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Hepatic steatosis is associated with significant morbidity and mortality after liver resection and transplantation. This study focuses on the role of autophagy in regulating sensitivity of fatty livers to ischemia and reperfusion (I/R) injury. Quantitative immunohistochemistry conducted on human liver allograft biopsies showed that, the reduction of autophagy markers LC3 and Beclin-1 at 1 h after reperfusion, was correlated with hepatic steatosis and poor survival of liver transplant recipients. In animal studies, western blotting and confocal imaging analysis associated the increase in sensitivity to I/R injury with low autophagy activity in fatty livers. Screening of autophagy-related proteins showed that Atg3 and Atg7 expression levels were marked decreased, whereas calpain 2 expression was upregulated during I/R in fatty livers. Calpain 2 inhibition or knockdown enhanced autophagy and suppressed cell death. Further point mutation experiments revealed that calpain 2 cleaved Atg3 and Atg7 at Atg3Δ92–97 and Atg7Δ344–349, respectively. In vivo and in vitro overexpression of Atg3 or Atg7 enhanced autophagy and suppressed cell death after I/R in fatty livers. Collectively, calpain 2-mediated degradation of Atg3 and Atg7 in fatty livers increases their sensitivity to I/R injury. Increasing autophagy may ameliorate fatty liver damage and represent a valuable method to expand the liver donor pool.

BACKGROUND AND PURPOSE: Total brain volume and total intracranial volume are important measures for assessing whole-brain atrophy in Alzheimer disease, dementia, and other neurodegenerative diseases. Unlike MR imaging, which has a number of well-validated fully-automated methods, only a handful of methods segment CT images. Available methods either use enhanced CT, do not estimate both volumes, or require formal validation. Reliable computation of total brain volume and total intracranial volume from CT is needed because head CTs are more widely used than head MRIs in the clinical setting. We present an automated head CT segmentation method (CTseg) to estimate total brain volume and total intracranial volume. MATERIALS AND METHODS: CTseg adapts a widely used brain MR imaging segmentation method from the Statistical Parametric Mapping toolbox using a CT-based template for initial registration. CTseg was tested and validated using head CT images from a clinical archive. RESULTS: CTseg showed excellent agreement with 20 manually segmented head CTs. The intraclass correlation was 0.97 (P , .001) for total intracranial volume and 0.94 (P , .001) for total brain volume. When CTseg was applied to a cross-sectional Alzheimer disease dataset (58 with Alzheimer disease patients and 58 matched controls), CTseg detected a loss in percentage total brain volume (as a percentage of total intracranial volume) with age (P , .001) as well as a group difference between patients with Alzheimer disease and controls (P , .01). We observed similar results when total brain volume was modeled with total intracranial volume as a confounding variable. CONCLUSIONS: In current clinical practice, brain atrophy is assessed by inaccurate and subjective "eyeballing" of CT images. Manual segmentation of head CT images is prohibitively arduous and time-consuming. CTseg can potentially help clinicians to automatically measure total brain volume and detect and track atrophy in neurodegenerative diseases. In addition, CTseg can be applied to large clinical archives for a variety of research studies. ABBREVIATIONS: AD 4 Alzheimer disease; BET 4 Brain Extraction Tool; ICC 4 intraclass correlation coefficient; TBV 4 total brain volume; TIV 4 total intracranial volume; TPM 4 tissue probability map