Relative electron density calibration of CT scanners for radiotherapy treatment planning.

Thomas, S J

doi:10.1259/bjr.72.860.10624344

Cited by 132 publications

(96 citation statements)

References 7 publications

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“…raw wood plug phantom are determined by dividing the mass (g) of sample to measured volume (cm 3 ) as shown in Table 1. Table 1 illustrates that all plug phantoms achieved target densities near the value of water (1.004 g/cm 3 ). The average, and standard deviation of CT number for each samples in comparison to water is shown in Table 2.…”

Section: Resultsmentioning

confidence: 96%

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Determination of CT number and density profile of binderless, pre-treated and tannin-based Rhizophora spp. particleboards using computed tomography imaging and electron density phantom

Yusof¹,

Hamid

Bauk

et al. 2015

AIP Conference Proceedings

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Mass attenuation coefficient of binderless, pre-treated and tannin-based Rhizophora spp. particleboards using 16. 59 -25.26 Investigation of public exposure resulted from the radioiodine delay tank facility of nuclear medicine department AIP Conference Proceedings 1704, 050002 (2016) Abstract.Plug density phantoms were constructed in accordance to CT density phantom model 062M CIRS using binderless, pre-treated and tannin-based Rhizophora Spp. particleboards. The Rhizophora Spp. plug phantoms were scanned along with the CT density phantom using Siemens Somatom Definition AS CT scanner at three CT energies of 80, 120 and 140 kVp. 15 slices of images with 1.0 mm thickness each were taken from the central axis of CT density phantom for CT number and CT density profile analysis. The values were compared to water substitute plug phantom from the CT density phantom. The tannin-based Rhizophora Spp. gave the nearest value of CT number to water substitute at 80 and 120 kVp CT energies with χ 2 value of 0.011 and 0.014 respectively while the binderless Rhizphora Spp. gave the nearest CT number to water substitute at 140 kVp CT energy with χ 2 value of 0.023. The tannin-based Rhizophora Spp. gave the nearest CT density profile to water substitute at all CT energies. This study indicated the suitability of Rhizophora Spp. particleboard as phantom material for the use in CT imaging studies.

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Section: Resultsmentioning

confidence: 96%

“…All particleboards were fabricated at target density of 1.0 g/cm 3 . A pressing mould was used to fabricate the particle board at 20cm x 20 cm x 0.5 cm dimension.…”

Section: Fabrication Of Particleboardmentioning

confidence: 99%

Determination of CT number and density profile of binderless, pre-treated and tannin-based Rhizophora spp. particleboards using computed tomography imaging and electron density phantom

Yusof¹,

Hamid

Bauk

et al. 2015

AIP Conference Proceedings

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“…In previous studies, Thomas (15) reported a resulting dose difference of 1% for an electron density difference of 8% for typical radiotherapy beams, and Hatton et al (16) similarly showed that 21% difference in electron density resulted in 2.6% dose difference. Thus, IVDCs for the same machine that were within 8% difference in density were combined into one curve.…”

Section: Resultsmentioning

confidence: 97%

“…Thus, IVDCs for the same machine that were within 8% difference in density were combined into one curve. For the CT, TrueBeam and TomoTherapy units, all calibration points were within 8% of each other, which resulted in less than 1% dose difference according to Thomas (15) . Thus, the TrueBeam and Tomotherapy units required only one IVDC each, despite using different imaging protocols.…”

Section: Resultsmentioning

confidence: 99%

Assessment of image quality and dose calculation accuracy on kV CBCT, MV CBCT, and MV CT images for urgent palliative radiotherapy treatments

Held

Cremers

Sneed

et al. 2016

J Applied Clin Med Phys

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A clinical workflow was developed for urgent palliative radiotherapy treatments that integrates patient simulation, planning, quality assurance, and treatment in one 30‐minute session. This has been successfully tested and implemented clinically on a linac with MV CBCT capabilities. To make this approach available to all clinics equipped with common imaging systems, dose calculation accuracy based on treatment sites was assessed for other imaging units. We evaluated the feasibility of palliative treatment planning using on‐board imaging with respect to image quality and technical challenges. The purpose was to test multiple systems using their commercial setup, disregarding any additional in‐house development. kV CT, kV CBCT, MV CBCT, and MV CT images of water and anthropomorphic phantoms were acquired on five different imaging units (Philips MX8000 CT Scanner, and Varian TrueBeam, Elekta VersaHD, Siemens Artiste, and Accuray Tomotherapy linacs). Image quality (noise, contrast, uniformity, spatial resolution) was evaluated and compared across all machines. Using individual image value to density calibrations, dose calculation accuracies for simple treatment plans were assessed for the same phantom images. Finally, image artifacts on clinical patient images were evaluated and compared among the machines. Image contrast to visualize bony anatomy was sufficient on all machines. Despite a high noise level and low contrast, MV CT images provided the most accurate treatment plans relative to kV CT‐based planning. Spatial resolution was poorest for MV CBCT, but did not limit the visualization of small anatomical structures. A comparison of treatment plans showed that monitor units calculated based on a prescription point were within 5% difference relative to kV CT‐based plans for all machines and all studied treatment sites (brain, neck, and pelvis). Local dose differences >5% were found near the phantom edges. The gamma index for 3%/3 mm criteria was ≥95% in most cases. Best dose calculation results were obtained when the treatment isocenter was near the image isocenter for all machines. A large field of view and immediate image export to the treatment planning system were essential for a smooth workflow and were not provided on all devices. Based on this phantom study, image quality of the studied kV CBCT, MV CBCT, and MV CT on‐board imaging devices was sufficient for treatment planning in all tested cases. Treatment plans provided dose calculation accuracies within an acceptable range for simple, urgently planned palliative treatments. However, dose calculation accuracy was compromised towards the edges of an image. Feasibility for clinical implementation should be assessed separately and may be complicated by machine specific features. Image artifacts in patient images and the effect on dose calculation accuracy should be assessed in a separate, machine‐specific study.PACS number(s): 87.55.D‐, 87.57.C‐, 87.57.Q‐

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“…The design of simulation CT used for radiotherapy is very similar to a diagnostic CT, except for its larger bore, a flat couch and some immobilization accessories. However, the simulation CT is not only used for diagnostic imaging, but also essential for the dose calculation by providing the electron density of the medium [20]. Although the correlation between the Hounsfield Unit (HU) and the density is subject to the scanning parameters [21], most treatment planning systems adopt single conversion table even if the planning CTuses different settings to scan various body regions [22].…”

Section: Personalized Ct Scansmentioning

confidence: 99%

Toward Personalized Imaging in Image-guided Radiotherapy

Zhang¹,

Deng

2014

Cancer Sci Res

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Relative electron density calibration of CT scanners for radiotherapy treatment planning.

Cited by 132 publications

References 7 publications

Determination of CT number and density profile of binderless, pre-treated and tannin-based Rhizophora spp. particleboards using computed tomography imaging and electron density phantom

Determination of CT number and density profile of binderless, pre-treated and tannin-based Rhizophora spp. particleboards using computed tomography imaging and electron density phantom

Assessment of image quality and dose calculation accuracy on kV CBCT, MV CBCT, and MV CT images for urgent palliative radiotherapy treatments

Toward Personalized Imaging in Image-guided Radiotherapy

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