Sergei Kurenov

Simulation for Training With the Autosuture TM Endo StitchTM Device

The rapid development and deployment of novel laparoscopic instruments present the surgical educator and trainee with a significant challenge. Several useful instruments have been particularly difficult to teach the novice. We have developed a platform that allows the combination of the actual instrument handle with a virtual re-creation of the instrument tip. We chose the AutosutureTM Endo StitchTM device as the prototypical instrument because it satisfies our subjective experience of “useful, but hard to teach.” A software package was developed to support the re-creation of the needle and suture that accompany the device. The apparatus has haptic capabilities and collision detection so that the needle driver is “aware” of suture and instrument contact. The developed virtual environment allows re-creation of the necessary motion to simulate the instrument, the trainee can use the actual instrument handle, and the system can be altered to accommodate other instruments.

Developing a multimedia environment for customized teaching of an adrenalectomy

We have developed a computer based simulation process which allows a surgical expert to create a customized operative environment. This virtual environment, the Toolkit for Illustration of Procedures in Surgery (3D TIPS), is deployed on a low-cost computer system and requires minimal training for the programmer. The learner can be engaged in training immediately and the educator can modify the system and annotate the procedure to highlight specific points using video clips, operative images, and the like. A laparoscopic adrenalectomy is presented as a proof of concept in the accompanying article.

Virtual interrupted suturing exercise with the Endo stitch suturing device

This paper presents the surgical suturing simulator for wound closure, which is designed for education and training purposes. Currently it is designed specifically to support a simulation of the Autosuture™ Endo Stitch™ suturing, but could be extended for other surgical instruments designed for intracorporeal suturing. The simulator allows a trainee to perform a virtual wound closure by interrupted suture with real surgical instrument handles customized to fit on haptic devices. The wound simulation is based on a triangular surface mesh embedded in a linear hexahedral finite element mesh, whereas the suture simulation is based on a simplified Cosserat theory of elastic rods. Our novel heuristic combination of physically-based and control-based simulations makes the simulator run efficiently in real time on mid-level desktop PCs and notebooks.

Preoperative survival calculator for resectable hepatocellular carcinoma

Background Estimation of preoperative overall survival (OS) of hepatocellular carcinoma (HCC) may guide surgical decision-making. Methods OS was analyzed using the National Cancer Data Base from 1998-2012. Patients with HCC who underwent wedge resection, lobectomy or extended lobectomy were selected. Patients who had metastatic disease or previous treatment prior to surgery were excluded. Data was randomly allocated to model building (nb =4,364) and validation cohorts (nv =1,091). Multivariable regression analyses of the nb were used to construct prediction models and optimized using nv. Results HCC patients (n=5,455) who underwent curative resection had a median OS of 36 months (95% CI, 34-38 months) with 1- and 3-year OS of 73% (95% CI, 72-74%) and 50% (95% CI, 49-51%), respectively. The patient median age was 65, 66% of patients were male, median tumor size was 60 mm; clinical stage 1 =25%, stage 2 =30% and stage 3 =45%. Alpha fetoprotein (AFP) was elevated in 63% of patients. Factors significant in the prediction model included degree of resection, age, race, tumor size, grade, and histologic subtype. Conclusions A preoperative OS calculator was developed to assist in the treatment evaluation and OS prediction of HCC patients.

Surgeon-Authored Virtual Laparoscopic Adrenalectomy Module Is Judged Effective and Preferred Over Traditional Teaching Tools:

Objective. The study assesses user acceptance and effectiveness of a surgeon-authored virtual reality (VR) training module authored by surgeons using the Toolkit for Illustration of Procedures in Surgery (TIPS). Methods. Laparoscopic adrenalectomy was selected to test the TIPS framework on an unusual and complex procedure. No commercial simulation module exists to teach this procedure. A specialist surgeon authored the module, including force-feedback interactive simulation, and designed a quiz to test knowledge of the key procedural steps. Five practicing surgeons, with 15 to 24 years of experience, peer reviewed and tested the module. In all, 14 residents and 9 fellows trained with the module and answered the quiz, preuse and postuse. Participants received an overview during Surgical Grand Rounds session and a 20-minute one-on-one tutorial followed by 30 minutes of instruction in addition to a force-feedback interactive simulation session. Additionally, in answering questionnaires, the trainees reflected on their learning experience and their experience with the TIPS framework. Results. Correct quiz response rates on procedural steps improved significantly postuse over preuse. In the questionnaire, 96% of the respondents stated that the TIPS module prepares them well or very well for the adrenalectomy, and 87% indicated that the module successfully teaches the steps of the procedure. All participants indicated that they preferred the module compared to training using purely physical props, one-on-one teaching, medical atlases, and video recordings. Conclusions. Improved quiz scores and endorsement by the participants of the TIPS adrenalectomy module establish the viability of surgeons authoring VR training.

Perioperative calculator to predict complications for patients with hepatocellular carcinoma resection.

446 Background: Hepatocellular carcinoma (HCC) is a common cancer worldwide, but few patients are optimal surgical candidates due to liver disease. Current prediction models (Childs-Pugh and MELD) poorly estimate serious morbidity risks for those patients considering resection. Methods: Using ACS-NSQIP database, patients with HCC were selected from 2006-2013. Patients included had a curative resection (partial hepatectomy or formal lobectomy) and were excluded if they had emergency surgery or disseminated cancer. Outcomes included 30 day morbidity and serious morbidity. Data was randomly divided into testing (n=1764) and validation (n=441) cohorts. Regression analyses of the testing cohorts were used to construct prediction models, then optimized using the validation cohort. Results: We identified 2,205 patients. Major morbidity or serious morbidity occurred in 34% (n=745) and 21% (n=456). Patient demographics are shown in Table 1. Factors significant for morbidity include age, surgical procedure, BMI, AS...