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

In vivo assessment of bladder cancer with diffuse reflectance and fluorescence spectroscopy: A comparative study

OBJECTIVES

The aim of this work is to assess the performance of multimodal spectroscopic approach combined with single core optical fiber for detection of bladder cancer during surgery in vivo.

METHODS

Multimodal approach combines diffuse reflectance spectroscopy (DRS), fluorescence spectroscopy in the visible (405 nm excitation) and near-infrared (NIR) (690 nm excitation) ranges, and high-wavenumber Raman spectroscopy. All four spectroscopic methods were combined in a single setup. For 21 patients with suspected bladder cancer or during control cystoscopy optical spectra of bladder cancer, healthy bladder wall tissue and/or scars were measured. Classification of cancerous and healthy bladder tissue was performed using machine learning methods.

RESULTS

Statistically significant differences in relative total haemoglobin content, oxygenation, scattering, and visible fluorescence intensity were found between tumor and normal tissues. The combination of DRS and visible fluorescence spectroscopy allowed detecting cancerous tissue with sensitivity and specificity of 78% and 91%, respectively. The addition of features extracted from NIR fluorescence and Raman spectra did not improve the quality of classification.

CONCLUSIONS

This study demonstrates that multimodal spectroscopic approach allows increasing sensitivity and specificity of bladder cancer detection in vivo. The developed approach does not require special probes and can be used with single-core optical fibers applied for laser surgery.

Beneath the surface: A systematic review on intraoperative imaging techniques for deep margin assessment in oral squamous cell carcinoma

Resection margins of oral squamous cell carcinoma (SCC) are often inadequate. A systematic review on clinical intraoperative whole-specimen imaging techniques to obtain adequate deep resection margins in oral SCC is lacking. Such a review may render better alternatives for the current insufficient intraoperative techniques: palpation and frozen section analyses (FSA). This review resulted in ten publications investigating ultrasound (US), four investigating fluorescence, and three investigating MRI. Both US and fluorescence were able to image the tumor intraorally and perform ex-vivo imaging of the resection specimen. Fluorescence was also able to image residual tumor tissue in the wound bed. MRI could only be used on the ex-vivo specimen. The 95 % confidence intervals for sensitivity and specificity were large, due to the small sample sizes for all three techniques. The sensitivity and specificity of US for identifying < 5 mm margins ranged from 0 % to 100 % and 60 % to 100 %, respectively. For fluorescence, this ranged from 0 % to 100 % and 76 % to 100 %, respectively. For MRI, this ranged from 7 % to 100 % and 81 % to 100 %, respectively. US, MRI and fluorescence are the currently available imaging techniques that can potentially be used intraoperatively and which can image the entire tumor-free margin, although they have insufficient sensitivity for identifying < 5 mm margins. Further research on larger cohorts is needed to improve the sensitivity by determining cut-off points on imaging for inadequate margins. This improves the number of adequate resections of oral SCC's and pave the way for routine clinical implementation of these techniques.

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

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.

Differentiation of Salivary Gland and Salivary Gland Tumor Tissue via Raman Imaging Combined with Multivariate Data Analysis

Salivary gland tumors (SGTs) are a relevant, highly diverse subgroup of head and neck tumors whose entity determination can be difficult. Confocal Raman imaging in combination with multivariate data analysis may possibly support their correct classification. For the analysis of the translational potential of Raman imaging in SGT determination, a multi-stage evaluation process is necessary. By measuring a sample set of Warthin tumor, pleomorphic adenoma and non-tumor salivary gland tissue, Raman data were obtained and a thorough Raman band analysis was performed. This evaluation revealed highly overlapping Raman patterns with only minor spectral differences. Consequently, a principal component analysis (PCA) was calculated and further combined with a discriminant analysis (DA) to enable the best possible distinction. The PCA-DA model was characterized by accuracy, sensitivity, selectivity and precision values above 90% and validated by predicting model-unknown Raman spectra, of which 93% were classified correctly. Thus, we state our PCA-DA to be suitable for parotid tumor and non-salivary salivary gland tissue discrimination and prediction. For evaluation of the translational potential, further validation steps are necessary.

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

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.

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

Introduction

Oral 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.

Methods

Toward 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.

Results

The 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.

Discussion

Thus, this prototype proposed in this study has great potential for rapid, non-invasive, and label-free pathological diagnosis of oral cancer.