Realistic anatomical prostate models for surgical skills workshops using ballistic gelatin for nerve-sparing radical prostatectomy and fruit for simple prostatectomy

3D printed patient-specific prostate cancer models to guide nerve-sparing robot-assisted radical prostatectomy: a systematic review

Precise knowledge of each patient's index cancer and surrounding anatomy is required for nerve-sparing robot-assisted radical prostatectomy (NS-RARP). Complementary to this, 3D printing has proven its utility in improving the visualisation of complex anatomy. This is the first systematic review to critically assess the potential of 3D printed patient-specific prostate cancer models in improving visualisation and the practice of NS-RARP. A literature search of PubMed and OVID Medline databases was performed using the terms "3D Printing", "Robot Assisted Radical Prostatectomy" and related index terms as per the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Eight articles were included; six were identified via database searches, to which a further two articles were located via a snowballing approach. Eight papers were identified for review. There were five prospective single centre studies, one case series, one technical report and one letter to the editor. Of these articles, five publications (62.5%) reported on the utility of 3D printed models for NS-RARP planning. Two publications (25%) utilised 3D printed prostate models for simulation and training, and two publications (25%) used the models for patient engagement. Despite the nascency of the field, 3D printed models are emerging in the uro-oncological literature as a useful tool in visualising complex anatomy. This has proven useful in NS-RARP for preoperative planning, simulation and patient engagement. However, best practice guidelines, the future regulatory landscape, and health economic considerations need to be addressed before this synergy of new technologies is ready for the mainstream.

A novel palpation-based method for tumor nodule quantification in soft tissue-computational framework and experimental validation

Variation in mechanical properties is a useful marker for cancer in soft tissue and has been used in clinical diagnosis for centuries. However, to develop such methods as instrumented palpation, there remain challenges in using the mechanical response during palpation to quantify tumor load. This study proposes a computational framework of identification and quantification of cancerous nodules in soft tissue without a priori knowledge of its geometry, size, and depth. The methodology, using prostate tissue as an exemplar, is based on instrumented palpation performed at positions with various indentation depths over the surface of the relevant structure (in this case, the prostate gland). The profile of force feedback results is then compared with the benchmark in silico models to estimate the size and depth of the cancerous nodule. The methodology is first demonstrated using computational models and then validated using tissue-mimicking gelatin phantoms, where the depth and volume of the tumor nodule is estimated with good accuracy. The proposed framework is capable of quantifying a tumor nodule in soft tissue without a priori information about its geometry, thus presenting great promise in clinical palpation diagnosis for a wide variety of solid tumors including breast and prostate cancer.

Graphical abstract

Incorporation and validation of clinically relevant performance metrics of simulation (CRPMS) into a novel full-immersion simulation platform for nerve-sparing robot-assisted radical prostatectomy (NS-RARP) utilizing three-dimensional printing and hydrogel casting technology

OBJECTIVES

To incorporate and validate clinically relevant performance metrics of simulation (CRPMS) into a hydrogel model for nerve-sparing robot-assisted radical prostatectomy (NS-RARP).

MATERIALS AND METHODS

Anatomically accurate models of the human pelvis, bladder, prostate, urethra, neurovascular bundle (NVB) and relevant adjacent structures were created from patient MRI by injecting polyvinyl alcohol (PVA) hydrogels into three-dimensionally printed injection molds. The following steps of NS-RARP were simulated: bladder neck dissection; seminal vesicle mobilization; NVB dissection; and urethrovesical anastomosis (UVA). Five experts (caseload >500) and nine novices (caseload <50) completed the simulation. Force applied to the NVB during the dissection was quantified by a novel tension wire sensor system fabricated into the NVB. Post-simulation margin status (assessed by induction of chemiluminescent reaction with fluorescent dye mixed into the prostate PVA) and UVA weathertightness (via a standard 180-mL leak test) were also assessed. Objective scoring, using Global Evaluative Assessment of Robotic Skills (GEARS) and Robotic Anastomosis Competency Evaluation (RACE), was performed by two blinded surgeons. GEARS scores were correlated with forces applied to the NVB, and RACE scores were correlated with UVA leak rates.

RESULTS

The expert group achieved faster task-specific times for nerve-sparing (P = 0.007) and superior surgical margin results (P = 0.011). Nerve forces applied were significantly lower for the expert group with regard to maximum force (P = 0.011), average force (P = 0.011), peak frequency (P = 0.027) and total energy (P = 0.003). Higher force sensitivity (subcategory of GEARS score) and total GEARS score correlated with lower nerve forces (total energy in Joules) applied to NVB during the simulation with a correlation coefficient (r value) of -0.66 (P = 0.019) and -0.87 (P = 0.000), respectively. Both total and force sensitivity GEARS scores were significantly higher in the expert group compared to the novice group (P = 0.003). UVA leak rate highly correlated with total RACE score r value = -0.86 (P = 0.000). Mean RACE scores were also significantly different between novices and experts (P = 0.003).

CONCLUSION

We present a realistic, feedback-driven, full-immersion simulation platform for the development and evaluation of surgical skills pertinent to NS-RARP. The correlation of validated objective metrics (GEARS and RACE) with our CRPMS suggests their application as a novel method for real-time assessment and feedback during robotic surgery training. Further work is required to assess the ability to predict live surgical outcomes.

Novel Use of Household Items in Open and Robotic Surgical Skills Resident Education

Background

The aim of this study was to investigate the effectiveness of surgical simulators created using household items and to determine their potential role in surgical skills training.

Methods

Ten urology residents attended a surgical skills workshop and practiced using surgical simulators and models. These included a wound closure model, an open prostatectomy model, a delicate tissue simulation, a knot-tying station, and a laparoscopic simulator. After the workshop, the residents completed a 5-point Likert questionnaire. Primary outcome was face validity of the models. Secondary outcomes included usefulness as a training tool and ability to replicate the models.

Results

All models were easily created and successfully represented the surgical task being simulated. Residents evaluated the activities as being useful for training purposes overall. They also felt confident that they could recreate the simulators.

Conclusion

Low-fidelity training models can be used to improve surgical skills at a reasonable cost. The models will require further evaluation to determine construct validity and to determine how the improvements translate to OR performance. While high-fidelity simulators may continue to be utilized in formal surgical training, residents should be encouraged to supplement their training with innovative homemade models.

Analysis of a practical surgical skills laboratory for nerve sparing radical prostatectomy

PURPOSE

With the rapidly expanding anatomical and technical knowledge surrounding nervesparing radical prostatectomy (NSRP), anatomical and operative textbooks have failed to keep pace with the literature. A surgical skill laboratory (SSL) was designed to educate urology trainees on surgical anatomy and techniques for NSRP. The objective was to assess the validity of a SSL program.

METHODS

A low-fidelity, anatomically accurate prostate model with its appropriate fascial coverings and location of the neurovascular bundle was created. Participants were surveyed prior to a SSL workshop for their knowledge of NSRP focusing on clinical and anatomical considerations. An interactive 2-h tutorial and workshop was then undertaken outlining the clinical and anatomical nuances for NSRP, with participants then practising an intra and inter-fascial NSRP on the model. Participants were resurveyed immediately after the workshop and at 6 months.

RESULTS

Thirty participants completed the NSRP workshop. Significant differences (p < 0.0001) in anatomical and clinical knowledge were noted after the workshop with improvements for both junior and senior trainees. The knowledge was retained at 6 months following the workshop.

CONCLUSIONS

A low-fidelity bench-top model is a feasible and reproducible technique for improving the understanding of periprostatic anatomy and the different surgical approaches for NSRP. The SSL is useful and knowledge gained appears to be retained by workshop participants. SSL workshops are a valid hands-on approach to teaching surgical skills and should remain an integral part of urology training.

A constitutive model for ballistic gelatin at surgical strain rates

This paper describes a constitutive model for ballistic gelatin at the low strain rates experienced, for example, by soft tissues during surgery. While this material is most commonly associated with high speed projectile penetration and impact investigations, it has also been used extensively as a soft tissue simulant in validation studies for surgical technologies (e.g. surgical simulation and guidance systems), for which loading speeds and the corresponding mechanical response of the material are quite different. We conducted mechanical compression experiments on gelatin specimens at strain rates spanning two orders of magnitude (~0.001-0.1s(-1)) and observed a nonlinear load-displacement history and strong strain rate-dependence. A compact and efficient visco-hyperelastic constitutive model was then formulated and found to fit the experimental data well. An Ogden type strain energy density function was employed for the elastic component. A single Prony exponential term was found to be adequate to capture the observed rate-dependence of the response over multiple strain rates. The model lends itself to immediate use within many commercial finite element packages.