Single isocenter versus dual isocenter treatment using flattening filter-free and jaw-tracking volumetrically modulated arc therapy for boot-shaped lung cancer: Evaluation of dosimetric and feasibility.

BACKGROUND: To determine whether a dual-isocenter volumetrically modulated arc therapy (VMAT) technique results in lower normal pulmonary dosage compared to a traditional single isocenter technique for boot-shaped lung cancer. METHODS: A cohort of 15 patients with advanced peripheral or central lung cancer who had metastases in the mediastinum and supraclavicular lymph nodes was randomly selected for this retrospective study. VMAT plans were generated for each patient using two different beam alignment techniques with the 6-MV flattening filter-free (FFF) photon beam: single-isocenter jaw-tracking VMAT based on the Varian TrueBeam linear accelerator (S-TV), and dual-isocenter VMAT based on both TrueBeam (D-TV) and Halcyon linear accelerator (D-HV). For all 45 treatment plans, planning target volume (PTV) dose coverage, conformity/homogeneity index (CI/HI), mean heart dose (MHD), mean lung dose (MLD) and the total lung tissue receiving 5, 20, 30 Gy (V5, V20, V30) were evaluated. The monitor units (MUs), delivery time, and plan quality assurance (QA) results were recorded. RESULTS: The quality of the objectives of the three plans was comparable to each other. In comparison with S-TV, D-TV and D-HV improved the CI and HI of the PTV (p < 0.05). The MLD was 13.84 ± 1.44 Gy (mean ± SD) for D-TV, 14.22 ± 1.30 Gy and 14.16 ± 1.42 Gy for S-TV and D-HV, respectively. Lungs-V5Gy was 50.78 ± 6.24%, 52.00 ± 7.32% and 53.36 ± 8.48%, Lungs-V20Gy was 23.72 ± 2.27%, 26.18 ± 2.86% and 24.96 ± 3.09%, Lungs-V30Gy was 15.69 ± 1.76%, 17.20 ± 1.72% and 16.52 ± 2.07%. Compared to S-TV, D-TV provided statistically significant better protection for the total lung, with the exception of the lungs-V5. All plans passed QA according the gamma criteria of 3%/3 mm. CONCLUSIONS: Taking into account the dosimetric results and published clinical data on radiation-induced pulmonary injury, dual-isocenter jaw-tracking VMAT may be the optimal choice for treating boot-shaped lung cancer.

A novel EPID-based MLC QA method with log files achieving submillimeter accuracy.

The purpose of this study is to develop an electronic portal imaging device-based multi-leaf collimator calibration procedure using log files. Picket fence fields with 2-14 mm nominal strip widths were performed and normalized by open field. Normalized pixel intensity profiles along the direction of leaf motion for each leaf pair were taken. Three independent algorithms and an integration method derived from them were developed according to the valley value, valley area, full-width half-maximum (FWHM) of the profile, and the abutment width of the leaf pairs obtained from the log files. Three data processing schemes (Scheme A, Scheme B, and Scheme C) were performed based on different data processing methods. To test the usefulness and robustness of the algorithm, the known leaf position errors along the direction of perpendicular leaf motion via the treatment planning system were introduced in the picket fence field with nominal 5, 8, and 11 mm. Algorithm tests were performed every 2 weeks over 4 months. According to the log files, about 17.628% and 1.060% of the leaves had position errors beyond ± 0.1 and ± 0.2 mm, respectively. The absolute position errors of the algorithm tests for different data schemes were 0.062 ± 0.067 (Scheme A), 0.041 ± 0.045 (Scheme B), and 0.037 ± 0.043 (Scheme C). The absolute position errors of the algorithms developed by Scheme C were 0.054 ± 0.063 (valley depth method), 0.040 ± 0.038 (valley area method), 0.031 ± 0.031 (FWHM method), and 0.021 ± 0.024 (integrated method). For the efficiency and robustness test of the algorithm, the absolute position errors of the integration method of Scheme C were 0.020 ± 0.024 (5 mm), 0.024 ± 0.026 (8 mm), and 0.018 ± 0.024 (11 mm). Different data processing schemes could affect the accuracy of the developed algorithms. The integration method could integrate the benefits of each algorithm, which improved the level of robustness and accuracy of the algorithm. The integration method can perform multi-leaf collimator (MLC) quality assurance with an accuracy of 0.1 mm. This method is simple, effective, robust, quantitative, and can detect a wide range of MLC leaf position errors.

Radiation pneumonia predictive model for radiotherapy in esophageal carcinoma patients.

BACKGROUND: The machine learning models with dose factors and the deep learning models with dose distribution matrix have been used to building lung toxics models for radiotherapy and achieve promising results. However, few studies have integrated clinical features into deep learning models. This study aimed to explore the role of three-dimension dose distribution and clinical features in predicting radiation pneumonitis (RP) in esophageal cancer patients after radiotherapy and designed a new hybrid deep learning network to predict the incidence of RP. METHODS: A total of 105 esophageal cancer patients previously treated with radiotherapy were enrolled in this study. The three-dimension (3D) dose distributions within the lung were extracted from the treatment planning system, converted into 3D matrixes and used as inputs to predict RP with ResNet. In total, 15 clinical factors were normalized and converted into one-dimension (1D) matrixes. A new prediction model (HybridNet) was then built based on a hybrid deep learning network, which combined 3D ResNet18 and 1D convolution layers. Machine learning-based prediction models, which use the traditional dosiomic factors with and without the clinical factors as inputs, were also constructed and their predictive performance compared with that of HybridNet using tenfold cross validation. Accuracy and area under the receiver operator characteristic curve (AUC) were used to evaluate the model effect. DeLong test was used to compare the prediction results of the models. RESULTS: The deep learning-based model achieved superior prediction results compared with machine learning-based models. ResNet performed best in the group that only considered dose factors (accuracy, 0.78 ± 0.05; AUC, 0.82 ± 0.25), whereas HybridNet performed best in the group that considered both dose factors and clinical factors (accuracy, 0.85 ± 0.13; AUC, 0.91 ± 0.09). HybridNet had higher accuracy than that of Resnet (p = 0.009). CONCLUSION: Based on prediction results, the proposed HybridNet model could predict RP in esophageal cancer patients after radiotherapy with significantly higher accuracy, suggesting its potential as a useful tool for clinical decision-making. This study demonstrated that the information in dose distribution is worth further exploration, and combining multiple types of features contributes to predict radiotherapy response.

Estimating the accumulative dose uncertainty for intracavitary and interstitial brachytherapy.

BACKGROUND: Image-guided adaptive brachytherapy shows the ability to deliver high doses to tumors while sparing normal tissues. However, interfraction dose delivery introduces uncertainties to high dose estimation, which relates to normal tissue toxicity. The purpose of this study was to investigate the high-dose regions of two applicator approaches in brachytherapy. METHOD: For 32 cervical cancer patients, the CT images from each fraction were wrapped to a reference image, and the displacement vector field (DVF) was calculated with a hybrid intensity-based deformable registration algorithm. The fractional dose was then accumulated to calculate the position and the overlap of high dose (D2cc) during multiple fractions. RESULT: The overall Dice similarity coefficient (DSC) of the deformation algorithm for the bladder and the rectum was (0.97 and 0.91). No significant difference was observed between the two applicators. However, the location of the intracavitary brachytherapy (ICBT) high-dose region was relatively concentrated. The overlap volume of bladder and rectum D2cc was 0.42 and 0.71, respectively, which was higher than that of interstitial brachytherapy (ISBT) (0.26 and 0.31). The cumulative dose was overestimated in ISBT cases when using the GEC-recommended method. The ratio of bladder and rectum D2cc to the GEC method was 0.99 and 1, respectively, which was higher than that of the ISBT method (0.96 and 0.94). CONCLUSION: High-dose regions for brachytherapy based on different applicator types were different. The 3D-printed ICBT has better high-dose region consistency than freehand ISBT and hence is more predictable.

Choice of immobilization of stereotactic body radiotherapy in lung tumor patient by BMI.

BACKGROUND: An accurate, reproducible, and comfortable immobilization device is essential for stereotactic radiotherapy (SBRT) in patients with lung cancer. This study compared thermoplastic masks (TMP) and vacuum cushion (VCS) system to assess the differences in interfraction and intrafraction setup accuracy and the impact of body mass index (BMI) with respect to the immobilization choice. METHODS: This retrospective study was conducted on patients treated with lung SBRT between 2012 and 2015 at the Zhejiang cancer hospital. The treatment setup accuracy was analyzed in 121 patients. A total of 687 cone beam computed tomography (CBCT) scans before treatment and 126 scans after treatment were recorded to determine the uncertainties, and plan target volume margins. Data were further stratified and analyzed by immobilization methods and patients' BMI. The t-test (Welch) was used to assess the differences between the two immobilization systems when stratified by the patients' BMI. RESULTS: For patients with BMI ≥ 24, the mean displacements for the TMP and VCS systems were 1.4 ± 1.2 vs. 2.4 ± 2.0 mm at medial-lateral (ML) direction (p < 0.001); 2.0 ± 1.9 vs. 2.0 ± 1.9 mm at cranial-caudal (CC) direction (p = 0.917); and 2.4 ± 1.4 vs. 2.6 ± 2.1 mm at anterior-posterior (AP) direction, (p = 0.546). The rate of acceptable errors increased dramatically when immobilized by TMP. In the case of patients with BMI < 24, the mean displacements for the TMP and VCS systems were 1.8 ± 1.4 vs. 2.1 ± 1.8 mm at ML direction (p = 0.098); 2.9 ± 2.3 vs. 2.2 ± 2.2 mm at CC direction (p = 0.001); and 1.8 ± 1.8 vs. 2.3 ± 2.0 mm at CC direction, (p = 0.006). The proportion of acceptable errors increased after immobilization by VCS. No difference was detected in the intrafraction setup error by different immobilization methods. CONCLUSIONS: The immobilization choice of SBRT for lung tumors depends on the BMI of the patients. For patients with BMI ≥ 24, TMP offers a better reproducibility with significantly less interfractional setup displacement than VCS, resulting in fewer CBCT scans. However, VCS may be preferred over TMP for the patients with BMI < 24. Therefore, an optimal immobilization system needs to be considered in different BMI groups for lung SBRT.

Approach and assessment of automated stereotactic radiotherapy planning for early stage non-small-cell lung cancer.

BACKGROUND: Intensity-modulated radiotherapy (IMRT) and volumetric-modulated arc therapy (VMAT) are standard physical technologies of stereotactic body radiotherapy (SBRT) that are used for patients with non-small-cell lung cancer (NSCLC). The treatment plan quality depends on the experience of the planner and is limited by planning time. An automated planning process can save time and ensure a high-quality plan. This study aimed to introduce and demonstrate an automated planning procedure for SBRT for patients with NSCLC based on machine-learning algorithms. The automated planning was conducted in two steps: (1) determining patient-specific optimized beam orientations; (2) calculating the organs at risk (OAR) dose achievable for a given patient and setting these dosimetric parameters as optimization objectives. A model was developed using data of historical expertise plans based on support vector regression. The study cohort comprised patients with NSCLC who were treated using SBRT. A training cohort (N = 125) was used to calculate the beam orientations and dosimetric parameters for the lung as functions of the geometrical feature of each case. These plan-geometry relationships were used in a validation cohort (N = 30) to automatically establish the SBRT plan. The automatically generated plans were compared with clinical plans established by an experienced planner. RESULTS: All 30 automated plans (100%) fulfilled the dose criteria for OARs and planning target volume (PTV) coverage, and were deemed acceptable according to evaluation by experienced radiation oncologists. An automated plan increased the mean maximum dose for ribs (31.6 ± 19.9 Gy vs. 36.6 ± 18.1 Gy, P < 0.05). The minimum, maximum, and mean dose; homogeneity index; conformation index to PTV; doses to other organs; and the total monitor units showed no significant differences between manual plans established by experts and automated plans (P > 0.05). The hands-on planning time was reduced from 40-60 min to 10-15 min. CONCLUSION: An automated planning method using machine learning was proposed for NSCLC SBRT. Validation results showed that the proposed method decreased planning time without compromising plan quality. Plans generated by this method were acceptable for clinical use.

Efficacy and Safety of Chemotherapy Combined with Stereotactic Radiotherapy in the Treatment of Nasopharyngeal Carcinoma.

BACKGROUND The aim of this study was to investigate the efficacy and safety of chemotherapy (CT) combined with stereotactic radiotherapy (SRT) in the treatment of nasopharyngeal carcinoma (NPC). MATERIAL AND METHODS A total of 329 NPC patients without any previous treatment were included in this study between January 2009 and November 2013. These patients were divided into three groups: CT group (n=114), SRT group (n=109), and CT + SRT group (n=106). Contrast-enhanced nasopharyngeal computed tomography (CT)/magnetic resonance (MR) scan was performed on the third month after treatment. Short-term efficacy was evaluated according to the Response Evaluation Criteria in Solid Tumors (RECIST). Toxicity was graded according to the Acute Radiation Morbidity Scoring Criteria (RTOG) and the World Health Organization (WHO) toxicity grading scale. Overall survival (OS), progression free survival (PFS), and incidence rate of acute toxicity (grade ≥3) were calculated after a 24 month follow-up. RESULTS Total response rate of all patients was 85.41%. Compared with the CT group and the SRT group, the CT + SRT group showed a substantially improved efficacy in NPC treatment. The incidence rate of the acute toxicity in the CT + SRT group was slightly higher than in the CT group and the SRT group, but the difference was not statistically significant. No treatment-related deaths were observed. The CT + SRT group had the highest two-year OS and PFS, followed by the CT group and the SRT group. CONCLUSIONS It was shown that NPC patients treated with CT + SRT had better short- and long-term efficacy than those treated with CT or SRT alone.

The effect of lymphadenectomy on survival and recurrence in patients with ovarian cancer: a systematic review and meta-analysis.

OBJECTIVE: Our objective was to perform a meta-analysis examining the effectiveness of lymphadenectomy in patients with ovarian cancer. METHODS: PubMed and CENTRAL databases were searched on 15 November 2015 using the terms 'lymphadenectomy', 'ovarian cancer', 'dissection', 'para-aortic', 'pelvic' and survival. Prospective and retrospective studies comparing the outcomes of surgery with or without lymphadenectomy were included. Outcomes were 5-year overall survival, progression-free survival and recurrence rate. RESULTS: Of the 556 studies identified, 3 randomized controlled trials and 11 retrospective studies were included. Lymphadenectomy was associated with greater 5-year overall survival than no lymphadenectomy (pooled odds ratio = 1.58, 95% confidence interval: 1.41-1.77, p < 0.001). There was no difference in progression-free survival between the groups (pooled overall survival = 1.62, 95% confidence interval: 0.82-3.21, p = 0.168). Lymphadenectomy was associated with greater progression-free survival in randomized clinical trials (pooled overall survival = 1.57, 95% confidence interval: 1.11-2.21, p = 0.010), but not in retrospective studies. Lymphadenectomy was associated with a significantly lower recurrence rate (pooled overall survival = 0.51, 95% confidence interval: 0.30-0.85, p = 0.011). Lymphadenectomy was associated with greater 5-year overall survival in patients with both early and advanced stage cancer, but was associated with greater progression-free survival and lower recurrence rate only in patients with advanced stage cancer. CONCLUSION: Lymphadenectomy is associated with greater 5-year overall survival in patients with early and advanced stage ovarian cancer, but an effect on progression-free survival and recurrence rate was only found in patients with advanced stage ovarian cancer.

Comparative dosimetric analysis of normal brain tissue in patients with Nasopharyngeal carcinoma at different stages after radiation therapy.

INTRODUCTION: Radiotherapy (RT) is the main treatment for patients with nasopharyngeal carcinoma (NPC). NPC patients at different stages have varying levels of damage to normal brain tissue after RT. No study has yet thoroughly analyzed the variations in radiation dosages in the brain for different stages of NPC patients treated with RT. This study aims to examine these variations. METHODS: 1446 NPC patients' CT and RTdose data were retrospectively reviewed. Analysis of the radiation dosage was executed on these 803 patients. The RTdose images for several patient groups were averaged after registering each patient's RTdose data to the CT brain template created in our earlier study. The voxel-based (VB) analysis was used to examine the dose variations in the brains of three groups of NPC patients: the early-stage group, the stage III group, and the stage IV group. RESULTS: As the disease progresses from early to advanced stages, the intensity and volume of radiation in the brain increase. The normal brain tissue accepted a substantially larger dosage in more advanced NPC patients. Differences in brain regions between stage III and early-stage patients were minimal compared to any other two groups. Brain regions exhibited substantial variations between the stage IV group and all other patient groups were broadly distributed. CONCLUSION: Our findings highlight the critical role of NPC staging in the therapeutic strategy, emphasizing the heterogeneity of radiation-induced tissue damage across disease stages and implying the need to develop stage-specific RT plans.

A Review of Artificial Intelligence Application for Radiotherapy.

Background and Purpose: Artificial intelligence (AI) is a technique which tries to think like humans and mimic human behaviors. It has been considered as an alternative in a lot of human-dependent steps in radiotherapy (RT), since the human participation is a principal uncertainty source in RT. The aim of this work is to provide a systematic summary of the current literature on AI application for RT, and to clarify its role for RT practice in terms of clinical views. Materials and Methods: A systematic literature search of PubMed and Google Scholar was performed to identify original articles involving the AI applications in RT from the inception to 2022. Studies were included if they reported original data and explored the clinical applications of AI in RT. Results: The selected studies were categorized into three aspects of RT: organ and lesion segmentation, treatment planning and quality assurance. For each aspect, this review discussed how these AI tools could be involved in the RT protocol. Conclusions: Our study revealed that AI was a potential alternative for the human-dependent steps in the complex process of RT.

A new target localization method for image-guided radiation therapy of prostate cancer.

In imaged-guided radiation therapy (IGRT), target localization is usually done with rigid-body registration based on anatomy matching. Problems arise when the target volume can only be matched partially due to inter-fractional organ motion and deformation, resulting in deteriorated target coverage and critical structure sparing. A new target localization method is investigated in which the treatment target volume is aligned with the prescription isodose surface. Our study included 15 prostate patients previously treated with intensity-modulated radiation therapy (IMRT). Patient setup and target localization were performed using a CT-on-rails system before and after the IMRT treatment. IMRT plans were generated on the original simulation CTs (15) and the same MUs and leaf sequences were used to compute the dose distributions on post-treatment CTs (98) with the isocenter adjustments based on either anatomical structure matching or prescription isodose surface alignment. When patients were aligned with the traditional anatomy matching method, the dose to 95% of the CTV, D95, received 74.0 - 77.6 Gy and the minimum CTV dose, Dmin, was 61.9 - 71.6 Gy, respectively, in the cumulative dose distributions. The rectal dose-volume constraints were violated in 35.7% of the treatment fractions. When patients were aligned using the new localization method, the dose to 95% of the CTV, D95, received 74.0 - 78.2 Gy and the minimum CTV dose, Dmin, was 68.4 - 71.6 Gy, respectively, in the cumulative dose distributions. The rectal dose-volume constraints were violated in 17.3% of the treatment fractions. Traditional IGRT target localization based on anatomy matching is effective for population-based PTV margins but not ideal for those patients with large inter-fractional prostate rotation/deformation due to large rectal and bladder volume variation. The new method using the prescription isodose surface to align the target volume could improve the target coverage and rectal sparing for these patients, which can be implemented clinically to improve target dose delivery accuracy.

Improving the registration stability of cone-beam computed tomography with the Sphere-Mask Optical Positioning System: a feasibility study.

Background: Cone-beam computed tomography (CBCT) is an important tool for patient positioning in radiotherapy due to its outstanding advantages. However, the CBCT registration shows errors due to the limitations of the automatic registration algorithm and the nonuniqueness of manual verification results. The purpose of this study was to verify the feasibility of using the Sphere-Mask Optical Positioning System (S-M_OPS) to improve the registration stability of CBCT through clinical trials. Methods: From November 2021 to February 2022, 28 patients who received intensity-modulated radiotherapy and site verification with CBCT were included in this study. S-M_OPS was used as an independent third-party system to supervise the CBCT registration result in real time. The supervision error was calculated based on the CBCT registration result and using the S-M_OPS registration result as the standard. For the head and neck, patients with a supervision error ≥3 or ≤-3 mm in 1 direction were selected. For the thorax, abdomen, pelvis, or other body parts, patients with a supervision error ≥5 or ≤-5 mm in 1 direction were selected. Then, re-registration was performed for all patients (selected and unselected). The registration errors of CBCT and S-M_OPS were calculated based on the re-registration results as the standard. Results: For selected patients with large supervision errors, CBCT registration errors (mean ± standard deviation) in the latitudinal (LAT; left/right), vertical (VRT; superior/inferior), and longitudinal (LNG; anterior/posterior) directions were 0.90±3.20, -1.70±0.98, and 7.30±2.14 mm, respectively. The S-M_OPS registration errors were 0.40±0.14, 0.32±0.66, and 0.24±1.12 mm in the LAT, VRT, and LNG directions, respectively. For all patients, CBCT registration errors in the LAT, VRT, and LNG directions were 0.39±2.69, -0.82±1.47, and 2.39±2.93 mm, respectively. The S-M_OPS registration errors were -0.25±1.33, 0.55±1.27, and 0.36±1.34 mm for all patients in the LAT, VRT, and LNG directions, respectively. Conclusions: This study shows that S-M_OPS registration offers comparable accuracy to CBCT for daily registration. S-M_OPS, as an independent third-party tool, can prevent large errors in CBCT registration, thereby improving the accuracy and stability of CBCT registration.

A model of radiation-induced temporomandibular joint damage in mice.

PURPOSE: A small animal radiation research platform (SARRP) equipped with a miniature beam system, an image-guided positioning system, and a dose planning system was used to develop and evaluate a mouse model of radiation-induced temporomandibular damage. METHODS: Left jaw disks of adult male C57BL/6 mice and C3H mice were targeted using the SARRP for image-guided irradiation. The total radiation dose was 75 Gy. Experiment 1 (Scoping study): Mice in the C57BL/6 mouse test and control groups were sacrificed at 1, 3, 6, 9, 12, 15, and 18 weeks after irradiation, whereas mice in the C3H test and control groups were sacrificed at 1, 3, 6, 9, and 12 weeks after irradiation. Experiment 2 (Full -scale validation study): Mice in the C57BL/6 mouse test and control groups were sacrificed at 1, 3 and 6 weeks after irradiation. Histopathological analysis of the temporomandibular skeletal muscle in each group was performed using hematoxylin and eosin (H&E) and Masson staining; the temporal mandibular bone was examined through H&E staining. RESULTS: SARRP delivered the rated dose to the temporomandibular joints of C57BL/6 and C3H mice. C3H and C57BL/6 mice in the test group showed different degrees of osteocytic necrosis and osteoporosis at different time points. H&E staining of skeletal muscle tissue showed slight fibrosis in the C57BL/6 test at 3 and 6 weeks time point. CONCLUSION: We established a model of radiation-induced damage in the temporomandibular joint of C57BL/6 mice and demonstrated that the observed physiological and histological changes correspond to radiation damage observed in humans. Furthermore, the SARRP can deliver precise radiation doses.

Dosimetric advantages of robust optimization combined with flattening filter free in treating cancer of the left breast.

OBJECTIVE: By comparing the target dose distribution with or without the robust optimization, the dosimetric advantages of robust optimization and flattening filter free (FFF) in radiation therapy for postmastectomy cancer of the left breast was explored when part of the chest wall target was moved out in case of respiratory motion. MATERIALS AND METHODS: This is a retrospective study. The data of 21 postmastectomy patients with cancer of the left breast from 2019 to 2020 were retrospectively collected. The planned target volume (PTV) dose was prescribed 50 Gy/25 fractions and the treatment plans were designed using 6 MV FFF X ray and volumetric modulated arc therapy (VMAT) technology in RayStation treatment planning system (TPS), with and without robust optimization. The movement of the target area of the internal chest wall (0.50 cm) caused by respiratory movement was simulated by moving the isocenter of the beams. RESULTS: When the chest wall target moved outward, the PTV target area D98, D95, D2, conformity index (CI) and homogeneity index (HI) with robust optimization were better than those without robust optimization. The coverage rate of Planned Target Volume-Chest (PTV-T) V50 with robust optimization was significantly higher than that with no-robust optimization (P<0.001). Clinical target volume (CTV) V50 coverage with robust optimization was 14.49% higher than that with no-robust optimization. In terms of organ-at-risk parameters, the average spinal cord dose of the plan with robust optimization was 13.19% lower than that of the plan with no-robust optimization, and the Lung-L V5 of the plan with no-robust optimization was slightly (1.94%) lower than that of the plan with robust optimization. There was no significant difference in machine execution efficiency between the two groups (P>0.05). CONCLUSIONS: Robust optimization could be adopted in the postoperative radiotherapy planning for cancer in the left breast, for it ensures that the target dose coverage and the dose limit of organ-at-risk still meet the clinical requirements under condition of chest wall displacement caused by respiratory movement.

Setup error assessment based on "Sphere-Mask" Optical Positioning System: Results from a multicenter study.

Background: The setup accuracy plays an extremely important role in the local control of tumors. The purpose of this study is to verify the feasibility of "Sphere-Mask" Optical Positioning System (S-M_OPS) for fast and accurate setup. Methods: From 2016 to 2021, we used S-M_OPS to supervise 15441 fractions in 1981patients (with the cancer in intracalvarium, nasopharynx, esophagus, lung, liver, abdomen or cervix) undergoing intensity-modulated radiation therapy (IMRT), and recorded the data such as registration time and mask deformation. Then, we used S-M_OPS, laser line and cone beam computed tomography (CBCT) for co-setup in 277 fractions, and recorded laser line-guided setup errors and S-M_OPS-guided setup errors with CBCT-guided setup result as the standard. Results: S-M_OPS supervision results: The average time for laser line-guided setup was 31.75s. 12.8% of the reference points had an average deviation of more than 2 mm and 5.2% of the reference points had an average deviation of more than 3 mm. Co-setup results: The average time for S-M_OPS-guided setup was 7.47s, and average time for CBCT-guided setup was 228.84s (including time for CBCT scan and manual verification). In the LAT (left/right), VRT (superior/inferior) and LNG (anterior/posterior) directions, laser line-guided setup errors (mean±SD) were -0.21±3.13mm, 1.02±2.76mm and 2.22±4.26mm respectively; the 95% confidence intervals (95% CIs) of laser line-guided setup errors were -6.35 to 5.93mm, -4.39 to 6.43mm and -6.14 to 10.58mm respectively; S-M_OPS-guided setup errors were 0.12±1.91mm, 1.02±1.81mm and -0.10±2.25mm respectively; the 95% CIs of S-M_OPS-guided setup errors were -3.86 to 3.62mm, -2.53 to 4.57mm and -4.51 to 4.31mm respectively. Conclusion: S-M_OPS can greatly improve setup accuracy and stability compared with laser line-guided setup. Furthermore, S-M_OPS can provide comparable setup accuracy to CBCT in less setup time.

[Enoxaparin for the prevention of post surgical pulmonary embolism].

OBJECTIVE: To evaluate the efficacy and safety of the administration of enoxaparin, a low molecular weight heparin (LMWH), in the prevention of post surgical deep vein thrombosis (DVT) and pulmonary embolism (PE). METHODS: 1928 patients hospitalized for general surgery were randomly divided into: (1) test group (n = 960) to receive enoxaparin (40 mg, s.c., 12 hours before and after surgery, then once daily for 7 consecutive days); (2) control group (n = 968) without intervention. The incidence of DVT,PE and bleeding were recorded for statistical analysis during hospitalization and a 2 months follow-up after discharge. RESULTS: (1) No significant difference was found between the two groups in age, sex, average body mass index, type of surgery, and DVT / PE risk factors (obesity, varicose veins, and history of: venous thrombosis, chronic obstructive pulmonary disease, chronic heart failure, and hormone therapy). The percentage of non-malignant / malignant tumor surgery were 36.5% / 63.5% (average operation time 2.3 hours) in control group and 35.6% / 64.4% (2.2 hours) in test group (both P > 0.05). (2) During the hospitalization period, 59 cases (incidence=6.1%) of DVT and 14 cases (incidence=1.4%) of PE (among them 6 were fetal, 42.8% of all PE cases) were found in the control group, while 28 cases of DVT (2.9%) and 3 cases (0.3%) of PE (1 fetal, 33.3% of all PE cases) were found in test group. The incidence of DVT, PE (total), and PE (fetal) were significant lower in test group (P < 0.05 or P < 0.01). During the follow up, 14 more cases of DVT (1.4%) and 1 more case (0.1%) of PE (a fetal) were found in the control group, and 2 more DVT cases (0.2%) in test group, with the DVT incidence in test group significantly lower (P < 0.01). (3) During the enoxaparin administration, 30 cases (3.1%) minor bleeding and 8 cases (0.8%) major bleeding were found in the control group, while 33 cases (3.4%) minor bleeding events and 9 cases (0.9%) major bleeding events were found in the test group. THE RESULTS: in the two groups were not significantly different in either type of bleeding events (both P > 0.05). Also no significant difference was found in the bleeding events after the ending of enoxaparin administration and during the follow up. CONCLUSION: Enoxaparin may reduce the incidence of DVT and PE in patients undergoing general surgery without increased risk of bleeding.

Fully convolutional network-based multi-output model for automatic segmentation of organs at risk in thorax.

PURPOSE: To propose a multi-output fully convolutional network (MOFCN) to segment bilateral lung, heart and spinal cord in the planning thoracic computed tomography (CT) slices automatically and simultaneously. METHODS: The MOFCN includes two components: one main backbone and three branches. The main backbone extracts the features about lung, heart and spinal cord. The extracted features are transferred to three branches which correspond to three organs respectively. The longest branch to segment spinal cord is nine layers, including input and output layers. The MOFCN was evaluated on 19,277 CT slices from 966 patients with cancer in the thorax. In these slices, the organs at risk (OARs) were delineated and validated by experienced radiation oncologists, and served as ground truth for training and evaluation. The data from 61 randomly chosen patients were used for training and validation. The remaining 905 patients' slices were used for testing. The metric used to evaluate the similarity between the auto-segmented organs and their ground truth was Dice. Besides, we compared the MOFCN with other published models. To assess the distinct output design and the impact of layer number and dilated convolution, we compared MOFCN with a multi-label learning model and its variants. By analyzing the not good performances, we suggested possible solutions. RESULTS: MOFCN achieved Dice of 0.95 ± 0.02 for lung, 0.91 ± 0.03 for heart and 0.87 ± 0.06 for spinal cord. Compared to other models, MOFCN could achieve a comparable accuracy with the least time cost. CONCLUSION: The results demonstrated the MOFCN's effectiveness. It uses less parameters to delineate three OARs simultaneously and automatically, and thus shows a relatively low requirement for hardware and has potential for broad application.

Dosimetric evaluation of image-guided radiation therapy for prostate cancer.

The aim of this study was to investigate the dosimetric accuracy of imaged-guided radiation therapy for prostate patients using the in-room computed tomography (CT) target localization technique. A Siemens CT-on-rails system was used for patient setup and target localization for intensity-modulated radiation therapy (IMRT) of prostate cancer. Fifteen previously treated prostate patients were included in this retrospective study. CT-on-Rails scans were performed before and after the IMRT treatment under local IRB approval. A total of 15 original simulation CT scans and 98 post-treatment CT scans were contoured by the same oncologist to delineate the prostate target, bladder, and rectum. IMRT plans were generated on the original simulation CTs and the same MUs and leaf sequences were used to compute the dose distributions using post-treatment CTs. Varian Velocity deformable registration was used for the summation of the fractional doses and the cumulative doses were compared with the planned doses. For the 15 patients investigated, the mean isocenter shift was up to 4.0 mm in the left-right direction, 5.9 mm in the anterior-posterior direction and 5.6 mm in the superior-inferior direction due to interfractional organ motion. The mean rectal volume varied from 0.6 to 1.73 times and the mean bladder volume varied from 0.59 to 3.65 times between simulation and the end of treatment. The prescription dose to 95% of the PTV, Dp, was set to 76 Gy for all treatment plans. The dose to 95% of the clinical treatment volume (CTV), D95, was 74.0 to 77.6 Gy and the minimum CTV dose, Dmin, was 61.0 to 71.6 Gy, respectively, in the cumulative dose distributions. Detailed analyses showed that 7.1% of the treatment fractions had cold spots (< 85% of Dp) in the peripheral CTV, leading to Dmin < 64 Gy in the cumulative dose distributions for 4 patients. The rectal dose-volume constraints were violated in 35.7% of the treatment fractions while the bladder dose was much improved in 82.7% of the treatment fractions. The current IGRT procedure for patient setup and target localization using rigid-body registration based on contour/anatomy matching is effective for population-based PTV margins. For a small group of patients, specific PTV margins and/or real-time target monitoring/tracking will be necessary due to significant prostate deformation/rotation caused by inter- and intrafractional bladder and rectal volume variation.

Comparing of two dimensional and three dimensional fully convolutional networks for radiotherapy dose prediction in left-sided breast cancer.

Fully convolutional networks were developed for predicting optimal dose distributions for patients with left-sided breast cancer and compared the prediction accuracy between two-dimensional and three-dimensional networks. Sixty cases treated with volumetric modulated arc radiotherapy were analyzed. Among them, 50 cases were randomly chosen to conform the training set, and the remaining 10 were to construct the test set. Two U-Net fully convolutional networks predicted the dose distributions, with two-dimensional and three-dimensional convolution kernels, respectively. Computed tomography images, delineated regions of interest, or their combination were considered as input data. The accuracy of predicted results was evaluated against the clinical dose. Most types of input data retrieved a similar dose to the ground truth for organs at risk (p > 0.05). Overall, the two-dimensional model had higher performance than the three-dimensional model (p < 0.05). Moreover, the two-dimensional region of interest input provided the best prediction results regarding the planning target volume mean percentage difference (2.40 ± 0.18%), heart mean percentage difference (4.28 ± 2.02%), and the gamma index at 80% of the prescription dose are with tolerances of 3 mm and 3% (0.85 ± 0.03), whereas the two-dimensional combined input provided the best prediction regarding ipsilateral lung mean percentage difference (4.16 ± 1.48%), lung mean percentage difference (2.41 ± 0.95%), spinal cord mean percentage difference (0.67 ± 0.40%), and 80% Dice similarity coefficient (0.94 ± 0.01). Statistically, the two-dimensional combined inputs achieved higher prediction accuracy regarding 80% Dice similarity coefficient than the two-dimensional region of interest input (0.94 ± 0.01 vs 0.92 ± 0.01, p < 0.05). The two-dimensional data model retrieves higher performance than its three-dimensional counterpart for dose prediction, especially when using region of interest and combined inputs.

Automatic Planning for Nasopharyngeal Carcinoma Based on Progressive Optimization in RayStation Treatment Planning System.

OBJECTIVE: To evaluate and quantify the planning performance of automatic planning (AP) with manual planning (MP) for nasopharyngeal carcinoma in the RayStation treatment planning system (TPS). METHODS: A progressive and effective design method for AP of nasopharyngeal carcinoma was realized through automated scripts in this study. A total of 30 patients with nasopharyngeal carcinoma with initial treatment was enrolled. The target coverage, conformity index (CI), homogeneity index (HI), organs at risk sparing, and the efficiency of design and execution were compared between automatic and manual volumetric modulated arc therapy (VMAT) plans. RESULTS: The results of the 2 design methods met the clinical dose requirement. The differences in D95 between the 2 groups in PTV1 and PTV2 showed statistical significance, and the MPs are higher than APs, but the difference in absolute dose was only 0.21% and 0.16%. The results showed that the conformity index of planning target volumes (PTV1, PTV2, PTVnd and PGTVnx+rpn [PGTVnx and PGTVrpn]), homogeneity index of PGTVnx+rpn, and HI of PTVnd in APs are better than that in MPs. For organs at risk, the APs are lower than the MPs, and the difference was statistically significant (P < .05). The manual operation time in APs was 83.21% less than that in MPs, and the computer processing time was 34.22% more. CONCLUSION: IronPython language designed by RayStation TPS has clinical application value in the design of automatic radiotherapy plan for nasopharyngeal carcinoma. The dose distribution of tumor target and organs at risk in the APs was similar or better than those in the MPs. The time of manual operation in the plan design showed a sharp reduction, thus significantly improving the work efficiency in clinical application.