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Background: Quantitative imaging studies of the pancreas have often targeted the three main anatomical segments, head, body, and tail, using manual region of interest strategies to assess geographic heterogeneity. Existing automated analyses have implemented whole‐organ segmentation, providing overall quantification but failing to address spatial heterogeneity. Purpose: To develop and validate an automated method for pancreas segmentation into head, body, and tail subregions in abdominal MRI. Study Type: Retrospective. Subjects: One hundred and fifty nominally healthy subjects from UK Biobank (100 subjects for method development and 50 subjects for validation). A separate 390 UK Biobank triples of subjects including type 2 diabetes mellitus (T2DM) subjects and matched nondiabetics. Field strength/Sequence: A 1.5 T, three‐dimensional two‐point Dixon sequence (for segmentation and volume assessment) and a two‐dimensional axial multiecho gradient‐recalled echo sequence. Assessment: Pancreas segments were annotated by four raters on the validation cohort. Intrarater agreement and interrater agreement were reported using Dice overlap (Dice similarity coefficient [DSC]). A segmentation method based on template registration was developed and evaluated against annotations. Results on regional pancreatic fat assessment are also presented, by intersecting the three‐dimensional parts segmentation with one available proton density fat fraction (PDFF) image. Statistical Test: Wilcoxon signed rank test and Mann–Whitney U‐test for comparisons. DSC and volume differences for evaluation. A P value < 0.05 was considered statistically significant. Results: Good intrarater (DSC mean, head: 0.982, body: 0.940, tail: 0.961) agreement and interrater (DSC mean, head: 0.968, body: 0.905, tail: 0.943) agreement were observed. No differences (DSC, head: P = 0.4358, body: P = 0.0992, tail: P = 0.1080) were observed between the manual annotations and our method's segmentations (DSC mean, head: 0.965, body: 0.893, tail: 0.934). Pancreatic body PDFF was different between T2DM and nondiabetics matched by body mass index. Data Conclusion: The developed segmentation's performance was no different from manual annotations. Application on type 2 diabetes subjects showed potential for assessing pancreatic disease heterogeneity. Level of Evidence: 4 Technical Efficacy Stage: 3 [ABSTRACT FROM AUTHOR]

Magnitude-based PDFF (Proton Density Fat Fraction) and R 2 ∗ mapping with resolved water-fat ambiguity is extended to calculate field inhomogeneity (field map) using the phase images. The estimation is formulated in matrix form, resolving the field map in a least-squares sense. PDFF and R 2 ∗ from magnitude fitting may be updated using the estimated field maps. The limits of quantification of our voxel-independent implementation were assessed. Bland-Altman was used to compare PDFF and field maps from our method against a reference complex-based method on 152 UK Biobank subjects (1.5 T Siemens). A separate acquisition (3 T Siemens) presenting field inhomogeneities was also used. The proposed field mapping was accurate beyond double the complex-based limit range. High agreement was obtained between the proposed method and the reference in UK. Robust field mapping was observed at 3 T, for inhomogeneities over 400 Hz including rapid variation across edges. Field mapping following unambiguous magnitude-based water-fat separation was demonstrated in-vivo and showed potential at 3 T. [ABSTRACT FROM AUTHOR]

Early UK surveillance data revealed that people living with HIV were overrepresented among cases of monkeypox (mpox). However, it remains unknown whether mpox infection is more severe in people living with well-controlled HIV. All laboratory-confirmed mpox cases presenting between May and December 2022 to one London hospital service were identified via pathology reporting systems. We extracted demographic and clinical data to allow comparison of clinical presentation and severity of mpox among people with and without HIV. We identified 150 people with mpox (median age 36 years, 99.3% male, 92.7% reporting sex with other men). HIV status was available for 144 individuals, 58 (40.3%) of whom were HIV positive (only 3/58 had CD4 cell counts <200 cells/mm 3 and 5/58 had HIV RNA >200 copies/mL). People with HIV had similar clinical presentations to those without HIV, including indicators of more widespread disease, such as extragenital lesions (74.1% vs. 64.0%, p  = .20) and nondermatological symptoms (87.9% vs. 82.6%, p  = .38). People with HIV also experienced a similar time from onset of symptoms to discharge from all inpatient or outpatient clinical follow-up ( p  = .63) and total time under follow-up ( p  = .88) compared with people without HIV. A similar proportion of people with HIV required review in the hospital emergency department (36.2% vs. 25.6%, p  = .17) or admission to hospital (19.0% vs. 9.3%, p  = .09). There were no recorded deaths. In this cohort of people with mpox, there was a high prevalence of HIV coinfection, the majority of which was well-controlled. We find no evidence that people with well-controlled HIV experienced more severe mpox infection.

Purpose: Several studies have demonstrated the accuracy, precision, and reproducibility of proton density fat fraction (PDFF) quantification using vendor-specific image acquisition protocols and PDFF estimation methods. The purpose of this work is to validate a confounder-corrected, cross-vendor, cross field-strength, in-house variant LMS IDEAL of the IDEAL method licensed from the University of Wisconsin, which has been developed for routine clinical use., Methods: LMS IDEAL is implemented using a combination of patented and/or published acquisition and some novel model fitting methods required to correct confounds which result from the imaging and estimation processes, including: water-fat ambiguity; T2* relaxation; multi-peak fat modelling; main field inhomogeneity; T1 and noise bias; bipolar readout gradients; and eddy currents. LMS IDEAL has been designed to use image acquisition protocols that can be installed on most MRI scanners and cloud-based image processing to provide fast, standardized clinical results. Publicly available phantom data were used to validate LMS IDEAL PDFF calculations against results from originally published IDEAL methodology. LMS PDFF and T2* measurements were also compared with an independent technique in human volunteer data (n = 179) acquired as part of the UK Biobank study., Results: We demonstrate excellent agreement of LMS IDEAL across vendors, field strengths, and over a wide range of PDFF and T2* values in the phantom study. The performance of LMS IDEAL was then assessed in vivo against widely accepted PDFF and T2* estimation methods (LMS Dixon and LMS T2*, respectively), demonstrating the robustness of LMS IDEAL to potential sources of error., Conclusion: The development and clinical validation of the LMS IDEAL algorithm as a chemical shift-encoded MRI method for PDFF and T2* estimation contributes towards robust, unbiased applications for quantification of hepatic steatosis and iron overload, which are key features of chronic liver disease., Competing Interests: The authors of this manuscript have the following competing interests: Perspectum Diagnostics employees: Chloe Hutton, Michael L. Gyngell, Matteo Milanesi, Alexandre Bagur, Michael Brady; Perspectum Diagnostics stockholders: Chloe Hutton, Michael L. Gyngell, Matteo Milanesi, Alexandre Bagur, Michael Brady. This does not alter our adherence to PLOS ONE policies on sharing data and materials.