Literature DB >> 34739140

A comparison of proton stopping power measured with proton CT and x-ray CT in fresh postmortem porcine structures.

Don F DeJongh1, Ethan A DeJongh1, Victor Rykalin1, Greg DeFillippo2, Mark Pankuch2, Andrew W Best3, George Coutrakon3, Kirk L Duffin4, Nicholas T Karonis4,5, Caesar E Ordoñez4, Christina Sarosiek3, Reinhard W Schulte6, John R Winans4, Alec M Block7,8, Courtney L Hentz7,8, James S Welsh7,8.   

Abstract

PURPOSE: Currently, calculations of proton range in proton therapy patients are based on a conversion of CT Hounsfield units of patient tissues into proton relative stopping power. Uncertainties in this conversion necessitate larger proximal and distal planned target volume margins. Proton CT can potentially reduce these uncertainties by directly measuring proton stopping power. We aim to demonstrate proton CT imaging with complex porcine samples, to analyze in detail three-dimensional regions of interest, and to compare proton stopping powers directly measured by proton CT to those determined from x-ray CT scans.
METHODS: We have used a prototype proton imaging system with single proton tracking to acquire proton radiography and proton CT images of a sample of porcine pectoral girdle and ribs, and a pig's head. We also acquired close in time x-ray CT scans of the same samples and compared proton stopping power measurements from the two modalities. In the case of the pig's head, we obtained x-ray CT scans from two different scanners and compared results from high-dose and low-dose settings.
RESULTS: Comparing our reconstructed proton CT images with images derived from x-ray CT scans, we find agreement within 1% to 2% for soft tissues and discrepancies of up to 6% for compact bone. We also observed large discrepancies, up to 40%, for cavitated regions with mixed content of air, soft tissue, and bone, such as sinus cavities or tympanic bullae.
CONCLUSIONS: Our images and findings from a clinically realistic proton CT scanner demonstrate the potential for proton CT to be used for low-dose treatment planning with reduced margins.
© 2021 American Association of Physicists in Medicine.

Entities:  

Keywords:  digitally reconstructed radiograph; iterative algorithm; proton computed tomography; proton imaging; proton radiography; relative stopping power

Mesh:

Substances:

Year:  2021        PMID: 34739140      PMCID: PMC8678357          DOI: 10.1002/mp.15334

Source DB:  PubMed          Journal:  Med Phys        ISSN: 0094-2405            Impact factor:   4.071


  29 in total

1.  Olfactory neuroblastomas: survival rate and prognostic factor.

Authors:  Sung-Kyun Hwang; Sun-Ha Paek; Dong Gyu Kim; Yoon-Kyung Jeon; Je G Chi; Hee-Won Jung
Journal:  J Neurooncol       Date:  2002-09       Impact factor: 4.130

2.  Patient-specific stopping power calibration for proton therapy planning based on single-detector proton radiography.

Authors:  P J Doolan; M Testa; G Sharp; E H Bentefour; G Royle; H-M Lu
Journal:  Phys Med Biol       Date:  2015-02-10       Impact factor: 3.609

3.  Experimental comparison of proton CT and dual energy x-ray CT for relative stopping power estimation in proton therapy.

Authors:  George Dedes; Jannis Dickmann; Katharina Niepel; Philipp Wesp; Robert P Johnson; Mark Pankuch; Vladimir Bashkirov; Simon Rit; Lennart Volz; Reinhard W Schulte; Guillaume Landry; Katia Parodi
Journal:  Phys Med Biol       Date:  2019-08-14       Impact factor: 3.609

4.  Technical Note: CT calibration for proton treatment planning by cross-calibration with proton CT data.

Authors:  Paolo Farace; Francesco Tommasino; Roberto Righetto; Francesco Fracchiolla; Monica Scaringella; Mara Bruzzi; Carlo Civinini
Journal:  Med Phys       Date:  2021-02-06       Impact factor: 4.071

5.  The effect of beam purity and scanner complexity on proton CT accuracy.

Authors:  P Piersimoni; J Ramos-Méndez; T Geoghegan; V A Bashkirov; R W Schulte; B A Faddegon
Journal:  Med Phys       Date:  2017-01-09       Impact factor: 4.071

Review 6.  Myths and realities of range uncertainty.

Authors:  Antony John Lomax
Journal:  Br J Radiol       Date:  2019-12-23       Impact factor: 3.039

7.  Esthesioneuroblastoma: the University of Iowa experience 1978-1998.

Authors:  J H Simon; W Zhen; T M McCulloch; H T Hoffman; A C Paulino; N A Mayr; J M Buatti
Journal:  Laryngoscope       Date:  2001-03       Impact factor: 3.325

8.  Effectiveness of robust optimization in intensity-modulated proton therapy planning for head and neck cancers.

Authors:  Wei Liu; Steven J Frank; Xiaoqiang Li; Yupeng Li; Peter C Park; Lei Dong; X Ronald Zhu; Radhe Mohan
Journal:  Med Phys       Date:  2013-05       Impact factor: 4.071

9.  Esthesioneuroblastoma: the massachusetts eye and ear infirmary and massachusetts general hospital experience with craniofacial resection, proton beam radiation, and chemotherapy.

Authors:  Anthony C Nichols; Annie W Chan; William T Curry; Fred G Barker; Daniel G Deschler; Derrick T Lin
Journal:  Skull Base       Date:  2008-09

Review 10.  Range uncertainties in proton therapy and the role of Monte Carlo simulations.

Authors:  Harald Paganetti
Journal:  Phys Med Biol       Date:  2012-05-09       Impact factor: 3.609

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  3 in total

1.  The accuracy of helium ion CT based particle therapy range prediction: an experimental study comparing different particle and x-ray CT modalities.

Authors:  L Volz; C-A Collins-Fekete; E Bär; S Brons; C Graeff; R P Johnson; A Runz; C Sarosiek; R W Schulte; J Seco
Journal:  Phys Med Biol       Date:  2021-11-29       Impact factor: 3.609

2.  An Iterative Least Squares Method for Proton CT Image Reconstruction.

Authors:  Don F DeJongh; Ethan A DeJongh
Journal:  IEEE Trans Radiat Plasma Med Sci       Date:  2021-05-11

3.  Radiation shielding assessment of high-energy proton imaging at a proton therapy facility.

Authors:  Scott N Penfold
Journal:  Med Phys       Date:  2022-06-06       Impact factor: 4.506

  3 in total

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