Operational Ontology for Oncology (O3): A Professional Society-Based, Multistakeholder, Consensus-Driven Informatics Standard Supporting Clinical and Research Use of Real-World Data From Patients Treated for Cancer.

PURPOSE: The ongoing lack of data standardization severely undermines the potential for automated learning from the vast amount of information routinely archived in electronic health records (EHRs), radiation oncology information systems, treatment planning systems, and other cancer care and outcomes databases. We sought to create a standardized ontology for clinical data, social determinants of health, and other radiation oncology concepts and interrelationships. METHODS AND MATERIALS: The American Association of Physicists in Medicine's Big Data Science Committee was initiated in July 2019 to explore common ground from the stakeholders' collective experience of issues that typically compromise the formation of large inter- and intra-institutional databases from EHRs. The Big Data Science Committee adopted an iterative, cyclical approach to engaging stakeholders beyond its membership to optimize the integration of diverse perspectives from the community. RESULTS: We developed the Operational Ontology for Oncology (O3), which identified 42 key elements, 359 attributes, 144 value sets, and 155 relationships ranked in relative importance of clinical significance, likelihood of availability in EHRs, and the ability to modify routine clinical processes to permit aggregation. Recommendations are provided for best use and development of the O3 to 4 constituencies: device manufacturers, centers of clinical care, researchers, and professional societies. CONCLUSIONS: O3 is designed to extend and interoperate with existing global infrastructure and data science standards. The implementation of these recommendations will lower the barriers for aggregation of information that could be used to create large, representative, findable, accessible, interoperable, and reusable data sets to support the scientific objectives of grant programs. The construction of comprehensive "real-world" data sets and application of advanced analytical techniques, including artificial intelligence, holds the potential to revolutionize patient management and improve outcomes by leveraging increased access to information derived from larger, more representative data sets.

Quality and Safety With Technological Advancements in Radiotherapy: An Overview and Journey Narrative From a Low- and Middle-Income Country Institution.

PURPOSE: To present an overview of quality and safety in radiotherapy from the context of low- and middle-income countries on the basis of a recently conducted annual meeting of our institution and our experience of implementing an error management system at our center. METHODS: The minutes of recently concluded annual Evidence-Based Medicine (EBM-2021) meeting on the basis of technology in radiation oncology were reviewed. The session on quality and safety, which had international experts as speakers, was reviewed. Along with this, we reviewed the literature for preventive and reactive measures proposed to manage errors including error reporting and learning systems (ILSs). Concise summary for the same was prepared for this article. RESULTS: We also reviewed the journey of development of our institutional ILS and present here a summary of achievements, challenges, and future vision. CONCLUSION: Preventive and reactive measures must be followed to achieve high-quality and safe radiotherapy. Despite resource constraints, a successful ILS program can be developed in a low- and middle-income country center by first understanding the patterns of error and developing one that suits the working ecosystem.

Automated data abstraction for quality surveillance and outcome assessment in radiation oncology.

Rigorous radiotherapy quality surveillance and comprehensive outcome assessment require electronic capture and automatic abstraction of clinical, radiation treatment planning, and delivery data. We present the design and implementation framework of an integrated data abstraction, aggregation, and storage, curation, and analytics software: the Health Information Gateway and Exchange (HINGE), which collates data for cancer patients receiving radiotherapy. The HINGE software abstracts structured DICOM-RT data from the treatment planning system (TPS), treatment data from the treatment management system (TMS), and clinical data from the electronic health records (EHRs). HINGE software has disease site-specific "Smart" templates that facilitate the entry of relevant clinical information by physicians and clinical staff in a discrete manner as part of the routine clinical documentation. Radiotherapy data abstracted from these disparate sources and the smart templates are processed for quality and outcome assessment. The predictive data analyses are done on using well-defined clinical and dosimetry quality measures defined by disease site experts in radiation oncology. HINGE application software connects seamlessly to the local IT/medical infrastructure via interfaces and cloud services and performs data extraction and aggregation functions without human intervention. It provides tools to assess variations in radiation oncology practices and outcomes and determines gaps in radiotherapy quality delivered by each provider.

VA-Radiation Oncology Quality Surveillance Program.

PURPOSE: We sought to develop a quality surveillance program for approximately 15,000 US veterans treated at the 40 radiation oncology facilities at the Veterans Affairs (VA) hospitals each year. METHODS AND MATERIALS: State-of-the-art technologies were used with the goal to improve clinical outcomes while providing the best possible care to veterans. To measure quality of care and service rendered to veterans, the Veterans Health Administration established the VA Radiation Oncology Quality Surveillance program. The program carries forward the American College of Radiology Quality Research in Radiation Oncology project methodology of assessing the wide variation in practice pattern and quality of care in radiation therapy by developing clinical quality measures (QM) used as quality indices. These QM data provide feedback to physicians by identifying areas for improvement in the process of care and identifying the adoption of evidence-based recommendations for radiation therapy. RESULTS: Disease-site expert panels organized by the American Society for Radiation Oncology (ASTRO) defined quality measures and established scoring criteria for prostate cancer (intermediate and high risk), non-small cell lung cancer (IIIA/B stage), and small cell lung cancer (limited stage) case presentations. Data elements for 1567 patients from the 40 VA radiation oncology practices were abstracted from the electronic medical records and treatment management and planning systems. Overall, the 1567 assessed cases passed 82.4% of all QM. Pass rates for QM for the 773 lung and 794 prostate cases were 78.0% and 87.2%, respectively. Marked variations, however, were noted in the pass rates for QM when tumor site, clinical pathway, or performing centers were separately examined. CONCLUSIONS: The peer-review protected VA-Radiation Oncology Surveillance program based on clinical quality measures allows providers to compare their clinical practice to peers and to make meaningful adjustments in their personal patterns of care unobtrusively.

Knowledge Models as Teaching Aid for Training Intensity Modulated Radiation Therapy Planning: A Lung Cancer Case Study.

Purpose: Artificial intelligence (AI) employs knowledge models that often behave as a black-box to the majority of users and are not designed to improve the skill level of users. In this study, we aim to demonstrate the feasibility that AI can serve as an effective teaching aid to train individuals to develop optimal intensity modulated radiation therapy (IMRT) plans. Methods and Materials: The training program is composed of a host of training cases and a tutoring system that consists of a front-end visualization module powered by knowledge models and a scoring system. The current tutoring system includes a beam angle prediction model and a dose-volume histogram (DVH) prediction model. The scoring system consists of physician chosen criteria for clinical plan evaluation as well as specially designed criteria for learning guidance. The training program includes six lung/mediastinum IMRT patients: one benchmark case and five training cases. A plan for the benchmark case is completed by each trainee entirely independently pre- and post-training. Five training cases cover a wide spectrum of complexity from easy (2), intermediate (1) to hard (2). Five trainees completed the training program with the help of one trainer. Plans designed by the trainees were evaluated by both the scoring system and a radiation oncologist to quantify planning quality. Results: For the benchmark case, trainees scored an average of 21.6% of the total max points pre-training and improved to an average of 51.8% post-training. In comparison, the benchmark case's clinical plans score an average of 54.1% of the total max points. Two of the five trainees' post-training plans on the benchmark case were rated as comparable to the clinically delivered plans by the physician and all five were noticeably improved by the physician's standards. The total training time for each trainee ranged between 9 and 12 h. Conclusion: This first attempt at a knowledge model based training program brought unexperienced planners to a level close to experienced planners in fewer than 2 days. The proposed tutoring system can serve as an important component in an AI ecosystem that will enable clinical practitioners to effectively and confidently use KBP.

AAPM medical physics practice guideline 7.a.: Supervision of medical physicist assistants.

The American Association of Physicists in Medicine (AAPM) is a nonprofit professional society whose primary purposes are to advance the science, education and professional practice of medical physics. The AAPM has more than 8,000 members and is the principal organization of medical physicists in the United States. The AAPM will periodically define new practice guidelines for medical physics practice to help advance the science of medical physics and to improve the quality of service to patients throughout the United States. Existing medical physics practice guidelines will be reviewed for the purpose of revision or renewal, as appropriate, on their fifth anniversary or sooner. Each medical physics practice guideline represents a policy statement by the AAPM, has undergone a thorough consensus process in which it has been subjected to extensive review, and requires the approval of the Professional Council. The medical physics practice guidelines recognize that the safe and effective use of diagnostic and therapeutic radiology requires specific training, skills, and techniques, as described in each document. Reproduction or modification of the published practice guidelines and technical standards by those entities not providing these services is not authorized. The following terms are used in the AAPM practice guidelines: Must and Must Not: Used to indicate that adherence to the recommendation is considered necessary to conform to this practice guideline. Should and Should Not: Used to indicate a prudent practice to which exceptions may occasionally be made in appropriate circumstances. Approved by AAPM's Executive Committee May 28, 2019.

Quality Improvements of Veterans Health Administration Radiation Oncology Services Through Partnership for Accreditation With the ACR.

Approximately 20,000 US veterans receive radiation oncology services at a Veterans Healthcare Administration (VHA) medical facility each year. They currently have access to advanced technologies, which include image-guided intensity-modulated radiotherapy, stereotactic radiosurgery, and stereotactic body radiation therapy. Although this provides access to cancer therapies that are modern, safe, and efficient, the technical complexities of these treatments and clinical decision making that goes into the patient selection and prescriptions demand quality assurances at each VHA practice. To meet the challenges of this need, the VHA established a partnership in 2008 with the ACR's Radiation Oncology Practice Accreditation Program (ACR-ROPA). This report summarizes the experience of this ongoing partnership and demonstrates the combined impact of the VHA's mandate for ACR-ROPA accreditation and internal monitoring of all identified corrective actions at each of its radiation oncology practices.

Executive summary of AAPM Report Task Group 113: Guidance for the physics aspects of clinical trials.

The charge of AAPM Task Group 113 is to provide guidance for the physics aspects of clinical trials to minimize variability in planning and dose delivery for external beam trials involving photons and electrons. Several studies have demonstrated the importance of protocol compliance on patient outcome. Minimizing variability for treatments at different centers improves the quality and efficiency of clinical trials. Attention is focused on areas where variability can be minimized through standardization of protocols and processes through all aspects of clinical trials. Recommendations are presented for clinical trial designers, physicists supporting clinical trials at their individual clinics, quality assurance centers, and manufacturers.

Technical note: real-time web-based wireless visual guidance system for radiotherapy.

Describe a Web-based wireless visual guidance system that mitigates issues associated with hard-wired audio-visual aided patient interactive motion management systems that are cumbersome to use in routine clinical practice. Web-based wireless visual display duplicates an existing visual display of a respiratory-motion management system for visual guidance. The visual display of the existing system is sent to legacy Web clients over a private wireless network, thereby allowing a wireless setting for real-time visual guidance. In this study, active breathing coordinator (ABC) trace was used as an input for visual display, which captured and transmitted to Web clients. Virtual reality goggles require two (left and right eye view) images for visual display. We investigated the performance of Web-based wireless visual guidance by quantifying (1) the network latency of visual displays between an ABC computer display and Web clients of a laptop, an iPad mini 2 and an iPhone 6, and (2) the frame rate of visual display on the Web clients in frames per second (fps). The network latency of visual display between the ABC computer and Web clients was about 100 ms and the frame rate was 14.0 fps (laptop), 9.2 fps (iPad mini 2) and 11.2 fps (iPhone 6). In addition, visual display for virtual reality goggles was successfully shown on the iPhone 6 with 100 ms and 11.2 fps. A high network security was maintained by utilizing the private network configuration. This study demonstrated that a Web-based wireless visual guidance can be a promising technique for clinical motion management systems, which require real-time visual display of their outputs. Based on the results of this study, our approach has the potential to reduce clutter associated with wired-systems, reduce space requirements, and extend the use of medical devices from static usage to interactive and dynamic usage in a radiotherapy treatment vault.

The report of Task Group 100 of the AAPM: Application of risk analysis methods to radiation therapy quality management.

The increasing complexity of modern radiation therapy planning and delivery challenges traditional prescriptive quality management (QM) methods, such as many of those included in guidelines published by organizations such as the AAPM, ASTRO, ACR, ESTRO, and IAEA. These prescriptive guidelines have traditionally focused on monitoring all aspects of the functional performance of radiotherapy (RT) equipment by comparing parameters against tolerances set at strict but achievable values. Many errors that occur in radiation oncology are not due to failures in devices and software; rather they are failures in workflow and process. A systematic understanding of the likelihood and clinical impact of possible failures throughout a course of radiotherapy is needed to direct limit QM resources efficiently to produce maximum safety and quality of patient care. Task Group 100 of the AAPM has taken a broad view of these issues and has developed a framework for designing QM activities, based on estimates of the probability of identified failures and their clinical outcome through the RT planning and delivery process. The Task Group has chosen a specific radiotherapy process required for "intensity modulated radiation therapy (IMRT)" as a case study. The goal of this work is to apply modern risk-based analysis techniques to this complex RT process in order to demonstrate to the RT community that such techniques may help identify more effective and efficient ways to enhance the safety and quality of our treatment processes. The task group generated by consensus an example quality management program strategy for the IMRT process performed at the institution of one of the authors. This report describes the methodology and nomenclature developed, presents the process maps, FMEAs, fault trees, and QM programs developed, and makes suggestions on how this information could be used in the clinic. The development and implementation of risk-assessment techniques will make radiation therapy safer and more efficient.

International outreach: what is the responsibility of ASTRO and the major international radiation oncology societies?

In this era of globalization and rapid advances in radiation oncology worldwide, the American Society for Radiation Oncology (ASTRO) is committed to help decrease profound regional disparities through the work of the International Education Subcommittee (IES). The IES has expanded its base, reach, and activities to foster educational advances through a variety of educational methods with broad scope, in addition to committing to the advancement of radiation oncology care for cancer patients around the world, through close collaboration with our sister radiation oncology societies and other educational, governmental, and organizational groups.

Monitor unit calculations for external photon and electron beams: Report of the AAPM Therapy Physics Committee Task Group No. 71.

A protocol is presented for the calculation of monitor units (MU) for photon and electron beams, delivered with and without beam modifiers, for constant source-surface distance (SSD) and source-axis distance (SAD) setups. This protocol was written by Task Group 71 of the Therapy Physics Committee of the American Association of Physicists in Medicine (AAPM) and has been formally approved by the AAPM for clinical use. The protocol defines the nomenclature for the dosimetric quantities used in these calculations, along with instructions for their determination and measurement. Calculations are made using the dose per MU under normalization conditions, D'0, that is determined for each user's photon and electron beams. For electron beams, the depth of normalization is taken to be the depth of maximum dose along the central axis for the same field incident on a water phantom at the same SSD, where D'0 = 1 cGy/MU. For photon beams, this task group recommends that a normalization depth of 10 cm be selected, where an energy-dependent D'0 ≤ 1 cGy/MU is required. This recommendation differs from the more common approach of a normalization depth of dm, with D'0 = 1 cGy/MU, although both systems are acceptable within the current protocol. For photon beams, the formalism includes the use of blocked fields, physical or dynamic wedges, and (static) multileaf collimation. No formalism is provided for intensity modulated radiation therapy calculations, although some general considerations and a review of current calculation techniques are included. For electron beams, the formalism provides for calculations at the standard and extended SSDs using either an effective SSD or an air-gap correction factor. Example tables and problems are included to illustrate the basic concepts within the presented formalism.

Redesigning radiotherapy quality assurance: opportunities to develop an efficient, evidence-based system to support clinical trials--report of the National Cancer Institute Work Group on Radiotherapy Quality Assurance.

PURPOSE: In the context of national calls for reorganizing cancer clinical trials, the National Cancer Institute sponsored a 2-day workshop to examine challenges and opportunities for optimizing radiotherapy quality assurance (QA) in clinical trial design. METHODS AND MATERIALS: Participants reviewed the current processes of clinical trial QA and noted the QA challenges presented by advanced technologies. The lessons learned from the radiotherapy QA programs of recent trials were discussed in detail. Four potential opportunities for optimizing radiotherapy QA were explored, including the use of normal tissue toxicity and tumor control metrics, biomarkers of radiation toxicity, new radiotherapy modalities such as proton beam therapy, and the international harmonization of clinical trial QA. RESULTS: Four recommendations were made: (1) to develop a tiered (and more efficient) system for radiotherapy QA and tailor the intensity of QA to the clinical trial objectives (tiers include general credentialing, trial-specific credentialing, and individual case review); (2) to establish a case QA repository; (3) to develop an evidence base for clinical trial QA and introduce innovative prospective trial designs to evaluate radiotherapy QA in clinical trials; and (4) to explore the feasibility of consolidating clinical trial QA in the United States. CONCLUSION: Radiotherapy QA can affect clinical trial accrual, cost, outcomes, and generalizability. To achieve maximum benefit, QA programs must become more efficient and evidence-based.

Developing a national radiation oncology registry: From acorns to oaks.

PURPOSE: The National Radiation Oncology Registry (NROR) is a collaborative initiative of the Radiation Oncology Institute and the American Society of Radiation Oncology, with input and guidance from other major stakeholders in oncology. The overarching mission of the NROR is to improve the care of cancer patients by capturing reliable information on treatment delivery and health outcomes. METHODS: The NROR will collect patient-specific radiotherapy data electronically to allow for rapid comparison of the many competing treatment modalities and account for effectiveness, outcome, utilization, quality, safety, and cost. It will provide benchmark data and quality improvement tools for individual practitioners. The NROR steering committee has determined that prostate cancer provides an appropriate model to test the concept and the data capturing software in a limited number of sites. The NROR pilot project will begin with this disease-gathering treatment and outcomes data from a limited number of treatment sites across the range of practice; once feasibility is proven, it will scale up to more sites and diseases. RESULTS: When the NROR is fully implemented, all radiotherapy facilities, along with their radiation oncologists, will be solicited to participate in it. With the broader participation of the radiation oncology community, NROR has the potential to serve as a resource for determining national patterns of care, gaps in treatment quality, comparative effectiveness, and hypothesis generation to identify new linkages between therapeutic processes and outcomes. CONCLUSIONS: The NROR will benefit radiation oncologists and other care providers, payors, vendors, policy-makers, and, most importantly, cancer patients by capturing reliable information on population-based radiation treatment delivery.

An image quality comparison study between XVI and OBI CBCT systems.

The purpose of this study is to evaluate and compare image quality characteristics for two commonly used and commercially available CBCT systems: the X-ray Volumetric Imager and the On-Board Imager. A commonly used CATPHAN image quality phantom was used to measure various image quality parameters, namely, pixel value stability and accuracy, noise, contrast to noise ratio (CNR), high-contrast resolution, low contrast resolution and image uniformity. For the XVI unit, we evaluated the image quality for four manufacturer-supplied protocols as a function of mAs. For the OBI unit, we did the same for the full-fan and half-fan scanning modes, which were respectively used with the full bow-tie and half bow-tie filters. For XVI, the mean pixel values of regions of interest were found to generally decrease with increasing mAs for all protocols, while they were relatively stable with mAs for OBI. Noise was slightly lower on XVI and was seen to decrease with increasing mAs, while CNR increased with mAs for both systems. For XVI and OBI, the high-contrast resolution was approximately limited by the pixel resolution of the reconstructed image. On OBI images, up to 6 and 5 discs of 1% and 0.5% contrast, respectively, were visible for a high mAs setting using the full-fan mode, while none of the discs were clearly visible on the XVI images for various mAs settings when the medium resolution reconstruction was used. In conclusion, image quality parameters for XVI and OBI have been quantified and compared for clinical protocols under various mAs settings. These results need to be viewed in the context of a recent study that reported the dose-mAs relationship for the two systems and found that OBI generally delivered higher imaging doses than XVI.

The American Society for Radiation Oncology's 2010 core physics curriculum for radiation oncology residents.

PURPOSE: In 2004, the American Society for Radiation Oncology (ASTRO) published its first physics education curriculum for residents, which was updated in 2007. A committee composed of physicists and physicians from various residency program teaching institutions was reconvened again to update the curriculum in 2009. METHODS AND MATERIALS: Members of this committee have associations with ASTRO, the American Association of Physicists in Medicine, the Association of Residents in Radiation Oncology, the American Board of Radiology (ABR), and the American College of Radiology. Members reviewed and updated assigned subjects from the last curriculum. The updated curriculum was carefully reviewed by a representative from the ABR and other physics and clinical experts. RESULTS: The new curriculum resulted in a recommended 56-h course, excluding initial orientation. Learning objectives are provided for each subject area, and a detailed outline of material to be covered is given for each lecture hour. Some recent changes in the curriculum include the addition of Radiation Incidents and Bioterrorism Response Training as a subject and updates that reflect new treatment techniques and modalities in a number of core subjects. The new curriculum was approved by the ASTRO board in April 2010. We anticipate that physicists will use this curriculum for structuring their teaching programs, and subsequently the ABR will adopt this educational program for its written examination. Currently, the American College of Radiology uses the ASTRO curriculum for their training examination topics. In addition to the curriculum, the committee updated suggested references and the glossary. CONCLUSIONS: The ASTRO physics education curriculum for radiation oncology residents has been updated. To ensure continued commitment to a current and relevant curriculum, the subject matter will be updated again in 2 years.

Quality assessment of frameless fractionated stereotactic radiotherapy using cone beam computed tomography.

PURPOSE: A quality assessment of intracranial stereotactic radiotherapy was performed using cone beam computed tomography (CBCT). Setup errors were analyzed for two groups of patients: (1) those who were positioned using a frameless SonArray (FSA) system and immobilized with a bite plate and thermoplastic (TP) mask (the bFSA group); and (2) those who were positioned by room laser and immobilized using a TP mask (the mLAS group). METHODS AND MATERIALS: A quality assurance phantom was used to study the system differences between FSA and CBCT. The quality assessment was performed using an Elekta Synergy imager (XVI) (Elekta Oncology Systems, Norcross, GA) and an On-Board Imager (OBI) (Varian Medical Systems, Palo Alto, CA) for 25 patients. For the first three fractions, and weekly thereafter, the FSA system was used for patient positioning, after which CBCT was performed to obtain setup errors. RESULTS: (1) Phantom tests: The mean differences in the isocenter displacements for the two systems was 1.2 ± 0.7 mm. No significant variances were seen between the XVI and OBI units (p~0.208). (2)Patient tests: The mean of the displacements between FSA and CBCT were independent of the CBCT system used; mean setup errors for the bFSA group were smaller (1.2 mm) than those of the mLAS group (3.2 mm) (p < 0.005). For the mLAS patients, the 90th percentile and the maximum rotational displacements were 3° and 5°, respectively. A 4-mm drift in setup accuracy occurred over the treatment course for 1 bFSA patient. CONCLUSIONS: System differences of less than 1 mm between CBCT and FSA were seen. Error regression was observed for the bFSA patients, using CBCT (up to 4 mm) during the treatment course. For the mLAS group, daily CBCT imaging was needed to obtain acceptable setup accuracies.

Application of a novel dose-uncertainty model for dose-uncertainty analysis in prostate intensity-modulated radiotherapy.

PURPOSE: To analyze dose uncertainty using a previously published dose-uncertainty model, and to assess potential dosimetric risks existing in prostate intensity-modulated radiotherapy (IMRT). METHODS AND MATERIALS: The dose-uncertainty model provides a three-dimensional (3D) dose-uncertainty distribution in a given confidence level. For 8 retrospectively selected patients, dose-uncertainty maps were constructed using the dose-uncertainty model at the 95% CL. In addition to uncertainties inherent to the radiation treatment planning system, four scenarios of spatial errors were considered: machine only (S1), S1 + intrafraction, S1 + interfraction, and S1 + both intrafraction and interfraction errors. To evaluate the potential risks of the IMRT plans, three dose-uncertainty-based plan evaluation tools were introduced: confidence-weighted dose-volume histogram, confidence-weighted dose distribution, and dose-uncertainty-volume histogram. RESULTS: Dose uncertainty caused by interfraction setup error was more significant than that of intrafraction motion error. The maximum dose uncertainty (95% confidence) of the clinical target volume (CTV) was smaller than 5% of the prescribed dose in all but two cases (13.9% and 10.2%). The dose uncertainty for 95% of the CTV volume ranged from 1.3% to 2.9% of the prescribed dose. CONCLUSIONS: The dose uncertainty in prostate IMRT could be evaluated using the dose-uncertainty model. Prostate IMRT plans satisfying the same plan objectives could generate a significantly different dose uncertainty because a complex interplay of many uncertainty sources. The uncertainty-based plan evaluation contributes to generating reliable and error-resistant treatment plans.

Assessment of the setup dependence of detector response functions for mega-voltage linear accelerators.

PURPOSE: Accurate modeling of beam profiles is important for precise treatment planning dosimetry. Calculated beam profiles need to precisely replicate profiles measured during machine commissioning. Finite detector size introduces perturbations into the measured profiles, which, in turn, impact the resulting modeled profiles. The authors investigate a method for extracting the unperturbed beam profiles from those measured during linear accelerator commissioning. METHODS: In-plane and cross-plane data were collected for an Elekta Synergy linac at 6 MV using ionization chambers of volume 0.01, 0.04, 0.13, and 0.65 cm3 and a diode of surface area 0.64 mm2. The detectors were orientated with the stem perpendicular to the beam and pointing away from the gantry. Profiles were measured for a 10 x 10 cm2 field at depths ranging from 0.8 to 25.0 cm and SSDs from 90 to 110 cm. Shaping parameters of a Gaussian response function were obtained relative to the Edge detector. The Gaussian function was deconvolved from the measured ionization chamber data. The Edge detector profile was taken as an approximation to the true profile, to which deconvolved data were compared. Data were also collected with CC13 and Edge detectors for additional fields and energies on an Elekta Synergy, Varian Trilogy, and Siemens Oncor linear accelerator and response functions obtained. Response functions were compared as a function of depth, SSD, and detector scan direction. Variations in the shaping parameter were introduced and the effect on the resulting deconvolution profiles assessed. RESULTS: Up to 10% setup dependence in the Gaussian shaping parameter occurred, for each detector for a particular plane. This translated to less than a +/- 0.7 mm variation in the 80%-20% penumbral width. For large volume ionization chambers such as the FC65 Farmer type, where the cavity length to diameter ratio is far from 1, the scan direction produced up to a 40% difference in the shaping parameter between in-plane and cross-plane measurements. This is primarily due to the directional difference in penumbral width measured by the FC65 chamber, which can more than double in profiles obtained with the detector stem parallel compared to perpendicular to the scan direction. For the more symmetric CC13 chamber the variation was only 3% between in-plane and cross-plane measurements. CONCLUSIONS: The authors have shown that the detector response varies with detector type, depth, SSD, and detector scan direction. In-plane vs. cross-plane scanning can require calculation of a direction dependent response function. The effect of a 10% overall variation in the response function, for an ionization chamber, translates to a small deviation in the penumbra from that of the Edge detector measured profile when deconvolved. Due to the uncertainties introduced by deconvolution the Edge detector would be preferable in obtaining an approximation of the true profile, particularly for field sizes where the energy dependence of the diode can be neglected. However, an averaged response function could be utilized to provide a good approximation of the true profile for large ionization chambers and for larger fields for which diode detectors are not recommended.