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Background: Iron rims (IRs) surrounding white matter lesions (WMLs) are suggested to predict a more severe disease course. Only small longitudinal cohorts of patients with and without iron rim lesions (IRLs) have been reported so far. Objective: To assess whether the presence and number of IRLs in patients with clinically isolated syndrome (CIS) and multiple sclerosis (MS) are associated with long-term disability or progressive disease. Methods: Ninety-one CIS/MS patients were recruited between 2008 and 2013 and scanned with 7 T magnetic resonance imaging (MRI). Expanded Disability Status Scale (EDSS) was used to calculate Age-related Multiple Sclerosis Severity Score (ARMSS) at the time of scan and at the latest clinical follow-up after 9 years. WMLs were assessed for the presence of IRL using Susceptibility weighted imaging (SWI)-filtered phase images. Results: In all, 132 IRLs were detected in 42 patients (46%); 9% of WMLs had IRs; 54% of the cohort had no rims, 30% had 1–3 rims and 16% had ⩾4. Patients with IRL had a higher EDSS and ARMSS. Presence of IRL was also a predictor of long-term disability, especially in patients with ⩾4 IRLs. IRLs have a greater impact on disability compared to the WML number and volume. Conclusion: The presence and number of perilesional IR on MRI hold prognostic value for long-term clinical disability in MS.

Connecting the wellbore and reservoir rock systems through perforating is the primary mechanism to provide a flow path for hydrocarbons. In stimulation, this pathway becomes two dimensional (in functionality) because it is required to facilitate injection of fracturing fluids and production of reservoir fluids. Ineffective perforation can add of near-wellbore complexities. In this study, we looked at different perforation techniques from classical to recent contemporary. We investigated both stimulation and intervention aspects to provide pros and cons for these techniques and evaluate their effectiveness. Six challenging scenarios in stimulation were detailed with lessons learnt, best practices, and guidelines. These included deviated wells, soft rock formations, double pipe completions, fracture diversion requirement, horizontal wells with plug-and-perforate completions, and a mature asset. The workflows included perspectives such as perforating, fracture pressure analysis, and diagnostic injections. Efficient workflows for the well engineering cycle were also developed for the case when the injection rate cannot be established due to the inefficient wellbore−rock connection. Contingency interventions and bottomhole assembly (BHA) configurations were investigated with the goal of enabling a flexible strategy in a single intervention run to enhance injectivity.Currently, operational efficiency and business needs are paramount. This work presents integrated understanding, established practices, and resulting workflows to manage tradeoff and optimize the net present value of integrated projects.

BackgroundType 2 diabetes mellitus impacts the brain microstructural environment. Diffusion tensor imaging (DTI) has been widely used to characterize white matter microstructural abnormalities in type 2 diabetes but fails to fully characterise disease effects on complex white matter tracts. Neurite orientation dispersion and density imaging (NODDI) has been proposed as an alternative to DTI with higher specificity to characterize white matter microstructures. Although NODDI has not been widely applied in diabetes, this biophysical model has the potential to investigate microstructural changes in white matter pathology.Aims and objectives(1) To investigate brain white matter alterations in people with type 2 diabetes using DTI and NODDI; (2) To assess the association between white matter changes in type 2 diabetes with disease duration and diabetes control as reflected by glycated haemoglobin (HbA1c) levels.MethodsWe examined white matter microstructure in 48 white matter tracts using data from the UK Biobank in 3,338 participants with type 2 diabetes (36% women, mean age 66 years) and 30,329 participants without type 2 diabetes (53% women, mean age 64 years). The participants had undergone 3.0T multiparametric brain imaging, including T1 weighted imaging and diffusion imaging for DTI and NODDI. Region of interest analysis of fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), radial diffusivity (RD), orientation dispersion index (ODI), intracellular volume fraction (ICVF), and isotropic water fraction (IsoVF) were conducted to assess white matter abnormalities. A general linear model was applied to evaluate intergroup white matter differences and their association with the metabolic profile.ResultReduced FA and ICVF and increased MD, AD, RD, ODI, and IsoVF values were observed in participants with type 2 diabetes compared to non-type 2 diabetes participants (PPPDiscussionNODDI detected microstructural changes in brain white matter in participants with type 2 diabetes. The revealed abnormalities are proxies for lower neurite density and loss of fibre orientation coherence, which correlated with longer disease duration and an index of poorly controlled blood sugar. NODDI contributed to DTI in capturing white matter differences in participants with type 2 diabetes, suggesting the feasibility of NODDI in detecting white matter alterations in type 2 diabetes.ConclusionType 2 diabetes can cause white matter microstructural abnormalities that have associations with glucose control. The NODDI diffusion model allows the characterisation of white matter neuroaxonal pathology in type 2 diabetes, giving biophysical information for understanding the impact of type 2 diabetes on brain microstructure.

Last year, the oil and gas industry was hit with one of the biggest challenges in the history of the industry — COVID-19. This has been a pandemic no one imagined would cripple the whole world and threaten our very existence. It caused an imbalance to the oil supply and demand where the global oil market had more than it could use or store, which drove oil prices to a record low. Despite this, projects in development have to be completed to accommodate the future rise in demand that is expected to occur after the pandemic. This paper will showcase how the rigless operations in Saudi Arabia in the oil and gas fields managed to continue with their activities toward tackling this challenge by capitalizing on two main principles. The first principle was business continuity management; preparing a strategic and operational framework to actively increase resilience to prevent suspension of the rigless operations or services, and thereby fulfilling the industry demand and preventing a cash flow interruption to the stakeholders. The second principle was the risk management process (RMP); identifying, monitoring, and managing all risks related to COVID-19, which minimized, and in some cases eliminated, its impact on the rigless operations. Both principles were the main pillars to first preserve lives and second to assure business continuity, which resulted in the continuation of the rigless operation and the profitability under the COVID-19 challenge for the company. COVID-19 was a risk no one accounted for. It was a true test to business continuity management and the risk management process. The integration of both processes in the oil industry, and specifically in rigless operations for the first time due to this pandemic, was essential to overcome the COVID-19 crises in addition to tailoring specific steps to address this challenge. Therefore, the rigless operations continued with planned activities while preserving people's lives.

Introduction Early identification of patients at high risk of progression could help with a personalised treatment strategy. Magnetic resonance imaging (MRI) measures have been proposed to predict long-term disability in multiple sclerosis (MS), but a reliable predictor that can be easily implemented clinically is still needed. Aim Assess MRI measures during the first 5 years of the MS disease course for the ability to predict progression at 10+ years. Methods Eighty-two MS patients (53 females), with ≥10 years of clinical follow-up and having two MRI scans, were included. Clinical data were obtained at baseline, follow-up and at ≥10 years. White matter lesion (WML) counts and volumes, and four linear brain sizes were measured on T2/FLAIR ‘Fluid-Attenuated-Inversion-Recovery’ and T1-weighted images. Results Baseline and follow-up inter-caudate diameter (ICD) and third ventricular width (TVW) measures correlated positively with Expanded Disability Status Scale, ≥10 or more of WMLs showed a high sensitivity in predicting progression, at ≥10 years. A steeper rate of lesion volume increase was observed in subjects converting to secondary progressive MS. The sensitivity and specificity of both ICD and TVW, to predict disability at ≥10 years were 60% and 64%, respectively. Conclusion Despite advances in brain imaging and computerised volumetric analysis, ICD and TVW remain relevant as they are simple, fast and have the potential in predicting long-term disability. However, in this study, despite the statistical significance of these measures, the clinical utility is still not reliable.

IntroductionIdentifying accurate prognostic imaging biomarkers in multiple sclerosis (MS) is crucial. Iron rims (IR) surrounding white matter lesions (WML) are suggested to predict a more severe disease course. Only small longitudinal cohorts of patients with and without IRL have been reported so far.ObjectiveTo assess if the presence and number of IRL in patients with CIS and MS are associated with worse long-term clinical disability.MethodsNinety-one CIS/MS patients were recruited between 2008 and 2013 and scanned with 7T MRI. Age-Related Multiple Sclerosis Score (ARMSS), a validated measure of disease severity, was calculated for patients at the time of scan and at the latest clinical follow-up after 9 years. WMLs were assessed for the presence of IRL using SWI-filtered phase images.Results132 IRLs were detected in 42 patients (46%). 9% of WMLs had IR. 54% of the cohort had no rims, 30% had 1-3 rims and 16% had ≥4. Patients with IRL at baseline had a higher EDSS and ARMSS. Presence of IRL was also a predictor of long-term disability especially in those patients with ≥4 IRL. The effect of IRL on disability was greater than the baseline WML numbers, another known prognostic biomarker.ConclusionThe presence and number of perilesional IR at a baseline scan hold prognostic value for long term clinical disability in MS.