Shear-Wave Elastography for Detection of Prostate Cancer: A Systematic Review and Diagnostic Meta-Analysis

Advances in prostate cancer imaging

Many exciting advances in medical imaging have been made in recent years that will alter the way we diagnose, stage, and treat patients with prostate cancer. Multiparametric magnetic resonance imaging (MRI) is emerging as the main modality for prostate cancer imaging. Contrast-enhanced ultrasound and shear wave elastography may be strong alternatives in patients who cannot undergo MRI. Prostate-specific membrane antigen-directed positron emission tomography/computed tomography has proven to be valuable in the primary staging of high-risk disease and for detecting disease in patients with biochemical recurrence. As more studies continue to emerge, it is becoming clear that the standard algorithm for diagnosing and staging prostate cancer will undergo significant changes in the near future.

Machine learning for medical ultrasound: status, methods, and future opportunities

Ultrasound (US) imaging is the most commonly performed cross-sectional diagnostic imaging modality in the practice of medicine. It is low-cost, non-ionizing, portable, and capable of real-time image acquisition and display. US is a rapidly evolving technology with significant challenges and opportunities. Challenges include high inter- and intra-operator variability and limited image quality control. Tremendous opportunities have arisen in the last decade as a result of exponential growth in available computational power coupled with progressive miniaturization of US devices. As US devices become smaller, enhanced computational capability can contribute significantly to decreasing variability through advanced image processing. In this paper, we review leading machine learning (ML) approaches and research directions in US, with an emphasis on recent ML advances. We also present our outlook on future opportunities for ML techniques to further improve clinical workflow and US-based disease diagnosis and characterization.

Principles of ultrasound elastography

Tissue stiffness has long been known to be a biomarker of tissue pathology. Ultrasound elastography measures tissue mechanical properties by monitoring the response of tissue to acoustic energy. Different elastographic techniques have been applied to many different tissues and diseases. Depending on the pathology, patient-based factors, and ultrasound operator-based factors, these techniques vary in accuracy and reliability. In this review, we discuss the physical principles of ultrasound elastography, discuss differences between different ultrasound elastographic techniques, and review the advantages and disadvantages of these techniques in clinical practice.

The role of real-time elastography-targeted biopsy in the detection and diagnosis of prostate cancer: A systematic review and meta-analysis

BACKGROUND

The role of real-time elastography (RTE)-targeted biopsy in the detection and diagnosis of prostate cancer (PCa) remains controversial.

METHODS

We searched Medline, Embase, and Cochrane Library from inception to July 31, 2017 and used the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool to assess the quality of the identified studies. We applied the relative sensitivity value to assess the diagnostic accuracy of RTE-targeted biopsy using the 10-core systematic biopsy as the reference standard.

RESULTS

Seven studies comprising 5 cohorts and 2 randomized controlled trials (RCTs) were included. Of the 5 cohorts that encompassed 698 participants, we found that RTE-targeted biopsy did not outperform systematic biopsy in either overall PCa detection (69.5% vs 80.5%, relative sensitivity 0.92, 95% CI 0.80-1.06) or for the initial biopsy (56.8% vs 64.0%, relative sensitivity 0.93, 95% CI 0.79-1.11). For the core-by-core analysis, more positive cores were detected by RTE-targeted biopsy than systematic biopsy (21% vs 11%, relative sensitivity 2.17, 95% CI 1.61-2.95). The 2 RCTs showed a favorable trend toward greater PCa detection when a combination of systematic biopsies and RTE-targeted biopsies was used than when systematic biopsy alone was used (45.5% vs 39.5%, risk ratio (RR) 1.18, 95% CI 0.98-1.43).

CONCLUSION

Currently, there is not enough evidence to demonstrate that RTE-targeted biopsy can outperform systematic biopsy, but the combination of systematic and RTE-targeted biopsy may be a promising approach for improving PCa detection.