Intraoperative Spectroscopic Evaluation of Sentinel Lymph Nodes in Breast Cancer Surgery: An Interview with William F. Meggers Award Winner Ioan Notingher

In a recent paper, Ioan Notingher and a team of researchers from the University of Nottingham and the University of London presented a non-destructive technique based on autofluorescence (AF) imaging and Raman spectroscopy for intra-operative assessment of sentinel lymph nodes (SLNs) excised in breast cancer surgery. Positive SLNs on histological examination can lead to a subsequent surgery for axillary lymph node clearance (ALNC). Notingher will be receiving the William F. Meggers Award, given to the author(s) of the most outstanding paper appearing in Applied Spectroscopyat this year’s SciX conference, to be held from October 20 through October 25, in Raleigh, North Carolina. As part of an ongoing series of this year’s SciX conference honorees, Ioan spoke to Spectroscopy Magazine about technique, and what being named the Meggers Award recipient means to him.

The papers that you sent for us to review dealt mostly with cancer treatment, yet you’re affiliated with the School of Physics and Astronomy at the University of Nottingham. How would you explain the disconnect, or, if you’d like, how might you explain that there was no disconnect at all? What made you interested in this type of treatment?

University of Nottingham is a great place for inter-disciplinary research, and the physics-medicine interface has a particular significance. The School of Physics and Astronomy is the birthplace of Magnetic Resonance Imaging (MRI), for which Sir Peter Mansfield was awarded the 2003 Nobel Prize for Physiology or Medicine. This heritage is indeed very inspiring.

Your university website bio (1), states that your research group develops biophotonics techniques based on Raman spectroscopy to study nanomaterials, live cells, and disease diagnosis. What makes Raman spectroscopy your technique of choice in your studies?

Raman spectroscopy has huge potential in biophysics and medicine. All biological processes in cells and tissues involve complex molecular interactions, which can be the cause of or the consequences of disease. The advantages of Raman spectroscopy come from two key features: its molecular specificity and the way in which the information is obtained. Raman spectroscopy uses light to excite and read the molecular information, therefore the measurements can be non-invasive, which is ideal for medical applications or when time-course measurements are required to follow a biological process in cells. Secondly, the light can be focused to a tiny spot and scanned on the sample to obtain molecular-specific images with microscopic information. These two features make Raman spectroscopy unique for biomedical applications.

A recent paper written by you and your associates (2) discusses a non-destructive technique based on autofluorescence (AF) imaging and Raman spectroscopy for intra-operative assessment of sentinel nymph nodes (SLNs) excised in breast cancer surgery. What are the potential benefits of your technique as opposed to those that are currently in use?

While there is a clear benefit for intra-operative diagnosis of lymph nodes during the initial surgery, current technologies have significant shortcomings. Frozen section histology and imprint cytology have low accuracy and require additional pathology resources. One-step nucleic acid amplification (OSNA) can be used intra-operatively to detect specific molecular markers, this technique consumes the tissue, compromising histology evaluation of the nodes. Because of these shortcomings, in practice, intraoperative methods for assessing SLNs are rarely used in the clinic.

A weakness of Raman micro-spectroscopy is that each measurement takes approximately 1 s. This is indeed not a problem if only few measurements are required. This becomes a problem when you need to scan real tissue samples resected during surgery, which can be several centimeters is scale. In such cases tens of thousands of spectra are needed to generate useful diagnosis images. Using conventional raster scanning measurements can take several hours, or even days. To overcome this challenge we combined Raman spectroscopy, which has high molecular specificity, with a less specific but faster optical technique that can generate images to highlight the key area of the sample where the Raman measurements should be focused on. For our current applications, autofluorescence imaging has proven the ideal solution: it can guide the Raman measurements to the high-risk areas such that the number of Raman spectroscopy measurements is reduced to only to few hundred. Using multivariate classification techniques on these spectra, and overlaying these on the segmented autofluorescence images, pseudo-Raman images are created that can help clinicians identify the disease.

Briefly state your findings.

The main finding of this study, which included a total of 166 lymph nodes from 138 patients undergoing breast cancer surgery at the Nottingham University Hospitals (85 samples used for training the algorithms, and 81 for independent testing), indicated an overall 94% detection accuracy of lymph nodes containing malignant cells, with measurements times of only 20-30 minutes. In a regime that maximises specificity, this translated in 97% specificity and 80% sensitivity. To note that for assessing the spread of breast cancer to the lymph nodes, detection specificity is more important than sensitivity because it is key to avoid excision of lymph nodes that do not have cancer cells, because of side effects. Even if sensitivity is not perfect, and positive nodes are missed by the AF-Raman instrument, the nodes would still be detected by histology (1-2 weeks) and patients will have a second surgery. However, the performance demonstrated in our study indicates that the AF-Raman technique would avoid a second surgery for 80% of patients, with only 3% rate of false positives.

Was there anything you observed that was unexpected in terms of analysis results and that stands out from your perspective?

While we expected the classification accuracy of the Raman spectroscopy models to be high, given previous work on lymph nodes by other groups, the power of multimodal integrations of optical techniques was unexpected. With developments in machine learning and image analysis techniques, one can obtain rich information about the overall sample morphology and structure at a microscopic level, that can hugely reduce the number of Raman spectra required to obtain very accurate medical diagnosis. Somehow, it is funny because in our community often auto-fluorescence is a nuisance, and many colleagues try to find way to eliminate it. In our work, we found ways to use this information to complement the Raman spectroscopy data.

Were there any serious or noteworthy limitations or challenges you encountered in your work? How likely is this method to be used in clinical trials or additional studies?

The main objective of this study was to investigate whether a dual-modality technique combining AF imaging and Raman spectroscopy could be used to detect metastatic lymph nodes within timescales compatible with intra-operative use. The results from our study are very promising: even when considering our laboratory prototype, we were able to obtain a high detection accuracy with measurements times of only 20-30 min. With 80% sensitivity it means that the surgeon could identify lymph nodes containing malignant cells during the first operation and help 80% of patients avoid a second surgery – in England, this means approximately 8,000 patients per year.

However, there are two main limitations for in the current study. The first is the limited number of samples used in the training of the classification models. For example, we had only few Raman spectra from histocytes in the training set, which led to several cases of false positives. Targeting and measuring more Raman spectra of histiocytes to retrain the Raman classification models may improve the discrimination between metastasis and normal lymph nodes. Secondly, the measurement speed. The overall measurement and analysis time for this prototype instrument varied between 20 to 30 min, which was considered acceptable for this proof-of-concept study. While this time is similar to other techniques, it could be significantly reduced by optimising the Raman spectrometer to reduce the acquisition time per spectrum. In our previous studies using optimised Raman spectrometers we reported acquisition times as short as 1 s per spectrum, compared to 5 s utilised here. Such instrument optimisation would reduce the total measurement and analysis time to only 5-10 min. We also showed that using multi-foci Raman spectroscopy in power-sharing mode to measure Raman spectra from several locations simultaneously. Speed is important because surgeons need to analyze up to 6-8 lymph nodes during surgery.

What best practices can you recommend in this type of analysis for both instrument parameters and data analysis?

As the main aim of this research is to develop tools for surgeons to help identify cancer in tissue, it is paramount that the calibration of instruments and validation of the diagnosis models are performed at the highest standards. This is important to ensure the diagnosis accuracy is maintained when using different instruments in the clinic.

Can you please summarize the feedback that you have received from others regarding this work?

We have received excellent feedback from clinicians encouraging us to develop further this technology into instruments that they could use in the operating theatres. A substantial advantage of the AF-Raman technique is that the analysis provides a quantitative diagnosis image that requires no subjective interpretation by the user. The surgeons really liked this feature because it allows the use of the instrument by any member of the team with minimal training and minimal sample prep. Compared to other imaging techniques that rely on subjective decisions based on structural or morphological characteristics of tissue, quantitative techniques can reduce inter-user variability and minimise the time required for user training.

We have also received positive feedback from breast cancer patients. Patients have emphasized the anxiety of waiting for histology results, the trauma of undergoing multiple surgery procedures and the importance of developing more efficient methods to ensure complete removal of cancer in the first operation.

What are the next steps in this research?

We have started working with an industrial partner to develop a first prototype based on this technology. Such fully integrated prototype will allow us to integrate the technology in the clinical pathway and evaluate its performance in the real-world. We are also exploring further development and applications of the technology. The AF-Raman technology could potentially be adapted to determine the status of lymph nodes infiltrated by other cancer types, by optimising the classification algorithms to specific tissue types. This means we could also help patients with other cancers, including colorectal, skin, gynaecological and prostate.

What are your thoughts regarding your being named the recipient of the Meggers Award?

With so many outstanding researchers working in this field, of course I am delighted to receive this prestigious award. I am also very proud because this award acknowledges the work of my research group and collaborators, which include scientists in different fields, clinicians, and industry partners.

References

1. Notingher biography, University of Nottingham website.

https://www.nottingham.ac.uk/physics/people/ioan.notingher (accessed 2024-05-20).

2. Barkur, S.;Boitor, R.; Mihai, R.; Gopal, N.; Leeney, S.; Koloydenko, A.; Khout, H.;Rakha, E.; Notingher, I. Intraoperative Spectroscopic Evaluation of Sentinel Lymph Nodes in Breast Cancer Surgery. Breast Cancer Res. Treat. 2024, 207, 223–232. DOI: 10.1007/s10549-024-07349-z

Ioan Notingher, of the School of Physics and Astronomy at the University of Nottingham,

graduated from Babes-Bolyai University Cluj-Napoca (Romania), PhD at London South Bank University (Photophysics Research Group), followed by postdoctoral research at Imperial College London and Edinburgh University. He was appointed lecturer in 2006 at the University of Nottingham, where he has established the Biophotonics Group. His research focuses on optical microscopy and spectroscopy techniques for label-free molecular imaging of biomaterials, cells, and tissues. His team has developed numerous links with clinicians, cancer research academics, and international leaders in optics and microscopy, as well as partnerships with industry. He is a fellow of the Institute of Physics (IOP) and senior member of the Optica and held an EPSRC Fellowship (2014-2019). He was Associate Editor of the Optica Biomedical Optics Express (2016-2023) and the Journal of Biological Engineering (2009-2016).