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Title: SU-C-207A-01: A Novel Maximum Likelihood Method for High-Resolution Proton Radiography/proton CT

Abstract

Purpose: Multiple Coulomb scattering is the largest contributor to blurring in proton imaging. Here we tested a maximum likelihood least squares estimator (MLLSE) to improve the spatial resolution of proton radiography (pRad) and proton computed tomography (pCT). Methods: The object is discretized into voxels and the average relative stopping power through voxel columns defined from the source to the detector pixels is optimized such that it maximizes the likelihood of the proton energy loss. The length spent by individual protons in each column is calculated through an optimized cubic spline estimate. pRad images were first produced using Geant4 simulations. An anthropomorphic head phantom and the Catphan line-pair module for 3-D spatial resolution were studied and resulting images were analyzed. Both parallel and conical beam have been investigated for simulated pRad acquisition. Then, experimental data of a pediatric head phantom (CIRS) were acquired using a recently completed experimental pCT scanner. Specific filters were applied on proton angle and energy loss data to remove proton histories that underwent nuclear interactions. The MTF10% (lp/mm) was used to evaluate and compare spatial resolution. Results: Numerical simulations showed improvement in the pRad spatial resolution for the parallel (2.75 to 6.71 lp/cm) and conical beam (3.08more » to 5.83 lp/cm) reconstructed with the MLLSE compared to averaging detector pixel signals. For full tomographic reconstruction, the improved pRad were used as input into a simultaneous algebraic reconstruction algorithm. The Catphan pCT reconstruction based on the MLLSE-enhanced projection showed spatial resolution improvement for the parallel (2.83 to 5.86 lp/cm) and conical beam (3.03 to 5.15 lp/cm). The anthropomorphic head pCT displayed important contrast gains in high-gradient regions. Experimental results also demonstrated significant improvement in spatial resolution of the pediatric head radiography. Conclusion: The proposed MLLSE shows promising potential to increase the spatial resolution (up to 244%) in proton imaging.« less

Authors:
 [1];  [2];  [3];  [3];  [4];  [1];  [2];  [5];  [3];  [6]
  1. Universite Laval, Quebec, Quebec (Canada)
  2. (Canada)
  3. (United States)
  4. Loma Linda University, Loma Linda, CA (United States)
  5. Mass General Hospital (United States)
  6. (Germany)
Publication Date:
OSTI Identifier:
22624336
Resource Type:
Journal Article
Resource Relation:
Journal Name: Medical Physics; Journal Volume: 43; Journal Issue: 6; Other Information: (c) 2016 American Association of Physicists in Medicine; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
61 RADIATION PROTECTION AND DOSIMETRY; 60 APPLIED LIFE SCIENCES; ALGORITHMS; BEAMS; BIOMEDICAL RADIOGRAPHY; COMPUTERIZED SIMULATION; COULOMB SCATTERING; ENERGY LOSSES; FILTERS; HEAD; IMAGES; LEAST SQUARE FIT; PEDIATRICS; PHANTOMS; PROTON COMPUTED TOMOGRAPHY; PROTON RADIOGRAPHY; SPATIAL RESOLUTION; STOPPING POWER; FUNDAMENTAL INTERACTIONS

Citation Formats

Collins-Fekete, C, Centre Hospitalier University de Quebec, Quebec, QC, Mass General Hospital, Harvard Medical, Boston MA, Schulte, R, Beaulieu, L, Centre Hospitalier University de Quebec, Quebec, QC, Seco, J, Harvard Medical, Boston MA, and Department of Medical Physics in Radiooncology, DKFZ German Cancer Research Center, Heidelberg. SU-C-207A-01: A Novel Maximum Likelihood Method for High-Resolution Proton Radiography/proton CT. United States: N. p., 2016. Web. doi:10.1118/1.4955576.
Collins-Fekete, C, Centre Hospitalier University de Quebec, Quebec, QC, Mass General Hospital, Harvard Medical, Boston MA, Schulte, R, Beaulieu, L, Centre Hospitalier University de Quebec, Quebec, QC, Seco, J, Harvard Medical, Boston MA, & Department of Medical Physics in Radiooncology, DKFZ German Cancer Research Center, Heidelberg. SU-C-207A-01: A Novel Maximum Likelihood Method for High-Resolution Proton Radiography/proton CT. United States. doi:10.1118/1.4955576.
Collins-Fekete, C, Centre Hospitalier University de Quebec, Quebec, QC, Mass General Hospital, Harvard Medical, Boston MA, Schulte, R, Beaulieu, L, Centre Hospitalier University de Quebec, Quebec, QC, Seco, J, Harvard Medical, Boston MA, and Department of Medical Physics in Radiooncology, DKFZ German Cancer Research Center, Heidelberg. 2016. "SU-C-207A-01: A Novel Maximum Likelihood Method for High-Resolution Proton Radiography/proton CT". United States. doi:10.1118/1.4955576.
@article{osti_22624336,
title = {SU-C-207A-01: A Novel Maximum Likelihood Method for High-Resolution Proton Radiography/proton CT},
author = {Collins-Fekete, C and Centre Hospitalier University de Quebec, Quebec, QC and Mass General Hospital and Harvard Medical, Boston MA and Schulte, R and Beaulieu, L and Centre Hospitalier University de Quebec, Quebec, QC and Seco, J and Harvard Medical, Boston MA and Department of Medical Physics in Radiooncology, DKFZ German Cancer Research Center, Heidelberg},
abstractNote = {Purpose: Multiple Coulomb scattering is the largest contributor to blurring in proton imaging. Here we tested a maximum likelihood least squares estimator (MLLSE) to improve the spatial resolution of proton radiography (pRad) and proton computed tomography (pCT). Methods: The object is discretized into voxels and the average relative stopping power through voxel columns defined from the source to the detector pixels is optimized such that it maximizes the likelihood of the proton energy loss. The length spent by individual protons in each column is calculated through an optimized cubic spline estimate. pRad images were first produced using Geant4 simulations. An anthropomorphic head phantom and the Catphan line-pair module for 3-D spatial resolution were studied and resulting images were analyzed. Both parallel and conical beam have been investigated for simulated pRad acquisition. Then, experimental data of a pediatric head phantom (CIRS) were acquired using a recently completed experimental pCT scanner. Specific filters were applied on proton angle and energy loss data to remove proton histories that underwent nuclear interactions. The MTF10% (lp/mm) was used to evaluate and compare spatial resolution. Results: Numerical simulations showed improvement in the pRad spatial resolution for the parallel (2.75 to 6.71 lp/cm) and conical beam (3.08 to 5.83 lp/cm) reconstructed with the MLLSE compared to averaging detector pixel signals. For full tomographic reconstruction, the improved pRad were used as input into a simultaneous algebraic reconstruction algorithm. The Catphan pCT reconstruction based on the MLLSE-enhanced projection showed spatial resolution improvement for the parallel (2.83 to 5.86 lp/cm) and conical beam (3.03 to 5.15 lp/cm). The anthropomorphic head pCT displayed important contrast gains in high-gradient regions. Experimental results also demonstrated significant improvement in spatial resolution of the pediatric head radiography. Conclusion: The proposed MLLSE shows promising potential to increase the spatial resolution (up to 244%) in proton imaging.},
doi = {10.1118/1.4955576},
journal = {Medical Physics},
number = 6,
volume = 43,
place = {United States},
year = 2016,
month = 6
}
  • Purpose: While the energy of therapeutic proton beams can be adjusted to penetrate to any given depth in water, range uncertainties arise in patients due in part to imprecise knowledge of the stopping power of protons in human tissues [1]. Proton radiography is one approach to reduce the beam range uncertainty [2], thereby allowing for a reduction in treatment margins and dose escalation. Methods: The authors have adapted a novel detector technology based on Micromesh Gaseous Structure (“Micromegas”) for proton therapy beams and have demonstrated fine spatial and time resolution of magnetically scanned proton pencil beams, as well as widemore » dynamic range for dosimetry [3]. The authors have constructed a prototype imaging system comprised of 5 Micromegas layers. Proton radiographs were obtained downstream of solid water assemblies. The position-sensitive monitor chambers in the IBA proton delivery nozzle provide the beam entrance position. Results: Our technique achieves spatial resolution as low as 300 µm and water-equivalent thickness (WET) resolution as good as 0.02% (60 µm out of 31 cm total thickness). The dose delivered to the patient is kept below 2 cGy. The spatial resolution as a function of sample rate and number of delivered protons is found to be near the theoretical Cramer-Rao lower bound. By extrapolating the CR bound, we argue that the imaging dose could be further lowered to 1 mGy, while still achieving submillimeter spatial resolution, by achievable instrumentation and beam delivery modifications. Conclusion: For proton radiography, high spatial and WET resolution can be achieved, with minimal additional dose to patient, by using magnetically scanned proton pencil beams and Micromegas detectors.« less
  • Purpose: Studies show that WEPL can be determined from modulated dose rate functions (DRF). However, the previous calibration method based on statistics of the DRF is sensitive to energy mixing of protons due to scattering through different materials (termed as range mixing here), causing inaccuracies in the determination of WEPL. This study intends to explore time-domain features of the DRF to reduce the effect of range mixing in proton radiography (pRG) by this technique. Methods: An amorphous silicon flat panel (PaxScan™ 4030CB, Varian Medical Systems, Inc., Palo Alto, CA) was placed behind phantoms to measure DRFs from a proton beammore » modulated by a specially designed modulator wheel. The performance of two methods, the previously used method based on the root mean square (RMS) and the new approach based on time-domain features of the DRF, are compared for retrieving WEPL and RSP from pRG of a Gammex phantom. Results: Calibration by T{sub 80} (the time point for 80% of the major peak) was more robust to range mixing and produced WEPL with improved accuracy. The error of RSP was reduced from 8.2% to 1.7% for lung equivalent material, with the mean error for all other materials reduced from 1.2% to 0.7%. The mean error of the full width at half maximum (FWHM) of retrieved inserts was decreased from 25.85% to 5.89% for the RMS and T{sub 80} method respectively. Monte Carlo simulations in simplified cases also demonstrated that the T{sub 80} method is less sensitive to range mixing than the RMS method. Conclusion: WEPL images have been retrieved based on single flat panel measured DRFs, with inaccuracies reduced by exploiting time-domain features as the calibration parameter. The T{sub 80} method is validated to be less sensitive to range mixing and can thus retrieve the WEPL values in proximity of interfaces with improved numerical and spatial accuracy for proton radiography.« less
  • Purpose: To develop a 4D MRI method for assessing respiration-induced abdominal organ motion in children receiving radiation therapy. Methods: A 4D MRI using internal image-based respiratory surrogate has been developed and implemented on a clinical scanner (1.5T Siemens Avanto). Ten patients (younger group: N=6, 2–5 years, anesthetized; older group: N=4, 11–15 years) with neuroblastoma, Wilm’s tumor rhabdomyosarcoma, or desmoplastic small round cell tumor received free breathing 4D MRI scans for treatment planning. Coronal image slices of the entire abdomen were retrospectively constructed in 10 respiratory phases. A B-spline deformable registration (Metz et al. 2011) was performed on 4D datasets tomore » automatically derive motion trajectories of selected anatomical landmarks, including the dome and the center of the liver, and the superior edges of kidneys and spleen. The extents of the motion in three dimensions (anteroposterior, AP; mediolateral, ML; superoinferior, SI) and the correlations between organ motion trajectories were quantified. Results: The 4D MRI scans were successfully performed in <20 minutes for all patients without the use of any external device. Organ motion extents were larger in adolescents (kidneys: 3–13 mm SI, liver and spleen: 6–18 mm SI) than in younger children (kidneys:<3mm in all directions; liver and spleen: 1–8 mm SI, 1–5 mm ML and AP). The magnitude of respiratory motion in some adolescents may warrant special motion management. Motion trajectories were not synchronized across selected anatomical landmarks, particularly in the ML and AP directions, indicating inter- and intra-organ variations of the respiratory-induced motion. Conclusion: The developed 4D MRI acquisition and motion analysis methods provide a non-ionizing, non-invasive approach to automatically measure the organ motion trajectory in the pediatric abdomen. It is useful for defining ITV and PRV, monitoring changes in target motion patterns during the treatment course, and studying interplay effects in proton scanning.« less
  • Purpose: Sparse-view computed tomography (CT) reconstruction is an effective strategy to reduce the radiation dose delivered to patients. Due to its insufficiency of measurements, traditional non-local means (NLM) based reconstruction methods often lead to over-smoothness in image edges. To address this problem, an adaptive NLM reconstruction method based on rotational invariance (RIANLM) is proposed. Methods: The method consists of four steps: 1) Initializing parameters; 2) Algebraic reconstruction technique (ART) reconstruction using raw projection data; 3) Positivity constraint of the image reconstructed by ART; 4) Update reconstructed image by using RIANLM filtering. In RIANLM, a novel similarity metric that is rotationalmore » invariance is proposed and used to calculate the distance between two patches. In this way, any patch with similar structure but different orientation to the reference patch would win a relatively large weight to avoid over-smoothed image. Moreover, the parameter h in RIANLM which controls the decay of the weights is adaptive to avoid over-smoothness, while it in NLM is not adaptive during the whole reconstruction process. The proposed method is named as ART-RIANLM and validated on Shepp-Logan phantom and clinical projection data. Results: In our experiments, the searching neighborhood size is set to 15 by 15 and the similarity window is set to 3 by 3. For the simulated case with a resolution of 256 by 256 Shepp-Logan phantom, the ART-RIANLM produces higher SNR (35.38dB<24.00dB) and lower MAE (0.0006<0.0023) reconstructed image than ART-NLM. The visual inspection demonstrated that the proposed method could suppress artifacts or noises more effectively and preserve image edges better. Similar results were found for clinical data case. Conclusion: A novel ART-RIANLM method for sparse-view CT reconstruction is presented with superior image. Compared to the conventional ART-NLM method, the SNR and MAE from ART-RIANLM increases 47% and decreases 74%, respectively.« less
  • Purpose: Reducing x-ray exposure and speeding up data acquisition motived studies on projection data undersampling. It is an important question that for a given undersampling ratio, what the optimal undersampling approach is. In this study, we propose a new undersampling scheme: random-ray undersampling. We will mathematically analyze its projection matrix properties and demonstrate its advantages. We will also propose a new reconstruction method that simultaneously performs CT image reconstruction and projection domain data restoration. Methods: By representing projection operator under the basis of singular vectors of full projection operator, matrix representations for an undersampling case can be generated and numericalmore » singular value decomposition can be performed. We compared properties of matrices among three undersampling approaches: regular-view undersampling, regular-ray undersampling, and the proposed random-ray undersampling. To accomplish CT reconstruction for random undersampling, we developed a novel method that iteratively performs CT reconstruction and missing projection data restoration via regularization approaches. Results: For a given undersampling ratio, random-ray undersampling preserved mathematical properties of full projection operator better than the other two approaches. This translates to advantages of reconstructing CT images at lower errors. Different types of image artifacts were observed depending on undersampling strategies, which were ascribed to the unique singular vectors of the sampling operators in the image domain. We tested the proposed reconstruction algorithm on a Forbid phantom with only 30% of the projection data randomly acquired. Reconstructed image error was reduced from 9.4% in a TV method to 7.6% in the proposed method. Conclusion: The proposed random-ray undersampling is mathematically advantageous over other typical undersampling approaches. It may permit better image reconstruction at the same undersampling ratio. The novel algorithm suitable for this random-ray undersampling was able to reconstruct high-quality images.« less