Quantitative Metrics for Assessing Plan Quality

Moore, Kevin L.; Brame, R. Scott; Low, Daniel A.; Mutic, Sasa

doi:10.1016/j.semradonc.2011.09.005

Cited by 55 publications

(31 citation statements)

References 45 publications

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“…Most previous work on automating the planning process has built on knowledge of previously treated patients. One approach of extracting information from previously treated patients is utilizing the overlap volume histogram method, which measures the position of an OAR relative to the target (19,29,30,31) . Knowledge of overlap volume histograms from previously treated patients can be used to predict the likely achievable irradiation level of specific OARs.…”

Section: Discussionmentioning

confidence: 99%

“…A number of uncertainties and variations are present in radiotherapy such as absolute dose precision, (1) delivery precision, (2,3,4,5) precision of calculated dose distributions, (6,7,8,9) and radioresponsiveness of the specific tumor and normal tissues (10,11,12,13,14,15) . Two of the largest variations within radiotherapy are the heterogeneity in target definition (16,17,18) and the variation among treatment plans for a given geometry both intra‐ and interinstitutional (19,20) . Most treatment plans are likely to have sufficient dose coverage of the delineated targets, but large variations in dose to healthy tissues occur.…”

Section: Introductionmentioning

confidence: 99%

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Automatic planning of head and neck treatment plans

Hazell

Bzdusek

Kumar

et al. 2016

J Applied Clin Med Phys

129

145

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Treatment planning is time‐consuming and the outcome depends on the person performing the optimization. A system that automates treatment planning could potentially reduce the manual time required for optimization and could also provide a method to reduce the variation between persons performing radiation dose planning (dosimetrist) and potentially improve the overall plan quality. This study evaluates the performance of the Auto‐Planning module that has recently become clinically available in the Pinnacle3 radiation therapy treatment planning system. Twenty‐six clinically delivered head and neck treatment plans were reoptimized with the Auto‐Planning module. Comparison of the two types of treatment plans were performed using DVH metrics and a blinded clinical evaluation by two senior radiation oncologists using a scale from one to six. Both evaluations investigated dose coverage of target and dose to healthy tissues. Auto‐Planning was able to produce clinically acceptable treatment plans in all 26 cases. Target coverages in the two types of plans were similar, but automatically generated plans had less irradiation of healthy tissue. In 94% of the evaluations, the autoplans scored at least as high as the previously delivered clinical plans. For all patients, the Auto‐Planning tool produced clinically acceptable head and neck treatment plans without any manual intervention, except for the initial target and OAR delineations. The main benefit of the method is the likely improvement in the overall treatment quality since consistent, high‐quality plans are generated which even can be further optimized, if necessary. This makes it possible for the dosimetrist to focus more time on difficult dose planning goals and to spend less time on the more tedious parts of the planning process.PACS number: 87.55.de

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Automatic planning of head and neck treatment plans

Hazell

Bzdusek

Kumar

et al. 2016

J Applied Clin Med Phys

129

145

View full text Add to dashboard Cite

show abstract

“…A number of recent methods have used prior plans to establish dose volume effects (i.e., predicting clinical outcomes based on delivered dose and other patient conditions. ) (2‐5) Other methods have employed prior plans for quality control, (6‐9) and demonstrated that prior plan can serve as an important reference for improving and homogenizing the quality of new plans (10) . More recently, predicting achievable dose‐volume histograms (DVHs) using prior knowledge has been reported (9,11,12) .…”

Section: Introductionmentioning

confidence: 99%

Quantitative comparison of automatic and manual IMRT optimization for prostate cancer: the benefits of DVH prediction

Yang

Yuan

et al. 2015

J Applied Clin Med Phys

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A recent publication indicated that the patient anatomical feature (PAF) model was capable of predicting optimal objectives based on past experience. In this study, the benefits of IMRT optimization using PAF‐predicted objectives as guidance for prostate were evaluated. Three different optimization methods were compared. 1) Expert Plan: Ten prostate cases (16 plans) were planned by an expert planner using conventional trial‐and‐error approach started with institutional modified OAR and PTV constraints. Optimization was stopped at 150 iterations and that plan was saved as Expert Plan. 2) Clinical Plan: The planner would keep working on the Expert Plan till he was satisfied with the dosimetric quality and the final plan was referred to as Clinical Plan. 3) PAF Plan: A third sets of plans for the same ten patients were generated fully automatically using predicted DVHs as guidance. The optimization was based on PAF‐based predicted objectives, and was continued to 150 iterations without human interaction. DMAX and D98% for PTV, DMAX for femoral heads, DMAX, D10cc, normalD25%/normalD17%, and D40% for bladder/rectum were compared. Clinical Plans are further optimized with more iterations and adjustments, but in general provided limited dosimetric benefits over Expert Plans. PTV D98% agreed within 2.31% among Expert, Clinical, and PAF plans. Between Clinical and PAF Plans, differences for DMAX of PTV, bladder, and rectum were within 2.65%, 2.46%, and 2.20%, respectively. Bladder D10cc was higher for PAF but <1.54% in general. Bladder D25% and D40% were lower for PAF, by up to 7.71% and 6.81%, respectively. Rectum D10cc, D17%, and D40% were 2.11%, 2.72%, and 0.27% lower for PAF, respectively. DMAX for femoral heads were comparable (<35 Gy on average). Compared to Clinical Plan (Primary+Boost), the average optimization time for PAF plan was reduced by 5.2 min on average, with a maximum reduction of 7.1 min. Total numbers of MUs per plan for PAF Plans were lower than Clinical Plans, indicating better delivery efficiency. The PAF‐guided planning process is capable of generating clinical‐quality prostate IMRT plans with no human intervention. Compared to manual optimization, this automatic optimization increases planning and delivery efficiency, while maintaining plan quality.PACS numbers: 87.55.D‐, 87.55.de, 87.53.Jw

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“…European Organization for the Research and Treatment of Cancer (EO-RTC) designed a complex quality assurance program to ensure safe and effective treatment delivery 10 . But it only focuses on radiotherapy, which is assured by mature process management system, such as radiotherapy plan quality 11 and QC of thermal therapy 12 . For QC of chemotherapy 13 concentrates on Real-Time Patient-Reported Outcomes for clinical practice decisions and quality improvement programs.…”

Section: Discussionmentioning

confidence: 99%

Abstracts of the Medical Engineering and Bioinformatics 2015 (MEB 2015), China, 7 June 2015

2015

Basic Clin Pharma Tox

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Aims: The laparoscopy reduces the damage to body and shortens the postoperative recovery period, so it is becoming the standard surgical operation. However, the indirect method of observing and manipulating in laparoscopy impairs the surgeon's eye-hand coordination, which makes it difficult to carry out a laparoscopic operation successfully. Then we initiate the optical see-through technique in order to find solutions for these difficulties of laparoscopy. Methods: The floating display mechanism of optical see-through technique is proposed and deeply researched to overcome the mislocation of camera picture and the misorientation of instrument movements. The line-of-sight of endoscope is transformed and coincides with the surgeon's natural line-of-sight. The pictures of endoscope are projected onto the semi-transparent mirror between the surgeon's eyes and the abdomen, and the pre-operative information from X-ray, ultrasound or MRI images are also mapped onto the endoscope camera pictures, which gives the surgeon the visual sense of seeing through the skin. An experimental optical see-through system is constructed. Results: Extensive experiments are conducted on phantoms to verify the accuracy and stability of the constructed system. Experimental results show that the optical see-through system has better performance and overcomes the eye-hand coordination problem. Conclusions:The optical see-through system shows its superiority in laparoscopy, and has a broad application prospect in the future. We will develop its new functions for other kinds of surgeries such as arthroscopy. Its disadvantages such as complex calibration procedure have to be resolved in the future. College of Information System and Management, National University of Defense Technology, Changsha, Hunan, China Aims: One ubiquitous limitation of most previous studies in Health Monitoring Systems is they just focused on the architecture but disregard the acquired data. This manuscript try to obtain better monitor effect though an improved Statistical Process Control (SPC) control chart. Methods: Two groups of volunteers participated in the questionnaire. They had diabete or hypertension separately, and their living habits and environments were similar. Under the control of Minimum Mean Squared Error (MMSE), we can eliminate the influence of autocorrelation and cyclical change. The system would send timely warning signs by inputting the convert white noises to the Cumulative Sum (CUSUM) and Exponentially Weighted Moving-Average (EWMA) control chart. Results: Since the introduction of CUSUM and EWMA control chart, the system could detect the tiny changes of cumulating trend. In addition, it becomes more sensitive after the utilization of a positive feedback when the correlation of data is high. Conclusions: The system presented in this article bring better results, as the ability to get change of accumulation has more practical value in keeping healthy. The number of cases was inadequate, however, the correctness and validity of the improved method h...

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Quantitative Metrics for Assessing Plan Quality

Cited by 55 publications

References 45 publications

Automatic planning of head and neck treatment plans

Automatic planning of head and neck treatment plans

Quantitative comparison of automatic and manual IMRT optimization for prostate cancer: the benefits of DVH prediction

Abstracts of the Medical Engineering and Bioinformatics 2015 (MEB 2015), China, 7 June 2015

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