Evaluation of Novel Cone-Beam CT for Guidance and Adaptation of Precision Radiotherapy

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.

Study Overview

• Status: Completed
• Conditions: Breast Cancer; Lung Cancer; Liver Cancer; Other Cancer
• Intervention / Treatment: Device: CBCT Imaging

Detailed Description

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.

• Study Type: Interventional
• Enrollment (Actual): 31
• Phase: Not Applicable

Contacts and Locations

Study Locations

• Canada
  • Nova Scotia
    • Halifax, Nova Scotia, Canada, B3H 2E2
      • Nova Scotia Health (QEII)

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 19 years and older (Adult, Older Adult)
• Accepts Healthy Volunteers: No

Description

Inclusion Criteria:

• Subject is scheduled for treatment on one of the five TrueBeam platforms at the NS Health QE2 site.
• Subject is receiving radiation therapy using a breath-hold technique (for example, lung, liver and left breast cancers).

Exclusion Criteria:

• Patient is pregnant or has plans for pregnancy during the period of treatment.
• Patient is unwilling to consent to participating to the study, or for whom informed consent is not possible.

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Other
• Allocation: N/A
• Interventional Model: Single Group Assignment
• Masking: None (Open Label)

Number of Arms

1

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Experimental: High-performance CBCT imaging; Two additional study imaging sets are acquired.	Device: CBCT Imaging; Two research CBCT images will be acquired per subject.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	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
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

Secondary Outcome Measures

Outcome Measure	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.	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

Collaborators and Investigators

• Sponsor: Varian, a Siemens Healthineers Company

Study record dates

Study Major Dates

• Study Start (Actual): December 20, 2022
• Primary Completion (Actual): July 30, 2023
• Study Completion (Actual): July 30, 2023

Study Registration Dates

• First Submitted: December 16, 2021
• First Submitted That Met QC Criteria: December 16, 2021
• First Posted (Actual): January 4, 2022

Study Record Updates

• Last Update Posted (Actual): May 6, 2026
• Last Update Submitted That Met QC Criteria: April 15, 2026
• Last Verified: April 1, 2026

More Information

Terms related to this study

• Additional Relevant MeSH Terms: Neoplasms by Site; Neoplasms; Respiratory Tract Diseases; Digestive System Neoplasms; Digestive System Diseases; Lung Diseases; Liver Diseases; Respiratory Tract Neoplasms; Thoracic Neoplasms; Skin Diseases; Breast Diseases; Skin and Connective Tissue Diseases; Lung Neoplasms; Breast Neoplasms; Liver Neoplasms
• Other Study ID Numbers: VAR-2021-12

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: Yes
• product manufactured in and exported from the U.S.: Yes