A deep-learning-based scatter correction with water equivalent path length map for digital radiography.

We proposed a new deep learning (DL) model for accurate scatter correction in digital radiography. The proposed network featured a pixel-wise water equivalent path length (WEPL) map of subjects with diverse sizes and 3D inner structures. The proposed U-Net model comprises two concatenated modules: one for generating a WEPL map and the other for predicting scatter using the WEPL map as auxiliary information. First, 3D CT images were used as numerical phantoms for training and validation, generating observed and scattered images by Monte Carlo simulation, and WEPL maps using Siddon's algorithm. Then, we optimised the model without overfitting. Next, we validated the proposed model's performance by comparing it with other DL models. The proposed model obtained scatter-corrected images with a peak signal-to-noise ratio of 44.24 ± 2.89 dB and a structural similarity index measure of 0.9987 ± 0.0004, which were higher than other DL models. Finally, scatter fractions (SFs) were compared with other DL models using an actual phantom to confirm practicality. Among DL models, the proposed model showed the smallest deviation from measured SF values. Furthermore, using an actual radiograph containing an acrylic object, the contrast-to-noise ratio (CNR) of the proposed model and the anti-scatter grid were compared. The CNR of the images corrected using the proposed model are 16% and 82% higher than those of the raw and grid-applied images, respectively. The advantage of the proposed method is that no actual radiography system is required for collecting training dataset, as the dataset is created from CT images using Monte Carlo simulation.

Commissioning and Validation of CT Number to SPR Calibration in Carbon Ion Therapy Facility.

Purpose: We performed computed tomography (CT)-stopping power ratio (SPR) calibration in a carbon-ion therapy facility and evaluated SPR estimation accuracy. Materials and Methods: A polybinary tissue model method was used for the calibration of CT numbers and SPR. As a verification by dose calculation, we created a virtual phantom to which the CT-SPR calibration table was applied. Then, SPR was calculated from the change in the range of the treatment planning beam when changing to 19 different CT numbers, and the accuracy of the treatment planning system (TPS) calculation of SPR values from the CT-SPR calibration table was validated. As a verification by measurement, 5 materials (water, milk, olive oil, ethanol, 40% K2HPO4) were placed in a container, and the SPR was obtained by measurement from the change in the range of the beam that passed through the materials. Results: The results of the dose calculations of the TPS showed that the results agreed within 1% for the lower CT numbers up to 1000 HU, but there was a difference of 3.0% in the higher CT number volume. The difference between the SPR calculated by TPS and the SPR caused by the difference in the energy of the incident particles agreed within 0.51%. The accuracy of SPR estimation was measured, and the error was within 2% for all materials tested. Conclusion: These results indicate that the SPR estimation errors are within the range of errors that can be expected in particle therapy. From commissioning and verification results, the CT-SPR calibration table obtained during this commissioning process is clinically applicable.

Current status of remote radiotherapy treatment planning in Japan: findings from a national survey†.

The purpose of this study was to investigate the status of remote-radiotherapy treatment planning (RRTP) in Japan through a nationwide questionnaire survey. The survey was conducted between 29 June and 4 August 2022, at 834 facilities in Japan that were equipped with linear accelerators. The survey utilized a Google form that comprised 96 questions on facility information, information about the respondent, utilization of RRTP between facilities, usage for telework and the inclination to implement RRTPs in the respondent's facility. The survey analyzed the utilization of the RRTP system in four distinct implementation types: (i) utilization as a supportive facility, (ii) utilization as a treatment facility, (iii) utilization as a teleworker outside of the facility and (iv) utilization as a teleworker within the facility. The survey response rate was 58.4% (487 facilities responded). Among the facilities that responded, 10% (51 facilities) were implementing RRTP. 13 served as supportive facilities, 23 as treatment facilities, 17 as teleworkers outside of the facility and 5 as teleworkers within the facility. In terms of system usage between supportive and treatment facilities, 70-80% of the participants utilized the system for emergencies or as overtime work for external workers. A substantial number of facilities (38.8%) reported that they were unfamiliar with RRTP implementation. The survey showed that RRTP utilization in Japan is still limited, with a significant number of facilities unfamiliar with the technology. The study highlights the need for greater understanding and education about RRTP and financial funds of economical compensation.

Error on the stopping power ratio of ERKODENT's mouthpiece for head and neck carbon ion radiotherapy treatment.

The errors on the stopping power ratio (SPR) of mouthpiece samples from ERKODENT were evaluated. Erkoflex and Erkoloc-pro from ERKODENT and samples that combined Erkoflex and Erkoloc-pro were computed tomography (CT)-scanned using head and neck (HN) protocol at the East Japan Heavy Ion Center (EJHIC), and the values were averaged to obtain the CT number. The integral depth dose of the Bragg curve with and without these samples was measured for 292.1, 180.9, and 118.8 MeV/u of the carbon-ion pencil beam using an ionization chamber with concentric electrodes at the horizontal port of the EJHIC. The average value of the water equivalent length (WEL) of each sample was obtained from the difference between the range of the Bragg curve and the thickness of the sample. To calculate the difference between the theoretical and measured values, the theoretical CT number and SPR value of the sample were calculated using the stoichiometric calibration method. Compared with the Hounsfield unit (HU)-SPR calibration curve used at the EJHIC, the SPR error on each measured and theoretical value was calculated. The WEL value of the mouthpiece sample had an error of approximately 3.5% in the HU-SPR calibration curve. From this error, it was evaluated that for a mouthpiece with a thickness of 10 mm, a beam range error of approximately 0.4 mm can occur, and for a mouthpiece with a thickness of 30 mm, a beam range error of approximately 1 mm can occur. For a beam passing through the mouthpiece in HN treatment, it would be practical to consider a mouthpiece margin of 1 mm to avoid beam range errors if ions pass through the mouthpiece.

Radiation pneumonitis prediction model with integrating multiple dose-function features on 4DCT ventilation images.

PURPOSE: Radiation pneumonitis (RP) is dose-limiting toxicity for non-small-cell cancer (NSCLC). This study developed an RP prediction model by integrating dose-function features from computed four-dimensional computed tomography (4DCT) ventilation using the least absolute shrinkage and selection operator (LASSO). METHODS: Between 2013 and 2020, 126 NSCLC patients were included in this study who underwent a 4DCT scan to calculate ventilation images. We computed two sets of candidate dose-function features from (1) the percentage volume receiving > 20 Gy or the mean dose on the functioning zones determined with the lower cutoff percentile ventilation value, (2) the functioning zones determined with lower and upper cutoff percentile ventilation value using 4DCT ventilation images. An RP prediction model was developed by LASSO while simultaneously determining the regression coefficient and feature selection through fivefold cross-validation. RESULTS: We found 39.3 % of our patients had a ≥ grade 2 RP. The mean area under the curve (AUC) values for the developed models using clinical, dose-volume, and dose-function features with a lower cutoff were 0.791, and the mean AUC values with lower and upper cutoffs were 0.814. The relative regression coefficient (RRC) on dose-function features with upper and lower cutoffs revealed a relative impact of dose to each functioning zone to RP. RRCs were 0.52 for the mean dose on the functioning zone, with top 20 % of all functioning zone was two times greater than that of 0.19 for these with 60 %-80 % and 0.17 with 40 %-60 % (P < 0.01). CONCLUSIONS: The introduction of dose-function features computed from functioning zones with lower and upper cutoffs in a machine learning framework can improve RP prediction. The RRC given by LASSO using dose-function features allows for the quantification of the RP impact of dose on each functioning zones and having the potential to support treatment planning on functional image-guided radiotherapy.

Adherence to methotrexate and associated factors considering social desirability in patients with rheumatoid arthritis: a multicenter cross-sectional study.

BACKGROUND: Assessing medication adherence in rheumatoid arthritis (RA) is clinically significant as low adherence is associated with high disease activity. Self-reported medication adherence surveys have been shown to have problems with overestimation of adherence due to social desirability bias. However, no MTX adherence studies adjusted for social desirability have been conducted to date. This study aimed to evaluate adherence to MTX and perform an investigatory search for factors associated with MTX adherence including social desirability. METHODS: This cross-sectional multicenter study was conducted among adult RA patients consuming oral MTX for ≥ 3 months. We examined the distribution of MTX adherence, according to the eight-item Morisky Medication Adherence Scale (MMAS-8). Social desirability was using the Social Desirability Scale (SDS). Furthermore, an exploratory factor analysis involving social desirability was examined to identify factors associated with MTX adherence using linear regression analysis. To deal with missing values, we used multiple imputations with chained equations methods. RESULTS: A total of 165 RA patients were enrolled. The median age was 64 years, and 86.1% were women. Based on the MMAS-8, low, medium, and high adherences were noted in 12.1%, 60.0%, and 27.9% of participants, respectively. High social desirability (coefficient, 0.14; 95% confidence interval [CI], 0.05-0.23; p < 0.05) and high age (coefficient per 10 years, 0.16; 95% CI, 0.01-0.03; p < 0.05) were associated with high MTX adherence, whereas full-time work was negatively associated with high MTX adherence (coefficient, -0.50; 95% CI, -0.95--0.05; p < 0.05). CONCLUSIONS: A large proportion of patients with RA do not take MTX as prescribed. High social desirability, high educational level, and non-full-time work may be associated with high MTX adherence. Physicians should confirm MTX adherence before switching or adding disease-modifying anti-rheumatic drugs in cases of uncontrolled disease activity.

Development of a quantitative analysis method for assessing patient body surface deformation using an optical surface tracking system.

This study aimed to develop a new method to quantitatively analyze body shape changes in patients during radiotherapy without additional radiation exposure using an optical surface tracking system. This method's accuracy was evaluated using a cubic phantom with a known shift. Surface images of three-dimensionally printed phantoms, which simulated the head and neck shapes of real patients before and after treatment, were used to create a deformation surface area histogram. The near-maximum deformation value covering an area of 2 cm2 in the surface image (Def-2cm2) was calculated. A volumetric modulated arc therapy (VMAT) plan was also created on the pre-treatment phantom, and the dose distribution was recalculated on the post-treatment phantom to compare the dose indices. Surface images of four patients were analyzed to evaluate Def-2cm2 and examine whether this method can be used in clinical cases. Experiments with the cubic phantom resulted in a mean deformation error of 0.08 mm. With head and neck phantoms, the Def-2cm2 value was 17.5 mm, and the dose that covered 95% of the planning target volume in the VMAT plan decreased by 11.7%, indicating that deformation of the body surface may affect the dose distribution. Although analysis of the clinical data showed no clinically relevant deformation in any of the cases, slight skin sagging and respiratory changes in the body surface were observed. The proposed method can quantitatively and accurately evaluate the deformation of a body surface. This method is expected to be used to make decisions regarding modifications to treatment plans.

Assessment of a computed tomography-based radiomics approach for assessing lung function in lung cancer patients.

PURPOSE: We aimed to assess radiomics approaches for estimating three pulmonary function test (PFT) results (forced expiratory volume in one second [FEV1], forced vital capacity [FVC], and the ratio of FEV1 to FVC [FEV1/FVC]) using data extracted from chest computed tomography (CT) images. METHODS: This retrospective study included 85 lung cancer patients (mean age, 75 years ±8; 69 men) who underwent stereotactic body radiotherapy between 2012 and 2020. Their pretreatment chest breath-hold CT and PFT data before radiotherapy were obtained. A total of 107 radiomics features (Shape: 14, Intensity: 18, Texture: 75) were extracted using two methods: extraction of the lung tissue (<-250 HU) (APPROACH 1), and extraction of small blood vessels and lung tissue (APPROACH 2). The PFT results were estimated using the least absolute shrinkage and selection operator regression. Pearson's correlation coefficients (r) were determined for all PFT results, and the area under the curve (AUC) was calculated for FEV1/FVC (<70 %). Finally, we compared our approaches with the conventional formula (Conventional). RESULTS: For the estimated FEV1/FVC, the Pearson's r were 0.21 (P =.06), 0.69 (P <.01), and 0.73 (P <.01) for Conventional, APPROACH 1, and APPROACH 2, respectively; the AUCs for FEV1/FVC (<70 %) were 0.67 (95 % confidence interval [CI]: 0.55, 0.79), 0.82 (CI: 0.72, 0.91; P =.047) and 0.86 (CI: 0.78, 0.94; P =.01), respectively. CONCLUSIONS: The radiomics approach performed better than the conventional equation and may be useful for assessing lung function based on CT images.

Prediction of radiation pneumonitis with machine learning using 4D-CT based dose-function features.

In this article, we highlight the fundamental importance of the simultaneous use of dose-volume histogram (DVH) and dose-function histogram (DFH) features based on functional images calculated from 4-dimensional computed tomography (4D-CT) and deformable image registration (DIR) in developing a multivariate radiation pneumonitis (RP) prediction model. The patient characteristics, DVH features and DFH features were calculated from functional images by Hounsfield unit (HU) and Jacobian metrics, for an RP grade ≥ 2 multivariate prediction models were computed from 85 non-small cell lung cancer patients. The prediction model is developed using machine learning via a kernel-based support vector machine (SVM) machine. In the patient cohort, 21 of the 85 patients (24.7%) presented with RP grade ≥ 2. The median area under curve (AUC) was 0.58 for the generated 50 prediction models with patient clinical features and DVH features. When HU metric and Jacobian metric DFH features were added, the AUC improved to 0.73 and 0.68, respectively. We conclude that predictive RP models that incorporate DFH features were successfully developed via kernel-based SVM. These results demonstrate that effectiveness of the simultaneous use of DVH features and DFH features calculated from 4D-CT and DIR on functional image-guided radiotherapy.

Prediction of the minimum spacer thickness required for definitive radiotherapy with carbon ions and photons for pelvic tumors: an in silico planning study using virtual spacers.

We aimed to predict the minimum distance between a tumor and the gastrointestinal (GI) tract that can satisfy the dose constraint by creating simulation plans with carbon-ion (C-ion) radiotherapy (RT) and photon RT for each case assuming insertion of virtual spacers of various thicknesses. We enrolled 55 patients with a pelvic tumor adjacent to the GI tract. Virtual spacers were defined as the overlap volume between the GI tract and the volume expanded 7-17 mm from the gross tumor volume (GTV). Simulation plans (70 Gy in 35 fractions for at least 95% of the planning target volume [PTV]) were created with the lowest possible dose to the GI tract under conditions that meet the dose constraints of the PTV. We defined the minimum thickness of virtual spacers meeting D2 cc of the GI tract <50 Gy as 'MTS'. Multiple regression was used with explanatory variables to develop a model to predict MTS. We discovered that MTSs were at most 9 mm and 13 mm for C-ion RT and photon RT plans, respectively. The volume of overlap between the GI tract and a virtual spacer of 14 mm in thickness (OV14)-PTV was found to be the most important explanatory variable in the MTS prediction equation for both C-ion and photon RT plans. Multiple R2 values for the regression model were 0.571 and 0.347 for C-ion RT and photon RT plans, respectively. In conclusion, regression equations were developed to predict MTS in C-ion RT and photon RT.

Four-dimensional carbon-ion pencil beam treatment planning comparison between robust optimization and range-adapted internal target volume for respiratory-gated liver and lung treatment.

We investigated the dose differences between robust optimization-based treatment planning (4DRO) and range-adapted internal target volume (rITV). We used 4DCT dataset of 20 lung cancer and 20 liver cancer patients, respectively, who had been treated with respiratory-gated carbon-ion pencil beam scanning therapy. 4DRO and rITV plans were created with the same clinical target volume (CTV) and organs at risk (OAR) contours. Four-dimensional dose distribution was calculated using deformable image registration. Dose metrics (e.g. D95, V20) were analyzed. Statistical significance was assessed by the Wilcoxon signed-rank test. For the lung cases, the mean CTV-D95 value for the rITV plan (=98.5%) was same as that for the 4DRO plan (=98.5%, P = 0.106), while the mean D95 value for the CTV + setup margin contour for the rITV plan (=98.2%) was higher than that for the 4DRO plan (95.2%, P < 0.001). For the liver cases, the mean CTV-D95 value for the rITV plan (=98.1%) was slightly lower than that for the 4DRO plan (=98.5%, P < 0.01), while the mean D95 value for the CTV + setup margin contour for the rITV plan (=98.0%) was higher than that for the 4DRO plan (94.1%, P < 0.001). For the doses to the organs at risk (OARs), the ipsilateral lung-V20/liver-V20 values for the rITV plan (=10.1%/19.7%) was significantly higher than that for the 4DRO plan (=8.6%/17.6, P < 0.001). Although the target coverage for 4DRO plan may be worse than that for rITV plan in the presence of the setup error, the 4DRO plan can improve OAR dose while preserving acceptable target dose coverage.

Evaluation of four-dimensional cone beam computed tomography ventilation images acquired with two different linear accelerators at various gantry speeds using a deformable lung phantom.

We evaluated four-dimensional cone beam computed tomography (4D-CBCT) ventilation images (VICBCT) acquired with two different linear accelerator systems at various gantry speeds using a deformable lung phantom. The 4D-CT and 4D-CBCT scans were performed using a computed tomography (CT) scanner, an X-ray volume imaging system (Elekta XVI) mounted in Versa HD, and an On-Board Imager (OBI) system mounted in TrueBeam. Intensity-based deformable image registration (DIR) was performed between peak-exhale and peak-inhale images. VICBCT- and 4D-CT-based ventilation images (VICT) were derived by DIR using two metrics: one based on the Jacobian determinant and one on changes in the Hounsfield unit (HU). Three different DIR regularization values (λ) were used for VICBCT. Correlations between the VICBCT and VICT values were evaluated using voxel-wise Spearman's rank correlation coefficient (r). In case of both metrics, the Jacobian-based VICBCT with a gantry speed of 0.6 deg/sec in Versa HD showed the highest correlation for all the gantry speeds (e.g., λ = 0.05 and r = 0.68). Thus, the r value of the Jacobian-based VICBCT was greater or equal to that of the HU-based VICBCT. In addition, the ventilation accuracy of VICBCT increased at low gantry speeds. Thus, the image quality of VICBCT was affected by the change in gantry speed in both the imaging systems. Additionally, DIR regularization considerably influenced VICBCT in both the imaging systems. Our results have the potential to assist in designing CBCT protocols, incorporating VICBCT imaging into the functional avoidance planning process.

The impact of 4DCT-ventilation imaging-guided proton therapy on stereotactic body radiotherapy for lung cancer.

Functional lung avoidance during radiotherapy can help reduce pulmonary toxicity. This study assessed the potential impact of four-dimensional computed tomography (4DCT)-ventilation imaging-guided proton radiotherapy (PT) on stereotactic body radiotherapy (SBRT) by comparing it with three-dimensional conformal radiotherapy (3D-CRT) and volumetric modulated arc therapy (VMAT), which employ photon beams. Thirteen lung cancer patients who received SBRT with 3D-CRT were included in the study. 4DCT ventilation was calculated using the patients' 4DCT data, deformable image registration, and a density-change-based algorithm. Three functional treatment plans sparing the functional lung regions were developed for each patient using 3D-CRT, VMAT, and PT. The prescribed doses and dose constraints were based on the Radiation Therapy Oncology Group 0618 protocol. We evaluated the region of interest (ROI) and functional map-based dose-function metrics for 4DCT ventilation and the irradiated dose. Using 3D-CRT, VMAT, and PT, the percentages of the functional lung regions that received ≥ 5 Gy (fV5) were 26.0%, 21.9%, and 10.7%, respectively; the fV10 were 14.4%, 11.4%, and 9.0%, respectively; and fV20 were 6.5%, 6.4%, and 6.6%, respectively, and the functional mean lung doses (fMLD) were 5.6 Gy, 5.2 Gy, and 3.8 Gy, respectively. These results indicated that PT resulted in a significant reduction in fMLD, fV5, and fV10, but not fV20. The use of PT reduced the radiation to highly functional lung regions compared with those for 3D-CRT and VMAT while meeting all dose constraints.

Evaluation of the effect of user-guided deformable image registration of thoracic images on registration accuracy among users.

User-guided deformable image registration (DIR) has allowed users to actively participate in the DIR process and is expected to improve DIR accuracy. The purpose of this study was to evaluate the time required for and effect of user-guided DIR on registration accuracy for thoracic images among users. In this study, 4-dimensional computed tomographic images of 10 thoracic cancer patients were used. The dataset for these patients was provided by DIR-Lab (www.dir-lab.com) and included a coordinate list of anatomical landmarks (300 bronchial bifurcations). Four medical physicists from different institutions performed DIR between peak-inhale and peak-exhale images with/without the user-guided DIR tool, Reg Refine, implemented in MIM Maestro (MIM software, Cleveland, OH). DIR accuracy was quantified by using target registration errors (TREs) for 300 anatomical landmarks in each patient. The average TREs with user-guided DIR in the 10 images by the 4 medical physicists were 1.48, 1.80, 3.46, and 3.55 mm, respectively, whereas the TREs without user-guided DIR were 3.28, 3.45, 3.56, and 3.28 mm, respectively. The average times taken by the 4 physicists to use the user-guided DIR were 10.0, 6.7, 7.1, and 8.0 min, respectively. This study demonstrated that user-guided DIR can improve DIR accuracy and requires only a moderate amount of time (<10 min). However, 2 of the 4 users did not show much improvement in DIR accuracy, which indicated the necessity of training prior to use of user-guided DIR.

In silico comparison of the dosimetric impacts of a greater omentum spacer for abdominal and pelvic tumors in carbon-ion, proton and photon radiotherapy.

PURPOSE: The purpose of this study was to compare carbon-ion (C-ion), proton and photon radiotherapy (RT) plans with regard to dose reduction of the gastrointestinal (GI) tract by using a greater omentum spacer (GO spacer). METHODS: We retrospectively retrieved data for ten patients who received the GO spacer as surgical spacer placement for abdominal and pelvic tumors. Simulation plans were created on pre-spacer Computed Tomography (CT) and post-spacer CT for C-ion RT, proton RT and photon RT to compare the dose of the GI tract. The plans were normalized so that at least 95% of the planning target volume (PTV) received 70 Gy (relative biological effectiveness equivalent) delivered in 35 fractions. All plans were created with the lowest possible dose to the GI tract under conditions that meet the dose constraints for the PTV and spinal cord (maximum dose < 45 Gy). The part of the GI tract to be evaluated was defined as that most adjacent to the PTV. C-ion RT plans and proton RT plans were calculated by a spot scanning technique, and photon RT plans were calculated employing by fixed-field intensity-modulated radiation therapy. RESULTS: D2 cc and V10-70 of the GI tract were significantly lower on post-spacer plans than on pre-spacer plans for all three RT modalities. Regarding post-spacer plans, D2 cc of the GI tract was significantly lower on C-ion RT plans and proton RT plans than on photon RT plans (C-ion vs photon p = 0.001, proton vs photon p = 0.002). However, there was no significant difference between C-ion RT plans and proton RT plans for D2 cc of the GI tract (C-ion vs proton p = 0.992). In the photon RT plan for one patient, D2 cc of the GI tract did not meet < 50 Gy. CONCLUSIONS: The GO spacer shows a significant dose reduction effect on the GI tract.

Evaluation of patient positional reproducibility on the treatment couch and its impact on dose distribution using rotating gantry system in scanned carbon-ion beam therapy.

PURPOSE: The daily variations in patient setup may cause beam range uncertainties. We evaluated the reproducibility of relative position between the patient and the treatment couch throughout the treatment course and assessed its effects on dose distributions when a beam passes through treatment couch using rotating gantry system. METHODS: We enrolled 1023 patients (=13072 fractions) treated by carbon-ion pencil beam scanning therapy. Seven treatment sites including prostate, head and neck, bone and soft tissue, rectum, liver, lung, and pancreas were investigated. Inter-fractional changes in couch position relative to the patient were defined as translational errors. Changes in couch rotation were defined as rotational errors. Treatment planning was performed for 4 patients in each of the treatment sites. Dose distributions were then re-calculated after the couch was shifted according to average, 95th percentile, and maximum values of translational error. RESULTS: Large positional errors (>1.5 cm) were observed in 5% of treatment fractions. Positional errors were largest in prostate and pancreas patients, while smallest in head and neck and lung patients. There were no or only small changes in PTV-D95 and CTV-D95 values for almost all treatment sites. Clinically significant changes were observed in the duodenum (difference in D2cc values ranged from -55% to 28% with maximum couch shift) in pancreas treatment. CONCLUSIONS: Although underdosage to the PTV or CTV was limited, significant overdoses to organs at risk were found. The improvement of immobilization technique and appropriate selection of gantry angles could reduce the uncertainties due to changes in patient position.

Evaluation of functionally weighted dose-volume parameters for thoracic stereotactic ablative radiotherapy (SABR) using CT ventilation.

For the purpose of reducing radiation pneumontisis (RP), four-dimensional CT (4DCT)-based ventilation can be used to reduce functionally weighted lung dose. This study aimed to evaluate the functionally weighted dose-volume parameters and to investigate an optimal weighting method to realize effective planning optimization in thoracic stereotactic ablative radiotherapy (SABR). Forty patients treated with SABR were analyzed. Ventilation images were obtained from 4DCT using deformable registration and Hounsfield unit-based calculation. Functionally-weighted mean lung dose (fMLD) and functional lung fraction receiving at least x Gy (fVx) were calculated by two weighting methods: thresholding and linear weighting. Various ventilation thresholds (5th-95th, every 5th percentile) were tested. The predictive accuracy for CTCAE grade ≧ 2 pneumonitis was evaluated by area under the curve (AUC) of receiver operating characteristic analysis. AUC values varied from 0.459 to 0.570 in accordance with threshold and dose-volume metrics. A combination of 25th percentile threshold and fV30 showed the best result (AUC: 0.570). AUC values with fMLD, fV10, fV20, and fV40 were 0.541, 0.487, 0.548 and 0.563 using a 25th percentile threshold. Although conventional MLD, V10, V20, V30 and V40 showed lower AUC values (0.516, 0.477, 0.534, 0.552 and 0.527), the differences were not statistically significant. fV30 with 25th percentile threshold was the best predictor of RP. Our results suggested that the appropriate weighting should be used for better treatment outcomes in thoracic SABR.