Fatty liver disease, including liver steatosis, is a major health problem worldwide. In liver transplantation, macrovesicular steatosis in donor livers is a major cause of graft failure and remains difficult to assess. On one hand, several imaging modalities can be used for the assessment of liver fat, but liver biopsy, which is still considered the gold standard, may be difficult to perform in this context. On the other hand, computed tomography (CT) is commonly used by teams managing cadaveric donors to assess donors and to minimize the risk of complications in recipients. The purpose of our study was to validate the use of CT as a semiquantitative method for assessing macrovesicular steatosis in cadaveric donors with liver biopsy as a reference standard. A total of 109 consecutive cadaveric donors were included between October 2009 and May 2011. Brain death was diagnosed according to French legislation. Liver biopsy and then CT were performed on the same day to determine the degree of macrovesicular steatosis. All liver biopsies and CT scans were analyzed in a double-blinded fashion by a senior pathologist and a senior radiologist, respectively. For CT, we used the liver-to-spleen (L/S) attenuation ratio, which is a validated method for determining 30% or greater steatosis in living liver donors. Fourteen of 109 biopsies exhibited macrovesicular steatosis > 30% upon histologic analysis. A receiver operating characteristic curve was generated for the L/S ratio to identify its ability to predict significant steatosis, which was defined as >30%. A cutoff value of 0.9 for the CT L/S ratio provided a sensitivity of 79% and a specificity of 97% to detect significant steatosis. Liver Transpl 21:690-695, 2015. V C 2015 AASLD.

Premature beats originating in clinically concealed areas of local early repolarization promote ventricular arrhythmias and sudden cardiac arrest.

Background Cardiovascular magnetic resonance T1ρ mapping may detect myocardial injuries without exogenous contrast agent. However, multiple co-registered acquisitions are required, and the lack of robust motion correction limits its clinical translation. We introduce a single breath-hold myocardial T1ρ mapping method that includes model-based non-rigid motion correction. Methods A single-shot electrocardiogram (ECG)-triggered balanced steady state free precession (bSSFP) 2D adiabatic T1ρ mapping sequence that collects five T1ρ-weighted (T1ρw) images with different spin lock times within a single breath-hold is proposed. To address the problem of residual respiratory motion, a unified optimization framework consisting of a joint T1ρ fitting and model-based non-rigid motion correction algorithm, insensitive to contrast change, was implemented inline for fast (~ 30 s) and direct visualization of T1ρ maps. The proposed reconstruction was optimized on an ex vivo human heart placed on a motion-controlled platform. The technique was then tested in 8 healthy subjects and validated in 30 patients with suspected myocardial injury on a 1.5T CMR scanner. The Dice similarity coefficient (DSC) and maximum perpendicular distance (MPD) were used to quantify motion and evaluate motion correction. The quality of T1ρ maps was scored. In patients, T1ρ mapping was compared to cine imaging, T2 mapping and conventional post-contrast 2D late gadolinium enhancement (LGE). T1ρ values were assessed in remote and injured areas, using LGE as reference. Results Despite breath holds, respiratory motion throughout T1ρw images was much larger in patients than in healthy subjects (5.1 ± 2.7 mm vs. 0.5 ± 0.4 mm, P < 0.01). In patients, the model-based non-rigid motion correction improved the alignment of T1ρw images, with higher DSC (87.7 ± 5.3% vs. 82.2 ± 7.5%, P < 0.01), and lower MPD (3.5 ± 1.9 mm vs. 5.1 ± 2.7 mm, P < 0.01). This resulted in significantly improved quality of the T1ρ maps (3.6 ± 0.6 vs. 2.1 ± 0.9, P < 0.01). Using this approach, T1ρ mapping could be used to identify LGE in patients with 93% sensitivity and 89% specificity. T1ρ values in injured (LGE positive) areas were significantly higher than in the remote myocardium (68.4 ± 7.9 ms vs. 48.8 ± 6.5 ms, P < 0.01). Conclusions The proposed motion-corrected T1ρ mapping framework enables a quantitative characterization of myocardial injuries with relatively low sensitivity to respiratory motion. This technique may be a robust and contrast-free adjunct to LGE for gaining new insight into myocardial structural disorders.