Deep learning-based automatic segmentation of cardiac substructures for lung cancers.

PURPOSE: Accurate and comprehensive segmentation of cardiac substructures is crucial for minimizing the risk of radiation-induced heart disease in lung cancer radiotherapy. We sought to develop and validate deep learning-based auto-segmentation models for cardiac substructures. MATERIALS AND METHODS: Nineteen cardiac substructures (whole heart, 4 heart chambers, 6 great vessels, 4 valves, and 4 coronary arteries) in 100 patients treated for non-small cell lung cancer were manually delineated by two radiation oncologists. The valves and coronary arteries were delineated as planning risk volumes. An nnU-Net auto-segmentation model was trained, validated, and tested on this dataset with a split ratio of 75:5:20. The auto-segmented contours were evaluated by comparing them with manually drawn contours in terms of Dice similarity coefficient (DSC) and dose metrics extracted from clinical plans. An independent dataset of 42 patients was used for subjective evaluation of the auto-segmentation model by 4 physicians. RESULTS: The average DSCs were 0.95 (+/- 0.01) for the whole heart, 0.91 (+/- 0.02) for 4 chambers, 0.86 (+/- 0.09) for 6 great vessels, 0.81 (+/- 0.09) for 4 valves, and 0.60 (+/- 0.14) for 4 coronary arteries. The average absolute errors in mean/max doses to all substructures were 1.04 (+/- 1.99) Gy and 2.20 (+/- 4.37) Gy. The subjective evaluation revealed that 94% of the auto-segmented contours were clinically acceptable. CONCLUSION: We demonstrated the effectiveness of our nnU-Net model for delineating cardiac substructures, including coronary arteries. Our results indicate that this model has promise for studies regarding radiation dose to cardiac substructures.

Stereotactic ablative radiotherapy with or without immunotherapy for early-stage or isolated lung parenchymal recurrent node-negative non-small-cell lung cancer: an open-label, randomised, phase 2 trial.

BACKGROUND: Stereotactic ablative radiotherapy (SABR) is the standard treatment for medically inoperable early-stage non-small-cell lung cancer (NSCLC), but regional or distant relapses, or both, are common. Immunotherapy reduces recurrence and improves survival in people with stage III NSCLC after chemoradiotherapy, but its utility in stage I and II cases is unclear. We therefore conducted a randomised phase 2 trial of SABR alone compared with SABR with immunotherapy (I-SABR) for people with early-stage NSCLC. METHODS: We did an open-label, randomised, phase 2 trial comparing SABR to I-SABR, conducted at three different hospitals in TX, USA. People aged 18 years or older with histologically proven treatment-naive stage IA-IB (tumour size ≤4 cm, N0M0), stage IIA (tumour size ≤5 cm, N0M0), or stage IIB (tumour size >5 cm and ≤7 cm, N0M0) as per the American Joint Committee on Cancer version 8 staging system or isolated parenchymal recurrences (tumour size ≤7 cm) NSCLC (TanyNanyM0 before definitive surgery or chemoradiotherapy) were included in this trial. Participants were randomly assigned (1:1; using the Pocock & Simon method) to receive SABR with or without four cycles of nivolumab (480 mg, once every 4 weeks, with the first dose on the same day as, or within 36 h after, the first SABR fraction). This trial was unmasked. The primary endpoint was 4-year event-free survival (local, regional, or distant recurrence; second primary lung cancer; or death). Analyses were both intention to treat (ITT) and per protocol. This trial is registered with ClinicalTrials.gov (NCT03110978) and is closed to enrolment. FINDINGS: From June 30, 2017, to March 22, 2022, 156 participants were randomly assigned, and 141 participants received assigned therapy. At a median 33 months' follow-up, I-SABR significantly improved 4-year event-free survival from 53% (95% CI 42-67%) with SABR to 77% (66-91%; per-protocol population, hazard ratio [HR] 0·38; 95% CI 0·19-0·75; p=0·0056; ITT population, HR 0·42; 95% CI 0·22-0·80; p=0·0080). There were no grade 3 or higher adverse events associated with SABR. In the I-SABR group, ten participants (15%) had grade 3 immunologial adverse events related to nivolumab; none had grade 3 pneumonitis or grade 4 or higher toxicity. INTERPRETATION: Compared with SABR alone, I-SABR significantly improved event-free survival at 4 years in people with early-stage treatment-naive or lung parenchymal recurrent node-negative NSCLC, with tolerable toxicity. I-SABR could be a treatment option in these participants, but further confirmation from a number of currently accruing phase 3 trials is required. FUNDING: Bristol-Myers Squibb and MD Anderson Cancer Center Alliance, National Cancer Institute at the National Institutes of Health through Cancer Center Core Support Grant and Clinical and Translational Science Award to The University of Texas MD Anderson Cancer Center.

The potential of biology-guided radiation therapy in thoracic cancer: A preliminary treatment planning study.

Purpose: We investigated the feasibility of biology-guided radiotherapy (BgRT), a technique that utilizes real-time positron emission imaging to minimize tumor motion uncertainties, to spare nearby organs at risk. Methods: Volumetric modulated arc therapy (VMAT), intensity-modulated proton (IMPT) therapy, and BgRT plans were created for a paratracheal node recurrence (case 1; 60 Gy in 10 fractions) and a primary peripheral left upper lobe adenocarcinoma (case 2; 50 Gy in four fractions). Results: For case 1, BgRT produced lower bronchus V40 values compared to VMAT and IMPT. For case 2, total lung V20 was lower in the BgRT case compared to VMAT and IMPT. Conclusions: BgRT has the potential to reduce the radiation dose to proximal critical structures but requires further detailed investigation.

Adding customized electron energy beams to TrueBeam linear accelerators.

PURPOSE: To better meet clinical needs and facilitate optimal treatment planning, we added two new electron energy beams (7 and 11 MeV) to two Varian TrueBeam linacs. METHODS: We worked with the vendor to create two additional customized electron energies without hardware modifications. For each beam, we set the bending magnet current and then optimized other beam-specific parameters to achieve depths of 50% ionization (I50 ) of 2.9 cm for 7 MeV and 4.2 cm for the 11 MeV beam with the 15 × 15 cm2 cone at 100 cm source-to-surface distance (SSD) by using an ionization chamber profiler (ICP) with a double-wedge (DW) phantom. Beams were steered and balanced to optimize symmetry with the ICP. After all parameters were set, full commissioning was done including measuring beam profiles, percent depth doses (PDDs), output factors (OFs) at standard, and extended SSDs. Measured data were compared between the two linacs and against the values calculated by our RayStation treatment planning system (TPS) following Medical Physics Practice Guideline 5.a (MPPG 5.a) guidelines. RESULTS: The I50 values initially determined with the ICP/DW agreed with those from a PDD-scanned in-water phantom within 0.2 mm for the 7 and 11 MeV on both linacs. Comparison of the beam characteristics from the two linacs indicated that flatness and symmetry agreed within 0.4%, and point-by-point differences in PDD were within 0.01% ± 0.3% for the 7 MeV and 0.01% ± 0.3% for the 11 MeV. The OF ratios between the two linacs were 1.000 ± 0.007 for the 7 MeV and 1.004 ± 0.007 for the 11 MeV. Agreement between TPS-calculated outputs and measurements were -0.1% ± 1.0% for the 7 MeV and 0.2% ± 0.8% for the 11 MeV. All other parameters met the MPPG 5.a's 3%/3-mm criteria. CONCLUSION: We were able to add two new beam energies with no hardware modifications. Tuning of the new beams was facilitated by the ICP/DW system allowing us to have the procedures done in a few hours and achieve highly consistent results across two linacs. PACS numbers: 87.55.Qr, 87.56.Fc.

Using Failure Mode and Effects Analysis to Evaluate Risk in the Clinical Adoption of Automated Contouring and Treatment Planning Tools.

PURPOSE: In this study, we applied the failure mode and effects analysis (FMEA) approach to an automated radiation therapy contouring and treatment planning tool to assess, and subsequently limit, the risk of deploying automated tools. METHODS AND MATERIALS: Using an FMEA, we quantified the risks associated with the Radiation Planning Assistant (RPA), an automated contouring and treatment planning tool currently under development. A multidisciplinary team identified and scored each failure mode, using a combination of RPA plan data and experience for guidance. A 1-to-10 scale for severity, occurrence, and detectability of potential errors was used, following American Association of Physicists in Medicine Task Group 100 recommendations. High-risk failure modes were further explored to determine how the workflow could be improved to reduce the associated risk. RESULTS: Of 290 possible failure modes, we identified 126 errors that were unique to the RPA workflow, with a mean risk priority number (RPN) of 56.3 and a maximum RPN of 486. The top 10 failure modes were caused by automation bias, operator error, and software error. Twenty-one failure modes were above the action threshold of RPN = 125, leading to corrective actions. The workflow was modified to simplify the user interface and better training resources were developed, which highlight the importance of thorough review of the output of automated systems. After the changes, we rescored the high-risk errors, resulting in a final mean and maximum RPN of 33.7 and 288, respectively. CONCLUSIONS: We identified 126 errors specific to the automated workflow, most of which were caused by automation bias or operator error, which emphasized the need to simplify the user interface and ensure adequate user training. As a result of changes made to the software and the enhancement of training resources, the RPNs subsequently decreased, showing that FMEA is an effective way to assess and reduce risk associated with the deployment of automated planning tools.

Body region-specific 3D age-scaling functions for scaling whole-body computed tomography anatomy for pediatric late effects studies.

Purpose.Radiation epidemiology studies of childhood cancer survivors treated in the pre-computed tomography (CT) era reconstruct the patients' treatment fields on computational phantoms. For such studies, the phantoms are commonly scaled to age at the time of radiotherapy treatment because age is the generally available anthropometric parameter. Several reference size phantoms are used in such studies, but reference size phantoms are only available at discrete ages (e.g.: newborn, 1, 5, 10, 15, and Adult). When such phantoms are used for RT dose reconstructions, the nearest discrete-aged phantom is selected to represent a survivor of a specific age. In this work, we (1) conducted a feasibility study to scale reference size phantoms at discrete ages to various other ages, and (2) evaluated the dosimetric impact of using exact age-scaled phantoms as opposed to nearest age-matched phantoms at discrete ages.Methods.We have adopted the University of Florida/National Cancer Institute (UF/NCI) computational phantom library for our studies. For the feasibility study, eight male and female reference size UF/NCI phantoms (5, 10, 15, and 35 years) were downscaled to fourteen different ages which included next nearest available lower discrete ages (1, 5, 10 and 15 years) and the median ages at the time of RT for Wilms' tumor (3.9 years), craniospinal (8.0 years), and all survivors (9.1 years old) in the Childhood Cancer Survivor Study (CCSS) expansion cohort treated with RT. The downscaling was performed using our in-house age scaling functions (ASFs). To geometrically validate the scaling, Dice similarity coefficient (DSC), mean distance to agreement (MDA), and Euclidean distance (ED) were calculated between the scaled and ground-truth discrete-aged phantom (unscaled UF/NCI) for whole-body, brain, heart, liver, pancreas, and kidneys. Additionally, heights of the scaled phantoms were compared with ground-truth phantoms' height, and the Centers for Disease Control and Prevention (CDC) reported 50th percentile height. Scaled organ masses were compared with ground-truth organ masses. For the dosimetric assessment, one reference size phantom and seventeen body-size dependent 5-year-old phantoms (9 male and 8 female) of varying body mass indices (BMI) were downscaled to 3.9-year-old dimensions for two different radiation dose studies. For the first study, we simulated a 6 MV photon right-sided flank field RT plan on a reference size 5-year-old and 3.9-year-old (both of healthy BMI), keeping the field size the same in both cases. Percent of volume receiving dose ≥15 Gy (V15) and the mean dose were calculated for the pancreas, liver, and stomach. For the second study, the same treatment plan, but with patient anatomy-dependent field sizes, was simulated on seventeen body-size dependent 5- and 3.9-year-old phantoms with varying BMIs. V15, mean dose, and minimum dose received by 1% of the volume (D1), and by 95% of the volume (D95) were calculated for pancreas, liver, stomach, left kidney (contralateral), right kidney, right and left colons, gallbladder, thoracic vertebrae, and lumbar vertebrae. A non-parametric Wilcoxon rank-sum test was performed to determine if the dose to organs of exact age-scaled and nearest age-matched phantoms were significantly different (p < 0.05).Results.In the feasibility study, the best DSCs were obtained for the brain (median: 0.86) and whole-body (median: 0.91) while kidneys (median: 0.58) and pancreas (median: 0.32) showed poorer agreement. In the case of MDA and ED, whole-body, brain, and kidneys showed tighter distribution and lower median values as compared to other organs. For height comparison, the overall agreement was within 2.8% (3.9 cm) and 3.0% (3.2 cm) of ground-truth UF/NCI and CDC reported 50th percentile heights, respectively. For mass comparison, the maximum percent and absolute differences between the scaled and ground-truth organ masses were within 31.3% (29.8 g) and 211.8 g (16.4%), respectively (across all ages). In the first dosimetric study, absolute difference up to 6% and 1.3 Gy was found for V15and mean dose, respectively. In the second dosimetric study, V15and mean dose were significantly different (p < 0.05) for all studied organs except the fully in-beam organs. D1and D95were not significantly different for most organs (p > 0.05).Conclusion.We have successfully evaluated our ASFs by scaling UF/NCI computational phantoms from one age to another age, which demonstrates the feasibility of scaling any CT-based anatomy. We have found that dose to organs of exact age-scaled and nearest aged-matched phantoms are significantly different (p < 0.05) which indicates that using the exact age-scaled phantoms for retrospective dosimetric studies is a better approach.

Stereotactic ablative radiotherapy for operable stage I non-small-cell lung cancer (revised STARS): long-term results of a single-arm, prospective trial with prespecified comparison to surgery.

BACKGROUND: A previous pooled analysis of the STARS and ROSEL trials showed higher survival after stereotactic ablative radiotherapy (SABR) than with surgery for operable early-stage non-small-cell lung cancer (NSCLC), but that analysis had notable limitations. This study reports long-term results of the revised STARS trial, in which the SABR group was re-accrued with a larger sample size, along with a protocol-specified propensity-matched comparison with a prospectively registered, contemporary institutional cohort of patients who underwent video-assisted thoracoscopic surgical lobectomy with mediastinal lymph node dissection (VATS L-MLND). METHODS: This single-arm prospective trial was done at the University of Texas MD Anderson Cancer Center (Houston, TX, USA) and enrolled patients aged 18 years or older with a Zubrod performance status of 0-2, newly diagnosed and histologically confirmed NSCLC with N0M0 disease (squamous cell, adenocarcinoma, large cell, or NSCLC not otherwise specified), and a tumour diameter of 3 cm or less. This trial did not include patients from the previous pooled analysis. SABR dosing was 54 Gy in three fractions (for peripheral lesions) or 50 Gy in four fractions (for central tumours; simultaneous integrated boost to gross tumour totalling 60 Gy). The primary endpoint was the 3-year overall survival. For the propensity-matching analysis, we used a surgical cohort from the MD Anderson Department of Thoracic and Cardiovascular Surgery's prospectively registered, institutional review board-approved database of all patients with clinical stage I NSCLC who underwent VATS L-MLND during the period of enrolment in this trial. Non-inferiority could be claimed if the 3-year overall survival rate after SABR was lower than that after VATS L-MLND by 12% or less and the upper bound of the 95% CI of the hazard ratio (HR) was less than 1·965. Propensity matching consisted of determining a propensity score using a multivariable logistic regression model including several covariates (age, tumour size, histology, performance status, and the interaction of age and sex); based on the propensity scores, one patient in the SABR group was randomly matched with one patient in the VATS L-MLND group using a 5:1 digit greedy match algorithm. This study is registered with ClinicalTrials.gov, NCT02357992. FINDINGS: Between Sept 1, 2015, and Jan 31, 2017, 80 patients were enrolled and included in efficacy and safety analyses. Median follow-up time was 5·1 years (IQR 3·9-5·8). Overall survival was 91% (95% CI 85-98) at 3 years and 87% (79-95) at 5 years. SABR was tolerated well, with no grade 4-5 toxicity and one (1%) case each of grade 3 dyspnoea, grade 2 pneumonitis, and grade 2 lung fibrosis. No serious adverse events were recorded. Overall survival in the propensity-matched VATS L-MLND cohort was 91% (95% CI 85-98) at 3 years and 84% (76-93) at 5 years. Non-inferiority was claimed since the 3-year overall survival after SABR was not lower than that observed in the VATS L-MLND group. There was no significant difference in overall survival between the two patient cohorts (hazard ratio 0·86 [95% CI 0·45-1·65], p=0·65) from a multivariable analysis. INTERPRETATION: Long-term survival after SABR is non-inferior to VATS L-MLND for operable stage IA NSCLC. SABR remains promising for such cases but multidisciplinary management is strongly recommended. FUNDING: Varian Medical Systems and US National Cancer Institute (National Institutes of Health).

Beam energy metrics for the acceptance and quality assurance of Halcyon linear accelerator.

PURPOSE: Establish and compare two metrics for monitoring beam energy changes in the Halcyon platform and evaluate the accuracy of these metrics across multiple Halcyon linacs. METHOD: The first energy metric is derived from the diagonal normalized flatness (FDN ), which is defined as the ratio of the average measurements at a fixed off-axis equal distance along the open profiles in two diagonals to the measurement at the central axis with an ionization chamber array (ICA). The second energy metric comes from the area ratio (AR) of the quad wedge (QW) profiles measured with the QW on the top of the ICA. Beam energy is changed by adjusting the magnetron current in a non-clinical Halcyon. With D10cm measured in water at each beam energy, the relationships between FDN or AR energy metrics to D10cm in water is established with linear regression across six energy settings. The coefficients from these regressions allow D10cm (FDN ) calculation from FDN using open profiles and D10cm (QW) calculation from AR using QW profiles. RESULTS: Five Halcyon linacs from five institutions were used to evaluate the accuracy of the D10cm (FDN ) and the D10cm (QW) energy metrics by comparing to the D10cm values computed from the treatment planning system (TPS) and D10cm measured in water. For the five linacs, the D10cm (FDN ) reported by the ICA based on FDN from open profiles agreed with that calculated by TPS within -0.29 ± 0.23% and 0.61% maximum discrepancy; the D10cm (QW) reported by the QW profiles agreed with that calculated by TPS within -0.82 ± 1.27% and -2.43% maximum discrepancy. CONCLUSION: The FDN -based energy metric D10cm (FDN ) can be used for acceptance testing of beam energy, and also for the verification of energy in periodic quality assurance (QA) processes.

Our Experience Leading a Large Medical Physics Practice During the COVID-19 Pandemic.

PURPOSE: To provide a series of suggestions for other Medical Physics practices to follow in order to provide effective radiation therapy treatments during the COVID-19 pandemic. METHODS AND MATERIALS: We reviewed our entire Radiation Oncology infrastructure to identify a series of workflows and policy changes that we implemented during the pandemic that yielded more effective practices during this time. RESULTS: We identified a structured list of several suggestions that can help other Medical Physics practices overcome the challenges involved in delivering high quality radiotherapy services during this pandemic. CONCLUSIONS: Our facility encompasses 4 smaller Houston Area Locations (HALs), a main campus with 8 distinct services based on treatment site (ie. Thoracic, Head and Neck, Breast, Gastrointestinal, Gynecology, Genitourinary, Hematologic Malignancies, Melanoma and Sarcoma and Central Nervous System/Pediatrics), a Proton Center facility, an MR-Linac, a Gamma Knife clinic and an array of brachytherapy services. Due to the scope of our services, we have gained experience in dealing with the rapidly changing pandemic effects on our clinical practice. Our paper provides a resource to other Medical Physics practices in search of workflows that have been resilient during these challenging times.

Dose calculation errors as a component of failing IROC lung and spine phantom irradiations.

PURPOSE: Between July 2013 and August 2019, 22% of the imaging and radiation oncology core (IROC) spine, and 15% of the moving lung phantom irradiations have failed to meet established acceptability criteria. The spine phantom simulates a highly modulated stereotactic body radiation therapy (SBRT) case, whereas the lung phantom represents a low-to-none modulation moving target case. In this study, we assessed the contribution of dose calculation errors to these phantom results and evaluated their effects on failure rates. METHODS: We evaluated dose calculation errors by comparing the calculation accuracy of various institutions' treatment planning systems (TPSs) vs IROC-Houston's previously established independent dose recalculation system (DRS). Each calculation was compared with the measured dose actually delivered to the phantom; cases in which the recalculation was more accurate were interpreted as a deficiency in the institution's TPS. A total of 258 phantom irradiation plans (172 lung and 86 spine) were recomputed. RESULTS: Overall, the DRS performed better than the TPSs in 47% of the spine phantom cases. However, the DRS was more accurate in 93% of failing spine phantom cases (with an average improvement of 2.35%), indicating a deficiency in the institution's treatment planning system. Deficiencies in dose calculation accounted for 60% of the overall discrepancy between measured and planned doses among spine phantoms. In contrast, lung phantom DRS calculations were more accurate in only 35% and 42% of all and failing lung phantom cases respectively, indicating that dose calculation errors were not substantially present. These errors accounted for only 30% of the overall discrepancy between measured and planned doses. CONCLUSIONS: Dose calculation errors are common and substantial in IROC spine phantom irradiations, highlighting a major failure mode in this phantom and in clinical treatment management of these cases. In contrast, dose calculation accuracy had only a minimal contribution to failing lung phantom results, indicating that other failure modes drive problems with this phantom and similar clinical treatments.

Stereotactic ablative radiation therapy for pulmonary metastases: Improving overall survival and identifying subgroups at high risk of local failure.

BACKGROUND & PURPOSE: Stereotactic ablative radiation therapy (SABR) is an emerging treatment option for patients with pulmonary metastases; identifying patients who would benefit from SABR can improve outcomes. MATERIALS & METHODS: We retrospectively analyzed local failure (LF), distant failure (DF), overall survival (OS), and toxicity in 317 patients with 406 pulmonary metastases treated with SABR in January 2006-September 2017 at a tertiary cancer center. RESULTS: Median follow-up time was 23 months. Primary adrenal, colorectal, sarcoma, or pancreatic ("less responsive") tumors led to high rates of LF. LF rates for patients with less responsive vs. responsive tumors were 4.6% vs. 1.6% at 12 months and 12.8% vs. 3.9% at 24 months (hazard ratio [HR] 0.29, 95% confidence interval [CI] 0.11-0.73; Log-Rank P = 0.0087). A nomogram for 24-month local control was created using Cox multivariate factors (surgical history, planning target volume, primary disease site, lung lobe location). Treating patients with ≤3 pulmonary metastases vs. >3 pulmonary metastases was associated with improved 24-month (74.2% vs. 59.3%) and 48-month (47.7% vs. 35.1%) OS (HR 0.66, 95% CI 0.47-0.95; Log-Rank P = 0.043), and reduced 12-month (22.5% vs. 50.8%) and 24-month (31.8% vs. 61.4%) intrathoracic DF (HR 0.53, 95% CI 0.38-0.74; Log-Rank P < 0.0001). The most common toxicity was asymptomatic pneumonitis (14.8%). Six patients had grade 3 events (5 pneumonitis, 1 brachial plexus). CONCLUSIONS: SABR for pulmonary metastases was effective and well tolerated. Irradiating limited intrathoracic sites of disease led to improved OS and intrathoracic DM. Higher SABR doses or surgery could be considered for less radio-responsive primary tumors.

Development of an age-scalable 3D computational phantom in DICOM standard for late effects studies of childhood cancer survivors.

Purpose: We previously developed an age-scalable 3D computational phantom that has been widely used for retrospective whole-body dose reconstructions of conventional two-dimensional historic radiation therapy (RT) treatments in late effects studies of childhood cancer survivors. This phantom is modeled in the FORTRAN programming language and is not readily applicable for dose reconstructions for survivors treated with contemporary RT whose treatment plans were designed using computed tomography images and complex treatment fields. The goal of this work was to adapt the current FORTRAN model of our age-scalable computational phantom into Digital Imaging and Communications in Medicine (DICOM) standard so that it can be used with any treatment planning system (TPS) to reconstruct contemporary RT. Additionally, we report a detailed description of the phantom's age-based scaling functions, information that was not previously published. Method: We developed a Python script that adapts our phantom model from FORTRAN to DICOM. To validate the conversion, we compared geometric parameters for the phantom modeled in FORTRAN and DICOM scaled to ages 1 month, 6 months, 1, 2, 3, 5, 8, 10, 15, and 18 years. Specifically, we calculated the percent differences between the corner points and volume of each body region and the normalized mean square distance (NMSD) between each of the organs. In addition, we also calculated the percent difference between the heights of our DICOM age-scaled phantom and the heights (50th percentile) reported by the World Health Organization (WHO) and Centers for Disease Control and Prevention (CDC) for male and female children of the same ages. Additionally, we calculated the difference between the organ masses for our DICOM phantom and the organ masses for two reference phantoms (from International Comission on Radiation Protection (ICRP) 89 and the University of Florida/National Cancer Institute reference hybrid voxel phantoms) for ages newborn, 1, 5, 10, 15 and adult. Lastly, we conducted a feasibility study using our DICOM phantom for organ dose calculations in a commercial TPS. Specifically, we simulated a 6 MV photon right-sided flank field RT plan for our DICOM phantom scaled to age 3.9 years; treatment field parameters and age were typical of a Wilms tumor RT treatment in the Childhood Cancer Survivor Study. For comparison, the same treatment was simulated using our in-house dose calculation system with our FORTRAN phantom. The percent differences (between FORTRAN and DICOM) in mean dose and percent of volume receiving dose ⩾5 Gy were calculated for two organs at risk, liver and pancreas. Results: The percent differences in corner points and the volumes of head, neck, and trunk body regions between our phantom modeled in FORTRAN and DICOM agreed within 3%. For all of the ages, the NMSDs were negliglible with a maximum NMSD of 7.80 × 10-2 mm for occiptital lobe of 1 month. The heights of our age-scaled phantom agreed with WHO/CDC data within 7% from infant to adult, and within 2% agreement for ages 5 years and older. We observed that organ masses in our phantom are less than the organ masses for other reference phantoms. Dose calculations done with our in-house calculation system (with FORTRAN phantom) and commercial TPS (with DICOM phantom) agreed within 7%. Conclusion: We successfully adapted our phantom model from the FORTRAN language to DICOM standard and validated its geometric consistency. We also demonstrated that our phantom model is representative of population height data for infant to adult, but that the organ masses are smaller than in other reference phantoms and need further refinement. Our age-scalable computational phantom modeled in DICOM standard can be scaled to any age at RT and used within a commercial TPS to retrospectively reconstruct doses from contemporary RT in childhood cancer survivors.

Evaluation of a multiview architecture for automatic vertebral labeling of palliative radiotherapy simulation CT images.

PURPOSE: The purpose of this work was to evaluate the performance of X-Net, a multiview deep learning architecture, to automatically label vertebral levels (S2-C1) in palliative radiotherapy simulation CT scans. METHODS: For each patient CT scan, our automated approach 1) segmented spinal canal using a convolutional-neural network (CNN), 2) formed sagittal and coronal intensity projection pairs, 3) labeled vertebral levels with X-Net, and 4) detected irregular intervertebral spacing using an analytic methodology. The spinal canal CNN was trained via fivefold cross validation using 1,966 simulation CT scans and evaluated on 330 CT scans. After labeling vertebral levels (S2-C1) in 897 palliative radiotherapy simulation CT scans, a volume of interest surrounding the spinal canal in each patient's CT scan was converted into sagittal and coronal intensity projection image pairs. Then, intensity projection image pairs were augmented and used to train X-Net to automatically label vertebral levels using fivefold cross validation (n = 803). Prior to testing upon the final test set (n = 94), CT scans of patients with anatomical abnormalities, surgical implants, or other atypical features from the final test set were placed in an outlier group (n = 20), whereas those without these features were placed in a normative group (n = 74). The performance of X-Net, X-Net Ensemble, and another leading vertebral labeling architecture (Btrfly Net) was evaluated on both groups using identification rate, localization error, and other metrics. The performance of our approach was also evaluated on the MICCAI 2014 test dataset (n = 60). Finally, a method to detect irregular intervertebral spacing was created based on the rate of change in spacing between predicted vertebral body locations and was also evaluated using the final test set. Receiver operating characteristic analysis was used to investigate the performance of the method to detect irregular intervertebral spacing. RESULTS: The spinal canal architecture yielded centroid coordinates spanning S2-C1 with submillimeter accuracy (mean ± standard deviation, 0.399 ± 0.299 mm; n = 330 patients) and was robust in the localization of spinal canal centroid to surgical implants and widespread metastases. Cross-validation testing of X-Net for vertebral labeling revealed that the deep learning model performance (F1 score, precision, and sensitivity) improved with CT scan length. The X-Net, X-Net Ensemble, and Btrfly Net mean identification rates and localization errors were 92.4% and 2.3 mm, 94.2% and 2.2 mm, and 90.5% and 3.4 mm, respectively, in the final test set and 96.7% and 2.2 mm, 96.9% and 2.0 mm, and 94.8% and 3.3 mm, respectively, within the normative group of the final test set. The X-Net Ensemble yielded the highest percentage of patients (94%) having all vertebral bodies identified correctly in the final test set when the three most inferior and superior vertebral bodies were excluded from the CT scan. The method used to detect labeling failures had 67% sensitivity and 95% specificity when combined with the X-Net Ensemble and flagged five of six patients with atypical vertebral counts (additional thoracic (T13), additional lumbar (L6) or only four lumbar vertebrae). Mean identification rate on the MICCAI 2014 dataset using an X-Net Ensemble was increased from 86.8% to 91.3% through the use of transfer learning and obtained state-of-the-art results for various regions of the spine. CONCLUSIONS: We trained X-Net, our unique convolutional neural network, to automatically label vertebral levels from S2 to C1 on palliative radiotherapy CT images and found that an ensemble of X-Net models had high vertebral body identification rate (94.2%) and small localization errors (2.2 ± 1.8 mm). In addition, our transfer learning approach achieved state-of-the-art results on a well-known benchmark dataset with high identification rate (91.3%) and low localization error (3.3 mm ± 2.7 mm). When we pre-screened radiotherapy CT images for the presence of hardware, surgical implants, or other anatomic abnormalities prior to the use of X-Net, it labeled the spine correctly in more than 97% of patients and 94% of patients when scans were not prescreened. Automatically generated labels are robust to widespread vertebral metastases and surgical implants and our method to detect labeling failures based on neighborhood intervertebral spacing can reliably identify patients with an additional lumbar or thoracic vertebral body.

Monitoring linear accelerators electron beam energy constancy with a 2D ionization chamber array and double-wedge phantom.

Validate that a two-dimensional (2D) ionization chamber array (ICA) combined with a double-wedge plate (DWP) can track changes in electron beam energy well within 2.0 mms as recommended by TG-142 for monthly quality assurance (QA). Electron beam profiles of 4-22 MeV were measured for a 25 × 25 cm2 cone using an ICA with a DWP placed on top of it along one diagonal axis. The relationship between the full width half maximum (FWHM) field size created by DWP energy degradation across the field and the depth of 50% dose in water (R50 ) is calibrated for a given ICA/DWP combination in beams of know energies (R50 values). Once this relationship is established, the ICA/DWP system will report the R50 FWHM directly. We calibrated the ICA/DWP on a linear accelerator with energies of 6, 9, 12, 16, 20, and 22 MeV. The R50 FWHM values of these beams and eight other beams with different R50 values were measured and compared with the R50 measured in water, that is, R50 Water. Resolving changes of R50 up to 0.2 cm with ICA/DWP was tested by adding solid-water to shift the energy and was verified with R50 Water measurements. To check the long-term reproducibility of ICA/DWP we measured R50 FWHM on a monthly basis for a period of 3 yr. We proposed a universal calibration procedure considering the off-axis corrections and compared calibrations and measurements on three types of linacs (Varian TrueBeam, Varian C-series, and Elekta) with different nominal energies and R50 values. For all 38 beams on same type of linac with R50 values over a range of 2-8.8 cm, the R50 FWHM reported by the ICA/DWP system agreed with that measured in water within 0.01 ± 0.03 cm (mean ± 1σ) and maximum discrepancy of 0.07 cm. Long-term reproducibility results show the ICA/DWP system to be within 0.04 cm of their baseline over 3 yr. With the universal calibration the maximum discrepancy between R50 FWHM and R50 Water for different types of linac reduced from 0.25 to 0.06 cm. Comparison of R50 FWHM values and R50 Water values and long-term reproducibility of R50 FWHM values indicates that the ICA/DWP can be used for monitoring of electron beam energy constancy well within TG-142 recommended tolerance.

Acceptance and verification of the Halcyon-Eclipse linear accelerator-treatment planning system without 3D water scanning system.

We tested whether an ionization chamber array (ICA) and a one-dimensional water scanner (1DS) could be used instead of a three-dimensional water scanning system (3DWS) for acceptance testing and commissioning verification of the Varian Halcyon-Eclipse Treatment Planning System (TPS). The Halcyon linear accelerator has a single 6-MV flattening-filter-free beam and a nonadjustable beam model for the TPS. Beam data were measured with a 1DS, ICA, ionization chambers, and electrometer. Acceptance testing and commissioning were done simultaneously by comparing the measured data with TPS-calculated percent-depth-dose (PDD) and profiles. The ICA was used to measure profiles of various field sizes (10-, 20-, and 28 cm2 ) at depths of dmax (1.3 cm), 5-, 10-, and 20 cm. The 1DS was used for output factors (OFs) and PDDs. OFs were measured with 1DS for various fields (2-28 cm2 ) at a source-to-surface distance of 90 cm. All measured data were compared with TPS-calculations. Profiles, off-axis ratios (OAR), PDDs and OFs were also measured with a 3DWS as a secondary check. Profiles between the ICA and TPS (ICA and 3DWS) at various depths across the fields indicated that the maximum discrepancies in high-dose and low-dose tail were within 2% and 3%, respectively, and the maximum distance-to-agreement in the penumbra region was <3 mm. The largest OAR differences between ICA and TPS (ICA and 3DWS) values were 0.23% (-0.25%) for a 28 × 28 cm2 field, and the largest point-by-point PDD differences between 1DS and TPS (1DS and 3DWS) were -0.41% ± 0.12% (-0.32% ± 0.17%) across the fields. Both OAR and PDD showed the beam energy is well matched to the TPS model. The average ratios of 1DS-measured OFs to the TPS (1DS to 3DWS) values were 1.000 ± 0.002 (0.999 ± 0.003). The Halcyon-Eclipse system can be accepted and commissioned without the need for a 3DWS.

Dosimetric impact and detectability of multi-leaf collimator positioning errors on Varian Halcyon.

The purpose of this study is to investigate the dosimetric impact of multi-leaf collimator (MLC) positioning errors on a Varian Halcyon for both random and systematic errors, and to evaluate the effectiveness of portal dosimetry quality assurance in catching clinically significant changes caused by these errors. Both random and systematic errors were purposely added to 11 physician-approved head and neck volumetric modulated arc therapy (VMAT) treatment plans, yielding a total of 99 unique plans. Plans were then delivered on a preclinical Varian Halcyon linear accelerator and the fluence was captured by an opposed portal dosimeter. When comparing dose-volume histogram (DVH) values of plans with introduced MLC errors to known good plans, clinically significant changes to target structures quickly emerged for plans with systematic errors, while random errors caused less change. For both error types, the magnitude of clinically significant changes increased as error size increased. Portal dosimetry was able to detect all systematic errors, while random errors of ±5 mm or less were unlikely to be detected. Best detection of clinically significant errors, while minimizing false positives, was achieved by following the recommendations of AAPM TG-218. Furthermore, high- to moderate correlation was found between dose DVH metrics for normal tissues surrounding the target and portal dosimetry pass rates. Therefore, it may be concluded that portal dosimetry on the Halcyon is robust enough to detect errors in MLC positioning before they introduce clinically significant changes to VMAT treatment plans.

Automated treatment planning of postmastectomy radiotherapy.

PURPOSE: Breast cancer is the most common cancer in women globally and radiation therapy is a cornerstone of its treatment. However, there is an enormous shortage of radiotherapy staff, especially in low- and middle-income countries. This shortage could be ameliorated through increased automation in the radiation treatment planning process, which may reduce the workload on radiotherapy staff and improve efficiency in preparing radiotherapy treatments for patients. To this end, we sought to create an automated treatment planning tool for postmastectomy radiotherapy (PMRT). METHODS: Algorithms to automate every step of PMRT planning were developed and integrated into a commercial treatment planning system. The only required inputs for automated PMRT planning are a planning computed tomography scan, a plan directive, and selection of the inferior border of the tangential fields. With no other human input, the planning tool automatically creates a treatment plan and presents it for review. The major automated steps are (a) segmentation of relevant structures (targets, normal tissues, and other planning structures), (b) setup of the beams (tangential fields matched with a supraclavicular field), and (c) optimization of the dose distribution by using a mix of high- and low-energy photon beams and field-in-field modulation for the tangential fields. This automated PMRT planning tool was tested with ten computed tomography scans of patients with breast cancer who had received irradiation of the left chest wall. These plans were assessed quantitatively using their dose distributions and were reviewed by two physicians who rated them on a three-tiered scale: use as is, minor changes, or major changes. The accuracy of the automated segmentation of the heart and ipsilateral lung was also assessed. Finally, a plan quality verification tool was tested to alert the user to any possible deviations in the quality of the automatically created treatment plans. RESULTS: The automatically created PMRT plans met the acceptable dose objectives, including target coverage, maximum plan dose, and dose to organs at risk, for all but one patient for whom the heart objectives were exceeded. Physicians accepted 50% of the treatment plans as is and required only minor changes for the remaining 50%, which included the one patient whose plan had a high heart dose. Furthermore, the automatically segmented contours of the heart and ipsilateral lung agreed well with manually edited contours. Finally, the automated plan quality verification tool detected 92% of the changes requested by physicians in this review. CONCLUSIONS: We developed a new tool for automatically planning PMRT for breast cancer, including irradiation of the chest wall and ipsilateral lymph nodes (supraclavicular and level III axillary). In this initial testing, we found that the plans created by this tool are clinically viable, and the tool can alert the user to possible deviations in plan quality. The next step is to subject this tool to prospective testing, in which automatically planned treatments will be compared with manually planned treatments.

Magnetic Resonance-based Response Assessment and Dose Adaptation in Human Papilloma Virus Positive Tumors of the Oropharynx treated with Radiotherapy (MR-ADAPTOR): An R-IDEAL stage 2a-2b/Bayesian phase II trial.

BACKGROUND: Current standard radiotherapy for oropharynx cancer (OPC) is associated with high rates of severe toxicities, shown to adversely impact patients' quality of life. Given excellent outcomes of human papilloma virus (HPV)-associated OPC and long-term survival of these typically young patients, treatment de-intensification aimed at improving survivorship while maintaining excellent disease control is now a central concern. The recent implementation of magnetic resonance image - guided radiotherapy (MRgRT) systems allows for individual tumor response assessment during treatment and offers possibility of personalized dose-reduction. In this 2-stage Bayesian phase II study, we propose to examine weekly radiotherapy dose-adaptation based on magnetic resonance imaging (MRI) evaluated tumor response. Individual patient's plan will be designed to optimize dose reduction to organs at risk and minimize locoregional failure probability based on serial MRI during RT. Our primary aim is to assess the non-inferiority of MRgRT dose adaptation for patients with low risk HPV-associated OPC compared to historical control, as measured by Bayesian posterior probability of locoregional control (LRC). METHODS: Patients with T1-2 N0-2b (as per AJCC 7th Edition) HPV-positive OPC, with lymph node <3 cm and <10 pack-year smoking history planned for curative radiotherapy alone to a dose of 70 Gy in 33 fractions will be eligible. All patients will undergo pre-treatment MRI and at least weekly intra-treatment MRI. Patients undergoing MRgRT will have weekly adaptation of high dose planning target volume based on gross tumor volume response. The stage 1 of this study will enroll 15 patients to MRgRT dose adaptation. If LRC at 6 months with MRgRT dose adaptation is found sufficiently safe as per the Bayesian model, stage 2 of the protocol will expand enrollment to an additional 60 patients, randomized to either MRgRT or standard IMRT. DISCUSSION: Multiple methods for safe treatment de-escalation in patients with HPV-positive OPC are currently being studied. By leveraging the ability of advanced MRI techniques to visualize tumor and soft tissues through the course of treatment, this protocol proposes a workflow for safe personalized radiation dose-reduction in good responders with radiosensitive tumors, while ensuring tumoricidal dose to more radioresistant tumors. MRgRT dose adaptation could translate in reduced long term radiation toxicities and improved survivorship while maintaining excellent LRC outcomes in favorable OPC. TRIAL REGISTRATION: ClinicalTrials.gov ID: NCT03224000; Registration date: 07/21/2017.

A snapshot of medical physics practice patterns.

A large number of surveys have been sent to the medical physics community addressing many clinical topics for which the medical physicist is, or may be, responsible. Each survey provides an insight into clinical practice relevant to the medical physics community. The goal of this study was to create a summary of these surveys giving a snapshot of clinical practice patterns. Surveys used in this study were created using SurveyMonkey and distributed between February 6, 2013 and January 2, 2018 via the MEDPHYS and MEDDOS listserv groups. The format of the surveys included questions that were multiple choice and free response. Surveys were included in this analysis if they met the following criteria: more than 20 responses, relevant to radiation therapy physics practice, not single-vendor specific, and formatted as multiple-choice questions (i.e., not exclusively free-text responses). Although the results of free response questions were not explicitly reported, they were carefully reviewed, and the responses were considered in the discussion of each topic. Two-hundred and fifty-two surveys were available, of which 139 passed the inclusion criteria. The mean number of questions per survey was 4. The mean number of respondents per survey was 63. Summaries were made for the following topics: simulation, treatment planning, electron treatments, linac commissioning and quality assurance, setup and treatment verification, IMRT and VMAT treatments, SRS/SBRT, breast treatments, prostate treatments, brachytherapy, TBI, facial lesion treatments, clinical workflow, and after-hours/emergent treatments. We have provided a coherent overview of medical physics practice according to surveys conducted over the last 5 yr, which will be instructive for medical physicists.

Retrospective Validation and Clinical Implementation of Automated Contouring of Organs at Risk in the Head and Neck: A Step Toward Automated Radiation Treatment Planning for Low- and Middle-Income Countries.

Purpose We assessed automated contouring of normal structures for patients with head-and-neck cancer (HNC) using a multiatlas deformable-image-registration algorithm to better provide a fully automated radiation treatment planning solution for low- and middle-income countries, provide quantitative analysis, and determine acceptability worldwide. Methods Autocontours of eight normal structures (brain, brainstem, cochleae, eyes, lungs, mandible, parotid glands, and spinal cord) from 128 patients with HNC were retrospectively scored by a dedicated HNC radiation oncologist. Contours from a 10-patient subset were evaluated by five additional radiation oncologists from international partner institutions, and interphysician variability was assessed. Quantitative agreement of autocontours with independently physician-drawn structures was assessed using the Dice similarity coefficient and mean surface and Hausdorff distances. Automated contouring was then implemented clinically and has been used for 166 patients, and contours were quantitatively compared with the physician-edited autocontours using the same metrics. Results Retrospectively, 87% of normal structure contours were rated as acceptable for use in dose-volume-histogram-based planning without edit. Upon clinical implementation, 50% of contours were not edited for use in treatment planning. The mean (± standard deviation) Dice similarity coefficient of autocontours compared with physician-edited autocontours for parotid glands (0.92 ± 0.10), brainstem (0.95 ± 0.09), and spinal cord (0.92 ± 0.12) indicate that only minor edits were performed. The average mean surface and Hausdorff distances for all structures were less than 0.15 mm and 1.8 mm, respectively. Conclusion Automated contouring of normal structures generates reliable contours that require only minimal editing, as judged by retrospective ratings from multiple international centers and clinical integration. Autocontours are acceptable for treatment planning with no or, at most, minor edits, suggesting that automated contouring is feasible for clinical use and in the ongoing development of automated radiation treatment planning algorithms.