Evidence map›Paper›PMID 27277029›Full record

ArticleMedical physics2016

Characterizing spatiotemporal information loss in sparse-sampling-based dynamic MRI for monitoring respiration-induced tumor motion in radiotherapy.

Tatsuya J Arai, Joris Nofiele, Ananth J Madhuranthakam, Qing Yuan, Ivan Pedrosa, Rajiv Chopra, Amit Sawant

Abstract read
In one paragraph

Article in Medical physics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

The trial behind it

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Tatsuya J AraiDepartment of Radiation Oncology, UT Southwestern Medical Center, Dallas, Texas 75390.
Joris NofieleDepartment of Radiology, UT Southwestern Medical Center, Dallas, Texas 75390.
Ananth J MadhuranthakamDepartment of Radiology, UT Southwestern Medical Center, Dallas, Texas 75390 and Advanced Imaging Research Center, UT Southwestern Medical Center, Dallas, Texas 75390.
Qing YuanDepartment of Radiology, UT Southwestern Medical Center, Dallas, Texas 75390.
Ivan PedrosaDepartment of Radiology, UT Southwestern Medical Center, Dallas, Texas 75390 and Advanced Imaging Research Center, UT Southwestern Medical Center, Dallas, Texas 75390.
Rajiv ChopraDepartment of Radiology, UT Southwestern Medical Center, Dallas, Texas 75390 and Advanced Imaging Research Center, UT Southwestern Medical Center, Dallas, Texas 75390.
Amit SawantDepartment of Radiation Oncology, UT Southwestern Medical Center, Dallas, Texas 75390; Department of Radiology, UT Southwestern Medical Center, Dallas, Texas 75390; and Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, Maryland, 21201.

Funding

Personalized Motion Management for truly 4D Lung Stereotactic Body RadiotherapyR01CA169102 · NCI · UT SOUTHWESTERN MEDICAL CENTER · PI SAWANT, AMIT · 2013 to 2018
$2.8M
NCI NIH HHS R01 CA169102
6 · The paper itself

Abstract

purposeSparse-sampling and reconstruction techniques represent an attractive strategy to achieve faster image acquisition speeds, while maintaining adequate spatial resolution and signal-to-noise ratio in rapid magnetic resonance imaging (MRI). The authors investigate the use of one such sequence, broad-use linear acquisition speed-up technique (k-t BLAST) in monitoring tumor motion for thoracic and abdominal radiotherapy and examine the potential trade-off between increased sparsification (to increase imaging speed) and the potential loss of "true" information due to greater reliance on a priori information.

methodsLung tumor motion trajectories in the superior-inferior direction, previously recorded from ten lung cancer patients, were replayed using a motion phantom module driven by an MRI-compatible motion platform. Eppendorf test tubes filled with water which serve as fiducial markers were placed in the phantom. The modeled rigid and deformable motions were collected in a coronal image slice using balanced fast field echo in conjunction with k-t BLAST. Root mean square (RMS) error was used as a metric of spatial accuracy as measured trajectories were compared to input data. The loss of spatial information was characterized for progressively increasing acceleration factor from 1 to 16; the resultant sampling frequency was increased approximately from 2.5 to 19 Hz when the principal direction of the motion was set along frequency encoding direction. In addition to the phantom study, respiration-induced tumor motions were captured from two patients (kidney tumor and lung tumor) at 13 Hz over 49 s to demonstrate the impact of high speed motion monitoring over multiple breathing cycles. For each subject, the authors compared the tumor centroid trajectory as well as the deformable motion during free breathing.

resultsIn the rigid and deformable phantom studies, the RMS error of target tracking at the acquisition speed of 19 Hz was approximately 0.3-0.4 mm, which was smaller than the reconstructed pixel resolution of 0.67 mm. In the patient study, the dynamic 2D MRI enabled the monitoring of cycle-to-cycle respiratory variability present in the tumor position. It was seen that the range of centroid motion as well as the area covered due to target motion during each individual respiratory cycle was underestimated compared to the entire motion range observed over multiple breathing cycles.

conclusionsThe authors' initial results demonstrate that sparse-sampling- and reconstruction-based dynamic MRI can be used to achieve adequate image acquisition speeds without significant information loss for the task of radiotherapy guidance. Such monitoring can yield spatial and temporal information superior to conventional offline and online motion capture methods used in thoracic and abdominal radiotherapy.

Indexed as

RespirationAgedAged, 80 and overHumansKidney NeoplasmsLung NeoplasmsMagnetic Resonance ImagingMaleModels, BiologicalMotionPhantoms, ImagingRadiotherapy, Image-GuidedRespiratory-Gated Imaging Techniques

Identifiers

PMID27277029
PMCPMC4866962

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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.