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BackgroundPancreatic ductal adenocarcinoma has dismal prognosis. Most patients receive radiation therapy (RT), which is complicated by respiration induced organ motion in upper abdomen. The purpose of this study is to report our early clinical experience in a novel self-gated k-space sorted four-dimensional magnetic resonance imaging (4D-MRI) with slab-selective (SS) excitation to highlight tumor infiltrating blood vessels for pancreatic RT.MethodsTen consecutive patients with borderline resectable or locally advanced pancreatic cancer were recruited to the study. Non-contrast 4D-MRI with and without slab-selective excitation and 4D-CT with delay contrast were performed on all patients. Vessel-tissue CNR were calculated for aorta and critical vessels (superior mesenteric artery or superior mesenteric vein) encompassed by tumor. Respiratory motion trajectories for tumor, as well as involved vessels were analyzed on SS-4D-MRI. Intra-class cross correlation (ICC) between tumor volume and involved vessels were calculated.ResultsAmong all 4D imaging modalities evaluated, SS-4D-MRI sampling trajectory results in images with highest vessel-tissue CNR comparing to non-slab-selective 4D-MRI and 4D-CT for all patients studied. Average (±standard deviation) CNR for involved vessels are 13.1 ± 8.4 and 3.2 ± 2.7 for SS-4D-MRI and 4D-CT, respectively. The ICC factors comparing tumor and involved vessels motion trajectories are 0.93 ± 0.10, 0.65 ± 0.31 and 0.77 ± 0.23 for superior-inferior, anterior-posterior and medial-lateral directions respectively.ConclusionsA novel 4D-MRI sequence based on 3D-radial sampling and slab-selective excitation has been assessed for pancreatic cancer patients. The non-contrast 4D-MRI images showed significantly better contrast to noise ratio for the vessels that limit tumor resectability compared to 4D-CT with delayed contrast. The sequence has great potential in accurately defining both the tumor and boost volume margins for pancreas RT with simult

PurposeTo quantify and elucidate factors affecting error sensitivity in current IMRT QA comparisons performed with the gamma comparison, to investigate causes for gamma comparison insensitivity, and to utilize these results to develop and validate a new method for analyzing IMRT QA dose distributions in the clinic. MethodsOver 20,000 gamma comparisons were performed for three detector geometries – ArcCHECK, MapCHECK, and Delta 4 – for a variety of IMRT and VMAT cases in the presence of induced errors. Differences in error sensitivity for each device geometry and delivery technique were studied with the use of 1mm vs. 1mm calculation-only comparisons and in-house MATLAB gamma comparison software developed specifically for this project. Additionally, the effects of spatial sampling for each device were evaluated using gamma comparisons performed at the true spatial sampling of each detector compared to those at 1mm. Patterns of gamma failures were also investigated in the presence of induced errors of increasing magnitude. Results from these gamma comparisons were considered in developing a new comparison technique for IMRT QA analysis. A new analysis method that segments the IMRT QA comparisons by different dose and gradient thresholds was developed with the use of known induced errors in a calculation-only scenario for the ArcCHECK, MapCHECK, and Delta 4 measurement geometries. Results from the new method were validated for a separate cohort of patient plans, as well as with the use of real plan measurements with and without intentional errors on the MapCHECK device. ResultsDifferences in gamma comparison error sensitivity were observed for the ArcCHECK, MapCHECK, and Delta 4 geometries when removing the effects of different spatial sampling for each device. While sensitivity was error type-specific for most studied gamma criteria, a gamma criterion with a 10% low dose threshold and local dose difference normalization appeared to offer similar sensitivity across the

PurposeTo quantify and elucidate factors affecting error sensitivity in current IMRT QA comparisons performed with the gamma comparison, to investigate causes for gamma comparison insensitivity, and to utilize these results to develop and validate a new method for analyzing IMRT QA dose distributions in the clinic. MethodsOver 20,000 gamma comparisons were performed for three detector geometries – ArcCHECK, MapCHECK, and Delta 4 – for a variety of IMRT and VMAT cases in the presence of induced errors. Differences in error sensitivity for each device geometry and delivery technique were studied with the use of 1mm vs. 1mm calculation-only comparisons and in-house MATLAB gamma comparison software developed specifically for this project. Additionally, the effects of spatial sampling for each device were evaluated using gamma comparisons performed at the true spatial sampling of each detector compared to those at 1mm. Patterns of gamma failures were also investigated in the presence of induced errors of increasing magnitude. Results from these gamma comparisons were considered in developing a new comparison technique for IMRT QA analysis. A new analysis method that segments the IMRT QA comparisons by different dose and gradient thresholds was developed with the use of known induced errors in a calculation-only scenario for the ArcCHECK, MapCHECK, and Delta 4 measurement geometries. Results from the new method were validated for a separate cohort of patient plans, as well as with the use of real plan measurements with and without intentional errors on the MapCHECK device. ResultsDifferences in gamma comparison error sensitivity were observed for the ArcCHECK, MapCHECK, and Delta 4 geometries when removing the effects of different spatial sampling for each device. While sensitivity was error type-specific for most studied gamma criteria, a gamma criterion with a 10% low dose threshold and local dose difference normalization appeared to offer similar sensitivity across the

BackgroundPancreatic ductal adenocarcinoma has dismal prognosis. Most patients receive radiation therapy (RT), which is complicated by respiration induced organ motion in upper abdomen. The purpose of this study is to report our early clinical experience in a novel self-gated k-space sorted four-dimensional magnetic resonance imaging (4D-MRI) with slab-selective (SS) excitation to highlight tumor infiltrating blood vessels for pancreatic RT.MethodsTen consecutive patients with borderline resectable or locally advanced pancreatic cancer were recruited to the study. Non-contrast 4D-MRI with and without slab-selective excitation and 4D-CT with delay contrast were performed on all patients. Vessel-tissue CNR were calculated for aorta and critical vessels (superior mesenteric artery or superior mesenteric vein) encompassed by tumor. Respiratory motion trajectories for tumor, as well as involved vessels were analyzed on SS-4D-MRI. Intra-class cross correlation (ICC) between tumor volume and involved vessels were calculated.ResultsAmong all 4D imaging modalities evaluated, SS-4D-MRI sampling trajectory results in images with highest vessel-tissue CNR comparing to non-slab-selective 4D-MRI and 4D-CT for all patients studied. Average (±standard deviation) CNR for involved vessels are 13.1 ± 8.4 and 3.2 ± 2.7 for SS-4D-MRI and 4D-CT, respectively. The ICC factors comparing tumor and involved vessels motion trajectories are 0.93 ± 0.10, 0.65 ± 0.31 and 0.77 ± 0.23 for superior-inferior, anterior-posterior and medial-lateral directions respectively.ConclusionsA novel 4D-MRI sequence based on 3D-radial sampling and slab-selective excitation has been assessed for pancreatic cancer patients. The non-contrast 4D-MRI images showed significantly better contrast to noise ratio for the vessels that limit tumor resectability compared to 4D-CT with delayed contrast. The sequence has great potential in accurately defining both the tumor and boost volume margins for pancreas RT with simult

BackgroundTo stratify risks of pancreatic adenocarcinoma (PA) patients using pre- and post-radiotherapy (RT) PET/CT images, and to assess the prognostic value of texture variations in predicting therapy response of patients.MethodsTwenty-six PA patients treated with RT from 2011-2013 with pre- and post-treatment 18F-FDG-PET/CT scans were identified. Tumor locoregional texture was calculated using 3D kernel-based approach, and texture variations were identified by fitting discrepancies of texture maps of pre- and post-treatment images. A total of 48 texture and clinical variables were identified and evaluated for association with overall survival (OS). The prognostic heterogeneity features were selected using lasso/elastic net regression, and further were evaluated by multivariate Cox analysis.ResultsMedian age was 69 y (range, 46-86 y). The texture map and temporal variations between pre- and post-treatment were well characterized by histograms and statistical fitting. The lasso analysis identified seven predictors (age, node stage, post-RT SUVmax, variations of homogeneity, variance, sum mean, and cluster tendency). The multivariate Cox analysis identified five significant variables: age, node stage, variations of homogeneity, variance, and cluster tendency (with P=0.020, 0.040, 0.065, 0.078, and 0.081, respectively). The patients were stratified into two groups based on the risk score of multivariate analysis with log-rank P=0.001: a low risk group (n=11) with a longer mean OS (29.3 months) and higher texture variation (>30%), and a high risk group (n=15) with a shorter mean OS (17.7 months) and lower texture variation (<15%).ConclusionsLocoregional metabolic texture response provides a feasible approach for evaluating and predicting clinical outcomes following treatment of PA with RT. The proposed method can be used to stratify patient risk and help select appropriate treatment strategies for individual patients toward implementing response-driven adaptive

PurposeTo develop a four-dimensional MRI (4D-MRI) technique to characterize the average respiratory tumor motion for abdominal radiotherapy planning.MethodsA continuous spoiled gradient echo sequence was implemented with 3D radial trajectory and 1D self-gating for respiratory motion detection. Data were retrospectively sorted into different respiratory phases based on their temporal locations within a respiratory cycle, and each phase was reconstructed by means of a self-calibrating CG-SENSE program. Motion phantom, healthy volunteer and patient studies were performed to validate the respiratory motion detected by the proposed method against that from a 2D real-time protocol.ResultsThe proposed method successfully visualized the respiratory motion in phantom and human subjects. The 4D-MRI and real-time 2D-MRI yielded comparable superior-inferior (SI) motion amplitudes (intraclass correlation = 0.935) with up-to one pixel mean absolute differences in SI displacements over 10 phases and high cross-correlation between phase-resolved displacements (phantom: 0.985; human: 0.937-0.985). Comparable anterior-posterior and left-right displacements of the tumor or gold fiducial between 4D and real-time 2D-MRI were also observed in the two patients, and the hysteresis effect was shown in their 3D trajectories.ConclusionWe demonstrated the feasibility of the proposed 4D-MRI technique to characterize abdominal respiratory motion, which may provide valuable information for radiotherapy planning.

The increasing complexity of modern radiation therapy planning and delivery challenges traditional prescriptive quality management (QM) methods, such as many of those included in guidelines published by organizations such as the AAPM, ASTRO, ACR, ESTRO, and IAEA. These prescriptive guidelines have traditionally focused on monitoring all aspects of the functional performance of radiotherapy (RT) equipment by comparing parameters against tolerances set at strict but achievable values. Many errors that occur in radiation oncology are not due to failures in devices and software; rather they are failures in workflow and process. A systematic understanding of the likelihood and clinical impact of possible failures throughout a course of radiotherapy is needed to direct limit QM resources efficiently to produce maximum safety and quality of patient care. Task Group 100 of the AAPM has taken a broad view of these issues and has developed a framework for designing QM activities, based on estimates of the probability of identified failures and their clinical outcome through the RT planning and delivery process. The Task Group has chosen a specific radiotherapy process required for "intensity modulated radiation therapy (IMRT)" as a case study. The goal of this work is to apply modern risk-based analysis techniques to this complex RT process in order to demonstrate to the RT community that such techniques may help identify more effective and efficient ways to enhance the safety and quality of our treatment processes. The task group generated by consensus an example quality management program strategy for the IMRT process performed at the institution of one of the authors. This report describes the methodology and nomenclature developed, presents the process maps, FMEAs, fault trees, and QM programs developed, and makes suggestions on how this information could be used in the clinic. The development and implementation of risk-assessment techniques will make radiation therapy sa

PurposeMRI is increasingly being used for radiotherapy planning, simulation, and in-treatment-room motion monitoring. To provide more detailed temporal and spatial MR data for these tasks, we have recently developed a novel self-gated (SG) MRI technique with advantage of k-space phase sorting, high isotropic spatial resolution, and high temporal resolution. The current work describes the validation of this 4D-MRI technique using a MRI- and CT-compatible respiratory motion phantom and comparison to 4D-CT.MethodsThe 4D-MRI sequence is based on a spoiled gradient echo-based 3D projection reconstruction sequence with self-gating for 4D-MRI at 3 T. Respiratory phase is resolved by using SG k-space lines as the motion surrogate. 4D-MRI images are reconstructed into ten temporal bins with spatial resolution 1.56 × 1.56 × 1.56 mm(3). A MRI-CT compatible phantom was designed to validate the performance of the 4D-MRI sequence and 4D-CT imaging. A spherical target (diameter 23 mm, volume 6.37 ml) filled with high-concentration gadolinium (Gd) gel is embedded into a plastic box (35 × 40 × 63 mm(3)) and stabilized with low-concentration Gd gel. The phantom, driven by an air pump, is able to produce human-type breathing patterns between 4 and 30 respiratory cycles/min. 4D-CT of the phantom has been acquired in cine mode, and reconstructed into ten phases with slice thickness 1.25 mm. The 4D images sets were imported into a treatment planning software for target contouring. The geometrical accuracy of the 4D MRI and CT images has been quantified using target volume, flattening, and eccentricity. The target motion was measured by tracking the centroids of the spheres in each individual phase. Motion ground-truth was obtained from input signals and real-time video recordings.ResultsThe dynamic phantom has been operated in four respiratory rate (RR) settings, 6, 10, 15, and 20/min, and was scanned with 4D-MRI and 4D-CT. 4D-CT images have target-stretching, partial-missing, and other

PurposeTo apply a novel self-gating k-space sorted 4-dimensional MRI (SG-KS-4D-MRI) method to overcome limitations due to anisotropic resolution and rebinning artifacts and to monitor pancreatic tumor motion.Methods and materialsTen patients were imaged using 4D-CT, cine 2-dimensional MRI (2D-MRI), and the SG-KS-4D-MRI, which is a spoiled gradient recalled echo sequence with 3-dimensional radial-sampling k-space projections and 1-dimensional projection-based self-gating. Tumor volumes were defined on all phases in both 4D-MRI and 4D-CT and then compared.ResultsAn isotropic resolution of 1.56 mm was achieved in the SG-KS-4D-MRI images, which showed superior soft-tissue contrast to 4D-CT and appeared to be free of stitching artifacts. The tumor motion trajectory cross-correlations (mean ± SD) between SG-KS-4D-MRI and cine 2D-MRI in superior-inferior, anterior-posterior, and medial-lateral directions were 0.93 ± 0.03, 0.83 ± 0.10, and 0.74 ± 0.18, respectively. The tumor motion trajectories cross-correlations between SG-KS-4D-MRI and 4D-CT in superior-inferior, anterior-posterior, and medial-lateral directions were 0.91 ± 0.06, 0.72 ± 0.16, and 0.44 ± 0.24, respectively. The average standard deviation of gross tumor volume calculated from the 10 breathing phases was 0.81 cm(3) and 1.02 cm(3) for SG-KS-4D-MRI and 4D-CT, respectively (P=.012).ConclusionsA novel SG-KS-4D-MRI acquisition method capable of reconstructing rebinning artifact-free, high-resolution 4D-MRI images was used to quantify pancreas tumor motion. The resultant pancreatic tumor motion trajectories agreed well with 2D-cine-MRI and 4D-CT. The pancreatic tumor volumes shown in the different phases for the SG-KS-4D-MRI were statistically significantly more consistent than those in the 4D-CT.

PurposeTo evaluate use of breath-hold CTs and implanted fiducials for definition of the internal target volume (ITV) margin for upper abdominal stereotactic body radiation therapy (SBRT). To study the statistics of inter- and intra-fractional motion information.Methods and materials11 patients treated with SBRT for locally advanced pancreatic cancer (LAPC) or liver cancer were included in the study. Patients underwent fiducial implantation, free-breathing CT and breath-hold CTs at end inhalation/exhalation. All patients were planned and treated with SBRT using volumetric modulated arc therapy (VMAT). Two margin strategies were studied: Strategy I uses PTV = ITV + 3 mm; Strategy II uses PTV = GTV + 1.5 cm. Both CBCT and kV orthogonal images were taken and analyzed for setup before patient treatments. Tumor motion statistics based on skeletal registration and on fiducial registration were analyzed by fitting to Gaussian functions.ResultsAll 11 patients met SBRT planning dose constraints using strategy I. Average ITV margins for the 11 patients were 2 mm RL, 6 mm AP, and 6 mm SI. Skeletal registration resulted in high probability (RL = 69%, AP = 4.6%, SI = 39%) that part of the tumor will be outside the ITV. With the 3 mm ITV expansion (Strategy 1), the probability reduced to RL 32%, AP 0.3%, SI 20% for skeletal registration; and RL 1.2%, AP 0%, SI 7% for fiducial registration. All 7 pancreatic patients and 2 liver patients failed to meet SBRT dose constraints using strategy II. The liver dose was increased by 36% for the other 2 liver patients that met the SBRT dose constraints with strategy II.ConclusionsImage guidance matching to skeletal anatomy is inadequate for SBRT positioning in the upper abdomen and usage of fiducials is highly recommended. Even with fiducial implantation and definition of an ITV, a minimal 3 mm planning margin around the ITV is needed to accommodate intra-fractional uncertainties.

Optimization problems in IMRT inverse planning are inherently multicriterial since they involve multiple planning goals for targets and their neighbouring critical tissue structures. Clinical decisions are generally required, based on tradeoffs among these goals. Since the tradeoffs cannot be quantitatively determined prior to optimization, the decision-making process is usually indirect and iterative, requiring many repetitive optimizations. This situation becomes even more challenging for cases with a large number of planning goals. To address this challenge, a multicriteria optimization strategy called lexicographic ordering (LO) has been implemented and evaluated for IMRT planning. The LO approach is a hierarchical method in which the planning goals are categorized into different priority levels and a sequence of sub-optimization problems is solved in order of priority. This prioritization concept is demonstrated using two clinical cases (a simple prostate case and a relatively complex head and neck case). In addition, a unique feature of LO in a decision support role is discussed. We demonstrate that a comprehensive list of planning goals (e.g., ∼23 for the head and neck case) can be optimized using only a few priority levels. Tradeoffs between different levels have been successfully prohibited using the LO method, making the large size problem representations simpler and more manageable. Optimization time needed for each level was practical, ranging from ∼26 s to ∼217 s. Using prioritization, the LO approach mimics the mental process often used by physicians as they make decisions handling the various conflicting planning goals. This method produces encouraging results for difficult IMRT planning cases in a highly intuitive manner.

In this study, we show that beam model differences play an important role in the comparison of dose calculated with various algorithms for lung cancer treatment planning. These differences may impact the accurate correlation of dose with clinical outcome. To accomplish this, we modified the beam model penumbral parameters in an equivalent path length (EPL) algorithm and subsequently compared the EPL doses with those generated with Monte Carlo (MC). A single AP beam was used for beam fitting. Two different beam models were generated for EPL calculations: (1) initial beam model (init_fit) and (2) optimized beam model (best_fit), with parameters optimized to produce the best agreement with MC calculated profiles at several depths in a water phantom. For the 6 MV, AP beam, EPL(init_fit) calculations were on average within 2%/2 mm (1.4 mm max.) agreement with MC; the agreement for EPL(best_fit) was 2%/0.5 mm (1.0 mm max.). For the 15 MV, AP beam, average agreements with MC were 5%/2 mm (7.4%/2.6 mm max.) for EPL(init_fit) and 2%/1.0 mm (1.3 mm max.) for EPL(best_fit). Treatment planning was performed using a realistic lung phantom using 6 and 15 MV photons. In all homogeneous phantom plans, EPL(best_fit) calculations were in better agreement with MC. In the heterogeneous 6 MV plan, differences between EPL(best_fit and init_fit) and MC were significant for the tumour. The EPL(init_fit), unlike the EPL(best_fit) calculation, showed large differences in the lung relative to MC. For the 15 MV heterogeneous plan, clinically important differences were found between EPL(best_fit or init_fit) and MC for tumour and lung, suggesting that the algorithmic difference in inhomogeneous tissues was most influential in this case. Finally, an example is presented for a 6 MV conformal clinical treatment plan. In both homogeneous and heterogeneous cases, differences between EPL(best_fit) and MC for lung tissues were smaller compared to those between EPL(init_fit) and MC. Although the extent

Monte Carlo studies have recently renewed interest in the use of the effect of strong transverse and longitudinal magnetic fields to manipulate the dose characteristics of clinical photon and electron beams. A 3.5??T superconducting solenoidal magnet was used to evaluate the effect of a longitudinal field on both photon and electron beams. This note describes the apparatus and demonstrates some of the effects on the beam trajectory and dose distributions for measurements in a homogeneous phantom. The effects were studied using film in air and in phantoms which fit in the magnet bore. The magnetic field focused and collimated the electron beams. The converging, non-uniform field confined the beam and caused it to converge with increasing depth in the phantom. Due to the field's collecting and focusing effect, the beam flux density increased, leading to increased dose deposition near the magnetic axis, especially near the surface of the phantom. This study illustrates some benefits and challenges associated with the use of non-uniform longitudinal magnetic fields in conjunction with clinical electron and photon beams.

A comprehensive set of measurements and calculations has been conducted to investigate the accuracy of the Dose Planning Method (DPM) Monte Carlo code for electron beam dose calculations in heterogeneous media. Measurements were made using 10 MeV and 50 MeV minimally scattered, uncollimated electron beams from a racetrack microtron. Source distributions for the Monte Carlo calculations were reconstructed from in-air ion chamber scans and then benchmarked against measurements in a homogeneous water phantom. The in-air spatial distributions were found to have FWHM of 4.7 cm and 1.3 cm, at 100 cm from the source, for the 10 MeV and 50 MeV beams respectively. Energy spectra for the electron beams were determined by simulating the components of the microtron treatment head using the code MCNP4B. Profile measurements were made using an ion chamber in a water phantom with slabs of lung or bone-equivalent materials submerged at various depths. DPM calculations are, on average, within 2% agreement with measurement for all geometries except for the 50 MeV incident on a 6 cm lung-equivalent slab. Measurements using approximately monoenergetic, 50 MeV, ‘pencil-beam’-type electrons in heterogeneous media provide conditions for maximum electronic disequilibrium and hence present a stringent test of the code's electron transport physics; the agreement noted between calculation and measurement illustrates that the DPM code is capable of accurate dose calculation even under such conditions.

We present the creation and use of a generalized cost function methodology based on costlets for automated optimization for conformal and intensity modulated radiotherapy treatment plans. In our approach, cost functions are created by combining clinically relevant???costlets???. Each costlet is created by the user, using an???evaluator??? of the plan or dose distribution which is incorporated into a function or???modifier??? to create an individual costlet. Dose statistics, dose-volume points, biological model results, non-dosimetric parameters, and any other information can be converted into a costlet. A wide variety of different types of costlets can be used concurrently. Individual costlet changes affect not only the results for that structure, but also all the other structures in the plan (e.g., a change in a normal tissue costlet can have large effects on target volume results as well as the normal tissue). Effective cost functions can be created from combinations of dose-based costlets, dose-volume costlets, biological model costlets, and other parameters. Generalized cost functions based on costlets have been demonstrated, and show potential for allowing input of numerous clinical issues into the optimization process, thereby helping to achieve clinically useful optimized plans. In this paper, we describe and illustrate the use of the costlets in an automated planning system developed and used clinically at the University of Michigan Medical Center. We place particular emphasis on the flexibility of the system, and its ability to discover a variety of plans making various trade-offs between clinical goals of the treatment that may be difficult to meet simultaneously.