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BACKGROUND: Patients with cirrhosis are growing older and the overlap between hepatic encephalopathy (HE) & pre-dementia mild cognitive impairment (MCI) is unclear. HE affects visuospatial/psychomotor speed while MCI affects memory. Aim: Determine the performance of elderly cirrhotics on tests for HE and dementia and their impact on quality of life (QOL). METHODS: Outpatient cirrhotics and controls ages 65–95 years were recruited at 4 centers. Subjects had to have MMSE > 25, no current HE or dementia to be eligible. All subjects got tests for HE (psychometric hepatic encephalopathy score, PHES: 5 tests & low score = poor, EncephalApp, OffTime + OnTime, high score = poor) and QOL: Sickness Impact profile (SIP, high score = poor QOL). Cirrhotics also got tests for MCI; RBANS (tests immediate memory, delayed memory, language, visuo-spatial & attention). A neuro-psychologist evaluated results and divided cirrhotics into (A) unimpaired (B) MCI only (C) HE only & (D) (MCI/HE overlap). Demographics, MELD, alcohol etiology, and SIP were compared. Finally, age, gender and education-adjusted norms were created for PHES and EncephalApp based on the controls. Presence of MHE and sensitivity of EncephalApp for MHE diagnosis were evaluated. RESULTS: 109 cirrhotics and 100 non-cirrhotic subjects were included. Demographics/education levels were statistically similar between centers. Controls were older than cirrhotics (74.9 ± 6.6 vs 70.5 ± 4.4, P < 0.05) and had similar education/gender distribution. Despite this, controls performed better than cirrhotics on all tests (PHES 2.9 ± 12.4 vs −4.5 ± +4.5, P < 0.001, EncephalApp Off+On 181.4 ± +71.9 vs 218.2 ± +80.0, P = 0.03) and had a better QOL (SIP total 3.8 ± +7.1 vs 7.9 ± +9.5, Psych 3.3 ± +8.4 vs 7.2 ± +11.1, Phys 3.0 ± +6.2 vs 6.7 ± +9.5, all P < 0.001). Within cirrhosis subgroups (Table 1), demographics, MELD/alc & MMSE were similar. Pts with both MCI/HE had worse cognition on all tests, which translated into a worse QOL compared to other groups. Presence of HE, with/without MCI, contributed towards poor QOL. Norms for PHES/EncephalApp: Adjusting for age, gender & education, 17% (n = 17) patients were positive for MHE on PHES compared to controls. On EncephalApp, 49% (n = 47) patients were positive. AUC for EncephalApp using PHES as the gold standard was 0.86 (0.78-0.95 CI). CONCLUSIONS: In this multi-center study, adjusted norms defining the high sensitivity of EncephalApp to diagnose HE in older individuals were created. Presence of HE regardless of MCI contributed towards poor cognition and QOL in patients >65 years.

PurposeTo quantify the effects of DCE acquisition and pharmacokinetic modeling processing methodologies on the absolute accuracy and precision of derived pharmacokinetic (PK) parameter values using a novel anthropomorphic phantom test device in which “ground truth” values were known a priori.MethodsGround truth arterial input function (AIF), tumor, and healthy tissue contrast agent concentration‐time curves (CTCs) were established within the phantom and repeatedly measured on a 3T MRI scanner with varying temporal resolution (Tres = 1.22–30.6 s). Ground truth CTCs, Ktrans, ve, and kep values were directly compared to measured values as a function of Tres, with and without the application of voxel‐wise flip‐angle corrections applied to the data and PK modeling performed using linear and nonlinear forms of the standard Tofts model.ResultsMeasurement of the AIF was strongly affected by the Tres used (AIF curve‐shape feature errors: 3%–222% for Tres: 1.22–30.6 s), which directly translated to errors in the derived Ktrans, ve, and kep values of 1%–24%, 2%–5%, and 1%–26% respectively across this Tres range (flip‐angle correction applied). Further appreciable improvements in accuracy and precision arising from the use of flip angle corrections and nonlinear least squares fitting were quantified and used to identify optimal acquisition and analysis methodologies for which measurement errors could be constrained below threshold levels.ConclusionThis quantitative study provides insight into how errors in AIF measurement propagate to errors in PK parameter outputs. Absolute quantification of the accuracy and precision of MR‐measured CTCs, and resultant PK parameter values, allowed for an optimal temporal resolution to be defined commensurate with maintaining Ktrans, ve, and kep measurement errors below 5% and 10% levels. An appreciable gain in PK parameter estimation accuracy at the analysis stage was also demonstrated using flip‐angle corrections and a linear approach to PK model fitting.

BackgroundMR image intensity nonuniformity is often observed at 7T. Reference scans from the body coil used for uniformity correction at lower field strengths are typically not available at 7T.PurposeTo evaluate the efficacy of a novel algorithm, Uniform Combined Reconstruction (UNICORN), to correct receive coil‐induced nonuniformity in musculoskeletal 7T MRI without the use of a reference scan.Study TypeRetrospective image analysis study.SubjectsMRI data of 20 subjects was retrospectively processed offline.Field Strength/Sequence: Knees of 20 subjects were imaged at 7T with a single‐channel transmit, 28‐channel phased‐array receive knee coil. A turbo‐spin‐echo sequence was used to acquire 33 series of images.AssessmentThree fellowship‐trained musculoskeletal radiologists with cumulative experience of 42 years reviewed the images. The uniformity, contrast, signal‐to‐noise ratio (SNR), and overall image quality were evaluated for images with no postprocessing, images processed with N4 bias field correction algorithm, and the UNICORN algorithm.Statistical TestsIntraclass correlation coefficient (ICC) was used for measuring the interrater reliability. ICC and 95% confidence intervals (CIs) were calculated using the R statistical package employing a two‐way mixed‐effects model based on a mean rating (k = 3) for absolute agreement. The Wilcoxon signed‐rank test with continuity correction was used for analyzing the overall image quality scores.ResultsUNICORN was preferred among the three methods evaluated for uniformity in 97.9% of the pooled ratings, with excellent interrater agreement (ICC of 0.98, CI 0.97–0.99). UNICORN was also rated better than N4 for contrast and equivalent to N4 in SNR with ICCs of 0.80 (CI 0.72–0.86) and 0.67 (CI 0.54–0.77), respectively. The overall image quality scores for UNICORN were significantly higher than N4 (P < 6 × 10‐13), with good to excellent interrater agreement (ICC 0.90, CI 0.86–0.93).Data ConclusionWithout the use of a reference scan, UNICORN provides better image uniformity, contrast, and overall image quality at 7T compared with the N4 bias field‐correction algorithm.Level of Evidence: 4Technical Efficacy: Stage 1J. Magn. Reson. Imaging 2019;50:1534–1544.