A Prospective Study to Evaluate the Application of EndoScell Intraoperative Cellular Probing Technology in Breast Conserving Therapy and Sentinel Lymph Node Biopsy for Early-Stage Breast Cancer

In recent years, the incidence of breast cancer in China has risen rapidly. Over the past two decades, the annual average incidence rate has increased from 15 per 100,000 to about 30 per 100,000. In first-tier cities like Shanghai, the incidence rate even exceeds 60 per 100,000, making breast cancer the leading malignant tumor threatening women's health. Compared to Western countries, the onset age of breast cancer in Chinese women is relatively younger, with over 54% of cases occurring before menopause. Surgery remains the mainstay of comprehensive treatment for breast cancer. Nearly half of the patients require mastectomy due to the extent or location of the tumor, resulting in significant disfigurement and long-term psychological trauma. In recent years, the demand for postoperative breast appearance among breast cancer patients in China has been increasing, leading to a rise in the proportion of conventional breast-conserving surgery, breast-conserving surgery, and various types of breast reconstruction surgeries.

Breast-conserving surgery combined with postoperative radiotherapy can improve the postoperative breast appearance and quality of life while achieving tumor safety equal to or even better than that of total mastectomy. Breast-conserving oncoplastic surgery, which combine the principles of conventional breast conservation with plastic surgery techniques, further enhance the feasibility and safety of breast-conserving surgery.

The development of breast-conserving oncoplastic surgery has created a more urgent need to ensure negative margins intraoperatively. Despite expanding surgical indications due to the application of oncoplastic techniques, the positive margin rate of breast-conserving oncoplastic surgery is not significantly different from that of conventional breast-conserving surgery, ranging from 5% to 15%. Although re-excision after a positive margin does not affect local recurrence risk, it significantly diminishes postoperative cosmetic outcomes. More importantly, the design of oncoplastic surgery incisions becomes a challenge if mastectomy is needed based on margin status. Currently, the most accurate method for margin assessment is postoperative margin staining followed by radial sectioning and paraffin pathology examination. To enable timely intraoperative margin assessment, various methods have been proposed, including intraoperative frozen section analysis, specimen X-ray photography, and micro-computed tomography. However, these methods require ex vivo specimen evaluation and have limited sensitivity. Small sample studies have used micro-PET/CT technology for specimen imaging, but its high cost prevents widespread clinical validation and application.

The EndoScell Scaner (ES) is a novel intraoperative cell detection technology that uses a modified real-time miniaturized fluorescence microscope system for image acquisition, achieving ultra-high resolution at the cellular level. Previous studies have shown that its accuracy and sensitivity in intraoperative sentinel lymph node detection are comparable to those of cytological imprinting but with greater speed. This technology employs sodium fluorescein and methylene blue as fluorescent dyes, is non-invasive, and does not consume tissue samples.

This study aims to evaluate the clinical value of the EndoScell Scaner (ES) novel intraoperative cell probing technology for intraoperative margin assessment in patients undergoing conventional breast-conserving surgery and breast-conserving oncoplastic surgery combined with sentinel lymph node biopsy. The primary objective is to compare the accuracy of ES technology in assessing margin status and sentinel lymph node status using paraffin pathology as the gold standard. The primary endpoints are the accuracy of ES technology, positive margin rate, and reoperation rate; the secondary endpoints are ES detection image quality score, learning curve of surgeons, and detection time.