Evidence map›Paper›PMID 41457830›Full record

ArticleJournal of applied clinical medical physics2026

Dynamic blood dose estimates in radiotherapy and correlations with adverse clinical outcomes in brain, head-and-neck, and lung cancer patients.

Sebastian Tattenberg, Jungwook Shin, Cornelia Hoehr, Xuanfeng Ding, Rohan L Deraniyagala, Wonmo Sung

Abstract read
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Article in Journal of applied clinical medical physics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Sebastian TattenbergSchool of Natural Sciences, Laurentian University, Sudbury, Ontario, Canada.
Jungwook ShinDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, Maryland, USA.
Cornelia HoehrLife Sciences Division, TRIUMF, Vancouver, British Columbia, Canada.
Xuanfeng DingDepartment of Radiation Oncology, Beaumont Health, Royal Oak, Michigan, USA.
Rohan L DeraniyagalaDepartment of Radiation Oncology, Beaumont Health, Royal Oak, Michigan, USA.
Wonmo SungDepartment of Biomedical Engineering, College of Medicine, The Catholic University of Korea, Seoul, South Korea.ORCID https://orcid.org/0000-0002-0172-0646

Funding

Develop a novel multi-approach dynamic Spot Scanning Proton Arc optimization frameworkR01CA301448 · NCI · WILLIAM BEAUMONT HOSPITAL RESEARCH INST · PI Xuanfeng Ding · 2025 to 2026
$2.2M
National Institutes of Health (NIH) R01CA301448National Research Foundation of Korea 2021R1C1C1005930
6 · The paper itself

Abstract

backgroundIn cancer radiotherapy, radiation-induced lymphopenia (RIL) has been reported to be correlated with adverse clinical outcomes such as reduced locoregional control (LRC), distant-metastasis-free survival (DMFS), and overall survival (OS) in various treatment sites. Frameworks to simulate the radiation dose to circulating blood have been developed in response, and simulated blood dose values have been reported to be correlated with severe RIL and/or adverse clinical outcomes. However, validations with different patient datasets or expansions to additional treatment sites, as well as the identification of particularly relevant blood dose metrics and blood compartments to allow for their inclusion during radiotherapy treatment planning, remain lacking. PURPOSE: This study aims to investigate a potential correlation between simulated blood dose values and adverse clinical outcomes in 215 patients with head-and-neck squamous cell carcinoma (HNSCC), 180 patients with glioblastoma (GBM), and 490 patients with non-small-cell lung cancer (NSCLC), and to identify particularly relevant blood dose metrics and blood compartments to allow for their inclusion during radiotherapy treatment planning and thereby enable the optimization of the estimated dose delivered to circulating blood.

methodsFor all 885 patients, TotalSegmentator was used to automatically delineate additional organs-at-risk (OARs), blood vessels, and tissues which were not already manually delineated for radiotherapy treatment planning. Subsequently, the dynamic HEDOS model, which considers temporal aspects such as blood flow dynamics and treatment delivery time, was used to simulate the radiation dose delivered to circulate blood during radiotherapy. Static blood dose models consisting of the mean dose to the union of all HEDOS blood compartments (D

resultsDuring multivariable Cox regression analysis, the blood dose estimates from the dynamic blood dose model exhibited a statistically significant (p < 0.05) correlation with DMFS and OS in the HNSCC and NSCLC datasets as well as with LRC in the HNSCC dataset. D

conclusionsThe dynamic blood dose model exhibited a statistically significant correlation with adverse clinical outcomes in five out of seven cases, compared to just two cases for the static blood dose models. Consideration of temporal aspects such as blood flow dynamics and treatment delivery time was therefore essential to some of the observed correlations. For each treatment site, particularly relevant blood compartments were identified, allowing for their inclusion during radiotherapy treatment planning as part of future studies which aim to reduce the estimated dose to circulating blood.

Indexed as

Brain NeoplasmsCarcinoma, Non-Small-Cell LungGlioblastomaHead and Neck NeoplasmsLung NeoplasmsLymphopeniaRadiotherapy Planning, Computer-AssistedAdultAgedFemaleHumansMaleMiddle AgedOrgans at RiskPrognosisRadiotherapy Dosageblood dosedose‐response relationshipradiation‐induced lymphopeniaradiotherapy

Identifiers

PMID41457830
PMCPMC12745927

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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.