Pelvic Sentinel Lymph Node Biopsy for Endometrial Cancer with Multi-Modal Infrared Signal Technology: A Video Article.
Federica PerelliEmanuele Arturo FeraMarco GiustiAlberto MatteiGiuseppe VizzielliMartina ArcieriGabriele CentiniErrico ZupiGiovanni ScambiaAnna Franca CavaliereGiulia RoveroPublished in: Healthcare (Basel, Switzerland) (2024)
This video article summarizes a case study involving the use of pelvic sentinel lymph node (SLN) biopsy for endometrial cancer (EC) staging and treatment utilizing a multi-modal infrared signal technology. This innovative approach combines cervical injection of fluorescent dye indocyanine green (ICG) and near-infrared imaging to enhance SLN detection rates in early-stage EC patients. The study showcases the successful application of advanced technology in improving surgical staging procedures and reducing postoperative morbidity for patients. Multi-modal infrared signal technology consists of different modes of fluorescence imaging used to identify lymph nodes based on near-infrared signals. Each mode serves a specific purpose: overlay image combines white light and near-infrared signals in green, monochromatic visualization shows near-infrared signal in greyscale, and intensity map combines signals in a color scale to differentiate signal intensity. Yellow denotes strong near-infrared signals while blue represents weaker signals. By utilizing a multi-modal approach, surgeons can accurately identify and remove SLN, thus avoiding unnecessary removal of secondary or tertiary echelons.
Keyphrases
- sentinel lymph node
- lymph node
- early stage
- endometrial cancer
- fluorescence imaging
- end stage renal disease
- neoadjuvant chemotherapy
- chronic kidney disease
- ejection fraction
- newly diagnosed
- radiation therapy
- prognostic factors
- patients undergoing
- ultrasound guided
- rectal cancer
- photodynamic therapy
- machine learning
- computed tomography
- patient reported outcomes
- deep learning
- magnetic resonance
- pet ct
- quantum dots
- smoking cessation
- locally advanced