Towards intra-operative diagnosis of tumours during breast conserving surgery by selective-sampling Raman micro-spectroscopy

Abstract

Breast-conserving surgery (BCS) is increasingly employed for the treatment of early stage breast cancer. One of the key challenges in BCS is to ensure complete removal of the tumour while conserving as much healthy tissue as possible. In this study we have investigated the potential of Raman micro-spectroscopy (RMS) for automated intra-operative evaluation of tumour excision. First, a multivariate classification model based on Raman spectra of normal and malignant breast tissue samples was built and achieved diagnosis of mammary ductal carcinoma (DC) with 95.6% sensitivity and 96.2% specificity (5-fold cross-validation). The tumour regions were discriminated from the healthy tissue structures based on increased concentration of nucleic acids and reduced concentration of collagen and fat. The multivariate classification model was then applied to sections from fresh tissue of new patients to produce diagnosis images for DC. The diagnosis images obtained by raster scanning RMS were in agreement with the conventional histopathology diagnosis but were limited to long data acquisition times (typically 10,000 spectra mm(-2), which is equivalent to ~5 h mm(-2)). Selective-sampling based on integrated auto-fluorescence imaging and Raman spectroscopy was used to reduce the number of Raman spectra to ~20 spectra mm(-2), which is equivalent to an acquisition time of ~15 min for 5 × 5 mm(2) tissue samples. This study suggests that selective-sampling Raman microscopy has the potential to provide a rapid and objective intra-operative method to detect mammary carcinoma in tissue and assess resection margins.

Raman spectroscopy: techniques and applications in the life sciences

“…Although fewer Raman measuremens are acquired, which reduces the acquisition time by two orders of magnitude, the spatial resolution of the SSRS images are determined by the first imaging modality. Kong et al showed that it is possible to use integrated confocal auto-fluorescence imaging and Raman spectroscopy for fast detection of tumors in surgical resessions of skin [144] and breast tissue [446]. The auto-fluorescence image provided high resolution, while Raman spectroscopy provided chemical specificity for accuracy diagnosis.…”

“…34. Example of selective Raman scanning of (a) skin (scale bar is 0.5 mm) [144] and (b) breast tissue [446] using integrated autofluorescence and Raman microscopy. The series of images for each tissue type includes: auto-fluorescence image(s), segmented image with automated Raman sampling points, Raman diagnosis image(s), and an H&E image.…”

Label‐Free Molecular Imaging of Biological Cells and Tissues by Linear and Nonlinear Raman Spectroscopic Approaches

“…[114] Automated segmentation of autofluorescence images was used to select and prioritize sparse sampling points for Raman spectroscopy.T his automated sampling strategy yielded classification models with 100 %s ensitivity and 92 %s pecificity,a nd allowed for objective diagnoses to be made faster than by frozen section histopathology and faster than IR or Raman imaging alone. [115] Raster scanning Raman microspectroscopy of tissue sections is slow with typically 10 000 spectra per mm 2 , which is equivalent to 5hper mm 2 .Selective sampling based on integrated autofluorescence and Raman spectroscopy reduced the number of Raman spectra to 20 spectra per mm 2 ,which is equivalent to an acquisition time of 15 min for an area of 5 5mm 2 . [115] Raster scanning Raman microspectroscopy of tissue sections is slow with typically 10 000 spectra per mm 2 , which is equivalent to 5hper mm 2 .Selective sampling based on integrated autofluorescence and Raman spectroscopy reduced the number of Raman spectra to 20 spectra per mm 2 ,which is equivalent to an acquisition time of 15 min for an area of 5 5mm 2 .…”

Rapid evaporative ionisation mass spectrometry of electrosurgical vapours for the identification of breast pathology: towards an intelligent knife for breast cancer surgery

“…Similarly, the ClearEdge™ system measures tissue-specific electrical properties with promising preliminary data (sensitivity ~85%, specificity ~80%) [25]. Optical spectroscopy techniques such as diffuse reflectance [26–28], Raman spectroscopy [29], optical coherence tomography (OCT) [30], spatial frequency domain imaging [31], fluorescence techniques [32] and confocal microscopy [33] all measure tissue response to light at various wavelengths, and whilst preliminary results are promising [34], the diagnostic accuracy of the techniques is inferior to pathological margin assessment and technological developments are required to increase image processing time and improve the ease of use.…”