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D Markel - One of the best experts on this subject based on the ideXlab platform.

  • Dosimetric comparison between the prostate intensity-modulated radiotherapy (IMRT) and volumetric-modulated arc therapy (VMAT) plans using the planning target volume (PTV) dose–volume factor
    Journal of Radiotherapy in Practice, 2016
    Co-Authors: James C. L. Chow, Runqing Jiang, Alexander Kiciak, D Markel
    Abstract:

    Background We demonstrated that our proposed planning target volume (PTV) dose–volume factor (PDVF) can be used to evaluate the PTV dose coverage between the intensity-modulated radiotherapy (IMRT) and volumetric-modulated arc therapy (VMAT) plans based on 90 prostate patients. Purpose PDVF were determined from the prostate IMRT and VMAT plans to compare their variation of PTV dose coverage. Comparisons of the PDVF with other plan evaluation parameters such as D 5% , D 95% , D 99% , D mean , conformity index (CI), homogeneity index (HI), gradient index (GI) and prostate tumour control probability (TCP) were carried out. Methods and materials Prostate IMRT and VMAT plans using the 6 MV photon beams were created from 40 and 50 patients, respectively. Dosimetric indices (CI, HI and GI), dose–volume points ( D 5% , D 95% , D 99% and D mean ) and prostate TCP were calculated according to the PTV dose–volume histograms (DVHs) of the plans. All PTV DVH curves were fitted using the Gaussian Error Function (GEF) model. The PDVF were calculated based on the GEF parameters. Results From the PTV DVHs of the prostate IMRT and VMAT plans, the average D 99% of the PTV for IMRT and VMAT were 74·1 and 74·5 Gy, respectively. The average prostate TCP were 0·956 and 0·958 for the IMRT and VMAT plans, respectively. The average PDVF of the IMRT and VMAT plans were 0·970 and 0·983, respectively. Although both the IMRT and VMAT plans showed very similar prostate TCP, the dosimetric and radiobiological results of the VMAT technique were slightly better than IMRT. Conclusion The calculated PDVF for the prostate IMRT and VMAT plans agreed well with other dosimetric and radiobiological parameters in this study. PDVF was verified as an alternative of evaluation parameter in the quality assurance of prostate treatment planning.

  • Poster - Thur Eve - 59: Dosimetric evaluation on the variation of PTV coverage due to patient size reduction using the prostate dose-volume factor in prostate radiotherapy.
    Medical Physics, 2012
    Co-Authors: James C. L. Chow, R Jiang, D Markel
    Abstract:

    We proposed to use the prostate dose‐volume factor (PDVF), derived from the dose‐volume dataset of planning target volume (PTV) in prostate radiotherapy to evaluate treatment plans of prostate volumetric modulated arc therapy (VMAT) and intensity modulated radiotherapy(IMRT). To demonstrate plan evaluation using PDVF, VMAT and 7‐beam IMRT plans were created in three patients with prostate volumes equal to 32, 48.4 and 86.5 cm3. Dose variation of PTV was made by reducing the body contour of the patients with reduced depth equal to 0.5 – 2 cm, mimicking a patient size reduction in the treatment. The Gaussian Error Function was used to model the cumulative dose‐volume histogram of the PTV, and PDVF was calculated as per the parameters of the Error Function. PDVF = 1 reflects an ideal PTV coverage (i.e. 100% prescribed dose in 100% target volume). We found that for PDVF ranged 0.98 – 1 in prostate VMAT and IMRT without patient size change, reduced depth led to PDVF decreasing 0.03 ± 4.7 × 10−4 (VMAT) and 0.04 ± 9.7 × 10−3(IMRT) per cm for the patients. The variation of PTV coverage on the prostate volume due to the reduced depth was less significant in VMAT plans than IMRT. It is concluded that PDVF was successfully used to evaluate the variation of PTV coverage due to the weight loss of patient in prostate VMAT and IMRT. Degradation of PTV coverage in prostate VMAT regarding patient size reduction is less significant than that in IMRT.

  • su e t 658 calculation of the prostate equivalent uniform dose for interfraction organ motion using the Gaussian Error Function model
    Medical Physics, 2011
    Co-Authors: W Shan, D Markel, J Chow, R Jiang
    Abstract:

    Purpose: The Gaussian Error Function (GEF) model was used to fit into the dose‐volume histograms (DVHs) of prostate IMRT and calculate the prostate equivalent uniform dose (EUD) associated with interfraction organ motion. Methods: Three patients with small (39 cc), medium (60 cc) and large (87 cc) prostate volume were selected from a group of twenty in this study. Cumulative DVHs for the prostate that were shifted in the anterior‐posterior directions based on a 7‐beam IMRT plan were calculated and modeled using the Pinnacle3 treatment planning system (TPS) and GEF. To simulate the interfraction prostate motion, the prostate was shifted 1 cm in the anterior and posterior directions in 2 mm steps, using the dose distribution based on the IMRT plan without actual prostate motion. The prostate cumulative DVHs were converted to corresponding differential DVHs to calculate the prostate EUDs in each interfraction motion using MATLAB. Results: Prostate EUD was computed to per fraction in order to measure the equivalent dose at each movement step. Prostate EUDs were found to decrease as the prostate shifted to both the anterior and posterior directions. The prostate EUD was also expected to have the maximum value at the isocentre, since the target received the best dose coverage when the prostate displacement remains zero. Our result showed that patient with the smallest prostate volume (39 cc) in the group has the smallest prostate EUD, when the prostate was shifted 1 cm anteriorly and posteriorly. Since the percentage difference of the prostate EUD calculated by the TPS and GEF is significantly less than 0.5%, we consider the GEF model a good potential alternative to determine the prostate EUD. Conclusions: We validated our GEF model which can predict the prostate EUD with accuracy less than 0.5% compared to the results from the TPS.

  • SU‐E‐T‐658: Calculation of the Prostate Equivalent Uniform Dose for Interfraction Organ Motion Using the Gaussian Error Function Model
    Medical Physics, 2011
    Co-Authors: W Shan, D Markel, J Chow, R Jiang
    Abstract:

    Purpose: The Gaussian Error Function (GEF) model was used to fit into the dose‐volume histograms (DVHs) of prostate IMRT and calculate the prostate equivalent uniform dose (EUD) associated with interfraction organ motion. Methods: Three patients with small (39 cc), medium (60 cc) and large (87 cc) prostate volume were selected from a group of twenty in this study. Cumulative DVHs for the prostate that were shifted in the anterior‐posterior directions based on a 7‐beam IMRT plan were calculated and modeled using the Pinnacle3 treatment planning system (TPS) and GEF. To simulate the interfraction prostate motion, the prostate was shifted 1 cm in the anterior and posterior directions in 2 mm steps, using the dose distribution based on the IMRT plan without actual prostate motion. The prostate cumulative DVHs were converted to corresponding differential DVHs to calculate the prostate EUDs in each interfraction motion using MATLAB. Results: Prostate EUD was computed to per fraction in order to measure the equivalent dose at each movement step. Prostate EUDs were found to decrease as the prostate shifted to both the anterior and posterior directions. The prostate EUD was also expected to have the maximum value at the isocentre, since the target received the best dose coverage when the prostate displacement remains zero. Our result showed that patient with the smallest prostate volume (39 cc) in the group has the smallest prostate EUD, when the prostate was shifted 1 cm anteriorly and posteriorly. Since the percentage difference of the prostate EUD calculated by the TPS and GEF is significantly less than 0.5%, we consider the GEF model a good potential alternative to determine the prostate EUD. Conclusions: We validated our GEF model which can predict the prostate EUD with accuracy less than 0.5% compared to the results from the TPS.

  • SU‐E‐T‐652: Rectal Equivalent Uniform Dose Analysis on the Prostate IMRT for Interfraction Organ Motion Using the Gaussian Error Function
    Medical Physics, 2011
    Co-Authors: W Shan, D Markel, J Chow, R Jiang
    Abstract:

    Purpose: The aim of this study is to verify the calculation of rectal equivalent uniform dose (EUD) using the Gaussian Error Function (GEF), which can reduce the dose‐volume database to enhance the computing efficiency. Methods: For a group of 20 prostate patients, cumulative dose‐volume histograms (cDVHs) for the rectum, shifted in the anterior—posterior directions based on a 7‐beam IMRT plan, were calculated and modeled using the Pinnacle3 treatment planning system (TPS) and GEF, respectively. The range of rectal shift for each patient was measured by daily electronic portal imaging with fiducial gold markers in the prostate. The shape of cDVH curve was fitted into the GEF model, and then the cDVHs were converted to corresponding differential DVHs to calculate the rectal EUDs in each interfraction organ motion. Results: Rectal EUD was calculated per fraction to determine the equivalent dose at each movement step. Our results showed that rectal EUDs increased as the rectum shifted to anterior direction and decreased in the posterior direction. Moreover, it is found that rectal EUDs have a negative linear relationship with respect to the organ displacement. Based on the results, the patient with the smallest prostate (volume = 40 cc) in the group received the highest rectal EUD when the rectum shifted 8 mm anterior. Percentage difference of rectal EUD using the TPS and GEF has been calculated for each movement. Since the results are less than 0.5%, the GEF model is considered a good potential alternative of the TPS. Conclusions: We concluded that the calculation of rectal EUD using the GEF model was validated with Error less than 0.5%.

James C. L. Chow - One of the best experts on this subject based on the ideXlab platform.

  • Dosimetric variations in calculation grid size in prostate VMAT: a dose-volume histogram analysis using the Gaussian Error Function
    Journal of Radiotherapy in Practice, 2017
    Co-Authors: James C. L. Chow, Runqing Jiang, Daniel Markel
    Abstract:

    Background Varying the calculation grid size can change the results of dose-volume and radiobiological parameters in a treatment plan, and therefore has an impact on the treatment planning quality assurance. Purpose This study investigated the dosimetric influence of the calculation grid size variation in the prostate volumetric modulated arc therapy (VMAT) plan. Methods and materials Dose distributions of 10 prostate VMAT plans were acquired using calculation grid sizes of 1–5 mm. Dose-volume histogram (DVH) analysis was carried out to determine the dose-volume variation corresponding to the grid size change using the Gaussian Error Function (GEF). At the same time, dose-volume points, dose-volume parameters and radiobiological parameters were calculated based on DVHs of targets and organs at risk (OARs) for each grid size. Results Comparing percentage variations of GEF parameters between the planning target volume (PTV) and clinical target volume (CTV), GEF parameters of the PTV were found varied more significantly than the CTV. This resulted in larger variations of dose-volume (%ΔCI=40·02 versus 13·55%, %ΔHI=12·45 versus 2·93% and %ΔGI=0·22 versus 0·06%) and radiobiological parameters (%ΔTCP=0·61 versus 0·25% and %ΔEUD=2·11 versus 0·26%) of the PTV compared with CTV. For OARs, the rectal wall showed a larger dose-volume variation than the rectum. However, similar dose-volume variation due to grid size change was not found in the bladder, bladder wall and femur. Conclusions Knowing the dosimetric variation in this study is important to the radiotherapy staff in the quality assurance for the prostate VMAT planning.

  • Dosimetric comparison between the prostate intensity-modulated radiotherapy (IMRT) and volumetric-modulated arc therapy (VMAT) plans using the planning target volume (PTV) dose–volume factor
    Journal of Radiotherapy in Practice, 2016
    Co-Authors: James C. L. Chow, Runqing Jiang, Alexander Kiciak, D Markel
    Abstract:

    Background We demonstrated that our proposed planning target volume (PTV) dose–volume factor (PDVF) can be used to evaluate the PTV dose coverage between the intensity-modulated radiotherapy (IMRT) and volumetric-modulated arc therapy (VMAT) plans based on 90 prostate patients. Purpose PDVF were determined from the prostate IMRT and VMAT plans to compare their variation of PTV dose coverage. Comparisons of the PDVF with other plan evaluation parameters such as D 5% , D 95% , D 99% , D mean , conformity index (CI), homogeneity index (HI), gradient index (GI) and prostate tumour control probability (TCP) were carried out. Methods and materials Prostate IMRT and VMAT plans using the 6 MV photon beams were created from 40 and 50 patients, respectively. Dosimetric indices (CI, HI and GI), dose–volume points ( D 5% , D 95% , D 99% and D mean ) and prostate TCP were calculated according to the PTV dose–volume histograms (DVHs) of the plans. All PTV DVH curves were fitted using the Gaussian Error Function (GEF) model. The PDVF were calculated based on the GEF parameters. Results From the PTV DVHs of the prostate IMRT and VMAT plans, the average D 99% of the PTV for IMRT and VMAT were 74·1 and 74·5 Gy, respectively. The average prostate TCP were 0·956 and 0·958 for the IMRT and VMAT plans, respectively. The average PDVF of the IMRT and VMAT plans were 0·970 and 0·983, respectively. Although both the IMRT and VMAT plans showed very similar prostate TCP, the dosimetric and radiobiological results of the VMAT technique were slightly better than IMRT. Conclusion The calculated PDVF for the prostate IMRT and VMAT plans agreed well with other dosimetric and radiobiological parameters in this study. PDVF was verified as an alternative of evaluation parameter in the quality assurance of prostate treatment planning.

  • SU-E-J-164: Estimation of DVH Variation for PTV Due to Interfraction Organ Motion in Prostate VMAT Using Gaussian Error Function
    Medical Physics, 2015
    Co-Authors: C Lewis, R Jiang, James C. L. Chow
    Abstract:

    Purpose: We developed a method to predict the change of DVH for PTV due to interfraction organ motion in prostate VMAT without repeating the CT scan and treatment planning. The method is based on a pre-calculated patient database with DVH curves of PTV modelled by the Gaussian Error Function (GEF). Methods: For a group of 30 patients with different prostate sizes, their VMAT plans were recalculated by shifting their PTVs 1 cm with 10 increments in the anterior-posterior, left-right and superior-inferior directions. The DVH curve of PTV in each replan was then fitted by the GEF to determine parameters describing the shape of curve. Information of parameters, varying with the DVH change due to prostate motion for different prostate sizes, was analyzed and stored in a database of a program written by MATLAB. Results: To predict a new DVH for PTV due to prostate interfraction motion, prostate size and shift distance with direction were input to the program. Parameters modelling the DVH for PTV were determined based on the pre-calculated patient dataset. From the new parameters, DVH curves of PTVs with and without considering the prostate motion were plotted for comparison. The program was verified with different prostate cases involving interfraction prostate shifts and replans. Conclusion: Variation of DVH for PTV in prostate VMAT can be predicted using a pre-calculated patient database with DVH curve fitting. The computing time is fast because CT rescan and replan are not required. This quick DVH estimation can help radiation staff to determine if the changed PTV coverage due to prostate shift is tolerable in the treatment. However, it should be noted that the program can only consider prostate interfraction motions along three axes, and is restricted to prostate VMAT plan using the same plan script in the treatment planning system.

  • SU-E-T-385: Evaluation of DVH Change for PTV Due to Patient Weight Loss in Prostate VMAT Using Gaussian Error Function
    Medical Physics, 2015
    Co-Authors: H Viraganathan, R Jiang, James C. L. Chow
    Abstract:

    Purpose: We proposed a method to predict the change of dose-volume histogram (DVH) for PTV due to patient weight loss in prostate volumetric modulated arc therapy (VMAT). This method is based on a pre-calculated patient dataset and DVH curve fitting using the Gaussian Error Function (GEF). Methods: Pre-calculated dose-volume data from patients having weight loss in prostate VMAT was employed to predict the change of PTV coverage due to reduced depth in external contour. The effect of patient weight loss in treatment was described by a prostate dose-volume factor (PDVF), which was evaluated by the prostate PTV. Along with the PDVF, the GEF was used to fit into the DVH curve for the PTV. To predict a new DVH due to weight loss, parameters from the GEF describing the shape of DVH curve were determined. Since the parameters were related to the PDVF as per the specific reduced depth, we could first predict the PDVF at a reduced depth based on the prostate size from the pre-calculated dataset. Then parameters of the GEF could be determined from the PDVF to plot the new DVH for the PTV corresponding to the reduced depth. Results: A MATLAB program was built basing on the patient dataset with different prostate sizes. We input data of the prostate size and reduced depth of the patient into the program. The program then calculated the PDVF and DVH for the PTV considering the patient weight loss. The program was verified by different patient cases with various reduced depths. Conclusion: Our method can estimate the change of DVH for the PTV due to patient weight loss quickly without CT rescan and replan. This would help the radiation staff to predict the change of PTV coverage, when patient’s external contour reduced in prostate VMAT.

  • Poster - Thur Eve - 59: Dosimetric evaluation on the variation of PTV coverage due to patient size reduction using the prostate dose-volume factor in prostate radiotherapy.
    Medical Physics, 2012
    Co-Authors: James C. L. Chow, R Jiang, D Markel
    Abstract:

    We proposed to use the prostate dose‐volume factor (PDVF), derived from the dose‐volume dataset of planning target volume (PTV) in prostate radiotherapy to evaluate treatment plans of prostate volumetric modulated arc therapy (VMAT) and intensity modulated radiotherapy(IMRT). To demonstrate plan evaluation using PDVF, VMAT and 7‐beam IMRT plans were created in three patients with prostate volumes equal to 32, 48.4 and 86.5 cm3. Dose variation of PTV was made by reducing the body contour of the patients with reduced depth equal to 0.5 – 2 cm, mimicking a patient size reduction in the treatment. The Gaussian Error Function was used to model the cumulative dose‐volume histogram of the PTV, and PDVF was calculated as per the parameters of the Error Function. PDVF = 1 reflects an ideal PTV coverage (i.e. 100% prescribed dose in 100% target volume). We found that for PDVF ranged 0.98 – 1 in prostate VMAT and IMRT without patient size change, reduced depth led to PDVF decreasing 0.03 ± 4.7 × 10−4 (VMAT) and 0.04 ± 9.7 × 10−3(IMRT) per cm for the patients. The variation of PTV coverage on the prostate volume due to the reduced depth was less significant in VMAT plans than IMRT. It is concluded that PDVF was successfully used to evaluate the variation of PTV coverage due to the weight loss of patient in prostate VMAT and IMRT. Degradation of PTV coverage in prostate VMAT regarding patient size reduction is less significant than that in IMRT.

R Jiang - One of the best experts on this subject based on the ideXlab platform.

  • SU-E-J-164: Estimation of DVH Variation for PTV Due to Interfraction Organ Motion in Prostate VMAT Using Gaussian Error Function
    Medical Physics, 2015
    Co-Authors: C Lewis, R Jiang, James C. L. Chow
    Abstract:

    Purpose: We developed a method to predict the change of DVH for PTV due to interfraction organ motion in prostate VMAT without repeating the CT scan and treatment planning. The method is based on a pre-calculated patient database with DVH curves of PTV modelled by the Gaussian Error Function (GEF). Methods: For a group of 30 patients with different prostate sizes, their VMAT plans were recalculated by shifting their PTVs 1 cm with 10 increments in the anterior-posterior, left-right and superior-inferior directions. The DVH curve of PTV in each replan was then fitted by the GEF to determine parameters describing the shape of curve. Information of parameters, varying with the DVH change due to prostate motion for different prostate sizes, was analyzed and stored in a database of a program written by MATLAB. Results: To predict a new DVH for PTV due to prostate interfraction motion, prostate size and shift distance with direction were input to the program. Parameters modelling the DVH for PTV were determined based on the pre-calculated patient dataset. From the new parameters, DVH curves of PTVs with and without considering the prostate motion were plotted for comparison. The program was verified with different prostate cases involving interfraction prostate shifts and replans. Conclusion: Variation of DVH for PTV in prostate VMAT can be predicted using a pre-calculated patient database with DVH curve fitting. The computing time is fast because CT rescan and replan are not required. This quick DVH estimation can help radiation staff to determine if the changed PTV coverage due to prostate shift is tolerable in the treatment. However, it should be noted that the program can only consider prostate interfraction motions along three axes, and is restricted to prostate VMAT plan using the same plan script in the treatment planning system.

  • SU-E-T-385: Evaluation of DVH Change for PTV Due to Patient Weight Loss in Prostate VMAT Using Gaussian Error Function
    Medical Physics, 2015
    Co-Authors: H Viraganathan, R Jiang, James C. L. Chow
    Abstract:

    Purpose: We proposed a method to predict the change of dose-volume histogram (DVH) for PTV due to patient weight loss in prostate volumetric modulated arc therapy (VMAT). This method is based on a pre-calculated patient dataset and DVH curve fitting using the Gaussian Error Function (GEF). Methods: Pre-calculated dose-volume data from patients having weight loss in prostate VMAT was employed to predict the change of PTV coverage due to reduced depth in external contour. The effect of patient weight loss in treatment was described by a prostate dose-volume factor (PDVF), which was evaluated by the prostate PTV. Along with the PDVF, the GEF was used to fit into the DVH curve for the PTV. To predict a new DVH due to weight loss, parameters from the GEF describing the shape of DVH curve were determined. Since the parameters were related to the PDVF as per the specific reduced depth, we could first predict the PDVF at a reduced depth based on the prostate size from the pre-calculated dataset. Then parameters of the GEF could be determined from the PDVF to plot the new DVH for the PTV corresponding to the reduced depth. Results: A MATLAB program was built basing on the patient dataset with different prostate sizes. We input data of the prostate size and reduced depth of the patient into the program. The program then calculated the PDVF and DVH for the PTV considering the patient weight loss. The program was verified by different patient cases with various reduced depths. Conclusion: Our method can estimate the change of DVH for the PTV due to patient weight loss quickly without CT rescan and replan. This would help the radiation staff to predict the change of PTV coverage, when patient’s external contour reduced in prostate VMAT.

  • Poster - Thur Eve - 59: Dosimetric evaluation on the variation of PTV coverage due to patient size reduction using the prostate dose-volume factor in prostate radiotherapy.
    Medical Physics, 2012
    Co-Authors: James C. L. Chow, R Jiang, D Markel
    Abstract:

    We proposed to use the prostate dose‐volume factor (PDVF), derived from the dose‐volume dataset of planning target volume (PTV) in prostate radiotherapy to evaluate treatment plans of prostate volumetric modulated arc therapy (VMAT) and intensity modulated radiotherapy(IMRT). To demonstrate plan evaluation using PDVF, VMAT and 7‐beam IMRT plans were created in three patients with prostate volumes equal to 32, 48.4 and 86.5 cm3. Dose variation of PTV was made by reducing the body contour of the patients with reduced depth equal to 0.5 – 2 cm, mimicking a patient size reduction in the treatment. The Gaussian Error Function was used to model the cumulative dose‐volume histogram of the PTV, and PDVF was calculated as per the parameters of the Error Function. PDVF = 1 reflects an ideal PTV coverage (i.e. 100% prescribed dose in 100% target volume). We found that for PDVF ranged 0.98 – 1 in prostate VMAT and IMRT without patient size change, reduced depth led to PDVF decreasing 0.03 ± 4.7 × 10−4 (VMAT) and 0.04 ± 9.7 × 10−3(IMRT) per cm for the patients. The variation of PTV coverage on the prostate volume due to the reduced depth was less significant in VMAT plans than IMRT. It is concluded that PDVF was successfully used to evaluate the variation of PTV coverage due to the weight loss of patient in prostate VMAT and IMRT. Degradation of PTV coverage in prostate VMAT regarding patient size reduction is less significant than that in IMRT.

  • SU‐E‐T‐658: Calculation of the Prostate Equivalent Uniform Dose for Interfraction Organ Motion Using the Gaussian Error Function Model
    Medical Physics, 2011
    Co-Authors: W Shan, D Markel, J Chow, R Jiang
    Abstract:

    Purpose: The Gaussian Error Function (GEF) model was used to fit into the dose‐volume histograms (DVHs) of prostate IMRT and calculate the prostate equivalent uniform dose (EUD) associated with interfraction organ motion. Methods: Three patients with small (39 cc), medium (60 cc) and large (87 cc) prostate volume were selected from a group of twenty in this study. Cumulative DVHs for the prostate that were shifted in the anterior‐posterior directions based on a 7‐beam IMRT plan were calculated and modeled using the Pinnacle3 treatment planning system (TPS) and GEF. To simulate the interfraction prostate motion, the prostate was shifted 1 cm in the anterior and posterior directions in 2 mm steps, using the dose distribution based on the IMRT plan without actual prostate motion. The prostate cumulative DVHs were converted to corresponding differential DVHs to calculate the prostate EUDs in each interfraction motion using MATLAB. Results: Prostate EUD was computed to per fraction in order to measure the equivalent dose at each movement step. Prostate EUDs were found to decrease as the prostate shifted to both the anterior and posterior directions. The prostate EUD was also expected to have the maximum value at the isocentre, since the target received the best dose coverage when the prostate displacement remains zero. Our result showed that patient with the smallest prostate volume (39 cc) in the group has the smallest prostate EUD, when the prostate was shifted 1 cm anteriorly and posteriorly. Since the percentage difference of the prostate EUD calculated by the TPS and GEF is significantly less than 0.5%, we consider the GEF model a good potential alternative to determine the prostate EUD. Conclusions: We validated our GEF model which can predict the prostate EUD with accuracy less than 0.5% compared to the results from the TPS.

  • su e t 658 calculation of the prostate equivalent uniform dose for interfraction organ motion using the Gaussian Error Function model
    Medical Physics, 2011
    Co-Authors: W Shan, D Markel, J Chow, R Jiang
    Abstract:

    Purpose: The Gaussian Error Function (GEF) model was used to fit into the dose‐volume histograms (DVHs) of prostate IMRT and calculate the prostate equivalent uniform dose (EUD) associated with interfraction organ motion. Methods: Three patients with small (39 cc), medium (60 cc) and large (87 cc) prostate volume were selected from a group of twenty in this study. Cumulative DVHs for the prostate that were shifted in the anterior‐posterior directions based on a 7‐beam IMRT plan were calculated and modeled using the Pinnacle3 treatment planning system (TPS) and GEF. To simulate the interfraction prostate motion, the prostate was shifted 1 cm in the anterior and posterior directions in 2 mm steps, using the dose distribution based on the IMRT plan without actual prostate motion. The prostate cumulative DVHs were converted to corresponding differential DVHs to calculate the prostate EUDs in each interfraction motion using MATLAB. Results: Prostate EUD was computed to per fraction in order to measure the equivalent dose at each movement step. Prostate EUDs were found to decrease as the prostate shifted to both the anterior and posterior directions. The prostate EUD was also expected to have the maximum value at the isocentre, since the target received the best dose coverage when the prostate displacement remains zero. Our result showed that patient with the smallest prostate volume (39 cc) in the group has the smallest prostate EUD, when the prostate was shifted 1 cm anteriorly and posteriorly. Since the percentage difference of the prostate EUD calculated by the TPS and GEF is significantly less than 0.5%, we consider the GEF model a good potential alternative to determine the prostate EUD. Conclusions: We validated our GEF model which can predict the prostate EUD with accuracy less than 0.5% compared to the results from the TPS.

Runqing Jiang - One of the best experts on this subject based on the ideXlab platform.

  • Dosimetric variations in calculation grid size in prostate VMAT: a dose-volume histogram analysis using the Gaussian Error Function
    Journal of Radiotherapy in Practice, 2017
    Co-Authors: James C. L. Chow, Runqing Jiang, Daniel Markel
    Abstract:

    Background Varying the calculation grid size can change the results of dose-volume and radiobiological parameters in a treatment plan, and therefore has an impact on the treatment planning quality assurance. Purpose This study investigated the dosimetric influence of the calculation grid size variation in the prostate volumetric modulated arc therapy (VMAT) plan. Methods and materials Dose distributions of 10 prostate VMAT plans were acquired using calculation grid sizes of 1–5 mm. Dose-volume histogram (DVH) analysis was carried out to determine the dose-volume variation corresponding to the grid size change using the Gaussian Error Function (GEF). At the same time, dose-volume points, dose-volume parameters and radiobiological parameters were calculated based on DVHs of targets and organs at risk (OARs) for each grid size. Results Comparing percentage variations of GEF parameters between the planning target volume (PTV) and clinical target volume (CTV), GEF parameters of the PTV were found varied more significantly than the CTV. This resulted in larger variations of dose-volume (%ΔCI=40·02 versus 13·55%, %ΔHI=12·45 versus 2·93% and %ΔGI=0·22 versus 0·06%) and radiobiological parameters (%ΔTCP=0·61 versus 0·25% and %ΔEUD=2·11 versus 0·26%) of the PTV compared with CTV. For OARs, the rectal wall showed a larger dose-volume variation than the rectum. However, similar dose-volume variation due to grid size change was not found in the bladder, bladder wall and femur. Conclusions Knowing the dosimetric variation in this study is important to the radiotherapy staff in the quality assurance for the prostate VMAT planning.

  • Dosimetric comparison between the prostate intensity-modulated radiotherapy (IMRT) and volumetric-modulated arc therapy (VMAT) plans using the planning target volume (PTV) dose–volume factor
    Journal of Radiotherapy in Practice, 2016
    Co-Authors: James C. L. Chow, Runqing Jiang, Alexander Kiciak, D Markel
    Abstract:

    Background We demonstrated that our proposed planning target volume (PTV) dose–volume factor (PDVF) can be used to evaluate the PTV dose coverage between the intensity-modulated radiotherapy (IMRT) and volumetric-modulated arc therapy (VMAT) plans based on 90 prostate patients. Purpose PDVF were determined from the prostate IMRT and VMAT plans to compare their variation of PTV dose coverage. Comparisons of the PDVF with other plan evaluation parameters such as D 5% , D 95% , D 99% , D mean , conformity index (CI), homogeneity index (HI), gradient index (GI) and prostate tumour control probability (TCP) were carried out. Methods and materials Prostate IMRT and VMAT plans using the 6 MV photon beams were created from 40 and 50 patients, respectively. Dosimetric indices (CI, HI and GI), dose–volume points ( D 5% , D 95% , D 99% and D mean ) and prostate TCP were calculated according to the PTV dose–volume histograms (DVHs) of the plans. All PTV DVH curves were fitted using the Gaussian Error Function (GEF) model. The PDVF were calculated based on the GEF parameters. Results From the PTV DVHs of the prostate IMRT and VMAT plans, the average D 99% of the PTV for IMRT and VMAT were 74·1 and 74·5 Gy, respectively. The average prostate TCP were 0·956 and 0·958 for the IMRT and VMAT plans, respectively. The average PDVF of the IMRT and VMAT plans were 0·970 and 0·983, respectively. Although both the IMRT and VMAT plans showed very similar prostate TCP, the dosimetric and radiobiological results of the VMAT technique were slightly better than IMRT. Conclusion The calculated PDVF for the prostate IMRT and VMAT plans agreed well with other dosimetric and radiobiological parameters in this study. PDVF was verified as an alternative of evaluation parameter in the quality assurance of prostate treatment planning.

  • Technical note: calculation of normal tissue complication probability using Gaussian Error Function model.
    Medical physics, 2010
    Co-Authors: James C. L. Chow, D Markel, Runqing Jiang
    Abstract:

    Purpose: The Gaussian Error Function was first used and verified in normal tissue complication probability (NTCP) calculation to reduce the dose-volume histogram (DVH) database by replacing the dose-volume bin set with the Error Function parameters for the differential DVH (dDVH). Methods: Seven-beam intensity modulated radiation therapy(IMRT)treatment planning was performed in three patients with small ( 40 cm 3 ) , medium ( 53 cm 3 ) , and large ( 87 cm 3 ) prostate volume, selected from a group of 20 patients. Rectal dDVH varying with the interfraction prostate motion along the anterior-posterior direction was determined by the treatment planning system (TPS) and modeled by the Gaussian Error Function model for the three patients. Rectal NTCP was then calculated based on the routine dose-volume bin set of the rectum by the TPS and the Error Function model. The variations in the rectal NTCP with the prostate motion and volume were studied. Results: For the ranges of prostate motion of 8–2, 4–8, and 4–3 mm along the anterior-posterior direction for the small, medium, and large prostate patient, the rectal NTCP was determined varying in the ranges of 4.6%–4.8%, 4.5%–4.7%, and 4.6%–4.7%, respectively. The deviation of the rectal NTCP calculated by the TPS and the Gaussian Error Function model was within ±0.1%. Conclusions: The Gaussian Error Function was successfully applied in the NTCP calculation by replacing the dose-volume bin set with the model parameters. This provides an option in the NTCP calculation using a reduced size of dose-volumedatabase. Moreover, the rectal NTCP was found varying in about ±0.2% with the interfraction prostate motion along the anterior-posterior direction in the radiation treatment. The dependence of the variation in the rectal NTCP with the interfraction prostate motion on the prostate volume was found to be more significant in the patient with larger prostate.

  • Poster — Thur Eve — 18: Differential Dose‐Volume Histogram Modeling Using the Gaussian Error Function
    Medical Physics, 2010
    Co-Authors: James C. L. Chow, D Markel, Runqing Jiang
    Abstract:

    The Gaussian Error Function (GEF) was first used to model rectal differential dose‐volume histograms (dDVH) for prostate intensity modulated radiation therapy(IMRT) plans incorporated with the interfraction prostate motion. Seven‐beam IMRTtreatment plans were created in three patients with small (40 cm3), medium (53 cm3) and large (87 cm3) prostate volume, selected from a group of 20 patients. The interfraction prostate motions were measured by comparing the digitally‐reconstructed radiographs (anterior and lateral views) from the original treatment plans to the corresponding daily electronic portal images in the treatment unit based on the implanted fiducial gold markers. The ranges of prostate motion were found to be 8 – 2 mm, 4 – 8 mm and 4 – 3 mm along the anterior‐posterior directions for the small, medium and large prostate patient, respectively. Rectal dDVH varying with the interfraction prostate motion were determined by the treatment planning system (TPS), and modeled by the GEF for the three patients. It was found that the rectal dDVH from the prostate plans modeled by the GEF agreed well with those calculated by the TPS. The successful modeling of dDVH results in a significant reduction of the dDVH database, because typically about 12 parameters of the GEF model can be used to substitute about 800 – 1000 dose‐volume bin set for each dDVH. This can greatly reduce the computer memory in the normal tissue complication probability calculation associated with a huge dDVH database.

  • poster thur eve 18 differential dose volume histogram modeling using the Gaussian Error Function
    Medical Physics, 2010
    Co-Authors: James C. L. Chow, D Markel, Runqing Jiang
    Abstract:

    The Gaussian Error Function (GEF) was first used to model rectal differential dose‐volume histograms (dDVH) for prostate intensity modulated radiation therapy(IMRT) plans incorporated with the interfraction prostate motion. Seven‐beam IMRTtreatment plans were created in three patients with small (40 cm3), medium (53 cm3) and large (87 cm3) prostate volume, selected from a group of 20 patients. The interfraction prostate motions were measured by comparing the digitally‐reconstructed radiographs (anterior and lateral views) from the original treatment plans to the corresponding daily electronic portal images in the treatment unit based on the implanted fiducial gold markers. The ranges of prostate motion were found to be 8 – 2 mm, 4 – 8 mm and 4 – 3 mm along the anterior‐posterior directions for the small, medium and large prostate patient, respectively. Rectal dDVH varying with the interfraction prostate motion were determined by the treatment planning system (TPS), and modeled by the GEF for the three patients. It was found that the rectal dDVH from the prostate plans modeled by the GEF agreed well with those calculated by the TPS. The successful modeling of dDVH results in a significant reduction of the dDVH database, because typically about 12 parameters of the GEF model can be used to substitute about 800 – 1000 dose‐volume bin set for each dDVH. This can greatly reduce the computer memory in the normal tissue complication probability calculation associated with a huge dDVH database.

Guibing Zhu - One of the best experts on this subject based on the ideXlab platform.

  • Robust Adaptive Finite-Time Tracking Control for Uncertain Euler-Lagrange Systems With Input Saturation
    IEEE Access, 2020
    Co-Authors: Chao Chen, Guibing Zhu, Qaing Zhang, Jianwei Zhang
    Abstract:

    In this paper, a robust adaptive finite-time (FT) tracking control scheme is proposed for Euler-Lagrange systems (ELSs) subject to nonparametric uncertainties, unknown disturbances and input saturation. In the design procedure, a Gaussian Error Function is utilized to approximate the input saturation nonlinearity. Following that, by employing the natural property that the upper bound of model parameters uncertainties is linear-in-parameters, the lumped uncertain term caused by uncertain model parameters and external disturbances is formulated by a linear-parametric form with a single parameter. And then, a novel robust adaptive tracking control law is designed to resolve the tracking control problem of uncertain ELSs. The proposed control scheme is featured by FT convergence rate, and robustness against uncertainties and unknown disturbances. Furthermore, the robust adaptive FT tracking control scheme is insensitive to the character of the uncertainties, and is with low computational burden and easy to implement in engineering applications. And its rigorous stability is analyzed with the aid of the Lyapunov stability theory, and its effectiveness is verified by simulation results and comparison.

  • Single-parameter-learning-based finite-time tracking control of underactuated MSVs under input saturation
    Control Engineering Practice, 2020
    Co-Authors: Guibing Zhu
    Abstract:

    Abstract This paper investigates the adaptive finite-time (FT) tracking control problem of underactuated marine surface vehicles (MSVs) subject to parameter uncertainties and external disturbances under input saturation. The input saturation nonlinearity is approximated employing Gaussian Error Function. Definition of hand position is extended to transform the original motion mathematical model of underactuated MSVs into the standard integral cascade form. The compounded uncertain vector synthesizing the uncertain parameters and unknown external disturbances is transformed into a linear parameterized form with a single parameter. Then, by employing the adaptive vector-backstepping design framework, a novel adaptive FT tracking control law is designed, and the estimation of the single unknown parameter is provided by an adaptive law online. Theoretical analysis shows that under the proposed tracking control scheme, FT convergence of position tracking Errors of underactuated MSVs into a small set around the origin is ensured, while all signals in the closed-loop tracking control system are bounded. Simulation and comparison verify the effectiveness of the proposed novel adaptive tracking control scheme.

  • Global Robust Adaptive Trajectory Tracking Control for Surface Ships Under Input Saturation
    IEEE Journal of Oceanic Engineering, 2020
    Co-Authors: Guibing Zhu
    Abstract:

    In this paper, we investigate the trajectory tracking control problem of surface ships subject to unknown parameters, unknown time-varying disturbances, and input saturation. The input saturation is approximated using a Gaussian Error Function. The compounded uncertain term caused by the unknown parameters and disturbances is transformed into a linear parametric form with a single parameter called virtual parameter. Then, a novel robust adaptive ship trajectory tracking control law is designed using the adaptive vector-backstepping design method, where the adaptive law online provides the estimation of the virtual parameter. Further, a finite-time control scheme is developed injecting a power Function vector of the position and velocity Errors into the proposed control scheme such that the control performance is improved. Both our control schemes are simple to compute and easy to implement in engineering applications. Theoretical analysis indicates that the designed control laws can force the surface ship to track the desired trajectory while guaranteeing the global uniform ultimate boundedness of all the signals in the closed-loop trajectory tracking control system of surface ships. Simulation results and comparison verify the effectiveness of our novel robust adaptive trajectory tracking control schemes.

  • Robust adaptive neural trajectory tracking control of unmanned surface vessels under input saturation
    2019 Chinese Control Conference (CCC), 2019
    Co-Authors: Guibing Zhu
    Abstract:

    In this paper, we investigate the trajectory tracking control problem for unmanned surface vessels (UVSs) with the dynamic uncertainties and unknown external disturbances under input saturation. The input saturation nonlinearity is approximated by a Gaussian Error Function, the FTNTD is used to remove the derivation operation of virtual control law, and the adaptive NN is applied to reconstruct the dynamic uncertainties of USVs. A novel nonlinear Function featured by “large-Error versus small-gain, small-Error versus large-gain” is embedded into virtual and actual control laws to improve the control performance and relieve the adverse effect of input saturation. Based on these methods, a novel robust adaptive neural trajectory tracking control scheme is proposed using the vector-backstepping design method. By means of a newly constructed non-quadratic Lyapunov Function, it is theoretically shown that all the signals in the closed-loop trajectory tracking control system of UVSs are bounded. Finally, simulation results verify the effectiveness of our novel robust adaptive neural trajectory tracking control scheme.

  • Error-Driven-Based Nonlinear Feedback Recursive Design for Adaptive NN Trajectory Tracking Control of Surface Ships With Input Saturation
    IEEE Intelligent Transportation Systems Magazine, 2019
    Co-Authors: Guibing Zhu
    Abstract:

    In this paper, we investigate the trajectory tracking control problem of surface ship subject to the dynamic uncertainties, unknown time-varying disturbances and input saturation. To handle the non-smooth input saturation nonlinearity and compensate the ship dynamic uncertainties, Gaussian Error Function and adaptive neural network technique are employed. In control design, to obtain the transient motion reference signal, finite-time nonlinear tracking differentiator is applied to generate virtual reference signal and to extract the derivative of virtual control law. Referring to the effects of the kinematics subsystem on the kinetics subsystem caused by the Error of tracking differentiator, and the effects of the input saturation on the control accuracy and the dynamic quality of the trajectory tracking control system, we propose an Error-driven-based nonlinear feedback recursive design technique to design trajectory tracking control law, and employ a new non-quadratic Lyapunov Functions to analyze the trajectory tracking control system stability. The proposed control scheme fully embodies the characteristics of the lowgain and high-gain control, and overcomes the effect of tracking differentiator Error on closed-loop system by recursive design method. Simulation results verify the effectiveness of our proposed control scheme.