To evaluate the effectiveness of prostate cancer detection with method of cognitive mpMRI/TRUS fusion biopsy using strain sonoelastography. Materials and methods. Cognitive transrectal fusion biopsy of prostate was performed in 32 patients. According to the data of a preliminary conducted mpMRI, 33 foci suspicious of prostate cancer were included (PIRADSv2 = 3-5). Before the biopsy, all patients underwent ultrasound planning using compression sonoelastography. Results. The overall sensitivity was 76% for the targeted biopsy, and 49% for systematic biopsy. The number of biopsy specimens with a clinically significant Gleason grade in the targeted biopsy group was 85% of all columns with cancer specimens, in the systematic biopsy group this number was 68%. On average, the Gleason grade after targeted biopsy was 7.5 ± 0.9, and it was 7.2 ± 0.9 in the columns after systematic biopsy. On average, the percentage of tumor in the columns after targeted biopsy was 72% ± 29% and it was 55% ± 35% in the columns after systematic biopsy. The false positive for mpMRI was 15%. The overall sensitivity for the strain sonoelastography was 69% in this study, clinically significant cancer was detected in 71% of all columns with cancer specimens. False positive for elastography was observed in 18% of cases. Conclusion. Comparing with systematic biopsy, cognitive mpMRI / TRUS fusion biopsy can improve the detection rate of clinically significant prostate cancer and reduce the number of detected cases of clinically insignificant cancer. In cases of a total or subtotal tumor lesion in the peripheral zone detected on mpMRI, it is possible to take fewer columns for morphological verification of the tumor. The use of compression sonoelastography as an additional parameter of navigation in cognitive mpMRI/TRUS fusion biopsy can be considered as a promising way to increase the detection rate of clinically significant prostate cancer.
Translated title of the contributionCOGNITIVE MPMRI/TRUS BIOPSY OF THE PROSTATE WITH USING STRAIN ELASTOGRAPHY
Original languageRussian
Pages (from-to)100-108
JournalМЕДИЦИНСКАЯ ВИЗУАЛИЗАЦИЯ
Volume23
Issue number2
StatePublished - 2019

ID: 51559151