Intraoperative assessment of resection margins by Raman spectroscopy to guide oral cancer surgery

Aaboubout, Yassine; Soares, Maria R Nunes; Schut, Tom C. Bakker; Barroso, Elisa M.; Wolf, Martin van der; Sokolova, Elena A.; Artyushenko, Viacheslav; Bocharnikov, Alexey; Usenov, Iskander; Lanschot, Cornelia G.F. van; Ottevanger, Lars; Mast, Hetty; Hove, Ivo ten; Jonker, Brend P.; Keereweer, Stijn; Monserez, Dominiek; Sewnaik, Aniel; Hardillo, José A.; Jong, Robert J. Baatenburg de; Koljenović, Senada; Puppels, Gerwin J.

doi:10.1039/d3an00650f

Cited by 8 publications

(6 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Recently, an OSCC surgery guidance system was developed, combining high-wavenumber RS and ML to build a tissue classification model and a margin length prediction model. The former could discriminate OSCC from healthy oral tissue with 85% sensitivity and 92% specificity, while the latter could predict margin length with commendable accuracy (a mean difference of −0.17 mm, as compared to histopathology) 242 . Tighe et al .…”

Section: Assessment Of Head and Neck Squamous Cell Carcinoma Marginsmentioning

confidence: 99%

Surgical margins in head and neck squamous cell carcinoma: a narrative review

Chen,

Zhong,

Cao

et al. 2024

International Journal of Surgery

View full text Add to dashboard Cite

Head and neck squamous cell carcinoma (HNSCC), a prevalent and frequently recurring malignancy, often necessitates surgical intervention. The surgical margin (SM) plays a pivotal role in determining the postoperative treatment strategy and prognostic evaluation of HNSCC. Nonetheless, the process of clinical appraisal and assessment of the SMs remains a complex and indeterminate endeavor, thereby leading to potential difficulties for surgeons in defining the extent of resection. In this regard, we undertake a comprehensive review of the suggested surgical distance in varying circumstances, diverse methods of margin evaluation, and the delicate balance that must be maintained between tissue resection and preservation in head and neck surgical procedures. This review is intended to provide surgeons with pragmatic guidance in selecting the most suitable resection techniques, and in improving patients’ quality of life by achieving optimal functional and aesthetic restoration.

show abstract

Section: Assessment Of Head and Neck Squamous Cell Carcinoma Marginsmentioning

confidence: 99%

Surgical margins in head and neck squamous cell carcinoma: a narrative review

Chen,

Zhong,

Cao

et al. 2024

International Journal of Surgery

View full text Add to dashboard Cite

show abstract

“…By utilizing spectroscopy as part of the IOARM, surgeons have more accurate and efficient means to achieve successful surgical outcomes. While current methods for margin assessment can be laborious, subjective, and logistically demanding, spectroscopy offers a potential solution to overcome these limitations [ 53 ]. With further research and development, this technique can revolutionize intraoperative evaluations, providing surgeons with more accurate and efficient means to improve margin assessment and to achieve successful surgical outcomes.…”

Section: Spectroscopy For the Intraoperative Assessment Of The Resect...mentioning

confidence: 99%

“…This probe can be inserted into the specimen and can rapidly determine the distance between the resection surface and the tumor border. Aaboubout Y et al elaborated a promising margin length prediction and tissue classification model for the quick and accurate assessment of resection margins [ 53 ].…”

Section: Spectroscopy For the Intraoperative Assessment Of The Resect...mentioning

confidence: 99%

Intraoperative Assessment of Resection Margin in Oral Cancer: The Potential Role of Spectroscopy

Vlocskó,

Piffkó,

Janovszky

2023

Cancers

View full text Add to dashboard Cite

In parallel with the increasing number of oncological cases, the need for faster and more efficient diagnostic tools has also appeared. Different diagnostic approaches are available, such as radiological imaging or histological staining methods, but these do not provide adequate information regarding the resection margin, intraoperatively, or are time consuming. The purpose of this review is to summarize the current knowledge on spectrometric diagnostic modalities suitable for intraoperative use, with an emphasis on their relevance in the management of oral cancer. The literature agrees on the sensitivity, specificity, and accuracy of spectrometric diagnostic modalities, but further long-term prospective, multicentric clinical studies are needed, which may standardize the intraoperative assessment of the resection margin and the use of real-time spectroscopic approaches.

show abstract

“…Concurrently, Aaboubout et al. ( 27 ) analyzed freshly removed tissues, distinguishing between benign and malignant samples with a sensitivity of 85% and a 92% accuracy rate. Our prior research underscored the potential of portable fiber-optic Raman spectroscopy (PFORS), in conjunction with various machine learning algorithms, to differentiate between cancerous and adjacent tissues in patients afflicted with gum and cheek cancers ( 28 ).…”

Section: Introductionmentioning

confidence: 99%

Rapid multi-task diagnosis of oral cancer leveraging fiber-optic Raman spectroscopy and deep learning algorithms

Li,

Sun

et al. 2023

Front. Oncol.

View full text Add to dashboard Cite

IntroductionOral cancer, a predominant malignancy in developing nations, represents a global health challenge with a five-year survival rate below 50%. Nonetheless, substantial reductions in both its incidence and mortality rates can be achieved through early detection and appropriate treatment. Crucial to these treatment plans and prognosis predictions is the identification of the pathological type of oral cancer.MethodsToward this end, fiber-optic Raman spectroscopy emerges as an effective tool. This study combines Raman spectroscopy technology with deep learning algorithms to develop a portable intelligent prototype for oral case analysis. We propose, for the first time, a multi-task network (MTN) Raman spectroscopy classification model that utilizes a shared backbone network to simultaneously achieve different clinical staging and histological grading diagnoses.ResultsThe developed model demonstrated accuracy rates of 94.88%, 94.57%, and 94.34% for tumor staging, lymph node staging, and histological grading, respectively. Its sensitivity, specificity, and accuracy compare closely with the gold standard: routine histopathological examination.DiscussionThus, this prototype proposed in this study has great potential for rapid, non-invasive, and label-free pathological diagnosis of oral cancer.

show abstract

Intraoperative assessment of resection margins by Raman spectroscopy to guide oral cancer surgery

Abstract: Patients with oral cavity cancer are almost always treated with surgery. The goal is to remove the tumor with a margin of more than 5 mm of surrounding healthy tissue....

Cited by 8 publications

References 31 publications

Surgical margins in head and neck squamous cell carcinoma: a narrative review

Surgical margins in head and neck squamous cell carcinoma: a narrative review

Intraoperative Assessment of Resection Margin in Oral Cancer: The Potential Role of Spectroscopy

Rapid multi-task diagnosis of oral cancer leveraging fiber-optic Raman spectroscopy and deep learning algorithms

Contact Info

Product

Resources

About