Should standard concurrent chemoradiotherapy remain the preferred treatment for elderly patients with locoregionally advanced nasopharyngeal carcinoma? [0.03%]
Shuhan Zhao,Jieying Zhang,Yun Zhu et al.
Shuhan Zhao et al.
Background: Elderly patients are underrepresented in clinical studies supporting platinum-based concurrent chemoradiotherapy (CCRT) as the standard therapy (ST) for locoregionally advanced nasopharyngeal carcinoma (LA-NPC...
Preliminary results from a phase II trial of spatially fractionated radiotherapy combined with immunotherapy and anti-angiogenic therapy in patients with bulky solid tumors: early evidence of promising efficacy and favorable safety [0.03%]
Yuntao Zhou,Yanwei Li,Hui Zhu et al.
Yuntao Zhou et al.
Elective nodal irradiation of high-risk regions is superior to involved field radiotherapy for limited-stage small cell lung cancer: a propensity score-matched retrospective study [0.03%]
高危区域的选择性淋巴结照射优于广泛期小细胞肺癌的受累野放疗：倾向匹配队列分析
Zheng Zhang,Meng Yan,Jiakun Gao et al.
Zheng Zhang et al.
SHAP-based interpretable machine learning with longitudinal delta-radiomics across seven weeks of treatment for xerostomia prediction in head-and-neck cancer [0.03%]
基于SHAP的可解释机器学习与纵向变化影像组学参数预测头颈肿瘤放疗诱导口腔干燥症七年周疗效
Damilola Oluwafemi Samson,Mahayu Ismail,Mohd Ariff Mohamed Hanifa et al.
Damilola Oluwafemi Samson et al.
Quantifying intrafractional colon tumor motion on 1.5 T MR-linac cine-MRI and applying anisotropic residual-motion margins for SBRT [0.03%]
基于1.5T磁共振直线加速器上大肠肿瘤的动态运动分析以及立体定向放疗的各向异性余量研究
Guoqing Liu,Min Liu,Li Pan et al.
Guoqing Liu et al.
Purpose: To noninvasively quantify the intrafraction motion of unresectable locally advanced colon cancer (UNLACC) via 1.5 T magnetic resonance imaging and linear accelerator (MR-linac) cine-MRI and assess the preliminary...
A deep learning-driven automated treatment planning framework for cervical cancer patients treated with volumetric modulated arc therapy [0.03%]
基于深度学习的自动治疗计划框架用于接受容积旋转调强放疗的宫颈癌患者
Boda Ning,Xiuyan Liang,Zhenguo Cui et al.
Boda Ning et al.
Background and purpose: The rapid and efficient generation of high-quality, dose-consistency volumetric modulated arc therapy (VMAT) plans remains challenging in radiotherapy. This study proposes a deep learning (DL) end-...
Learning CT-to-electron-density mapping for radiotherapy treatment planning using neural networks [0.03%]
基于神经网络的放射治疗计划中的CT到电子密度映射学习
Shaohua Yan,Heling Zhu,Ying Zhou et al.
Shaohua Yan et al.
Investigation of cellular senescence in the mouse liver caused by low dose fractionated X-ray therapy [0.03%]
低剂量分次照射引起的小鼠肝脏细胞衰老的初步研究
Xin Lan,Lina Cai,Lingyu Zhang et al.
Xin Lan et al.
Machine learning approach to estimation of in vivo measured dose and treatment planning for total body irradiation [0.03%]
基于机器学习的大分割全身照射治疗在体剂量估计和计划研究
Sangmin Lee,Jung-In Kim,Seonghee Kang et al.
Sangmin Lee et al.
Dosimetric advantages and clinical feasibility of a novel lateral decubitus position for left breast cancer patients undergoing PORT [0.03%]
一种新型侧卧位在左侧乳腺癌患者术后放疗中的剂量学优势及临床可行性研究
Yingying Zhou,Jinfeng Xu,Yuan Deng et al.
Yingying Zhou et al.