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Tumor lesion detection in patients with cervical cancer by indocyanine green near-infrared imaging.
Li, Pengfei; Liu, Jiaqi; He, Kunshan; Gong, Shipeng; Chi, Chongwei; Liu, Pan; Su, Guidong; Li, Weili; Duan, Hui; Liu, Ping; Tian, Jie; Chen, Chunlin.
  • Li P; Department of Obstetrics and Gynecology, Nanfang Hospital, Southern Medical University, No. 1838, Guangzhou Avenue, Guangzhou, 510515, China.
  • Liu J; Department of Obstetrics and Gynecology, Nanfang Hospital, Southern Medical University, No. 1838, Guangzhou Avenue, Guangzhou, 510515, China.
  • He K; Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, School of Medicine and Engineering, Beihang University, Beijing, 100191, China.
  • Gong S; Key Laboratory of Big Data-Based Precision Medicine, Ministry of Industry and Information Technology, Beihang University, 100191, Beijing, China.
  • Chi C; CAS Key Laboratory of Molecular Imaging, the State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China.
  • Liu P; Department of Obstetrics and Gynecology, Nanfang Hospital, Southern Medical University, No. 1838, Guangzhou Avenue, Guangzhou, 510515, China.
  • Su G; CAS Key Laboratory of Molecular Imaging, the State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China.
  • Li W; Department of Obstetrics and Gynecology, Nanfang Hospital, Southern Medical University, No. 1838, Guangzhou Avenue, Guangzhou, 510515, China.
  • Duan H; Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, School of Medicine and Engineering, Beihang University, Beijing, 100191, China.
  • Liu P; Department of Obstetrics and Gynecology, Nanfang Hospital, Southern Medical University, No. 1838, Guangzhou Avenue, Guangzhou, 510515, China.
  • Tian J; Department of Obstetrics and Gynecology, Nanfang Hospital, Southern Medical University, No. 1838, Guangzhou Avenue, Guangzhou, 510515, China.
  • Chen C; Department of Obstetrics and Gynecology, Nanfang Hospital, Southern Medical University, No. 1838, Guangzhou Avenue, Guangzhou, 510515, China. lpivy@126.com.
Eur J Nucl Med Mol Imaging ; 50(4): 1252-1261, 2023 03.
Article en En | MEDLINE | ID: mdl-36450938
ABSTRACT

PURPOSE:

To investigate the feasibility and accuracy of near-infrared fluorescence (NIRF) imaging for detecting the extent of tumor invasion in cervical cancer using indocyanine green (ICG).

METHODS:

We enrolled 51 patients who were diagnosed with cervical cancer with FIGO stage IB1-IIA2 disease. Patients were administered indocyanine green (ICG) at a dose of 5 mg/kg 24 h prior to surgery. A customized near-infrared fluorescence (NIRF) imaging system was used to identify the extent of tumor invasion when radical hysterectomy specimens were harvested. The relationship between tumor fluorescence intensity and clinicopathological characteristics was analyzed.

RESULTS:

Of the 51 enrolled patients, 3 patients did not have residual tumors after cervical conization, and tumor lesions were identified by NIRF imaging in all the remaining 48 patients. The results of NIRF imaging were in agreement with the postoperative pathological findings in 95.8% of the patients with stromal invasion, 100% of those with surgical margin invasion, 100% of those with parametrial tumor involvement, and 100% of patients with uterine corpus invasion. The mean signal-to-background ratio (SBR) of the cervical tumors was 2.91 ± 1.64, and the SBR was independent of clinicopathological characteristics. Fluorescence microscopy confirmed that ICG fluorescence was present in the tumor nests.

CONCLUSIONS:

NIRF imaging enables objective, accurate, and safe identification of tumor invasion during cervical cancer surgery. CLINICAL TRIAL REGISTRATION ClinicalTrials.gov NCT04224467.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Neoplasias del Cuello Uterino Tipo de estudio: Diagnostic_studies / Prognostic_studies Límite: Female / Humans Idioma: En Año: 2023 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Neoplasias del Cuello Uterino Tipo de estudio: Diagnostic_studies / Prognostic_studies Límite: Female / Humans Idioma: En Año: 2023 Tipo del documento: Article