AI Article Synopsis

  • Multiparametric magnetic resonance imaging (mpMRI) enhances prostate cancer diagnosis by minimizing unnecessary biopsies and improving accuracy, but systematic biopsies are still recommended due to mpMRI's 15-20% false negative rate.
  • New advanced imaging techniques like elastography and contrast-enhanced ultrasound, along with the emerging multiparametric ultrasound (mpUS) and micro-ultrasound (MicroUS), show better sensitivity and specificity for detecting prostate cancer.
  • The study highlights the role of innovative imaging methods and the potential transformative impact of artificial intelligence on radiology and pathology in the future of prostate cancer diagnosis and treatment.

Article Abstract

Multiparametric magnetic resonance imaging (mpMRI) has improved systematic prostate biopsy procedures in the diagnosis of clinically significant prostate cancer (csPCa) by reducing the number of unnecessary biopsies; numerous level one evidence studies have confirmed the accuracy of MRI-targeted biopsy, but, still today, systematic prostate biopsy is recommended to reduce the 15-20% false negative rate of mpMRI. New advanced imaging has been proposed to detect suspicious lesions and perform targeted biopsies especially when mpMRI cannot be performed. Transrectal ultrasound (TRUS) modalities are emerging as methods with greater sensitivity and specificity for the detection of PCa compared to the traditional TRUS; these techniques include elastography and contrast-enhanced ultrasound, as well as improved B-mode and Doppler techniques. These modalities can be combined to define a novel ultrasound approach: multiparametric ultrasound (mpUS). More recently, micro-ultrasound (MicroUS) and prostate-specific membrane antigen (PSMA) positron emission tomography/computed tomography (PET/CT) have demonstrated to be sensitive for the detection of primary prostatic lesions resulting highly correlated with the aggressiveness of the primary prostatic tumor. In parallel, artificial intelligence is advancing and is set out to deeply change both radiology and pathology. In this study we address the role, advantages and shortcomings of novel imaging techniques for Pca, and discuss future directions including the applications of artificial intelligence-based techniques to imaging as well as histology. The significance of these findings for the practicing pathologist is discussed.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10938278PMC
http://dx.doi.org/10.32074/1591-951X-925DOI Listing

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