Predicting post one-year durability of glucose-lowering monotherapies in patients with newly-diagnosed type 2 diabetes mellitus – A MASTERMIND precision medicine approach (UKPDS 87)

This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this record Aims: Predicting likely durability of glucose-lowering therapies for people with type 2 diabetes (T2D) could help inform individualised therapeutic choices. Methods: We used data from UKPDS patients with newly-diagnosed T2D randomised to first-line glucose-lowering monotherapy with chlorpropamide–glibenclamide–basal insulin or metformin. In 2339 participants who achieved one-year HbA1c values <7.5% (<59 mmol/mol)–we assessed relationships between one-year characteristics and time to monotherapy-failure (HbA1c ≥ 7.5% or requiring second-line therapy). Model validation was performed using bootstrap sampling. Results: Follow-up was median (IQR) 11.0 (8.0–14.0) years. Monotherapy-failure occurred in 72%–82%–75% and 79% for those randomised to chlorpropamide–glibenclamide–basal insulin or metformin respectively–after median 4.5 (3.0–6.6)–3.7 (2.6–5.6)–4.2 (2.7–6.5) and 3.8 (2.6– 5.2) years. Time-to-monotherapy-failure was predicted primarily by HbA1c and BMI values–with other risk factors varying by type of monotherapy–with predictions to within ±2.5 years for 55%–60%–56% and 57% of the chlorpropamide–glibenclamide–basal insulin and metformin monotherapy cohorts respectively. Conclusions: Post one-year glycaemic durability can be predicted robustly in individuals with newly-diagnosed T2D who achieve HbA1c values < 7.5% one year after commencing traditional monotherapies. Such information could be used to help guide glycaemic management for individual patients.Medical Research Council (MRC

Pulmonary 18F-FDG uptake helps refine current risk stratification in idiopathic pulmonary fibrosis (IPF).

PURPOSE: There is a lack of prognostic biomarkers in idiopathic pulmonary fibrosis (IPF) patients. The objective of this study is to investigate the potential of 18F-FDG-PET/ CT to predict mortality in IPF. METHODS: A total of 113 IPF patients (93 males, 20 females, mean age ± SD: 70 ± 9 years) were prospectively recruited for 18F-FDG-PET/CT. The overall maximum pulmonary uptake of 18F-FDG (SUVmax), the minimum pulmonary uptake or background lung activity (SUVmin), and target-to-background (SUVmax/ SUVmin) ratio (TBR) were quantified using routine region-of-interest analysis. Kaplan-Meier analysis was used to identify associations of PET measurements with mortality. We also compared PET associations with IPF mortality with the established GAP (gender age and physiology) scoring system. Cox analysis assessed the independence of the significant PET measurement(s) from GAP score. We investigated synergisms between pulmonary 18F-FDG-PET measurements and GAP score for risk stratification in IPF patients. RESULTS: During a mean follow-up of 29 months, there were 54 deaths. The mean TBR ± SD was 5.6 ± 2.7. Mortality was associated with high pulmonary TBR (p = 0.009), low forced vital capacity (FVC; p = 0.001), low transfer factor (TLCO; p  4.9 was 24 months. Combining PET data with GAP data ("PET modified GAP score") refined the ability to predict mortality. CONCLUSIONS: A high pulmonary TBR is independently associated with increased risk of mortality in IPF patients

New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk.

Levels of circulating glucose are tightly regulated. To identify new loci influencing glycemic traits, we performed meta-analyses of 21 genome-wide association studies informative for fasting glucose, fasting insulin and indices of beta-cell function (HOMA-B) and insulin resistance (HOMA-IR) in up to 46,186 nondiabetic participants. Follow-up of 25 loci in up to 76,558 additional subjects identified 16 loci associated with fasting glucose and HOMA-B and two loci associated with fasting insulin and HOMA-IR. These include nine loci newly associated with fasting glucose (in or near ADCY5, MADD, ADRA2A, CRY2, FADS1, GLIS3, SLC2A2, PROX1 and C2CD4B) and one influencing fasting insulin and HOMA-IR (near IGF1). We also demonstrated association of ADCY5, PROX1, GCK, GCKR and DGKB-TMEM195 with type 2 diabetes. Within these loci, likely biological candidate genes influence signal transduction, cell proliferation, development, glucose-sensing and circadian regulation. Our results demonstrate that genetic studies of glycemic traits can identify type 2 diabetes risk loci, as well as loci containing gene variants that are associated with a modest elevation in glucose levels but are not associated with overt diabetes

The effect of respiratory induced density variations on non-TOF PET quantitation in the lung

Accurate PET quantitation requires a matched attenuation map. Obtaining matched CT attenuation maps in the thorax is difficult due to the respiratory cycle which causes both motion and density changes. Unlike with motion, little attention has been given to the effects of density changes in the lung on PET quantitation. This work aims to explore the extent of the errors caused by pulmonary density attenuation map mismatch on dynamic and static parameter estimates. Dynamic XCAT phantoms were utilised using clinically relevant 18F-FDG and 18F-FMISO time activity curves for all organs within the thorax to estimate the expected parameter errors. The simulations were then validated with PET data from 5 patients suffering from idiopathic pulmonary fibrosis who underwent PET/Cine-CT. The PET data were reconstructed with three gates obtained from the Cine-CT and the average Cine-CT. The lung TACs clearly displayed differences between true and measured curves with error depending on global activity distribution at the time of measurement. The density errors from using a mismatched attenuation map were found to have a considerable impact on PET quantitative accuracy. Maximum errors due to density mismatch were found to be as high as 25% in the XCAT simulation. Differences in patient derived kinetic parameter estimates and static concentration between the extreme gates were found to be as high as 31% and 14%, respectively. Overall our results show that respiratory associated density errors in the attenuation map affect quantitation throughout the lung, not just regions near boundaries. The extent of this error is dependent on the activity distribution in the thorax and hence on the tracer and time of acquisition. Consequently there may be a significant impact on estimated kinetic parameters throughout the lung

Evaluation of a direct motion estimation/correction method in respiratory-gated PET/MRI with motion-adjusted attenuation

Purpose Respiratory motion compensation in PET/CT and PET/MRI is essential as motion is a source of image degradation (motion blur, attenuation artifacts). In previous work, we developed a direct method for joint image reconstruction/motion estimation (JRM) for attenuation-corrected (AC) respiratory-gated PET, which uses a single attenuation-map (μ-map). This approach was successfully implemented for respiratory-gated PET/CT, but since it relied on an accurate μ-map for motion estimation, the question of its applicability in PET/MRI is open. The purpose of this work is to investigate the feasibility of JRM in PET/MRI and to assess the robustness of the motion estimation when a degraded μ-map is used. Methods We performed a series of JRM reconstructions from simulated PET data using a range of simulated Dixon MRI sequence derived μ-maps with wrong attenuation values in the lungs, from −100% (no attenuation) to +100% (double attenuation), as well as truncated arms. We compared the estimated motions with the one obtained from JRM in ideal conditions (no noise, true μ-map as an input). We also applied JRM on 4 patient datasets of the chest, 3 of them containing hot lesions. Patient list-mode data were gated using a principal component analysis method. We compared SUVmax values of the JRM reconstructed activity images and non motion-corrected images. We also assessed the estimated motion fields by comparing the deformed JRM-reconstructed activity with individually non-AC reconstructed gates. Results Experiments on simulated data showed that JRM-motion estimation is robust to μ-map degradation in the sense that it produces motion fields similar to the ones obtained when using the true μ-map, regardless of the attenuation errors in the lungs (\u3c 0.5% mean absolute difference with the reference motion field). When using a μ-map with truncated arms, JRM estimates a motion field that stretches the μ-map in order to match the projection data. Results on patient datasets showed that using JRM improves the SUVmax values of hot lesions significantly and suppresses motion blur. When the estimated motion fields are applied to the reconstructed activity, the deformed images are geometrically similar to the non-AC individually reconstructed gates. Conclusion Motion estimation by JRM is robust to variation of the attenuation values in the lungs. JRM successfully compensates for motion when applied to PET/MRI clinical datasets. It provides a potential alternative to existing methods where the motion fields are pre-estimated from separate MRI measurements

Density variation during respiration affects PET quantitation in the lung

PET quantitation depends on the accuracy of the CT-derived attenuation correction map. In the lung, respiration leads to both positional and density mismatches, causing PET quantitation errors at lung borders but also within the whole lung. The aim of this work is to determine the extent of the associated errors on the measured time activity curves (TACs) and the corresponding kinetic parameter estimates. 5 patients with idiopathic pulmonary fibrosis underwent dynamic 18F-FDG PET and cine-CT imaging as part of an ongoing study. The cine-CT was amplitude gated using PCA techniques to produce end expiration (EXP), end inspiration (INS) and mid-breathing cycle (MID) gates representative of a short clinical CT acquisition. The ungated PET data were reconstructed with each CT gate and the TACs and kinetic parameters compared. Patient representative XCAT simulations with varying lung density, both with and without motion, were also produced to represent the above study allowing comparison of true to measured results. In all cases, the obtained PET TACs differed with each CT gate. For ROIs internal to the lung, the effect was dominated by changes in density, as opposed to motion. The errors in the TACs varied with time, providing evidence that errors due to attenuation mismatch depend on activity distribution. In the simulations, some kinetic parameters were over- and under-estimated by a factor of 2 in the INS and EXP gates respectively. For the patients, the maximum variation in kinetic parameters was 20%. Our results show that whole lung density changes during the respiratory cycle have a significant impact on PET quantitation. This is especially true of the kinetic parameter estimates as the extent of the error is dependent on tracer distribution which varies with time. It is therefore vital to use matched PET/CT for attenuation correction

Pulmonary 18F-FDG uptake helps refine current risk stratification in idiopathic pulmonary fibrosis (IPF).

PURPOSE: There is a lack of prognostic biomarkers in idiopathic pulmonary fibrosis (IPF) patients. The objective of this study is to investigate the potential of 18F-FDG-PET/ CT to predict mortality in IPF. METHODS: A total of 113 IPF patients (93 males, 20 females, mean age ± SD: 70 ± 9 years) were prospectively recruited for 18F-FDG-PET/CT. The overall maximum pulmonary uptake of 18F-FDG (SUVmax), the minimum pulmonary uptake or background lung activity (SUVmin), and target-to-background (SUVmax/ SUVmin) ratio (TBR) were quantified using routine region-of-interest analysis. Kaplan-Meier analysis was used to identify associations of PET measurements with mortality. We also compared PET associations with IPF mortality with the established GAP (gender age and physiology) scoring system. Cox analysis assessed the independence of the significant PET measurement(s) from GAP score. We investigated synergisms between pulmonary 18F-FDG-PET measurements and GAP score for risk stratification in IPF patients. RESULTS: During a mean follow-up of 29 months, there were 54 deaths. The mean TBR ± SD was 5.6 ± 2.7. Mortality was associated with high pulmonary TBR (p = 0.009), low forced vital capacity (FVC; p = 0.001), low transfer factor (TLCO; p  4.9 was 24 months. Combining PET data with GAP data ("PET modified GAP score") refined the ability to predict mortality. CONCLUSIONS: A high pulmonary TBR is independently associated with increased risk of mortality in IPF patients