Artificial intelligence in radiation oncology

E Huynh, A Hosny, C Guthier, DS Bitterman… - Nature Reviews …, 2020 - nature.com
Artificial intelligence (AI) has the potential to fundamentally alter the way medicine is
practised. AI platforms excel in recognizing complex patterns in medical data and provide a …

Spatial descriptions of radiotherapy dose: normal tissue complication models and statistical associations

MA Ebert, S Gulliford, O Acosta… - Physics in Medicine …, 2021 - iopscience.iop.org
For decades, dose-volume information for segmented anatomy has provided the essential
data for correlating radiotherapy dosimetry with treatment-induced complications. Dose …

[HTML][HTML] Clinical evaluation of deep learning and atlas-based auto-contouring of bladder and rectum for prostate radiation therapy

WJ Zabel, JL Conway, A Gladwish, J Skliarenko… - Practical Radiation …, 2021 - Elsevier
Purpose Auto-contouring may reduce workload, interobserver variation, and time associated
with manual contouring of organs at risk. Manual contouring remains the standard due in …

NCCN Guidelines® insights: Hodgkin lymphoma, version 2.2022: Featured updates to the NCCN Guidelines

RT Hoppe, RH Advani, WZ Ai, RF Ambinder… - Journal of the National …, 2022 - jnccn.org
Hodgkin lymphoma (HL) is an uncommon malignancy of B-cell origin. Classical HL (cHL)
and nodular lymphocyte–predominant HL are the 2 main types of HL. The cure rates for HL …

[HTML][HTML] Organ at risk delineation for radiation therapy clinical trials: Global Harmonization Group consensus guidelines

R Mir, SM Kelly, Y **ao, A Moore, CH Clark… - Radiotherapy and …, 2020 - Elsevier
Abstract Background and purpose The Global Quality Assurance of Radiation Therapy
Clinical Trials Harmonization Group (GHG) is a collaborative group of Radiation Therapy …

Evaluation of deep learning-based autosegmentation in breast cancer radiotherapy

HK Byun, JS Chang, MS Choi, J Chun, J Jung… - Radiation …, 2021 - Springer
Purpose To study the performance of a proposed deep learning-based autocontouring
system in delineating organs at risk (OARs) in breast radiotherapy with a group of experts …

General and custom deep learning autosegmentation models for organs in head and neck, abdomen, and male pelvis

A Amjad, J Xu, D Thill, C Lawton, W Hall… - Medical …, 2022 - Wiley Online Library
Purpose To reduce workload and inconsistencies in organ segmentation for radiation
treatment planning, we developed and evaluated general and custom autosegmentation …

Medical Physics Practice Guideline (MPPG) 11. a: Plan and chart review in external beam radiotherapy and brachytherapy

P **a, BJ Sintay, VC Colussi, C Chuang… - Journal of applied …, 2021 - Wiley Online Library
A therapeutic medical physicist is responsible for reviewing radiation therapy treatment
plans and patient charts, including initial treatment plans and new chart review, on treatment …

NRG oncology assessment of artificial intelligence deep learning–based auto-segmentation for radiation therapy: current developments, clinical considerations, and …

Y Rong, Q Chen, Y Fu, X Yang, HA Al-Hallaq… - International Journal of …, 2024 - Elsevier
Deep learning neural networks (DLNN) in Artificial intelligence (AI) have been extensively
explored for automatic segmentation in radiotherapy (RT). In contrast to traditional model …

A systematic review of contouring guidelines in radiation oncology: Analysis of frequency, methodology, and delivery of consensus recommendations

D Lin, K Lapen, MV Sherer, J Kantor, Z Zhang… - International Journal of …, 2020 - Elsevier
Purpose Clinical trials have described variation in radiation therapy plan quality, of which
contour delineation is a key component, and linked this to inferior patient outcomes. In …