Observer study-based evaluation of TGAN architecture used to generate oncological PET images

The application of computer-vision algorithms in medical imaging has increased rapidly in recent years. However, algorithm training is challenging due to limited sample sizes, lack of labeled samples, as well as privacy concerns regarding data sharing. To address these issues, we previously developed (Bergen et al. 2022) a synthetic PET dataset for Head and Neck (H and N) cancer using the temporal generative adversarial network (TGAN) architecture and evaluated its performance segmenting lesions and identifying radiomics features in synthesized images. In this work, a two-alternative forced-choice (2AFC) observer study was performed to quantitatively evaluate the ability of human observers to distinguish between real and synthesized oncological PET images. In the study eight trained readers, including two board-certified nuclear medicine physicians, read 170 real/synthetic image pairs presented as 2D-transaxial using a dedicated web app. For each image pair, the observer was asked to identify the real image and input their confidence level with a 5-point Likert scale. P-values were computed using the binomial test and Wilcoxon signed-rank test. A heat map was used to compare the response accuracy distribution for the signed-rank test. Response accuracy for all observers ranged from 36.2% [27.9-44.4] to 63.1% [54.8-71.3]. Six out of eight observers did not identify the real image with statistical significance, indicating that the synthetic dataset was reasonably representative of oncological PET images. Overall, this study adds validity to the realism of our simulated H&N cancer dataset, which may be implemented in the future to train AI algorithms while favoring patient confidentiality and privacy protection

Assessing Privacy Leakage in Synthetic 3-D PET Imaging using Transversal GAN

Training computer-vision related algorithms on medical images for disease diagnosis or image segmentation is difficult in large part due to privacy concerns. For this reason, generative image models are highly sought after to facilitate data sharing. However, 3-D generative models are understudied, and investigation of their privacy leakage is needed. We introduce our 3-D generative model, Transversal GAN (TrGAN), using head & neck PET images which are conditioned on tumour masks as a case study. We define quantitative measures of image fidelity, utility and privacy for our model. These metrics are evaluated in the course of training to identify ideal fidelity, utility and privacy trade-offs and establish the relationships between these parameters. We show that the discriminator of the TrGAN is vulnerable to attack, and that an attacker can identify which samples were used in training with almost perfect accuracy (AUC = 0.99). We also show that an attacker with access to only the generator cannot reliably classify whether a sample had been used for training (AUC = 0.51). This suggests that TrGAN generators, but not discriminators, may be used for sharing synthetic 3-D PET data with minimal privacy risk while maintaining good utility and fidelity.Comment: arXiv admin note: text overlap with arXiv:2111.0186

Transcript Expression Data from Human Islets Links Regulatory Signals from Genome-Wide Association Studies for Type 2 Diabetes and Glycemic Traits to Their Downstream Effectors

The intersection of genome-wide association analyses with physiological and functional data indicates that variants regulating islet gene transcription influence type 2 diabetes (T2D) predisposition and glucose homeostasis. However, the specific genes through which these regulatory variants act remain poorly characterized. We generated expression quantitative trait locus (eQTL) data in 118 human islet samples using RNA-sequencing and high-density genotyping. We identified fourteen loci at which cis-exon-eQTL signals overlapped active islet chromatin signatures and were coincident with established T2D and/or glycemic trait associations. ‎At some, these data provide an experimental link between GWAS signals and biological candidates, such as DGKB and ADCY5. At others, the cis-signals implicate genes with no prior connection to islet biology, including WARS and ZMIZ1. At the ZMIZ1 locus, we show that perturbation of ZMIZ1 expression in human islets and beta-cells influences exocytosis and insulin secretion, highlighting a novel role for ZMIZ1 in the maintenance of glucose homeostasis. Together, these findings provide a significant advance in the mechanistic insights of T2D and glycemic trait association loci

Transcript Expression Data from Human Islets Links Regulatory Signals from Genome-Wide Association Studies for Type 2 Diabetes and Glycemic Traits to Their Downstream Effectors.

The intersection of genome-wide association analyses with physiological and functional data indicates that variants regulating islet gene transcription influence type 2 diabetes (T2D) predisposition and glucose homeostasis. However, the specific genes through which these regulatory variants act remain poorly characterized. We generated expression quantitative trait locus (eQTL) data in 118 human islet samples using RNA-sequencing and high-density genotyping. We identified fourteen loci at which cis-exon-eQTL signals overlapped active islet chromatin signatures and were coincident with established T2D and/or glycemic trait associations. ‎At some, these data provide an experimental link between GWAS signals and biological candidates, such as DGKB and ADCY5. At others, the cis-signals implicate genes with no prior connection to islet biology, including WARS and ZMIZ1. At the ZMIZ1 locus, we show that perturbation of ZMIZ1 expression in human islets and beta-cells influences exocytosis and insulin secretion, highlighting a novel role for ZMIZ1 in the maintenance of glucose homeostasis. Together, these findings provide a significant advance in the mechanistic insights of T2D and glycemic trait association loci

Human islet function following 20 years of cryogenic biobanking.

Aims/hypothesisThere are potential advantages to the low-temperature (-196 °C) banking of isolated islets, including the maintenance of viable islets for future research. We therefore assessed the in vitro and in vivo function of islets cryopreserved for nearly 20 years.MethodsHuman islets were cryopreserved from 1991 to 2001 and thawed between 2012 and 2014. These were characterised by immunostaining, patch-clamp electrophysiology, insulin secretion, transcriptome analysis and transplantation into a streptozotocin (STZ)-induced mouse model of diabetes.ResultsThe cryopreservation time was 17.6 ± 0.4 years (n = 43). The thawed islets stained positive with dithizone, contained insulin-positive and glucagon-positive cells, and displayed levels of apoptosis and transcriptome profiles similar to those of freshly isolated islets, although their insulin content was lower. The cryopreserved beta cells possessed ion channels and exocytotic responses identical to those of freshly isolated beta cells. Cells from a subset of five donors demonstrated similar perifusion insulin secretion profiles pre- and post-cryopreservation. The transplantation of cryopreserved islets into the diabetic mice improved their glucose tolerance but did not completely normalise their blood glucose levels. Circulating human insulin and insulin-positive grafts were detectable at 10 weeks post-transplantation.Conclusions/interpretationWe have demonstrated the potential for long-term banking of human islets for research, which could enable the use of tissue from a large number of donors with future technologies to gain new insight into diabetes

Human islet function following 20 years of cryogenic biobanking.

Aims/hypothesisThere are potential advantages to the low-temperature (-196 °C) banking of isolated islets, including the maintenance of viable islets for future research. We therefore assessed the in vitro and in vivo function of islets cryopreserved for nearly 20 years.MethodsHuman islets were cryopreserved from 1991 to 2001 and thawed between 2012 and 2014. These were characterised by immunostaining, patch-clamp electrophysiology, insulin secretion, transcriptome analysis and transplantation into a streptozotocin (STZ)-induced mouse model of diabetes.ResultsThe cryopreservation time was 17.6 ± 0.4 years (n = 43). The thawed islets stained positive with dithizone, contained insulin-positive and glucagon-positive cells, and displayed levels of apoptosis and transcriptome profiles similar to those of freshly isolated islets, although their insulin content was lower. The cryopreserved beta cells possessed ion channels and exocytotic responses identical to those of freshly isolated beta cells. Cells from a subset of five donors demonstrated similar perifusion insulin secretion profiles pre- and post-cryopreservation. The transplantation of cryopreserved islets into the diabetic mice improved their glucose tolerance but did not completely normalise their blood glucose levels. Circulating human insulin and insulin-positive grafts were detectable at 10 weeks post-transplantation.Conclusions/interpretationWe have demonstrated the potential for long-term banking of human islets for research, which could enable the use of tissue from a large number of donors with future technologies to gain new insight into diabetes

Islet eQTL data identifies ZMIZ1 as a novel gene involved in maintenance of glucose homeostasis in the human islet.

<p>(a) Regional plot showing the T2D-associated variant rs12571751 is in strong LD with the lead eQTL variant for ZMIZ1, and overlaps a long stretch of islet enhancer chromatin (denoted as red and blue in the tracks underneath the plot). (b) Immunofluorescence shows ZMIZ1 localizes to the islet within human pancreas sections, with staining in both alpha- and beta-cells. Effect of ZMIZ1 over-expression (c) and knockdown (d) on insulin secretion in human islets, showing significant (p<0.05) reduction in glucose- and KCl-stimulated insulin secretion during over-expression, and KCl-stimulated insulin secretion only during knockdown. (e) Western blot analysis confirms higher levels of ZMIZ1 after ZMIZ1 over-expression (left). Exocytosis was measured from single human beta-cells, expressing GFP alone or together with ZMIZ1, as increases in membrane capacitance during a train of membrane depolarizations. Representative traces (right) and (f) averaged data from 6 human donors (41–44 beta-cells) are show the significant (p<0.05) reduction in exocytosis in ZMIZ1-transfected beta-cells compared to GFP-controls. (g) Voltage-dependent Ca2+ currents were measured from human beta-cells expressing GFP alone or together with ZMIZ1. The average total Ca2+ charge entry during the depolarization (24–27 beta-cells from 3 individuals) was unchanged by ZMIZ1 over-expression.</p

Fourteen loci with co-localizing islet exon-eQTL and GWAS signals at loci for T2D and glycemic traits.

<p>Information on each of the fourteen loci for type 2 diabetes and/or glycemic traits where islet eQTL data provided putative effector transcripts. *Effect on gene expression is given for the allele associated with the trait effect directions in the column “Associated trait effects of eQTL allele”.</p