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

Fatty-marrow transformation following radiotherapy for pancreatic cancer detected using dual-energy computed tomography: A case report

Bone damage, a late side effect of radiotherapy, occurs concurrently with the replacement of fat cells in the bone marrow, causing changes in bone composition. Changes in composition can affect bone quality and disease states, and reduced bone mass can reduce quality of life by increasing the risk of fractures. A 70-year-old woman presented to the orthopedic outpatient clinic with the chief complaint of lower-back pain. The patient reported no history of trauma but was in great pain and had difficulty walking. Since the patient had a history of pancreatic cancer, tumor-marker testing, bone scintigraphy, and dual-energy computed tomography were performed. Although the tumor-marker levels were normal, dual-energy computed tomography and bone scintigraphy revealed fresh compression fractures of the L1 and L3 vertebrae. In addition, dual-energy computed tomography material-discrimination analysis suggested high fat density in the L2 vertebral body. The patient had received approximately 30 Gy radiation to the L2 vertebral body for her pancreatic cancer, which resulted in fatty myelination in the bone. The diagnosis of fatty myelination is made on T1-weighted magnetic resonance images; however, diagnosis remains challenging because of the difficulty in assessing bone morphology on magnetic resonance images. Moreover, some patients are not candidates for magnetic resonance imaging. Dual-energy computed tomography-based material-discrimination analysis can visually depict changes in the bone marrow, and is a valuable diagnostic tool owing to its simplicity.

Adult obesity diagnostic tool: A narrative review

Obesity is a complex chronic metabolic disorder characterized by abnormalities in lipid metabolism. Obesity is not only associated with various chronic diseases but also has negative effects on physiological functions such as the cardiovascular, endocrine and immune systems. As a global health problem, the incidence and prevalence of obesity have increased significantly in recent years. Therefore, understanding assessment methods and measurement indicators for obesity is critical for early screening and effective disease control. Current methods for measuring obesity in adult include density calculation, anthropometric measurements, bioelectrical impedance analysis, dual-energy X-ray absorptiometry, computerized imaging, etc. Measurement indicators mainly include weight, hip circumference, waist circumference, neck circumference, skinfold thickness, etc. This paper provides a comprehensive review of the literature to date, summarizes and analyzes various assessment methods and measurement indicators for adult obesity, and provides insights and guidance for the innovation of obesity assessment indicators.

Correlation between magnetic resonance imaging proton density fat fraction (MRI-PDFF) and liver biopsy to assess hepatic steatosis in obesity

Obesity is highly associated with Non-alcoholic fatty liver disease (NAFLD) and increased risk of liver cirrhosis and liver cancer-related death. We determined the diagnostic performance of the complex-based chemical shift technique MRI-PDFF for quantifying liver fat and its correlation with histopathologic findings in an obese population within 24 h before bariatric surgery. This was a prospective, cross-sectional, Institutional Review Board-approved study of PDFF-MRI of the liver and MRI-DIXON image volume before bariatric surgery. Liver tissues were obtained during bariatric surgery. The prevalence of NAFLD in the investigated cohort was as high as 94%. Histologic hepatic steatosis grades 0, 1, 2, and 3 were observed in 3 (6%), 25 (50%), 14 (28%), and 8 (16%) of 50 obese patients, respectively. The mean percentages of MRI-PDFF from the anterior and posterior right hepatic lobe and left lobe vs. isolate left hepatic lobe were 15.6% (standard deviation [SD], 9.28%) vs. 16.29% (SD, 9.25%). There was a strong correlation between the percentage of steatotic hepatocytes and MRI-PDFF in the left hepatic lobe (r = 0.82, p < 0.001) and the mean value (r = 0.78, p < 0.001). There was a strong correlation between MRI-derived subcutaneous adipose tissue volume and total body fat mass by dual-energy X-ray absorptiometry, especially at the L2-3 and L4 level (r = 0.85, p < 0.001). MRI-PDFF showed good performance in assessing hepatic steatosis and was an excellent noninvasive technique for monitoring hepatic steatosis in an obese population.

Hepatic fat quantification in dual-layer computed tomography using a three-material decomposition algorithm

OBJECTIVES

The purpose of this study was to evaluate a three-material decomposition algorithm for hepatic fat quantification using a dual-layer computed tomography (DL-CT) and MRI as reference standard on a large patient cohort.

METHOD

A total of 104 patients were retrospectively included in our study, i.e., each patient had an MRI exam and a DL-CT exam in our institution within a maximum of 31 days. Four regions of interest (ROIs) were positioned blindly and similarly in the liver, by two independent readers on DL-CT and MRI images. For DL-CT exams, all imaging phases were included. Fat fraction agreement between CT and MRI was performed using intraclass correlation coefficients (ICC), determination coefficients R2, and Bland-Altman plots. Diagnostic performance was determined using sensitivity, specificity, and positive and negative predictive values. The cutoff for steatosis was 5%.

RESULTS

Correlation between MRI and CT data was excellent for all perfusion phases with ICC calculated at 0.99 for each phase. Determination coefficients R2 were also good for all perfusion phases (about 0.95 for all phases). Performance of DL-CT in the diagnosis of hepatic steatosis was good with sensitivity between 89 and 91% and specificity ranging from 75 to 80%, depending on the perfusion phase. The positive predictive value was ranging from 78 to 93% and the negative predictive value from 82 to 86%.

CONCLUSION

Multi-material decomposition in DL-CT allows quantification of hepatic fat fraction with a good correlation to MRI data.

CLINICAL RELEVANCE STATEMENT

The use of DL-CT allows for detection of hepatic steatosis. This is especially interesting as an opportunistic finding CT performed for other reasons, as early detection can help prevent or slowdown the development of liver metabolic disease.

KEY POINTS

• Hepatic fat fractions provided by the dual-layer CT algorithm is strongly correlated with that measured on MRI. • Dual-layer CT is accurate to detect hepatic steatosis ≥ 5%. • Dual-layer CT allows opportunistic detection of steatosis, on CT scan performed for various indications.

Principles and Applications of Dual-Layer Spectral CT in Gastrointestinal Imaging

The advance in technology allows for the development of different CT scanners in the field of dual-energy computed tomography (DECT). In particular, a recently developed detector-based technology can collect data from different energy levels, thanks to its layers. The use of this system is suited for material decomposition with perfect spatial and temporal registration. Thanks to post-processing techniques, these scanners can generate conventional, material decomposition (including virtual non-contrast (VNC), iodine maps, Z-effective imaging, and uric acid pair images) and virtual monoenergetic images (VMIs). In recent years, different studies have been published regarding the use of DECT in clinical practice. On these bases, considering that different papers have been published using the DECT technology, a review regarding its clinical application can be useful. We focused on the usefulness of DECT technology in gastrointestinal imaging, where DECT plays an important role.

Spectral CT: Current Liver Applications

Using two different energy levels, dual-energy computed tomography (DECT) allows for material differentiation, improves image quality and iodine conspicuity, and allows researchers the opportunity to determine iodine contrast and radiation dose reduction. Several commercialized platforms with different acquisition techniques are constantly being improved. Furthermore, DECT clinical applications and advantages are continually being reported in a wide range of diseases. We aimed to review the current applications of and challenges in using DECT in the treatment of liver diseases. The greater contrast provided by low-energy reconstructed images and the capability of iodine quantification have been mostly valuable for lesion detection and characterization, accurate staging, treatment response assessment, and thrombi characterization. Material decomposition techniques allow for the non-invasive quantification of fat/iron deposition and fibrosis. Reduced image quality with larger body sizes, cross-vendor and scanner variability, and long reconstruction time are among the limitations of DECT. Promising techniques for improving image quality with lower radiation dose include the deep learning imaging reconstruction method and novel spectral photon-counting computed tomography.

Characterizing incidental mass lesions in abdominal dual-energy CT compared to conventional contrast-enhanced CT

BACKGROUND

Incidental findings are common in abdominal computed tomography (CT) and often warrant further investigations with economic implications as well as implications for patients.

PURPOSE

To evaluate the potential of dual-energy CT (DECT) in the identification and/or characterization of abdominal incidental mass lesions compared to conventional contrast-enhanced CT.

MATERIAL AND METHODS

This retrospective study from a major tertiary hospital included 96 patients, who underwent contrast-enhanced abdominal DECT. Incidental lesions in adrenals, kidneys, liver, and pancreas were evaluated by two board-certified abdominal radiologists. Observer 1 only had access to standard CT reconstructions, while observer 2 had access to standard CT as well as DECT reconstructions. Disagreements were resolved by consensus review and used as a reference for observers using McNemar's test.

RESULTS

Observers 1 and 2 identified a total of 40 and 34 findings, respectively. Furthermore, observer 1 registered 13 lesions requiring follow-up, of which seven (two renal and five adrenal lesions) were resolved following consensus review using DECT (P = 0.008). The inter-observer agreement was near perfect (κ = 0.82).

CONCLUSION

DECT has the potential to improve the immediate characterization of incidental findings when compared to conventional CT for abdominal imaging.

Hepatic Fat Quantification with the Multi-Material Decomposition Algorithm by Using Low-Dose Non-Contrast Material-Enhanced Dual-Energy Computed Tomography in a Prospectively Enrolled Cohort

The early diagnosis of hepatic steatosis is important. No study has assessed hepatic fat quantification by using low-dose dual-energy computed tomography (CT). We assessed the accuracy of hepatic fat quantification using the multi-material decomposition (MMD) algorithm with low-dose non-contrast material-enhanced dual-energy CT. We retrospectively reviewed 33 prospectively enrolled patients who had undergone low-dose non-contrast material-enhanced dual-energy CT and magnetic resonance image (MRI) proton density fat fraction (PDFF) on the same day. Percentage fat volume fraction (FVF) images were generated using the MMD algorithm on the low-dose dual-energy CT data. We assessed the correlation between FVFs and MRI-PDFFs by using Spearman's rank correlation. With a 5% cutoff value of MRI-PDFF for fatty liver, a receiver operating characteristic (ROC) curve analysis was performed to identify the optimal criteria of FVF for diagnosing fatty liver. CTDIvol of CT was 2.94 mGy. FVF showed a strong correlation with MRI-PDFF (r = 0.756). The ROC curve analysis demonstrated that FVF ≥ 4.61% was the optimal cutoff for fatty liver. With this cutoff value for diagnosing the fatty liver on low-dose dual-energy CT, the sensitivity, specificity, and area under the curve were 90%, 100%, and 0.987, respectively. The MMD algorithm using low-dose non-contrast material-enhanced dual-energy CT is feasible for quantifying hepatic fat.