Quantitative OCT-Raman spectral imaging for intra-operative detection of positive margins in breast conserving surgery

Breast cancer is the most common cancer among women, with 55,000 new patients diagnosed each year in the UK. Breast conserving surgery is the most widely used procedure for cutting the cancer out. Surgery aims to remove the entire cancer with the smallest scar possible. To minimise the risks of the cancer returning, the surgeon cuts the cancer out including a margin of normal-looking tissue. However, at the time of surgery it is often difficult to know how much normal tissue to remove. Too wide a margin increases the risk of damage to nearby tissue and leads to a larger scar. Cutting too narrow margins may leave some cancer cells behind, which increases the risk of the cancer to re-grow. During the operation, surgeons have limited tools where the tumour ends, and mainly rely on their fingers to judge how much tissue to cut out. To confirm whether the whole cancer was cut out successfully, the removed tissue is transferred to the histology laboratory where it is cut into thin sections, stained with some special dies, and then observed under a microscope by a specialist histopathologist. However, this take long time (several days to one week) and therefore cannot be done during the surgery. If histopathology identifies cancer cells at the surface of the cut out tissue (positive margins), the patient is rescheduled for another surgery. Currently, one in five patients (~10,000 per year) undergoing breast conserving surgery in England needs a re-operation; this number is similar to other countries in Europe and the USA.

The outcome of breast cancer surgery could be significantly improved, and the need of second operation reduced, if surgeons were able to check while the patients is in the operating room whether the entire cancer is out or not. In the last decade our team has developed a new imaging technique that can discriminate between healthy breast tissue and cancer. This technique, called Raman spectroscopy, measures molecular properties of breast tissue and detects changes related to cancer. By combining Raman spectroscopy with optical coherence tomography, a technique that can scan quickly the whole margins and identify high risk areas, we plan to develop a new instrument that could scan the surface of whole breast tissue specimen and build images that can identify even small regions of tumour, that often may not be felt by surgeons. Thus, this new instrument could be a very useful tool for surgeons as they could analyse the breast tissue cut during the surgery, while the patient is still under anaesthesia in the operating room. If any cancer cells are detected, they could on the spot remove additional tissue, and repeat this procedure until the whole cancer is out.

In this project we want to build on our decade-long research and develop a first-generation instrument that can be used by surgeons in the operating room. To achieve this, we have assembled a team of scientists specialists in optics, microscopy and advance data processing, breast cancer surgeons and patients, to design a cost effective instrument that can be integrated in the operating room and then be adopted across the NHS. If successful, the new technology could lead to a step-change in breast cancer surgery by helping to maximise the chances for complete cancer removal in a single operation. We know that additional surgery causes huge emotional stress to patients, often leads to poorer cosmetic outcome, delays other treatment, require longer recovery times for patients, and increases costs to the NHS.

Breast conserving surgery is the most common procedure for resection of breast cancers. However, positive margins are detected for 20-30% of operations, and patients require additional surgery to achieve complete excision. Currently, surgical margins are assessed by post-operative histopathology (takes ~1 week). Detecting positive margins intra-operatively would allow excision of the cancer in a single operation. However, this would require scanning the whole excised specimen within few minutes. Considering the spatial resolution and diagnosis accuracy required, this remains a challenge. Raman microscopy is a potential solution. It can detect molecular differences between normal tissue and cancer but requires impractical times to scan whole specimen at high resolution. Optical coherence tomography (OCT) can image structural differences between tumour and normal tissue at high-speeds but lacks molecular specificity.
To overcome this challenge we propose a dual-modality approach that maximises the complementary strengths of OCT (speed, spatial resolution) and Raman spectroscopy (molecular specificity). We will build a unique combined system using an optimised OCT scanning procedure that integrates Raman measurements to analyse whole specimen within 10 minutes. Machine learning algorithms will be developed to process OCT images to identify high-risk areas at the specimen surface, from where Raman spectra will be recorded to deliver quantitative diagnosis (tumour present Yes/No). We will test the OCT-Raman system using lumpectomy specimens from patients undergoing surgery to obtain estimates of performance (sensitivity/specificity, analysis time). The OCT-Raman system will enable surgeons to detect positive margins while the patient is in the operating room, leading to a step-change in breast cancer surgery: surgeons could excise the tumour in a single operation. Second surgery leads to poorer outcomes for patients, long recovery times and increased healthcare costs.