Application of Artificial Intelligence in Radiotherapy of Nasopharyngeal Carcinoma with Magnetic Resonance Imaging

Abstract

The value of automatic organ-at-risk outlining software for radiotherapy is based on artificial intelligence technology in clinical applications. The accuracy of automatic segmentation of organs at risk (OARs) in radiotherapy for nasopharyngeal carcinoma was investigated. In the automatic segmentation model which is proposed in this paper, after CT scans and manual segmentation by physicians, CT images of 147 nasopharyngeal cancer patients and their corresponding outlined OARs structures were selected and grouped into a training set (115 cases), a validation set (12 cases), and a test set (20 cases) by complete randomization. Adaptive histogram equalization is used to preprocess the CT images. End-to-end training is utilized to improve modeling efficiency and an improved network based on 3D Unet (AUnet) is implemented to introduce organ size as prior knowledge into the convolutional kernel size design to enable the network to adaptively extract features from organs of different sizes, thus improving the performance of the model. The DSC (Dice Similarity Coefficient) coefficients and Hausdorff (HD) distances of automatic and manual segmentation are compared to verify the effectiveness of the AUnet network. The mean DSC and HD of the test set were 0.86 ± 0.02 and 4.0 ± 2.0 mm, respectively. Except for optic nerve and optic cross, there was no statistical difference between AUnet and manual segmentation results ( P > 0.05). With the introduction of the adaptive mechanism, AUnet can achieve automatic segmentation of the endangered organs of nasopharyngeal carcinoma based on CT images more accurately, which can substantially improve the efficiency and consistency of segmentation of doctors in clinical applications.

Minimally Invasive Surgery for Early-Stage Nasopharyngeal Carcinoma

“…Endoscopic surgery is no longer only used to treat inflammatory diseases of the nasal cavity and sinus, but also gradually applied to the complex nasopharyngeal-skull base anatomy. 28 In addition, artificial intelligence-assisted technology 26,29 and 3-dimensional navigation technology 30,31 also guide and help surgeons to perform delicate and accurate dissection. All these factors provide favorable conditions for endoscopic surgery in the treatment of earlystage NPC.…”

Retracted: Application of Artificial Intelligence in Radiotherapy of Nasopharyngeal Carcinoma with Magnetic Resonance Imaging

“…This article has been retracted by Hindawi, as publisher, following an investigation undertaken by the publisher [ 1 ]. This investigation has uncovered evidence of systematic manipulation of the publication and peer-review process.…”