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05.08.2019 | Head and Neck Oncology

Margin Analysis in Head and Neck Cancer: State of the Art and Future Directions

verfasst von: Michael M. Li, MD, Sidharth V. Puram, MD, PhD, Dustin A. Silverman, MD, Matthew O. Old, MD, James W. Rocco, MD, PhD, Stephen Y. Kang, MD

Erschienen in: Annals of Surgical Oncology | Ausgabe 12/2019

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Abstract

Background

The status of surgical margins is the most important prognosticator for patients undergoing surgical resection of head and neck squamous cell carcinoma (HNSCC). Despite this, analysis of surgical margins is fraught with inconsistencies, including the ways in which margins are sampled and interpreted. Fundamentally, even the definition what constitutes a “clear” (or negative) margin may vary between institutions, surgeons, and pathologists.

Methods

The PubMed database was queried for articles relevant to the topic, and experts in the field were consulted regarding key articles for inclusion. Abstracts were reviewed and the full text was accessed for articles of particular interest.

Results

Data regarding various approaches to traditional margin analysis have been published without consensus. Several next-generation technologies have emerged in recent years that hold promise.

Conclusion

An overview and appraisal of traditional margin analysis techniques are provided. Additionally, we explore novel technologies that may assist in more accurate margin assessment, guide the extent of surgical resections intraoperatively, and inform decisions regarding adjuvant treatment postoperatively.

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Titel: Margin Analysis in Head and Neck Cancer: State of the Art and Future Directions
verfasst von: Michael M. Li, MD
Sidharth V. Puram, MD, PhD
Dustin A. Silverman, MD
Matthew O. Old, MD
James W. Rocco, MD, PhD
Stephen Y. Kang, MD
Publikationsdatum: 05.08.2019
Verlag: Springer International Publishing
Erschienen in: Annals of Surgical Oncology / Ausgabe 12/2019
Print ISSN: 1068-9265
Elektronische ISSN: 1534-4681
DOI: https://doi.org/10.1245/s10434-019-07645-9

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Abstract

Background

Methods

Results

Conclusion

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