Aortic and hepatic contrast enhancement with abdominal 64-MDCT in pediatric patients: effect of body weight and iodine dose

Computed tomography numbers obtained for varying iodine contrast concentrations by different-generation dual-energy computed tomography scanners

We compared the computed tomography (CT) numbers from monochromatic images obtained using the first-generation (Discovery CT750 HD: GE Healthcare, Milwaukee, WI) and second-generation (Revolution CT: GE HealthCare) dual-energy CT (first and second DECT) scanners in phantom and clinical studies. In a polypropylene phantom, eight polypropylene tubes containing iodine at various concentrations (0.5, 1, 2, 5, 10, 12, 20, 30 mg I per ml) were arranged in an outer circle. The iodine densities and CT numbers obtained after imaging with different-generation DECT scanners were analyzed. The CT numbers from images obtained from 61 consecutive patients with aortic disease who underwent CT with different-generation DECT scanners were compared during the arterial and delayed phases. The iodine concentration obtained from second DECT was more accurate than that from the first DECT in the phantom study. A significantly higher contrast enhancement was observed with the second DECT compared with the first DECT during the arterial phase in the clinical study. Contrast enhancement was higher with the second DECT than with the first DECT, and the second DECT was effective in minimizing the use of contrast materials.

Machine learning-based identification of contrast-enhancement phase of computed tomography scans

Contrast-enhanced computed tomography scans (CECT) are routinely used in the evaluation of different clinical scenarios, including the detection and characterization of hepatocellular carcinoma (HCC). Quantitative medical image analysis has been an exponentially growing scientific field. A number of studies reported on the effects of variations in the contrast enhancement phase on the reproducibility of quantitative imaging features extracted from CT scans. The identification and labeling of phase enhancement is a time-consuming task, with a current need for an accurate automated labeling algorithm to identify the enhancement phase of CT scans. In this study, we investigated the ability of machine learning algorithms to label the phases in a dataset of 59 HCC patients scanned with a dynamic contrast-enhanced CT protocol. The ground truth labels were provided by expert radiologists. Regions of interest were defined within the aorta, the portal vein, and the liver. Mean density values were extracted from those regions of interest and used for machine learning modeling. Models were evaluated using accuracy, the area under the curve (AUC), and Matthew's correlation coefficient (MCC). We tested the algorithms on an external dataset (76 patients). Our results indicate that several supervised learning algorithms (logistic regression, random forest, etc.) performed similarly, and our developed algorithms can accurately classify the phase of contrast enhancement.

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.

Individualized Scan Protocols in Abdominal Computed Tomography: Radiation Versus Contrast Media Dose Optimization

BACKGROUND

In contrast-enhanced abdominal computed tomography (CT), radiation and contrast media (CM) injection protocols are closely linked to each other, and therefore a combination is the basis for achieving optimal image quality. However, most studies focus on optimizing one or the other parameter separately.

PURPOSE

Reducing radiation dose may be most important for a young patient or a population in need of repetitive scanning, whereas CM reduction might be key in a population with insufficient renal function. The recently introduced technical solution, in the form of an automated tube voltage selection (ATVS) slider, might be helpful in this respect. The aim of the current study was to systematically evaluate feasibility of optimizing either radiation or CM dose in abdominal imaging compared with a combined approach.

METHODS

Six Göttingen minipigs (mean weight, 38.9 ± 4.8 kg) were scanned on a third-generation dual-source CT. Automated tube voltage selection and automated tube current modulation techniques were used, with quality reference values of 120 kVref and 210 mAsref. Automated tube voltage selection was set at 90 kV semimode. Three different abdominal scan and CM protocols were compared intraindividually: (1) the standard "combined" protocol, with the ATVS slider position set at 7 and a body weight-adapted CM injection protocol of 350 mg I/kg body weight, iodine delivery rate (IDR) of 1.1 g I/s; (2) the CM dose-saving protocol, with the ATVS slider set at 3 and CM dose lowered to 294 mg I/kg, resulting in a lower IDR of 0.9 g I/s; (3) the radiation dose-saving protocol, with the ATVS slider position set at 11 and a CM dose of 441 mg I/kg and an IDR 1.3 g I/s, respectively. Scans were performed with each protocol in arterial, portal venous, and delayed phase. Objective image quality was evaluated by measuring the attenuation in Hounsfield units, signal-to-noise ratio, and contrast-to-noise ratio of the liver parenchyma. The overall image quality, contrast quality, noise, and lesion detection capability were rated on a 5-point Likert scale (1 = excellent, 5 = very poor). Protocols were compared for objective image quality parameters using 1-way analysis of variance and for subjective image quality parameters using Friedman test.

RESULTS

The mean radiation doses were 5.2 ± 1.7 mGy for the standard protocol, 7.1 ± 2.0 mGy for the CM dose-saving protocol, and 3.8 ± 0.4 mGy for the radiation dose-saving protocol. The mean total iodine load in these groups was 13.7 ± 1.7, 11.4 ± 1.4, and 17.2 ± 2.1 g, respectively. No significant differences in subjective overall image or contrast quality were found. Signal-to-noise ratio and contrast-to-noise ratio were not significantly different between protocols in any scan phase. Significantly more noise was seen when using the radiation dose-saving protocol (P < 0.01). In portal venous and delayed phases, the mean attenuation of the liver parenchyma significantly differed between protocols (P < 0.001). Lesion detection was significantly better in portal venous phase using the CM dose-saving protocol compared with the radiation dose-saving protocol (P = 0.037).

CONCLUSIONS

In this experimental setup, optimizing either radiation (-26%) or CM dose (-16%) is feasible in abdominal CT imaging. Individualizing either radiation or CM dose leads to comparable objective and subjective image quality. Personalized abdominal CT examination protocols can thus be tailored to individual risk assessment and might offer additional degrees of freedom.

Prediction of Patient Height and Weight With a 3-Dimensional Camera

OBJECTIVE

The aim of this study was to determine accuracy of height and weight prediction by a 3-dimensional (3D) camera.

METHODS

A total of 453 patients whose computed tomography imaging used a 3D camera from December 19, 2018 to March 19, 2019 were retrospectively identified. An image of each patient was taken before the computed tomography by a 3D camera mounted to the ceiling. Using infrared imaging and machine learning algorithms, patient height and weight were estimated from this 3D camera image. A total of 363 images were used for training. The test set consisted of 90 images. The height and weight estimates were compared with true height and weight to determine absolute and percent error. A value of P < 0.05 indicated statistical significance.

RESULTS

There was 2.0% (SD, 1.4) error in height estimation by the 3D camera, corresponding to 3.35 cm (SD, 2.39) absolute deviation (P = 1, n = 86). Weight estimation error was 5.1% (SD, 4.3), corresponding to 3.99 kg (SD, 3.11) absolute error (P = 0.74, n = 90).

CONCLUSION

Pictures obtained from a 3D camera can accurately predict patient height and weight.

A Solution for Homogeneous Liver Enhancement in Computed Tomography: Results From the COMpLEx Trial

OBJECTIVES

The aim of the study was to reach homogeneous enhancement of the liver, irrespective of total body weight (TBW) or tube voltage. An easy-to-use rule of thumb, the 10-to-10 rule, which pairs a 10 kV reduction in tube voltage with a 10% decrease in contrast media (CM) dose, was evaluated.

MATERIALS AND METHODS

A total of 256 patients scheduled for an abdominal CT in portal venous phase were randomly allocated to 1 of 4 groups. In group 1 (n = 64), a tube voltage of 120 kV and a TBW-adapted CM injection protocol was used: 0.521 g I/kg. In group 2 (n = 63), tube voltage was 90 kV and the TBW-adapted CM dosing factor remained 0.521 g I/kg. In group 3 (n = 63), tube voltage was reduced by 20 kV and CM dosing factor by 20% compared with group 1, in line with the 10-to-10 rule (100 kV; 0.417 g I/kg). In group 4 (n = 66), tube voltage was decreased by 30 kV paired with a 30% decrease in CM dosing factor compared with group 1, in line with the 10-to-10 rule (90 kV; 0.365 g I/kg). Objective image quality was evaluated by measuring attenuation in Hounsfield units (HU), signal-to-noise ratio, and contrast-to-noise ratio in the liver. Overall subjective image quality was assessed by 2 experienced readers by using a 5-point Likert scale. Two-sided P values below 0.05 were considered significant.

RESULTS

Mean attenuation values in groups 1, 3, and 4 were comparable (118.2 ± 10.0, 117.6 ± 13.9, 117.3 ± 21.6 HU, respectively), whereas attenuation in group 2 (141.0 ± 18.2 HU) was significantly higher than all other groups (P < 0.01). No significant difference in attenuation was found between weight categories 80 kg or less and greater than 80 kg within the 4 groups (P ≥ 0.371). No significant differences in subjective image quality were found (P = 0.180).

CONCLUSIONS

The proposed 10-to-10 rule is an easily reproducible method resulting in similar enhancement in portal venous CT of the liver throughout the patient population, irrespective of TBW or tube voltage.

Tailoring Contrast Media Protocols to Varying Tube Voltages in Vascular and Parenchymal CT Imaging: The 10-to-10 Rule

The latest technical developments in CT have created the possibility for individualized scan protocols at variable kV settings. Lowering tube voltages closer to the K-edge of iodine increases attenuation. However, the latter is also influenced by patient characteristics such as total body weight. To maintain a robust contrast enhancement throughout the patient population in both vascular and parenchymal CT scans, one must adapt the contrast media administration protocols to both the selected kV setting and patient body habitus. This article proposes a simple rule of thumb for how to adapt the contrast media protocol to any kV setting: the 10-to-10 rule.

Individually Body Weight-Adapted Contrast Media Application in Computed Tomography Imaging of the Liver at 90 kVp

OBJECTIVES

The aim of the present study was to evaluate the attenuation and image quality (IQ) of a body weight-adapted contrast media (CM) protocol compared with a fixed injection protocol in computed tomography (CT) of the liver at 90 kV.

MATERIALS AND METHODS

One hundred ninety-nine consecutive patients referred for abdominal CT imaging in portal venous phase were included. Group 1 (n = 100) received a fixed CM dose with a total iodine load (TIL) of 33 g I at a flow rate of 3.5 mL/s, resulting in an iodine delivery rate (IDR) of 1.05 g I/s. Group 2 (n = 99) received a body weight-adapted CM protocol with a dosing factor of 0.4 g I/kg with a subsequent TIL adapted to the patients' weight. Injection time of 30 seconds was kept identical for all patients. Therefore, flow rate and IDR changed with different body weight. Patients were divided into 3 weight categories; 70 kg or less, 71 to 85 kg, and 86 kg or greater. Attenuation (HU) in 3 segments of the liver, signal-to-noise ratio, and contrast-to-noise ratio were used to evaluate objective IQ. Subjective IQ was assessed by a 5-point Likert scale. Differences between groups were statistically analyzed (P < 0.05 was considered statistically significant).

RESULTS

No significant differences in baseline characteristics were found between groups. The CM volume and TIL differed significantly between groups (P < 0.01), with mean values in group 1 of 110 mL and 33 g I, and in group 2 of 104.1 ± 21.2 mL and 31.2 ± 6.3 g I, respectively. Flow rate and IDR were not significantly different between groups (P > 0.05). Body weight-adapted protocoling led to more homogeneous enhancement of the liver parenchyma compared with a fixed protocol with a mean enhancement per weight category in group 2 of 126.5 ± 15.8, 128.2 ± 15.3, and 122.7 ± 21.2 HU compared with that in group 1 of 139.9 ± 21.4, 124.6 ± 24.8, and 116.2 ± 17.8 HU, respectively.

CONCLUSIONS

Body weight-adapted CM injection protocols result in more homogeneous enhancement of the liver parenchyma at 90 kV in comparison to a fixed CM volume with comparable objective and subjective IQ, whereas overall CM volume can be safely reduced in more than half of patients.

MDCT of the liver in obese patients: evaluation of a different method to optimize iodine dose

PURPOSE

To prospectively compare two different approaches for estimating the amount of intravenous contrast media (CM) needed for multiphasic MDCT of the liver in obese patients.

MATERIALS AND METHODS

This single-center, HIPAA-compliant prospective study was approved by our Institutional Review Board. Ninety-six patients (55 men, 41 women), with a total of 42 hypovascular liver lesions, underwent MDCT of the liver. The amount of contrast medium injected was computed according to the patient's lean body weight which was estimated using either a bioimpedance device (Group A) or the James formula (Group B). The following variables were compared between the two groups: the amount of contrast medium injected (in grams of Iodine, gI), the contrast enhancement index (CEI) and the lesion-to-liver contrast-to-noise ratio.

RESULTS

Protocols A and B yielded significant differences in the amount of CM injected (mean values 41.9 ± 4.41 gI in Group A vs. 35.9 ± 5.75 gI in Group B; P = 0.021). The mean CEI value and lesion-to-liver contrast-to-noise ratio measured on the portal phase were significantly higher with protocol A than with protocol B (P < 0.05).

CONCLUSIONS

Our study shows that the adoption of a bioimpedance device in obese patients improves liver parenchymal enhancement and lesion conspicuity.

A comparison of dynamic contrast-enhanced CT and MR imaging-derived measurements in patients with cervical cancer

This work is to compare the kinetic parameters derived from the DCE-CT and -MR data of a group of 37 patients with cervical cancer. The modified Tofts model and the reference tissue method were applied to estimate kinetic parameters. In the MR kinetic analyses using the modified Tofts model for each patient data set, both the arterial input function (AIF) measured from DCE-MR images and a population-averaged AIF from the literature were applied to the analyses, while the measured AIF was used for the CT kinetic analysis. The kinetic parameters obtained from both modalities were compared. Significant moderate correlations were found in modified Tofts parameters [volume transfer constant(K(trans) ) and rate constant (k(ep) )] between CT and MR analysis for MR with the measured AIFs (R = 0·45, P<0·01 and R = 0·40, P<0·01 in high-K(trans) region; R = 0·38, P<0·01 and R = 0·80, P<0·01 in low-K(trans) region) as well as with the population-averaged AIF (R = 0·59, P<0·01 and R = 0·62, P<0·01 in high-K(trans) region; R = 0·50, P<0·01 and R = 0·63, P<0·01 in low-K(trans) region), respectively. In addition, from the Bland-Altman plot analysis, it was found that the systematic biases (the mean difference) between the modalities were drastically reduced in magnitude by adopting the population-averaged AIF for the MR analysis instead of the measured ones (from 51·5% to 18·9% for K(trans) and from 21·7% to 4·1% for k(ep) in high-K(trans) region; from 73·0% to 29·4% for K(trans) and from 63·4% to 24·5% for k(ep) in low-K(trans) region). The preliminary results showed the feasibility in the interchangeable use of the two imaging modalities in assessing cervical cancers.

Differential diagnosis of sclerosing cholangitis with autoimmune pancreatitis and periductal infiltrating cancer in the common bile duct at dynamic CT, endoscopic retrograde cholangiography and MR cholangiography

OBJECTIVES

To compare findings at dynamic computed tomography (CT), endoscopic retrograde cholangiography (ERC) and magnetic resonance cholangiography (MRC) in patients with sclerosing cholangitis with autoimmune pancreatitis (SC-AIP) and periductal infiltrating cancer in the common bile duct (CBD), and to evaluate the diagnostic performance of ERC and MRC in differentiating between the two diseases.

METHODS

Bile duct changes at dynamic CT, ERC and MRC were compared in 58 patients with SC-AIP and CBD involvement and 93 patients with periductal infiltrating CBD cancer. Two radiologists rated their confidence in differentiating between the two diseases and the diagnostic performances of ERC and MRC were compared.

RESULTS

At CT, SC-AIP was more frequently associated with intrapancreatic CBD involvement, thinner CBD walls, concentric wall thickening, smooth outer margins, and lower degrees of upstream ductal dilatation and contrast enhancement (P ≤ 0.05) than CBD cancer. At ERC and MRC, SC-AIP was more frequently associated with smooth margins, gradual and symmetric narrowing, multifocal involvement and hourglass appearance (P ≤ 0.027) than CBD cancer. MRC showed good diagnostic performance comparable to ERC.

CONCLUSIONS

Dynamic CT, ERC and MRC can be helpful in distinguishing SC-AIP from periductal infiltrating CBD cancer. MRC may be a useful diagnostic alternative to ERC in differentiating between the two diseases.

KEY POINTS

• SC-AIP often mimics periductal infiltrating ductal cancer. • Imaging findings of SC-AIP and periductal infiltrating CBD cancer can be similar. • Dynamic CT, ERC and MRC help differentiate between these two diseases. • MRC may be a useful diagnostic alternative to ERC.

Multidetector CT in children: current concepts and dose reduction strategies

The recent technical development of multidetector CT (MDCT) has contributed to a substantial increase in its diagnostic applications and accuracy in children. A major drawback of MDCT is the use of ionising radiation with the risk of inducing secondary cancer. Therefore, justification and optimisation of paediatric MDCT is of great importance in order to minimise these risks ("as low as reasonably achievable" principle). This review will focus on all technical and non-technical aspects relevant for paediatric MDCT optimisation and includes guidelines for radiation dose level-based CT protocols.