Assessment of CT-to-physical density table for multiple image reconstruction functions with a large-bore scanner for radiotherapy treatment planning
•Comprehensive investigation of HU accuracy for a large-bore CT for RT planning.•Marginal impact on CT values with deep learning-based reconstruction.•Minimal difference in dose calculation among multiple reconstruction algorithms.•CT values remain stable as long as the subject fits within the scan...
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| Published in | Physica medica Vol. 133; p. 104970 |
|---|---|
| Main Authors | , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Italy
Elsevier Ltd
01.05.2025
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1120-1797 1724-191X 1724-191X |
| DOI | 10.1016/j.ejmp.2025.104970 |
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| Abstract | •Comprehensive investigation of HU accuracy for a large-bore CT for RT planning.•Marginal impact on CT values with deep learning-based reconstruction.•Minimal difference in dose calculation among multiple reconstruction algorithms.•CT values remain stable as long as the subject fits within the scan FOV of 70 cm.
To evaluate the performance of the Aquilion Exceed LB computed tomography (CT) scanner for radiotherapy treatment planning, this study examined the effect of different combinations of the image reconstruction function (IRF) (AiCE and AIDR) and scan parameters on the CT-to-physical density (CT-PD) table and radiation dose in the phantom, and the effect of different object positions on CT values.
To investigate IRF’s influence on each material, we calculated CT values by varying tube current, pitch, field of view (FOV), and phantom position for each IRF, comparing them with reference values using filtered back projection (FBP). Furthermore, we evaluated changes in depth dose values due to IRF differences using a solid phantom.
In the combinations of changes in IRF and scan parameters the change in CT value (ΔHU) of each material was within ±10 HU, except for most conditions. The change in physical density (ΔPD) was within ±0.02 g/cm3 for all combinations. For changes in phantom position, ΔHU was within ±25 HU for changes within the scan FOV, except for Bone 200 mg/cc and 1250 mg/cc. In areas outside the scan FOV with an expanded FOV, ΔHU was significantly larger than within the scan FOV. Variations in depth dose for different IRFs using solid phantoms were within ±0.5 %, except at material boundaries.
Our evaluations of the CT values and dose calculations suggested no need to change the CT-PD table, even with multiple IRFs. |
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| AbstractList | •Comprehensive investigation of HU accuracy for a large-bore CT for RT planning.•Marginal impact on CT values with deep learning-based reconstruction.•Minimal difference in dose calculation among multiple reconstruction algorithms.•CT values remain stable as long as the subject fits within the scan FOV of 70 cm.
To evaluate the performance of the Aquilion Exceed LB computed tomography (CT) scanner for radiotherapy treatment planning, this study examined the effect of different combinations of the image reconstruction function (IRF) (AiCE and AIDR) and scan parameters on the CT-to-physical density (CT-PD) table and radiation dose in the phantom, and the effect of different object positions on CT values.
To investigate IRF’s influence on each material, we calculated CT values by varying tube current, pitch, field of view (FOV), and phantom position for each IRF, comparing them with reference values using filtered back projection (FBP). Furthermore, we evaluated changes in depth dose values due to IRF differences using a solid phantom.
In the combinations of changes in IRF and scan parameters the change in CT value (ΔHU) of each material was within ±10 HU, except for most conditions. The change in physical density (ΔPD) was within ±0.02 g/cm3 for all combinations. For changes in phantom position, ΔHU was within ±25 HU for changes within the scan FOV, except for Bone 200 mg/cc and 1250 mg/cc. In areas outside the scan FOV with an expanded FOV, ΔHU was significantly larger than within the scan FOV. Variations in depth dose for different IRFs using solid phantoms were within ±0.5 %, except at material boundaries.
Our evaluations of the CT values and dose calculations suggested no need to change the CT-PD table, even with multiple IRFs. To evaluate the performance of the Aquilion Exceed LB computed tomography (CT) scanner for radiotherapy treatment planning, this study examined the effect of different combinations of the image reconstruction function (IRF) (AiCE and AIDR) and scan parameters on the CT-to-physical density (CT-PD) table and radiation dose in the phantom, and the effect of different object positions on CT values. To investigate IRF's influence on each material, we calculated CT values by varying tube current, pitch, field of view (FOV), and phantom position for each IRF, comparing them with reference values using filtered back projection (FBP). Furthermore, we evaluated changes in depth dose values due to IRF differences using a solid phantom. In the combinations of changes in IRF and scan parameters the change in CT value (ΔHU) of each material was within ±10 HU, except for most conditions. The change in physical density (ΔPD) was within ±0.02 g/cm for all combinations. For changes in phantom position, ΔHU was within ±25 HU for changes within the scan FOV, except for Bone 200 mg/cc and 1250 mg/cc. In areas outside the scan FOV with an expanded FOV, ΔHU was significantly larger than within the scan FOV. Variations in depth dose for different IRFs using solid phantoms were within ±0.5 %, except at material boundaries. Our evaluations of the CT values and dose calculations suggested no need to change the CT-PD table, even with multiple IRFs. To evaluate the performance of the Aquilion Exceed LB computed tomography (CT) scanner for radiotherapy treatment planning, this study examined the effect of different combinations of the image reconstruction function (IRF) (AiCE and AIDR) and scan parameters on the CT-to-physical density (CT-PD) table and radiation dose in the phantom, and the effect of different object positions on CT values.PURPOSETo evaluate the performance of the Aquilion Exceed LB computed tomography (CT) scanner for radiotherapy treatment planning, this study examined the effect of different combinations of the image reconstruction function (IRF) (AiCE and AIDR) and scan parameters on the CT-to-physical density (CT-PD) table and radiation dose in the phantom, and the effect of different object positions on CT values.To investigate IRF's influence on each material, we calculated CT values by varying tube current, pitch, field of view (FOV), and phantom position for each IRF, comparing them with reference values using filtered back projection (FBP). Furthermore, we evaluated changes in depth dose values due to IRF differences using a solid phantom.METHODSTo investigate IRF's influence on each material, we calculated CT values by varying tube current, pitch, field of view (FOV), and phantom position for each IRF, comparing them with reference values using filtered back projection (FBP). Furthermore, we evaluated changes in depth dose values due to IRF differences using a solid phantom.In the combinations of changes in IRF and scan parameters the change in CT value (ΔHU) of each material was within ±10 HU, except for most conditions. The change in physical density (ΔPD) was within ±0.02 g/cm3 for all combinations. For changes in phantom position, ΔHU was within ±25 HU for changes within the scan FOV, except for Bone 200 mg/cc and 1250 mg/cc. In areas outside the scan FOV with an expanded FOV, ΔHU was significantly larger than within the scan FOV. Variations in depth dose for different IRFs using solid phantoms were within ±0.5 %, except at material boundaries.RESULTSIn the combinations of changes in IRF and scan parameters the change in CT value (ΔHU) of each material was within ±10 HU, except for most conditions. The change in physical density (ΔPD) was within ±0.02 g/cm3 for all combinations. For changes in phantom position, ΔHU was within ±25 HU for changes within the scan FOV, except for Bone 200 mg/cc and 1250 mg/cc. In areas outside the scan FOV with an expanded FOV, ΔHU was significantly larger than within the scan FOV. Variations in depth dose for different IRFs using solid phantoms were within ±0.5 %, except at material boundaries.Our evaluations of the CT values and dose calculations suggested no need to change the CT-PD table, even with multiple IRFs.CONCLUSIONOur evaluations of the CT values and dose calculations suggested no need to change the CT-PD table, even with multiple IRFs. |
| ArticleNumber | 104970 |
| Author | Okumura, Takuro Koganezawa, Akito S. Ochi, Yusuke Murakami, Yuji Tsubouchi, Kento Nakashima, Takeo |
| Author_xml | – sequence: 1 givenname: Takuro orcidid: 0009-0005-7102-328X surname: Okumura fullname: Okumura, Takuro organization: Department of Clinical Practice and Support, Hiroshima University Hospital, Hiroshima 734-8551, Japan – sequence: 2 givenname: Akito S. orcidid: 0000-0002-7823-5884 surname: Koganezawa fullname: Koganezawa, Akito S. email: koganezawa.akito.ow@teikyo-u.ac.jp organization: Department of Information and Electronic Engineering, Faculty of Science and Engineering, Teikyo University, Tochigi 320-8551, Japan – sequence: 3 givenname: Takeo surname: Nakashima fullname: Nakashima, Takeo organization: Department of Clinical Practice and Support, Hiroshima University Hospital, Hiroshima 734-8551, Japan – sequence: 4 givenname: Yusuke surname: Ochi fullname: Ochi, Yusuke organization: Department of Clinical Practice and Support, Hiroshima University Hospital, Hiroshima 734-8551, Japan – sequence: 5 givenname: Kento surname: Tsubouchi fullname: Tsubouchi, Kento organization: Department of Clinical Practice and Support, Hiroshima University Hospital, Hiroshima 734-8551, Japan – sequence: 6 givenname: Yuji orcidid: 0000-0003-3596-3010 surname: Murakami fullname: Murakami, Yuji organization: Department of Radiation Oncology, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima 734-8551, Japan |
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| Keywords | Large-bore CT CT number Dose calculation Treatment planning Image reconstruction algorithm |
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| SubjectTerms | CT number Dose calculation Humans Image Processing, Computer-Assisted - methods Image reconstruction algorithm Large-bore CT Phantoms, Imaging Radiation Dosage Radiotherapy Planning, Computer-Assisted - instrumentation Radiotherapy Planning, Computer-Assisted - methods Tomography, X-Ray Computed - instrumentation Treatment planning |
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