Computed Tomography Acquisition Parameters Research Articles

Opportunistic Screening With CT: Comparison of Phantomless BMD Calibration Methods.

Opportunistic screening is a new promising technique to identify individuals at high risk for osteoporotic fracture using computed tomography (CT) scans originally acquired for an clinical purpose unrelated to osteoporosis. In these CT scans, a calibration phantom traditionally required to convert measured CT values to bone mineral density (BMD) is missing. As an alternative, phantomless calibration has been developed. This study aimed to review the principles of four existing phantomless calibration methods and to compare their performance against the gold standard of simultaneous calibration (ΔBMD). All methods were applied to a dataset of 350 females scanned with a highly standardized CT protocol (DS1) and to a second dataset of 114 patients (38 female) from clinical routine covering a large range of CT acquisition and reconstruction parameters (DS2). Three of the phantomless calibration methods must be precalibrated with a reference dataset containing a calibration phantom. Sixty scans from DS1 and 57 from DS2 were randomly selected for this precalibration. For each phantomless calibration method first the best combination of internal reference materials (IMs) was selected. These were either air and blood or subcutaneous adipose tissue, blood, and cortical bone. In addition, for phantomless calibration a fifth method based on average calibration parameters derived from the reference dataset was applied. For DS1, ΔBMD results (mean standard deviation) for the phantomless calibration methods requiring a precalibration ranged from 0.1 2.7 mg/cm3 to 2.4 3.5 mg/cm3 with similar means but significantly higher standard deviations for DS2. Performance of the phantomless calibration method, which does not require a precalibration was worse (ΔBMD DS1: 12.6 13.2 mg/cm3 , DS2: 0.5 8.8 mg/cm3 ). In conclusion, phantomless BMD calibration performs well if precalibrated with a reference dataset. © 2023 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).

A customized anthropomorphic 3D-printed phantom to reproducibility assessment in computed tomography: an oncological case study.

Studies on computed tomography (CT) reproducibility at different acquisition parameters have to take into account radiation dose administered and related ethical issues. 3D-printed phantoms provide the possibility to investigate these features deeply and to foster CT research, also taking advantage by outperforming new generation scanners. The aim of this study is to propose a new anthropomorphic 3D-printed phantom for chest lesions, tailored on a real patient CT scan, to investigate the variability of volume and Hounsfield Unit (HU) measurements at different CT acquisition parameters. The chest CT of a 75-year-old patient with a paramediastinal lung lesion was segmented based on an eight-compartment approach related to HU ranges (air lung, lung interstitium, fat, muscle, vascular, skin, bone, and lesion). From each mask produced, the 3D.stl model was exported and linked to a different printing infill value, based on a preliminary test and HU ratios derived from the patient scan. Fused deposition modeling (FDM) technology printing was chosen with filament materials in polylactic acid (PLA). Phantom was acquired at 50 mAs and three different tube voltages of 80, 100, and 120 kVp on two different scanners, namely, Siemens Somatom Force (Siemens Healthineers, Erlangen, Germany; same setting of real patient for 80 kVp acquisition) and GE 750 HD CT (GE Healthcare, Chicago, IL). The same segmentation workflow was then applied on each phantom acquisition after coregistration pipeline, and Dice Similarity Coefficient (DSC) and HU averages were extracted and compared for each compartment. DSC comparison among real patient versus phantom scans at different kVp, and on both CT scanners, demonstrated a good overlap of different compartments and lesion vascularization with a higher similarity for lung and lesion masks for each setting (about 0.9 and 0.8, respectively). Although mean HU was not comparable with real data, due to the PLA material, the proportion of intensity values for each compartment remains respected. The proposed approach demonstrated the reliability of 3D-printed technology for personalized approaches in CT research, opening to the application of the same workflow to other oncological fields.

Beam filtration for object-tailored X-ray CT of multi-material cultural heritage objects

Computed tomography (CT) is a powerful non-invasive tool to analyze cultural heritage objects by allowing museum professionals to obtain 3D information about the objects’ interior. These insights can help with the conservation or restoration of the objects, as well as provide contextual information on the objects’ history or making process. Cultural heritage objects exist in a wide variety and have characteristics which present challenges for CT scanning: multi-scale internal features, a diversity of sizes and shapes, and multi-material objects. Because X-ray absorption is related to the density, thickness of the material, and atomic composition, the challenges are greater when the object consists of multiple different materials with varying densities. This is especially true for cases with extreme density contrasts such as that between metals and textiles. An untailored acquisition of CT scans of multi-material objects can lead to reduced image quality and heavy visual errors called image artifacts, which can influence the perception or representation of information. A tailored acquisition can reduce these artifacts and lead to a higher information gain. In this work, we firstly discuss how the X-ray beam properties and the beam-object interaction influence CT image formation and how to use filters to manipulate the emitted X-ray beam to improve image quality for multi-material objects. We showcase that this can be achieved with limited resources in a low-cost DIY fashion with thin sheets of metal as filters, 3D-printed filter frames and a filter holder. Secondly, we give a qualitative analysis of the influence of the CT acquisition parameters illustrated with two case study objects from the textile collection of the Rijksmuseum, Amsterdam, The Netherlands. With this we provide insights and intuitions on tailoring the CT scan to the cultural heritage objects. Thirdly, we extract a general concept of steps for museum professionals to design an object-tailored CT scan for individual cases.

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.

The impact of CT image parameters and skull heterogeneity modeling on the accuracy of transcranial focused ultrasound simulations

Objective. Low-intensity transcranial ultrasound stimulation (TUS) is a promising non-invasive brain stimulation (NIBS) technique. TUS can reach deeper areas and target smaller regions in the brain than other NIBS techniques, but its application in humans is hampered by the lack of a straightforward and reliable procedure to predict the induced ultrasound exposure. Here, we examined how skull modeling affects computer simulations of TUS. Approach. We characterized the ultrasonic beam after transmission through a sheep skull with a hydrophone and performed computed tomography (CT) image-based simulations of the experimental setup. To study the skull model’s impact, we varied: CT acquisition parameters (tube voltage, dose, filter sharpness), image interpolation, segmentation parameters, acoustic property maps (speed-of-sound, density, attenuation), and transducer-position mismatches. We compared the impact of modeling parameter changes on model predictions and on measurement agreement. Spatial-peak intensity and location, total power, and the Gamma metric (a measure for distribution differences) were used as quantitative criteria. Modeling-based sensitivity analysis was also performed for two human head models. Main results. Sheep skull attenuation assignment and transducer positioning had the most important impact on spatial peak intensity (overestimation up to 300%, respectively 30%), followed by filter sharpness and tube voltage (up to 20%), requiring calibration of the mapping functions. Positioning and skull-heterogeneity-structure strongly affected the intensity distribution (gamma tolerances exceeded in 80%, respectively 150%, of the focus-volume in water), necessitating image-based personalized modeling. Simulation results in human models consistently demonstrate a high sensitivity to the skull-heterogeneity model, attenuation tuning, and transducer shifts, the magnitude of which depends on the underlying skull structure complexity. Significance. Our study reveals the importance of properly modeling the skull-heterogeneity and its structure and of accurately reproducing the transducer position. The results raise red flags when translating modeling approaches among clinical sites without proper standardization and/or recalibration of the imaging and modeling parameters.

Impact of slice thickness, pixel size, and CT dose on the performance of automatic contouring algorithms.

PurposeTo investigate the impact of computed tomography (CT) image acquisition and reconstruction parameters, including slice thickness, pixel size, and dose, on automatic contouring algorithms.MethodsEleven scans from patients with head‐and‐neck cancer were reconstructed with varying slice thicknesses and pixel sizes. CT dose was varied by adding noise using low‐dose simulation software. The impact of these imaging parameters on two in‐house auto‐contouring algorithms, one convolutional neural network (CNN)‐based and one multiatlas‐based system (MACS) was investigated for 183 reconstructed scans. For each algorithm, auto‐contours for organs‐at‐risk were compared with auto‐contours from scans with 3 mm slice thickness, 0.977 mm pixel size, and 100% CT dose using Dice similarity coefficient (DSC), Hausdorff distance (HD), and mean surface distance (MSD).ResultsIncreasing the slice thickness from baseline value of 3 mm gave a progressive reduction in DSC and an increase in HD and MSD on average for all structures. Reducing the CT dose only had a relatively minimal effect on DSC and HD. The rate of change with respect to dose for both auto‐contouring methods is approximately 0. Changes in pixel size had a small effect on DSC and HD for CNN‐based auto‐contouring with differences in DSC being within 0.07. Small structures had larger deviations from the baseline values than large structures for DSC. The relative differences in HD and MSD between the large and small structures were small.ConclusionsAuto‐contours can deviate substantially with changes in CT acquisition and reconstruction parameters, especially slice thickness and pixel size. The CNN was less sensitive to changes in pixel size, and dose levels than the MACS. The results contraindicated more restrictive values for the parameters should be used than a typical imaging protocol for head‐and‐neck.

Dose Optimization of Hybrid Imaging.

Hybrid imaging combines the functional and molecular imaging of positron emission computed tomography and single-photon emission computed tomography with the anatomical information available from computed tomography and magnetic resonance imaging. As a result, the clinical utility of positron emission computed tomography/computed tomography and single-photon emission computed tomography/computed tomography has been clearly established in the past 17 y. In addition, the use of positron emission computed tomography/magnetic resonance, which was introduced to the clinic in the past decade, has continued to grow. These multimodality approaches to medical imaging have substantial dosimetric aspects associated with their practice in both adults and children. For positron emission computed tomography/computed tomography and single-photon emission computed tomography/computed tomography, one must consider the radiation dose delivered from both the radiopharmaceutical and the computed tomography portion of the hybrid scan. Whether the computed tomography is to be used solely for attenuation correction, anatomical correlation of patient, or full diagnosis must be taken into account when deciding on the computed tomography acquisition parameters. Even after 17 y, the most appropriate approach to the acquisition of these modalities is not fully established. When appropriately used, positron emission computed tomography/magnetic resonance provides the opportunity for notable dose reduction. In addition to the elimination of the radiation dose from the computed tomography, one may consider the higher sensitivity of the positron emission computed tomography component relative to that used in positron emission computed tomography/computed tomography and the longer acquisition time to reduce the amount of administered activity of the radiopharmaceutical. However, one must realize that magnetic resonance presents a different set of safety concerns outside of those associated with ionizing radiation. As with all medical procedures, the benefits as well as the potential risks of the procedure need to be evaluated in the context of choosing the most appropriate procedure to be performed and the optimization of acquisition protocol to assure high-quality clinical information with the least potential for risk possible.

Experimental assessment on feasibility of computed tomography-based thermometry for radiofrequency ablation on tissue equivalent polyacrylamide phantom

Purpose: This study aimed to evaluate the effects of various computed tomography (CT) acquisition parameters and metal artifacts on CT number measurement for CT thermometry during CT-guided thermal ablation.Methods: The effects of tube voltage (100–140 kVp), tube current (20–250 mAs), pitch (0.6–1.5) and gantry rotation time (0.5, 1.0 s) as well as metal artifacts from a radiofrequency ablation (RFA) needle on CT number were evaluated using liver tissue equivalent polyacrylamide (PAA) phantom. The correlation between CT number and temperature from 37 to 80 °C was studied on PAA phantom using optimum CT acquisition parameters.Results: No statistical significant difference (p > 0.05) was found on CT numbers under the variation of different acquisition parameters for the same temperature setting. On the other hand, the RFA needle has induced metal artifacts on the CT images of up to 8 mm. The CT numbers decreased linearly when the phantom temperature increased from 37 to 80 °C. A linear regression analysis on the CT numbers and temperature suggested that the CT thermal sensitivity was –0.521 ± 0.061 HU/°C (R2 = 0.998).Conclusion: CT thermometry is feasible for temperature assessment during RFA with the current CT technology, which produced a high CT number reproducibility and stable measurement at different CT acquisition parameters. Despite being affected by metal artifacts, the CT-based thermometry could be further developed as a tissue temperature monitoring tool during CT-guided thermal ablation.

Radiomics of CT Features May Be Nonreproducible and Redundant: Influence of CT Acquisition Parameters

Purpose To identify the reproducible and nonredundant radiomics features (RFs) for computed tomography (CT). Materials and Methods Two phantoms were used to test RF reproducibility by using test-retest analysis, by changing the CT acquisition parameters (hereafter, intra-CT analysis), and by comparing five different scanners with the same CT parameters (hereafter, inter-CT analysis). Reproducible RFs were selected by using the concordance correlation coefficient (as a measure of the agreement between variables) and the coefficient of variation (defined as the ratio of the standard deviation to the mean). Redundant features were grouped by using hierarchical cluster analysis. Results A total of 177 RFs including intensity, shape, and texture features were evaluated. The test-retest analysis showed that 91% (161 of 177) of the RFs were reproducible according to concordance correlation coefficient. Reproducibility of intra-CT RFs, based on coefficient of variation, ranged from 89.3% (151 of 177) to 43.1% (76 of 177) where the pitch factor and the reconstruction kernel were modified, respectively. Reproducibility of inter-CT RFs, based on coefficient of variation, also showed large material differences, from 85.3% (151 of 177; wood) to only 15.8% (28 of 177; polyurethane). Ten clusters were identified after the hierarchical cluster analysis and one RF per cluster was chosen as representative. Conclusion Many RFs were redundant and nonreproducible. If all the CT parameters are fixed except field of view, tube voltage, and milliamperage, then the information provided by the analyzed RFs can be summarized in only 10 RFs (each representing a cluster) because of redundancy.

Effect of varying computed tomography acquisition and reconstruction parameters on semi-automated clot volume quantification.

AIMTo examine effects of computed tomography (CT) image acquisition/reconstruction parameters on clot volume quantification in vitro for research method validation purposes.METHODSThis study was performed in conformance with HIPAA and IRB Regulations (March 2015-November 2016). A ten blood clot phantom was designed and scanned on a dual-energy CT scanner (SOMATOM Force, Siemens Healthcare GmBH, Erlangen, Germany) with varying pitch, iterative reconstruction, energy level and slice thickness. A range of clot and tube sizes were used in an attempt to replicate in vivo emboli found within central and segmental branches of the pulmonary arteries in patients with pulmonary emboli. Clot volume was the measured parameter and was analyzed by a single image analyst using a semi-automated region growing algorithm implemented in the FDA-approved Siemens syngo.via image analysis platform. Mixed model analysis was performed on the data.RESULTSOn the acquisition side, the continuous factor of energy showed no statistically significant effect on absolute clot volume quantification (P = 0.9898). On the other hand, when considering the fixed factor of pitch, there were statistically significant differences in clot volume quantification (P < 0.0001). On the reconstruction side, with the continuous factor of reconstruction slice thickness no statistically significant effect on absolute clot volume quantification was demonstrated (P = 0.4500). Also on the reconstruction side, with the fixed factor of using iterative reconstructions there was also no statistically significant effect on absolute clot volume quantification (P = 0.3011). In addition, there was excellent R2 correlation between the scale-measured mass of the clots both with respect to the CT measured volumes and with respect to volumes measure by the water displacement method.CONCLUSIONAside from varying pitch, changing CT acquisition parameters and using iterative reconstructions had no significant impact on clot volume quantification with a semi-automated region growing algorithm.

Quantification of abdominal aortic calcification: Inherent measurement errors in current computed tomography imaging.

ObjectiveQuantification software for coronary calcification is often used to measure abdominal aortic calcification on computed tomography (CT) images. However, there is no evidence substantiating the reliability and accuracy of these tools in this setting. Differences in coronary and abdominal CT acquisition and presence of intravascular contrast may affect the results of these tools. Therefore, this study investigates the effects of CT acquisition parameters and iodine contrast on automated quantification of aortic calcium on CT.MethodsCalcium scores, provided in volume and mass, were assessed by automated calcium quantification software on CT scans. First, differences in calcium scores between the abdominal and coronary CT scanning protocols were assessed by imaging a thorax phantom containing calcifications of 9 metrical variations. Second, aortic calcification was quantified in 50 unenhanced and contrast-enhanced clinical abdominal CT scans at a calcification threshold of 299 Hounsfield Units (HU). Also, the lowest possible HU threshold for calcifications was calculated per individual patient and compared to a 130 HU threshold between contrast-enhanced and unenhanced CT images, respectively.ResultsNo significant differences in volume and mass scores between the abdominal and the coronary CT protocol were found. However, volume and mass of all calcifications were overestimated compared to the physical volume and mass (volume range: 0–649%; mass range: 0–2619%). In comparing unenhanced versus contrast-enhanced CT images showed significant volume differences for both thresholds, as well as for mass differences for the 130 vs patient-specific threshold (230 ± 22.6 HU).ConclusionCalcification scoring on CT angiography tends to grossly overestimate volume and mass suggesting a low accuracy and reliability. These are reduced further by interference of intravascular contrast. Future studies applying calcium quantification tools on CT angiography imaging should acknowledge these issues and apply corrective measures to ensure the validity of their outcomes.

Influence of CT acquisition and reconstruction parameters on radiomic feature reproducibility.

High-dimensional imaging features extracted from diagnostic imaging, called radiomics, are increasingly reported for diagnosis, prognosis, and response to therapy. Establishing the sensitivity of radiomic features to variation in scan protocols is necessary because acquisition and reconstruction parameters can vary widely across and within institutions. Our objective was to assess the reproducibility of radiomic features derived from computed tomography (CT) images by varying tube current (mA), noise index, and reconstruction [adaptive statistical iterative reconstruction (ASiR)], parameters increasingly varied by institutions seeking to reduce radiation dose in their patients. We extracted radiomic features from CT images of a uniform water phantom, anthropomorphic phantom, and a human scan. Scans were acquired from the phantoms with six tube currents (50, 100, 200, 300, 400, and 500mA) and five noise index levels (12, 14, 16, 18, and 20), respectively. Scans of the phantoms and patient were reconstructed from 0% ASiR (i.e., filtered back projection) to 100% ASiR in increments of 10%. Two hundred and forty-eight well-known radiomic features were extracted from all scans. The concordance correlation coefficient was used to assess agreement of features. Our analysis suggests that image acquisition parameters (tube current, noise index) as well as the reconstruction technique strongly influence radiomic feature reproducibility and demonstrate a subset of reproducible features potentially usable in clinical practice.

Effect of CT acquisition parameters of spiral CT on image quality and radiation dose

Abstract Additive Manufacturing (AM) is the most advanced manufacturing process in medical and dental industry. Computed Tomography (CT) images are the primary source to fabricate the medical models. Spiral CT scanner captures larger volume tissue in a short scan time. The major defects that appear in CT image acquisition process are Beam Hardening (BH), image noise and radiation dose. Tube voltage, tube current and pitch are the major parameters for CT image acquisition. In the present work, an attempt has been made to investigate the effect of various CT image acquisition parameters in the CT image acquisition of dry mandible phantom. A Taguchi L9 orthogonal array was used for experimental plan. The scanning defects of BH artifact and image noise were calculated by using Beam Hardening Correction Factor (BHCF) and the standard deviation of X- ray photons in the voxel respectively. Similarly radiation dose was measured with CT Dose Index volume (CTDIvolume). Grey Relational Analysis (GRA) method is used to optimize the CT image acquisition parameters, resulting increase in quality of CT images with less radiation dose. It was found that the image defects were less at optimal parameters found from GRA method compared to default image acquisition parameters.

Radiation dose in cardiac SPECT/CT: An estimation of SSDE and effective dose

AimsThe dose levels for Computed Tomography (CT) localization and attenuation correction of Single Photon Emission Computed Tomography (SPECT) are limited and reported as Volume Computed Tomography Dose Index (CTDIvol) and Dose-Length Product (DLP). This work presents CT dose estimation from Cardiac SPECT/CT based on new American Association of Physicists in Medicine (AAPM) Size Specific Dose Estimation (SSDE) parameter, effective dose, organ doses and also emission dose from nuclear issue. Material and methodsMyocardial perfusion SPECT/CT for 509 patients was included in the study. SSDE, effective dose and organ dose were calculated using AAPM guideline and Impact-Dose software. Data were analyzed using R and SPSS statistical software. Spearman-Pearson correlation test and linear regression models were used for finding correlations and relationships among parameters. ResultsThe mean CTDIvol was 1.34 mGy±0.19 and the mean SSDE was 1.7 mGy±0.16. The mean±SD of effective dose from emission, CT and total dose were 11.5±1.4, 0.49±0.11 and 12.67±1.73 (mSv) respectively. The mean±SD of effective dose from emission, CT and total dose were 11.5±1.4, 0.49±0.11 and 12.67±1.73 (mSv) respectively. The spearman test showed that correlation between body size and organ doses is significant except thyroid and red bone marrow. CTDIvol was strongly dependent on patient size, but SSDE was not. Emission dose was strongly dependent on patient weight, but its dependency was lower to effective diameter. ConclusionThe dose parameters including CTDIvol, DLP, SSDE, effective dose values reported here are very low and below the reference level. This data suggest that appropriate CT acquisition parameters in SPECT/CT localization and attenuation correction are very beneficial for patients and lowering cancer risks.

Quantitative Myocardial Perfusion with Dynamic Contrast-Enhanced Imaging in MRI and CT: Theoretical Models and Current Implementation.

Technological advances in magnetic resonance imaging (MRI) and computed tomography (CT), including higher spatial and temporal resolution, have made the prospect of performing absolute myocardial perfusion quantification possible, previously only achievable with positron emission tomography (PET). This could facilitate integration of myocardial perfusion biomarkers into the current workup for coronary artery disease (CAD), as MRI and CT systems are more widely available than PET scanners. Cardiac PET scanning remains expensive and is restricted by the requirement of a nearby cyclotron. Clinical evidence is needed to demonstrate that MRI and CT have similar accuracy for myocardial perfusion quantification as PET. However, lack of standardization of acquisition protocols and tracer kinetic model selection complicates comparison between different studies and modalities. The aim of this overview is to provide insight into the different tracer kinetic models for quantitative myocardial perfusion analysis and to address typical implementation issues in MRI and CT. We compare different models based on their theoretical derivations and present the respective consequences for MRI and CT acquisition parameters, highlighting the interplay between tracer kinetic modeling and acquisition settings.

Visualization and Characterization of Heterogeneous Water Flow in Double-Porosity Media by Means of X-ray Computed Tomography

Three-dimensional visualization of dynamic water transport process in soil by 1 computed tomography (CT) technique is still limited by its low temporal resolution. In order 2 to monitor dynamically water transport in soil, a compromise has to be found between water 3 flow velocity and CT acquisition time. Furthermore, an efficient image analysis method is 1 4 necessary. In this work, we followed the water transport in three dimensions by CT imaging 5 across a double-porosity media constituted of two distinct materials, i.e. sand and porous 6 clay spheres. The CT acquisition parameters were adjusted to the water pore velocity so that 7 we succeeded to register the water front displacement per time range of 25 min. We also used 8 the image subtraction method to extract water distribution evolution with time with a space 9 resolution of 6 × 10 −3 cm. Both time and space resolution are relatively high compared with 10 other dynamic studies. The water content profiles showed that the clay spheres remained 11 in their dry state during water infiltration, while the water transport only occurred in the 12 sand matrix. These results are consistent with macroscopic experiments. The water front 13 visualized by CT showed a non-symmetrical shape which was related to water transfer in 14 non-equilibrium as shown by column displacement experiments.

Optimizing parameters of an open-source airway segmentation algorithm using different CT images.

Background Computed tomography (CT) helps physicians locate and diagnose pathological conditions. In some conditions, having an airway segmentation method which facilitates reconstruction of the airway from chest CT images can help hugely in the assessment of lung diseases. Many efforts have been made to develop airway segmentation algorithms, but methods are usually not optimized to be reliable across different CT scan parameters.MethodsIn this paper, we present a simple and reliable semi-automatic algorithm which can segment tracheal and bronchial anatomy using the open-source 3D Slicer platform. The method is based on a region growing approach where trachea, right and left bronchi are cropped and segmented independently using three different thresholds. The algorithm and its parameters have been optimized to be efficient across different CT scan acquisition parameters. The performance of the proposed method has been evaluated on EXACT’09 cases and local clinical cases as well as on a breathing pig lung phantom using multiple scans and changing parameters. In particular, to investigate multiple scan parameters reconstruction kernel, radiation dose and slice thickness have been considered. Volume, branch count, branch length and leakage presence have been evaluated. A new method for leakage evaluation has been developed and correlation between segmentation metrics and CT acquisition parameters has been considered.ResultsAll the considered cases have been segmented successfully with good results in terms of leakage presence. Results on clinical data are comparable to other teams’ methods, as obtained by evaluation against the EXACT09 challenge, whereas results obtained from the phantom prove the reliability of the method across multiple CT platforms and acquisition parameters. As expected, slice thickness is the parameter affecting the results the most, whereas reconstruction kernel and radiation dose seem not to particularly affect airway segmentation.ConclusionThe system represents the first open-source airway segmentation platform. The quantitative evaluation approach presented represents the first repeatable system evaluation tool for like-for-like comparison between different airway segmentation platforms. Results suggest that the algorithm can be considered stable across multiple CT platforms and acquisition parameters and can be considered as a starting point for the development of a complete airway segmentation algorithm.

Implications of CT noise and artifacts for quantitative 99mTc SPECT/CT imaging

This paper evaluates the effects of computed tomography (CT) image noise and artifacts on quantitative single-photon emission computed-tomography (SPECT) imaging, with the aim of establishing an appropriate range of CT acquisition parameters for low-dose protocols with respect to accurate SPECT attenuation correction (AC). SPECT images of two geometric and one anthropomorphic phantom were reconstructed iteratively using CT scans acquired at a range of dose levels (CTDIvol = 0.4 to 46 mGy). Resultant SPECT image quality was evaluated by comparing mean signal, background noise, and artifacts to SPECT images reconstructed using the highest dose CT for AC. Noise injection was performed on linear-attenuation (μ) maps to determine the CT noise threshold for accurate AC. High levels of CT noise (σ ∼ 200-400 HU) resulted in low μ-maps noise (σ ∼ 1%-3%). Noise levels greater than ∼ 10% in 140 keV μ-maps were required to produce visibly perceptible increases of ∼ 15% in (99m)Tc SPECT images. These noise levels would be achieved at low CT dose levels (CTDIvol = 4 μGy) that are over 2 orders of magnitude lower than the minimum dose for diagnostic CT scanners. CT noise could also lower (bias) the expected μ values. The relative error in reconstructed SPECT signal trended linearly with the relative shift in μ. SPECT signal was, on average, underestimated in regions corresponding with beam-hardening artifacts in CT images. Any process that has the potential to change the CT number of a region by ∼ 100 HU (e.g., misregistration between CT images and SPECT images due to motion, the presence of contrast in CT images) could introduce errors in μ140 keV on the order of 10%, that in turn, could introduce errors on the order of ∼ 10% into the reconstructed (99m)Tc SPECT image. The impact of CT noise on SPECT noise was demonstrated to be negligible for clinically achievable CT parameters. Because CT dose levels that affect SPECT quantification is low (CTDIvol ∼ 4 μGy), the low dose limit for the CT exam as part of SPECT/CT will be guided by CT image quality requirements for anatomical localization and artifact reduction. A CT technique with higher kVp in combination with lower mAs is recommended when low-dose CT images are used for AC to minimize beam-hardening artifacts.

Evaluation of a semiautomated lung mass calculation technique for internal dosimetry applications

The authors sought to evaluate a simple, semiautomated lung mass estimation method using computed tomography (CT) scans obtained using a variety of acquisition techniques and reconstruction parameters for mass correction of medical internal radiation dose-based internal radionuclide radiation absorbed dose estimates. CT scans of 27 patients with lung cancer undergoing stereotactic body radiation therapy treatment planning with PET∕CT were analyzed retrospectively. For each patient, free-breathing (FB) and respiratory-gated 4DCT scans were acquired. The 4DCT scans were sorted into ten respiratory phases, representing one complete respiratory cycle. An average CT reconstruction was derived from the ten-phase reconstructions. Mid expiration breath-hold CT scans were acquired in the same session for many patients. Deep inspiration breath-hold diagnostic CT scans of many of the patients were obtained from different scanning sessions at similar time points to evaluate the effect of contrast administration and maximum inspiration breath-hold. Lung mass estimates were obtained using all CT scan types, and intercomparisons made to assess lung mass variation according to scan type. Lung mass estimates using the FB CT scans from PET∕CT examinations of another group of ten male and ten female patients who were 21-30 years old and did not have lung disease were calculated and compared with reference lung mass values. To evaluate the effect of varying CT acquisition and reconstruction parameters on lung mass estimation, an anthropomorphic chest phantom was scanned and reconstructed with different CT parameters. CT images of the lungs were segmented using the OsiriX MD software program with a seed point of about -850 HU and an interval of 1000. Lung volume, and mean lung, tissue, and air HUs were recorded for each scan. Lung mass was calculated by assuming each voxel was a linear combination of only air and tissue. The specific gravity of lung volume was calculated using the formula (lung HU - air HU)∕(tissue HU - air HU), and mass = specific gravity × total volume × 1.04 g∕cm(3). The range of calculated lung masses was 0.51-1.29 kg. The average male and female lung masses during FB CT were 0.80 and 0.71 kg, respectively. The calculated lung mass varied across the respiratory cycle but changed to a lesser degree than did lung volume measurements (7.3% versus 15.4%). Lung masses calculated using deep inspiration breath-hold and average CT were significantly larger (p < 0.05) than were some masses calculated using respiratory-phase and FB CT. Increased voxel size and smooth reconstruction kernels led to high lung mass estimates owing to partial volume effects. Organ mass correction is an important component of patient-specific internal radionuclide dosimetry. Lung mass calculation necessitates scan-based density correction to account for volume changes owing to respiration. The range of lung masses in the authors' patient population represents lung doses for the same absorbed energy differing from 25% below to 64% above the dose found using reference phantom organ masses. With proper management of acquisition parameters and selection of FB or midexpiration breath hold scans, lung mass estimates with about 10% population precision may be achieved.

Strategies for Radiation Dose Optimization

This article reviews strategies for radiation dose optimization for computed tomography (CT). A brief overview of dose metrics including computed tomographic dose index, dose length product and effective dose is provided. The impact of age and gender on the sensitivity to radiation is discussed with the aim of tailoring CT acquisition parameters to patient demographics. Dose reduction technologies are reviewed including: tube current modulation, kVp modulation, scan length modification, dynamic z-axis collimation, iterative reconstruction and dual energy. Optimal selection of CT acquisition parameters requires review of clinical information and patient demographics prior to imaging. The authors conclude that with the appropriate application of dose reduction technologies there can be substantial reduction in patient radiation dose while maintaining high diagnostic quality images.