Abstract CT220: Expansion into multiple institutions for training in the use of the LUM Imaging System for intraoperative detection of residual cancer in the tumor bed of female subjects with breast cancer
Authors: Kate Smith, Jorge M. Ferrer, Barbara L. Smith, E. Shelley Hwang, Kelly K. Hunt, Daleela G. Dodge, Stephen E. Karp, Stephanie A. Valente, Irene L. Wapnir, Lynne P. Clark, David R. Carr, Peter D. Beitsch, Donna L. Dyess, Beth-Ann Lesnikoski, Peter W. Blumencranz, Nayana S. Dekhne, Linsey P. Gold, Anees Chagpar, Katherine Kacena, Livia Gjylameti, Felix Geissler
Journal: Cancer Research (2019)

Abstract Background: Obtaining tumor-free margins is critical for local control in breast conserving surgery. Currently, 20-40% of lumpectomy patients have positive margins that require surgical re-excision; this is a significant burden for patients, surgeons and the healthcare system. Therefore, it is of paramount importance that all cancer be resected from the tumor bed during lumpectomy surgery. The LUM Imaging System consists of a fluorescence-based imaging agent, a hand-held wide-field detector (LUM Imaging Device) used to image the surgical cavity walls intraoperatively in real-time after the resection of the main lumpectomy specimen, and a proprietary tumor detection algorithm that highlights regions in the tumor bed suspected to contain residual cancer. Methods: This multi-site clinical study is designed to refine the tumor detection algorithm developed in previous studies by correlating images generated by the LUM Imaging System with histopathology results. This is a prospective, interventional feasibility study and is an introductory arm to a pivotal study which will evaluate the safety and efficacy of the LUM Imaging System in reducing the positive margin rate during standard of care lumpectomies. Up to 250 adult female breast cancer patients undergoing lumpectomies are being enrolled at sixteen medical centers across the US. The novel imaging agent, LUM015, is injected into all enrolled subjects prior to their lumpectomy procedure. Subjects undergo the standard of care lumpectomy followed by intraoperative use of the LUM Imaging System which helps guide surgeons in identifying potential residual tumor tissue. The primary objective is to assess performance characteristics of the LUM Imaging System and to fine-tune the tumor detection algorithm. A secondary objective is to develop and refine the process of implementing the LUM Imaging System into institution-specific workflows during lumpectomies. A comprehensive process to evaluate the LUM Imaging System has been implemented and will be reported. This study is being conducted under an Investigational Device Exemption (IDE) approved by the FDA. To date, 72 subjects have been imaged using the LUM Imaging System. Successful implementation of standardized tissue collection, naming conventions, and LUM Imaging System training is intended to improve the quality and integrity of the data collected in the upcoming pivotal clinical trial to evaluate the safety and efficacy of the LUM Imaging System. This study is partially funded by a grant from the National Cancer Institute (award 1R44CA211013) to support biomedical technology development and Lumicell Inc. and is registered on Clinical Trials.gov as NCT03321929. Citation Format: Kate Smith, Jorge M. Ferrer, Barbara L. Smith, E. Shelley Hwang, Kelly K. Hunt, Daleela G. Dodge, Stephen E. Karp, Stephanie A. Valente, Irene L. Wapnir, Lynne P. Clark, David R. Carr, Peter D. Beitsch, Donna L. Dyess, Beth-Ann Lesnikoski, Peter W. Blumencranz, Nayana S. Dekhne, Linsey P. Gold, Anees Chagpar, Katherine Kacena, Livia Gjylameti, Felix Geissler. Expansion into multiple institutions for training in the use of the LUM Imaging System for intraoperative detection of residual cancer in the tumor bed of female subjects with breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr CT220.