Orthogonal kV Research Articles

Automated detection of vertebral body misalignments in orthogonal kV and MV guided radiotherapy: application to a comprehensive retrospective dataset

Objective. In image-guided radiotherapy (IGRT), off-by-one vertebral body misalignments are rare but potentially catastrophic. In this study, a novel detection method for such misalignments in IGRT was investigated using densely-connected convolutional networks (DenseNets) for applications towards real-time error prevention and retrospective error auditing. Approach. A total of 4213 images acquired from 527 radiotherapy patients aligned with planar kV or MV radiographs were used to develop and test error-detection software modules. Digitally reconstructed radiographs (DRRs) and setup images were retrieved and co-registered according to the clinically applied alignment contained in the DICOM REG files. A semi-automated algorithm was developed to simulate patient positioning errors on the anterior-posterior (AP) and lateral (LAT) images shifted by one vertebral body. A DenseNet architecture was designed to classify either AP images individually or AP and LAT image pairs. Receiver-operator characteristic curves (ROC) and areas under the curves (AUC) were computed to evaluate the classifiers on test subsets. Subsequently, the algorithm was applied to the entire dataset in order to retrospectively determine the absolute off-by-one vertebral body error rate for planar radiograph guided RT at our institution from 2011–2021. Main results. The AUCs for the kV models were 0.98 for unpaired AP and 0.99 for paired AP-LAT. The AUC for the MV AP model was 0.92. For a specificity of 95%, the paired kV model achieved a sensitivity of 99%. Application of the model to the entire dataset yielded a per-fraction off-by-one vertebral body error rate of 0.044% [0.0022%, 0.21%] for paired kV IGRT including one previously unreported error. Significance. Our error detection algorithm was successful in classifying vertebral body positioning errors with sufficient accuracy for retrospective quality control and real-time error prevention. The reported positioning error rate for planar radiograph IGRT is unique in being determined independently of an error reporting system.

Patient-Specific 3D CT Images Reconstruction from 2D KV Images Via Vision Transformer-Based Deep-Learning

In some proton therapy facilities, patient alignment relies on two 2D orthogonal kV images, taken at fixed, oblique angles, as no 3D on-the-bed-imaging is available. The visibility of the tumor in kV images is limited since the patient's 3D anatomy is projected onto a 2D plane, especially when the tumor is behind a high-density structure such as bone. This can lead to a large patient setup error. A solution to this problem is to reconstruct the 3D CT image from the kV images obtained in the treatment position. An asymmetric autoencoder-like network built with vision-transformer blocks was developed. The data was collected from a head and neck patient: 2 orthogonal kV images (1024X1024 voxels), 1 3D CT with padding (512X512X512) acquired from the in-room CT-on-rails before kVs were taken and 2 digitally-reconstructed-radiograph (DRR) images (512X512) based on the CT. We resampled kV images every 8 voxels and DRR and CT every 4 voxels, thus formed a dataset consisting of 262,144 samples, in which the images had a dimension of 128 for each direction. The value of each voxel in CT was normalized to range 0-1 with a uniform shift of 1000 and a denominator of 4000. For kV and DRR, we ranked all voxels value in an ascending order and normalized the values of the first 80% voxels to range 0-0.8 and the rest to range 0.8-1, thus yielding a quasi-Gaussian distribution, which was favorable by the deep neural networks. We further cropped kV and DRR images with a self-supervised bitmap based on the voxels' gradients. In training, both kV and DRR were utilized, and the encoder was encouraged to learn the same feature maps for kV images and its corresponding DRR images with mean-absolute-error (MAE) as the similarity loss. Then the decoder would reconstruct the 3D CT image from the feature maps of the kV images with the CT-on-rails as ground-truth (gCT) and MAE as the reconstruction loss. In testing, only independent kV images were used. The full-size synthetic CT (sCT) was achieved by concatenating the sCTs generated by the model according to their spatial information. The image quality of the sCT was evaluated using MAE and per-voxel-absolute-CT-number-difference volume histogram (CDVH). The proposed network was implemented with PyTorch deep learning library and both distributed data parallel (DDP) and automatic mixed precision (AMP) were applied to saving memory and accelerating the training speed. We used the AdamW optimizer with β1 = 0.9 and β2 = 0.999 and a cosine annealing learning rate scheduler with an initial learning of 1e-7 and 20 warm-up epochs. The model achieved a MAE of <40HU and the CDVH showed that <5% of the voxels had a per-voxel-absolute-CT-number-difference larger than 185HU. The profile of a typical gCT slice and its corresponding sCT slice exhibited a high agreement, indicating the high similarity between the gCT and sCT. A patient-specific vision-transformer-based network was developed and shown to be accurate and efficient to reconstruct 3D CT images from kV images.

Pencil Beam Scanning Proton Stereotactic Body Radiation Therapy (SBRT): A Robust Single Institution Experience

To describe the feasibility of treating a complex and diverse group of patients using pencil beam scanning (PBS) proton stereotactic body radiation therapy (SBRT: 5 or fewer fractions, with a fraction size of at least 5 Gy). Our center treats on average 105-120 PBS proton treatments daily, of which 9.5% of treatment courses are proton SBRT. Statistics of disease sites, treatment planning parameters (target volume, prescriptions, number of fields, SFO vs. MFO), and treatment efficiencies (scheduled time slots, actual treatment time) are presented for 305 consecutive SBRT patients receiving 1507 fractions in the past three years. Thermoplastic masks or Vacuum-lock bags are used to immobilize SBRT patients and index the patients' treatment position. Imaging guidance of orthogonal kV images and volumetric cone-beam CT is routinely used for patient setup. SBRT patients are grouped based on the target locations: pelvis (31%), liver (17%), thoracic (13%), spine (8%), abdominal (8%), brain (7%), non-spine bone (7%), ocular (6%), and head and neck (2%). Only 112 patients (37%) were receiving their 1st RT course, whereas 113 (37%) had one prior in-field RT course, and 80 (26%) had multiple prior in-field RT courses. The median [IQR] target volume was 65.4 [29.3, 168] cc (range: 0.3-2475 cc). 72% of cases were planned with SFO and 28% with MFO. On average, 3.76 fields (range: 2 to 12) were planned for each treatment. 44% of the treatments were planned with three or fewer fields, and 10% received more than five fields, most of which involved repainting for moving targets. Over 97% of treatments were delivered in 5 fractions, with ∼3% delivered in 3 fractions. The median [IQR] prescription per treatment was 8 [7, 10] Gy (range: 5-18 Gy per treatment). 85% (84%) of the SBRT treatments were scheduled (delivered) in a 45-minute or shorter slot, and 6% (7%) of treatments were scheduled (delivered) in over a one-hour slot, most commonly for multiple isocenter treatments. 93% of treatments were delivered within 15 minutes of the planned treatment time or shorter. Deep-inspiration breath-hold (DIBH) was applied to 45% of liver SBRT cases, with the remaining 55% planned on 4D CT with (14%) or without (86%) abdominal compression. DIBH was applied in 13% of lung SBRT cases. The application of other motion mitigation approaches, such as volumetric repainting, was determined by the target motion amplitude and whether the patient could tolerate DIBH. In the most diverse and largest proton SBRT experience delivered in the world over the past 3 years, over 300 patients were treated, demonstrating the feasibility and efficiency of delivering proton SBRT in a very busy center. The planning and treatment parameter statistics reported serve as a helpful reference for the proton community.

Evaluation of Patient-Specific Quality Control (QC) for Markerless Dynamic Tumor Tracking (MDTT) Deliveries

To report on the patient-specific QC for MDTT for liver and lung tumors treated using the dome-of-liver/diaphragm as a surrogate for the target position and compare to the QC of conventional fiducial-based tracking. Vero4DRT is a linear accelerator that has a gimbal-mounted waveguide and collimation system allowing the radiation beam to perform dynamic tumor tracking based on a patient's respiratory motion. A correlation model is built between an external IR marker placed on the chest and an internal structure, which may be implanted fiducial surrogates or in the case of MDTT, an anatomic landmark. During treatment an orthogonal kV image pair is taken every second. The auto detected internal structure position versus the predicted position is recorded in treatment log files. Five IMRT tracking plans were delivered to two commercial motion phantoms with in-house additions for patient-specific tracking QC. For point dose measurements, a 0.6cc farmer chamber was placed inside the dynamic tracking phantom which contains fiducials for fiducial-based tracking delivery and an anatomic landmark for MDTT. For 2D dose distribution measurements, a radiographic film insert for the Quasar Respiratory Motion Phantom was constructed. The phantom contains both fiducials and has a liver-dome shape at one end to facilitate MDTT. Both motion platforms were interfaced with software that enabled patient-specific respiratory motion traces acquired during a 4DCT scan. Each plan was delivered three times on each phantom: 1) in static mode, 2) during fiducial-based tracking, and 3) during MDTT. Chamber measurements taken during static and tracked delivery were compared to the average chamber dose from the treatment planning software (TPS). Film distributions measured during tracked deliveries were compared to the static film distribution using gamma analysis with FILMQA PRO software. Finally, dynamic tracking treatment statistics, extracted from log files, were compared between fiducial and markerless tracking deliveries. All chamber measurements resulted in dose differences <2.5% compared with the TPS. Dose differences between fiducial-based and MDTT were 0.26% on average (range 0.03-0.62%). For film dose map analysis, gamma pass rates were >95% for all plans for all tracking methods. The average gamma pass rate for 3%/3mm was 99.4% (fiducial-based) vs 98.4% (markerless). For 2%/2mm, the average gamma pass rate was 96.4% (fiducial-based tracking) vs 95.6% (MDTT). Dynamic treatment statistics from logs files reported an average 3D absolute deviation from predicted position of 0.52mm (±0.24) for fiducial tracking and 1.19mm (±0.50) for MDTT. Both fiducial-based and MDTT plans meet passing criteria for patient-specific QC. 3D absolute deviation of detected versus predicted position are larger for MDTT compared to fiducial tracking, however no significant impact on dose delivery was measured.

Technical note: Comprehensive evaluations of gantry and couch rotation isocentricities for implementing proton stereotactic radiosurgery.

Mechanical accuracy should be verified before implementing a proton stereotactic radiosurgery (SRS) program. Linear accelerator (Linac)-based SRS systems often use electronic portal imaging devices (EPIDs) to verify beam isocentricity. Because proton therapy systems do not have EPID, beam isocentricity tests of proton SRS may still rely on films, which are not efficient. To validate that our proton SRS system meets mechanical precision requirements and to present an efficient method to evaluate the couch and gantry's rotational isocentricity for our proton SRS system. A dedicated applicator to hold brass aperture for proton SRS system was designed. The mechanical precision of the system was tested using a metal ball and film for 11 combinations of gantry and couch angles. A more efficient quality assurance (QA) procedure was developed, which used a scintillator device to replace the film. The couch rotational isocentricity tests were performed using orthogonal kV x-rays with the couch rotated isocentrically to five positions (0°, 315°, 270°, 225°, and 180°). At each couch position, the distance between the metal ball in kV images and the imaging isocenter was measured. The gantry isocentricity tests were performed using a cone-shaped scintillator and proton beams at five gantry angles (0°, 45°, 90°, 135°, and 180°), and the isocenter position and the distance of each beam path to the isocenter were obtained. Daily QA procedure was performed for 1month to test the robustness and reproducibility of the procedure. The gantry and couch rotational isocentricity exhibited sub-mm precision, with most measurements within ±0.5mm. The 1-month QA results showed that the procedure was robust and highly reproducible to within ±0.2mm. The gantry isocentricity test using the cone-shaped scintillator was accurate and sensitive to variations of ±0.2mm. The QA procedure was efficient enough to be completed within 30min. The 1-month isocentricity position variations were within 0.5mm, which demonstrating that the overall proton SRS system was stable and precise. The proton SRS Winston-Lutz QA procedure using a cone-shaped scintillator was efficient and robust. We were able to verify radiation delivery could be performed with sub-mm mechanical precision.

Feasibility study of deep learning-based markerless real-time lung tumor tracking with orthogonal X-ray projection images.

The feasibility of a deep learning-based markerless real-time tumor tracking (RTTT) method was retrospectively studied with orthogonal kV X-ray images and clinical tracking records acquired during lung cancer treatment. Ten patients with lung cancer treated with marker-implanted RTTT were included. The prescription dose was 50Gy in four fractions, using seven- to nine-port non-coplanar static beams. This corresponds to 14-18 X-ray tube angles for an orthogonal X-ray imaging system rotating with the gantry. All patients underwent 10 respiratory phases four-dimensional computed tomography. After a data augmentation approach, for each X-ray tube angle of a patient, 2250 digitally reconstructed radiograph (DRR) images with gross tumor volume (GTV) contour labeled were obtained. These images were adopted to train the patient and X-ray tube angle-specific GTV contour prediction model. During the testing, the model trained with DRR images predicted GTV contour on X-ray projection images acquired during treatment. The predicted three-dimensional (3D) positions of the GTV were calculated based on the centroids of the contours in the orthogonal images. The 3D positions of GTV determined by the marker-implanted RTTT during the treatment were considered as the ground truth. The 3D deviations between the prediction and the ground truth were calculated to evaluate the performance of the model. The median GTV volume and motion range were 7.42 (range, 1.18-25.74) cm3 and 22 (range, 11-28) mm, respectively. In total, 8993 3D position comparisons were included. The mean calculation time was 85ms per image. The overall median value of the 3D deviation was 2.27 (interquartile range: 1.66-2.95) mm. The probability of the 3D deviation smaller than 5mm was 93.6%. The evaluation results and calculation efficiency show the proposed deep learning-based markerless RTTT method may be feasible for patients with lung cancer.

Clinical Outcomes of Stereotactic Body Radiation Therapy across Treatment Platforms Employing Varied Approaches to Respiratory Management at a Single Institution

<h3>Purpose/Objective(s)</h3> Stereotactic Body Radiation Therapy (SBRT) has been the standard of care for early-stage non-small cell lung cancer patients who do not undergo surgery since soon after the publication of RTOG 0236. Since then, various linear accelerator platforms have been employed with a variety of approaches to respiratory management, treatment planning and treatment delivery. Comparisons of local control and survival end points using a variety of treatment platforms in addition to respiratory management techniques have not been reported. Here, we present the results of our analysis of clinical outcomes at a single institution across multiple treatment platforms representative of the available technology since the widespread adoption of SBRT for early-stage lung cancer. <h3>Materials/Methods</h3> Consecutive patients who underwent SBRT for early-stage lung cancer between 2011 and 2018 at a single institution were retrospectively analyzed. Treatments were planned and delivered with standardized simulation, dose and fractionation per institutional guidelines. Overall Survival (OS), Local Control (LC), Distant Metastasis Free Survival (DMFS), and Progression Free Survival (PFS) were calculated for the entire cohort. Log rank comparisons of all survival endpoints were then calculated by treatment platform: stereoscopic orthogonal kV x-ray localization with conventional Linac (Linac1), volumetric cone beam CT localization with conventional Linac (Linac2), and megavoltage CT with helical tomotherapy (Linac3). Comparisons were also performed by respiratory management technique: free breath (FB), breath hold (BH) or end expiration respiratory gating (RG). <h3>Results</h3> A total of 240 patients were included in the analysis. Treatment platform utilization was well balanced in the group: 28% on Linac1, 32% on Linac2, and 40% on Linac3. The majority of patients were treated with FB, 72%. Median OS for the entire cohort was 50 months. The crude rate of local recurrence was 7%. Kaplan-Meier estimate of LC for the entire cohort was 94% at 3 years. The median time to local recurrence was not reached. LC was not impacted by treatment platform, p = 0.897, or respiratory management technique, p = 0.623. Comparisons by treatment platform and respiratory management technique revealed no significant differences in OS, DMFS, and PFS. <h3>Conclusion</h3> Irrespective of treatment platform or approach to respiratory management, SBRT remains highly effective at providing durable LC in patients with early-stage lung cancer. Differences in treatment delivery platform and respiratory management do not significantly influence other disease control and survival outcomes.

Patient Reported Outcomes after Frameless Virtual Cone Radiosurgery for Trigeminal Neuralgia

<h3>Purpose/Objective(s)</h3> The Virtual Cone is an MLC delivery sequence designed to mimic the dose distribution of a physical cone. In this prospective trial we assessed the efficacy and patient reported outcomes of frameless MLC-based radiosurgery for trigeminal neuralgia. <h3>Materials/Methods</h3> RAD1501 (ClinicalTrials.gov Identifier: NCT02708810) started enrollment in November 2015. Patients had a BNI score of IV or V and MRI to demonstrate no intracranial lesion to explain symptoms. All patients received 80-85 Gy to Dmax to a 5mm target at the dorsal root entry zone. All patients were treated in an Encompass immobilization device. Image guidance started with orthogonal kV images followed by CBCT. During treatment, the patient position was continuously monitored with optical surface imaging. The primary endpoint was an improvement in the Barrow Neurologic Index from IV/V to III or less. Secondary outcomes were assessed by comparing the mean scores of 8 different scales of SF-36 questionnaire at 3 months and 6 months. <h3>Results</h3> At the time of analysis, 44 patients completed treatment with clinical follow up exceeding 6 months. The mean age was 65.8 years (range 35-94 years). Sex distribution was 56.8 % females and 43.2% males. Post treatment BNI at 3 months was 30.8% BNI of 4, 38.5% BNI of 3, 11.2% BNI of 2 and 19.3% with BNI of 1. Post treatment BNI at 6 months was 19% with BNI of 4, 52.4% BNI of 3, 4.8% BNI of 2 and 23.8% with BNI of 1. Regarding secondary outcomes measured by SF-36 questionnaire there was a statistically significant improvement at 3 months in role limitation due to physical health (<i>p=0.023)</i>, energy (<i>p= 0.014)</i>, emotion wellbeing (<i>p=0.002)</i>, social functioning (<i>p=0.008)</i>, and pain (<i>p<0.001).</i> At 6 month there was statistically significant improvement in energy (<i>p= 0.002)</i>, emotion wellbeing (<i>p<0.001)</i>, social functioning (<i>p=0.030)</i>, and pain (<i>p=<0.001).</i> At 3 months 27/27 (100%) of patients were satisfied with the procedure and would recommend it to family member or friend. <h3>Conclusion</h3> From our initial analysis frameless virtual cone stereotactic radiosurgery for trigeminal neuralgia appears to provide similar outcomes in pain relief (∼80% at 6 months) when compared to stereotactic radiosurgery as demonstrated in previous studies. Patient quality of life improves and there is high satisfaction with the procedure.

Evaluation of intrafraction couch shifts for proton treatment delivery in head-and-neck cancer patients: Toward optimal imaging frequency.

Treatment planning for head-and-neck (H&N) cancer, in particular oropharynx, nasopharynx, and paranasal sinus cases, at our center requires noncoplanar proton beams due to the complexity of the anatomy and target location. Targeting accuracy for all beams is carefully evaluated by using image guidance before delivering proton beam therapy (PBT). In this study, we analyzed couch shifts to evaluate whether imaging is required before delivering each field with different couch angles. After the Institutional Review Board approval, a retrospective analysis was performed on data from 28 H&N patients treated with PBT. Each plan was made with two-to-three noncoplanar and two-to-three coplanar fields. Cone-beam computed tomography and orthogonal kilovoltage (kV) images were acquired for setup and before delivering each field, respectively. The Cartesian (longitudinal, vertical, and lateral) and angular (pitch and roll) shifts for each field were recorded from the treatment summary on the first two fractions and every subsequent fifth fraction. A net magnitude of the three-dimensional (3D) shift in Cartesian coordinates was calculated, and a 3D vector was created from the 6 degrees of freedom coordinates for transforming couch shifts in the system coordinate to the beam's-eye view. A total of 3219 Cartesian and 2146 angular shift values were recorded for 28 patients. Of the Cartesian shifts, 2069 were zero (64.3%), and 1150 (35.7%) were nonzero (range, -7 to 11mm). Of the angular shifts, 1034 (48.2%) were zero, and 1112 (51.8%) were nonzero (range, -3.0° to 3.2°). For 17 patients, the couch shifts increased toward the end of the treatment course. We also found that patients with higher body mass index (BMI) presented increased net couch shifts (p<0.001). With BMI<27, all overall net shift averages were <2mm, and overall maximum net shifts were <6mm. These results confirm the need for orthogonal kV imaging before delivering each field of H&N PBT at our center, where a couch rotation is involved.

Retrospective analysis of MV-kV imaging-based fiducial tracking in prostate SBRT treatment.

PurposeMotion management is critical for prostate stereotactic body radiotherapy (SBRT) due to its high fractional dose and proximity to organs at risk. This study seeks to quantify the advantages of MV–kV tracking over kV imaging alone through a retrospective analysis of over 300 patients who underwent prostate SBRT treatment using MV–kV tracking.MethodsAn MV–kV imaging‐based fiducial tracking technique has been developed at our institute and become a standard clinical practice. This technique calculates three‐dimensional (3D) fiducial displacement in real time from orthogonal kV and MV images acquired simultaneously. The patient will be repositioned if for two consecutive MV–kV data points, the motion is larger than a tolerance of 1.5 mm in any of the lateral, superior–inferior, and/or anterior–posterior directions. This study retrospectively analyzed detected 3D motions using an MV–kV approach of 324 patients who recently underwent prostate SBRT treatments. An algorithm was developed to recover the 2D motion components as if they were detected by kV or MV imaging alone.ResultsOur results indicated that out‐of‐tolerance motions were primarily limited to the range of 1.5–3 mm (>95%). The motions are primarily anterior–posterior and superior–inferior, with less than 14.8% of the occurrences in the lateral direction. Compared to out‐of‐tolerance occurrences detected by MV–kV approach, kV alone caught 46.6% of motions in all three directions, and MV alone caught 46.7%. kV alone shows an overall missing rate of 45.8% for superior–inferior motions and 38.6% for lateral motions. It is also demonstrated that the detectability of motion in specific directions greatly depends on gantry angles, as does the missing rate.ConclusionsOur study demonstrated that MV–kV imaging‐based intrafraction motion tracking is superior to single kV imaging for prostate SBRT in clinical practice.

Development of a deep learning‐based patient‐specific target contour prediction model for markerless tumor positioning

For pancreatic cancer patients, image guided radiation therapy and real-time tumor tracking (RTTT) techniques can deliver radiation to the target accurately. Currently, for the radiation therapy machine with kV X-ray imaging systems, internal markers must be implemented to facilitate tumor tracking. The purpose of this study was to develop a markerless deep learning-based pancreatic tumor positioning procedure for real-time tumor tracking with a kV X-ray imaging system. Fourteen pancreatic cancer patients treated with intensity-modulated radiation therapy from six fixed gantry angles with a gimbal-head radiotherapy system were included in this study. For a gimbal-head radiotherapy system, the three-dimensional (3D) intrafraction target position can be determined using an orthogonal kV X-ray imaging system. All patients underwent four-dimensional computed tomography (4DCT) simulations for treatment planning, which were divided into 10 respiratory phases. After a patient's 4DCT was acquired, for each X-ray tube angle, 10 digitally reconstructed radiograph (DRR) images were obtained. Then, a data augmentation procedure was conducted. The data augmentation procedure first rotated the CT volume around the superior-inferior and anterior-posterior directions from -3° to 3° in 1.5° intervals. Then, the Super-SloMo model was adapted to interpolate 10 frames between respiratory phases. In total, the data augmentation procedure expanded the data scale 250-fold. In this study, for each patient, 12 datasets containing the DRR images from each specific X-ray tube angle based on the radiation therapy plan were obtained. The augmented dataset was randomly divided into training and testing datasets. The training dataset contained 2000 DRR images with clinical target volume (CTV) contours labeled for fine-tuning the pre-trained target contour prediction model. After the fine-tuning, the patient and X-ray tube angle-specific CTV contour prediction model was acquired. The testing dataset contained the remaining 500 images to evaluate the performance of the CTV contour prediction model. The dice similarity coefficient (DSC) between the area enclosed by the CTV contour and predicted contour was calculated to evaluate the model's contour prediction performance. The 3D position of the CTV was calculated based on the centroid of the contour in the orthogonal DRR images, and the 3D error of the prediction position was calculated to evaluate the CTV positioning performance. For each patient, the DSC results from 12 X-ray tube angles and 3D error from 6 gantry angles were calculated, representing the novelty of this study. The mean and standard deviation (SD) of all patients' DSCs were 0.98 and 0.015, respectively. The mean and SD of the 3D error were 0.29mm and 0.14mm, respectively. The global maximum 3D error was 1.66mm, and the global minimum DSC was 0.81. The mean calculation time for CTV contour prediction was 55ms per image. This fulfills the requirement of RTTT. Regarding the positioning accuracy and calculation efficiency, the presented procedure can provide a solution for markerless real-time tumor tracking for pancreatic cancer patients.

Faster and more accurate patient positioning with surface guided radiotherapy for ultra-hypofractionated prostate cancer patients.

The aim of this study was to evaluate if surface guided radiotherapy (SGRT) can decrease patient positioning time for localized prostate cancer patients compared to the conventional 3-point localization setup method. The patient setup accuracy was also compared between the two setup methods. A total of 40 localized prostate cancer patients were enrolled in this study, where 20 patients were positioned with surface imaging (SI) and 20 patients were positioned with 3-point localization. The setup time was obtained from the system log files of the linear accelerator and compared between the two methods. The patient setup was verified with daily orthogonal kV images which were matched based on the implanted gold fiducial markers. Resulting setup deviations between planned and online positions were compared between SI and 3-point localization. Median setup time was 2:50min and 3:28min for SI and 3-point localization, respectively (p<0.001). The median vector offset was 4.7mm (range: 0-10.4mm) for SI and 5.2mm for 3-point localization (range: 0.41-17.3mm) (p=0.01). Median setup deviation in the individual translations for SI and 3-point localization respectively was: 1.1mm and 1.9mm in lateral direction (p=0.02), 1.8 and 1.6mm in the longitudinal direction (p=0.41) and 2.2mm and 2.6mm in the vertical direction (p=0.04). Using SGRT for positioning of prostate cancer patients provided a faster and more accurate patient positioning compared to the conventional 3-point localization setup.

Intrafraction motion during partial breast irradiation depends on treatment time

IntroductionAs the prognosis of early-stage breast cancer patients is excellent, prevention of radiation-induced toxicity has become crucial. Reduction of margins compensating for intrafraction motion reduces non-target dose. We assessed motion of the tumor bed throughout APBI treatment fractions and calculated CTV-PTV margins for breathing and drift. MethodsThis prospective clinical trial included patients treated with APBI on a Cyberknife with fiducial tracking. Paired orthogonal kV images made throughout the entire fraction were used to extract the tumor bed position. The images used for breathing modelling were used to calculate breathing amplitudes. The margins needed to compensate for breathing and drift were calculated according to Engelsman and Van Herk respectively. ResultsTwenty-two patients, 110 fractions and 5087 image pairs were analyzed. The margins needed for breathing were 0.3–0.6 mm. The margin for drift increased with time after the first imaging for positioning. For a total fraction duration up to 8 min, a margin of 1.0 mm is sufficient. For a fraction of 32 min, 2.5 mm is needed. Techniques that account for breathing motion can reduce the margin by 0.1 mm. There was a systematic trend in the drift in the caudal, medial and posterior direction. To compensate for this, 0.7 mm could be added to the margins. ConclusionsThe margin needed to compensate for intrafraction motion increased with longer fraction duration due to drifting of the target. It doubled for a fraction of 24 min compared to 8 min. Breathing motion has a limited effect.

How low can you go? A CBCT dose reduction study.

PurposeCone beam computed tomography (CBCT) is often used for patient setup based solely on bony anatomy. The goal of this work was to evaluate whether CBCT dose can be lowered to the level of kV image pair doses when used for bony anatomy‐based IGRT without compromising positioning accuracy.MethodsAn anthropomorphic phantom was CT scanned in the head, head and neck, chest, and pelvis regions and setup on the linear accelerator couch with the isocenter near the planned location. Cone beam computed tomographies were performed with the standard “full dose” protocol supplied by the linac vendor. With sequentially lowering the dose, three‐dimensional (3D) matching was performed for each without shifting the couch. The standard kV image pair protocol for each site was also used to image the phantoms. For all studies, six degrees of freedom was included in the 2D or 3D matching to the extent they could be employed. Imaging doses were determined in air at isocenter following the TG‐61 formalism.ResultsCone beam computed tomography dose was reduced by 81–98% of the standard CBCT protocol to nearly that of the standard kV image pair dose for each site. Relative to the standard CBCT shift values, translational shifts were within 0.3 and 1.6 mm for all sites, for the reduced dose CBCT and kV image pair, respectively. Rotational shifts were within 0.2 degree and 0.7 degrees for all sites, for the reduced dose CBCTs and kV image pair, respectively.ConclusionFor bony anatomy‐based image guidance, CBCT dose can be reduced to a value similar to that of a kV image pair with similar or better patient positioning accuracy than kV image pair alignment. Where rotations are important to correct, CBCT will be superior to orthogonal kV imaging without significantly increased imaging dose. This is especially important for image guidance for pediatric patient treatments.

Using patient-specific bolus for pencil beam scanning proton treatment of periorbital disease.

PurposeA unique mantle cell lymphoma case with bilateral periorbital disease unresponsive to chemotherapy and with dosimetry not conducive to electron therapy was treated with pencil beam scanning (PBS) proton therapy. This patient presented treatment planning challenges due to the thin target, immediately adjacent organs at risk (OAR), and nonconformal orbital surface anatomy. Therefore, we developed a patient‐specific bolus and hypothesized that it would provide superior setup robustness, dose uniformity and dose conformity.Materials/MethodsA blue‐wax patient‐specific bolus was generated from the patient's face contour to conform to his face and eliminate air gaps. A relative stopping power ratio (RSP) of 0.972 was measured for the blue‐wax, and the HUs were overridden accordingly in the treatment planning system (TPS). Orthogonal kV images were used for bony alignment and then to ensure positioning of the bolus through fiducial markers attached to the bolus and their contours in TPS. Daily CBCT was used to confirm the position of the bolus in relation to the patient's surface. Dosimetric characteristics were compared between (a) nonbolus, (b) conventional gel bolus and (c) patient‐specific bolus plans. An in‐house developed workflow for assessment of daily treatment dose based on CBCT images was used to evaluate inter‐fraction dose accumulation.ResultsThe patient was treated to 24 cobalt gray equivalent (CGE) in 2 CGE daily fractions to the bilateral periorbital skin, constraining at least 50% of each lacrimal gland to under 20 Gy. The bolus increased proton beam range by adding 2–3 energy layers of different fields to help achieve better dose uniformity and adequate dose coverage. In contrast to the plan with conventional gel bolus, dose uniformity was significantly improved with patient‐specific bolus. The global maximum dose was reduced by 7% (from 116% to 109%). The max and mean doses were reduced by 6.0% and 7.7%, respectively, for bilateral retinas, and 3.0% and 13.9% for bilateral lacrimal glands. The max dose of the lens was reduced by 2.1%. The rigid shape, along with lightweight, and smooth fit to the patient face was well tolerated and reported as “very comfortable” by the patient. The daily position accuracy of the bolus was within 1 mm based on IGRT marker alignment. The daily dose accumulation indicates that the target coverage and OAR doses were highly consistent with the planning intention.ConclusionOur patient‐specific blue‐wax bolus significantly increased dose uniformity, reduced OAR doses, and maintained consistent setup accuracy compared to conventional bolus. Quality PBS proton treatment for periorbital tumors and similar challenging thin and shallow targets can be achieved using such patient‐specific bolus with robustness on both setup and dosimetry.

Comparison of kV Orthogonal Radiographs and kV-Cone-Beam Computed Tomography Image-Guided Radiotherapy Methods With and Without Implanted Fiducials in Prostate Cancer.

IntroductionThe aim of this study is to investigate the performance of kilovoltage (kV) cone-beam computed tomography (CBCT)-based adjustments with respect to kV-orthogonal fiducial marker-based matching in a group of patients with prostate cancer. MethodsTwenty prostate cancer patients were evaluated retrospectively: 10 with implanted fiducial markers and 10 without. Daily orthogonal kV imaging was recorded prior to radiation delivery. Images were evaluated in the left-right (LR), anterior-posterior (AP), and superior-inferior (SI) directions by matching either the implanted fiducials or going off bony anatomy, depending on the presence or absence of markers, respectively. Cone-beam computed tomography (CBCT) imaging was also subsequently acquired and images were aligned with the planning CT. The couch shifts were calculated and the patient’s position was adjusted accordingly. Standard deviations and random errors were also computed. Pearson correlation and Bland-Altman analysis were performed to evaluate relationships between the datasets.ResultsA total of 240 images were evaluated. The Pearson correlation coefficient for shifts applied to patients with markers using kV and CBCT was 88.3%, 87.8%, and 94.5% for the LR, AP, and SI directions, respectively. For those without markers, the respective values for the LR, AP, and SI directions were: 39.3%, 22.4%, and 3.7%. A Bland-Altman analysis comparing kV and CBCT in patients with markers, revealed R2 values of 0.152, 0.282, and 0.097 in the LR, AP, and SI directions, respectively. The R2 values for patients without markers were 0.008, 0.01, and 0.057, in the LR, AP, and SI directions, respectively.ConclusionsOur data suggest that CBCT can be a viable option for image-guidance in clinical settings where fiducial markers are unavailable such as situations of inaccessibility or medical contraindications.

Direct measurement and correction of both megavoltage and kilovoltage scattered x-rays for orthogonal kilovoltage imaging subsystems with dual flat panel detectors.

PurposeTo measure the scattered x‐rays of megavoltage (MV) and kilovoltage (kV) beams (MV scatter and kV scatter, respectively) on the orthogonal kV imaging subsystems of Vero4DRT.MethodsImages containing MV‐ and kV‐scatter from another source only (i.e., MV‐ and kV‐scatter maps) were acquired for each investigated flat panel detector. The reference scatterer was a water‐equivalent cuboid phantom. The maps were acquired by changing one of the following parameters from the reference conditions while keeping the others fixed: field size: 10.0 × 10.0 cm2; dose rate: 400 MU/min; gantry and ring angles: 0°; kV collimator aperture size at isocenter: 10.0 × 10.0 cm2: tube voltage: 110 kV; and exposure: 0.8 mAs. The average pixel values of MV‐ and kV‐scatter (i.e., the MV‐ and kV‐scatter values) at the center of each map were calculated and normalized to the MV‐scatter value under the reference conditions (MV‐ and kV‐scatter value factor, respectively). In addition, an MV‐ and kV‐scatter correction experiment with intensity‐modulated beams was performed using a phantom with four gold markers (GMs). The ratios between the intensities of the GMs and those of their surroundings were calculated.ResultsThe measurements showed a strong dependency of the MV‐scatter on the field size and dose rate. The maximum MV‐scatter value factors were 2.0 at a field size of 15.0 × 15.0 cm2 and 2.5 at a dose rate of 500 MU/min. The maximum kV‐scatter value was 0.48 with a fully open kV collimator aperture. In the phantom experiment, the intensity ratios of kV images with MV‐ and kV‐scatter were decreased from the reference ones. After correction of kV‐scatter only, MV‐scatter only, and both MV‐ and kV‐scatter, the intensity ratios gradually improved.ConclusionsMV‐ and kV‐scatter could be corrected by subtracting the scatter maps from the projections, and the correction improved the intensity ratios of the GMs.

Proton pencil beam scanning treatment with feedback based voluntary moderate breath hold

Introduction The aim of this article is to introduce a novel protocol for proton pencil beam scanning treatment with moderate deep inspiration breath hold (mDIBH) and report on our clinical implementation results. Methods Three computed tomography (CT) scannings to build the patient's anatomy model were performed during the patient's voluntary mDIBH. All 3 CT scans were used in the optimization during the treatment planning process. Both orthogonal kV imaging and cone-beam computed tomography (CBCT) were implemented for patient alignment with BH prior to the treatment. The BH CBCT images were analyzed for BH reproducibility and the virtual total dose (VTD) retrospectively. To find the VTD, a series of deformable image registrations (DIR) were performed between CBCT and pCT. The effect of the variation of lung density on the dose distribution was also analyzed in the study. Results The values of the mean, standard deviation, maximum, and minimum of the tumor location difference between the CBCT and pCT were 1.9, 1.6, 4.7, and 0.0 mm, respectively. The percentage difference in D99% of CTVs between VTD and the nominal plan was within 1.5%. Conclusions The feedback-based voluntary moderate BH proton PBS treatment was successfully performed in our clinic. This study shows that there is a potential to implement the BH treatment widely in proton centers.

Impact of use of optical surface imaging on initial patient setup for stereotactic body radiotherapy treatments.

PurposeTo evaluate the effectiveness of surface image guidance (SG) for pre‐imaging setup of stereotactic body radiotherapy (SBRT) patients, and to investigate the impact of SG reference surface selection on this process.Methods and materials284 SBRT fractions (SG‐SBRT = 113, non‐SG‐SBRT = 171) were retrospectively evaluated. Differences between initial (pre‐imaging) and treatment couch positions were extracted from the record‐and‐verify system and compared for the two groups. Rotational setup discrepancies were also computed. The utility of orthogonal kVs in reducing CBCT shifts in the SG‐SBRT/non‐SG‐SBRT groups was also calculated. Additionally, the number of CBCTs acquired for setup was recorded and the average for each cohort was compared. These data served to evaluate the effectiveness of surface imaging in pre‐imaging patient positioning and its potential impact on the necessity of including orthogonal kVs for setup. Since reference surface selection can affect SG setup, daily surface reproducibility was estimated by comparing camera‐acquired surface references (VRT surface) at each fraction to the external surface of the planning CT (DICOM surface) and to the VRT surface from the previous fraction.ResultsThe reduction in all initial‐to‐treatment translation/rotation differences when using SG‐SBRT was statistically significant (Rank‐Sum test, α = 0.05). Orthogonal kV imaging kept CBCT shifts below reimaging thresholds in 19%/51% of fractions for SG‐SBRT/non‐SG‐SBRT cohorts. Differences in average number of CBCTs acquired were not statistically significant. The reference surface study found no statistically significant differences between the use of DICOM or VRT surfaces.ConclusionsSG‐SBRT improved pre‐imaging treatment setup compared to in‐room laser localization alone. It decreased the necessity of orthogonal kV imaging prior to CBCT but did not affect the average number of CBCTs acquired for setup. The selection of reference surface did not have a significant impact on initial patient positioning.

A novel approach to Verify air gap and SSD for proton radiotherapy using surface imaging

PurposeTo develop a novel approach to accurately verify patient set up in proton radiotherapy, especially for the verification of the nozzle – body surface air gap and source-to-skin distance (SSD), the consistency and accuracy of which is extremely important in proton treatment.MethodsPatient body surfaces can be captured and monitored with the optical surface imaging system during radiation treatment for improved intrafraction accuracy. An in-house software package was developed to reconstruct the patient body surface in the treatment position from the optical surface imaging reference capture and to calculate the corresponding nozzle – body surface air gap and SSD. To validate this method, a mannequin was scanned on a CT simulator and proton plans were generated for a Mevion S250 Proton machine with 20 gantry/couch angle combinations, as well as two different snout sizes, in the Varian Eclipse Treatment Planning Systems (TPS). The surface generated in the TPS from the CT scan was imported into the optical imaging system as an RT Structure for the purpose of validating and establishing a benchmark for ground truth comparison. The optical imaging surface reference capture was acquired at the treatment setup position after orthogonal kV imaging to confirm the positioning. The air gaps and SSDs calculated with the developed method from the surface captured at the treatment setup position (VRT surface) and the CT based surface imported from the TPS were compared to those calculated in TPS. The same approach was also applied to 14 clinical treatment fields for 10 patients to further validate the methodology.ResultsThe air gaps and SSDs calculated from our program agreed well with the corresponding values derived from the TPS. For the phantom results, using the CT surface, the absolute differences in the air gap were 0.45 mm ± 0.33 mm for the small snout, and 0.51 mm ± 0.49 mm for the large snout, and the absolute differences in SSD were 0.68 mm ± 0.42 mm regardless of snout size. Using the VRT surface, the absolute differences in air gap were 1.17 mm ± 1.17 mm and 2.1 mm ± 3.09 mm for the small and large snouts, respectively, and the absolute differences in SSD were 0.81 mm ± 0.45 mm. Similarly, for patient data, using the CT surface, the absolute differences in air gap were 0.42 mm ± 0.49 mm, and the absolute differences in SSD were 1.92 mm ± 1.4 mm. Using the VRT surface, the absolute differences in the air gap were 2.35 mm ± 2.3 mm, and the absolute differences in SSD were 2.7 mm ± 2.17 mm.ConclusionThese results showed the feasibility and robustness of using an optical surface imaging approach to conveniently determine the air gap and SSD in proton treatment, providing an accurate and efficient way to confirm the target depth at treatment.