Skip to main content

Advertisement

Log in

Dynamic infrared thermography (DIRT) for assessment of skin blood perfusion in cranioplasty: a proof of concept for qualitative comparison with the standard indocyanine green video angiography (ICGA)

  • Original Article
  • Published:
International Journal of Computer Assisted Radiology and Surgery Aims and scope Submit manuscript

Abstract

Purpose

Complications in wound healing after neurosurgical operations occur often due to scarred dehiscence with skin blood perfusion disturbance. The standard imaging method for intraoperative skin perfusion assessment is the invasive indocyanine green video angiography (ICGA). The noninvasive dynamic infrared thermography (DIRT) is a promising alternative modality that was evaluated by comparison with ICGA.

Methods

The study was carried out in two parts: (1) investigation of technical conditions for intraoperative use of DIRT for its comparison with ICGA, and (2) visual and quantitative comparison of both modalities in a proof of concept on nine patients. Time–temperature curves in DIRT and time–intensity curves in ICGA for defined regions of interest were analyzed. New perfusion parameters were defined in DIRT and compared with the usual perfusion parameters in ICGA.

Results

The visual observation of the image data in DIRT and ICGA showed that operation material, anatomical structures and skin perfusion are represented similarly in both modalities. Although the analysis of the curves and perfusion parameter values showed differences between patients, no complications were observed clinically. These differences were represented in DIRT and ICGA equivalently.

Conclusions

DIRT has shown a great potential for intraoperative use, with several advantages over ICGA. The technique is passive, contactless and noninvasive. The practicability of the intraoperative recording of the same operation field section with ICGA and DIRT has been demonstrated. The promising results of this proof of concept provide a basis for a trial with a larger number of patients.

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

Access this article

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

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

References

  1. de Bonis P, Frassanito P, Mangiola A, Nucci CG, Anile C, Pompucci A (2012) Cranial repair: how complicated is filling a “hole”? J Neurotrauma 29:1071–1076. https://doi.org/10.1089/neu.2011.2116

  2. Riordan MA, Simpson VM, Hall WA (2016) Analysis of factors contributing to infections after cranioplasty: a single-institution retrospective chart review. World Neurosurg 87:207–213. https://doi.org/10.1016/j.wneu.2015.11.070

    Article  PubMed  Google Scholar 

  3. Reddy S, Khalifian S, Flores JM, Bellamy J, Manson PN, Rodriguez ED, Dorafshar AH (2014) Clinical outcomes in cranioplasty: risk factors and choice of reconstructive material. Plast Reconstr Surg 133:864–873. https://doi.org/10.1097/PRS.0000000000000013

    Article  CAS  PubMed  Google Scholar 

  4. Wachter D, Reineke K, Behm T, Rohde V (2013) Cranioplasty after decompressive hemicraniectomy: underestimated surgery-associated complications? Clin Neurol Neurosurg 115:1293–1297. https://doi.org/10.1016/j.clineuro.2012.12.002

    Article  PubMed  Google Scholar 

  5. Giese H, Sauvigny T, Sakowitz OW, Bierschneider M, Güresir E, Henker C, Höhne J, Lindner D, Mielke D, Pannewitz R, Rohde V, Scholz M, Schuss P, Regelsberger J (2015) German Cranial Reconstruction Registry (GCRR): protocol for a prospective, multicentre, open registry. BMJ Open 5:e009273

    Article  PubMed  PubMed Central  Google Scholar 

  6. Lindner D, Schlothofer-Schumann K, Kern B-C, Marx O, Müns A, Meixensberger J (2017) Cranioplasty using custom-made hydroxyapatite versus titanium: a randomized clinical trial. J Neurosurg 126(1):175–183

    Article  PubMed  Google Scholar 

  7. Holm C (2010) Clinical applications of ICG fluorescence imaging in plastic and reconstructive surgery. Open Surg Oncol J 2:37–47

    Article  Google Scholar 

  8. McGregor AD, McGregor IA (2000) Fundamental techniques of plastic surgery and their surgical applications, 10th edn. Churchill Livingstone, London, New York

    Google Scholar 

  9. Ishihara H, Otomo N, Suzuki A, Takamura K, Tsubo T, Matsuki A (1998) Detection of capillary protein leakage by glucose and indocyanine green dilutions during the early post-burn period. Burns 24:525–531

    Article  CAS  PubMed  Google Scholar 

  10. Toogood JH (1987) Beta-blocker therapy and the risk of anaphylaxis. CMAJ 136:929–933

    CAS  PubMed  PubMed Central  Google Scholar 

  11. Speich R, Saesseli B, Hoffmann U, Neftel KA, Reichen J (1988) Anaphylactoid reactions after indocyanine-green administration. Ann Intern Med 109:345–346

    Article  CAS  PubMed  Google Scholar 

  12. Lohman RF, Ozturk CN, Ozturk C, Jayaprakash V, Djohan R (2015) An analysis of current techniques used for intraoperative flap evaluation. Ann Plast Surg 75:679–685. https://doi.org/10.1097/SAP.0000000000000235

    Article  CAS  PubMed  Google Scholar 

  13. Muntean MV, Strilciuc S, Ardelean F, Pestean C, Lacatus R, Badea AF, Georgescu A (2015) Using dynamic infrared thermography to optimize color Doppler ultrasound mapping of cutaneous perforators. Med Ultrasono 17:503–508. https://doi.org/10.11152/mu.2013.2066.174.dyn

    Google Scholar 

  14. Klaessens JHGM, Nelisse M, Verdaasdonk RM, Noordmans HJ (2013) Non-contact tissue perfusion and oxygenation imaging using a LED based multispectral and a thermal imaging system, first results of clinical intervention studies. Adv Biomed Clin Diagn Syst XI 8572:857207. https://doi.org/10.1117/12.2003807

    Article  Google Scholar 

  15. de Weerd L, Mercer JB, Setsa LB (2006) Intraoperative dynamic infrared thermography and free-flap surgery. Ann Plast Surg 57:279–284. https://doi.org/10.1097/01.sap.0000218579.17185.c9

    Article  PubMed  Google Scholar 

  16. de Weerd L, Weum S, Mercer JB (2009) The value of dynamic infrared thermography (DIRT) in perforator selection and planning of free DIEP flaps. Ann Plast Surg 63:274–279. https://doi.org/10.1097/SAP.0b013e318190321e

    Article  PubMed  Google Scholar 

  17. Ring EF, Ammer K (2012) Infrared thermal imaging in medicine. Physiol Meas 33:R33–46. https://doi.org/10.1088/0967-3334/33/3/R33

    Article  CAS  PubMed  Google Scholar 

  18. Gerasimova E, Audit B, Roux SG, Khalil A, Gileva O, Argoul F, Naimark O, Arneodo A (2014) Wavelet-based multifractal analysis of dynamic infrared thermograms to assist in early breast cancer diagnosis. Front Physiol 5:176. https://doi.org/10.3389/fphys.2014.00176

    Article  PubMed  PubMed Central  Google Scholar 

  19. Jiang L, Zhan W, Loew MH (2011) Modeling static and dynamic thermography of the human breast under elastic deformation. Phys Med Biol 56:187–202. https://doi.org/10.1088/0031-9155/56/1/012

    Article  PubMed  Google Scholar 

  20. Cruz-Ramírez N, Mezura-Montes E, Ameca-Alducin MY, Martín-Del-Campo-Mena E, Acosta-Mesa HG, Pérez-Castro N, Guerra-Hernández A, Hoyos-Rivera GdJ, Barrientos-Martínez RE (2013) Evaluation of the diagnostic power of thermography in breast cancer using Bayesian network classifiers. Comput Math Methods Med 2013:264246. https://doi.org/10.1155/2013/264246

    Google Scholar 

  21. Pirtini Çetingül M, Herman C (2011) Quantification of the thermal signature of a melanoma lesion. Int J Therm Sci 50:421–431. https://doi.org/10.1016/j.ijthermalsci.2010.019

    Article  Google Scholar 

  22. Szentkuti A, Kavanagh HS, Grazio S (2011) Infrared thermography and image analysis for biomedical use. Period Biol 113:385–392

    Google Scholar 

  23. Jin C, Yang Y, Zu-Jun X, Liu KM, Liu J (2013) Automated analysis method for screening knee osteoarthritis using medical infrared thermography. J Med Biol Eng 33:471. https://doi.org/10.5405/jmbe.1054

    Article  Google Scholar 

  24. Kateb B, Yamamoto V, Yu C, Grundfest W, Gruen JP (2009) Infrared thermal imaging: a review of the literature and case report. Neuroimage 47:T154–62. https://doi.org/10.1016/j.neuroimage.2009.03.043

    Article  PubMed  Google Scholar 

  25. Steiner G, Sobottka SB, Koch E, Schackert G, Kirsch M (2011) Intraoperative imaging of cortical cerebral perfusion by time-resolved thermography and multivariate data analysis. J Biomed Opt 16:16001. https://doi.org/10.1117/1.3528011

    Article  Google Scholar 

  26. Chubb DP, Taylor GI, Ashton MW (2013) True and ’choke’ anastomoses between perforator angiosomes: part II. Dynamic thermographic identification. Plast Reconstr Surg 132:1457–1464. https://doi.org/10.1097/01.prs.0000434407.73390.82

    Article  CAS  PubMed  Google Scholar 

  27. Just M, Chalopin C, Unger M, Halama D, Neumuth T, Dietz A, Fischer M (2015) Monitoring of microvascular free flaps following oropharyngeal reconstruction using infrared thermography: first clinical experiences. Eur Arch Otorhinolaryngol 273:2659–2667. https://doi.org/10.1007/s00405-015-3780-9

  28. Wilson SB, Spence VA (1989) Dynamic thermographic imaging method for quantifying dermal perfusion: potential and limitations. Med Biol Eng Comput 27:496–501

    Article  CAS  PubMed  Google Scholar 

  29. Igari K, Kudo T, Toyofuku T, Jibiki M, Inoue Y, Kawano T (2013) Quantitative evaluation of the outcomes of revascularization procedures for peripheral arterial disease using indocyanine green angiography. Eur J Vasc Endovasc Surg 46:460–465. https://doi.org/10.1016/j.ejvs.2013.07.016

    Article  CAS  PubMed  Google Scholar 

  30. Matsui A, Lee BT, Winer JH, Laurence RG, Frangioni JV (2009) Quantitative assessment of perfusion and vascular compromise in perforator flaps using a near-infrared fluorescence-guided imaging system. Plast Reconstr Surg 124:451–460. https://doi.org/10.1097/PRS.0b013e3181adcf7d

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Wilson SB, Spence VA (1988) A tissue heat transfer model for relating dynamic skin temperature changes to physiological parameters. Phys Med Biol 33:895–912

    Article  CAS  PubMed  Google Scholar 

  32. Preim B, Oeltze S, Mlejnek M, Gröeller E, Hennemuth A, Behrens S (2009) Survey of the visual exploration and analysis of perfusion data. IEEE Trans Vis Comput Graph 15:205–220. https://doi.org/10.1109/TVCG.2008.95

    Article  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to C. Chalopin.

Ethics declarations

Conflict of interest

The authors declare no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in the study.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Rathmann, P., Chalopin, C., Halama, D. et al. Dynamic infrared thermography (DIRT) for assessment of skin blood perfusion in cranioplasty: a proof of concept for qualitative comparison with the standard indocyanine green video angiography (ICGA). Int J CARS 13, 479–490 (2018). https://doi.org/10.1007/s11548-017-1683-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11548-017-1683-5

Keywords

Navigation