Evidence mapPaperPMID 42212205Full record

ArticlePhysics and imaging in radiation oncology2026

Feasibility of longitudinal relaxation rate mapping with non-Cartesian sampling and compressed sensing on a 1.5 T magnetic resonance linear accelerator.

Lucas McCullum, Michael J van Rijssel, Ken-Pin Hwang, Yao Ding, Chad Tang, Comron Hassanzadeh, Jinzhong Yang, Peter A Balter, Jihong Wang, Clifton D Fuller and 1 more

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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

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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

11 authors.

Lucas McCullumDepartment of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Michael J van RijsselDepartment of Radiotherapy, UMC Utrecht, Utrecht, the Netherlands.
Ken-Pin HwangDepartment of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Yao DingDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Chad TangDepartment of Genitourinary Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Comron HassanzadehDepartment of Genitourinary Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Jinzhong YangDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Peter A BalterDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Jihong WangDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Clifton D FullerDepartment of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Ergys D SubashiDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and purpose: Quantitative T1 mapping is a major building block in several multiparametric magnetic resonance imaging (MRI) protocols intended for adaptive radiation therapy. The implementation of these protocols is challenging in anatomical sites that experience large physiological motion. The purpose of this study was to implement and validate motion-resolved quantitative T1 mapping on a 1.5 T MRI linear accelerator (MR-Linac) combining non-Cartesian k-space sampling trajectories with compressed sensing (CS) reconstruction. Materials and methods: Four 3-dimensional non-Cartesian k-space trajectories were evaluated: kooshball and stack-of-stars sampling using half- and full-spoke coverage. A variable flip angle acquisition was performed using the spoiled gradient-echo sequence. Gradient delay timing was optimized to minimize trajectory-induced artifacts. Eight CS reconstruction strategies were tested using spatial/spatiotemporal regularization operators. Reconstructions were evaluated and sorted by spatial resolution, bias, and variability. Motion-resolved T1 mapping was validated using two standard phantoms, one healthy volunteer, and one kidney cancer patient using respiratory self-gating and phase-sorted reconstruction. Results: All non-Cartesian T1 maps demonstrated high repeatability and low longitudinal bias in phantom studies, with coefficients of variation below 3.3%. Spatiotemporal regularization preserved spatial resolution and quantitative accuracy at undersampling factors up to 20-fold. In human subjects, non-Cartesian T1 mapping provided improved accuracy and reduced variability in mobile abdominal tissues compared to Cartesian acquisitions. Conclusions: Quantitative T1 mapping using non-Cartesian trajectories and CS reconstruction is feasible on a 1.5 T MR-Linac. The proposed approach enables accurate motion-resolved quantitative imaging within clinically practical acquisition times, establishing a foundation for multiparametric MRI in adaptive radiotherapy.

Indexed as

AccelerationCompressed sensingKooshballLongitudinal relaxation rateMR-LinacNon CartesianQuantitativeR1RadialRelaxometryStack-of-starsT1

Identifiers

PMID42212205
PMCPMC13214301

What Socratic holds

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LicenceCC BY-NC-ND
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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 Socratic graph.