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
| Type | Name | Description |
|---|---|---|
| DRUG | Indocyanine green | Injection 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
- FDA-regulated drug study
Source: ClinicalTrials.gov record NCT05623280. Inclusion in this directory is not an endorsement.