Motion-induced dose perturbations in photon radiotherapy and proton therapy measured by deformable liver-shaped 3D dosimeters in an anthropomorphic phantom.

Background and purpose: The impact of intrafractional motion and deformations on clinical radiotherapy delivery has so far only been investigated by simulations as well as point and planar dose measurements. The aim of this study was to combine anthropomorphic 3D dosimetry with a deformable abdominal phantom to measure the influence of intra-fractional motion and gating in photon radiotherapy and evaluate the applicability in proton therapy. Material and methods: An abdominal phantom was modified to hold a deformable anthropomorphic 3D dosimeter shaped as a human liver. A liver-specific photon radiotherapy and a proton pencil beam scanning therapy plan were delivered to the phantom without motion as well as with 12 mm sinusoidal motion while using either no respiratory gating or respiratory gating. Results: Using the stationary irradiation as reference the local 3 %/2 mm 3D gamma index pass rate of the motion experiments in the planning target volume (PTV) was above 97 % (photon) and 78 % (proton) with gating whereas it was below 74 % (photon) and 45 % (proton) without gating. Conclusions: For the first time a high-resolution deformable anthropomorphic 3D dosimeter embedded in a deformable abdominal phantom was applied for experimental validation of both photon and proton treatments of targets exhibiting respiratory motion. It was experimentally shown that gating improves dose coverage and the geometrical accuracy for both photon radiotherapy and proton therapy.

Deformable scintillation dosimeter: II. Real-time simultaneous measurements of dose and tracking of deformation vector fields.

Anatomical motion and deformation pose challenges to the understanding of the delivered dose distribution during radiotherapy treatments. Hence, deformable image registration (DIR) algorithms are increasingly used to map contours and dose distributions from one image set to another. However, the lack of validation tools slows their clinical adoption, despite their commercial availability. This work presents a novel water-equivalent deformable dosimeter that simultaneously measures the dose distribution and tracks deformation vector fields (DVF). The dosimeter in made of an array of 19 scintillating fiber detectors embedded in a cylindrical elastomer matrix. It is imaged by two pairs of stereoscopic cameras tracking the position and angulation of the scintillators, while measuring the dose. The resulting system provides a precision of 0.3 mm on DVF measurements. The dosimeter was irradiated with 5 × 3, 4 × 3 and 3 × 3 cm26 MV photon beams in both fixed and deformed conditions. The measured DVF was compared to the one computed with a DIR algorithm (Plastimatch). The deviations between the computed and measured DVFs was below 1.5 mm. As for dose measurements, the dosimeter acquired the dose distribution in fixed and deformed conditions within 1% of the treatment planning system calculation and complementary dose validation using the Hyperscint dosimetry system. Using the demonstrated qualities of scintillating detectors, we developed a real-time, water-equivalent deformable dosimeter. Given it's sensor tracking position precision and dose measurements accuracy, the developed detector is a promising tools for the validation of DIR algorithms as well as dose distribution measurements under fixed and deformed conditions.

Evaluation of the accuracy of deformable image registration on MRI with a physical phantom.

BACKGROUND AND PURPOSE: Magnetic resonance imaging (MRI) has gained popularity in radiation therapy simulation because it provides superior soft tissue contrast, which facilitates more accurate target delineation compared with computed tomography (CT) and does not expose the patient to ionizing radiation. However, image registration errors in commercial software have not been widely reported. Here we evaluated the accuracy of deformable image registration (DIR) by using a physical phantom for MRI. METHODS AND MATERIALS: We used the "Wuphantom" for end-to-end testing of DIR accuracy for MRI. This acrylic phantom is filled with water and includes several fillable inserts to simulate various tissue shapes and properties. Deformations and changes in anatomic locations are simulated by changing the rotations of the phantom and inserts. We used Varian Velocity DIR software (v4.0) and CT (head and neck protocol) and MR (T1- and T2-weighted head protocol) images to test DIR accuracy between image modalities (MRI vs CT) and within the same image modality (MRI vs MRI) in 11 rotation deformation scenarios. Large inserts filled with Mobil DTE oil were used to simulate fatty tissue, and small inserts filled with agarose gel were used to simulate tissues slightly denser than water (e.g., prostate). Contours of all inserts were generated before DIR to provide a baseline for contour size and shape. DIR was done with the MR Correctable Deformable DIR method, and all deformed contours were compared with the original contours. The Dice similarity coefficient (DSC) and mean distance to agreement (MDA) were used to quantitatively validate DIR accuracy. We also used large and small regions of interest (ROIs) during between-modality DIR tests to simulate validation of DIR accuracy for organs at risk (OARs) and propagation of individual clinical target volume (CTV) contours. RESULTS: No significant differences in DIR accuracy were found for T1:T1 and T2:T2 comparisons (P > 0.05). DIR was less accurate for between-modality comparisons than for same-modality comparisons, and was less accurate for T1 vs CT than for T2 vs CT (P < 0.001). For between-modality comparisons, use of a small ROI improved DIR accuracy for both T1 and T2 images. CONCLUSION: The simple design of the Wuphantom allows seamless testing of DIR; here we validated the accuracy of MRI DIR in end-to-end testing. T2 images had superior DIR accuracy compared with T1 images. Use of small ROIs improves DIR accuracy for target contour propagation.

Development of a deformable lung phantom with 3D-printed flexible airways.

PURPOSE: Deformable lung phantoms have been proposed to investigate four-dimensional (4D) imaging and radiotherapy delivery techniques. However, most phantoms mimic only the lung and tumor without pulmonary airways. The purpose of this study was to develop a reproducible, deformable lung phantom with three-dimensional (3D)-printed airways. METHODS: The phantom consists of: (a) 3D-printed flexible airways, (b) flexible polyurethane foam infused with iodinated contrast agents, and (c) a motion platform. The airways were simulated using publicly available breath-hold computed tomography (CT) image datasets of a human lung through airway segmentation, computer-aided design modeling, and 3D printing with a rubber-like material. The lung was simulated by pouring liquid expanding foam into a mold with the 3D-printed airways attached. Iodinated contrast agents were infused into the lung phantom to emulate the density of the human lung. The lung/airways phantom was integrated into our previously developed motion platform, which allows for compression and decompression of the phantom in the superior-inferior direction. We quantified the reproducibility of the density (lung), motion/deformation (lung and airways), and position (airways) using breath-hold CT scans (with the phantom compressed and decompressed) repeated every two weeks over a 2-month period as well as 4D CT scans (with the phantom continuously compressed and decompressed) repeated twice over four weeks. The density reproducibility was quantified with a difference image (created by subtracting the rigidly registered baseline and the repeated images) in each of the compressed and decompressed states. Reproducibility of the motion/deformation was evaluated by comparing the baseline displacement vector fields (DVFs) derived from deformable image registration (DIR) between the compressed and decompressed phantom CT images with those of repeated scans and calculating the difference in the displacement vectors. Reproducibility of the airway position was quantified based on DIR between the baseline and repeated images. RESULTS: For the breath-hold CT scans, the mean difference in lung density between baseline and week 8 was -1.3 (standard deviation 33.5) Hounsfield unit (HU) in the compressed state and 0.4 (36.8) HU in the decompressed state, while large local differences were observed around the high-contrast structures (caused by small misalignments). By visual inspection, the DVFs (between the compressed and decompressed states) at baseline and last time point (week 8 for the breath-hold CT scans) demonstrated a similar pattern. The mean lengths of displacement vector differences between baseline and week 8 were 0.5 (0.4) mm for the lung and 0.3 (0.2) mm for the airways. The mean airway displacements between baseline and week 8 were 0.6 (0.5) mm in the compressed state and 0.6 (0.4) mm in the decompressed state. We also observed similar results for the 4D CT scans (week 0 vs week 4) as well as for the breath-hold CT scans at other time points (week 0 vs weeks 2, 4, and 6). CONCLUSIONS: We have developed a deformable lung phantom with 3D-printed airways based on a human lung CT image. Our findings indicate reproducible density, motion/deformation, and position. This phantom is based on widely available materials and technology, which represents advantages over other deformable phantoms.

Quantifying the accuracy of deformable image registration for cone-beam computed tomography with a physical phantom.

PURPOSE: Kilo-voltage cone-beam computed tomography (CBCT) is widely used for patient alignment, contour propagation, and adaptive treatment planning in radiation therapy. In this study, we evaluated the accuracy of deformable image registration (DIR) for CBCT under various imaging protocols with different noise and patient dose levels. METHODS: A physical phantom previously developed to facilitate end-to-end testing of the DIR accuracy was used with Varian Velocity v4.0 software to evaluate the performance of image registration from CT to CT, CBCT to CT, and CBCT to CBCT. The phantom is acrylic and includes several inserts that simulate different tissue shapes and properties. Deformations and anatomic changes were simulated by changing the rotations of both the phantom and the inserts. CT images (from a head and neck protocol) and CBCT images (from pelvis, head and "Image Gently" protocols) were obtained with different image noise and dose levels. Large inserts were filled with Mobil DTE oil to simulate soft tissue, and small inserts were filled with bone materials. All inserts were contoured before the DIR process to provide a ground truth contour size and shape for comparison. After the DIR process, all deformed contours were compared with the originals using Dice similarity coefficient (DSC) and mean distance to agreement (MDA). Both large and small volume of interests (VOIs) for DIR volume selection were tested by simulating a DIR process that included whole patient image volume and clinical target volumes (CTV) only (for CTVs propagation). RESULTS: For cross-modality DIR registration (CT to CBCT), the DSC were >0.8 and the MDA were <3 mm for CBCT pelvis, and CBCT head protocols. For CBCT to CBCT and CT to CT, the DIR accuracy was improved relative to the cross-modality tests. For smaller VOIs, the DSC were >0.8 and MDA <2 mm for all modalities. CONCLUSIONS: The accuracy of DIR depends on the quality of the CBCT image at different dose and noise levels.

Deformable phantoms of the prostatic urinary tract for urodynamic investigations.

PURPOSE: Assessment of urethral dynamics is clinically regarded to be important in analyzing the functional impact of pathological features like urethral obstruction, albeit it is difficult to perform directly in vivo. To facilitate such an assessment, urethra phantoms may serve well as investigative tools by reconstructing urethral dynamics based on anthropomorphic factors. Here, our aim is to design a new class of anatomically realistic, deformable urethra phantoms that can simulate the geometric, mechanical, and hydrodynamic characteristics of the male prostatic urethra. METHODS: A new lost-core tube casting protocol was devised. It first involved the drafting of urethra geometry in computer-aided design software. Next, 3D printing was used to fabricate the urethra geometry and an outer mold. These parts were then used to cast a urinary tract using a polyvinyl alcohol (PVA)-based material (with 26.6 ± 4.0 kPa Young's elastic modulus). After forming a surrounding tissue-mimicking slab using an agar-gelatin mixture (with 17.4 ± 3.4 kPa Young's modulus), the completed urethra phantom was connected to a flow circuit that simulates voiding. To assess the fabricated phantoms' morphology, ultrasound imaging was performed over different planes. Also, color Doppler imaging was performed to visualize the flow profile within the urinary tract. RESULTS: Deformable phantoms were devised for the normal urethra and a diseased urethra with obstruction due to benign prostatic hyperplasia (BPH). During voiding, the short-axis lumen diameter at the verumontanum of the BPH-featured phantom (0.91 ± 0.08 mm) was significantly smaller than that for the normal phantom (2.49 ± 0.20 mm). Also, the maximum flow velocity of the BPH-featured phantom (59.3 ± 5.8 cm/s; without Doppler angle correction) was found to be higher than that of the normal phantom (22.7 ± 9.0 cm/s). CONCLUSION: The fabricated phantoms were effective in simulating urethra deformation resulting from urine passage during voiding. They can be used for mechanistic studies of urethral dynamics and for the testing of urodynamic diagnostic techniques in urology.

A multiparametric method to assess the MIM deformable image registration algorithm.

A quantitative evaluation of the performances of the deformable image registration (DIR) algorithm implemented in MIM-Maestro was performed using multiple similarity indices. Two phantoms, capable of mimicking different anatomical bending and tumor shrinking were built and computed tomography (CT) studies were acquired after applying different deformations. Three different contrast levels between internal structures were artificially created modifying the original CT values of one dataset. DIR algorithm was applied between datasets with increasing deformations and different contrast levels and manually refined with the Reg Refine tool. DIR algorithm ability in reproducing positions, volumes, and shapes of deformed structures was evaluated using similarity indices such as: landmark distances, Dice coefficients, Hausdorff distances, and maximum diameter differences between segmented structures. Similarity indices values worsen with increasing bending and volume difference between reference and target image sets. Registrations between images with low contrast (40 HU) obtain scores lower than those between images with high contrast (970 HU). The use of Reg Refine tool leads generally to an improvement of similarity parameters values, but the advantage is generally less evident for images with low contrast or when structures with large volume differences are involved. The dependence of DIR algorithm on image deformation extent and different contrast levels is well characterized through the combined use of multiple similarity indices.

Characterization of a new physical phantom for testing rigid and deformable image registration.

The purpose of this study was to describe a new user-friendly, low-cost phantom that was developed to test the accuracy of rigid and deformable image registration (DIR) systems and to demonstrate the functional efficacy of the new phantom. The phantom was constructed out of acrylic and includes a variety of inserts that simulate different tissue shapes and properties. It can simulate deformations and location changes in patient anatomy by changing the rotations of both the phantom and the inserts. CT scans of this phantom were obtained and used to test the rigid and deformable registration accuracy of the Velocity software. Eight rotation and translation scenarios were used to test the rigid registration accuracy, and 11 deformation scenarios were used to test the DIR accuracy. The mean rotation accuracies in the X-Y (axial) and X-Z (coronal) planes were 0.50° and 0.13°, respectively. The mean translation accuracy was 1 mm in both the X and Y direction and was tested in soft tissue and bone. The DIR accuracies for soft tissue and bone were 0.93 (mean Dice similarity coefficient), 8.3 and 4.5 mm (mean Hausdouff distance), 0.95 and 0.79 mm (mean distance), and 1.13 and 1.12 (mean volume ratio) for soft tissue content (DTE oil) and bone, respectively. The new phantom has a simple design and can be constructed at a low cost. This phantom will allow DIR systems to be effectively and efficiently verified to ensure system performance.

Accuracy of deformable image registration on magnetic resonance images in digital and physical phantoms.

PURPOSE: Accurate deformable image registration is necessary for longitudinal studies. The error associated with commercial systems has been evaluated using computed tomography (CT). Several in-house algorithms have been evaluated for use with magnetic resonance imaging (MRI), but there is still relatively little information about MRI deformable image registration. This work presents an evaluation of two deformable image registration systems, one commercial (Velocity) and one in-house (demons-based algorithm), with MRI using two different metrics to quantify the registration error. METHODS: The registration error was analyzed with synthetic MR images. These images were generated from interpatient and intrapatient variation models trained on 28 patients. Four synthetic post-treatment images were generated for each of four synthetic pretreatment images, resulting in 16 image registrations for both the T1- and T2-weighted images. The synthetic post-treatment images were registered to their corresponding synthetic pretreatment image. The registration error was calculated between the known deformation vector field and the generated deformation vector field from the image registration system. The registration error was also analyzed using a porcine phantom with ten implanted 0.35-mm diameter gold markers. The markers were visible on CT but not MRI. CT, T1-weighted MR, and T2-weighted MR images were taken in four different positions. The markers were contoured on the CT images and rigidly registered to their corresponding MR images. The MR images were deformably registered and the distance between the projected marker location and true marker location was measured as the registration error. RESULTS: The synthetic images were evaluated only on Velocity. Root mean square errors (RMSEs) of 0.76 mm in the left-right (LR) direction, 0.76 mm in the anteroposterior (AP) direction, and 0.69 mm in the superior-inferior (SI) direction were observed for the T1-weighted MR images. RMSEs of 1.1 mm in the LR direction, 0.75 mm in the AP direction, and 0.81 mm in the SI direction were observed for the T2-weighted MR images. The porcine phantom MR images, when evaluated with Velocity, had RMSEs of 1.8, 1.5, and 2.7 mm in the LR, AP, and SI directions for the T1-weighted images and 1.3, 1.2, and 1.6 mm in the LR, AP, and SI directions for the T2-weighted images. When the porcine phantom images were evaluated with the in-house demons-based algorithm, RMSEs were 1.2, 1.5, and 2.1 mm in the LR, AP, and SI directions for the T1-weighted images and 0.81, 1.1, and 1.1 mm in the LR, AP, and SI directions for the T2-weighted images. CONCLUSIONS: The MRI registration error was low for both Velocity and the in-house demons-based algorithm according to both image evaluation methods, with all RMSEs below 3 mm. This implies that both image registration systems can be used for longitudinal studies using MRI.

An anthropomorphic abdominal phantom for deformable image registration accuracy validation in adaptive radiation therapy.

PURPOSE: To design and construct a three-dimensional (3D) anthropomorphic abdominal phantom for geometric accuracy and dose summation accuracy evaluations of deformable image registration (DIR) algorithms for adaptive radiation therapy (ART). METHOD: Organ molds, including liver, kidney, spleen, stomach, vertebra, and two metastasis tumors, were 3D printed using contours from an ovarian cancer patient. The organ molds were molded with deformable gels made of different mixtures of polyvinyl chloride (PVC) and the softener dioctyl terephthalate. Gels with different densities were obtained by a polynomial fitting curve that described the relation between the Hounsfield unit (HU) and PVC-softener blending ratio. The rigid vertebras were constructed by molding of white cement and cellulose pulp. The final abdominal phantom was assembled by arranging all the fabricated organs inside a hollow dummy according to their anatomies, and sealed by deformable gel with averaged HU of muscle and fat. Fiducial landmarks were embedded inside the phantom for spatial accuracy and dose accumulation accuracy studies. Two channels were excavated to facilitate ionization chamber insertion for dosimetric measurements. Phantom properties such as deformable gel elasticity and HU stability were studied. The dosimetric measurement accuracy in the phantom was performed, and the DIR accuracies of three DIR algorithms available in the open source DIR toolkit-DIRART were also validated. RESULTS: The constructed deformable gel showed elastic behavior and was stable in HU values over times, proving to be a practical material for the deformable phantom. The constructed abdominal phantom consisted of realistic anatomies in terms of both anatomical shapes and densities when compared with its reference patient. The dosimetric measurements showed a good agreement with the calculated doses from the treatment planning system. Fiducial-based accuracy analysis conducted on the constructed phantom demonstrated the feasibility of applying the phantom for organ-wise DIR accuracy assessment. CONCLUSIONS: We have designed and constructed an anthropomorphic abdominal deformable phantom with satisfactory elastic property, realistic organ density, and anatomy. This physical phantom can be used for routine validations of DIR geometric accuracy and dose accumulation accuracy in ART.

Construction of an anthropopathic abdominal phantom for accuracy validation of deformable image registration.

The purpose of this study is to design and fabricate an anthropopathic abdominal phantom for accuracy evaluation of deformable image registration (DIR) algorithms in adaptive radiation therapy. The constructed deformable organs, including the liver, kidney, spleen and stomach, are made of mixture of polyvinyl chloride (PVC) and softener dioctyl terephthalate, while the rigid structures, i.e. vertebrae, are made of white cement. Relation between the PVC-softener blending ratio and organ CT number is studied, and three-dimensional printing technic is employed to create highly anthropopathic organs in terms of organ shape and density. Detailed steps for phantom construction, landmark point placement and choice of phantom ingredients and construction recipe are introduced. Preliminary results of the mechanical properties of the fabricated organs are also presented. The experimental results indicate that the constructed phantom has satisfactory elastic characteristics and close CT number with corporal organs, and can potentially be applied to simulate real abdominal organ deformation in geometric accuracy validation of DIR algorithms.