AIMC Topic: Nasopharyngeal Neoplasms

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A deep learning MR-based radiomic nomogram may predict survival for nasopharyngeal carcinoma patients with stage T3N1M0.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology Jul 4, 2020
PURPOSE: To estimate the prognostic value of deep learning (DL) magnetic resonance (MR)-based radiomics for stage T3N1M0 nasopharyngeal carcinoma (NPC) patients receiving induction chemotherapy (ICT) prior to concurrent chemoradiotherapy (CCRT).
Nomograms Magnetic Resonance Spectroscopy Nasopharyngeal Carcinoma Nasopharyngeal Neoplasms Humans Prognosis Deep Learning
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Automatic T Staging Using Weakly Supervised Deep Learning for Nasopharyngeal Carcinoma on MR Images.

Journal of magnetic resonance imaging : JMRI Jun 24, 2020
BACKGROUND: Recent studies have shown that deep learning can help tumor staging automatically. However, automatic nasopharyngeal carcinoma (NPC) staging is difficult due to the lack of large and slice-level annotated datasets.
Retrospective Studies Deep Learning Magnetic Resonance Imaging Neoplasm Staging Humans Nasopharyngeal Carcinoma Nasopharyngeal Neoplasms
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Machine-learning based MRI radiomics models for early detection of radiation-induced brain injury in nasopharyngeal carcinoma.

BMC cancer Jun 1, 2020
BACKGROUND: Early radiation-induced temporal lobe injury (RTLI) diagnosis in nasopharyngeal carcinoma (NPC) is clinically challenging, and prediction models of RTLI are lacking. Hence, we aimed to develop radiomic models for early detection of RTLI.
Image Interpretation, Computer-Assisted Adult Radiation Injuries Male Nasopharyngeal Carcinoma ROC Curve Middle Aged Machine Learning Nasopharyngeal Neoplasms Predictive Value of Tests Humans Longitudinal Studies Algorithms Temporal Lobe Aftercare Magnetic Resonance Imaging Retrospective Studies Models, Biological Brain Injuries Female
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Computer-Aided Pathologic Diagnosis of Nasopharyngeal Carcinoma Based on Deep Learning.

The American journal of pathology Apr 29, 2020
The pathologic diagnosis of nasopharyngeal carcinoma (NPC) by different pathologists is often inefficient and inconsistent. We have therefore introduced a deep learning algorithm into this process and compared the performance of the model with that o...
Nasopharyngeal Neoplasms Neural Networks, Computer Databases, Factual Reproducibility of Results Sensitivity and Specificity Diagnosis, Computer-Assisted Deep Learning Nasopharyngeal Carcinoma Humans
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Multi-sequence MR image-based synthetic CT generation using a generative adversarial network for head and neck MRI-only radiotherapy.

Medical physics Feb 26, 2020
PURPOSE: The purpose of this study is to investigate the effect of different magnetic resonance (MR) sequences on the accuracy of deep learning-based synthetic computed tomography (sCT) generation in the complex head and neck region.
Deep Learning Image Processing, Computer-Assisted Magnetic Resonance Imaging Radiotherapy Dosage Humans Tomography, X-Ray Computed Nasopharyngeal Neoplasms Radiotherapy, Image-Guided
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Machine Learning Analysis of Image Data Based on Detailed MR Image Reports for Nasopharyngeal Carcinoma Prognosis.

BioMed research international Feb 21, 2020
We aimed to assess the use of automatic machine learning (AutoML) algorithm based on magnetic resonance (MR) image data to assign prediction scores to patients with nasopharyngeal carcinoma (NPC). We also aimed to develop a 4-group classification sys...
Nasopharyngeal Carcinoma Nasopharyngeal Neoplasms Magnetic Resonance Imaging Nasopharynx Neoplasm Staging Image Interpretation, Computer-Assisted Humans Female Machine Learning Adult Prognosis Male Retrospective Studies Middle Aged
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Deep learning pathological microscopic features in endemic nasopharyngeal cancer: Prognostic value and protentional role for individual induction chemotherapy.

Cancer medicine Dec 20, 2019
BACKGROUND: To explore the prognostic value and the role for treatment decision of pathological microscopic features in patients with nasopharyngeal carcinoma (NPC) using the method of deep learning.
China Image Processing, Computer-Assisted Antineoplastic Combined Chemotherapy Protocols Neoplasm Staging Cisplatin Fluorouracil Progression-Free Survival Male Middle Aged Risk Assessment Deep Learning Humans Nasopharyngeal Neoplasms Retrospective Studies Prognosis Female Endemic Diseases Radiotherapy, Intensity-Modulated Adult Nasopharynx Kaplan-Meier Estimate Induction Chemotherapy Chemoradiotherapy
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Cervical-transoral robotic nasopharyngectomy: A preclinical study.

Head & neck Nov 21, 2019
BACKGROUND: We performed a preclinical study to assess the feasibility of the cervical-transoral robotic pharyngectomy procedure in surgery for nasopharyngeal cancer, where deep margins and vascular safety are key issues.
Humans Nasopharyngeal Neoplasms Robotics Pharyngectomy Robotic Surgical Procedures Nasopharyngeal Carcinoma
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Use of artificial neural network for pretreatment verification of intensity modulation radiation therapy fields.

The British journal of radiology Jul 24, 2019
OBJECTIVE: The accuracy of dose delivery for intensity modulated radiotherapy (IMRT) treatments should be determined by an accurate quality assurance procedure. In this work, we used artificial neural networks (ANNs) as an application for the pre-tre...
Radiotherapy, Intensity-Modulated Male Nasopharyngeal Neoplasms Humans Prostatic Neoplasms Particle Accelerators Neural Networks, Computer Quality Control Machine Learning Radiotherapy Dosage
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A preliminary study of using a deep convolution neural network to generate synthesized CT images based on CBCT for adaptive radiotherapy of nasopharyngeal carcinoma.

Physics in medicine and biology Jul 16, 2019
This study aims to utilize a deep convolutional neural network (DCNN) for synthesized CT image generation based on cone-beam CT (CBCT) and to apply the images to dose calculations for nasopharyngeal carcinoma (NPC). An encoder-decoder 2D U-Net neural...
Radiotherapy, Intensity-Modulated Nasopharyngeal Neoplasms Spiral Cone-Beam Computed Tomography Image Processing, Computer-Assisted Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Humans Neural Networks, Computer Algorithms Cone-Beam Computed Tomography
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