Clinical Trials Directory

Trials / Unknown

UnknownNCT05623280

Artificial Intelligence Analysis of Fluorescence Image to Intraoperatively Detect Metastatic Sentinel Lymph Node.

Artificial Intelligence Analysis of Fluorescence Image to Intraoperatively Detect Metastatic Sentinel Lymph Node in Patients With Breast Cancer.

Status
Unknown
Phase
Study type
Observational
Enrollment
40 (estimated)
Sponsor
Xiang'an Hospital of Xiamen University · Academic / Other
Sex
Female
Age
18 Years – 70 Years
Healthy volunteers
Not accepted

Summary

The purpose of this study is to analysis the fluorescence image of the breast sentinel lymph node (SLN) using Indocyanine green (ICG). Moreover, to investigate whether an artificial intelligence protocol was suitable for identifying metastatic status of SLN during the surgery, and evaluate the diagnosis consistency of the AI technique and pathological examinations for lymph node with and without metastasis.

Detailed description

Assessment of the sentinel lymph node (SLN) in patients with early stage breast cancer is vital in selecting the appropriate surgical approach. But identification of metastatic LNs within the fibro-adipose tissue of the fossa axillaris specimen remains a challenge. Recently, indocyanine green (ICG) and methylene blue are commonly used in clinical practice. ICG as a fluorescent dyes, has effectiveness in mapping SLNs during surgery. Surgeons can follow the fluorescence display to detect SLN, and simultaneously capture real-time fluorescent video images. Several other groups has been demonstrated that the usage of ICG fluorescent surgical navigation system to detect SLNs in breast cancer patients is technically feasible. But no study investigate the variability between fluorescent images of breast sentinel lymph node with and without metastasis in the existing paper. Deep learning (DL) artificial intelligence (AI) algorithms in medical imaging are rapidly expanding. In this study, the investigators aim to develop and validate an easy-to-use artificial intelligence prediction model to intraoperatively identify the sentinel lymph node metastasis status. Furthermore, to explore whether this independent and parallel intraoperative lymph node assessment workflow can provide rapid and accurate skull base on lymph node fluorescent images analysis, meanwhile detecting occult lymph node (micro-) metastasis, using optical imaging and artificial intelligence.

Conditions

Interventions

TypeNameDescription
DRUGIndocyanine greenInjection around the areola with 2-4 points Indocyanine green with 2ml of 1.25mg/mL

Timeline

Start date
2021-11-01
Primary completion
2024-12-01
Completion
2024-12-01
First posted
2022-11-21
Last updated
2022-11-28

Locations

1 site across 1 country: China

Regulatory

Source: ClinicalTrials.gov record NCT05623280. Inclusion in this directory is not an endorsement.