Using the ACR CT accreditation phantom for routine image quality assurance on both CT and CBCT imaging systems in a radiotherapy environment

Hobson, Maritza A.; Soisson, E; Davis, Stephen D.; Parker, William

doi:10.1120/jacmp.v15i4.4835

Cited by 18 publications

(19 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Target detectability of CBCT is a very important image quality metric to achieve a high level of patient positioning and treatment accuracy 10, 11, 12, 13. In spite of the increasing use of CBCT to verify and correct patient setup, the contrast resolution of CBCT in delineating soft tissue structures is lower than that of MDCT 14, 15. MDCT has approximately 3 Hounsfield units (HU) contrast resolution, while CBCT allows a contrast resolution of 10 HU 16.…”

Section: Introductionmentioning

confidence: 99%

Optimizing the target detectability of cone beam CT performed in image‐guided radiation therapy for patients of different body sizes

Yang

Ruan

et al. 2018

J Applied Clin Med Phys

View full text Add to dashboard Cite

PurposeThe target detectability of cone beam computed tomography (CBCT) performed in image‐guided radiation therapy (IGRT) was investigated to achieve sufficient image quality for patient positioning over a course of treatment session while maintaining radiation exposure from CBCT imaging as low as reasonably achievable (ALARA).MethodsBody CBCT scans operated in half‐fan mode were acquired with three different protocols: CBCTlowD, CBCTmidD, and CBCThighD, which resulted in weighted CT dose index (CTDIw) of 0.36, 1.43, and 2.78 cGy, respectively. An electron density phantom that is 18 cm in diameter was covered by four layers of 2.5‐cm‐thick bolus to simulate patients of different body sizes. Multivariate analysis was used to examine the impact of body size, radiation exposure, and tissue type on the target detectability of CBCT imaging, quantified as contrast‐to‐noise ratio (CNR).ResultsCBCTmidD allows sufficient target detection of adipose, breast, muscle, liver in a background of water for normal‐weight adults with cross‐sectional diameter less than 28 cm, while CBCThighD is suitable for adult patients with larger body sizes or body mass index over 25 kg/m2. Once the cross‐sectional diameter of adult patients is larger than 35 cm, the CTDIw of CBCT scans should be higher than 2.78 cGy to achieve required CNR. As for pediatric and adolescent patients with cross‐sectional diameter less than 25 cm, CBCTlowD is able to produce images with sufficient target detection.ConclusionThe target detectability of soft tissues in default CBCT scans may not be sufficient for overweight or obese adults. Contrary, pediatric and adolescent patients would receive unnecessarily high radiation exposure from default CBCT scans. Therefore, the selection of acquisition parameters for CBCT scans optimized according to patient body size was proposed to ensure sufficient image quality for daily patient positioning in radiation therapy while achieving the ALARA principle.

show abstract

Section: Introductionmentioning

confidence: 99%

Optimizing the target detectability of cone beam CT performed in image‐guided radiation therapy for patients of different body sizes

Yang

Ruan

et al. 2018

J Applied Clin Med Phys

View full text Add to dashboard Cite

show abstract

“…Similar to their recommendations for the volume, Hobson et al [16] reported comparative recommendations for CBCT, and state that due to the higher fraction of scatter encountered in cone beam imaging, the center to edge HU variation in reconstructed image slices should be more generous, namely within ±22 HU.…”

Section: Resultsmentioning

confidence: 95%

“…Hobson et al [16], recently published a study using the ACR CT accreditation phantom on CBCT systems, and proposed image quality recommendations for CBCT, after comparing 4 different radiation therapy CBCT devices. The Hobson report states that due to the high variability introduced by x-ray cone beams, the ± 7 HU limit for water is unrealistic, and therefore based on experimental measurements, suggest a range of ±16 HU for water in a reconstructed volume, and ±22 HU variation from center to edge in a coronal slice.…”

Section: Discussionmentioning

confidence: 99%

“…Various manufacturers and other authors have experimentally determined some quality assurance (QA) guidelines and a range of image quality values that CBCT systems can comply with [15–17]. Hobson et al [16] have recently also published similar guidelines for CBCT systems wherein they suggest an acceptable range of ±16 HU for water in a reconstructed volume, and ±22 HU variation from center to edge in a coronal slice. This study aims to characterize the HU values of a dedicated and versatile BCT system and more importantly, tease out acquisition trajectory related differences in HU variability and uniformity for various cylindrical phantoms of different sizes and range of clinically viable breast densities.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Characterization of CT Hounsfield Units for 3D acquisition trajectories on a dedicated breast CT system

Shah

Mann

McKinley

et al. 2018

Journal of X-Ray Science and Technology: Clinical Applications

View full text Add to dashboard Cite

Hounsfield Units (HU) are used clinically in differentiating tissue types in a reconstructed CT image, and therefore the HU accuracy of a system is important, especially when using multiple sources, novel detector and non-traditional trajectories. Dedicated clinical breast CT (BCT) systems therefore should be similarly evaluated. In this study, uniform cylindrical phantoms filled with various uniform density fluids were used to characterize differences in HU values between simple circular and complex 3D (saddle) orbits. Based on ACR recommendations, the HU accuracy, center-to-edge variability within a slice, and overall variability within the reconstructed volume were characterized for simple and complex acquisitions possible on a single versatile BCT system. Results illustrate the statistically significantly better performance of the saddle orbit, especially close to the chest and nipple regions of what would clinically be a pendant breast volume. The incomplete cone beam acquisition of a simple circular orbit causes shading artifacts near the nipple, due to insufficient sampling, rendering a major portion of the scanned phantom unusable, whereas the saddle orbit performs exceptionally well and provides a tighter distribution of HU values throughout the reconstructed volumes. This study further establishes the advantages of using 3D acquisition trajectories for breast CT as well as other applications by demonstrating the robustness of HU values throughout large reconstructed volumes.

show abstract

“…The ACR Accreditation process [32], with modality specific accreditation programs and image review, establishes standards for image quality and also educates facilities on how to improve. There is evidence that there is improved image quality on examinations that follow accreditation specifications and participate in accreditation programs [23][24][25][26][27][28][29][30][31][32][33][34][35]. Site accreditation can provide assurance to patients and referring physicians that their facilities are meeting national requirements for adequacy of personnel, image protocols and image quality.…”

Section: Protocol Selection and Image Acquisitionmentioning

confidence: 99%

Improving diagnosis in health care: perspectives from the American College of Radiology

et al. 2017

View full text Add to dashboard Cite

Abstract:In September of 2014, the American College of Radiology joined a number of other organizations in sponsoring the 2015 National Academy of Medicine report, Improving Diagnosis In Health Care. Our presentation to the Academy emphasized that although diagnostic errors in imaging are commonly considered to result only from failures in disease detection or misinterpretation of a perceived abnormality, most errors in diagnosis result from failures in information gathering, aggregation, dissemination and ultimately integration of that information into our patients' clinical problems. Diagnostic errors can occur at any point on the continuum of imaging care from when imaging is first considered until results and recommendations are fully understood by our referring physicians and patients. We used the concept of the Imaging Value Chain and the ACR's Imaging 3.0 initiative to illustrate how better information gathering and integration at each step in imaging care can mitigate many of the causes of diagnostic errors. Radiologists are in a unique position to be the aggregators, brokers and disseminators of information critical to making an informed diagnosis, and if radiologists were empowered to use our expertise and informatics tools to manage the entire imaging chain, diagnostic errors would be reduced and patient outcomes improved. Heath care teams should take advantage of radiologists' ability to fully manage information related to medical imaging, and simultaneously, radiologists must be ready to meet these new challenges as health care evolves. The radiology community stands ready work with all stakeholders to design and implement solutions that minimize diagnostic errors.

show abstract

Using the ACR CT accreditation phantom for routine image quality assurance on both CT and CBCT imaging systems in a radiotherapy environment

Cited by 18 publications

References 21 publications

Optimizing the target detectability of cone beam CT performed in image‐guided radiation therapy for patients of different body sizes

Optimizing the target detectability of cone beam CT performed in image‐guided radiation therapy for patients of different body sizes

Characterization of CT Hounsfield Units for 3D acquisition trajectories on a dedicated breast CT system

Improving diagnosis in health care: perspectives from the American College of Radiology

Contact Info

Product

Resources

About