Evidence map›Paper›PMID 39608610›Full record

ArticleInternational journal of radiation oncology, biology, physics2025

Evaluating the Impact of Liver Vasculature Model Complexity for Estimating Dose to Circulating Blood During Radiation Therapy.

Shu Xing, Camilo M Correa-Alfonso, Jungwook Shin, Jennifer Pursley, Nicolas Depauw, Sean Domal, Julia Withrow, Wesley Bolch, Clemens Grassberger, Harald Paganetti

Abstract readEvaluation Study
PubMed Full text at PMC Publisher
In one paragraph

Article in International journal of radiation oncology, biology, physics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Shu XingDepartment of Radiation Oncology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts; Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York City, New York. Electronic address: xings@mskcc.org.
Camilo M Correa-AlfonsoDepartment of Biomedical Engineering, University of Florida, Gainesville, Florida; Radiation Physics Department, University of Texas MD Anderson Cancer Center, Houston, Texas.
Jungwook ShinDepartment of Radiation Oncology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts; Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, Maryland.
Jennifer PursleyDepartment of Radiation Oncology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts.
Nicolas DepauwDepartment of Radiation Oncology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts.
Sean DomalDepartment of Biomedical Engineering, University of Florida, Gainesville, Florida; Department of Radiation Oncology, UT Southwestern Medical Center, Dallas, Texas.
Julia WithrowDepartment of Biomedical Engineering, University of Florida, Gainesville, Florida.
Wesley BolchDepartment of Biomedical Engineering, University of Florida, Gainesville, Florida.
Clemens GrassbergerDepartment of Radiation Oncology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts; Department of Radiation Oncology, University of Washington, Seattle, Washington.
Harald PaganettiDepartment of Radiation Oncology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts.

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI SELWYN M VICKERS · 1985 to 2026
$347.4M
Project 3: Enhanced Sensitivity of Tumors to Proton Beam Therapy: Mechanisms and Biomarkers.P01CA261669 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI TITT, UWE · 2021 to 2025
$14.0M
Developing whole-body computational phantoms for blood dosimetry to model the impact of radiation on the immune systemR01CA248901 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI BOLCH, WESLEY E, PAGANETTI, HARALD · 2020 to 2024
$2.4M
A Computational Method to Calculate the Radiation Dose to CirculatingLymphocytesR21CA248118 · NCI · UNIVERSITY OF WASHINGTON · PI GRASSBERGER, CLEMENS · 2020 to 2020
$429k
NCI NIH HHS P01 CA261669NCI NIH HHS P30 CA008748NCI NIH HHS R01 CA248901NCI NIH HHS R21 CA248118
6 · The paper itself

Abstract

purposeTo assess the impact of liver model complexity on the estimated radiation dose to circulating blood during radiation therapy. METHODS AND MATERIALS: Six patients with hepatocellular carcinoma (HCC) were selected covering a range of clinical treatment volume (CTV) sizes and locations. Photon and proton treatment plans were generated for each patient. Planning computed tomography, CTV contours, and dose distributions were deformably registered to the reference livers provided by the International Commission on Radiological Protection report. Three vasculature models were considered: (1) main vascular tree (MVT), (2) coarse vascular tree (CVT) of 1045 vessels, and (3) detailed vascular tree (DVT) of 2041 vessels. Blood dose-volume histograms (bDVH

resultsFor the 3 lesions located in the left lobe, the estimated μ

conclusionOur study revealed that the impact of liver vasculature model complexity on the estimated dose to blood depended on lesion-specific characteristics. For lesions with larger CTV size on the right liver lobe treated with photons, modeling only major vessels could generate bDVHs that are dosimetrically comparable with bDVHs of more complex vascular models. Increased tumor v

Indexed as

Carcinoma, HepatocellularLiverLiver NeoplasmsBlood Flow VelocityHumansMonte Carlo MethodPhotonsProton TherapyRadiotherapy DosageRadiotherapy Planning, Computer-AssistedTumor Burden

Identifiers

PMID39608610
PMCPMC11911079

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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.