Patient specific dose evaluation and reporting is becoming increasingly important for x-ray imaging systems. Even imaging systems with lower patient dose such as CBCT scanners for extremities can benefit from accurate and size-specific dose assessment and reporting. This paper presents CTDI dose measurements performed on a prototype CBCT extremity imaging system across a range of body part sizes (5, 10, 16, and 20 cm effective diameter) and kVp (70, 80, and 90 kVp - with 0.1 mm Cu added filtration). The ratio of the CTDI measurements for the 5, 10, and 20 cm phantoms to the CTDI measurements for the 16 cm phantom were calculated and results were compared to size-specific dose estimates conversion factors (AAPM Report 204), which were evaluated on a conventional CT scanner. Due to the short scan nature of the system (220 degree acquisition angle), the dependence of CTDI values on the initial angular orientation of the phantom with respect to the imager was also evaluated. The study demonstrated that for a 220 degree acquisition sequence, the initial angular position of the conventional CTDI phantom with respect to the scanner does not significantly affect CTDI measurements (varying by less than 2% overall across the range of possible initial angular positions). The size-specific conversion factor was found to be comparable to the Report 204 factors for the large phantom size (20 cm) but lower, by up to 12%, for the 5 cm phantom (i.e., 1.35 for CBCT vs 1.54 for CT). The factors dependence on kVp was minimal, but dependence on kVp was most significant for smaller diameters. These results indicate that specific conversion factors need to be used for CBCT systems with short scans in order to provide more accurate dose reporting across the range of body sizes found in extremity scanners.
In Cone Beam CT Imaging, metallic and other dense objects, such as implantable orthopedic appliances, surgical clips
and staples, and dental fillings, are often acquired as part of the image dataset. These high-density, high atomic mass
objects attenuate X-rays in the diagnostic energy range much more strongly than soft tissue or bony structures, resulting
in photon starvation at the detector. In addition, signal behind the metal objects suffer from increased quantum noise,
scattered radiation, and beam hardening. All of these effects combine to create nonlinearities which are further amplified
by the reconstruction algorithm, such as conventional filtered back-projection (FBP), producing strong artifacts in the
form of streaking. They reduce image quality by masking soft tissue structures, not only in the immediate vicinity of the
dense object, but also throughout the entire image volume. A novel, physical-model-based, metal-artifact reduction
scheme (MAR) is proposed to mitigate the metal-induced artifacts. The metal objects are segmented in the projection
domain, and a physical model based method is adopted to fill in the segmented area. The FDK1 reconstruction algorithm
is then used for the final reconstruction.
The quantification of lung nodule volume based on CT images provides valuable information for disease
diagnosis and staging. However, the precision of the quantification is protocol, system, and technique
dependent and needs to be evaluated for each specific case. To efficiently investigate the quantitative
precision and find an optimal operating point, it is important to develop a predictive model based on basic
system parameters. In this study, a Fourier-based metric, the estimability index (e') was proposed as such a
predictor, and validated across a variety of imaging conditions. To first obtain the ground truth of quantitative
precision, an anthropomorphic chest phantom with synthetic spherical nodules were imaged on a 64 slice CT
scanner across a range of protocols (five exposure levels and two reconstruction algorithms). The volumes of
nodules were quantified from the images using clinical software, with the precision of the quantification
calculated for each protocol. To predict the precision, e' was calculated for each protocol based on several
Fourier-based figures of merit, which modeled the characteristic of the quantitation task and the imaging
condition (resolution, noise, etc.) of a particular protocol. Results showed a strong correlation (R2=0.92)
between the measured and predicted precision across all protocols, indicating e' as an effective predictor of
the quantitative precision. This study provides a useful framework for quantification-oriented optimization of
CT protocols.
The increasing availability of iterative reconstruction (IR) algorithms on clinical scanners is creating a
demand for effectively and efficiently evaluating imaging performance and potential dose reduction. In this
study, the location- and task-specific evaluation was performed using detectability index (d') by combining a
task function, the task transfer function (TTF), and the noise power spectrum (NPS). Task function modeled a
wide variety detection tasks in terms of shape and contrast. The TTF and NPS were measured from a physical
phantom as a function of contrast and dose levels. Measured d' values were compared between three IRs
(IRIS, SAFIRE3 and SAFIRE5) and conventional filtered back-projection (FBP) at various dose levels,
showing an equivalent performance of IR at lower dose levels. AUC further calculated from d' showed that
compared to FBP, SAFIRE5 may reduce dose by up to 50-60%; SAFIRE3 and IRIS by up to 20-30%. This
study provides an initial framework for the localized and task-specific evaluation of IRs in CT and a guideline
for the identification of optimal operating dose point with iterative reconstructions.
The relationship between theoretical descriptions of imaging performance (Fourier-based) and the
performance of real human observers was investigated for detection tasks in multi-slice CT. The detectability
index for the Fisher-Hotelling model observer and non-prewhitening model observer (with and without
internal noise and eye filter) was computed using: 1) the measured modulation transfer function (MTF) and
noise-power spectrum (NPS) for CT; and 2) a Fourier description of imaging task. Based upon CT images of
human patients with added simulated lesions, human observer performance was assessed via an observer
study in terms of the area under the ROC curve (Az). The degree to which the detectability index correlated
with human observer performance was investigated and results for the non-prewhitening model observer with
internal noise and eye filter (NPWE) were found to agree best with human performance over a broad range of
imaging conditions. Results provided initial validation that CT image acquisition and reconstruction
parameters can be optimized for observer performance rather than system performance (i.e., contrast-to-noise
ratio, MTF, and NPS). The NPWE model was further applied for the comparison of FBP with a novel modelbased
iterative reconstruction algorithm to assess its potential for dose reduction.
KEYWORDS: Modulation transfer functions, Breast, Optical spheres, Imaging systems, 3D modeling, Systems modeling, 3D metrology, 3D image processing, Stereoscopy, 3D acquisition
This study aimed to investigate a method for empirically evaluating 3D imaging task performance of breast
tomosynthesis imaging systems. A simulation and experimental approach was used to develop a robust
method for performance assessment. To identify a method for experimentally assessing the 3D modulation
transfer function (MTF), a breast tomosysnthesis system was first simulated using cascaded system analysis
to model the signal and noise characteristics of the projections. A range of spheres with varying contrast and
size were reconstructed using filtered back projection from which the 3D MTF was evaluated. Results
revealed that smaller spheres result in lower artifacts in the measured MTF, where a sphere of 0.5 mm was
found ideal for experimental purposes. A clinical tomosynthesis unit was used as a platform for quantifying
the effect of acquisition and processing parameters (e.g., angular extent and sampling, dose, and voxel size)
on breast imaging performance. The 3D noise-power spectrum (NPS) was measured using a uniform phantom
and 3D MTF was measured using 0.5 mm ruby spheres. These metrics were combined with a mathematical
description of imaging task to generate a figure of merit called the detectability index for system evaluation
and optimization. Clinically relevant imaging tasks were considered, such as the detection and localization of
a spherical mass. The detectability index was found to provide a useful metric that accounts for the complex
3D imaging characteristics of breast tomosynthesis. Results highlighted the dependence of optimal technique
on the imaging task. They further provided initial validation of an empirically assessed figure of merit for
clinical performance assessment and optimization of breast tomosynthesis systems.
KEYWORDS: Modulation transfer functions, Imaging systems, Breast, Performance modeling, 3D modeling, Systems modeling, Statistical analysis, 3D acquisition, Medical imaging, Optical spheres
This study aimed to extend Fourier-based imaging metrics for the modeling of quantitative imaging performance. Breast
tomosynthesis was used as a platform for investigating acquisition and processing parameters (e.g., acquisition angle and
dose) that can significantly affect 3D signal and noise, and consequently quantitative imaging performance. The
detectability index was computed using the modulation transfer function and noise-power spectrum combined with a
Fourier description of imaging task. Three imaging tasks were considered: detection, area estimation (in coronal slice),
and volume estimation of a 4 mm diameter spherical target. Task functions for size estimation were generated by using
measured performance of the maximum-likelihood estimator as training data. The detectability index computed with the
size estimation tasks correlated well with precision measurements for area and volume estimation over a fairly broad
range of imaging conditions and provided a meaningful figure of merit for quantitative imaging performance.
Furthermore, results highlighted that optimal breast tomosynthesis acquisition parameters depend significantly on
imaging task. Mass detection was optimal at an acquisition angle of 85° while area and volume estimation for the same
mass were optimal at ~100° and 125° acquisition angles, respectively. These findings provide key initial validation that
the Fourier-based detectability index extended to estimation tasks can represent a meaningful metric and predictor of
quantitative imaging performance.
Current lung nodule size assessment methods typically rely on one-dimensional estimation of lesions. While
new 3D volume assessment techniques using MSCT scan data have enabled improved estimation of lesion
size, the effect of acquisition and reconstruction parameters on accuracy and precision of such estimation has
not been adequately investigated. To characterize such dependencies, we scanned an anthropomorphic
thoracic phantom containing synthetic nodules with different protocols, including various acquisition and
reconstruction parameters. We also scanned the phantom repeatedly with the same protocol to investigate
repeatability. The nodule's volume was estimated by a clinical lung analysis software package, LungVCAR.
Accuracy (bias) and precision (variance) of the volume assessment were calculated across the nodules and
compared between protocols via Generalized Estimating Equation analysis. Results suggest a strong
dependence of accuracy and precision on dose level but little dependence on reconstruction thickness, thus
providing possible guidelines for protocol optimization for quantitative tasks.
KEYWORDS: Breast, Monte Carlo methods, Digital breast tomosynthesis, Tissues, Computed tomography, Expectation maximization algorithms, Calibration, Mammography, Sensors, Chest
Conventional mammography is largely limited by superimposed anatomy which is alleviated by breast tomosynthesis and CT. Limited acquisition in tomosynthesis can result in significant out of plane artifacts while large angular acquisition span in CT can limit the imaging coverage of the chest wall near the breast. We propose a new breast imaging modality, wide-angle breast tomosynthesis (WBT), aimed to provide a practical compromise between 3D
sampling and chest-wall coverage. This study compares lesion detection between conventional digital breast tomosynthesis, WBT, and breast CT (44°, 99°, and 198° total angle range, respectively) under equal patient dose conditions. A Monte Carlo (MC) code based on the Penelope package modeled a virtual flat-panel breast tomosynthesis system. The modalities were simulated at four breast compression levels. Glandular dose to the breast was estimated and
the radiation flux was subsequently adjusted to achieve a constant mean glandular dose level of 1.5 mGy, independent of the breast thickness and acquisition geometry. Reconstructed volumes were generated using iterative reconstruction methods. Lesion detectability was estimated using contrast-to-noise-ratio. Results showed improved detection with increased angular span and compression. Evaluations also showed improved performance of WBT over DBT at lower compression levels, therefore highlighting potential for reduced breast compression when using a larger acquisition angle.
The relationship between theoretical descriptions of imaging performance (Fourier-based cascaded systems analysis)
and the performance of real human observers was investigated for various detection and discrimination
tasks. Dual-energy (DE) imaging provided a useful basis for investigating this relationship, because it presents a
host of acquisition and processing parameters that can significantly affect signal and noise transfer characteristics
and, correspondingly, human observer performance. The detectability index was computed theoretically using:
1) cascaded systems analysis of the modulation transfer function (MTF), and noise-power spectrum (NPS) for
DE imaging; 2) a Fourier description of imaging task; and 3.) integration of MTF, NPS, and task function
according to various observer models, including Fisher-Hotelling and non-prewhitening with and without an eye
filter and internal noise. Three idealized tasks were considered: sphere detection, shape discrimination (sphere
vs. disk), and texture discrimination (uniform vs. textured disk). Using images of phantoms acquired on a
prototype DE imaging system, human observer performance was assessed in multiple-alternative forced choice
(MAFC) tests, giving an estimate of area under the ROC curve (AΖ). The degree to which the theoretical
detectability index correlated with human observer performance was investigated, and results agreed well over
a broad range of imaging conditions, depending on the choice of observer model. Results demonstrated that
optimal DE image acquisition and decomposition parameters depend significantly on the imaging task. These
studies provide important initial validation that the detectability index derived theoretically by Fourier-based
cascaded systems analysis correlates well with actual human observer performance and represents a meaningful
metric for system optimization.
Mounting evidence suggests that the superposition of anatomical clutter in a projection radiograph poses a major
impediment to the detectability of subtle lung nodules. Through decomposition of projections acquired at multiple kVp,
dual-energy (DE) imaging offers to dramatically improve lung nodule detectability and, in part through quantitation of
nodule calcification, increase specificity in nodule characterization. The development of a high-performance DE chest
imaging system is reported, with design and implementation guided by fundamental imaging performance metrics. A
diagnostic chest stand (Kodak RVG 5100 digital radiography system) provided the basic platform, modified to include:
(i) a filter wheel, (ii) a flat-panel detector (Trixell Pixium 4600), (iii) a computer control and monitoring system for
cardiac-gated acquisition, and (iv) DE image decomposition and display. Computational and experimental studies of
imaging performance guided optimization of key acquisition technique parameters, including: x-ray filtration, allocation
of dose between low- and high-energy projections, and kVp selection. A system for cardiac-gated acquisition was
developed, directing x-ray exposures to within the quiescent period of the heart cycle, thereby minimizing anatomical
misregistration. A research protocol including 200 patients imaged following lung nodule biopsy is underway, allowing
preclinical evaluation of DE imaging performance relative to conventional radiography and low-dose CT.
The application of high-performance flat-panel detectors (FPDs) to dual-energy (DE) imaging offers the potential for dramatically improved detection and characterization of subtle lesions through reduction of "anatomical noise," with applications ranging from thoracic imaging to image-guided interventions. In this work, we investigate DE imaging performance from first principles of image science to preclinical implementation, including: 1.) generalized task-based formulation of NEQ and detectability as a guide to system optimization; 2.) measurements of imaging performance on a DE imaging benchtop; and 3.) a preclinical system developed in our laboratory for cardiac-gated DE chest imaging in a research cohort of 160 patients. Theoretical and benchtop studies directly guide clinical implementation, including the advantages of double-shot versus single-shot DE imaging, the value of differential added filtration between low- and high-kVp projections, and optimal selection of kVp pairs, filtration, and dose allocation. Evaluation of task-based NEQ indicates that the detectability of subtle lung nodules in double-shot DE imaging can exceed that of single-shot DE
imaging by a factor of 4 or greater. Filter materials are investigated that not only harden the high-kVp beam (e.g., Cu or
Ag) but also soften the low-kVp beam (e.g., Ce or Gd), leading to significantly increased contrast in DE images. A preclinical imaging system suitable for human studies has been constructed based upon insights gained from these theoretical and experimental studies. An important component of the system is a simple and robust means of cardiac-gated DE image acquisition, implemented here using a fingertip pulse oximeter. Timing schemes that provide cardiac-gated
image acquisition on the same or successive heartbeats is described. Preclinical DE images to be acquired under research protocol will afford valuable testing of optimal deployment, facilitate the development of DE CAD, and support comparison of DE diagnostic imaging performance to low-dose CT and radiography.
Dual-energy (DE) imaging is a promising x-ray modality for the screening and early detection of lung cancer but has seen limited application primarily due to the lack of an adequate image detector. Recent development of flat-panel detectors (FPDs) for advanced imaging applications provide a promising technology for DE imaging, and a theoretical framework to quantify the imaging performance of FPD-based DE imaging systems is useful for system design and optimization. Traditional methods employed to describe imaging performance in radiographic systems [i.e., detective quantum efficiency (DQE) and noise-equivalent quanta (NEQ)] are extended in this paper to DE imaging systems using FPDs. To quantify the essential advantage imparted by DE imaging, we incorporate a spatial-frequency-dependent “anatomical noise” term associated with overlying structures to yield the generalized DQE and NEQ. We estimate anatomical noise in DE images through measurements using an anthropomorphic chest phantom and parameterize the measurements using a 1/f model. Cascaded systems analysis of the generalized NEQ is shown to reveal the tradeoffs between anatomical noise and quantum noise in DE image reconstructions. The generalized dual-energy NEQ is combined with idealized task functions to compute the detectability index, providing an estimate of ideal observer performance in a variety of detection and discrimination tasks. The generalized analysis is employed to investigate optimal tissue cancellation and kVp selection as a function of dose and imaging task.
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