Comparison of Three Commercial Methods of Cone-Beam Computed Tomography-Based Dosimetric Analysis of Head-and-Neck Patients with Weight Loss.

Purpose: This investigation compares three commercial methods of cone-beam computed tomography (CBCT)-based dosimetric analysis to a method based on repeat computed tomography (CT). Materials and Methods: Seventeen head-and-neck patients treated in 2020, and with a repeat CT, were included in the analyses. The planning CT was deformed to anatomy in repeat CT to generate a reference plan. Two of the CBCT-based methods generated test plans by deforming the planning CT to CBCT of fraction N using VelocityAI™ and SmartAdapt®. The third method compared directly calculated doses on the CBCT for fraction 1 and fraction N, using PerFraction™. Maximum dose to spinal cord (Cord_dmax) and dose to 95% volume (D95) of planning target volumes (PTVs) were used to assess "need to replan" criteria. Results: The VelocityAI™ method provided results that most accurately matched the reference plan in "need to replan" criteria using either Cord_dmax or PTV D95. SmartAdapt® method overestimated the change in Cord_dmax (6.77% vs. 3.85%, P < 0.01) and change in cord volume (9.56% vs. 0.67%, P < 0.01) resulting in increased false positives in "need to replan" criteria, and performed similarly to VelocityAI™ for D95, but yielded more false negatives. PerFraction™ method underestimated Cord_dmax, did not perform any volume deformation, and missed all "need to replan" cases based on cord dose. It also yielded high false negatives using the D95 PTV criteria. Conclusions: The VelocityAI™-based method using fraction N CBCT is most similar to the reference plan using repeat CT; the other two methods had significant differences.

Impact of a parallel magnetic field on radiation dose beneath thin copper and aluminum foils.

PURPOSE: The RF coils for magnetic resonance image guided radiotherapy (MRIgRT) may be constructed using thin and/or low-density conductors, along with thinner enclosure materials. This work measures the surface dose increases for lightweight conductors and enclosure materials in a magnetic field parallel to a 6 MV photon beam. METHODS: Aluminum and copper foils (9-127 µm thick), as well as samples of polyimide (17 µm) and polyester (127 µm) films are positioned atop a polystyrene phantom. A parallel plate ion chamber embedded into the top of the phantom measures the surface dose in 6 MV photon beam. Measurements (% of dose at the depth of maximum dose) are performed with and without a parallel magnetic field (0.22T at magnet center). RESULTS: In the presence of a magnetic field, the unobstructed surface dose is higher (31.9%Dmax versus 22.2%Dmax). The surface dose is found to increase linearly with thickness for thin (<25 µm) copper (0.339%Dmax µm-1) and aluminum (0.116%Dmax µm-1) foils. In the presence of a magnetic field the slope is lower (copper: 0.16%Dmax µm-1, aluminum: 0.06%Dmax µm-1). The effect of in-beam foils is reduced due to partial shielding of the surface from contaminant electrons. Copper causes a surface dose increase ≈3 times higher than aluminum of the same thickness, consistent with their relative electron density. Polyester film (127µm) increases the surface dose (to 35% Dmax with field) about as much as a gown (36% Dmax with field), while the increase with polyimide film (17µm) is less than 1% above the open field dose. CONCLUSIONS: Thin copper and aluminum conductors increase surface dose by an amount comparable to a hospital gown. Similarly, enclosure materials made of thin polyester or polyimide film increase surface dose by only a few %Dmax in excess of an unobstructed beam. Based on measurements in this study, in-beam, surface RF coils are feasible for MRIgRT systems.

Technical Note: Sensitive volume effects on ion chamber responses in longitudinal magnetic fields.

PURPOSE: It has been shown that ion chamber dose response Monte Carlo simulations, in transverse magnetic fields, are susceptible to small changes in the scored sensitive volume. Changes in sensitive volumes have been investigated as a surrogate for modeling the true collection volume governed by the electric field. This work has not been fully extended to longitudinal fields. This study investigates the effect of the sensitive volume of ion chambers on magnetic field dose response within longitudinal magnetic fields. METHODS: The egs_chamber application within EGSnrc was used to model the Exradin A19, A28, and A1SL ion chambers within a uniform longitudinal magnetic field. The sensitive volume of the ion chambers was varied by removing portions of the air volume (from 0.2 to 3 mm) closest to the chamber stem from the dose scoring region; the dose to the scoring volume as a function of magnetic fields strength was normalized to 0 T in all cases. RESULTS: With the chamber long axis oriented parallel to the radiation and magnetic fields, for every magnetic field strength, all investigated chambers' dose response remained inside statistical variations for all investigated chamber sensitive volumes. When the chamber long axis is oriented perpendicular to the radiation and magnetic fields, the A28 and A1SL show negligible sensitive volume effects, while the A19 under responded by 0.5% for the largest removed volume of 3 mm. CONCLUSIONS: When the ion chambers' long axis is parallel to the radiation and magnetic fields, the magnetic field dose response is unaffected by small changes in sensitive volume. When oriented perpendicularly, only the A19 exhibits sensitive volume based magnetic field dose response changes, and only with ≥ 1 mm of assumed insensitive volume. We can therefore safely assume complete charge collection in Monte Carlo calculated correction factors involving similar chambers in similar conditions.

Technical Note: EPID's response to 6 MV photons in a strong, parallel magnetic field.

PURPOSE: Electronic portal imaging devices (EPIDs) are potentially useful for dosimetric verification in integrated MRI-linac systems. This work presents the reproducibility, linearity, image lag, and radiation field profiles in a conventional EPID, with and without a 0.5 T parallel magnetic field present in a 6 MV photon beam. METHODS: An aS500 EPID was modified to function in strong magnetic fields. All measurements were made using the linac-MR installed at the Cross Cancer Institute. The EPID remained stationary on the couch between the measurements made with and without magnetic field. We measured short-term reproducibility of dark and flood fields, signal linearity from 1 to 500 MU irradiations, and image lag post 100 MU irradiation. An ion chamber was used to measure any linac output variations to correct the EPID signal due to these variations for the duration of experiment. X-axis and Y-axis radiation field profiles were obtained from the EPID image resulting from a 10 × 10 cm2 radiation field delivery. RESULTS: The average pixel value (±standard deviation) of flood field with and without magnetic fields were 57,876 ± 379 and 57,703 ± 366, respectively, and the corresponding average dark field pixel values were -32.05 ± 0.85 and -32.19 ± 0.97. The maximum difference in image linearity data with and without magnetic field is 0.2% which is well within the measurement uncertainty of 0.65%. Similarly, the image lag curves, with and without the magnetic field, were nearly identical. The first measured point, with mean lag signal of 1.44% without and 1.41% with magnetic field, shows that the largest difference is well below the uncertainty in the EPID signal measurement. The radiation field profiles obtained with and without magnetic fields were nearly identical; 91.3% of the X-axis and 95.2% of the Y-axis profile points pass a gamma criterion of 1% and 1 mm. CONCLUSIONS: A conventional EPID imager with a 0.1 cm copper plate responds to 6 MV photons similarly irrespective of the strong magnetic field being off or on in the parallel orientation to the radiation beam. Thus, the EPID is a potentially useful tool for pretreatment dosimetric verification in linac-MR systems using parallel magnetic field.

Technical Note: Experimental verification of EGSnrc calculated depth dose within a parallel magnetic field in a lung phantom.

PURPOSE: The calculation of depth doses from a 6 MV photon beam in polystyrene using EGSnrc Monte Carlo, within a parallel magnetic field, has been previously verified against measured data. The current work experimentally investigates the accuracy of EGSnrc calculated depth doses in lung within the same parallel magnetic field. METHODS: Two cylindrical bore electromagnets produced a magnetic field parallel to the central axis of a Varian Silhouette beam. A Gammex lung phantom was used, along with a parallel plate ion chamber, for the depth dose measurements. Two experimental setups were investigated: top of phantom coinciding with the top of the magnet's bore, and top of phantom coinciding with the center of the bore. EGSnrc was modified to read the 3D magnetic field distribution and then used to simulate the depth dose in lung. RESULTS: The parallel magnetic field caused measurable increases in dose at the surface and in the buildup region for both setups. For the setup where the top of the lung phantom coincides with the top of the magnet, the surface dose increased by ~11% compared to the no magnetic field case but the depth of maximum dose remained unchanged. When the phantom's top surface coincided with the center of the magnet, the surface dose increased by 32% and dose maximum occurred at a shallower depth. EGSnrc was able to calculate these dose increases due to the magnetic field accurately for both setups. All the simulated depth dose values were within 2% (with respect to Dmax ) of the measured ones, and most of the investigated points were within 1.5%. CONCLUSIONS: Surface and dose increases due to a parallel magnetic field have been measured in a lung phantom at two separate locations within the magnetic field. EGSnrc has been shown to match these measurements to within 2%.

Evaluating performance of a user-trained MR lung tumor autocontouring algorithm in the context of intra- and interobserver variations.

PURPOSE: Real-time tracking of lung tumors using magnetic resonance imaging (MRI) has been proposed as a potential strategy to mitigate the ill-effects of breathing motion in radiation therapy. Several autocontouring methods have been evaluated against a "gold standard" of a single human expert user. However, contours drawn by experts have inherent intra- and interobserver variations. In this study, we aim to evaluate our user-trained autocontouring algorithm with manually drawn contours from multiple expert users, and to contextualize the accuracy of these autocontours within intra- and interobserver variations. METHODS: Six nonsmall cell lung cancer patients were recruited, with institutional ethics approval. Patients were imaged with a clinical 3 T Philips MR scanner using a dynamic 2D balanced SSFP sequence under free breathing. Three radiation oncology experts, each in two separate sessions, contoured 130 dynamic images for each patient. For autocontouring, the first 30 images were used for algorithm training, and the remaining 100 images were autocontoured and evaluated. Autocontours were compared against manual contours in terms of Dice's coefficient (DC) and Hausdorff distances (dH ). Intra- and interobserver variations of the manual contours were also evaluated. RESULTS: When compared with the manual contours of the expert user who trained it, the algorithm generates autocontours whose evaluation metrics (same session: DC = 0.90(0.03), dH  = 3.8(1.6) mm; different session DC = 0.88(0.04), dH  = 4.3(1.5) mm) are similar to or better than intraobserver variations (DC = 0.88(0.04), and dH  = 4.3(1.7) mm) between two sessions. The algorithm's autocontours are also compared to the manual contours from different expert users with evaluation metrics (DC = 0.87(0.04), dH  = 4.8(1.7) mm) similar to interobserver variations (DC = 0.87(0.04), dH  = 4.7(1.6) mm). CONCLUSIONS: Our autocontouring algorithm delineates tumor contours (<20 ms per contour), in dynamic MRI of lung, that are comparable to multiple human experts (several seconds per contour), but at a much faster speed. At the same time, the agreement between autocontours and manual contours is comparable to the intra- and interobserver variations. This algorithm may be a key component of the real time tumor tracking workflow for our hybrid Linac-MR device in the future.

Technical Note: Ion chamber angular dependence in a magnetic field.

PURPOSE: There have been several studies investigating dose deposition effects within radiation detectors in the presence of a magnetic field. However, to date there has only been a passing investigation which explicitly investigates detector dose-response as a function of detector orientation. Herein we will investigate the dose-response as a function angular orientation of a PR06C ionization chamber. We will also benchmark the Monte Carlo code PENELOPE with the newly developed magnetic field Fano test. METHODS: The PENELOPE Monte Carlo package was used to simulate a PR06C ionization chamber in 0.35 T through 1.5 T magnetic fields oriented either parallel or orthogonal to an incident 6 MV radiation beam. The ionization chamber was rotated through a number of polar and azimuthal angles. The dose deposited within the chamber at each angular position and magnetic field strength was scored then normalized to that deposited in the same orientation with no magnetic field. The simulation was also benchmarked via a Fano test in magnetic field. RESULTS: The Fano test yielded a 0.4% difference between simulation and expected result, which is similar to previous findings and sufficient for the purposes of this study. The angular dose-response map in all cases where the magnetic field is oriented orthogonal to the radiation beam is quite varied and can range from 0.89 to 1.08. Angular deviations as small as 3° can lead to dose-response changes in excess of 1%. When the magnetic field is parallel to the photon beam, the angular dose-response map is homogeneous and less than 1% below 1.0 T. CONCLUSIONS: Within a magnetic field-oriented orthogonal to the radiation beam, the ionization chamber dose-response fluctuates greatly as a function of polar and azimuthal angle, where a parallel field yields a more homogeneous dose-response.

Experimental verification of EGSnrc Monte Carlo calculated depth doses within a realistic parallel magnetic field in a polystyrene phantom.

PURPOSE: Integrating a linac with a magnetic resonance imager (MRI) will revolutionize the accuracy of external beam radiation treatments. Irradiating in the presence of a strong magnetic field, however, will modify the dose distribution. These dose modifications have been investigated previously, mainly using Monte Carlo simulations. The purpose of this work is to experimentally verify the use of the EGSnrc Monte Carlo (MC) package for calculating percent depth doses (PDDs) in a homogeneous phantom, in the presence of a realistic parallel magnetic field. METHODS: Two cylindrical electromagnets were used to produce a 0.207 T magnetic field parallel to the central axis of a 6 MV photon beam from a clinical linac. The magnetic field was measured at discrete points along orthogonal axes, and these measurements were used to validate a full 3D magnetic field map generated using COMSOL Multiphysics. Using a small parallel plate ion chamber, the depth dose was measured in a polystyrene phantom placed inside the electromagnet bore at two separate locations: phantom top surface coinciding with top of bore, and phantom top surface coinciding with center of bore. BEAMnrc MC was used to model the linac head which was benchmarked against the linac's commissioning measurements. The depth dose in polystyrene was simulated using DOSXYZnrc MC. For the magnetic field case, the DOSXYZnrc code was slightly modified to implement the previously calculated 3D magnetic field map to be used in the standard electromagnetic macros. RESULTS: The calculated magnetic field matched the measurements within 2% of the maximum central field (0.207 T) with most points within the experimental uncertainty (1.5%). For the MC linac head model, over 93% of all simulated points passed the 2%, 2 mm γ acceptance criterion, when comparing measured and simulated lateral beam and depth dose profiles. The parallel magnetic field caused a surface dose increase, compared to the no magnetic field case, due to the Lorentz force confining contaminant electrons within the beam. The surface dose increase was measured to be approximately 10% (relative to no field Dmax ) when the phantom surface coincided with the top of the electromagnet's bore. This effect was enhanced by moving the phantom surface to the center of the magnet's bore in relatively high magnetic field (> 0.13 T). The surface dose for this setup increased by 30% and the entire buildup region was affected. When the dimensions and composition of the ion chamber air cavity and entrance window were included, EGSnrc was able to accurately simulate these dose increases, both at the surface and in the buildup region. All the simulated points were within 1% of the measurements for both setups. The ferromagnetic linac head was determined to have a negligible effect on the final PDD comparison. CONCLUSIONS: Irradiating in the presence of a parallel magnetic field causes measurable surface and buildup depth dose increases. We have experimentally verified that the EGSnrc Monte Carlo package is able to accurately calculate the PDDs with these surface and buildup dose modifications in a homogeneous phantom.

Sliding window prior data assisted compressed sensing for MRI tracking of lung tumors.

PURPOSE: Hybrid magnetic resonance imaging and radiation therapy devices are capable of imaging in real-time to track intrafractional lung tumor motion during radiotherapy. Highly accelerated magnetic resonance (MR) imaging methods can potentially reduce system delay time and/or improves imaging spatial resolution, and provide flexibility in imaging parameters. Prior Data Assisted Compressed Sensing (PDACS) has previously been proposed as an acceleration method that combines the advantages of 2D compressed sensing and the KEYHOLE view-sharing technique. However, as PDACS relies on prior data acquired at the beginning of a dynamic imaging sequence, decline in image quality occurs for longer duration scans due to drifts in MR signal. Novel sliding window-based techniques for refreshing prior data are proposed as a solution to this problem. METHODS: MR acceleration is performed by retrospective removal of data from the fully sampled sets. Six patients with lung tumors are scanned with a clinical 3 T MRI using a balanced steady-state free precession (bSSFP) sequence for 3 min at approximately 4 frames per second, for a total of 650 dynamics. A series of distinct pseudo-random patterns of partial k-space acquisition is generated such that, when combined with other dynamics within a sliding window of 100 dynamics, covers the entire k-space. The prior data in the sliding window are continuously refreshed to reduce the impact of MR signal drifts. We intended to demonstrate two different ways to utilize the sliding window data: a simple averaging method and a navigator-based method. These two sliding window methods are quantitatively compared against the original PDACS method using three metrics: artifact power, centroid displacement error, and Dice's coefficient. The study is repeated with pseudo 0.5 T images by adding complex, normally distributed noise with a standard deviation that reduces image SNR, relative to original 3 T images, by a factor of 6. RESULTS: Without sliding window implemented, PDACS-reconstructed dynamic datasets showed progressive increases in image artifact power as the 3 min scan progresses. With sliding windows implemented, this increase in artifact power is eliminated. Near the end of a 3 min scan at 3 T SNR and 5× acceleration, implementation of an averaging (navigator) sliding window method improves our metrics by the following ways: artifact power decreases from 0.065 without sliding window to 0.030 (0.031), centroid error decreases from 2.64 to 1.41 mm (1.28 mm), and Dice coefficient agreement increases from 0.860 to 0.912 (0.915). At pseudo 0.5 T SNR, the improvements in metrics are as follows: artifact power decreases from 0.110 without sliding window to 0.0897 (0.0985), centroid error decreases from 2.92 mm to 1.36 mm (1.32 mm), and Dice coefficient agreements increases from 0.851 to 0.894 (0.896). CONCLUSIONS: In this work we demonstrated the negative impact of slow changes in MR signal for longer duration PDACS dynamic scans, namely increases in image artifact power and reductions of tumor tracking accuracy. We have also demonstrated sliding window implementations (i.e., refreshing of prior data) of PDACS are effective solutions to this problem at both 3 T and simulated 0.5 T bSSFP images.

Neural-network based autocontouring algorithm for intrafractional lung-tumor tracking using Linac-MR.

PURPOSE: To develop a neural-network based autocontouring algorithm for intrafractional lung-tumor tracking using Linac-MR and evaluate its performance with phantom and in-vivo MR images. METHODS: An autocontouring algorithm was developed to determine both the shape and position of a lung tumor from each intrafractional MR image. A pulse-coupled neural network was implemented in the algorithm for contrast improvement of the tumor region. Prior to treatment, to initiate the algorithm, an expert user needs to contour the tumor and its maximum anticipated range of motion in pretreatment MR images. During treatment, however, the algorithm processes each intrafractional MR image and automatically generates a tumor contour without further user input. The algorithm is designed to produce a tumor contour that is the most similar to the expert's manual one. To evaluate the autocontouring algorithm in the author's Linac-MR environment which utilizes a 0.5 T MRI, a motion phantom and four lung cancer patients were imaged with 3 T MRI during normal breathing, and the image noise was degraded to reflect the image noise at 0.5 T. Each of the pseudo-0.5 T images was autocontoured using the author's algorithm. In each test image, the Dice similarity index (DSI) and Hausdorff distance (HD) between the expert's manual contour and the algorithm generated contour were calculated, and their centroid positions were compared (Δd centroid). RESULTS: The algorithm successfully contoured the shape of a moving tumor from dynamic MR images acquired every 275 ms. From the phantom study, mean DSI of 0.95-0.96, mean HD of 2.61-2.82 mm, and mean Δd centroid of 0.68-0.93 mm were achieved. From the in-vivo study, the author's algorithm achieved mean DSI of 0.87-0.92, mean HD of 3.12-4.35 mm, as well as Δd centroid of 1.03-1.35 mm. Autocontouring speed was less than 20 ms for each image. CONCLUSIONS: The authors have developed and evaluated a lung tumor autocontouring algorithm for intrafractional tumor tracking using Linac-MR. The autocontouring performance in the Linac-MR environment was evaluated using phantom and in-vivo MR images. From the in-vivo study, the author's algorithm achieved 87%-92% of contouring agreement and centroid tracking accuracy of 1.03-1.35 mm. These results demonstrate the feasibility of lung tumor autocontouring in the author's laboratory's Linac-MR environment.

Prior data assisted compressed sensing: a novel MR imaging strategy for real time tracking of lung tumors.

PURPOSE: Hybrid radiotherapy-MRI devices promise real time tracking of moving tumors to focus the radiation portals to the tumor during irradiation. This approach will benefit from the increased temporal resolution of MRI's data acquisition and reconstruction. In this work, the authors propose a novel spatial-temporal compressed sensing (CS) imaging strategy for the real time MRI--prior data assisted compressed sensing (PDACS), which aims to improve the image quality of the conventional CS without significantly increasing reconstruction times. METHODS: Conventional 2D CS requires a random sampling of partial k-space data, as well as an iterative reconstruction that simultaneously enforces the image's sparsity in a transform domain as well as maintains the fidelity to the acquired k-space. PDACS method requires the additional acquisition of the prior data, and for reconstruction, it additionally enforces fidelity to the prior k-space domain similar to viewsharing. In this work, the authors evaluated the proposed PDACS method by comparing its results to those obtained from the 2D CS and viewsharing methods when performed individually. All three methods are used to reconstruct images from lung cancer patients whose tumors move and who are likely to benefit from lung tumor tracking. The patients are scanned, using a 3T MRI, under free breathing using the fully sampled k-space with 2D dynamic bSSFP sequence in a sagittal plane containing lung tumor. These images form a reference set for the evaluation of the partial k-space methods. To create partial k-space, the fully sampled k-space is retrospectively undersampled to obtain a range of acquisition acceleration factors, and reconstructed with 2D-CS, PDACS, and viewshare methods. For evaluation, metrics assessing global image artifacts as well as tumor contour shape fidelity are determined from the reconstructed images. These analyses are performed both for the original 3T images and those at a simulated 0.5T equivalent noise level. RESULTS: In the 3.0T images, the PDACS strategy is shown to give superior results compared to viewshare and conventional 2D CS using all metrics. The 2D-CS tends to perform better than viewshare at the low acceleration factors, while the opposite is true at the high acceleration factors. At simulated 0.5T images, PDACS method performs only marginally better than the viewsharing method, both of which are superior compared to 2D CS. The PDACS image reconstruction time (0.3 s/image) is similar to that of the conventional 2D CS. CONCLUSIONS: The PDACS method can potentially improve the real time tracking of moving tumors by significantly increasing MRI's data acquisition speeds. In 3T images, the PDACS method does provide a benefit over the other two methods in terms of both the overall image quality and the ability to accurately and automatically contour the tumor shape. MRI's data acquisition may be accelerated using the simpler viewsharing strategy at the lower, 0.5T magnetic field, as the marginal benefit of the PDACS method may not justify its additional reconstruction times.

Clinical evaluation of normalized metal artifact reduction in kVCT using MVCT prior images (MVCT-NMAR) for radiation therapy treatment planning.

PURPOSE: To evaluate the metal artifacts in diagnostic kilovoltage computed tomography (kVCT) images of patients that are corrected by use of a normalized metal artifact reduction (NMAR) method with megavoltage CT (MVCT) prior images: MVCT-NMAR. METHODS AND MATERIALS: MVCT-NMAR was applied to images from 5 patients: 3 with dual hip prostheses, 1 with a single hip prosthesis, and 1 with dental fillings. The corrected images were evaluated for visualization of tissue structures and their interfaces and for radiation therapy dose calculations. They were compared against the corresponding images corrected by the commercial orthopedic metal artifact reduction algorithm in a Phillips CT scanner. RESULTS: The use of MVCT images for correcting kVCT images in the MVCT-NMAR technique greatly reduces metal artifacts, avoids secondary artifacts, and makes patient images more useful for correct dose calculation in radiation therapy. These improvements are significant, provided the MVCT and kVCT images are correctly registered. The remaining and the secondary artifacts (soft tissue blurring, eroded bones, false bones or air pockets, CT number cupping within the metal) present in orthopedic metal artifact reduction corrected images are removed in the MVCT-NMAR corrected images. A large dose reduction was possible outside the planning target volume (eg, 59.2 Gy to 52.5 Gy in pubic bone) when these MVCT-NMAR corrected images were used in TomoTherapy treatment plans without directional blocks for a prostate cancer patient. CONCLUSIONS: The use of MVCT-NMAR corrected images in radiation therapy treatment planning could improve the treatment plan quality for patients with metallic implants.

Modulation factors calculated with an EPID-derived MLC fluence model to streamline IMRT/VMAT second checks.

This work outlines the development of a robust method of calculating modulation factors used for the independent verification of MUs for IMRT and VMAT treatments, to replace onerous ion chamber measurements. Two-dimensional fluence maps were calculated for dynamic MLC fields that include MLC interleaf leakage, transmission, and tongue-and-groove effects, as characterized from EPID-acquired images. Monte Carlo-generated dose kernels were then used to calculate doses for a modulated field and that field with the modulation removed at a depth specific to the calculation point in the patient using in-house written software, Mod_Calc. The ratio of these two doses was taken to calculate modulation factors. Comparison between Mod_Calc calculation and ion chamber measurement of modulation factors for 121 IMRT fields yielded excellent agreement, where the mean difference between the two was -0.3% ± 1.2%. This validated use of Mod_Calc clinically. Analysis of 5,271 dynamic fields from clinical use of Mod_Calc gave a mean difference of 0.3% ± 1.0% between Mod_Calc and Eclipse-generated factors. In addition, 99.3% and 96.5% fields pass 5% and 2% criteria, respectively, for agreement between these two predictions. The development and use of Mod_Calc at our clinic has considerably streamlined our QA process for IMRT and RapidArc fields, compared to our previous method based on ion chamber measurements. As a result, it has made it feasible to maintain our established and trusted current in-house method of MU verification, without resorting to commercial software alternatives.

First demonstration of intrafractional tumor-tracked irradiation using 2D phantom MR images on a prototype linac-MR.

PURPOSE: To demonstrate intrafractional MR tumor tracking using a prototype linac-MR by delivering radiation to a moving target undergoing simulated tumor motions. METHODS: A prototype linac-MR at the Cross Cancer Institute was used for intrafractional MR imaging and simultaneous beam delivery. A Varian 52-leaf MK-II multileaf collimator (MLC) was used for beam collimation. The authors used an inhouse built MR compatible motion phantom to simulate tumor motions during tracking with two different motion patterns (sine and modified cosine). Gafchromic film was inserted in the phantom to measure radiation exposure, and this film measurement was converted to dose (cGy) for further analysis. The authors demonstrated intrafractional tracking in various scenarios: [Scenario 0 (S0)] no phantom motion + no beam margin, (S1) no phantom motion + maximum beam margin, (S2) phantom motion + no beam margin, (S3) S2 + MLC tracking, and (S4) S3 + motion prediction. S0 emulates a perfect tumor tracking scenario, and its result was used as a "gold-standard" to evaluate tracking accuracy from other scenarios. The authors compared (1) time difference in phantom and MLC motion curves in S3 and S4, and (2) dose profiles (50% beam width, 80%-20% penumbra width) from scenarios S1-S4 to S0. RESULTS: In S4, no observable time difference exists between the phantom and MLC motion curves, indicating that MLC tracks phantom motion accurately. Comparing S4 to S0, 50% beam width reveals minimal differences of < 0.5 mm, while the increase in 80%-20% penumbra width is limited to 0.4 and 1.7 mm in the sine and modified cosine patterns, respectively. CONCLUSIONS: The authors report the first demonstration of intrafractional tumor tracking using 2D MR images. During 2 min of tracking, the authors delivered highly conformal dose to a moving target that simulates tumor motions. Compared to static target irradiation, the 50% beam width remains essentially the same (within 0.5 mm), with an increase in 80%-20% penumbra width of less than 1.7 mm in moving target irradiation. These results illustrate potential dosimetric advantages of intrafractional MR tumor tracking in treating mobile tumors as shown for the phantom case.

Effect of radiation induced current on the quality of MR images in an integrated linac-MR system.

PURPOSE: In integrated linac-MRI systems, the RF coils are exposed to the linac's pulsed radiation, leading to a measurable radiation induced current (RIC). This work (1) visualizes the RIC in MRI raw data and determines its effect on the MR image signal-to-noise ratio (SNR) (b) examines the effect of linac dose rate on SNR degradations, (c) examines the RIC effect on different MRI sequences, (d) examines the effect of altering the MRI sequence timing on the RIC, and (e) uses a postprocessing method to reduce the RIC signal from the MR raw data. METHODS: MR images were acquired on the linac-MR prototype system using various imaging sequences (gradient echo, spin echo, and bSSFP), dose rates (0, 50, 100, 150, 200, and 250 MU∕min) and repetition times (TR) with the gradient echo sequence. The images were acquired with the radiation beam either directly incident or blocked from the RF coils. The SNR was calculated for each of these scenarios, showing a loss in SNR due to RIC. Finally, a postprocessing method was applied to the image k-space data in order to remove partially the RIC signal and recover some of the lost SNR. RESULTS: The RIC produces visible spikes in the k-space data acquired with the linac's radiation incident on the RF coils. This RIC leads to a loss in imaging SNR that increases with increasing linac dose rate (15%-18% loss at 250 MU∕min). The SNR loss seen with increasing linac dose rate appears to be largely independent of the MR sequence used. Changing the imaging TR had interesting visual effects on the appearance of RIC in k-space due to the timing between the linac's pulsing and the MR sequence, but did not change the SNR loss for a given linac dose rate. The use of a postprocessing algorithm was able to remove much of the RIC noise spikes from the MR image k-space data, resulting in the recovery of a significant portion, up to 81% (Table II), of the lost image SNR. CONCLUSIONS: The presence of RIC in MR RF coils leads to a loss of SNR which is directly related to the linac dose rate. The RIC related loss in SNR is likely to increase for systems that are able to provide larger than 250 MU∕min dose. Some of this SNR loss can be recovered through the use of a postprocessing algorithm, which removes the RIC artefact from the image k-space.

Radiation induced current in the RF coils of integrated linac-MR systems: the effect of buildup and magnetic field.

PURPOSE: In integrated linac-MRI systems, a measurable radiation induced current (RIC) is caused in RF coils by pulsed irradiation. This work (1) tests a buildup method of RIC removal in planar conductors; (2) validates a Monte Carlo method of RIC calculation in metal conductors; and (3) uses the Monte Carlo method to examine the effects of magnetic fields on both planar conductor and practical cylindrical coil geometries. METHODS: The RIC was measured in copper and aluminum plates, taken as the RF coil conductor surrogates, as a function of increasing thickness of buildup materials (teflon and copper). Based on the Penelope Monte Carlo code, a method of RIC calculation was implemented and validated against measurements. This method was then used to calculate the RIC in cylindrical coil geometries with various air gaps between the coil conductor and the enclosed water phantom. Magnetic fields, both parallel and perpendicular to the radiation beam direction, were then included in the simulation program. The effect of magnetic fields on the effectiveness of RIC removal with the application of buildup material was examined in both the planar and the cylindrical geometries. RESULTS: Buildup reduced RIC in metal plate conductors. For copper detector∕copper buildup case, the RIC amplitude was reduced to zero value with 0.15 cm copper buildup. However, when the copper is replaced with teflon as buildup atop the copper conductor, the RIC was only reduced to 80% of its value at zero buildup since the true electronic equilibrium cannot be obtained in this case. For the aluminum detector∕teflon buildup case, the initial amplitude of the RIC was reduced by 90% and 92% in planar aluminum conductor and a surface coil, respectively. In case of cylindrical coils made of aluminum, teflon buildup around the coil's outer surface was generally effective but failed to remove RIC when there was an air gap between the coil and the phantom. Stronger magnetic fields (>0.5 T) perpendicular to the beam direction showed a modest decrease in the RIC for planar conductors with buildup. In the cylindrical geometries, the effect of magnetic fields was very small compared to the effect of introducing air gaps. Loss in signal-to-noise ratio (SNR) due to RIC was reduced from 11% to 5% when a simple buildup was applied to the solenoid in a preliminary experiment. CONCLUSIONS: The RIC in RF coils results from the lack of electronic equilibrium in the coil conductor as the RIC in planar conductor was completely removed by identical buildup of adequate thickness to create electronic equilibrium. The buildup method of RIC removal is effective in cylindrical coil geometry when the coil conductor is in direct contact with the patient. The presence of air makes this method of RIC removal less effective although placing buildup still reduces the RIC by up to 60%. The RIC Monte Carlo simulation is a useful tool for practical coil design where radiation effects must be considered. The SNR is improved in the images obtained concurrently withradiation if buildup is applied to the coil.

An artificial neural network (ANN)-based lung-tumor motion predictor for intrafractional MR tumor tracking.

PURPOSE: To address practical issues of implementing artificial neural networks (ANN) for lung-tumor motion prediction in MRI-based intrafractional lung-tumor tracking. METHODS: A feedforward four-layered ANN structure is used to predict future tumor positions. A back-propagation algorithm is used for ANN learning. Adaptive learning is incorporated by continuously updating weights and learning rate during prediction. An ANN training scheme specific for MRI-based tracking is developed. A multiple-ANN structure is developed to reduce tracking failures caused by the lower imaging rates of MRI. We used particle swarm optimization to optimize the ANN structure and initial weights (IW) for each patient and treatment fraction. Prediction accuracy is evaluated using the 1D superior-inferior lung-tumor motions of 29 lung cancer patients for system delays of 120-520 ms, in increments of 80 ms. The result is compared with four different scenarios: (1), (2) ANN structure optimization + with∕without IW optimization, and (3), (4) no ANN structure optimization + with∕without IW optimization, respectively. An additional simulation is performed to assess the value of optimizing the ANN structure for each treatment fraction. RESULTS: For 120-520 ms system delays, mean RMSE values (ranges 0.0-2.8 mm from 29 patients) of 0.5-0.9 mm are observed, respectively. Using patient specific ANN structures, a 30%-60% decrease in mean RMSE values is observed as a result of IW optimization, alone. No significant advantages in prediction performance are observed, however, by optimizing for each fraction. CONCLUSIONS: A new ANN-based lung-tumor motion predictor is developed for MRI-based intrafractional tumor tracking. The prediction accuracy of our predictor is evaluated using a realistic simulated MR imaging rate and system delays. For 120-520 ms system delays, mean RMSE values of 0.5-0.9 mm (ranges 0.0-2.8 mm from 29 patients) are achieved. Further, the advantage of patient specific ANN structure and IW in lung-tumor motion prediction is demonstrated by a 30%-60% decrease in mean RMSE values.

Evaluation of a lung tumor autocontouring algorithm for intrafractional tumor tracking using low-field MRI: a phantom study.

PURPOSE: The first aim of this study is to investigate the feasibility of online autocontouring of tumor in low field MR images (0.2 and 0.5 T) by means of a phantom and simulation study for tumor-tracking in linac-MR systems. The second aim of this study is to develop an MR compatible, lung tumor motion phantom. METHODS: An autocontouring algorithm was developed to determine both the position and shape of a lung tumor from each intra fractional MR image. To initiate the algorithm, an expert user contours the tumor and its maximum anticipated range of motion (herein termed the Background) using pretreatment scan data. During treatment, the algorithm processes each intrafractional MR image and automatically contours the tumor. To evaluate this algorithm, the authors built a phantom that replicates the low field contrast parameters (proton density, T(1), T(2)) of lung tumors and healthy lung parenchyma. This phantom allows simulation of MR images with the expected lung tumor CNR at 0.2 and 0.5 T by using a single 3 T scanner. Dynamic bSSFP images (approximately 4 images per second) are acquired while the phantom undergoes a series of preprogrammed motions based on patient lung tumor motion data. These images are autocontoured off-line using our algorithm. The fidelity of autocontouring is assessed by comparing autocontoured tumor shape and its centroid position to the actual tumor shape and its position. RESULTS: The algorithm successfully contoured the shape of a moving tumor model from dynamic MR images acquired every 275 ms. Dice's coefficients of > 0.96 and > 0.93 are achieved in 0.5 and 0.2 T equivalent images, respectively. Also, the algorithm tracked tumor position during dynamic studies, with root mean squared error (RMSE) values of < 0.55 and < 0.92 mm for 0.5 and 0.2 T equivalent images, respectively. Autocontouring speed is approximately 5 ms for each image. CONCLUSIONS: Dice's coefficients of > 0.96 and > 0.93 are achieved between autocontoured and real tumor shapes, and the position of a tumor can be tracked with RMSE values of < 0.55 and < 0.92 mm in 0.5 and 0.2 T equivalent images, respectively. These results demonstrate the feasibility of lung tumor autocontouring in low field MR images, and, by extension, intrafractional lung tumor tracking with our laboratory's linac-MR system.

Temporal lung tumor volume changes in small-cell lung cancer patients undergoing chemoradiotherapy.

PURPOSE: Small-cell lung cancer is considered to be relatively chemosensitive and radiosensitive. Small-cell tumor volume changes during concurrent chemoradiotherapy have not been quantified. The purpose of this work is to quantify small-cell lung tumor volume variations in limited-stage patients undergoing chemoradiotherapy. METHODS AND MATERIALS: Eligible patients had pathologically confirmed limited-stage small-cell lung cancer, underwent concurrent chemoradiotherapy, and signed study-specific consent forms. Patients underwent serial chest computed tomography (CT) scans on a CT simulator with images acquired at the same phase of patients' respiratory cycle. Computed tomography scans were obtained at the time of planning CT scan and 3 times a week during radiotherapy (RT). Gross tumor volumes (GTVs) were contoured on each CT scan. Gross tumor volumes defined on each CT scan were analyzed for volume changes relative to pre-RT scans. RESULTS: We obtained 104 CT scans (median, 11.5 scans per patient). The median tumor dose was 50 Gy. The median pre-RT GTV was 98.9 cm(3) (range, 57.8-412.4 cm(3)). The median GTV at the final serial CT scan was 10.0 cm(3) (range, 4.2-81.6 cm(3)). The mean GTV relative to pre-RT volume at the end of each RT week was 53.0% for Week 1, 29.8% for Week 2, 22.9% for Week 3, 19.5% for Week 4, and 12.4% for Week 5. CONCLUSIONS: Dramatic shrinkage of small-cell lung tumors occurred in patients undergoing chemoradiotherapy in this trial. Most of the observed GTV shrinkage occurred during the first week of RT.