Evaluating outcomes and toxicities for a newly implemented MRI-based brachytherapy program for cervical cancer.

OBJECTIVE: We report an updated analysis of the outcomes and toxicities of MRI-based brachytherapy for locally advanced cervical cancer from a U.S. academic center. METHODS: A retrospective review was performed on patients treated with MRI-based brachytherapy for cervical cancer. EBRT was standardly 45 Gy in 25 fractions with weekly cisplatin. MRI was performed with the brachytherapy applicator in situ. Dose specification was most commonly 7 Gy for 4 fractions with optimization aim of D90 HR-CTV EQD2 of 85-95 Gyα/ß=10 Gy in 2 implants each delivering 2 fractions. RESULTS: Ninety-eight patients were included with median follow up of 24.5 months (IQR 11.9-39.8). Stage IIIA-IVB accounted for 31.6% of cases. Dosimetry results include median GTV D98 of 101.0 Gy (IQR 93.3-118.8) and HR-CTV D90 of 89 Gy (IQR 86.1-90.6). Median D2cc bladder, rectum, sigmoid, and bowel doses were 82.1 Gy (IQR 75.9-88.0), 65.9 Gy (IQR 59.6-71.2), 65.1 Gy (IQR 57.7-69.6), and 55 Gy (IQR 48.9-60.9). Chronic grade 3+ toxicities were seen in the bladder (8.2%), rectosigmoid (4.1%), and vagina (1.0%). Three-year LC, PFS, and OS were estimated to be 84%, 61.7%, and 76.1%, respectively. CONCLUSION: MRI-based brachytherapy demonstrates excellent local control and acceptable rates of high-grade morbidity. These results are possible in our population with relatively large volume primary tumors and extensive local disease.

Geometric and dosimetric evaluation for breast and regional nodal auto-segmentation structures.

The accuracy of artificial intelligence (AI) generated contours for intact-breast and post-mastectomy radiotherapy plans was evaluated. Geometric and dosimetric comparisons were performed between auto-contours (ACs) and manual-contours (MCs) produced by physicians for target structures. Breast and regional nodal structures were manually delineated on 66 breast cancer patients. ACs were retrospectively generated. The characteristics of the breast/post-mastectomy chestwall (CW) and regional nodal structures (axillary [AxN], supraclavicular [SC], internal mammary [IM]) were geometrically evaluated by Dice similarity coefficient (DSC), mean surface distance, and Hausdorff Distance. The structures were also evaluated dosimetrically by superimposing the MC clinically delivered plans onto the ACs to assess the impact of utilizing ACs with target dose (Vx%) evaluation. Positive geometric correlations between volume and DSC for intact-breast, AxN, and CW were observed. Little or anti correlations between volume and DSC for IM and SC were shown. For intact-breast plans, insignificant dosimetric differences between ACs and MCs were observed for AxNV95% (p = 0.17) and SCV95% (p = 0.16), while IMNV90% ACs and MCs were significantly different. The average V95% for intact-breast MCs (98.4%) and ACs (97.1%) were comparable but statistically different (p = 0.02). For post-mastectomy plans, AxNV95% (p = 0.35) and SCV95% (p = 0.08) were consistent between ACs and MCs, while IMNV90% was significantly different. Additionally, 94.1% of AC-breasts met ΔV95% variation <5% when DSC > 0.7. However, only 62.5% AC-CWs achieved the same metrics, despite AC-CWV95% (p = 0.43) being statistically insignificant. The AC intact-breast structure was dosimetrically similar to MCs. The AC AxN and SC may require manual adjustments. Careful review should be performed for AC post-mastectomy CW and IMN before treatment planning. The findings of this study may guide the clinical decision-making process for the utilization of AI-driven ACs for intact-breast and post-mastectomy plans. Before clinical implementation of this auto-segmentation software, an in-depth assessment of agreement with each local facilities MCs is needed.

Effect of scattered megavoltage x-rays on markerless tumor tracking using dual energy kilovoltage imaging.

PURPOSE: To determine the effect of megavoltage (MV) scatter on the accuracy of markerless tumor tracking (MTT) for lung tumors using dual energy (DE) imaging and to consider a post-processing technique to mitigate the effects of MV scatter on DE-MTT. METHODS: A Varian TrueBeam linac was used to acquire a series of interleaved 60/120 kVp images of a motion phantom with simulated tumors (10 and 15 mm diameter). Two sets of consecutive high/low energy projections were acquired, with and without MV beam delivery. The MV field sizes (FS) ranged from 2 × 2 cm2 -6 × 6 cm2 in steps of 1 × 1 cm2 . Weighted logarithmic subtraction was performed on sequential images to produce soft-tissue images for kV only (DEkV ) and kV with MV beam on (DEkV+MV ). Wavelet and fast Fourier transformation filtering (wavelet-FFT) was used to remove stripe noise introduced by MV scatter in the DE images ( DE kV + MV Corr ${\rm{DE}}_{{\rm{kV}} + {\rm{MV}}}^{{\rm{Corr}}}$ ). A template-based matching algorithm was then used to track the target on DEkV, DEkV+MV , and DE kV + MV Corr ${\rm{DE}}_{{\rm{kV}} + {\rm{MV}}}^{{\rm{Corr}}}$ images. Tracking accuracy was evaluated using the tracking success rate (TSR) and mean absolute error (MAE). RESULTS: For the 10 and 15 mm targets, the TSR for DEkV images was 98.7% and 100%, and MAE was 0.53 and 0.42 mm, respectively. For the 10 mm target, the TSR, including the effects of MV scatter, ranged from 86.5% (2 × 2 cm2 ) to 69.4% (6 × 6 cm2 ), while the MAE ranged from 2.05 mm to 4.04 mm. The application of wavelet-FFT algorithm to remove stripe noise ( DE kV + MV Corr ${\rm{DE}}_{{\rm{kV}} + {\rm{MV}}}^{{\rm{Corr}}}$ ) resulted in TSR values of 96.9% (2 × 2 cm2 ) to 93.4% (6 × 6 cm2 ) and subsequent MAE values were 0.89 mm to 1.37 mm. Similar trends were observed for the 15 mm target. CONCLUSION: MV scatter significantly impacts the tracking accuracy of lung tumors using DE images. Wavelet-FFT filtering can improve the accuracy of DE-MTT during treatment.

Effect of different noise reduction techniques and template matching parameters on markerless tumor tracking using dual-energy imaging.

PURPOSE: To evaluate the impact of various noise reduction algorithms and template matching parameters on the accuracy of markerless tumor tracking (MTT) using dual-energy (DE) imaging. METHODS: A Varian TrueBeam linear accelerator was used to acquire a series of alternating 60 and 120 kVp images (over a 180° arc) using fast kV switching, on five early-stage lung cancer patients. Subsequently, DE logarithmic weighted subtraction was performed offline on sequential images to remove bone. Various noise reduction techniques-simple smoothing, anticorrelated noise reduction (ACNR), noise clipping (NC), and NC-ACNR-were applied to the resultant DE images. Separately, tumor templates were generated from the individual planning CT scans, and band-pass parameter settings for template matching were varied. Template tracking was performed for each combination of noise reduction techniques and templates (based on band-pass filter settings). The tracking success rate (TSR), root mean square error (RMSE), and missing frames (percent unable to track) were evaluated against the estimated ground truth, which was obtained using Bayesian inference. RESULTS: DE-ACNR, combined with template band-pass filter settings of σlow  = 0.4 mm and σhigh  = 1.6 mm resulted in the highest TSR (87.5%), RMSE (1.40 mm), and a reasonable amount of missing frames (3.1%). In comparison to unprocessed DE images, with optimized band-pass filter settings of σlow  = 0.6 mm and σhigh  = 1.2 mm, the TSR, RMSE, and missing frames were 85.3%, 1.62 mm, and 2.7%, respectively. Optimized band-pass filter settings resulted in improved TSR values and a lower missing frame rate for both unprocessed DE and DE-ACNR as compared to the use previously published band-pass parameters based on single energy kV images. CONCLUSION: Noise reduction strategies combined with the optimal selection of band-pass filter parameters can improve the accuracy and TSR of MTT for lung tumors when using DE imaging.

Efficient quality assurance method with automated data acquisition of a single phantom setup to determine radiation and imaging isocenter congruence.

We developed a quality assurance (QA) method to determine the isocenter congruence of Optical Surface Monitoring System (OSMS, Varian, CA, USA), kilovoltage (kV), and megavoltage (MV) imaging, and the radiation isocenter using a single setup of the OSMS phantom for frameless Stereotactic Radiosurgery (SRS) treatment. After aligning the phantom to the OSMS isocenter, a cone-beam computed tomography (CBCT) of the phantom was acquired and registered to a computed tomography (CT) scan of the phantom to determine the CBCT isocenter. Without moving the phantom, MV and kV images were simultaneously acquired at four gantry angles to localize MV and kV isocenters. Then, Winston-Lutz (W-L) test images of the central BB in the phantom were acquired to analyze the radiation isocenter. The gantry and couch were automatically controlled using the TrueBeam Developer Mode during MV, kV, and W-L image acquisition. All the images were acquired weekly for 17 weeks to track the congruence of all the imaging modalities' isocenter in six-dimensional (6D) translations and rotations, and the radiation isocenter in three-dimensional (3D) translations. The shifts of isocenters of all imaging modalities and the radiation isocenter from the OSMS isocenter were within 0.2 mm and 0.2° on average over 17 weeks. The maximum discrepancy between OSMS and other imaging modalities or radiation isocenters was 0.8 mm and 0.3°. However, systematic shifts of radiation isocenter anteriorly and laterally relative to the OSMS isocenter were observed. The measured discrepancies were consistent from week-to-week except for two weeks when the isocenter discrepancies of 0.8 mm were noted due to drifts of the OSMS isocenter. Once recalibration was performed on OSMS, the discrepancy was reduced to 0.3 mm and 0.2°.By performing the proposed QA on a weekly basis, the isocenter congruencies of multiple imaging systems and radiation isocenter were validated for a linear accelerator.

A survey on table tolerances and couch overrides in radiotherapy.

The purpose of this study was to survey current departmental policies on treatment couch overrides and the values of table tolerances used clinically. A 25-question electronic survey on couch overrides and tolerances was sent to full members of the American Association of Physicists in Medicine (AAPM). The first part of the survey asked participants if table overrides were allowed at their institution, who was allowed to perform these overrides, and if imaging was required with overrides. The second part of the survey asked individuals to provide table tolerance data for the following treatment sites: brain/head and neck (H&N), lung, breast, abdo-men/pelvis and prostate. Each site was further divided into IMRT/VMAT and 3D conformal techniques. Spaces for free-text were provided, allowing respondents to enter any table tolerance data they were unable to specify under the treatment sites listed. A total of 361 individuals responded, of which approximately half partici-pated in the couch tolerances portion of the survey. Overall, 86% of respondents' institutions allow couch tolerance overrides at treatment. Therapists were the most common staff members permitted to perform overrides, followed by physicists, dosimetrists, and physicians, respectively. Of the institutions allowing overrides, 34% reported overriding daily. More than half of the centers document the over-ride and/or require a setup image to radiographically verify the treatment site. With respect to table tolerances, SRS/SBRT table tolerances were the tightest, while clinical setup table tolerances were the largest. There were minimal statistically significant differences between IMRT/VMAT and 3D conformal table tolerances. Our results demonstrated that table overrides are relatively common in radiotherapy despite being a potential safety concern. Institutions should review their override policy and table tolerance values in light of the practices of other institutions. Careful attention to these matters is crucial in ensuring the safe and accurate delivery of radiotherapy.

Calculation of alpha particle single-event spectra using a neural network.

Introduction: A neural network was trained to accurately predict the entire single-event specific energy spectra for use in alpha-particle microdosimetry calculations. Methods: The network consisted of 4 inputs and 21 outputs and was trained on data calculated using Monte Carlo simulation where input parameters originated both from previously published data as well as randomly generated parameters that fell within a target range. The 4 inputs consisted of the source-target configuration (consisting of both cells in suspension and in tissue-like geometries), alpha particle energy (3.97-8.78 MeV), nuclei radius (2-10 µm), and cell radius (2.5-20 µm). The 21 output values consisted of the maximum specific energy (zmax), and 20 values of the single-event spectra, which were expressed as fractional values of zmax. The neural network consisted of two hidden layers with 10 and 26 nodes, respectively, with the loss function characterized as the mean square error (MSE) between the actual and predicted values for zmax and the spectral outputs. Results: For the final network, the root mean square error (RMSE) values of zmax for training, validation and testing were 1.57 x10-2, 1.51 x 10-2 and 1.35 x 10-2, respectively. Similarly, the RMSE values of the spectral outputs were 0.201, 0.175 and 0.199, respectively. The correlation coefficient, R2, was > 0.98 between actual and predicted values from the neural network. Discussion: In summary, the network was able to accurately reproduce alpha-particle single-event spectra for a wide range of source-target geometries.

Dosimetric and workflow impact of synthetic-MRI use in prostate high-dose-rate brachytherapy.

PURPOSE: Target and organ delineation during prostate high-dose-rate (HDR) brachytherapy treatment planning can be improved by acquiring both a postimplant CT and MRI. However, this leads to a longer treatment delivery workflow and may introduce uncertainties due to anatomical motion between scans. We investigated the dosimetric and workflow impact of MRI synthesized from CT for prostate HDR brachytherapy. METHODS AND MATERIALS: Seventy-eight CT and T2-weighted MRI datasets from patients treated with prostate HDR brachytherapy at our institution were retrospectively collected to train and validate our deep-learning-based image-synthesis method. Synthetic MRI was assessed against real MRI using the dice similarity coefficient (DSC) between prostate contours drawn using both image sets. The DSC between the same observer's synthetic and real MRI prostate contours was compared with the DSC between two different observers' real MRI prostate contours. New treatment plans were generated targeting the synthetic MRI-defined prostate and compared with the clinically delivered plans using target coverage and dose to critical organs. RESULTS: Variability between the same observer's prostate contours from synthetic and real MRI was not significantly different from the variability between different observer's prostate contours on real MRI. Synthetic MRI-planned target coverage was not significantly different from that of the clinically delivered plans. There were no increases above organ institutional dose constraints in the synthetic MRI plans. CONCLUSIONS: We developed and validated a method for synthesizing MRI from CT for prostate HDR brachytherapy treatment planning. Synthetic MRI use may lead to a workflow advantage and removal of CT-to-MRI registration uncertainty without loss of information needed for target delineation and treatment planning.

Prostate segmentation accuracy using synthetic MRI for high-dose-rate prostate brachytherapy treatment planning.

Objective. Both computed tomography (CT) and magnetic resonance imaging (MRI) images are acquired for high-dose-rate (HDR) prostate brachytherapy patients at our institution. CT is used to identify catheters and MRI is used to segment the prostate. To address scenarios of limited MRI access, we developed a novel generative adversarial network (GAN) to generate synthetic MRI (sMRI) from CT with sufficient soft-tissue contrast to provide accurate prostate segmentation without MRI (rMRI).Approach. Our hybrid GAN, PxCGAN, was trained utilizing 58 paired CT-MRI datasets from our HDR prostate patients. Using 20 independent CT-MRI datasets, the image quality of sMRI was tested using mean absolute error (MAE), mean squared error (MSE), peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM). These metrics were compared with the metrics of sMRI generated using Pix2Pix and CycleGAN. The accuracy of prostate segmentation on sMRI was evaluated using the Dice similarity coefficient (DSC), Hausdorff distance (HD) and mean surface distance (MSD) on the prostate delineated by three radiation oncologists (ROs) on sMRI versus rMRI. To estimate inter-observer variability (IOV), these metrics between prostate contours delineated by each RO on rMRI and the prostate delineated by treating RO on rMRI (gold standard) were calculated.Main results. Qualitatively, sMRI images show enhanced soft-tissue contrast at the prostate boundary compared with CT scans. For MAE and MSE, PxCGAN and CycleGAN have similar results, while the MAE of PxCGAN is smaller than that of Pix2Pix. PSNR and SSIM of PxCGAN are significantly higher than Pix2Pix and CycleGAN (p < 0.01). The DSC for sMRI versus rMRI is within the range of the IOV, while the HD for sMRI versus rMRI is smaller than the HD for the IOV for all ROs (p ≤ 0.03).Significance. PxCGAN generates sMRI images from treatment-planning CT scans that depict enhanced soft-tissue contrast at the prostate boundary. The accuracy of prostate segmentation on sMRI compared to rMRI is within the segmentation variation on rMRI between different ROs.

Alpha particle microdosimetry calculations using a shallow neural network.

A shallow neural network was trained to accurately calculate the microdosimetric parameters, 〈z1〉 and 〈z12〉 (the first and second moments of the single-event specific energy spectra, respectively) for use in alpha-particle microdosimetry calculations. The regression network of four inputs and two outputs was created in MATLAB and trained on a data set consisting of both previously published microdosimetric data and recent Monte Carlo simulations. The input data consisted of the alpha-particle energies (3.97-8.78 MeV), cell nuclei radii (2-10µm), cell radii (2.5-20µm), and eight different source-target configurations. These configurations included both single cells in suspension and cells in geometric clusters. The mean square error (MSE) was used to measure the performance of the network. The sizes of the hidden layers were chosen to minimize MSE without overfitting. The final neural network consisted of two hidden layers with 13 and 20 nodes, respectively, each with tangential sigmoid transfer functions, and was trained on 1932 data points. The overall training/validation resulted in a MSE = 3.71 × 10-7. A separate testing data set included input values that were not seen by the trained network. The final test on 892 separate data points resulted in a MSE = 2.80 × 10-7. The 95th percentile testing data errors were within ±1.4% for 〈z1〉 outputs and ±2.8% for 〈z12〉 outputs, respectively. Cell survival was also predicted using actual versus neural network generated microdosimetric moments and showed overall agreement within ±3.5%. In summary, this trained neural network can accurately produce microdosimetric parameters used for the study of alpha-particle emitters. The network can be exported and shared for tests on independent data sets and new calculations.

The markerless lung target tracking AAPM Grand Challenge (MATCH) results.

PURPOSE: Lung stereotactic ablative body radiotherapy (SABR) is a radiation therapy success story with level 1 evidence demonstrating its efficacy. To provide real-time respiratory motion management for lung SABR, several commercial and preclinical markerless lung target tracking (MLTT) approaches have been developed. However, these approaches have yet to be benchmarked using a common measurement methodology. This knowledge gap motivated the MArkerless lung target Tracking CHallenge (MATCH). The aim was to localize lung targets accurately and precisely in a retrospective in silico study and a prospective experimental study. METHODS: MATCH was an American Association of Physicists in Medicine sponsored Grand Challenge. Common materials for the in silico and experimental studies were the experiment setup including an anthropomorphic thorax phantom with two targets within the lungs, and a lung SABR planning protocol. The phantom was moved rigidly with patient-measured lung target motion traces, which also acted as ground truth motion. In the retrospective in silico study a volumetric modulated arc therapy treatment was simulated and a dataset consisting of treatment planning data and intra-treatment kilovoltage (kV) and megavoltage (MV) images for four blinded lung motion traces was provided to the participants. The participants used their MLTT approach to localize the moving target based on the dataset. In the experimental study, the participants received the phantom experiment setup and five patient-measured lung motion traces. The participants used their MLTT approach to localize the moving target during an experimental SABR phantom treatment. The challenge was open to any participant, and participants could complete either one or both parts of the challenge. For both the in silico and experimental studies the MLTT results were analyzed and ranked using the prospectively defined metric of the percentage of the tracked target position being within 2 mm of the ground truth. RESULTS: A total of 30 institutions registered and 15 result submissions were received, four for the in silico study and 11 for the experimental study. The participating MLTT approaches were: Accuray CyberKnife (2), Accuray Radixact (2), BrainLab Vero, C-RAD, and preclinical MLTT (5) on a conventional linear accelerator (Varian TrueBeam). For the in silico study the percentage of the 3D tracking error within 2 mm ranged from 50% to 92%. For the experimental study, the percentage of the 3D tracking error within 2 mm ranged from 39% to 96%. CONCLUSIONS: A common methodology for measuring the accuracy of MLTT approaches has been developed and used to benchmark preclinical and commercial approaches retrospectively and prospectively. Several MLTT approaches were able to track the target with sub-millimeter accuracy and precision. The study outcome paves the way for broader clinical implementation of MLTT. MATCH is live, with datasets and analysis software being available online at https://www.aapm.org/GrandChallenge/MATCH/ to support future research.

Part II. Initial molecular and cellular characterization of high nitric oxide-adapted human tongue squamous cell carcinoma cell lines.

It is not understood why some head and neck squamous cell carcinomas, despite having identical morphology, demonstrate different tumor aggressiveness, including radioresistance. High levels of the free radical nitric oxide (NO) and increased expression of the NO-producing enzyme nitric oxide synthase (NOS) have been implicated in tumor progression. We previously adapted three human tongue cancer cell lines to high NO (HNO) levels by gradually exposing them to increasing concentrations of an NO donor; the HNO cells grew faster than their corresponding untreated ("parent") cells, despite being morphologically identical. Herein we initially characterize the HNO cells and compare the biological properties of the HNO and parent cells. HNO/parent cell line pairs were analyzed for cell cycle distribution, DNA damage, X-ray and ultraviolet radiation response, and expression of key cellular enzymes, including NOS, p53, glutathione S-transferase-pi (GST-pi), apurinic/apyrimidinic endonuclease-1 (APE1), and checkpoint kinases (Chk1, Chk2). While some of these properties were cell line-specific, the HNO cells typically exhibited properties associated with a more aggressive behavior profile than the parent cells (greater S-phase percentage, radioresistance, and elevated expression of GST-pi/APE1/Chk1/Chk2). To correlate these findings with conditions in primary tumors, we examined the NOS, GST-pi, and APE1 expression in human tongue squamous cell carcinomas. A majority of the clinical samples exhibited elevated expression levels of these enzymes. Together, the results herein suggest cancer cells exposed to HNO levels can develop resistance to free radicals by upregulating protective mechanisms, such as GST-pi and APE1. These upregulated defense mechanisms may contribute to their aggressive expression profile.

Dosimetric assessment of brass mesh bolus and transparent polymer-gel type bolus for commonly used breast treatment delivery techniques.

We investigated skin dose enhancements of brass mesh bolus (BMB) and a recently developed transparent polymer-gel bolus (PGB) for clinically relevant breast treatment delivery techniques. The dose enhancement of the breast surface with BMB and PGB were compared to that of tissue-equivalent bolus. Three breast treatment plans were generated on CT scans of an anthropomorphic chest phantom: tangential step-and-shoot 3D conformal (3DCRT) planned using Field-in-Field (FiF), tangential sliding-window 3DCRT using Electronic Compensator (EC), and volumetric modulated arc therapy (VMAT). All plans were created using 6 MV photons and a prescription dose (Rx) of 180 cGy per fraction. Skin doses of all 3 plans were measured with radiochromic films, separately delivered in triplicate. Each plan was delivered to the phantom without bolus, and then with BMB (1 or 2 layers; 3 or 10 mm tissue-equivalent), PGB, and Superflab (3, 5, and 10 mm tissue-equivalent). Doses were determined by reading the radiochromic films with a flatbed scanner, and analyzing the images using a calibration curve for each specific batch. For all bolus types and plans, surface doses averaged over the 3 measurements were between 88.4% and 107.4% of Rx. Without bolus, average measured skin doses were between 51.2% and 64.2% of Rx. Skin doses with BMB and PGB were comparable to that with tissue-equivalent bolus. Over all 3 treatment delivery techniques, using BMB resulted in average skin doses of 92.8% and 102.1% for 1- and 2 layers, respectively, and using PGB results in average skin doses of 94.8%, 98.2%, and 99.7% for 3, 5, and 10-mm tissue-equivalent, respectively. The average measured skin doses with BMB and PGB agreed within ± 3% compared to the tissue-equivalent thickness bolus. We concluded that BMB and PGB are clinically equivalent in skin dose enhancement for breast treatment as the 3, 5, and 10 mm tissue-equivalent bolus.

Failure mode and effects analysis of linac-based liver stereotactic body radiotherapy.

PURPOSE: Although stereotactic body radiation therapy (SBRT) is an attractive noninvasive approach for liver irradiation, it presents specific challenges associated with respiration-induced liver motion, daily tumor localization due to liver deformation, and poor visualization of target with respect to adjacent normal liver in computed tomography (CT). We aim to identify potential hazards and develop a set of mitigation strategies to improve the safety of our liver SBRT program, using failure mode and effect analysis (FMEA). MATERIALS AND METHODS: A multidisciplinary group consisting of two physicians, three physicists, two dosimetrists, and two therapists was formed. A process map covering ten major stages of the liver SBRT program from the initial diagnosis to posttreatment follow-up was generated. A total of 102 failure modes (FM), together with their causes and effects, were identified. The occurrence (O), severity (S), and lack of detectability (D) were independently scored using a scale from 1 (lowest risk) to 10 (largest risk). The ranking was done using the risk probability number (RPN) defined as the product of average O, S, and D numbers for each mode. Two fault tree analyses were performed. The failure modes with the highest RPN values as well as highest severity score were considered for investigation and a set of mitigation strategies was developed to address these. RESULTS: The median RPN (RPNmed ) values for all modes ranged from of 9 to 105 and the highest median S score (Smed ) was 8. Fourteen FMs were identified to be significant by both RPNmed and Smed (top ten RPNmed ranked and highest Smed FMs) and 12 of them were considered for risk mitigation efforts. The remaining two were omitted due to either sufficient checks already in place, or lack of practical mitigation strategies. Implemented measures consisted of five physics tasks, two physician tasks, and three workflow changes. CONCLUSIONS: The application of FMEA to our liver SBRT program led to the identification of potential FMs and allowed improvement measures to enhance the safety of our clinical practice.

Microdosimetry-based determination of tumour control probability curves for treatments with 225Ac-PSMA of metastatic castration resistant prostate cancer.

We performed Monte Carlo simulations in order to determine, by means of microdosimetry calculations, tumour control probability (TCP) curves for treatments with 225Ac-PSMA of metastatic castration resistant prostate cancer (mCRPC). Realistic values of cell radiosensitivity, nucleus size and lesion size were used for calculations. As the cell radiosensitivity decreased, the nucleus size decreased and the lesion size increased, the absorbed dose to reach a given TCP increased. The widest variations occurred with regard to the cell radiosensitivity. For the Monte Carlo simulations, in order to address a non-uniform PSMA expression, different 225Ac-PSMA distributions were considered. The effect of these different PSMA distributions resulted in small variations in the TCP curves (maximum variation of 5%). Absorbed doses to reach a TCP of 0.9 for a uniform 225Ac-PSMA distribution, considering a relative biological effectiveness (RBE) of 5, ranged between 35.0 Gy and 116.5 Gy. The lesion absorbed doses per administered activity reported in a study on treatments with 225Ac-PSMA of mCRPC ranged between 1.3 Gy MBq-1 and 9.8 Gy MBq-1 for a RBE = 5. For a 70 kg-patient to whom 100 kBq kg-1 of 225Ac-PSMA are administered, the range of lesion absorbed doses would be between 9.1 Gy and 68.6 Gy. Thus, for a single cycle of 100 kBq kg-1, a number of lesions would not receive an absorbed dose high enough to reach a TCP of 0.9.

Adaptive weighted log subtraction based on neural networks for markerless tumor tracking using dual-energy fluoroscopy.

PURPOSE: To present a novel method, based on convolutional neural networks (CNN), to automate weighted log subtraction (WLS) for dual-energy (DE) fluoroscopy to be used in conjunction with markerless tumor tracking (MTT). METHODS: A CNN was developed to automate WLS (aWLS) of DE fluoroscopy to enhance soft tissue visibility. Briefly, this algorithm consists of two phases: training a CNN architecture to predict pixel-wise weighting factors followed by application of WLS subtraction to reduce anatomical noise. To train the CNN, a custom phantom was built consisting of aluminum (Al) and acrylic (PMMA) step wedges. Per-pixel ground truth (GT) weighting factors were calculated by minimizing the contrast of Al in the step wedge phantom to train the CNN. The pretrained model was then utilized to predict pixel-wise weighting factors for use in WLS. For comparison, the weighting factor was manually determined in each projection (mWLS). A thorax phantom with five simulated spherical targets (5-25 mm) embedded in a lung cavity, was utilized to assess aWLS performance. The phantom was imaged with fast-kV dual-energy (120 and 60 kVp) fluoroscopy using the on-board imager of a commercial linear accelerator. DE images were processed offline to produce soft tissue images using both WLS methods. MTT was compared using soft tissue images produced with both mWLS and aWLS techniques. RESULTS: Qualitative evaluation demonstrated that both methods achieved soft tissue images with similar quality. The use of aWLS increased the number of tracked frames by 1-5% compared to mWLS, with the largest increase observed for the smallest simulated tumors. The tracking errors for both methods produced agreement to within 0.1 mm. CONCLUSIONS: A novel method to perform automated WLS for DE fluoroscopy was developed. Having similar soft tissue quality as well as bone suppression capability as mWLS, this method allows for real-time processing of DE images for MTT.

Fast-switching dual energy cone beam computed tomography using the on-board imager of a commercial linear accelerator.

To evaluate fast-kV switching (FS) dual energy (DE) cone beam computed tomography (CBCT) using the on-board imager (OBI) of a commercial linear accelerator to produce virtual monoenergetic (VM) and relative electron density (RED) images. Using an polynomial attenuation mapping model, CBCT phantom projections obtained at 80 and 140 kVp with FS imaging, were decomposed into equivalent thicknesses of aluminum (Al) and polymethyl methacrylate (PMMA). All projections were obtained with the titanium foil and bowtie filter in place. Basis material projections were then recombined to create VM images by using the linear attenuation coefficients at the specified energy for each material. Similarly, RED images were produced by replacing the linear attenuation values of Al and PMMA by their respective RED values in the projection space. VM and RED images were reconstructed using Feldkamp-Davis-Kress (FDK) and an iterative algorithm (iCBCT, Varian Medical Systems). Hounsfield units (HU), contrast-to-noise ratio (CNR) and RED values were compared against known values. The results after VM-CBCT production showed good material decomposition and consistent HUVM values, with measured root mean square errors (RMSE) from theoretical values, after FDK reconstruction, of 20.5, 5.7, 12.8 and 21.7 HU for 50, 80, 100 and 150 keV, respectively. The largest CNR improvements, when compared to polychromatic images, were observed for the 50 keV VM images. Image noise was reduced up to 28% in the VM-CBCT images after iterative image reconstruction. RED values measured for our method resulted in a mean percentage error of 0.0% ± 1.8%. This study describes a method to generate VM-CBCT and RED images using FS-DE scans obtained using the OBI of a linac, including the effects of the bowtie filter. The creation of VM and RED images increases the dynamic range of CBCT images, and provides additional data that may be used for adaptive radiotherapy, and on table verification for radiotherapy treatments.

Characterization of Markerless Tumor Tracking Using the On-Board Imager of a Commercial Linear Accelerator Equipped With Fast-kV Switching Dual-Energy Imaging.

PURPOSE: To describe and characterize fast-kV switching, dual-energy (DE) imaging implemented within the on-board imager of a commercial linear accelerator for markerless tumor tracking (MTT). METHODS AND MATERIALS: Fast-kV switching, DE imaging provides for rapid switching between programmed tube voltages (ie, 60 and 120 kVp) from one image frame to the next. To characterize this system, the weighting factor used for logarithmic subtraction and signal difference-to-noise ratio were analyzed as a function of time and frame rate. MTT was evaluated using a thorax motion phantom and fast kV, DE imaging was compared versus single energy (SE) imaging over 360 degrees of rotation. A template-based matching algorithm was used to track target motion on both DE and SE sequences. Receiver operating characteristics were used to compare tracking results for both modalities. RESULTS: The weighting factor was inversely related to frame rate and stable over time. After applying the frame rate-dependent weighting factor, the signal difference-to-noise ratio was consistent across all frame rates considered for simulated tumors ranging from 5 to 25 mm in diameter. An analysis of receiver operating characteristics curves showed improved tracking with DE versus SE imaging. The area under the curve for the 10-mm target ranged from 0.821 to 0.858 for SE imaging versus 0.968 to 0.974 for DE imaging. Moreover, the residual tracking errors for the same target size ranged from 2.02 to 2.18 mm versus 0.79 to 1.07 mm for SE and DE imaging, respectively. CONCLUSIONS: Fast-kV switching, DE imaging was implemented on the on-board imager of a commercial linear accelerator. DE imaging resulted in improved MTT accuracy over SE imaging. Such an approach may have application for MTT of patients with lung cancer receiving stereotactic body radiation therapy, particularly for small tumors where MTT with SE imaging may fail.

ACR-ASTRO Practice Parameter for Image-guided Radiation Therapy (IGRT).

AIM/OBJECTIVES/BACKGROUND: The American College of Radiology (ACR) and the American Society for Radiation Oncology (ASTRO) have jointly developed the following practice parameter for image-guided radiation therapy (IGRT). IGRT is radiation therapy that employs imaging to maximize accuracy and precision throughout the entire process of treatment delivery with the goal of optimizing accuracy and reliability of radiation therapy to the target, while minimizing dose to normal tissues. METHODS: The ACR-ASTRO Practice Parameter for IGRT was revised according to the process described on the ACR website ("The Process for Developing ACR Practice Parameters and Technical Standards," www.acr.org/ClinicalResources/Practice-Parametersand-Technical-Standards) by the Committee on Practice Parameters of the ACR Commission on Radiation Oncology in collaboration with the ASTRO. Both societies then reviewed and approved the document. RESULTS: This practice parameter is developed to serve as a tool in the appropriate application of IGRT in the care of patients with conditions where radiation therapy is indicated. It addresses clinical implementation of IGRT including personnel qualifications, quality assurance standards, indications, and suggested documentation. CONCLUSIONS: This practice parameter is a tool to guide clinical use of IGRT and does not make recommendations on site-specific IGRT directives. It focuses on the best practices and principles to consider when using IGRT effectively, especially with the significant increase in imaging data that is now available with IGRT. The clinical benefit and medical necessity of the imaging modality and frequency of IGRT should be assessed for each patient.

Dosimetric feasibility of brain stereotactic radiosurgery with a 0.35 T MRI-guided linac and comparison vs a C-arm-mounted linac.

PURPOSE: MRI is the gold-standard imaging modality for brain tumor diagnosis and delineation. The purpose of this work was to investigate the feasibility of performing brain stereotactic radiosurgery (SRS) with a 0.35 T MRI-guided linear accelerator (MRL) equipped with a double-focused multileaf collimator (MLC). Dosimetric comparisons were made vs a conventional C-arm-mounted linac with a high-definition MLC. METHODS: The quality of MRL single-isocenter brain SRS treatment plans was evaluated as a function of target size for a series of spherical targets with diameters from 0.6 cm to 2.5 cm in an anthropomorphic head phantom and six brain metastases (max linear dimension = 0.7-1.9 cm) previously treated at our clinic on a conventional linac. Each target was prescribed 20 Gy to 99% of the target volume. Step-and-shoot IMRT plans were generated for the MRL using 11 static coplanar beams equally spaced over 360° about an isocenter placed at the center of the target. Couch and collimator angles are fixed for the MRL. Two MRL planning strategies (VR1 and VR2) were investigated. VR1 minimized the 12 Gy isodose volume while constraining the maximum point dose to be within ±1 Gy of 25 Gy which corresponded to normalization to an 80% isodose volume. VR2 minimized the 12 Gy isodose volume without the maximum dose constraint. For the conventional linac, the TB1 method followed the same strategy as VR1 while TB2 used five noncoplanar dynamic conformal arcs. Plan quality was evaluated in terms of conformity index (CI), conformity/gradient index (CGI), homogeneity index (HI), and volume of normal brain receiving ≥12 Gy (V12Gy ). Quality assurance measurements were performed with Gafchromic EBT-XD film following an absolute dose calibration protocol. RESULTS: For the phantom study, the CI of MRL plans was not significantly different compared to a conventional linac (P > 0.05). The use of dynamic conformal arcs and noncoplanar beams with a conventional linac spared significantly more normal brain (P = 0.027) and maximized the CGI, as expected. The mean CGI was 95.9 ± 4.5 for TB2 vs 86.6 ± 3.7 (VR1), 88.2 ± 4.8 (VR2), and 88.5 ± 5.9 (TB1). Each method satisfied a normal brain V12Gy  ≤ 10.0 cm3 planning goal for targets with diameter ≤2.25 cm. The mean V12Gy was 3.1 cm3 for TB2 vs 5.5 cm3 , 5.0 cm3 and 4.3 cm3 , for VR1, VR2, and TB1, respectively. For a 2.5-cm diameter target, only TB2 met the V12Gy planning objective. The MRL clinical brain plans were deemed acceptable for patient treatment. The normal brain V12Gy was ≤6.0 cm3 for all clinical targets (maximum target volume = 3.51 cm3 ). CI and CGI ranged from 1.12-1.65 and 81.2-88.3, respectively. Gamma analysis pass rates (3%/1mm criteria) exceeded 97.6% for six clinical targets planned and delivered on the MRL. The mean measured vs computed absolute dose difference was -0.1%. CONCLUSIONS: The MRL system can produce clinically acceptable brain SRS plans for spherical lesions with diameter ≤2.25 cm. Large lesions (>2.25 cm) should be treated with a linac capable of delivering noncoplanar beams.