Evaluation of the plan delivery accuracy of intensity-modulated radiation therapy by texture analysis using fluence maps

Park, So Yeon; Kim, Jung-In; Oh, Do Hoon; Park, Jong Min

doi:10.1016/j.ejmp.2019.02.016

Cited by 5 publications

(4 citation statements)

References 33 publications

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“…However, several groups [2,4,19] have reported the following limitations in evaluating the uncertainty related to the MLC leaf position: (i) insensitivity to dose errors, (ii) absence of correlations with clinical dose errors, (iii) di culty in de ning the root cause of the existing discrepancy between dose distributions, (iv) differences between the gamma results produced by different measurement devices [20], and (v) different standard criteria proposed in the Imaging and Radiation Oncology Core (IROC) and TG218 reports [26]. Recently, dosiomics (or radiomics) [2,4,[21][22][23][24][25] and structural similarity (SSIM) [2] analyses have been conducted to determine whether they can be used to overcome the limitations of conventional gamma analysis.…”

Section: Introductionmentioning

confidence: 99%

“…However, no strong indicators or harmonized error characterization or prediction results were reported due to the measurement device bias and patient-speci c heterogeneity when using patient data. [2,4,[23][24][25][26][27][28]. For these reasons, essential research is needed to discover and analyze basic indicators in a state where heterogeneity due to measurement devices and patients is removed before direct application to the clinical practice of various conditions [2,4,23,25,[27][28][29][30][31][32][33][34].…”

Section: Introductionmentioning

confidence: 99%

“…[2,4,[23][24][25][26][27][28]. For these reasons, essential research is needed to discover and analyze basic indicators in a state where heterogeneity due to measurement devices and patients is removed before direct application to the clinical practice of various conditions [2,4,23,25,[27][28][29][30][31][32][33][34].…”

Section: Introductionmentioning

confidence: 99%

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Investigation of the characteristics of multileaf collimator position errors: dose distribution- based error classification

Sheen

Shin

Kim

et al. 2022

Preprint

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Background The characteristics of the multileaf collimator (MLC) position error were investigated without clinical variability and other factors affecting the error analysis. An index indicating the attributes of MLC position error was found and used for MLC position error prediction model. The dose-volume histogram (DVH) was examined to investigate the clinical relationship.Methods: The dose distribution was investigated using the gamma index, structural similarity (SSIM) index, and dosiomics index. The cases from the American Association of Physicists in Medicine Task Group 119 were planned, and systematic and random MLC position errors were simulated. All error-free and error datasets were generated in the treatment plan system. The indices were obtained from distribution maps, and then statistically significant indices were selected. An MLC position error prediction model was developed using the selected indices and logistic regression method. The final model was determined when all values of the area under the curve (AUC), accuracy, precision, sensitivity, and specificity were higher than 0.8 (p<0.05). DVH relative percentage difference between the error-free and error datasets was examined to investigate clinical relations.Results: Statistically common significant indices were found, GLCM_Energy in Class-I and Class-III and GLRLM_LRHGE in Class-II. The final model was developed using indices that satisfied the statistical criteria. The number of finalized univariate predictive models was five in Class-I and Class-II and four in Class-III. Seven multivariate predictive models were finalized. The DVH relative percentage difference between the error-free and error dataset almost linearly increased as systematic error increased. In the case of random errors, the tendency of the DVH relative percentage difference was dependent on the structure’s location.Conclusion: Our study highlights three novel vital results. First, the common significant dosiomics indices (GLCM Energy and GLRLM_LRHGE) can characterize the MLC position error. Second, the finalized logistic regression model for MLC position error prediction showed excellent performance with AUC > 0.9. Third, the results of DVH were related to dosiomics analysis in that it reflects the characteristics of the MLC position error, and it was shown that dosiomics analysis could provide important information on localized dose distribution differences in addition to DVH information.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Investigation of the characteristics of multileaf collimator position errors: dose distribution- based error classification

Sheen

Shin

Kim

et al. 2022

Preprint

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“…With the development of radiation therapy technology, intensity-modulated radiation therapy (IMRT) and volumetric modulated radiation therapy (VMAT) are being widely used in various cancer treatments [1][2][3][4]. They can modulate fluence maps by using the multi-leaf collimator (MLC) to deliver high-dose radiation to treatment targets while delivering minimal dose of radiation to surrounding normal organs [5]. To deliver optimized dose distribution to patients, fluence complexity must be improved, and many MLC movements are required for its implementation.…”

Section: Introductionmentioning

confidence: 99%

Development of a Beam Source Modeling Approach to Calculate Head Scatter Factors for a 6 MV Unflattened Photon Beam

Park

Choi

Jang

2021

Progress in Medical Physics

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This study aimed to investigate the accuracy of head scatter factor (S c ) by applying a developed multi-leaf collimator (MLC) scatter source model for an unflattened photon beam.Methods: Sets of S c values were measured for various jaw-defined square and rectangular fields and MLC-defined square fields for developing dual-source model (DSM) and MLC scatter model. A 6 MV unflattened photon beam has been used. Measurements were performed using a 0.125 cm 3 cylindrical ionization chamber and a mini phantom. Then, the parameters of both models have been optimized, and S c has been calculated. The DSM and MLC scatter models have been verified by comparing the calculated values to the three S c set measurement values of the jaw-defined field and the two S c set measurement values of MLC-defined fields used in the existing modeling, respectively.Results: For jaw-defined fields, the calculated S c using the DSM was consistent with the measured S c value. This demonstrates that the DSM was properly optimized and modeled for the measured values. For the MLC-defined fields, the accuracy between the calculated and measured S c values with the addition of the MLC scatter source appeared to be high, but the only use of the DSM resulted in a significantly bigger differences.Conclusions: Both the DSM and MLC models could also be applied to an unflattened beam. When considering scattered radiation from the MLC by adding an MLC scatter source model, it showed a higher degree of agreement with the actual measured S c value than when using only DSM in the same way as in previous studies.

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Define dose field to assess the modulation complexity of intensity-modulated radiation therapy

et al. 2021

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Evaluation of the plan delivery accuracy of intensity-modulated radiation therapy by texture analysis using fluence maps

Cited by 5 publications

References 33 publications

Investigation of the characteristics of multileaf collimator position errors: dose distribution- based error classification

Investigation of the characteristics of multileaf collimator position errors: dose distribution- based error classification

Development of a Beam Source Modeling Approach to Calculate Head Scatter Factors for a 6 MV Unflattened Photon Beam

Define dose field to assess the modulation complexity of intensity-modulated radiation therapy

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