Purpose: Nonalcoholic fatty liver disease (NAFLD) is the most common chronic hepatic disease worldwide, with functional impairment of the mitochondria occurring from early stages. Technetium-99m methoxy-isobutyl-isonitrile (99mTc-MIBI) is a lipophilic agent trapped in the mitochondria. This study aims to evaluate the utility of 99mTc-MIBI heart/liver uptake ratio in screening for NAFLD during myocardial perfusion imaging (MPI). Methods: Seventy eligible patients underwent a 2-d rest/stress 99mTc-MIBI scan with a 2-min planar image acquired in rest phase, at 30, 60, and 120 min postradiotracer administration. Heart/liver uptake ratio was calculated by placing identical regions of interest on the heart and liver dome. All patients underwent liver ultrasound and were allocated into groups A, having NAFLD; and B, healthy individuals without NAFLD. Results: Mean count per pixel heart/liver ratios gradually increased over time in either group; nonetheless the values were significantly higher in group A, regardless of acquisition timing; with the p-value equal to 0.007, 0.014, and 0.010 at 30, 60, and 120 min, respectively. Conclusion: Determining 99mTc-MIBI heart/liver uptake ratio during rest phase in patients undergoing MPI may be a useful, noninvasive screening method for NAFLD; with no additional cost, radiation burden, or adverse effects in these patients. Trial registration number: IR.SBMU.MSP.REC.1398.308.

Nonalcoholic fatty liver disease (NAFLD) is a complex metabolic-inflammatory disease associated with poor outcomes and decreased quality of life. NAFLD is overrepresented in patients with psychiatric disorders like depression, bipolar disorder, and schizophrenia; however, a comprehensive review on NAFLD and psychiatric disorders remains to be delineated. This review endeavors to investigate the association of NAFLD with psychiatric disorders, including shared pathogenesis and future clinical derivatives. Extant literature suggests that patients with psychiatric disorders (in particular, mood disorders) are more susceptible to the development of NAFLD due to multiple reasons, including but not limited to hypothalamic-pituitary-adrenal axis dysregulation, metabolic syndrome, and chronic perceived stress. Moreover, the clinical manifestations of mood disorders (e.g., anhedonia, psychomotor retardation, lifestyle modification, etc.), and potentially long-term treatment with weight-gaining agents, differentially affect these patients, making them more prone to NAFLD. Considering the increased morbidity associated with both mood disorders and NAFLD, our review recommends regular screenings for NAFLD in select patients with mood disorders exhibiting signs of increased risk (i.e., obesity, metabolic syndrome, diabetes, or family history of NAFLD) for better diagnosis and holistic care of both potentially interrelated conditions.

Many adults have risk factors for non-alcoholic fatty liver disease (NAFLD). Screening all adults with risk factors for NAFLD using imaging is not feasible.

To develop a practical scoring tool for predicting NAFLD using participant demographics, medical history, anthropometrics, and lab values.

Cross-sectional.

Data came from 6194 white, African American, Hispanic, and Chinese American participants from the Multi-Ethnic Study of Atherosclerosis cohort, ages 45-85 years.

NAFLD was identified by liver computed tomography (≤ 40 Hounsfield units indicating > 30% hepatic steatosis) and data on 14 predictors was assessed for predicting NAFLD. Random forest variable importance was used to identify the minimum subset of variables required to achieve the highest predictive power. This subset was used to derive (n = 4132) and validate (n = 2063) a logistic regression-based score (NAFLD-MESA Index). A second NAFLD-Clinical Index excluding laboratory predictors was also developed.

NAFLD prevalence was 6.2%. The model included eight predictors: age, sex, race/ethnicity, type 2 diabetes, smoking history, body mass index, gamma-glutamyltransferase (GGT), and triglycerides (TG). The NAFLD-Clinical Index model excluded GGT and TG. In the NAFLD-MESA model, the derivation set achieved an AUCNAFLD-MESA = 0.83 (95% CI, 0.81 to 0.86), and the validation set an AUCNAFLD-MESA = 0.80 (0.77 to 0.84). The NAFLD-Clinical Index model was AUCClinical = 0.78 [0.75 to 0.81] in the derivation set and AUCClinical = 0.76 [0.72 to 0.80] in the validation set (pBonferroni-adjusted < 0.01).

The two models are simple but highly predictive tools that can aid clinicians to identify individuals at high NAFLD risk who could benefit from imaging.