AI Article Synopsis
- The study explored the use of intraoperative indocyanine green (ICG) fluorescence imaging, guided by preoperative computed tomographic lymphography (CTLG), to identify sentinel lymph nodes (SLNs) in patients with superficial esophageal cancer.
- All 20 patients were able to have their lymphatic vessels and SLNs identified preoperatively using CTLG, achieving a 100% detection rate intraoperatively via CTLG and a 95% rate with IGFI.
- The results indicated that this combined method is clinically useful, providing a less-invasive approach for treating superficial esophageal cancer while accurately identifying SLNs and improving efficiency in the surgical process.
Article Abstract
Background: The sentinel lymph node (SLN) concept has been gaining attention for gastrointestinal neoplasms but remains controversial for esophageal cancer. This study evaluated the feasibility of SLN identification using intraoperative indocyanine green (ICG) fluorescence imaging (IGFI) navigated by preoperative computed tomographic lymphography (CTLG) to treat superficial esophageal cancer.
Methods: Subjects comprised 20 patients clinically diagnosed with superficial esophageal cancer. Five minutes after endoscopic submucosal injection of iopamidol around the primary lesion using a four-quadrant injection pattern with a 23-gauge endoscopic injection sclerotherapy needle, three-dimensional multidetector computed tomography was performed to identify SLNs and lymphatic routes. ICG solution was injected intraoperatively around the tumor. Fluorescence imaging was obtained by infrared ray electronic endoscopy. Thoracoscope-assisted standard radical esophagectomy with lymphadenectomy was performed to confirm fluorescent lymph nodes detected by CTLG.
Results: Lymphatic vessels and SLNs were identified preoperatively using CTLG in all cases. Intraoperative detection rates were 100% using CTLG and 95% using IGFI. Lymph node metastases were found in four cases, including one false-negative case with SLNs occupied by bulky metastatic tumor that were not enhanced with both methods. The other 19 cases, including three cases of metastatic lymph nodes, were accurately identified by both procedures.
Conclusions: Preoperative CTLG visualized the correct number and site of SLNs in surrounding anatomy during routine computed tomography to evaluate distant metastases. Referring to CTLG, SLNs were identified using IGFI, resulting in successful SLN navigation and saving time and cost. This method appears clinically applicable as a less-invasive method for treating superficial esophageal cancer.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1245/s10434-011-1922-x | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Esophageal squamous cell carcinoma (ESCC) remains a significant global health challenge, being the sixth leading cause of cancer mortality with pronounced geographic variability. The incidence rates range from 125 per 100,000 in northern China to 1-1.5 per 100,000 in the United States, driven by environmental and lifestyle factors such as tobacco and alcohol use, dietary habits, and pollution.
View Article and Find Full Text PDFObjectives: The efficacy and safety of a sedation regimen combining dexmedetomidine and midazolam during endoscopic submucosal dissection for upper gastrointestinal tumors remains unclear. In this study, we aimed to evaluate the efficacy and safety of this sedation regimen, where non-anesthesiologists performed sedation.
Methods: Sixty-eight patients who underwent endoscopic submucosal dissection for upper gastrointestinal tumors, sedated by non-anesthesiologists, were retrospectively evaluated.
Development of Deep Learning-Based Virtual Lugol Chromoendoscopy for Superficial Esophageal Squamous Cell Carcinoma.
J Gastroenterol Hepatol
December 2024
Division of Gastroenterology and Hepatology, Department of Internal Medicine, School of Medicine, Iwate Medical University, Iwate, Japan.
Background: Lugol chromoendoscopy has been shown to increase the sensitivity of detection of esophageal squamous cell carcinoma (ESCC). We aimed to develop a deep learning-based virtual lugol chromoendoscopy (V-LCE) method.
Methods: We developed still V-LCE images for superficial ESCC using a cycle-consistent generative adversarial network (CycleGAN).
Computer-aided endoscopic diagnostic system modified with hyperspectral imaging for the classification of esophageal neoplasms.
Front Oncol
December 2024
Department of Mechanical Engineering, National Chung Cheng University, Chiayi, Taiwan.
Introduction: The early detection of esophageal cancer is crucial to enhancing patient survival rates, and endoscopy remains the gold standard for identifying esophageal neoplasms. Despite this fact, accurately diagnosing superficial esophageal neoplasms poses a challenge, even for seasoned endoscopists. Recent advancements in computer-aided diagnostic systems, empowered by artificial intelligence (AI), have shown promising results in elevating the diagnostic precision for early-stage esophageal cancer.
View Article and Find Full Text PDFImpact of preceding treatment for head and neck squamous cell carcinoma on synchronous superficial esophageal squamous cell carcinoma.
J Gastroenterol
December 2024
Department of Head and Neck Surgery, Osaka International Cancer Institute, Osaka, Japan.
Background: Patients with esophageal squamous cell carcinoma (ESCC) frequently develop synchronous head and neck squamous cell carcinoma (HNSCC). With advances in endoscopic technology and widespread screening of synchronous cancers, the detection of synchronous HNSCC and superficial ESCC (SESCC) is increasing. We aimed to evaluate the impact of preceding HNSCC treatment on synchronous SESCC.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!