Can we predict necrosis intra-operatively? Real-time optical quantitative perfusion imaging in surgery: study protocol for a prospective, observational, in vivo pilot study

Sanne M Jansen, Daniel M de Bruin, Mark I van Berge Henegouwen, Simon D Strackee, Denise P Veelo, Ton G van Leeuwen, Suzanne S Gisbertz, Sanne M Jansen, Daniel M de Bruin, Mark I van Berge Henegouwen, Simon D Strackee, Denise P Veelo, Ton G van Leeuwen, Suzanne S Gisbertz

Abstract

Background: Compromised perfusion as a result of surgical intervention causes a reduction of oxygen and nutrients in tissue and therefore decreased tissue vitality. Quantitative imaging of tissue perfusion during reconstructive surgery, therefore, may reduce the incidence of complications. Non-invasive optical techniques allow real-time tissue imaging, with high resolution and high contrast. The objectives of this study are, first, to assess the feasibility and accuracy of optical coherence tomography (OCT), sidestream darkfield microscopy (SDF), laser speckle contrast imaging (LSCI), and fluorescence imaging (FI) for quantitative perfusion imaging and, second, to identify/search for criteria that enable risk prediction of necrosis during gastric tube and free flap reconstruction.

Methods: This prospective, multicenter, observational in vivo pilot study will assess tissue perfusion using four optical technologies: OCT, SDF, LSCI, and FI in 40 patients: 20 patients who will undergo gastric tube reconstruction after esophagectomy and 20 patients who will undergo free flap surgery. Intra-operative images of gastric perfusion will be obtained directly after reconstruction at four perfusion areas. Feasibility of perfusion imaging will be analyzed per technique. Quantitative parameters directly related to perfusion will be scored per perfusion area, and differences between biologically good versus reduced perfusion will be tested statistically. Patient outcome will be correlated to images and perfusion parameters. Differences in perfusion parameters before and after a bolus of ephedrine will be tested for significance.

Discussion: This study will identify quantitative perfusion-related parameters for an objective assessment of tissue perfusion during surgery. This will likely allow early risk stratification of necrosis development, which will aid in achieving a reduction of complications in gastric tube reconstruction and free flap transplantation.

Trial registration: Clinicaltrials.gov registration number NCT02902549. Dutch Central Committee on Research Involving Human Subjects registration number NL52377.018.15.

Keywords: Accuracy; Anastomotic leakage; Feasibility; Fluorescence imaging; Laser speckle contrast imaging; Monitoring; Necrosis; Optical coherence tomography; Optical technologies; Perfusion; Risk prediction; Sidestream darkfield microscopy.

Conflict of interest statement

Ethics approval and consent to participate

This study is approved by the medical ethical committee of the Academic Medical Center, Amsterdam (2015_057). The protocol is registered by The Dutch Central Committee on Research Involving Human Subjects (NL52377.018.15). Also, this study is submitted at the Consent for publication

Not applicable

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Figures

Fig. 1
Fig. 1
Study protocol flowchart
Fig. 2
Fig. 2
Gastric tube with four image areas and perfusion bar: good-reduced
Fig. 3
Fig. 3
Flap with four image areas and perfusion bar: good-reduced [37]

References

    1. Futier E, Robin E, Jabaudon M, Guerin R, Petit A, Bazin J-E, et al. Central venous O2 saturation and venous-to-arterial CO2 difference as complementary tools for goal-directed therapy during high-risk surgery. Crit Care. 2010;14:R193. doi: 10.1186/cc9310.
    1. Ng JM. Perioperative anesthetic management for Esophagectomy. Anesthesiol Clin. 2008;26:293–304. doi: 10.1016/j.anclin.2008.01.004.
    1. van Hagen P, Hulshof MCCMC, van Lanschot JJBJ, Steyerberg EWW, van Berge Henegouwen MI, Wijnhoven BPLP, et al. Preoperative chemoradiotherapy for esophageal or junctional cancer. N Engl J Med. 2012;366:2074–2084. doi: 10.1056/NEJMoa1112088.
    1. van Heijl M, Gooszen JA, Fockens P, Busch OR, van Lanschot JJ, van Berge Henegouwen MI. Risk factors for development of benign cervical strictures after esophagectomy. Ann Surg. 2010;251:1064–1069. doi: 10.1097/SLA.0b013e3181deb4b7.
    1. Hur C, Miller M, Kong CY, Dowling EC, Nattinger KJ, Dunn M, et al. Trends in esophageal adenocarcinoma incidence and mortality. Cancer. 2013;119:1149–1158. doi: 10.1002/cncr.27834.
    1. Wong AK, Nguyen TJ, Peric M, Shahbi MP, Vidar EN, Hwang BH, et al. Analysis of risk factors associated with microvascular free flap failure using a multi-institutional database. Microsurgery. 2010;30:242–248.
    1. American Society of Plastic Surgeons. 2015 Reconstructive Plastic Surgery Statistics, Reconstructive Procedure Trends, Plastic Surgery Statistics Report. 2014;2015. Available from:
    1. Huang D, Swanson EA, Lin CP, Schuman JS, Stinson WG, Chang W, et al. Optical coherence tomography. Science (80-. ). [Internet]. 1991 [cited 2015 Jun 1];254:1178–81. Available from:
    1. Grousson R, Mallick S. Study of flow pattern in a fluid by scattered laser light. Appl Opt. 1977;16:2334–2336. doi: 10.1364/AO.16.002334.
    1. Goedhart PT, Khalilzada M, Bezemer R, Merza J, Ince C. Sidestream dark field (SDF) imaging: a novel stroboscopic LED ring-based imaging modality for clinical assessment of the microcirculation. Opt Express. 2007;15:15101–15114. doi: 10.1364/OE.15.015101.
    1. Frangioni JV. In vivo near-infrared fluorescence imaging. Curr Opin Chem Biol. 2003;7:626–634. doi: 10.1016/j.cbpa.2003.08.007.
    1. White B, Pierce M, Nassif N, Cense B, Park B, Tearney G, et al. In vivo dynamic human retinal blood flow imaging using ultra-high-speed spectral domain optical coherence tomography. Opt. Express [Internet]. 2003;11:3490. Available from: Papers/W/White et al. 200.
    1. Wessels R, De Bruin DM, Faber DJ, Van Leeuwen TG, Van Beurden M, Ruers TJ. Optical biopsy of epithelial cancers by optical coherence tomography (OCT). Lasers Med Sci. 2013/03/19. Department of Surgical Oncology, Netherlands Cancer Institute-Antoni van Leeuwenhoek Hospital, PO Box 90203, Amsterdam, 1006 BE, The Netherlands, ronniwessels@gmail.com.; 2014;29:1297–305.
    1. McCulloch P, Altman DG, Campbell WB, Flum DR, Glasziou P, Marshall JC, et al. No surgical innovation without evaluation: the IDEAL recommendations. Lancet Elsevier Ltd. 2009;374:1105–1112. doi: 10.1016/S0140-6736(09)61116-8.
    1. Vandenbroucke JP, von Elm E, Altman DG, Gøtzsche PC, Mulrow CD, Pocock SJ, et al. Strengthening the Reporting of Observational Studies in Epidemiology (STROBE): explanation and elaboration. Int J Surg Elsevier Ltd. 2014;12:1500–1524. doi: 10.1016/j.ijsu.2014.07.014.
    1. Bossuyt PM. The STARD statement for reporting studies of diagnostic accuracy: explanation and elaboration. Clin Chem. 2003;49:7–18. doi: 10.1373/49.1.7.
    1. ICH. GUIDELINE FOR GOOD CLINICAL PRACTICE E6(R1). 2016;6.
    1. World Medical Association. Declaration of Helsinki World Medical Association Declaration of Helsinki. 2001;79.
    1. Low DE, Alderson D, Cecconello I, Chang AC, Darling GE, Journo XBD, et al. International consensus on standardization of data collection for complications associated with esophagectomy. Ann Surg. 2015;262
    1. Borenstein M, Hedges LV, Higgins JPT, Rothstein HR. Introduction to meta-analysis. John Wiley Sons 2009;21–32.
    1. Cohen J. Statistical Power Analysis for the Behavioral Sciences (2nd ed.) [Internet]. Stat. Power Anal. Behav. Sci. 1988. Available from: .
    1. Fleiss J, Cohen J. The equivalence of weighted kappa and the intraclass correlation coefficient as measures of reliability. 1973. p. 613–9.
    1. Landis JR, Koch GG. The measurement of observer agreement for categorical data. Biometrics. 1977;33:159–174. doi: 10.2307/2529310.
    1. Huang D, Swanson EA, Lin CP, Schuman JS, Stinson WG, Chang W, et al. Optical coherence tomography. Science. 1991;254:1178–1181. doi: 10.1126/science.1957169.
    1. Balestra GM, Bezemer R, Boerma EC, Yong Z-Y, Sjauw KD, Engstrom AE, et al. Improvement of sidestream dark field imaging with an image acquisition stabilizer. BMC Med Imaging. 2010;10:15. doi: 10.1186/1471-2342-10-15.
    1. Dobbe JGG, Streekstra GJ, Atasever B, van Zijderveld R, Ince C. Measurement of functional microcirculatory geometry and velocity distributions using automated image analysis. Med Biol Eng Comput. 2008;46:659–670. doi: 10.1007/s11517-008-0349-4.
    1. De Backer D, Ospina-Tascon G, Sagado D, Favory R, Creteur J, Vincent JL. Monitoring the microcirculation in the critically ill patient: current methods and future approaches. Intensive Care Med. 2010;36:1813–1825. doi: 10.1007/s00134-010-2005-3.
    1. Senarathna J, Member S, Rege A, Li N, Thakor NV. Laser speckle contrast imaging: theory, instrumentation and applications. 2013;6:99–110.
    1. Briers D, Duncan DD, Hirst E, Kirkpatrick Sean J, Marcus L, Steenbergen W, Stromberg T, Thompson OB. Laser speckle contrast imaging: theoretical and practical limitations. J Biomed Opt. 2013;18:066018–066011. doi: 10.1117/1.JBO.18.6.066018.
    1. Jansen SM, de Bruin DM, Faber DJ, Dobbe IJGG, Heeg E, Milstein DMJ, Strackee SD, van Leeuwen TG. Applicability of quantitative optical imaging techniques for intraoperative perfusion diagnostics: a comparison of laser speckle contrast imaging, sidestream dark-field microscopy, and optical coherence tomography. J Biomed Opt. 2017;22(8):086004.
    1. Wong RCK, Yazdanfar S, Izatt JA, Kulkarni MD, Barton JK, Welch AJ, et al. Visualization of subsurface blood vessels by color Doppler optical coherence tomography in rats: before and after hemostatic therapy. Gastrointest Endosc. 2002;55:88–95. doi: 10.1067/mge.2002.120104.
    1. Turek Z, Černý V, Pařízková R. Noninvasive in vivo assessment of the skeletal muscle and small intestine serous surface microcirculation in rat: sidestream dark-field (SDF) imaging. Physiol Res. 2008;57:365–371.
    1. de Bruin AFJ, Kornmann VNN, van der Sloot K, van Vugt JL, Gosselink MP, Smits A, et al. Sidestream dark field imaging of the serosal microcirculation during gastrointestinal surgery. Color Dis. 2016;18:O103–O110. doi: 10.1111/codi.13250.
    1. Klijn E, Niehof S, De Jonge J, Gommers D, Ince C, Van Bommel J. The effect of perfusion pressure on gastric tissue blood flow in an experimental gastric tube model. Anesth Analg. 2010;110:541–546. doi: 10.1213/ANE.0b013e3181c84e33.
    1. Milstein DMJ, Ince C, Gisbertz SS, Boateng KB, Geerts BF, Hollmann MW, et al. Laser speckle contrast imaging identifies ischemic areas on gastric tube reconstructions following esophagectomy. Medicine (Baltimore). 2016;95.
    1. Zehetner J, DeMeester SR, Alicuben ET, Oh DS, Lipham JC, Hagen JA et al. Intraoperative assessment of perfusion of the gastric graft and correlation with anastomotic leaks after esophagectomy. Ann Surg 2014;0:1–5. Available from: .
    1. Schrey A. Free flap monitoring using tissue oxygen measurement and positron emission tomography. Turku, Finland; 2009.

Source: PubMed

スポンサーと協力者

医学的状態

薬物療法

3
購読する