Citations

Background Detection of small renal calculi has benefitted from recent advances in computed tomography (CT) scanner design. Information regarding observer performance when using state-of-the-art CT scanners for this application is needed. Purpose To assess observer performance and the impact of radiation dose for detection and size measurement of <4 mm renal stones using CT with integrated circuit detectors and iterative reconstruction. Material and Methods Twenty-nine <4 mm calcium oxalate stones were randomly placed in 20 porcine kidneys in an anthropomorphic phantom. Four radiologists used a workstation to record each calculus detection and size. JAFROC Figure of Merit (FOM), sensitivity, false positive detections, and calculus size were calculated. Results Mean calculus size was 2.2 ± 0.7 mm. The CTDI vol values corresponding to the automatic exposure control settings of 160, 80, 40, 25, and 10 Quality Reference mAs (QRM) were 15.2, 7.9, 4.2, 2.7, and 1.3 mGy, respectively. JAFROC FOM was ≥ 0.97 at ≥ 80 QRM, ≥ 0.89 at ≥ 25 QRM, and was inferior to routine dose (160 QRM) at 10 QRM (0.72, P < 0.05). Per-calculus sensitivity remained ≥ 85% for every reader at ≥ 25 QRM. Mean total false positive detections per reader were ≤ 3 at ≥ 80 QRM, but increased substantially for two readers ( ≥ 12) at ≤ 40 QRM. Measured calculus size significantly decreased at ≤ 25 QRM ( P ≤ 0.01). Conclusion Using low dose renal CT with iterative reconstruction and ≥ 25 QRM results in high sensitivity, but false positive detections increase for some readers at very low dose levels (≤ 40 QRM). At very low doses with iterative reconstruction, measured calculus size will artifactually decrease.

Background and purpose Because computed tomography (CT) is the most commonly used imaging modality for the evaluation of acute ischemic stroke patients, developing CT-based techniques for improving clot characterization could prove useful. The purpose of this in-vitro study was to determine which single-energy or dual-energy CT techniques provided optimum discrimination between red blood cell (RBC) and fibrin-rich clots. Materials and methods Seven clot types with varying fibrin and RBC densities were made (90% RBC, 99% RBC, 63% RBC, 36% RBC, 18% RBC and 0% RBC with high and low fibrin density) and their composition was verified histologically. Ten of each clot type were created and scanned with a second generation dual source scanner using three single (80 kV, 100 kV, 120 kV) and two dual-energy protocols (80/Sn 140 kV and 100/Sn 140 kV). A region of interest (ROI) was placed over each clot and mean attenuation was measured. Receiver operating characteristic curves were calculated at each energy level to determine the accuracy at differentiating RBC-rich clots from fibrin-rich clots. Results Clot attenuation increased with RBC content at all energy levels. Single-energy at 80 kV and 120 kV and dual-energy 80/Sn 140 kV protocols allowed for distinguishing between all clot types, with the exception of 36% RBC and 18% RBC. On receiver operating characteristic curve analysis, the 80/Sn 140 kV dual-energy protocol had the highest area under the curve for distinguishing between fibrin-rich and RBC-rich clots (area under the curve 0.99). Conclusions Dual-energy CT with 80/Sn 140 kV had the highest accuracy for differentiating RBC-rich and fibrin-rich in-vitro thrombi. Further studies are needed to study the utility of non-contrast dual-energy CT in thrombus characterization in acute ischemic stroke.

PurposeTo compare algorithms performing material decomposition and classification in dual‐energy CT, it is desirable to know the ground truth of the lesion to be analyzed in real patient data. In this work, we developed and validated a framework to insert digital lesions of arbitrary chemical composition into patient projection data acquired on a dual‐source, dual‐energy CT system.MethodsA model that takes into account beam‐hardening effects was developed to predict the CT number of objects with known chemical composition. The model utilizes information about the x‐ray energy spectra, the patient/phantom attenuation, and the x‐ray detector energy response. The beam‐hardening model was validated on samples of iodine (I) and calcium (Ca) for a second‐generation dual‐source, dual‐energy CT scanner for all tube potentials available and a wide range of patient sizes. The seven most prevalent mineral components of renal stones were modeled and digital stones were created with CT numbers computed for each patient/phantom size and x‐ray energy spectra using the developed beam‐hardening model. Each digital stone was inserted in the dual‐energy projection data of a water phantom scanned on a dual‐source scanner and reconstructed with the routine algorithms in use in our practice. The geometry of the forward projection for dual‐energy data was validated by comparing CT number accuracy and high‐contrast resolution of simulated dual‐energy CT data of the ACR phantom with experimentally acquired data.ResultsThe beam‐hardening model and forward projection method accurately predicted the CT number of I and Ca over a wide range of tube potentials and phantom sizes. The images reconstructed after the insertion of digital kidney stones were consistent with the images reconstructed from the scanner, and the CT number ratios for different kidney stone types were consistent with data in the literature. A sample application of the proposed tool was also demonstrated.ConclusionA framework was developed and validated for the creation of digital objects of known mineral composition, and for inserting the digital objects into projection data from a commercial dual‐source, dual‐energy CT scanner. Among other applications, it will allow a systematic investigation of the impact of scan and reconstruction parameters on kidney stone dual‐energy properties under rigorously controlled conditions.

PurposeTo develop and evaluate an image‐domain noise reduction method for multi‐energy CT (MECT) data.MethodsMulti‐Energy Non‐Local Means (MENLM) is a technique that uses the redundant information in MECT images to achieve noise reduction. In this method, spatio‐spectral features are used to determine the similarity between pixels, making the similarity evaluation more robust to image noise. The performance of this MENLM filter was tested on images acquired on a whole‐body research photon counting CT system. The impact of filtering on image quality was quantitatively evaluated in phantom studies in terms of image noise level (standard deviation of pixel values), noise power spectrum (NPS), in‐plane and cross‐plane spatial resolution, CT number accuracy, material decomposition performance, and subjective low‐contrast spatial resolution using the American College of Radiology (ACR) CT accreditation phantom. Clinical feasibility was assessed by performing MENLM on contrast‐enhanced swine images and unenhanced cadaver head images using clinically relevant doses and dose rates.ResultsThe phantom studies demonstrated that the MENLM filter reduced noise substantially and still preserved the shape and peak frequency of the NPS. With 80% noise reduction, MENLM filtering caused no degradation of high‐contrast spatial resolution, as illustrated by the modulation transfer function (MTF) and slice sensitivity profile (SSP). CT number accuracy was also maintained for all energy channels, demonstrating that energy resolution was not affected by filtering. Material decomposition performance was improved with MENLM filtering. The subjective evaluation using the ACR phantom demonstrated an improvement in low‐contrast performance. MENLM achieved effective noise reduction in both contrast‐enhanced swine images and unenhanced cadaver head images, resulting in improved detection of subtle vascular structures and the differentiation of white/gray matter.ConclusionIn MECT, MENLM achieved around 80% noise reduction and greatly improved material decomposition performance and the detection of subtle anatomical/low‐contrast features while maintaining spatial and energy resolution. MENLM filtering may improve diagnostic or functional analysis accuracy and facilitate radiation dose and contrast media reduction for MECT.