Correlation of (18)F-FDG avid volumes on pre-radiation therapy and post-radiation therapy FDG PET scans in recurrent lung cancer

PURPOSE

To investigate the spatial correlation between high uptake regions of 2-deoxy-2-[(18)F]-fluoro-D-glucose positron emission tomography ((18)F-FDG PET) before and after therapy in recurrent lung cancer.

METHODS AND MATERIALS

We enrolled 106 patients with inoperable lung cancer into a prospective study whose primary objectives were to determine first, the earliest time point when the maximum decrease in FDG uptake representing the maximum metabolic response (MMR) is attainable and second, the optimum cutoff value of MMR based on its predicted tumor control probability, sensitivity, and specificity. Of those patients, 61 completed the required 4 serial (18)F-FDG PET examinations after therapy. Nineteen of 61 patients experienced local recurrence at the primary tumor and underwent analysis. The volumes of interest (VOI) on pretherapy FDG-PET were defined by use of an isocontour at ≥50% of maximum standard uptake value (SUVmax) (≥50% of SUVmax) with correction for heterogeneity. The VOI on posttherapy images were defined at ≥80% of SUVmax. The VOI of pretherapy and posttherapy (18)F-FDG PET images were correlated for the extent of overlap.

RESULTS

The size of VOI at pretherapy images was on average 25.7% (range, 8.8%-56.3%) of the pretherapy primary gross tumor volume (GTV), and their overlap fractions were 0.8 (95% confidence interval [CI]: 0.7-0.9), 0.63 (95% CI: 0.49-0.77), and 0.38 (95% CI: 0.19-0.57) of VOI of posttherapy FDG PET images at 10 days, 3 months, and 6 months, respectively. The residual uptake originated from the pretherapy VOI in 15 of 17 cases.

CONCLUSIONS

VOI defined by the SUVmax-≥50% isocontour may be a biological target volume for escalated radiation dose.

2D/4D marker-free tumor tracking using 4D CBCT as the reference image

Tumor motion caused by respiration is an important issue in image-guided radiotherapy. A 2D/4D matching method between 4D volumes derived from cone beam computed tomography (CBCT) and 2D fluoroscopic images was implemented to track the tumor motion without the use of implanted markers. In this method, firstly, 3DCBCT and phase-rebinned 4DCBCT are reconstructed from cone beam acquisition. Secondly, 4DCBCT volumes and a streak-free 3DCBCT volume are combined to improve the image quality of the digitally reconstructed radiographs (DRRs). Finally, the 2D/4D matching problem is converted into a 2D/2D matching between incoming projections and DRR images from each phase of the 4DCBCT. The diaphragm is used as a target surrogate for matching instead of using the tumor position directly. This relies on the assumption that if a patient has the same breathing phase and diaphragm position as the reference 4DCBCT, then the tumor position is the same. From the matching results, the phase information, diaphragm position and tumor position at the time of each incoming projection acquisition can be derived. The accuracy of this method was verified using 16 candidate datasets, representing lung and liver applications and one-minute and two-minute acquisitions. The criteria for the eligibility of datasets were described: 11 eligible datasets were selected to verify the accuracy of diaphragm tracking, and one eligible dataset was chosen to verify the accuracy of tumor tracking. The diaphragm matching accuracy was 1.88 ± 1.35 mm in the isocenter plane and the 2D tumor tracking accuracy was 2.13 ± 1.26 mm in the isocenter plane. These features make this method feasible for real-time marker-free tumor motion tracking purposes.

Hypofractionated proton therapy for prostate cancer: dose delivery uncertainty due to interfractional motion

PURPOSE

The α-to-β (α/β) ratio for prostate tumor is likely lower than that for the surrounding normal organs, such as rectum and bladder (≈ 3 Gy). As a result, hypofractionation is expected to improve the therapeutic ratio in prostate radiation therapy. However, with the use of fewer, larger fractions, the accuracy of treatment dose delivery becomes more influenced by the physical uncertainties resulting from motion and radiobiological uncertainties in the α/β ratio of the prostate tumor. The purpose of this study is to evaluate the impact of interfractional motion on treatment dose delivery within the likely range of the tumor α/β ratio.

METHODS

Serial CT images acquired at simulation and daily treatment for three prostate patients were studied retrospectively. A conventional 3D-conformal proton plan was created for each patient, delivering 25 fractions of 2 Gy to ITV1 (internal target volume, expanded from the prostate and clinically involved seminal vesicles) followed by 14 fractions to ITV2 (expanded from the prostate). The plans were renormalized for a series of hypofractionated protocols of between five and 28 fractions. The fractional doses were computed on daily CT and were mapped onto simulation CT using deformable registration. In each course, the doses from the fractions with the lowest D97% of the ITV2 were summed to approximate the lower limit (worst case) of target coverage. The uncertainty in dose and coverage was estimated as the deviation of the worst case from the nominal plan.

RESULTS

For treatments in 28 to five fractions, the uncertainty arising from interfractional motion ranged from ≈ 1% to 4% for V100% and ≈ 2% to 6% for D100% of the ITV2. The uncertainties in V95% and D95% were both minimal (<1%) for all protocols. For tumors with a low α/β of 1.0 Gy, the treatment in five fractions could deliver an additional 21.0 and 17.4 GyEQD2 to 95% and 100% of the ITV2, respectively, compared to that in 28 fractions. This advantage disappeared for tumors with α/β > 2.5 Gy, assuming the worst case for interfractional motion.

CONCLUSIONS

In hypofractionated proton therapy for prostate cancer, the dosimetric uncertainties due to interfractional motion were minimal for the ITV2 coverage at 95% isodose level and the dose received by 95% of the ITV2. Although hypofractionation could yield an increase in equivalent dose to the target for tumors with low α/β, the gain was cancelled out by the uncertainty due to interfractional motion for tumors with α/β > 2.5 Gy.

The distance discordance metric-a novel approach to quantifying spatial uncertainties in intra- and inter-patient deformable image registration

Previous methods to estimate the inherent accuracy of deformable image registration (DIR) have typically been performed relative to a known ground truth, such as tracking of anatomic landmarks or known deformations in a physical or virtual phantom. In this study, we propose a new approach to estimate the spatial geometric uncertainty of DIR using statistical sampling techniques that can be applied to the resulting deformation vector fields (DVFs) for a given registration. The proposed DIR performance metric, the distance discordance metric (DDM), is based on the variability in the distance between corresponding voxels from different images, which are co-registered to the same voxel at location (X) in an arbitrarily chosen 'reference' image. The DDM value, at location (X) in the reference image, represents the mean dispersion between voxels, when these images are registered to other images in the image set. The method requires at least four registered images to estimate the uncertainty of the DIRs, both for inter- and intra-patient DIR. To validate the proposed method, we generated an image set by deforming a software phantom with known DVFs. The registration error was computed at each voxel in the 'reference' phantom and then compared to DDM, inverse consistency error (ICE), and transitivity error (TE) over the entire phantom. The DDM showed a higher Pearson correlation (Rp) with the actual error (Rp ranged from 0.6 to 0.9) in comparison with ICE and TE (Rp ranged from 0.2 to 0.8). In the resulting spatial DDM map, regions with distinct intensity gradients had a lower discordance and therefore, less variability relative to regions with uniform intensity. Subsequently, we applied DDM for intra-patient DIR in an image set of ten longitudinal computed tomography (CT) scans of one prostate cancer patient and for inter-patient DIR in an image set of ten planning CT scans of different head and neck cancer patients. For both intra- and inter-patient DIR, the spatial DDM map showed large variation over the volume of interest (the pelvis for the prostate patient and the head for the head and neck patients). The highest discordance was observed in the soft tissues, such as the brain, bladder, and rectum, due to higher variability in the registration. The smallest DDM values were observed in the bony structures in the pelvis and the base of the skull. The proposed metric, DDM, provides a quantitative tool to evaluate the performance of DIR when a set of images is available. Therefore, DDM can be used to estimate and visualize the uncertainty of intra- and/or inter-patient DIR based on the variability of the registration rather than the absolute registration error.

Interplay effects in proton scanning for lung: a 4D Monte Carlo study assessing the impact of tumor and beam delivery parameters

Relative motion between a tumor and a scanning proton beam results in a degradation of the dose distribution (interplay effect). This study investigates the relationship between beam scanning parameters and the interplay effect, with the goal of finding parameters that minimize interplay. 4D Monte Carlo simulations of pencil beam scanning proton therapy treatments were performed using the 4DCT geometry of five lung cancer patients of varying tumor size (50.4-167.1 cc) and motion amplitude (2.9-30.1 mm). Treatments were planned assuming delivery in 35 × 2.5 Gy(RBE) fractions. The spot size, time to change the beam energy (τes), time required for magnet settling (τss), initial breathing phase, spot spacing, scanning direction, scanning speed, beam current and patient breathing period were varied for each of the five patients. Simulations were performed for a single fraction and an approximation of conventional fractionation. For the patients considered, the interplay effect could not be predicted using the superior-inferior motion amplitude alone. Larger spot sizes (σ ~ 9-16 mm) were less susceptible to interplay, giving an equivalent uniform dose (EUD) of 99.0 ± 4.4% (1 standard deviation) in a single fraction compared to 86.1 ± 13.1% for smaller spots (σ ~ 2-4 mm). The smaller spot sizes gave EUD values as low as 65.3% of the prescription dose in a single fraction. Reducing the spot spacing improved the target dose homogeneity. The initial breathing phase can have a significant effect on the interplay, particularly for shorter delivery times. No clear benefit was evident when scanning either parallel or perpendicular to the predominant axis of motion. Longer breathing periods decreased the EUD. In general, longer delivery times led to lower interplay effects. Conventional fractionation showed significant improvement in terms of interplay, giving a EUD of at least 84.7% and 100.0% of the prescription dose for the small and larger spot sizes respectively. The interplay effect is highly patient specific, depending on the motion amplitude, tumor location and the delivery parameters. Large degradations of the dose distribution in a single fraction were observed, but improved significantly using conventional fractionation.

Computer models to study uterine activation at labour

Improving our understanding of the initiation of labour is a major aim of modern obstetric research, in order to better diagnose and treat pregnant women in which the process occurs abnormally. In particular, increased knowledge will help us identify the mechanisms responsible for preterm labour, the single biggest cause of neonatal morbidity and mortality. Attempts to improve our understanding of the initiation of labour have been restricted by the inaccessibility of gestational tissues to study during pregnancy and at labour, and by the lack of fully informative animal models. However, computer modelling provides an exciting new approach to overcome these restrictions and offers new insights into uterine activation during term and preterm labour. Such models could be used to test hypotheses about drugs to treat or prevent preterm labour. With further development, an effective computer model could be used by healthcare practitioners to develop personalized medicine for patients on a pregnancy-by-pregnancy basis. Very promising work is already underway to build computer models of the physiology of uterine activation and contraction. These models aim to predict changes and patterns in uterine electrical excitation during term labour. There have been far fewer attempts to build computer models of the molecular pathways driving uterine activation and there is certainly scope for further work in this area. The integration of computer models of the physiological and molecular mechanisms that initiate labour will be particularly useful.

Contour-driven regression for label inference in atlas-based segmentation

We present a novel method for inferring tissue labels in atlas-based image segmentation using Gaussian process regression. Atlas-based segmentation results in probabilistic label maps that serve as input to our method. We introduce a contour-driven prior distribution over label maps to incorporate image features of the input scan into the label inference problem. The mean function of the Gaussian process posterior distribution yields the MAP estimate of the label map and is used in the subsequent voting. We demonstrate improved segmentation accuracy when our approach is combined with two different patch-based segmentation techniques. We focus on the segmentation of parotid glands in CT scans of patients with head and neck cancer, which is important for radiation therapy planning.

Numerical solutions of the γ-index in two and three dimensions

The γ-index is used routinely to establish correspondence between two dose distributions. The definition of the γ-index can be written with a single equation but solving this equation at millions of points is computationally expensive, especially in three dimensions. Our goal is to extend the vector-equation method in Bakai et al (2003 Phys. Med. Biol.48 3543-53) to higher order for better accuracy and, as important, to determine the magnitude of accuracy in a higher order solution. We construct a numerical framework for calculating the γ-index in two and three dimensions and present an efficient method for calculating the γ-index with zeroth-, first- and second-order methods using tricubic spline interpolation. For an intensity-modulated radiation therapy example with 1.78 × 10⁶ voxels, the zeroth-order, first-order, first-order iterations and semi-second-order methods calculate the three-dimensional γ-index in 1.5, 4.7, 34.7 and 35.6 s with 36.7%, 1.1%, 0.2% and 0.8% accuracy, respectively. The accuracy of linear interpolation with this example is 1.0%. We present efficient numerical methods for calculating the three-dimensional γ-index with tricubic spline interpolation. The first-order method with iterations is the most accurate and fastest choice of the numerical methods if the dose distributions may have large second-order gradients. Furthermore, the difference between iterations can be used to determine the accuracy of the method.

A voluntary breath-hold treatment technique for the left breast with unfavorable cardiac anatomy using surface imaging

PURPOSE

Breath-hold (BH) treatments can be used to reduce cardiac dose for patients with left-sided breast cancer and unfavorable cardiac anatomy. A surface imaging technique was developed for accurate patient setup and reproducible real-time BH positioning.

METHODS AND MATERIALS

Three-dimensional surface images were obtained for 20 patients. Surface imaging was used to correct the daily setup for each patient. Initial setup data were recorded for 443 fractions and were analyzed to assess random and systematic errors. Real time monitoring was used to verify surface placement during BH. The radiation beam was not turned on if the BH position difference was greater than 5 mm. Real-time surface data were analyzed for 2398 BHs and 363 treatment fractions. The mean and maximum differences were calculated. The percentage of BHs greater than tolerance was calculated.

RESULTS

The mean shifts for initial patient setup were 2.0 mm, 1.2 mm, and 0.3 mm in the vertical, longitudinal, and lateral directions, respectively. The mean 3-dimensional vector shift was 7.8 mm. Random and systematic errors were less than 4 mm. Real-time surface monitoring data indicated that 22% of the BHs were outside the 5-mm tolerance (range, 7%-41%), and there was a correlation with breast volume. The mean difference between the treated and reference BH positions was 2 mm in each direction. For out-of-tolerance BHs, the average difference in the BH position was 6.3 mm, and the average maximum difference was 8.8 mm.

CONCLUSIONS

Daily real-time surface imaging ensures accurate and reproducible positioning for BH treatment of left-sided breast cancer patients with unfavorable cardiac anatomy.

Ranking of stopping criteria for log domain diffeomorphic demons application in clinical radiation therapy

Deformable Image Registration is a complex optimization algorithm with the goal of modeling a non-rigid transformation between two images. A crucial issue in this field is guaranteeing the user a robust but computationally reasonable algorithm. We rank the performances of four stopping criteria and six stopping value computation strategies for a log domain deformable registration. The stopping criteria we test are: (a) velocity field update magnitude, (b) vector field Jacobian, (c) mean squared error, and (d) harmonic energy. Experiments demonstrate that comparing the metric value over the last three iterations with the metric minimum of between four and six previous iterations is a robust and appropriate strategy. The harmonic energy and vector field update magnitude metrics give the best results in terms of robustness and speed of convergence.

Centerline extraction with principal curve tracing to improve 3D level set esophagus segmentation in CT images

For radiotherapy planning, contouring of target volume and healthy structures at risk in CT volumes is essential. To automate this process, one of the available segmentation techniques can be used for many thoracic organs except the esophagus, which is very hard to segment due to low contrast. In this work we propose to initialize our previously introduced model based 3D level set esophagus segmentation method with a principal curve tracing (PCT) algorithm, which we adapted to solve the esophagus centerline detection problem. To address challenges due to low intensity contrast, we enhanced the PCT algorithm by learning spatial and intensity priors from a small set of annotated CT volumes. To locate the esophageal wall, the model based 3D level set algorithm including a shape model that represents the variance of esophagus wall around the estimated centerline is utilized. Our results show improvement in esophagus segmentation when initialized by PCT compared to our previous work, where an ad hoc centerline initialization was performed. Unlike previous approaches, this work does not need a very large set of annotated training images and has similar performance.

WE-E-213CD-02: Gaussian Weighted Multi-Atlas Based Segmentation for Head and Neck Radiotherapy Planning

PURPOSE

To develop a multi-atlas segmentation strategy for IMRT head and neck therapy planning.

METHODS

The method was tested on thirty-one head and neck simulation CTs, without demographic or pathology pre-clustering. We compare Fixed Number (FN) and Thresholding (TH) selection (based on normalized mutual information ranking) of the atlases to be included for current patient segmentation. Next step is a pairwise demons Deformable Registration (DR) onto current patient CT. DR was extended to automatically compensate for patient different field of view. Propagated labels are combined according to a Gaussian Weighted (GW) fusion rule, adapted to poor soft tissues contrast. Agreement with manual segmentation was quantified in terms of Dice Similarity Coefficient (DSC). Selection methods, number of atlases used, as well as GW, average and majority voting fusion were discriminated by means of Friedman Test (a=5%). Experimental tuning of the algorithm parameters was performed on five patients, deriving an optimal configuration for each structure.

RESULTS

DSC reduction was not significant when ten or more atlases are selected, whereas DSC for single most similar atlas selection is 10% lower in median. DSC of FN selection rule were significantly higher for most structures. Tubular structures may benefit from computing average contour rather than looking at the singular voxel contribution, whereas the best performing strategy for all other structures was GW. When half database is selected, final median DSC were 0.86, 0.80, 0.51, 0.81, 0.69 and 0.79 for mandible, spine, optical nerves, eyes, parotids and brainstem respectively.

CONCLUSION

We developed an efficient algorithm for multiatlas based segmentation of planning CT volumes, based on DR and GW. FN selection of database atlases is foreseen to increase computational efficiency. The absence of clinical pre-clustering and specific imaging protocol on database subjects makes the results closer to real clinical application. "Progetto Roberto Rocca" funded by the Fondazione Fratelli Agostino and Enrico Rocca, Italy.

Evaluation of registration methods on thoracic CT: the EMPIRE10 challenge

EMPIRE10 (Evaluation of Methods for Pulmonary Image REgistration 2010) is a public platform for fair and meaningful comparison of registration algorithms which are applied to a database of intrapatient thoracic CT image pairs. Evaluation of nonrigid registration techniques is a nontrivial task. This is compounded by the fact that researchers typically test only on their own data, which varies widely. For this reason, reliable assessment and comparison of different registration algorithms has been virtually impossible in the past. In this work we present the results of the launch phase of EMPIRE10, which comprised the comprehensive evaluation and comparison of 20 individual algorithms from leading academic and industrial research groups. All algorithms are applied to the same set of 30 thoracic CT pairs. Algorithm settings and parameters are chosen by researchers expert in the configuration of their own method and the evaluation is independent, using the same criteria for all participants. All results are published on the EMPIRE10 website (http://empire10.isi.uu.nl). The challenge remains ongoing and open to new participants. Full results from 24 algorithms have been published at the time of writing. This paper details the organization of the challenge, the data and evaluation methods and the outcome of the initial launch with 20 algorithms. The gain in knowledge and future work are discussed.

Evaluation of the dosimetric impact of interfractional anatomical variations on prostate proton therapy using daily in-room CT images

PURPOSE

To quantify interfractional anatomical variations and their dosimetric impact during the course of fractionated proton therapy (PT) of prostate cancer and to assess the robustness of the current treatment planning techniques.

METHODS

Simulation and daily in-room CT scans from ten prostate carcinoma patients were analyzed. PT treatment plans (78 Gy in 39 fractions of 2 Gy) were created on the simulation CT, delivering 25 fractions to PTV1 (expanded from prostate and seminal vesicles), followed by 14 boost fractions to PTV2 (expanded from prostate). Plans were subsequently applied to daily CT, with beams aligned to the prostate center in the sagittal plane. For five patients having a sufficiently large daily imaging volume, structure contours were manually drawn, and plans were evaluated for all CT sets. For the other five patients, the plans were evaluated for six selected fractions. The daily CT was matched to the simulation CT through deformable registration. The registration accuracy was validated for each fraction, and the three patients with a large number of accurately registered fractions were used for dose accumulation.

RESULTS

In individual fractions, the coverage of the prostate, seminal vesicles, and PTV1 was generally maintained at the corresponding prescription dose. For PTV2, the volume covered by the fractional prescription dose of 2 Gy (i.e., V2) was, on average, reduced by less than 3% compared to the simulation plan. Among the 225 (39 x 5 + 6 x 5) fractions examined, 15 showed a V2 reduction larger than 5%, of which ten were caused by a large variation in rectal gas, and five were due to a prostate shift in the craniocaudal direction. The fractional dose to the anterior rectal wall was found to increase for one patient who had large rectal gas volume in 25 of the 39 fractions, and another who experienced significant prostate volume reduction during the treatment. The fractional bladder dose generally increased with decreasing fullness. In the total accumulated dose for the three patients after excluding a few fractions with inaccurate registration due to a large amount of rectal gas (a condition inconsistent with RTOG protocol), 98.5%, 96.6%, and 98.2% of the PTV2 received the prescription dose of 78 Gy. The V75 and V70 of the anterior rectal wall and bladder both remained within tolerance.

CONCLUSIONS

The results confirm that the PT planning techniques and dose constraints used at our institution ensure that target coverage to the prescription dose is maintained in the presence of interfractional anatomical variations. Dose coverage in individual fractions can be compromised, and normal tissue dose increased, due to deviations in the bladder and rectal volume compared to the simulation plans or progressive changes in the prostate volume during the treatment. Deviations from the plan can be reduced with efforts aimed at maintaining consistent daily patient anatomy.

Evaluation and commissioning of a surface based system for respiratory sensing in 4D CT

The purpose of this study is to assess the temporal and reconstruction accuracy of a surface imaging system, the GateCT under ideal conditions, and compare the device with a commonly used respiratory surrogate: the Varian RPM. A clinical CT scanner, run in cine mode, was used with two optical devices, GateCT and RPM, to detect respiratory motion. A radiation detector, GM-10, triggers the X-ray on/off to GateCT system, while the RPM is directly synchronized with the CT scanner through an electronic connection. Two phantoms were imaged: the first phantom translated on a rigid plate along the anterior-posterior (AP) direction, and was used to assess the temporal synchronization of each optical system with the CT scanner. The second phantom, consisting of five spheres translating 3 cm peak-to-peak in the superior-inferior direction, was used to assess the quality of rebinned images created by GateCT and RPM. Calibration assessment showed a nearly perfect synchronization with the scanner for both the RPM and GateCT systems, thus demonstrating the good performance of the radiation detector. Results for the volume rebinning test showed discrepancies in volumes for the 3D reconstruction (compared to ground truth) of up to 36% for GateCT and up to 40% for RPM. No statistical difference was proven between the two systems in volume sorting. Errors are mainly due to phase detection inaccuracies and to the large motion of the phantom. This feasibility study assessed the consistency of two optical systems in synchronizing the respiratory signal with the image acquisition. A new patient protocol based on both RPM and GateCT will be soon started.

Locally Deformable Shape Model to Improve 3D Level Set based Esophagus Segmentation

In this paper we propose a supervised 3D segmentation algorithm to locate the esophagus in thoracic CT scans using a variational framework. To address challenges due to low contrast, several priors are learned from a training set of segmented images. Our algorithm first estimates the centerline based on a spatial model learned at a few manually marked anatomical reference points. Then an implicit shape model is learned by subtracting the centerline and applying PCA to these shapes. To allow local variations in the shapes, we propose to use nonlinear smooth local deformations. Finally, the esophageal wall is located within a 3D level set framework by optimizing a cost function including terms for appearance, the shape model, smoothness constraints and an air/contrast model.

In vivo proton beam range verification using spine MRI changes

PURPOSE

In proton therapy, uncertainty in the location of the distal dose edge can lead to cautious treatment plans that reduce the dosimetric advantage of protons. After radiation exposure, vertebral bone marrow undergoes fatty replacement that is visible on magnetic resonance imaging (MRI). This presents an exciting opportunity to observe radiation dose distribution in vivo. We used quantitative spine MRI changes to precisely detect the distal dose edge in proton radiation patients.

METHODS AND MATERIALS

We registered follow-up T1-weighted MRI images to planning computed tomography scans from 10 patients who received proton spine irradiation. A radiation dose-MRI signal intensity curve was created using the lateral beam penumbra in the sacrum. This curve was then used to measure range errors in the lumbar spine.

RESULTS

In the lateral penumbra, there was an increase in signal intensity with higher dose throughout the full range of 0-37.5 Gy (RBE). In the distal fall-off region, the beam sometimes appeared to penetrate farther than planned. The mean overshoot in 10 patients was 1.9 mm (95% confidence interval, 0.8-3.1 mm), on the order of the uncertainties inherent to our range verification method.

CONCLUSIONS

We have demonstrated in vivo proton range verification using posttreatment spine MRI changes. Our analysis suggests the presence of a systematic overshoot of a few millimeters in some proton spine treatments, but the range error does not exceed the uncertainty incorporated into the treatment planning margin. It may be possible to extend our technique to MRI sequences that show early bone marrow changes, enabling adaptive treatment modification.