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Navigated tissue characterization during skin cancer surgery

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International Journal of Computer Assisted Radiology and Surgery Aims and scope Submit manuscript

Abstract

Purpose

Basal cell carcinoma (BCC) is the most commonly diagnosed skin cancer and is treated by surgical resection. Incomplete tumor removal requires surgical revision, leading to significant healthcare costs and impaired cosmesis. We investigated the clinical feasibility of a surgical navigation system for BCC surgery, based on molecular tissue characterization using rapid evaporative ionization mass spectrometry (REIMS).

Methods

REIMS enables direct tissue characterization by analysis of cell-specific molecules present within surgical smoke, produced during electrocautery tissue resection. A tissue characterization model was built by acquiring REIMS spectra of BCC, healthy skin and fat from ex vivo skin cancer specimens. This model was used for tissue characterization during navigated skin cancer surgery. Navigation was enabled by optical tracking and real-time visualization of the cautery relative to a contoured resection volume. The surgical smoke was aspirated into a mass spectrometer and directly analyzed with REIMS. Classified BCC was annotated at the real-time position of the cautery. Feasibility of the navigation system, and tissue classification accuracy for ex vivo and intraoperative surgery were evaluated.

Results

Fifty-four fresh excision specimens were used to build the ex vivo model of BCC, normal skin and fat, with 92% accuracy. While 3 surgeries were successfully navigated without breach of sterility, the intraoperative performance of the ex vivo model was low (< 50%). Hypotheses are: (1) the model was trained on heterogeneous mass spectra that did not originate from a single tissue type, (2) during surgery mixed tissue types were resected and thus presented to the model, and (3) the mass spectra were not validated by pathology.

Conclusion

REIMS-navigated skin cancer surgery has the potential to detect and localize remaining tumor intraoperatively. Future work will be focused on improving our model by using a precise pencil cautery tip for burning localized tissue types, and having pathology-validated mass spectra.

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References

  1. Mackiewicz-Wysocka M, Bowszyc-Dmochowska M, Strzelecka-Weklar D, Dańczak-Pazdrowska A, Adamski Z (2013) Basal cell carcinoma—diagnosis. Wspolczesna Onkologia 17:337–342. https://doi.org/10.5114/wo.2013.35684

    Article  PubMed  PubMed Central  Google Scholar 

  2. Verkouteren JAC, Ramdas KHR, Wakkee M, Nijsten T (2017) Epidemiology of basal cell carcinoma: scholarly review. Br J Dermatol 177:359–372. https://doi.org/10.1111/bjd.15321

    Article  CAS  PubMed  Google Scholar 

  3. Peris K, Fargnoli MC, Garbe C, Kaufmann R, Bastholt L, Seguin NB, Bataille V, Marmol VD, Dummer R, Harwood CA, Hauschild A, Höller C, Haedersdal M, Malvehy J, Middleton MR, Morton CA, Nagore E, Stratigos AJ, Szeimies RM, Tagliaferri L, Trakatelli M, Zalaudek I, Eggermont A, Grob JJ, European Dermatology Forum (EDF), the European Association of Dermato-Oncology (EADO) and the European Organization for Research and Treatment of Cancer (EORTC) (2019) Diagnosis and treatment of basal cell carcinoma: European consensus-based interdisciplinary guidelines. Eur J Cancer 118:10–34. https://doi.org/10.1016/j.ejca.2019.06.003

    Article  CAS  PubMed  Google Scholar 

  4. Dessinioti C, Antoniou C, Katsambas A, Stratigos AJ (2010) Basal cell carcinoma: what’s new under the sun. Photochem Photobiol 86:481–491. https://doi.org/10.1111/j.1751-1097.2010.00735.x

    Article  CAS  PubMed  Google Scholar 

  5. Alter M, Hillen U, Leiter U, Sachse M, Gutzmer R (2015) Current diagnosis and treatment of basal cell carcinoma. J Dtsch Dermatol Ges 13:863–874. https://doi.org/10.1111/ddg.12798

    Article  PubMed  Google Scholar 

  6. Wilson AW, Howsam G, Santhanam V, Macpherson D, Grant J, Pratt CA, Townend JV (2004) Surgical management of incompletely excised basal cell carcinomas of the head and neck. Br J Oral Maxillofac Surg 42:311–314

    Article  CAS  PubMed  Google Scholar 

  7. Nagore E, Grau C, Molinero J, Fortea J (2003) Positive margins in basal cell carcinoma: relationship to clinical features and recurrence risk. A retrospective study of 248 patients. J Eur Acad Dermatol Venereol 17:167–170

    Article  CAS  PubMed  Google Scholar 

  8. Liu F-F, Maki E, Warde P, Payne D, Fitzpatrick P (1989) A management approach to incompletely excised basal cell carcinomas of skin. Int J Radiat Oncol Biol Phys 20:423–428

    Article  Google Scholar 

  9. Sussman LAE, Liggins DF (1996) Incompletely excised basal cell carcinoma: a management dilemma? Aust N Z J Surg 66:276–278

    Article  CAS  PubMed  Google Scholar 

  10. Sexton M, Jones DB, Maloney ME (1990) Histologic pattern analysis of basal cell carcinoma. Study of a series of 1039 consecutive neoplasms. J Am Acad Dermatol 23:1118–1126

    Article  CAS  PubMed  Google Scholar 

  11. Agar NYR, Kowalski JM, Kowalski PJ, Wong JH, Agar JN (2010) Tissue preparation for the in situ MALDI MS imaging of proteins, lipids, and small molecules at cellular resolution. Methods Mol Biol 656:415–431

    Article  CAS  PubMed  Google Scholar 

  12. Santoro AL, Drummond RD, Silva IT, Ferreira SS, Juliano L, Vendramini PH, Lemos MBDC, Eberlin MN, Andrade VP (2020) In situ Desi-MSI lipidomic profiles of breast cancer molecular subtypes and precursor lesions. Cancer Res 80:1246–1257

    Article  CAS  PubMed  Google Scholar 

  13. Marcus D, Savage A, Balog J, Kudo H, Abda J, Dina R, Takats Z, Ghaem-Maghami S (2019) Endometrial cancer: can the iKnife diagnose endometrial cancer? Int J Gynecol Cancer 29:A100–A101

    Google Scholar 

  14. Balog J, Szaniszlo T, Schaefer KC, Denes J, Lopata A, Godorhazy L, Szalay D, Balogh L, Sasi-Szabo L, Toth M, Takats Z (2010) Identification of biological tissues by rapid evaporative ionization mass spectrometry. Anal Chem 82:7343–7350. https://doi.org/10.1021/ac101283x

    Article  CAS  PubMed  Google Scholar 

  15. Phelps DL, Balog J, Gildea LF, Bodai Z, Savage A, El-Bahrawy MA, Speller AV, Rosini F, Kudo H, McKenzie JS, Brown R, Takáts Z, Ghaem-Maghami S (2018) The surgical intelligent knife distinguishes normal, borderline and malignant gynaecological tissues using rapid evaporative ionisation mass spectrometry (REIMS). Br J Cancer 118:1349–1358. https://doi.org/10.1038/s41416-018-0048-3

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Lasso A, Heffter T, Rankin A, Pinter C, Ungi T, Fichtinger G (2014) PLUS: open-source toolkit for ultrasound-guided intervention systems. IEEE Trans Biomed Eng 61:2527–2537. https://doi.org/10.1109/tbme.2014.2322864

    Article  PubMed  PubMed Central  Google Scholar 

  17. Ungi T, Lasso A, Fichtinger G (2016) Open-source platforms for navigated image-guided interventions. Med Image Anal 33:181–186. https://doi.org/10.1016/j.media.2016.06.011

    Article  PubMed  Google Scholar 

  18. Fedorov A, Beichel R, Kalpathy-Cramer J, Finet J, Fillion-Robin JC, Pujol S, Bauer C, Jennings D, Fennessy F, Sonka M, Buatti J, Aylward S, Miller JV, Pieper S, Kikinis R (2012) 3D Slicer as an image computing platform for the Quantitative Imaging Network. Magn Reson Imaging 30:1323–1341. https://doi.org/10.1016/j.mri.2012.05.001

    Article  PubMed  PubMed Central  Google Scholar 

  19. St John ER, Balog J, McKenzie JS, Rossi M, Covington A, Muirhead L, Bodai Z, Rosini F, Speller AVM, Shousha S, Ramakrishnan R, Darzi A, Takats Z, Leff DR (2017) Rapid evaporative ionisation mass spectrometry of electrosurgical vapours for the identification of breast pathology: towards an intelligent knife for breast cancer surgery. Breast Cancer Res 19:1–14. https://doi.org/10.1186/s13058-017-0845-2

    Article  CAS  Google Scholar 

  20. Balog J, Sasi-Szabó L, Kinross J, Lewis MR, Muirhead LJ, Veselkov K, Mirnezami R, Dezső B, Damjanovich L, Darzi A, Nicholson JK, Takáts Z (2013) Intraoperative tissue identification using rapid evaporative ionization mass spectrometry. Sci Transl Med 5:194ra93. https://doi.org/10.1126/scitranslmed.3005623

    Article  CAS  PubMed  Google Scholar 

  21. Asselin M, Jamzad A, Lasso A, Ungi T, Rudan J, Fichtinger G (2019) Identification of the electrocautery state to enable spatially navigated intra-operative mass spectrometry tissue analysis. In: Proceedings in The 12th Hamlyn Symposium on Medical Robotics, pp 57–58

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Funding

Gabor Fichtinger is supported as a Canada Research Chair in Computer-Integrated Surgery. This work was funded, in part, by NIH/NIBIB and NIH/NIGMS (via Grant 1R01EB021396-01A1 - Slicer + PLUS: Point-of-Care Ultrasound) and by CANARIE’s Research Software Program.

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Author notes

  1. Natasja N. Y. Janssen and Martin Kaufmann have contributed equally to this work.

Authors and Affiliations

  1. School of Computing, Queen’s University, Kingston, ON, Canada

    Natasja N. Y. Janssen, Alice Santilli, Amoon Jamzad, Tamas Ungi, Parvin Mousavi & Gabor Fichtinger

  2. Department of Surgery, Queen’s University, Kingston, ON, Canada

    Martin Kaufmann, John F. Rudan & Doug McKay

  3. Department of Pathology, Queen’s University, Kingston, ON, Canada

    Kaitlin Vanderbeck, Kevin Yi Mi Ren & Ami Wang

Authors
  1. Natasja N. Y. Janssen
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  2. Martin Kaufmann
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  3. Alice Santilli
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  4. Amoon Jamzad
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  7. Tamas Ungi
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Correspondence to Natasja N. Y. Janssen.

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Janssen, N.N.Y., Kaufmann, M., Santilli, A. et al. Navigated tissue characterization during skin cancer surgery. Int J CARS 15, 1665–1672 (2020). https://doi.org/10.1007/s11548-020-02200-4

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  • DOI: https://doi.org/10.1007/s11548-020-02200-4

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