Successful breast conserving surgery consists of complete removal of the tumor while sparing healthy surrounding tissue. Despite currently available imaging and margin assessment tools, recognizing tumor tissue at a resection margin during surgery is challenging. Diffuse reflectance spectroscopy (DRS), which uses light for tissue characterization, can potentially guide surgeons to prevent tumor positive margins. However, inter-patient variation and changes in tissue physiology occurring during the resection might hamper this light-based technology. Here we investigate how inter-patient variation and tissue status (in vivo vs ex vivo) affect the performance of the DRS optical parameters. In vivo and ex vivo measurements of 45 breast cancer patients were obtained and quantified with an analytical model to acquire the optical parameters. The optical parameter representing the ratio between fat and water provided the best discrimination between normal and tumor tissue, with an area under the receiver operating characteristic curve of 0.94. There was no substantial influence of other patient factors such as menopausal status on optical measurements. Contrary to expectations, normalization of the optical parameters did not improve the discriminative power. Furthermore, measurements taken in vivo were not significantly different from the measurements taken ex vivo. These findings indicate that DRS is a robust technology for the detection of tumor tissue during breast conserving surgery.@en

In vivo data acquisition using fiberoptic diffuse reflectance spectroscopy (DRS) is more complicated and less controlled compared to ex vivo data acquisition. It would be of great benefit if classifiers for in vivo tissue discrimination based on DRS could be trained on data obtained ex vivo. In this study, in vivo and ex vivo DRS measurements are obtained during colorectal cancer surgery. A mixed model statistical analysis is used to examine the differences between the two datasets. Furthermore, classifiers are trained and tested using in vivo and ex vivo data. It is found that with a classifier trained on ex vivo data and tested on in vivo data, similar results are obtained compared to a classifier trained and tested on in vivo data. In conclusion, under the conditions used in this study, classifiers intended for in vivo tissue discrimination can be trained on ex vivo data.@en

Diffuse reflectance spectroscopy (DRS) can discriminate different tissue types based on optical characteristics. Since this technology has the ability to detect tumor tissue, several groups have proposed to use DRS for margin assessment during breast-conserving surgery for breast cancer. Nowadays, an increasing number of patients with breast cancer are being treated by neoadjuvant chemotherapy. Limited research has been published on the influence of neoadjuvant chemotherapy on the optical characteristics of the tissue. Hence, it is unclear whether margin assessment based on DRS is feasible in this specific group of patients. We investigate whether there is an effect of neoadjuvant chemotherapy on optical measurements of breast tissue. To this end, DRS measurements were performed on 92 ex-vivo breast specimens from 92 patients, treated with neoadjuvant chemotherapy and without neoadjuvant chemotherapy. Generalized estimating equation (GEE) models were generated, comparing the measurements of patients with and without neoadjuvant chemotherapy in datasets of different tissue types using a significance level of 5%. As input for the GEE models, either the intensity at a specific wavelength or a fit parameter, derived from the spectrum, was used. In the evaluation of the intensity, no influence of neoadjuvant chemotherapy was found, since none of the wavelengths were significantly different between the measurements with and the measurements without neoadjuvant chemotherapy in any of the datasets. These results were confirmed by the analysis of the fit parameters, which showed a significant difference for the amount of collagen in only one dataset. All other fit parameters were not significant for any of the datasets. These findings may indicate that assessment of the resection margin with DRS is also feasible in the growing population of breast cancer patients who receive neoadjuvant chemotherapy. However, it is possible that we did not detect neoadjuvant chemotherapy effect in the some of the datasets due to the small number of measurements in those datasets.@en