First Measurement of the Z→μ^{+}μ^{-} Angular Coefficients in the Forward Region of pp Collisions at sqrt[s]=13 TeV

The first study of the angular distribution of μ^{+}μ^{-} pairs produced in the forward rapidity region via the Drell-Yan reaction pp→γ^{*}/Z+X→ℓ^{+}ℓ^{-}+X is presented, using data collected with the LHCb detector at a center-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 5.1  fb^{-1}. The coefficients of the five leading terms in the angular distribution are determined as a function of the dimuon transverse momentum and rapidity. The results are compared to various theoretical predictions of the Z-boson production mechanism and can also be used to probe transverse-momentum-dependent parton distributions within the proton.

POS0573 MUSCULOSKELEATAL ULTRASOUND STUDIES ARE CRITICAL FOR DETECTING SERONEGATIVE INFLAMMATORY ARTHRITIS

Background

The autoantibody status of rheumatoid factor (RF) and anti-cyclic citrullinated peptide antibodies (anti-CCP Ab) has gained widespread recognition for its role in the diagnosis of rheumatoid arthritis (RA) based on the latest diagnostic criteria for RA.1 However, in early disease, the rates of antibody expression have been reported as low as 50%2, rendering early diagnosis of RA difficult. Furthermore, the nature of seronegative rheumatoid arthritis is unknown, though it is presumed to have less aggressive disease course as compared to its seropositive counterparts. Musculoskeletal (MS) ultrasound studies have been widely used in recent clinical practice to assess soft-tissue abnormalities of the joints and disease states in RA, such as synovitis and bone erosions. MS ultrasound studies were recently shown to be more sensitive to detect early synovial changes and erosions than other radiographic methods while maintaining cost-effectiveness.3-5 We hypothesize that MS ultrasound studies are more sensitive to detecting inflammatory changes in seronegative inflammatory arthritis, which is often subclinical in presentation.

Objectives

To assess the role of MS ultrasound studies in detecting early inflammatory changes in the joints and diagnosing seronegative inflammatory arthritis.

Methods

A retrospective electronic medical record review was performed of all patients at the two University at Buffalo rheumatology clinics who underwent MS ultrasound studies after complaining of multiple joint pain. All these patients were previously seen and evaluated by at least one other medical provider, who found no evidence of inflammatory arthritis on physical examination. These patients did not meet diagnostic criteria for rheumatoid arthritis due to a lack of gross joint swelling and/or positive serological makeup. As part of their clinical care, they were referred to obtain MS ultrasound studies to rule out inflammatory arthritis. All patients were de-identified at initial data collection. Information pertaining to the patients’ 1) demographics (gender, age, ethnicity, etc.), 2) findings of MS ultrasound studies, and 3) serological studies (RF, anti-CCP Ab, HLA-B27) was collected and tabulated.

Results

Of the 363 patients who underwent MS ultrasound studies, 280 of them (77.1%) of them were found to have synovial hypertrophy [minimal = 23%, mild = 46%, moderate = 29%, severe = 2%] in bilateral MCP, PIP, carpal, and/or MTP joints, therefore conferring a diagnosis of inflammatory arthritis. The average age of these 280 patients was 48.35 ± 14.86 years old at the time of diagnosis, with female to male ratio of 4.38:1. Surprisingly, of these 280 patients with evidence of inflammatory arthritis, 69 (24.6%) of them were found to have joint erosions with either MCP or MTP joints, supporting a diagnosis of advanced inflammatory arthritis with erosive disease. The erosions were predominantly located in MTP joints (77.1%) as compared to MCP joints (22.9%). Therefore, our findings clearly demonstrated distinct clinical and ultrasonography features of seronegative inflammatory arthritis (SNIA) as compared to seropositive RA.

Conclusion

MS ultrasound studies are more sensitive to and critical for detecting inflammatory changes and joint damages in SNIA due to its subclinical presentation. Based on our findings, SN IA is underdiagnosed in individuals who complain of joint pain without gross synovitis. SNIA also likely has distinct pathophysiology that needs further characterization.

References

[1]Aydin, S.Z. et al. Eur J Rheumatol. 2017; 4(2):118-121.

[2]Barra, L. et al. J of Rheum 2014;41(12):2361-2369.

[3]Mathiessen, A. et al. Ann Rheum Dis 2017:72;51-56.

[4]Tamas, M.M. et al. Rheumatol (Oxford) 2014; 53(6):1100-1107.

[5]Salaffi, F. et al. Clin Exp Rheumatol 2014;32.1(80):S85-S90.

Disclosure of Interests

Clarice Lin: None declared, Richard Chou Consultant of: Sun Pharmaceuticals Industries Limited.

Needlestick injuries in radiology: prevention and management

Needlestick injuries are common and often underreported in invasive radiological procedures. Prior needlestick injuries have been reported in 86-91% of interventional radiologists, and on average, one needlestick injury occurs for every 5 years of practice. Of those that have had a needlestick injury, only 58% had formal education on needlestick injury prevention. Needlestick injuries can often result in long-term debility if not properly managed. Injuries can result in transmission of blood-borne pathogens, such as hepatitis B, hepatitis C, and human immunodeficiency virus. Preventative measures, such as vaccination, proper sharps selection, handling, and disposal during radiological procedures, minimising procedure time, and team communication, can decrease the risk of needlestick injuries and pathogen transmission rate. Initial management involves proper cleaning of the wound and activating the injury reporting system. Further lab testing and post-exposure prophylaxis will depend on the serology status of the source and exposed patient. Needlestick injuries with pathogen transmission can result in long-term health issues and psychological damage, therefore, it is imperative for radiologists to understand factors that increase the risk for transmission, methods to prevent injury, and how to manage an injury when it occurs.

Social determinants of health influence disease activity and functional disability in Polyarticular Juvenile Idiopathic Arthritis

BACKGROUND

Social determinants of health (SDH) greatly influence outcomes during the first year of treatment in rheumatoid arthritis, a disease similar to polyarticular juvenile idiopathic arthritis (pJIA). We investigated the correlation of community poverty level and other SDH with the persistence of moderate to severe disease activity and functional disability over the first year of treatment in pJIA patients enrolled in the Childhood Arthritis and Rheumatology Research Alliance Registry.

METHODS

In this cohort study, unadjusted and adjusted generalized linear mixed effects models analyzed the effect of community poverty and other SDH on disease activity, using the clinical Juvenile Arthritis Disease Activity Score-10, and disability, using the Child Health Assessment Questionnaire, measured at baseline, 6, and 12 months.

RESULTS

One thousand six hundred eighty-four patients were identified. High community poverty (≥20% living below the federal poverty level) was associated with increased odds of functional disability (OR 1.82, 95% CI 1.28-2.60) but was not statistically significant after adjustment (aOR 1.23, 95% CI 0.81-1.86) and was not associated with increased disease activity. Non-white race/ethnicity was associated with higher disease activity (aOR 2.48, 95% CI: 1.41-4.36). Lower self-reported household income was associated with higher disease activity and persistent functional disability. Public insurance (aOR 1.56, 95% CI 1.06-2.29) and low family education (aOR 1.89, 95% CI 1.14-3.12) was associated with persistent functional disability.

CONCLUSION

High community poverty level was associated with persistent functional disability in unadjusted analysis but not with persistent moderate to high disease activity. Race/ethnicity and other SDH were associated with persistent disease activity and functional disability.

Circ_0003645 serves as miR-335-5p sponge to promote the biological process of diffuse large B-cell lymphoma by upregulating NFIB

BACKGROUND

Circular RNAs (circRNAs) are critical regulators for the development of many tumours, including diffuse large B-cell lymphoma (DLBCL). However, the role and mechanism of circ_0003645 in DLBCL progression remains obscure.

METHODS

Quantitative real-time PCR was performed to measure the expression of circ_0003645, microRNA (miR)-335-5p and nuclear factor I/B (NFIB). Cell viability, apoptosis and cell cycle were measured by cell counting kit 8 assay and flow cytometry. Protein expression was assessed using western blot analysis, and cell glycolysis was evaluated by detecting glucose consumption and ATP/ADP ratios. Besides, dual-luciferase reporter assay and RIP assay were used to confirm RNA interaction.

RESULTS

Our data showed that circ_0003645 expression was significantly upregulated in DLBCL tumour tissues. After circ_0003645 knockdown, the viability, cell cycle and glycolysis of DLBCL cells were inhibited, while cell apoptosis was promoted. MiR-335-5p could be sponged by circ_0003645, and NFIB was confirmed to be a downstream target of miR-335-5p. Function analysis revealed that anti-miR-335-5p reversed the regulation of si-circ_0003645 on DLBCL cell progression, and NFIB overexpression also abolished miR-335-5p-mediated the biological functions of DLBCL cells.

CONCLUSION

The present study revealed that circ_0003645 promoted the proliferation and glycolysis of DLBCL cells by the miR-335-5p/NFIB axis, which might provide a novel insight for DLBCL treatment.

Activated Epithelial FGF8 Signaling Induces Fused Supernumerary Incisors

FGF8, which is specifically expressed in the dental epithelium prior to the E12.5 bud stage, is a key player during odontogenesis, being responsible for the initiation of tooth development. Here, to investigate the impact of persistent FGF8 signaling on tooth development, we forcibly activated FGF8 signaling in the dental epithelium after the bud stage by generating K14-Cre;R26R-Fg8 mice. We found that a unique type of fused supernumerary incisors is formed, although morphologically resembling the features of type II dens invaginatus in humans. Further analysis revealed that ectopically activated epithelial FGF8 alters the cell fate of the incisor lingual outer enamel epithelium, endowing it with odontogenic potential by the activation of several key tooth genes, including Pitx2, Sox2, Lef-1, p38, and Erk1/2, and induces de novo formation of an extra incisor crown lingually in parallel to the original one, leading to the formation of an extra incisor crown and fused with the original incisor eventually. Meanwhile, the overdosed epithelial FGF8 signaling dramatically downregulates the expression of mesenchymal Bmp4, leading to severely impaired enamel mineralization. Based on the location of the extra incisors, we propose that they are likely to be rescued replacement teeth. Our results further demonstrate the essential role of FGF8 signaling for tooth initiation and the establishment of progenitor cells of dental epithelial stem cells during development.

[Exendin-4 promotes autophagy to relieve lipid deposition in a NAFLD cell model by activating AKT/mTOR signaling pathway]

OBJECTIVE

To investigate the effect of exendin-4 on lipid deposition in hepatocytes and explore its possible mechanism for treatment of nonalcoholic fatty liver disease (NAFLD).

METHODS

Human normal hepatocyte line LO2 and hepatoma cell line HepG2 were treated with palmitic acid (PA) to mimic hepatocyte steatosis or with combined treatments with PA+exendin-4 or PA+exendin-4+3BDO. Lipid deposition and proliferation of the two cell lines following treatment with PA or PA+exendin-4 were detected using Oil Red O staining and CCK8 assay, and the expression of p-mTOR, m-TOR, p-AKT, AKT and autophagy-related proteins LC3-Ⅰ/Ⅱ and p62 were detected with Western blotting; the expression of GLP-1R was detected with both Western blotting and immunofluorescence assay. The expression of LC3-Ⅰ/Ⅱ and p62 in the cells following treatment with PA+exendin-4 and PA+exendin-4+3BDO was detected with Western blotting.

RESULTS

Lipid deposition in the two cell lines increased significantly after PA treatment, but was alleviated by co-treatment with exendin-4. PA treatment significantly inhibited the proliferation of the two cell lines (P < 0.01), and this inhibitory effect was obviously attenuated by exendin-4 (P < 0.05). Immunofluorescence assay showed that both LO2 and HepG2 cells expressed GLP-1R. The expression of p-mTOR was significantly lower and that of p-AKT was higher in cells treated with PA+exendin-4 than in PA-treated cells. Exendin-4 also down-regulated the autophagy-associated protein p62 and up-regulated the expression of LC3-Ⅱ in PA-treated cells, and this effect was obviously reversed by 3BDO.

CONCLUSION

Exendin-4 may activate the AKT-mTOR signal pathway to promote autophagy via its direct action on GLP-1R. Exendin-4 can also alleviate lipid deposition and promote proliferation of PA-treated hepatocytes, suggesting its important role in PA-induced lipid deposition in hepatocytes.

[Research advances on the effects and mechanism of curcumin in promoting diabetic wound healing]

Diabetic wound is a common complication of diabetes, and the effect of current treatment is still poor. Curcumin has many pharmacological effects, such as anti-inflammatory, anti-oxidation, antimicrobial, anti-cancer, and improving insulin resistance. In this paper, the research advances on the effects and mechanism of curcumin in promoting diabetic wound healing were mainly reviewed.

Study of the K_{L}→π^{0}νν[over ¯] Decay at the J-PARC KOTO Experiment

The rare decay K_{L}→π^{0}νν[over ¯] was studied with the dataset taken at the J-PARC KOTO experiment in 2016, 2017, and 2018. With a single event sensitivity of (7.20±0.05_{stat}±0.66_{syst})×10^{-10}, three candidate events were observed in the signal region. After unveiling them, contaminations from K^{±} and scattered K_{L} decays were studied, and the total number of background events was estimated to be 1.22±0.26. We conclude that the number of observed events is statistically consistent with the background expectation. For this dataset, we set an upper limit of 4.9×10^{-9} on the branching fraction of K_{L}→π^{0}νν[over ¯] at the 90% confidence level.

DNA methylation-mediated silencing of microRNA-204 enhances T cell acute lymphoblastic leukemia by up-regulating MMP-2 and MMP-9 via NF-κB

T cell acute lymphoblastic leukaemia (T‐ALL) is a highly aggressive haematological cancer of the bone marrow. The abnormal expression of microRNAs (miRNAs) is reportedly involved in T‐ALL development and progression. Thus, we aimed to decipher the involvement of miR‐204 silencing mediated by DNA methylation in the occurrence of T cell acute lymphoblastic leukaemia (T‐ALL). miR‐204 expression was determined in bone marrow and peripheral blood samples from T‐ALL patients by real‐time quantitative PCR (RT‐qPCR) with its effect on cell proliferation evaluated by functional assays. In addition, bisulphite sequencing PCR was employed to detect the DNA methylation level of the miR‐204 promoter region, and the binding site between miR‐204 and IRAK1 was detected by luciferase assay. We found that miR‐204 was down‐regulated in T cells of T‐ALL patients, which was caused by the increased DNA methylation in the promoter region of miR‐204. Moreover, overexpression of miR‐204 inhibited T‐ALL cell proliferation while enhancing their apoptosis through interleukin receptor‐associated kinase 1 (IRAK1), which enhanced the expression of matrix metalloproteinase‐2 (MMP‐2) and MMP‐9 through activation of p‐p65. Thus, miR‐204 modulated MMP‐2 and MMP‐9 through IRAK1/NF‐κB signalling pathway, which was confirmed by in vivo assay. Taken together, DNA methylation‐mediated miR‐204 silencing increased the transcription of IRAK1, thus activating the NF‐κB signalling pathway and up‐regulating the downstream targets MMP‐2/MMP‐9.

Blockade of BK channels attenuates chronic visceral hypersensitivity in an IBS-like rat model

BACKGROUND

Visceral hypersensitivity in irritable bowel syndrome (IBS) is still poorly understood, despite that chronic abdominal pain is the most common symptoms in IBS patients. To study effects of BK channels on visceral hypersensitivity in IBS rats and the underlying mechanisms, IBS rats were established by colorectal distention (CRD) in postnatal rats. The expression of large-conductance calcium and voltage-dependent potassium ion channels (BK channels) of the thoracolumbar spinal cord was examined in IBS and control rats. The effects of BK channel blockade on visceral hypersensitivity were evaluated. The interaction of BK channels and N-methyl-D-aspartate acid (NMDA) receptors was explored, and synaptic transmission at superficial dorsal horn (SDH) neurons of the thoracolumbar spinal cord was recorded by whole-cell patch clamp in IBS rats.

RESULTS

The expression of the BK channels of the thoracolumbar spinal cord in IBS rats was significantly reduced. The blockade of BK channels could reduce the visceral hypersensitivity in IBS rats. There was an interaction between BK channels and NMDA receptors in the spinal cord. The frequency of spontaneous inhibitory postsynaptic currents (sIPSCs) in SDH neurons is significantly reduced in IBS rats. The blockade of BK channels depolarizes the inhibitory interneuron membrane and increases their excitability in IBS rats.

CONCLUSIONS

BK channels could interact with NMDA receptors in the thoracolumbar spinal cord of rats and regulate visceral hypersensitivity in IBS rats.

Reducing scan time of paediatric 99mTc-DMSA SPECT via deep learning

AIM

To investigate the feasibility of reducing the scan time of paediatric technetium 99m (^99mTc) dimercaptosuccinic acid (DMSA) single-photon-emission computed tomographic (SPECT) using a deep learning (DL) method.

MATERIAL AND METHODS

A total of 112 paediatric ^99mTc-DMSA renal SPECT scans were analysed retrospectively. Of the 112 examinations, 88 (84 for training and four for validation) were used to train a DL-based model that could generate full-acquisition-time reconstructed SPECT images from half-time acquisition. The remaining 24 examinations were used to evaluate the performance of the trained model.

RESULTS

DL-based SPECT images obtained from half-time acquisition have image quality similar to the standard clinical SPECT images obtained from full-acquisition-time acquisition. Moreover, the accuracy, sensitivity and specificity of the DL-based SPECT images for detection of affected kidneys were 91.7%, 83.3%, and 100%, respectively.

CONCLUSION

These preliminary results suggest that DL has the potential to reduce the scan time of paediatric ^99mTc-DMSA SPECT imaging while maintaining diagnostic accuracy.

Toward High Precision XCO2 Retrievals From TanSat Observations: Retrieval Improvement and Validation Against TCCON Measurements

TanSat is the 1st Chinese carbon dioxide (CO2) measurement satellite, launched in 2016. In this study, the University of Leicester Full Physics (UoL-FP) algorithm is implemented for TanSat nadir mode XCO2 retrievals. We develop a spectrum correction method to reduce the retrieval errors by the online fitting of an 8th order Fourier series. The spectrum-correction model and its a priori parameters are developed by analyzing the solar calibration measurement. This correction provides a significant improvement to the O2 A band retrieval. Accordingly, we extend the previous TanSat single CO2 weak band retrieval to a combined O2 A and CO2 weak band retrieval. A Genetic Algorithm (GA) has been applied to determine the threshold values of post-screening filters. In total, 18.3% of the retrieved data is identified as high quality compared to the original measurements. The same quality control parameters have been used in a footprint independent multiple linear regression bias correction due to the strong correlation with the XCO2 retrieval error. Twenty sites of the Total Column Carbon Observing Network (TCCON) have been selected to validate our new approach for the TanSat XCO2 retrieval. We show that our new approach produces a significant improvement on the XCO2 retrieval accuracy and precision when compared to TCCON with an average bias and RMSE of -0.08 ppm and 1.47 ppm, respectively. The methods used in this study can help to improve the XCO2 retrieval from TanSat and subsequently the Level-2 data production, and hence will be applied in the TanSat operational XCO2 processing.

Phase states, microstructure and dielectric characteristics of solid solutions (1 - x)NaNbO3 - xCa2Nb2O7 and (1 - x)NaNbO3 - xSr2Nb2O7

Ceramics of binary systems solid solutions (1 – x)NaNbO₃ – xCa₂Nb₂O₇ and (1 – x)NaNbO₃ – xSr₂Nb₂O₇ with non-isostructural extreme components were prepared by the solid-phase reactions technique with the following sintering using conventional ceramic technology. It was found that ceramics with x ≤ 0.2 have a perovskite structure. Layered type of structure predominates in the concentration range 0.2 < x ≤ 1. Phase diagrams of both systems at room temperature have been determined in the perovskite area. It was shown that this area contains two concentration regions with the different crystal structures and the morphotropic phase boundary between them. Microstructure and dielectric characteristics of selected solid solutions were investigated. The influence of technological regulations, such as mechanical activation and variation of sintering temperatures, on the formation of the microstructure and dielectric characteristics was studied for the individually selected concentrations (x = 0.1 and x = 0.25). Dielectric characteristics of ceramics revealed the presence of the Maxwell-Wagner polarization and its corresponding relaxation in the solid solutions (1 – x)NaNbO₃ – xCa₂Nb₂O₇ at x > 0.20.

International normalised ratio as an independent predictor of mortality in limb necrotising fasciitis with sepsis

INTRODUCTION

Necrotising fasciitis with sepsis is a life threatening disease. The aim of this study was to analyse the association between international normalised ratio (INR) and mortality in sepsis patients with necrotising fasciitis.

METHODS

A retrospective review was undertaken of 106 patients suffering from necrotising fasciitis with sepsis between November 2007 and December 2016. Data on comorbidities, clinical manifestations, laboratory findings, causative microbiological organisms, APACHE II (Acute Physiology and Chronic Health Evaluation II) score and outcomes were extracted. Logistic regression was carried out to examine the factors affecting mortality.

RESULTS

Forty patients (37.7%) died. There was no significant difference in the white blood count (WBC) for the survivor and non-survivor groups. Non-survivors had a lower mean oxygenation index (OI) (288.7mmHg vs 329.4mmHg, p=0.032) and platelet count (PC) (139.5 vs 214.8 x 10⁹/l, p=0.028), and a higher mean INR (1.9 vs 1.3, p=0.000), activated partial thromboplastin time (APTT) (54.6 vs 44.2 seconds, p=0.005) and serum creatinine (2.3mg/dl vs 1.4mg/dl, p=0.007). Mortality in patients with INR >1.5 was significantly higher than in those with INR <1.5 when all risk factors (WBC, PC, OI, INR, APTT, creatinine) were considered (odds ratio: 4.414, 95% confidence interval: 1.263-15.428, p=0.020). Even after adjusting for age, sex, bacteraemia, diabetes and hepatic disorders, the data still exhibited elevated mortality for patients with INR >1.5 (odds ratio: 5.600, 95% confidence interval: 1.415-22.166, p=0.014).

CONCLUSIONS

INR is a significant independent predictor of mortality in sepsis patients diagnosed with necrotising fasciitis.

The invasion status of lymphovascular space and lymph nodes in cervical cancer assessed by mono-exponential and bi-exponential DWI-related parameters

AIM

To investigate whether mono-exponential and bi-exponential diffusion-weighted imaging (DWI)-related parameters of the primary tumour can evaluate the status of lymphovascular space invasion (LVSI) and lymph node metastasis (LNM) in patients with cervical carcinoma preoperatively.

MATERIALS AND METHODS

Eighty patients with cervical carcinoma were enrolled, who underwent preoperative multi b-value DWI and radical hysterectomy. They were classified into LVSI(+) versus LVSI(-) and LNM(+) versus LNM(-) according to postoperative pathology. The apparent diffusion coefficient (ADC), pure molecular diffusion (D), pseudo-diffusion coefficient (D∗), and perfusion fraction (f) were calculated from the whole tumour (__whole) and tumour margin (__margin). All parameters were compared between LVSI(+) and LVSI(-) and between LNM(+) and LNM(-). Logistic regression analysis and receiver operating characteristic (ROC) curve analysis were performed to evaluate the diagnostic performance of these parameters.

RESULTS

f__margin and D∗__whole showed significant differences in differentiating LVSI(+) from LVSI(-) tumours (p=0.002, 0.008, respectively), while LNM(+) tumours presented with significantly higher ADC__margin than that of LNM(-) tumours (p=0.009). The other parameters were not independent related factors with the status of LVSI or LNM according to logistic regression analysis (p>0.05). The area under the ROC curve of f__margin combined with D∗__whole in discriminating LVSI(+) from LVSI(-) was 0.826 (95% confidence interval [CI]: 0.691-0.961), while ADC__margin in differentiating LNM(+) from LNM(-) was 0.788 (95% CI: 0.648-0.928).

CONCLUSIONS

The parameters generated from mono-exponential and bi-exponential DWI of the primary cervical carcinoma could help discriminate its status regarding LVSI (f__margin and D∗__whole) and LNM (ADC__margin).

SAT0564 BONE TEXTURE ANALYSIS WITH DEEP LEARNING IN HAND RADIOGRAPHS FOR ASSESSING THE RISK OF RHEUMATOID ARTHRITIS

Background:

Conventional x-rays are essential to identify radiographic changes of rheumatoid arthritis (RA) in structure and bone texture. Limited evidence suggests that the bone texture analysis may quantify the radiographic changes in RA;1however, current techniques such as the fractal dimension characterize fixed texture features. Deep learning offers novel methods to ‘learn’ radiographic texture features relevant to RA.

Objectives:

To develop a deep learning model to assess the radiographic bone texture in the distal metacarpal bone relevant to RA.

Methods:

We collected 3,738 conventional hand radiographs from 2,128 individuals (RA, n = 908; non-RA, n = 1220). The second, third, and fourth metacarpal bone images were segmented using a curve Graph Convolutional Network (GCN), and the distal third was used as the input to train a texture model to classify RA. The texture model was based on the Deep Texture Encoding Network (Deep-TEN) architecture (figure 1),2which put an encoding layer on top of a pre-trained 18-layered residual network (ResNet18). The vectors produced by the model represent the orderless texture features that were used to generate a texture score for RA. Five texture models are trained using 5-fold cross-validation and are ensembled during inference by averaging the model outputs to produce the final score. We then validate the model using hand radiographs of 166 RA patients and 166 non-RA patients. Overall model performance was measured by area under the curve of the receiver operator curve (AUROC). Multivariate logistic regression was used to estimate the odds ratio (OR) and 95% confidence interval (CI) of RA.

Figure 1.

Schematic representation of deep learning models to extract and encode texture features for RA classification.

Results:

We included 140 women and 26 men with RA (mean age, 55.9±1.8 years) and 166 non-RA individuals (F: M, 140:26; mean age, 55.5 ± 1.8 years). The mean texture score was 0.49 (95% CI, 0.48–0.50) in RA patients, which is significantly higher than non-RA patients (0.42, 95% CI, 0.40–0.43; p<0.01). The AUROC of the model was 0.68. In the multivariate logistic regression model, a high texture score (>0.43) is associated with an OR (95% CI) of 3.42 (2.48–4.72) for RA, adjusted by age and sex.

Conclusion:

This study indicates that the texture model can delineate radiographic changes in texture relevant to RA and, coupled with automatic joint detection and segmentation, it has the potential to aid early RA diagnosis and monitor radiographic progression.

References:

[1]Zandieh S, Haller J, Bernt R, et al. Fractal analysis of subchondral bone changes of the hand in rheumatoid arthritis. Medicine (Baltimore) 2017;96(11):e6344.

[2]Zhang H, Xue J, Dana K. Deep TEN: Texture Encoding Network. The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2017:708-17.

Disclosure of Interests:

None declared

OP0301 PREDICTION OF LOW BONE MINERAL DENSITY AND FRAX SCORE BY ASSESSING HIP BONE TEXTURE WITH DEEP LEARNING

Background:

Osteoporosis is a widespread health concern associated with an increased risk of fractures in individuals with low bone mineral density (BMD). Dual-energy x-ray absorptiometry (DXA) is the gold standard to measure BMD, but methods based on the assessment of plain films, such as the digital radiogrammetry,1are also available. We describe a novel approach based on the assessment of hip texture with deep learning to estimate BMD.

Objectives:

To compare the BMD estimated by assessing hip texture using a deep learning model and that measured by DXA.

Methods:

In this study, we identified 1,203 patients who underwent DXA of left hip and hip plain film within six months. The dataset was split into a training set with 1,024 patients and a testing set with 179 patients. Hip images were obtained and regions of interest (ROI) around left hips were segmented using a tool based on the curve Graph Convolutional Network. The ROIs are processed using a Deep Texture Encoding Network (Deep-TEN) model,2which comprises the first 3 blocks of Residual Network with 18 layers (ResNet-18) model followed by a dictionary encoding operator (Figure 1). The encoded features are processed using a fully connected layer to estimate BMD. Five-fold cross-validation was conducted. Pearson’s correlation coefficient was used to assess the correlation between predicted and reference BMD. We also test the performance of the model to identify osteoporosis (T-score ≤ -2.5)

Figure 1.

Schematic representation of deep learning models to extract and encode texture features for estimation of hip bone density.

Results:

We included 151 women and 18 men in the testing dataset (mean age, 66.1 ± 1.7 years). The mean predicted BMD was 0.724 g/cm2compared with the mean BMD measured by DXA of 0.725 g/cm2(p = 0.51). Pearson’s correlation coefficient between predicted and true BMD was 0.88. The performance of the model to detect osteoporosis/osteopenia was shown in Table 1. The positive predictive value was 87.46% for a T-score ≤ -1 and 83.3% for a T-score ≤ -2.5. Furthermore, the mean FRAX® 10-year major fracture risk did not differ significantly between scores based on predicted (6.86%) and measured BMD (7.67%, p=0.52). The 10-year probability of hip fracture was lower in the predicted score (1.79%) than the measured score (2.43%, p = 0.01).

Table 1.

Performance matrices of the deep texture model to detect osteoporosis/osteopenia

T-score ≤ -1T-score ≤ -2.5Sensitivity91.11%(95% CI, 83.23% to 96.08%)33.33%(95% CI, 17.29% to 52.81%)Specificity86.08%(95% CI, 76.45% to 92.84%)98.56%(95% CI, 94.90% to 99.83%)Positive predictive value88.17%(95% CI, 81.10% to 92.83%)83.33%(95% CI, 53.58% to 95.59%)Negative predictive value89.47%(95% CI, 81.35% to 94.31%)87.26%(95% CI, 84.16% to 89.83%)

Conclusion:

This study demonstrates the potential of the bone texture model to detect osteoporosis and to predict the FRAX score using plain hip radiographs.

References:

[1]Zandieh S, Haller J, Bernt R, et al. Fractal analysis of subchondral bone changes of the hand in rheumatoid arthritis. Medicine (Baltimore) 2017;96(11):e6344.

[2]Zhang H, Xue J, Dana K. Deep TEN: Texture Encoding Network. The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2017:708-17.

Disclosure of Interests:

None declared

OP0062 PREDICTIVE VALUE OF BONE TEXTURE FEATURES EXTRACTED BY DEEP LEARNING MODELS FOR THE DETECTION OF OSTEOARTHRITIS: DATA FROM THE OSTEOARTHRITIS INITIATIVE

Background:

Osteoarthritis is a degenerative disorder characterized by radiographic features of asymmetric loss of joint space, subchondral sclerosis, and osteophyte formation. Conventional plain films are essential to detect structural changes in osteoarthritis. Recent evidence suggests that fractal- and entropy-based bone texture parameters may improve the prediction of radiographic osteoarthritis.1In contrast to the fixed texture features, deep learning models allow the comprehensive texture feature extraction and recognition relevant to osteoarthritis.

Objectives:

To assess the predictive value of deep learning-extracted bone texture features in the detection of radiographic osteoarthritis.

Methods:

We used data from the Osteoarthritis Initiative, which is a longitudinal study with 4,796 patients followed up and assessed for osteoarthritis. We used a training set of 25,978 images from 3,086 patients to develop the textual model. We use the BoneFinder software2to do the segmentation of distal femur and proximal tibia. We used the Deep Texture Encoding Network (Deep-TEN)3to encode the bone texture features into a vector, which is fed to a 5-way linear classifier for Kellgren and Lawrence grading for osteoarthritis classification. We also developed a Residual Network with 18 layers (ResNet18) for comparison since it deals with contours as well. Spearman’s correlation coefficient was used to assess the correlation between predicted and reference KL grades. We also test the performance of the model to identify osteoarthritis (KL grade≥2).

Results:

We obtained 6,490 knee radiographs from 446 female and 326 male patients who were not in the training sets to validate the performance of the models. The distribution of the KL grades in the training and testing sets were shown in Table 1. The Spearman’s correlation coefficient was 0.60 for the Deep-TEN and 0.67 for the ResNet18 model. Table 2 shows the performance of the models to detect osteoarthritis. The positive predictive value for Deep-TEN and ResNet18 model classification for OA was 81.37% and 87.46%, respectively.

Table 1

Distribution of KL grades in the training and testing sets.

KL grades01234TotalTraining set1089341.9%458218.7%611423.5%332012.8%7993.1%25,978Testing set247238.1%135320.8%169626.1%77511.9%1943.0%6,490Table 2

Performance matrices of the Deep-Ten and ResNet18 models to detect osteoarthritis

Deep-TENResNet18Sensitivity62.29%(95% CI, 60.42%–64.13%)59.14%(95% CI, 57.24%–61.01%)Specificity90.07%(95% CI, 89.07%–91.00%)94.09%(95% CI, 93.30%–94.82%)Positive predictive value81.37%(95% CI, 79.81%–82.84%)87.46%(95% CI, 85.96%–88.82%)Negative predictive value77.42%(95% CI, 77.64%–79.65%)76.77%(95% CI, 75.93%–77.59%)

Conclusion:

This study demonstrates that the bone texture model performs reasonably well to detect radiographic osteoarthritis with a similar performance to the bone contour model.

References:

[1]Bertalan Z, Ljuhar R, Norman B, et al. Combining fractal- and entropy-based bone texture analysis for the prediction of osteoarthritis: data from the multicenter osteoarthritis study (MOST). Osteoarthritis Cartilage 2018;26:S49.

[2]Lindner C, Wang CW, Huang CT, et al. Fully Automatic System for Accurate Localisation and Analysis of Cephalometric Landmarks in Lateral Cephalograms. Sci Rep 2016;6:33581.

[3]Zhang H, Xue J, Dana K. Deep TEN: Texture Encoding Network. The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2017:708-17.

Disclosure of Interests:

None declared

0659 A Safe and Precise Tongue Base Surgery for Obstructive Sleep Apnea: Real-Time Intraoperative Ultrasound-Assisted Transoral Robotic Surgery

Introduction

Lingual artery (LA) injury is a devastating complication of tongue base surgery. Compared with the anatomic findings of computed tomography angiography (CTA), intraoperative blade of mouth gag might change the thickness of base of tongue (BOT) and anatomy of LA. We aimed to investigate the position of LA in the BOT with intraoperative ultrasound (IOU) imaging during transoral robotic surgery (TORS), and evaluate the bleeding complications when assisted with / without IOU.

Methods

Adult obstructive sleep apnea (OSA) patients who received TORS in BOT resection were recruited since 2016. Assessment tools were pre-op over-night hospital polysomnography (PSG) and anatomy-based Friedman Staging System. Ultrasound imaging was utilized to identify anatomic parameters of LA in BOT, including distance to midline, arterial depth and diameter.

Results

Ninety-three OSA patients (82 male, 88.2%) were analyzed. The mean age was 42.2±10.0 years old and body mass index was 29.2±4.5 kg/m2. The average apnea hypopnea index (AHI) was 58.1±21.4 events/hour. There were 66 (71.0%), 24 (25.8%) and 3 (3.2%) patients in Friedman stages II, III and IV, respectively. Seventy patients underwent TORS with IOU had shorter operation time (191.7±3.8 minutes) than 23 patients without IOU (220.1±6.6 minutes), less total blood loss (11.3±10.8 versus 19.6±26.7 ml), and more BOT tissue reduction volume (7.1±2.5 versus 3.9±1.6 ml). Significant predictors of arterial depth were higher AHI level during rapid-eye-movement (REM) sleep stage (p=0.038), bigger tonsil size (p=0.034) and more elevated Friedman tongue position (p=0.012). Postoperative complication associated with LA injury was not found in the patients with use of IOU.

Conclusion

When tongue retracted with blade, the distance to midline and depth of LA were altered in BOT. With IOU assisted, surgeon could identify LA position confidently. It is expectable to maximize efficiency and minimize catastrophic bleeding complications when OSA patients received TORS in BOT resection.

Support

nil

0032 Timing of Daily Rhythm of Cardiac Autonomic Control Contributes to Weight Loss Resistance, Independent of Daily Energy Intake and Physical Activity Level

Introduction

Obesity is a major health problem. Many treatments have been designed to help overweight/obese people to lose weight, but their effectiveness is highly variable. The same treatments may work for some persons while others have no responses — weight loss resistance. We tested whether the daily rhythm of cardiac autonomic control contributes to weight loss resistance.

Methods

We studied 39 overweight/obese Caucasian women (BMI&gt;25; age: 21–62 years old) who completed (1) an obesity dietary treatment of up to 30 weeks with weekly assessments of body weight, and (2) ambulatory monitoring of electrocardiogram (ECG) for up to 3.5 days. Heartbeat intervals were derived from ECG. Cardiac autonomic control was assessed in each 1-h bin by examining the temporal correlation in heartbeat fluctuations — a nonlinear measure that quantifies the delicate dynamic interplay between sympathetic and vagal outflows. Daily rhythm was estimated using the cosinor analysis.

Results

Weight loss was highly variable (range: 0.68%-21.78 % of initial body weight). The correlation in heartbeat fluctuations displayed a 24-h rhythm (p&lt;0.0001) with fewer correlations (more random) during the nighttime. The phase (peak timing) of the rhythm was highly variable, i.e., 10AM to 8PM for most participants, and after midnight in four participants. Weight loss evolution depended on the phase (p=0.006) in a nonlinear manner. Specifically, participants with the phase between 2PM-8PM lost weight faster than those with phases before 2PM and those after 8PM. The effect was independent of total energy intake, physical activity level, and sleep/wake schedules.

Conclusion

Cardiac autonomic control in overweight/obese women displayed a daily rhythm. The timing of the rhythm had previously un-identified contributions to weight loss. The inter-individual differences in the timing may reflect different circadian regulation of autonomic function and its interaction with the daily behavioral cycle.

Support

This work was supported by NIH grants R01AG048108, RF1AG059867, RF1AG064312, R01AG017917, and R01NS078009.

1027 Differences in Polysomnography-Based Sleep Disorders Between HIV-Infected Persons and Matched Controls

Introduction

Sleep disturbance is a prevalent problem among HIV-infected persons. The recognition of comorbid sleep disorders in patients with HIV is currently hampered by limited knowledge of sleep-related symptoms, sleep architecture, and types of sleep disorders. We aimed to compare the differences in sleep-related symptoms and polysomnography-based sleep disorders between HIV-infected persons and controls.

Methods

The study included 170 men with a Pittsburgh sleep quality index (PSQI) greater than 5, composed of 44 HIV-infected men and 126 male controls who were frequency-matched by sex, age (-/+ 3.0 years) and BMI (-/+ 3.0 kg/m2). For all participants an overnight sleep study using a Somte V1 monitor was conducted. Differences in sleep-related symptoms and sleep disorders between HIV-infected patients and controls were examined using t-tests or Chi-square tests.

Results

HIV-infected persons with sleep disturbances more often had psychological disturbances (72.7% vs. 40.5%, p&lt;0.001) and suspected rapid eye movement (REM) behavior disorder (RBD) (25.0% vs. 4.8%, p&lt;0.01) than that of controls. The sleep-disordered breathing (SDB) in HIV-infected persons was less common than that in controls (56.8% vs. 87.3%, p&lt;0.001). The mean percentage of REM sleep among HIV-infected patients was higher than that among the controls (20.6% vs. 16.6%, p&lt;0.001). Enuresis was more common in HIV-infected persons than controls (40.9% vs. 22.2%, p=0.02).

Conclusion

Psychological disturbances and SDB can be the possible explanations of sleep disturbances in HIV-infected persons, in which suspected RBD is notable. Further studies are warranted to examine underlying factors of suspected RBD among HIV-infected persons with sleep disturbances.

Support

This work was supported by the Ministry of Science and Technology, Executive Yuan of Taiwan [MOST 105-3011-E-006-002], and National Cheng Kung University Hospital [NCKUH-10702022]