OBJECTIVE: To investigate the value of dynamic contrast-enhanced (DCE)-ultrasonography (US) and software-generated parametric maps in predicting biopsy outcome and their potential to reduce the amount of negative biopsy cores. MATERIALS AND METHODS: For 651 prostate biopsy locations (82 consecutive patients) we correlated the interpretation of DCE-US recordings with and without parametric maps with biopsy results. The parametric maps were generated by software which extracts perfusion parameters that differentiate benign from malignant tissue from DCE-US recordings. We performed a stringent analysis (all tumours) and a clinical analysis (clinically significant tumours). We calculated the potential reduction in biopsies (benign on imaging) and the resultant missed positive biopsies (false-negatives). Additionally, we evaluated the performance in terms of sensitivity, specificity negative predictive value (NPV) and positive predictive value (PPV) on a per-prostate level. RESULTS: Based on DCE-US, 470/651 (72.2%) of biopsy locations appeared benign, resulting in 40 false-negatives (8.5%), considering clinically significant tumours only. Including parametric maps, 411/651 (63.1%) of the biopsy locations appeared benign, resulting in 23 false-negatives (5.6%). In the per-prostate clinical analysis, DCE-US classified 38/82 prostates as benign, missing eight diagnoses. Including parametric maps, 31/82 prostates appeared benign, missing three diagnoses. Sensitivity, specificity, PPV and NPV were 73, 58, 50 and 79%, respectively, for DCE-US alone and 91, 56, 57 and 90%, respectively, with parametric maps. CONCLUSION: The interpretation of DCE-US with parametric maps allows good prediction of biopsy outcome. A two-thirds reduction in biopsy cores seems feasible with only a modest decrease in cancer diagnosis.
OBJECTIVE: To investigate the value of dynamic contrast-enhanced (DCE)-ultrasonography (US) and software-generated parametric maps in predicting biopsy outcome and their potential to reduce the amount of negative biopsy cores. MATERIALS AND METHODS: For 651 prostate biopsy locations (82 consecutive patients) we correlated the interpretation of DCE-US recordings with and without parametric maps with biopsy results. The parametric maps were generated by software which extracts perfusion parameters that differentiate benign from malignant tissue from DCE-US recordings. We performed a stringent analysis (all tumours) and a clinical analysis (clinically significant tumours). We calculated the potential reduction in biopsies (benign on imaging) and the resultant missed positive biopsies (false-negatives). Additionally, we evaluated the performance in terms of sensitivity, specificity negative predictive value (NPV) and positive predictive value (PPV) on a per-prostate level. RESULTS: Based on DCE-US, 470/651 (72.2%) of biopsy locations appeared benign, resulting in 40 false-negatives (8.5%), considering clinically significant tumours only. Including parametric maps, 411/651 (63.1%) of the biopsy locations appeared benign, resulting in 23 false-negatives (5.6%). In the per-prostate clinical analysis, DCE-US classified 38/82 prostates as benign, missing eight diagnoses. Including parametric maps, 31/82 prostates appeared benign, missing three diagnoses. Sensitivity, specificity, PPV and NPV were 73, 58, 50 and 79%, respectively, for DCE-US alone and 91, 56, 57 and 90%, respectively, with parametric maps. CONCLUSION: The interpretation of DCE-US with parametric maps allows good prediction of biopsy outcome. A two-thirds reduction in biopsy cores seems feasible with only a modest decrease in cancer diagnosis.
Authors: Jean-Michel Correas; Ethan J Halpern; Richard G Barr; Sangeet Ghai; Jochen Walz; Sylvain Bodard; Charles Dariane; Jean de la Rosette Journal: World J Urol Date: 2020-04-18 Impact factor: 4.226
Authors: D Cody Morris; Derek Y Chan; Mark L Palmeri; Thomas J Polascik; Wen-Chi Foo; Kathryn R Nightingale Journal: Ultrasound Med Biol Date: 2021-04-06 Impact factor: 3.694
Authors: A W Postema; M J V Scheltema; C K Mannaerts; R J G Van Sloun; T Idzenga; M Mischi; M R E Engelbrecht; J J M C H De la Rosette; H Wijkstra Journal: BMC Urol Date: 2017-04-05 Impact factor: 2.264