To a degree, the use of soft-tissue modeling for updating image-guided navigational systems has not been embraced by the mainstream scientific community. It has only just recently found application within the neuronavigation community (although no commercial systems are available yet) and is still under investigation. Much of this frustration is not due to the growing number of methodologies but rather to a misunderstanding of the goals of model-updating, and an inability to test and validate. With respect to the former, it is naove to believe that modeling can account for all fine-scale deformations. However, the question to be answered is, within the confines of surgical margin, can model-updating significantly impact surgical resection? This is a central research hypothesis to be investigated within this application. What sets this application apart is that if the milestones are achieved, the outcome could result in a soft-tissue deformation correction system for image- guided liver surgery systems that could be immediately commercially available for patient care. More specifically, at the conclusion of this work, an image-guided liver surgical system capable of deformation correction will be generated, a preliminary experience with the fidelity of those corrections will be established, and the technology will be commercially available. This is possible because this application will leverage an ongoing relationship with Pathfinder Therapeutics Incorporated (PTI) that is in the process of testing their image-guided liver surgery (IGLS) system and an independent clinical evaluator at Memorial Sloan Kettering Cancer Center. PTI has agreed to share their technological platform with the PD as well as provide open systems and support to support the integration of the novel tissue deformation correction strategy proposed herein. Members of the PTI team have already contributed to the methodologies within this application and have vested scientific interest to continue within the scope of this application with the PD. The hypothesis that models can be used to correct for deformation within IGLS will be supported by three specific aims which involve: (1) incorporate the non-rigid correction compute node controller into the Pathfinder Therapeutics Inc. guidance platform, test, and then deploy to our clinical site, (2) evaluate intraoperative deformation correction using the compute node controller in a clinical trial, and (3) begin to investigate the controller/system within the context of minimally invasive procedures. Previous work involved the development of our registration methods and deformation correction compute node controller. We have succeeded in this endeavor and have shown promise. We are poised to complete the next phase with the deployment into a commercially available IGLS system, and the testing at an independent clinical site in two 25 patient studies as well as address minimally invasive procedures. In addition, it should be noted that while the controller will be integrated into a specific platform, the technology itself is amenable to integration with any image-guided surgery platform.

Public Health Relevance

Primary and metastatic cancer within the liver is becoming increasingly common. There is significant evidence that intra-abdominal liver surgery improves survival times for patients afflicted with metastatic disease. Currently the patient population is limited largely due to the complexity of this procedure. Better visualization and guidance would provide surgeons more confidence and would increase the number of surgical candidates and improve the outcome for these patients. If this application is successful, it would lead to the first commercially available image-guided liver surgery system capable of soft-tissue deformation correction. The proposed deformation correction compute node controller would have more widespread impact by being readily adaptable to other surgical systems with similar data. In addition, the strategy would also be compatible with minimally invasive surgeries provided that information regarding organ shape can be acquired using the minimally invasive approach we have identified. Currently, the only commercial means to correct for soft-tissue deformation is to use intraoperative magnetic resonance (iMR) and computed tomography (iCT). These systems are of considerable expense, require staff, incur radiation in the latter, and can be costly to maintain. Due to their cumbersome nature, the patient through-put is also considerably less than a conventional operating room. iCT has been available since the mid-1980's and iMR has been available since the mid-1990's, yet there are still only a handful of systems being used throughout the world. While these are disadvantages, it should be noted that these systems will not be dispensed with and will continue to be developed. However, it is highly probable that these facilities will become referral centers for the most critical cases rather than available as a mainstream technology. The strategy of augmenting an existing image- guidance system with a deformation correction compute node controller is very low cost, may be as effective as the iMR/iCT solution, and is translatable to any medical center with an image-guided surgery system. This application will play an important role in remedying a disconnection between these sparse referral centers and the vast assortment of local medical centers available to the general population.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
5R01CA162477-03
Application #
8474723
Study Section
Special Emphasis Panel (ZRG1-SBIB-U (55))
Program Officer
Baker, Houston
Project Start
2011-08-01
Project End
2016-05-31
Budget Start
2013-06-01
Budget End
2014-05-31
Support Year
3
Fiscal Year
2013
Total Cost
$581,471
Indirect Cost
$155,055
Name
Vanderbilt University Medical Center
Department
Surgery
Type
Schools of Medicine
DUNS #
004413456
City
Nashville
State
TN
Country
United States
Zip Code
37212
Simpson, Amber; Miga, Michael (2018) Special Section Guest Editorial: Technology Platforms for Treatment and Discovery in Human Systems: Novel Work in Image-Guided Procedures, Robotic Interventions, and Modeling. J Med Imaging (Bellingham) 5:021201
Heiselman, Jon S; Clements, Logan W; Collins, Jarrod A et al. (2018) Characterization and correction of intraoperative soft tissue deformation in image-guided laparoscopic liver surgery. J Med Imaging (Bellingham) 5:021203
Clements, Logan W; Collins, Jarrod A; Weis, Jared A et al. (2017) Deformation correction for image guided liver surgery: An intraoperative fidelity assessment. Surgery 162:537-547
Collins, Jarrod A; Weis, Jared A; Heiselman, Jon S et al. (2017) Improving Registration Robustness for Image-Guided Liver Surgery in a Novel Human-to-Phantom Data Framework. IEEE Trans Med Imaging 36:1502-1510
Zaydfudim, Victor M; Vachharajani, Neeta; Klintmalm, Goran B et al. (2016) Liver Resection and Transplantation for Patients With Hepatocellular Carcinoma Beyond Milan Criteria. Ann Surg 264:650-8
Ong, Rowena; Glisson, Courtenay L; Burgner-Kahrs, Jessica et al. (2016) A novel method for texture-mapping conoscopic surfaces for minimally invasive image-guided kidney surgery. Int J Comput Assist Radiol Surg 11:1515-26
Clements, Logan W; Collins, Jarrod A; Weis, Jared A et al. (2016) Evaluation of model-based deformation correction in image-guided liver surgery via tracked intraoperative ultrasound. J Med Imaging (Bellingham) 3:015003
Kassab, Ghassan S; An, Gary; Sander, Edward A et al. (2016) Augmenting Surgery via Multi-scale Modeling and Translational Systems Biology in the Era of Precision Medicine: A Multidisciplinary Perspective. Ann Biomed Eng 44:2611-25
Miga, Michael I (2016) Computational Modeling for Enhancing Soft Tissue Image Guided Surgery: An Application in Neurosurgery. Ann Biomed Eng 44:128-38
Simpson, Amber L; Leal, Julie N; Pugalenthi, Amudhan et al. (2015) Chemotherapy-induced splenic volume increase is independently associated with major complications after hepatic resection for metastatic colorectal cancer. J Am Coll Surg 220:271-80

Showing the most recent 10 out of 24 publications