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At least 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

Simultaneous reduction of radiation dose and scatter for CBCT by using collimators

Purpose: On-board cone-beam CT (CBCT) imaging has been widely available in radiotherapy clinic for target localization. However, the extra radiation dose from CBCT is always a concern for its frequent use. Additionally, the relatively large scatter in CBCT often degrades the image quality. By using collimators, some of the X-rays can be stopped from reaching the patient and the detectors, hence both the scatter and the patient doses are simultaneously reduced. The authors show in this work that the collimated CBCT data can be reconstructed without any noticeable artifacts for certain collimator blocking ratios and blocking patterns, and the focus of this work is to study the relationship between the image quality and these two collimator factors.Methods: A CBCT system with collimators was simulated following the typical geometry used in clinic. Different collimator designs were tested by varying the size and the number of the collimator slits, and at the same time, the ratio of transmitted beams to total beams was varied from 100% to 10%, resulting in hundreds of different simulation scenarios. Lung and pelvis phantoms created from patients CT images were used in the simulations, and an iterative reconstruction algorithm using the compressed sensing technique was adopted. The image quality was examined by root mean square errors (RMSEs) and compared with the conventional CBCT images.Results: The CBCT image quality increases as the amount of beams passing through the collimators increases, and decreases as the size of the collimator slits increases. With ultra-high resolution collimators, the RMSEs were comparable to the conventional CBCT image quality until the beam transmission rate is reduced below 25%.Conclusions: Collimators can reduce the scatters and radiation dose, however, the collimated CBCT image quality is strongly dependent on both the collimator blocking ratio and the blocking pattern. To achieve image quality comparable to the conventional CBCT, the amount of information and data format must be adequate.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2014

Grating-based phase contrast tomosynthesis imaging: Proof-of-concept experimental studies

Purpose: This paper concerns the feasibility of x-ray differential phase contrast (DPC) tomosynthesis imaging using a grating-based DPC benchtop experimental system, which is equipped with a commercial digital flat-panel detector and a medical-grade rotating-anode x-ray tube. An extensive system characterization was performed to quantify its imaging performance. Methods: The major components of the benchtop system include a diagnostic x-ray tube with a 1.0 mm nominal focal spot size, a flat-panel detector with 96 μm pixel pitch, a sample stage that rotates within a limited angular span of ±30°, and a Talbot-Lau interferometer with three x-ray gratings. A total of 21 projection views acquired with 3° increments were used to reconstruct three sets of tomosynthetic image volumes, including the conventional absorption contrast tomosynthesis image volume (AC-tomo) reconstructed using the filtered-backprojection (FBP) algorithm with the ramp kernel, the phase contrast tomosynthesis image volume (PC-tomo) reconstructed using FBP with a Hilbert kernel, and the differential phase contrast tomosynthesis image volume (DPC-tomo) reconstructed using the shift-and-add algorithm. Three inhouse physical phantoms containing tissue-surrogate materials were used to characterize the signal linearity, the signal difference-to-noise ratio (SDNR), the three-dimensional noise power spectrum (3D NPS), and the through-plane artifact spread function (ASF). Results: While DPC-tomo highlights edges and interfaces in the image object, PC-tomo removes the differential nature of the DPC projection data and its pixel values are linearly related to the decrement of the real part of the x-ray refractive index. The SDNR values of polyoxymethylene in water and polystyrene in oil are 1.5 and 1.0, respectively, in AC-tomo, and the values were improved to 3.0 and 2.0, respectively, in PC-tomo. PC-tomo and AC-tomo demonstrate equivalent ASF, but their noise characteristics quantified by the 3D NPS were found to be different due to the difference in the tomosynthesis image reconstruction algorithms. Conclusions: It is feasible to simultaneously generate x-ray differential phase contrast, phase contrast, and absorption contrast tomosynthesis images using a grating-based data acquisition setup. The method shows promise in improving the visibility of several low-density materials and therefore merits further investigation.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

Model-based PSF and MTF estimation and validation from skeletal clinical CT images

Purpose: A method was developed to correct for systematic errors in estimating the thickness of thin bones due to image blurring in CT images using bone interfaces to estimate the point-spread-function (PSF). This study validates the accuracy of the PSFs estimated using said method from various clinical CT images featuring cortical bones. Methods: Gaussian PSFs, characterized by a different extent in the z (scan) direction than in the x and y directions were obtained using our method from 11 clinical CT scans of a cadaveric craniofacial skeleton. These PSFs were estimated for multiple combinations of scanning parameters and reconstruction methods. The actual PSF for each scan setting was measured using the slanted-slit technique within the image slice plane and the longitudinal axis. The Gaussian PSF and the corresponding modulation transfer function (MTF) are compared against the actual PSF and MTF for validation. Results: The differences (errors) between the actual and estimated full-width half-max (FWHM) of the PSFs were 0.09 ± 0.05 and 0.14 ± 0.11 mm for the xy and z axes, respectively. The overall errors in the predicted frequencies measured at 75%, 50%, 25%, 10%, and 5% MTF levels were 0.06 ± 0.07 and 0.06 ± 0.04 cycles/mm for the xy and z axes, respectively. The accuracy of the estimates was dependent on whether they were reconstructed with a standard kernel (Toshiba's FC68, mean error of 0.06 ± 0.05 mm, MTF mean error 0.02 ± 0.02 cycles/mm) or a high resolution bone kernel (Toshiba's FC81, PSF FWHM error 0.12 ± 0.03 mm, MTF mean error 0.09 ± 0.08 cycles/mm). Conclusions: The method is accurate in 3D for an image reconstructed using a standard reconstruction kernel, which conforms to the Gaussian PSF assumption but less accurate when using a high resolution bone kernel. The method is a practical and self-contained means of estimating the PSF in clinical CT images featuring cortical bones, without the need phantoms or any prior knowledge about the scanner-specific parameters.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

Towards local progression estimation of pulmonary emphysema using CT

Purpose: Whole lung densitometry on chest CT images is an accepted method for measuring tissue destruction in patients with pulmonary emphysema in clinical trials. Progression measurement is required for evaluation of change in health condition and the effect of drug treatment. Information about the location of emphysema progression within the lung may be important for the correct interpretation of drug efficacy, or for determining a treatment plan. The purpose of this study is therefore to develop and validate methods that enable the local measurement of lung density changes, which requires proper modeling of the effect of respiration on density. Methods: Four methods, all based on registration of baseline and follow-up chest CT scans, are compared. The first naïve method subtracts registered images. The second employs the so-called dry sponge model, where volume correction is performed using the determinant of the Jacobian of the transformation. The third and the fourth introduce a novel adaptation of the dry sponge model that circumvents its constant-mass assumption, which is shown to be invalid. The latter two methods require a third CT scan at a different inspiration level to estimate the patient-specific density-volume slope, where one method employs a global and the other a local slope. The methods were validated on CT scans of a phantom mimicking the lung, where mass and volume could be controlled. In addition, validation was performed on data of 21 patients with pulmonary emphysema. Results: The image registration method was optimized leaving a registration error below half the slice increment (median 1.0 mm). The phantom study showed that the locally adapted slope model most accurately measured local progression. The systematic error in estimating progression, as measured on the phantom data, was below 2 gr/l for a 70 ml (6%) volume difference, and 5 gr/l for a 210 ml (19%) difference, if volume correction was applied. On the patient data an underlying linearity assumption relating lung volume change with density change was shown to hold (fitR{sup 2} = 0.94), and globalized versions of the local models are consistent with global results (R{sup 2} of 0.865 and 0.882 for the two adapted slope models, respectively). Conclusions: In conclusion, image matching and subsequent analysis of differences according to the proposed lung models (i) has good local registration accuracy on patient data, (ii) effectively eliminates a dependency on inspiration level at acquisition time, (iii) accurately predicts progression in phantom data, and (iv) is reasonably consistent with global results in patient data. It is therefore a potential future tool for assessing local emphysema progression in drug evaluation trials and in clinical practice.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

Measuring linac photon beam energy through EPID image analysis of physically wedged fields

Purpose: Electronic portal imaging devices (EPIDs) have proven to be useful tools for measuring several parameters of interest in linac quality assurance (QA). However, a method for measuring linac photon beam energy using EPIDs has not previously been reported. In this report, such a method is devised and tested, based on fitting a second order polynomial to the profiles of physically wedged beams, where the metric of interest is the second order coefficientα. The relationship between α and the beam quality index [percentage depth dose at 10 cm depth (PDD{sub 10})] is examined to produce a suitable calibration curve between these two parameters. Methods: Measurements were taken in a water-tank for beams with a range of energies representative of the local QA tolerances about the nominal value 6 MV. In each case, the beam quality was found in terms of PDD{sub 10} for 100 × 100 mm{sup 2} square fields. EPID images of 200 × 200 mm{sup 2} wedged fields were then taken for each beam and the wedge profile was fitted in MATLAB 2010b (The MathWorks, Inc., Natick, MA). α was then plotted against PDD{sub 10} and fitted with a linear relation to produce the calibration curve. The uncertainty in α was evaluated by taking five repeat EPID images of the wedged field for a beam of 6 MV nominal energy. The consistency of measuring α was found by taking repeat measurements on a single linac over a three month period. The method was also tested at 10 MV by repeating the water-tank crosscalibration for a range of energies centered approximately about a 10 MV nominal value. Finally, the calibration curve from the test linac and that from a separate clinical machine were compared to test consistency of the method across machines in a matched fleet. Results: The relationship betweenα and PDD{sub 10} was found to be strongly linear (R{sup 2} = 0.979) while the uncertainty in α was found to be negligible compared to that associated with measuring PDD{sub 10} in the water-tank (±0.3%). The repeat measurements over a three month period showed the method to be reasonably consistent (i.e., well within the limits defined by local QA tolerances). The measurements were repeated on a matched machine and the same linear relationship between α and PDD{sub 10} was observed. The results for both machines were found to be indistinguishable across the energy range of interest (i.e., across and close to the thresholds defined by local QA tolerances), hence a single relation could be established across a matched fleet. Finally, the experiment was repeated on both linacs at 10 MV, where the linear relationship between α and PDD{sub 10} was again observed. Conclusions: The authors conclude that EPID image analysis of physically wedged beam profiles can be used to measure linac photon beam energy. The uncertainty in such a measurement is dominated by that associated with measuring PDD{sub 10} in the water-tank; hence, the accuracies of these two methods are directly comparable. This method provides a useful technique for quickly performing energy constancy measurements while saving significant clinical downtime for QA.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2014

The effect of excitation and preparation pulses on nonslice selective 2D UTE bicomponent analysis of bound and free water in cortical bone at 3T

Purpose: The purpose of this study was to investigate the effect of excitation, fat saturation, long T2 saturation, and adiabatic inversion pulses on ultrashort echo time (UTE) imaging with bicomponent analysis of bound and free water in cortical bone for potential applications in osteoporosis. Methods: Six bovine cortical bones and six human tibial midshaft samples were harvested for this study. Each bone sample was imaged with eight sequences using 2D UTE imaging at 3T with half and hard excitation pulses, without and with fat saturation, long T2 saturation, and adiabatic inversion recovery (IR) preparation pulses. Single- and bicomponent signal models were utilized to calculate the T2{sup *}s and/or relative fractions of short and long T2{sup *}s. Results: For all bone samples UTE T2{sup *} signal decay showed bicomponent behavior. A higher short T2{sup *} fraction was observed on UTE images with hard pulse excitation compared with half pulse excitation (75.6% vs 68.8% in bovine bone, 79.9% vs 73.2% in human bone). Fat saturation pulses slightly reduced the short T2{sup *} fraction relative to regular UTE sequences (5.0% and 2.0% reduction, respectively, with half and hard excitation pulses for bovine bone, 6.3% and 8.2% reduction, respectively, with half and hard excitation pulses for human bone). Long T2 saturation pulses significantly reduced the long T2{sup *} fraction relative to regular UTE sequence (18.9% and 17.2% reduction, respectively, with half and hard excitation pulses for bovine bone, 26.4% and 27.7% reduction, respectively, with half and hard excitation pulses for human bone). With IR-UTE preparation the long T2{sup *} components were significantly reduced relative to regular UTE sequence (75.3% and 66.4% reduction, respectively, with half and hard excitation pulses for bovine bone, 87.7% and 90.3% reduction, respectively, with half and hard excitation pulses for human bone). Conclusions: Bound and free water T2{sup *}s and relative fractions can be assessed using UTE bicomponent analysis. Long T2{sup *} components are affected more by long T2 saturation and IR pulses, and short T2{sup *} components are affected more by fat saturation pulses.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

Mammographic quantitative image analysis and biologic image composition for breast lesion characterization and classification

Purpose: To investigate whether biologic image composition of mammographic lesions can improve upon existing mammographic quantitative image analysis (QIA) in estimating the probability of malignancy. Methods: The study population consisted of 45 breast lesions imaged with dual-energy mammography prior to breast biopsy with final diagnosis resulting in 10 invasive ductal carcinomas, 5 ductal carcinomain situ, 11 fibroadenomas, and 19 other benign diagnoses. Analysis was threefold: (1) The raw low-energy mammographic images were analyzed with an established in-house QIA method, “QIA alone,” (2) the three-compartment breast (3CB) composition measure—derived from the dual-energy mammography—of water, lipid, and protein thickness were assessed, “3CB alone”, and (3) information from QIA and 3CB was combined, “QIA + 3CB.” Analysis was initiated from radiologist-indicated lesion centers and was otherwise fully automated. Steps of the QIA and 3CB methods were lesion segmentation, characterization, and subsequent classification for malignancy in leave-one-case-out cross-validation. Performance assessment included box plots, Bland–Altman plots, and Receiver Operating Characteristic (ROC) analysis. Results: The area under the ROC curve (AUC) for distinguishing between benign and malignant lesions (invasive and DCIS) was 0.81 (standard error 0.07) for the “QIA alone” method, 0.72 (0.07) for “3CB alone” method, and 0.86 (0.04) for “QIA+3CB” combined. The difference in AUC was 0.043 between “QIA + 3CB” and “QIA alone” but failed to reach statistical significance (95% confidence interval [–0.17 to + 0.26]). Conclusions: In this pilot study analyzing the new 3CB imaging modality, knowledge of the composition of breast lesions and their periphery appeared additive in combination with existing mammographic QIA methods for the distinction between different benign and malignant lesion types.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

Automatic CT simulation optimization for radiation therapy: A general strategy

Purpose: In radiation therapy, x-ray computed tomography (CT) simulation protocol specifications should be driven by the treatment planning requirements in lieu of duplicating diagnostic CT screening protocols. The purpose of this study was to develop a general strategy that allows for automatically, prospectively, and objectively determining the optimal patient-specific CT simulation protocols based on radiation-therapy goals, namely, maintenance of contouring quality and integrity while minimizing patient CT simulation dose. Methods: The authors proposed a general prediction strategy that provides automatic optimal CT simulation protocol selection as a function of patient size and treatment planning task. The optimal protocol is the one that delivers the minimum dose required to provide a CT simulation scan that yields accurate contours. Accurate treatment plans depend on accurate contours in order to conform the dose to actual tumor and normal organ positions. An image quality index, defined to characterize how simulation scan quality affects contour delineation, was developed and used to benchmark the contouring accuracy and treatment plan quality within the predication strategy. A clinical workflow was developed to select the optimal CT simulation protocols incorporating patient size, target delineation, and radiation dose efficiency. An experimental study using an anthropomorphic pelvis phantom with added-bolus layers was used to demonstrate how the proposed prediction strategy could be implemented and how the optimal CT simulation protocols could be selected for prostate cancer patients based on patient size and treatment planning task. Clinical IMRT prostate treatment plans for seven CT scans with varied image quality indices were separately optimized and compared to verify the trace of target and organ dosimetry coverage. Results: Based on the phantom study, the optimal image quality index for accurate manual prostate contouring was 4.4. The optimal tube potentials for patient sizes of 38, 43, 48, 53, and 58 cm were 120, 140, 140, 140, and 140 kVp, respectively, and the corresponding minimum CTDIvol for achieving the optimal image quality index 4.4 were 9.8, 32.2, 100.9, 241.4, and 274.1 mGy, respectively. For patients with lateral sizes of 43–58 cm, 120-kVp scan protocols yielded up to 165% greater radiation dose relative to 140-kVp protocols, and 140-kVp protocols always yielded a greater image quality index compared to the same dose-level 120-kVp protocols. The trace of target and organ dosimetry coverage and the γ passing rates of seven IMRT dose distribution pairs indicated the feasibility of the proposed image quality index for the predication strategy. Conclusions: A general strategy to predict the optimal CT simulation protocols in a flexible and quantitative way was developed that takes into account patient size, treatment planning task, and radiation dose. The experimental study indicated that the optimal CT simulation protocol and the corresponding radiation dose varied significantly for different patient sizes, contouring accuracy, and radiation treatment planning tasks.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

The influence of respiratory motion on CT image volume definition

Purpose: Radiotherapy treatments are based on geometric and density information acquired from patient CT scans. It is well established that breathing motion during scan acquisition induces motion artifacts in CT images, which can alter the size, shape, and density of a patient's anatomy. The aim of this work is to examine and evaluate the impact of breathing motion on multislice CT imaging with respiratory synchronization (4DCT) and without it (3DCT). Methods: A specific phantom with a movable insert was used. Static and dynamic phantom acquisitions were obtained with a multislice CT. Four sinusoidal breath patterns were simulated to move known geometric structures longitudinally. Respiratory synchronized acquisitions (4DCT) were performed to generate images during inhale, intermediate, and exhale phases using prospective and retrospective techniques. Static phantom data were acquired in helical and sequential mode to define a baseline for each type of respiratory 4DCT technique. Taking into account the fact that respiratory 4DCT is not always available, 3DCT helical image studies were also acquired for several CT rotation periods. To study breath and acquisition coupling when respiratory 4DCT was not performed, the beginning of the CT image acquisition was matched with inhale, intermediate, or exhale respiratory phases, for each breath pattern. Other coupling scenarios were evaluated by simulating different phantom and CT acquisition parameters. Motion induced variations in shape and density were quantified by automatic threshold volume generation and Dice similarity coefficient calculation. The structure mass center positions were also determined to make a comparison with their theoretical expected position. Results: 4DCT acquisitions provided volume and position accuracies within ±3% and ±2 mm for structure dimensions >2 cm, breath amplitude ≤15 mm, and breath period ≥3 s. The smallest object (1 cm diameter) exceeded 5% volume variation for the breath patterns of higher frequency and amplitude motion. Larger volume differences (>10%) and inconsistencies between the relative positions of objects were detected in image studies acquired without respiratory control. Increasing the 3DCT rotation period caused a higher distortion in structures without obtaining their envelope. Simulated data showed that the slice acquisition time should be at least twice the breath period to average object movement. Conclusions: Respiratory 4DCT images provide accurate volume and position of organs affected by breath motion detecting higher volume discrepancies as amplitude length or breath frequency are increased. For 3DCT acquisitions, a CT should be considered slow enough to include lesion envelope as long as the slice acquisition time exceeds twice the breathing period. If this requirement cannot be satisfied, a fast CT (along with breath-hold inhale and exhale CTs to estimate roughly the ITV) is recommended in order to minimize structure distortion. Even with an awareness of a patient's respiratory cycle, its coupling with 3DCT acquisition cannot be predicted since patient anatomy is not accurately known.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

Evaluation of the spline reconstruction technique for PET

Purpose: The spline reconstruction technique (SRT), based on the analytic formula for the inverse Radon transform, has been presented earlier in the literature. In this study, the authors present an improved formulation and numerical implementation of this algorithm and evaluate it in comparison to filtered backprojection (FBP). Methods: The SRT is based on the numerical evaluation of the Hilbert transform of the sinogram via an approximation in terms of “custom made” cubic splines. By restricting reconstruction only within object pixels and by utilizing certain mathematical symmetries, the authors achieve a reconstruction time comparable to that of FBP. The authors have implemented SRT in STIR and have evaluated this technique using simulated data from a clinical positron emission tomography (PET) system, as well as real data obtained from clinical and preclinical PET scanners. For the simulation studies, the authors have simulated sinograms of a point-source and three digital phantoms. Using these sinograms, the authors have created realizations of Poisson noise at five noise levels. In addition to visual comparisons of the reconstructed images, the authors have determined contrast and bias for different regions of the phantoms as a function of noise level. For the real-data studies, sinograms of an{sup 18}F-FDG injected mouse, a NEMA NU 4-2008 image quality phantom, and a Derenzo phantom have been acquired from a commercial PET system. The authors have determined: (a) coefficient of variations (COV) and contrast from the NEMA phantom, (b) contrast for the various sections of the Derenzo phantom, and (c) line profiles for the Derenzo phantom. Furthermore, the authors have acquired sinograms from a whole-body PET scan of an {sup 18}F-FDG injected cancer patient, using the GE Discovery ST PET/CT system. SRT and FBP reconstructions of the thorax have been visually evaluated. Results: The results indicate an improvement in FWHM and FWTM in both simulated and real point-source studies. In all simulated phantoms, the SRT exhibits higher contrast and lower bias than FBP at all noise levels, by increasing the COV in the reconstructed images. Finally, in real studies, whereas the contrast of the cold chambers are similar for both algorithms, the SRT reconstructed images of the NEMA phantom exhibit slightly higher COV values than those of FBP. In the Derenzo phantom, SRT resolves the 2-mm separated holes slightly better than FBP. The small-animal and human reconstructions via SRT exhibit slightly higher resolution and contrast than the FBP reconstructions. Conclusions: The SRT provides images of higher resolution, higher contrast, and lower bias than FBP, by increasing slightly the noise in the reconstructed images. Furthermore, it eliminates streak artifacts outside the object boundary. Unlike other analytic algorithms, the reconstruction time of SRT is comparable with that of FBP. The source code for SRT will become available in a future release of STIR.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

Statistical model based iterative reconstruction (MBIR) in clinical CT systems: Experimental assessment of noise performance

Purpose: To reduce radiation dose in CT imaging, the statistical model based iterative reconstruction (MBIR) method has been introduced for clinical use. Based on the principle of MBIR and its nonlinear nature, the noise performance of MBIR is expected to be different from that of the well-understood filtered backprojection (FBP) reconstruction method. The purpose of this work is to experimentally assess the unique noise characteristics of MBIR using a state-of-the-art clinical CT system. Methods: Three physical phantoms, including a water cylinder and two pediatric head phantoms, were scanned in axial scanning mode using a 64-slice CT scanner (Discovery CT750 HD, GE Healthcare, Waukesha, WI) at seven different mAs levels (5, 12.5, 25, 50, 100, 200, 300). At each mAs level, each phantom was repeatedly scanned 50 times to generate an image ensemble for noise analysis. Both the FBP method with a standard kernel and the MBIR method (Veo{sup ®}, GE Healthcare, Waukesha, WI) were used for CT image reconstruction. Three-dimensional (3D) noise power spectrum (NPS), two-dimensional (2D) NPS, and zero-dimensional NPS (noise variance) were assessed both globally and locally. Noise magnitude, noise spatial correlation, noise spatial uniformity and their dose dependence were examined for the two reconstruction methods. Results: (1) At each dose level and at each frequency, the magnitude of the NPS of MBIR was smaller than that of FBP. (2) While the shape of the NPS of FBP was dose-independent, the shape of the NPS of MBIR was strongly dose-dependent; lower dose lead to a “redder” NPS with a lower mean frequency value. (3) The noise standard deviation (σ) of MBIR and dose were found to be related through a power law of σ ∝ (dose){sup −β} with the component β ≈ 0.25, which violated the classical σ ∝ (dose){sup −0.5} power law in FBP. (4) With MBIR, noise reduction was most prominent for thin image slices. (5) MBIR lead to better noise spatial uniformity when compared with FBP. (6) A composite image generated from two MBIR images acquired at two different dose levels (D1 and D2) demonstrated lower noise than that of an image acquired at a dose level of D1+D2. Conclusions: The noise characteristics of the MBIR method are significantly different from those of the FBP method. The well known tradeoff relationship between CT image noise and radiation dose has been modified by MBIR to establish a more gradual dependence of noise on dose. Additionally, some other CT noise properties that had been well understood based on the linear system theory have also been altered by MBIR. Clinical CT scan protocols that had been optimized based on the classical CT noise properties need to be carefully re-evaluated for systems equipped with MBIR in order to maximize the method's potential clinical benefits in dose reduction and/or in CT image quality improvement.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

Analysis of perceived similarity between pairs of microcalcification clusters in mammograms

Purpose: Content-based image retrieval aims to assist radiologists by presenting example images with known pathology that are visually similar to the case being evaluated. In this work, the authors investigate several fundamental issues underlying the similarity ratings between pairs of microcalcification (MC) lesions on mammograms as judged by radiologists: the degree of variability in the similarity ratings, the impact of this variability on agreement between readers in retrieval of similar lesions, and the factors contributing to the readers’ similarity ratings. Methods: The authors conduct a reader study on a set of 1000 image pairs of MC lesions, in which a group of experienced breast radiologists rated the degree of similarity between each image pair. The image pairs are selected, from among possible pairings of 222 cases (110 malignant, 112 benign), based on quantitative image attributes (features) and the results of a preliminary reader study. Next, the authors apply analysis of variance (ANOVA) to quantify the level of variability in the readers’ similarity ratings, and study how the variability in individual reader ratings affects consistency between readers. The authors also measure the extent to which readers agree on images which are most similar to a given query, for which the Dice coefficient is used. To investigate how the similarity ratings potentially relate to the attributes underlying the cases, the authors study the fraction of perceptually similar images that also share the same benign or malignant pathology as the query image; moreover, the authors apply multidimensional scaling (MDS) to embed the cases according to their mutual perceptual similarity in a two-dimensional plot, which allows the authors to examine the manner in which similar lesions relate to one another in terms of benign or malignant pathology and clustered MCs. Results: The ANOVA results show that the coefficient of determination in the reader similarity ratings is 0.59. The variability level in the similarity ratings is proved to be a limiting factor, leading to only moderate correlation between the readers in their readings. The Dice coefficient, measuring agreement between readers in retrieval of similar images, can vary from 0.45 to 0.64 with different levels of similarity for individual readers, but is higher for average ratings from a group of readers (from 0.59 to 0.78). More importantly, the fraction of retrieved cases that match the benign or malignant pathology of the query image was found to increase with the degree of similarity among the retrieved images, reaching average value as high as 0.69 for the radiologists (p-value <10{sup −4} compared to random guessing). Moreover, MDS embedding of all the cases shows that cases having the same pathology tend to cluster together, and that neighboring cases in the plot tend to be similar in their clustered MCs. Conclusions: While individual readers exhibit substantial variability in their similarity ratings, similarity ratings averaged from a group of readers can achieve a high level of intergroup consistency and agreement in retrieval of similar images. More importantly, perceptually similar cases are also likely to be similar in their underlying benign or malignant pathology and image features of clustered MCs, which could be of diagnostic value in computer-aided diagnosis for lesions with clustered MCs.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

Automatic segmentation of head and neck CT images for radiotherapy treatment planning using multiple atlases, statistical appearance models, and geodesic active contours

Purpose: Accurate delineation of organs at risk (OARs) is a precondition for intensity modulated radiation therapy. However, manual delineation of OARs is time consuming and prone to high interobserver variability. Because of image artifacts and low image contrast between different structures, however, the number of available approaches for autosegmentation of structures in the head-neck area is still rather low. In this project, a new approach for automated segmentation of head-neck CT images that combine the robustness of multiatlas-based segmentation with the flexibility of geodesic active contours and the prior knowledge provided by statistical appearance models is presented. Methods: The presented approach is using an atlas-based segmentation approach in combination with label fusion in order to initialize a segmentation pipeline that is based on using statistical appearance models and geodesic active contours. An anatomically correct approximation of the segmentation result provided by atlas-based segmentation acts as a starting point for an iterative refinement of this approximation. The final segmentation result is based on using model to image registration and geodesic active contours, which are mutually influencing each other. Results: 18 CT images in combination with manually segmented labels of parotid glands and brainstem were used in a leave-one-out cross validation scheme in order to evaluate the presented approach. For this purpose, 50 different statistical appearance models have been created and used for segmentation. Dice coefficient (DC), mean absolute distance and max. Hausdorff distance between the autosegmentation results and expert segmentations were calculated. An average Dice coefficient of DC = 0.81 (right parotid gland), DC = 0.84 (left parotid gland), and DC = 0.86 (brainstem) could be achieved. Conclusions: The presented framework provides accurate segmentation results for three important structures in the head neck area. Compared to a segmentation approach based on using multiple atlases in combination with label fusion, the proposed hybrid approach provided more accurate results within a clinically acceptable amount of time.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

Feature-space assessment of electrical impedance tomography coregistered with computed tomography in detecting multiple contrast targets

Purpose: Fusion of electrical impedance tomography (EIT) with computed tomography (CT) can be useful as a clinical tool for providing additional physiological information about tissues, but requires suitable fusion algorithms and validation procedures. This work explores the feasibility of fusing EIT and CT images using an algorithm for coregistration. The imaging performance is validated through feature space assessment on phantom contrast targets. Methods: EIT data were acquired by scanning a phantom using a circuit, configured for injecting current through 16 electrodes, placed around the phantom. A conductivity image of the phantom was obtained from the data using electrical impedance and diffuse optical tomography reconstruction software (EIDORS). A CT image of the phantom was also acquired. The EIT and CT images were fused using a region of interest (ROI) coregistration fusion algorithm. Phantom imaging experiments were carried out on objects of different contrasts, sizes, and positions. The conductive medium of the phantoms was made of a tissue-mimicking bolus material that is routinely used in clinical radiation therapy settings. To validate the imaging performance in detecting different contrasts, the ROI of the phantom was filled with distilled water and normal saline. Spatially separated cylindrical objects of different sizes were used for validating the imaging performance in multiple target detection. Analyses of the CT, EIT and the EIT/CT phantom images were carried out based on the variations of contrast, correlation, energy, and homogeneity, using a gray level co-occurrence matrix (GLCM). A reference image of the phantom was simulated using EIDORS, and the performances of the CT and EIT imaging systems were evaluated and compared against the performance of the EIT/CT system using various feature metrics, detectability, and structural similarity index measures. Results: In detecting distilled and normal saline water in bolus medium, EIT as a stand-alone imaging system showed contrast discrimination of 47%, while the CT imaging system showed a discrimination of only 1.5%. The structural similarity index measure showed a drop of 24% with EIT imaging compared to CT imaging. The average detectability measure for CT imaging was found to be 2.375 ± 0.19 before fusion. After complementing with EIT information, the detectability measure increased to 11.06 ± 2.04. Based on the feature metrics, the functional imaging quality of CT and EIT were found to be 2.29% and 86%, respectively, before fusion. Structural imaging quality was found to be 66% for CT and 16% for EIT. After fusion, functional imaging quality improved in CT imaging from 2.29% to 42% and the structural imaging quality of EIT imaging changed from 16% to 66%. The improvement in image quality was also observed in detecting objects of different sizes. Conclusions: The authors found a significant improvement in the contrast detectability performance of CT imaging when complemented with functional imaging information from EIT. Along with the feature assessment metrics, the concept of complementing CT with EIT imaging can lead to an EIT/CT imaging modality which might fully utilize the functional imaging abilities of EIT imaging, thereby enhancing the quality of care in the areas of cancer diagnosis and radiotherapy treatment planning.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

Fiducial marker-based correction for involuntary motion in weight-bearing C-arm CT scanning of knees. II. Experiment

Purpose: A C-arm CT system has been shown to be capable of scanning a single cadaver leg under loaded conditions by virtue of its highly flexible acquisition trajectories. In Part I of this study, using the 4D XCAT-based numerical simulation, the authors predicted that the involuntary motion in the lower body of subjects in weight-bearing positions would seriously degrade image quality and the authors suggested three motion compensation methods by which the reconstructions could be corrected to provide diagnostic image quality. Here, the authors demonstrate that a flat-panel angiography system is appropriate for scanning both legs of subjectsin vivo under weight-bearing conditions and further evaluate the three motion-correction algorithms using in vivo data. Methods: The geometry of a C-arm CT system for a horizontal scan trajectory was calibrated using the PDS-2 phantom. The authors acquired images of two healthy volunteers while lying supine on a table, standing, and squatting at several knee flexion angles. In order to identify the involuntary motion of the lower body, nine 1-mm-diameter tantalum fiducial markers were attached around the knee. The static mean marker position in 3D, a reference for motion compensation, was estimated by back-projecting detected markers in multiple projections using calibrated projection matrices and identifying the intersection points in 3D of the back-projected rays. Motion was corrected using three different methods (described in detail previously): (1) 2D projection shifting, (2) 2D deformable projection warping, and (3) 3D rigid body warping. For quantitative image quality analysis, SSIM indices for the three methods were compared using the supine data as a ground truth. Results: A 2D Euclidean distance-based metric of subjects’ motion ranged from 0.85 mm (±0.49 mm) to 3.82 mm (±2.91 mm) (corresponding to 2.76 to 12.41 pixels) resulting in severe motion artifacts in 3D reconstructions. Shifting in 2D, 2D warping, and 3D warping improved the SSIM in the central slice by 20.22%, 16.83%, and 25.77% in the data with the largest motion among the five datasets (SCAN5); improvement in off-center slices was 18.94%, 29.14%, and 36.08%, respectively. Conclusions: The authors showed that C-arm CT control can be implemented for nonstandard horizontal trajectories which enabled us to scan and successfully reconstruct both legs of volunteers in weight-bearing positions. As predicted using theoretical models, the proposed motion correction methods improved image quality by reducing motion artifacts in reconstructions; 3D warping performed better than the 2D methods, especially in off-center slices.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

Upright cone beam CT imaging using the onboard imager

Purpose: Many patients could benefit from being treated in an upright position. The objectives of this study were to determine whether cone beam computed tomography (CBCT) could be used to acquire upright images for treatment planning and to demonstrate whether reconstruction of upright images maintained accurate geometry and Hounsfield units (HUs). Methods: A TrueBeam linac was programmed in developer mode to take upright CBCT images. The gantry head was positioned at 0°, and the couch was rotated to 270°. The x-ray source and detector arms were extended to their lateral positions. The x-ray source and gantry remained stationary as fluoroscopic projections were taken and the couch was rotated from 270° to 90°. The x-ray tube current was normalized to deposit the same dose (measured using a calibrated Farmer ion chamber) as that received during a clinical helical CT scan to the center of a cylindrical, polyethylene phantom. To extend the field of view, two couch rotation scans were taken with the detector offset 15 cm superiorly and then 15 cm inferiorly. The images from these two scans were stitched together before reconstruction. Upright reconstructions were compared to reconstructions from simulation CT scans of the same phantoms. Two methods were investigated for correcting the HUs, including direct calibration and mapping the values from a simulation CT. Results: Overall geometry, spatial linearity, and high contrast resolution were maintained in upright reconstructions. Some artifacts were created and HU accuracy was compromised; however, these limitations could be removed by mapping the HUs from a simulation CT to the upright reconstruction for treatment planning. Conclusions: The feasibility of using the TrueBeam linac to take upright CBCT images was demonstrated. This technique is straightforward to implement and could be of enormous benefit to patients with thoracic tumors or those who find a supine position difficult to endure.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

Quasi real time in vivo dosimetry for VMAT

Purpose: Results about the feasibility of a method for quasi real timein vivo dosimetry (IVD) at the isocenter point for volumetric modulated arc therapy (VMAT) are here reported. The method is based on correlations between the EPID signal and the dose on the beam central axis. Moreover, the γ-analysis of EPID images was adopted to verify off-axis reproducibility of fractionated plan delivery. Methods: An algorithm to reconstructin vivo the isocenter dose, D{sub iso}, for RapidArc treatments has been developed. 20 VMAT plans, optimized with two opposite arcs, for prostate, pancreas, and head treatments have been delivered by a Varian linac both to a conic PMMA phantom with elliptical section and to patients. The ratios R between reconstructed D{sub iso} and the planned doses were determined for phantom and patient irradiations adopting an acceptance criterion of ±5%. In total, 40 phantom checks and 400 patient checks were analyzed. Moreover, 3% and 3 mm criteria were adopted for portal image γ-analysis to assess patient irradiation reproducibility. Results: The average ratio R, between reconstructed and planned doses for the PMMA phantom irradiations was equal to 1.007 ± 0.024. When the IVD method was applied to the 20 patients, the average R ratio was equal to 1.003 ± 0.017 and 96% of the tests were within the acceptance criteria. The portal image γ-analysis supplied 88% of the tests within the pass rates γ{sub mean} ≤ 0.4 and P{sub γ<1} ≥ 98%. All the warnings were understood comparing the CT and the cone beam CT images and in one case a patient's setup error was detected and corrected for the successive fractions. Conclusions: This preliminary experience suggests that the method is able to detect dosimetric errors in quasi real time at the end of the therapy session. The authors intend to extend this procedure to other pathologies with the integration of in-room imaging verification by cone beam CT.

62 RADIOLOGY AND NUCLEAR MEDICINE↗