Abstract
This paper introduces the fundamental concepts of computational surgery—Garbey et al. [Computational surgery and dual training, Springer, XVI, 315pp (Hardcover, ISBN: 978-1-4419-1122-3, 2009), 2010]—and proposes a road map for progress in this new multidisciplinary field of applied investigation. Recognizing this introduction will serve as common ground for discussion for both communities, surgeons and computational scientists, the scope of the presentation is broad rather than deep. Indeed, the field of computational surgery is sufficiently young that even the definition of computational surgery is still in the making. In this introduction, we propose multiple areas of investigation where the intersection of surgery and computational sciences is clearly in practice at the present time, though surprisingly unrecognized to date. We present examples of these intersections and demonstrate the usefulness and novelty of computational surgery as a new field of research. While some of the elements we present may be considered as basic for a specialized investigator, the simplicity of the presentation is intended as a proof of principle that basic concepts in computational sciences are of core value in solving many existing problems in clinical surgery; we also hope this initial evaluation will highlight potential obstacles and challenges. As the digital revolution transforms the working environment of the surgeon, close collaboration between surgeons and computational scientists is not only unavoidable but also essential to harness the capabilities of both fields to optimize the surgical care. We believe that this new collaboration will allow the community not only to develop the predictive models for the outcomes of surgery but also to enhance the process of surgery—from procedural planning, to execution of procedures and technology interfaces, to assessment of the healing process—investigations that will potentially provide great impact on patient care that far beyond the operating room.
Keywords
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
LeRoy Heinrichs W, Srivastava S, Montgomery K, Dev P (2004) The fundamental manipulations of surgery: a structured vocabulary for designing surgical curricula and simulators. J Am Assoc Gynecol Laparosc 11(4):450–456
Paré A (1983) Oeuvres completes remises en ordre et en franais moderne. In de Bissy F, Guerrand R-H (eds) Union latine d’edition, Paris (3 tomes et un index)
Satava RM (1998) Cybersurgery: advanced technologies for surgical practice, Protocols in general surgery series. Wiley-Liss, New York
Marescaux J, Leroy J, Gagner M, Rubino F, Mutter D, Vix M, Butner SE, Smith MK (2001) Transatlantic robot-assisted telesurgery. Nature 413:379–380
Clapworthy G, Viceconti M, Coveney PV, Kohl P (2008) The Virtual Physiological Human: building a framework for computational biomedicine I. Editorial. Philos Trans A Math Phys Eng Sci 366(1878):29758
Padoy N, Blum T, Ahmadi SA, Feussner H, Berger MO, Navab N (2012) Statistical modeling and recognition of surgical workflow. Med Image Anal 16(3):632–641
Swanson KR, Alvord EC Jr, Murray JD (2000) A quantitative model for differential motility of gliomas in grey and white matter. Cell Prolif 33:317–329
Murray JD (2003) Mathematical biology: II spatial models and biomedical applications, 3rd edn. Springer, New York
Silbergeld DL, Chicoine MR (1997) Isolation and characterization of human malignant glioma cells from histologically normal brain. J. Neurosurg 86(3):525–31
Kelley PJ, Hunt C (1994) The limited value of Cytoreductive surgery in elderly patients with malignant gliomas, J. Neurosurg 34:62–67
Rockne R, Rockhill JK, Mrugala M, Spence AM, Kalet I, Hendrickson K, Lai A, Cloughesy T, Alvord EC Jr, Swanson KR (2010) Predicting the efficacy of radiotherapy in individual glioblastoma patients in vivo: a mathematical modelling approach. Phys Med Biol 55(12):3271–3285
Wang C, Rockhill JK, Mrugala M, Peacock DL, Lai A, Jusenius K, Wardlaw JM, Cloughesy T, Spence AM, Rockne R, Alvord EC Jr, Swanson KR (2009) Prognostic significance of growth kinetics in newly diagnosed glioblastomas revealed by combining serial imaging with a novel biomathematical model. Cancer Res 69(23):9133–9140
Chaplain MAJ (2008) Modelling aspects of cancer growth: insight from mathematical and numerical analysis and computational simulation, multiscale problems in the life sciences. Lecture Notes in Mathematics. Springer Verlag 1940:147–200
Cristini V, Lowengrub J (2010) Multiscale modeling of cancer: an integrated experimental and mathematical modeling approach. Cambridge University Press, Cambridge
Gatenby RA, Gillies RJ, Brown JS (2010) The evolutionary dynamics of cancer prevention. Nat Rev Cancer 10:526–527
Lefor A (2011) Computational oncology. Jpn J Clin Oncol 41(8):937–947
Colin T, Iollo A, Lombardi D, Saut O (2012) System identification in tumour growth modeling using semi-empirical eigenfunctions. Math Models Methods Appl Sci 22(6):1250003–1250001
Benzekry S, Andre N, Benabdallah A, Ciccolini J, Faivre C, Hubert F, Barbolosi D (2012) Modeling the impact of anticancer agents on metastatic spreading. Math Model Nat Phenom 7(1):306–336
Berceli SA, Tran-Son-Tay R, Garbey M, Jiang Z (2009) Hemodynamically driven vein graft remodeling: a systems biology approach. Vascular 17(S1):24–31
Gibbons GH, Dzau VJ (1994) The emerging concept of vascular remodeling. N Engl J Med 330(20):1431–1438
Hwang M, Garbey M, Berceli SA, Tran Son Tay R (2009) Ruled-based simulation of multi-cellular biological systems – a review of modeling techniques. Cell Mol Bioeng 2(3):285–295
Hwang M, Berceli SA, Garbey M, Kim NH, Tran Son Tay R (2012) The dynamics of vein graft remodeling induced by hemodynamic forces – a mathematical model. Biomech Model Mechanobiol 11(3–4):411–423
Budrukkar A, Sarin R, Shrivastava S, Deshpande D, Dinshaw K (2007) Cosmesis, late sequelae and local control after breast-conserving therapy: influence of type of tumour bed boost and adjuvant chemotherapy. Clin Oncol 19:596–603
Pleijhuis R, Graafland M, deVries J, Bart J, deJong J, van Dam G (2009) Obtaining adequate surgical margins in breast-conserving therapy for patients with early-stage breast cancer: current modalities and future directions. Ann Surg Oncol 16(10):2717–2730. doi:10.1245/s10434-009-0609-z
Azar FS, Metaxas DN, Schnall MD (1999) A finite element model of the breast for predicting mechanical deformations during interventional procedures. Proc Int Soc Magn Reson Med 7:1084
Chung J-H (2008) Modelling mammographic mechanics. Auckland Bioengineering Institute, The University of Auckland, Auckland
Dormand EL, Banwell PE, EE Goodacre T (2005) Radiotherapy and wound healing. Int Wound J 2(2):112–117 (Blackwell Publishing Ltd and Medicalhelplines.com Inc)
Mi Q, Riviere B, Clermont G, Steed DL, Vodovotz Y (2007) Agentbased model of inflammation and wound healing: insights into diabetic foot ulcer pathology and the role of transforming growth factor-β1. Wound Repair Regen 15:671–682
Peirce SM (2008) Computational and mathematical modeling of angiogenesis. Microcirculation 15:739–751
Rodriguez E, Hoger A, McCulloch A (1994) Stress-dependent finite growth in soft elastic tissues. J Biomech 27(4):455–467
Garbey M, Bass B, Berceli S (2012) Multiscale mechanobiology modeling for surgery assessment. Acta Mech Sin 28(4):1176–1192
Garbey M, Salmon R, Thanoon D, Bass B (2013) Multiscale modeling and distributed computing to predict cosmesis outcome after a lumpectomy. J Comput Phys 244:321–335 (available on line 23 August 2012)
Acknowledgments
This work was partially funded by the Methodist Research Institute, the Partner University Funds and the Atlantis Program.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer New York
About this chapter
Cite this chapter
Bass, B.L., Garbey, M. (2014). A Road Map for Computational Surgery: Challenges and Opportunities. In: Garbey, M., Bass, B., Berceli, S., Collet, C., Cerveri, P. (eds) Computational Surgery and Dual Training. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8648-0_1
Download citation
DOI: https://doi.org/10.1007/978-1-4614-8648-0_1
Published:
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4614-8647-3
Online ISBN: 978-1-4614-8648-0
eBook Packages: EngineeringEngineering (R0)