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Register a new userQuantifying allowable motion to achieve safe dose escalation in pancreatic SBRT
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Tumor motion plays a key role in the safe delivery of Stereotactic Body Radiotherapy (SBRT) for pancreatic cancer. The purpose of this study was to use tumor motion data measured in patients to establish limits on motion magnitude for safe delivery of pancreatic SBRT. Using 91 sets of pancreatic tumor motion data measured in patients, we calculated motion-convolved dose for 25 pancreatic cancer patients, and established the maximum amount of motion allowable while satisfying error thresholds on key dose metrics. In our patient cohort, the mean [min-max] allowable motion for 33/40/50 Gy to the PTV was 11.9 [6.3-22.4], 10.4 [5.2-19.1] and 9.0 [4.2-16.0] mm, respectively. Maximum allowable motion decreased as dose was escalated, and was smaller in patients with larger tumors. The effects of motion on pancreatic SBRT are highly variable between patients and there is potential to allow more motion in certain patients, even in dose-escalated scenarios. In our dataset, a conservative limit of 6.3 mm would ensure safe treatment of all patients treated to 33 Gy in 5 fractions.
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Stereotactic body radiation therapy (SBRT) for pancreatic cancer requires a skillful approach to deliver ablative doses to the tumor while limiting dose to the highly sensitive duodenum, stomach, and small bowel. Here, we develop knowledge-based artificial neural network dose models (ANN-DMs) to predict dose distributions that would be approved by experienced physicians. Using dose distributions calculated by a commercial treatment planning system (TPS), physician-approved treatment plans were used to train ANN-DMs that could predict physician-approved dose distributions based on a set of geometric parameters (vary from voxel to voxel) and plan parameters (constant across all voxels for a given patient). Differences between TPS and ANN-DM dose distributions were used to evaluate model performance. ANN-DM design, including neural network structure and parameter choices, were evaluated to optimize dose model performance. Mean dose errors were less than 5% at all distances from the PTV, and mean absolute dose errors were on the order of 5%, but no more than 10%. Dose-volume histogram errors demonstrated good model performance above 25 Gy, but much larger errors were seen at lower doses. ANN-DM dose distributions showed excellent overall agreement with TPS dose distributions, and accuracy was substantially improved when each physicians treatment approach was taken into account by training their own dedicated models. In this manner, one could feasibly train ANN-DMs that could predict the dose distribution desired by a given physician for a given treatment site.
Dose painting of hypoxic tumour sub-volumes using positron-emission tomography (PET) has been shown to improve tumour control in silico in several sites. Pancreatic cancer presents a more stringent challenge, given its proximity to critical organs-at-risk (OARs) and anatomic motion. A radiobiological model was developed to estimate clonogen survival fraction (SF), using 18F-fluoroazomycin arabinoside PET (FAZA PET) images from ten patients with pancreatic cancer to quantify oxygen enhancement effects. For each patient, four simulated five-fraction stereotactic body radiotherapy (SBRT) plans were generated: 1) a standard SBRT plan aiming to cover the planning target volume with 40 Gy, 2) dose painting plans delivering escalated doses to FAZA-avid hypoxic sub-volumes, 3) dose painting plans with simulated spacer separating the duodenum and pancreatic head, and 4), plans with integrated boosts to geometric contractions of the tumour (GTV). All plans saturated at least one OAR dose limit. SF was calculated for each plan and sensitivity of SF to simulated hypoxia quantification errors was evaluated. Dose painting resulted in a 55% reduction in SF as compared to standard SBRT; 78% with spacer. Integrated boosts to hypoxia-blind geometric contractions resulted in a 41% reduction in SF. The reduction in SF for dose-painting plans persisted for all hypoxia quantification parameters studied, including registration and rigid motion errors that resulted in shifts and rotations of the GTV and hypoxic sub-volumes by as much as 1 cm and 10 degrees. Although proximity to OARs ultimately limited dose escalation, with estimated SFs (~10^-5) well above levels required to completely ablate a ~10 cm^3 tumour, dose painting robustly reduced clonogen survival when accounting for expected treatment and imaging uncertainties and thus, may improve local response and associated morbidity.
Fetal functional Magnetic Resonance Imaging (fMRI) has emerged as a powerful tool for investigating brain development in utero, holding promise for generating developmental disease biomarkers and supporting prenatal diagnosis. However, to date its clinical applications have been limited by unpredictable fetal and maternal motion during image acquisition. Even after spatial realigment, these cause spurious signal fluctuations confounding measures of functional connectivity and biasing statistical inference of relationships between connectivity and individual differences. As there is no ground truth for the brains functional structure, especially before birth, quantifying the quality of motion correction is challenging. In this paper, we propose evaluating the efficacy of different regression based methods for removing motion artifacts after realignment by assessing the residual relationship of functional connectivity with estimated motion, and with the distance between areas. Results demonstrate the sensitivity of our evaluations criteria to reveal the relative strengths and weaknesses among different artifact removal methods, and underscore the need for greater care when dealing with fetal motion.
This paper focuses on some dosimetry aspects of proton therapy and pencil beam scanning based on the experience accumulated at Paul Scherrer Institute(PSI). The basic formalism for absolute dosimetry in proton therapy is outlined and the two main techniques and equipment to perform the primary beam monitor chamber calibration are presented. Depth-dose curve and lateral beam width measurements are exposed and discussed in detail, with particular attention to the size of the ionization chamber and the characteristic of scintillating-CCD dosimetry systems, respectively. It is also explained how the angular-spatial distribution of individual pencil beams can be determined in practice. The equipment and the techniques for performing regularmachine-specific quality checks are focused on (i)output constancy checks, (ii)pencil beam position and size checks and (iii)beam energy checks. Finally, patient-specific verification is addressed.
A new variant of the pencil-beam (PB) algorithm for dose distribution calculation for radiotherapy with protons and heavier ions, the grid-dose spreading (GDS) algorithm, is proposed. The GDS algorithm is intrinsically faster than conventional PB algorithms due to approximations in convolution integral, where physical calculations are decoupled from simple grid-to-grid energy transfer. It was effortlessly implemented to a carbon-ion radiotherapy treatment planning system to enable realistic beam blurring in the field, which was absent with the broad-beam (BB) algorithm. For a typical prostate treatment, the slowing factor of the GDS algorithm relative to the BB algorithm was 1.4, which is a great improvement over the conventional PB algorithms with a typical slowing factor of several tens. The GDS algorithm is mathematically equivalent to the PB algorithm for horizontal and vertical coplanar beams commonly used in carbon-ion radiotherapy while dose deformation within the size of the pristine spread occurs for angled beams, which was within 3 mm for a single proton pencil beam of $30^circ$ incidence, and needs to be assessed against the clinical requirements and tolerances in practical situations.
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