Feasibility and Significance of Dose Adaptation via Linear Couch Translations to Correct for Rotational Shifts During Frameless Brain Radiosurgery with the Gamma Knife Icon™.

OBJECTIVE: The present study aimed to examine the technical feasibility and effectiveness of adapting the radiation dose distributions with three-dimensional (3D) linear couch translations in contrast to full six-dimensional couch maneuvers to correct for rotational shifts during frameless radiosurgical treatment with the Gamma Knife Icon™ (Elekta AB; Stockholm, Sweden). METHODS: The original magnetic resonance images used for radiosurgery treatment planning (15 targets) were digitally processed to simulate rotational shifts of ±1, ±2, ±3, ±5, and ±10 degrees in the transverse plane and imported back into Leksell GammaPlan® (Elekta AB), creating "uncorrected" treatment plans. In addition, geometrically optimized 3D translation shifts were consequently applied to each isocenter in all "uncorrected" treatment plans to account for systematically introduced rotational shifts and to produce "corrected" treatment plans. The differences in the dose distribution between the original treatment plans and the "uncorrected" and "corrected" treatment plans were calculated and compared at each rotational shift position. RESULTS: The "uncorrected" treatment plans resulted in a significant deterioration in target coverage (by 8-72%) and selectivity (by 2-42%), with some targets being missed completely with rotations of ±3 or more degrees. In contrast, in all "corrected" treatment plans, the average decreases in target coverage and selectivity were only 1% (maximum values 4-5%). CONCLUSION: Applications of 3D linear couch translations successfully overcome gross uncertainties in dose distributions caused by up to ±10 degrees of rotational shifts in a target. As a result, rapid dose adaptation with 3D couch translations is unique and effective for frameless radiosurgery with the Gamma Knife Icon™.

Ensuring High Quality Treatment Plans with a Plan Quality Review Checklist.

Treatment plan quality is a crucial component for a successful outcome of radiation therapy treatments. As the complexity of radiation therapy planning and delivery techniques increases, the role of the medical physicist in assessing treatment plan quality becomes more critical. Integrating plan quality review throughout the treatment planning process allows improvements without delaying treatment or rushing to produce changes at the last minute. In this work, we aim to provide practical check items for physicists to reference when assessing treatment plan quality with a critical eye, asking questions such as "is this the best dose distribution feasible for this patient?," "could we change any planning parameters to improve plan quality?," and "could we change the planning strategy for this particular patient or for future patients?"; and to work with planners and physicians to create a multidisciplinary collaborative culture that achieves the best plan feasible for every patient. We tabulate the features that affect plan quality in each process step and check details for individual items. This report is aimed at medical physicists, planners, radiation oncologists, and other professionals who are involved in treatment planning.

Computational ECG mapping and respiratory gating to optimize stereotactic ablative radiotherapy workflow for refractory ventricular tachycardia.

BACKGROUND: Stereotactic ablative radiotherapy (SAbR) is an emerging therapy for refractory ventricular tachycardia (VT). However, the current workflow is complicated, and the precision and safety in patients with significant cardiorespiratory motion and VT targets near the stomach may be suboptimal. OBJECTIVE: We hypothesized that automated 12-lead electrocardiogram (ECG) mapping and respiratory-gated therapy may improve the ease and precision of SAbR planning and facilitate safe radiation delivery in patients with refractory VT. METHODS: Consecutive patients with refractory VT were studied at 2 hospitals. VT exit sites were localized using a 3-D computational ECG algorithm noninvasively and compared to available prior invasive mapping. Radiotherapy (25 Gy) was delivered at end-expiration when cardiac respiratory motion was ≥0.6 cm or targets were ≤2 cm from the stomach. RESULTS: In 6 patients (ejection fraction 29% ± 13%), 4.2 ± 2.3 VT morphologies per patient were mapped. Overall, 7 out of 7 computational ECG mappings (100%) colocalized to the identical cardiac segment when prior invasive electrophysiology study was available. Respiratory gating was associated with smaller planning target volumes compared to nongated volumes (71 ± 7 vs 153 ± 35 cc, P < .01). In 2 patients with inferior wall VT targets close to the stomach (6 mm proximity) or significant respiratory motion (22 mm excursion), no GI complications were observed at 9- and 12-month follow-up. Implantable cardioverter-defibrillator shocks decreased from 23 ± 12 shocks/patient to 0.67 ± 1.0 (P < .001) post-SAbR at 6.0 ± 4.9 months follow-up. CONCLUSIONS: A workflow including computational ECG mapping and protocol-guided respiratory gating is feasible, is safe, and may improve the ease of SAbR planning. Studies to validate this workflow in larger populations are required.

Evaluating the impact of extended field-of-view CT reconstructions on CT values and dosimetric accuracy for radiation therapy.

PURPOSE: Wide bore CT scanners use extended field-of-view (eFOV) reconstruction algorithms to attempt to recreate tissue truncated due to large patient habitus. Radiation therapy planning systems rely on accurate CT numbers in order to correctly plan and calculate radiation dose. This study looks at the impact of eFOV reconstructions on CT numbers and radiation dose calculations in real patient geometries. METHODS: A large modular phantom based on real patient geometries was created to surround a CIRS Model 062M phantom. The modular sections included a smooth patient surface, a skin fold in the patient surface, and the addition of arms for simulation of the patient in arms up or arms down position. This phantom was used to evaluate the accuracy of CT numbers for three extended FOV algorithms implemented on Siemens CT scanners: eFOV, HDFOV, and HDProFOV. Six different configurations of the phantoms were scanned and images were reconstructed for the three different extended FOV algorithms. The CIRS phantom inserts and overall phantom geometry were contoured in each image, and the Hounsfield units (HU) numbers were compared to an image of the phantom within the standard scan FOV (sFOV) without the modular sections. To evaluate the effect on dose calculations, six radiotherapy patients previously treated at our institution (three head and neck and three chest/pelvis) whose body circumferences extended past the 50 cm sFOV in the treatment planning CT were used. Images acquired on a Siemens Sensation Open scanner were reconstructed using sFOV, eFOV and HDFOV algorithms. A physician and dosimetrist identified the radiation target, critical organs, and external patient contour. A benchmark CT was created for each patient, consisting of an average of the 3 CT reconstructions with a density override applied to regions containing truncation artifacts. The benchmark CT was used to create an optimal radiation treatment plan. The plan was copied onto each CT reconstruction without density override and dose was recalculated. RESULTS: Tissue extending past the sFOV impacts the HU numbers for tissues inside and outside the sFOV when using extended FOV reconstructions. On average, the HU for all CIRS density inserts in the arms up (arms down) position varied by 43 HU (67 HU), 39 HU (73 HU), and 18 HU (51 HU) for the eFOV, HDFOV, and HDProFOV scans, respectively. In the patient dose calculations, patients with a smooth patient contour had the least deviation from the benchmark in the HDFOV (0.1-0.5%) compared to eFOV (0.4-1.8%) reconstructions. In cases with large amounts of tissue and irregular skin folds, the eFOV deviated the least from the benchmark (range 0.2-0.6% dose difference) compared to HDFOV (range 1.3-1.8% dose difference). CONCLUSIONS: All reconstruction algorithms demonstrated good CT number accuracy in the center of the image. Larger artifacts are seen near and extending outside the scan FOV, however, dose calculations performed using typical beam arrangements using the extended FOV reconstructions were still mostly within 2.5% of best estimated reference values.

Improved rectal dosimetry with the use of SpaceOAR during high-dose-rate brachytherapy.

PURPOSE: Hydrogel spacers have been suggested to limit rectal radiation dose with improvements in clinical outcomes in patients undergoing external beam radiation treatment for prostate cancer. No studies to date have assessed the utility and dosimetric effect of SpaceOAR (Augmenix, Inc, Waltham, MA), the only Food and Drug Administration-approved hydrogel rectal spacer, for high-dose-rate (HDR) brachytherapy. METHODS: Eighteen consecutive patients scheduled for HDR brachytherapy in the treatment of prostate cancer underwent transperineal ultrasound-guided placement of 10 cc of SpaceOAR hydrogel following catheter implantation. Treatment plans were generated using an inverse planning simulated annealing algorithm. Rectal dosimetry for these 18 patients was compared with the 36 preceding patients treated with HDR brachytherapy without SpaceOAR. RESULTS: Fifty-four plans were analyzed. There was no difference in age, pretreatment prostate-specific antigen, Gleason score, clinical stage, prostate volume, or contoured rectal volume between those who received SpaceOAR and those who did not. Patients who received SpaceOAR hydrogel had significantly lower dose to the rectum as measured by percent of contoured organ at risk (median, V80 < 0.005% vs. 0.010%, p = 0.003; V75 < 0.005% vs. 0.14%, p < 0.0005; V70 0.09% vs. 0.88%, p < 0.0005; V60 = 1.16% vs. 3.08%, p < 0.0005); similar results were seen for rectal volume in cubic centimeters. One patient who received SpaceOAR developed a perineal abscess 1 month after treatment. CONCLUSIONS: Transperineal insertion of SpaceOAR hydrogel at the time of HDR brachytherapy is feasible and decreases rectal radiation dose. Further investigation is needed to assess the clinical impact of this dosimetric improvement and potential toxicity reduction.

A continuous arc delivery optimization algorithm for CyberKnife m6.

PURPOSE: This study aims to reduce the delivery time of CyberKnife m6 treatments by allowing for noncoplanar continuous arc delivery. To achieve this, a novel noncoplanar continuous arc delivery optimization algorithm was developed for the CyberKnife m6 treatment system (CyberArc-m6). METHODS AND MATERIALS: CyberArc-m6 uses a five-step overarching strategy, in which an initial set of beam geometries is determined, the robotic delivery path is calculated, direct aperture optimization is conducted, intermediate MLC configurations are extracted, and the final beam weights are computed for the continuous arc radiation source model. This algorithm was implemented on five prostate and three brain patients, previously planned using a conventional step-and-shoot CyberKnife m6 delivery technique. The dosimetric quality of the CyberArc-m6 plans was assessed using locally confined mutual information (LCMI), conformity index (CI), heterogeneity index (HI), and a variety of common clinical dosimetric objectives. RESULTS: Using conservative optimization tuning parameters, CyberArc-m6 plans were able to achieve an average CI difference of 0.036 ± 0.025, an average HI difference of 0.046 ± 0.038, and an average LCMI of 0.920 ± 0.030 compared with the original CyberKnife m6 plans. Including a 5 s per minute image alignment time and a 5-min setup time, conservative CyberArc-m6 plans achieved an average treatment delivery speed up of 1.545x ± 0.305x compared with step-and-shoot plans. CONCLUSIONS: The CyberArc-m6 algorithm was able to achieve dosimetrically similar plans compared to their step-and-shoot CyberKnife m6 counterparts, while simultaneously reducing treatment delivery times.

Characterization of the effect of a new commercial transmission detector on radiation therapy beams.

PURPOSE: To evaluate the influence of a new commercial transmission detector on radiation therapy beams. METHODS AND MATERIALS: A transmission detector designed for online treatment monitoring was characterized on a TrueBeam STx linear accelerator with 6-MV, 6-flattening filter free, 10-MV, and 10-flattening filter free beams. Measurements of percentage depth doses, in-plane and cross-plane off-axis profiles at different depths, transmission factors, and skin dose were acquired with 3 × 3, 5 × 5, 10 × 10, 20 × 20, and 40 × 40 cm2 field sizes at 100 cm and 80 cm source-to-surface distance (SSD). A CC04 chamber was used for all profile and transmission factor measurements. Skin dose was assessed at 100, 90, and 80 cm SSD using a variety of detectors (Roos and Markus parallel-plate chambers and optically stimulated luminescent dosimeters [OSLDs]). Skin dose was also assessed for various patient sample plans with OSLDs. RESULTS: The percentage depth doses showed small differences between the unperturbed and perturbed beams for 100 cm SSD (≤4 mm depth of maximum dose difference, <1.2% average profile difference) for all field sizes. At 80 cm SSD, the differences were larger (≤8 mm depth of maximum dose difference, <3% average profile difference). The differences were larger for the flattened beams and larger field sizes. The off-axis profiles showed similar trends. Field penumbras looked similar with and without the transmission detector. Comparisons in the profile central 80% showed a maximum average (maximum) profile difference between all field sizes of 1.0% (2.6%) and 1.4% (6.3%) for 100 and 80 cm SSD, respectively. The average measured skin dose increase at 100 cm (80 cm) SSD for a 10 × 10 cm2 field size was <4% (<35%) for all energies. For a 40 × 40 cm2 field size, this increased to <31% (≤63%). For the sample patient plans, the average skin dose difference was 0.53% (range, -6.6% to 10.4%). CONCLUSIONS: The transmission detector has minimal effect on clinically relevant radiation therapy beams for intensity modulated radiation therapy and volumetric arc therapy (field sizes 10 × 10 cm2 and less). For larger field sizes, some perturbations are observable that would need to be assessed for clinical impact.

CyberArc: a non-coplanar-arc optimization algorithm for CyberKnife.

The goal of this study is to demonstrate the feasibility of a novel non-coplanar-arc optimization algorithm (CyberArc). This method aims to reduce the delivery time of conventional CyberKnife treatments by allowing for continuous beam delivery. CyberArc uses a 4 step optimization strategy, in which nodes, beams, and collimator sizes are determined, source trajectories are calculated, intermediate radiation models are generated, and final monitor units are calculated, for the continuous radiation source model. The dosimetric results as well as the time reduction factors for CyberArc are presented for 7 prostate and 2 brain cases. The dosimetric quality of the CyberArc plans are evaluated using conformity index, heterogeneity index, local confined normalized-mutual-information, and various clinically relevant dosimetric parameters. The results indicate that the CyberArc algorithm dramatically reduces the treatment time of CyberKnife plans while simultaneously preserving the dosimetric quality of the original plans.

Development and validation of a rapid and robust method to determine visceral adipose tissue volume using computed tomography images.

BACKGROUND: Visceral adiposity is a risk factor for many chronic diseases. Existing methods to quantify visceral adipose tissue volume using computed tomographic (CT) images often use a single slice, are manual, and are time consuming, making them impractical for large population studies. We developed and validated a method to accurately, rapidly, and robustly measure visceral adipose tissue volume using CT images. METHODS: In-house software, Medical Executable for the Efficient and Robust Quantification of Adipose Tissue (MEERQAT), was developed to calculate visceral adipose tissue volume using a series of CT images within a manually identified region of interest. To distinguish visceral and subcutaneous adipose tissue, ellipses are drawn through the rectus abdominis and transverse abdominis using manual and automatic processes. Visceral and subcutaneous adipose tissue volumes are calculated by counting the numbers of voxels corresponding to adipose tissue in the region of interest. MEERQAT's ellipse interpolation method was validated by comparing visceral adipose volume from 10 patients' CT scans with corresponding results from manually delineated scans. Accuracy of visceral adipose quantification was tested using a phantom consisting of animal fat and tissues. Robustness of the method was tested by determining intra-observer and inter-observer coefficients of variation (CV). RESULTS: The mean difference in visceral adipose tissue volume between manual and elliptical delineation methods was -0.54 ± 4.81%. In the phantom, our measurement differed from the known adipose volume by ≤ 7.5% for all scanning parameters. Mean inter-observer CV for visceral adipose tissue volume was 0.085, and mean intra-observer CV for visceral adipose tissue volume was 0.059. CONCLUSIONS: We have developed and validated a robust method of accurately and quickly determining visceral adipose tissue volume in any defined region of interest using CT imaging.

A novel dose-based positioning method for CT image-guided proton therapy.

PURPOSE: Proton dose distributions can potentially be altered by anatomical changes in the beam path despite perfect target alignment using traditional image guidance methods. In this simulation study, the authors explored the use of dosimetric factors instead of only anatomy to set up patients for proton therapy using in-room volumetric computed tomographic (CT) images. METHODS: To simulate patient anatomy in a free-breathing treatment condition, weekly time-averaged four-dimensional CT data near the end of treatment for 15 lung cancer patients were used in this study for a dose-based isocenter shift method to correct dosimetric deviations without replanning. The isocenter shift was obtained using the traditional anatomy-based image guidance method as the starting position. Subsequent isocenter shifts were established based on dosimetric criteria using a fast dose approximation method. For each isocenter shift, doses were calculated every 2 mm up to ± 8 mm in each direction. The optimal dose alignment was obtained by imposing a target coverage constraint that at least 99% of the target would receive at least 95% of the prescribed dose and by minimizing the mean dose to the ipsilateral lung. RESULTS: The authors found that 7 of 15 plans did not meet the target coverage constraint when using only the anatomy-based alignment. After the authors applied dose-based alignment, all met the target coverage constraint. For all but one case in which the target dose was met using both anatomy-based and dose-based alignment, the latter method was able to improve normal tissue sparing. CONCLUSIONS: The authors demonstrated that a dose-based adjustment to the isocenter can improve target coverage and/or reduce dose to nearby normal tissue.

Statistical assessment of proton treatment plans under setup and range uncertainties.

PURPOSE: To evaluate a method for quantifying the effect of setup errors and range uncertainties on dose distribution and dose-volume histogram using statistical parameters; and to assess existing planning practice in selected treatment sites under setup and range uncertainties. METHODS AND MATERIALS: Twenty passively scattered proton lung cancer plans, 10 prostate, and 1 brain cancer scanning-beam proton plan(s) were analyzed. To account for the dose under uncertainties, we performed a comprehensive simulation in which the dose was recalculated 600 times per given plan under the influence of random and systematic setup errors and proton range errors. On the basis of simulation results, we determined the probability of dose variations and calculated the expected values and standard deviations of dose-volume histograms. The uncertainties in dose were spatially visualized on the planning CT as a probability map of failure to target coverage or overdose of critical structures. RESULTS: The expected value of target coverage under the uncertainties was consistently lower than that of the nominal value determined from the clinical target volume coverage without setup error or range uncertainty, with a mean difference of -1.1% (-0.9% for breath-hold), -0.3%, and -2.2% for lung, prostate, and a brain cases, respectively. The organs with most sensitive dose under uncertainties were esophagus and spinal cord for lung, rectum for prostate, and brain stem for brain cancer. CONCLUSIONS: A clinically feasible robustness plan analysis tool based on direct dose calculation and statistical simulation has been developed. Both the expectation value and standard deviation are useful to evaluate the impact of uncertainties. The existing proton beam planning method used in this institution seems to be adequate in terms of target coverage. However, structures that are small in volume or located near the target area showed greater sensitivity to uncertainties.