Wenbin Yu1, XiaoLi Cao2, Guihu Xu3, Yuntao Song3, Guojun Li4, Hongliang Zheng5, Naisong Zhang3. 1. Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Head and Neck surgery, Peking University Cancer Hospital and Institute Beijing, China. Electronic address: yuwenbin429@qq.com. 2. Department of Ultrasound, Yantai Yuhuangding Hospital, Yantai, China. 3. Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Head and Neck surgery, Peking University Cancer Hospital and Institute Beijing, China. 4. Department of Head and Neck Surgery, The University of Texas MD Anderson Cancer Center, Houston, TX. Electronic address: gli@mdanderson.org. 5. Department of Otorhinolaryngology-Head and Neck Surgery, Changhai Hospital, Second Military Medical University, Shanghai, China.
Abstract
BACKGROUND: The purpose of this study was to investigate the use and clinical utility of carbon nanoparticles as a lymph node tracer in the central neck lymph node dissection of patients with papillary thyroid cancer. METHODS:One hundred forty consecutive patients were divided into a carbon nanoparticle group (n = 70) and a control group (n = 70). All patients underwent total or near-total thyroidectomy with bilateral central neck dissection. RESULTS: The carbon nanoparticle and control groups had different rates of metastatic lymph nodes (P = .017), total detected numbers of lymph nodes (P = .0001), total numbers of dissected lymph nodes <5 mm (P = .0001), and numbers of metastatic lymph nodes <5 mm (P = .0001). Of the 682 lymph nodes dissected in the carbon nanoparticle group, 579 (85%) were stained black, and of these, 147 (25%) were metastatic lymph nodes. There were 63 metastatic lymph nodes <5 mm among the black-stained metastatic lymph nodes, while there were 12 non-black-stained metastatic lymph nodes <5 mm. Of the total number of metastatic lymph nodes (n = 193), 147 (76%) were stained black. Moreover, pathologic results revealed that 5 accidental parathyroid resections occurred in the carbon nanoparticle group, compared with 14 in the control group (P = .046). CONCLUSION:Carbon nanoparticles might help to detect lymph nodes and increase the number of metastatic lymph nodes visualized and preserved. Therefore, use of carbon nanoparticles may reflect the metastatic condition of the central neck and have the potential to protect parathyroid glands.
RCT Entities:
BACKGROUND: The purpose of this study was to investigate the use and clinical utility of carbon nanoparticles as a lymph node tracer in the central neck lymph node dissection of patients with papillary thyroid cancer. METHODS: One hundred forty consecutive patients were divided into a carbon nanoparticle group (n = 70) and a control group (n = 70). All patients underwent total or near-total thyroidectomy with bilateral central neck dissection. RESULTS: The carbon nanoparticle and control groups had different rates of metastatic lymph nodes (P = .017), total detected numbers of lymph nodes (P = .0001), total numbers of dissected lymph nodes <5 mm (P = .0001), and numbers of metastatic lymph nodes <5 mm (P = .0001). Of the 682 lymph nodes dissected in the carbon nanoparticle group, 579 (85%) were stained black, and of these, 147 (25%) were metastatic lymph nodes. There were 63 metastatic lymph nodes <5 mm among the black-stained metastatic lymph nodes, while there were 12 non-black-stained metastatic lymph nodes <5 mm. Of the total number of metastatic lymph nodes (n = 193), 147 (76%) were stained black. Moreover, pathologic results revealed that 5 accidental parathyroid resections occurred in the carbon nanoparticle group, compared with 14 in the control group (P = .046). CONCLUSION:Carbon nanoparticles might help to detect lymph nodes and increase the number of metastatic lymph nodes visualized and preserved. Therefore, use of carbon nanoparticles may reflect the metastatic condition of the central neck and have the potential to protect parathyroid glands.
Authors: Jacek Baj; Robert Sitarz; Marek Łokaj; Alicja Forma; Marcin Czeczelewski; Amr Maani; Gabriella Garruti Journal: Molecules Date: 2020-04-09 Impact factor: 4.411