Carri Glide-Hurst

Technical Note: Characterization and correction of gradient nonlinearity induced distortion on a 1.0 T open bore MRâ SIM

PURPOSEnDistortions in magnetic resonance imaging (MRI) compromise spatial fidelity, potentially impacting delineation and dose calculation. We characterized 2D and 3D large field of view (FOV), sequence-independent distortion at various positions in a 1.0 T high-field open MR simulator (MR-SIM) to implement correction maps for MRI treatment planning.nnnMETHODSnA 36 × 43 × 2 cm(3) phantom with 255 known landmarks (∼1 mm(3)) was scanned using 1.0 T high-field open MR-SIM at isocenter in the transverse, sagittal, and coronal axes, and a 465 × 350 × 168 mm(3) 3D phantom was scanned by stepping in the superior-inferior direction in three overlapping positions to achieve a total 465 × 350 × 400 mm(3) sampled FOV yielding >13u2009800 landmarks (3D Gradient-Echo, TE/TR/α = 5.54 ms/30 ms/28°, voxel size = 1 × 1 × 2 mm(3)). A binary template (reference) was generated from a phantom schematic. An automated program converted MR images to binary via masking, thresholding, and testing for connectivity to identify landmarks. Distortion maps were generated by centroid mapping. Images were corrected via warping with inverse distortion maps, and temporal stability was assessed.nnnRESULTSnOver the sampled FOV, non-negligible residual gradient distortions existed as close as 9.5 cm from isocenter, with a maximum distortion of 7.4 mm as close as 23 cm from isocenter. Over six months, average gradient distortions were -0.07 ± 1.10 mm and 0.10 ± 1.10 mm in the x and y directions for the transverse plane, 0.03 ± 0.64 and -0.09 ± 0.70 mm in the sagittal plane, and 0.4 ± 1.16 and 0.04 ± 0.40 mm in the coronal plane. After implementing 3D correction maps, distortions were reduced to <1 pixel width (1 mm) for all voxels up to 25 cm from magnet isocenter.nnnCONCLUSIONSnInherent distortion due to gradient nonlinearity was found to be non-negligible even with vendor corrections applied, and further corrections are required to obtain 1 mm accuracy for large FOVs. Statistical analysis of temporal stability shows that sequence independent distortion maps are consistent within six months of characterization.

Implementation of a Novel Algorithm For Generating Synthetic CT Images From Magnetic Resonance Imaging Data Sets for Prostate Cancer Radiation Therapy

PURPOSEnTo describe and evaluate a method for generating synthetic computed tomography (synCT) images from magnetic resonance simulation (MR-SIM) data for accurate digitally reconstructed radiograph (DRR) generation and dose calculations in prostate cancer radiation therapy.nnnMETHODS AND MATERIALSnA retrospective evaluation was performed in 9 prostate cancer patients who had undergone MR-SIM in addition to CT simulation (CT-SIM). MR-SIM data were used to generate synCT images by using a novel, voxel-based weighted summation approach. A subset of patients was used for weight optimization, and the number of patients to use during optimization was determined. Hounsfield unit (HU) differences between CT-SIM and synCT images were analyzed via mean absolute error (MAE). Original, CT-based treatment plans were mapped onto synCTs. DRRs were generated, and agreement between CT and synCT-generated DRRs was evaluated via Dice similarity coefficient (DSC). Dose was recalculated, and dose-volume metrics and gamma analysis were used to evaluate resulting treatment plans.nnnRESULTSnFull field-of-view synCT MAE across all patients was 74.3 ± 10.9 HU with differences from CTs of 2.0 ± 8.1 HU and 11.9 ± 46.7 HU for soft tissue structures (prostate, bladder, and rectum) and femoral bones, respectively. Calculated DSCs for anterior-posterior and lateral DRRs were 0.90 ± 0.04 and 0.92 ± 0.05, respectively. Differences in D99%, mean dose, and maximum dose to the clinical target volume from CT-SIM dose calculations were 0.75% ± 0.35%, 0.63% ± 0.34%, and 0.54% ± 0.33%, respectively, for synCT-generated plans. Gamma analysis (2%/2 mm dose difference/distance to agreement) revealed pass rates of 99.9% ± 0.1% (range, 99.7%-100%).nnnCONCLUSIONnGenerated synCTs enabled accurate DRR generation and dose computation for prostate MR-only simulation. Dose recalculated on synCTs agreed well with original planning distributions. Further validation using a larger patient cohort is warranted.

Evaluation of the deformation and corresponding dosimetric implications in prostate cancer treatment

The cone-beam computed tomography (CBCT) imaging modality is an integral component of image-guided adaptive radiation therapy (IGART), which uses patient-specific dynamic/temporal information for potential treatment plan modification. In this study, an offline process for the integral component IGART framework has been implemented that consists of deformable image registration (DIR) and its validation, dose reconstruction, dose accumulation and dose verification. This study compares the differences between planned and estimated delivered doses under an IGART framework of five patients undergoing prostate cancer radiation therapy. The dose calculation accuracy on CBCT was verified by measurements made in a Rando pelvic phantom. The accuracy of DIR on patient image sets was evaluated in three ways: landmark matching with fiducial markers, visual image evaluation and unbalanced energy (UE); UE has been previously demonstrated to be a feasible method for the validation of DIR accuracy at a voxel level. The dose calculated on each CBCT image set was reconstructed and accumulated over all fractions to reflect the actual dose delivered to the patient. The deformably accumulated (delivered) plans were then compared to the original (static) plans to evaluate tumor and normal tissue dose discrepancies. The results support the utility of adaptive planning, which can be used to fully elucidate the dosimetric impact based on the simulated delivered dose to achieve the desired tumor control and normal tissue sparing, which may be of particular importance in the context of hypofractionated radiotherapy regimens.

Using patient-specific phantoms to evaluate deformable image registration algorithms for adaptive radiation therapy

The quality of adaptive treatment planning depends on the accuracy of its underlying deformable image registration (DIR). The purpose of this study is to evaluate the performance of two DIR algorithms, B‐spline‐based deformable multipass (DMP) and deformable demons (Demons), implemented in a commercial software package. Evaluations were conducted using both computational and physical deformable phantoms. Based on a finite element method (FEM), a total of 11 computational models were developed from a set of CT images acquired from four lung and one prostate cancer patients. FEM generated displacement vector fields (DVF) were used to construct the lung and prostate image phantoms. Based on a fast‐Fourier transform technique, image noise power spectrum was incorporated into the prostate image phantoms to create simulated CBCT images. The FEM‐DVF served as a gold standard for verification of the two registration algorithms performed on these phantoms. The registration algorithms were also evaluated at the homologous points quantified in the CT images of a physical lung phantom. The results indicated that the mean errors of the DMP algorithm were in the range of 1.0~3.1mm for the computational phantoms and 1.9 mm for the physical lung phantom. For the computational prostate phantoms, the corresponding mean error was 1.0–1.9 mm in the prostate, 1.9–2.4 mm in the rectum, and 1.8–2.1 mm over the entire patient body. Sinusoidal errors induced by B‐spline interpolations were observed in all the displacement profiles of the DMP registrations. Regions of large displacements were observed to have more registration errors. Patient‐specific FEM models have been developed to evaluate the DIR algorithms implemented in the commercial software package. It has been found that the accuracy of these algorithms is patient‐dependent and related to various factors including tissue deformation magnitudes and image intensity gradients across the regions of interest. This may suggest that DIR algorithms need to be verified for each registration instance when implementing adaptive radiation therapy. PACS numbers: 87.10.Kn, 87.55.km, 87.55.Qr, 87.57.nj

Improving radiotherapy planning, delivery accuracy, and normal tissue sparing using cutting edge technologies

In the United States, more than half of all new invasive cancers diagnosed are non-small cell lung cancer, with a significant number of these cases presenting at locally advanced stages, resulting in about one-third of all cancer deaths. While the advent of stereotactic ablative radiation therapy (SABR, also known as stereotactic body radiotherapy, or SBRT) for early-staged patients has improved local tumor control to >90%, survival results for locally advanced stage lung cancer remain grim. Significant challenges exist in lung cancer radiation therapy including tumor motion, accurate dose calculation in low density media, limiting dose to nearby organs at risk, and changing anatomy over the treatment course. However, many recent technological advancements have been introduced that can meet these challenges, including four-dimensional computed tomography (4DCT) and volumetric cone-beam computed tomography (CBCT) to enable more accurate target definition and precise tumor localization during radiation, respectively. In addition, advances in dose calculation algorithms have allowed for more accurate dosimetry in heterogeneous media, and intensity modulated and arc delivery techniques can help spare organs at risk. New delivery approaches, such as tumor tracking and gating, offer additional potential for further reducing target margins. Image-guided adaptive radiation therapy (IGART) introduces the potential for individualized plan adaptation based on imaging feedback, including bulky residual disease, tumor progression, and physiological changes that occur during the treatment course. This review provides an overview of the current state of the art technology for lung cancer volume definition, treatment planning, localization, and treatment plan adaptation.

Voxel-based statistical analysis of uncertainties associated with deformable image registration

Deformable image registration (DIR) algorithms have inherent uncertainties in their displacement vector fields (DVFs).The purpose of this study is to develop an optimal metric to estimate DIR uncertainties. Six computational phantoms have been developed from the CT images of lung cancer patients using a finite element method (FEM). The FEM generated DVFs were used as a standard for registrations performed on each of these phantoms. A mechanics-based metric, unbalanced energy (UE), was developed to evaluate these registration DVFs. The potential correlation between UE and DIR errors was explored using multivariate analysis, and the results were validated by landmark approach and compared with two other error metrics: DVF inverse consistency (IC) and image intensity difference (ID). Landmark-based validation was performed using the POPI-model. The results show that the Pearson correlation coefficient between UE and DIR error is rUE-errorxa0= 0.50. This is higher than rIC-errorxa0= 0.29 for IC and DIR error and rID-errorxa0= 0.37 for ID and DIR error. The Pearson correlation coefficient between UE and the product of the DIR displacements and errors is rUE-errorxa0×xa0DVFxa0= 0.62 for the six patients and rUE-errorxa0×xa0DVFxa0= 0.73 for the POPI-model data. It has been demonstrated that UE has a strong correlation with DIR errors, and the UE metric outperforms the IC and ID metrics in estimating DIR uncertainties. The quantified UE metric can be a useful tool for adaptive treatment strategies, including probability-based adaptive treatment planning.

Direct dose mapping versus energy/mass transfer mapping for 4D dose accumulation: fundamental differences and dosimetric consequences

The direct dose mapping (DDM) and energy/mass transfer (EMT) mapping are two essential algorithms for accumulating the dose from different anatomic phases to the reference phase when there is organ motion or tumor/tissue deformation during the delivery of radiation therapy. DDM is based on interpolation of the dose values from one dose grid to another and thus lacks rigor in defining the dose when there are multiple dose values mapped to one dose voxel in the reference phase due to tissue/tumor deformation. On the other hand, EMT counts the total energy and mass transferred to each voxel in the reference phase and calculates the dose by dividing the energy by mass. Therefore it is based on fundamentally sound physics principles. In this study, we implemented the two algorithms and integrated them within the Eclipse treatment planning system. We then compared the clinical dosimetric difference between the two algorithms for ten lung cancer patients receiving stereotactic radiosurgery treatment, by accumulating the delivered dose to the end-of-exhale (EE) phase. Specifically, the respiratory period was divided into ten phases and the dose to each phase was calculated and mapped to the EE phase and then accumulated. The displacement vector field generated by Demons-based registration of the source and reference images was used to transfer the dose and energy. The DDM and EMT algorithms produced noticeably different cumulative dose in the regions with sharp mass density variations and/or high dose gradients. For the planning target volume (PTV) and internal target volume (ITV) minimum dose, the difference was up to 11% and 4% respectively. This suggests that DDM might not be adequate for obtaining an accurate dose distribution of the cumulative plan, instead, EMT should be considered.

High-Quality T2-Weighted 4-Dimensional Magnetic Resonance Imaging for Radiation Therapy Applications

PURPOSEnThe purpose of this study was to improve triggering efficiency of the prospective respiratory amplitude-triggered 4-dimensional magnetic resonance imaging (4DMRI) method and to develop a 4DMRI imaging protocol that could offer T2 weighting for better tumor visualization, good spatial coverage and spatial resolution, and respiratory motion sampling within a reasonable amount of time for radiation therapy applications.nnnMETHODS AND MATERIALSnThe respiratory state splitting (RSS) and multi-shot acquisition (MSA) methods were analytically compared and validated in a simulation study by using the respiratory signals from 10 healthy human subjects. The RSS method was more effective in improving triggering efficiency. It was implemented in prospective respiratory amplitude-triggered 4DMRI. 4DMRI image datasets were acquired from 5 healthy human subjects. Liver motion was estimated using the acquired 4DMRI image datasets.nnnRESULTSnThe simulation study showed the RSS method was more effective for improving triggering efficiency than the MSA method. The average reductions in 4DMRI acquisition times were 36% and 10% for the RSS and MSA methods, respectively. The human subject study showed that T2-weighted 4DMRI with 10 respiratory states, 60 slices at a spatial resolution of 1.5 × 1.5 × 3.0 mm(3) could be acquired in 9 to 18 minutes, depending on the individuals breath pattern. Based on the acquired 4DMRI image datasets, the ranges of peak-to-peak liver displacements among 5 human subjects were 9.0 to 12.9 mm, 2.5 to 3.9 mm, and 0.5 to 2.3 mm in superior-inferior, anterior-posterior, and left-right directions, respectively.nnnCONCLUSIONSnWe demonstrated that with the RSS method, it was feasible to acquire high-quality T2-weighted 4DMRI within a reasonable amount of time for radiation therapy applications.

Advances in Treatment Techniques Arc-Based and Other Intensity Modulated Therapies

Treatment planning and radiation delivery techniques have advanced significantly during the past 2 decades. The development of the multileaf collimator has changed the scope of radiotherapy. The dynamic conformal arc technique emerged from traditional cone-based conformal arc therapies, which aim to improve target dose uniformity and reduce normal tissue doses. With dynamic conformal arc, the multileaf collimator aperture is shaped dynamically to conform to the target. With the advent of intensity-modulated radiotherapy (IMRT), the concept of arc therapy in combination with IMRT has enabled better-quality dose distributions and more efficient delivery. Helical tomotherapy has been developed to treat targets sequentially by modulating the beam intensity in each slice of the patient. Helical tomotherapy offers improved dose distributions for complicated treatments, such as whole-body radiation. Intensity-modulated arc therapy has been studied to modulate fluences in a cone beam rather than fan beam geometry to improve delivery efficiency. This article reviews arc-based IMRT, intensity-modulated arc therapy, and helical tomotherapy techniques. We compare the dosimetric results reported in the literature for each technique in various treatment sites. We also review the application of these techniques in specialized clinical procedures including total marrow irradiation, simultaneous treatment of multiple brain metastases, dose painting, simultaneous integrated boost, and stereotactic radiosurgery.

Evaluation of two synchronized external surrogates for 4D CT sorting

The purpose of this study was to quantify the performance and agreement between two different external surrogate acquisition systems: Varians Real‐Time Position Management (RPM) and Philips Medical Systems pneumatic bellows, in the context of waveform and 4D CT image analysis. Eight patient displacement curves derived from RPM data were inputted into a motion platform with varying amplitudes (0.5 to 3 cm) and patterns. Simultaneous 4D CT acquisition, with synchronized X‐ray on detection, was performed with the bellows and RPM block placed on the platform. Bellows data were used for online retrospective phase‐based sorting, while RPM data were used for off‐line reconstruction of raw 4D CT data. RPM and bellows breathing curves were resampled, normalized, and analyzed to determine associations between different external surrogates, relative amplitude differences, and system latency. Maximum intensity projection (MIP) images were generated, phantom targets were delineated, and volume differences, overlap index, and Dice similarity coefficient differences were evaluated. A prospective patient study of ten patients was performed and waveforms were evaluated for latency (i.e., absolute time differences) and overall agreement. 4D CT sorting quality and subtraction images were assessed. Near perfect associations between the RPM and bellows‐acquired breathing traces were found (Pearson′sr=0.987−0.999). Target volumes were 200.4±12ccand199.8±12.6cc for RPM and bellows targets, respectively, which was not significantly different (U=33,p>0.05). Negligible centroid variations were observed between bellows and RPM‐contoured MIP targets (largest discrepancy=−0.24±0.31mm in superior‐inferior direction). The maximum volume difference was observed for an RPM target 2.5 cc (1%) less than bellows, yielding the largest difference in centroid displacement (0.9 mm). Strong correlations in bellows and RPM waveforms were observed for all patients (0.947±0.037). Latency between external surrogates was <100ms for phantom and patient data. Negligible differences were observed between MIP, end‐exhale, and end‐inhale phase images for all cases, with delineated RPM and bellows lung volumes demonstrating a mean difference of −0.3±0.51%. Dice similarity coefficients and overlap indices were near unity for phantom target volumes and patient lung volumes. Slight differences were observed in waveform and latency analysis between Philips bellows and Varians RPM, although these did not translate to differences in image quality or impact delineations. Therefore, the two systems were found to be equivalent external surrogates in the context of 4D CT for treatment planning purposes. PACS numbers: 87.57.Q‐, 07.07.Df