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Abstract A sensitive and efficient imaging technique is required to assess the subtle abnormalities occurring in the normal-appearing white matter (NAWM) and normal-appearing grey matter (NAGM) in patients with relapsing–remitting multiple sclerosis (RRMS). In this study, a fast 3D macromolecular proton fraction (MPF) quantification based on spin-lock (fast MPF-SL) sequence was proposed for brain MPF mapping. Thirty-four participants, including 17 healthy controls and 17 RRMS patients were prospectively recruited. We conducted group comparison and correlation between conventional MPF-SL, fast MPF-SL, and DWI, and compared differences in quantified parameters within MS lesions and the regional NAWM, NAGM, and normal-appearing deep grey matter (NADGN). MPF of MS lesions was significantly reduced (7.17% ± 1.15%, $$P$$ P < 0.01) compared to all corresponding normal-appearing regions. MS patients also showed significantly reduced mean MPF values compared with controls in NAGM (4.87% ± 0.38% vs 5.21% ± 0.32%, $$P$$ P = 0.01), NAWM (9.49% ± 0.69% vs 10.32% ± 0.59%, $$P$$ P < 0.01) and NADGM (thalamus 5.59% ± 0.67% vs 6.00% ± 0.41%, $$P$$ P = 0.04; caudate 5.10% ± 0.55% vs 5.53% ± 0.58%, $$P$$ P = 0.03). MPF and ADC showed abnormalities in otherwise normal appearing close to lesion areas (P

Federated ML (FL) provides an alternative to train accurate and generalizable ML models, by only sharing numerical model updates. Here, the authors present the largest FL study to-date to generate an automatic tumor boundary detector for glioblastoma.

Abstract Purpose Nodal size is an important imaging criterion for differentiating benign from malignant nodes in the head and neck cancer staging. This study evaluated the size of normal nodes in less well-documented nodal groups in the upper head and neck on magnetic resonance imaging (MRI). Methods Analysis was performed on 289 upper head and neck MRIs of patients without head and neck cancer. The short axial diameters (SAD) of the largest node in the parotid, submandibular, occipital, facial, retroauricular and Level IIb of the upper internal jugular nodal groups were documented and compared to the commonly used threshold of ≥ 10 mm for diagnosis of a malignant node. Results Normal nodes in the parotid, occipital, retroauricular and Level IIb groups were small with a mean SAD ranging from 3.8 to 4.4 mm, nodes in the submandibular group were larger with a mean SAD of 5.5 mm and facial nodes were not identified. A size ≥ 10 mm was found in 0.8% of submandibular nodes. Less than 10% of the other nodal group had a SAD of ≥ 6 mm and none of them had a SAD ≥ 8 mm. Conclusion To identify malignant neck nodes in these groups there is scope to reduce the size threshold of ≥ 10 mm to improve sensitivity without substantial loss of specificity.

Abstract Purposes To systematically review and perform meta-analysis to evaluate the prognostic value of cervical nodal necrosis (CNN) on the staging computed tomography/magnetic resonance imaging (MRI) of nasopharyngeal carcinoma (NPC) in era of intensity-modulated radiotherapy. Methods Literature search through PubMed, EMBASE, and Cochrane Library was conducted. The hazard ratios (HRs) with 95% confidence intervals (CIs) of CNN for distant metastasis-free survival (DMFS), disease free survival (DFS) and overall survival (OS) were extracted from the eligible studies and meta-analysis was performed to evaluate the pooled HRs with 95%CI. Results Nine studies, which investigated the prognostic values of 6 CNN patterns on MRI were included. Six/9 studies were eligible for meta-analysis, which investigated the CNN presence/absence in any nodal group among 4359 patients. The pooled unadjusted HRs showed that the CNN presence predicted poor DMFS (HR =1.89, 95%CI =1.72-2.08), DFS (HR =1.57, 95%CI =1.08-2.26), and OS (HR =1.87, 95%CI =1.69-2.06). The pooled adjusted HRs also showed the consistent results for DMFS (HR =1.34, 95%CI =1.17-1.54), DFS (HR =1.30, 95%CI =1.08-1.56), and OS (HR =1.61, 95%CI =1.27-2.04). Results shown in the other studies analysing different CNN patterns indicated the high grade of CNN predicted poor outcome, but meta-analysis was unable to perform because of the heterogeneity of the analysed CNN patterns. Conclusion The CNN observed on the staging MRI is a negative factor for NPC outcome, suggesting that the inclusion of CNN is important in the future survival analysis. However, whether and how should CNN be included in the staging system warrant further evaluation.

Blunt cerebrovascular injury (BCVI) is an often underrecognized injury occurring in the carotid or vertebral arteries, associated with a risk of ischemic stroke and potential for poor neurological outcome or death. Computed tomographic angiography (CTA) is the most common modality for initial screening and diagnosis. Vessel wall intimal injuries, intraluminal thrombus, dissection, intramural hematoma, pseudoaneurysm, vessel transection, and arteriovenous fistula, are potential findings to be considered in approach to imaging. Identification of high-risk trauma patients based on clinical and radiological risk factors can determine patients at risk of BCVI for targeted screening.

Abstract Data privacy mechanisms are essential for rapidly scaling medical training databases to capture the heterogeneity of patient data distributions toward robust and generalizable machine learning systems. In the current COVID-19 pandemic, a major focus of artificial intelligence (AI) is interpreting chest CT, which can be readily used in the assessment and management of the disease. This paper demonstrates the feasibility of a federated learning method for detecting COVID-19 related CT abnormalities with external validation on patients from a multinational study. We recruited 132 patients from seven multinational different centers, with three internal hospitals from Hong Kong for training and testing, and four external, independent datasets from Mainland China and Germany, for validating model generalizability. We also conducted case studies on longitudinal scans for automated estimation of lesion burden for hospitalized COVID-19 patients. We explore the federated learning algorithms to develop a privacy-preserving AI model for COVID-19 medical image diagnosis with good generalization capability on unseen multinational datasets. Federated learning could provide an effective mechanism during pandemics to rapidly develop clinically useful AI across institutions and countries overcoming the burden of central aggregation of large amounts of sensitive data.

Foramen tympanicum (FT), or foramen of Huschke, describes an uncommon anatomicvariant of a persistent bony defect connecting the external acoustic meatus to the temporomandibular joint (TMJ). Although rare, it can be associated with significant complications, such as TMJ herniation, salivary gland fistula, infectious or tumoral spread between the external acoustic meatus and the TMJ, or result in inadvertent ear injury during TMJ arthroscopy. To the best of our knowledge, this is the first case report of a symptomatic FT with a full description of computed tomography and magnetic resonance imaging findings. Surgical exploration confirmed the presence of FT with TMJ herniation with subsequent successful closure of the defect obtained. Keywords: External acoustic canal, Temporomandibular joint, Anatomic variation, Magnetic resonance imaging, X-ray computed tomography

Laparoscopic sleeve gastrectomy (LSG), the most common bariatric surgical procedure, leads to durable weight loss and improves obesity-related comorbidities. However, it induces abnormalities in bone metabolism. One unexplored potential contributor is the gut microbiome, which influences bone metabolism and is altered after surgery. We characterized the relationship between the gut microbiome and skeletal health in severe obesity and after LSG. In a prospective cohort study, 23 adults with severe obesity underwent skeletal health assessment and stool collection preoperatively and 6 mo after LSG. Gut microbial diversity and composition were characterized using 16S rRNA gene sequencing, and fecal concentrations of short-chain fatty acids (SCFA) were measured with LC-MS/MS. Spearman's correlations and PERMANOVA analyses were applied to assess relationships between the gut microbiome and bone health measures including serum bone turnover markers (C-terminal telopeptide of type 1 collagen [CTx] and procollagen type 1 N-terminal propeptide [P1NP]), areal BMD, intestinal calcium absorption, and calciotropic hormones. Six months after LSG, CTx and P1NP increased (by median 188% and 61%, P

Type 2 diabetes (T2D) has negative effects on skeletal health. A proposed mechanism of diabetic bone disease connects hyperlipidemia to increased bone marrow adiposity and decreased bone quality. Previous research on Type 1 diabetes reported positive associations between serum lipid levels and marrow adiposity, but no data exist for T2D. In addition, marrow adiposity is sex-dependent in healthy populations, but sex has not been addressed adequately in previous reports of marrow adiposity in T2D. The purpose of this study was to quantify associations of marrow adiposity and composition with T2D status, serum lipid levels, and sex. T2D patients and normoglycemic controls (n = 39/37) were included. Single-voxel magnetic resonance spectroscopy (MRS) was performed at the spine and tibia. Quantitative MRS outcomes of marrow adiposity and composition were calculated. Linear regression models were used to compare MRS outcomes among groups and to evaluate associations of MRS outcomes with serum lipid levels. All analyses were performed on sex-stratified subgroups. Total, unsaturated, and saturated fat content at the spine were lower in T2D participants compared to controls in age-adjusted models; these differences were significant in men but not in women. In our study cohort, total cholesterol, low-density lipoprotein (LDL), and high-density lipoprotein (HDL) were lower in T2D participants compared to controls. Adjustment for LDL, HDL, and statin use attenuated the association of T2D status with unsaturated fat but not saturated fat in men. Further analysis confirmed significant associations between serum lipid levels and MRS outcomes. Specifically, we found a positive association between LDL cholesterol and total marrow fat in the male T2D group and a negative association between HDL and total marrow fat in the female T2D group. In conclusion, our results suggest that marrow adiposity and composition are associated with lipid levels as well as T2D status, and these relationships are sex-specific. © 2023 American Society for Bone and Mineral Research (ASBMR).

Fracture risk is increased in type 2 diabetes, which may in part be due to altered bone marrow adiposity. Cross sectional studies have reported that people with type 2 diabetes have lower unsaturated BMAT lipid levels than people without diabetes, although there are limited data on longitudinal changes. We hypothesized that Roux-en-Y gastric bypass (RYGB), which dramatically improves glycemic status, would have differential effects on BMAT composition, with increases in the unsaturated lipid index in people with diabetes. Given reports that axial BMAT is responsive to metabolic stimuli while appendicular BMAT is stable, we hypothesized that BMAT changes would occur at the spine but not the tibia. We enrolled 30 obese women, stratified by diabetes status, and used magnetic resonance spectroscopy to measure BMAT at the spine in all participants, and the tibia in a subset (n = 19). At baseline, BMAT parameters were similar between those with and without diabetes, except tibial marrow fat content was lower in women with diabetes (97.4 % ± 1.0 % versus 98.2 % ± 0.4 %, p = 0.04). Six months after surgery, both groups experienced similar weight loss of 27 kg ± 7 kg. At the spine, there was a significant interaction between diabetes status and changes in both marrow fat content and the unsaturated lipid index (p = 0.02, p

ObjectiveSome patients with rheumatic diseases might be at higher risk for coronavirus disease 2019 (COVID-19) acute respiratory distress syndrome (ARDS). We aimed to develop a prediction model for COVID-19 ARDS in this population and to create a simple risk score calculator for use in clinical settings.MethodsData were derived from the COVID-19 Global Rheumatology Alliance Registry from March 24, 2020, to May 12, 2021. Seven machine learning classifiers were trained on ARDS outcomes using 83 variables obtained at COVID-19 diagnosis. Predictive performance was assessed in a US test set and was validated in patients from four countries with independent registries using area under the curve (AUC), accuracy, sensitivity, and specificity. A simple risk score calculator was developed using a regression model incorporating the most influential predictors from the best performing classifier.ResultsThe study included 8633 patients from 74 countries, of whom 523 (6%) had ARDS. Gradient boosting had the highest mean AUC (0.78; 95% confidence interval [CI]: 0.67-0.88) and was considered the top performing classifier. Ten predictors were identified as key risk factors and were included in a regression model. The regression model that predicted ARDS with 71% (95% CI: 61%-83%) sensitivity in the test set, and with sensitivities ranging from 61% to 80% in countries with independent registries, was used to develop the risk score calculator.ConclusionWe were able to predict ARDS with good sensitivity using information readily available at COVID-19 diagnosis. The proposed risk score calculator has the potential to guide risk stratification for treatments, such as monoclonal antibodies, that have potential to reduce COVID-19 disease progression.

ObjectivesTo investigate factors associated with severe COVID-19 in people with idiopathic inflammatory myopathy (IIM).MethodsDemographic data, clinical characteristics and COVID-19 outcome severity of adults with IIM were obtained from the COVID-19 Global Rheumatology Alliance physician-reported registry. A 3-point ordinal COVID-19 severity scale was defined: (1) no hospitalisation, (2) hospitalisation (and no death) and (3) death. ORs were estimated using multivariable ordinal logistic regression. Sensitivity analyses were performed using a 4-point ordinal scale: (1) no hospitalisation, (2) hospitalisation with no oxygen (and no death), (3) hospitalisation with oxygen/ventilation (and no death) and 4) death.ResultsOf 348 patients, 48% were not hospitalised, 39% were hospitalised (and did not die) and 13% died. Older age (OR=1.59/decade, 95% CI 1.31 to 1.91), high disease activity (OR=3.50, 95% CI 1.25 to 9.83; vs remission), ≥2 comorbidities (OR=2.63, 95% CI 1.39 to 4.98; vs none), prednisolone-equivalent dose >7.5 mg/day (OR=2.40, 95% CI 1.09 to 5.28; vs no intake) and exposure to rituximab (OR=2.71, 95% CI 1.28 to 5.72; vs conventional synthetic disease-modifying antirheumatic drugs only) were independently associated with severe COVID-19. In addition to these variables, in the sensitivity analyses, male sex (OR range: 1.65-1.83; vs female) was also significantly associated with severe outcomes, while COVID-19 diagnosis after 1 October 2020 (OR range: 0.51-0.59; vs on/before 15 June 2020) was significantly associated with less severe outcomes, but these associations were not significant in the main model (OR=1.57, 95% CI 0.95 to 2.59; and OR=0.61, 95% CI 0.37 to 1.00; respectively).ConclusionsThis is the first large registry data on outcomes of COVID-19 in people with IIM. Older age, male sex, higher comorbidity burden, high disease activity, prednisolone-equivalent dose >7.5 mg/day and rituximab exposure were associated with severe COVID-19. These findings will enable risk stratification and inform management decisions for patients with IIM.

BackgroundDifferences in the distribution of individual-level clinical risk factors across regions do not fully explain the observed global disparities in COVID-19 outcomes. We aimed to investigate the associations between environmental and societal factors and country-level variations in mortality attributed to COVID-19 among people with rheumatic disease globally.MethodsIn this observational study, we derived individual-level data on adults (aged 18-99 years) with rheumatic disease and a confirmed status of their highest COVID-19 severity level from the COVID-19 Global Rheumatology Alliance (GRA) registry, collected between March 12, 2020, and Aug 27, 2021. Environmental and societal factors were obtained from publicly available sources. The primary endpoint was mortality attributed to COVID-19. We used a multivariable logistic regression to evaluate independent associations between environmental and societal factors and death, after controlling for individual-level risk factors. We used a series of nested mixed-effects models to establish whether environmental and societal factors sufficiently explained country-level variations in death.Findings14 044 patients from 23 countries were included in the analyses. 10 178 (72·5%) individuals were female and 3866 (27·5%) were male, with a mean age of 54·4 years (SD 15·6). Air pollution (odds ratio 1·10 per 10 μg/m3 [95% CI 1·01-1·17]; p=0·0105), proportion of the population aged 65 years or older (1·19 per 1% increase [1·10-1·30]; p

AimTo determine characteristics associated with more severe outcomes in a global registry of people with systemic lupus erythematosus (SLE) and COVID-19.MethodsPeople with SLE and COVID-19 reported in the COVID-19 Global Rheumatology Alliance registry from March 2020 to June 2021 were included. The ordinal outcome was defined as: (1) not hospitalised, (2) hospitalised with no oxygenation, (3) hospitalised with any ventilation or oxygenation and (4) death. A multivariable ordinal logistic regression model was constructed to assess the relationship between COVID-19 severity and demographic characteristics, comorbidities, medications and disease activity.ResultsA total of 1606 people with SLE were included. In the multivariable model, older age (OR 1.03, 95% CI 1.02 to 1.04), male sex (1.50, 1.01 to 2.23), prednisone dose (1-5 mg/day 1.86, 1.20 to 2.66, 6-9 mg/day 2.47, 1.24 to 4.86 and ≥10 mg/day 1.95, 1.27 to 2.99), no current treatment (1.80, 1.17 to 2.75), comorbidities (eg, kidney disease 3.51, 2.42 to 5.09, cardiovascular disease/hypertension 1.69, 1.25 to 2.29) and moderate or high SLE disease activity (vs remission; 1.61, 1.02 to 2.54 and 3.94, 2.11 to 7.34, respectively) were associated with more severe outcomes. In age-adjusted and sex-adjusted models, mycophenolate, rituximab and cyclophosphamide were associated with worse outcomes compared with hydroxychloroquine; outcomes were more favourable with methotrexate and belimumab.ConclusionsMore severe COVID-19 outcomes in individuals with SLE are largely driven by demographic factors, comorbidities and untreated or active SLE. Patients using glucocorticoids also experienced more severe outcomes.

Felis catus gammaherpesvirus-1 (FcaGHV1), a novel candidate oncogenic virus, infects cats worldwide. Whether the oropharynx is a site of virus shedding and persistence, and whether oronasal carcinomas harbor FcaGHV1 nucleic acid were investigated. In a prospective molecular epidemiological study, FcaGHV1 DNA was detected by cPCR in oropharyngeal swabs from 26/155 (16.8%) of cats. Oropharyngeal shedding was less frequently detected in kittens ≤3 months of age (5/94, 5.3%) than in older animals; >3 months to ≤1 year: 8/26, 30.8%, (p = 0.001, OR 7.91, 95% CI (2.320, 26.979)); >1 year to ≤6 years: 10/20, 50%, (p < 0.001, OR 17.8 95% CI (5.065, 62.557)); >6 years: 3/15, 33% (p = 0.078). Provenance (shelter-owned/privately owned) was not associated with shedding. In situ hybridization (ISH) identified FcaGHV1-infected cells in salivary glandular epithelium but not in other oronasal tissues from two of three cats shedding viral DNA in the oropharynx. In a retrospective dataset of 11 oronasopharyngeal carcinomas, a single tumor tested positive for FcaGHV1 DNA by ISH, a papillary carcinoma, where scattered neoplastic cells showed discrete nuclear hybridization. These data support the oronasopharynx as a site of FcaGHV1 shedding, particularly after maternal antibodies are expected to decline. The salivary epithelium is identified as a potential site of FcaGHV1 persistence. No evidence supporting a role for FcaGHV1 in feline oronasal carcinomas was found in the examined tumours.

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing.

BackgroundPatients with primary systemic vasculitis or polymyalgia rheumatica might be at a high risk for poor COVID-19 outcomes due to the treatments used, the potential organ damage cause by primary systemic vasculitis, and the demographic factors associated with these conditions. We therefore aimed to investigate factors associated with COVID-19 outcomes in patients with primary systemic vasculitis or polymyalgia rheumatica.MethodsIn this retrospective cohort study, adult patients (aged ≥18 years) diagnosed with COVID-19 between March 12, 2020, and April 12, 2021, who had a history of primary systemic vasculitis (antineutrophil cytoplasmic antibody [ANCA]-associated vasculitis, giant cell arteritis, Behçet's syndrome, or other vasculitis) or polymyalgia rheumatica, and were reported to the COVID-19 Global Rheumatology Alliance registry were included. To assess COVID-19 outcomes in patients, we used an ordinal COVID-19 severity scale, defined as: (1) no hospitalisation; (2) hospitalisation without supplemental oxygen; (3) hospitalisation with any supplemental oxygen or ventilation; or (4) death. Multivariable ordinal logistic regression analyses were used to estimate odds ratios (ORs), adjusting for age, sex, time period, number of comorbidities, smoking status, obesity, glucocorticoid use, disease activity, region, and medication category. Analyses were also stratified by type of rheumatic disease.FindingsOf 1202 eligible patients identified in the registry, 733 (61·0%) were women and 469 (39·0%) were men, and their mean age was 63·8 years (SD 17·1). A total of 374 (31·1%) patients had polymyalgia rheumatica, 353 (29·4%) had ANCA-associated vasculitis, 183 (15·2%) had giant cell arteritis, 112 (9·3%) had Behçet's syndrome, and 180 (15·0%) had other vasculitis. Of 1020 (84·9%) patients with outcome data, 512 (50·2%) were not hospitalised, 114 (11·2%) were hospitalised and did not receive supplemental oxygen, 239 (23·4%) were hospitalised and received ventilation or supplemental oxygen, and 155 (15·2%) died. A higher odds of poor COVID-19 outcomes were observed in patients who were older (per each additional decade of life OR 1·44 [95% CI 1·31-1·57]), were male compared with female (1·38 [1·05-1·80]), had more comorbidities (per each additional comorbidity 1·39 [1·23-1·58]), were taking 10 mg/day or more of prednisolone compared with none (2·14 [1·50-3·04]), or had moderate, or high or severe disease activity compared with those who had disease remission or low disease activity (2·12 [1·49-3·02]). Risk factors varied among different disease subtypes.InterpretationAmong patients with primary systemic vasculitis and polymyalgia rheumatica, severe COVID-19 outcomes were associated with variable and largely unmodifiable risk factors, such as age, sex, and number of comorbidities, as well as treatments, including high-dose glucocorticoids. Our results could be used to inform mitigation strategies for patients with these diseases.FundingAmerican College of Rheumatology and the European Alliance of Associations for Rheumatology.