Material Density Hepatic Steatosis Quantification on Intravenous Contrast-Enhanced Rapid Kilovolt (Peak)–Switching Single-Source Dual-Energy Computed Tomography:

CT-based methods for assessment of metabolic dysfunction associated with fatty liver disease

Metabolic dysfunction-associated fatty liver disease (MAFLD), previously called metabolic nonalcoholic fatty liver disease, is the most prevalent chronic liver disease worldwide. The multi-factorial nature of MAFLD severity is delineated through an intricate composite analysis of the grade of activity in concert with the stage of fibrosis. Despite the preeminence of liver biopsy as the diagnostic and staging reference standard, its invasive nature, pronounced interobserver variability, and potential for deleterious effects (encompassing pain, infection, and even fatality) underscore the need for viable alternatives. We reviewed computed tomography (CT)-based methods for hepatic steatosis quantification (liver-to-spleen ratio; single-energy "quantitative" CT; dual-energy CT; deep learning-based methods; photon-counting CT) and hepatic fibrosis staging (morphology-based CT methods; contrast-enhanced CT biomarkers; dedicated postprocessing methods including liver surface nodularity, liver segmental volume ratio, texture analysis, deep learning methods, and radiomics). For dual-energy and photon-counting CT, the role of virtual non-contrast images and material decomposition is illustrated. For contrast-enhanced CT, normalized iodine concentration and extracellular volume fraction are explained. The applicability and salience of these approaches for clinical diagnosis and quantification of MAFLD are discussed.Relevance statementCT offers a variety of methods for the assessment of metabolic dysfunction-associated fatty liver disease by quantifying steatosis and staging fibrosis.Key points• MAFLD is the most prevalent chronic liver disease worldwide and is rapidly increasing.• Both hardware and software CT advances with high potential for MAFLD assessment have been observed in the last two decades.• Effective estimate of liver steatosis and staging of liver fibrosis can be possible through CT.

Dual-Energy, Spectral and Photon Counting Computed Tomography for Evaluation of the Gastrointestinal Tract

The use of dual-energy computed tomography (CT) allows for reconstruction of energy- and material-specific image series. The combination of low-energy monochromatic images, iodine maps, and virtual unenhanced images can improve lesion detection and disease characterization in the gastrointestinal tract in comparison with single-energy CT.

Non-Invasive Imaging Methods to Evaluate Non-Alcoholic Fatty Liver Disease with Fat Quantification: A Review

Hepatic steatosis without specific causes (e.g., viral infection, alcohol abuse, etc.) is called non-alcoholic fatty liver disease (NAFLD), which ranges from non-alcoholic fatty liver (NAFL) to non-alcoholic steatohepatitis (NASH), fibrosis, and NASH-related cirrhosis. Despite the usefulness of the standard grading system, liver biopsy has several limitations. In addition, patient acceptability and intra- and inter-observer reproducibility are also concerns. Due to the prevalence of NAFLD and limitations of liver biopsies, non-invasive imaging methods such as ultrasonography (US), computed tomography (CT), and magnetic resonance imaging (MRI) that can reliably diagnose hepatic steatosis have developed rapidly. US is widely available and radiation-free but cannot examine the entire liver. CT is readily available and helpful for detection and risk classification, significantly when analyzed using artificial intelligence; however, it exposes users to radiation. Although expensive and time-consuming, MRI can measure liver fat percentage with magnetic resonance imaging proton density fat fraction (MRI-PDFF). Specifically, chemical shift-encoded (CSE)-MRI is the best imaging indicator for early liver fat detection. The purpose of this review is to provide an overview of each imaging modality with an emphasis on the recent progress and current status of liver fat quantification.

Dual-energy CT: Technical considerations and clinical applications

Although dual-energy CT was initially described by Hounsfield in 1973, it remains underused in clinical practice. It is therefore important to emphasize the clinical benefits and limitations of this technique. Iodine mapping makes it possible to quantify the uptake of iodine, which is very important in characterizing tumors, lung perfusion, pulmonary nodules, and the tumor response to new treatments. Dual-energy CT also makes it possible to obtain virtual single-energy images and virtual images without iodinated contrast or without calcium, as well as to separate materials such as uric acid or fat and to elaborate hepatic iron overload maps. In this article, we review some of the clinical benefits and technical limitations to improve understanding of dual-energy CT and expand its use in clinical practice.

Detection of fatty liver using virtual non-contrast dual-energy CT

PURPOSE

Determine whether liver attenuation measured on dual-energy CT (DECT) virtual non-contrast examinations predicts the presence of fatty liver.

METHODS

Single-institution retrospective review from 2016 to 2020 found patients with DECT and proton density fat fraction MRI (MRI PDFF) within 30 days. MRI PDFF was the reference standard for determining hepatic steatosis. Attenuation measurements from VNC and mixed 120 kVp-like images were compared to MRI PDFF in the right and left lobes. Performance of VNC was compared to measurement of the liver-spleen attenuation difference (LSAD).

RESULTS

128 patients were included (69 men, 59 women) with mean age 51.6 years (range 14-98 years). > 90% of patients received CT and MRI in the emergency department or as inpatients. Median interval between DECT and MRI PDFF was 2 days (range 0-28 days). Prevalence of fatty liver using the reference standard (MRI PDFF > 6%) was 24%. Pearson correlation coefficient between VNC and MRI- DFF was -0.64 (right) and -0.68 (left, both p < 0.0001). For LSAD, correlation was - 0.43 in both lobes (p < 0.0001). Considering MRI PDFF > 6% as diagnostic of steatosis, area under the receiver operator characteristic curve (AUC) was 0.834 and 0.872 in the right and left hepatic lobes, with an optimal threshold of 54.8 HU (right) and 52.5 HU (left), yielding sensitivity/specificity of 57%/93.9% (right) and 67.9%/90% (left). For LSAD, AUC was 0.808 (right) and 0.767 (left) with optimal sensitivity/specificity of 93.3%/57.1% (right) and 78.6%/68% (left).

CONCLUSION

Attenuation measured at VNC CT was moderately correlated with liver fat content and had > 90% specificity for diagnosis of fatty liver.

Assessment of Liver Fat: Dual-Energy CT versus Conventional CT with and without Contrast

We assessed the correlation between liver fat percentage using dual-energy CT (DECT) and Hounsfield unit (HU) measurements in contrast and non-contrast CT. This study included 177 patients in two patient groups: Group A (n = 125) underwent whole body non-contrast DECT and group B (n = 52) had a multiphasic DECT including a conventional non-contrast CT. Three regions of interest were placed on each image series, one in the left liver lobe and two in the right to measure Hounsfield Units (HU) as well as liver fat percentage. Linear regression analysis was performed for each group as well as combined. Receiver operating characteristic (ROC) curve was generated to establish the optimal fat percentage threshold value in DECT for predicting a non-contrast threshold of 40 HU correlating to moderate-severe liver steatosis. We found a strong correlation between fat percentage found with DECT and HU measured in non-contrast CT in group A and B individually (R² = 0.81 and 0.86, respectively) as well as combined (R² = 0.85). No significant difference was found when comparing venous and arterial phase DECT fat percentage measurements in group B (p = 0.67). A threshold of 10% liver fat found with DECT had 95% sensitivity and 95% specificity for the prediction of a 40 HU threshold using non-contrast CT. In conclusion, liver fat quantification using DECT shows high correlation with HU measurements independent of scan phase.

Dual-Energy Computed Tomography in Diffuse Liver Diseases

Dual-energy computed tomography (DECT) is an advancement in the field of CT, where images are acquired at two energies. Materials are identified and quantified based on their attenuation pattern at two different energy beams using various material decomposition algorithms. With its ability to identify and quantify materials such as fat, calcium, iron, and iodine, DECT adds great value to conventional CT and has innumerable applications in body imaging. Continuous technological advances in CT scanner hardware, material decomposition algorithms, and image reconstruction software have led to considerable growth of these applications. Among all organs, the liver is the most widely investigated by DECT, and DECT has shown promising results in most liver applications. In this article, we aim to provide an overview of the role of DECT in the assessment of diffuse liver diseases, mainly the deposition of fat, fibrosis, and iron and review the most relevant literature.

Quantitative assessment of liver steatosis using ultrasound: dual-energy CT

Reflecting the growing interest in early diagnosis of non-alcoholic fatty liver disease in recent years, the development of noninvasive and reliable fat quantification methods is needed. Dual-energy computed tomography (DE-CT) is a quantitative diagnostic imaging method that estimates the composition of the imaging target using a material decomposition technique based on the X-ray absorption characteristics peculiar to substances from DE-CT scanning using X-rays generated with different energies (tube voltage). In this review article, we first explain the basic principles and technical aspects of DE-CT. Then, we will present the current diagnostic ability of DE-CT and the factors influencing the quantitative evaluation of liver steatosis using DE-CT as compared to multi-modal methods including ultrasound and magnetic resonance imaging-based methods. In brief, DE-CT may have comparable diagnostic performance to the modern US-based liver fat measurement methods. However, the current material decomposition technique using DE-CT does not seem to have added value to the simple quantitative assessment of liver steatosis, because DE-CT measurement does not improve the accuracy of fat quantification over conventional single-energy computed tomography (SE-CT) attenuation. The most significant influencing factor for the quantitative assessment of liver steatosis using DE-CT can be hepatic iron deposition. An iron-specific multi-material decomposition algorithm correcting for the influences of iron in the liver has been under development. The current material decomposition algorithm can still have added value in a specific situation such as the quantitative assessment of liver steatosis using contrast-enhanced DE-CT. However, there is a lack of evidence for the influence of liver fibrosis in the quantitative assessment of liver steatosis using DE-CT.

Utility of material-specific fat images derived from rapid-kVp-switch dual-energy renal mass CT for diagnosis of renal angiomyolipoma

BACKGROUND

Renal angiomyolipoma (AML) are benign masses that require detection of macroscopic fat for accurate diagnosis.

PURPOSE

To evaluate fat material-specific images derived from dual-energy computed tomography (DECT) to diagnose renal AML.

MATERIAL AND METHODS

This retrospective case-control study evaluated 25 renal AML and 44 solid renal masses (41 renal cell carcinomas, three other tumors) imaged with rapid-kVp-switch DECT (120 kVp non-contrast-enhanced [NECT], 70-keV corticomedullary [CM], and 120-kVp nephrographic [NG]-phase CECT) during 2017-2018. A radiologist measured attenuation (Hounsfield Units [HU]) on NECT, CM-CECT, NG-CECT, and fat concentration (mg/mL) using fat-water base-pair images.

RESULTS

At NECT, 100% (44/44) non-AML and 4.0% (1/25) AML measured >-15 HU. At CM-CECT and NG-CECT, 24.0% (6/25) and 20.0% (5/25) AML measured >-15 HU (size 6-20 mm). To diagnose AML, area under receiver operating characteristic curve (AUC) using -15 HU was: 0.98 (95% confidence interval [CI] 0.98-1.00) NECT, 0.88 (95% CI 0.79-0.91) CM-CECT, and 0.90 (95% CI 0.82-0.98) NG-CECT. At DECT, fat concentration was higher in AML (163.7 ± 333.9 [-553.0 to 723.5] vs. -2858.1 ± 460.3 [-2421.2 to -206.0] mg/mL, P<0.001). AUC to diagnose AML using ≥-206.0 mg/mL threshold was 0.98 (95% CI 0.95-1.0) with sensitivity/specificity of 92.0%/96.7%. Of AML, 8.0% (2/25) were incorrectly classified; one of these was fat-poor. AUC was higher for fat concentration compared to HU measurements on CM-CECT and NG-CECT (P=0.009-0.050) and similar to NECT (P=0.98).

CONCLUSION

DECT material-specific fat images can help confirm the presence of macroscopic fat in renal AML which may be useful to establish a diagnosis if unenhanced CT is unavailable.

Computed Tomography Techniques, Protocols, Advancements, and Future Directions in Liver Diseases

Computed tomography (CT) is often performed as the initial imaging study for the workup of patients with known or suspected liver disease. Our article reviews liver CT techniques and protocols in clinical practice along with updates on relevant CT advances, including wide-detector CT, radiation dose optimization, and multienergy scanning, that have already shown clinical impact. Particular emphasis is placed on optimizing the late arterial phase of enhancement, which is critical to evaluation of hepatocellular carcinoma. We also discuss emerging techniques that may soon influence clinical care.

Dual-energy CT of the liver: True noncontrast vs. virtual noncontrast images derived from multiple phases for the diagnosis of fatty liver

PURPOSE

To evaluate the difference in liver density and to compare the performance to diagnose fatty liver between true noncontrast (TNC) images and virtual noncontrast (VNC) images generated from dual-energy CT (DECT).

MATERIALS AND METHODS

Patients who underwent liver dynamic DECT and MRI were included (n = 49). Two observers measured the liver and spleen densities on TNC images and three VNC images from the arterial, portal and delayed phases of DECT (VNCa, VNCp and VNCd, respectively). The liver-minus-spleen density (density L-S) and liver-to-spleen ratio (density L/S) were calculated. The CT parameters were compared between normal liver patients and fatty liver patients by using the independent t-test. Differences and agreements between measurements on TNC images and VNC images were evaluated by using the paired t-test and Bland-Altman analysis. Receiver operating characteristic (ROC) curve analysis was used to evaluate the diagnostic performance of CT parameters for diagnosing fatty liver.

RESULTS

All CT parameters measured on TNC and VNC images were significantly higher in normal liver patients than in fatty liver patients. Although the mean liver densities on VNC images were significantly lower than those on TNC images, all CT parameters showed good agreement between TNC images and VNC images. The diagnostic performances of CT parameters on VNC images were not significantly different from those on TNC images.

CONCLUSION

Although the liver and spleen density on VNC images was significantly lower than that on TNC images, the diagnostic performances of CT parameters on three VNC images from multiple phases were similar to those on TNC images for diagnosing fatty liver.

Clinical Implementation of Dual-Energy CT for Gastrointestinal Imaging

Dual-energy CT (DECT) overcomes several limitations of conventional single-energy CT (SECT) for the evaluation of gastrointestinal diseases. This article provides an overview of practical aspects of the DECT technology and acquisition protocols, reviews existing clinical applications, discusses current challenges, and describes future directions, with a focus on gastrointestinal imaging. A head-to-head comparison of technical specifications among DECT scanner implementations is provided. Energy- and material-specific DECT image reconstructions enable retrospective (i.e., after examination acquisition) image quality adjustments that are not possible using SECT. Such adjustments may, for example, correct insufficient contrast bolus or metal artifacts, thereby potentially avoiding patient recalls. A combination of low-energy monochromatic images, iodine maps, and virtual unenhanced images can be included in protocols to improve lesion detection and disease characterization. Relevant literature is reviewed regarding use of DECT for evaluation of the liver, gallbladder, pancreas, and bowel. Challenges involving cost, workflow, body habitus, and variability in DECT measurements are considered. Artificial intelligence and machine-learning image reconstruction algorithms, PACS integration, photon-counting hardware, and novel contrast agents are expected to expand the multienergy capability of DECT and further augment its value.

Dual-energy CT in diffuse liver disease: is there a role?

Dual-energy CT (DECT) can be defined as the use of two different energy levels to identify and quantify material composition. Since its inception, DECT has benefited from remarkable improvements in hardware and clinical applications. DECT enables accurate identification and quantification of multiple materials, including fat, iron, and iodine. As a consequence, multiple studies have investigated the potential role of DECT in the assessment of diffuse liver diseases. While this role is evolving, this article aims to review the most relevant literature on use of DECT for assessment of diffuse liver diseases. Moreover, the basic concepts on DECT techniques, types of image reconstruction, and DECT-dedicated software will be described, focusing on the areas that are most relevant for the evaluation of diffuse liver diseases. Also, we will review the evidence of added value of DECT in detection and assessment of hepatocellular carcinoma which is a known risk in patients with diffuse liver disease.

Dual-Energy Computed Tomography for Fat Quantification in the Liver and Bone Marrow: A Literature Review

Background With dual-energy computed tomography (DECT) it is possible to quantify certain elements and tissues by their specific attenuation, which is dependent on the X-ray spectrum. This systematic review provides an overview of the suitability of DECT for fat quantification in clinical diagnostics compared to established methods, such as histology, magnetic resonance imaging (MRI) and single-energy computed tomography (SECT).

Method Following a systematic literature search, studies which validated DECT fat quantification by other modalities were included. The methodological heterogeneity of all included studies was processed. The study results are presented and discussed according to the target organ and specifically for each modality of comparison.

Results Heterogeneity of the study methodology was high. The DECT data was generated by sequential CT scans, fast-kVp-switching DECT, or dual-source DECT. All included studies focused on the suitability of DECT for the diagnosis of hepatic steatosis and for the determination of the bone marrow fat percentage and the influence of bone marrow fat on the measurement of bone mineral density. Fat quantification in the liver and bone marrow by DECT showed valid results compared to histology, MRI chemical shift relaxometry, magnetic resonance spectroscopy, and SECT. For determination of hepatic steatosis in contrast-enhanced CT images, DECT was clearly superior to SECT. The measurement of bone marrow fat percentage via DECT enabled the bone mineral density quantification more reliably.

Conclusion DECT is an overall valid method for fat quantification in the liver and bone marrow. In contrast to SECT, it is especially advantageous to diagnose hepatic steatosis in contrast-enhanced CT examinations. In the bone marrow DECT fat quantification allows more valid quantification of bone mineral density than conventional methods. Complementary studies concerning DECT fat quantification by split-filter DECT or dual-layer spectral CT and further studies on other organ systems should be conducted.

Key points:

Citation Format

Dual-Energy CT of Material Decomposition Analysis for Detection with Bone Marrow Edema in Patients with Vertebral Compression Fractures

RATIONALE AND OBJECTIVES

This study investigated detecting bone marrow edema (BME) in patients with vertebral compression fractures. We compared dual-energy material density analysis images to magnetic resonance imaging (MRI), which is considered the gold standard.

MATERIALS AND METHODS

In this retrospective study, 260 vertebral bodies from 30 patients (11 males, 19 females, mean age of 81) were assessed by MRI and dual-energy material density analysis. Diagnostic accuracy was assessed using the receiver operating characteristic (ROC) curve. Fifty-two of the 260 vertebral bodies were considered to have BME based on the dual-energy material density analysis images; 50 were deemed to have BME by MRI.

RESULTS

ROC analysis of the dual-energy material density analysis values revealed an area under the ROC curve of 0.95 for radiologist 1, 0.97 for radiologist 2, and 0.96 for radiologist 3. A mean cutoff value of 1032.6 mg/cm³ provided an overall sensitivity of 93.0% (95% confidence intervals [CI]: 86.0%-99.9%), specificity of 98.0% (95% CI: 95.5%-99.0%), accuracy of 97.0% (95% CI: 95.2%-99.0%), positive predictive value of 95.0% (95% CI: 81.0%-97.5%), and negative predictive value of 98.0% (95% CI: 93.0%-99.9%).

CONCLUSION

BME in patients with vertebral compression fractures can be detected using dual-energy material density analysis images.

Quantification of Liver Fat Content With Unenhanced MDCT: Phantom and Clinical Correlation With MRI Proton Density Fat Fraction

OBJECTIVE

The purpose of this study was to evaluate the relation between unenhanced CT liver attenuation values and MRI-derived proton density fat fraction (PDFF) for estimation of liver fat content at CT.

MATERIALS AND METHODS

A CT-MRI phantom was constructed and imaged containing 12 vials with lipid fractions ranging from 0% to 100%. For the retrospective clinical arm, 221 patients (120 men, 101 women; mean age, 54 years) underwent both unenhanced CT and chemical shift-encoded MRI of the liver between 2007 and 2017. Among these patients, 92 had more than one 120-kV CT scan for comparison. CT attenuation and MRI PDFF were derived with coregistered ROI measurements in the right hepatic lobe. The 120-kV subgroup of CT examinations performed within 1 month of MRI PDFF examinations (n = 72) served as the primary cohort for linear correlation. The effects of different tube voltage settings, time intervals between CT and MRI, and iron overload were assessed. Linear least squares regression analysis was performed.

RESULTS

Phantom results showed excellent linear fit between CT attenuation and MRI PDFF (r² = 0.986). In patients, 120-kV CT performed within 1 month of MRI PDFF exhibited strong linear correlation (r² = 0.828) that closely matched the phantom data, yielding the following clinical CT-MRI conversion formula: MRI PDFF (%) = -0.58 × CT attenuation (HU) + 38.2. Correlation worsened for CT-to-MRI intervals longer than 1 month (r² = 0.565), and this specific relationship did not apply as well to non-120-kV settings (r² = 0.554). For patients with multiple scans, correlation progressively worsened over time. CT-based liver fat content was underestimated in several patients with iron overload.

CONCLUSION

The linear correlation between unenhanced CT attenuation and MRI PDFF allows quantification of liver fat content by means of unenhanced CT in clinical practice. As expected, correlation worsened with increasing CT-MRI time interval, variable tube voltage settings, and iron overload.

Association between abdominal adiposity and subclinical measures of left-ventricular remodeling in diabetics, prediabetics and normal controls without history of cardiovascular disease as measured by magnetic resonance imaging: results from the KORA-FF4 Study

OBJECTIVES

Local, abdominal fat depots may be related to alterations in cardiac function and morphology due to a metabolic linkage. Thus, we aimed to determine their association with subtle cardiac changes and the potential interaction with hyperglycemic metabolic states.

METHODS

Subjects from the general population and without history of cardiovascular disease were drawn from the Cooperative Health Research in the Region of Augsburg FF4 cohort and underwent 3 T cardiac and body MRI. Measures of abdominal adiposity such as hepatic proton-density fat fraction [PDFF_hepatic], subcutaneous (SAT) and visceral abdominal fat (VAT) as well as established cardiac left-ventricular (LV) measures including LV remodeling index (LVCI) were derived. Associations were determined using linear regression analysis based on standard deviation normalized predictors.

RESULTS

Among a total of 374 subjects (56.2 ± 9.1 years, 58% males), 49 subjects had diabetes, 99 subjects had prediabetes and 226 represented normal controls. Only subtle cardiac alterations were observed (e.g. LVCI: 1.13 ± 0.30). While SAT was not associated, increasing VAT and increasing PDFF_hepatic were independently associated with increasing LVCI (β = 0.11 and 0.06, respectively), decreasing LV end-diastolic volume (β = - 6.70 and 3.23, respectively), and decreasing LV stroke volume (β = - 3.91 and - 2.20, respectively). Hyperglycemic state did not modify the associations between VAT or PDFF and LV measures (interaction term: all p ≥ 0.29).

CONCLUSION

In a healthy population, VAT but also PDFF_hepatic were associated with subclinical measures of LV remodeling without evidence for a modifying effect of hyperglycemic state.

Material Separation Using Dual-Energy CT: Current and Emerging Applications

Dual-energy (DE) computed tomography (CT) offers the opportunity to generate material-specific images on the basis of the atomic number Z and the unique mass attenuation coefficient of a particular material at different x-ray energies. Material-specific images provide qualitative and quantitative information about tissue composition and contrast media distribution. The most significant contribution of DE CT-based material characterization comes from the capability to assess iodine distribution through the creation of an image that exclusively shows iodine. These iodine-specific images increase tissue contrast and amplify subtle differences in attenuation between normal and abnormal tissues, improving lesion detection and characterization in the abdomen. In addition, DE CT enables computational removal of iodine influence from a CT image, generating virtual noncontrast images. Several additional materials, including calcium, fat, and uric acid, can be separated, permitting imaging assessment of metabolic imbalances, elemental deficiencies, and abnormal deposition of materials within tissues. The ability to obtain material-specific images from a single, contrast-enhanced CT acquisition can complement the anatomic knowledge with functional information, and may be used to reduce the radiation dose by decreasing the number of phases in a multiphasic CT examination. DE CT also enables generation of energy-specific and virtual monochromatic images. Clinical applications of DE CT leverage both material-specific images and virtual monochromatic images to expand the current role of CT and overcome several limitations of single-energy CT. (©)RSNA, 2016.

White Paper of the Society of Computed Body Tomography and Magnetic Resonance on Dual-Energy CT, Part 4: Abdominal and Pelvic Applications

This is the fourth of a series of 4 white papers that represent expert consensus documents developed by the Society of Computed Body Tomography and Magnetic Resonance through its task force on dual-energy computed tomography. This article, part 4, discusses DECT for abdominal and pelvic applications and, at the end of each, will offer our consensus opinions on the current clinical utility of the application and opportunities for further research.

Accuracy analysis of intrahepatic fat density measurements using dual-energy computed tomography: Validation using a test phantom

BACKGROUND

Currently, no standardized method for measuring intrahepatic fat density via conventional computed tomography (CT) exists.

OBJECTIVE

We aim to quantify intrahepatic fat density via material decomposition analysis using rapid kilovolt peak-switching dual-energy (RSDE) CT.

METHODS

Homogenized porcine liver and fat (lard) were mixed in various ratios to produce phantoms for fat density verification. The actual fat density was measured on the basis of the phantom volume and weight, and these measurements were used as reference densities. The fat and liver mass attenuation coefficients, which were used as the material basis pairs, were employed in the material decomposition analysis. Then, the measured fat density of each phantom was compared with the reference densities.

RESULTS

For fat content differences exceeding 2%, the measured fat density for the phantoms became statistically significant (p < 0.01). The correlation between the reference densities and RSDE-measured fat densities was reasonably high (R > 0.9997); this indicates the validity of this analysis method.

CONCLUSIONS

Intrahepatic fat density can be measured using the mass attenuation coefficients of fat and liver in a material decomposition analysis. Given the knowledge of the accuracy and the limitations found in this study, our method can quantitatively evaluate fat density.

[Evaluation of Fat Quantification in the Liver Using Dual Energy CT]

BACKGROUND AND PURPOSE

Recently, the number of patients with nonalcoholic fatty liver disease (NAFLD) has been increasing, and some of them progresses to cirrhosis and hepatocellular carcinoma. Dual energy CT allows the discrimination of substance using monochromatic image (MI), and steatosis exhibit specifically the CT value of each energy level. The purpose is to evaluate the fat quantification in the liver using spectral HU curve and CT value compare to a conventional image diagnosis.

METHODS

Dual energy CT and liver biopsy were performed in 54 patients between October 2014 and April 2016. The CT value of 40 keV MI was measured by spectral HU curve setting 3 points ROI on the right and left liver. The CT value of 40 keV MI was compared with steatosis area and the NAFLD activity score (NAS). Additionally, steatosis area was compared with the conventional CT value scan and hepatorenal echo contrast value.

RESULTS AND DISCUSSION

The CT value of 40 keV MI exhibited a negative correlation for the stenosis area (R²=0.619), and NAS (R²=0.147). Steatosis area exhibited correlation for the conventional CT value (R²=0.407), and hepatorenal echo contrast (R²=0.135). This study suggests that the evaluation of the fat quantification in the liver using the spectral HU curve and CT value improved in comparison to the conventional image diagnosis.