The Effect of Contrast Material on Radiation Dose at CT: Part I. Incorporation of Contrast Material Dynamics in Anthropomorphic Phantoms

Performance evaluation of a 4D similarity filter for dynamic CT angiography imaging of the liver

BACKGROUND

Dynamic computed tomography (CT) angiography of the abdomen provides perfusion information and characteristics of the tissues present in the abdomen. This information could potentially help characterize liver metastases. However, radiation dose has to be relatively low for the patient, causing the images to have very high noise content. Denoising methods are needed to increase image quality.

PURPOSE

The purpose of this study was to investigate the performance, limitations, and behavior of a new 4D filtering method, called the 4D Similarity Filter (4DSF), to reduce image noise in temporal CT data.

METHODS

The 4DSF averages voxels with similar time-intensity curves (TICs). Each phase is filtered individually using the information of all phases except for the one being filtered. This approach minimizes the bias toward the noise initially present in this phase. Since the 4DSF does not base similarity on spatial proximity, loss of spatial resolution is avoided. The 4DSF was evaluated on a 12-phase liver dynamic CT angiography acquisition of 52 digital anthropomorphic phantoms, each containing one hypervascular 1 cm lesion with a small necrotic core. The metrics used for evaluation were noise reduction, lesion contrast-to-noise ratio (CNR), CT number accuracy using peak-time and peak-intensity of the TICs, and resolution loss. The results were compared to those obtained by the time-intensity profile similarity (TIPS) filter, which uses the whole TIC for determining similarity, and the combination 4DSF followed by TIPS filter (4DSF + TIPS).

RESULTS

The 4DSF alone resulted in a median noise reduction by a factor of 6.8, which is lower than that obtained by the TIPS filter at 8.1, and 4DSF + TIPS at 12.2. The 4DSF increased the median CNR from 0. 44 to 1.85, which is less than the TIPS filter at 2.59 and 4DSF + TIPS at 3.12. However, the peak-intensity accuracy in the TICs was superior for the 4DSF, with a median intensity decrease of -34 HU compared to -88 and -50 HU for the hepatic artery when using the TIPS filter and 4DSF + TIPS, respectively. The median peak-time accuracy was inferior for the 4DSF filter and 4DSF + TIPS, with a time shift of -1 phases for the portal vein TIC compared to no shift in time when using the TIPS. The analysis of the full-width-at-half-maximum (FWHM) of a small artery showed significantly less spatial resolution loss for the 4DSF at 3.2 pixels, compared to the TIPS filter at 4.3 pixels, and 3.4 pixels for the 4DSF + TIPS.

CONCLUSION

The 4DSF can reduce noise with almost no resolution loss, making the filter very suitable for denoising 4D CT data for detection tasks, even in very low dose, i.e., very high noise level, situations. In combination with the TIPS filter, the noise reduction can be increased even further.

Development and Clinical Evaluation of a Contrast Optimizer for Contrast-Enhanced CT Imaging of the Liver

OBJECTIVE

Patient characteristics, iodine injection, and scanning parameters can impact the quality and consistency of contrast enhancement of hepatic parenchyma in CT imaging. Improving the consistency and adequacy of contrast enhancement can enhance diagnostic accuracy and reduce clinical practice variability, with added positive implications for safety and cost-effectiveness in the use of contrast medium. We developed a clinical tool that uses patient attributes (height, weight, sex, age) to predict hepatic enhancement and suggest alternative injection/scanning parameters to optimize the procedure.

METHODS

The tool was based on a previously validated neural network prediction model that suggested adjustments for patients with predicted insufficient enhancement. We conducted a prospective clinical study in which we tested this tool in 24 patients aiming for a target portal-venous parenchyma CT number of 110 HU ± 10 HU.

RESULTS

Out of the 24 patients, 15 received adjustments to their iodine contrast injection parameters, resulting in median reductions of 8.8% in volume and 9.1% in injection rate. The scan delays were reduced by an average of 42.6%. We compared the results with the patients' previous scans and found that the tool improved consistency and reduced the number of underenhanced patients. The median enhancement remained relatively unchanged, but the number of underenhanced patients was reduced by half, and all previously overenhanced patients received enhancement reductions.

CONCLUSIONS

Our study showed that the proposed patient-informed clinical framework can predict optimal contrast enhancement and suggest empiric injection/scanning parameters to achieve consistent and sufficient contrast enhancement of hepatic parenchyma. The described GUI-based tool can prospectively inform clinical decision-making predicting optimal patient's hepatic parenchyma contrast enhancement. This reduces instances of nondiagnostic/insufficient enhancement in patients.

Development of physiologically-informed computational coronary artery plaques for use in virtual imaging trials

BACKGROUND

As a leading cause of death, worldwide, cardiovascular disease is of great clinical importance. Among cardiovascular diseases, coronary artery disease (CAD) is a key contributor, and it is the attributed cause of death for 10% of all deaths annually. The prevalence of CAD is commensurate with the rise in new medical imaging technologies intended to aid in its diagnosis and treatment. The necessary clinical trials required to validate and optimize these technologies require a large cohort of carefully controlled patients, considerable time to complete, and can be prohibitively expensive. A safer, faster, less expensive alternative is using virtual imaging trials (VITs), utilizing virtual patients or phantoms combined with accurate computer models of imaging devices.

PURPOSE

In this work, we develop realistic, physiologically-informed models for coronary plaques for application in cardiac imaging VITs.

METHODS

Histology images of plaques at micron-level resolution were used to train a deep convolutional generative adversarial network (DC-GAN) to create a library of anatomically variable plaque models with clinical anatomical realism. The stability of each plaque was evaluated by finite element analysis (FEA) in which plaque components and vessels were meshed as volumes, modeled as specialized tissues, and subjected to the range of normal coronary blood pressures. To demonstrate the utility of the plaque models, we combined them with the whole-body XCAT computational phantom to perform initial simulations comparing standard energy-integrating detector (EID) CT with photon-counting detector (PCD) CT.

RESULTS

Our results show the network is capable of generating realistic, anatomically variable plaques. Our simulation results provide an initial demonstration of the utility of the generated plaque models as targets to compare different imaging devices.

CONCLUSIONS

Vast, realistic, and variable CAD pathologies can be generated to incorporate into computational phantoms for VITs. There they can serve as a known truth from which to optimize and evaluate cardiac imaging technologies quantitatively.

Ultra-short Echo-time MR Angiography Combined with a Modified Signal Targeting Alternating Radio Frequency with Asymmetric Inversion Slabs Technique to Assess Visceral Artery Aneurysm after Coil Embolization

Contrast-enhanced CT and MR angiography are widely used for follow-up of visceral artery aneurysms after coil embolization. However, potential adverse reactions to contrast agents and image deterioration due to susceptibility artifacts from the coils are major drawbacks of these modalities. Herein, we introduced a novel non-contrast-enhanced MR angiography technique using ultra-short TE combined with a modified signal targeting alternating radio frequency with asymmetric inversion slabs, which could provide a serial hemodynamic vascular image with fewer susceptibility artifacts for follow-up after coil embolization.

Surface-based anthropomorphic bone structures for use in high-resolution simulated medical imaging

Objective.Virtual imaging trials enable efficient assessment and optimization of medical image devices and techniques via simulation rather than physical studies. These studies require realistic, detailed ground-truth models or phantoms of the relevant anatomy or physiology. Anatomical structures within computational phantoms are typically based on medical imaging data; however, for small and intricate structures (e.g. trabecular bone), it is not reasonable to use existing clinical data as the spatial resolution of the scans is insufficient. In this study, we develop a mathematical method to generate arbitrary-resolution bone structures within virtual patient models (XCAT phantoms) to model the appearance of CT-imaged trabecular bone.Approach. Given surface definitions of a bone, an algorithm was implemented to generate stochastic bicontinuous microstructures to form a network to define the trabecular bone structure with geometric and topological properties indicative of the bone. For an example adult male XCAT phantom (50th percentile in height and weight), the method was used to generate the trabecular structure of 46 chest bones. The produced models were validated in comparison with published properties of bones. The utility of the method was demonstrated with pilot CT and photon-counting CT simulations performed using the accurate DukeSim CT simulator on the XCAT phantom containing the detailed bone models.Main results. The method successfully generated the inner trabecular structure for the different bones of the chest, having quantiative measures similar to published values. The pilot simulations showed the ability of photon-counting CT to better resolve the trabecular detail emphasizing the necessity for high-resolution bone models.Significance.As demonstrated, the developed tools have great potential to provide ground truth simulations to access the ability of existing and emerging CT imaging technology to provide quantitative information about bone structures.

Estimating cardiac output from coronary CT angiography: an individualized compartment model in comparison to the Stewart-Hamilton method

Background

Attenuation is correlated with the concentration of contrast medium (CM) in the arteries. The cardiac output (CO) affects the concentration of CM in the circulatory system; therefore, CO affects the time-density curve (TDC). Thus, estimating CO using TDC from test-bolus images acquired in computed tomography (CT) is possible. In this study, we compare two methods of estimating CO, namely, an individualized mathematical compartment model, integrating patient, contrast, and scanning factors with TDC, and the Stewart-Hamilton method based on the area under the curve of the TDC.

Materials and methods

Attenuation in the aorta was measured during test-bolus in 40 consecutive patients with a clinical indication for coronary CT angiography (CCTA). Each participant underwent cardiac magnetic resonance imaging following CCTA to validate the estimated CO. The individual compartment model used TDC in conjunction with scanning and patient-specific parameters to estimate the concentration of CM and CO over time. This was compared to the CO calculated from the area under the curve using the Stewart-Hamilton method.

Results

Both CO estimated with our individualized compartment model (r = 0.66, p < 0.01) and the Stewart-Hamilton method (r = 0.53, p < 0.01) were moderately correlated with CO measured with cardiac MRI. Body surface area (BSA) and time to peak (TTP) affected the accuracy of our model. Lower BSA resulted in overestimation, and lower TTP resulted in CO underestimation, respectively. We found no gender-specific difference in the accuracy of our model when correcting for BSA. The Stewart-Hamilton method performed better with a more complete TDC, whereas the compartment model performed better overall with a partial TDC.

Conclusion

The TDC acquired in CCTA allows for CO estimation. Both the Stewart-Hamilton method and our mathematical compartment model show moderate correlation when applied to our data, although each method has its strengths and limitations. If the majority of the TDC is known, the Stewart-Hamilton method may be more reliable, but an individual compartment model is preferable when there are insufficient data points in the TDC. Regardless, both methods can potentially increase the diagnostic information acquired from a CCTA, which is increasingly recommended in clinical guidelines.

Third-Generation Cardiovascular Phantom: The Next Generation of Preclinical Research in Diagnostic Imaging

OBJECTIVE

Different types of preclinical research tools used in the field of diagnostic imaging such as dynamic flow circulation phantoms have built the foundation for optimization and advancement of clinical procedures including new imaging techniques. The objective was to introduce a third-generation phantom, building on the limitations of earlier versions and unlocking new opportunities for preclinical investigation.

MATERIAL AND METHODS

A third-generation phantom was designed and constructed comprising physiological vascular models from head to toe, including a 4-chamber heart with embedded heart valves and a controllable electromechanical pump. The models include modular segments, allowing for interchangeability between healthy and diseased vessels. Clinical sanity checks were performed using the phantom in combination with a dual-head power injector on a third-generation dual-source computed tomography scanner. Contrast media was injected at 1.5 g I/s, and the phantom was configured with a cardiac output of 5.3 L/min. Measurements of mean transit times between key vascular landmarks and peak enhancement values in Hounsfield units (HUs) were measured to compare with expected in vivo results estimated from literature.

RESULTS

Good agreement was obtained between literature reference values from physiology and measured results. Contrast arrival between antecubital vein and right ventricle was measured to be 13.1 ± 0.3 seconds. Transit time from right ventricle to left ventricle was 12.0 ± 0.2 seconds, from left internal carotid artery to left internal jugular vein 7.7 ± 0.4 seconds, and 2.9 ± 0.2 seconds from aortic arch to aortic bifurcation. The peak enhancement measured in the regions of interest was between 336 HU and 557 HU.

CONCLUSIONS

The third-generation phantom demonstrated the capability of simulating physiologic in vivo conditions with accurate contrast media transport timing, good repeatability, and expected enhancement profiles. As a nearly complete cardiovascular system including a functioning 4-chamber heart and interchangeable disease states, the third-generation phantom presents new opportunities for the expansion of preclinical research in diagnostic imaging.

A patient-informed approach to predict iodinated-contrast media enhancement in the liver

OBJECTIVE

To devise a patient-informed time series model that predicts liver contrast enhancement, by integrating clinical data and pharmacokinetics models, and to assess its feasibility to improve enhancement consistency in contrast-enhanced liver CT scans.

METHODS

The study included 1577 Chest/Abdomen/Pelvis CT scans, with 70-30% training/validation-testing split. A Gaussian function was used to approximate the early arterial, late arterial, and the portal venous phases of the contrast perfusion curve of each patient using their respective bolus tracking and diagnostic scan data. Machine learning models were built to predict the Gaussian parameters of each patient using the patient attributes (weight, height, age, sex, BMI). Pearson's coefficient, mean absolute error, and root mean squared error were used to assess the prediction accuracy.

RESULTS

The integration of the pharmacokinetics model with a two-layered neural network achieved the highest prediction accuracy on the test data (R2 = 0.61), significantly exceeding the performance of the pharmacokinetics model alone (R2 = 0.11). Applying the model demonstrated that adjusting the contrast administration directed by the model may reduce clinical enhancement inconsistency by up to 40 %.

CONCLUSIONS

A new model using a Gaussian function and supervised machine learning can be used to build liver parenchyma contrast enhancement prediction model. The model can have utility in clinical settings to optimize and improve consistency in contrast-enhanced liver imaging.

Contrast Medium Use in Computed Tomography for Patients Presenting with Headache: 4-year Retrospective Two-Center Study in Central and Western Regions of Ghana

Background

Contrast medium (CM) administration during computed tomography (CT) enhances the accuracy in the detection and interpretation of abnormalities. Evidence from literature also validate the essence of CM in imaging studies. CT, by virtue of its ubiquity, ease of use, speed, and lower financial footprint, is usually the first investigation in cases of headache. Through a multicenter retrospective analysis, we compared findings of contrast-enhanced CT (CECT) to noncontrast-enhanced CT (NCECT) head examinations among patients presenting with headache.

Methods

A multicenter retrospective analysis of four years' CT head examination data at two radiology centers located in Central and Western Regions of Ghana were reviewed. Records of patients who presented with headache as principal complaint between January 2017 and December 2020 were reviewed. A total of 477 records of patients with headache were identified, retrieved and evaluated. A Chi-square test and Fisher exact test were used to compare the CECT and NCECT groups. Binary logistic regression analysis was computed to assess association between CECT and each CT findings. Statistical significance was considered at p < 0.05 with a 95% confidence interval.

Results

A significant proportion of the patients was females (51.8% in CECT and 60% in NCECT). The NCECT group (40.06 ± 14.76 years) was relatively older than the CECT group (38.43 ± 17.64 years). There was a significant difference between the CECT and NCECT in terms of age (p=0.002) and facility CT was performed (p < 0.0001). The rate of abnormalities was higher in CECT (43.5%, 166/382) compared NCECT (37.9%, 36/95). There was no significant association between CT head findings and contrast enhancement.

Conclusion

CECT examination accounted for 5.6% increase in the detection of head abnormalities. Efforts required to establish local standard operation procedures (SOPs) for contrast medium use especially in CT head examinations. Further studies to improve the knowledge of agents, mechanism of action, and safety of contrast media used among practitioners in Ghana is recommended.

Anatomically and physiologically informed computational model of hepatic contrast perfusion for virtual imaging trials

PURPOSE

Virtual (in silico) imaging trials (VITs), involving computerized phantoms and models of the imaging process, provide a modern alternative to clinical imaging trials. VITs are faster, safer, and enable otherwise-impossible investigations. Current phantoms used in VITs are limited in their ability to model functional behavior such as contrast perfusion which is an important determinant of dose and image quality in CT imaging. In our prior work with the XCAT computational phantoms, we determined and modeled inter-organ (organ to organ) intravenous contrast concentration as a function of time from injection. However, intra-organ concentration, heterogeneous distribution within a given organ, was not pursued. We extend our methods in this work to model intra-organ concentration within the XCAT phantom with a specific focus on the liver.

METHODS

Intra-organ contrast perfusion depends on the organ's vessel network. We modeled the intricate vascular structures of the liver, informed by empirical and theoretical observations of anatomy and physiology. The developed vessel generation algorithm modeled a dual-input-single-output vascular network as a series of bifurcating surfaces to optimally deliver flow within the bounding surface of a given XCAT liver. Using this network, contrast perfusion was simulated within voxelized versions of the phantom by using knowledge of the blood velocities in each vascular structure, vessel diameters and length, and the time since the contrast entered the hepatic artery. The utility of the enhanced phantom was demonstrated through a simulation study with the phantom voxelized prior to CT simulation with the relevant liver vasculature prepared to represent blood and iodinated contrast media. The spatial extent of the blood-contrast mixture was compared to clinical data.

RESULTS

The vascular structures of the liver were generated with size and orientation which resulted in minimal energy expenditure required to maintain blood flow. Intravenous contrast was simulated as having known concentration and known total volume in the liver as calibrated from time-concentration curves. Measurements of simulated CT ROIs were found to agree with clinically observed values of early arterial phase contrast enhancement of the parenchyma (∼ 5 $ \sim 5$ HU). Similarly, early enhancement in the hepatic artery was found to agree with average clinical enhancement( 180 $(180$ HU).

CONCLUSIONS

The computational methods presented here furthered the development of the XCAT phantoms allowing for multi-timepoint contrast perfusion simulations, enabling more anthropomorphic virtual clinical trials intended for optimization of current clinical imaging technologies and applications.

A NEW METHOD FOR ESTIMATING INCREASE IN RADIATION DOSE ASSOCIATED WITH IODINATED CONTRAST USE

This work investigates the impact of iodinated contrast medium (ICM) on radiation dose in computed tomography (CT) scans using linear models established through a phantom study. Thermoluminescence dosemeters (TLDs) were calibrated using semi-conductor X-ray dosemeters. An electron density phantom, with a vial containing TLDs and different concentrations of iodinated blood, were scanned at different tube voltages. Irradiated TLD outputs were measured and absorbed dose to iodinated blood calculated. CT numbers (tissue attenuation as measured by Hounsfield units) were plotted against absorbed doses to obtain linear models. Data from 49 real patient scans were used to validate the linear models. At each X-ray energy, CT numbers were linearly correlated with the absorbed doses, that is with the increase of blood iodine concentration, the CT number increased and the absorbed dose increased accordingly. ICM can cause an increase of organ dose; the average dose increases were 31.8 ± 8.9% for thyroid, 37.1 ± 9.2% for cardiac muscle, 77.7 ± 14.0% for cardiac chamber, 7.1 ± 2.3% for breast, 26.1 ± 7.3% for liver, 39.8 ± 11.8% for spleen, 96.3 ± 12.2% for renal cortex and 82.4 ± 11.6% for medulla nephrica. ICM used in enhanced CT scan resulted in increased organ doses. Our models for estimating organ dose based on CT number were established by experiment and verified in clinical use.

A PHANTOM EVALUATION OF THE USE OF CT AUTOMATIC TUBE CURRENT MODULATION WITH LOW TUBE POTENTIALS FOR IODINATED CONTRAST STUDIES

This paper aimed to investigate effects of different tube voltage and image quality settings on radiation dose and image quality for patients undergoing computed tomography iodinated contrast studies using automatic tube current modulation system and to recommend settings to achieve improved radiation dose and image quality values. A Pagoda phantom with an additional rod of iodine contrast was scanned using different tube voltages and noise index (NI) settings. Size-specific dose estimate (SSDE) and image quality (noise, contrast, contrast-to-noise ratio (CNR) and figure of merit (FOM)) were analysed. Values of SSDE were maintained with similar NI settings. Contrast and CNR were higher for lower tube voltage settings. Better FOM values can be achieved with higher NI settings with the lower kVs. To achieve better CNR and SSDE compared with the standard setting of 120 kV, a 80 kV with an NI setting of 15 was recommended.

Ultrashort echo time time-spatial labeling inversion pulse magnetic resonance angiography with denoising deep learning reconstruction for the assessment of abdominal visceral arteries

Current contrast-enhanced magnetic resonance angiography (MRA) and non-contrast-enhanced balanced steady-state free precession (bSSFP) MRA cause susceptibility artifacts from metallic devices in assessing endovascular visceral-artery interventions. The aims of this study are to investigate and compare image quality (IQ) and susceptibility artifacts of three-dimensional (3D) ultrashort echo time (UTE) time-spatial labeling inversion pulse (Time-SLIP) with those of 3D bSSFP Time-SLIP and to assess denoising deep learning reconstruction (dDLR) for the improvement of the signal-to-noise ratio (SNR) in 3D UTE with sparse sampling in phantoms and human subjects. This is a prospective type of study. Pulsatile glycerin-water flow phantom with platinum-tungsten-alloy coil, stainless-steel, nitinol, and cobalt-alloy stents were used. Ten healthy volunteers (seven males) and three patients (two males) were included in this study. 3D UTE Time-SLIP and 3D bSSFP Time-SLIP at 3T were used. The phantom-based study compared the signal-intensity ratio of the device levels (SRdevice ) and distal segments (SRdistal ) to the proximal segments. The volunteer-based study measured SNR, contrast ratio (CR), and IQ. The patient study evaluated local artifacts from metallic devices. Statistical tests included paired t-tests, Wilcoxon-signed rank tests, and Kruskal-Wallis tests. In the phantom-based study, SRdevice was small with UTE Time-SLIP, except the stainless-steel stent. SRdistal was greater (49.1%-90.4%) on bSSFP images than UTE images (-11.1% to 9.6%). Among volunteers, dDLR in UTE images improved SNR (p < 0.05) and IQ (p < 0.05), but CR was unaffected. UTE Time-SLIP showed inferior SNR and IQ than bSSFP Time-SLIP in images with and without dDLR (p < 0.05 for each). However, among patients, UTE Time-SLIP showed reduced metal artifacts compared to bSSFP Time-SLIP. Irrespective of the lower SNR and IQ of 3D UTE Time-SLIP than those of 3D bSSFP Time-SLIP, the former appeared to better depict flow after stenting or coiling. This indicates the potential of 3D UTE Time-SLIP to provide suitable diagnostic images of target vessels. dDLR improved SNR with reducing artifacts related to radial sampling, while maintaining the contrast. LEVEL OF EVIDENCE: 2. TECHNICAL EFFICACY STAGE: 2.

The presence of contrast agent increases organ radiation dose in contrast-enhanced CT

Objectives

Routine dosimetry calculations do not account for the presence of iodine in organs and tissues during CT acquisition. This study aims to investigate the impact of contrast agent (CA) on radiation dose.

Methods

First, relation between absorbed radiation dose and iodine concentrations was investigated using a cylindrical water phantom with iodine-saline dilution insertions. Subsequently, a retrospective study on abdominal dual-energy CT (DECT) patient data was performed to assess the increase of the local absorbed radiation dose compared to a non-contrast scan. Absorbed doses were estimated with Monte Carlo simulations using the individual CT voxel data of phantom and patients. Further, organ segmentations were performed to obtain the dose in liver, liver parenchyma, left kidney, right kidney, aorta, and spleen.

Results

In the phantom study, a linear relation was observed between the radiation dose normalized by computed tomography dose index (CTDI) and CA concentrations I_conc (mg/ml) for three tube voltages; \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ \frac{D_{80 kVp}}{CTDI_{vol}} $$\end{document}D80kVpCTDIvol = 0.14 × I_conc + 1.02, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ \frac{D_{120 kVp}}{CTDI_{vol}} $$\end{document}D120kVpCTDIvol = 0.16 × I_conc + 1.21, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ \frac{D_{140 kVp}}{CTDI_{vol}} $$\end{document}D140kVpCTDIvol = 0.16 × I_conc + 1.24, and for DECT acquisition; \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ \frac{D_{DECT}}{CTDI_{vol}} $$\end{document}DDECTCTDIvol = 0.15 × I_conc + 1.09. Similarly, a linear relation was observed between the dose increase and the organ iodine contents (R² = 0.86 and p_value < 0.01) in the patient study. The relative doses increased in the liver (21 ± 5%), liver parenchyma (20 ± 5%), right kidney (37 ± 7%), left kidney (39 ± 7%), aorta (34 ± 6%) and spleen (26 ± 4%). In addition, the local dose distributions changed based on patient’s anatomy and physiology.

Conclusions

Compared to a non-contrast scan, the organ doses increase by 30% in contrast-enhanced abdominal CT. This study suggests considering CA in dosimetry calculations, epidemiological studies, and organ dose estimations while developing new CT protocols.

Key Points

• The presence of contrast media increases radiation absorption in CT, and this increase is related to the iodine content in the organs.

• The increased radiation absorption due to contrast media can lead to an average 30% increase in absorbed organ dose.

• Iodine should be considered in CT radiation safety studies.

Challenges estimating patient organs doses undergoing enhanced chest CT examination: exploratory study

Purpose: Estimate organs doses (ODs) of patients subjected to unenhanced (S1) and enhanced (S2) chest CT studies relying on image parameters such as Hounsfield Units (HUs).Materials and Methods: CT scans and images of a total of 16 patients who underwent two series of chest CT studies were obtained and retrospectively examined. OD increments of liver and pancreas for both series (S1 & S2) were estimated using two different independent methods, namely simulation approach using CT-EXPO and Amato's phantom-based fitting model (APFM). HUs were quantified for each organ by manually drawing fixed area-sized regions of interest (ROIs). The mean HUs were collected to obtain the ODs increments following APFM. Regression analysis was applied to find and assess the relationship between the HUs and the OD increments estimated using APFM and that using CT-EXPO. Spearman Coefficient and Wilcoxon Matched Pairedt-testwere conducted to show statistical correlation and difference between ODs increments using the two methods.Results:A strong significant difference was depicted between S1 and S2 scan series of liver and pancreas using CT-EXPO simulation. Mean HU values for S1 were lower than S2, resulting in statistically significant (p < 0.0001) HU changes. CT-EXPO simulation yielded significantly higher difference in ODs compared to the APFM for liver (p = 0.0455) and pancreas (p = 0.0031). Regression analysis revealed a strong relationship between HU of S1 and S2 and ODs increments using APFM in both organs (R² = 0.99), dissimilar to CT-EXPO (R² = 0.39 in liver andR² = 0.05 in pancreas).Conclusions: Although CT-EXPO allows for estimating ODs accounting for major acquisition scan parameters, it is not a reliable tool to evaluate the impact of contrast enhancement on ODs. On the other hand, the APFM accounts for contrast enhancement accumulation yet only provides relative OD increments, an information of limited clinical use.

Decreasing the radiation dose for contrast-enhanced abdominal spectral CT with a half contrast dose: a matched-pair comparison with a 120 kVp protocol

Objectives

To compare the estimated radiation dose of 50% reduced iodine contrast medium (halfCM) for virtual monochromatic images (VMIs) with that of standard CM (stdCM) with a 120 kVp imaging protocol for contrast-enhanced CT (CECT).

Methods

We enrolled 30 adults with renal dysfunction who underwent abdominal CT with halfCM for spectral CT. As controls, 30 matched patients without renal dysfunction using stdCM were also enrolled. CT images were reconstructed with the VMIs at 55 keV with halfCM and 120 kVp images with stdCM and halfCM. The Monte-Carlo simulation tool was used to simulate the radiation dose. The organ doses were normalized to CTDIvol for the liver, pancreas, spleen, and kidneys and measured between halfCM and stdCM protocols.

Results

For the arterial phase, the mean organ doses normalized to CTDIvol for stdCM and halfCM were 1.22 and 1.29 for the liver, 1.50 and 1.35 for the spleen, 1.75 and 1.51 for the pancreas, and 1.89 and 1.53 for the kidneys. As compared with non-enhanced CT, the average increase in the organ dose was significantly lower for halfCM (13.8% ± 14.3 and 26.7% ± 16.7) than for stdCM (31.0% ± 14.3 and 38.5% ± 14.8) during the hepatic arterial and portal venous phases (p < 0.01).

Conclusion

As compared with stdCM with the 120 kVp imaging protocol, a 50% reduction in CM with VMIs with the 55 keV protocol allowed for a substantial reduction of the average organ dose of iodine CM while maintaining the iodine CT number for CECT.

Advances in knowledge

This study provides that the halfCM protocol for abdominal CT with a dual-layer-dual-energy CT can significantly reduce the increase in the average organ dose for non-enhanced CT as compared with the standard CM protocol.

A database of 40 patient-based computational models for benchmarking organ dose estimates in CT

PURPOSE

Patient radiation burden in computed tomography (CT) can best be characterized through risk estimates derived from organ doses. Organ doses can be estimated by Monte Carlo simulations of the CT procedures on computational phantoms assumed to emulate the patients. However, the results are subject to uncertainties related to how accurately the patient and CT procedure are modeled. Different methods can lead to different results. This paper, based on decades of organ dosimetry research, offers a database of CT scans, scan specifics, and organ doses computed using a validated Monte Carlo simulation of each patient and acquisition. It is aimed that the database can serve as means to benchmark different organ dose estimation methods against a benchmark dataset.

ACQUISITION AND VALIDATION METHODS

Organ doses were estimated for 40 adult patients (22 male, 18 female) who underwent chest and abdominopelvic CT examinations. Patient-based computational models were created for each patient including 26 organs for female and 25 organs for male cases. A Monte Carlo code, previously validated experimentally, was applied to calculate organ doses under constant and two modulated tube current conditions.

DATA FORMAT AND USAGE NOTES

The generated database reports organ dose values for chest and abdominopelvic examinations per patient and imaging condition. Patient information and images and scan specifications (energy spectrum, bowtie filter specification, and tube current profiles) are provided. The database is available at publicly accessible digital repositories.

POTENTIAL APPLICATIONS

Consistency in patient risk estimation, and associated justification and optimization requires accuracy and consistency in organ dose estimation. The database provided in this paper is a helpful tool to benchmark different organ dose estimation methodologies to facilitate comparisons, assess uncertainties, and improve risk assessment of CT scans based on organ dose.

Modeling Patient-Informed Liver Contrast Perfusion in Contrast-enhanced Computed Tomography

OBJECTIVE

To determine the correlation between patient attributes and contrast enhancement in liver parenchyma and demonstrate the potential for patient-informed prediction and optimization of contrast enhancement in liver imaging.

METHODS

The study included 418 chest/abdomen/pelvis computed tomography scans, with 75% to 25% training-testing split. Two regression models were built to predict liver parenchyma contrast enhancement over time: first model (model A) utilized patient attributes (height, weight, sex, age, bolus volume, injection rate, scan times, body mass index, lean body mass) and bolus-tracking data. A second model (model B) only used the patient attributes. Pearson coefficient was used to assess predictive accuracy.

RESULTS

Weight- and height-related features were found to be statistically significant predictors (P < 0.05), weight being the strongest. Of the 2 models, model A (r = 0.75) showed greater accuracy than model B (r = 0.42).

CONCLUSIONS

Patient attributes can be used to build prediction model for liver parenchyma contrast enhancement. The model can have utility in optimization and improved consistency in contrast-enhanced liver imaging.

The effect of contrast material on radiation dose during computed tomography pulmonary angiography

This study evaluated the impact of contrast material (CM) on radiation dose for adults undergoing computed tomography pulmonary angiography (CTPA). A previously developed physiologically based pharmacokinetic (PBPK) model and phantoms representing the average (reference) adult male and female individual were used to evaluate the iodine concentration in tissues as a function of time elapsed since the initiation of iodinated contrast medium administration. In order to estimate the radiation dose more accurately, a detailed model of pulmonary vessels was added to the phantoms. Then, the material composition of phantoms was modified to include the iodine concentration in different organs and tissues at different acquisition times after CM injection. The calculations were performed using Monte Carlo N-Particle extended code (MCNPX) version 2.6.0. The radiation dose estimates during CTPA were provided as a function of scan acquisition time after injection considering the distribution of iodinated CM within ICRP reference phantoms. It was shown that the estimated radiation dose to the lungs could be 31-40% (27-34%) larger when considering the effect of iodinated contrast administration with injection rate of 5 (3)mL/s. Moreover, the effective dose for contrast-enhanced CT (CECT) would be utmost 10-13% larger than that for non-enhanced CT (NECT). The radiation doses to the other organs in-/outside the scanned region would be decreased if the scan performed on time. In case of late scanning, absorbed dose decreases slightly for lungs (∼15-20%) whereas becomes (∼10% or more) higher than its NECT value for some organs such as heart muscle, kidneys, and spleen. To sum up, the late scanning (Δt>5s after the end of injection) is not recommended because of higher dose delivered to other organs than the lungs (particularly heart muscle).

Virtual clinical trials in medical imaging: a review

The accelerating complexity and variety of medical imaging devices and methods have outpaced the ability to evaluate and optimize their design and clinical use. This is a significant and increasing challenge for both scientific investigations and clinical applications. Evaluations would ideally be done using clinical imaging trials. These experiments, however, are often not practical due to ethical limitations, expense, time requirements, or lack of ground truth. Virtual clinical trials (VCTs) (also known as in silico imaging trials or virtual imaging trials) offer an alternative means to efficiently evaluate medical imaging technologies virtually. They do so by simulating the patients, imaging systems, and interpreters. The field of VCTs has been constantly advanced over the past decades in multiple areas. We summarize the major developments and current status of the field of VCTs in medical imaging. We review the core components of a VCT: computational phantoms, simulators of different imaging modalities, and interpretation models. We also highlight some of the applications of VCTs across various imaging modalities.

Balancing act between quantitative and qualitative image quality between nonionic iodinated dimer and monomer at various vessel sizes during computed tomography: a phantom study

PURPOSE

Investigate the impact of nonionic dimer and monomer on iodine quantification in different vessel sizes when employing a vascular specific phantom and varying iodinated contrast media (ICM) concentrations during computed tomography (CT).

MATERIALS AND METHODS

We created a vascular specific phantom (30 cm) to simulate human blood vessel diameters (25 cylinders of different diameters: 10 × 9mm, 10 × 12mm and 5 × 21mm). The phantom was filled with two ICM separately: Group: Iohexol(monomer)350 mg ml^-1 and B: Iodixanol(Dimer)320 mg ml^-1. Cylinders of same size were filled with increasing ICM concentration(10%-100%) while large cylinders were filled in quartiles(25%-100%). Phantom was scanned with different tube potential (80-140kVp), current (50-400mAs), reconstruction method [filtered back projection (FBP), hybrid-based iterative reconstruction (HBIR) and model-based iterative reconstruction (MBIR)] for each ICM. Chi-square was employed to compare mean opacification, contrast/noise ratio (CNR) and noise. Qualitative analysis was assessed by Visual grading characteristic (VGC) and Cohens-kappa analyses.

RESULTS

At 80 and140kVp significant difference in opacification between Group A (2054 ± 1040HU and 1696 ± 1027HU) and B (2169 ± 1105HU and 1568 ± 1034HU) was demonstrated (p < 0.001). However, at 100 and 120kVp no difference was noted (p > 0.05). When comparing image noise, it was higher in Group A compared to B (p < 0.05). CNR was higher in Group B (119.99 ± 126.10HU) than A (107.09 ± 102.56HU) (p < 0.0001). VGC: Group A outperformed B in image opacification in all vessel sizes and ICM concentrations except at medium vessels with concentration group 2(0.4-0.6 mg ml^-1). Cohens'-kappa: agreement in opacification between each ICM group and iodine concentration 1(0-0.3 mg ml^-1): κ = 0.253 and 0.014 respectively, concentration 2(0.4-0.6 mg ml^-1):κ = -0.017 and -0.005 respectively and concentration 3(0.7-1 mg ml^-1):κ = 0.031 and 0.115 respectively.

CONCLUSION

Nonionic dimer (Iodixanol) surpasses monomer (Iohexol) in quantitative image quality assessment by having lower image noise and higher CNR during CT.

Low Radiation Dose and High Image Quality of 320-Row Coronary Computed Tomography Angiography Using a Small Dose of Contrast Medium and Refined Scan Timing Prediction

OBJECTIVE

The aim of the study was to investigate the feasibility of coronary computed tomography (CT) angiography with a low kilovoltage peak scan and a refined scan timing prediction using a small contrast medium (CM) dose.

METHODS

In protocol A, 120-kVp scanning and a standard CM dose were used. The scan timing was fixed. In protocol B, 80 kVp and a 60% CM dose were used. The scan timing was determined according to the interval from the CM arrival to the peak time in the ascending aorta. We measured the CT number and recorded the radiation dose.

RESULTS

Higher CT numbers were observed in the left circumflex (proximal, P = 0.0235; middle, P = 0.0007; distal, P < 0.0001) in protocol B compared with protocol A. The radiation dose in protocol B was significantly lower than in protocol A (2.2 ± 0.9 vs 4.3 ± 1.7 mSv).

CONCLUSIONS

Low-contrast, low-radiation dose, high-image quality coronary CT angiography can be performed with low kilovoltage peak scanning and a refined scan timing prediction.

A real-time Monte Carlo tool for individualized dose estimations in clinical CT

The increasing awareness of the adverse effects associated with radiation exposure in computed tomography (CT) has necessesitated the quantification of dose delivered to patients for better risk assessment in the clinic. The current methods for dose quantification used in the clinic are approximations, lacking realistic models for the irradiation conditions utilized in the scan and the anatomy of the patient being imaged, which limits their relevance for a particular patient. The established gold-standard technique for individualized dose quantification uses Monte Carlo (MC) simulations to obtain patient-specific estimates of organ dose in anatomically realistic computational phantoms to provide patient-specific estimates of organ dose. Although accurate, MC simulations are computationally expensive, which limits their utility for time-constrained applications in the clinic. To overcome these shortcomings, a real-time GPU-based MC tool based on FDA's MC-GPU framework was developed for patient and scanner-specific dosimetry in the clinic. The tool was validated against (1) AAPM's TG-195 reference datasets and (2) physical measurements of dose acquired using TLD chips in adult and pediatric anthropomorphic phantoms. To demonstrate its utility towards providing individualized dose estimates, it was integrated with an automatic segmentation method for generating patient-specific models, which were then used to estimate patient- and scanner-specific organ doses for a select population of 50 adult patients using a clinically relevant CT protocol. The organ dose estimates were compared to corresponding dose estimates from a previously validated MC method based on Penelope. The dose estimates from our MC tool agreed within 5% for all organs (except thyroid) tabulated by TG-195 and within 10% for all TLD locations in the adult and pediactric phantoms, across all validation cases. Compared against Penelope, the organ dose estimates agreed within 3% on average for all organs in the patient population study. The average run duration for each patient was estimated at 23.79 s, representing a significant speedup (~700×) over existing non-parallelized MC methods. The accuracy of dose estimates combined with a significant improvement in execution times suggests a feasible solution utilizing the proposed MC tool for real-time individualized dosimetry in the clinic.

Development of a scanner-specific simulation framework for photon-counting computed tomography

The aim of this study was to develop and validate a simulation platform that generates photon-counting CT images of voxelized phantoms with detailed modeling of manufacturer-specific components including the geometry and physics of the x-ray source, source filtrations, anti-scatter grids, and photon-counting detectors. The simulator generates projection images accounting for both primary and scattered photons using a computational phantom, scanner configuration, and imaging settings. Beam hardening artifacts are corrected using a spectrum and threshold dependent water correction algorithm. Physical and computational versions of a clinical phantom (ACR) were used for validation purposes. The physical phantom was imaged using a research prototype photon-counting CT (Siemens Healthcare) with standard (macro) mode, at four dose levels and with two energy thresholds. The computational phantom was imaged with the developed simulator with the same parameters and settings used in the actual acquisition. Images from both the real and simulated acquisitions were reconstructed using a reconstruction software (FreeCT). Primary image quality metrics such as noise magnitude, noise ratio, noise correlation coefficients, noise power spectrum, CT number, in-plane modulation transfer function, and slice sensitivity profiles were extracted from both real and simulated data and compared. The simulator was further evaluated for imaging contrast materials (bismuth, iodine, and gadolinium) at three concentration levels and six energy thresholds. Qualitatively, the simulated images showed similar appearance to the real ones. Quantitatively, the average relative error in image quality measurements were all less than 4% across all the measurements. The developed simulator will enable systematic optimization and evaluation of the emerging photon-counting computed tomography technology.

Advances in Computational Human Phantoms and Their Applications in Biomedical Engineering - A Topical Review

Over the past decades, significant improvements have been made in the field of computational human phantoms (CHPs) and their applications in biomedical engineering. Their sophistication has dramatically increased. The very first CHPs were composed of simple geometric volumes, e.g., cylinders and spheres, while current CHPs have a high resolution, cover a substantial range of the patient population, have high anatomical accuracy, are poseable, morphable, and are augmented with various details to perform functionalized computations. Advances in imaging techniques and semi-automated segmentation tools allow fast and personalized development of CHPs. These advances open the door to quickly develop personalized CHPs, inherently including the disease of the patient. Because many of these CHPs are increasingly providing data for regulatory submissions of various medical devices, the validity, anatomical accuracy, and availability to cover the entire patient population is of utmost importance. The article is organized into two main sections: the first section reviews the different modeling techniques used to create CHPs, whereas the second section discusses various applications of CHPs in biomedical engineering. Each topic gives an overview, a brief history, recent developments, and an outlook into the future.

Application of the 4-D XCAT Phantoms in Biomedical Imaging and Beyond

The four-dimensional (4-D) eXtended CArdiac-Torso (XCAT) series of phantoms was developed to provide accurate computerized models of the human anatomy and physiology. The XCAT series encompasses a vast population of phantoms of varying ages from newborn to adult, each including parameterized models for the cardiac and respiratory motions. With great flexibility in the XCAT's design, any number of body sizes, different anatomies, cardiac or respiratory motions or patterns, patient positions and orientations, and spatial resolutions can be simulated. As such, the XCAT phantoms are gaining a wide use in biomedical imaging research. There they can provide a virtual patient base from which to quantitatively evaluate and improve imaging instrumentation, data acquisition, techniques, and image reconstruction and processing methods which can lead to improved image quality and more accurate clinical diagnoses. The phantoms have also found great use in radiation dosimetry, radiation therapy, medical device design, and even the security and defense industry. This review paper highlights some specific areas in which the XCAT phantoms have found use within biomedical imaging and other fields. From these examples, we illustrate the increasingly important role that computerized phantoms and computer simulation are playing in the research community.

Effect of contrast material injection duration on arterial enhancement at CT in patients with various cardiac indices: Analysis using computer simulation

Arterial peak enhancement on contrast-enhanced CT (CECT) images is thought to be higher in patients with low cardiac function. Using computer simulations, we tested the hypothesis that the relationship between the cardiac index and the aortic peak CT number (PCTN) is affected by the contrast material (CM) injection duration. We created computer simulation software for the contrast enhancement of various organs and vessels based on the Bae pharmacokinetics model and implemented models for CM transmission within organs and CM diffusion in blood plasma based on the osmotic pressure. Aortic contrast enhancement at coronary- and abdominal CT angiographs (CTA) was simulated for a representative 60-year-old Japanese male 166 cm in height and 65.0 kg in weight. The injection protocol for coronary CTA was: CM dose 45.5 ml, iodine dose, 245 mg/kg body weight (BW); injection duration 8–20 sec in 2-sec increments. For abdominal CTA it was CM dose 74.3 ml; iodine dose 400 mg/kg BW; injection duration 10–40 sec in 5-sec increments. In both protocols the iodine concentration was 350 mgI/ml, osmotic pressure was 590 mOsm/kgH₂O, and the cardiac index ranged from 0.1–6.0 l/min/m². Under all protocols, the aortic PCTN increased as the injection duration decreased and as the cardiac index rose to the cardiac index value. It then decreased as it exceeded the cardiac index value. At coronary CTA, at an injection duration of 8 or 10 sec, the PCTN exceeded 350 Hounsfield units (HU) at a cardiac index from 0.9–5.6 l/min/m². At an HU value greater than 350, the range of the cardiac index narrowed when the injection duration was 12 sec or longer. On abdominal CTA scans performed with an injection duration of 10-, 15-, or 20 sec, the PCTN exceeded 350 HU at a cardiac index ranging from 0.4–5.3 l/min/m². When the injection duration ranged from 25–40 sec, there was narrowing of the range of the cardiac index at which the PCTN exceeded 350 HU. For coronary and abdominal CTA, contrast enhancement protocols with shorter injection durations yield a diagnostically adequate aortic PCTN at a wide range of cardiac indices.

The impact of iodinated contrast media on intravascular and extravascular absorbed doses in X-ray imaging: A microdosimetric analysis

Studies suggest iodinated contrast media (ICM) may increase organ dose and blood cell DNA damage for a given X-ray exposure. The impact of ICM on dose/damage to extravascular cells and cancer risks is unclear.

METHODS

We used Monte Carlo modelling to investigate the microscopic distribution of absorbed dose outside the lumen of arteries, capillaries and interstitial fluids containing blood and various concentrations of iodine. Models were irradiated with four X-ray spectra representing clinical procedures.

RESULTS

For the artery model, The average dose enhancement factors (DEF) to blood were 1.70, 2.38, 7.38, and 12.34 for mass concentrations of iodine in blood (ρiI) of 5, 10, 50 and 100 mg/ml, respectively, compared to 0 mg/ml. Average DEFs were reduced to 1.26, 1.51, 3.48 and 5.56, respectively, in the first micrometre of the vessel wall, falling to 1.01, 1.02, 1.06 and 1.09 at 40-50 μm from the lumen edge. For the capillary models, DEF for extravascular tissues was on average 48% lower than DEF for the whole model, including capillaries. A similar situation was observed for the interstitial model, with DEF to the cell nucleus being 35% lower than DEF for the whole model.

CONCLUSIONS

While ICM may modify the absorbed doses from diagnostic X-ray examinations, the effect is smaller than suggested by assays of circulating blood cells or blood dose enhancement. Conversely, the potentially large increase in dose to the endothelium of blood vessels means that macroscopic organ doses may underestimate the risk of radiation induced cardiovascular disease for ICM-enhanced exposures.

Assessment of Effective Dose Associated with Coronary Computed Tomography Angiography in Isfahan Province, Iran

Computed tomography coronary angiography (CTCA) has generated a great interest over the past two decades, due to its high diagnostic accuracy and efficacy in the assessment of patients having coronary artery disease. This method is associated with high radiation dose and this has raised serious concerns in the literature. Effective dose (E) is a single parameter meant to reflect the relative risk from exposure to ionizing radiation. Therefore, it is necessary to calculate this parameter to indicate ionizing radiation relative risk. The aim of this study was to calculate the effective dose from 64-slice CTCA in Isfahan. To calculate the effective dose, an ionization chamber and a body phantom with diameter of 32 cm and length of 15 cm were used. CTCA radiation conditions commonly used in two centers were applied for this work. For all scans, computed tomography volume dose index (CTDI_v), dose-length product (DLP), and effective dose were obtained using dose-length-product method. The obtained CTDI_v, DLP, and effective dose were compared in two centers, and mean, maximum, and minimum values of effective dose for heart coronary CT angiography (CCTA) examinations and calcium score were compared with other studies. The amount of average, maximum, and minimum effective doses for heart CCTA examinations in two centers are 4.65 ± 0.06, 6.0489, and 3.492 mSv, respectively, and for calcium score test are, 1.04 ± 0.04, 2.155, and 0.98 mSv, respectively. CTDI_v, DLP, and effective dose values did not show any significant difference in two centers. Although the effective dose of CTCA and calcium score was lower than that of other studies, it is reasonable to reduce the effective dose to the minimum possible value to reduce the risk of cancer associated with ionizing radiation. The results of this study can be used to introduce the effective dose as a local diagnostic reference dose (DRL) for CTCA examinations in Isfahan Province.

Enhanced radiation dose and DNA damage associated with iodinated contrast media in diagnostic X-ray imaging

A review was undertaken of studies reporting increased DNA damage in circulating blood cells and increased organ doses, for X-ray exposures enhanced by iodinated contrast media (ICM), compared to unenhanced imaging. This effect may be due to ICM molecules acting as a source of secondary radiation (Auger/photoelectrons, fluorescence X-rays) following absorption of primary X-ray photons. It is unclear if the reported increase in DNA damage to blood cells necessarily implies an increased risk of developing cancer. Upon ICM-enhancement, the attenuation properties of blood differ substantially from surrounding tissues. Increased energy deposition is likely to occur within very close proximity to ICM molecules (within a few tens of micrometres). Consequently, in many situations, damage and dose enhancement may be restricted to the blood and vessel wall only. Increased cancer risks may be possible, in cases where ICM molecules are given sufficient time to reach the capillary network and interstitial fluid at the time of exposure. In all situations, the extrapolation of blood cell damage to other tissues requires caution where contrast media are involved. Future research is needed to determine the impact of ICM on dose to cells outside the blood itself and vessel walls, and to determine the concentration of ICM in blood vessels and interstitial fluid at the time of exposure.

The Effect of Contrast Material on Radiation Dose at CT: Part II. A Systematic Evaluation across 58 Patient Models

Purpose To estimate the radiation dose as a result of contrast medium administration in a typical abdominal computed tomographic (CT) examination across a library of contrast material-enhanced computational patient models. Materials and Methods In part II of this study, first, the technique described in part I of this study was applied to enhance the extended cardiac-torso models with patient-specific iodine-time profiles reflecting the administration of contrast material. Second, the patient models were deployed to assess the patient-specific organ dose as a function of time in a typical abdominal CT examination using Monte Carlo simulation. In this hypothesis-generating study, organ dose refers to the total energy deposited in the unit mass of the tissue inclusive of iodine. Third, a study was performed as a strategy to anticipate the biologically relevant dose (absorbed dose to tissue) in highly perfused organs such as the liver and kidney. The time-varying organ-dose increment values relative to those for unenhanced CT examinations were reported. Results The results from the patient models subjected to the injection protocol indicated up to a total 53%, 30%, 35%, 54%, 27%, 18%, 17%, and 24% increase in radiation dose delivered to the heart, spleen, liver, kidneys, stomach, colon, small intestine, and pancreas, respectively. The biologically relevant dose increase with respect to the dose at an unenhanced CT examination was in the range of 0%-18% increase for the liver and 27% for the kidney across 58 patient models. Conclusion The administration of contrast medium increases the total radiation dose. However, radiation dose, while relevant to be included in estimating the risk associated with contrast-enhanced CT, may still not fully characterize the total biologic effects. Therefore, given the fact that many CT diagnostic decisions would be impossible without the use of iodine, this study suggests the need to consider the effect of iodinated contrast material on the organ doses to patients undergoing CT studies when designing CT protocols. ^© RSNA, 2017 Online supplemental material is available for this article.