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Summary Computational modeling has become a successful tool for scientific advances including understanding the behavior of biological and biomedical systems as well as improving clinical practice. In most cases, only general models are used without taking into account patient‐specific features. However, patient specificity has proven to be crucial in guiding clinical practice because of disastrous consequences that can arise should the model be inaccurate. This paper proposes a framework for the computational modeling applied to the example of the male pelvic cavity for the purpose of prostate cancer diagnostics using palpation. The effects of patient specific structural features on palpation response are studied in three selected patients with very different pathophysiological conditions whose pelvic cavities are reconstructed from MRI scans. In particular, the role of intrabladder pressure in the outcome of digital rectal examination is investigated with the objective of providing guidelines to practitioners to enhance the effectiveness of diagnosis. Furthermore, the presence of the pelvic bone in the model is assessed to determine the pathophysiological conditions in which it has to be modeled. The conclusions and suggestions of this work have potential use not only in clinical practice and also for biomechanical modeling where structural patient‐specificity needs to be considered. © 2015 The Authors. International Journal for Numerical Methods in Biomedical Engineering published by John Wiley & Sons Ltd.

INTRODUCTION: Minimally invasive radical prostatectomy (RP) (robotic and laparoscopic), have brought improvements in the outcomes of RP due to improved views and increased degrees of freedom of surgical devices. Robotic and laparoscopic surgeries do not incorporate haptic feedback, which may result in complications secondary to inadequate tissue dissection (causing positive surgical margins, rhabdosphincter damage, etc). We developed a micro-engineered device (6 mm2 sized) [E-finger]) capable of quantitative elasticity assessment, with amplitude ratio, mean ratio and phase lag representing this. The aim was to assess the utility of the device in differentiating peri-prostatic tissue types in order to guide prostate dissection. MATERIAL AND METHODS: Two embalmed and 2 fresh frozen cadavers were used in the study. Baseline elasticity values were assessed in bladder, prostate and rhabdosphincter of pre-dissected embalmed cadavers using the micro-engineered device. A measurement grid was created to span from the bladder, across the prostate and onto the rhabdosphincter of fresh frozen cadavers to enable a systematic quantitative elasticity assessment of the entire area by 2 independent assessors. Tissue was sectioned along each row of elasticity measurement points, and stained with haematoxylin and eosin (H&E). Image analysis was performed with Image Pro Premier to determine the histology at each measurement point. RESULTS: Statistically significant differences in elasticity were identified between bladder, prostate and sphincter in both embalmed and fresh frozen cadavers (p = < 0.001). Intra-class correlation (ICC) reliability tests showed good reliability (average ICC = 0.851). Sensitivity and specificity for tissue identification was 77% and 70% respectively to a resolution of 6 mm2. CONCLUSIONS: This cadaveric study has evaluated the ability of our elasticity assessment device to differentiate bladder, prostate and rhabdosphincter to a resolution of 6 mm2. The results provide useful data for which to continue to examine the use of elasticity assessment devices for tissue quality assessment with the aim of giving haptic feedback to surgeons performing complex surgery.

Computational modeling has become a successful tool for scientific advances including understanding the behavior of biological and biomedical systems as well as improving clinical practice. In most cases, only general models are used without taking into account patient-specific features. However, patient specificity has proven to be crucial in guiding clinical practice because of disastrous consequences that can arise should the model be inaccurate. This paper proposes a framework for the computational modeling applied to the example of the male pelvic cavity for the purpose of prostate cancer diagnostics using palpation. The effects of patient specific structural features on palpation response are studied in three selected patients with very different pathophysiological conditions whose pelvic cavities are reconstructed from MRI scans. In particular, the role of intrabladder pressure in the outcome of digital rectal examination is investigated with the objective of providing guidelines to practitioners to enhance the effectiveness of diagnosis. Furthermore, the presence of the pelvic bone in the model is assessed to determine the pathophysiological conditions in which it has to be modeled. The conclusions and suggestions of this work have potential use not only in clinical practice and also for biomechanical modeling where structural patient-specificity needs to be considered. © 2015 The Authors. International Journal for Numerical Methods in Biomedical Engineering published by John Wiley & Sons Ltd.