Dandan Zheng

University of Rochester
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Articles (11)

Year:

2025

Year:

2025

Year:

2025

Radiotherapy, a crucial technique in cancer therapy, has traditionally relied on the premise of largely unchanging patient anatomy during the treatment course and encompassing uncertainties by target margins. This review introduces adaptive radiotherapy (ART), a notable innovation that addresses anatomy changes and optimizes the therapeutic ratio. ART utilizes advanced imaging techniques such as CT, MRI, and PET to modify the treatment plan based on observed anatomical changes and even biological changes during the course of treatment. The narrative review provides a comprehensive guide on ART for healthcare professionals and trainees in radiation oncology and anyone else interested in the topic. The incorporation of artificial intelligence in ART has played a crucial role in improving effectiveness, particularly in contour segmentation, treatment planning, and quality assurance. This has expedited the process to render online ART feasible, lowered the burden for radiation oncology practitioners, and enhanced the precision of dynamically personalized treatment. Current technical and clinical progress on ART is discussed in this review, highlighting the ongoing development of imaging technologies and AI and emphasizing their contribution to enhancing the applicability and effectiveness of ART.

Year:

2024

Year:

2024

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2023

Year:

2023

Year:

2022

Year:

2021

Year:

2021

Year:

2020

Collaborators (7)

FIONA LI

Assistant Professor - Medical Physicist

University of Rochester

UNITED STATES
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Su-Min Zhou

Professor/Director of Physics

University of Nebraska Medical Center

UNITED STATES
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Hongfeng Yu

University of Nebraska - Lincoln

UNITED STATES
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Michael J. Baine

University of Nebraska Medical Center

UNITED STATES
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Matthew Webster

University of Rochester

UNITED STATES
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Chi Zhang

University of Nebraska - Lincoln

UNITED STATES
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Jihyung Yoon

University of Rochester Medical Center

UNITED STATES
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