Automation of Flow Cytometric Analysis for Quality-Assured Follow-up Assessment to Guide Curative Therapy for Acute Lymphoblastic Leukaemia in Children

01.02.2014 - 31.12.2019
Forschungsförderungsprojekt

Acute Lymphoblastic Leukaemia (ALL) is the most frequent leukaemia entity in children and adolescents. Despite continued progress and refinement of therapeutic approaches, disease relapse due to insufficient extinction of leukaemic blasts still remains the number one cause of treatment failure. About 15-20% of paediatric patients with the disease still suffer from relapse. Flow cytometry (FCM) is one of the methodologies most useful in this respect, because it is widely available and applicable to most patients. While sample preparation, antibody panels, staining procedures, and FCM acquisition can be harmonized straightforwardly, data analysis and interpretation rely largely on operator skills and experience. These assessments are time-consuming and costly to be attained via staff-training, online support between twinning laboratories, and continued quality control. Hence, these requirements represent the current bottleneck of safely applying the FCM-Minimal Residual Disease (MRD) methodology in a growing community of diagnostic laboratories to the benefit of an increasing number of patients with leukaemia. To address this bottleneck, AutoFLOW aims at developing an objective and automated tool for multi-parameter FCM data analysis with robust and reliable MRD quantification. The consortium aims at engaging professionals from the medical and ICT fields in a network where the exchange of knowledge will culminate in a valid solution for automated FCM analysis for clinical follow-up assessment of Acute Lymphoblastic Leukaemia.

Personen

Projektleiter_in

Projektmitarbeiter_innen

Institut

Förderungsmittel

  • Europäische Kommission - Rahmenprogamme (Internationale Förderung und Mischformen) Förderform Unterstützung für die Aus- und Weiterbildung von Forschern Förderinitiative RP7 III. MENSCHEN (Marie Curie Maßnahmen) Förderschiene 7.Rahmenprogramm für Forschung Förderprogramm Europäische Kommission - Rahmenprogamme Fördergeber Europäische Kommission Reichweite Internationale Förderung und Mischformen Projekttyp Forschungsförderungsprojekt Ausschreibungskennung FP7-PEOPLE-2013-IAPP Antragsnummer FP7-610872

Forschungsschwerpunkte

  • Information and Communication Technology

Schlagwörter

DeutschEnglisch
maschinelles Lernen, medizinische bildverarbeitungmachine learning, medical imaging

Externe Partner_innen

  • cogvis GmbH
  • Charite
  • Infokom
  • Labdia Labordiagnostik