Evidence map›Paper›PMID 42111618›Full record

ArticlePhysics and imaging in radiation oncology2026

Quality assurance incorporating artificial intelligence-generated reference contours in a phase II radiotherapy trial.

Wonhyeong Lee, Yeon-Joo Kim, Jin Hee Kim, Sung-Ja Ahn, Jong Hoon Lee, Younghee Park, Jin Hwa Choi, Jin-Ho Song, Yoonsun Chung

Abstract read
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In one paragraph

Article in Physics and imaging in radiation oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Wonhyeong LeeDepartment of Radiation Oncology, National Cancer Center, Goyang, the Republic of Korea.
Yeon-Joo KimDepartment of Radiation Oncology, National Cancer Center, Goyang, the Republic of Korea.
Jin Hee KimDepartment of Radiation Oncology, Keimyung University Dongsan Hospital, Daegu, the Republic of Korea.
Sung-Ja AhnDepartment of Radiation Oncology, Chonnam National University Medical School, Gwangju, the Republic of Korea.
Jong Hoon LeeDepartment of Radiation Oncology, St. Vincent's Hospital, The Catholic University of Korea College of Medicine, Seoul, the Republic of Korea.
Younghee ParkDepartment of Radiation Oncology, Ewha Woman's University College of Medicine, Seoul, the Republic of Korea.
Jin Hwa ChoiDepartment of Radiation Oncology, Chung-Ang University College of Medicine, Seoul, the Republic of Korea.
Jin-Ho SongDepartment of Radiation Oncology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, the Republic of Korea.
Yoonsun ChungDepartment of Nuclear Engineering, Hanyang University, Seoul, the Republic of Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and purpose: A dummy run quality assurance was conducted for a prospective phase II trial of tailored radiotherapy (RT) according to the response after neoadjuvant chemotherapy (NAC) followed by surgery in locally advanced breast cancer (RTaNAC). Since inter-institutional variations in dose distributions can impact clinical outcomes, this dummy run aimed to develop an RT plan protocol to minimize these variations. Material and methods: This study involved computed tomography images from three clinical scenarios: RT with no lymph node (LN) boost (Scenario 1), LN boost up to 60 Gy Results: Inter-institutional variation observed in Step 1 improved in Step 2 for breast and regional nodal areas. Specifically for Scenario 1, dose coverage for the nodal clinical target volumes of the axillary level I LN improved from 57.5% to 97.5% (p-value = 0.075), and that of the supraclavicular LN improved from 75.6% to 88.8% (p-value = 0.046). Conclusion: Variations in dose/volume metrics among institutions were mitigated by AI auto-contoured structures and LN boost target volume information. Through this dummy run, the participating institutions reached a consensus on an RT plan protocol to support multi-institutional expansion of RTaNAC.

Indexed as

Breast cancerDummy runMulti-institutional studyNeoadjuvant chemotherapyRegional nodal irradiation

Identifiers

PMID42111618
PMCPMC13150357

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.