Rapid discrimination of multiple myeloma patients by artificial neural networks coupled with mass spectrometry of peripheral blood plasma - Deulofeu, Meritxell; Kolářová, Lenka; Salvadó, Victoria; María Peña-Méndez, Eladia; Almáši, Martina; Štork, Martin; Pour, Luděk; Boadas-Vaello, Pere; Ševčíková, Sabina; Havel, Josef; Vaňhara, Petr (Scientific reports, 2019)
Multiple myeloma (MM) is a highly heterogeneous disease of malignant plasma cells. Diagnosis and monitoring of MM patients is based on bone marrow biopsies and detection of abnormal immunoglobulin in serum and/or urine. However, biopsies have a single-site bias; thus, new diagnostic tests and early detection strategies are needed. Matrix-Assisted Laser Desorption/Ionization Time-of Flight Mass Spectrometry (MALDI-TOF MS) is a powerful method that found its applications in clinical diagnostics. Artificial intelligence approaches, such as Artificial Neural Networks (ANNs), can handle non-linear data and provide prediction and classification of variables in multidimensional datasets. In this study, we used MALDI-TOF MS to acquire low mass profiles of peripheral blood plasma obtained from MM patients and healthy donors. Informative patterns in mass spectra served as inputs for ANN that specifically predicted MM samples with high sensitivity (100%), specificity (95%) and accuracy (98%). Thus, mass spectrometry coupled with ANN can provide a minimally invasive approach for MM diagnostics.
Keywords: senioři; analýza hlavních komponent; senioři nad 80 let; Multiple Myeloma; Immunoglobulins; Male; datové soubory jako téma; Middle Aged; Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization; mužské pohlaví; metabolom; studie případů a kontrol; Metabolic Networks and Pathways; kostní dřeň; Neural Networks, Computer; Metabolome; Aged, 80 and over; Artificial Intelligence; Principal Component Analysis; mnohočetný myelom; ženské pohlaví; neuronové sítě; Humans; Datasets as Topic; umělá inteligence; lidé středního věku; imunoglobuliny; spektrometrie hmotnostní - ionizace laserem za účasti matrice; Bone Marrow; metabolické sítě a dráhy; Female; Aged; lidé; Case-Control Studies