Digital Human Phantom Research Articles

Respiratory-Correlated 4-Dimensional Magnetic Resonance Fingerprinting for Liver Cancer Radiation Therapy Motion Management

The objective of this study was to develop a respiratory-correlated (RC) 4-dimensional (4D) imaging technique based on magnetic resonance fingerprinting (MRF) (RC-4DMRF) for liver tumor motion management in radiation therapy. Thirteen patients with liver cancer were prospectively enrolled in this study. k-space MRF signals of the liver were acquired during free-breathing using the fast acquisition with steady-state precession sequence on a 3T scanner. The signals were binned into 8 respiratory phases based on respiratory surrogates, and interphase displacement vector fields were estimated using a phase-specific low-rank optimization method. Hereafter, the tissue property maps, including T1 and T2 relaxation times, and proton density, were reconstructed using a pyramid motion-compensated method that alternatively optimized interphase displacement vector fields and subspace images. To evaluate the efficacy of RC-4DMRF, amplitude motion differences and Pearson correlation coefficients were determined to assess measurement agreement in tumor motion between RC-4DMRF and cine magnetic resonance imaging (MRI); mean absolute percentage errors of the RC-4DMRF-derived tissue maps were calculated to reveal tissue quantification accuracy using digital human phantom; and tumor-to-liver contrast-to-noise ratio of RC-4DMRF images was compared with that of planning CT and contrast-enhanced MRI (CE-MRI) images. A paired Student t test was used for statistical significance analysis with a P value threshold of .05. RC-4DMRF achieved excellent agreement in motion measurement with cine MRI, yielding the mean (± standard deviation) Pearson correlation coefficients of 0.95 ± 0.05 and 0.93 ± 0.09 and amplitude motion differences of 1.48 ± 1.06 mm and 0.81 ± 0.64 mm in the superior-inferior and anterior-posterior directions, respectively. Moreover, RC-4DMRF achieved high accuracy in tissue property quantification, with mean absolute percentage errors of 8.8%, 9.6%, and 5.0% for T1, T2, and proton density, respectively. Notably, the tumor contrast-to-noise ratio in RC-4DMRI-derived T1 maps (6.41 ± 3.37) was found to be the highest among all tissue property maps, approximately equal to that of CE-MRI (6.96 ± 1.01, P=.862), and substantially higher than that of planning CT (2.91 ± 1.97, P=.048). RC-4DMRF demonstrated high accuracy in respiratory motion measurement and tissue properties quantification, potentially facilitating tumor motion management in liver radiation therapy.

Tailoring Instantaneous Time Mirrors for Time Reversal Focusing in Absorbing Media

The time reversal symmetry of the wave equation allows wave refocusing back at the source. However, this symmetry does not hold in lossy media. We present a new strategy to compensate wave amplitude losses due to attenuation. The strategy leverages the instantaneous time mirror (ITM) which generates reversed waves by a sudden disruption of the medium properties. We create a heterogeneous ITM whose disruption is unequal throughout the space to create waves of different amplitude. The time-reversed waves can then cope with different attenuation paths as typically seen in heterogeneous and lossy environments. We consider an environment with biological tissues and apply the strategy to a two-dimensional digital human phantom from the abdomen. A stronger disruption is introduced where forward waves suffer a history of higher attenuation, with a weaker disruption elsewhere. Computer simulations show heterogeneous ITM is a promising technique to improve time reversal refocusing in heterogeneous, lossy, and dispersive spaces.

Improving liver tumor image contrast and synthesizing novel tissue contrasts by adaptive multiparametric MRI fusion.

Multiparametric MRI contains rich and complementary anatomical and functional information, which is often utilized separately. This study aims to propose an adaptive multiparametric MRI (mpMRI) fusion method and examine its capability in improving tumor contrast and synthesizing novel tissue contrasts among liver cancer patients. An adaptive mpMRI fusion method was developed with five components: image pre-processing, fusion algorithm, database, adaptation rules, and fused MRI. Linear-weighted summation algorithm was used for fusion. Weight-driven and feature-driven adaptations were designed for different applications. A clinical-friendly graphic-user-interface (GUI) was developed in Matlab and used for mpMRI fusion. Twelve liver cancer patients and a digital human phantom were included in the study. Synthesis of novel image contrast and enhancement of image signal and contrast were examined in patient cases. Tumor contrast-to-noise ratio (CNR) and liver signal-to-noise ratio (SNR) were evaluated and compared before and after mpMRI fusion. The fusion platform was applicable in both XCAT phantom and patient cases. Novel image contrasts, including enhancement of soft-tissue boundary, vertebral body, tumor, and composition of multiple image features in a single image were achieved. Tumor CNR improved from -1.70 ± 2.57 to 4.88 ± 2.28 (p < 0.0001) for T1-w, from 3.39 ± 1.89 to 7.87 ± 3.47 (p < 0.01) for T2-w, and from 1.42 ± 1.66 to 7.69 ± 3.54 (p < 0.001) for T2/T1-w MRI. Liver SNR improved from 2.92 ± 2.39 to 9.96 ± 8.60 (p < 0.05) for DWI. The coefficient of variation (CV) of tumor CNR lowered from 1.57, 0.56, and 1.17 to 0.47, 0.44, and 0.46 for T1-w, T2-w and T2/T1-w MRI, respectively. A multiparametric MRI fusion method was proposed and a prototype was developed. The method showed potential in improving clinically relevant features such as tumor contrast and liver signal. Synthesis of novel image contrasts including the composition of multiple image features into single image set was achieved.

Resolution Enhancement of UWB Time-Reversal Microwave Imaging in Dispersive Environments

Time Reversal (TR) techniques allow optimal refocusing of ultrawideband (UWB) electromagnetic waves in complex propagation environments, due to the invariance of the wave equations. Propagation of electromagnetic waves through dispersive or lossy media breaks this invariance. Consequently, such media degrade the refocusing ability of TR techniques. In this work, we propose a novel algorithm for the enhancement of the UWB TR microwave imaging resolution in dispersive environments. The presented algorithm takes into account the frequency-dependent complex permittivity of the propagation medium across the entire bandwidth of the UWB pulse. Using this complex permittivity, it models the medium-, time-, and frequency- dependent attenuation in the wavelet domain to create inverse filters which compensate for the effects of the attenuation. This is the first algorithm that constructs inverse filters in the wavelet domain using the complex permittivity of the dispersive propagation medium across the entire bandwidth, rather than at a center frequency, of the excitation pulse. We also introduce a smart scaling concept to minimize undesired noise amplification. While our proposed approach is agnostic to the application scenario and thus could be utilized in various disciplines, we apply it in a biomedical imaging scenario and achieve enhancement in the resolution of UWB microwave TR imaging of a simulated brain tumor inside the digital human phantom (DHP).

Primary, scatter, and penetration characterizations of parallel-hole and pinhole collimators for I-123 SPECT

Multi-pinhole (MPH) collimators are known to provide better trade-off between sensitivity and resolution for preclinical, as well as for smaller regions in clinical SPECT imaging compared to conventional collimators. In addition to this geometric advantage, MPH plates typically offer better stopping power for penetration than the conventional collimators, which is especially relevant for I-123 imaging. The I-123 emits a series of high-energy (>300 keV, ~2.5% abundance) gamma photons in addition to the primary emission (159 keV, 83% abundance). Despite their low abundance, high-energy photons penetrate through a low-energy parallel-hole (LEHR) collimator much more readily than the 159 keV photons, resulting in large downscatter in the photopeak window. In this work, we investigate the primary, scatter, and penetration characteristics of a single pinhole collimator that is commonly used for I-123 thyroid imaging and our two MPH collimators designed for I-123 DaTscan imaging for Parkinson’s Disease, in comparison to three different parallel-hole collimators through a series of experiments and Monte Carlo simulations. The simulations of a point source and a digital human phantom with DaTscan activity distribution showed that our MPH collimators provide superior count performance in terms of high primary counts, low penetration, and low scatter counts compared to the parallel-hole and single pinhole collimators. For example, total scatter, multiple scatter, and collimator penetration events for the LEHR were 2.5, 7.6 and 14 times more than that of MPH within the 15% photopeak window. The total scatter fraction for LEHR was 56% where the largest contribution came from the high-energy scatter from the back compartments (31%). For the same energy window, the total scatter for MPH was 21% with only 1% scatter from the back compartments. We therefore anticipate that using MPH collimators, higher quality reconstructions can be obtained in a substantially shorter acquisition time for I-123 DaTscan and thyroid imaging.

Respiratory motion compensation in interventional liver SPECT using simultaneous fluoroscopic and nuclear imaging.

PurposeQuantitative accuracy of the single photon emission computed tomography (SPECT) reconstruction of the pretreatment procedure of liver radioembolization is crucial for dosimetry; visual quality is important for detecting doses deposited outside the planned treatment volume. Quantitative accuracy is limited by respiratory motion. Conventional gating eliminates motion by count rejection but increases noise, which degrades the visual reconstruction quality. Motion compensation using all counts can be performed if the motion signal and motion vector field over time are known. The measurement of the motion signal of a patient currently requires a device (such as a respiratory belt) attached to the patient, which complicates the acquisition. The motion vector field is generally extracted from a previously acquired four‐dimensional scan and can differ from the motion in the scan performed during the intervention. The simultaneous acquisition of fluoroscopic and nuclear projections can be used to obtain both the motion vector field and the projections of the corresponding (moving) activity distribution. This eliminates the need for devices attached to the patient and provides an accurate motion vector field for SPECT reconstruction. Our approach to motion compensation would primarily be beneficial for interventional SPECT because the time‐critical setting requires fast scans and no inconvenience of an external apparatus. The purpose of this work is to evaluate the performance of the motion compensation approach for interventional liver SPECT by means of simulations.MethodsNuclear and fluoroscopic projections of a realistic digital human phantom with respiratory motion were generated using fast Monte Carlo simulators. Fluoroscopic projections were sampled at 1–5 Hz. Nuclear data were acquired continuously in list mode. The motion signal was extracted from the fluoroscopic projections by calculating the center‐of‐mass, which was then used to assign each photon to a corresponding motion bin. The fluoroscopic projections were reconstructed per bin and coregistered, resulting in a motion vector field that was used in the SPECT reconstruction. The influence of breathing patterns, fluoroscopic imaging dose, sampling rate, number of bins, and scanning time was studied. In addition, the motion compensation method was compared with conventional gating to evaluate the detectability of spheres with varying uptake ratios.ResultsThe liver motion signal was accurately extracted from the fluoroscopic projections, provided the motion was stable in amplitude and the sampling rate was greater than 2 Hz. The minimum total fluoroscopic dose for the proposed method to function in a 5‐min scan was 10 µGy. Although conventional gating improved the quantitative reconstruction accuracy, substantial background noise was observed in the short scans because of the limited counts available. The proposed method similarly improved the quantitative accuracy, but generated reconstructions with higher visual quality. The proposed method provided better visualization of low‐contrast features than when using gating.ConclusionThe proposed motion compensation method has the potential to improve SPECT reconstruction quality. The method eliminates the need for external devices to measure the motion signal and generates an accurate motion vector field for reconstruction. A minimal increase in the fluoroscopic dose is required to substantially improve the results, paving the way for clinical use.

A Multi-Source Adaptive MR Image Fusion Technique for MR-Guided Radiation Therapy

Current radiation oncology practice to capture clinical indications like tumor from MR images is to review multiple types of MRI separately, which can be inefficient and tumor contrast is limited by existing MRI. The purpose of this study is to develop an integrated MR image fusion technique to adaptively fuse multi-source standard MRI for improved MR-guided radiation therapy applications. The hypothesis is that by integrating multi-source MR images, tumor contrast can be enhanced and the efficiency of using multiple MR images can be improved. The multi-source adaptive MRI fusion technique is designed with five key components: input multiple MRI, image pre-processing, fusion algorithm, adaptation methods, and output fused MRI. T1-weighted (T1-w), T2-weighted (T2-w), cine and diffusion-weighted MRI (DWI) were used as source images. Deformable image registration is applied to align all images to T2-w MRI. A linear-weighting algorithm Yi = ∑wik⋅Xk is used for fusion, where Xk is the kth source image, wik is the weighting factor of the kth source image in the ith fused image Yi, w∈[-1,1] with an interval of 0.2. Features of fused images are extracted, including signal-to-noise-ratio (SNR) and contrast-to-noise-ratio (CNR) of tumor and major organs. The weighting factors and image features are pre-calculated and saved in a database for fast adaptation operation. Weighting-factor driven and image-feature driven approaches are developed for MRI fusion adaptation. Digital human phantom (XCAT) and seven liver cancer patients were evaluated. Multiple new organ contrasts were explored and tumor CNR were quantified and compared before and after adaptive fusion using Student’s t-test. Hundreds of fused MR images with versatile image contrasts were generated in both XCAT phantom and liver cancer patients. In XCAT phantom, versatile new organ contrasts were achieved, including tumor, vertebral body, and blood vessel enhancement, respectively. In the patient study, tumor contrasts were significantly improved (mean: 14.83 ± 7.72 vs. 1.5 ± 0.65, 2.54 ± 1.31, 2.24 ± 2.23, 3.72 ± 2.45 and 0.74 ± 0.66 in T1-w, T2-w, cine, DWI, and CT, respectively) (p-values: 0.003∼0.010). Multiple new contrast MR images were efficiently generated, including liver, vertebral body, and cerebrospinal fluid enhancement, respectively. A novel multi-source adaptive image fusion technique capable of generating versatile contrast MRI from a limited number of standard MR images was developed. This method has the potential to improve tumor contrast, as well as the effectiveness and efficiency of multiple MR applications in radiation therapy.

Four-dimensional diffusion-weighted MR imaging (4D-DWI): a feasibility study.

Diffusion-weighted Magnetic Resonance Imaging (DWI) has been shown to be a powerful tool for cancer detection with high tumor-to-tissue contrast. This study aims to investigate the feasibility of developing a four-dimensional DWI technique (4D-DWI) for imaging respiratory motion for radiation therapy applications. Image acquisition was performed by repeatedly imaging a volume of interest (VOI) using an interleaved multislice single-shot echo-planar imaging (EPI) 2D-DWI sequence in the axial plane. Each 2D-DWI image was acquired with an intermediately low b-value (b=500s/mm2 ) and with diffusion-encoding gradients in x, y, and z diffusion directions. Respiratory motion was simultaneously recorded using a respiratory bellow, and the synchronized respiratory signal was used to retrospectively sort the 2D images to generate 4D-DWI. Cine MRI using steady-state free precession was also acquired as a motion reference. As a preliminary feasibility study, this technique was implemented on a 4D digital human phantom (XCAT) with a simulated pancreas tumor. The respiratory motion of the phantom was controlled by regular sinusoidal motion profile. 4D-DWI tumor motion trajectories were extracted and compared with the input breathing curve. The mean absolute amplitude differences (D) were calculated in superior-inferior (SI) direction and anterior-posterior (AP) direction. The technique was then evaluated on two healthy volunteers. Finally, the effects of 4D-DWI on apparent diffusion coefficient (ADC) measurements were investigated for hypothetical heterogeneous tumors via simulations. Tumor trajectories extracted from XCAT 4D-DWI were consistent with the input signal: the average D value was 1.9mm (SI) and 0.4mm (AP). The average D value was 2.6mm (SI) and 1.7mm (AP) for the two healthy volunteers. A 4D-DWI technique has been developed and evaluated on digital phantom and human subjects. 4D-DWI can lead to more accurate respiratory motion measurement. This has a great potential to improve the visualization and delineation of cancer tumors for radiotherapy.

SU-F-R-29: The Influence of Four Dimensional Diffusion-Weighted MRI (4D-DWI) On Feature Analysis of Time-Resolved Apparent Diffusion Coefficient (ADC) Measurement: Initial Evaluation

Purpose: Diffusion-weighted imaging (DWI) has been shown to have superior tumor-to-tissue contrast for cancer detection compared to other MRI sequences and CT. This study aims at developing and evaluating the effects of the four dimensional DWI (4D-DWI) technique on the feature analysis of time-resolved Apparent Diffusion Coefficient (ADC) measurement. Methods: Image acquisition was performed by repeatedly imaging a volume of interest using a multi-slice single-shot 2D-DWI sequence in the axial planes. Each 2D-DWI image was acquired sequentially in the x, y, and z-diffusion-directions (b=500s/mm2). Respiratory motion was simultaneously recorded using bellows. Retrospective sorting was conducted to reconstruct 4D-DWI. As a comparison, free breathing DWI (FB-DWI) was also reconstructed using the same dataset. Subsequently, ADC maps were measured for 4D-DWI and FB-DWI data. The technique was implemented on a digital human phantom (XCAT). It was programmed to simulate regular motion. Motion trajectories of tumor were extracted from 4D-DWI and compared with average input breathing curve. The mean amplitude difference(D) was calculated. To quantitatively analyze the effect of 4D-DWI on time-resolved ADC maps, feature analysis was conducted on tumor region for the time-resolved ADC maps and the free breathing ADC maps. 3D XCAT images were served as the reference. The following features were calculated: mean tumor ADC value, entropy, energy, kurtosis, skewness, homogeneity, sphericity, tumor surface area and tumor contrast. Results: 4D-DWI of XCAT digital phantom demonstrated the respiratory motion clearly. The values of D were 1.9mm, 1.7mm and 2.0mm, respectively. The feature analysis shows that the texture of tumor demonstrated on time-resolved ADC maps was significantly closer to the reference than the free breathing ADC maps. Conclusion: The influence of 4D-DWI technique on feature analysis of time-resolved ADC measurement was initially evaluated on a digital human phantom. Comparing to free breathing DWI, 4D-DWI can lead to more accurate measurement of ADC. NIH (1R21CA165384-01A1)

TH‐EF‐BRA‐06: A Novel Retrospective 3D K‐Space Sorting 4D‐MRI Technique Using a Radial K‐Space Acquisition MRI Sequence

Purpose:Current retrospective 4D‐MRI provides superior tumor‐to‐tissue contrast and accurate respiratory motion information for radiotherapy motion management. The developed 4D‐MRI techniques based on 2D‐MRI image sorting require a high frame‐rate of the MR sequences. However, several MRI sequences provide excellent image quality but have low frame‐rate. This study aims at developing a novel retrospective 3D k‐space sorting 4D‐MRI technique using radial k‐space acquisition MRI sequences to improve 4D‐MRI image quality and temporal‐resolution for imaging irregular organ/tumor respiratory motion.Methods:The method is based on a RF‐spoiled, steady‐state, gradient‐recalled sequence with minimal echo time. A 3D radial k‐space data acquisition trajectory was used for sampling the datasets. Each radial spoke readout data line starts from the 3D center of Field‐of‐View. Respiratory signal can be extracted from the k‐space center data point of each spoke. The spoke data was sorted based on its self‐synchronized respiratory signal using phase sorting. Subsequently, 3D reconstruction was conducted to generate the time‐resolved 4D‐MRI images. As a feasibility study, this technique was implemented on a digital human phantom XCAT. The respiratory motion was controlled by an irregular motion profile. To validate using k‐space center data as a respiratory surrogate, we compared it with the XCAT input controlling breathing profile. Tumor motion trajectories measured on reconstructed 4D‐MRI were compared to the average input trajectory. The mean absolute amplitude difference (D) was calculated.Results:The signal extracted from k‐space center data matches well with the input controlling respiratory profile of XCAT. The relative amplitude error was 8.6% and the relative phase error was 3.5%. XCAT 4D‐MRI demonstrated a clear motion pattern with little serrated artifacts. D of tumor trajectories was 0.21mm, 0.23mm and 0.23mm in SI, AP and ML directions, respectively.Conclusion:A novel retrospective 3D k‐space sorting 4D‐MRI technique has been developed and evaluated on human digital phantom.NIH (1R21CA165384‐01A1)

Target-Matching Accuracy in Stereotactic Body Radiation Therapy of Lung Cancer: An Investigation Based on Four-Dimensional Digital Human Phantom

Aim: To investigate the effect of irregular respiratory on target-matching accuracy in lung stereotactic-body radiation therapy (SBRT). Methods: The four-dimensional extended cardiac torso (4D-XCAT) phantom was used to generate 4D computed tomography (4DCT) and cone-beam CT (CBCT) images. Images were generated for 1 regular and 10 irregular trajectories, and for 3 tumor size groups (1, 2, and 3 cm). Image registrations between CBCT and average intensity projection (AIP) images of 4DCT were performed based on target volume matching. Error of registration was determined as the difference between manual CBCT-to-AIP registration and known registration between the two. In addition, internal target volumes (ITVs) were contoured on and compared between AIP, maximum intensity projection (MIP), and CBCT. Results: Small inter-observer variations of registration were found: 0.2, 0.3, and 0.7 mm in the medial-lateral (ML), anterior-posterior (AP), and superior-inferior (SI) direction, respectively. Small errors of registration (median ≤ 0.5 mm) were found in all three directions for the regular respiratory profile. For the irregular profiles and on average of all tumor size groups, the median ± standard deviation (SD) errors of registration were 0.5 ± 0.3 mm, 0.4 ± 0.5 mm, and 1.9 ± 1.6 mm in the ML, AP, and SI direction, respectively. Significant differences were found between MIP and CBCT-based ITV volumes for the three tumor size groups (P = 0.011, 0.010, and 0.006 for 1, 2, and 3 cm tumor size group, respectively). Conclusion: Irregular breathing can induce error in CBCT-to-AIP registration in lung SBRT. This error increases as the breathing irregularity increases.

SU‐D‐18C‐01: A Novel 4D‐MRI Technology Based On K‐Space Retrospective Sorting

Purpose:Current 4D‐MRI techniques lack sufficient temporal/spatial resolution and consistent tumor contrast. To overcome these limitations, this study presents the development and initial evaluation of an entirely new framework of 4D‐MRI based on k‐space retrospective sorting.Methods:An important challenge of the proposed technique is to determine the number of repeated scans(NR) required to obtain sufficient k‐space data for 4D‐MRI. To do that, simulations using 29 cancer patients' respiratory profiles were performed to derive the relationship between data acquisition completeness(Cp) and NR, also relationship between NR(Cp=95%) and the following factors: total slice(NS), respiratory phase bin length(Lb), frame rate(fr), resolution(R) and image acquisition starting‐phase(P0). To evaluate our technique, a computer simulation study on a 4D digital human phantom (XCAT) were conducted with regular breathing (fr=0.5Hz; R=256×256). A 2D echo planer imaging(EPI) MRI sequence were assumed to acquire raw k‐space data, with respiratory signal and acquisition time for each k‐space data line recorded simultaneously. K‐space data was re‐sorted based on respiratory phases. To evaluate 4D‐MRI image quality, tumor trajectories were measured and compared with the input signal. Mean relative amplitude difference(D) and cross‐correlation coefficient(CC) are calculated. Finally, phase‐sharing sliding window technique was applied to investigate the feasibility of generating ultra‐fast 4D‐MRI.Result:Cp increased with NR(Cp=100*[1‐exp(‐0.19*NR)], when NS=30, Lb=100%/6). NR(Cp=95%) was inversely‐proportional to Lb (r=0.97), but independent of other factors. 4D‐MRI on XCAT demonstrated highly accurate motion information (D=0.67%, CC=0.996) with much less artifacts than those on image‐based sorting 4D‐MRI. Ultra‐fast 4D‐MRI with an apparent temporal resolution of 10 frames/second was reconstructed using the phase‐sharing sliding window technique.Conclusions:A novel 4D‐MRI technology based on k‐space sorting has been successfully developed and evaluated on the digital phantom. Framework established can be applied to a variety of MR sequences, showing great promises to develop the optimal 4D‐MRI technique for many radiation therapy applications.NIH (1R21CA165384‐01A1)

An Integrated Simulation System Based on Digital Human Phantom for 4D Radiation Therapy of Lung Cancer

Purpose: To develop and test an integrated simulation system based on the digital Extended Cardio Torso (XCAT) phantom for 4-dimensional (4D) radiation therapy of lung cancer. Methods: A computer program was developed to facilitate the characterization and implementation of the XCAT phantom for 4D radiation therapy applications. To verify that patient-specific motion trajectories are reproducible with the XCAT phantom, motion trajectories of the diaphragm and chest were extracted from previously acquired MRI scans of five subjects and were imported into the XCAT phantom. The input versus the measured trajectories was compared. Simulation methods of 4D-CT and 4D-cone-beam CT (CBCT) based on the XCAT phantom were developed and tested for regular and irregular respiratory patterns. Simulation of 4D dose delivery was illustrated in a simulated lung stereotactic-body radiation therapy (SBRT) case based on the XCAT phantom. Dosimetric comparison was performed between the planned dose and simulated delivered dose. Result: The overall mean (±standard deviation) difference in motion amplitude between the input and measured trajectories was 1.19 (±0.79) mm for the XCAT phantoms with voxel size of 2 mm. 4D-CT and 4D-CBCT images simulated based on the XCAT phantom were validated using regular respiratory patterns and tested for irregular respiratory patterns. Comparison between simulated 4D dose delivery and planned dose for the lung SBRT case showed comparable results in all dosimetric matrices: the relative differences were 0.3%, 4.0%, 0%, and 2.8%, respectively, for max cord dose, max esophagus dose, mean heart dose, and V20Gy of the lungs. 97.5% of planning target volume (PTV) received prescription dose in the simulated 4D delivery, as compared to 95% of PTV received prescription dose in the plan. Conclusion: We developed an integrated simulation system based on the XCAT digital phantom and illustrated its utility in 4D radiation therapy of lung cancer. This simulation system is potentially a useful tool for quality control and development of imaging and treatment techniques for 4D radiation therapy of lung cancer.

Breathing Irregularity-Induced Uncertainties in Patient Positioning of Lung SBRT: An Investigation Based on a Digital Human Phantom

It has been shown that patients’ irregular breathing can affect the accuracy of 4DCT and CBCT. It is therefore expected that it will also affect the registration between the two. This study aims to quantitatively assess breathing irregularity induced error in CBCT-based patient positioning in lung SBRT.

WE-C-116-07: Tumor Enhancement Using Deformable Image Registration for Four-Dimensional Magnetic Resonance Imaging (4D-MRI): A Feasibility Study

Purpose: We have previously developed a 4D‐MRI technique using the fast imaging sequence employing steady‐state acquisition (FIESTA) sequence, which has suboptimal tumor‐to‐tissue contrast‐to‐noise ratio (CNR) due to its T2*/T1 weighting. This study investigated the feasibility of enhancing the tumor‐to‐tissue CNR using deformable image registration (DIR). Methods: Five patients with cancers in the liver were included in an IRB‐approved study. 4D‐MRI images were acquired on a 1.5T GE scanner and reconstructed off line using in‐house developed program. All patients were also imaged with a T2‐w fast recovery fast spin‐echo (FRFSE) sequence at the end‐of‐exhalation phase. Deformation vectors between respiratory phases of the 4D‐MRI were determined using commercial software. Pseudo ‘enhanced’ 4D‐MRI was then generated by applying the deformation vectors to the T2‐w FRFSE MR images. Motion trajectories of tumor and diaphragm and tumor‐to‐tissue CNR were compared between the original T2*/T1‐w 4D‐MRI and the ‘enhanced’ T2‐w 4D‐MRI. To validate our method, we performed a simulation study based on a 4D digital human phantom. MR images with T2*/T1‐w and T2‐w with were generated by assigning organ intensities corresponding to those in FIESTA and FRFSE images, respectively. Results: In the phantom study, motion trajectories of the hypothesized ‘tumor’ matched excellently between the original T2*/T1‐w 4D‐MRI and the ‘enhanced’ T2‐w 4D‐MRI. Mean(±SD) absolute difference in motion amplitude was 0.66 (±0.62) mm. In the patient study, tumor and diaphragm motion trajectories closely matched between the two 4D‐MRIs: mean correlation coefficient was great than 0.97 in all directions; the mean (±SD) absolute difference in motion amplitude was smaller than 0.55(±0.19) mm. Tumor‐to‐tissue CNR was significantly improved from 7.57(±5.6) in the original 4D‐MRI to 23.75(±15.8) in the ‘enhanced’ 4D‐MRI. Conclusion: It is feasible to improve tumor‐to‐tissue CNR of T2*/T1‐w 4D‐MRI using the DIR method. The ‘enhanced’ 4D‐MRI retained comparable tumor motion information as the original 4D‐MRI. This work is partly supported by funding from NIH (1R21CA165384‐01A1) and a research grant from the Golfers Against Cancer (GAC) Foundation.

TH‐C‐141‐07: T2‐Weighted 4D‐MRI with Combined Phase and Amplitude Sorting

Purpose: T2‐weighted MR provides excellent delineation of malignant liver lesions due to its superior tumor‐to‐tissue contrast. This study aims to develop a novel T2‐weighted retrospective 4D‐MRI technique for imaging organ/tumor respiratory motion with improved soft‐tissue contrast. Method and Materials: Determine the number of repeated scans (NR) required obtaining sufficient phase information for each slice is the critical component in developing this technique and needs substantial testing with many samples. To do that, computer simulations using RPM respiratory signals of 29 cancer patients were performed to derive the relationships between NR and the following factors: number of slice to scanned (Ns), number of respiratory phases of the 4D‐MRI (Np), and starting phase at image acquisition (P0). Assuming T2‐w HASTE/SSFSE MR sequence to be used to acquire raw images for 4D‐MRI, frame rate of 2 frames/s was used in the simulation. To validate our technique, 4D‐MRI acquisition and reconstruction were simulated on a 4D digital human phantom using parameters derived from the above studies. Retrospective sorting of 4D‐MRI was achieved using a novel phase and amplitude hybrid sorting algorithm by effectively utilizing redundant images. Result: Percentage of complete acquisition of all required phases (Cp) increased as NR increased in an inverse‐exponential (Cp=100*[1‐exp(−0.11*NR)],when Ns=50,Np=10) fashion. NR to achieve 95% completion (Cp=95%) of all required phases, defined as the NR needed for 4D‐MRI, is linearly proportional to Np (Nr∼2.86*Np, r=1.0) but independent of NS and P0. Simulated 4D‐MRI on the digital phantom showed clear pattern of respiratory motion. Tumor motion trajectories measured on 4D‐MRI were comparable to the average input signal, with a mean relative difference in motion amplitude of 16%, presumably due to breathing irregularity. Conclusions: A novel T2‐weighted 4D‐MRI technique based on HASTE/SSFSE sequence have been developed and validated. Future evaluation on patients is desired. This work is partly supported by funding from NIH (1R21CA165384‐01A1) and a research grant from the Golfers Against Cancer (GAC) Foundation.

SU-D-218-02: 4D-MRI Based on Body Area (BA) Surrogate and Sagittal Image Acquisition.

4D-MRI based on body area (BA) surrogate using axial image acquisition has been demonstrated. Since respiratory motion mostly occurs in the superior-inferior (SI) direction, it is expected that sagittal acquisition may provide more robust and accurate breathing signal than axial acquisition. The aim of this study was to investigate the feasibility of extracting breathing signals from sagittal images using BA surrogate and its application in 4D-MRI. 7 human subjects were imaged continuously in a single (n=5) or multiple (n=2) sagittal planes using a steady-state precession sequence. Imaging parameters were: TR/TE, 3.7ms/1.21ms; Matrix, 256×166; FOV, 350×300mm; flip angle, 52°; slice thickness, 5mm; frame rate: ∼3 frames/s. Imaging time per slice is 2 minutes for single slice acquisition and ∼10 seconds for multi-slice acquisition. Breathing signals were generated for all subjects by tracking the change of BA. The multi-slice sagittal acquisition was performed on a MRI- compatible motion phantom with a cylindrical gel target and was simulated on a 4D digital human phantom. Breathing signals were extracted from the sagittal images using the BA surrogate. Respiratory phases were calculated. 4D-MRI of both phantoms were retrospectively reconstructed based on the respiratory phases. Breathing signals extracted from both single slice and multi-slice sagittal acquisitions showed stable and well- characterized patterns. 4D-MRI of the physical phantom showed clear sinusoidal motion of the gel target in all three planes with minimal artifacts. Simulated '4D-MRI' of the 4D digital phantom matched well with original images: the mean absolute difference in motion amplitude of the 'tumor' was 0.4±0.3mm. Small artifacts of discontinuity were observed in the SI direction in certain phases. It is feasible to extract breathing signals from sagittal images for 4D-MRI application. Further investigation is needed to test whether sagittal acquisition is more robust and accurate than axial acquisition for breathing signal extraction.

An Efficient FDTD Algorithm Based on the Equivalence Principle for Analyzing Onbody Antenna Performance

In this paper, on body antenna performance and its effect on the radio channel is analyzed. An efficient numerical technique based on the finite-difference time-domain technique and the equivalence principle is developed. The proposed technique begins with the problem decomposition by separately computing the wearable antennas and on body propagation involving the digital human phantom. The equivalence principle is used as an interface between the two computational domains. We apply this technique to analyze on body antenna and channel characteristics for three different planar body-worn antennas operating at the industrial-scientific-medical frequency band of 2.4 GHz. Simulated results are validated with measurement data with good agreement.

Evaluation of reconstruction techniques in regional cerebral blood flow SPECT using trade-off plots: A Monte Carlo study

The image quality of single photon emission computed tomography (SPECT) depends on the reconstruction algorithm used. The purpose of the present study was to evaluate parameters in ordered subset expectation maximization (OSEM) and to compare systematically with filtered back-projection (FBP) for reconstruction of regional cerebral blood flow (rCBF) SPECT, incorporating attenuation and scatter correction. The evaluation was based on the trade-off between contrast recovery and statistical noise using different sizes of subsets, number of iterations and filter parameters. Monte Carlo simulated SPECT studies of a digital human brain phantom were used. The contrast recovery was calculated as measured contrast divided by true contrast. Statistical noise in the reconstructed images was calculated as the coefficient of variation in pixel values. A constant contrast level was reached above 195 equivalent maximum likelihood expectation maximization iterations. The choice of subset size was not crucial as long as there were > or = 2 projections per subset. The OSEM reconstruction was found to give 5-14% higher contrast recovery than FBP for all clinically relevant noise levels in rCBF SPECT. The Butterworth filter, power 6, achieved the highest stable contrast recovery level at all clinically relevant noise levels. The cut-off frequency should be chosen according to the noise level accepted in the image. Trade-off plots are shown to be a practical way of deciding the number of iterations and subset size for the OSEM reconstruction and can be used for other examination types in nuclear medicine.