Computed Tomography Manufacturers Research Articles

Development and validation of a CT-based deep learning algorithm to augment non-invasive diagnosis of idiopathic pulmonary fibrosis

RationaleNon-invasive diagnosis of idiopathic pulmonary fibrosis (IPF) involves identification of usual interstitial pneumonia (UIP) pattern by computed tomography (CT) and exclusion of other known etiologies of interstitial lung disease (ILD). However, uncertainty in identification of radiologic UIP pattern leads to the continued need for invasive surgical biopsy. We thus developed and validated a machine learning algorithm using CT scans alone to augment non-invasive diagnosis of IPF. MethodsThe primary algorithm was a deep learning convolutional neural network (CNN) with model inputs of CT images only. The algorithm was trained to predict IPF among cases of ILD, with reference standard of multidisciplinary discussion (MDD) consensus diagnosis. The algorithm was trained using a multi-center dataset of more than 2000 cases of ILD. A US-based multi-site cohort (n = 295) was used for algorithm tuning, and external validation was performed with a separate dataset (n = 295) from European and South American sources. ResultsIn the tuning set, the model achieved an area under the receiver operating characteristic curve (AUC) of 0.87 (CI: 0.83–0.92) in differentiating IPF from other ILDs. Sensitivity and specificity were 0.67 (0.57–0.76) and 0.90 (0.83–0.95), respectively. By contrast, pre-recorded assessment prior to MDD diagnosis had sensitivity of 0.31 (0.23–0.42) and specificity of 0.92 (0.87–0.95). In the external test set, c-statistic was also 0.87 (0.83–0.91). Model performance was consistent across a variety of CT scanner manufacturers and slice thickness. ConclusionThe presented deep learning algorithm demonstrated consistent performance in identifying IPF among cases of ILD using CT images alone and suggests generalization across CT manufacturers.

Validation of a New Scintillating Fiber Dosimeter for Radiation Dose Quality Control in Computed Tomography.

(1) Background: The IVIscan is a commercially available scintillating fiber detector designed for quality assurance and in vivo dosimetry in computed tomography (CT). In this work, we investigated the performance of the IVIscan scintillator and associated method in a wide range of beam width from three CT manufacturers and compared it to a CT chamber designed for Computed Tomography Dose Index (CTDI) measurements. (2) Methods: We measured weighted CTDI (CTDIw) with each detector in accordance with the requirements of regulatory tests and international recommendations for the minimum, maximum and the most used beam width in clinic and investigated the accuracy of the IVIscan system based on the assessment of the CTDIw deviation from the CT chamber. We also investigated the IVIscan accuracy for the whole range of the CT scans kV. (3) Results: We found excellent agreement between the IVIscan scintillator and the CT chamber for the whole range of beam widths and kV, especially for wide beams used on recent technology of CT scans. (4) Conclusions: These findings highlight that the IVIscan scintillator is a relevant detector for CT radiation dose assessments, and the method associated with calculating the CTDIw saves a significant amount of time and effort when performing tests, especially with regard to new CT technologies.

Truncation Effects on Effective Diameter Measurement for Size-specific Dose Estimation in Computed Tomography (CT) Imaging

The determination of size specific dose estimation (SSDE) has been proposed for accurate CT dose assessment. The SSDE introduction has prompted numerous manufacturers and researchers to develop various methodologies that have progressed from manual to automated methods in SSDE determination. Few studies reported on truncation effects with respect to specific size and SSDE determination and CT manufacturers are yet to incorporate truncation correction in their system [1,2].
 This study aimed to evaluate the effects of truncation artifacts on the measurement of effective diameter (Deff) and SSDE in CT imaging. A phantom study was performed using CTDI phantom of different diameters, 22 and 32 cm with Siemens SOMATOM Definition AS+ CT scanner. Phantom images of different truncation percentage (TP) of 5%, 10%, 15%, and 20% were simulated and acquired. The Deff and SSDE were determined based on the displayed CTDIvol, and the AAPM correction factor table was used to calculate the SSDE accurately [3]. The percentage error for each TP in comparison with non-truncated image (TP 0%) was computed.
 Results showed the percentage error (PE) for both Deff and SSDE increased as the TP increased. The PE was determined by comparing the Deff and SSDE of each TP with non-truncated (TP 0%) image. Table 1 shows the values of PE of truncated images of different TP (5%, 10%, 15%, and 20%) for both Deff and SSDE in phantom sizes of 22 and 32 cm. However, it can be observed that PE values for SSDE of 5% and 10% truncation were similar for both phantom sizes. This is because the correction factors for 5% and 10% were similar and had resulted in similar calculated SSDE. The highest recorded PE was observed in 20% truncation that determined the largest difference in Deff and SSDE with non-truncated image.
 This study demonstrates that there is a linear relationship between truncation percentage with measured Deff and SSDE computation. It can be concluded that the percentage error in Deff measurement and calculated SSDE will increase as TP increased. Therefore, the effects of truncation artefacts should be carefully considered in SSDE calculation for accurate estimation especially in development of automated calculation.

Multi-domain CT translation by a routable translation network

Objective. To unify the style of computed tomography (CT) images from multiple sources, we propose a novel multi-domain image translation network to convert CT images from different scan parameters and manufacturers by simply changing a routing vector. Approach. Unlike the existing multi-domain translation techniques, our method is based on a shared encoder and a routable decoder architecture to maximize the expressivity and conditioning power of the network. Main results. Experimental results show that the proposed CT image conversion can minimize the variation of image characteristics caused by imaging parameters, reconstruction algorithms, and hardware designs. Quantitative results and clinical evaluation from radiologists also show that our method can provide accurate translation results. Significance. Quantitative evaluation of CT images from multi-site or longitudinal studies has been a difficult problem due to the image variation depending on CT scan parameters and manufacturers. The proposed method can be utilized to address this for the quantitative analysis of multi-domain CT images.

Calculation of scan length and size-specific dose at longitudinal positions of body CT scans using dose equilibrium function.

Dose evaluation at longitudinal positions of body computed tomography (CT) scans is useful for CT quality assurance programs and patient organ dose evaluation. Accurate estimates depend on both patient size and scan length. To propose practical evaluation of the average dose to the transverse slab of an axial image slice for adult body CT examinations, considering not only patient size but also scan length, and to compare the results with those of Monte Carlo (Geant4) simulation [Dsim (z)] and size-specific dose estimates at longitudinal positions of scans [SSDE(z)] from international standards (IEC publication no. 62985). In a scan series, the total dose at each z-axis location was calculated using the input information identical to the SSDE(z) evaluation. Each axial image slice (slice thickness, 2.5 or 5mm) was first considered independently. Its z-axis coverage and CTDIvol (from the DICOM headers) were used to directly calculate a z-axis dose profile for the average dose over the cross-section of a water phantom, using the approach to equilibrium function. The phantom diameter was taken to be equal to the patient water equivalent diameter at that slice. The above was repeated at all slices and the dose at each z-axis location was accumulated from all profiles, referred to as Dcalc (z). For validation, we considered a cohort of 65 patients, who underwent chest and abdominopelvic examinations. The resultant Dcalc (z) was compared with Dsim (z) and SSDE(z), both available in a previous paper. Dcalc (z) evaluation could be used to accurately assess the scan range average dose, with an accuracy of 7.1%-8.7% for 65 patients in two examinations. On individual image slices, the maximum difference in magnitude between Dcalc (z) and Dsim (z) [and between SSDE(z) and Dsim (z) in parentheses] was 37.5% (85%) [two edges (2×5cm) of chest scan range], 17.8% (35.2%) (the remaining central region of chest scan), 26.8% (74.1%) [two edges (2×5cm) of abdominopelvic scan range], and 14.2% (22.5%) (the remaining central region of abdominopelvic scan). Identical input data are used for Dcalc (z) and SSDE(z) evaluations. The latter is limited to the z-axis locations within scan range. At each image slice, SSDE(z) is equivalent to the midpoint dose of a fixed-mA scan of 15-30cm (scan length). In contrast, Dcalc (z) considers dose accumulation from varying scan length (from sub-centimeter to about 1m) and tube current, and dose profile is also computed outside scan range. Besides greatly improving dose evaluation for individual image slices, Dcalc (z) allows for evaluating dose accumulation from multiple series, which typically span different scan ranges. Our proposal may assist CT manufacturers and dose index monitoring software in assessing dose at longitudinal positions of body CT scans.

Repeatability and Reproducibility of Computed Tomography Radiomics for Pulmonary Nodules: A Multicenter Phantom Study.

BackgroundRadiomics can yield minable information from medical images, which can facilitate computer-aided diagnosis. However, the lack of repeatability and reproducibility of radiomic features (RFs) may hinder their generalizability in clinical applications.ObjectivesThe aims of this study were to explore 3 main sources of variability in RFs, investigate their influencing magnitudes and patterns, and identify a subset of robust RFs for further studies.Materials and MethodsA chest phantom with nodules was scanned with different computed tomography (CT) scanners repeatedly with varying acquisition and reconstruction parameters (April-May 2019) to evaluate 3 sources of variability: test-retest, inter-CT, and intra-CT protocol variability. The robustness of the RFs was measured using the concordance correlation coefficient, dynamic range, and intraclass correlation coefficient (ICC). The influencing magnitudes and patterns were analyzed using the Friedman test and Spearman rank correlation coefficient. Stable and informative RFs were selected, and their redundancy was eliminated using hierarchical clustering. Clinical validation was also performed to verify the clinical effectiveness and potential enhancement of the generalizability of radiomics research.ResultsA total of 1295 RFs that showed all 3 sources of variability were included. The reconstruction kernel and the iteration level showed the greatest (ICC, 0.35 ± 0.31) and the least (ICC, 0.63 ± 0.27) influence on magnitudes. The different sources of variability showed relatively consistent patterns of influence (false discovery rate <0.001). Finally, we obtained a subset of 19 stable, informative, and nonredundant RFs under all 3 sources of variability. These RFs exhibited clinical effectiveness and showed better prediction performance than unstable RFs in the validation dataset (P = 0.017, Delong test).ConclusionsThe stability of RFs was affected to different degrees by test-retest and differences in CT manufacturers and models and CT acquisition and reconstruction parameters, but the influences of these factors showed relatively consistent patterns. We also obtained a subset of 19 stable, informative, and nonredundant RFs that should be preferably used to enhance the generalizability of further radiomics research.

Issues of Ohmic Contacts in Human Medical Photon-Counting CT Detectors

Human medical computed tomography (CT) detectors based on photon-counting have to support high photon event rates and at the same time must not polarize. CZT/CdTe has become the most promising direct conversion material for this purpose and is in use on photon-counting CT prototype scanners at several CT manufacturers. An important design choice is the type of electrode contacts used. In the past, CdTe with Schottky contacts usually resulted in severe polarization already at low flux, while with ohmic contacts this was not observed giving rise to the view that ohmic contacts could help to reduce polarization. In our investigations toward CZT for high flux CT detectors, we found however that, despite a baseline restorer eliminating slowly changing additional currents efficiently, highly optimized CZT with ohmic contacts exhibited an unacceptable violation of the Poisson figure of merit “variance≤mean”, according to which the variance of the observed number of counts (OC) does not exceed the average of the OC (with the variance equaling the average at low flux). This violation is not observed with (semi)-blocking contacts. Based on a simple model for the mechanism of photoconduction known from the literature, two extreme cases are discussed. They both explain why the injection current causes additional noise in the number of observed counts due to the Poisson arrivals, which also modulate the injection current. For the second extreme case, the power spectral density of the injection current is estimated.

Robust contour propagation using deep learning and image registration for online adaptive proton therapy of prostate cancer.

PurposeTo develop and validate a robust and accurate registration pipeline for automatic contour propagation for online adaptive Intensity‐Modulated Proton Therapy (IMPT) of prostate cancer using elastix software and deep learning.MethodsA three‐dimensional (3D) Convolutional Neural Network was trained for automatic bladder segmentation of the computed tomography (CT) scans. The automatic bladder segmentation alongside the computed tomography (CT) scan is jointly optimized to add explicit knowledge about the underlying anatomy to the registration algorithm. We included three datasets from different institutes and CT manufacturers. The first was used for training and testing the ConvNet, where the second and the third were used for evaluation of the proposed pipeline. The system performance was quantified geometrically using the dice similarity coefficient (DSC), the mean surface distance (MSD), and the 95% Hausdorff distance (HD). The propagated contours were validated clinically through generating the associated IMPT plans and compare it with the IMPT plans based on the manual delineations. Propagated contours were considered clinically acceptable if their treatment plans met the dosimetric coverage constraints on the manual contours.ResultsThe bladder segmentation network achieved a DSC of 88% and 82% on the test datasets. The proposed registration pipeline achieved a MSD of 1.29 ± 0.39, 1.48 ± 1.16, and 1.49 ± 0.44 mm for the prostate, seminal vesicles, and lymph nodes, respectively, on the second dataset and a MSD of 2.31 ± 1.92 and 1.76 ± 1.39 mm for the prostate and seminal vesicles on the third dataset. The automatically propagated contours met the dose coverage constraints in 86%, 91%, and 99% of the cases for the prostate, seminal vesicles, and lymph nodes, respectively. A Conservative Success Rate (CSR) of 80% was obtained, compared to 65% when only using intensity‐based registration.ConclusionThe proposed registration pipeline obtained highly promising results for generating treatment plans adapted to the daily anatomy. With 80% of the automatically generated treatment plans directly usable without manual correction, a substantial improvement in system robustness was reached compared to a previous approach. The proposed method therefore facilitates more precise proton therapy of prostate cancer, potentially leading to fewer treatment‐related adverse side effects.

Perceptions and Use of Computed Tomography in a Hospital Emergency Department: Technicians' Perspectives.

This study traces the evolution of perceptions and use of computed tomography (CT) by radiology technicians in the emergency department (ED) of a hospital in Italy across a 7-year period. The sociotechnical context of the CT room of an ED has been neglected by scientific research-potentially impacting safety. Two studies were performed, one in 2011 and one in 2018. Six CT technicians were involved in each. Structured interviews were performed to gather information on perceptions related to the evolution of the use of CT according to nine different factors-e.g. the level of complexity, and mental workload. Observations were performed on duration of exams, the flow of people, conversations, and any critical issues. The CT technology is appreciated, used effectively and with confidence by CT technicians. From 2011-2018, the execution times of the exams have decreased but not the proportion of time dedicated to the patient. Expectations for future improvements are limited by issues concerning the design of both the user interface and the social context of the ED workplace. The safety and efficiency of the system as a whole are greatly dependent on the competence of the CT technicians. CT manufacturers rely on this competence to help compensate for the deficiencies created by suboptimal user interfaces and the lack of fit of the technology with the social context of the workplace. Training programs aimed at improving the management of relationships and communications between staff could improve performance and efficiency. CT manufacturers should try to better understand the cognitive and operational context of the workplaces where CT technicians work-and to design better diagnostic technology which accounts for these operational realities.

I121] Model observers applied to quality control in computed tomography

Model observers are mathematical algorithms that can include different aspects of the human visual system and aim to reproduce human performance for simple detection tasks. Their use has extended in different medical imaging modalities, such as mammography, computed tomography (CT) and nuclear medicine among others, in the past few years. Several model observers have shown good correlation with human observers for simple detection and discrimination tasks in image quality phantoms with uniform backgrounds. Some model observers have been used by CT manufacturers to obtain clearance for their image quality claims, in particular for low contrast detectability (LCD), in the USA. LCD is frequently assessed in CT by human observers scoring the visibility of simple objects (such as disks) of different contrast and size in phantom images. These studies might be biased as, in general, the observer knows the distribution of the objects in the phantom beforehand. A great inter- and intra-observer variability might also appear. The models that will be studied in the course are: the non-prewhitening matched filter with an eye filter (NPWE) and the channelized Hotelling observer (CHO). The NPWE model includes a mathematical implementation of the contrast sensitivity function (CSF) of the human eye. There exist different published functions for the CSF based on human observer studies. The CHO model includes channels that can have different shapes (Gabor, Laguerre-Gauss, difference of gaussians…) depending on the target object; the channels aim to mimic the neurons triggering in the human visual cortex. Different aspects the implementation of model observers in image quality assessment, in particular in CT will be explored in this refresher course. Among them, how to choose the task, how to implement a model observer and its limitations, and also a short introduction on how to validate the model results with human observer studies. Practical examples about the use of these models in routine quality control, for example for low contrast detectability assessment, will be shown. Tips about how to start implementing model observers, in particular with freeware (imageJ), will be shared.

Reducing radiation exposure with iterative reconstruction: an inter- and intra-scanner analysis

Our purpose in this study was to compare delivered radiation exposure via computed tomography dose index volume (CTDIvol) and dose length production (DLP) measurements from computed tomography (CT) examinations performed on scanners with and without image-quality enhancing iterative reconstruction (IR) software. A retrospective analysis was conducted on randomly selected chest, abdomen, and/or pelvis CT examinations from three different scanners from 1 January 2013 to 31 December 2013. CTDIvol and DLP measurements were obtained from two CT scanners with and one CT scanner without IR software. To evaluate inter-scanner variability, we compared measurements from the same model CT scanners, one with and one without IR software. To evaluate intra-scanner variability, we compared measurements between two scanners with IR software from different manufacturers. CT scanners with IR software aided in the overall reduction in radiation exposure, measured as CTDIvol by 30% and DLP by 39% when compared to a scanner without IR. There was no significant difference in CTDlvol or DLP measurements across different manufacturers with IR software. As a result, IR software significantly decreased the radiation exposure to patients, but there were no differences in radiation measurements across CT manufacturers with IR software.

Computed Tomography Scanner Productivity and Entry-Level Models in the Global Market.

Objective This study evaluated the productivity of computed tomography (CT) models and characterized their simplest (entry-level) models' supply in the world market. Methods CT exam times were measured in eight health facilities in the state of Rio de Janeiro, Brazil. Exams were divided into six stages: (1) arrival of patient records to the examination room; (2) patient arrival; (3) patient positioning; (4) data input prior to exam; (5) image acquisition; and (6) patient departure. CT exam productivity was calculated by dividing the total weekly working time by the total exam time for each model. Additionally, an internet search identified full-body CT manufacturers and their offered entry-level models. Results The time durations of 111 CT exams were obtained. Differences among average exam times were not large, and they were mainly due to stages not directly related to data acquisition or image reconstruction. The survey identified that most manufacturers offer 2- to 4-slice models for Asia, South America, and Africa, and one offers single-slice models (Asia). In the USA, two manufacturers offer models below 16-slice. Conclusion Productivity gains are not linearly related to “slice” number. It is suggested that the use of “shareable platforms” could make CTs cheaper, increasing their availability.

Truth or dare: Achieving lower radiation doses in CT

The continuous evolution of computed tomography (CT) technology has allowed for wider clinical CT utilization. However the increased radiation doses associated with CT have raised concerns about the risk of carcinogenesis among Radiation Protection Authorities, health professionals and patients. Although the benefit of a justified CT examination by and large outweighs the risk, optimization of the procedure is essential to further this risk. Moreover CT manufacturers have developed several dose reduction tools and dose alert platforms to modulate and record the radiation doses administered to patients. The scope of this presentation is to outline the significance of optimization in CT, to describe CT parameters, scanner dose output indices and the methodology to reduce dose without compromising diagnostic quality. Learning Outcomes: Following the presentation, participants will be able to: 1. Demonstrate the difference between CT scanner output and effective dose. 2. Fine-tune dose reduction parameters ensuring ALARA and according to clinical requirements (i.e. mAs and kV modulation, section collimation, detector array selection, pitch). 3. Distinguish between noise reduction iterative reconstruction algorithms and dose. 4. Correlate CT dose indices to national DRLs. 5. Participate in CT protocol design and continuous quality improvement programs. 6. Promote Radiation Protection Campaigns (i.e. Image Wisely, Image Gently, Eurosafe Imaging, RPOP). No disclosures.

CT dose optimization

The advances in computed tomography (CT) technology have expanded the clinical applications of CT imaging. As a result the use of CT has been markedly increased over the recent years raising concerns about the stochastic risks of radiation and consequently safety in patient’s care. To comply with the “as low as reasonably achievable” principle, there is need to develop appropriate strategies to optimize CT examinations. CT manufacturers strive to develop techniques to reduce radiation dose while delivering tomographic images of diagnostic quality. Automatic exposure control systems and iterative reconstruction algorithms constitute the state of the art techniques for radiation dose optimization in CT. However, technological advancements have led to the introduction of new parameters that complicate CT examination protocols. Parameters that affect radiation dose and image quality in CT include quality reference tube current, quality reference image noise, tube voltage, quality reference contrast to noise ratio, beam width, pitch, length of z-overscan, reconstruction kernel, weight of blending between filtered back projection and iterative reconstruction algorithms. To optimize CT examination protocols, a basic understanding of CT scan parameters and their effect on image quality is required. CT radiation dose optimization is an important issue that needs to be addressed first by CT vendors and consequently by radiologists, medical physicists and radiologic technologists. In this presentation the basic principles of CT radiation exposure and the strategies followed for CT radiation dose optimization from the medical physicist’s perspective are reviewed.

Evaluation of commercial extension plates for the ACR CT accreditation phantom

The American College of Radiology (ACR) Computed Tomography (CT) Accreditation Program requires submission of phantom scans acquired with the ACR accreditation phantom. There is a known issue with some wide‐beam scanners in which the Hounsfield unit (HU) value of water may be correct when using the scanner manufacturer's phantom, but will be out of range in some scan modes when scanning the accreditation phantom. The phantom manufacturer has developed a product known as Extension Plates to eliminate the water HU value issue. The purpose of this technical note is to evaluate the effectiveness of the Extension Plates in alleviating the water HU issue. The ACR phantom was scanned on nine different CT scanners representing four CT manufacturers at eight different facilities. Scanner models included 16‐ and 64‐channel geometries from each manufacturer. All scanners passed routine daily water HU testing per the manufacturer's instructions. The accreditation phantom was scanned in helical and axial modes both with and without the Extension Plates present. Regions of interest were placed on the linearity test objects as well as the water HU test object in Module 1 of the phantom. Mean values were recorded and compared with the acceptable ranges specified by the ACR accreditation phantom testing instructions. Water HU values failed for one scanner model when scanned in helical mode using the widest collimation available and the Extension Plates were not present. All other scanner models passed the water HU linearity test with or without the Extension Plates in both axial and helical scan modes. Three of the four manufacturers tested failed the linearity test for different materials. The presence of the Extension Plates only affected the HU measurement for the water test object.PACS number(s): 87.57Q, 87.57C

Measurement of bow tie profiles in CT scanners using a real-time dosimeter.

Several areas of computed tomography (CT) research require knowledge about the intensity profile of the x-ray fan beam that is introduced by a bow tie filter. This information is considered proprietary by CT manufacturers, so noninvasive measurement methods are required. One method using real-time dosimeters has been proposed in the literature. A commercially available dosimeter was used to apply that method, and analysis techniques were developed to extract fan beam profiles from measurements. A real-time ion chamber was placed near the periphery of an empty CT gantry and the dose rate versus time waveform was recorded as the x-ray source rotated about the isocenter. In contrast to previously proposed analysis methods that assumed a pointlike detector, the finite-size ion chamber received varying amounts of coverage by the collimated x-ray beam during rotation, precluding a simple relationship between the source intensity as a function of fan beam angle and measured intensity. A two-parameter model for measurement intensity was developed that included both effective collimation width and source-to-detector distance, which then was iteratively solved to minimize the error between duplicate measurements at corresponding fan beam angles, allowing determination of the fan beam profile from measured dose-rate waveforms. Measurements were performed on five different scanner systems while varying parameters such as collimation, kVp, and bow tie filters. On one system, direct measurements of the bow tie profile were collected for comparison with the real-time dosimeter technique. The data analysis method for a finite-size detector was found to produce a fan beam profile estimate with a relative error between duplicate measurement intensities of <5%. It was robust over a wide range of collimation widths (e.g., 1-40 mm), producing fan beam profiles that agreed with a relative error of 1%-5%. Comparison with a direct measurement technique on one system produced agreement with a relative error of 2%-6%. Fan beam profiles were found to differ for different filter types on a given system and between different vendors. A commercially available real-time dosimeter probe was found to be a convenient and accurate instrument for measuring fan beam profiles. An analysis method was developed that could handle a wide range of collimation widths by explicitly considering the finite width of the ion chamber. Relative errors in the profiles were found to be less than 5%. Measurements of five different clinical scanners demonstrate the variation in bow tie designs, indicating that generic bow tie models will not be adequate for CT system research.

Prostate Postimplant CT With Metal Artifacts Reduction for Improvement of Seed Localization

Low dose-rate brachytherapy involves the implantation of many (50-100) permanent radioactive seeds in and around the prostate volume. The standard dosimetry technique is based on computed tomography (CT) imaging, however, the CT images themselves suffer from metal artifacts due to the I-125 seeds, resulting in insufficient visualization of the I-125 seeds and prostate. Recently, some CT manufacturers unveiled the metal artifact reduction technique, which removes metal artifacts in images due to metallic implants in the body.

Model-based Iterative Reconstruction: A Promising Algorithm for Today's Computed Tomography Imaging

Because of its fast image acquisition and the rich diagnostic information it provides, computed tomography (CT) has gradually become a popular imaging modality among clinicians. Because CT scanners emit x-rays, the increased use of CT in clinical applications inevitably leads to increased medical radiation dose to the population. Because of the well-known cancer-inducing effects of high dose x-ray radiation, this increased dose has caused concerns among policy makers and general public that CT patients may be at a higher risk of developing cancer. Over the years, CT manufacturers have developed a variety of strategies to address this issue, the latest being a model-based iterative reconstruction (MBIR) algorithm. MBIR is an advanced CT algorithm that incorporates modeling of several key parameters that were omitted in earlier algorithms to reduce computational requirement and speed up scans. This review article examines the latest literature in the clinical CT field and discusses the general principles of MBIR, its dose and noise reduction potentials, its imaging characteristics, and its limitations. MBIR algorithm and its application in today's CT imaging will greatly reduce the radiation dose to patients and improve image quality for clinicians.

Assessment of the integrity of structural shielding of four computed tomography facilities in the greater ACCRA region of Ghana

The structural shielding thicknesses of the walls of four computed tomography (CT) facilities in Ghana were re-evaluated to verify the shielding integrity using the new shielding design methods recommended by the National Council on Radiological Protection and Measurements (NCRP). The shielding thickness obtained ranged from 120 to 155 mm using default DLP values proposed by the European Commission and 110 to 168 mm using derived DLP values from the four CT manufacturers. These values are within the accepted standard concrete wall thickness ranging from 102 to 152 mm prescribed by the NCRP. The ultrasonic pulse testing of all walls indicated that these are of good quality and free of voids since pulse velocities estimated were within the range of 3.496±0.005 km s(-1). An average dose equivalent rate estimated for supervised areas is 3.4±0.27 µSv week(-1) and that for the controlled area is 18.0±0.15 µSv week(-1), which are within acceptable values.

Medical Imaging Advocate Tackles Industry Challenges

BI&T Tell me about the Medical Imaging and Technology Alliance. David Fisher The Medical Imaging & Technology Alliance (MITA), a division of the National Electrical Manufacturers Association (NEMA), is the leading organization and collective voice of medical imaging equipment manufacturers, innovators, and product developers. It represents companies whose sales comprise more than 90 percent of the global market for medical imaging technology. The goals of MITA are to: • Increase the awareness and understanding of the value of medical imaging • Achieve efficient and reasonable regulation of medical imaging technologies • Interact with appropriate government agencies on reimbursement and technology assessment policies • Expand the global acceptance of the digital communications standard (DICOM) that allows digital imaging technologies to interact seamlessly • Improve regulatory harmonization of the global market for medical imaging products • Develop and represent industry positions in technical, trade and other issues • Provide market data unique to this industry