Fat Quantification in Dual-Layer Detector Spectral Computed Tomography

Abstract

Objectives Fat quantification by dual-energy computed tomography (DECT) provides contrast-independent objective results, for example, on hepatic steatosis or muscle quality as parameters of prognostic relevance. To date, fat quantification has only been developed and used for source-based DECT techniques as fast kVp-switching CT or dual-source CT, which require a prospective selection of the dual-energy imaging mode. It was the purpose of this study to develop a material decomposition algorithm for fat quantification in phantoms and validate it in vivo for patient liver and skeletal muscle using a dual-layer detector-based spectral CT (dlsCT), which automatically generates spectral information with every scan. Materials and Methods For this feasibility study, phantoms were created with 0%, 5%, 10%, 25%, and 40% fat and 0, 4.9, and 7.0 mg/mL iodine, respectively. Phantom scans were performed with the IQon spectral CT (Philips, the Netherlands) at 120 kV and 140 kV and 3 T magnetic resonance (MR) (Philips, the Netherlands) chemical-shift relaxometry (MRR) and MR spectroscopy (MRS). Based on maps of the photoelectric effect and Compton scattering, 3-material decomposition was done for fat, iodine, and phantom material in the image space. After written consent, 10 patients (mean age, 55 ± 18 years; 6 men) in need of a CT staging were prospectively included. All patients received contrast-enhanced abdominal dlsCT scans at 120 kV and MR imaging scans for MRR. As reference tissue for the liver and the skeletal muscle, retrospectively available non–contrast-enhanced spectral CT data sets were used. Agreement between dlsCT and MR was evaluated for the phantoms, 3 hepatic and 2 muscular regions of interest per patient by intraclass correlation coefficients (ICCs) and Bland-Altman analyses. Results The ICC was excellent in the phantoms for both 120 kV and 140 kV (dlsCT vs MRR 0.98 [95% confidence interval (CI), 0.94–0.99]; dlsCT vs MRS 0.96 [95% CI, 0.87–0.99]) and in the skeletal muscle (0.96 [95% CI, 0.89–0.98]). For log-transformed liver fat values, the ICC was moderate (0.75 [95% CI, 0.48–0.88]). Bland-Altman analysis yielded a mean difference of −0.7% (95% CI, −4.5 to 3.1) for the liver and of 0.5% (95% CI, −4.3 to 5.3) for the skeletal muscle. Interobserver and intraobserver agreement were excellent (>0.9). Conclusions Fat quantification was developed for dlsCT and agreement with MR techniques demonstrated for patient liver and muscle. Hepatic steatosis and myosteatosis can be detected in dlsCT scans from clinical routine, which retrospectively provide spectral information independent of the imaging mode.

Muscle quality determined by computed tomography predicts short-term and long-term survival after liver transplantation

“…Prospectively, it would be beneficial to also employ spectral CT scans such as dual-source, or dual-layer detector spectral CT, as those provide virtual non-contrast-enhanced images and thus contrast agent independent assessment of the muscle density. Also, in contrast to the indirect assessment of myosteatosis by muscle density, in spectral CT scans the muscular fat content can be directly assessed 15 , 16 , 46 which further improves reliability of radiological myosteatosis assessment.…”

“…In CT scans the muscle mass can easily be determined by the skeletal muscle area (SMA). Myosteatosis as a measure of muscle quality can be indirectly assessed by the muscle radiodensity attenuation 1 (MRA) or quantified directly by material decomposition in spectral CT techniques 15 , 16 .…”

Spectral CT: Current Liver Applications

“…Dual-energy CT can provide reliable material composition estimation without the need for unenhanced acquisitions (Figure 15) [6,69,70]. However, it has shown lower performance for fat quantification compared to SECT and has a moderate correlation with MR spectroscopy [66].…”

Fat quantification in dual-layer detector spectral CT: How to handle iron overload, varying tube voltage and radiation dose Indices

“…In dlCT it is advantageous, that no prospective selection of a spectral scan mode is necessary and spectral information thus automatically generated with every scan [ 9 ]. However, in contrast to the other spectral CT techniques, the feasibility of fat quantification with dlCT has only recently been demonstrated [ 10 ]. So far, dlCT has been validated in the context of contrast-phase independent quantification of hepatic steatosis [ 11 ] and for the detection of myosteatosis [ 10 ].…”

“…However, in contrast to the other spectral CT techniques, the feasibility of fat quantification with dlCT has only recently been demonstrated [ 10 ]. So far, dlCT has been validated in the context of contrast-phase independent quantification of hepatic steatosis [ 11 ] and for the detection of myosteatosis [ 10 ].…”