Forum for Science, Industry and Business

Sponsored by:     3M 
Search our Site:

 

AI-driven single blood cell classification: New method to support physicians in leukemia diagnostics

13.11.2019

For the first time, researchers from Helmholtz Zentrum München and the University Hospital of LMU Munich show that deep learning algorithms perform similar to human experts when classifying blood samples from patients suffering from acute myeloid leukemia (AML). Their proof of concept study paves the way for an automated, standardized and on-hand sample analysis in the near future. The paper was published in Nature Machine Intelligence.

Every day, millions of single blood cells are evaluated for disease diagnostics in medical laboratories and clinics. Most of this repetitive task is still done manually by trained cytologists who inspect cells in stained blood smears and classify them into roughly 15 different categories. This process suffers from classification variability and requires the presence and expertise of a trained cytologist.


Deep learning algorithms of AI analyses samples in an automated and standardized way. Left: What human experts classify. Right: Pixels important for AI analysis.

©Helmholtz Zentrum München / Carsten Marr

To improve evaluation efficiency, a team of researchers at Helmholtz Zentrum München and the University Hospital, LMU Munich, trained a deep neuronal network with almost 20.000 single cell images to classify them.

The team lead Dr. Carsten Marr and medical doctoral student Dr. Christian Matek from the Institute of Computational Biology at Helmholtz Zentrum München as well as Prof. Dr. med Karsten Spiekermann and Simone Schwarz from the Department of Medicine III, University Hospital, LMU Munich, used images which were extracted from blood smears of 100 patients suffering from the aggressive blood disease AML and 100 controls.

The new AI-driven approach was then evaluated by comparing its performance with the accuracy of human experts. The result showed that the AI-driven solution is able to identify diagnostic blast cells at least as good as a trained cytologist expert.

Applied research through AI and Big Data

Deep learning algorithms for image processing require two things: first, an appropriate convolutional neural network architecture with hundreds of thousands of parameters; second, a sufficiently large amount of training data. So far, no large digitized dataset of blood smears has been available, although these samples are used pervasively in clinics.

The research group at Helmholtz Zentrum München now provided the first large data set of that type. Currently, Marr and his team are collaborating closely with the Department of Medicine III at the University Hospital of LMU Munich and one of the largest European Leukemia laboratories, the Munich Leukemia Laboratory (MLL), to digitalize hundreds of patient blood smears more.

“To bring our approach to clinics, digitization of patients’ blood samples has to become routine. Algorithms have to be trained with samples from different sources to cope with the inherent heterogeneity in sample preparation and staining,” says Marr.

“Together with our partners we could prove that deep learning algorithms show a similar performance as human cytologists. In a next step, we will evaluate how well other disease characteristics, such as genetic mutations or translocations, can be predicted with this new AI-driven method.”

This method showcases the applied power of AI for translational research. It is an extension of the pioneering work of Helmholtz Zentrum München on single cell classification in blood stem cells (Buggenthin et al., Nature Methods, 2017) which has been awarded with the Erwin Schroedinger Prize of the Helmholtz Association in 2018. The study was supported by the SFB 1243 of the German Research Foundation (DFG) and by a PhD scholarship of the German José Carreras Leukaemia Foundation to Dr. Christian Matek.

Wissenschaftliche Ansprechpartner:

Dr. Carsten Marr
Institute of Computational Biology
Helmholtz Zentrum München
Deutsches Forschungszentrum für Gesundheit und Umwelt
Ingolstädter Landstr. 1
85764 Neuherberg

Originalpublikation:

Matek, C. et al., 2019: Human-level recognition of blast cells in acute myeloid leukaemia with convolutional neural networks (https://www.nature.com/articles/s42256-019-0101-9). Nature Machine Intelligence, DOI: 10.1038/s42256-019-0101-9

Verena Schulz | Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt
Further information:
http://www.helmholtz-muenchen.de

Further reports about: AI Computational Biology Forschungszentrum blood cell leukemia neural single cell

More articles from Life Sciences:

nachricht New yeast species discovered in Braunschweig, Germany
13.12.2019 | Leibniz-Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH

nachricht Saliva test shows promise for earlier and easier detection of mouth and throat cancer
13.12.2019 | Elsevier

All articles from Life Sciences >>>

The most recent press releases about innovation >>>

Die letzten 5 Focus-News des innovations-reports im Überblick:

Im Focus: Virus multiplication in 3D

Vaccinia viruses serve as a vaccine against human smallpox and as the basis of new cancer therapies. Two studies now provide fascinating insights into their unusual propagation strategy at the atomic level.

For viruses to multiply, they usually need the support of the cells they infect. In many cases, only in their host’s nucleus can they find the machines,...

Im Focus: Cheers! Maxwell's electromagnetism extended to smaller scales

More than one hundred and fifty years have passed since the publication of James Clerk Maxwell's "A Dynamical Theory of the Electromagnetic Field" (1865). What would our lives be without this publication?

It is difficult to imagine, as this treatise revolutionized our fundamental understanding of electric fields, magnetic fields, and light. The twenty original...

Im Focus: Highly charged ion paves the way towards new physics

In a joint experimental and theoretical work performed at the Heidelberg Max Planck Institute for Nuclear Physics, an international team of physicists detected for the first time an orbital crossing in the highly charged ion Pr⁹⁺. Optical spectra were recorded employing an electron beam ion trap and analysed with the aid of atomic structure calculations. A proposed nHz-wide transition has been identified and its energy was determined with high precision. Theory predicts a very high sensitivity to new physics and extremely low susceptibility to external perturbations for this “clock line” making it a unique candidate for proposed precision studies.

Laser spectroscopy of neutral atoms and singly charged ions has reached astonishing precision by merit of a chain of technological advances during the past...

Im Focus: Ultrafast stimulated emission microscopy of single nanocrystals in Science

The ability to investigate the dynamics of single particle at the nano-scale and femtosecond level remained an unfathomed dream for years. It was not until the dawn of the 21st century that nanotechnology and femtoscience gradually merged together and the first ultrafast microscopy of individual quantum dots (QDs) and molecules was accomplished.

Ultrafast microscopy studies entirely rely on detecting nanoparticles or single molecules with luminescence techniques, which require efficient emitters to...

Im Focus: How to induce magnetism in graphene

Graphene, a two-dimensional structure made of carbon, is a material with excellent mechanical, electronic and optical properties. However, it did not seem suitable for magnetic applications. Together with international partners, Empa researchers have now succeeded in synthesizing a unique nanographene predicted in the 1970s, which conclusively demonstrates that carbon in very specific forms has magnetic properties that could permit future spintronic applications. The results have just been published in the renowned journal Nature Nanotechnology.

Depending on the shape and orientation of their edges, graphene nanostructures (also known as nanographenes) can have very different properties – for example,...

All Focus news of the innovation-report >>>

Anzeige

Anzeige

VideoLinks
Industry & Economy
Event News

The Future of Work

03.12.2019 | Event News

First International Conference on Agrophotovoltaics in August 2020

15.11.2019 | Event News

Laser Symposium on Electromobility in Aachen: trends for the mobility revolution

15.11.2019 | Event News

 
Latest News

Supporting structures of wind turbines contribute to wind farm blockage effect

13.12.2019 | Physics and Astronomy

Chinese team makes nanoscopy breakthrough

13.12.2019 | Physics and Astronomy

Tiny quantum sensors watch materials transform under pressure

13.12.2019 | Materials Sciences

VideoLinks
Science & Research
Overview of more VideoLinks >>>