Diagnostic performance of automated MRI volumetry by icobrain dm for Alzheimer’s disease in a clinical setting: a REMEMBER study

Magnetic resonance imaging (MRI) has become important in the diagnostic work-up of neurodegenerative diseases. icobrain dm, a CE-labeled and FDA-cleared automated brain volumetry software, has shown potential in differentiating cognitively healthy controls (HC) from Alzheimer's disease (AD) dementia (ADD) patients in selected research cohorts. This study examines the diagnostic value of icobrain dm for AD in routine clinical practice, including a comparison to the widely used FreeSurfer software, and investigates if combined brain volumes contribute to establish an AD diagnosis. The study population included HC (n = 90), subjective cognitive decline (SCD, n = 93), mild cognitive impairment (MCI, n = 357), and ADD (n = 280) patients. Through automated volumetric analyses of global, cortical, and subcortical brain structures on clinical brain MRI T1w (n = 820) images from a retrospective, multi-center study (REMEMBER), icobrain dm's (v.4.4.0) ability to differentiate disease stages via ROC analysis was compared to FreeSurfer (v.6.0). Stepwise backward regression models were constructed to investigate if combined brain volumes can differentiate between AD stages. icobrain dm outperformed FreeSurfer in processing time (15-30 min versus 9-32 h), robustness (0 versus 67 failures), and diagnostic performance for whole brain, hippocampal volumes, and lateral ventricles between HC and ADD patients. Stepwise backward regression showed improved diagnostic accuracy for pairwise group differentiations, with highest performance obtained for distinguishing HC from ADD (AUC = 0.914; Specificity 83.0%; Sensitivity 86.3%). Automated volumetry has a diagnostic value for ADD diagnosis in routine clinical practice. Our findings indicate that combined brain volumes improve diagnostic accuracy, using real-world imaging data from a clinical setting

Reprogramming of human pancreatic exocrine cells to β-like cells

© 2015 Macmillan Publishers Limited. All rights reserved.Rodent acinar cells exhibit a remarkable plasticity as they can transdifferentiate to duct-, hepatocyte- and islet β-like cells. We evaluated whether exocrine cells from adult human pancreas can sim

Neurogenin 3 Expressing Cells in the Human Exocrine Pancreas Have the Capacity for Endocrine Cell Fate

Neurogenin 3 (NGN3) is necessary and sufficient for endocrine differentiation during pancreatic development and is expressed by a population of progenitor cells that give rise exclusively to hormone-secreting cells within islets. NGN3 protein can be detected in the adult rodent pancreas only following certain types of injury, when it is transiently expressed by exocrine cells undergoing reprogramming to an endocrine cell fate. Here, NGN3 protein can be detected in 2% of acinar and duct cells in living biopsies of histologically normal adult human pancreata and 10% in cadaveric biopsies of organ donor pancreata. The percentage and total number of NGN3+ cells increase during culture without evidence of proliferation or selective cell death. Isolation of highly purified and viable NGN3+ cell populations can be achieved based on coexpression of the cell surface glycoprotein CD133. Transcriptome and targeted expression analyses of isolated CD133+ / NGN3+ cells indicate that they are distinct from surrounding exocrine tissue with respect to expression phenotype and Notch signaling activity, but retain high level mRNA expression of genes indicative of acinar and duct cell function. NGN3+ cells have an mRNA expression profile that resembles that of mouse early endocrine progenitor cells. During in vitro differentiation, NGN3+ cells express genes in a pattern characteristic of endocrine development and result in cells that resemble beta cells on the basis of coexpression of insulin C-peptide, chromogranin A and pancreatic and duodenal homeobox 1. NGN3 expression in the adult human exocrine pancreas marks a dedifferentiating cell population with the capacity to take on an endocrine cell fate. These cells represent a potential source for the treatment of diabetes either through ex vivo manipulation, or in vivo by targeting mechanisms controlling their population size and endocrine cell fate commitment