Volume 41, Issue 12, December 2014
Index of content:
Within the next ten years treatment planning will become fully automated without the need for human intervention41(2014); http://dx.doi.org/10.1118/1.4894496View Description Hide Description
- MEDICAL PHYSICS LETTER
Anatomical background noise power spectrum in differential phase contrast and dark field contrast mammograms41(2014); http://dx.doi.org/10.1118/1.4901313View Description Hide DescriptionPurpose:
In x-ray absorption mammography, it has been found that the anatomical background noise can be characterized by a power law dependence on the spatial frequency, NPS a (f) ≈ αf −β . In this letter, the authors present the first experimental results of the corresponding exponents, β, for differential phase contrast (β DPC) and dark field contrast (β DF) mammography.Methods:
A grating-based x-ray multicontrast imaging acquisition benchtop system was used to simultaneously acquire mammograms with three different contrast mechanisms from 15 cadaver breasts under the same x-ray data acquisition conditions. The cadaver breasts were imaged in the coronal plane. The authors’ experimental implementation of the well documented method [Burgess, Jacobson, and Judy, Med. Phys. 28, 419–437 (2001)] to extract the exponent β was first validated using anonymized clinical mammograms. Experiments were then used to determine β for the three types of mammograms for each cadaver breast acquired with our multicontrast imaging system: absorption contrast mammogram (β Abs.), differential phase contrast mammogram (β DPC), and dark-field contrast mammogram (β DF).Results:
The measured β values, acquired in the coronal plane with the benchtop multicontrast imaging system are β Abs. = 3.61 ± 0.49, β DPC = 2.54 ± 0.75, and β DF = 1.44 ± 0.49 for absorption, differential phase, and dark field mammogram, respectively.Conclusions:
The β values for differential phase contrast and dark field mammography are significantly lower than the measured value of β for the corresponding absorption contrast mammograms. The greatly reduced β value of the anatomical background noise in differential phase contrast and dark field mammograms may suggest potentially improved diagnostic performance for certain types of breast cancer imaging tasks.
Radiotherapy beyond cancer: Target localization in real-time MRI and treatment planning for cardiac radiosurgery41(2014); http://dx.doi.org/10.1118/1.4901414View Description Hide DescriptionPurpose:
Atrial fibrillation (AFib) is the most common cardiac arrhythmia that affects millions of patients world-wide. AFib is usually treated with minimally invasive, time consuming catheter ablation techniques. While recently noninvasive radiosurgery to the pulmonary vein antrum (PVA) in the left atrium has been proposed for AFib treatment, precise target location during treatment is challenging due to complex respiratory and cardiac motion. A MRI linear accelerator (MRI-Linac) could solve the problems of motion tracking and compensation using real-time image guidance. In this study, the authors quantified target motion ranges on cardiac magnetic resonance imaging (MRI) and analyzed the dosimetric benefits of margin reduction assuming real-time motion compensation was applied.Methods:
For the imaging study, six human subjects underwent real-time cardiac MRI under free breathing. The target motion was analyzed retrospectively using a template matching algorithm. The planning study was conducted on a CT of an AFib patient with a centrally located esophagus undergoing catheter ablation, representing an ideal case for cardiac radiosurgery. The target definition was similar to the ablation lesions at the PVA created during catheter treatment. Safety margins of 0 mm (perfect tracking) to 8 mm (untracked respiratory motion) were added to the target, defining the planning target volume (PTV). For each margin, a 30 Gy single fraction IMRT plan was generated. Additionally, the influence of 1 and 3 T magnetic fields on the treatment beam delivery was simulated using Monte Carlo calculations to determine the dosimetric impact of MRI guidance for two different Linac positions.Results:
Real-time cardiac MRI showed mean respiratory target motion of 10.2 mm (superior–inferior), 2.4 mm (anterior–posterior), and 2 mm (left–right). The planning study showed that increasing safety margins to encompass untracked respiratory motion leads to overlapping structures even in the ideal scenario, compromising either normal tissue dose constraints or PTV coverage. The magnetic field caused a slight increase in the PTV dose with the in-line MRI-Linac configuration.Conclusions:
The authors’ results indicate that real-time tracking and motion compensation are mandatory for cardiac radiosurgery and MRI-guidance is feasible, opening the possibility of treating cardiac arrhythmia patients completely noninvasively.
- RADIATION THERAPY PHYSICS
Accuracy of surface registration compared to conventional volumetric registration in patient positioning for head-and-neck radiotherapy: A simulation study using patient data41(2014); http://dx.doi.org/10.1118/1.4898103View Description Hide DescriptionPurpose:
3D optical surface imaging has been applied to patient positioning in radiation therapy (RT). The optical patient positioning system is advantageous over conventional method using cone-beam computed tomography (CBCT) in that it is radiation free, frameless, and is capable of real-time monitoring. While the conventional radiographic method uses volumetric registration, the optical system uses surface matching for patient alignment. The relative accuracy of these two methods has not yet been sufficiently investigated. This study aims to investigate the theoretical accuracy of the surface registration based on a simulation study using patient data.Methods:
This study compares the relative accuracy of surface and volumetric registration in head-and-neck RT. The authors examined 26 patient data sets, each consisting of planning CT data acquired before treatment and patient setup CBCT data acquired at the time of treatment. As input data of surface registration, patient’s skin surfaces were created by contouring patient skin from planning CT and treatment CBCT. Surface registration was performed using the iterative closest points algorithm by point–plane closest, which minimizes the normal distance between source points and target surfaces. Six degrees of freedom (three translations and three rotations) were used in both surface and volumetric registrations and the results were compared. The accuracy of each method was estimated by digital phantom tests.Results:
Based on the results of 26 patients, the authors found that the average and maximum root-mean-square translation deviation between the surface and volumetric registrations were 2.7 and 5.2 mm, respectively. The residual error of the surface registration was calculated to have an average of 0.9 mm and a maximum of 1.7 mm.Conclusions:
Surface registration may lead to results different from those of the conventional volumetric registration. Only limited accuracy can be achieved for patient positioning with an approach based solely on surface information.
Toward optimizing patient-specific IMRT QA techniques in the accurate detection of dosimetrically acceptable and unacceptable patient plans41(2014); http://dx.doi.org/10.1118/1.4899177View Description Hide DescriptionPurpose:
The authors investigated the performance of several patient-specific intensity-modulated radiation therapy (IMRT) quality assurance (QA) dosimeters in terms of their ability to correctly identify dosimetrically acceptable and unacceptable IMRT patient plans, as determined by an in-house-designed multiple ion chamber phantom used as the gold standard. A further goal was to examine optimal threshold criteria that were consistent and based on the same criteria among the various dosimeters.Methods:
The authors used receiver operating characteristic (ROC) curves to determine the sensitivity and specificity of (1) a 2D diode array undergoing anterior irradiation with field-by-field evaluation, (2) a 2D diode array undergoing anterior irradiation with composite evaluation, (3) a 2D diode array using planned irradiation angles with composite evaluation, (4) a helical diode array, (5) radiographic film, and (6) an ion chamber. This was done with a variety of evaluation criteria for a set of 15 dosimetrically unacceptable and 9 acceptable clinical IMRT patient plans, where acceptability was defined on the basis of multiple ion chamber measurements using independent ion chambers and a phantom. The area under the curve (AUC) on the ROC curves was used to compare dosimeter performance across all thresholds. Optimal threshold values were obtained from the ROC curves while incorporating considerations for cost and prevalence of unacceptable plans.Results:
Using common clinical acceptance thresholds, most devices performed very poorly in terms of identifying unacceptable plans. Grouping the detector performance based on AUC showed two significantly different groups. The ion chamber, radiographic film, helical diode array, and anterior-delivered composite 2D diode array were in the better-performing group, whereas the anterior-delivered field-by-field and planned gantry angle delivery using the 2D diode array performed less well. Additionally, based on the AUCs, there was no significant difference in the performance of any device between gamma criteria of 2%/2 mm, 3%/3 mm, and 5%/3 mm. Finally, optimal cutoffs (e.g., percent of pixels passing gamma) were determined for each device and while clinical practice commonly uses a threshold of 90% of pixels passing for most cases, these results showed variability in the optimal cutoff among devices.Conclusions:
IMRT QA devices have differences in their ability to accurately detect dosimetrically acceptable and unacceptable plans. Field-by-field analysis with a MapCheck device and use of the MapCheck with a MapPhan phantom while delivering at planned rotational gantry angles resulted in a significantly poorer ability to accurately sort acceptable and unacceptable plans compared with the other techniques examined. Patient-specific IMRT QA techniques in general should be thoroughly evaluated for their ability to correctly differentiate acceptable and unacceptable plans. Additionally, optimal agreement thresholds should be identified and used as common clinical thresholds typically worked very poorly to identify unacceptable plans.
41(2014); http://dx.doi.org/10.1118/1.4900603View Description Hide DescriptionPurpose:
The authors combine the registration of 2D beam’s eye view (BEV) images and 3D planning computed tomography (CT) images, with relative, markerless tumor tracking to provide automatic absolute tracking of physician defined volumes such as the gross tumor volume (GTV).Methods:
During treatment of lung SBRT cases, BEV images were continuously acquired with an electronic portal imaging device (EPID) operating in cine mode. For absolute registration of physician-defined volumes, an intensity based 2D/3D registration to the planning CT was performed using the end-of-exhale (EoE) phase of the four dimensional computed tomography (4DCT). The volume was converted from Hounsfield units into electron density by a calibration curve and digitally reconstructed radiographs (DRRs) were generated for each beam geometry. Using normalized cross correlation between the DRR and an EoE BEV image, the best in-plane rigid transformation was found. The transformation was applied to physician-defined contours in the planning CT, mapping them into the EPID image domain. A robust multiregion method of relative markerless lung tumor tracking quantified deviations from the EoE position.Results:
The success of 2D/3D registration was demonstrated at the EoE breathing phase. By registering at this phase and then employing a separate technique for relative tracking, the authors are able to successfully track target volumes in the BEV images throughout the entire treatment delivery.Conclusions:
Through the combination of EPID/4DCT registration and relative tracking, a necessary step toward the clinical implementation of BEV tracking has been completed. The knowledge of tumor volumes relative to the treatment field is important for future applications like real-time motion management, adaptive radiotherapy, and delivered dose calculations.
41(2014); http://dx.doi.org/10.1118/1.4900828View Description Hide DescriptionPurpose:
The use of medical technology capable of tracking patient motion or positioning patients along 6 degree-of-freedom (6DOF) has steadily increased in the field of radiation therapy. However, due to the complex nature of tracking and performing 6DOF motion, it is critical that such technology is properly verified to be operating within specifications in order to ensure patient safety. In this study, a robotic motion phantom is presented that can be programmed to perform highly accurate motion along any X (left–right), Y (superior–inferior), Z (anterior–posterior), pitch (around X), roll (around Y), and yaw (around Z) axes. In addition, highly synchronized motion along all axes can be performed in order to simulate the dynamic motion of a tumor in 6D. The accuracy and reproducibility of this 6D motion were characterized.Methods:
An in-house designed and built 6D robotic motion phantom was constructed following the Stewart–Gough parallel kinematics platform archetype. The device was controlled using an inverse kinematics formulation, and precise movements in all 6 degrees-of-freedom (X, Y, Z, pitch, roll, and yaw) were performed, both simultaneously and separately for each degree-of-freedom. Additionally, previously recorded 6D cranial and prostate motions were effectively executed. The robotic phantom movements were verified using a 15 fps 6D infrared marker tracking system and the measured trajectories were compared quantitatively to the intended input trajectories. The workspace, maximum 6D velocity, backlash, and weight load capabilities of the system were also established.Results:
Evaluation of the 6D platform demonstrated translational root mean square error (RMSE) values of 0.14, 0.22, and 0.08 mm over 20 mm in X and Y and 10 mm in Z, respectively, and rotational RMSE values of 0.16°, 0.06°, and 0.08° over 10° of pitch, roll, and yaw, respectively. The robotic stage also effectively performed controlled 6D motions, as well as reproduced cranial trajectories over 15 min, with a maximal RMSE of 0.04 mm translationally and 0.04° rotationally, and a prostate trajectory over 2 min, with a maximal RMSE of 0.06 mm translationally and 0.04° rotationally.Conclusions:
This 6D robotic phantom has proven to be accurate under clinical standards and capable of reproducing tumor motion in 6D. Such functionality makes the robotic phantom usable for either quality assurance or research purposes.
Impact of spot size on plan quality of spot scanning proton radiosurgery for peripheral brain lesions41(2014); http://dx.doi.org/10.1118/1.4901260View Description Hide DescriptionPurpose:
To determine the plan quality of proton spot scanning (SS) radiosurgery as a function of spot size (in-air sigma) in comparison to x-ray radiosurgery for treating peripheral brain lesions.Methods:
Single-field optimized (SFO) proton SS plans with sigma ranging from 1 to 8 mm, cone-based x-ray radiosurgery (Cone), and x-ray volumetric modulated arc therapy (VMAT) plans were generated for 11 patients. Plans were evaluated using secondary cancer risk and brain necrosis normal tissue complication probability (NTCP).Results:
For all patients, secondary cancer is a negligible risk compared to brain necrosis NTCP. Secondary cancer risk was lower in proton SS plans than in photon plans regardless of spot size (p = 0.001). Brain necrosis NTCP increased monotonically from an average of 2.34/100 (range 0.42/100–4.49/100) to 6.05/100 (range 1.38/100–11.6/100) as sigma increased from 1 to 8 mm, compared to the average of 6.01/100 (range 0.82/100–11.5/100) for Cone and 5.22/100 (range 1.37/100–8.00/100) for VMAT. An in-air sigma less than 4.3 mm was required for proton SS plans to reduce NTCP over photon techniques for the cohort of patients studied with statistical significance (p = 0.0186). Proton SS plans with in-air sigma larger than 7.1 mm had significantly greater brain necrosis NTCP than photon techniques (p = 0.0322).Conclusions:
For treating peripheral brain lesions—where proton therapy would be expected to have the greatest depth-dose advantage over photon therapy—the lateral penumbra strongly impacts the SS plan quality relative to photon techniques: proton beamlet sigma at patient surface must be small (<7.1 mm for three-beam single-field optimized SS plans) in order to achieve comparable or smaller brain necrosis NTCP relative to photon radiosurgery techniques. Achieving such small in-air sigma values at low energy (<70 MeV) is a major technological challenge in commercially available proton therapy systems.
Using an external surrogate for predictor model training in real-time motion management of lung tumors41(2014); http://dx.doi.org/10.1118/1.4901252View Description Hide DescriptionPurpose:
Precise prediction of respiratory motion is a prerequisite for real-time motion compensation techniques such as beam, dynamic couch, or dynamic multileaf collimator tracking. Collection of tumor motion data to train the prediction model is required for most algorithms. To avoid exposure of patients to additional dose from imaging during this procedure, the feasibility of training a linear respiratory motion prediction model with an external surrogate signal is investigated and its performance benchmarked against training the model with tumor positions directly.Methods:
The authors implement a lung tumor motion prediction algorithm based on linear ridge regression that is suitable to overcome system latencies up to about 300 ms. Its performance is investigated on a data set of 91 patient breathing trajectories recorded from fiducial marker tracking during radiotherapy delivery to the lung of ten patients. The expected 3D geometric error is quantified as a function of predictor lookahead time, signal sampling frequency and history vector length. Additionally, adaptive model retraining is evaluated, i.e., repeatedly updating the prediction model after initial training. Training length for this is gradually increased with incoming (internal) data availability. To assess practical feasibility model calculation times as well as various minimum data lengths for retraining are evaluated. Relative performance of model training with external surrogate motion data versus tumor motion data is evaluated. However, an internal–external motion correlation model is not utilized, i.e., prediction is solely driven by internal motion in both cases.Results:
Similar prediction performance was achieved for training the model with external surrogate data versus internal (tumor motion) data. Adaptive model retraining can substantially boost performance in the case of external surrogate training while it has little impact for training with internal motion data. A minimum adaptive retraining data length of 8 s and history vector length of 3 s achieve maximal performance. Sampling frequency appears to have little impact on performance confirming previously published work. By using the linear predictor, a relative geometric 3D error reduction of about 50% was achieved (using adaptive retraining, a history vector length of 3 s and with results averaged over all investigated lookahead times and signal sampling frequencies). The absolute mean error could be reduced from (2.0 ± 1.6) mm when using no prediction at all to (0.9 ± 0.8) mm and (1.0 ± 0.9) mm when using the predictor trained with internal tumor motion training data and external surrogate motion training data, respectively (for a typical lookahead time of 250 ms and sampling frequency of 15 Hz).Conclusions:
A linear prediction model can reduce latency induced tracking errors by an average of about 50% in real-time image guided radiotherapy systems with system latencies of up to 300 ms. Training a linear model for lung tumor motion prediction with an external surrogate signal alone is feasible and results in similar performance as training with (internal) tumor motion. Particularly for scenarios where motion data are extracted from fluoroscopic imaging with ionizing radiation, this may alleviate the need for additional imaging dose during the collection of model training data.
41(2014); http://dx.doi.org/10.1118/1.4901522View Description Hide DescriptionPurpose:
Conventional spot scanning intensity modulated proton therapy (IMPT) treatment planning systems (TPSs) optimize proton spot weights based on analytical dose calculations. These analytical dose calculations have been shown to have severe limitations in heterogeneous materials. Monte Carlo (MC) methods do not have these limitations; however, MC-based systems have been of limited clinical use due to the large number of beam spots in IMPT and the extremely long calculation time of traditional MC techniques. In this work, the authors present a clinically applicable IMPT TPS that utilizes a very fast MC calculation.Methods:
An in-house graphics processing unit (GPU)-based MC dose calculation engine was employed to generate the dose influence map for each proton spot. With the MC generated influence map, a modified least-squares optimization method was used to achieve the desired dose volume histograms (DVHs). The intrinsic CT image resolution was adopted for voxelization in simulation and optimization to preserve spatial resolution. The optimizations were computed on a multi-GPU framework to mitigate the memory limitation issues for the large dose influence maps that resulted from maintaining the intrinsic CT resolution. The effects of tail cutoff and starting condition were studied and minimized in this work.Results:
For relatively large and complex three-field head and neck cases, i.e., >100 000 spots with a target volume of ∼1000 cm3 and multiple surrounding critical structures, the optimization together with the initial MC dose influence map calculation was done in a clinically viable time frame (less than 30 min) on a GPU cluster consisting of 24 Nvidia GeForce GTX Titan cards. The in-house MC TPS plans were comparable to a commercial TPS plans based on DVH comparisons.Conclusions:
A MC-based treatment planning system was developed. The treatment planning can be performed in a clinically viable time frame on a hardware system costing around 45 000 dollars. The fast calculation and optimization make the system easily expandable to robust and multicriteria optimization.
41(2014); http://dx.doi.org/10.1118/1.4901555View Description Hide DescriptionPurpose:
Monte Carlo track structures (MCTS) simulations have been recognized as useful tools for radiobiological modeling. However, the authors noticed several issues regarding the consistency of reported data. Therefore, in this work, they analyze the impact of various user defined parameters on simulated direct DNA damage yields. In addition, they draw attention to discrepancies in published literature in DNA strand break (SB) yields and selected methodologies.Methods:
The MCTS code Geant4-DNA was used to compare radial dose profiles in a nanometer-scale region of interest (ROI) for photon sources of varying sizes and energies. Then, electron tracks of 0.28 keV–220 keV were superimposed on a geometric DNA model composed of 2.7 × 106 nucleosomes, and SBs were simulated according to four definitions based on energy deposits or energy transfers in DNA strand targets compared to a threshold energy E TH. The SB frequencies and complexities in nucleosomes as a function of incident electron energies were obtained. SBs were classified into higher order clusters such as single and double strand breaks (SSBs and DSBs) based on inter-SB distances and on the number of affected strands.Results:
Comparisons of different nonuniform dose distributions lacking charged particle equilibrium may lead to erroneous conclusions regarding the effect of energy on relative biological effectiveness. The energy transfer-based SB definitions give similar SB yields as the one based on energy deposit when E TH ≈ 10.79 eV, but deviate significantly for higher E TH values. Between 30 and 40 nucleosomes/Gy show at least one SB in the ROI. The number of nucleosomes that present a complex damage pattern of more than 2 SBs and the degree of complexity of the damage in these nucleosomes diminish as the incident electron energy increases. DNA damage classification into SSB and DSB is highly dependent on the definitions of these higher order structures and their implementations. The authors’ show that, for the four studied models, different yields are expected by up to 54% for SSBs and by up to 32% for DSBs, as a function of the incident electrons energy and of the models being compared.Conclusions:
MCTS simulations allow to compare direct DNA damage types and complexities induced by ionizing radiation. However, simulation results depend to a large degree on user-defined parameters, definitions, and algorithms such as: DNA model, dose distribution, SB definition, and the DNA damage clustering algorithm. These interdependencies should be well controlled during the simulations and explicitly reported when comparing results to experiments or calculations.
A three-dimensional head-and-neck phantom for validation of multimodality deformable image registration for adaptive radiotherapy41(2014); http://dx.doi.org/10.1118/1.4901523View Description Hide DescriptionPurpose:
To develop a three-dimensional (3D) deformable head-and-neck (H&N) phantom with realistic tissue contrast for both kilovoltage (kV) and megavoltage (MV) imaging modalities and use it to objectively evaluate deformable image registration (DIR) algorithms.Methods:
The phantom represents H&N patient anatomy. It is constructed from thermoplastic, which becomes pliable in boiling water, and hardened epoxy resin. Using a system of additives, the Hounsfield unit (HU) values of these materials were tuned to mimic anatomy for both kV and MV imaging. The phantom opens along a sagittal midsection to reveal radiotransparent markers, which were used to characterize the phantom deformation. The deformed and undeformed phantoms were scanned with kV and MV imaging modalities. Additionally, a calibration curve was created to change the HUs of the MV scans to be similar to kV HUs, (MC). The extracted ground-truth deformation was then compared to the results of two commercially available DIR algorithms, from Velocity Medical Solutions and MIM software.Results:
The phantom produced a 3D deformation, representing neck flexion, with a magnitude of up to 8 mm and was able to represent tissue HUs for both kV and MV imaging modalities. The two tested deformation algorithms yielded vastly different results. For kV–kV registration, MIM produced mean and maximum errors of 1.8 and 11.5 mm, respectively. These same numbers for Velocity were 2.4 and 7.1 mm, respectively. For MV–MV, kV–MV, and kV–MC Velocity produced similar mean and maximum error values. MIM, however, produced gross errors for all three of these scenarios, with maximum errors ranging from 33.4 to 41.6 mm.Conclusions:
The application of DIR across different imaging modalities is particularly difficult, due to differences in tissue HUs and the presence of imaging artifacts. For this reason, DIR algorithms must be validated specifically for this purpose. The developed H&N phantom is an effective tool for this purpose.
41(2014); http://dx.doi.org/10.1118/1.4901553View Description Hide DescriptionPurpose:
Implanted gold markers for image-guided radiotherapy lead to streaking artifacts in cone-beam CT (CBCT) scans. Several methods for metal artifact reduction (MAR) have been published, but they all fail in scans with large motion. Here the authors propose and investigate a method for automatic moving metal artifact reduction (MMAR) in CBCT scans with cylindrical gold markers.Methods:
The MMAR CBCT reconstruction method has six steps. (1) Automatic segmentation of the cylindrical markers in the CBCT projections. (2) Removal of each marker in the projections by replacing the pixels within a masked area with interpolated values. (3) Reconstruction of a marker-free CBCT volume from the manipulated CBCT projections. (4) Reconstruction of a standard CBCT volume with metal artifacts from the original CBCT projections. (5) Estimation of the three-dimensional (3D) trajectory during CBCT acquisition for each marker based on the segmentation in Step 1, and identification of the smallest ellipsoidal volume that encompasses 95% of the visited 3D positions. (6) Generation of the final MMAR CBCT reconstruction from the marker-free CBCT volume of Step 3 by replacing the voxels in the 95% ellipsoid with the corresponding voxels of the standard CBCT volume of Step 4. The MMAR reconstruction was performed retrospectively using a half-fan CBCT scan for 29 consecutive stereotactic body radiation therapy patients with 2–3 gold markers implanted in the liver. The metal artifacts of the MMAR reconstructions were scored and compared with a standard MAR reconstruction by counting the streaks and by calculating the standard deviation of the Hounsfield units in a region around each marker.Results:
The markers were found with the same autosegmentation settings in 27 CBCT scans, while two scans needed slightly changed settings to find all markers automatically in Step 1 of the MMAR method. MMAR resulted in 15 scans with no streaking artifacts, 11 scans with 1–4 streaks, and 3 scans with severe streaking artifacts. The corresponding numbers for MAR were 8 (no streaks), 1 (1–4 streaks), and 20 (severe streaking artifacts). The MMAR method was superior to MAR in scans with more than 8 mm 3D marker motion and comparable to MAR for scans with less than 8 mm motion. In addition, the MMAR method was tested on a 4D CBCT reconstruction for which it worked equally well as for the 3D case. The markers in the 4D case had very low motion blur.Conclusions:
An automatic method for MMAR in CBCT scans was proposed and shown to effectively remove almost all streaking artifacts in a large set of clinical CBCT scans with implanted gold markers in the liver. Residual streaking artifacts observed in three CBCT scans may be removed with better marker segmentation.
- RADIATION IMAGING PHYSICS
41(2014); http://dx.doi.org/10.1118/1.4900819View Description Hide DescriptionPurpose:
The aim of this work is to create a model to predict the noise power spectra (NPS) for a range of mammographic radiographic factors. The noise model was necessary to degrade images acquired on one system to match the image quality of different systems for a range of beam qualities.Methods:
Five detectors and x-ray systems [Hologic Selenia (ASEh), Carestream computed radiography CR900 (CRc), GE Essential (CSI), Carestream NIP (NIPc), and Siemens Inspiration (ASEs)] were characterized for this study. The signal transfer property was measured as the pixel value against absorbed energy per unit area (E) at a reference beam quality of 28 kV, Mo/Mo or 29 kV, W/Rh with 45 mm polymethyl methacrylate (PMMA) at the tube head. The contributions of the three noise sources (electronic, quantum, and structure) to the NPS were calculated by fitting a quadratic at each spatial frequency of the NPS against E. A quantum noise correction factor which was dependent on beam quality was quantified using a set of images acquired over a range of radiographic factors with different thicknesses of PMMA. The noise model was tested for images acquired at 26 kV, Mo/Mo with 20 mm PMMA and 34 kV, Mo/Rh with 70 mm PMMA for three detectors (ASEh, CRc, and CSI) over a range of exposures. The NPS were modeled with and without the noise correction factor and compared with the measured NPS. A previous method for adapting an image to appear as if acquired on a different system was modified to allow the reference beam quality to be different from the beam quality of the image. The method was validated by adapting the ASEh flat field images with two thicknesses of PMMA (20 and 70 mm) to appear with the imaging characteristics of the CSI and CRc systems.Results:
The quantum noise correction factor rises with higher beam qualities, except for CR systems at high spatial frequencies, where a flat response was found against mean photon energy. This is due to the dominance of secondary quantum noise in CR. The use of the quantum noise correction factor reduced the difference from the model to the real NPS to generally within 4%. The use of the quantum noise correction improved the conversion of ASEh image to CRc image but had no difference for the conversion to CSI images.Conclusions:
A practical method for estimating the NPS at any dose and over a range of beam qualities for mammography has been demonstrated. The noise model was incorporated into a methodology for converting an image to appear as if acquired on a different detector. The method can now be extended to work for a wide range of beam qualities and can be applied to the conversion of mammograms.
41(2014); http://dx.doi.org/10.1118/1.4900820View Description Hide DescriptionPurpose:
To investigate the feasibility of characterizing a Si strip photon-counting detector using x-ray fluorescence.Methods:
X-ray fluorescence was generated by using a pencil beam from a tungsten anode x-ray tube with 2 mm Al filtration. Spectra were acquired at 90° from the primary beam direction with an energy-resolved photon-counting detector based on an edge illuminated Si strip detector. The distances from the source to target and the target to detector were approximately 19 and 11 cm, respectively. Four different materials, containing silver (Ag), iodine (I), barium (Ba), and gadolinium (Gd), were placed in small plastic containers with a diameter of approximately 0.7 cm for x-ray fluorescence measurements. Linear regression analysis was performed to derive the gain and offset values for the correlation between the measured fluorescence peak center and the known fluorescence energies. The energy resolutions and charge-sharing fractions were also obtained from analytical fittings of the recorded fluorescence spectra. An analytical model, which employed four parameters that can be determined from the fluorescence calibration, was used to estimate the detector response function.Results:
Strong fluorescence signals of all four target materials were recorded with the investigated geometry for the Si strip detector. The average gain and offset of all pixels for detector energy calibration were determined to be 6.95 mV/keV and −66.33 mV, respectively. The detector’s energy resolution remained at approximately 2.7 keV for low energies, and increased slightly at 45 keV. The average charge-sharing fraction was estimated to be 36% within the investigated energy range of 20–45 keV. The simulated detector output based on the proposed response function agreed well with the experimental measurement.Conclusions:
The performance of a spectral imaging system using energy-resolved photon-counting detectors is very dependent on the energy calibration of the detector. The proposed x-ray fluorescence technique offers an accurate and efficient way to calibrate the energy response of a photon-counting detector.
41(2014); http://dx.doi.org/10.1118/1.4900611View Description Hide DescriptionPurpose:
Beam-quality optimization in digital mammography traditionally considers detection of a target obscured by quantum noise in a homogeneous background. This does not correspond well to the clinical imaging task because real mammographic images contain a complex superposition of anatomical structures, resulting in anatomical noise that may dominate over quantum noise. The purpose of this paper is to assess the influence on optimal beam quality in mammography when anatomical noise is taken into account.Methods:
The detectability of microcalcifications and masses was quantified using a theoretical ideal-observer model that included quantum noise as well as anatomical noise and a simplified model of a photon-counting mammography system. The outcome was experimentally verified using two types of simulated tissue phantoms.Results:
The theoretical model showed that the detectability of tumors and microcalcifications behaves differently with respect to beam quality and dose. The results for small microcalcifications were similar to what traditional optimization methods yield, which is to be expected because quantum noise dominates over anatomical noise at high spatial frequencies. For larger tumors, however, low-frequency anatomical noise was the limiting factor. Because anatomical structure noise has similar energy dependence as tumor contrast, the optimal x-ray energy was found to be higher and the useful energy region was wider than traditional methods suggest. A simplified scalar model was able to capture this behavior using a fitted noise mixing parameter. The phantom measurements confirmed these theoretical results.Conclusions:
It was shown that since quantum noise constitutes only a small fraction of the noise, the dose could be reduced substantially without sacrificing tumor detectability. Furthermore, when anatomical noise is included, the tube voltage can be increased well beyond what is conventionally considered optimal and used clinically, without loss of image quality. However, no such conclusions can be drawn for the more complex mammographic imaging task as a whole.
Three-dimensional texture analysis of contrast enhanced CT images for treatment response assessment in Hodgkin lymphoma: Comparison with F-18-FDG PET41(2014); http://dx.doi.org/10.1118/1.4900821View Description Hide DescriptionPurpose:
To determine the diagnostic performance of three-dimensional (3D) texture analysis (TA) of contrast-enhanced computed tomography (CE-CT) images for treatment response assessment in patients with Hodgkin lymphoma (HL), compared with F-18-fludeoxyglucose (FDG) positron emission tomography/CT.Methods:
3D TA of 48 lymph nodes in 29 patients was performed on venous-phase CE-CT images before and after chemotherapy. All lymph nodes showed pathologically elevated FDG uptake at baseline. A stepwise logistic regression with forward selection was performed to identify classic CT parameters and texture features (TF) that enable the separation of complete response (CR) and persistent disease.Results:
The TF fraction of image in runs, calculated for the 45° direction, was able to correctly identify CR with an accuracy of 75%, a sensitivity of 79.3%, and a specificity of 68.4%. Classical CT features achieved an accuracy of 75%, a sensitivity of 86.2%, and a specificity of 57.9%, whereas the combination of TF and CT imaging achieved an accuracy of 83.3%, a sensitivity of 86.2%, and a specificity of 78.9%.Conclusions:
3D TA of CE-CT images is potentially useful to identify nodal residual disease in HL, with a performance comparable to that of classical CT parameters. Best results are achieved when TA and classical CT features are combined.
41(2014); http://dx.doi.org/10.1118/1.4901265View Description Hide DescriptionPurpose:
Prior images can be incorporated into the image reconstruction process to improve the quality of subsequent cone-beam CT (CBCT) images from sparse-view or low-dose projections. The purpose of this work is to develop a deformed prior image-based reconstruction (DPIR) strategy to mitigate the deformation between the prior image and the target image.Methods:
The deformed prior image is obtained by a projection-based registration approach. Specifically, the deformation vector fields used to deform the prior image are estimated through iteratively matching the forward projection of the deformed prior image and the measured on-treatment projections. The deformed prior image is then used as the prior image in the standard prior image constrained compressed sensing (PICCS) algorithm. A simulation study on an XCAT phantom and a clinical study on a head-and-neck cancer patient were conducted to evaluate the performance of the proposed DPIR strategy.Results:
The deformed prior image matches the geometry of the on-treatment CBCT more closely as compared to the original prior image. Consequently, the performance of the DPIR strategy from few-view projections is improved in comparison to the standard PICCS algorithm, based on both visual inspection and quantitative measures. In the XCAT phantom study using 20 projections, the average root mean squared error is reduced from 14% in PICCS to 10% in DPIR, and the average universal quality index increases from 0.88 in PICCS to 0.92 in DPIR.Conclusions:
The present DPIR approach provides a practical solution to the mismatch problem between the prior image and target image, which improves the performance of the original PICCS algorithm for CBCT reconstruction from few-view or low-dose projections.
41(2014); http://dx.doi.org/10.1118/1.4901412View Description Hide DescriptionPurpose:
The authors are developing a computerized system for automated segmentation of ureters in CTU, referred to as combined model-guided path-finding analysis and segmentation system (COMPASS). Ureter segmentation is a critical component for computer-aided diagnosis of ureter cancer.Methods:
COMPASS consists of three stages: (1) rule-based adaptive thresholding and region growing, (2) path-finding and propagation, and (3) edge profile extraction and feature analysis. With institutional review board approval, 79 CTU scans performed with intravenous (IV) contrast material enhancement were collected retrospectively from 79 patient files. One hundred twenty-four ureters were selected from the 79 CTU volumes. On average, the ureters spanned 283 computed tomography slices (range: 116–399, median: 301). More than half of the ureters contained malignant or benign lesions and some had ureter wall thickening due to malignancy. A starting point for each of the 124 ureters was identified manually to initialize the tracking by COMPASS. In addition, the centerline of each ureter was manually marked and used as reference standard for evaluation of tracking performance. The performance of COMPASS was quantitatively assessed by estimating the percentage of the length that was successfully tracked and segmented for each ureter and by estimating the average distance and the average maximum distance between the computer and the manually tracked centerlines.Results:
Of the 124 ureters, 120 (97%) were segmented completely (100%), 121 (98%) were segmented through at least 70%, and 123 (99%) were segmented through at least 50% of its length. In comparison, using our previous method, 85 (69%) ureters were segmented completely (100%), 100 (81%) were segmented through at least 70%, and 107 (86%) were segmented at least 50% of its length. With COMPASS, the average distance between the computer and the manually generated centerlines is 0.54 mm, and the average maximum distance is 2.02 mm. With our previous method, the average distance between the centerlines was 0.80 mm, and the average maximum distance was 3.38 mm. The improvements in the ureteral tracking length and both distance measures were statistically significant (p < 0.0001).Conclusions:
COMPASS improved significantly the ureter tracking, including regions across ureter lesions, wall thickening, and the narrowing of the lumen.
Web-based, GPU-accelerated, Monte Carlo simulation and visualization of indirect radiation imaging detector performance41(2014); http://dx.doi.org/10.1118/1.4901516View Description Hide DescriptionPurpose:
Monte Carlo simulations play a vital role in the understanding of the fundamental limitations, design, and optimization of existing and emerging medical imaging systems. Efforts in this area have resulted in the development of a wide variety of open-source software packages. One such package, hybridMANTIS, uses a novel hybrid concept to model indirect scintillator detectors by balancing the computational load using dual CPU and graphics processing unit (GPU) processors, obtaining computational efficiency with reasonable accuracy. In this work, the authors describe two open-source visualization interfaces, webMANTIS and visualMANTIS to facilitate the setup of computational experiments via hybridMANTIS.Methods:
The visualization tools visualMANTIS and webMANTIS enable the user to control simulation properties through a user interface. In the case of webMANTIS, control via a web browser allows access through mobile devices such as smartphones or tablets. webMANTIS acts as a server back-end and communicates with an NVIDIA GPU computing cluster that can support multiuser environments where users can execute different experiments in parallel.Results:
The output consists of point response and pulse-height spectrum, and optical transport statistics generated by hybridMANTIS. The users can download the output images and statistics through a zip file for future reference. In addition, webMANTIS provides a visualization window that displays a few selected optical photon path as they get transported through the detector columns and allows the user to trace the history of the optical photons.Conclusions:
The visualization tools visualMANTIS and webMANTIS provide features such as on the fly generation of pulse-height spectra and response functions for microcolumnar x-ray imagers while allowing users to save simulation parameters and results from prior experiments. The graphical interfaces simplify the simulation setup and allow the user to go directly from specifying input parameters to receiving visual feedback for the model predictions.