology using an established registration framework. Apparent Diffusion Coefficient (ADC) maps were computed from DWI and semi-quantitative and quantitative parameters from DCE MRI. Voxel-wise correlation analysis was conducted between mpMRI parameters and PET Standardised Uptake Value (SUV) for all tumour voxels. Classification models were built using radiomic and clinical features to predict IPLs at a voxel level and then classified further into high-grade or low-grade voxels.

RESULTS

Perfusion parameters from DCE MRI were more highly correlated with PET SUV than ADC or T2w. IPLs were best detected with a Random Forest Classifier using radiomic features from PET and mpMRI rather than either modality alone (sensitivity, specificity and area under the curve of 0.842, 0.804 and 0.890, respectively). The tumour grading model had an overall accuracy ranging from 0.671 to 0.992.

CONCLUSIONS

Machine learning classifiers using radiomic features from PSMA PET and mpMRI show promise for predicting IPLs and differentiating between high-grade and low-grade disease, which could be used to inform biologically targeted radiation therapy planning.

MicroRNAs as clinical tools for diagnosis, prognosis, and therapy in prostate cancer

Prostate cancer (PCa) is one of the most commonly diagnosed cancers among men worldwide. Despite the presence of accumulated clinical strategies for PCa management, limited prognostic/sensitive biomarkers are available to follow up on disease occurrence and progression. MicroRNAs (miRNAs) are small non-coding RNAs that control gene expression through post-transcriptional regulation of their complementary target messenger RNA (mRNA). MiRNAs modulate fundamental biological processes and play crucial roles in the pathology of various diseases, including PCa. Multiple evidence proved an aberrant miRNA expression profile in PCa, which is actively involved in the carcinogenic process. The robust and pleiotropic impact of miRNAs on PCa suggests them as potential candidates to help more understand the molecular landscape of the disease, which is likely to provide tools for early diagnosis and prognosis as well as additional therapeutic strategies to manage prostate tumors. Here, we emphasize the most consistently reported dysregulated miRNAs and highlight the contribution of their altered downstream targets with PCa hallmarks. Also, we report the potential effectiveness of using miRNAs as diagnostic/prognostic biomarkers in PCa and the high-throughput profiling technologies that are being used in their detection. Another key aspect to be discussed in this review is the promising implication of miRNAs molecules as therapeutic tools and targets for fighting PCa.

Prostate cancer

The management of prostate cancer continues to evolve rapidly, with substantial advances being made in understanding the genomic landscape and biology underpinning both primary and metastatic prostate cancer. Similarly, the emergence of more sensitive imaging methods has improved diagnostic and staging accuracy and refined surveillance strategies. These advances have introduced personalised therapeutics to clinical practice, with treatments targeting genomic alterations in DNA repair pathways now clinically validated. An important shift in the therapeutic framework for metastatic disease has taken place, with metastatic-directed therapies being evaluated for oligometastatic disease, aggressive management of the primary lesion shown to benefit patients with low-volume metastatic disease, and with several novel androgen pathway inhibitors significantly improving survival when used as a first-line therapy for metastatic disease. Research into the molecular characterisation of localised, recurrent, and progressive disease will undoubtedly have an impact on clinical management. Similarly, emerging research into novel therapeutics, such as targeted radioisotopes and immunotherapy, holds much promise for improving the lives of patients with prostate cancer.