Commentary on: Image-Guided Surgical Simulation in Minimally Invasive Liver Procedures: Development of a Liver Tumor Porcine Model Using a Multimodality Imaging Assessment by Vázquez et al.

The authors of “Image-guided surgical simulation in minimally invasive liver procedures: development of a liver tumor porcine model using a multimodality imaging assessment” provide a novel approach to a realistic hepatic tumor model. This model leverages multi-imaging modalities from which the primary goal is to provide a comprehensive formula in developing a realistic hepatic tumor model. Consequently, the authors were able to evaluate the usefulness of the hepatic tumor model for surgical training in image-guided liver procedures. ¹ With the high morbidity and mortality associated with hepatobiliary cancer, ² such a feasible and creative model can ensure that surgical trainees are equipped with the technical skills required to provide high-quality patient care for patients with hepatobiliary cancers.

The study further emphasizes the vast array of imaging modalities utilized in the diagnosis and treatment of hepatobiliary cancers. A comprehensive understanding of these various imaging modalities, and the associated interventional surgical techniques, is required in specific cases to guide decision-making treatment algorithms. The authors highlight the current overall trend within surgical specialties with a shift toward less invasive techniques in diagnosing and treatment of surgical pathologies. This trend places greater emphasis on the need for surgical trainees to be more precise in image-guided therapies, and since therapeutic success is correlated with the operator's expertise, training plays a fundamental role in providing the highest quality of patient care. ³

Unlike previous tumor models composed of materials that attempt to mimic the properties of natural tissue, which were developed only for training using sonography imaging, ⁴ the authors considered the rapid technological evolution in image modalities. In this regard, the authors take on the challenge of developing a high-quality hepatic tumor model with the goal of improving surgical training for the current minimally invasive therapies for premalignant and malignant hepatic lesions by creating a realistic tissue-like tumor model that is visible in the vast array of multimodality imaging currently utilized, not just through ultrasonography.

The authors' technique of injecting poly(amidoamine) (PAA)-based hydrogels into target porcine hepatic tissues allows the creation of both ex vivo and in vivo models by the injected liquid adapting its shape to the cavity in which it is injected into. This further ensures the continuity between the implanted material and the surrounding tissue. Without releasing any byproduct, they are considered biocompatible, and their formulation as injectable hydrogels has already been reported for endoscopic submucosal dissection and for the treatment of inguinal hernia. ¹

The authors' realistic hepatic tumor model with an application for image-guided interventions is well examined with a proof of concept phase using ex vivo livers and a feasibility/safety phase using in vivo porcine livers. This concept allowed the authors to develop a total of 40 tumors using the PAA-based hydrogels. The experimental study demonstrated successful utilization of these synthetic models using multiple imaging modalities such as cross-sectional imaging computed tomography scan, magnetic resonance imaging, Cone Beam Computed Tomography and ultrasound for effective and efficient liver biopsy, radiofrequency ablation, and laparoscopic liver resection. Although the experimental procedures were performed by experts in the field of hepatobiliary surgery, the authors expressed confidence in obtaining similar success if the models were to be tested with novice practitioners with the expectation that it will positively impact their training for clinical practice.

Unique to this article is the ability to develop a hepatic tumor model as well as provide a successful application of such a model while utilizing multimodal imaging in hopes of advancing a trainee's learning experience. As a longtime educator in the field of surgery, I would highly encourage the authors to further test this hypothesis so that they can show that this training model can effectively translate into trainees becoming more efficient and proficient in their surgical skills. If the training curriculum for image-guided liver procedures using the described hepatic tumor models proves to be more efficient and effective in surgical training, the cost, patient safety, and practicality of implementing such a curriculum should be taken into consideration and this model should become a standard in surgical training. Furthermore, it is conceivable for these models to be created to mimic an actual patient's hepatic tumor(s) noted on preoperative radiographic imaging so that the surgeons and/or trainee can “simulate” the operative procedure before implementing such techniques on live patient tissue. Being able to do so will certainly change the way we care for patients with complex hepatobiliary cancers and can potentially reduce cost, operative times, and perioperative complications, while hopefully improving patient safety and outcomes.