ArticleMedical physics2021
Technical Note: A methodology for improved accuracy in stopping power estimation using MRI and CT.
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.
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Who cites it
7 citing papers in PubMed.
- Validation of dual-energy CT-based composition analysis using fresh animal tissues and composition-optimized tissue equivalent samples.Physics in medicine and biology · 2024Article
- MRI-only based material mass density and relative stopping power estimation via deep learning for proton therapy: a preliminary study.Scientific reports · 2024Article
- Validation of an MR-based multimodal method for molecular composition and proton stopping power ratio determination usingPhysics in medicine and biology · 2023Article
- Validation of prompt gamma-ray spectroscopy for proton range verification in tissue-mimicking and porcine samples.Physics in medicine and biology · 2022Article
- Generation of synthetic megavoltage CT for MRI-only radiotherapy treatment planning using a 3D deep convolutional neural network.Medical physics · 2022Article
- Improved accuracy of relative electron density and proton stopping power ratio through CycleGAN machine learning.Physics in medicine and biology · 2022Article
- On the molecular relationship between Hounsfield Unit (HU), mass density, and electron density in computed tomography (CT).PloS one · 2020Article
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Authors and funding
6 authors.
Funding
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.
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