The MSACL Conference provides a forum for discussion of developments in the clinical application of mass spectrometry. The 8th Annual Conference MSACL 2016 US will be held in February 21 – 25, 2016 in Palm Springs, CA.
SCiLS participates with a poster presentation on „Automated tumor typing of tissue sections based on MALDI mass spectrometry imaging data and machine learning using characteristic spectral patterns“ given by Tobias Boskamp.
The abstract reads as follows:
We present an automated classification method for MALDI mass spectrometry imaging data with applications to tumor typing of FFPE tissue sections. The proposed method consists of a) data pre-processing, b) identification of characteristic spectral patterns using non-negative matrix factorization (NMF), and c) applying linear discriminant analysis (LDA) for classification. We apply this method to the discrimination of breast, lung, colon and pancreas cancer. MALDI data has been acquired from eight tissue micro arrays (TMAs), two for each tumor type, with a total of 943 cores from 285 patients. Four TMAs have been used for training, the remaining four TMAs for validation. A sensitivity on core level of 100.0% (lung), 99.5% (pancreas), 100.0% (colon), and 100.0% (breast) was achieved. Only limited effects of different preprocessing variants (normalization, filtering) were observed.