AIMC Topic: Nasopharyngeal Neoplasms

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Computer-aided diagnosis and regional segmentation of nasopharyngeal carcinoma based on multi-modality medical images.

International journal of computer assisted radiology and surgery Mar 29, 2021
PURPOSE: Nasopharyngeal carcinoma (NPC) is a category of tumors with high incidence in head-and-neck (H&N) body region, and the diagnosis and treatment planning are usually conducted by radiologists manually, which is tedious, time-consuming and unre...
Humans Neural Networks, Computer Magnetic Resonance Imaging Nasopharyngeal Carcinoma Nasopharyngeal Neoplasms Tomography, X-Ray Computed Diagnosis, Computer-Assisted Algorithms
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Convolutional neural network in nasopharyngeal carcinoma: how good is automatic delineation for primary tumor on a non-contrast-enhanced fat-suppressed T2-weighted MRI?

Japanese journal of radiology Feb 5, 2021
PURPOSE: Convolutional neural networks (CNNs) show potential for delineating cancers on contrast-enhanced MRI (ce-MRI) but there are clinical scenarios in which administration of contrast is not desirable. We investigated performance of the CNN for d...
Retrospective Studies Male Nasopharynx Magnetic Resonance Imaging Image Interpretation, Computer-Assisted Nasopharyngeal Carcinoma Humans Middle Aged Nasopharyngeal Neoplasms Neural Networks, Computer
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DVH Prediction for VMAT in NPC with GRU-RNN: An Improved Method by Considering Biological Effects.

BioMed research international Jan 19, 2021
PURPOSE: A recurrent neural network (RNN) and its variants such as gated recurrent unit-based RNN (GRU-RNN) were found to be very suitable for dose-volume histogram (DVH) prediction in our previously published work. Using the dosimetric information g...
Retrospective Studies Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Humans Neural Networks, Computer Nasopharyngeal Neoplasms Radiotherapy, Intensity-Modulated Nasopharyngeal Carcinoma
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Continual improvement of nasopharyngeal carcinoma segmentation with less labeling effort.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB) Dec 1, 2020
PURPOSE: Convolutional neural networks (CNNs) offer a promising approach to automated segmentation. However, labeling contours on a large scale is laborious. Here we propose a method to improve segmentation continually with less labeling effort.
Longitudinal Studies Nasopharyngeal Carcinoma Nasopharyngeal Neoplasms Neural Networks, Computer Image Processing, Computer-Assisted Humans
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A deep learning model to predict dose-volume histograms of organs at risk in radiotherapy treatment plans.

Medical physics Oct 15, 2020
PURPOSE: To develop a deep learning-based model to predict achievable dose-volume histograms (DVHs) of organs at risk (OARs) for automation of inverse planning.
Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Nasopharyngeal Neoplasms Radiotherapy, Intensity-Modulated Humans Deep Learning Organs at Risk
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Verification of the machine delivery parameters of a treatment plan via deep learning.

Physics in medicine and biology Sep 30, 2020
We developed a generative adversarial network (GAN)-based deep learning approach to estimate the multileaf collimator (MLC) aperture and corresponding monitor units (MUs) from a given 3D dose distribution. The proposed design of the adversarial netwo...
Phantoms, Imaging Nasopharyngeal Neoplasms Lung Neoplasms Rectal Neoplasms Radiotherapy Dosage Humans Radiotherapy, Intensity-Modulated Reproducibility of Results Radiotherapy Planning, Computer-Assisted Deep Learning
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Editorial for "MRI-Based Deep Learning Model for Distant Metastasis-Free Survival in Locoregionally Advanced Nasopharyngeal Carcinoma".

Journal of magnetic resonance imaging : JMRI Sep 17, 2020
Humans Deep Learning Disease-Free Survival Chemoradiotherapy Magnetic Resonance Imaging Nasopharyngeal Carcinoma Nasopharyngeal Neoplasms
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MRI-Based Deep-Learning Model for Distant Metastasis-Free Survival in Locoregionally Advanced Nasopharyngeal Carcinoma.

Journal of magnetic resonance imaging : JMRI Aug 9, 2020
BACKGROUND: Distant metastasis is the primary cause of treatment failure in locoregionally advanced nasopharyngeal carcinoma (LANPC).
Chemoradiotherapy Nasopharyngeal Carcinoma Humans Nasopharyngeal Neoplasms Deep Learning Retrospective Studies Herpesvirus 4, Human Epstein-Barr Virus Infections Magnetic Resonance Imaging
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A knowledge-based intensity-modulated radiation therapy treatment planning technique for locally advanced nasopharyngeal carcinoma radiotherapy.

Radiation oncology (London, England) Aug 3, 2020
BACKGROUND: To investigate the feasibility of a knowledge-based automated intensity-modulated radiation therapy (IMRT) planning technique for locally advanced nasopharyngeal carcinoma (NPC) radiotherapy.
Radiotherapy, Intensity-Modulated Nasopharyngeal Carcinoma Nasopharyngeal Neoplasms Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Retrospective Studies Humans Knowledge Bases Machine Learning Organs at Risk
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Deep learning for risk prediction in patients with nasopharyngeal carcinoma using multi-parametric MRIs.

Computer methods and programs in biomedicine Aug 2, 2020
BACKGROUND: Magnetic resonance images (MRI) is the main diagnostic tool for risk stratification and treatment decision in nasopharyngeal carcinoma (NPC). However, the holistic feature information of multi-parametric MRIs has not been fully exploited ...
Nasopharyngeal Neoplasms Deep Learning Humans Magnetic Resonance Imaging Nasopharyngeal Carcinoma Retrospective Studies
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