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Review
. 2023 Jul:9:e2200431.
doi: 10.1200/GO.22.00431.

Addressing the Global Expertise Gap in Radiation Oncology: The Radiation Planning Assistant

Laurence Court  1 , Ajay Aggarwal  2 , Hester Burger  3 , Carlos Cardenas  4 , Christine Chung  1 , Raphael Douglas  1 , Monique du Toit  5 , David Jaffray  1 , Anuja Jhingran  1 , Michael Mejia  6 , Raymond Mumme  1 , Sikudhani Muya  7 , Komeela Naidoo  5 , Jerry Ndumbalo  7 , Kelly Nealon  1 , Tucker Netherton  1 , Callistus Nguyen  1 , Niki Olanrewaju  1 , Jeannette Parkes  3 , Willie Shaw  8 , Christoph Trauernicht  5 , Melody Xu  9 , Jinzhong Yang  1 , Lifei Zhang  1 , Hannah Simonds  10 , Beth M Beadle  11
Affiliations
Review

Addressing the Global Expertise Gap in Radiation Oncology: The Radiation Planning Assistant

Laurence Court et al. JCO Glob Oncol. 2023 Jul.

Abstract

Purpose: Automation, including the use of artificial intelligence, has been identified as a possible opportunity to help reduce the gap in access and quality for radiotherapy and other aspects of cancer care. The Radiation Planning Assistant (RPA) project was conceived in 2015 (and funded in 2016) to use automated contouring and treatment planning algorithms to support the efforts of oncologists in low- and middle-income countries, allowing them to scale their efforts and treat more patients safely and efficiently (to increase access).

Design: In this review, we discuss the development of the RPA, with a particular focus on clinical acceptability and safety/risk across jurisdictions as these are important indicators for the successful future deployment of the RPA to increase radiotherapy availability and ameliorate global disparities in access to radiation oncology.

Results: RPA tools will be offered through a webpage, where users can upload computed tomography data sets and download automatically generated contours and treatment plans. All interfaces have been designed to maximize ease of use and minimize risk. The current version of the RPA includes automated contouring and planning for head and neck cancer, cervical cancer, breast cancer, and metastases to the brain.

Conclusion: The RPA has been designed to bring high-quality treatment planning to more patients across the world, and it may encourage greater investment in treatment devices and other aspects of cancer treatment.

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Conflict of interest statement

The following represents disclosure information provided by authors of this manuscript. All relationships are considered compensated unless otherwise noted. Relationships are self-held unless noted. I = Immediate Family Member, Inst = My Institution. Relationships may not relate to the subject matter of this manuscript. For more information about ASCO's conflict of interest policy, please refer to www.asco.org/rwc or ascopubs.org/go/authors/author-center.

Open Payments is a public database containing information reported by companies about payments made to US-licensed physicians (Open Payments).

Figures

FIG 1
FIG 1
Workflow for creating radiation therapy treatment plans, showing tasks performed by the clinical team (left side) and tasks that are automatically performed by the RPA (right side). User tasks marked with a are performed in the users own treatment planning system. The review and edit contours step is only performed for complex planning (ie, VMAT). The RPA preprocessing step includes automatic detection of the marked isocenter (described in the CT upload section of this paper). CT, computed tomography; RPA, radiation planning assistant; VMAT, volume-modulated arc therapy.
FIG 2
FIG 2
Screenshot of the service request user interface. GYN, gynecology; MRN, medical record number.
FIG 3
FIG 3
Screenshot of the treatment-specific questions for VMAT planning for head and neck cancer. Coverage selections are automatically populated after selection of the primary site and lymph node involvement, although the user can change these and must confirm their selections. CTV, clinical target volume; VMAT, volume-modulated arc therapy.
FIG 4
FIG 4
Screenshot of the user interface for CT approval. CT, computed tomography.
See this image and copyright information in PMC

References

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