Evidence map›Paper›PMID 33107997›Full record

ArticleMedical physics2021

Technical Note: A methodology for improved accuracy in stopping power estimation using MRI and CT.

Jessica E Scholey, Dharshan Chandramohan, Tarun Naren, William Liu, Peder Eric Zufall Larson, Atchar Sudhyadhom

Abstract read
In one paragraph

Article in Medical physics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

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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

6 authors.

Jessica E ScholeyDepartment of Radiation Oncology, The University of California, San Francisco, CA, USA.
Dharshan ChandramohanDepartment of Radiation Oncology, The University of California, San Francisco, CA, USA.
Tarun NarenDepartment of Radiation Oncology, The University of California, San Francisco, CA, USA.
William LiuDepartment of Radiation Oncology, The University of California, San Francisco, CA, USA.
Peder Eric Zufall LarsonDepartment of Radiology and Biomedical Imaging, The University of California, San Francisco, CA, USA.
Atchar SudhyadhomDepartment of Radiation Oncology, The University of California, San Francisco, CA, USA.

Funding

A Multimodal Imaging Approach Towards the Reduction of Proton Beam Range UncertaintiesR21EB026086 · NIBIB · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI SUDHYADHOM, ATCHAR · 2018 to 2020
$594k
NIBIB NIH HHS R21 EB026086NIH HHS R21EB026086
6 · The paper itself

Abstract

purposeProton therapy is becoming an increasingly popular cancer treatment modality due to the proton's physical advantage in that it deposits the majority of its energy at the distal end of its track where the tumor is located. The proton range in a material is determined from the stopping power ratio (SPR) of the material. However, SPR is typically estimated based on a computed tomography (CT) scan which can lead to range estimation errors due to the difference in x-ray and proton interactions in matter, which can preclude the ability to utilize protons to their full potential. Applications of magnetic resonance imaging (MRI) in radiotherapy have increased over the past decade and using MRI to calculate SPR directly could provide numerous advantages. The purpose of this study was to develop a practical implementation of a novel multimodal imaging method for estimating SPR and compare the results of this method to physical measurements in which values were computed directly using tissue substitute materials fabricated to mimic skin, muscle, adipose, and spongiosa bone.

methodsFor both the multimodal imaging method and physical measurements, SPR was calculated using the Bethe-Bloch equation from values of relative electron density and mean ionization potential determined for each tissue. Parameters used to estimate SPR using the multimodal imaging method were extracted from Dixon water-only and (

resultsResults showed that our multimodal imaging approach using MRI with either kVCT or MVCT was in close agreement to SPR calculated from physical measurements for the four tissue substitutes evaluated. Using MRI and MVCT, SPR values estimated using our method were within 1% of physical measurements and were more accurate than the stoichiometric method for the tissue types studied.

conclusionsWe have demonstrated the methodology for improved estimation of SPR using the proposed multimodal imaging framework.

Indexed as

Proton TherapyTomography, X-Ray ComputedElectronsMagnetic Resonance ImagingPhantoms, ImagingProtonsRadiotherapy Planning, Computer-AssistedProtonsdose calculation for radiotherapymagnetic resonance imagingproton therapyquantitative imaging

Identifiers

PMID33107997
PMCPMC8717393

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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.