Advancements in Prostate Cancer Imaging: Implications for Diagnosis and Treatment

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Yogesh R. Jadhav, Abhijeet Ravindranath Katkar, Asitkumar Lalankumar Choudhary, Sachin Shrimantrao MisalSenior, Aparna Patange

Abstract

The diagnostic and therapeutic approaches for prostate cancer have been completely transformed by the developments in imaging technology. The development of imaging modalities, such as positron emission tomography (PET) and multiparametric magnetic resonance imaging (mpMRI), is examined in this overview, with an emphasis on the diagnostic value of each and the consequences for treatment choices. These methods help with risk assessment and biopsy guiding by providing improved sensitivity and specificity in the detection and characterization of prostate lesions. Focal treatment and image-guided radiation therapy are two examples of imaging-guided therapies that take advantage of accurate lesion location to maximise therapeutic methods and minimise adverse effects. Furthermore, even at lower prostate-specific antigen (PSA) levels, the incorporation of new molecular imaging tracers—in particular, PSMA ligands—has revolutionised staging accuracy and treatment response evaluation.


Notwithstanding these developments, standardisation, affordability, and accessibility issues still exist, impeding wider use. It is important to tackle these obstacles in order to guarantee fair and consistent imaging procedures. Prospective avenues for advancement include the utilisation of cutting-edge technology such as artificial intelligence (AI) to enhance diagnostic precision and customise treatment plans. This thorough analysis highlights the revolutionary effects of cutting-edge imaging modalities on the treatment of prostate cancer and highlights the necessity of teamwork in order to overcome obstacles and improve patient care pathways.

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How to Cite
Yogesh R. Jadhav, et al. (2023). Advancements in Prostate Cancer Imaging: Implications for Diagnosis and Treatment. International Journal on Recent and Innovation Trends in Computing and Communication, 11(8), 479–484. https://doi.org/10.17762/ijritcc.v11i8.9438
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