Evaluating feasibility of an automated 3-dimensional scanner using Raman spectroscopy for intraoperative breast margin assessment

Abstract

Breast conserving surgery is the preferred treatment for women diagnosed with early stage invasive breast cancer. To ensure successful breast conserving surgeries, efficient tumour margin resection is required for minimizing tumour recurrence. Currently surgeons rely on touch preparation cytology or frozen section analysis to assess tumour margin status intraoperatively. These techniques have suboptimal accuracy and are time-consuming. Tumour margin status is eventually confirmed using postoperative histopathology that takes several days. Thus, there is a need for a real-time, accurate, automated guidance tool that can be used during tumour resection intraoperatively to assure complete tumour removal in a single procedure. In this paper, we evaluate feasibility of a 3-dimensional scanner that relies on Raman Spectroscopy to assess the entire margins of a resected specimen within clinically feasible time. We initially tested this device on a phantom sample that simulated positive tumour margins. This device first scans the margins of the sample and then depicts the margin status in relation to an automatically reconstructed image of the phantom sample. The device was further investigated on breast tissues excised from prophylactic mastectomy specimens. Our findings demonstrate immense potential of this device for automated breast tumour margin assessment to minimise repeat invasive surgeries.

Emerging Technologies for Real‐Time Intraoperative Margin Assessment in Future Breast‐Conserving Surgery

“…Notingher and co‐workers recently developed a multimodal imaging technique combining tissue autofluorescence (excitation at 405 nm, detection at 450–520 nm) and Raman spectroscopy (excitation at 785 nm, Raman shift detection at 600–1800 cm −1 ), which they called multimodal spectral histopathology ( Figure ). [ 17b ] They extensively optimized the sampling and data processing algorithms to use autofluorescence images to guide Raman measurements and achieve high spatial and spectral information in just 12–24 min, even when analyzing large tissue surfaces up to 4 cm × 6.5 cm. Analysis of 121 surgical marigin specimens from 107 patients, although not under real‐time intraoperative assessment conditions, could discriminate IDC and DCIS from NBG with 95% sensitivity and 82% specificity.…”

“…Adapted with permission. [ 17b ] Copyright 2018, Springer Nature. DCIS, ductal carcinoma in situ; DC‐NST, ductal carcinoma of no special type; IC, invasive carcinoma.…”

“…These methods include conventional specimen radiography (SR), [ 7 ] intraoperative ultrasonography (IOUSG), [ 8 ] radio‐frequency spectroscopy (MarginProbe device), [ 9 ] bioimpedance spectroscopy (ClearEdge device), [ 10 ] microcomputed tomography (micro‐CT), [ 11 ] optical coherence tomography (OCT), [ 12 ] ex vivo magnetic resonance imaging (ex vivo MRI), [ 13 ] ultraviolet photoacoustic microscopy (UV‐PAM), [ 14 ] microscopy with ultraviolet surface excitation (MUSE), [ 15 ] chemistry‐based fluorescent probes, [ 16 ] and a multimodal imaging technique combining tissue autofluorescence and Raman spectroscopy with both macro (tissue‐level) and micro (cell‐level) detection. [ 17 ]…”

Multiscale nonlinear microscopy and widefield white light imaging enables rapid histological imaging of surgical specimen margins

“…Extremely rapid molecular identification of breast margin composition has been recently demonstrated using depth-resolved Raman scattering combined with rotational specimen scanning, although the sensitivity of this technique to different pathologies is still under investigation [42]. Techniques such as OCT and RCM can perform label-free, structural imaging at extremely high speed but accurate histological evaluation is challenging because there is low nuclear contrast from scattering [26].…”

Spatially offset Raman spectroscopy for non-invasive analysis of turbid samples

“…The first proof of concept experiments in this area was performed by Keller et al [1,46]. More recently the team demonstrated an automated 3D SORS scanner useable to assess the entire margins of a resected specimen within clinically feasible time at operating theatre [47].…”