Citations

Objectives: The objectives of the study were to estimate the impact of high matrix image reconstruction on chest computed tomography (CT) compared to standard image reconstruction. Material and Methods: This retrospective study included patients with interstitial or parenchymal lung disease, airway disease, and pulmonary nodules who underwent chest CT. Chest CT images were reconstructed using high matrix (1024 × 1024) or standard matrix (512 × 512), with all other parameters matched. Two radiologists, blinded to reconstruction technique, independently examined each lung, viewing image sets side by side and rating the conspicuity of imaging findings using a 5-point relative conspicuity scale. The presence of pulmonary nodules and confidence in classification of internal attenuation was also graded. Overall image quality and subjective noise/artifacts were assessed. Results: Thirty-four patients with 68 lungs were evaluated. Relative conspicuity scores were significantly higher using high matrix image reconstruction for all imaging findings indicative of idiopathic lung fibrosis (peripheral airway visualization, interlobular septal thickening, intralobular reticular opacity, and end-stage fibrotic change; P ≤ 0.001) along with emphysema, mosaic attenuation, and fourth order bronchi for both readers (P ≤ 0.001). High matrix reconstruction did not improve confidence in the presence or classification of internal nodule attenuation for either reader. Overall image quality was increased but not subjective noise/artifacts with high matrix image reconstruction for both readers (P < 0.001). Conclusion: High matrix image reconstruction significantly improves the conspicuity of imaging findings reflecting interstitial lung disease and may be useful for diagnosis or treatment response assessment.

AbstractPurposeEye‐tracking approaches have been used to understand the visual search process in radiology. However, previous eye‐tracking work in computer tomography (CT) has been limited largely to single cross‐sectional images or video playback of the reconstructed volume, which do not accurately reflect radiologists' visual search activities and their interactivity with three‐dimensional image data at a computer workstation (e.g., scroll, pan, and zoom) for visual evaluation of diagnostic imaging targets. We have developed a platform that integrates eye‐tracking hardware with in‐house‐developed reader workstation software to allow monitoring of the visual search process and reader‐image interactions in clinically relevant reader tasks. The purpose of this work is to validate the spatial accuracy of eye‐tracking data using this platform for different eye‐tracking data acquisition modes.MethodsAn eye‐tracker was integrated with a previously developed workstation designed for reader performance studies. The integrated system captured real‐time eye movement and workstation events at 1000 Hz sampling frequency. The eye‐tracker was operated either in head‐stabilized mode or in free‐movement mode. In head‐stabilized mode, the reader positioned their head on a manufacturer‐provided chinrest. In free‐movement mode, a biofeedback tool emitted an audio cue when the head position was outside the data collection range (general biofeedback) or outside a narrower range of positions near the calibration position (strict biofeedback). Four radiologists and one resident were invited to participate in three studies to determine eye‐tracking spatial accuracy under three constraint conditions: head‐stabilized mode (i.e., with use of a chin rest), free movement with general biofeedback, and free movement with strict biofeedback. Study 1 evaluated the impact of head stabilization versus general or strict biofeedback using a cross‐hair target prior to the integration of the eye‐tracker with the image viewing workstation. In Study 2, after integration of the eye‐tracker and reader workstation, readers were asked to fixate on targets that were randomly distributed within a volumetric digital phantom. In Study 3, readers used the integrated system to scroll through volumetric patient CT angiographic images while fixating on the centerline of designated blood vessels (from the left coronary artery to dorsalis pedis artery). Spatial accuracy was quantified as the offset between the center of the intended target and the detected fixation using units of image pixels and the degree of visual angle.ResultsThe three head position constraint conditions yielded comparable accuracy in the studies using digital phantoms. For Study 1 involving the digital crosshairs, the median ± the standard deviation of offset values among readers were 15.2 ± 7.0 image pixels with the chinrest, 14.2 ± 3.6 image pixels with strict biofeedback, and 19.1 ± 6.5 image pixels with general biofeedback. For Study 2 using the random dot phantom, the median ± standard deviation offset values were 16.7 ± 28.8 pixels with use of a chinrest, 16.5 ± 24.6 pixels using strict biofeedback, and 18.0 ± 22.4 pixels using general biofeedback, which translated to a visual angle of about 0.8° for all three conditions. We found no obvious association between eye‐tracking accuracy and target size or view time. In Study 3 viewing patient images, use of the chinrest and strict biofeedback demonstrated comparable accuracy, while the use of general biofeedback demonstrated a slightly worse accuracy. The median ± standard deviation of offset values were 14.8 ± 11.4 pixels with use of a chinrest, 21.0 ± 16.2 pixels using strict biofeedback, and 29.7 ± 20.9 image pixels using general biofeedback. These corresponded to visual angles ranging from 0.7° to 1.3°.ConclusionsAn integrated eye‐tracker system to assess reader eye movement and interactive viewing in relation to imaging targets demonstrated reasonable spatial accuracy for assessment of visual fixation. The head‐free movement condition with audio biofeedback performed similarly to head‐stabilized mode.

Abstract We report a comprehensive evaluation of a full field-of-view (FOV) photon-counting detector (PCD) computed tomography (CT) system using phantoms, and qualitatively assess image quality in patient examples. A whole-body PCD-CT system with 50 cm FOV, 5.76 cm z-detector coverage and two acquisition modes (standard: 144 × 0.4 mm collimation and ultra-high resolution (UHR): 120 × 0.2 mm collimation) was used in this study. Phantoms were scanned to assess image uniformity, CT number accuracy, noise power spectrum, spatial resolution, material decomposition and virtual monoenergetic imaging (VMI) performance. Four patients were scanned on the PCD-CT system with matched or lower radiation dose than their prior clinical CT scans performed using energy-integrating detector (EID) CT, and the potential clinical impact of PCD-CT was qualitatively evaluated. Phantom results showed water CT numbers within ±5 HU, and image uniformity measured between peripheral and central regions-of-interests to be within ±5 HU. For the UHR mode using a dedicated sharp kernel, the cut-off spatial frequency was 40 line-pairs cm −1 , which corresponds to a 125 μ m limiting in-plane spatial resolution. The full-width-at-half-maximum for the section sensitivity profile was 0.33 mm for the smallest slice thickness (0.2 mm) using the UHR mode. Material decomposition in a multi-energy CT phantom showed accurate material classification, with a root-mean-squared-error of 0.3 mg cc −1 for iodine concentrations (2–15 mg cc −1 ) and 14.2 mg cc −1 for hydroxyapatite concentrations (200 and 400 mg cc −1 ). The average percent error for CT numbers corresponding to the iodine concentrations in VMI (40–70 keV) was 2.75%. Patient PCD-CT images demonstrated better delineation of anatomy for chest and temporal bone exams performed with the UHR mode, which allowed the use of very sharp kernels not possible with EID-CT. VMI and virtual non-contrast images generated from a patient head CT angiography exam using the standard acquisition mode demonstrated the multi-energy capability of the PCD-CT system.

PurposeChannelized Hotelling observer (CHO) models have been implemented to assess imaging performance in x‐ray angiography systems. While current methods are appropriate for assessing unprocessed images of moving test objects upon uniform‐exposure backgrounds, they are inadequate for assessing conditions which more appropriately mimic clinical imaging conditions including the combination of moving test objects, complex anthropomorphic backgrounds, and image processing. In support of this broad goal, the purpose of this work was to develop theory and methods to automatically select a subset of task‐specific efficient Gabor channels from a task‐generic Gabor channel base set. Also, previously described theory and methods to manage detectability index (d′) bias due to nonrandom temporal variations in image electronic noise will be revisited herein.MethodsStarting with a base set of 96 Gabor channels, backward elimination of channels was used to automatically identify an “efficient” channel subset which reduced the number of channels retained in the subset while maintaining the magnitude of the d′ estimate. The concept of a pixelwise Hotelling observer (PHO) model was introduced and similarly implemented to assess the performance of the efficient‐channel CHO model. Bias in d′ estimates arising from temporally variable nonstationary noise was modeled as a bivariate probability density function for normal distributions, where one variable corresponds to the signal from the test object and the other variable corresponds to the signal from temporally variable nonstationary noise. Theory and methods were tested on uniform‐exposure unprocessed angiography images with detector target dose (DTD) of 6, 18, and 120 nGy containing static disk‐shaped test objects with diameter in the range of 0.5 to 4 mm.ResultsConsidering all DTD levels and test object sizes, the proposed method reduced the number of Gabor channels in the final subset by 63–82% compared to the original 96 Gabor channel base set, while maintaining a mean relative performance () of 95% 4% with respect to the reference PHO model. Experimental results demonstrated that the bivariate approach to account for bias due to temporally variable nonstationary noise resulted in improved correlation between the CHO and PHO models as compared to a previously proposed univariate approach.ConclusionsComputationally efficient backward elimination can be used to select an efficient subset of Gabor channels from an initial channel base set without substantially compromising the magnitude of the d′ estimate. Bias due to temporally variable nonstationary noise can be modeled through a bivariate approach leading to an improved unbiased estimate of d′.

AbstractPurposeTo demonstrate that variation in chemical composition has a negligible effect on the mapping curve from relative electron density (RED) to proton stopping power ratio (SPR), and to establish the theoretical framework of using Megavoltage (MV) computed tomography (CT), instead of kilovoltage (kV) dual energy CT, to accurately estimate proton SPR.MethodsA simulation study was performed to evaluate the effect of chemical composition variation on kVCT number and proton SPR. The simulation study involved both reference and simulated human tissues. The reference human tissues, together with their physical densities and chemical compositions, came from the ICRP publication 23. The simulated human tissues were created from the reference human tissues assuming that elemental percentage weight followed a Gaussian distribution. For all tissues, kVCT number and proton SPR were obtained through (a) theoretical calculation from tissue’s physical density and chemical composition which served as the ground truth, and (b) estimation from RED using the calibration curves established from the stoichiometric method. Deviations of the estimated values from the calculated values were quantified as errors in using RED to estimate kVCT number and proton SPR.ResultsGiven a chemical composition variation of 5% (1σ) of the nominal percentage weights, the total estimation error of using RED to estimate kVCT number was 0.34%, 0.62%, and 0.77% and the total estimation error of using RED to estimate proton SPR was 0.30%, 0.22%, and 0.16% for fat tissues, non‐fat soft tissues and bone tissues, respectively.ConclusionChemical composition had a negligible effect on the method of using RED to determine proton SPR. RED itself is sufficient to accurately determine proton SPR. MVCT number maintains a superb linear relationship with RED because it is highly dominated by Compton scattering. Therefore, MVCT has great potential in reducing the proton range uncertainty.

Objective This study aims to determine if low iodine dynamic computed tomography angiography performed after a fixed delay or test bolus acquisition demonstrates high concordance with clinical computed tomography angiography (using a routine amount of iodinated contrast) to display lower extremity peripheral arterial disease. Methods After informed consent, low iodine dynamic computed tomography angiography examination (using either a fixed delay or test bolus) using 50 ml of iodine contrast media was performed. A subsequent clinical computed tomography angiography using standard iodine dose (115 or 145 ml) served as the reference standard. A vascular radiologist reviewed dynamic and clinical computed tomography angiography images to categorize the lumen into “not opacified”, “<50% stenosis”, “ 50 ̶70% stenosis”, “>70% stenosis”, and “occluded” for seven arterial segments in each lower extremity. Concordance between low iodine dynamic computed tomography angiography and the routine iodine reference standard was calculated. The clinical utility of 4D volume-rendered images was also evaluated. Results Sixty-eight patients (average age 66.1 ± 12.3 years, male; female = 49: 19) were enrolled, with 34 patients each undergoing low iodine dynamic computed tomography angiography using fixed delay and test bolus techniques, respectively. One patient assigned to the test bolus group did not undergo low iodine computed tomography angiography due to unavailable delayed time. The fixed delay was 13 s, with test bolus acquisition resulting in a mean variable delay prior to image acquisition of 19.5 s (range; 8–32 s). Run-off to the ankle was observed using low iodine dynamic computed tomography angiography following fixed delay and test bolus acquisition in 76.4% (26/34) and 100% (33/33) of patients, respectively ( p = 0.005). Considering extremities with run-off to the ankle and without severe artifact, the concordance rate between low iodine dynamic computed tomography angiography and the routine iodine reference standard was 86.8% (310/357) using fixed delay and 97.9% (425/434) using test bolus ( p < 0.001). 4D volume-rendered images using fixed delay and test bolus demonstrated asymmetric flow in 57.7% (15/26) and 58.1% (18/31) ( p = 0.978) of patients, and collateral blood flow in 11.5% (3/26) and 22.6% (7/31) of patients ( p = 0.319), respectively. Conclusion Low iodine dynamic computed tomography angiography with test bolus acquisition has a high concordance with routine peripheral computed tomography angiography performed with standard iodine dose, resulting in improved run-off to the ankle compared to dynamic computed tomography angiography performed after a fixed delay. This method is useful for minimizing iodine dose in patients at risk for contrast-induced nephropathy. 4D volume-rendered computed tomography angiography images provide useful dynamic information.

AbstractPurposeAn increasing number of implantable or external devices can impact whether patients can receive radiological imaging examinations. This study examines and tests the Neulasta (pegfilgrastim) Onpro on‐body injector in multiple imaging environments.MethodsThe injector was analyzed for four imaging modalities with testing protocols and strategies developed for each modality. In x‐ray and computed tomography (CT), scans with much higher exposure than clinical protocols were performed with the device attached to an anthropomorphic phantom. The device was monitored until the completion of drug delivery. For magnetic resonance imaging (MRI), the device was assessed using a hand‐held magnet and underwent the magnetically induced displacement testing in a 1.5T clinical MRI scanner room. For ultrasound, magnetic field changes were measured around an ultrasound scanner system with three transducers.ResultsFor x‐ray and CT no sign of device error was identified during or after the high radiation exposure scans. Drug delivery was completed at expected timing with expected volume. For MRI the device showed significant attractive force towards the hand‐held magnet and a 50‐degree deflection angle at 50 cm from the opening of the scanner bore. No further assessment from the gradient or radiofrequency field was deemed necessary. For ultrasound the maximum magnetic field change from baseline was measured to be +11.7 μT in comparison to +74.2 μT at 4 inches from a working microwave.ConclusionsNo device performance issue was identified under the extreme test conditions in x‐ray or CT. The device was found to be MR Unsafe. Magnetic field changes around an ultrasound system met the limitation set by manufacture. Patient ultrasound scanning is considered safe as long as the transducers do not inadvertently loosen the device.

PurposeTalbot‐Lau grating interferometry enables the use of polychromatic x‐ray sources, extending the range of potential applications amenable to phase contrast imaging. However, these sources introduce beam hardening effects not only from the samples but also from the gratings. As a result, grating inhomogeneities due to manufacturing imperfections can cause spectral nonuniformity artifacts when used with polychromatic sources. Consequently, the different energy dependencies of absorption, phase, and visibility contrasts impose challenges that so far have limited the achievable image quality. The purpose of this work was to develop and validate a correction strategy for grating‐based x‐ray imaging that accounts for beam hardening generated from both the imaged object and the gratings.MethodsThe proposed two‐variable polynomial expansion strategy was inspired by work performed to address beam hardening from a primary modulator. To account for the multicontrast nature of grating interferometry, this approach was extended to each contrast to obtain three sets of correction coefficients, which were determined empirically from a calibration scan. The method’s feasibility was demonstrated using a tabletop Talbot‐Lau grating interferometer micro‐computed tomography (CT) system using CT acquisitions of a water sample and a silicon sample, representing low and high atomic number materials. Spectral artifacts such as cupping and ring artifacts were quantified using mean squared error (MSE) from the beam‐hardening‐free target image and standard deviation within a reconstructed image of the sample. Finally, the model developed using the water sample was applied to a fixated murine lung sample to demonstrate robustness for similar materials.ResultsThe water sample’s absorption CT image was most impacted by spectral artifacts, but following correction to decrease ring artifacts, an 80% reduction in MSE and 57% reduction in standard deviation was observed. The silicon sample created severe artifacts in all contrasts, but following correction, MSE was reduced by 94% in absorption, 96% in phase, and 90% in visibility images. These improvements were due to the removal of ring artifacts for all contrasts and reduced cupping in absorption and phase images and reduced capping in visibility images. When the water calibration coefficients were applied to the lung sample, ring artifacts most prominent in the absorption contrast were eliminated.ConclusionsThe described method, which was developed to remove artifacts in absorption, phase, and normalized visibility micro‐CT images due to beam hardening in the system gratings and imaged object, reduced the MSE by up to 96%. The method depends on calibrations that can be performed on any system and does not require detailed knowledge of the x‐ray spectrum, detector energy response, grating attenuation properties and imperfections, or the geometry and composition of the imaged object.