Výsledky vyhledávání - "YU, NATHAN Y."

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Robust Optimization for Spot Scanning Proton Therapy based on Dose-Linear Energy Transfer (LET) Volume Constraints

Autor: Chen, Jingyuan, Yang, Yunze, Feng, Hongying, Zhang, Lian, Vargas, Carlos E., Yu, Nathan Y., Rwigema, Jean-Claude M., Keole, Sameer R., Vora, Sujay A., Shen, Jiajian, Liu, Wei

Purpose: Historically, spot scanning proton therapy (SSPT) treatment planning utilizes dose volume constraints and linear-energy-transfer (LET) volume constraints separately to balance tumor control and organs-at-risk (OARs) protection. We propose a

Externí odkaz: http://arxiv.org/abs/2405.03916

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Proton Pencil-Beam Scanning Stereotactic Body Radiation Therapy and Hypofractionated Radiation Therapy for Thoracic Malignancies: Patterns of Practice Survey and Recommendations for Future Development from NRG Oncology and PTCOG

Autor: Liu, Wei, Feng, Hongying, Taylor, Paige A., Kang, Minglei, Shen, Jiajian, Saini, Jatinder, Zhou, Jun, Giap, Huan B., Yu, Nathan Y., Sio, Terence S., Mohindra, Pranshu, Chang, Joe Y., Bradley, Jeffrey D., Xiao, Ying, Simone II, Charles B., Lin, Liyong

Stereotactic body radiation therapy (SBRT) and hypofractionation using pencil-beam scanning (PBS) proton therapy (PBSPT) is an attractive option for thoracic malignancies. Combining the advantages of target coverage conformity and critical organ spar

Externí odkaz: http://arxiv.org/abs/2402.00489

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Artificial Intelligence-Facilitated Online Adaptive Proton Therapy Using Pencil Beam Scanning Proton Therapy

Autor: Feng, Hongying, Shan, Jie, Vargas, Carlos E., Keole, Sameer R., Rwigema, Jean-Claude M., Yu, Nathan Y., Ding, Yuzhen, Zhang, Lian, Schild, Steven E., Wong, William W., Vora, Sujay A., Shen, JiaJian, Liu, Wei

We propose an oAPT workflow that incorporates all these functionalities and validate its clinical implementation feasibility with prostate patients. AI-based auto-segmentation tool AccuContourTM (Manteia, Xiamen, China) was seamlessly integrated into

Externí odkaz: http://arxiv.org/abs/2311.00448

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Beam mask and sliding window-facilitated deep learning-based accurate and efficient dose prediction for pencil beam scanning proton therapy

Autor: Zhang, Lian, Holmes, Jason M., Liu, Zhengliang, Vora, Sujay A., Sio, Terence T., Vargas, Carlos E., Yu, Nathan Y., Keole, Sameer R., Schild, Steven E., Bues, Martin, Li, Sheng, Liu, Tianming, Shen, Jiajian, Wong, William W., Liu, Wei

Purpose: To develop a DL-based PBSPT dose prediction workflow with high accuracy and balanced complexity to support on-line adaptive proton therapy clinical decision and subsequent replanning. Methods: PBSPT plans of 103 prostate cancer patients and

Externí odkaz: http://arxiv.org/abs/2305.18572

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Deep-Learning-based Fast and Accurate 3D CT Deformable Image Registration in Lung Cancer

Autor: Ding, Yuzhen, Feng, Hongying, Yang, Yunze, Holmes, Jason, Liu, Zhengliang, Liu, David, Wong, William W., Yu, Nathan Y., Sio, Terence T., Schild, Steven E., Li, Baoxin, Liu, Wei

Purpose: In some proton therapy facilities, patient alignment relies on two 2D orthogonal kV images, taken at fixed, oblique angles, as no 3D on-the-bed imaging is available. The visibility of the tumor in kV images is limited since the patient's 3D

Externí odkaz: http://arxiv.org/abs/2304.11135

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