Contrast Enhancement Of Liver Research Articles

Evaluation of Iodinated Contrast Media Use in Abdominal CT Scans in Cancer Assessments: A Cross-Sectional Study in Lomé (Togo).

There is great variability between centers regarding contrast injection protocols. They should only be injected if they can provide useful information for diagnosis with the necessary and sufficient quantity of iodine. We wanted to know through this study if the use of iodinated contrast media is optimised in abdominal CT scans performed for cancer assessment in Lomé. It was a cross-sectional, descriptive, and analytical study with a prospective collection over a period of 6 months in three CT units in Lomé. It involved abdominal CT scans performed for oncological evaluation. Data were reported as the mean ± standard deviation. The Pearson correlation coefficient, ANOVA, chi-square, and the Fisher test were used. A total of 218 examinations were recorded. The female sex represented 56.88% of the patients. The mean age was 50.92 ± 15.78 years. The mean weight was 70.46 ± 15.23 kg. The mean BMI was 24.91 ± 5.32 kg/m2. The examinations were performed with a voltage of 120 kV in 195 cases (89.45%). The mean dose of injected iodine was 0.42 ± 0.09 gI/kg with a dose of 0.40 gI/kg at 80 kV and 0.45 gI/kg at 130 kV. The mean injection rate was 2.90 ± 0.34 mL/s. The mean injected volume was 83.19 ± 7.29 mL. The mean duration of the injection was 30.60 ± 7.39 s. The mean iodine delivery rate was 0.98 ± 0.17 gI/s. There was no saline injection in 152 cases (69.72%). Liver contrast enhancement was satisfactory in 94.5% of cases. There was a strong negative linear correlation between the dose of injected iodine and weight. Optimization guidelines for the use of iodinated contrast media are not always applied. Therefore, monitoring and benchmarking programmes for iodinated contrast injection protocols that involve all radiology personnel should be implemented.

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

ObjectiveTo 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. MethodsThe 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. ResultsThe 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 %. ConclusionsA 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.

Interpretable Machine Learning for Characterization of Focal Liver Lesions by Contrast-Enhanced Ultrasound.

This work proposes an interpretable radiomics approach to differentiate between malignant and benign focal liver lesions (FLLs) on contrast-enhanced ultrasound (CEUS). Although CEUS has shown promise for differential FLLs diagnosis, current clinical assessment is performed only by qualitative analysis of the contrast enhancement patterns. Quantitative analysis is often hampered by the unavoidable presence of motion artifacts and by the complex, spatiotemporal nature of liver contrast enhancement, consisting of multiple, overlapping vascular phases. To fully exploit the wealth of information in CEUS, while coping with these challenges, here we propose combining features extracted by the temporal and spatiotemporal analysis in the arterial phase enhancement with spatial features extracted by texture analysis at different time points. Using the extracted features as input, several machine learning classifiers are optimized to achieve semiautomatic FLLs characterization, for which there is no need for motion compensation and the only manual input required is the location of a suspicious lesion. Clinical validation on 87 FLLs from 72 patients at risk for hepatocellular carcinoma (HCC) showed promising performance, achieving a balanced accuracy of 0.84 in the distinction between benign and malignant lesions. Analysis of feature relevance demonstrates that a combination of spatiotemporal and texture features is needed to achieve the best performance. Interpretation of the most relevant features suggests that aspects related to microvascular perfusion and the microvascular architecture, together with the spatial enhancement characteristics at wash-in and peak enhancement, are important to aid the accurate characterization of FLLs.

Experience of using contrast-enhanced ultrasound examination in the most common malignant neoplasms of the liver

Aim. To study the features of contrast enhancement of malignant neoplasms of the liver in patients with and without cirrhosis (LC), to study the differences in the dynamics of contrast enhancement of liver are metastatic lesions (MTS) and hepatocellular carcinoma (HCC).Material and methods. A retrospective analysis results 58 patients with HCC (group 1) and 51 patients with liver metastases (group 2) was carried out based on morphological data. According to the criterion for the presence of LC, group 1 was divided into two subgroups. The main method of radiological diagnostics was contrast enhancement ultrasound (CEUS).Results. The indicators of the dynamics of the Wash-in of an ultrasound contrast agent into the HCC node and the dynamics of the drug WASH-OUT from the focus in patients with LC did not significantly differ from those in patients without cirrhosis. HCC is characterized by the onset of leaching of the ultrasound contrast agent after 62 seconds from the beginning of the study, which significantly differs from MTS (p <0.05). The parameters in predicting the G3 stage of the tumor were as follows: the parameter “onset of WASH-OUT” of the from the focus <79 sec, the parameter “time of maximum WASH-OUT” of the ultrasound contrast agent <270 seconds. In our opinion, certain difficulties are presented by the diagnosis of highly differentiated carcinomas due to the absence of the WASH-OUT phenomenon in 50% of patients. Differential diagnosis of metastases should be based on a combination of a number of signs, the most important of which, in our opinion, are: early onset of elution of ultrasound contrast agent, “black hole” symptom, peripheral ring-shaped enhancement in arterial phase.Conclusion. The data obtained with the help of CEUS confirm the effect of “arterialization of hepatic blood flow” in patients with LC. Differences in the parameters of contrasting HCC nodes in subgroups of patients with and without LC are not statistically significant. The polymorphism of the signs detected in MTS in the liver is due to the morphology of the primary tumor and the size of the neoplasms. Differential diagnosis should be based on a combination of signs of the dynamics of ultrasound contrast agents.

Experience of using contrast-enhanced ultrasound examination in the most common malignant neoplasms of the liver

Aim. To study the features of contrast enhancement of malignant neoplasms of the liver in patients with and without cirrhosis (LC), to study the differences in the dynamics of contrast enhancement of liver are metastatic lesions (MTS) and hepatocellular carcinoma (HCC).Material and methods. A retrospective analysis results 58 patients with HCC (group 1) and 51 patients with liver metastases (group 2) was carried out based on morphological data. According to the criterion for the presence of LC, group 1 was divided into two subgroups. The main method of radiological diagnostics was contrast enhancement ultrasound (CEUS).Results. The indicators of the dynamics of the Wash-in of an ultrasound contrast agent into the HCC node and the dynamics of the drug WASH-OUT from the focus in patients with LC did not significantly differ from those in patients without cirrhosis. HCC is characterized by the onset of leaching of the ultrasound contrast agent after 62 seconds from the beginning of the study, which significantly differs from MTS (p <0.05). The parameters in predicting the G3 stage of the tumor were as follows: the parameter “onset of WASH-OUT” of the from the focus ><79 sec, the parameter “time of maximum WASH-OUT” of the ultrasound contrast agent ><270 seconds. In our opinion, certain difficulties are presented by the diagnosis of highly differentiated carcinomas due to the absence of the WASH-OUT phenomenon in 50% of patients. Differential diagnosis of metastases should be based on a combination of a number of signs, the most important of which, in our opinion, are: early onset of elution of ultrasound contrast agent, “black hole” symptom, peripheral ring-shaped enhancement in arterial phase.>Conclusion. The data obtained with the help of CEUS confirm the effect of “arterialization of hepatic blood flow” in patients with LC. Differences in the parameters of contrasting HCC nodes in subgroups of patients with and without LC are not statistically significant. The polymorphism of the signs detected in MTS in the liver is due to the morphology of the primary tumor and the size of the neoplasms. Differential diagnosis should be based on a combination of signs of the dynamics of ultrasound contrast agents.

Corrigendum: Aorta, liver and portal vein CT contrast enhancement during the portal venous phase are positively associated with abdominal fat percentage in dogs.

Corrigendum: Aorta, liver and portal vein CT contrast enhancement during the portal venous phase are positively associated with abdominal fat percentage in dogs.

Dual-Contrast Biphasic Liver Imaging With Iodine and Gadolinium Using Photon-Counting Detector Computed Tomography: An Exploratory Animal Study.

The aims of this study were to develop a single-scan dual-contrast protocol for biphasic liver imaging with 2 intravenous contrast agents (iodine and gadolinium) and to evaluate its effectiveness in an exploratory swine study using a photon-counting detector computed tomography (PCD-CT) system. A dual-contrast CT protocol was developed for PCD-CT to simultaneously acquire 2 phases of liver contrast enhancement, with the late arterial phase enhanced by 1 contrast agent (iodine-based) and the portal venous phase enhanced by the other (gadolinium-based). A gadolinium contrast bolus (gadobutrol: 64 mL, 8 mL/s) and an iodine contrast bolus (iohexol: 40 mL, 5 mL/s) were intravenously injected in the femoral vein of a healthy domestic swine, with the second injection initiated after 17 seconds from the beginning of the first injection; PCD-CT image acquisition was performed 12 seconds after the beginning of the iodine contrast injection. A convolutional neural network (CNN)-based denoising technique was applied to PCD-CT images to overcome the inherent noise magnification issue in iodine/gadolinium decomposition task. Iodine and gadolinium material maps were generated using a 3-material decomposition method in image space. A set of contrast samples (mixed iodine and gadolinium) was attached to the swine belly; quantitative accuracy of material decomposition in these inserts between measured and true concentrations was calculated using root mean square error. An abdominal radiologist qualitatively evaluated the delineation of arterial and venous vasculatures in the swine liver using iodine and gadolinium maps obtained using the dual-contrast PCD-CT protocol. The iodine and gadolinium samples attached to the swine were quantified with root mean square error values of 0.75 mg/mL for iodine and 0.45 mg/mL for gadolinium from the contrast material maps derived from the denoised PCD-CT images. Hepatic arteries containing iodine and veins containing gadolinium in the swine liver could be clearly visualized. Compared with the original images, better distinctions between 2 liver phases were achieved using CNN denoising, with approximately 60% to 80% noise reduction in contrast material maps acquired with the denoised PCD-CT images compared with the original images. Simultaneous biphasic liver imaging in a single multienergy PCD-CT acquisition using a dual-contrast (iodine and gadolinium) injection protocol and CNN denoising was demonstrated in a swine study, where the enhanced hepatic arteries (containing iodine) and the enhanced hepatic veins (containing gadolinium) could be clearly visualized and delineated in the swine liver.

Contrast media dose adjustment to allometric parameters of body mass in multiphasic CT of the liver: A comparison of different metrics

PurposeTo assess correlations of lean body weight (LBW) calculated with various formulas, total body weight (TBW), body height (BH), body mass index (BMI), body surface area (BSA) and fat-free mass (FFM) with vascular and parenchymal enhancement in multiphasic CT of the liver. MethodThirty consecutive patients underwent multiphasic CT of the liver using constant iodine dose and flow rate. Contrast enhancement of aorta, portal vein and liver was calculated by measuring mean vascular and parenchymal attenuation in pre-contrast and post-contrast phases. Correlations of TBW, BH, BMI, BSA, FFM, and LBW (calculated with formulas of Boer, Hume, James and Green&Duffull) with enhancement were tested using Spearman’s correlation coefficient. The method of Fieller et al. was used to calculate 95 % confidence intervals. A p-value ≤ 0.05 was considered statistically significant. ResultsAortal enhancement correlated strongly with TBW, BSA, LBWBoer and LBWHume and moderately with BH, BMI, FFM, LBWJames and LBWGreen&Duffull. Liver enhancement in the late arterial phase correlated moderately with TBW, FFM, LBWBoer, LBWHume and LBWGreen&Duffull and weakly with BSA. Liver enhancement in the portal venous phase correlated strongly with TBW, BSA, FFM, LBWBoer, LBWHume and LBWGreen&Duffull, whereby overlap of the 95 % CI graphs demonstrated that the differences in the correlation coefficients were not statistically significant. Liver enhancement in the delayed phase correlated moderately with BH but did not correlate significantly with any other parameter. ConclusionRegardless of the form used for calculation, LBW did not correlate statistically significantly stronger than TBW with vascular or parenchymal enhancement of the liver.

Optimization of contrast medium volume for abdominal CT in oncologic patients: prospective comparison between fixed and lean body weight-adapted dosing protocols

BackgroundPatient body size represents the main determinant of parenchymal enhancement and by adjusting the contrast media (CM) dose to patient weight may be a more appropriate approach to avoid a patient over dosage of CM. To compare the performance of fixed-dose and lean body weight (LBW)-adapted contrast media dosing protocols, in terms of image quality and parenchymal enhancement.ResultsOne-hundred cancer patients undergoing multiphasic abdominal CT were prospectively enrolled in this multicentric study and randomly divided in two groups: patients in fixed-dose group (n = 50) received 120 mL of CM while in LBW group (n = 50) the amount of CM was computed according to the patient’s LBW. LBW protocol group received a significantly lower amount of CM (103.47 ± 17.65 mL vs. 120.00 ± 0.00 mL, p < 0.001). Arterial kidney signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) and pancreatic CNR were significantly higher in LBW group (all p ≤ 0.004). LBW group provided significantly higher arterial liver, kidney, and pancreatic contrast enhancement index (CEI) and portal venous phase kidney CEI (all p ≤ 0.002). Significantly lower portal vein SNR and CNR were observed in LBW-Group (all p ≤ 0.020).ConclusionsLBW-adapted CM administration for abdominal CT reduces the volume of injected CM and improves both image quality and parenchymal enhancement.

Lean body weight versus total body weight to calculate the iodinated contrast media volume in abdominal CT: a randomised controlled trial

ObjectivesIodinated contrast media (ICM) could be more appropriately dosed on patient lean body weight (LBW) than on total body weight (TBW).MethodsAfter Ethics Committee approval, trial registration NCT03384979, patients aged ≥ 18 years scheduled for multiphasic abdominal CT were randomised for ICM dose to LBW group (0.63 gI/kg of LBW) or TBW group (0.44 gI/kg of TBW). Abdominal 64-row CT was performed using 120 kVp, 100–200 mAs, rotation time 0.5 s, pitch 1, Iopamidol (370 mgI/mL), and flow rate 3 mL/s. Levene, Mann–Whitney U, and χ2 tests were used. The primary endpoint was liver contrast enhancement (LCE).ResultsOf 335 enrolled patients, 17 were screening failures; 44 dropped out after randomisation; 274 patients were analysed (133 LBW group, 141 TBW group). The median age of LBW group (66 years) was slightly lower than that of TBW group (70 years). Although the median ICM-injected volume was comparable between groups, its variability was larger in the former (interquartile range 27 mL versus 21 mL, p = 0.01). The same was for unenhanced liver density (IQR 10 versus 7 HU) (p = 0.02). Median LCE was 40 (35–46) HU in the LBW group and 40 (35–44) HU in the TBW group, without significant difference for median (p = 0.41) and variability (p = 0.23). Suboptimal LCE (< 40 HU) was found in 64/133 (48%) patients in the LBW group and 69/141 (49%) in the TBW group, but no examination needed repeating.ConclusionsThe calculation of the ICM volume to be administered for abdominal CT based on the LBW does not imply a more consistent LCE.

Accelerating Chan–Vese model with cross-modality guided contrast enhancement for liver segmentation

Accurate and fast liver segmentation remains a challenging and important task for clinicians. Segmentation algorithms are slow and inaccurate due to noise and low quality images in computed tomography (CT) abdominal scans. Chan–Vese is an active contour based powerful and flexible method for image segmentation due to superior noise robustness. However, it is quite slow due to time-consuming partial differential equations, especially for large medical datasets. This can pose a problem for a real-time implementation of liver segmentation and hence, an efficient parallel implementation is highly desirable. Another important aspect is the contrast of CT liver images. Liver slices are sometimes very low in contrast which reduces the overall quality of liver segmentation. Hence, we implement cross-modality guided liver contrast enhancement as a pre-processing step to liver segmentation. GPU implementation of Chan–Vese improves average speedup by 99.811 (± 7.65) times and 14.647 (± 1.155) times with and without enhancement respectively in comparison with the CPU. Average dice, sensitivity and accuracy of liver segmentation are 0.656, 0.816 and 0.822 respectively on the original liver images and 0.877, 0.964 and 0.956 respectively on the enhanced liver images improving the overall quality of liver segmentation.

Prediction of Sufficient Liver Enhancement on the Gadoxetate Disodium-enhanced Hepatobiliary Phase Imaging Using Transitional Phase Images and Albumin-bilirubin Grade.

Purpose:To investigate whether the contrast enhancement effect in hepatobiliary phase (HBP) images can be predicted using transitional phase (3-min delay) images on liver magnetic resonance imaging (MRI) based on the quantitative liver–spleen contrast ratio (Q-LSC) and albumin–bilirubin (ALBI) grade.Methods:Overall, 212 patients (124 men and 88 women; mean age 66.7 ± 11.1 years) who underwent blood tests (assessed within 1 month of performing MRI) were included; patients with diffuse tumor, hepatectomy, splenectomy, Gamna–Gandy bodies in the spleen, and movement artifacts were excluded. Q-LSC was calculated using the signal intensity of the liver divided that of the spleen. Q-LSC > 1.5 (cut-off value) indicates a relatively higher sensitivity for detecting of hepatic lesions. To predict the contrast enhancement effect in HBP using Q-LSC of 3-min delay images, Q-LSC of 10- and 15-min delay images were compared for each ALBI grade based on Q-LSC of 3-min delay images. Furthermore, to verify the accuracy of this prediction, the proportion of cases with Q-LSC > 1.5 in 10- and 15 min delay images was calculated based on Q-LSC on 3-min delay images.Results:The higher the Q-LSC on the 3-min delay image, the higher was the Q-LSC on its 10- and 15-min delay images. The proportion of cases with Q-LSC > 1.5 in 10- and 15-min delay images was higher for ALBI grade 1 than for ALBI grades 2 and 3 even in the same Q-LSC on 3-min delay images. Q-LSC was <1 in a 3-min delay image and <1.5 in a 15-min delay image in 62.2% of patients with ALBI grade 1 and 82.1% of patients with ALBI grades 2 and 3.Conclusion:The liver contrast enhancement effect in HBP images could be predicted using a 3-min delay image based on Q-LSC and ALBI grade.

The aortic and hepatic contrast enhancement at CT and its correlations with various body size index

Objective To evaluate the effect of height (HT), total body weight (TBW), body mass index (BMI), lean body weight (LBW), body surface area (BSA) and blood volume (BV) on aortic and liver contrast enhancement during upper abdominal contrast-enhanced CT scans. Methods One hundred and thirteen enrolled patients underwent upper abdominal multiphase contrast-enhanced CT scans. The enhancement (ΔHU) of aorta in hepatic arterial phase and liver parenchyma in portal venous phase were measured and calculated. The ΔHU values difference of aorta and liver parenchyma in subgroups between males and females, TBW<60 kg and TBW≥60 kg, BMI<25 kg/m2 and BMI≥25 kg/m2 were compared. To evaluate the effect of the patient′s body parameters on aortic and hepatic enhancement, we performed simple linear regression analyses between the change in CT numbers per gram of iodine (ΔHU/gI) at aorta and liver and each of the following: HT, TBW, BMI, LBW, BSA, and BV. Pearson and t test were used. Results The mean ΔHU values of aorta and liver were significantly lower at males than that of at females (P<0.05). They were higher at TBW<60 kg patients than at TBW≥60 kg patients(P<0.05), and the mean ΔHU values of the liver at BMI<25 kg/m2 patients were significantly higher than at BMI≥25 kg/m2 patients(P<0.05). The proportion of the ΔHU values at liver less than 50 HU was higher at males (18.3%, 11/60) than at females (7.5%, 4/53). The most obvious negative correlation coefficients were found between the ΔHU/gI of aorta and LBW at hepatic arterial phase (r=-0.559, P<0.01), and between the ΔHU/gI of liver and BSA at portal venous phase (r=-0.680, P<0.01). Conclusion LBW or BSA could be the alternative body index to TBW for the calculation of personalized iodine dose protocol at aortic and liver enhanced CT scans. Key words: Contrast media; Tomography, X-ray computed; Aorta; Liver

Assessment of hepatitis and fibrosis using Gd-EOB-DTPA MRI in dogs

BackgroundGadoxetate sodium (Gd-EOB-DTPA) is taken into hepatocytes and excreted into the bile. Hepatocytes with reduced function or dysfunction due to hepatocellular carcinoma (HCC), hepatitis or hepatic fibrosis show impaired Gd-EOB-DTPA...

GPU acceleration of liver enhancement for tumor segmentation

Background and objective: Medical image segmentation plays a vital role in medical image analysis. There are many algorithms developed for medical image segmentation which are based on edge or region characteristics. These are dependent on the quality of the image. The contrast of a CT or MRI image plays an important role in identifying region of interest i.e. lesion(s). In order to enhance the contrast of image, clinicians generally use manual histogram adjustment technique which is based on 1D histogram specification. This is time consuming and results in poor distribution of pixels over the image. Cross modality based contrast enhancement is 2D histogram specification technique. This is robust and provides a more uniform distribution of pixels over CT image by exploiting the inner structure information from MRI image. This helps in increasing the sensitivity and accuracy of lesion segmentation from enhanced CT image. The sequential implementation of cross modality based contrast enhancement is slow. Hence we propose GPU acceleration of cross modality based contrast enhancement for tumor segmentation.Methods: The aim of this study is fast parallel cross modality based contrast enhancement for CT liver images. This includes pairwise 2D histogram, histogram equalization and histogram matching. The sequential implementation of the cross modality based contrast enhancement is computationally expensive and hence time consuming. We propose persistence and grid-stride loop based fast parallel contrast enhancement for CT liver images. We use enhanced CT liver image for the lesion or tumor segmentation. We implement the fast parallel gradient based dynamic seeded region growing for lesion segmentation.Results: The proposed parallel approach is 104.416 ( ± 5.166) times faster compared to the sequential implementation and increases the sensitivity and specificity of tumor segmentation.Conclusion: The cross modality approach is inspired by 2D histogram specification which incorporates spatial information existing in both guidance and input images for remapping the input image intensity values. The cross modality based liver contrast enhancement improves the quality of tumor segmentation.

Imaging Characteristics of USPIO Nanoparticles (

Iron nanoparticles have an increasingly more and more important role in MR molecular imaging due to their novel magnetic and surface chemical properties. They provide new possibilities for noninvasive diagnosis and treatment monitoring, especially for tissues that are rich in macrophages. The smaller size and prolongation of the plasma half-life change the in vivo fate of ultrasmall superparamagnetic iron oxide (USPIO) nanoparticles captured by liver in reticuloendothelial system (RES) or mononuclear phagocytic system (MPS). However, there is still a lack of MR imaging studies on the liver assessing USPIO nanoparticles <5 nm in size to reflect its absorption and clearance properties. In this study, we used MRI to study the in vitro phantom and in vivo rat liver imaging characteristics of USPIO nanoparticles (<5 nm). The results showed that USPIO nanoparticles (<5 nm) could potentially reduce longitudinal and transverse relaxation times and showed similar T1 relaxation rates compared with commercial gadolinium chelates. In addition, USPIO nanoparticles (<5 nm) in vivo demonstrated both positive (T1) and negative (T2) liver contrast enhancement in healthy rats' liver. Furthermore, USPIO nanoparticles showed relatively good in vitro biocompatibility and fast clearance (within 45.17 minutes after intravenous injection) in the normal liver. Taken together, these data might inspire a new personalized and precise diagnostic tool and stimulate new applications for specific targeted molecular probes.

State-of-the-art MR Imaging of Fat-containing Focal Lesions of the Liver.

Fat can be identified in numerous liver lesions, and usually is not a specific finding. Distinguishing between different kinds of fatty deposits is an important part of differential diagnosis. Magnetic Resonance Imaging (MRI) is superior to other imaging techniques because it allows distinguishing intracellular from macroscopic fat. Intracellular lipid may be found in focal hepatic steatosis, hepatic adenoma, hepatocellular carcinoma and, less commonly, in focal nodular hyperplasia as well as regenerative and dysplastic nodules. Macroscopic fat is seen in angiomyolipoma, lipoma, metastases from fatcontaining neoplasms, primary or metastatic liposarcoma, hydatid cyst, pseudolipoma of the Glisson capsule, pericaval fat collection, lipopeliosis, hepatic teratoma, focal hepatic extramedullary haematopoiesis and adrenal rest tumour. Liver nodules should be characterised with regard to underlying liver condition, MRI characteristics and contrast enhancement pattern, including hepatobiliary phase. In many cases, identification of fatty content may help narrowing the differential diagnosis.

Abdominal CT: a radiologist-driven adjustment of the dose of iodinated contrast agent approaches a calculation per lean body weight

BackgroundThe contrast agent (CA) dose for abdominal computed tomography (CT) is typically based on patient total body weight (TBW), ignoring adipose tissue distribution. We report on our experience of dosing according to the lean body weight (LBW).MethodsAfter Ethics Committee approval, we retrospectively screened 219 consecutive patients, 18 being excluded for not matching the inclusion criteria. Thus, 201 were analysed (106 males), all undergoing a contrast-enhanced abdominal CT with iopamidol (370 mgI/mL) or iomeprol (400 mgI/mL). LBW was estimated using validated formulas. Liver contrast-enhancement (CEL) was measured. Data were reported as mean ± standard deviation. Pearson correlation coefficient, ANOVA, and the Levene test were used.ResultsMean age was 66 ± 13 years, TBW 72 ± 15 kg, LBW 53 ± 11 kg, and LBW/TBW ratio 74 ± 8%; body mass index was 26 ± 5 kg/m2, with 9 underweight patients (4%), 82 normal weight (41%), 76 overweight (38%), and 34 obese (17%). The administered CA dose was 0.46 ± 0.06 gI/kg of TBW, corresponding to 0.63 ± 0.09 gI/kg of LBW. A negative correlation was found between TBW and CA dose (r = -0.683, p < 0.001). CEL (Hounsfield units) was 51 ± 18 in underweight patients, 44 ± 8 in normal weight, 42 ± 9 in overweight, and 40 ± 6 in obese, with a significant difference for both mean (p = 0.004) and variance (p < 0.001). A low but significant positive correlation was found between CEL and CA dose in gI per TBW (r = 0.371, p < 0.001) or per LBW (r = 0.333, p < 0.001).ConclusionsThe injected CA dose was highly variable, with obese patients receiving a lower dose than underweight patients, as a radiologist-driven ‘compensation effect’. Diagnostic abdomen CT examinations may be obtained using 0.63 gI/kg of LBW.

Lean Body Weight-Tailored Iodinated Contrast Injection in Obese Patient: Boer versus James Formula.

Purpose To prospectively compare the performance of James and Boer formula in contrast media (CM) administration, in terms of image quality and parenchymal enhancement in obese patients undergoing CT of the abdomen. Materials and Methods Fifty-five patients with a body mass index (BMI) greater than 35 kg/m2 were prospectively included in the study. All patients underwent 64-row CT examination and were randomly divided in two groups: 26 patients in Group A and 29 patients in Group B. The amount of injected CM was computed according to the patient's lean body weight (LBW), estimated using either Boer formula (Group A) or James formula (Group B). Patient's characteristics, CM volume, contrast-to-noise ratio (CNR) of liver, aorta and portal vein, and liver contrast enhancement index (CEI) were compared between the two groups. For subjective image analysis readers were asked to rate the enhancement of liver, kidneys, and pancreas based on a 5-point Likert scale. Results Liver CNR, aortic CNR, and portal vein CNR showed no significant difference between Group A and Group B (all P ≥ 0.177). Group A provided significantly higher CEI compared to Group B (P = 0.007). Group A and Group B returned comparable overall subjective enhancement values (3.54 and vs 3.20, all P ≥ 0.199). Conclusions Boer formula should be the method of choice for LBW estimation in obese patients, leading to an accurate CM amount calculation and an optimal liver contrast enhancement in CT.

Acetylated Polyethylenimine-Entrapped Gold Nanoparticles Enable Negative Computed Tomography Imaging of Orthotopic Hepatic Carcinoma

Developing an effective computed tomography (CT) contrast agent is still a challenging task for precise diagnosis of hepatic carcinoma (HCC). Here, we present the use of acetylated polyethylenimine (PEI)-entrapped gold nanoparticles (Ac-PE-AuNPs) without antifouling modification for negative CT imaging of HCC. PEI was first linked to fluorescein isothiocyanate (FI) and then utilized as a vehicle for the entrapment of AuNPs. The particles were then acetylated to reduce its positive surface potential. The designed Ac-PE-AuNPs were characterized by various techniques. We find that the Ac-PE-AuNPs with a uniform size distribution (mean diameter = 2.3 nm) are colloidally stable and possess low toxicity in the studied range of concentration. Owing to the fact that the particles without additional antifouling modification were mainly gathered in liver, the Ac-PE-AuNPs could greatly improve the CT contrast enhancement of normal liver, whereas poor CT contrast enhancement appeared in liver necrosis region caused by HCC. As a result, HCC could be easily and precisely diagnosed. The designed Ac-PE-AuNPs were demonstrated to have biocompatibility through in vivo biodistribution and histological studies, hence holding an enormous potential to be adopted as an effective negative CT contrast agent for diagnosis of hepatoma carcinoma.