CT automated exposure control using a generalized detectability index.

PURPOSE: Identifying an appropriate tube current setting can be challenging when using iterative reconstruction due to the varying relationship between spatial resolution, contrast, noise, and dose across different algorithms. This study developed and investigated the application of a generalized detectability index ( d gen ' ) to determine the noise parameter to input to existing automated exposure control (AEC) systems to provide consistent image quality (IQ) across different reconstruction approaches. METHODS: This study proposes a task-based automated exposure control (AEC) method using a generalized detectability index ( d gen ' ). The proposed method leverages existing AEC methods that are based on a prescribed noise level. The generalized d gen ' metric is calculated using lookup tables of task-based modulation transfer function (MTF) and noise power spectrum (NPS). To generate the lookup tables, the American College of Radiology CT accreditation phantom was scanned on a multidetector CT scanner (Revolution CT, GE Healthcare) at 120 kV and tube current varied manually from 20 to 240 mAs. Images were reconstructed using a reference reconstruction algorithm and four levels of an in-house iterative reconstruction algorithm with different regularization strengths (IR1-IR4). The task-based MTF and NPS were estimated from the measured images to create lookup tables of scaling factors that convert between d gen ' and noise standard deviation. The performance of the proposed d gen ' -AEC method in providing a desired IQ level over a range of iterative reconstruction algorithms was evaluated using the American College of Radiology (ACR) phantom with elliptical shell and using a human reader evaluation on anthropomorphic phantom images. RESULTS: The study of the ACR phantom with elliptical shell demonstrated reasonable agreement between the d gen ' predicted by the lookup table and d ' measured in the images, with a mean absolute error of 15% across all dose levels and maximum error of 45% at the lowest dose level with the elliptical shell. For the anthropomorphic phantom study, the mean reader scores for images resulting from the d gen ' -AEC method were 3.3 (reference image), 3.5 (IR1), 3.6 (IR2), 3.5 (IR3), and 2.2 (IR4). When using the d gen ' -AEC method, the observers' IQ scores for the reference reconstruction were statistical equivalent to the scores for IR1, IR2, and IR3 iterative reconstructions (P > 0.35). The d gen ' -AEC method achieved this equivalent IQ at lower dose for the IR scans compared to the reference scans. CONCLUSIONS: A novel AEC method, based on a generalized detectability index, was investigated. The proposed method can be used with some existing AEC systems to derive the tube current profile for iterative reconstruction algorithms. The results provide preliminary evidence that the proposed d gen ' -AEC can produce similar IQ across different iterative reconstruction approaches at different dose levels.

Application of fractal dimension for quantifying noise texture in computed tomography images.

PURPOSE: Evaluation of noise texture information in CT images is important for assessing image quality. Noise texture is often quantified by the noise power spectrum (NPS), which requires numerous image realizations to estimate. This study evaluated fractal dimension for quantifying noise texture as a scalar metric that can potentially be estimated using one image realization. METHODS: The American College of Radiology CT accreditation phantom (ACR) was scanned on a clinical scanner (Discovery CT750, GE Healthcare) at 120 kV and 25 and 90 mAs. Images were reconstructed using filtered back projection (FBP/ASIR 0%) with varying reconstruction kernels: Soft, Standard, Detail, Chest, Lung, Bone, and Edge. For each kernel, images were also reconstructed using ASIR 50% and ASIR 100% iterative reconstruction (IR) methods. Fractal dimension was estimated using the differential box-counting algorithm applied to images of the uniform section of ACR phantom. The two-dimensional Noise Power Spectrum (NPS) and one-dimensional-radially averaged NPS were estimated using established techniques. By changing the radiation dose, the effect of noise magnitude on fractal dimension was evaluated. The Spearman correlation between the fractal dimension and the frequency of the NPS peak was calculated. The number of images required to reliably estimate fractal dimension was determined and compared to the number of images required to estimate the NPS-peak frequency. The effect of Region of Interest (ROI) size on fractal dimension estimation was evaluated. Feasibility of estimating fractal dimension in an anthropomorphic phantom and clinical image was also investigated, with the resulting fractal dimension compared to that estimated within the uniform section of the ACR phantom. RESULTS: Fractal dimension was strongly correlated with the frequency of the peak of the radially averaged NPS curve, having a Spearman rank-order coefficient of 0.98 (P-value < 0.01) for ASIR 0%. The mean fractal dimension at ASIR 0% was 2.49 (Soft), 2.51 (Standard), 2.52 (Detail), 2.57 (Chest), 2.61 (Lung), 2.66 (Bone), and 2.7 (Edge). A reduction in fractal dimension was observed with increasing ASIR levels for all investigated reconstruction kernels. Fractal dimension was found to be independent of noise magnitude. Fractal dimension was successfully estimated from four ROIs of size 64 × 64 pixels or one ROI of 128 × 128 pixels. Fractal dimension was found to be sensitive to non-noise structures in the image, such as ring artifacts and anatomical structure. Fractal dimension estimated within a uniform region of an anthropomorphic phantom and clinical head image matched that estimated within the ACR phantom for filtered back projection reconstruction. CONCLUSIONS: Fractal dimension correlated with the NPS-peak frequency and was independent of noise magnitude, suggesting that the scalar metric of fractal dimension can be used to quantify the change in noise texture across reconstruction approaches. Results demonstrated that fractal dimension can be estimated from four, 64 × 64-pixel ROIs or one 128 × 128 ROI within a head CT image, which may make it amenable for quantifying noise texture within clinical images.

Household air pollution and lung function in Indian adults: a cross-sectional study.

Exposure to air pollution produced by cooking is common in developing countries, and represents a potentially avoidable cause of lung disease. Cross-sectional data were collected by the World Health Organization's Study on Global AGEing and Adult Health conducted in India between 2007 and 2010. Exposure to biomass cooking was also associated with a decrease in forced expiratory volume in 1 s (FEV1) (-70 ml, 95%CI -111 to -30) and FEV1/FVC (forced vital capacity) ratio (-0.025, 95%CI -0.035 to -0.015) compared to those who were not exposed. These associations were predominantly observed in males (P < 0.05 for interaction analyses). Intervention studies using non-biomass fuels in India are required to ascertain potential respiratory health benefits.

A Combination of Spatial and Recursive Temporal Filtering for Noise Reduction when Using Region of Interest (ROI) Fluoroscopy for Patient Dose Reduction in Image Guided Vascular Interventions with Significant Anatomical Motion.

Because x-ray based image-guided vascular interventions are minimally invasive they are currently the most preferred method of treating disorders such as stroke, arterial stenosis, and aneurysms; however, the x-ray exposure to the patient during long image-guided interventional procedures could cause harmful effects such as cancer in the long run and even tissue damage in the short term. ROI fluoroscopy reduces patient dose by differentially attenuating the incident x-rays outside the region-of-interest. To reduce the noise in the dose-reduced regions previously recursive temporal filtering was successfully demonstrated for neurovascular interventions. However, in cardiac interventions, anatomical motion is significant and excessive recursive filtering could cause blur. In this work the effects of three noise-reduction schemes, including recursive temporal filtering, spatial mean filtering, and a combination of spatial and recursive temporal filtering, were investigated in a simulated ROI dose-reduced cardiac intervention. First a model to simulate the aortic arch and its movement was built. A coronary stent was used to simulate a bio-prosthetic valve used in TAVR procedures and was deployed under dose-reduced ROI fluoroscopy during the simulated heart motion. The images were then retrospectively processed for noise reduction in the periphery, using recursive temporal filtering, spatial filtering and a combination of both. Quantitative metrics for all three noise reduction schemes are calculated and are presented as results. From these it can be concluded that with significant anatomical motion, a combination of spatial and recursive temporal filtering scheme is best suited for reducing the excess quantum noise in the periphery. This new noise-reduction technique in combination with ROI fluoroscopy has the potential for substantial patient-dose savings in cardiac interventions.

Micro-Computed tomography (CT) based assessment of dental regenerative therapy in the canine mandible model.

High-resolution 3D bone-tissue structure measurements may provide information critical to the understanding of the bone regeneration processes and to the bone strength assessment. Tissue engineering studies rely on such nondestructive measurements to monitor bone graft regeneration area. In this study, we measured bone yield, fractal dimension and trabecular thickness through micro-CT slices for different grafts and controls. Eight canines underwent surgery to remove a bone volume (defect) in the canine's jaw at a total of 44 different locations. We kept 11 defects empty for control and filled the remaining ones with three regenerative materials; NanoGen (NG), a FDA-approved material (n=11), a novel NanoCalcium Sulfate (NCS) material (n=11) and NCS alginate (NCS+alg) material (n=11). After a minimum of four and eight weeks, the canines were sacrificed and the jaw samples were extracted. We used a custom-built micro-CT system to acquire the data volume and developed software to measure the bone yield, fractal dimension and trabecular thickness. The software used a segmentation algorithm based on histograms derived from volumes of interest indicated by the operator. Using bone yield and fractal dimension as indices we are able to differentiate between the control and regenerative material (p<0.005). Regenerative material NCS showed an average 63.15% bone yield improvement over the control sample, NCS+alg showed 55.55% and NanoGen showed 37.5%. The bone regeneration process and quality of bone were dependent upon the position of defect and time period of healing. This study presents one of the first quantitative comparisons using non-destructive Micro-CT analysis for bone regenerative material in a large animal with a critical defect model. Our results indicate that Micro-CT measurement could be used to monitor in-vivo bone regeneration studies for greater regenerative process understanding.

Water quality simulation of sewage impacts on the west coast of Mumbai, India.

Most coastal cities use the ocean as a site of waste disposal where pollutant loading degrades the quality of coastal waters. Presently, the west coast of Mumbai receives partially treated effluent from wastewater treatment facilities through ocean outfalls and discharges into creeks as well as wastewater/sewage from various open drains and nallahs which affect the water quality of creek and coastal water. Therefore, the objective of this paper is to simulate and assess the hydrodynamic behaviour and water quality due to impact of sewage and wastewater discharges from the west coast of Mumbai. Hydrodynamics and water quality were simulated based on present conditions and validated by using measured tide, current data and observed DO, BOD and FC. Observed and simulated results indicated non compliance to standards in Malad, Mahim creeks and the impact zones of ocean outfalls. The developed model could be used for generating various conditions of hydrodynamics and water quality considering the improvement in wastewater collection systems, treatment levels and proper disposal for proper planning and management of creeks and coastal environment.