AIMC Topic: Lymphoma, Large B-Cell, Diffuse
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Harnessing Deep Learning for Accurate Pathological Assessment of Brain Tumor Cell Types.
Journal of imaging informatics in medicine
Aug 16, 2024
Primary diffuse central nervous system large B-cell lymphoma (CNS-pDLBCL) and high-grade glioma (HGG) often present similarly, clinically and on imaging, making differentiation challenging. This similarity can complicate pathologists' diagnostic effo...
Detection of disease-specific signatures in B cell repertoires of lymphomas using machine learning.
PLoS computational biology
Jul 2, 2024
The classification of B cell lymphomas-mainly based on light microscopy evaluation by a pathologist-requires many years of training. Since the B cell receptor (BCR) of the lymphoma clonotype and the microenvironmental immune architecture are importan...
Prognosis Prediction of Diffuse Large B-Cell Lymphoma in F-FDG PET Images Based on Multi-Deep-Learning Models.
IEEE journal of biomedical and health informatics
Jul 2, 2024
Diffuse large B-cell lymphoma (DLBCL), a cancer of B cells, has been one of the most challenging and complicated diseases because of its considerable variation in clinical behavior, response to therapy, and prognosis. Radiomic features from medical i...
Artificial intelligence-based prognostic model accurately predicts the survival of patients with diffuse large B-cell lymphomas: analysis of a large cohort in China.
BMC cancer
May 22, 2024
BACKGROUND: Diffuse large B-cell lymphomas (DLBCLs) display high molecular heterogeneity, but the International Prognostic Index (IPI) considers only clinical indicators and has not been updated to include molecular data. Therefore, we developed a wi...
Semi-supervised learning towards automated segmentation of PET images with limited annotations: application to lymphoma patients.
Physical and engineering sciences in medicine
Mar 21, 2024
Manual segmentation poses a time-consuming challenge for disease quantification, therapy evaluation, treatment planning, and outcome prediction. Convolutional neural networks (CNNs) hold promise in accurately identifying tumor locations and boundarie...
Translating prognostic quantification of c-MYC and BCL2 from tissue microarrays to whole slide images in diffuse large B-cell lymphoma using deep learning.
Diagnostic pathology
Jan 19, 2024
BACKGROUND: c-MYC and BCL2 positivity are important prognostic factors for diffuse large B-cell lymphoma. However, manual quantification is subject to significant intra- and inter-observer variability. We developed an automated method for quantificat...
SurvIAE: Survival prediction with Interpretable Autoencoders from Diffuse Large B-Cells Lymphoma gene expression data.
Computer methods and programs in biomedicine
Dec 2, 2023
BACKGROUND: In Diffuse Large B-Cell Lymphoma (DLBCL), several methodologies are emerging to derive novel biomarkers to be incorporated in the risk assessment. We realized a pipeline that relies on autoencoders (AE) and Explainable Artificial Intellig...
Broadening the horizon: potential applications of CAR-T cells beyond current indications.
Frontiers in immunology
Nov 27, 2023
Engineering immune cells to treat hematological malignancies has been a major focus of research since the first resounding successes of CAR-T-cell therapies in B-ALL. Several diseases can now be treated in highly therapy-refractory or relapsed condit...
Robust deep learning-based PET prognostic imaging biomarker for DLBCL patients: a multicenter study.
European journal of nuclear medicine and molecular imaging
Aug 22, 2023
OBJECTIVE: To develop and independently externally validate robust prognostic imaging biomarkers distilled from PET images using deep learning techniques for precise survival prediction in patients with diffuse large B cell lymphoma (DLBCL).
Prediction of lymphoma response to CAR T cells by deep learning-based image analysis.
PloS one
Jul 21, 2023
Clinical prognostic scoring systems have limited utility for predicting treatment outcomes in lymphomas. We therefore tested the feasibility of a deep-learning (DL)-based image analysis methodology on pre-treatment diagnostic computed tomography (dCT...
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