Browsing by Subject "Radiographic Image Interpretation, Computer-Assisted"
Now showing 1 - 11 of 11
- Results Per Page
- Sort Options
Item Open Access A neural network-based method for spectral distortion correction in photon counting x-ray CT.(Physics in medicine and biology, 2016-08) Touch, Mengheng; Clark, Darin P; Barber, William; Badea, Cristian TSpectral CT using a photon counting x-ray detector (PCXD) shows great potential for measuring material composition based on energy dependent x-ray attenuation. Spectral CT is especially suited for imaging with K-edge contrast agents to address the otherwise limited contrast in soft tissues. We have developed a micro-CT system based on a PCXD. This system enables both 4 energy bins acquisition, as well as full-spectrum mode in which the energy thresholds of the PCXD are swept to sample the full energy spectrum for each detector element and projection angle. Measurements provided by the PCXD, however, are distorted due to undesirable physical effects in the detector and can be very noisy due to photon starvation in narrow energy bins. To address spectral distortions, we propose and demonstrate a novel artificial neural network (ANN)-based spectral distortion correction mechanism, which learns to undo the distortion in spectral CT, resulting in improved material decomposition accuracy. To address noise, post-reconstruction denoising based on bilateral filtration, which jointly enforces intensity gradient sparsity between spectral samples, is used to further improve the robustness of ANN training and material decomposition accuracy. Our ANN-based distortion correction method is calibrated using 3D-printed phantoms and a model of our spectral CT system. To enable realistic simulations and validation of our method, we first modeled the spectral distortions using experimental data acquired from (109)Cd and (133)Ba radioactive sources measured with our PCXD. Next, we trained an ANN to learn the relationship between the distorted spectral CT projections and the ideal, distortion-free projections in a calibration step. This required knowledge of the ground truth, distortion-free spectral CT projections, which were obtained by simulating a spectral CT scan of the digital version of a 3D-printed phantom. Once the training was completed, the trained ANN was used to perform distortion correction on any subsequent scans of the same system with the same parameters. We used joint bilateral filtration to perform noise reduction by jointly enforcing intensity gradient sparsity between the reconstructed images for each energy bin. Following reconstruction and denoising, the CT data was spectrally decomposed using the photoelectric effect, Compton scattering, and a K-edge material (i.e. iodine). The ANN-based distortion correction approach was tested using both simulations and experimental data acquired in phantoms and a mouse with our PCXD-based micro-CT system for 4 bins and full-spectrum acquisition modes. The iodine detectability and decomposition accuracy were assessed using the contrast-to-noise ratio and relative error in iodine concentration estimation metrics in images with and without distortion correction. In simulation, the material decomposition accuracy in the reconstructed data was vastly improved following distortion correction and denoising, with 50% and 20% reductions in material concentration measurement error in full-spectrum and 4 energy bins cases, respectively. Overall, experimental data confirms that full-spectrum mode provides superior results to 4-energy mode when the distortion corrections are applied. The material decomposition accuracy in the reconstructed data was vastly improved following distortion correction and denoising, with as much as a 41% reduction in material concentration measurement error for full-spectrum mode, while also bringing the iodine detectability to 4-6 mg ml(-1). Distortion correction also improved the 4 bins mode data, but to a lesser extent. The results demonstrate the experimental feasibility and potential advantages of ANN-based distortion correction and joint bilateral filtration-based denoising for accurate K-edge imaging with a PCXD. Given the computational efficiency with which the ANN can be applied to projection data, the proposed scheme can be readily integrated into existing CT reconstruction pipelines.Item Open Access An automated method for comparing motion artifacts in cine four-dimensional computed tomography images.(Journal of applied clinical medical physics, 2012-11-08) Cui, Guoqiang; Jew, Brian; Hong, Julian C; Johnston, Eric W; Loo, Billy W; Maxim, Peter GThe aim of this study is to develop an automated method to objectively compare motion artifacts in two four-dimensional computed tomography (4D CT) image sets, and identify the one that would appear to human observers with fewer or smaller artifacts. Our proposed method is based on the difference of the normalized correlation coefficients between edge slices at couch transitions, which we hypothesize may be a suitable metric to identify motion artifacts. We evaluated our method using ten pairs of 4D CT image sets that showed subtle differences in artifacts between images in a pair, which were identifiable by human observers. One set of 4D CT images was sorted using breathing traces in which our clinically implemented 4D CT sorting software miscalculated the respiratory phase, which expectedly led to artifacts in the images. The other set of images consisted of the same images; however, these were sorted using the same breathing traces but with corrected phases. Next we calculated the normalized correlation coefficients between edge slices at all couch transitions for all respiratory phases in both image sets to evaluate for motion artifacts. For nine image set pairs, our method identified the 4D CT sets sorted using the breathing traces with the corrected respiratory phase to result in images with fewer or smaller artifacts, whereas for one image pair, no difference was noted. Two observers independently assessed the accuracy of our method. Both observers identified 9 image sets that were sorted using the breathing traces with corrected respiratory phase as having fewer or smaller artifacts. In summary, using the 4D CT data of ten pairs of 4D CT image sets, we have demonstrated proof of principle that our method is able to replicate the results of two human observers in identifying the image set with fewer or smaller artifacts.Item Open Access Clinical assessment and characterization of a dual tube kilovoltage X-ray localization system in the radiotherapy treatment room.(Journal of applied clinical medical physics, 2008-01-13) Lee, Sung-Woo; Jin, Jian-Yue; Guan, Huaiqun; Martin, Flavious; Kim, Jae Ho; Yin, Fang-FangINTRODUCTION:Although flat-panel based X-ray imaging has been well tested in diagnostic radiology, its use as an image-guided-radiotherapy (IGRT) system in a treatment room is new and requires systematic assessment. MATERIALS AND METHODS:BrainLab Novalis IGRT system was used for this study. It consists of two floor mounted kV X-ray tubes projecting obliquely into two flat-panel detectors mounted on the ceiling. The system automatically fuses the 2D localization images with 3D simulation CT image to provide positioning guidance. The following characteristics of the system were studied: (1) Coincidence of the isocenters between the IGRT and Linac; (2) Image quality; (3) Exposure; (4) Linearity, uniformity and repeatability. RESULTS:(1) Localization accuracy and coincidence of the isocenters between the IGRT and Linac was better than 1-mm. (2) The spatial resolution was quantified using the relative modulation-transfer-function with f50=0.7-0.9 lp/mm. The variation of contrast-noise-ratio with technical settings was measured. (3) The maximal exposure of an image was less than 95 mR. An empirical relation between the exposure and the X-ray technical setting was derived. (4) The linearity, uniformity and repeatability of the system generally meet the requirements. CONCLUSION:The system can be safely and reliably used as a target localization device.Item Open Access Dual-energy computed tomography with advanced postimage acquisition data processing: improved determination of urinary stone composition.(J Endourol, 2010-03) Ferrandino, MN; Pierre, SA; Simmons, WN; Paulson, EK; Albala, DM; Preminger, GMINTRODUCTION: The characterization of urinary calculi using noninvasive methods has the potential to affect clinical management. CT remains the gold standard for diagnosis of urinary calculi, but has not reliably differentiated varying stone compositions. Dual-energy CT (DECT) has emerged as a technology to improve CT characterization of anatomic structures. This study aims to assess the ability of DECT to accurately discriminate between different types of urinary calculi in an in vitro model using novel postimage acquisition data processing techniques. METHODS: Fifty urinary calculi were assessed, of which 44 had >or=60% composition of one component. DECT was performed utilizing 64-slice multidetector CT. The attenuation profiles of the lower-energy (DECT-Low) and higher-energy (DECT-High) datasets were used to investigate whether differences could be seen between different stone compositions. RESULTS: Postimage acquisition processing allowed for identification of the main different chemical compositions of urinary calculi: brushite, calcium oxalate-calcium phosphate, struvite, cystine, and uric acid. Statistical analysis demonstrated that this processing identified all stone compositions without obvious graphical overlap. CONCLUSION: Dual-energy multidetector CT with postprocessing techniques allows for accurate discrimination among the main different subtypes of urinary calculi in an in vitro model. The ability to better detect stone composition may have implications in determining the optimum clinical treatment modality for urinary calculi from noninvasive, preprocedure radiological assessment.Item Open Access Evaluation of integrated respiratory gating systems on a Novalis Tx system.(Journal of applied clinical medical physics, 2011-04-04) Chang, Zheng; Liu, Tonghai; Cai, Jing; Chen, Qing; Wang, Zhiheng; Yin, Fang-FangThe purpose of this study was to investigate the accuracy of motion tracking and radiation delivery control of integrated gating systems on a Novalis Tx system. The study was performed on a Novalis Tx system, which is equipped with Varian Real-time Position Management (RPM) system, and BrainLAB ExacTrac gating systems. In this study, the two systems were assessed on accuracy of both motion tracking and radiation delivery control. To evaluate motion tracking, two artificial motion profiles and five patients' respiratory profiles were used. The motion trajectories acquired by the two gating systems were compared against the references. To assess radiation delivery control, time delays were measured using a single-exposure method. More specifically, radiation is delivered with a 4 mm diameter cone within the phase range of 10%-45% for the BrainLAB ExacTrac system, and within the phase range of 0%-25% for the Varian RPM system during expiration, each for three times. Radiochromic films were used to record the radiation exposures and to calculate the time delays. In the work, the discrepancies were quantified using the parameters of mean and standard deviation (SD). Pearson's product-moment correlational analysis was used to test correlation of the data, which is quantified using a parameter of r. The trajectory profiles acquired by the gating systems show good agreement with those reference profiles. A quantitative analysis shows that the average mean discrepancies between BrainLAB ExacTrac system and known references are 1.5 mm and 1.9 mm for artificial and patient profiles, with the maximum motion amplitude of 28.0 mm. As for the Varian RPM system, the corresponding average mean discrepancies are 1.1 mm and 1.7 mm for artificial and patient profiles. With the proposed single-exposure method, the time delays are found to be 0.20 ± 0.03 seconds and 0.09 ± 0.01 seconds for BrainLAB ExacTrac and Varian RPM systems, respectively. The results indicate the systems can track motion and control radiation delivery with reasonable accuracy. The proposed single-exposure method has been demonstrated to be feasible in measuring time delay efficiently.Item Open Access Hybrid spectral CT reconstruction.(PLoS One, 2017) Clark, Darin P; Badea, Cristian TCurrent photon counting x-ray detector (PCD) technology faces limitations associated with spectral fidelity and photon starvation. One strategy for addressing these limitations is to supplement PCD data with high-resolution, low-noise data acquired with an energy-integrating detector (EID). In this work, we propose an iterative, hybrid reconstruction technique which combines the spectral properties of PCD data with the resolution and signal-to-noise characteristics of EID data. Our hybrid reconstruction technique is based on an algebraic model of data fidelity which substitutes the EID data into the data fidelity term associated with the PCD reconstruction, resulting in a joint reconstruction problem. Within the split Bregman framework, these data fidelity constraints are minimized subject to additional constraints on spectral rank and on joint intensity-gradient sparsity measured between the reconstructions of the EID and PCD data. Following a derivation of the proposed technique, we apply it to the reconstruction of a digital phantom which contains realistic concentrations of iodine, barium, and calcium encountered in small-animal micro-CT. The results of this experiment suggest reliable separation and detection of iodine at concentrations ≥ 5 mg/ml and barium at concentrations ≥ 10 mg/ml in 2-mm features for EID and PCD data reconstructed with inherent spatial resolutions of 176 μm and 254 μm, respectively (point spread function, FWHM). Furthermore, hybrid reconstruction is demonstrated to enhance spatial resolution within material decomposition results and to improve low-contrast detectability by as much as 2.6 times relative to reconstruction with PCD data only. The parameters of the simulation experiment are based on an in vivo micro-CT experiment conducted in a mouse model of soft-tissue sarcoma. Material decomposition results produced from this in vivo data demonstrate the feasibility of distinguishing two K-edge contrast agents with a spectral separation on the order of the energy resolution of the PCD hardware.Item Open Access Impact of beta-blockade premedication on image quality of ECG-gated thoracic aorta CT angiography.(Acta radiologica (Stockholm, Sweden : 1987), 2014-12) Entezari, Pegah; Collins, Jeremy; Chalian, Hamid; Tore, Huseyin Gurkan; Carr, James; Yaghmai, VahidBACKGROUND: Thoracic aortic aneurysm is one of the most common aorta pathologies worldwide, which is commonly evaluated by computed tomography angiography (CTA). One of the routine methods to improve the image quality of CTA is heart rate reduction prior to study by beta-blockade administration. PURPOSE: To assess the effect of beta-blockade on image quality of the ascending aorta in electrocardiography (ECG)-gated dual-source CTA (DSCTA) images. MATERIAL AND METHODS: In this retrospective study, ECG-gated thoracic aorta CTA images of 40 patients without beta-blocker administration were compared with ECG-gated images of 40 patients with beta-blockade. Images of the aorta were analyzed objectively and subjectively at three levels: sinus of Valsalva (sinus), sinotubular junction (STJ), and mid ascending aorta (MAA). Quantitative sharpness index (SI) and signal-to-noise ratio (SNR) were calculated and two radiologists evaluated the image quality using a 3-point scale. RESULTS: Mean heart rate in beta-blocker and non-beta-blocker groups was 61.7 beats per minute (bpm) (range, 58.1-63.9 bpm) and 72.9 bpm (range, 69.3-84.1 bpm), respectively (P < 0.05). Aorta wall SI, SNR, and subjective grading were comparable between the two groups at all three levels (P > 0.05). CONCLUSION: Beta-blocker premedication may not be necessary for imaging of ascending aorta with ECG-gated DSCTA.Item Open Access Impact of magnitude and percentage of global sagittal plane correction on health-related quality of life at 2-years follow-up.(Neurosurgery, 2012-08) Blondel, Benjamin; Schwab, Frank; Ungar, Benjamin; Smith, Justin; Bridwell, Keith; Glassman, Steven; Shaffrey, Christopher; Farcy, Jean-Pierre; Lafage, VirginieBackground
Sagittal plane malalignment has been established as the main radiographic driver of disability in adult spinal deformity (ASD).Objective
To evaluate the amount of sagittal correction needed for a patient to perceive improvement (minimal clinically important difference, MCID) in health-related quality of life (HRQOL) scores.Methods
This was a multicenter, retrospective analysis of prospectively consecutively enrolled ASD patients. Inclusion criterion was a sagittal vertical axis (SVA) >80 mm. Demographic, radiographic, and HRQOL preoperative and 2-year postsurgery data were collected. Surgical treatment was categorized based on SVA correction: <60 mm, 60 mm to 120 mm, and >120 mm. Changes in parameters were analyzed using paired t test, 1-way analysis of variance, and χ2 test.Results
Seventy-six patients (preoperative SVA = 140 mm) were analyzed; each subgroup revealed significant HRQOL improvements following surgery. Compared with the <60 mm correction group, the likelihood of reaching MCID was significantly improved for the >120 mm group (Oswestry Disability Index) but not for the 60 mm to 120 mm group. A significantly greater likelihood of reaching MCID thresholds was observed for corrections above 66% of preoperative SVA.Conclusion
Best HRQOL outcomes for ASD patients with severe sagittal plane deformity were obtained with a correction >120 mm for SVA and at least 66% of correction. Although lesser amounts of SVA correction yielded clinical improvement, the rate of MCID threshold improvement was not significantly different for mild or modest corrections. These results underline the need for complete sagittal plane deformity correction if high rates of HRQOL benefit are sought for patients with marked sagittal plane deformity.Item Open Access Investigation of sliced body volume (SBV) as respiratory surrogate.(Journal of applied clinical medical physics, 2013-01-07) Cai, Jing; Chang, Zheng; O'Daniel, Jennifer; Yoo, Sua; Ge, Hong; Kelsey, Christopher; Yin, Fang-FangThe purpose of this study was to evaluate the sliced body volume (SBV) as a respiratory surrogate by comparing with the real-time position management (RPM) in phantom and patient cases. Using the SBV surrogate, breathing signals were extracted from unsorted 4D CT images of a motion phantom and 31 cancer patients (17 lung cancers, 14 abdominal cancers) and were compared to those clinically acquired using the RPM system. Correlation coefficient (R), phase difference (D), and absolute phase difference (D(A)) between the SBV-derived breathing signal and the RPM signal were calculated. 4D CT reconstructed based on the SBV surrogate (4D CT(SBV)) were compared to those clinically generated based on RPM (4D CT(RPM)). Image quality of the 4D CT were scored (S(SBV) and S(RPM), respectively) from 1 to 5 (1 is the best) by experienced evaluators. The comparisons were performed for all patients, and for the lung cancer patients and the abdominal cancer patients separately. RPM box position (P), breathing period (T), amplitude (A), period variability (V(T)), amplitude variability (V(A)), and space-dependent phase shift (F) were determined and correlated to S(SBV). The phantom study showed excellent match between the SBV-derived breathing signal and the RPM signal (R = 0.99, D= -3.0%, D(A) = 4.5%). In the patient study, the mean (± standard deviation (SD)) R, D, D(A), T, V(T), A, V(A), and F were 0.92 (± 0.05), -3.3% (± 7.5%), 11.4% (± 4.6%), 3.6 (± 0.8) s, 0.19 (± 0.10), 6.6 (± 2.8) mm, 0.20 (± 0.08), and 0.40 (± 0.18) s, respectively. Significant differences in R and D(A) (p = 0.04 and 0.001, respectively) were found between the lung cancer patients and the abdominal cancer patients. 4D CT(RPM) slightly outperformed 4D CT(SBV): the mean (± SD) S(RPM) and S(SBV) were 2.6 (± 0.6) and 2.9 (± 0.8), respectively, for all patients, 2.5 (± 0.6) and 3.1 (± 0.8), respectively, for the lung cancer patients, and 2.6 (± 0.7) and 2.8 (± 0.9), respectively, for the abdominal cancer patients. The difference between S(RPM) and S(SBV) was insignificant for the abdominal patients (p = 0.59). F correlated moderately with S(SBV) (r = 0.72). The correlation between SBV-derived breathing signal and RPM signal varied between patients and was significantly better in the abdomen than in the thorax. Space-dependent phase shift is a limiting factor of the accuracy of the SBV surrogate.Item Open Access Optimization of reduced-dose MDCT of thoracic aorta using iterative reconstruction.(Journal of computer assisted tomography, 2014-01) Töre, Hüseyin Gürkan; Entezari, Pegah; Chalian, Hamid; Gonzalez-Guindalini, Fernanda Dias; Botelho, Marcos Paulo Ferreira; Yaghmai, VahidOBJECTIVE: To evaluate the contribution of iterative reconstruction on image quality of reduced-dose multidetector computed tomography of the thoracic aorta. METHODS: A torso phantom was scanned using two tube potentials (80 and 120 kVp) and five different tube currents (110, 75, 40, 20, and 10 mAs). All images were reconstructed with both filtered back projection (FBP) and iterative reconstruction. Aortic attenuation, image noise within the thoracic aorta, signal-to-noise ratio, and sharpness of the aortic wall were quantified in the phantom for the two reconstruction algorithms. Data were analyzed using paired t test. A value of P < 0.05 was considered significant. RESULTS: The aortic attenuation was similar for FBP and iterative reconstruction (P > 0.05). Image noise level was lower (P < 0.0001), and image sharpness was higher (P = 0.046) with iterative reconstruction. Signal-to-noise ratios were higher with iterative reconstruction compared with those with FBP (P < 0.0001). Signal-to-noise ratio at 80 kVp with iterative reconstruction (9.8 ± 4.4) was similar to the signal-to-noise ratio at 120 kVp with FBP (8.4 ± 3.3) (P = 0.196). CONCLUSIONS: Less image noise and higher image sharpness may be achieved with iterative reconstruction in reduced-dose multidetector computed tomography of the thoracic aorta.Item Open Access Spectrotemporal CT data acquisition and reconstruction at low dose.(Med Phys, 2015-11) Clark, Darin P; Lee, Chang-Lung; Kirsch, David G; Badea, Cristian TPURPOSE: X-ray computed tomography (CT) is widely used, both clinically and preclinically, for fast, high-resolution anatomic imaging; however, compelling opportunities exist to expand its use in functional imaging applications. For instance, spectral information combined with nanoparticle contrast agents enables quantification of tissue perfusion levels, while temporal information details cardiac and respiratory dynamics. The authors propose and demonstrate a projection acquisition and reconstruction strategy for 5D CT (3D+dual energy+time) which recovers spectral and temporal information without substantially increasing radiation dose or sampling time relative to anatomic imaging protocols. METHODS: The authors approach the 5D reconstruction problem within the framework of low-rank and sparse matrix decomposition. Unlike previous work on rank-sparsity constrained CT reconstruction, the authors establish an explicit rank-sparse signal model to describe the spectral and temporal dimensions. The spectral dimension is represented as a well-sampled time and energy averaged image plus regularly undersampled principal components describing the spectral contrast. The temporal dimension is represented as the same time and energy averaged reconstruction plus contiguous, spatially sparse, and irregularly sampled temporal contrast images. Using a nonlinear, image domain filtration approach, the authors refer to as rank-sparse kernel regression, the authors transfer image structure from the well-sampled time and energy averaged reconstruction to the spectral and temporal contrast images. This regularization strategy strictly constrains the reconstruction problem while approximately separating the temporal and spectral dimensions. Separability results in a highly compressed representation for the 5D data in which projections are shared between the temporal and spectral reconstruction subproblems, enabling substantial undersampling. The authors solved the 5D reconstruction problem using the split Bregman method and GPU-based implementations of backprojection, reprojection, and kernel regression. Using a preclinical mouse model, the authors apply the proposed algorithm to study myocardial injury following radiation treatment of breast cancer. RESULTS: Quantitative 5D simulations are performed using the MOBY mouse phantom. Twenty data sets (ten cardiac phases, two energies) are reconstructed with 88 μm, isotropic voxels from 450 total projections acquired over a single 360° rotation. In vivo 5D myocardial injury data sets acquired in two mice injected with gold and iodine nanoparticles are also reconstructed with 20 data sets per mouse using the same acquisition parameters (dose: ∼60 mGy). For both the simulations and the in vivo data, the reconstruction quality is sufficient to perform material decomposition into gold and iodine maps to localize the extent of myocardial injury (gold accumulation) and to measure cardiac functional metrics (vascular iodine). Their 5D CT imaging protocol represents a 95% reduction in radiation dose per cardiac phase and energy and a 40-fold decrease in projection sampling time relative to their standard imaging protocol. CONCLUSIONS: Their 5D CT data acquisition and reconstruction protocol efficiently exploits the rank-sparse nature of spectral and temporal CT data to provide high-fidelity reconstruction results without increased radiation dose or sampling time.