Dataset Information

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.

ABSTRACT:

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.

SUBMITTER: Bekelman JE

PROVIDER: S-EPMC3361528 | biostudies-literature | 2012 Jul

REPOSITORIES: biostudies-literature

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Publications

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.

Bekelman Justin E JE Deye James A JA Vikram Bhadrasain B Bentzen Soren M SM Bruner Deborah D Curran Walter J WJ Dignam James J Efstathiou Jason A JA FitzGerald T J TJ Hurkmans Coen C Ibbott Geoffrey S GS Lee J Jack JJ Merchant Thomas E TE Michalski Jeff J Palta Jatinder R JR Simon Richard R Ten Haken Randal K RK Timmerman Robert R Tunis Sean S Coleman C Norman CN Purdy James J

International journal of radiation oncology, biology, physics 20120315 3

<h4>Purpose</h4>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.<h4>Methods and materials</h4>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 di ...[more]

PMID: 22425219

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Project description:BackgroundSCOPE 1 was the first UK based multi-centre trial involving radiotherapy of the oesophagus. A comprehensive radiotherapy trials quality assurance programme was launched with two main aims: 1. To assist centres, where needed, to adapt their radiotherapy techniques in order to achieve protocol compliance and thereby enable their participation in the trial. 2. To support the trial's clinical outcomes by ensuring the consistent planning and delivery of radiotherapy across all participating centres.MethodsA detailed information package was provided and centres were required to complete a benchmark case in which the delineated target volumes and organs at risk, dose distribution and completion of a plan assessment form were assessed prior to recruiting patients into the trial. Upon recruiting, the quality assurance (QA) programme continued to monitor the outlining and planning of radiotherapy treatments. Completion of a questionnaire was requested in order to gather information about each centre's equipment and techniques relating to their trial participation and to assess the impact of the trial nationally on standard practice for radiotherapy of the oesophagus. During the trial, advice was available for individual planning issues, and was circulated amongst the SCOPE 1 community in response to common areas of concern using bulletins.Results36 centres were supported through QA processes to enable their participation in SCOPE1. We discuss the issues which have arisen throughout this process and present details of the benchmark case solutions, centre questionnaires and on-trial protocol compliance. The range of submitted benchmark case GTV volumes was 29.8-67.8cm3; and PTV volumes 221.9-513.3 cm3. For the dose distributions associated with these volumes, the percentage volume of the lungs receiving 20Gy (V20Gy) ranged from 20.4 to 33.5%. Similarly, heart V40Gy ranged from 16.1 to 33.0%. Incidence of incorrect outlining of OAR volumes increased from 50% of centres at benchmark case, to 64% on trial. Sixty-five percent of centres, who returned the trial questionnaire, stated that their standard practice had changed as a result of their participation in the SCOPE1 trial.ConclusionsThe SCOPE 1 QA programme outcomes lend support to the trial's clinical conclusions. The range of patient planning outcomes for the benchmark case indicated, at the outset of the trial, the significant degree of variation present in UK oesophageal radiotherapy planning outcomes, despite the presence of a protocol. This supports the case for increasingly detailed definition of practice by means of consensus protocols, training and peer review. The incidence of minor inconsistencies of technique highlights the potential for improved QA systems and the need for sufficient resource for this to be addressed within future trials. As indicated in questionnaire responses, the QA exercise as a whole has contributed to greater consistency of oesophageal radiotherapy in the UK via the adoption into standard practice of elements of the protocol.Trial registrationThe SCOPE1 trial is an International Standard Randomized Controlled Trial, ISRCTN47718479 .

Project description:Purpose: More and more automatic segmentation tools are being introduced in routine clinical practice. However, physicians need to spend a considerable amount of time in examining the generated contours slice by slice. This greatly reduces the benefit of the tool's automaticity. In order to overcome this shortcoming, we developed an automatic quality assurance (QA) method for automatic segmentation using convolutional neural networks (CNNs). Materials and Methods: The study cohort comprised 680 patients with early-stage breast cancer who received whole breast radiation. The overall architecture of the automatic QA method for deep learning-based segmentation included the following two main parts: a segmentation CNN model and a QA network that was established based on ResNet-101. The inputs were from computed tomography, segmentation probability maps, and uncertainty maps. Two kinds of Dice similarity coefficient (DSC) outputs were tested. One predicted the DSC quality level of each slice ([0.95, 1] for "good," [0.8, 0.95] for "medium," and [0, 0.8] for "bad" quality), and the other predicted the DSC value of each slice directly. The performances of the method to predict the quality levels were evaluated with quantitative metrics: balanced accuracy, F score, and the area under the receiving operator characteristic curve (AUC). The mean absolute error (MAE) was used to evaluate the DSC value outputs. Results: The proposed methods involved two types of output, both of which achieved promising accuracy in terms of predicting the quality level. For the good, medium, and bad quality level prediction, the balanced accuracy was 0.97, 0.94, and 0.89, respectively; the F score was 0.98, 0.91, and 0.81, respectively; and the AUC was 0.96, 0.93, and 0.88, respectively. For the DSC value prediction, the MAE was 0.06 ± 0.19. The prediction time was approximately 2 s per patient. Conclusions: Our method could predict the segmentation quality automatically. It can provide useful information for physicians regarding further verification and revision of automatic contours. The integration of our method into current automatic segmentation pipelines can improve the efficiency of radiotherapy contouring.

Dataset Information

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

Methods and materials

Results

Conclusion

Publications

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.

Similar Datasets

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