Detecting Prostate Cancer

Prostate Cancer is a high incidence cancer in men with a small percentage being very aggressive and potentially lethal. PSA has been used for over two decades and despite the USPTF negative stand it still finds use, especially in men with a family history of aggressive PCa.

However the next step in diagnosis is a biopsy, and the classic multi core approach has its own problems. Namely it samples at best 2-3% of the prostate and for early stage PCa this may not be adequate.

Fused MRI and TRUS is now coming of age and is used more frequently. In a recent paper by Bodman et al the authors have examined the performance of such tests.

They report:

MRI/TRUS fusion–assisted targeted biopsy improves the detection rate of prostate cancer after a previous negative biopsy. Targeted biopsy is more likely to reveal clinically significant cancer than systematic biopsy; nevertheless, systematic biopsy should still be performed, even if the MRI findings are negative...The MRI/TRUS fusion biopsy approach is a promising method for detecting prostate cancer after a prior negative histological result. Combining MRI-guided targeted biopsies of suspicious lesions with a systematic 12-core biopsy protocol increases the overall cancer detection rate and leads to more clinically relevant cancers being found. Our data suggests that taking additional fusion-guided biopsies from lesions with a low risk score, based on MRI analysis,  is not necessary.

Systematic biopsy remains necessary even when MRI results in inconspicuous images. The strategy of a single targeted biopsy without a systematic biopsy is not to be recommended. MRI-guided   fusion biopsy holds great promise for the future but must still undergo careful verification. As no unified technical standardization or systematic training exist for this method to date, a high amount of examiner experience is necessary. Finally, because the MRI/TRUS fusion strategy has not yet been considered in the current S3 guidelines for primary diagnosis of prostate cancer, the value of this method should be analyzed in large multicenter studies.

Overall the results indicated:

Grayscale TRUS: Senstivity % 18.3, Specificity % 90.4
MRI/TRUS: Senstivity % 58, Specificity % 93

This can be a substantial improvement. It would be useful to have a similar model as we had developed for Grayscale TRUS using a Bayesian model.