Neural signals-based respiratory motion tracking: a proof-of-concept study.

Objective.Respiratory motion tracking techniques can provide optimal treatment accuracy for thoracoabdominal radiotherapy and robotic surgery. However, conventional imaging-based respiratory motion tracking techniques are time-lagged owing to the system latency of medical linear accelerators and surgical robots. This study aims to investigate the precursor time of respiratory-related neural signals and analyze the potential of neural signals-based respiratory motion tracking.Approach.The neural signals and respiratory motion from eighteen healthy volunteers were acquired simultaneously using a 256-channel scalp electroencephalography (EEG) system. The neural signals were preprocessed using the MNE python package to extract respiratory-related EEG neural signals. Cross-correlation analysis was performed to assess the precursor time and cross-correlation coefficient between respiratory-related EEG neural signals and respiratory motion.Main results.Respiratory-related neural signals that precede the emergence of respiratory motion are detectable via non-invasive EEG. On average, the precursor time of respiratory-related EEG neural signals was 0.68 s. The representative cross-correlation coefficients between EEG neural signals and respiratory motion of the eighteen healthy subjects varied from 0.22 to 0.87.Significance.Our findings suggest that neural signals have the potential to compensate for the system latency of medical linear accelerators and surgical robots. This indicates that neural signals-based respiratory motion tracking is a potential promising solution to respiratory motion and could be useful in thoracoabdominal radiotherapy and robotic surgery.

Guaranteed performance of individual control chart used in gamma passing rate-based patient-specific quality assurance.

PURPOSE: To assess the effect of sampling variability on the performance of individual charts (I-charts) for PSQA and provide a robust and reliable method for unknown PSQA processes. MATERIALS AND METHODS: A total of 1327 pretreatment PSQAs were analyzed. Different datasets with samples in the range of 20-1000 were used to estimate the lower control limit (LCL). Based on the iterative "Identify-Eliminate-Recalculate" and direct calculation without any outlier filtering procedures, five I-charts methods, namely the Shewhart, quantile, scaled weighted variance (SWV), weighted standard deviation (WSD), and skewness correction (SC) method, were used to compute the LCL. The average run length (ARL0) and false alarm rate (FAR0) were calculated to evaluate the performance of LCL. RESULTS: The ground truth of the values of LCL, FAR0, and ARL0 obtained via in-control PSQAs were 92.31%, 0.135%, and 740.7, respectively. Further, for in-control PSQAs, the width of the 95% confidence interval of LCL values for all methods tended to decrease with the increase in sample size. In all sample ranges of in-control PSQAs, only the median LCL and ARL0 values obtained via WSD and SWV methods were close to the ground truth. For the actual unknown PSQAs, based on the "Identify-Eliminate-Recalculate" procedure, only the median LCL values obtained by the WSD method were closest to the ground truth. CONCLUSIONS: Sampling variability seriously affected the I-chart performance in PSQA processes, particularly for small samples. For unknown PSQAs, the WSD method based on the implementation of the iterative "Identify-Eliminate-Recalculate" procedure exhibited sufficient robustness and reliability.

Application of thermoplastic elastomer (TPE) bolus in postmastectomy radiotherapy.

PURPOSE: To assess the planned dose, in vivo dosimetry, acute skin toxicity, pain, and distress using Thermoplastic Elastomer (TPE) bolus for postmastectomy radiotherapy (PMRT). MATERIAL AND METHODS: Thirty-two PMRT patients with TPE bolus (17 patients for 25 fractions, 15 patients for the first 20 fractions) were selected for the study. The acute skin toxicity, pain, and psychological distress were assessed from the first treatment week to the fourth week after the end of treatment. At the first treatment, the MOSFET was used in vivo dosimetry measurement. RESULTS: In vivo dosimetry with the bolus, the dose deviation ranged from -6.22% to -1.56% for 5 points. The presence of grade 1 and 2 skin toxicity reached its peak (70.0% and 13.3%) in the sixth week. Two patients (6.6%) with 25 fractions bolus experienced moist desquamation in the fifth and seventh week, with pain score 2 and 3, and interruptions of 3 and 5 days, respectively. The incidence of pain score 1, 2, and 3 peaked in the fifth (33.3%), fourth (33.3%), and seventh (10.0%) week. No patients experienced grade 3 skin toxicity and severe pain. One patient had significant anxiety, and two patients had significant depression. CONCLUSION: The TPE bolus can accurately fit skin and improve the surface dose to more than 90%. Twenty fractions with TPE bolus had similar skin toxicity and pain to those without bolus and did not increase patients' distress and clinical workload, compared with the literature's data, which is an alternative to the 3D printing bolus for PMRT.

Prediction of proton beam range in phantom with metals based on monochromatic energy CT images.

The purpose of the study was to evaluate the accuracy of monochromatic energy (MonoE) computed tomography (CT) images reconstructed by spectral CT in predicting the stopping power ratio $( SP{R}_w)$ of materials in the presence of metal. The CIRS062 phantom was scanned three times using spectral CT. In the first scan, a solid water insert was placed at the center of the phantom $(C{T}_{no\ metal})$. In the second scan, the solid water insert was replaced with a titanium alloy femoral head $(C{T}_{metal})$. The metal artifact reduction (MAR) algorithm was used in the last scan $(C{T}_{metal+ MAR})$. The MonoE-CT images of 40 keV and 80 keV were reconstructed. Finally, the single-energy CT method (SECT) and the dual-energy CT method (DECT) were used to calculate the $SP{R}_w$. The mean absolute error (MAE) of the $SP{R}_w$ of the inner layer inserts calculated by the SECT method were 3.19%, 13.88% and 2.71%, corresponding to $C{T}_{no\ metal}$, $C{T}_{metal}$ and $C{T}_{metal+ MAR}$, respectively. For the outer layer inserts, the MAE of $SP{R}_w$ were 3.43%, 5.42% and 2.99%, respectively. Using the DECT method, the MAE of the $SP{R}_w$ of the inner layer inserts was 1.30%, 3.69% and 1.46% and the MAE of the outer layer inserts- was 1.34%, 1.36% and 1.05%. The studies shows that, compared with the SECT method, the accuracy of the DECT method in predicting the $SP{R}_w$ of a material is more robust to the presence of metal. Using the MAR algorithm when performing CT scans can further improve the accuracy of predicting the SPR of materials in the presence of metal.

Evaluating the impact of possible interobserver variability in CBCT-based soft-tissue matching using TCP/NTCP models for prostate cancer radiotherapy.

BACKGROUND: Prostate alignment is subject to interobserver variability in cone-beam CT (CBCT)-based soft-tissue matching. This study aims to analyze the impact of possible interobserver variability in CBCT-based soft-tissue matching for prostate cancer radiotherapy. METHODS: Retrospective data, consisting of 156 CBCT images from twelve prostate cancer patients with elective nodal irradiation were analyzed in this study. To simulate possible interobserver variability, couch shifts of 2 mm relative to the resulting patient position of prostate alignment were assumed as potential patient positions (27 possibilities). For each CBCT, the doses of the potential patient positions were re-calculated using deformable image registration-based synthetic CT. The impact of the simulated interobserver variability was evaluated using tumor control probabilities (TCPs) and normal tissue complication probabilities (NTCPs). RESULTS: No significant differences in TCPs were found between prostate alignment and potential patient positions (0.944 ± 0.003 vs 0.945 ± 0.003, P = 0.117). The average NTCPs of the rectum ranged from 5.16 to 7.29 (%) among the potential patient positions and were highly influenced by the couch shift in the anterior-posterior direction. In contrast, the average NTCPs of the bladder ranged from 0.75 to 1.12 (%) among the potential patient positions and were relatively negligible. CONCLUSIONS: The NTCPs of the rectum, rather than the TCPs of the target, were highly influenced by the interobserver variability in CBCT-based soft-tissue matching. This study provides a theoretical explanation for daily CBCT-based image guidance and the prostate-rectum interface matching procedure. TRIAL REGISTRATION: Not applicable.

A robust approach to establish tolerance limits for the gamma passing rate-based patient-specific quality assurance using the heuristic control charts.

PURPOSE: Establishing the tolerance limits of patient-specific quality assurance (PSQA) processes based on the gamma passing rate (GPR) by using normal statistical process control (SPC) methods involves certain problems. The aim of this study was threefold: (a) to show that the heuristic SPC method can replace the quantile method for establishing tolerance limits in PSQA processes and is more robust, (b) to introduce an iterative procedure of "Identify-Eliminate-Recalculate" for establishing the tolerance limits in PSQA processes with unknown states based on retrospective GPRs, and (c) to recommend a workflow to define tolerance limits based on actual clinical retrospective GPRs. MATERIALS AND METHODS: A total of 1671 volumetric-modulated arc therapy (VMAT) pretreatment plans were measured on four linear accelerators (linacs) and analyzed by treatment sites using the GPRs under the 2%/2 mm, 3%/2 mm, and 3%/3 mm criteria. Normality testing was performed using the Anderson-Darling (AD) statistic and the optimal distributions of GPRs were determined using the Fitter Python package. The iterative "Identify-Eliminate-Recalculate" procedure was used to identify the PSQA outliers. The tolerance limits of the initial PSQAs, remaining PSQAs after elimination, and in-control PSQAs after correction were calculated using the conventional Shewhart method, two transformation methods, three heuristic methods, and two quantile methods. The tolerance limits of PSQA processes with different states for the respective methods, linacs, and treatment sites were comprehensively compared and analyzed. RESULTS: It was found that 75% of the initial PSQA processes and 63% of the in-control processes were non-normal (AD test, p < 0.05). The optimal distributions of GPRs for the initial and in-control PSQAs varied with different linacs and treatment sites. In the implementation of the "Identify-Eliminate-Recalculate" procedure, the quantile methods could not identify the out-of-control PSQAs effectively due to the influence of outliers. The tolerance limits of the in-control PSQAs, calculated using the quantile of optimal fitting distributions, represented the ground truth. The tolerance limits of the in-control PSQAs and remaining PSQAs after elimination calculated using the heuristic methods were considerably close to the ground truth (the maximum average absolute deviations were 0.50 and 1.03%, respectively). Some transformation failures occurred under both transformation methods. For the in-control PSQAs at 3%/2 mm gamma criteria, the maximum differences in the tolerance limits for four linacs and different treatment sites were 3.10 and 5.02%, respectively. CONCLUSIONS: The GPR distributions of PSQA processes vary with different linacs and treatment sites but most are skewed. In applying SPC methodologies to PSQA processes, heuristic methods are robust. For in-control PSQA processes, the tolerance limits calculated by heuristic methods are in good agreement with the ground truth. For unknown PSQA processes, the tolerance limits calculated by the heuristic methods after the iterative "Identify-Eliminate-Recalculate" procedure are closest to the ground truth. Setting linac- and treatment site-specific tolerance limits for PSQA processes is necessary for clinical applications.

Analysis of the amplitude changes and baseline shifts of respiratory motion using intra-fractional CBCT in liver stereotactic body radiation therapy.

PURPOSE: Using intra-fractional cone-beam CT (CBCT) to evaluate the amplitude changes and baseline shifts of respiratory motion in liver stereotactic body radiation therapy (SBRT). METHODS: The amplitude changes and baseline shifts of respiratory motion for 24 liver patients were evaluated by the four-dimensional (4D) CT, inter- and intra-fractional CBCT. The difference of the average liver position errors among all treatment fractions and the 4D CT representthe baseline shifts. According to the baseline shifts, the ITV to PTV margin was recalculated and the plan was re-designed to compare the dosimetric variation. RESULTS: The systematic and random errors of the baseline shifts for intra-fractional CBCT in the left-right (LR), superior-inferior (SI), and anterior-posterior (AP) directions were 0.99/1.60 mm, 2.03/2.46 mm, and 1.02/2.07 mm, respectively. The new ITV to PTV margins should be 4.0 mm, 7.0 mm, and 4.0 mm, respectively. The amplitude change of motion between the 4D CT and the intra-fractional CBCT was 1.03 ± 4.35 mm, with 31% of fractions exceeding 5 mm. To achieve the same dose coverage of the new PTV, the Dmean, V50, V40, V30, V25 of normal liver and maximum dose of the duodenum were significantly different. CONCLUSIONS: Significant amplitude changes and baseline shifts of motion occurred during dose delivery compared with those in 4D CT. Using the ITV to PTV margin of 4.0 mm (LR), 7.0 mm (SI), and 4.0 mm (AP) can ensure the target dose coverage and keep the dose constrain of normal tissues at an acceptable level.

[Application of Virtual Monochromatic Images Reconstructed by Dual-energy Computed Tomography in Radiotherapy Treatment Planning System].

Virtual monochromatic images (VMI) that reconstructed on dual-energy computed tomography (DECT) have further application prospects in radiotherapy, and there is still a lack of clinical dose verification. In this study, GE Revolution CT scanner was used to perform conventional imaging and gemstone spectral imaging on the simulated head and body phantom. The CT images were imported to radiotherapy treatment planning system (TPS), and the same treatment plans were transplanted to compare the CT value and the dose distribution. The results show that the VMI can be imported into TPS for CT value-relative electron density conversion and dose calculation. Compared to conventional images, the VMI varies from 70 to 140 keV, has little difference in dose distribution of 6 MV photon treatment plan.

Radiomics analysis of EPID measurements for patient positioning error detection in thyroid associated ophthalmopathy radiotherapy.

PURPOSE: Electronic portal imaging detector (EPID)-based patient positioning verification is an important component of safe radiotherapy treatment delivery. In computer simulation studies, learning-based approaches have proven to be superior to conventional gamma analysis in the detection of positioning errors. To approximate a clinical scenario, the detectability of positioning errors via EPID measurements was assessed using radiomics analysis for patients with thyroid-associated ophthalmopathy. METHODS: Treatment plans of 40 patients with thyroid-associated ophthalmopathy were delivered to a solid anthropomorphic head phantom. To simulate positioning errors, combinations of 0-, 2-, and 4-mm translation errors in the left-right (LR), superior-inferior (SI), and anterior-posterior (AP) directions were introduced to the phantom. The positioning errors-induced dose differences between measured portal dose images were used to predict the magnitude and direction of positioning errors. The detectability of positioning errors was assessed via radiomics analysis of the dose differences. Three classification models-support vector machine (SVM), k-nearest neighbors (KNN), and XGBoost-were used for the detection of positioning errors (positioning errors larger or smaller than 3 mm in an arbitrary direction) and direction classification (positioning errors larger or smaller than 3 mm in a specific direction). The receiver operating characteristic curve and the area under the ROC curve (AUC) were used to evaluate the performance of classification models. RESULTS: For the detection of positioning errors, the AUC values of SVM, KNN, and XGBoost models were all above 0.90. For LR, SI, and AP direction classification, the highest AUC values were 0.76, 0.91, and 0.80, respectively. CONCLUSIONS: Combined radiomics and machine learning approaches are capable of detecting the magnitude and direction of positioning errors from EPID measurements. This study is a further step toward machine learning-based positioning error detection during treatment delivery with EPID measurements.

Analysis of the Influence of Peripheral Anatomical Changes for CBCT-Guided Prostate Cancer Radiotherapy.

PURPOSE: To analyze the influence of the bladder and rectum filling and the body contour changes on the prostate target dose. METHODS: A total of 190 cone-beam CT (CBCT) image data sets from 16 patients with prostate cancer were used in this study. Dose reconstruction was performed on the virtual CT generated by the deformable planning CT. Then, the effects of the bladder filling, rectal filling, and the patient's body contour changes of the PCTV1 (the prostate area, B1) and PCTV2 (the seminal vesicle area, B2) on the target dose were analyzed. Correlation analysis was performed for the ratio of bladder and rectal volume variation and the variation of the bladder and rectal dose. RESULTS: The mean Dice coefficients of B1, B2, bladder, and rectum were 0.979, 0.975, 0.888 and 0.827, respectively, and the mean Hausdorff distances were 0.633, 1.505, 2.075, and 1.533, respectively. With the maximum volume variations of 142.04 ml for the bladder and 40.50 ml for the rectum, the changes of V100, V95, D2, and D98 were 1.739 ± 1.762 (%), 0.066 ± 0.169 (%), 0.562 ± 0.442 (%), and 0.496 ± 0.479 (%) in PCTV1 and 1.686 ± 1.051 (%), 0.240 ± 0.215 (%), 1.123 ± 0.925 (%), and 0.924 ± 0.662 (%) in PCTV2, respectively. With a 10% increase in the volume of the bladder and rectum, the V75, V70, and V65 of rectum increased at 0.73 (%), 0.71 (%), and 1.18 (%), and the V75, V70, and V65 of bladder changed at -0.21 (%), -0.32 (%), and -0.39 (%), respectively. CONCLUSION: Significant correlations were observed between the volume variation and the dose variation of the bladder and rectum. However, when a bladder and rectal filling protocol was adopted, the target dose coverage can be effectively ensured based on CBCT guidance to correct the prostate target position.

[Two-Dimensional Electron Beam Radiotherapy Planning System with Modeling Function].

In order to adapt to different target shapes and protect the surrounding normal tissues, the design of two-dimensional electron beam radiotherapy planning requires additional lead blocks. But the Pinnacle treatment planning system can not directly shape the lead block conformity to the size of the beam field given by the doctor. Every time, physicists need to manually drag the lead block to form the required beam field. When meeting a two-dimensional electron beam treatment planning with the same field parameters as before, physicists need to rearrange the field for dose calculation, which greatly reduces the design efficiency of the two-dimensional electron beam treatment planning. In this study, we independently developed a two-dimensional electron beam radiotherapy planning system based on Qt Creator. The system can quickly design a two-dimensional electron beam radiotherapy plan, which reduces the repeated work of physicists.

Description and evaluation of a new volumetric-modulated arc therapy plan complexity metric.

This study describes a new plan complexity metric for volumetric-modulated arc therapy (VMAT) and evaluates the relationship of this metric with the VMAT dosimetric accuracy. The new modulation complexity score for VMAT (NMCSv) that is based on the aperture shape and multi-leaf collimator (MLC) leaf travel is described. Its performance is evaluated through correlation and receiver operating characteristic (ROC) analyses with patient-specific gamma passing rates using 2 3-dimensional diode arrays. For comparison, the following metrics are evaluated using the same correlation analyses: average field width, average leaf travel, modulation complexity score, and leaf travel modulation complexity score. Spearman's rank correlation analysis is performed to examine any relationships between the complexity metrics and the patient-specific gamma passing rates. ROC curves are used to assess the performance of the plan metrics using a gamma passing rate of 3%/3 mm criterion with a 95% tolerance level. In both the diode arrays, the gamma passing rates (3%/3 mm and 2%/2 mm) for patient-specific dosimetric verification of VMAT plans are moderately or weakly correlated to all the complexity metrics. NMCSv demonstrates the highest correlation with the passing rates (r = 0.652, p < 0.001 for Delta4 and r = 0.499, p < 0.001 for ArcCheck) and the highest area under the curve value (0.809, p < 0.01 for Delta4 and 0.734, p < 0.01 for ArcCheck). While using the Delta4 system, NMCSv exhibits an excellent classification performance with area under the curves of 0.926 (sensitivity: 0.913; specificity: 0.860; p < 0.01) and 0.918 (sensitivity: 0.943; specificity: 0.720; p < 0.01) for rectal and cervical cancer plans, respectively. NMCSv as a novel potential clinical plan complexity metric is moderately correlated with the gamma passing rate. It demonstrates the best performance with respect to distinguishing the dosimetric accuracy of VMAT plans among the evaluated metrics. The classification performance of complexity metrics can be affected by various dosimetry verification devices and treatment sites.

[Accuracy and Influence Analysis of 4D CBCT Automatic Registration Algorithm under the Guidance of Chest Tumor Image].

OBJECTIVE: In order to provide guidance for clinical use of four-dimensional cone-beam CT (4D CBCT), the accuracy of image registration and its influencing factors were analyzed using the automatic registration method when 4D CBCT was used as an image guidance strategy for patients with chest tumors. METHODS: The respiratory motion model and two kinds of lung plug-ins were used to simulate two types of tumors and their movements in the chest. 4D CT was scanned for each kind of simulated tumor, and 4D CBCT was scanned under various artificial positioning errors. For the registration of 4D CBCT, the manual and automatic registration methods were used for each group. RESULTS: There were more obvious mismatches in the intrapulmonary adhesion tumor group. When the masks were created based on the size of the target area or expanding the target area by 0.5 cm, the results between the automatic registration and manual registration were statistically different. There were no significant mismatches in the isolated lung tumor group, and there was no statistical difference between the results of automatic registration and manual registration. CONCLUSIONS: When 4D CBCT is used as an image guidance strategy for patients with chest tumors, the automatic registration procedure should not be used for tumors adhering to chest wall and mediastinum. For solitary lung tumors, the automatic registration method and the manual registration method have similar registration accuracy, but significant mismatches need to be excluded.

Long-Term Results of Partial Breast Irradiation After Breast-Conserving Surgery for Early Stage Breast Cancer: A Prospective Phase II Trial in China.

BACKGROUND: Partial breast radiotherapy (PBI) has emerged as an option after breast-conserving surgery for early stage breast cancer patients. METHODS: A total of 55 patients with early stage breast cancer between 2009 and 2013 were enrolled in this single-institutional phase II prospective clinical trial. All patients received adjuvant PBI-IMRT after lumpectomy, with the prescription of 48 Gy in 12 fractions at 4 Gy per fraction, 5 days a week. The primary endpoint was ipsilateral breast tumor recurrence (IBTR), the other endpoints were a regional nodal failure (RNF), distant metastasis (DM) rate, disease-free survival (DFS), and overall survival (OS). These endpoints were used to evaluate clinical outcomes. The cosmetic effects and the late toxicity were assessed according to Harvard standard scale and CTCAE 3.0, respectively. RESULTS: In our cohorts, the median age was 45.60 years old (range 31-65 years) and 29.09% of these patients were post-menopause (n = 16). Most patients were T1 stage (65.45%) or N0 stage (70.91%). 80% of patients were ER-positive, 67.27% PR positive, and 61.82% HER2 negative. At the median follow-up of 9.25 years, RNF was 0% and IBTR occurred in only one patient (1.82%) to the chest wall. Except for one patient (1.82%) had DM to lung and pleura and died from disease progression, the remaining patients were alive at the end of the 10-year follow-up. The 10-year DFS and OS were 94.55 and 98.18%. One patient (1.82%) was diagnosed with endometrial cancer after PBI. Except for 9 patients who declined the cosmetic assessment, the rest of the 46 patients (83.64%) were all rated as good and well-satisfied with the appearance of the irradiated breast. No breast retraction and fibrosis were observed in any of the patients. Additionally, only 4 patients experienced grade 1 late toxicity (7.28%). None had grade 3 or higher late toxicity. CONCLUSION: This is the first study to report the 10-year results of PBI after breast-conserving surgery in Chinese patients. Our study suggested that PBI had durable local control and maintained good cosmetic outcomes with minimal late toxicity at long term follow up for the early stage breast cancer patients.

Application of 3D-print silica bolus for nasal NK/T-cell lymphoma radiation therapy.

The aim of the study was to evaluate the clinical feasibility of a 3D-print silica bolus for nasal NK/T-cell lymphoma radiation therapy. Intensity modulated radiotherapy (IMRT) and volumetric modulated arc therapy (VMAT) plans were designed using an anthropomorphic head phantom with a 3D-print silica bolus and other kinds of bolus used clinically, and the surface dose was measured by a metal oxide semiconductor field-effect transistor (MOSFET) dosimeter. Four nasal NK/T patients with or without 3D-print silica bolus were treated and the nose surface dose was measured using a MOSFET dosimeter during the first treatment. Plans for the anthropomorphic head phantom with 3D-print bolus have more uniform dose and higher conformity of the planning target volume (PTV) compared to other boluses; the homogeneity index (HI) and conformity index (CI) of the VMAT plan were 0.0589 and 0.7022, respectively, and the HI and CI of the IMRT plan were 0.0550 and 0.7324, respectively. The MOSFET measurement results showed that the surface dose of the phantom with 3D-print bolus was >180 cGy, and that of patients with 3D-print bolus was higher than patients without bolus. The air gap volume between the 3D-print bolus and the surface of patients was <0.3 cc. The 3D-print silica bolus fitted well on the patient's skin, effectively reducing air gaps between bolus and patient surface. Meanwhile, the 3D-print silica bolus provided patients with higher individuation, and improved the conformity and uniformity of the PTV compared to other kinds of boluses.

Design of a new breast vacuum bag to reduce the global and local setup errors and to reduce PTV margin in post-mastectomy radiation therapy.

To design a new breast vacuum bag to reduce global and local setup errors in post-mastectomy radiation therapy (PMRT). A total of 24 PMRT patients were immobilized with an old vacuum bag and 26 PMRT patients were immobilized with a new vacuum bag. The registration results were analysed using four regions of interest (ROI): the global ROI [including the whole region of the planning target volume (PTV), GROI], the supraclavicular area (SROI), the ipsilateral chest wall region (CROI) and the ipsilateral arm region (AROI). The global and local setup errors of the two groups were compared. The global setup errors of the new vacuum group were significantly smaller than those in the old vacuum group with the exception of yaw axes (P < 0.05). The systematic error (Σ) and random error (σ) ranged from 1.21 to 2.13 mm. In the new vacuum group, the local setup errors in the medial-lateral (ML) direction and roll axes for CROI (the Σ and σ ranged from 0.65 to 1.35 mm), and the local setup errors in ML and superior-inferior (SI) directions for SROI were significantly smaller than those in the old vacuum group. The total required PTV margins for the chest wall in ML, SI, and anterior-posterior (AP) were 4.40, 3.12 and 3.77 mm respectively. The new vacuum bag can significantly reduce the global setup errors and local setup errors in PMRT. The respiratory motion of the chest wall was negligible, and the 5 mm PTV margin could cover the local setup errors in PMRT using the new vacuum bag with cone beam CT (CBCT) correction.

Low-dose cone-beam CT (LD-CBCT) reconstruction for image-guided radiation therapy (IGRT) by three-dimensional dual-dictionary learning.

BACKGROUND: To develop a low-dose cone beam CT (LD-CBCT) reconstruction method named simultaneous algebraic reconstruction technique and dual-dictionary learning (SART-DDL) joint algorithm for image guided radiation therapy (IGRT) and evaluate its imaging quality and clinical application ability. METHODS: In this retrospective study, 62 CBCT image sets from February 2018 to July 2018 at west china hospital were randomly collected from 42 head and neck patients (mean [standard deviation] age, 49.7 [11.4] years, 12 females and 30 males). All image sets were retrospectively reconstructed by SART-DDL (resultant D-CBCT image sets) with 18% less clinical raw projections. Reconstruction quality was evaluated by quantitative parameters compared with SART and Total Variation minimization (SART-TV) joint reconstruction algorithm with paired t test. Five-grade subjective grading evaluations were done by two oncologists in a blind manner compared with clinically used Feldkamp-Davis-Kress algorithm CBCT images (resultant F-CBCT image sets) and the grading results were compared by paired Wilcoxon rank test. Registration results between D-CBCT and F-CBCT were compared. D-CBCT image geometry fidelity was tested. RESULTS: The mean peak signal to noise ratio of D-CBCT was 1.7 dB higher than SART-TV reconstructions (P < .001, SART-DDL vs SART-TV, 36.36 ± 0.55 dB vs 34.68 ± 0.28 dB). All D-CBCT images were recognized as clinically acceptable without significant difference with F-CBCT in subjective grading (P > .05). In clinical registration, the maximum translational and rotational difference was 1.8 mm and 1.7 degree respectively. The horizontal, vertical and sagittal geometry fidelity of D-CBCT were acceptable. CONCLUSIONS: The image quality, geometry fidelity and clinical application ability of D-CBCT are comparable to that of the F-CBCT for head-and-neck patients with 18% less projections by SART-DDL.

Statistical process control and process capability analysis for non-normal volumetric modulated arc therapy patient-specific quality assurance processes.

PURPOSE: Applying statistical process control (SPC) to intensity-modulated radiotherapy (IMRT)/volumetric modulated arc therapy (VMAT) patient-specific quality assurance (PSQA) program was recommended by the American Association of Physics in Medicine Task Group 218 report, but a comprehensive analysis of PSQA processes with non-normal distributions is lacking. This study investigates SPC and process capability analysis (PCA) methods for non-normal IMRT/VMAT PSQA processes. METHODS: 1119 VMAT PSQAs were performed on three beam-matched linear accelerators (linacs), using gamma analysis. The Anderson-Darling statistic was used to test normality. The control charts for each PSQA process were obtained using three non-normal-based methods and compared with the conventional Shewhart method. The ability of each PSQA process to produce an output within the specification limit was measured using the C pk index; in this study, the C pk index was calculated using two transformation methods and compared with that calculated using the conventional method. The performances of the three linacs were assessed using SPC and PCA methods. RESULTS: All three PSQA processes were non-normal (P < 0.005). Compared to the non-normal-based SPC and PCA methods, the false alarm rates of the conventional method for linac1, linac2, and linac3 were 0.83%, 3.77%, and 4.95% respectively; the minimum overestimated C pk values were 0.59, 0.87, and 1.49, respectively. The process capabilities of the three beam-matched linacs were at different levels. CONCLUSION: For non-normal VMAT PSQA processes, the conventional SPC and PCA methods increase the false alarm rates and overestimate process capabilities. Instead, non-normal-based SPC and PCA methods are more reliable and accurate in non-normal PSQA processes. Statistical process control and PCA are useful tools for assessing the performance of beam-matched linacs.

Analysis of local setup errors of sub-regions in cone-beam CT-guided post-mastectomy radiation therapy.

The purpose of the study was to quantify local setup errors and evaluate the planning target volume (PTV) margins for sub-regions in cone-beam computed tomography (CBCT)-guided post-mastectomy radiation therapy (PMRT). The local setup errors of 20 patients undergoing CBCT-guided PMRT were analysed retrospectively. Image registration between CBCT and planning CT was performed using four sub-regions of interest (ROIs): the supraclavicular area (SROI), ipsilateral chest wall region (CROI), ipsilateral chest wall plus supraclavicular region (SROI + CROI) and vertebral region (TROI). Bland-Altman analysis, correlation, local setup errors and PTV margins among these ROIs were evaluated. There was no significant consistency or correlation for registration results between the TROI and the CROI or SROI regions on any translational axis. When using the SROI + CROI as the ROI, the systematic error (Σ) and random error (σ) of the local setup errors for the CROI region were 1.81, 1.19 and 1.76 mm and 1.84, 2.64 and 3.00 mm along the medial-lateral (ML), superior-inferior (SI) and anterior-posterior (AP) directions, respectively. The PTV margins for the CROI region were 5.80, 4.82 and 6.50 mm. The Σ and σ of the local setup errors for the SROI region were 1.29, 1.15 and 0.77 mm and 1.96, 2.65 and 2.2 mm, respectively, and the PTV margins were 4.59, 4.73 and 3.47 mm. Large setup errors and local setup errors occur in PMRT. The vertebral body should not be a position surrogate for the supraclavicular region or chest wall. To compensate for the local setup errors, different PTV margins are required, even with CBCT guidance.