Effect of lung volume on helical radiotherapy in esophageal cancer: are there predictive factors to achieve acceptable lung doses?

Bolukbas, Meltem Kirli; Karaca, Sibel

doi:10.1007/s00066-020-01581-4

Cited by 6 publications

(8 citation statements)

References 22 publications

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“…According to the results shown in Tables 5 and 6, for the three technologies, the group with lower PCTV i -L and PCTV i -L /TL L could significantly reduce MLD, V5, V10, V13, V15, V20, and V30 of the total lung. This result was similar to that of Bolukbas et al (22). Gong et al (30) found that the lung volume increased, but the heart dose did not decrease.…”

Section: Discussionsupporting

confidence: 90%

“…On this basis, we added eight more factors to find genuinely effective predictors. Unlike Bolukbas et al (22), our study is based on real targets of patients, and the predictors and cutoff points identified are closer to the real clinic situation.…”

Section: Introductionmentioning

confidence: 91%

“…In order to find more comprehensive and accurate predictors of lung dose, as many parameters as possible were included in this study. Based on the published literature (22,24) and years of clinical experience of our department, 10 parameters were finally counted in this study, namely, PCTV width (PCTV W ), PCTV length (PCTV L ), PCTV volume (PCTV V ), total lung volume (TL V ), total lung length (TL L ), PCTV volume/total lung volume (PCTV V /TL V ), PCTV inferior volume (PCTV i-V ), PCTV inferior length (PCTV i-L ), PCTV inferior volume/total lung volume (PCTV i-V /TL V ), and PCTV inferior length/total lung length (PCTV i-L /TL L ). These parameters consider factors such as target shape and target length and to a certain extent can comprehensively analyze the predictive ability of target parameters for lung dose.…”

Section: Treatment Planning Evaluationmentioning

confidence: 99%

“…The predictors could predict whether the plan can meet the constraints of lungs before designing the plan. Bolukbas et al (22) found that lung volume and lung volume/ PTV volume are acceptable predictors of lung dose using TOMO by contouring the virtual radiotherapy volume of upper EC. It provides a method for the design of treatment plans based on the linear accelerator for T-shaped UMEC.…”

Section: Introductionmentioning

confidence: 99%

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Investigation of Predictors to Achieve Acceptable Lung Dose in T-Shaped Upper and Middle Esophageal Cancer With IMRT and VMAT

et al. 2021

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PurposeThe purpose of this study is to investigate whether there are predictors and cutoff points that can predict the acceptable lung dose using intensity-modulated radiation therapy (IMRT) and volume-modulated arc therapy (VMAT) in radiotherapy for upper ang middle esophageal cancer.Material and MethodsEighty-two patients with T-shaped upper-middle esophageal cancer (UMEC) were enrolled in this retrospective study. Jaw-tracking IMRT plan (JT-IMRT), full-arc VMAT plan (F-VMAT), and pactial-arc VMAT plan (P-VMAT) were generated for each patient. Dosimetric parameters such as MLD and V20 of total lung were compared among the three plannings. Ten factors such as PCTVinferior length and PCTVinferior length/total lung length were calculated to find the predictors and cutoff points of the predictors. All patients were divided into two groups according to the cutoff points, and the dosimetric differences between the two groups of the three plans were compared. ANOVA, receiver operating characteristic (ROC) analysis, and Mann–Whitney U-test were performed for comparisons between datasets. A p <0.05 was considered statistically significant.ResultThe quality of the targets of the three plannings was comparable. The total lung dose in P-VMAT was significantly lower than that in JT IMRT and F-VMAT. Monitor unit (MU) of F-VMAT and P-VMAT was significantly lower than that of JT IMRT. ROC analysis showed that among JT IMRT, F-VMAT, and P-VMAT, PCTVi-L, and PCTVi-L/TLL had diagnostic power to predict the suitability of RT plans according to lung dose constraints of our department. For JT IMRT, the cutoff points of PCTVi-L and PCTVi-L/TLL were 16.6 and 0.59. For F-VMAT, the cutoff points of PCTVi-L and PCTVi-L/TLL were 16.75 and 0.62. For P-VMAT, the cutoff points of PCTVi-L and PCTVi-L/TLL were 15.15 and 0.59. After Mann–Whitney U-test analysis, it was found that among the three plannings, the group with lower PCTVi-L and PCTVi-L/TLL could significantly reduce the dose of total lung and heart (p <0.05).ConclusionPCTVi-L <16.6 and PCTVi-L/TLL <0.59 for JT IMRT, PCTVi-L <16.75 and PCTVi-L/TLL <0.62 for F-VMAT and PCTVi-L <15.15, and PCTVi-L/TLL <0.59 for P-VMAT can predict whether patients with T-shaped UMEC can meet the lung dose limits of our department.

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Section: Discussionsupporting

confidence: 90%

Section: Introductionmentioning

confidence: 91%

Section: Treatment Planning Evaluationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Investigation of Predictors to Achieve Acceptable Lung Dose in T-Shaped Upper and Middle Esophageal Cancer With IMRT and VMAT

et al. 2021

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“…PTV/lung volume ratio has been shown a reliable factor for predicting lung dose [ 17 , 18 ]. In this study, as 6 out of 20 patients had neck lymph node metastasis, physical and EQD 2 total lung V 20 had poor linear correlations with volume ratio (LN to total lung) .…”

Section: Discussionmentioning

confidence: 99%

Regression models for predicting physical and EQD2 plan parameters of two methods of hybrid planning for stage III NSCLC

Wang

Zhou

Gan³

et al. 2021

Radiat Oncol

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Background/purpose To establish regression models of physical and equivalent dose in 2 Gy per fraction (EQD2) plan parameters of two kinds of hybrid planning for stage III NSCLC. Methods Two kinds of hybrid plans named conventional fraction radiotherapy & stereotactic body radiotherapy (C&S) and conventional fraction radiotherapy & simultaneous integrated boost (C&SIB) were retrospectively made for 20 patients with stage III NSCLC. Prescription dose of C&S plans was 2 Gy × 30f for planning target volume of lymph node (PTVLN) and 12.5 Gy × 4f for planning target volume of primary tumor (PTVPT), while prescription dose of C&SIB plans was 2 Gy × 26f for PTVLN and sequential 2 Gy × 4f for PTVLN combined with 12.5 Gy × 4f for PTVPT. Regression models of physical and EQD2 plan parameters were established based on anatomical geometry features for two kinds of hybrid plans. The features were mainly characterized by volume ratio, min distance and overlapping slices thickness of two structures. The possibilities of regression models of EQD2 plan parameters were verified by spearman’s correlation coefficients between physical and EQD2 plan parameters, and the influence on the consistence of fitting goodness between physical and EQD2 models was investigated by the correlations between physical and EQD2 plan parameters. Finally, physical and EQD2 models predictions were compared with plan parameters for two new patients. Results Physical and EQD2 plan parameters of PTVLN CI60Gy have shown strong positive correlations with PTVLN volume and min distance(PT to LN), and strong negative correlations with PTVPT volume for two kinds of hybrid plans. PTV(PT+LN) CI60Gy is not only correlated with above three geometry features, but also negatively correlated with overlapping slices thickness(PT and LN). When neck lymph node metastasis was excluded from PTVLN volume, physical and EQD2 total lung V20 showed a high linear correlation with corrected volume ratio(LN to total lung). Meanwhile, physical total lung mean dose (MLD) had a high linear correlation with corrected volume ratio(LN to total lung), while EQD2 total lung MLD was not only affected by corrected volume ratio(LN to total lung) but also volume ratio(PT to total lung). Heart D5, D30 and mean dose (MHD) would be more susceptible to overlapping structure(heart and LN). Min distance(PT to ESO) may be an important feature for predicting EQD2 esophageal max dose for hybrid plans. It’s feasible for regression models of EQD2 plan parameters, and the consistence of the fitting goodness of physical and EQD2 models had a positive correlation with spearman’s correlation coefficients between physical and EQD2 plan parameters. For total lung V20, ipsilateral lung V20, and ipsilateral lung MLD, the models could predict that C&SIB plans were higher than C&S plans for two new patients. Conclusion The regression models of physical and EQD2 plan parameters were established with at least moderate fitting goodness in this work, and the models have a potential to predict physical and EQD2 plan parameters for two kinds of hybrid planning.

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AS-NeSt: A Novel 3D Deep Learning Model for Radiation Therapy Dose Distribution Prediction in Esophageal Cancer Treatment With Multiple Prescriptions

Duan,

Wang,

et al. 2024

International Journal of Radiation Oncology*Biology*Physics

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Effect of lung volume on helical radiotherapy in esophageal cancer: are there predictive factors to achieve acceptable lung doses?

Cited by 6 publications

References 22 publications

Investigation of Predictors to Achieve Acceptable Lung Dose in T-Shaped Upper and Middle Esophageal Cancer With IMRT and VMAT

Investigation of Predictors to Achieve Acceptable Lung Dose in T-Shaped Upper and Middle Esophageal Cancer With IMRT and VMAT

Regression models for predicting physical and EQD2 plan parameters of two methods of hybrid planning for stage III NSCLC

AS-NeSt: A Novel 3D Deep Learning Model for Radiation Therapy Dose Distribution Prediction in Esophageal Cancer Treatment With Multiple Prescriptions

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