Multiparametric Ultrasound of the Prostate

Prostate cancer (PCa) is the second most prevalent cancer in men and has the potential to develop metastasis and become life-threatening. Therefore, early and accurate detection of clinically significant (cs)PCa is key to optimizing treatment outcomes and lowering both mortality and morbidity.

With tumor progression, factors such as increased cellular proliferation, neoangiogenesis, and loss of differentiation in the tumor cells result in physiological tissue changes. These changes can be characterized using one of many ultrasound (US) modalities: B-mode provides structural and textural information, Doppler and contrast-enhanced US reveal vascularization, and elastography assesses tissue stiffness. While independently, the different modalities have shown promise in detecting PCa, when combined into multiparametric (mp)US, the performance in detecting PCa has greatly improved.

Protocols adding targeted biopsies are more sensitive to csPCa than systematic biopsy alone, thus missing fewer cancerous tumors. Acquisitions using mpUS have the advantage of being close to real-time and need minimal tissue registration thanks to current dynamic 3D imaging systems.

Computerized tools (such as machine learning models) can be used when the dimensionality of the mpUS data becomes too demanding to cognitively combine the parameters. In that case, a probabilistic map of the prostate is usually produced, reflecting the local likelihood of malignancy.

The recent advances in mpUS have painted it as a valuable tool for the detection of PCa in clinical practice. There, its cost-effective acquisitions paired with accurate cancer detection systems are expected to make it a very compelling tool for screening and PCa diagnostics. This chapter will provide insights into the developments of separate US modalities, which are often combined for mpUS imaging of the prostate.