Abstract
Intraoperative confirmation of negative resection margins is an essential component of soft tissue sarcoma surgery. Frozen section examination of samples from the resection bed after excision of sarcomas is the gold standard for intraoperative assessment of margin status. However, it takes time to complete histologic examination of these samples, and the technique does not provide real-time diagnosis in the operating room (OR), which delays completion of the operation. This paper presents a study and development of sensing technology using Raman spectroscopy that could be used for detection and classification of the tumor after resection with negative sarcoma margins in real time. We acquired Raman spectra from samples of sarcoma and surrounding benign muscle, fat, and dermis during surgery and developed (i) a quantitative method (QM) and (ii) a machine learning method (MLM) to assess the spectral patterns and determine if they could accurately identify these tissue types when compared to findings in adjacent H&E-stained frozen sections. High classification accuracy (>85%) was achieved with both methods, indicating that these four types of tissue can be identified using the analytical methodology. A hand-held Raman probe could be employed to further develop the methodology to obtain spectra in the OR to provide real-time in vivo capability for the assessment of sarcoma resection margin status.
Highlights
Soft tissue sarcomas are cancers that originate from mesenchymal progenitor cells and commonly arise in muscles and soft tissues of the extremities
As described in Section 3.1.4, the unknown spectra in a blind test are compared against the reference spectra of the tumor, muscle, dermis, and fat using the quantitative method with the reference tables which contain the threshold values and the associated wavenumbers
The results of blind tests demonstrated that the quantitative method was able to correlate the unknown spectra with the reference correctly with an overall accuracy Pq = 83:0% (39/47) for the classification of all patients
Summary
Soft tissue sarcomas are cancers that originate from mesenchymal progenitor cells and commonly arise in muscles and soft tissues of the extremities. The mainstay of treatment is complete surgical resection of the entire tumor bed, and the primary goal of surgery is to “leave no tumor cell behind.”. Despite this goal, local recurrence (i.e., reappearance of a tumor mass despite initial surgical resection) remains a major problem in soft tissue sarcomas if they are not completely removed with negative resection margins [1]. The surgeon takes small samples of tissue from parts of the surgical cavity where the distance between the tumor and the margin is closest and sends these for frozen section histologic examination by a pathologist. There is an unmet clinical need to develop methods that can more quickly and accurately determine if surgical margins of sarcomas are negative
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