Near infrared lymphatic mapping in thoracic malignancies
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Abstract
Lung cancer is the leading cause of all cancer deaths in men and women combined, killing more than 150,000 patients per year. Lymph node status is the best predictor of survival in patients with surgically resectable lung cancer. The 5 year survival rates for node negative (N0), hilar node positive (N1), and mediastinal node positive (N2) disease is 53.8%, 26.3%, and 20.8%, respectively. Accurate staging of the disease will lead to the most effective adjuvant therapy strategy. However, routine pathologic analysis of sampled lymph nodes underestimates the prevalence of metastatic disease. Patients with missed metastatic disease do not receive proper treatment which likely contributes to the high recurrence rate and poor 5 year survival of lung cancer patients. Detection of lymph nodes at highest risk for harboring metastatic disease (i.e. sentinel lymph nodes (SLN)) may permit more intensive histologic analysis to detect occult disease. Presently there is no safe and reliable method for detecting SLNs. The overall objective of this project was to identify the SLNs and treat them.
To do this, we looked at the feasibility of using indocyanine green (ICG) and near infrared (NIR) imaging in a minimally invasive video assisted thoracic surgery procedure to identify the SLNs in patients with suspected Stage I/II non small cell lung cancer (NSCLC). Previous attempts at SLN identification in patients with NSCLC using radioisotopes and blue dyes have been ineffective. ICG and NIR imaging for identification of SLNs has become standard of care in both melanoma and breast cancer. We looked to extend this technology to NSCLC. Patients were given an intraparenchymal, peritumoral injection of ICG and imaged with a NIR camera noting lymphatic migration, time to SLN identification, number of SLNs, and lymph node station. Our results demonstrated the increased rate of SLN identification over the previous studies. [TRUNCATED]
Description
Thesis (M.A.)--Boston University