Development of a CT number calibration audit phantom in photon radiation therapy: A pilot study

Nakao, Minoru; Ozawa, Shogo; Miura, Hideharu; Yamada, Kiyoshi; Habara, Kosaku; Hayata, Masahiro; Kusaba, Hayate; Kawahara, Daisuke; Miki, K.; Nakashima, Takeo; Ochi, Yusuke; Tsuda, S.; Seido, Mineaki; Morimoto, Yoshiharu; Kawakubo, Atsushi; Nozaki, Hiroshige; Nagata, Yasushi

doi:10.1002/mp.14077

Cited by 14 publications

(12 citation statements)

References 23 publications

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“…In Bibb et al (2011) up to 128 HU difference (average 28 HU) is reported for the same sample scanned either on the head phantom, or in the foam block. This difference, again, emphasizes the importance of well-defined scanning conditions, as is best demonstrated by CT quality control or electron density calibration phantoms used in radiotherapy planning ( Constantinou et al, 1992 ; Nakao et al, 2020 ), where the calibration cylinders are embedded into a water equivalent material in a cylindrical phantom of appropriate diameter.…”

Section: Discussionmentioning

confidence: 99%

Classification of X-Ray Attenuation Properties of Additive Manufacturing and 3D Printing Materials Using Computed Tomography From 70 to 140 kVp

Buschmann

Unger

et al. 2021

Front. Bioeng. Biotechnol.

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Additive manufacturing and 3D printing is particularly useful in the production of phantoms for medical imaging applications including determination and optimization of (diagnostic) image quality and dosimetry. Additive manufacturing allows the leap from simple slab and stylized to (pseudo)-anthropomorphic phantoms. This necessitates the use of materials with x-ray attenuation as close as possible to that of the tissues or organs mimicked. X-ray attenuation properties including their energy dependence were determined for 35 printing materials comprising photocured resins and thermoplastic polymers. Prior to measuring x-ray attenuation in CT from 70 to 140 kVp, printing parameters were thoroughly optimized to ensure maximum density avoiding too low attenuation due to microscopic or macroscopic voids. These optimized parameters are made available. CT scanning was performed in a water filled phantom to guarantee defined scan conditions and accurate HU value determination. The spectrum of HU values covered by polymers printed using fused deposition modeling reached from −258 to +1,063 at 120 kVp (−197 to +1,804 at 70 kVp, to −266 to +985 at 140 kVp, respectively). Photocured resins covered 43 to 175 HU at 120 kVp (16–156 at 70, and 57–178 at 140 kVp). At 120 kVp, ASA mimics water almost perfectly (+2 HU). HIPS (−40 HU) is found close to adipose tissue. In all photocurable resins, and 17 printing filaments HU values decreased with increasing beam hardness contrary to soft tissues except adipose tissue making it difficult to mimic water or average soft tissue in phantoms correctly over a range of energies with one single printing material. Filled filaments provided both, the HU range, and an appropriate energy dependence mimicking bone tissues. A filled material with almost constant HU values was identified potentially allowing mimicking soft tissues by reducing density using controlled under-filling. The measurements performed in this study can be used to design phantoms with a wide range of x-ray contrasts, and energy dependence of these contrasts by combining appropriate materials. Data provided on the energy dependence can also be used to correct contrast or contrast to noise ratios from phantom measurements to real tissue contrasts or CNRs.

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Section: Discussionmentioning

confidence: 99%

Classification of X-Ray Attenuation Properties of Additive Manufacturing and 3D Printing Materials Using Computed Tomography From 70 to 140 kVp

Buschmann

Unger

et al. 2021

Front. Bioeng. Biotechnol.

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“…phantoms. The theoretical CT numbers using the stoichiometric CT number calibration method with three free parameters 25,28 were found to be more consistent with the measured CT numbers than conventional methods. 17,18 The standard tissue model 29…”

Section: Discussionmentioning

confidence: 63%

“…[21][22][23][24] A CT number calibration audit using a stoichiometric method was established for photon therapy, and a pilot study was conducted in five radiotherapy institutes. 25 In this study, the number of participating institutes, CT scanners, scan conditions, and TPSs were increased, and the interinstitute variations in the CT-ρ and CT-ρ e calibration curves were evaluated for each phantom vendor and TPS.…”

Section: Introductionmentioning

confidence: 99%

“…In contrast, CT number calibration audit using a stoichiometric method 17–20 flexibly responds to variations in radiation type and its energy, as well as to updates on standard tissue data 21–24 . A CT number calibration audit using a stoichiometric method was established for photon therapy, and a pilot study was conducted in five radiotherapy institutes 25 . In this study, the number of participating institutes, CT scanners, scan conditions, and TPSs were increased, and the inter‐institute variations in the CT‐ ρ and CT‐ ρ e calibration curves were evaluated for each phantom vendor and TPS.…”

Section: Introductionmentioning

confidence: 99%

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CT number calibration audit in photon radiation therapy

Nakao,

Ozawa,

Miura

et al. 2023

Medical Physics

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BackgroundInadequate computed tomography (CT) number calibration curves affect dose calculation accuracy. Although CT number calibration curves registered in treatment planning systems (TPSs) should be consistent with human tissues, it is unclear whether adequate CT number calibration is performed because CT number calibration curves have not been assessed for various types of CT number calibration phantoms and TPSs.PurposeThe purpose of this study was to investigate CT number calibration curves for mass density (ρ) and relative electron density (ρe).MethodsA CT number calibration audit phantom was sent to 24 Japanese photon therapy institutes from the evaluating institute and scanned using their individual clinical CT scan protocols. The CT images of the audit phantom and institute‐specific CT number calibration curves were submitted to the evaluating institute for analyzing the calibration curves registered in the TPSs at the participating institutes. The institute‐specific CT number calibration curves were created using commercial phantom (Gammex, Gammex Inc., Middleton, WI, USA) or CIRS phantom (Computerized Imaging Reference Systems, Inc., Norfolk, VA, USA)). At the evaluating institute, theoretical CT number calibration curves were created using a stoichiometric CT number calibration method based on the CT image, and the institute‐specific CT number calibration curves were compared with the theoretical calibration curve. Differences in ρ and ρe over the multiple points on the curve (Δρm and Δρe,m, respectively) were calculated for each CT number, categorized for each phantom vendor and TPS, and evaluated for three tissue types: lung, soft tissues, and bones. In particular, the CT‐ρ calibration curves for Tomotherapy TPSs (ACCURAY, Sunnyvale, CA, USA) were categorized separately from the Gammex CT‐ρ calibration curves because the available tissue‐equivalent materials (TEMs) were limited by the manufacturer recommendations. In addition, the differences in ρ and ρe for the specific TEMs (ΔρTEM and Δρe,TEM, respectively) were calculated by subtracting the ρ or ρe of the TEMs from the theoretical CT‐ρ or CT‐ρe calibration curve.ResultsThe mean ± standard deviation (SD) of Δρm and Δρe,m for the Gammex phantom were −1.1 ± 1.2 g/cm3 and −0.2 ± 1.1, −0.3 ± 0.9 g/cm3 and 0.8 ± 1.3, and −0.9 ± 1.3 g/cm3 and 1.0 ± 1.5 for lung, soft tissues, and bones, respectively. The mean ± SD of Δρm and Δρe,m for the CIRS phantom were 0.3 ± 0.8 g/cm3 and 0.9 ± 0.9, 0.6 ± 0.6 g/cm3 and 1.4 ± 0.8, and 0.2 ± 0.5 g/cm3 and 1.6 ± 0.5 for lung, soft tissues, and bones, respectively. The mean ± SD of Δρm for Tomotherapy TPSs was 2.1 ± 1.4 g/cm3 for soft tissues, which is larger than those for other TPSs. The mean ± SD of Δρe,TEM for the Gammex brain phantom (BRN‐SR2) was −1.8 ± 0.4, implying that the tissue equivalency of the BRN‐SR2 plug was slightly inferior to that of other plugs.ConclusionsLatent deviations between human tissues and TEMs were found by comparing the CT number calibration curves of the various institutes.

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“…The CT number linearity test is carried out by graphing the mean CT number against the density of each phantom material [14,15]. A higher material density value should have a higher CT number, and vice versa [16][17][18].…”

Section: Introductionmentioning

confidence: 99%

The automated measurement of CT number linearity using an ACR accreditation phantom

Anam

Amilia

Naufal

et al. 2022

Biomed. Phys. Eng. Express

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We developed software to automatically measure the CT number linearity using an ACR accreditation phantom image and investigated the CT number linearity of 16 different CT scanners. The software implemented a segmentation-rotation method. After segmenting five objects within the phantom image, the mean CT number of each object was measured and a graph between CT numbers and their densities plotted. Linear regression and its R2 were automatically calculated. The software was used to investigate the CT number linearity of 16 CT scanners from Toshiba, Siemens, Hitachi, and GE installed in 16 hospitals in Indonesia. The linearity of the CT number obtained on most of the scanners showed a strong linear correlation (R2 > 0.99) between the CT numbers and their densities. Two scanners (Siemens Emotion 16) had the strongest linear correlation with R2 = 0.999, and two Hitachi Eclos scanners had the weakest linear correlation with R2 < 0.99.

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Development of a CT number calibration audit phantom in photon radiation therapy: A pilot study

Cited by 14 publications

References 23 publications

Classification of X-Ray Attenuation Properties of Additive Manufacturing and 3D Printing Materials Using Computed Tomography From 70 to 140 kVp

Classification of X-Ray Attenuation Properties of Additive Manufacturing and 3D Printing Materials Using Computed Tomography From 70 to 140 kVp

CT number calibration audit in photon radiation therapy

The automated measurement of CT number linearity using an ACR accreditation phantom

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