Objective To assess the use of real-time elastography (RTE) for detecting prostate cancer in patients scheduled for radical prostatectomy (RP), as most solid tumours differ in their consistency from the deriving tissue, and RTE might offer a new tool for cancer detection. Patients and methods We examined 15 patients (mean age 56 years, SD 6.2, range 46-71) with RTE, using an ultrasonography (US) system with a 7.5-MHz transrectal probe as a transducer. RTE is capable of visualizing displacements between pairs of US images of tissues when placed under axial compression. The stiffness of the lesion was displayed from blue (soft) to black (hard). Hard lesions with a diameter of >= 5 mm were considered as malignant. All patients had the diagnosis of prostate cancer confirmed by biopsy and had a mean (range) prostate specific antigen (PSA) level of 4.6 (1.4-16.1) ng/mL; all were scheduled for RP. US was performed by two investigators and interpreted by consensus. Cancer location and size was determined in the RTE mode only. One pathologist classified tumour location, grade and stage. The RTE findings were compared with the pathological findings. Results There were no major complications during RP in any patient; all had a pT2 tumour on histopathological examination, the Gleason score was 5-9 and the mean (range) tumour size 1.1 (0.6-2.5) cm. Thirty-five foci of prostate cancer were present at the pathological evaluation; multiple foci were found in 11 of the 15 glands. RTE detected 28 of 35 cancer foci (sensitivity 80%). The per-patient analysis showed that RTE detected at least one cancer area in each of the 15 patients. Only four sites with false-positive findings on RTE and no histopathological correlation were detected; these findings were obtained in the first five patients (period of learning). Conclusions RTE can be used to visualize differences in tissue elasticity. Our results show that RTE allows the detection of prostate cancer and estimation of tumour location and size. RTE of the prostate is a new imaging method with great potential for detecting prostate cancer.
Useful keywords (using NLM MeSH Indexing)
Predictive Value of Tests
Sensitivity and Specificity
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