Details

Autor(en) / Beteiligte

• Aguado-Sarrió, E.
• Prats-Montalbán, J.M.
• Sanz-Requena, R.
• Garcia-Martí, G.
• Martí-Bonmatí, L.
• Ferrer, A.

Titel

Biomarker comparison and selection for prostate cancer detection in Dynamic Contrast Enhanced-Magnetic Resonance Imaging (DCE-MRI)

Ist Teil von

• Chemometrics and intelligent laboratory systems, 2017-06, Vol.165, p.38-45

Ort / Verlag

Elsevier B.V

Erscheinungsjahr

2017

Link zum Volltext

Quelle

Elsevier ScienceDirect Journals Complete

Beschreibungen/Notizen

• In this work, the capability of imaging biomarkers obtained from multivariate curve resolution-alternating least squares (MCR-ALS), in combination with those obtained from first and second-generation pharmacokinetic models, have been studied for improving prostate cancer tumor depiction using partial least squares-discriminant analysis (PLS-DA). The main goal of this work is to improve tissue classification properties selecting the best biomarkers in terms of prediction. A wrapped double cross-validation method has been applied for the variable selection process. Using the best PLS-DA model, prostate tissues can be classified obtaining 13.4% of false negatives and 7.4% of false positives. Using MCR-ALS biomarkers yields the best models in terms of parsimony and classification performance. •MCR-ALS and pharmacokinetic biomarkers has been studied for cancer depiction.•PLS-DA and variable selection have been employed for tissue classification.•Significant results prove that MCR biomarkers perform better than pharmacokinetics.