Automated field-in-field whole brain radiotherapy planning

Article Radiology, Nuclear Medicine & Medical Imaging

Customizable landmark-based field aperture design for automated whole-brain radiotherapy treatment planning

Yao Xiao et al.

Summary: This study developed an automated pipeline for whole-brain radiotherapy treatment planning using deep learning-based auto-contouring and customizable landmark-based field aperture design. The generated field shapes and dose distributions were comparable to the original clinical plans, as demonstrated by both quantitative and qualitative evaluations.

JOURNAL OF APPLIED CLINICAL MEDICAL PHYSICS (2023)

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Article Radiology, Nuclear Medicine & Medical Imaging

Feasibility of automated planning for whole-brain radiation therapy using deep learning

Jesang Yu et al.

Summary: The study developed an automated planning for whole-brain radiation therapy using a U-net-based deep-learning model to predict the multileaf collimator shape, bypassing contouring processes. The deep-learning technique showed consistent results in training and validation with good dose coverage for target volume.

JOURNAL OF APPLIED CLINICAL MEDICAL PHYSICS (2021)

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Article Oncology

Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries

Hyuna Sung et al.

Summary: The global cancer burden in 2020 saw an estimated 19.3 million new cancer cases and almost 10.0 million cancer deaths. Female breast cancer surpassed lung cancer as the most commonly diagnosed cancer, while lung cancer remained the leading cause of cancer death. These trends are expected to rise in 2040, with transitioning countries experiencing a larger increase compared to transitioned countries due to demographic changes and risk factors associated with globalization and a growing economy. Efforts to improve cancer prevention measures and provision of cancer care in transitioning countries will be crucial for global cancer control.

CA-A CANCER JOURNAL FOR CLINICIANS (2021)

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Article Radiology, Nuclear Medicine & Medical Imaging

Clinical implementation of automated treatment planning for whole-brain radiotherapy

Eun Young Han et al.

Summary: This study developed and clinically deployed an automated, deep learning-based approach for treatment planning in whole-brain radiotherapy. Results demonstrated that the predicted fields were consistent with clinically used fields, and the predicted plans were dosimetrically comparable.

JOURNAL OF APPLIED CLINICAL MEDICAL PHYSICS (2021)

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Article Radiology, Nuclear Medicine & Medical Imaging