CT Protocol Optimization Research Articles

Survey of CT radiation doses and iodinated contrast medium administration: an international multicentric study.

To assess the relationship between intravenous iodinated contrast media (ICM) administration usage and radiation doses for contrast-enhanced (CE) CT of head, chest, and abdomen-pelvis (AP) in international, multicenter settings. Our international (n = 16 countries), multicenter (n = 43 sites), and cross-sectional (ConRad) study had two parts. Part 1: Redcap survey with questions on information related to CT and ICM manufacturer/brand and respective protocols. Part 2: Information on 3,258 patients (18-96 years; M:F 1654:1604) who underwent CECT for a routine head (n = 456), chest (n = 528), AP (n = 599), head CT angiography (n = 539), pulmonary embolism (n = 599), and liver CT examinations (n = 537) at 43 sites across five continents. The following information was recorded: hospital name, patient age, gender, body mass index [BMI], clinical indications, scan parameters (number of scan phases, kV), IV-contrast information (concentration, volume, flow rate, and delay), and dose indices (CTDIvol and DLP). Most routine chest (58.4%) and AP (68.7%) CECT exams were performed with 2-4 scan phases with fixed scan delay (chest 71.4%; AP 79.8%, liver CECT 50.7%) following ICM administration. Most sites did not change kV across different patients and scan phases; most CECT protocols were performed at 120-140 kV (83%, 1979/2685). There were no significant differences between radiation doses for non-contrast (CTDIvol 24 [16-30] mGy; DLP 633 [414-702] mGy·cm) and post-contrast phases (22 [19-27] mGy; 648 [392-694] mGy·cm) (p = 0.142). Sites that used bolus tracking for chest and AP CECT had lower CTDIvol than sites with fixed scan delays (p < 0.001). There was no correlation between BMI and CTDIvol (r2 ≤ - 0.1 to 0.1, p = 0.931). Our study demonstrates up to ten-fold variability in ICM injection protocols and radiation doses across different CT protocols. The study emphasizes the need for optimizing CT scanning and contrast protocols to reduce unnecessary contrast and radiation exposure to patients. The wide variability and lack of standardization of ICM media and radiation doses in CT protocols suggest the need for education and optimization of contrast usage and scan factors for optimizing image quality in CECT. There is a lack of patient-centric CT protocol optimization taking into consideration mainly patients' size. There is a lack of correlation between ICM volume and CT radiation dose across CT protocol. A ten-fold variation in iodine-load for the same CT protocol in sites suggests a lack of standardization.

Pre-TAVI imaging: an Italian survey by the CT PRotocol optimization (CT-PRO) group

PurposeThe purpose of this survey was to evaluate the current state-of-art of pre-TAVI imaging in a large radiological professional community.MethodsBetween December 2022 and January 2023 all members of the Italian Society of Medical and Interventional Radiology (SIRM) were invited by the CT PRotocol Optimization group (CT-PRO group) to complete an online 24-item questionnaire about pre-TAVI imaging.Results557 SIRM members participated in the survey. The greatest part of respondents were consultant radiologists employed in public hospitals and 84% claimed to routinely perform pre-TAVI imaging at their institutions. The most widespread acquisition protocol consisted of an ECG-gated CT angiography (CTA) scan of the aortic root and heart followed by a non-ECG-synchronized CTA of the thorax, abdomen, and pelvis. Contrast agent administration was generally tailored on the patient’s body weight with a preference for using high concentration contrast media. The reports were commonly written by radiologists with expertise in cardiovascular imaging, and included all the measurements suggested by current guidelines for adequate pre-procedural planning. About 60% of the subjects affirmed that the Heart Team is present at their institutions, however only 7% of the respondents regularly attended the multidisciplinary meetings.ConclusionsThis survey defines the current pre-TAVI imaging practice in a large radiological professional community. Interestingly, despite the majority of radiologists follow the current guidelines regarding acquisition and reporting of pre-TAVI imaging studies, there is still a noteworthy absence from multidisciplinary meetings and from the Heart Team.

Optimization of pediatric brain CT protocols

PurposeDue to the higher radiosensitivity of the tissues and the larger life expectancy in children than in adults, the present study presented the process of optimizing pediatric brain CT protocols, for the age groups 0 to 2 years, 3 to 5 years, and 6 to 12 years, evaluating the parameters of image acquisition and dose reduction, without loss of quality in image diagnostics. Methods: The CTDIvol index and DLP were verified in samples of routinely used protocols for patients in the age groups previously specified, as well as the image acquisition parameters. Based on these data, experimental protocols were developed and the contrast-to-noise ratios of the images produced were analyzed. The figure of merit (FOM) was used as a quality metric for quality analysis in comparison with CTDIvol and DLP levels. Results: The results showed a reduction in the CTDIvol index in the three studied protocols: 10.5% in the 0 to 2 years protocol, 33% in the 3 to 6 years protocol, and 16% in the 6 to 12 years protocol. DLP was also reduced by 14%, 41% and 25%, respectively, for the three age groups, in relation to previously used protocols. With regard to FOM, there were increases in quality of 6%, 19%, and 43%, respectively, for the three age groups. Conclusion: Considering the alteration of the image acquisition parameters, it was possible to achieve a dose reduction, without loss of diagnostic quality, according to the FOM metric.

Optimization of chest CT protocols based on pixel image matrix, kernels and iterative reconstruction levels – A phantom study

IntroductionThis study investigated the impact of high matrix image reconstruction in combination with different reconstruction kernels and levels of iterative reconstructions on image quality in chest CT. MethodsAn anthropomorphic chest phantom (Kyoto Kagaku Co., Ltd., Kyoto, Japan), and a Catphan® 600 (The Phantom Laboratory, Greenwich, NY, USA) phantom were scanned using a dual source scanner. Standard institutional protocol with 512 × 512 matrix was used as a reference. Reconstructions were performed for 768 × 768 and 1024 × 1024 matrices and all possible combinations of three different kernels and five levels of iterative reconstructions were included. Signal difference to noise ratio (SdNR) and line pairs per cm (lp/cm) were manually measured. A Linear regression model was applied for objective image analysis (SdNR) and inter–and intra-reader agreement was given as Cohen's kappa for the visual image assessment. ResultsMatrix size did not have a significant impact on SdNR (p = 0.595). Kernel (p = 0.014) and ADMIRE level (p = 0.001) had a statistically significant impact on SdNR. The spatial resolution ranged from 7 lp/cm to 9 lp/cm. The highest spatial resolution was achieved using kernel Br64 and ADMIRE 1, 2 and 3 in both 768- and 1024-matrices, and with Br59 with ADMIRE 2 and 4 and 768-matrix, all visualizing 9 lp/cm. Both readers scored kernel Br59 highest, and the scoring increased with increasing levels of Iterative Reconstruction. ConclusionMatrix size did not influence image quality, however, the choice of kernel and degree of IR had an impact on objective and visual image quality in 768 - and 1024-matrices, suggesting that increased degree of IR may improve diagnostic image quality in chest CT. Implications for practiceImage quality in CT of the lung may be improved by increasing the level of IR.

UNet and MobileNet CNN-based model observers for CT protocol optimization: comparative performance evaluation by means of phantom CT images.

The aim of this work is the development and characterization of a model observer (MO) based on convolutional neural networks (CNNs), trained to mimic human observers in image evaluation in terms of detection and localization of low-contrast objects in CT scans acquired on a reference phantom. The final goal is automatic image quality evaluation and CT protocol optimization to fulfill the ALARA principle. Preliminary work was carried out to collect localization confidence ratings of human observers for signal presence/absence from a dataset of 30,000 CT images acquired on a PolyMethyl MethAcrylate phantom containing inserts filled with iodinated contrast media at different concentrations. The collected data were used to generate the labels for the training of the artificial neural networks. We developed and compared two CNN architectures based respectively on Unet and MobileNetV2, specifically adapted to achieve the double tasks of classification and localization. The CNN evaluation was performed by computing the area under localization-ROC curve (LAUC) and accuracy metrics on the test dataset. The mean of absolute percentage error between the LAUC of the human observer and MO was found to be below 5% for the most significative test data subsets. An elevated inter-rater agreement was achieved in terms of S-statistics and other common statistical indices. Very good agreement was measured between the human observer and MO, as well as between the performance of the two algorithms. Therefore, this work is highly supportive of the feasibility of employing CNN-MO combined with a specifically designed phantom for CT protocol optimization programs.

Optimization of CT Protocols for Newborn Patients by Ingenuity 128, Philips. A Phantom Study

Purpose: To evaluate the impact of CT scan protocol parameters on patient dose and image quality for optimization of protocols for newborn patients.&#x0D; Materials and methods: Three anatomical areas (chest, abdomen and combined chest + abdomen area) of a newborn PH-50 Newborn Whole-Body Phantom (Kyoto Kagaku Co, LTD, Japan) were scanned on Ingenuity 128 CT scanner (Philips) using different scan parameters. The values of weighted CT dose index (CTDIvol) and dose length product (DLP) were used as dose characteristics and the noise of CT image was chosen to estimate the image quality. The noise was determined in the soft tissues in the areas of shoulder girdle and diaphragm in images with the reconstruction kernel B, as well as in lung tissue of lung apices for images with the reconstruction kernel YC for chest and chest + abdomen; and in soft tissues (for reconstruction kernel B) in the area of the diaphragm for abdomen.&#x0D; Results: The analysis of the impact of tube voltage and dose right index (DRI) on dose characteristics and image quality made it possible to determine the optimal parameters of CT protocols for selected CT department: chest – 80 kV at DRI -– 19, abdomen – 100 kV at DRI – 22, chest + abdomen – 120 kV at DRI – 22. These protocol parameters provide an effective dose of newborn patients – 1.4, 1.7 and 2,8 mSv for chest, abdomen and chest + abdomen scans, respectively.&#x0D; Conclusion: The impact of different scan parameters (tube voltage and DRI) of chest, abdomen and chest + abdomen protocols on patient dose and image noise was evaluated. The study allowed setting optimized protocol parameters to improve the image quality.

Deep Learning-based calculation of patient size and attenuation surrogates from localizer Image: Toward personalized chest CT protocol optimization

PurposeExtracting water equivalent diameter (DW), as a good descriptor of patient size, from the CT localizer before the spiral scan not only minimizes truncation errors due to the limited scan field-of-view but also enables prior size-specific dose estimation as well as scan protocol optimization. This study proposed a unified methodology to measure patient size, shape, and attenuation parameters from a 2D anterior-posterior localizer image using deep learning algorithms without the need for labor-intensive vendor-specific calibration procedures. Methods3D CT chest images and 2D localizers were collected for 4005 patients. A modified U-NET architecture was trained to predict the 3D CT images from their corresponding localizer scans. The algorithm was tested on 648 and 138 external cases with fixed and variable table height positions. To evaluate the performance of the prediction model, structural similarity index measure (SSIM), body area, body contour, Dice index, and water equivalent diameter (DW) were calculated and compared between the predicted 3D CT images and the ground truth (GT) images in a slicewise manner. ResultsThe average age of the patients included in this study (1827 male and 1554 female) was 53.8 ± 17.9 (18–120) years. The DW, tube current ,and CTDIvol measured on original axial images in the external 138 cases group were significantly larger than those of the external 648 cases (P < 0.05). The SSIM and Dice index calculated between the prediction and GT for body contour were 0.998 ± 0.001 and 0.950 ± 0.016, respectively. The average percentage error in the calculation of DW was 2.7 ± 3.5 %. The error in the DW calculation was more considerable in larger patients (p-value < 0.05). ConclusionsWe developed a model to predict the patient size, shape, and attenuation factors slice-by-slice prior to spiral scanning. The model exhibited remarkable robustness to table height variations. The estimated parameters are helpful for patient dose reduction and protocol optimization.

A Health System's Response to the Ongoing Global Shortage of Iodinated Contrast Media.

A production facility shutdown related to containment measures during the COVID-19 pandemic has resulted in a global shortage of iodinated contrast media. This article describes the strategies implemented at one large U.S. health system to maintain care continuity during the ongoing shortage. The strategies have included attempts to procure additional stock, repackage existing stock for use in larger numbers of patients, use noncontrast CT or alternative imaging modalities in place of contrast-enhanced CT, and collaborate with specialties outside of radiology to participate in conservation efforts. In addition, individual CT protocols underwent tailored modifications to use dual-energy technique and/or lower tube voltages, to allow lower contrast media doses with maintained visualization of tissue enhancement. The experiences during this period provide insights to facilitate long-term reductions in contrast media doses and ongoing CT protocol optimization after supplies return to normal levels. Critical throughout the efforts to mitigate the impact of the shortage have been system-level action, operational flexibility, and close communication by the health system's radiologists, technologists, physicists, pharmacists, and ordering providers.

Analysis of a monocentric computed tomography dosimetric database using a radiation dose index monitoring software: dose levels and alerts before and after the implementation of the adaptive statistical iterative reconstruction on CT images.

To analyze dosimetric data of a single center by a radiation dose index monitoring software evaluating quantitatively the dose reduction obtained with the implementation of the adaptive statistical iterative reconstruction (ASIR) on Computed Tomography in terms of both the value of the dose length product (DLP) and the alerts provided by the dose tool. Dosimetric quantities were acquired using Qaelum DOSE tool (QAELUM NV, Leuven-Heverlee, Belgium). Dose data pertaining to CT examinations were performed using a General Electric Healthcare CT tomography with 64 detectors. CT dose data were collected over 4years (January 1, 2017 to December 31, 2020) and included CT dose length product (DLP). Moreover, all CT examinations that triggered a high radiation dose (twice the median for that study description), termed alerts on Dose tool, were retrieved for the analysis. Two radiologists retrospectively assessed CT examinations in consensus for the images quality and for the causes of the alerts issued. A Chi-square test was used to assess whether there were any statistically significant differences among categorical variable while a Kruskal Wallis test was considered to assess differences statistically significant for continuous variables. Differences statistically significant were found for the DLP median values between the dosimetric data recorded on 2017-2018 versus 2019-2020. The differences were linked to the implementation of ASIR technique at the end of 2018 on the CT scanner. The highest percentage of alerts was reported in the CT study group "COMPLETE ABDOMEN + CHEST + HEAD" (range from 1.26% to 2.14%). A reduction year for year was relieved linked to the CT protocol optimization with a difference statistically significant. The highest percentage of alerts was linked to wrong study label/wrong study protocol selection with a range from 29 to 40%. Automated methods of radiation dose data collection allowed for detailed radiation dose analysis according to protocol and equipment over time. The use of CT ASIR technique could determine considerable reduction in radiation dose.

Toward a comparison and an optimization of CT protocols using new metrics of dose and image quality part I: prediction of human observers using a model observer for detection and discrimination tasks in low-dose CT images in various scanning conditions

In the context of reducing the patient dose coming from CT scanner examinations without penalizing the diagnosis, the assessment of both patient dose and image quality (IQ) with relevant metrics is crucial. The present study represents the first stage in a larger work, aiming to compare and optimize CT protocols using dose and IQ new metrics. We proposed here to evaluate the capacity of the Non-PreWhitening matched filter with an eye (NPWE) model observer to be a robust and accurate estimation of IQ. We focused our work on two types of clinical tasks: a low contrast detection task and a discrimination task. We designed a torso-shaped phantom, including Plastic Water® slabs with cylindrical inserts of different diameters, sections and compositions. We led a human observer study with 13 human observers on images acquired in multiple irradiation and reconstruction scanning conditions (voltage, pitch, slice thickness, noise level of the reconstruction algorithm, energy level in dual-energy mode and dose), to evaluate the behavior of the model observer compared to the human responses faced to changing conditions. The model observer presented the same trends as the human observers with generally better results. We rescaled the NPWE model on the human responses by scanning conditions (kVp, pitch, slice thickness) to obtain the best agreement between both observer types, estimated using the Bland-Altman method. The impact of some scanning parameters was estimated using the correct answer rate given by the rescaled NPWE model, for both tasks and each insert size. In particular, the comparison between the dual-energy mode at 74 keV and the single-energy mode at 120 kVp showed that, if the 120 kVp voltage provided better results for the smallest insert at the lower doses for both tasks, their responses were equivalent in many cases.

A Web-Based Software Platform for Efficient and Quantitative CT Image Quality Assessment and Protocol Optimization.

Channelized Hotelling observer (CHO), which has been shown to be well correlated with human observer performance in many clinical CT tasks, has a great potential to become the method of choice for objective image quality assessment. However, the use of CHO in clinical CT is still quite limited, mainly due to its complexity in measurement and calculation in practice, and the lack of access to an efficient and validated software tool for most clinical users. In this work, a web-based software platform for CT image quality assessment and protocol optimization (CTPro) was introduced. A validated CHO tool, along with other common image quality assessment tools, was made readily accessible through this web platform for clinical users and researchers without the need of installing additional software. An example of its application to evaluation of convolutional-neural-network (CNN)-based denoising was demonstrated.

Chest CT in COVID-19: What the Radiologist Needs to Know.

Chest CT has a potential role in the diagnosis, detection of complications, and prognostication of coronavirus disease 2019 (COVID-19). Implementation of appropriate precautionary safety measures, chest CT protocol optimization, and a standardized reporting system based on the pulmonary findings in this disease will enhance the clinical utility of chest CT. However, chest CT examinations may lead to both false-negative and false-positive results. Furthermore, the added value of chest CT in diagnostic decision making is dependent on several dynamic variables, most notably available resources (real-time reverse transcription–polymerase chain reaction [RT-PCR] tests, personal protective equipment, CT scanners, hospital and radiology personnel availability, and isolation room capacity) and the prevalence of both COVID-19 and other diseases with overlapping manifestations at chest CT. Chest CT is valuable to detect both alternative diagnoses and complications of COVID-19 (acute respiratory distress syndrome, pulmonary embolism, and heart failure), while its role for prognostication requires further investigation. The authors describe imaging and managing care of patients with COVID-19, with topics including (a) chest CT protocol, (b) chest CT findings of COVID-19 and its complications, (c) the diagnostic accuracy of chest CT and its role in diagnostic decision making and prognostication, and (d) reporting and communicating chest CT findings. The authors also review other specific topics, including the pathophysiology and clinical manifestations of COVID-19, the World Health Organization case definition, the value of performing RT-PCR tests, and the radiology department and personnel impact related to performing chest CT in COVID-19.©RSNA, 2020

Chest CT practice and protocols for COVID-19 from radiation dose management perspective.

The global pandemic of coronavirus disease 2019 (COVID-19) has upended the world with over 6.6 million infections and over 391,000 deaths worldwide. Reverse-transcription polymerase chain reaction (RT-PCR) assay is the preferred method of diagnosis of COVID-19 infection. Yet, chest CT is often used in patients with known or suspected COVID-19 due to regional preferences, lack of availability of PCR assays, and false-negative PCR assays, as well as for monitoring of disease progression, complications, and treatment response. The International Atomic Energy Agency (IAEA) organized a webinar to discuss CT practice and protocol optimization from a radiation protection perspective on April 9, 2020, and surveyed participants from five continents. We review important aspects of CT in COVID-19 infection from the justification of its use to specific scan protocols for optimizing radiation dose and diagnostic information. Key Points • Chest CT provides useful information in patients with moderate to severe COVID-19 pneumonia. • When indicated, chest CT in most patients with COVID-19 pneumonia must be performed with non-contrast, low-dose protocol. • Although chest CT has high sensitivity for diagnosis of COVID-19 pneumonia, CT findings are non-specific and overlap with other viral infections including influenza and H1N1.

A Comprehensive CT Radiation Dose Reduction and Protocol Standardization Program in a Complex, Tertiary Hospital System

PurposeTo present our experience in reducing CT radiation doses in a complex tertiary health system through CT protocol standardization and optimization. MethodsA CT radiation task force was created to reduce CT protocol heterogeneity and radiation doses. Redundant protocols were eliminated. By an iterative process, protocols with least radiation dose were identified. Radiation dose tracking software was used to store and analyze radiation doses. CT protocols were published in an intranet site after training of technologists. SOPs were established for maintaining and changing protocols. The radiation doses for each CT protocol before and after optimization were compared using geometric means. ResultsA total of 222 CT protocols were reviewed, with elimination of 86 protocols. One-year follow-up showed homogeneous protocols with lower radiation doses. The improvement in radiation doses ranged from 23% to 58% (P< 0.001). ConclusionCT radiation dose reduction of up to 58% can be achieved by homogenizing and optimizing CT protocols through a comprehensive CT operations program.

CT Protocol Optimization in Trauma Imaging: A Review of Current Evidence

Trauma constitutes a social and a clinical problem. The CT protocol to be adopted in polytrauma patients is still not standardized across institutions. A variety of protocols can be found in the available literature, which differ from each other in timing acquisition and number of phases. Even if multiple recent studies are investigating the role of split bolus technique, multiphasic protocol has been shown to be associated with early detection and adequate characterization of vascular injuries, so it should be still considered as the “best” CT protocol for the assessment of high-energy trauma patients. The article provides a review on the currently available literature on the CT protocols adopted in polytraumatized patients.

Patient-Specific Organ and Effective Dose Estimates in Adult Oncologic CT.

OBJECTIVE. Patient-specific organ and effective dose provides essential information for CT protocol optimization. However, such information is not readily available in the scan records. The purpose of this study was to develop a method to obtain accurate examination- and patient-specific organ and effective dose estimates by use of available scan data and patient body size information for a large cohort of patients. MATERIALS AND METHODS. The data were randomly collected for 1200 patients who underwent CT in a 2-year period. Physical characteristics of the patients and CT technique were processed as inputs for the dose estimator. Organ and effective doses were estimated by use of the inputs and computational human phantoms matched to patients on the basis of sex and effective diameter. Size-based ratios were applied to correct for patient-phantom body size differences. RESULTS. Patients received a mean of 59.9 mGy to the lens of the eye per brain scan, 10.1 mGy to the thyroid per chest scan, 17.5 mGy to the liver per abdomen and pelvis scan, and 19.0 mGy to the liver per body scan. A factor of 2 difference in dose estimates was observed between patients of various habitus. CONCLUSION. Examination- and patient-specific organ and effective doses were estimated for 1200 adult oncology patients undergoing CT. The dose conversion factors calculated facilitate rapid organ and effective dose estimation in clinics. Compared with nonspecific dose estimation methods, patient dose estimations with data specific to the patient and examination can differ by a factor of 2.

Radiation dosimetry changes in radiotherapy treatment plans for adult patients arising from the selection of the CT image reconstruction kernel.

Objective:The reconstruction kernel used for a CT scan strongly influences the image quality. This work investigates the changes in Hounsfield units (HUs) which can arise when altering the image reconstruction kernel for planning CT images and the associated changes in dose in the radiotherapy treatment plan if the treatment planning system (TPS) is not re-calibrated.Methods:Head and neck, prostate and lung CT images from four centres were used. For a specific scan, the base image was acquired using the original reconstruction kernel (used when the TPS was calibrated) and the treatment plan produced. The treatment plan was applied to all images from the other reconstruction kernels. Differences in dose-volume metrics for the planning target volume (PTV) and organs at risk (OARs) were noted and HU differences between images measured for air, soft tissue and bone.Results: HU change in soft tissue had the greatest influence on dose change. When within ±20 HU for soft tissue and ±50 HU for bone and air the dose change in the PTV and OAR was within ±0.5% and ±1% respectively.Conclusions: When imaging parameters were changed, if HU change was within ±20 HU for soft tissue and ±50 HU for bone and air, the change in the PTV and OAR doses was below 1%.Advances in knowledge:The degree of dose change in the treatment plan with HU change is demonstrated for current TPS algorithms. This adds to the limited evidence base for recommendations on HU tolerances as a tool for radiotherapy CT protocol optimization.

Radiation Dose and Image Quality in Pediatric Neck CT

Optimization of pediatric neck CT protocols is of critical importance in order to maintain good diagnostic image quality while reducing the radiation burden. Our aim was to evaluate the image quality of pediatric neck CT studies before and after the implementation of a low radiation dose protocol. We retrospectively reviewed 179 pediatric neck CT studies, 75 before and 104 after the implementation of low-dose protocols, performed in children 0-16 years of age. The 2 cohorts were divided into 3 age groups, 0-4, 5-9, and 10-16 years. The signal-to-noise ratio was calculated using the axial image through the true vocal folds. Three neuroradiologists assessed the image quality of the same CT scan using a 5-point scoring system. We compared the CT dose index volume, dose-length product, image-quality ratings, and SNR of studies conducted at baseline and with low-dose protocols. Image-quality ratings were lower in the low-dose than in the baseline cohort in children 10-16 years of age, but not in children 0-4 and 5-9 years of age. The SNR was lower in the low-dose cohort than in the baseline cohort in children 0-4 and 10-16 years of age, but not in children 5-9 years of age. Despite the decrease in image-quality scores in older children, 97% of the studies (73/75) in the baseline cohort and 96% of studies (100/104) in the low-dose cohort were considered of sufficient image quality. Images acquired with the low-dose CT protocols were deemed to be of sufficient quality for making a clinical diagnosis. Our initial results suggest that there may be an opportunity for further radiation dose reduction without compromising diagnostic image quality using iterative reconstruction algorithms.

DukeSim: A Realistic, Rapid, and Scanner-Specific Simulation Framework in Computed Tomography.

The purpose of this study was to develop a CT simulation platform that is: 1) compatible with voxel-based computational phantoms; 2) capable of modeling the geometry and physics of commercial CT scanners; and 3) computationally efficient. Such a simulation platform is designed to enable the virtual evaluation and optimization of CT protocols and parameters for achieving a targeted image quality while reducing radiation dose. Given a voxelized computational phantom and a parameter file describing the desired scanner and protocol, the developed platform DukeSim calculates projection images using a combination of ray-tracing and Monte Carlo techniques. DukeSim includes detailed models for the detector quantum efficiency, quantum and electronic noise, detector crosstalk, subsampling of the detector and focal spot areas, focal spot wobbling, and the bowtie filter. DukeSim was accelerated using GPU computing. The platform was validated using physical and computational versions of a phantom (Mercury phantom). Clinical and simulated CT scans of the phantom were acquired at multiple dose levels using a commercial CT scanner (Somatom Definition Flash; Siemens Healthcare). The real and simulated images were compared in terms of image contrast, noise magnitude, noise texture, and spatial resolution. The relative error between the clinical and simulated images was less than 1.4%, 0.5%, 2.6%, and 3%, for image contrast, noise magnitude, noise texture, and spatial resolution, respectively, demonstrating the high realism of DukeSim. The runtime, dependent on the imaging task and the hardware, was approximately 2-3 minutes per rotation in our study using a computer with 4 GPUs. DukeSim, when combined with realistic human phantoms, provides the necessary toolset with which to perform large-scale and realistic virtual clinical trials in a patient and scanner-specific manner.

Optimization of CT protocols using cause-and-effect analysis of outliers

The aim of this study was to implement an outlier marking and analysis methodology to optimize CT examination protocols.CT Head examination data, including dose metrics along with technical parameters, were stored in an automatic dose registry system. Reference dose metrics distribution was obtained throughout a 1-year period. Outlier thresholds were calculated taking into account the specific shape of the distribution, by using a robust measure of the skewness; the medcouple parameter. Subsequently, outliers from a 4-month period were marked and Cause-and-Effect analysis was carried out by a multidisciplinary dose committee.Reference Dose metrics distributions were obtained from 3690 CT Head examinations. Both CTDIvol and DLP showed a certain degree of skewness, with a medcouple value of 0.05 and 0.11, respectively. All of the upper-outliers fell within 3 identifiable groups of causes, ordered by relative importance: i) inadequate protocol selection, ii) arms or objects in the field-of-view, and iii) abnormal scanning region diameter. Regarding the lower-outliers, 90% were attributable to the inclusion of additional series in the original head protocol and the remaining 10% to unknown causes. Also, a general Cause-and-Effect diagram for outliers was elaborated.While the Dose Reference Level method applies to the general performance of a CT protocol and allows comparison with other centers, the outlier method represents a step further in the optimization process. The proposed method focuses on detecting incorrect utilization of the CT, which mainly arises from inadequate knowledge of CT technology.