Computer Assisted Detection of Cancer Cells in Minimal Samples of Lung Cancer

We present and validate a quantitative, multidimensional image analysis protocol to assist in the early detection of lung cancer in minimal samples of bronchoalveolar lavage (BAL). To that end we stained BAL samples using Fluorescence Immunophenotyping and Interphase Cytogenetics as a Tool for the Investigation of Neoplasms (FICTION). Our method allows preliminary immunophenotypic detection of rare cancerous candidate cells, followed by accurate three-dimensional analysis of genomic integrity, to confirm or refute the initial assessment. Our results show that our automated analysis can accurately assist a human expert in the diagnostic evaluation of BAL samples.