Evidence map›Paper›PMID 41022256›Full record

ArticleInternational journal of radiation oncology, biology, physics2026

Functional Avoidance Liver 4π Stereotactic Body Radiation Therapy Informed by Quantitative Gadoxetic Acid Contrast-Enhanced Magnetic Resonance T1 Mapping.

Joshua Everts, Yang Yang, Qifan Xu, Qihui Lyu, Mary Feng, Jessica Scholey, Michael Ohliger, William C Chen, Alexandra E Hotca, Mekhail Anwar and 4 more

Abstract read
In one paragraph

Article in International journal of radiation oncology, biology, physics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

14 authors.

Joshua EvertsDepartment of Radiation Oncology, UC San Francisco, San Francisco, California.
Yang YangDepartment of Radiology, UC San Francisco, San Francisco, California.
Qifan XuDepartment of Radiation Oncology, UC San Francisco, San Francisco, California.
Qihui LyuDepartment of Radiation Oncology, UC San Francisco, San Francisco, California.
Mary FengDepartment of Radiation Oncology, UC San Francisco, San Francisco, California.
Jessica ScholeyDepartment of Radiation Oncology, UC San Francisco, San Francisco, California.
Michael OhligerDepartment of Radiology, UC San Francisco, San Francisco, California.
William C ChenDepartment of Radiation Oncology, UC San Francisco, San Francisco, California.
Alexandra E HotcaDepartment of Radiation Oncology, UC San Francisco, San Francisco, California.
Mekhail AnwarDepartment of Radiation Oncology, UC San Francisco, San Francisco, California.
Junzhou ChenDepartment of Radiology, University of Southern California, Los Angeles, California.
Zhaoyang FanDepartment of Radiology, University of Southern California, Los Angeles, California.
Ke ShengDepartment of Radiation Oncology, UC San Francisco, San Francisco, California.
Wensha YangDepartment of Radiation Oncology, UC San Francisco, San Francisco, California. Electronic address: Wensha.Yang@ucsf.edu.

Funding

Multi-Task MR Simulation for Abdominal Radiation Treatment PlanningR01EB029088 · NIBIB · UNIVERSITY OF SOUTHERN CALIFORNIA · PI FAN, ZHAOYANG, YANG, WENSHA · 2020 to 2023
$2.5M
Functional Avoidance Liver Stereotactic Body Radiation Therapy Guided by MR Multitasking-driven Abdominal Integrated Imaging (MT-AI2)R01CA301509 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Zhaoyang Fan, Mary Feng · 2026 to 2026
$701k
NCI NIH HHS R01 CA301509NIBIB NIH HHS R01 EB029088
6 · The paper itself

Abstract

purposeRecent studies have identified the T1 reduction rates (k1) from gadoxetic acid-enhanced magnetic resonance (MR) imaging as a biomarker for liver function. In this study, we validate k1 maps as a functional biomarker and develop 4π noncoplanar treatment plans using k1 maps to guide the optimization for liver functional avoidance stereotactic body radiation therapy (FA-SBRT). METHODS AND MATERIALS: One hundred six patients underwent precontrast and postcontrast T1 mapping MR. Mean k1 values extracted from liver mask excluding gross tumor volume (liver-GTV) were correlated with Child-Pugh and albumin-bilirubin scores. The high-function (HF) liver region was identified and masked using a patient-specific threshold from the Gaussian decomposition of the k1 histogram. Twenty patients were retrospectively planned with coplanar and noncoplanar 4π-SBRT with and without functional avoidance. Tumor coverage was maintained at a minimum of 90% planning target volume to receive prescription, and standard organ at risk constraints were set for all plans. Dose metrics included mean dose to the HF liver and HF liver volume receiving 6 Gy, which was shown to impact patient liver function. A paired, 2-tailed t test was used to determine the statistical significance.

resultsk1 values were inversely correlated with Child-Pugh and albumin-bilirubin scores. The 4π FA-SBRT plans reduced the mean dose to the HF liver volume by 21.8% (from 9.2 Gy to 6.5 Gy) (P < .0001) and the volume of HF liver receiving >6 Gy by 39.5% (from 507.5 cm

conclusionsThis study validates k1 derived from free-breathing T1 mapping MR as a liver function biomarker in a cancer patient cohort. Gaussian decomposition can threshold the k1 distribution to create patient-specific HF liver masks. The 4π FA-SBRT planning guided by k1 maps significantly reduced the mean dose to the HF liver, as well as the volume of HF receiving >6 Gy.

Indexed as

Contrast MediaGadolinium DTPALiverLiver NeoplasmsMagnetic Resonance ImagingOrgan Sparing TreatmentsRadiosurgeryAgedAged, 80 and overBilirubinFemaleHumansMaleMiddle AgedOrgans at RiskRadiotherapy DosageBilirubinContrast MediaGadolinium DTPAgadolinium ethoxybenzyl DTPA

Identifiers

PMID41022256
PMCPMC13321400

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.