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.
Ortiz-de-Solorzano
Carlos
C
Oncology Division, Center for Applied Medical Research, University of Navarra, Pamplona, Spain.
Ucar-Vargas
Beatriz
B
Pengo
Thomas
T
Zudaire
Isabel
I
Montuenga
Luis M
LM
Munoz-Barrutia
Arrate
A
D000465:Algorithms; D001185:Artificial Intelligence; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008175:Lung Neoplasms / Q000473:pathology*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D018401:Sample Size; D012680:Sensitivity and Specificity