Spots Global Cancer Trial Database for Light-CT in the Diagnosis of Breast Tumor and Lymph Node

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Trial Identification

Brief Title: Light-CT in the Diagnosis of Breast Tumor and Lymph Node

Official Title: Achieving Rapid Diagnosis During Breast Cancer Surgery Using Light-CT (High-resolution Full-field Optical Coherence Tomography and Dynamic Cell Imaging)

Study ID: NCT03791853

Conditions

Breast Neoplasms

Interventions

Light-CT

Study Description

Brief Summary: Intraoperative pathological diagnosis such as frozen section and imprint cytology is not routinely recommended in clinical practice because of time and accuracy concerns. Full-field optical coherence tomography (FF-OCT) is a new optical imaging technique that could generate sectioning tomogram from fresh tissue and provide close-to-pathology depiction of the morphological structure and pathological changes in minutes without conventional tissue preparation, slicing, and staining, and dynamic cell imaging (DCI) added the viability information of cells/tissue, which could be more important in cancer diagnosis. This study was to evaluate the feasibility and diagnostic value of FF-OCT and DCI in breast lesions and lymph node specimens during breast cancer surgery. We evaluated normal breast tissue, benign breast lesions, breast cancer and axillary lymph node specimens resected from patients undergoing breast surgery.

Detailed Description: Light-CT, a special-designed pathology-approximation system which is based on the lighting feature or dynamic feature of tissue and cells, is used to detect malignant cells or tissue in fresh specimens. Morphological structure and pathological changes could be captured in minutes, which implies a possible application in intraoperative diagnosis. In this study, fresh breast tissue, fat, benign breast lesions, breast cancer and axillary lymph node specimens are collected to assess the usefulness of Light-CT. During the in vitro examination, both FF-OCT and DCI images are obtained and stored. Imaging analysis would be performed in traditional imaging analysis like manner and an artificial intelligence aided approach as well. In this study, breast and lymph node specimens would be collected and imaged both through light imaging and conventional pathological analysis.