Usefulness and Prospects of Sentinel Lymph Node Biopsy for Patients With Breast Cancer Using the Medical Imaging Projection System

Application value of indocyanine green fluorescence imaging in guiding sentinel lymph node biopsy diagnosis of gastric cancer: Meta-analysis

BACKGROUND

Gastric cancer is a common malignant tumor of the digestive system worldwide, and its early diagnosis is crucial to improve the survival rate of patients. Indocyanine green fluorescence imaging (ICG-FI), as a new imaging technology, has shown potential application prospects in oncology surgery. The meta-analysis to study the application value of ICG-FI in the diagnosis of gastric cancer sentinel lymph node biopsy is helpful to comprehensively evaluate the clinical effect of this technology and provide more reliable guidance for clinical practice.

AIM

To assess the diagnostic efficacy of optical imaging in conjunction with indocyanine green (ICG)-guided sentinel lymph node (SLN) biopsy for gastric cancer.

METHODS

Electronic databases such as PubMed, Embase, Medline, Web of Science, and the Cochrane Library were searched for prospective diagnostic tests of optical imaging combined with ICG-guided SLN biopsy. Stata 12.0 software was used for analysis by combining the "bivariable mixed effect model" with the "midas" command. The true positive value, false positive value, false negative value, true negative value, and other information from the included literature were extracted. A literature quality assessment map was drawn to describe the overall quality of the included literature. A forest plot was used for heterogeneity analysis, and P < 0.01 was considered to indicate statistical significance. A funnel plot was used to assess publication bias, and P < 0.1 was considered to indicate statistical significance. The summary receiver operating characteristic (SROC) curve was used to calculate the area under the curve (AUC) to determine the diagnostic accuracy. If there was interstudy heterogeneity (I² > 50%), meta-regression analysis and subgroup analysis were performed.

RESULTS

Optical imaging involves two methods: Near-infrared (NIR) imaging and fluorescence imaging. A combination of optical imaging and ICG-guided SLN biopsy was useful for diagnosis. The positive likelihood ratio was 30.39 (95%CI: 0.92-1.00), the sensitivity was 0.95 (95%CI: 0.82-0.99), and the specificity was 1.00 (95%CI: 0.92-1.00). The negative likelihood ratio was 0.05 (95%CI: 0.01-0.20), the diagnostic odds ratio was 225.54 (95%CI: 88.81-572.77), and the SROC AUC was 1.00 (95%CI: The crucial values were sensitivity = 0.95 (95%CI: 0.82-0.99) and specificity = 1.00 (95%CI: 0.92-1.00). The Deeks method revealed that the "diagnostic odds ratio" funnel plot of SLN biopsy for gastric cancer was significantly asymmetrical (P = 0.01), suggesting significant publication bias. Further meta-subgroup analysis revealed that, compared with fluorescence imaging, NIR imaging had greater sensitivity (0.98 vs 0.73). Compared with optical imaging immediately after ICG injection, optical imaging after 20 minutes obtained greater sensitivity (0.98 vs 0.70). Compared with that of patients with an average SLN detection number < 4, the sensitivity of patients with a SLN detection number ≥ 4 was greater (0.96 vs 0.68). Compared with hematoxylin-eosin (HE) staining, immunohistochemical (+ HE) staining showed greater sensitivity (0.99 vs 0.84). Compared with subserous injection of ICG, submucosal injection achieved greater sensitivity (0.98 vs 0.40). Compared with 5 g/L ICG, 0.5 and 0.05 g/L ICG had greater sensitivity (0.98 vs 0.83), and cT1 stage had greater sensitivity (0.96 vs 0.72) than cT2 to cT3 clinical stage. Compared with that of patients ≤ 26, the sensitivity of patients > 26 was greater (0.96 vs 0.65). Compared with the literature published before 2010, the sensitivity of the literature published after 2010 was greater (0.97 vs 0.81), and the differences were statistically significant (all P < 0.05).

CONCLUSION

For the diagnosis of stomach cancer, optical imaging in conjunction with ICG-guided SLN biopsy is a therapeutically viable approach, especially for early gastric cancer. The concentration of ICG used in the SLN biopsy of gastric cancer may be too high. Moreover, NIR imaging is better than fluorescence imaging and may obtain higher sensitivity.

Indocyanine green fluorescence versus blue dye, technetium-99M, and the dual-marker combination of technetium-99M + blue dye for sentinel lymph node detection in early breast cancer-meta-analysis including consistency analysis

BACKGROUND

Axillary sentinel lymph node biopsies are standard of care in patients with breast cancer and no clinically apparent metastases. Traditionally, technetium-99m, blue dye, or both have been used to identify sentinel lymph nodes. However, blue dyes miss up to 40% of sentinel lymph nodes, while technetium-99m use is complex, costly, and exposes patients to radiation. Over the past decade, studies have consistently found the biologically inert fluorescent indocyanine green to be 95% to 100% sensitive in detecting breast cancer sentinel lymph nodes, yet indocyanine green remains infrequently used.

METHODS

We conducted an extensive meta-analysis comparing indocyanine green against blue dye, technetium-99m, and the dual-marker combination of technetium-99m + BD. Unlike prior meta-analyses that only assessed either per-case or per-node sentinel lymph node detection, we analyzed the following 5 metrics: per-case and per-node sentinel lymph node detection and metastasis-positive sentinel lymph node sensitivity, and mean number of sentinel lymph nodes/case. We further examined the consistency and magnitude of between-study superiority and statistically significant within-study superiority of each marker against others.

RESULTS

For every metric and analysis approach, indocyanine green was clearly superior to blue dye and at least non-inferior, if not superior, to technetium-99m and technetium-99m + blue dye. Assessing the consistency of superiority by at least 2.0%, indocyanine green was superior to blue dye 73 times versus 1, to technetium-99m 42 times versus 9, and to technetium-99m + blue dye 6 times versus 0. Within-study statistically significant differences favored indocyanine green over blue dye 29 times versus 0 and over technetium-99m 11 times versus 2.

DISCUSSION

For sentinel lymph node detection in patients with breast cancer with no clinically apparent metastases, indocyanine green is clearly and consistently superior to blue dye and either non-inferior or superior to technetium-99m and technetium-99m + blue dye.

Meta-analysis of the application value of indocyanine green fluorescence imaging in guiding sentinel lymph node biopsy for breast cancer

OBJECTIVE

The main objective of this study was to compare the application value of indocyanine green fluorescence imaging (ICGFI) and its combined tracing method with the blue dye method in guiding sentinel lymph node biopsy for breast cancer.

MATERIALS AND METHODS

A computerized search of the Pubmed, Embase, Web of Science, and Cochrane Library databases was conducted to identify all relevant literature on ICGFI compared to the sole methylene blue (MB) tracing method in guiding sentinel lymph node biopsy for breast cancer. The search was performed up until May 2023. After assessing the quality of the included studies, a meta-analysis was conducted using STATA 12.0 software.

RESULTS

A total of 11 relevant studies were included in this research. The analysis results showed that, in terms of the detection rate, the ICGFI group had a higher detection rate to the MB group [odds ratio (OR) = 8.64, 95% CI: 5.46-13.66, P = 0.000], and had a higher quantity compared to the MB group [weighted mean difference (WMD) = 0.72, 95% CI 0.31-1.13, P = 0.001], and it also had a lower false-negative rate [OR = 0.10, 95% CI 0.02-0.43, P = 0.002]. However, there was no statistically significant difference in the positive detection rate, and sensitivity comparison.

CONCLUSION

The indocyanine green fluorescence imaging and tracing method for sentinel lymph node biopsy for breast cancer are simple and effective, and they are well suited for clinical use. A multicenter randomized controlled trial with a large sample size should be conducted in the future for further validation of the method.

Image-guided cancer surgery: a narrative review on imaging modalities and emerging nanotechnology strategies

Surgical resection is the cornerstone of solid tumour treatment. Current techniques for evaluating margin statuses, such as frozen section, imprint cytology, and intraoperative ultrasound, are helpful. However, an intraoperative assessment of tumour margins that is accurate and safe is clinically necessary. Positive surgical margins (PSM) have a well-documented negative effect on treatment outcomes and survival. As a result, surgical tumour imaging methods are now a practical method for reducing PSM rates and improving the efficiency of debulking surgery. Because of their unique characteristics, nanoparticles can function as contrast agents in image-guided surgery. While most image-guided surgical applications utilizing nanotechnology are now in the preclinical stage, some are beginning to reach the clinical phase. Here, we list the various imaging techniques used in image-guided surgery, such as optical imaging, ultrasound, computed tomography, magnetic resonance imaging, nuclear medicine imaging, and the most current developments in the potential of nanotechnology to detect surgical malignancies. In the coming years, we will see the evolution of nanoparticles tailored to specific tumour types and the introduction of surgical equipment to improve resection accuracy. Although the promise of nanotechnology for producing exogenous molecular contrast agents has been clearly demonstrated, much work remains to be done to put it into practice.

Real-time Navigation for Vascularized Lymph-node Transplantation Using Projection Mapping with Indocyanine Green Fluorescence

The medical imaging projection system (MIPS) is a real-time surgical navigation device using indocyanine green (ICG) emission signals and active projection mapping. The difference between the object and the projected image is within 1 mm, and the time lag is within 0.1 seconds. We herein report the application of the MIPS to vascularized lymph-node transplantation (VLNT) surgery for lower extremity lymphedema to detect inguinal lymph nodes and perform color-coded navigation surgery for lymph-node resection. A left superficial inguinal lymph node was planned to be used as a donor for VLNT to the right lower leg in a 73-year-old woman with lower extremity lymphedema. Under general anesthesia, multiple intradermal injections of 0.1 ml of ICG were administered around the left inguinal donor site. The MIPS showed a clear linear projection image from a lateral injected point connecting to a lateral superficial inguinal lymph node. The left superficial circumflex iliac artery and vein were dissected for vascularized VLNT. Intraoperative real-time MIPS navigation continuously guided the transection plane colored by ICG fluorescence signals without shifting the visual focus from the surgical field. This is the first report of the intraoperative use of ICG projection mapping for VLNT donor-site surgery. The MIPS was able to visualize functional lymph nodes to facilitate minimally invasive donor-site surgery.

Indocyanine green-enhanced thoracoscopic localization of parasternal lymph node: How to do it

Small, non-palpable, parasternal lymph nodes can be difficult to locate during minimally invasive thoracoscopy. We here present a simple technique for thoracoscopic localization of small parasternal lymph nodes using echo-guided injection of indocyanine green. This technique rapidly marks the whole chain of enhanced lymph nodes for radical resection, enabling accurate endoscopic resection of small parasternal lymph nodes.

Multimodal Imaging of Target Detection Algorithm under Artificial Intelligence in the Diagnosis of Early Breast Cancer

This study aimed to analyze the diagnostic value of multimodal images based on artificial intelligence target detection algorithms for early breast cancer, so as to provide help for clinical imaging examinations of breast cancer. This article combined residual block with inception block, constructed a new target detection algorithm to detect breast lumps, used deep convolutional neural network and ultrasound imaging in diagnosing benign and malignant breast lumps, took breast density grading with mammography, compared the convolutional neural network (CNN) algorithm with the proposed algorithm, and then applied the proposed algorithm to the diagnosis of 120 female patients with breast lumps. According to the results, accuracy rates of breast lump detection (94.76%), benign and malignant breast lumps diagnosis (98.22%), and breast grading (93.65%) with the algorithm applied in this study were significantly higher than those (75.67%, 87.23%, and 79.54%) with CNN algorithm, and the difference was statistically significant (P < 0.05); among 62 patients with malignant breast lumps of the 120 patients with breast lumps, 37 were patients with invasive ductal carcinoma, 8 with lobular carcinoma in situ, 16 with intraductal carcinoma, and 4 with mucinous carcinoma; among the remaining 58 patients with benign breast lumps, 28 were patients with fibrocystic breast disease, 17 with intraductal papilloma, 4 with breast hyperplasia, and 9 with adenopathy; the differences in shape, growth direction, edge, and internal echo of multimodal ultrasound imaging of patients with benign and malignant breast lumps had statistical significance (P < 0.05); the malignant constituent ratios of patients with breast density grades I to IV were 0%, 7.10%, 80.40%, and 100%, respectively. In short, the multimodal imaging diagnosis under the algorithm in this article was superior to CNN algorithm in all aspects; according to the judgment on benign and malignant breast lumps and breast density with multimodal imaging features, the higher the breast density, the higher the probability of breast cancer.