Traffic Exposure and Breast Cancer Mortality by Area of Residence: Incorporating Clinical and Socioeconomic Data.

Incorporating clinical and environmental data holds promise for monitoring vulnerable populations at the community level. This spatial epidemiology study explores the link between traffic-related air pollution and breast cancer mortality in Seoul, using public socioeconomic and clinical data from Samsung Medical Center's registry (N=6,089). Traffic and socioeconomic status were collected from official sources and integrated for spatial analysis. The findings revealed a significant association between adult breast cancer mortality and districts with high road density, NO2 emissions, and family income (p<0.05). Significant spatial autocorrelation of residuals was observed (Moran's I test p<0.001).

Identification of reproducible radiomic features from on-board volumetric images: A multi-institutional phantom study.

BACKGROUND: Radiomics analysis using on-board volumetric images has attracted research attention as a method for predicting prognosis during treatment; however, the lack of standardization is still one of the main concerns. PURPOSE: This study investigated the factors that influence the reproducibility of radiomic features extracted from on-board volumetric images using an anthropomorphic radiomics phantom. Furthermore, a phantom experiment was conducted with different treatment machines from multiple institutions as external validation to identify reproducible radiomic features. METHODS: The phantom was designed to be 35 × 20 × 20 cm with eight types of heterogeneous spheres (⌀ = 1, 2, and 3 cm). On-board volumetric images were acquired using 15 treatment machines from eight institutions. Of these, kilovoltage cone-beam computed tomography (kV-CBCT) image data acquired from four treatment machines at one institution were used as an internal evaluation dataset to explore the reproducibility of radiomic features. The remaining image data, including kV-CBCT, megavoltage-CBCT (MV-CBCT), and megavoltage computed tomography (MV-CT) provided by seven different institutions (11 treatment machines), were used as an external validation dataset. A total of 1,302 radiomic features, including 18 first-order, 75 texture, 465 (i.e., 93 × 5) Laplacian of Gaussian (LoG) filter-based, and 744 (i.e., 93 × 8) wavelet filter-based features, were extracted within the spheres. The intraclass correlation coefficient (ICC) was calculated to explore feature repeatability and reproducibility using an internal evaluation dataset. Subsequently, the coefficient of variation (COV) was calculated to validate the feature variability of external institutions. An absolute ICC exceeding 0.85 or COV under 5% was considered indicative of a highly reproducible feature. RESULTS: For internal evaluation, ICC analysis showed that the median percentage of radiomic features with high repeatability was 95.2%. The ICC analysis indicated that the median percentages of highly reproducible features for inter-tube current, reconstruction algorithm, and treatment machine were decreased by 20.8%, 29.2%, and 33.3%, respectively. For external validation, the COV analysis showed that the median percentage of reproducible features was 31.5%. A total of 16 features, including nine LoG filter-based and seven wavelet filter-based features, were indicated as highly reproducible features. The gray-level run-length matrix (GLRLM) was classified as containing the most frequent features (N = 8), followed by the gray-level dependence matrix (N = 7) and gray-level co-occurrence matrix (N = 1) features. CONCLUSIONS: We developed the standard phantom for radiomics analysis of kV-CBCT, MV-CBCT, and MV-CT images. With this phantom, we revealed that the differences in the treatment machine and image reconstruction algorithm reduce the reproducibility of radiomic features from on-board volumetric images. Specifically, the most reproducible features for external validation were LoG or wavelet filter-based GLRLM features. However, the acceptability of the identified features should be examined in advance at each institution before applying the findings to prognosis prediction.

Investigation of Halcyon multi-leaf collimator model in Eclipse treatment planning system: A focus on the VMAT dose calculation with the Acuros XB algorithm.

PURPOSE: The dual-layer multi-leaf collimator (MLC) in Halcyon involves further complexities in the dose calculation process, because the leaf-tip transmission varies according to the leaf trailing pattern. For the volumetric modulated arc therapy (VMAT) treatment, the prescribed dose for the target volume can be sensitive to the leaf-tip transmission change. This report evaluates the dosimetric consequence due to the uncertainty of the dual-layer MLC model in Eclipse through the dose verifications for clinical VMAT. Additionally, the Halcyon leaf-tip model is empirically adjusted for the VMAT dose calculation with the Acuros XB. MATERIALS AND METHODS: For this evaluation, an in-house program that analyzes the leaf position in each layer was developed. Thirty-two clinical VMAT plans were edited into three leaf sequences: dual layer (original), proximal single layer, or distal single layer. All leaf sequences were verified using Delta4 according to the dose difference (DD) and the global gamma index (GI). To improve the VMAT dose calculation accuracy, the dosimetric leaf gap (DLG) was adjusted to minimize the DD in single-layer leaf sequences. RESULTS: The mean of DD were -1.35%, -1.20%, and -1.34% in the dual-layer, proximal single-layer, and distal single-layer leaf sequences, respectively. The changes in the mean of DD between leaf sequences were within 0.2%. However, the calculated doses differed from the measured doses by approximately 1% in all leaf sequences. The tuned DLG was increased by 0.8 mm from the original DLG in Eclipse. When the tuned DLG was used in the dose calculation, the mean of DD neared 0% and GI with a criterion of 2%/2 mm yielded a pass rate of more than 98%. CONCLUSION: No significant change was confirmed in the dose calculation accuracy between the leaf sequences. Therefore, it is suggested that the dosimetric consequence due to the leaf trailing was negligibly small in clinical VMAT plans. The DLG tuning for Halcyon can be useful for reducing the dose calculation uncertainties in Eclipse VMAT and required in the commissioning for Acuros XB.

Evaluation of gantry angle during respiratory-gated VMAT using triggered kilovoltage x-ray image.

Respiratory-gated volumetric modulated arc therapy (gated VMAT) involves further complexities to the dose delivery process because the gantry rotation must repeatedly stop and restart according to the gating signals. In previous studies, the gantry rotation performances were evaluated by the difference between the plan and the machine log. However, several reports pointed out that log analysis does not sufficiently replicate the machine performance. In this report, a measurement-based quality assurance of the relation between the gantry angle and gate-on or gate-off using triggered kilovoltage imaging and a cylinder phantom with 16 ball bearings is proposed. For the analysis, an in-house program that estimates and corrects the phantom offset was developed. The gantry angle in static and gated arc delivery was compared between the machine log and the proposed method. The gantry was set every 5 deg through its full motion range in static delivery, and rotated at three speeds (2, 4 and 6 deg s-1 ) with different gating intervals (1.5 or 3.0 s) in gated arc delivery. The mean and standard deviation of the angular differences between the log and the proposed method was -0.05 deg ± 0.12 deg in static delivery. The mean of the angular difference was within ±0.10 deg and the largest difference was 0.41 deg in gated arc delivery. The log records the output of the encoder so that miscalibration and mechanical sagging will be disregarded. However, the proposed method will help the users to detect the mechanical issues due to the repeated gantry stops and restarts in gated VMAT.