Quality assurance for image‐guided radiation therapy utilizing CT‐based technologies: A report of the AAPM TG‐179

Bissonnette, Jean Pierre; Balter, Peter A; Dong, Lei; Langen, K; Lovelock, D. Michael; Miften, Moyed; Moseley, D; Pouliot, Jean; Sonke, Jan‐Jakob; Yoo, Sua

doi:10.1118/1.3690466

Cited by 271 publications

(267 citation statements)

References 201 publications

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“…The same is placed at the physical isocenter. A specific displacement of the couch from isocenter using a random number generator is applied (the movement in all axis is within 2 cm to be in agreement with TG‐179 (2) ). Then, a localization CBCT image dataset to assess the couch motion required to align the phantom with a reference CT dataset is acquired.…”

Section: Methodsmentioning

confidence: 96%

“…

Test 1: Imaging and treatment coordinate coincidence. After the initial geometric calibration has been performed using procedures similar to that described by Bissonnette et al, (2) a daily geometric accuracy QA consists of stability and consistency tests is performed. The MIMI phantom (Standard Imaging Inc., Middleton WI), which has embedded BBs, was used to take portal images and CBCT, and the positions of the embedded BBs on these daily images as compared to the base line were used to verify the imager's consistency.

Test 2: Couch position and repositioning.

…”

Section: Methodsmentioning

confidence: 99%

“…Flat‐panel detectors have also increasingly been used for dosimetric applications. Task Group 179 and the AAPM Medical Physics Practice Guideline 2.a provide consensus recommendations for the quality assurance protocols of the imaging system of these linacs, especially those dedicated to image‐guided radiation therapy (IGRT) 1 , 2 . For daily QA, tests to verify the imaging and radiation isocenter agreement, as well as the accuracy of the couch positioning and repositioning, are emphasized.…”

Section: Introductionmentioning

confidence: 99%

“…For monthly QA, more comprehensive tests are proposed where not only agreement between the imaging and radiation isocenter, as well as the couch position and repositioning accuracy, are verified, but also extensive image quality tests and geometry calibration. These tests add between 3 to 5 hrs of extra monthly QA, according to TG‐179 and AAPM Medical Physics Practice Guideline 2.a 1 , 2 . Several efforts have been made to simplify the complexity of these tests.…”

Section: Introductionmentioning

confidence: 99%

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Use of TrueBeam developer mode for imaging QA

Valdés

Morin

Valenciaga

et al. 2015

J Applied Clin Med Phys

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The purpose of this study was to automate regular Imaging QA procedures to become more efficient and accurate. Daily and monthly imaging QA for SRS and SBRT protocols were fully automated on a Varian linac. A three‐step paradigm where the data are automatically acquired, processed, and analyzed was defined. XML scripts were written and used in developer mode in a TrueBeam linac to automatically acquire data. MATLAB R013B was used to develop an interface that could allow the data to be processed and analyzed. Hardware was developed that allowed the localization of several phantoms simultaneously on the couch. 14 KV CBCTs from the Emma phantom were obtained using a TrueBeam onboard imager as example of data acquisition and analysis. The images were acquired during two months. Artifacts were artificially introduced in the images during the reconstruction process using iTool reconstructor. Support vector machine algorithms to automatically identify each artifact were written using the Machine Learning MATLAB R2011 Toolbox. A daily imaging QA test could be performed by an experienced medical physicist in 14.3±2.4 min. The same test, if automated using our paradigm, could be performed in 4.2±0.7 min. In the same manner, a monthly imaging QA could be performed by a physicist in 70.7±8.0 min and, if fully automated, in 21.8±0.6 min. Additionally, quantitative data analysis could be automatically performed by Machine Learning Algorithms that could remove the subjectivity of data interpretation in the QA process. For instance, support vector machine algorithms could correctly identify beam hardening, rings and scatter artifacts. Traditional metrics, as well as metrics that describe texture, are needed for the classification. Modern linear accelerators are equipped with advanced 2D and 3D imaging capabilities that are used for patient alignment, substantially improving IGRT treatment accuracy. However, this extra complexity exponentially increases the number of QA tests needed. Using the new paradigm described above, not only the bare minimum — but also best practice — QA programs could be implemented with the same manpower.PACS number: 87, 87.10.‐e

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Section: Methodsmentioning

confidence: 96%

“…

Test 2: Couch position and repositioning.

…”

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Use of TrueBeam developer mode for imaging QA

Valdés

Morin

Valenciaga

et al. 2015

J Applied Clin Med Phys

Self Cite

View full text Add to dashboard Cite

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“…Recommendations for IGRT system QA are provided in AAPM TG‐179 report 4. This includes the recommendation for testing the imaging and treatment isocenters coincidence.…”

Section: Introductionmentioning

confidence: 99%

Beam focal spot position: The forgotten linac QA parameter. An EPID‐based phantomless method for routine Stereotactic linac QA

Chojnowski

Barnes

Sykes

et al. 2017

J Applied Clin Med Phys

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Modern day Stereotactic treatments require high geometric accuracy of the delivered treatment. To achieve the required accuracy the IGRT imaging isocenter needs to closely coincide with the treatment beam isocenter. An influence on this isocenter coincidence and on the spatial positioning of the beam itself is the alignment of the treatment beam focal spot with collimator rotation axis. The positioning of the focal spot is dependent on the linac beam steering and on the stability of the monitor chamber and beam steering servo system. As such, there is the potential for focal spot misalignment and this should be checked on a regular basis. Traditional methods for measuring focal spot position are either indirect, inaccurate, or time consuming and hence impractical for routine use. In this study a novel, phantomless method has been developed using the EPID (Electronic Portal Imaging Device) that utilizes the different heights of the MLC and jaws. The method has been performed on four linear accelerators and benchmarked against an alternate ion chamber‐based method. The method has been found to be reproducible to within ±0.012 mm (1 SD) and in agreement with the ion chamber‐based method to within 0.001 ± 0.015 mm (1 SD). The method could easily be incorporated into a departmental routine linac QA (Quality Assurance) program.

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Image guidance in radiation therapy for better cure of cancer

Grégoire

Gückenberger

Haustermans³

et al. 2020

Molecular Oncology

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The key goal and main challenge of radiation therapy is the elimination of tumors without any concurring damages of the surrounding healthy tissues and organs. Radiation doses required to achieve sufficient cancer‐cell kill exceed in most clinical situations the dose that can be tolerated by the healthy tissues, especially when large parts of the affected organ are irradiated. High‐precision radiation oncology aims at optimizing tumor coverage, while sparing normal tissues. Medical imaging during the preparation phase, as well as in the treatment room for localization of the tumor and directing the beam, referred to as image‐guided radiotherapy (IGRT), is the cornerstone of precision radiation oncology. Sophisticated high‐resolution real‐time IGRT using X‐rays, computer tomography, magnetic resonance imaging, or ultrasound, enables delivery of high radiation doses to tumors without significant damage of healthy organs. IGRT is the most convincing success story of radiation oncology over the last decades, and it remains a major driving force of innovation, contributing to the development of personalized oncology, for example, through the use of real‐time imaging biomarkers for individualized dose delivery.

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Quality assurance for image‐guided radiation therapy utilizing CT‐based technologies: A report of the AAPM TG‐179

Abstract: A program for quality control of CT-based image-guidance systems has been produced, with focus on geometry, image quality, image dose, system operation, and safety. Agreement and clarification with respect to reports from the AAPM TG-101, TG-104, TG-142, and TG-148 has been addressed.

Cited by 271 publications

References 201 publications

Use of TrueBeam developer mode for imaging QA

Use of TrueBeam developer mode for imaging QA

Beam focal spot position: The forgotten linac QA parameter. An EPID‐based phantomless method for routine Stereotactic linac QA

Image guidance in radiation therapy for better cure of cancer

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