Skip to main content
SpringerLink
Log in

Hyperspektral-Imaging bei gastrointestinalen Anastomosen

Hyperspectral imaging of gastrointestinal anastomoses

  • Originalien
  • Published:
Der Chirurg Aims and scope Submit manuscript

Zusammenfassung

Einleitung

Anastomoseninsuffizienzen (AIs) sind die schwerwiegendsten Komplikationen in der gastrointestinalen Chirurgie mit assoziierter Verlängerung des stationären Aufenthalts und signifikanter Mortalität. Hyperspektralbildgebung („hyperspectral imaging“, HSI) ist ein relativ neues Bildgebungsverfahren, das für die Erkennung von Strukturen und für die Auswertung der Gewebedurchblutung, -oxygenierung sowie dessen Wasserhaushalts in der Wundtherapie vielversprechende Ergebnisse gezeigt hat. Zur In-vivo-Beurteilung gastrointestinaler Anastomosen liegen allerdings bisher noch keine Daten vor.

Methodik

Es wurde die intraoperative HS-Bildgebung mit dem TIVITA™ Tissue-Kamerasystem der Firma Diaspective Vision GmbH (Pepelow, Deutschland) angewandt. Bei 47 Patienten mit gastrointestinalen (GI) Anastomosen an Ösophagus, Magen, Pankreas, Dünn- und Dickdarm sowie Rektum wurden 97 auswertbare Aufnahmen generiert. Es wurden an den Anastomosen die Parameter Gewebeoxygenierung („tissue O2 saturation“, StO2), Gewebe-Hämoglobin-Index („tissue hemoglobin index“, THI), Nahinfrarot-Perfusions-Index („near-infrared[NIR] perfusion index“) und Gewebe-Wasser-Index („tissue water index“, TWI) erhoben.

Ergebnisse

Die Anwendung der nichtinvasiven HSI war bei allen Anastomosierungen technisch gut praktikabel mit robusten Ergebnissen. Dabei fand sich ein NIR-Gradient längs und quer entlang der Anastomose. Auch die Gewebewasserverteilung und -oxygenierung zeigten spezifische Verläufe rund um die Anastomosenregion.

Schlussfolgerung

HSI bietet als kontaktfreie, nichtinvasive und kontrastmittellose intraoperative Bildgebungsmethode eine objektive Real-time-Messung physiologischer Anastomosenparameter, die möglicherweise dazu beitragen kann, die „ideale“ Anastomosenregion/-höhe zu determinieren. Hierzu ist eine weitere Etablierung der Methodik in der Viszeralchirurgie mit Generierung von Norm- bzw. Cut-off-Werten für die unterschiedlichen intestinalen Anastomosenarten erforderlich.

Abstract

Introduction

Anastomotic insufficiency (AI) remains the most feared surgical complication in gastrointestinal surgery, which is closely associated with a prolonged inpatient hospital stay and significant postoperative mortality. Hyperspectral imaging (HSI) is a relatively new medical imaging procedure which has proven to be promising in tissue identification as well as in the analysis of tissue oxygenation and water content. Until now, no data exist on the in vivo HSI analysis of gastrointestinal anastomoses.

Methods

Intraoperative images were obtained using the TIVITA™ tissue system HSI camera from Diaspective Vision GmbH (Pepelow, Germany). In 47 patients who underwent gastrointestinal surgery with esophageal, gastric, pancreatic, small bowel or colorectal anastomoses, 97 assessable recordings were generated. Parameters obtained at the sites of the anastomoses included tissue oxygenation (StO2), the tissue hemoglobin index (THI), near-infrared (NIR) perfusion index, and tissue water index (TWI).

Results

Obtaining and analyzing the intraoperative images with this non-invasive imaging system proved practicable and delivered good results on a consistent basis. A NIR gradient along and across the anastomosis was observed and, furthermore, analysis of the tissue water and oxygenation content showed specific changes at the site of anastomosis.

Conclusion

The HSI method provides a non-contact, non-invasive, intraoperative imaging procedure without the use of a contrast medium, which enables a real-time analysis of physiological anastomotic parameters, which may contribute to determine the ”ideal“ anastomotic region. In light of this, the establishment of this methodology in the field of visceral surgery, enabling the generation of normal or cut off values for different gastrointestinal anastomotic types, is an obvious necessity.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Abb. 1
Abb. 2
Abb. 3
Abb. 4
Abb. 5

Literatur

  1. Rogalski P, Daniluk J, Baniukiewicz A, Wroblewski E, Dabrowski A (2015) Endoscopic management of gastrointestinal perforations, leaks and fistulas. World J Gastroenterol 21:10542–10552

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  2. Telem DA, Chin EH, Nguyen SQ, Divino CM (2010) Risk factors for anastomotic leak following colorectal surgery: a case-control study. Arch Surg 145:371–376 (discussion 376)

    Article  PubMed  Google Scholar 

  3. Frasson M, Flor-Lorente B, Rodríguez JL, Granero-Castro P, Hervás D, Alvarez RMA, Brao MJ, Sánchez González JM, Garcia-Granero E, ANACO Study Group (2015) Risk factors for anastomotic leak after colon resection for cancer: multivariate analysis and nomogram from a multicentric, prospective, national study with 3193 patients. Ann Surg 262:321–330

    Article  PubMed  Google Scholar 

  4. Pommergaard HC, Gessler B, Burcharth J, Angenete E, Haglind E, Rosenberg J (2014) Preoperative risk factors for anastomotic leakage after resection for colorectal cancer: a systematic review and meta-analysis. Colorectal Dis 16:662–671

    Article  PubMed  CAS  Google Scholar 

  5. Kingham TP, Pachter HL (2009) Colonic anastomotic leak: risk factors, diagnosis, and treatment. J Am Coll Surg 208:269–278

    Article  PubMed  Google Scholar 

  6. Akça O (2011) Managing intraoperative blood pressure with norepinephrine: effects on perfusion and oxygenation of the intestinal tract. Anesthesiology 114:488–489

    Article  PubMed  Google Scholar 

  7. Goh SL, De Silva RP, Dhital K, Gett RM (2015) Is low serum albumin associated with postoperative complications in patients undergoing oesophagectomy for oesophageal malignancies? Interact Cardiovasc Thorac Surg 20:107–113

    Article  PubMed  Google Scholar 

  8. Nessim C, Sidéris L, Turcotte S, Vafiadis P, Lapostole AC, Simard S, Koch P, Fortier LP, Dubé P (2013) The effect of fluid overload in the presence of an epidural on the strength of colonic anastomoses. J Surg Res 183:567–573

    Article  PubMed  Google Scholar 

  9. Glatz T, Boldt J, Timme S, Kulemann B, Seifert G, Holzner PA, Chikhladze S, Grüneberger JM, Küsters S, Sick O, Höppner J, Hopt UT, Marjanovic G (2014) Impact of intraoperative temperature and humidity on healing of intestinal anastomoses. Int J Colorectal Dis 29:469–475

    Article  PubMed  Google Scholar 

  10. Hoffmann H, Delko T, Kirchhoff P, Rosenthal R, Schäfer J, Kraljevic M, Kettelhack C (2017) Colon perfusion patterns during colorectal resection using visible light spectroscopy. World J Surg. https://doi.org/10.1007/s00268-017-4100-x

    Article  PubMed  Google Scholar 

  11. Karliczek A, Harlaar NJ, Zeebregts CJ, Wiggers T, Baas PC, van Dam GM (2009) Surgeons lack predictive accuracy for anastomotic leakage in gastrointestinal surgery. Int J Colorectal Dis 24:569–576

    Article  PubMed  CAS  Google Scholar 

  12. Wada T, Kawada K, Takahashi R, Yoshitomi M, Hida K, Hasegawa S, Sakai Y (2017) ICG fluorescence imaging for quantitative evaluation of colonic perfusion in laparoscopic colorectal surgery. Surg Endosc. https://doi.org/10.1007/s00464-017-5475-3

    Article  PubMed  Google Scholar 

  13. Kudszus S, Roesel C, Schachtrupp A, Hoer JJ (2010) Intraoperative laser fluorescence angiography in colorectal surgery: a noninvasive analysis to reduce the rate of anastomotic leakage. Langenbecks Arch Surg 395:1025–1030

    Article  PubMed  Google Scholar 

  14. Jafari MD, Lee KH, Halabi WJ, Mills SD, Carmichael JC, Stamos MJ, Pigazzi A (2013) The use of indocyanine green fluorescence to assess anastomotic perfusion during robotic assisted laparoscopic rectal surgery. Surg Endosc 27:3003–3008

    Article  PubMed  Google Scholar 

  15. Hellan M, Spinoglio G, Pigazzi A, Lagares-Garcia JA (2014) The influence of fluorescence imaging on the location of bowel transection during robotic left-sided colorectal surgery. Surg Endosc 28:1695–1702

    Article  PubMed  Google Scholar 

  16. Jafari MD, Wexner SD, Martz JE, McLemore EC, Margolin DA, Sherwinter DA, Lee SW, Senagore AJ, Phelan MJ, Stamos MJ (2015) Perfusion assessment in laparoscopic left-sided/anterior resection (PILLAR II): a multi-institutional study. J Am Coll Surg 220:82–92

    Article  PubMed  Google Scholar 

  17. Degett TH, Andersen HS, Gögenur I (2016) Indocyanine green fluorescence angiography for intraoperative assessment of gastrointestinal anastomotic perfusion: a systematic review of clinical trials. Langenbecks Arch Surg 401:767–775

    Article  PubMed  Google Scholar 

  18. Kawada K, Hasegawa S, Wada T, Takahashi R, Hisamori S, Hida K, Sakai Y (2017) Evaluation of intestinal perfusion by ICG fluorescence imaging in laparoscopic colorectal surgery with DST anastomosis. Surg Endosc 31:1061–1069

    Article  PubMed  Google Scholar 

  19. Lu G, Fei B (2014) Medical hyperspectral imaging: a review. J Biomed Opt 19:10901

    Article  PubMed  CAS  Google Scholar 

  20. Khouj Y, Dawson J, Coad J, Vona-Davis L (2017) Abstract B16. The detection of ductal carcinoma using noninvasive hyperspectral imaging. Cancer Res 77(2 Supplement):B16–B16. https://doi.org/10.1158/1538-7445.EPSO16-B16

    Article  Google Scholar 

  21. Goto A, Nishikawa J, Kiyotoki S, Nakamura M, Nishimura J, Okamoto T, Ogihara H, Fujita Y, Hamamoto Y, Sakaida I (2015) Use of hyperspectral imaging technology to develop a diagnostic support system for gastric cancer. J Biomed Opt 20:16017

    Article  PubMed  Google Scholar 

  22. Pike R, Lu G, Wang D, Chen ZG, Fei B (2016) A minimum spanning forest-based method for noninvasive cancer detection with hyperspectral imaging. IEEE Trans Biomed Eng 63:653–663

    Article  PubMed  Google Scholar 

  23. Akbari H, Uto K, Kosugi Y, Kojima K, Tanaka N (2011) Cancer detection using infrared hyperspectral imaging. Cancer Sci 102:852–857

    Article  PubMed  CAS  Google Scholar 

  24. Kumashiro R, Konishi K, Chiba T, Akahoshi T, Nakamura S, Murata M, Tomikawa M, Matsumoto T, Maehara Y, Hashizume M (2016) Integrated endoscopic system based on optical imaging and hyperspectral data analysis for colorectal cancer detection. Anticancer Res 36:3925–3932

    PubMed  CAS  Google Scholar 

  25. Ravi D, Fabelo H, Callic GM, Yang GZ (2017) Manifold embedding and semantic segmentation for intraoperative guidance with hyperspectral brain imaging. IEEE Trans Med Imaging 36:1845–1857

    Article  PubMed  Google Scholar 

  26. Schols RM, ter Laan M, Stassen LPS, Bouvy ND, Amelink A, Wieringa FP, Alic L (2014) Differentiation between nerve and adipose tissue using wide-band (350-1,830 nm) in vivo diffuse reflectance spectroscopy. Lasers Surg Med 46:538–545

    Article  PubMed  Google Scholar 

  27. Sumpio BJ, Citoni G, Chin JA, Sumpio BE (2016) Use of hyperspectral imaging to assess endothelial dysfunction in peripheral arterial disease. J Vasc Surg 64:1066–1073

    Article  PubMed  Google Scholar 

  28. Allen J, Howell K (2014) Microvascular imaging: techniques and opportunities for clinical physiological measurements. Physiol Meas 35:R91–R141. https://doi.org/10.1088/0967-3334/35/7/R91

    Article  PubMed  Google Scholar 

  29. Holmer A, Tetschke F, Marotz J, Malberg H, Markgraf W, Thiele C, Kulcke A (2016) Oxygenation and perfusion monitoring with a hyperspectral camera system for chemical based tissue analysis of skin and organs. Physiol Meas 37:2064–2078

    Article  PubMed  Google Scholar 

  30. Holmer A, Kämmerer PW, Dau M, Grambow E, Wahl P (2017) The ability of hyperspectral imaging to detect perfusion disorders. In: Dehghani H, Wabnitz H (Hrsg) Diffuse optical spectroscopy and imaging VI Proc. of SPIE-OSA Vol. 10412 1041213-1. SPIE. https://doi.org/10.1117/12.2286207

  31. Grambow E, Dau M, Holmer A, Lipp V, Frerich B, Klar E, Vollmar B, Kämmerer PW (2017) Hyperspectral imaging for monitoring of perfusion failure upon microvascular anastomosis in the rat hind limb. Microvasc Res. https://doi.org/10.1016/j.mvr.2017.10.005

    Article  PubMed  Google Scholar 

  32. Chin MS, Freniere BB, Lo YC, Saleeby JH, Baker SP, Strom HM, Ignotz RA, Lalikos JF, Fitzgerald TJ (2012) Hyperspectral imaging for early detection of oxygenation and perfusion changes in irradiated skin. J Biomed Opt 17:26010

    Article  PubMed  CAS  Google Scholar 

  33. Denstedt M, Pukstad BS, Paluchowski LA, Hernandez-Palacios JE, Randeberg LL (2013) Hyperspectral imaging as a diagnostic tool for chronic skin ulcers. In: Kollias N, Choi B, Zeng H, Kang HW, Knudsen BE, Wong BJ et al (Hrsg) SPIE BiOS SPIE, San Francisco, 02.2.2013. SPIE (SPIE Proceedings 85650N)

  34. Myers D, McGraw M, George M, Mulier K, Beilman B (2009) Tissue hemoglobin index: a non-invasive optical measure of total tissue hemoglobin. Crit Care 13(Suppl 5):S2

    Article  PubMed  PubMed Central  Google Scholar 

  35. Calin MA, Coman T, Parasca SV, Bercaru N, Savastru R, Manea D (2015) Hyperspectral imaging-based wound analysis using mixture-tuned matched filtering classification method. J Biomed Opt 20:46004

    Article  PubMed  Google Scholar 

  36. Paul DW, Ghassemi P, Ramella-Roman JC, Prindeze NJ, Moffatt LT, Alkhalil A, Shupp JW (2015) Noninvasive imaging technologies for cutaneous wound assessment: a review. Wound Repair Regen 23:149–162

    Article  PubMed  Google Scholar 

  37. Fox PM, Zeidler K, Carey J, Lee GK (2013) White light spectroscopy for free flap monitoring. Microsurgery 33:198–202

    Article  PubMed  Google Scholar 

  38. Zuzak KJ, Naik SC, Alexandrakis G, Hawkins D, Behbehani K, Livingston EH (2007) Characterization of a near-infrared laparoscopic hyperspectral imaging system for minimally invasive surgery. Anal Chem 79:4709–4715

    Article  PubMed  CAS  Google Scholar 

  39. Leitner R, De Biasio M, Arnold T et al (2013) Multi-spectral video endoscopy system for the detection of cancerous tissue. Pattern Recognit Lett 34:85–93

    Article  Google Scholar 

  40. Marotz J, Siafliakis A, Holmer A, Kulcke A, Siemers F (2015) First results of a new hyperspectral camera system for chemical based wound analysis. Wound Med 10–11:17–22

    Article  Google Scholar 

  41. Tetschke F, Markgraf W, Gransow M, Koch S, Thiele C, Kulcke A, Malberg H (2016) Hyperspectral imaging for monitoring oxygen saturation levels during normothermic kidney perfusion. J Sens Sens Syst 5:1–6

    Article  Google Scholar 

  42. Daeschlein G, Langner I, Wild T, von Podewils S, Sicher C, Kiefer T, Jünger M (2017) Hyperspectral imaging as a novel diagnostic tool in microcirculation of wounds. Clin Hemorheol Microcirc. https://doi.org/10.3233/CH-179228

    Article  PubMed  Google Scholar 

  43. Mühle R, Oelschlägel M, Sobottka SB, Kirsch M, Schackert G, Morgenstern U (2017) Workflow for intraoperative hyperspectral imaging in neurosurgery; session 20: hyperspectral imaging and optical techniques in medicine FS 22. Biomed Eng 62(s1):S71–S74. https://doi.org/10.1515/bmt-2017-5019 (Abstracts – BMTMedPhys 2017 – Dresden, September 10–13)

    Article  Google Scholar 

  44. Keller A (2009) A new dagnostic algorithm for early prediction of vascular compromise in 208 microsurgical flaps using tissue oxygen saturation measurements. Ann Plast Surg 62:538–543

    Article  PubMed  CAS  Google Scholar 

  45. Jafari-Saraf L, Wilson SE, Gordon IL (2012) Hyperspectral image measurements of skin hemoglobin compared with transcutaneous PO2 measurements. Ann Vasc Surg 26:537–548

    Article  PubMed  Google Scholar 

  46. Philimon SP, Huong AKC, Hafizah WM, Ong PE, Ngu XTI (2016) Optical investigation of variability in body region dependent transcutaneous oxygen saturation. IOP Conf Ser Mater Sci Eng 160:12089. https://doi.org/10.1088/1757-899X/160/1/012089 (International Engineering Research and Innovation Symposium (IRIS))

    Article  Google Scholar 

  47. Fife CE, Smart DR, Sheffield PJ, Hopf HW, Hawkins G, Clarke D (2009) Transcutaneous oximetry in clinical practice: consensus statements from an expert panel based on evidence. Undersea Hyperb Med 36:43–53

    PubMed  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Klinik für Viszeral‑, Transplantations‑, Thorax- und Gefäßchirurgie, Universitätsklinikum Leipzig AöR, Liebigstr. 20, 04103, Leipzig, Deutschland

    B. Jansen-Winkeln, J. P. Takoh, S. M. Rabe, M. Barberio &  I. Gockel MBA

  2. Innovation Center Computer Assisted Surgery (ICCAS), Universität Leipzig, Leipzig, Deutschland

    M. Maktabi, H. Köhler, T. Neumuth, A. Melzer & C. Chalopin

  3. Institut de Recherche contre les Cancers de l’Appareil Digestive (IRCAD), Straßburg, Frankreich

    M. Barberio

Authors
  1. B. Jansen-Winkeln
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. M. Maktabi
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. J. P. Takoh
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. S. M. Rabe
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. M. Barberio
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. H. Köhler
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. T. Neumuth
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. A. Melzer
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. C. Chalopin
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. I. Gockel MBA
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to I. Gockel MBA.

Ethics declarations

Interessenkonflikt

B. Jansen-Winkeln, M. Maktabi, J. P. Takoh, S. M. Rabe, M. Barberio, H. Köhler, T. Neumuth, A. Melzer, C. Chalopin und I. Gockel geben an, dass kein Interessenkonflikt besteht.

Dieser Beitrag beinhaltet keine von den Autoren durchgeführten Studien an Menschen oder Tieren.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Jansen-Winkeln, B., Maktabi, M., Takoh, J.P. et al. Hyperspektral-Imaging bei gastrointestinalen Anastomosen. Chirurg 89, 717–725 (2018). https://doi.org/10.1007/s00104-018-0633-2

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00104-018-0633-2

Schlüsselwörter

Keywords

Search

Navigation