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

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Abstract

Purpose

We aim to evaluate the accuracy of micro-ultrasound (microUS) in predicting extraprostatic extension (EPE) of Prostate Cancer (PCa) prior to surgery.

Methods

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.

Results

Overall, data from 140 patients were examined. All predictors were associated with non-organ-confined disease (p < 0.001). Final pathology showed that 79 patients (56.4%) had a pT2 disease and 61 (43.3%) ≥ 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%.

Conclusions

MicroUS can accurately predict EPE at the final pathology report in patients scheduled for RARP.

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Availability of data, materials, and code

Data, code, and analysis are available upon request.

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Funding

The authors did not receive support from any organization for the submitted work.

Author information

Authors and Affiliations

Authors

Contributions

VF: data collection or management, data analysis, manuscript writing/editing, protocol/project development. NMB: protocol/project development, manuscript writing/editing. FR: data collection or management, Manuscript writing/editing. MP: data collection or management, data analysis, manuscript writing/editing, Protocol/project development. FP: data collection or management, manuscript writing/editing. DM: data collection or management, Manuscript writing/editing. AU: data collection or management, manuscript writing/editing. AS: data collection or management, manuscript writing/editing. PC: data collection or management, manuscript writing/editing. RH: data collection or management, manuscript writing/editing. ML: data collection or management, manuscript writing/editing. GG: Data collection or management, manuscript writing/editing. GL: data collection or management, data analysis, manuscript writing/editing, protocol/project development.

Corresponding author

Correspondence to Nicolò Maria Buffi.

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Conflicts of interest

The authors have no relevant financial or non-financial interests to disclose.

Research involving human participants, their data or biological material

The study was approved by local authorities (Prot.n°2570-ICH-006) and all patients signed a written informed consent before enrollment.

Informed consent

Informed consent was obtained from all individual participants included in the study.

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Supplementary Information

Below is the link to the electronic supplementary material.

345_2021_3890_MOESM1_ESM.tiff

Supplementary file1 (TIFF 1521 KB) Figure depicting a PRIMUS 5 mixed-echo lesion on the right lateral aspect of the prostate with associated hypoechoic halo (orange arrows) and capsular bulging. Needle biopsy tracks con also be observed as hyperechoic lines

345_2021_3890_MOESM2_ESM.tiff

Supplementary file2 (TIFF 1521 KB) Figure depicting a PRIMUS 5 mixed-echo lesion on the left lateral aspect of the prostate with associated hypoechoic halo (orange arrows)

Supplementary file3 (JPG 49 KB) Flow chart of included, excluded, and finally enrolled patients

Supplementary file4 (DOCX 14 KB) Diagnostic performance of each predictor

345_2021_3890_MOESM5_ESM.docx

Supplementary file5 (DOCX 16 KB) Logistic regression univariate analysis and multivariate analysis of predictors and clinical risk factors

345_2021_3890_MOESM6_ESM.pdf

Supplementary file6 (PDF 75 KB) Diagnostic accuracy represented as the Area under the ROC curve, for two multivariate logistic regression model (MLRM) tested as clinical model alone, compared with a clinical added with the microUS parameters. represented teas the Area under the ROC curve. Outcome= non-organ-confined disease at final pathology report; dependent variables (clinical model)=total PSA, DRE, ISUP at biopsy, PRI-MUS; dependent variables (clinical + microUS predictors): clinical + visible ECE, capsular bulge, hypoechoic halo or ring at microUS

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Fasulo, V., Buffi, N.M., Regis, F. et al. Use of high-resolution micro-ultrasound to predict extraprostatic extension of prostate cancer prior to surgery: a prospective single-institutional study. World J Urol 40, 435–442 (2022). https://doi.org/10.1007/s00345-021-03890-4

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  • DOI: https://doi.org/10.1007/s00345-021-03890-4

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