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Convolutional neural networks to predict brain tumor grades and Alzheimer's disease with MR spectroscopic imaging data.

التفاصيل البيبلوغرافية
العنوان: Convolutional neural networks to predict brain tumor grades and Alzheimer's disease with MR spectroscopic imaging data.
المؤلفون: Jacopo Acquarelli, Twan van Laarhoven, Geert J Postma, Jeroen J Jansen, Anne Rijpma, Sjaak van Asten, Arend Heerschap, Lutgarde M C Buydens, Elena Marchiori
المصدر: PLoS ONE, Vol 17, Iss 8, p e0268881 (2022)
بيانات النشر: Public Library of Science (PLoS), 2022.
سنة النشر: 2022
المجموعة: LCC:Medicine
LCC:Science
مصطلحات موضوعية: Medicine, Science
الوصف: PurposeTo evaluate the value of convolutional neural network (CNN) in the diagnosis of human brain tumor or Alzheimer's disease by MR spectroscopic imaging (MRSI) and to compare its Matthews correlation coefficient (MCC) score against that of other machine learning methods and previous evaluation of the same data. We address two challenges: 1) limited number of cases in MRSI datasets and 2) interpretability of results in the form of relevant spectral regions.MethodsA shallow CNN with only one hidden layer and an ad-hoc loss function was constructed involving two branches for processing spectral and image features of a brain voxel respectively. Each branch consists of a single convolutional hidden layer. The output of the two convolutional layers is merged and fed to a classification layer that outputs class predictions for the given brain voxel.ResultsOur CNN method separated glioma grades 3 and 4 and identified Alzheimer's disease patients using MRSI and complementary MRI data with high MCC score (Area Under the Curve were 0.87 and 0.91 respectively). The results demonstrated superior effectiveness over other popular methods as Partial Least Squares or Support Vector Machines. Also, our method automatically identified the spectral regions most important in the diagnosis process and we show that these are in good agreement with existing biomarkers from the literature.ConclusionShallow CNNs models integrating image and spectral features improved quantitative and exploration and diagnosis of brain diseases for research and clinical purposes. Software is available at https://bitbucket.org/TeslaH2O/cnn_mrsi.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 1932-6203
Relation: https://doaj.org/toc/1932-6203
DOI: 10.1371/journal.pone.0268881
URL الوصول: https://doaj.org/article/670732cba2a14820b818ac418a082083
رقم الأكسشن: edsdoj.670732cba2a14820b818ac418a082083
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:19326203
DOI:10.1371/journal.pone.0268881