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Dataset related to article "Use of high-resolution micro-ultrasound to predict extraprostatic extension of prostate cancer prior to surgery: a prospective single-institutional study "

<p>This record contains raw data related to article &ldquo;Use of high-resolution micro-ultrasound to predict extraprostatic extension of prostate cancer prior to surgery: a prospective single institutional study&quot;</p> <p><strong>Purpose: </strong> We aim to evaluate the accuracy of micro-ultrasound (microUS) in predicting extraprostatic extension (EPE) of Prostate Cancer (PCa) prior to surgery.</p> <p><strong>Methods: </strong> Patients with biopsy-proven PCa scheduled for robot-assisted radical prostatectomy (RARP) were prospectively recruited. The following MRI-derived microUS features were evaluated: capsular bulging, visible breach of the prostate capsule (visible extracapsular extension; ECE), presence of hypoechoic halo, and obliteration of the vesicle-prostatic angle. The ability of each feature to predict EPE was determined.</p> <p><strong>Results: </strong> Overall, data from 140 patients were examined. All predictors were associated with non-organ-confined disease (p &lt; 0.001). Final pathology showed that 79 patients (56.4%) had a pT2 disease and 61 (43.3%) &ge; pT3. Rate of non-organ-confined disease increased from 44% in those individuals with only 1 predictor (OR 7.71) to 92.3% in those where 4 predictors (OR 72.00) were simultaneously observed. The multivariate logistic regression model including clinical parameters showed an area under the curve (AUC) of 82.3% as compared to an AUC of 87.6% for the model including both clinical and microUS parameters. Presence of ECE at microUS predicted EPE with a sensitivity of 72.1% and a specificity of 88%, a negative predictive value of 80.5% and positive predictive value of 83.0%, with an AUC of 80.4%.</p> <p><strong>Conclusions: </strong> MicroUS can accurately predict EPE at the final pathology report in patients scheduled for RARP.</p>

ShareScore

16/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
8
Harmonization
4
Access
0
Reuse readiness
0
Engagement
4

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