Lars Budaeus

Shear Wave Elastography for Localization of Prostate Cancer Lesions and Assessment of Elasticity Thresholds: Implications for Targeted Biopsies and Active Surveillance Protocols

PURPOSE Shear wave elastography allows the detection of cancer by using focused ultrasound pulses for locally deforming tissue. The differences in tissue elasticity and stiffness have been used increasingly in breast cancer imaging and help detect potential tumor lesions in the prostate. In this study we localized prostate cancer lesions using shear wave elastography before radical prostatectomy and assessed the examiner independent elasticity threshold for cancer foci detection. MATERIALS AND METHODS Shear wave elastography scanning of the whole prostate was performed before radical prostatectomy in 60 consecutive patients with high, intermediate and low risk disease. Localization of suspected lesions and density threshold (kPa) were recorded in up to 12 areas and resulted in 703 different fields. Shear wave elastography findings were correlated with final pathology. Initially 381 areas were used to establish shear wave elastography cutoffs (development cohort 32 patients). Subsequently these cutoffs were validated in 322 areas (validation cohort 28 patients). RESULTS Using shear wave elastography significant differences were recorded for the elasticity of benign tissue vs prostate cancer nodules at 42 kPa (range 29 to 71.3) vs 88 kPa (range 54 to 132) (all p <0.001). Median cancer lesion diameter was 26 mm (range 18 to 41). Applying the most informative cutoff of 50 kPa to the validation cohort resulted in 80.9% and 69.1% sensitivity and specificity, respectively, and 74.2% accuracy for detecting cancer nodules based on final pathological finding. The corresponding positive and negative predictive values were 67.1% and 82.2%, respectively. CONCLUSIONS Shear wave elastography allows the identification of cancer foci based on shear wave elastography differences. Moreover, reliable cutoffs for this approach can be established, allowing examiner independent localization of prostate cancer foci.

Functional and oncological outcomes of patients aged <50 years treated with radical prostatectomy for localised prostate cancer in a European population

To address the biochemical and functional outcomes after radical prostatectomy (RP) of men aged <50 years in a large European population.

Gleason 6 prostate cancer in one or two biopsy cores can harbor more aggressive disease

BACKGROUND AND PURPOSE Patients with Gleason (GL) 6 prostate cancer in one or two biopsy cores can be upgraded and/or upstaged at the time of surgery, which may adversely impact long-term outcome. A novel model for prediction of adverse pathologic outcomes was developed using preoperative characteristics. PATIENTS AND METHODS Between 2003 and 2007, 1159 patients underwent robot-assisted radical prostatectomy (RARP) at our institution. GL 6 prostate cancer in one or two biopsy cores was identified in 416 (36%) patients. Logistic regression analyses were used to assess the rate of GL ≥7 and/or extraprostatic extension at RARP. Covariates consisted of age, body mass index (BMI), number of positive cores, greatest percent of cancer in a core (GPC), clinical stage, and preoperative prostate-specific antigen (PSA) level. After backward variable selection, the developed model was internally validated using the area under the curve and subjected to methods of calibration. RESULTS Respectively, 278 (67%) and 138 (33%) patients had one or two positive biopsy cores. At RARP, 90 (22%) patients were upgraded to GL ≥7 and 37 (9%) had extraprostatic extension. The novel model relied on age, BMI, preoperative PSA level, and GPC for prediction of adverse pathologic outcomes and was 69% accurate. Calibration plot revealed a virtually perfect relationship between predicted and observed probabilities. CONCLUSIONS In patients with GL 6 prostate cancer in one or two biopsy cores, 25% have more ominous pathology at RARP. The model provides an individual assessment of adverse outcomes at surgery. Consequently, it may be considered when counseling patients regarding their management options.

MP78-17 IDENTIFYING THE MOST INFORMATIVE PREDICTION-TOOL FOR CANCER SPECIFIC MORTALITY AFTER RADICAL PROSTATECTOMY: COMPARATIVE ANALYSIS OF THREE COMMONLY USED PREOPERATIVE PREDICTION MODELS

Background: The D’Amico risk stratification, Cancer of the Prostate Risk Assessment (CAPRA) score, and Stephenson nomogram are widely used prediction tools for biochemical recurrence and survival after radical prostatectomy (RP). These models have not been compared with respect to cancer-specific mortality (CSM) prediction. Objective: To validate and compare the prediction tools for 10-yr CSM. Design, setting, and participants: Overall, 2485 prostate cancer patients underwent RP in a European tertiary care center. Outcome measurements and statistical analysis: Three preoperative models (D’Amico, CAPRA, and Stephenson) were compared in terms of their ability to predict 10-yr CSM; therefore, accuracy tests (area under the receiver operating characteristic curve [AUC]), calibration plots, and decision curve analysis (DCA) were assessed for each model. Results and limitations: CSM at 10 yr was 3.6%. The AUC was 0.76, 0.77, and 0.80 for the D’Amico, CAPRA, and Stephenson models, respectively. In calibration plots, predicted probabilities were close to the observed probabilities for the D’Amico model but showed underestimation of CSM for the Stephenson nomogram and overestimation of CSM for the CAPRA score. DCA identified a benefit for the CAPRA score. These results apply to patients treated at a European tertiary care center. Conclusions: Despite good discriminatory power, all tested models had some shortcomings in terms of prediction of 10-yr CSM. All three models showed good performance in North American cohorts, but our results suggested a lack of generalizability to European patients. To overcome this issue, local recalibration of the variable weights could be performed. Another possibility is the development of more universal markers that are independent of regional practice differences or, alternatively, the development of better tools to quantify clinical practice differences. Patient summary: Prediction tools can predict cancer survival prior surgery, relying on points for age, prostate-specific antigen levels, aggressiveness, and percentage of cancer at biopsy. These tools are reliable in North American patients but have shortcomings for identifying patients at high risk of prostate cancer death in Europe.