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This is a feasibility study investigating the image quality of a new, high-performance cone beam CT (CBCT) used for on-couch imaging during radiotherapy treatments.
This study focuses on potential benefits of a high performance cone beam CT (CBCT) image guidance system for improved precision in the delivery of radiotherapy. CBCT is currently used during radiation therapy to align the patient to their original treatment plan to increase the precision of radiation delivery. Current CBCT imaging technology requires approximately a minute to acquire an image. In order to acquire images with sufficient quality to allow accurate targeting, the patient may need to perform multiple breath hold maneuvers to "freeze" the motion of tumors that move with the breathing cycle (e.g. lung, liver, and breast tumors). The new high-performance CBCT can acquire an image in approximately 6 seconds, potentially enabling acquisition of images with a single breath hold. Improved motion compensation algorithms used in image reconstruction may allow acquisition of good quality images even while a patient is not holding their breath.
The methodology for the subject's treatment setup, CT simulation, treatment planning, image guidance and treatment delivery will be determined by the subject's treatment team and is not specified by this study. Enrollment in the study may occur after treatment delivery has started but must be prior to the fifth fraction.
Following completion of informed consent to participate in this study, high-performance CBCT imaging will be scheduled immediately before or after one of the subject's first five scheduled radiation treatment fractions. Two research CBCT images will be acquired, one with breath hold, the other with free breathing.
With minimal disruption for participating patients, this study will enable a comparison of (i) the subject's treatment planning fan-beam CT and (ii) the conventional CBCT acquired on an existing treatment unit with (iii) the high-performance CBCT. Image quality of the high performance CBCT image data will thereby be compared to both a best-case standard (fan-beam) and the status-quo for on-couch imaging to isolate and identify improvements.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| High-performance CBCT imaging | Experimental | Two additional study imaging sets are acquired. |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| CBCT Imaging | Device | Two research CBCT images will be acquired per subject. |
|
| Measure | Description | Time Frame |
|---|---|---|
| CBCT Image Quality - Artifact Index | Artifact Index (AI) is a measurement of the strength of imaging artifact and the degree to which is affects visibility of anatomical structures in the vicinity of the artifact. Artifacts can be produced in CT and CBCT images by a number of factors, such as metal implants, gas, or breathing motion. AI = sqrt((STD_VOI)^2 - (STD_background)^2), where STD_VOI is the standard deviation of the image Hounsfield Units in a region of interest at the location of an artifact, and STD_background is the standard deviation of the Hounsfield Unit values in the background (i.e. in similar tissue but away from the artifact. A lower AI value indicates that the artifact has a lower impact on image quality. Artifacts were identified in all study participants. The median AI across the study population is presented for four imaging modalities. | 1 day |
| CBCT Image Quality - Image Nonuniformity | Nonuniformity (NU) is a measure of the variation of CT image intensity in uniform tissue. NU = (HU_max - HU_min)/(HU_max + HU_min), where HU_max and HU_min are the maximum and minimum Hounsfield Unit values among multiple locations sampled within regions of uniform tissue that were relevant to the anatomy of interest (e.g., a uniform region of breast tissue for patients undergoing breast treatments). A lower NU represents greater uniformity of CT image intensity within a region of interest. Median NU across the study population is presented for four imaging modalities. | 1 day |
| CBCT Image Quality - Contrast | Contrast represents the ability to distinguish between two different regions in a CT image (e.g. to distinguish between two adjacent organs). Contrast = |HU1 - HU2| where HU1 and HU2 are the mean HU values in two different 100 mm^2 ROIs, where the ROIs were located in two different tissue types that were relevant to the site being treated (e.g., in the liver and in perihepatic fat for liver treatments). Higher contrast values indicate that it is easier to distinguish between regions (anatomical structures) in a CT image. Median contrast across the study population is presented for four imaging modalities. | 1 week |
| Measure | Description | Time Frame |
|---|---|---|
| Dosimetry Calculations - Gamma Pass Rate | Every trial participant had a radiation treatment plan calculated on their CT simulation image series. That same plan was then re-calculated on both the breath hold high-performance CBCT and conventional CBCT. The overall difference between calculated radiation distributions was evaluated using three different gamma pass criteria: 3% dose difference / 3 mm distance to agreement, 2%/2mm, and 1%/1mm. The gamma pass rate is expressed as a percentage of data points that meet the pass criteria. A gamma pass rate of > 95% is typically considered acceptable for 3%/3mm. As the gamma pass criteria become stricter, the pass rates decrease. Gamma pass rates were calculated to compare the CT simulation-based dose calculation and the high performance CBCT-based dose calculation. Gamma pass rates were also calculated to compare the CT simulation-based dose calculation and the conventional CBCT-based dose calculation. The median gamma pass rates across the entire study population are presented. |
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Inclusion Criteria:
Exclusion Criteria:
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Nova Scotia Health (QEII) | Halifax | Nova Scotia | B3H 2E2 | Canada |
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Patients who withdraw consent, who are removed from the study by the investigator, or who otherwise end their participation in the study prior to the acquisition of any study imaging could be replaced.
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| ID | Title | Description |
|---|---|---|
| FG000 | High-performance CBCT Imaging | Two additional study imaging sets are acquired. CBCT Imaging: Two research CBCT images will be acquired per subject. |
| Title | Milestones | Reasons Not Completed | ||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Overall Study |
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| ID | Title | Description |
|---|---|---|
| BG000 | High-performance CBCT Imaging | Two additional study imaging sets are acquired. CBCT Imaging: Two research CBCT images will be acquired per subject. |
| Units | Counts |
|---|---|
| Participants |
|
| Title | Description | Population Description | Parameter Type | Dispersion Type | Unit of Measure | Calculate Percentage | Denominator Units Selected | Denominators | Classes |
|---|---|---|---|---|---|---|---|---|---|
| Age, Continuous | Age on the date of consent for study participation |
| Type | Title | Description | Population Description | Reporting Status | Anticipated Posting Date | Parameter Type | Dispersion Type | Unit of Measure | Calculate Percentage | Time Frame | Units Analyzed | Denominator Units Selected | Arm/Group Information | Denominators | Classes | Analyses | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Primary | CBCT Image Quality - Artifact Index | Artifact Index (AI) is a measurement of the strength of imaging artifact and the degree to which is affects visibility of anatomical structures in the vicinity of the artifact. Artifacts can be produced in CT and CBCT images by a number of factors, such as metal implants, gas, or breathing motion. AI = sqrt((STD_VOI)^2 - (STD_background)^2), where STD_VOI is the standard deviation of the image Hounsfield Units in a region of interest at the location of an artifact, and STD_background is the standard deviation of the Hounsfield Unit values in the background (i.e. in similar tissue but away from the artifact. A lower AI value indicates that the artifact has a lower impact on image quality. Artifacts were identified in all study participants. The median AI across the study population is presented for four imaging modalities. | All study participants for whom at least one high-performance CBCT was acquired. | Posted | Median | Inter-Quartile Range | HU | 1 day |
|
1 week
All adverse events, including both Serious and Other (Not Including Serious) Adverse Events that could possibly, probably, or definitely be attributed to the high-performance CBCT imaging were recorded in the study database and reported here. Adverse Events (including Serious Adverse Events) related to a subject's cancer treatment are not reported here.
The All Cause Mortality reported here represents all causes of mortality during study participation, not just high-performance CBCT imaging.
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| ID | Title | Description | Deaths (Affected) | Deaths (At Risk) | Serious Events (Affected) | Serious Events (At Risk) | Other Events (Affected) | Other Events (At Risk) |
|---|---|---|---|---|---|---|---|---|
| EG000 | High-performance CBCT Imaging | Two additional study imaging sets are acquired. CBCT Imaging: Two research CBCT images will be acquired per subject. |
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| Title | Organization | Phone | Extension | |
|---|---|---|---|---|
| Sean Davidson | Varian Medical Systems | 14379918294 | sean.davidson@varian.com |
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| Type | Includes Protocol | Includes SAP | Includes ICF | Document Label | Document Date | Document Uploaded Date | Document File Name |
|---|---|---|---|---|---|---|---|
| Prot_SAP | Yes | Yes | No | Study Protocol and Statistical Analysis Plan | Jan 24, 2022 | Apr 1, 2026 | Prot_SAP_001.pdf |
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| ID | Term |
|---|---|
| D008175 | Lung Neoplasms |
| D008113 | Liver Neoplasms |
| D001943 | Breast Neoplasms |
| ID | Term |
|---|---|
| D012142 | Respiratory Tract Neoplasms |
| D013899 | Thoracic Neoplasms |
| D009371 | Neoplasms by Site |
| D009369 | Neoplasms |
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This is a single-site study designed to generate data describing the quality and applicability of on-couch high-performance CBCT imaging for anatomy visualization and radiation treatment dosimetry planning.
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| CBCT Image Quality - Contrast to Noise Ratio | Contrast to Noise Ratio (CNR) measures the ability to distinguish an object or lesion from its background. CNR = |HU1 - HU2|/[0.5 (STD1 + STD2)] where HU1 and HU2 are the mean Hounsfield Unit values in two different 100 mm^2 ROIs, where the ROIs were located in two different tissue types that were relevant to the site being treated (e.g., in the liver and in perihepatic fat for liver treatments), and STD1 and STD2 are the standard deviations of the HU values in those same ROIs. A higher CNR makes it easier to distinguish an object from its background. CNR analysis was limited to images with similar imaging dose. Median CNR across all study participants treated for lung cancer are presented for three CBCT modalities. | 1 week |
| CBCT Image Quality - HU Similarity to CT Simulation | The intensity of a pixel in a CT image is a function of its Hounsfield Unit (HU) value. HU is also directly related to the underlying electron density, which means that the pixel value of a CT image can be used directly in the calculation of dose for a prescribed radiation treatment plan. CT simulation scanners produce images with high HU accuracy and are regularly used for radiation treatment planning. Here, we present the difference in HU between CT simulation images and different CBCT images. ΔHU = HU_CBCT - HU_CTSim, where HU_CBCT and HU_CTSim are mean values among HU averages at 4 reference points in a CBCT image and the corresponding CT simulation image, respectively. The lower the ΔHU, the greater the HU accuracy of the CBCT image, and the greater the likelihood that CBCT imaging can be used for radiation treatment planning. Median ΔHU across the study population are presented for three different tissue types for three CBCT imaging modalities. | 1 week |
| 1 day |
| Dosimetry Calculations - Target DVH Volume Metrics | Every trial participant had a radiation treatment plan calculated on their CT simulation image series. That same plan was then re-calculated on both the breath hold high-performance CBCT and conventional CBCT. Dose-volume histograms (DVH) were calculated for individual target structures from all three dose distributions. Individual DVH metrics, such as V90(%) (the percentage of the structure volume receiving 90% of the prescribed radiation dose) were extracted for individual target structures from their DVH. The difference between a DVH metric derived from CT simulation-based dose calculation and the same metric derived from a CBCT-based dose calculation are reported. The smaller the difference, the greater the accuracy of the CBCT-based dose calculation. Median target DVH metric differences across the study population are presented. | 1 day |
| Dosimetry Calculations - Target DVH Dose Metrics | Every trial participant had a radiation treatment plan calculated on their CT simulation image series. That same plan was then re-calculated on both the breath hold high-performance CBCT and conventional CBCT. Dose-volume histograms (DVH) were calculated for individual target structures from all three dose distributions. Individual DVH dose metrics, such as D95(%) (the minimum dose covering 95% of the structure, expressed as a % of the prescription dose) were extracted for individual target structures from their DVH. The difference between a DVH metric derived from CT simulation-based dose calculation and the same metric derived from a CBCT-based dose calculation are reported. The smaller the difference, the greater the accuracy of the CBCT-based dose calculation. Median target DVH metric differences across the study population are presented. | 1 day |
| Dosimetry Calculations - Breast OAR DVH Metrics | Every trial participant had a radiation treatment plan calculated on their CT simulation image series. That same plan was then re-calculated on both the breath hold high-performance CBCT and conventional CBCT. Dose-volume histograms (DVH) were calculated for individual organs at risk (OAR) from all three dose distributions. The key organs at risk for patients being treated for breast cancer are the heart, ipsilateral lung, and contralateral breast. The differences between the D2%(%) (minimum dose received by the "hottest" 2% of the OAR, expressed as a % of the prescription dose) derived from CT simulation-based dose calculation and the same metric derived from a CBCT-based dose calculation are reported. The smaller the difference, the greater the accuracy of the CBCT-based dose calculation. Median differences in OAR D2%(%) across study participants treated for breast cancer are presented. | 1 day |
| Dosimetry Calculations - Lung OAR DVH Metrics | Every trial participant had a radiation treatment plan calculated on their CT simulation image series. That same plan was then re-calculated on both the breath hold high-performance CBCT and conventional CBCT. Dose-volume histograms (DVH) were calculated for individual organs at risk (OAR) from all three dose distributions. The key organs at risk for patients being treated for lung cancer are the heart, esophagus and spinal cord. The differences between the D2%(%) (minimum dose received by the "hottest" 2% of the OAR, expressed as a % of the prescription dose) derived from CT simulation-based dose calculation and the same metric derived from a CBCT-based dose calculation are reported. The smaller the difference, the greater the accuracy of the CBCT-based dose calculation. Median differences in OAR D2%(%) across study participants treated for lung cancer are presented. | 1 day |
| Dosimetry Calculations - Abdomen OAR DVH Metrics | Every trial participant had a radiation treatment plan calculated on their CT simulation image series. That same plan was then re-calculated on both the breath hold high-performance CBCT and conventional CBCT. Dose-volume histograms (DVH) were calculated for individual organs at risk (OAR) from all three dose distributions. The key organs at risk for patients being treated for abdominal cancer are the heart, bowel and kidneys. The differences between the D2%(%) (minimum dose received by the "hottest" 2% of the OAR, expressed as a % of the prescription dose) derived from CT simulation-based dose calculation and the same metric derived from a CBCT-based dose calculation are reported. The smaller the difference, the greater the accuracy of the CBCT-based dose calculation. Median differences in OAR D2%(%) across study participants treated for abdominal cancer are presented. | 1 day |
| Median |
| Standard Deviation |
| years |
|
| Sex: Female, Male | Count of Participants | Participants |
|
| Race and Ethnicity Not Collected | Race and Ethnicity were not collected from any participant. | Count of Participants | Participants |
|
| BMI | Body Mass Index | Mean | Full Range | kg/m^2 |
|
| Breath Hold High Performance CBCT |
High-Performance CBCT acquired under breath hold conditions. |
| OG001 | Free Breathing High Performance CBCT | High Performance CBCT acquired under free breathing conditions. |
| OG002 | Conventional CBCT | Conventional CBCT acquired under breath hold conditions. |
| OG003 | CT Simulation | Fan-beam CT acquired under breath hold conditions for the purpose of treatment simulation. |
|
|
| Primary | CBCT Image Quality - Image Nonuniformity | Nonuniformity (NU) is a measure of the variation of CT image intensity in uniform tissue. NU = (HU_max - HU_min)/(HU_max + HU_min), where HU_max and HU_min are the maximum and minimum Hounsfield Unit values among multiple locations sampled within regions of uniform tissue that were relevant to the anatomy of interest (e.g., a uniform region of breast tissue for patients undergoing breast treatments). A lower NU represents greater uniformity of CT image intensity within a region of interest. Median NU across the study population is presented for four imaging modalities. | All subjects for whom a high-performance CBCT was acquired. | Posted | Median | Inter-Quartile Range | ratio | 1 day |
|
|
|
| Primary | CBCT Image Quality - Contrast | Contrast represents the ability to distinguish between two different regions in a CT image (e.g. to distinguish between two adjacent organs). Contrast = |HU1 - HU2| where HU1 and HU2 are the mean HU values in two different 100 mm^2 ROIs, where the ROIs were located in two different tissue types that were relevant to the site being treated (e.g., in the liver and in perihepatic fat for liver treatments). Higher contrast values indicate that it is easier to distinguish between regions (anatomical structures) in a CT image. Median contrast across the study population is presented for four imaging modalities. | All subjects for whom high performance CBCT imaging was acquired. | Posted | Median | Inter-Quartile Range | HU | 1 week |
|
|
|
| Primary | CBCT Image Quality - Contrast to Noise Ratio | Contrast to Noise Ratio (CNR) measures the ability to distinguish an object or lesion from its background. CNR = |HU1 - HU2|/[0.5 (STD1 + STD2)] where HU1 and HU2 are the mean Hounsfield Unit values in two different 100 mm^2 ROIs, where the ROIs were located in two different tissue types that were relevant to the site being treated (e.g., in the liver and in perihepatic fat for liver treatments), and STD1 and STD2 are the standard deviations of the HU values in those same ROIs. A higher CNR makes it easier to distinguish an object from its background. CNR analysis was limited to images with similar imaging dose. Median CNR across all study participants treated for lung cancer are presented for three CBCT modalities. | This analysis was limited to patients being treated for lung CBCT since it is only with the thorax CBCT imaging modes that the imaging doses were matched, which is required for a fair comparison of CNR. | Posted | Median | Inter-Quartile Range | ratio | 1 week |
|
|
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| Primary | CBCT Image Quality - HU Similarity to CT Simulation | The intensity of a pixel in a CT image is a function of its Hounsfield Unit (HU) value. HU is also directly related to the underlying electron density, which means that the pixel value of a CT image can be used directly in the calculation of dose for a prescribed radiation treatment plan. CT simulation scanners produce images with high HU accuracy and are regularly used for radiation treatment planning. Here, we present the difference in HU between CT simulation images and different CBCT images. ΔHU = HU_CBCT - HU_CTSim, where HU_CBCT and HU_CTSim are mean values among HU averages at 4 reference points in a CBCT image and the corresponding CT simulation image, respectively. The lower the ΔHU, the greater the HU accuracy of the CBCT image, and the greater the likelihood that CBCT imaging can be used for radiation treatment planning. Median ΔHU across the study population are presented for three different tissue types for three CBCT imaging modalities. | Posted | Median | Inter-Quartile Range | HU | 1 week |
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|
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| Secondary | Dosimetry Calculations - Gamma Pass Rate | Every trial participant had a radiation treatment plan calculated on their CT simulation image series. That same plan was then re-calculated on both the breath hold high-performance CBCT and conventional CBCT. The overall difference between calculated radiation distributions was evaluated using three different gamma pass criteria: 3% dose difference / 3 mm distance to agreement, 2%/2mm, and 1%/1mm. The gamma pass rate is expressed as a percentage of data points that meet the pass criteria. A gamma pass rate of > 95% is typically considered acceptable for 3%/3mm. As the gamma pass criteria become stricter, the pass rates decrease. Gamma pass rates were calculated to compare the CT simulation-based dose calculation and the high performance CBCT-based dose calculation. Gamma pass rates were also calculated to compare the CT simulation-based dose calculation and the conventional CBCT-based dose calculation. The median gamma pass rates across the entire study population are presented. | Posted | Median | Standard Deviation | percentage | 1 day |
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|
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| Secondary | Dosimetry Calculations - Target DVH Volume Metrics | Every trial participant had a radiation treatment plan calculated on their CT simulation image series. That same plan was then re-calculated on both the breath hold high-performance CBCT and conventional CBCT. Dose-volume histograms (DVH) were calculated for individual target structures from all three dose distributions. Individual DVH metrics, such as V90(%) (the percentage of the structure volume receiving 90% of the prescribed radiation dose) were extracted for individual target structures from their DVH. The difference between a DVH metric derived from CT simulation-based dose calculation and the same metric derived from a CBCT-based dose calculation are reported. The smaller the difference, the greater the accuracy of the CBCT-based dose calculation. Median target DVH metric differences across the study population are presented. | Posted | Median | Inter-Quartile Range | % target volume (Vxx) | 1 day |
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| Secondary | Dosimetry Calculations - Target DVH Dose Metrics | Every trial participant had a radiation treatment plan calculated on their CT simulation image series. That same plan was then re-calculated on both the breath hold high-performance CBCT and conventional CBCT. Dose-volume histograms (DVH) were calculated for individual target structures from all three dose distributions. Individual DVH dose metrics, such as D95(%) (the minimum dose covering 95% of the structure, expressed as a % of the prescription dose) were extracted for individual target structures from their DVH. The difference between a DVH metric derived from CT simulation-based dose calculation and the same metric derived from a CBCT-based dose calculation are reported. The smaller the difference, the greater the accuracy of the CBCT-based dose calculation. Median target DVH metric differences across the study population are presented. | Posted | Median | Inter-Quartile Range | % prescription dose (Dxx) | 1 day |
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| Secondary | Dosimetry Calculations - Breast OAR DVH Metrics | Every trial participant had a radiation treatment plan calculated on their CT simulation image series. That same plan was then re-calculated on both the breath hold high-performance CBCT and conventional CBCT. Dose-volume histograms (DVH) were calculated for individual organs at risk (OAR) from all three dose distributions. The key organs at risk for patients being treated for breast cancer are the heart, ipsilateral lung, and contralateral breast. The differences between the D2%(%) (minimum dose received by the "hottest" 2% of the OAR, expressed as a % of the prescription dose) derived from CT simulation-based dose calculation and the same metric derived from a CBCT-based dose calculation are reported. The smaller the difference, the greater the accuracy of the CBCT-based dose calculation. Median differences in OAR D2%(%) across study participants treated for breast cancer are presented. | Of the total study population, nine participants were treated for cancer in the left breast. | Posted | Median | Inter-Quartile Range | % dose | 1 day |
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| Secondary | Dosimetry Calculations - Lung OAR DVH Metrics | Every trial participant had a radiation treatment plan calculated on their CT simulation image series. That same plan was then re-calculated on both the breath hold high-performance CBCT and conventional CBCT. Dose-volume histograms (DVH) were calculated for individual organs at risk (OAR) from all three dose distributions. The key organs at risk for patients being treated for lung cancer are the heart, esophagus and spinal cord. The differences between the D2%(%) (minimum dose received by the "hottest" 2% of the OAR, expressed as a % of the prescription dose) derived from CT simulation-based dose calculation and the same metric derived from a CBCT-based dose calculation are reported. The smaller the difference, the greater the accuracy of the CBCT-based dose calculation. Median differences in OAR D2%(%) across study participants treated for lung cancer are presented. | Of the total study population, ten participants were treated for lung cancer. | Posted | Median | Inter-Quartile Range | % dose | 1 day |
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| Secondary | Dosimetry Calculations - Abdomen OAR DVH Metrics | Every trial participant had a radiation treatment plan calculated on their CT simulation image series. That same plan was then re-calculated on both the breath hold high-performance CBCT and conventional CBCT. Dose-volume histograms (DVH) were calculated for individual organs at risk (OAR) from all three dose distributions. The key organs at risk for patients being treated for abdominal cancer are the heart, bowel and kidneys. The differences between the D2%(%) (minimum dose received by the "hottest" 2% of the OAR, expressed as a % of the prescription dose) derived from CT simulation-based dose calculation and the same metric derived from a CBCT-based dose calculation are reported. The smaller the difference, the greater the accuracy of the CBCT-based dose calculation. Median differences in OAR D2%(%) across study participants treated for abdominal cancer are presented. | Of the total study population, ten participants were treated for cancer in the abdomen (primarily for liver cancer, but also pancreas and other sub-sites). | Posted | Median | Inter-Quartile Range | % dose | 1 day |
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| 0 |
| 30 |
| 0 |
| 30 |
| 0 |
| 30 |
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| D008171 |
| Lung Diseases |
| D012140 | Respiratory Tract Diseases |
| D004067 | Digestive System Neoplasms |
| D004066 | Digestive System Diseases |
| D008107 | Liver Diseases |
| D001941 | Breast Diseases |
| D012871 | Skin Diseases |
| D017437 | Skin and Connective Tissue Diseases |
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| Tissue |
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| 1%/1mm |
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| V100(%) |
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| V105(%) |
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| D99(%) |
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| Dmax(%) |
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| Contralateral breast D2%(%) |
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| Spinal cord D2%(%) |
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| Kidneys D2%(%) |
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