Use Of Deformable Image Registration Research Articles

Validation of a deformable image registration produced by a commercial treatment planning system in head and neck

In recent years one of the areas of interest in radiotherapy has been adaptive radiation therapy (ART), with the most efficient way of performing ART being the use of deformable image registration (DIR). In this paper we use the distances between points of interest (POIs) in the computed tomography (CT) and the cone beam computed tomography (CBCT) acquisition images and the inverse consistence (IC) property to validate the RayStation treatment planning system (TPS) DIR algorithm. This study was divided into two parts: Firstly the distance-accuracy of the TPS DIR algorithm was ascertained by placing POIs on anatomical features in the CT and CBCT images from five head and neck cancer patients. Secondly, a method was developed for studying the implication of these distances on the dose by using the IC. This method compared the dose received by the structures in the CT, and the structures that were quadruply-deformed. The accuracy of the TPS was 1.7 ± 0.8 mm, and the distance obtained with the quadruply-deformed IC method was 1.7 ± 0.9 mm, i.e. the difference between the IC method multiplied by two, and that of the TPS validation method, was negligible. Moreover, the IC method shows very little variation in the dose-volume histograms when comparing the original and quadruply-deformed structures. This indicates that this algorithm is useful for planning adaptive radiation treatments using CBCT in head and neck cancer patients, although these variations must be taken into account when making a clinical decision to adapt a treatment plan.

Phantom based evaluation of CT to CBCT image registration for proton therapy dose recalculation

The ability to perform dose recalculation on the anatomy of the day is important in the context of adaptive proton therapy. The objective of this study was to investigate the use of deformable image registration (DIR) and cone beam CT (CBCT) imaging to generate the daily stopping power distribution of the patient. We investigated the deformation of the planning CT scan (pCT) onto daily CBCT images to generate a virtual CT (vCT) using a deformable phantom designed for the head and neck (H & N) region.The phantom was imaged at a planning CT scanner in planning configuration, yielding a pCT and in deformed, treatment day configuration, yielding a reference CT (refCT). The treatment day configuration was additionally scanned at a CBCT scanner. A Morphons DIR algorithm was used to generate a vCT. The accuracy of the vCT was evaluated by comparison to the refCT in terms of corresponding features as identified by an adaptive scale invariant feature transform (aSIFT) algorithm. Additionally, the vCT CT numbers were compared to those of the refCT using both profiles and regions of interest and the volumes and overlap (DICE coefficients) of various phantom structures were compared. The water equivalent thickness (WET) of the vCT, refCT and pCT were also compared to evaluate proton range differences. Proton dose distributions from the same initial fluence were calculated on the refCT, vCT and pCT and compared in terms of proton range. The method was tested on a clinical dataset using a replanning CT scan acquired close in time to a CBCT scan as reference using the WET evaluation.Results from the aSIFT investigation suggest a deformation accuracy of 2–3 mm. The use of the Morphon algorithm did not distort CT number intensity in uniform regions and WET differences between vCT and refCT were of the order of 2% of the proton range. This result was confirmed by proton dose calculations. The patient results were consistent with phantom observations. In conclusion, our phantom study suggests the vCT approach is adequate for proton dose recalculation on the basis of CBCT imaging.

Evaluation and mitigation of the interplay effects of intensity modulated proton therapy for lung cancer in a clinical setting

PurposeThe primary aim of this study was to evaluate the impact of the interplay effects of intensity modulated proton therapy (IMPT) plans for lung cancer in the clinical setting. The secondary aim was to explore the technique of isolayered rescanning to mitigate these interplay effects. Methods and materialsA single-fraction 4-dimensional (4D) dynamic dose without considering rescanning (1FX dynamic dose) was used as a metric to determine the magnitude of dosimetric degradation caused by 4D interplay effects. The 1FX dynamic dose was calculated by simulating the machine delivery processes of proton spot scanning on a moving patient, described by 4D computed tomography during IMPT delivery. The dose contributed from an individual spot was fully calculated on the respiratory phase that corresponded to the life span of that spot, and the final dose was accumulated to a reference computed tomography phase by use of deformable image registration. The 1FX dynamic dose was compared with the 4D composite dose. Seven patients with various tumor volumes and motions were selected for study. ResultsThe clinical target volume (CTV) prescription coverage for the 7 patients was 95.04%, 95.38%, 95.39%, 95.24%, 95.65%, 95.90%, and 95.53% when calculated with the 4D composite dose and 89.30%, 94.70%, 85.47%, 94.09%, 79.69%, 91.20%, and 94.19% when calculated with the 1FX dynamic dose. For these 7 patients, the CTV coverage calculated by use of a single-fraction dynamic dose was 95.52%, 95.32%, 96.36%, 95.28%, 94.32%, 95.53%, and 95.78%, with a maximum monitor unit limit value of 0.005. In other words, by increasing the number of delivered spots in each fraction, the degradation of CTV coverage improved up to 14.6%. ConclusionsA single-fraction 4D dynamic dose without rescanning was validated as a surrogate to evaluate the interplay effects of IMPT for lung cancer in the clinical setting. The interplay effects potentially can be mitigated by increasing the amount of isolayered rescanning in each fraction delivery.

Dosimetric and geometric evaluation of the use of deformable image registration in adaptive intensity-modulated radiotherapy for head-and-neck cancer.

The aim of this study was to carry out geometric and dosimetric evaluation of the usefulness of a deformable image registration algorithm utilized for adaptive head-and-neck intensity-modulated radiotherapy. Data consisted of seven patients, each with a planning CT (pCT), a rescanning CT (ReCT) and a cone beam CT (CBCT). The CBCT was acquired on the same day (±1 d) as the ReCT (i.e. at Fraction 17, 18, 23, 24 or 29). The ReCT served as ground truth. A deformed CT (dCT) with structures was created by deforming the pCT to the CBCT. The geometrical comparison was based on the volumes of the deformed, and the manually delineated structures on the ReCT. Likewise, the center of mass shift (CMS) and the Dice similarity coefficient were determined. The dosimetric comparison was performed by recalculating the initial treatment plan on the dCT and the ReCT. Dose–volume histogram (DVH) points and a range of conformity measures were used for the evaluation. We found a significant difference in the median volume of the dCT relative to that of the ReCT. Median CMS values were ∼2–5 mm, except for the spinal cord, where the median CMS was 8 mm. Dosimetric evaluation of target structures revealed small differences, while larger differences were observed for organs at risk. The deformed structures cannot fully replace manually delineated structures. Based on both geometrical and dosimetrical measures, there is a tendency for the dCT to overestimate the need for replanning, compared with the ReCT.

SU-E-J-222: Evaluation of Deformable Registration of PET/CT Images for Cervical Cancer Brachytherapy

Purpose: PET/CT provides important functional information for radiotherapy targeting of cervical cancer. However, repeated PET/CT procedures for external beam and subsequent brachytherapy expose patients to additional radiation and are not cost effective. Our goal is to investigate the possibility of propagating PET-active volumes for brachytherapy procedures through deformable image registration (DIR) of earlier PET/CT and ultimately to minimize the number of PET/CT image sessions required. Methods: Nine cervical cancer patients each received their brachytherapy preplanning PET/CT at the end of EBRT with a Syed template in place. The planning PET/CT was acquired on the day of brachytherapy treatment with the actual applicator (Syed or Tandem and Ring) and rigidly registered. The PET/CT images were then deformably registered creating a third (deformed) image set for target prediction. Regions of interest with standardized uptake values (SUV) greater than 65% of maximum SUV were contoured as target volumes in all three sets of PET images. The predictive value of the registered images was evaluated by comparing the preplanning and deformed PET volumes with the planning PET volume using Dice's coefficient (DC) and center-of-mass (COM) displacement. Results: The average DCs were 0.12±0.14 and 0.19±0.16 for rigid and deformable predicted target volumes, respectively. The averagemore » COM displacements were 1.9±0.9 cm and 1.7±0.7 cm for rigid and deformable registration, respectively. The DCs were improved by deformable registration, however, both were lower than published data for DIR in other modalities and clinical sites. Anatomical changes caused by different brachytherapy applicators could have posed a challenge to the DIR algorithm. The physiological change from interstitial needle placement may also contribute to lower DC. Conclusion: The clinical use of DIR in PET/CT for cervical cancer brachytherapy appears to be limited by applicator choice and requires further investigation.« less

TU‐A‐19A‐01: Image Registration I: Deformable Image Registration, Contour Propagation and Dose Mapping: 101 and 201

Deformable image registration, contour propagation and dose mapping have become common, possibly essential tools for modern image‐guided radiation therapy. Historically, these tools have been largely developed at academic medical centers and used in a rather limited and well controlled fashion. Today these tools are now available to the radiotherapy community at large, both as stand‐alone applications and as integrated components of both treatment planning and treatment delivery systems. Unfortunately, the details of how these tools work and their limitations are not generally documented or described by the vendors that provide them. Although “it looks right”, determining that unphysical deformations may have occurred is crucial. Because of this, understanding how and when to use, and not use these tools to support everyday clinical decisions is far from straight forward.The goal of this session will be to present both the theory (basic and advanced) and practical clinical use of deformable image registration, contour propagation and dose mapping. To the extent possible, the “secret sauce” that different vendor use to produce reasonable/acceptable results will be described. A detailed explanation of the possible sources of errors and actual examples of these will be presented. Knowing the underlying principles of the process and understanding the confounding factors will help the practicing medical physicist be better able to make decisions (about making decisions) using these tools available.Learning Objectives: Understand the basic (101) and advanced (201) principles of deformable image registration, contour propagation and dose mapping data mapping. Understand the sources and impact of errors in registration and data mapping and the methods for evaluating the performance of these tools. Understand the clinical use and value of these tools, especially when used as a “black box”.

TU‐A‐500‐01: Deformable Image Registration, Contour Propagation and Dose Mapping: 101 and 201

Deformable image registration, contour propagation and dose mapping have become common, possibly essential tools for modern image‐guided radiation therapy. Historically, these tools have been largely developed at academic medical centers and used in a rather limited and well controlled fashion. Today these tools are now available to the radiotherapy community at large, both as stand‐alone applications and as integrated components of treatment planning and treatment delivery systems. Unfortunately, the details of how these tools work and their limitations are not generally documented or described by the vendors that provide them. Although “it looks right”, determining that unphysical deformations may have occurred is crucial. Because of this, understanding how and when to use, and not use these tools to support everyday clinical decisions is far from straight forward.The goal of this session will be to present both the theory (basic and advanced) and practical clinical use of deformable image registration, contour propagation and dose mapping. To the extent possible, the “secret sauce” that different vendor use to produce reasonable/acceptable results will be described. A detailed explanation of the possible sources of errors and actual examples of these will be presented. Knowing the underlying principles of the process and understanding the confounding factors will help the practicing medical physicist be better able to make decisions (about making decisions) using the tools available.Learning Objectives:1. Understand the basic (101) and advanced (201) principles of deformable image registration, contour propagation and dose mapping data mapping2. Understand the sources and impact of errors in registration and data mapping and the methods for evaluating the performance of these tools3. Understand the clinical use and value of these tools, especially when used as a “black box”

Using Deformable Dose Registration to Improve Planning for High-dose Thoracic Reirradiation

A quarter of all patients with locally advanced non-small cell lung cancer (LA-NSCLC) treated with chemo-radiation develop isolated loco-regional recurrence. Re-irradiation (Re-RT) for this indication has been associated with improved survival. Accurate registration of previous radiation doses can improve planning and potentially limit the risk of toxicity associated with Re-RT. We compared the use of deformable image registration (DIR) for this purpose against rigid image registration (RIR) alone.

Live augmented reality: a new visualization method for laparoscopic surgery using continuous volumetric computed tomography

Current laparoscopic images are rich in surface detail but lack information on deeper structures. This report presents a novel method for highlighting these structures during laparoscopic surgery using continuous multislice computed tomography (CT). This has resulted in a more accurate augmented reality (AR) approach, termed "live AR," which merges three-dimensional (3D) anatomy from live low-dose intraoperative CT with live images from the laparoscope. A series of procedures with swine was conducted in a CT room with a fully equipped laparoscopic surgical suite. A 64-slice CT scanner was used to image the surgical field approximately once per second. The procedures began with a contrast-enhanced, diagnostic-quality CT scan (initial CT) of the liver followed by continuous intraoperative CT and laparoscopic imaging with an optically tracked laparoscope. Intraoperative anatomic changes included user-applied deformations and those from breathing. Through deformable image registration, an intermediate image processing step, the initial CT was warped to align spatially with the low-dose intraoperative CT scans. The registered initial CT then was rendered and merged with laparoscopic images to create live AR. Superior compensation for soft tissue deformations using the described method led to more accurate spatial registration between laparoscopic and rendered CT images with live AR than with conventional AR. Moreover, substitution of low-dose CT with registered initial CT helped with continuous visualization of the vasculature and offered the potential of at least an eightfold reduction in intraoperative X-ray dose. The authors proposed and developed live AR, a new surgical visualization approach that merges rich surface detail from a laparoscope with instantaneous 3D anatomy from continuous CT scanning of the surgical field. Through innovative use of deformable image registration, they also demonstrated the feasibility of continuous visualization of the vasculature and considerable X-ray dose reduction. This study provides motivation for further investigation and development of live AR.

Reconstruction of 3D lung models from 2D planning data sets for Hodgkin's lymphoma patients using combined deformable image registration and navigator channels

Late complications (cardiac toxicities, secondary lung, and breast cancer) remain a significant concern in the radiation treatment of Hodgkin's lymphoma (HL). To address this issue, predictive dose-risk models could potentially be used to estimate radiotherapy-related late toxicities. This study investigates the use of deformable image registration (DIR) and navigator channels (NCs) to reconstruct 3D lung models from 2D radiographic planning images, in order to retrospectively calculate the treatment dose exposure to HL patients treated with 2D planning, which are now experiencing late effects. Three-dimensional planning CT images of 52 current HL patients were acquired. 12 image sets were used to construct a male and a female population lung model. 23 "Reference" images were used to generate lung deformation adaptation templates, constructed by deforming the population model into each patient-specific lung geometry using a biomechanical-based DIR algorithm, MORFEUS. 17 "Test" patients were used to test the accuracy of the reconstruction technique by adapting existing templates using 2D digitally reconstructed radiographs. The adaptation process included three steps. First, a Reference patient was matched to a Test patient by thorax measurements. Second, four NCs (small regions of interest) were placed on the lung boundary to calculate 1D differences in lung edges. Third, the Reference lung model was adapted to the Test patient's lung using the 1D edge differences. The Reference-adapted Test model was then compared to the 3D lung contours of the actual Test patient by computing their percentage volume overlap (POL) and Dice coefficient. The average percentage overlapping volumes and Dice coefficient expressed as a percentage between the adapted and actual Test models were found to be 89.2 +/- 3.9% (Right lung = 88.8%; Left lung = 89.6%) and 89.3 +/- 2.7% (Right = 88.5%; Left = 90.2%), respectively. Paired T-tests demonstrated that the volumetric reconstruction method made a statistically significant improvement to the population lung model shape (p < 0.05). The error in the results were also comparable to the volume overlap difference observed between inhale and exhale lung volumes during free-breathing respiratory motion (POL: p = 0.43; Dice: p = 0.20), which implies that the accuracies of the reconstruction method are within breathing constraints and would not be the confining factor in estimating normal tissue dose exposure. The result findings show that the DIR-NC technique can achieve a high degree of reconstruction accuracy, and could be useful in approximating 3D dosimetric representations of historical 2D treatment. In turn, this could provide a better understanding of the biophysical relationship between dose-volume exposure and late term radiotherapy effects.

Use of Deformable Registration Tool for Verifying Tumor Position on Kilo-voltage Cone-beam CT Scans for Stage III Lung Cancer

Individualized target volumes for Stage III lung cancer can be generated using 4D-CT scans. However, verification of treatment delivery during respiration-gated and image-guided radiotherapy is suboptimal as: (1) conventional cone beam CT (KV-CBCT) images are time-averaged; (2) mediastinal nodes are poorly visualized on blurred images; and (3) coregistration on CBCT tumor volumes is unreliable. We evaluated the use of deformable image registration to propagate planning target volumes on CBCT images.

SU‐FF‐I‐155: A Novel Technique to Generate 3D Lung Volumes From 2D Hodgkin Lymphoma Planning Datasets Using Combined Deformable Image Registration and Navigator Channels

Purpose: To validate the use of deformable image registration and navigator channels (NC) to generate 3D lung volumes from 2D images, for retrospective dose calculation of Hodgkin Lymphoma (HL) patients treated with 2D planning. Methods and Materials: Forty‐seven HL patients with 3D images were acquired. Six patients were used to construct a population lung model, which was then registered, using a biomechanical model‐based deformable registration algorithm, MORFEUS, into 24 additional HL ‘reference’ patients to develop a lung motion model. This model was refined to describe the 3D lung volume and position of 17 HL ‘test’ patients, using only information in the 2D DRR constructed from 3D images. The refinement was performed by: 1) matching a reference patient to each test patient (using lung width and length measurements), 2) placing four NCs, or small regions of interest, on the lung boundary of the reference patient and automatically placing the corresponding NC on the test image in the same geometric position, 3) converting the image intensity in the NC into a 1D shift to match that location, 4) refining the lung motion model using the four 1D shifts to describe the 3D volume and position of the test patient's lung. The refined lung model was then compared to the actual 3D lung contour of the 17 test patients by computing the volume overlap. Results: The average percentage overlapping and non‐overlapping volumes between the NC‐refined lung model and test lungs were 89.2±3.9% (Right Lung=88.8%; Left Lung=89.6%) and 10.8±3.9% (Right=11.2%; Left=10.4%), respectively. NCs made a statistically significant improvement to the population lung model shape (T‐test: p &lt; 0.05). Conclusion: This technique will be used to generate 3D lung volumes for retrospective patients treated with 2D planning for longitudinal studies to improve understanding of the dose‐risk relationship and various late effects.

SU-FF-J-131: Improving Quantitation in Serial PET/CT with Improved Image Registration and Intra-Patient Metabolic Correction

Purpose: The goal of this study is to explore the use of deformable image registration in conjunction with an internal metabolic reference to improve quantitative treatment response assessment using F18‐FDG PET/CT. Method and Materials: To account for anatomic and positional changes, pre‐ and post‐radiotherapy (RT) PET/CT studies were aligned with a deformable image registration technique to the planning CT (PCT). Consequently, both CT‐ and PET‐based regions‐of‐interest on all co‐registered image sets can be used to determine uptake for the same anatomic volumes. The brainstem, contoured on PCT, was selected as an internal metabolic normalization structure to correct for study dependent variations; particularly, inconsistent injection‐to‐imaging time. The mean SUV was calculated using a threshold contour (40% of maximum) method, created on the pre‐RT PET/CT images. Student's t‐tests and receiver operating characteristic (ROC) analyses were performed for metabolically corrected (uptake ratio of tumor to brainstem) and uncorrected mean and maximum SUV. Results: A statistically detectable separation was improved between responding and non‐responding patients using the corrected post‐RT mean SUV for the threshold contour (P=0.017 vs. P=0.00); while no worsening was seen for the maximum SUV (P<0.00 vs. P<0.00). Reduction of uptake the between pre‐ and post‐RT images was only significant for the maximum SUV (P=0.033) and subsequently improved when corrected with the metabolic reference (P=0.012). Finally, ROC analysis of the maximum corrected post‐RT SUV showed improvement in specificity (94% vs. 85%) and similar results for the sensitivity (83% vs. 83%) level. However, ROC analyses of corrected and uncorrected mean post‐RT SUV derived from the threshold contour did not show improvement. Conclusions: Multiple lines of evidence demonstrate that correction of SUV with an internal metabolic reference may improve the quantitative potential of F18‐FDG PET/CT. Conflict of Interest: Research sponsored by Varian Medical Systems.

An energy transfer method for 4D Monte Carlo dose calculation

This article presents a new method for four-dimensional Monte Carlo dose calculations which properly addresses dose mapping for deforming anatomy. The method, called the energy transfer method (ETM), separates the particle transport and particle scoring geometries: Particle transport takes place in the typical rectilinear coordinate system of the source image, while energy deposition scoring takes place in a desired reference image via use of deformable image registration. Dose is the energy deposited per unit mass in the reference image. ETM has been implemented into DOSXYZnrc and compared with a conventional dose interpolation method (DIM) on deformable phantoms. For voxels whose contents merge in the deforming phantom, the doses calculated by ETM are exactly the same as an analytical solution, contrasting to the DIM which has an average 1.1% dose discrepancy in the beam direction with a maximum error of 24.9% found in the penumbra of a 6 MV beam. The DIM error observed persists even if voxel subdivision is used. The ETM is computationally efficient and will be useful for 4D dose addition and benchmarking alternative 4D dose addition algorithms.

WE-C-AUD C-02: Use of Deformable Image Registration in Generating Composite Plans Over Multi Treatment Modalities and Multi-Stage Planning

Purpose: Currently there are no commercially available tools to generate composite plans when the individual plans were generated on different image sets. Without a composite plan, some of the important dosimetrical parameters, such as the overall tumor coverage, the volume irradiated of critical structures are difficult to obtain for the overall treatment evaluation. This paper introduces a method to generate composite plans over multi radiotherapy treatment modalities, and multi‐stage plans using deformable image registration.Method and Materials: Two cases were studied. Case 1 was a prostate cancer with external beam IMRT and interstitial seed implant. Case 2 was a lungcancer with two treatment plans based on two separate CTimage sets. . Thin‐plate spline (TPS) and optical flow method (OFM) were used to generate deformation image maps. The deformations were verified by mapping the deformed image set back to the original image set and comparing. The deformation matrices were then applied to the dose matrices and doses were summed. In the case of the prostate cancer a local biological effective dose (BED) correction was applied prior to the deformation and sum. Results: The mapping of the deformed image set back to the original showed agreement within a voxel in over 99% of the volume. Composite plans and DVH were generated for both the cases. The use of local BED showed significant changes in doses to normal tissues. Conclusion: The generated composite plans using deformable image registration are informative and valuable in overall treatment plan evaluation. The use of local BED calculations must be included when combining treatment modalities such as Brachytherapy and external beam.

Dose mapping: Validation in 4D dosimetry with measurements and application in radiotherapy follow-up evaluation

The purpose of this paper is to validate a dose mapping program using optical flow method (OFM), and to demonstrate application of the program in radiotherapy follow-up evaluation. For the purpose of validation, the deformation matrices between four-dimensional (4D) CT data of different simulated respiration phases of a phantom were calculated using OFM. The matrices were then used to map doses of all phases to a single-phase image, and summed in equal time weighting. The calculated dose should closely represent the dose delivered to the moving phantom if the deformation matrices are accurately calculated. The measured point doses agreed with the OFM calculations better than 2% at isocenters, and dose distributions better than 1 mm for the 50% isodose line. To demonstrate proof-of-concept for the use of deformable image registration in dose mapping for treatment evaluation, the treatment-planning CT was registered with the post-treatment CT image from the positron emission tomography (PET)/CT resulting in a deformation matrix. The dose distribution from the treatment plan was then mapped onto the restaging PET/CT using the deformation matrix. Two cases in which patients had thoracic malignancies are presented. Each patient had CT-based treatment planning for radiotherapy and restaging fluorodeoxy glucose (FDG)-PET/CT imaging 4–6 weeks after completion of treatments. Areas of pneumonitis and recurrence were identified radiographically on both PET and CT restaging images. Local dose and standard uptake values for pneumonitis and recurrence were studied as a demonstration of this method. By comparing the deformable mapped dose to measurement, the treatment evaluation method which is introduced in this manuscript proved to be accurate. It thus provides a more accurate analysis than other rigid or linear dose-image registration when used in studying treatment outcome versus dose.

SU-EE-A3-04: ROI-Based Response Assessment Using Pre- and Post-RT 18F-FDG PET/CT

Purpose: To assess the therapy-induced changes of head and neck cancers using 18F-FDG PET/CT imaging studies performed prior to and following the completion of a course of radiotherapy (RT) through a region-of-interest based (ROI) analysis. Method and Materials: As part of an ongoing study, nine patients with carcinoma of the head and neck had PET/CT imaging studies performed prior to the start of treatment (range: 4 – 58 days; median: 36 days) and following the conclusion of treatment (range: 33 – 63 days; median: 59 days). RT contours, created with the Pinnacle treatment planning system and CT simulation images, from physician-approved plans were collected to align with pre- and post-RT PET/CT images. Utilizing in-house developed software, the contours were deformed to the pre- and post-RT PET/CT images through a non-rigid registration. The non-rigidly aligned RT contours were then used as ROIs to collect data from the pre-and post-RT PET images. The standard uptake value (SUV) was calculated assuming that identical structures were contained in the pre- and post-RT deformed volumes, which were altered by anatomic changes as a result of RT. Results: For the GTV contour, the mean pre- and post-RT SUV and standard deviation was (5.6 ± 0.9) and (2.4 ± 0.6), respectively. Within the GTV, the mean maximum SUV prior to RT was (23 ± 4.6), while after the conclusion of RT, the mean maximum SUV was (5.0 ± 1.9). Additionally, the mean ratio of the pre- to post-RT mean SUV was (2.5 ± 0.7), indicating an overall decrease in uptake of the tracer in tissues within the GTV contour. Conclusion: Through the use of deformable image registration, the feasibility of 18F-FDG PET/CT ROI-based analyses of RT-induced changes in patients with head and neck cancers has been demonstrated.

Deformable registration of brain tumor images via a statistical model of tumor-induced deformation

An approach to the deformable registration of three-dimensional brain tumor images to a normal brain atlas is presented. The approach involves the integration of three components: a biomechanical model of tumor mass-effect, a statistical approach to estimate the model's parameters, and a deformable image registration method. Statistical properties of the sought deformation map from the atlas to the image of a tumor patient are first obtained through tumor mass-effect simulations on normal brain images. This map is decomposed into the sum of two components in orthogonal subspaces, one representing inter-individual differences in brain shape, and the other representing tumor-induced deformation. For a new tumor case, a partial observation of the sought deformation map is obtained via deformable image registration and is decomposed into the aforementioned spaces in order to estimate the mass-effect model parameters. Using this estimate, a simulation of tumor mass-effect is performed on the atlas image in order to generate an image that is similar to tumor patient's image, thereby facilitating the atlas registration process. Results for a real tumor case and a number of simulated tumor cases indicate significant reduction in the registration error due to the presented approach as compared to the direct use of deformable image registration.

WE‐C‐ValA‐08: Development of a Patient Specific Respiratory Motion Model for Predicting Dose to Moving Organs During Radiotherapy

Purpose: Respiratory motion is an important limitation to accurate calculation of dose to organs in the thorax and abdomen during treatment. We describe a model to estimate 3‐dimensional motion in patient CT images. This model can be parameterized by navigators such as a signal from a respiratory monitor, or diaphragm position measured in fluoroscopy. We evaluate the accuracy of the model in predicting anatomic changes in respiration‐correlated CT (RCCT) images of lung cancer patients. Method and Experiment: Our method makes use of deformable image registration, thereby automating the model calibration and providing a complete determination of 3D trajectories for all tissue voxels of the moving organs. Calibration of the model uses a series of RCCT images. Each 3D image in the series is tagged by two navigators: current diaphragm position and precursor position which distinguishes between the inspiration and expiration portion of the respiratory cycle. Nonrigid registration is used to calculate the deformation field that maps each 3D image to a reference 3D image at end expiration. We perform a principle component analysis (PCA) to determine the 3D deformation parameterized by navigators. We evaluate the model by comparing the predicted 3D images with actual 3D images at different phases in the breathing cycle. Results: For RCCT images, predicted images calculated from the first two principal components at different respiration phases are found to accurately reproduce anatomic motion observed in the actual images, indicating the model's ability to predict the voxel trajectory anywhere in the cycle. Furthermore, the model can predict motion induced changes that were not in the original image set, such as deeper and shallower breathing. Conclusion: Preliminary experimental results indicate that the proposed method is a potentially useful tool for treatment planning and evaluation of dose to moving organs when patient breathing is monitored.

Monte Carlo as a four-dimensional radiotherapy treatment-planning tool to account for respiratory motion**Paper presented at World Congress on Medical Physics and Biomedical Engineering (Sydney)—WC2003.

Four-dimensional (4D) radiotherapy is the explicit inclusion of the temporal changes in anatomy during the imaging, planning and delivery of radiotherapy. Temporal anatomic changes can occur for many reasons, though the focus of the current investigation was respiration motion for lung tumours. The aims of the current research were first to develop a 4D Monte Carlo methodology and second to apply this technique to an existing 4D treatment plan. A 4D CT scan consisting of a series of 3D CT image sets acquired at different respiratory phases was used. Deformable image registration was performed to map each CT set from the end-inhale respiration phase to the CT image sets corresponding with subsequent respiration phases. This deformable registration allowed the contours drawn on the end-inhale CT to be automatically drawn on the other respiratory phase CT image sets. A treatment plan was created on the end-inhale CT image set and then automatically created on each of the 3D CT image sets corresponding with subsequent respiration phases, based on the beam arrangement and dose prescription in the end-inhale plan. Dose calculation using Monte Carlo was simultaneously performed on each of the N (=8) 3D image sets with 1/N fewer particles per calculation than for a 3D plan. The dose distribution from each respiratory phase CT image set was mapped back to the end-inhale CT image set for analysis. This use of deformable image registration to merge all the statistically noisy dose distributions back onto one CT image set effectively yielded a 4D Monte Carlo calculation with a statistical uncertainty equivalent to a 3D calculation, with a similar calculation time for the 3D and 4D methods. Monte Carlo as a dose calculation tool for 4D radiotherapy planning has two advantages: (1) higher accuracy for calculation in electronic disequilibrium conditions, such as those encountered during lung radiotherapy, and (2) if deformable image registration is used, the calculation time for Monte Carlo is independent of the number of 3D CT image sets constituting a 4D CT, unlike other algorithms for which the calculation time scales linearly with the number of 3D CT image sets constituting a 4D CT.