Intra-operative Detection of Positive Margins and Lymph Nodes in Breast Surgery

NCT06977698 | Recruiting

• 1 other identifier: 336788
• Study Type: observational
• Target: 120
• Locations: 1 country
• Sites: 1

Brief Summary

In this project, the investigators will develop novel optical coherence tomography (OCT)-Raman spectroscopy and autofluorescence (AF)-Raman spectroscopy systems based on a selective sampling approach optimised for high-resolution analysis of whole lumpectomy specimens and sentinel lymph node (SLN) biopsies, respectively. The aim of using optical coherence tomography is not to detect cancer directly, but rather to identify adipose tissue so that large adipose regions can be excluded from subsequent Raman spectroscopy measurements. Although OCT has limited ability to distinguish tumour tissue from the surrounding normal stroma, adipose tissue exhibits a distinctive appearance in optical coherence tomography images because of its low backscattering properties, resulting from adipocytes that are filled with lipids and contain small, flattened nuclei. In contrast, benign dense tissue (stroma, ducts, and lobules) and malignant tissue produce much stronger backscattering signals. These characteristic patterns enable adipose tissue to be distinguished from other breast tissues using classification models based on optical coherence tomography reflectivity profiles, achieving 94% sensitivity and 93% specificity. Excluding adipose tissue from further analysis reduces the number of Raman spectroscopy measurements required, allowing the remaining, smaller tissue regions to be examined to discriminate between benign and malignant tissue. This flexible and adaptable scanning strategy is expected to improve both diagnostic accuracy and scanning speed, enabling complete assessment of surgical margins within clinically practical timescales. In addition, the investigators will develop a novel (AF)-Raman spectroscopy system based on a selective sampling approach optimised for high-resolution analysis of sentinel lymph node specimens. The purpose of incorporating autofluorescence imaging is to identify the optimal sampling locations for subsequent Raman spectroscopy measurements, thereby improving the efficiency of tissue interrogation while maintaining diagnostic accuracy.

Conditions

Breast Cancer Invasive

Keywords

Breast cancer; Margins; Breast conserving surgery; Raman Spectroscopy; Sentinel Lymph Node; computational pathology.; intra-operative imaging; Autofluorescence

Outcome Measures

Primary Outcomes (1)

• Design and build unique OCT and AF-Raman system with integrated machine learning algorithms.

  To design and develop OCT-Raman and AF-Raman imaging systems, including their hardware and software architectures with integrated machine learning algorithms, and install both prototypes at UON for evaluation. The OCT-Raman system will be used to distinguish cancerous from normal breast tissue in lumpectomy and mastectomy specimens, while the AF-Raman system will be used to distinguish metastatic lymph nodes from normal lymphoid tissue. In each study, tissue samples will be scanned independently, and the measured area will be recorded in mm² for each specimen. Average Raman spectral intensities will then be calculated separately for cancerous and normal tissues, and a t-test will be performed to identify the Raman bands exhibiting the most significant differences between the two tissue types. Data acquisition, area measurements, and statistical analyses for the two experiments will be conducted independently by separate investigators.

  12 months

Secondary Outcomes (1)

• Feasibility and Diagnostic Performance of Intraoperative Raman Spectroscopy

  30 months

Interventions

OCT-Raman DIAGNOSTIC_TEST

a machine to detect positive margins in lumpectomy specimens

AF-Raman DIAGNOSTIC_TEST

a machine for detection sentinel lymph nodes in Breast conserving surgery.

Eligibility Criteria

• Sex: female
• Healthy Volunteers: No
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)
• Sampling Method: Probability Sample

Study Population

Patients undergoing Wide Local Excision (WLE) for breast cancer at the Breast Cancer Institute, Nottingham City Hospital.

You may qualify if:

• Patients undergoing breast surgery wide local excision (WLE).
• Able to give informed consent.
• Any age.

You may not qualify if:

• Patients where there is any doubt regarding the diagnosis from pathologist as ascertained by previous diagnostic biopsy.

Sponsors & Collaborators

• University of Nottingham: lead

Study Sites (1)

Nottingham university hospitals

Nottingham, United Kingdom

RECRUITING

MeSH Terms

Conditions

Breast Neoplasms; Margins of Excision

Condition Hierarchy (Ancestors)

Neoplasms by Site; Neoplasms; Breast Diseases; Skin Diseases; Skin and Connective Tissue Diseases; Morphological and Microscopic Findings; Pathological Conditions, Signs and Symptoms

Study Officials

• Ioan Notingher

  University of Nottingham

  PRINCIPAL INVESTIGATOR

• Andrew Green

  University of Nottingham

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Ioan Notingher

CONTACT

0)115 951 3082; ppzin@exmail.nottingham.ac.uk

Nehal Atallah

CONTACT

07521100084; msznma@nottingham.ac.uk

Study Design

• Study Type: observational
• Observational Model: CASE ONLY
• Time Perspective: CROSS SECTIONAL
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: May 9, 2025
• First Posted: May 18, 2025
• Study Start: October 1, 2023
• Primary Completion (Estimated): April 1, 2027
• Study Completion (Estimated): April 1, 2027
• Last Updated: July 30, 2026

Record last verified: 2026-06

Data Sharing

• IPD Sharing: Will not share

Locations

GB (1)