bluuebunny/crossref_metadata_2025_split huggingface dataset:
Computerized method for evaluating diagnostic image quality of calcified plaque images in cardiac CT: Validation on a physical dynamic cardiac phantom
Authors: King Martin , Rodgers Zachary , Giger Maryellen L. , Bardo Dianna M. E. , Patel Amit R. 
Published: November 2010

Purpose:In cardiac computed tomography (CT), important clinical indices, such as the coronary calcium score and the percentage of coronary artery stenosis, are often adversely affected by motion artifacts. As a result, the expert observer must decide whether or not to use these indices during image interpretation. Computerized methods potentially can be used to assist in these decisions. In a previous study, an artificial neural network (ANN) regression model provided assessability (image quality) indices of calcified plaque images from the softwareNCAT phantom that were highly agreeable with those provided by expert observers. The method predicted assessability indices based on computer‐extracted features of the plaque. In the current study, the ANN‐predicted assessability indices were used to identify calcified plaque images with diagnostic calcium scores (based on mass) from a physical dynamic cardiac phantom. The basic assumption was that better quality images were associated with more accurate calcium scores.Methods:A 64‐channel CT scanner was used to obtain 500 calcified plaque images from a physical dynamic cardiac phantom at different heart rates, cardiac phases, and plaque locations. Two expert observers independently provided separate sets of assessability indices for each of these images. Separate sets of ANN‐predicted assessability indices tailored to each observer were then generated within the framework of a bootstrap resampling scheme. For each resampling iteration, the absolute calcium score error between the calcium scores of the motion‐contaminated plaque image and its corresponding stationary image served as the ground truth in terms of indicating images with diagnostic calcium scores. The performances of the ANN‐predicted and observer‐assigned indices in identifying images with diagnostic calcium scores were then evaluated using ROC analysis.Results:Assessability indices provided by the first observer and the corresponding ANN performed similarly ( vs ) as that of the second observer and the corresponding ANN ( vs ). Moreover, the ANN‐predicted indices were generated in a fraction of the time required to obtain the observer‐assigned indices.Conclusions:ANN‐predicted assessability indices performed similar to observer‐assigned assessability indices in identifying images with diagnostic calcium scores from the physical dynamic cardiac phantom. The results of this study demonstrate the potential of using computerized methods for identifying images with diagnostic clinical indices in cardiac CT images.
Statistical analysis of dose heterogeneity in circulating blood: Implications for sequential methods of total body irradiation
Authors: Molloy Janelle A. 
Published: November 2010

Purpose:Improvements in delivery techniques for total body irradiation (TBI) using Tomotherapy® and intensity modulated radiation therapy have been proven feasible. Despite the promise of improved dose conformality, the application of these “sequential” techniques has been hampered by concerns over dose heterogeneity to circulating blood. The present study was conducted to provide quantitative evidence regarding the potential clinical impact of this heterogeneity.Methods:Blood perfusion was modeled analytically as possessing linear, sinusoidal motion in the craniocaudal dimension. The average perfusion period for human circulation was estimated to be approximately 78 s. Sequential treatment delivery was modeled as a Gaussian‐shaped dose cloud with a 10 cm length that traversed a 183 cm patient length at a uniform speed. Total dose to circulating blood voxels was calculated via numerical integration and normalized to 2 Gy per fraction. Dose statistics and equivalent uniform dose (EUD) were calculated for relevant treatment times, radiobiological parameters, blood perfusion rates, and fractionation schemes. The model was then refined to account for random dispersion superimposed onto the underlying periodic blood flow. Finally, a fully stochastic model was developed using binomial and trinomial probability distributions. These models allowed for the analysis of nonlinear sequential treatment modalities and treatment designs that incorporate deliberate organ sparing.Results:The dose received by individual blood voxels exhibited asymmetric behavior that depended on the coherence among the blood velocity, circulation phase, and the spatiotemporal characteristics of the irradiation beam. Heterogeneity increased with the perfusion period and decreased with the treatment time. Notwithstanding, heterogeneity was less than for perfusion periods less than 150 s. The EUD was compromised for radiosensitive cells, long perfusion periods, and short treatment times. However, the EUD was unaffected (within 10%) for perfusion periods of less than 150 s or treatment times of 20 min or greater. Treatment over six fractions improved the EUD per fraction such that all parametric combinations resulted in unaffected EUD. The stochastic models confirmed these results.Conclusions:Dose heterogeneity in circulating blood cells is clinically acceptable for typical treatment times, perfusion rates, and cell types. Development of conformal, sequential TBI treatment techniques should not be withheld based on concerns over circulating blood dose heterogeneity.
Estimation of the minimum detectable activity of preclinical PET imaging systems with an analytical method
Authors: Bao Qinan , Chatziioannou Arion F. 
Published: November 2010

Purpose:The traditional figures of merit used in the evaluation of positron emission tomography (PET) systems, including system sensitivity and spatial resolution, do not directly reflect the minimum detectable activity (MDA) performance, despite the fact that it is one of the most important tasks for a PET system. MDA, as a combination of the more traditional PET system parameters, is directly related to lesion detection. However, MDA evaluation is task specific and cannot be done by a single measurement. Therefore, a simple method to evaluate system detectability needs to be developed.Methods:In this work, an analytical method of MDA estimation was developed, taking into account system sensitivity, spatial resolution, source properties, and noise propagation in image reconstruction by using the Rose criterion and/or the Curie equation as the detection standard. In the implementation, the source background, as well as the intrinsic activity background from the scintillation material of the system, was also taken into consideration. The accuracy of this method was evaluated in two commercially available preclinical PET systems, with phantom experiments that were designed to closely mimicin vivo tumor uptake without introducing finite boundaries between the source and the background.Results:The lesion contrast‐to‐noise ratio calculated by the analytical evaluation showed good agreement with that obtained from the experiments. Visual assessment of the reconstructed images at the detection limit (based on analytical evaluation) also was in agreement with the Rose criterion. The MDA performance was quantitatively compared between the two preclinical PET systems and showed different detection limits under different imaging conditions, suggesting that the detection limit of a PET system strongly depends on the lesion properties and acquisition settings.Conclusions:An analytical method of evaluating the PET system detectability was developed and validated by experiments. Overall, the analytical MDA calculation provides a simple way to evaluate the signal detectability of a PET system and can be used for comparing different systems. It also provides guidelines for designing new PET tomographs as well as optimizing data acquisition protocols.
Scatter correction for cone‐beam computed tomography using moving blocker strips: A preliminary study
Authors: Wang Jing , Mao Weihua , Solberg Timothy 
Published: November 2010

Purpose:One well‐recognized challenge of cone‐beam computed tomography (CBCT) is the presence of scatter contamination within the projection images. Scatter degrades the CBCT image quality by decreasing the contrast, introducing shading artifacts, and leading to inaccuracies in the reconstructed CT number. The authors propose a blocker‐based approach to simultaneously estimate scatter signal and reconstruct the complete volume within the field of view (FOV) from a single CBCT scan.Methods:A physical strip attenuator (i.e., “blocker”), consisting of lead strips, is inserted between the x‐ray source and the patient. The blocker moves back and forth along the‐axis during the gantry rotation. With such a design, the data required for the filtering step of the Feldkamp–Davis–Kress (FDK) algorithm are complete in the unblocked region and the entire volume within the FOV has the measurements at different projection views. The two‐dimensional scatter fluence is estimated by interpolating the signal from the blocked regions. A modified FDK algorithm and an iterative reconstruction based on the constraint optimization are used to reconstruct CBCT images from unblocked projection data after the scatter signal is subtracted. A simulation study and an experimental study are performed to evaluate the performance of the proposed scatter correction scheme.Results:The scatter‐induced shading/cupping artifacts are substantially reduced in CBCT using the proposed strategy. In the simulation study, the mean relative error is reduced from 25% to 3% and 2% in the images reconstructed by the modified FDK and constraint optimization, respectively. In the experimental study using a CatPhan® 600 phantom, CT number errors in the selected regions of interest are reduced from 256 to less than 20.Conclusions:An effective scatter correction scheme is proposed for CBCT. A moving blocker consisting of lead strips is inserted between the x‐ray source and the patient during CBCT acquisition. The proposed method allows the authors to simultaneously estimate the scatter signal in projection data, reduce the imaging dose, and obtain complete volumetric information within the FOV.
A spatio‐temporal detective quantum efficiency and its application to fluoroscopic systems
Authors: Friedman S. N. , Cunningham I. A. 
Published: November 2010

Purpose:Fluoroscopic x‐ray imaging systems are used extensively in spatio‐temporal detection tasks and require a spatio‐temporal description of system performance. No accepted metric exists that describes spatio‐temporal fluoroscopic performance. The detective quantum efficiency (DQE) is a metric widely used in radiography to quantify system performance and as a surrogate measure of patient “dose efficiency.” It has been applied previously to fluoroscopic systems with the introduction of a temporal correction factor. However, the use of a temporally‐corrected DQE does not provide system temporal information and it is only valid under specific conditions, many of which are not likely to be satisfied by suboptimal systems. The authors propose a spatio‐temporal DQE that describes performance in both spaceand time and is applicable to all spatio‐temporal quantum‐based imaging systems.Methods:The authors define a spatio‐temporal DQE (two spatial‐frequency axes and one temporal‐frequency axis) in terms of a small‐signal spatio‐temporal modulation transfer function (MTF) and spatio‐temporal noise power spectrum (NPS). Measurements were made on an x‐ray image intensifier‐based bench‐top system using continuous fluoroscopy with an RQA‐5 beam at/frame and hardened 50 kVp beam (0.8 mm Cu filtration added) at /frame.Results:A zero‐frequency DQE value of 0.64 was measured under both conditions. Nonideal performance was noted at both larger spatialand temporal frequencies; DQE values decreased by at the cutoff temporal frequency of 15 Hz.Conclusions:The spatio‐temporal DQE enables measurements of decreased temporal system performance at larger temporal frequencies analogous to previous measurements of decreased (spatial) performance. This marks the first time that system performance and dose efficiency in both space and time have been measured on a fluoroscopic system using DQE and is the first step toward the generalized use of DQE on clinical fluoroscopic systems.
Use of a realistic breathing lung phantom to evaluate dose delivery errorsa)
Authors: Court Laurence E. , Seco Joao , Lu Xing‐Qi , Ebe Kazuyu , Mayo Charles , Ionascu Dan , Winey Brian , Giakoumakis Nikos , Aristophanous Michalis , Berbeco Ross , Rottman Joerg , Bogdanov Madeleine , Schofield Deborah , Lingos Tania 
Published: November 2010

Purpose:To compare the effect of respiration‐induced motion on delivered dose (the interplay effect) for different treatment techniques under realistic clinical conditions.Methods:A flexible resin tumor model was created using rapid prototyping techniques based on a computed tomography (CT) image of an actual tumor. Twenty micro‐MOSFETs were inserted into the tumor model and the tumor model was inserted into an anthropomorphic breathing phantom. Phantom motion was programed using the motion trajectory of an actual patient. A four‐dimensional CT image was obtained and several treatment plans were created using different treatment techniques and planning systems: Conformal (Eclipse), step‐and‐shoot intensity‐modulated radiation therapy (IMRT) (Pinnacle), step‐and‐shoot IMRT (XiO), dynamic IMRT (Eclipse), complex dynamic IMRT (Eclipse), hybrid IMRT [60% conformal, 40% dynamic IMRT (Eclipse)], volume‐modulated arc therapy (VMAT) [single‐arc (Eclipse)], VMAT [double‐arc (Eclipse)], and complex VMAT (Eclipse). The complex plans were created by artificially pushing the optimizer to give complex multileaf collimator sequences. Each IMRT field was irradiated five times and each VMAT field was irradiated ten times, with each irradiation starting at a random point in the respiratory cycle. The effect of fractionation was calculated by randomly summing the measured doses. The maximum deviation for each measurement point per fraction and the probability that 95% of the model tumor had dose deviations less than 2% and 5% were calculated as a function of the number of fractions. Tumor control probabilities for each treatment plan were calculated and compared.Results:After five fractions, measured dose deviations were less than 2% for more than 95% of measurement points within the tumor model for all plans, except the complex dynamic IMRT, step‐and‐shoot IMRT (XiO), complex VMAT, and single‐arc VMAT plans. Reducing the dose rate of the complex IMRT plans from 600 to 200 MU/min reduced the dose deviations to less than 2%. Dose deviations were less than 5% after five fractions for all plans, except the complex single‐arc VMAT plan.Conclusions:Rapid prototyping techniques can be used to create realistic tumor models. For most treatment techniques, the dose deviations averaged out after several fractions. Treatments with unusually complicated multileaf collimator sequences had larger dose deviations. For IMRT treat‐ments, dose deviations can be reduced by reducing the dose rate. For VMAT treatments, using two arcs instead of one is effective for reducing dose deviations.
A grating‐based single‐shot x‐ray phase contrast and diffraction method for in vivo imaging
Authors: Bennett Eric E. , Kopace Rael , Stein Ashley F. , Wen Han 
Published: November 2010

Purpose:The purpose of this study is to develop a single‐shot version of the grating‐based phase contrast x‐ray imaging method and demonstrate its capability ofin vivo animal imaging. Here, the authors describe the principle and experimental results. They show the source of artifacts in the phase contrast signal and optimal designs that minimize them. They also discuss its current limitations and ways to overcome them.Methods:A single lead grid was inserted midway between an x‐ray tube and an x‐ray camera in the planar radiography setting. The grid acted as a transmission grating and cast periodic dark fringes on the camera. The camera had sufficient spatial resolution to resolve the fringes. Refraction and diffraction in the imaged object manifested as position shifts and amplitude attenuation of the fringes, respectively. In order to quantify these changes precisely without imposing a fixed geometric relationship between the camera pixel array and the fringes, a spatial harmonic method in the Fourier domain was developed. The level of the differential phase (refraction) contrast as a function of hardware specifications and device geometry was derived and used to guide the optimal placement of the grid and object. Bothex vivo and in vivo images of rodent extremities were collected to demonstrate the capability of the method. The exposure time using a 50 W tube was 28 s.Results:Differential phase contrast images of glass beads acquired at various grid and object positions confirmed theoretical predictions of how phase contrast and extraneous artifacts vary with the device geometry. In anesthetized rats, a single exposure yielded artifact‐free images of absorption, differential phase contrast, and diffraction. Differential phase contrast was strongest at bone‐soft tissue interfaces, while diffraction was strongest in bone.Conclusions:The spatial harmonic method allowed us to obtain absorption, differential phase contrast, and diffraction images, all from a single raw image and is feasible in live animals. Because the sensitivity of the method scales with the density of the gratings, custom microfabricated gratings should be superior to off‐the‐shelf lead grids.
Spectral perturbations from silicon diode detector encapsulation and shielding in photon fields
Authors: Eklund Karin , Ahnesjö Anders 
Published: November 2010

Purpose:Silicon diodes are widely used as detectors for relative dose measurements in radiotherapy. The common manufacturing practice is to encapsulate the diodes in plastic for protection and to facilitate mounting in scanning devices. Diodes intended for use in photon fields commonly also have a shield of a high atomic number material (usually tungsten) integrated into the encapsulation to selectively absorb low‐energy photons to which silicon diodes would otherwise over‐response. However, new response models based on cavity theories and spectra calculations have been proposed for direct correction of the readout from unshielded (e.g., “electron”) diodes used in photon fields. This raises the question whether it is correct to assume that the spectrum in a water phantom at the location of the detector cavity is not perturbed by the detector encapsulation materials. The aim of this work is to investigate the spectral effects of typical encapsulations, including shielding, used for clinical diodes.Methods:The effects of detector encapsulation of an unshielded and a shielded commercial diode on the spectra at the detector cavity location are studied through Monte Carlo simulations withPENELOPE‐2005. Variance reduction based on correlated sampling is applied to reduce the CPU time needed for the simulations.Results:The use of correlated sampling is found to be efficient and to not introduce any significant bias to the results. Compared to reference spectra calculated in water, the encapsulation for an unshielded diode is demonstrated to not perturb the spectrum, while a tungsten shielded diode caused not only the desired decrease in low‐energy scattered photons but also a large increase of the primary electron fluence. Measurements with a shielded diode in a 6 MV photon beam proved that the shielding does not completely remove the field‐size dependence of the detector response caused by the over‐response from low‐energy photons. Response factors of a properly corrected unshielded diode were shown to give comparable, or better, results than the traditionally used shielded diode.Conclusions:Spectra calculated for photon fields in water can be directly used for modeling the response of unshielded silicon diodes with plastic encapsulations. Unshielded diodes used together with appropriate corrections can replace shielded diodes in photon dose measurements.
A neural network based 3D/3D image registration quality evaluator for the head‐and‐neck patient setup in the absence of a ground truth
Authors: Wu Jian , Murphy Martin J. 
Published: November 2010

Purpose:To develop a neural network based registration quality evaluator (RQE) that can identify unsuccessful 3D/3D image registrations for the head‐and‐neck patient setup in radiotherapy.Methods:A two‐layer feed‐forward neural network was used as a RQE to classify 3D/3D rigid registration solutions as successful or unsuccessful based on the features of the similarity surface near the point‐of‐solution. The supervised training and test data sets were generated by rigidly registering daily cone‐beam CTs to the treatment planning fan‐beam CTs of six patients with head‐and‐neck tumors. Two different similarity metrics (mutual information and mean‐squared intensity difference) and two different types of image content (entire image versus bony landmarks) were used. The best solution for each registration pair was selected from 50 optimizing attempts that differed only by the initial transformation parameters. The distance from each individual solution to the best solution in the normalized parametrical space was compared to a user‐defined error threshold to determine whether that solution was successful or not. The supervised training was then used to train the RQE. The performance of the RQE was evaluated using the test data set that consisted of registration results that were not used in training.Results:The RQE constructed using the mutual information had very good performance when tested using the test data sets, yielding the sensitivity, the specificity, the positive predictive value, and the negative predictive value in the ranges of 0.960–1.000, 0.993–1.000, 0.983–1.000, and 0.909–1.000, respectively. Adding a RQE into a conventional 3D/3D image registration system incurs only about 10%–20% increase of the overall processing time.Conclusions:The authors' patient study has demonstrated very good performance of the proposed RQE when used with the mutual information in identifying unsuccessful 3D/3D registrations for daily patient setup. The classifier had very good generality and required only to be trained once for each implementation. When the RQE is incorporated with an automated 3D/3D image registration system, it can improve the robustness of the system.