Deborah Joy Walter

Model-based detection of lung nodules in computed tomography exams1

Abstract Rationale and objectives In this study, we developed a prototype model-based computer aided detection (CAD) system designed to automatically detect both solid and subsolid pulmonary nodules in computed tomography (CT) images. By using this CAD algorithm, along with the radiologist’s initial interpretation, we aim to improve the sensitivity of radiologic readings of CT lung exams. Materials and methods We have developed a model-based CAD algorithm through the use of precise mathematic models that capture scanner physics and anatomic information. Our model-based CAD algorithm uses multiple segmentation algorithms to extract noteworthy structures in the lungs and a Bayesian statistical model selection framework to determine the probability of various anatomical events throughout the lung. We tested this algorithm on 50 low-dose CT lung cancer screening cases in which ground truth was produced through readings by three expert chest radiologists. Results Using this model-based CAD algorithm on 50 low-dose CT cases, we measured potential sensitivity improvements of 7% and 5% in two radiologists with respect to all noncalcified nodules, solid and subsolid, greater than 5 mm in diameter. The third radiologist did not miss any nodules in the ground truth set. The CAD algorithm produced 8.3 false positives per case. Conclusion Our prototype CAD system demonstrates promising results as a tool to improve the quality of radiologic readings by increasing radiologist sensitivity. A significant advantage of this model-based approach is that it can be easily extended to support additional anatomic models as clinical understanding and scanning practices improve.

Simulation of CT dose and contrast-to-noise as function of bowtie shape

Dose is becoming increasingly important for computed tomography clinical practice. It is of general interest to understand the impact that system design can have on dose and image quality. This study addresses the effect of bowtie shape on the dose and contrast-to-noise across the field of view. Simulation of the CT acquisition is used to calculate the energy deposition throughout a numerical phantom for a set of relevant system operating parameters and bowtie shapes. Mean absorbed dose is calculated by summing over the phantom volume and is compared with other typical dose specifications. A more aggressive attenuation profile of the bowtie which offers higher attenuation in the periphery of the field of view can offer the benefit of lower dose but at the expense of reduced contrast-to-noise at the edge of the cross-sectional image.

Accuracy and precision of dual energy CT imaging for the quantification of tissue fat content

We present the analysis of the accuracy and precision of dual energy material basis decomposition for the quantification of tissue fat content in computed tomography. We compare the benefits of a pre-reconstruction (sinogram-based) dual energy imaging technique versus a post-reconstruction (image) based dual energy decomposition technique using a numerical simulation. A phantom containing plastics of known composition is measured to validate the technique. The accuracy of the image based dual energy decomposition technique is contingent on the amount of beam hardening encountered in the phantom. The accuracy of the pre-reconstruction dual energy technique depends on how accurately the system spectral response can be modeled. In both cases the precision of the dual energy imaging is determined by the photon flux.

Dual kVp material decomposition using flat-panel detectors

In addition to a conventional Computed Tomography (CT) image, dual energy (dual kVp) imaging can be used to generate an image of the same anatomy that represents the equivalent density of a particular material, for example, calcium, iodine, water, etc. This image can be used to improve the differentiation of materials as well as improve the accuracy of absolute density measurements in a cross-sectional image. It is important to understand the certainty of the estimation of the density of the material. Both simulations and measurements are used to quantify these errors. Data are acquired using a flat-panel based volumetric CT system, by taking two scans and adjusting the maximum energy of the source spectrum (kVp). Physics based simulations are used to compare with the measurements. After validating the simulation algorithms, the accuracy of the dual kVp method is determined using the simulations in a perturbation study.

Future generation CT imaging

X-ray CT technology has been available for more than 30 years, yet continued technological advances have kept CT imaging at the forefront of medical imaging innovation. Consequently, the number of clinical CT applications has increased steadily. Other imaging modalities might be superior to CT imaging for some specific applications, but no other single modality is more often used in chest imaging today. Future technological developments in the area of high-resolution detectors, high-capacity x-ray tubes, advanced reconstruction algorithms, and improved visualization techniques will continue to expand the imaging capability. Future CT imaging technology will combine improved imaging capability with advanced and specific computer-assisted tools, which will expand the usefulness of CT imaging in many areas.

Dual energy for material differentiation in coronary arteries using electron-beam CT

The purpose of this paper is to investigate the use of electron-beam Computed Tomography (EBCT) dual energy scanning for improved differentiation of calcified coronary arteries from iodinated-contrasted blood, in fast moving cardiac vessels. The dual energy scanning technique can lead to an improved cardiac examination in a single breath hold with more robust calcium scoring and better vessel characterization. Dual energy can be used for material discrimination in CT imaging to differentiate materials with similar CT number, but different material attenuation properties. Mis-registration is the primary source of error in a dual energy application, since acquisitions have to be made at each energy, and motion between the acquisitions causes inconsistencies in the decomposition algorithm, which may lead to artifacts in the resultant images. Using EBCT to quickly switch x-ray source peak voltage potential (kVp), the mis-registration of patient anatomy is minimized since acquisitions at both energy spectra are completed in one study at the same cardiac phase. Two protocols for scanning the moving heart using EBCT were designed to minimize registration issues. Material basis function decomposition was used to differentiate regions containing calcium and iodine in the image. We find that this protocol is superior to CT imaging at one energy spectrum in discriminating calcium from contrast-enhanced lumen. Using dual energy EBCT scanning can enable accurate calcium scoring, and angiography applications to be performed in one exam.

Novel features of the x-ray scatter profile that are not modeled by convolution of the primary

A convolution model of scatter that is adaptable to rapid simulation and correction algorithms is tested against the measured scatter profiles. In the simple case of a uniform acrylic sheet, the convolution approach yields about 10% absolute agreement with the measured scatter profile. However, significant qualitative differences are demonstrated for phantoms with non-uniform thickness or composition. For example, the scatter profile is dependent on a bones vertical position in the phantom whereas the primary is unchanged. Similarly, a cusp shape in the scatter profile observed near the abrupt edge of an acrylic sheet is not produced in the convolution model. An alternate approach that calculates the scatter as a 3D integral over the object volume can reproduce this behavior.