Diagnostic and prognostic performance of artificial intelligence-based fully-automated on-site CT-FFR in patients with CAD

Currently, clinically available coronary CT angiography (CCTA) derived fractional flow reserve (CT-FFR) is time-consuming and complex. We propose a novel artificial intelligence-based fully-automated, on-site CT-FFR technology, which combines the automated coronary plaque segmentation and luminal extraction model with reduced order 3 dimentional (3D) computational fluid dynamics. A total of 463 consecutive patients with 600 vessels from the updated China CT-FFR study in Cohort 1 undergoing both CCTA and invasive fractional flow reserve (FFR) within 90 d were collected for diagnostic performance evaluation. For Cohort 2, a total of 901 chronic coronary syndromes patients with index CT-FFR and clinical outcomes at 3-year follow-up were retrospectively analyzed. In Cohort 3, the association between index CT-FFR from triple-rule-out CTA and major adverse cardiac events in patients with acute chest pain from the emergency department was further evaluated. The diagnostic accuracy of this CT-FFR in Cohort 1 was 0.82 with an area under the curve of 0.82 on a per-patient level. Compared with the manually dependent CT-FFR techniques, the operation time of this technique was substantially shortened by 3 times and the number of clicks from about 60 to 1. This CT-FFR technique has a highly successful (> 99%) calculation rate and also provides superior prediction value for major adverse cardiac events than CCTA alone both in patients with chronic coronary syndromes and acute chest pain. Thus, the novel artificial intelligence-based fully automated, on-site CT-FFR technique can function as an objective and convenient tool for coronary stenosis functional evaluation in the real-world clinical setting.

Prognostic Value of Non-alcoholic Fatty Liver Disease and RCA Pericoronary Adipose Tissue CT Attenuation in Patients with Acute Chest Pain

RATIONALE AND OBJECTIVES

Pericoronary adipose tissue (PCAT) CT attenuation of right coronary artery (RCA) and non-alcoholic fatty liver disease (NAFLD) have prognostic value for major adverse cardiovascular events (MACE) in patients with coronary artery disease. However, the superior prognostic value between RCA PCAT CT attenuation and NAFLD remains unclear in patients with acute chest pain. This study is to evaluate the prognostic value of NAFLD for MACE, and further assess the incremental prognostic value of NAFLD over PCAT CT attenuation.

MATERIALS AND METHODS

Between January 2011 and December 2021, all consecutive emergency patients with acute chest pain referred for coronary CT angiography (CCTA) were retrospectively enrolled. MACE included unstable angina requiring hospitalization, coronary revascularization, non-fatal myocardial infarction, and all-cause death. Patients' baseline and CCTA characteristics, RCA PCAT CT attenuation, and the presence of NAFLD were used to evaluate risk factors of MACE using multivariable Cox regression analysis. The prognostic value of NAFLD compared to RCA PCAT CT attenuation was analyzed.

RESULTS

A total of 514 patients were enrolled (mean age, 58.36 ± 13.05 years; 310 men). During a median follow-up of 31 months, 60 patients (11.67%) experienced MACE. NAFLD (HR = 2.599, 95% CI: 1.207, 5.598, P = 0.015) and RCA PCAT CT attenuation (HR = 1.026, 95% CI: 1.001, 1.051, P = 0.038) were independent predictors of MACE. The global Chi-square analysis showed that NAFLD improved the risk of MACE more than that using clinical risk factors and CCTA metrics (59.51 vs 54.44, P = 0.024) or combined with RCA PCAT CT attenuation (63.75 vs 59.51, P = 0.040).

CONCLUSION

NAFLD and RCA PCAT CT attenuation were predictors of MACE. NAFLD had an incremental prognostic value beyond RCA PCAT CT attenuation for MACE in patients with acute chest pain. Adding CT-FFR into the risk prediction of patients with acute chest pain is worth considering.

MRI radiomics predicts the efficacy of EGFR-TKI in EGFR-mutant non-small-cell lung cancer with brain metastasis

AIM

To develop and validate models based on magnetic resonance imaging (MRI) radiomics for predicting the efficacy of epidermal growth factor receptor tyrosine kinase inhibitor (EGFR-TKI) in EGFR-mutant non-small-cell lung cancer (NSCLC) patients with brain metastases.

MATERIALS AND METHODS

117 EGFR-mutant NSCLC patients with brain metastases who received EGFR-TKI treatment were included in this study from January 1, 2014 to December 31, 2021. Patients were randomly divided into training and validation cohorts in a ratio of 2:1. Radiomics features extracted from brain MRI were screened by least absolute shrinkage and selection operator (LASSO) algorithm. Logistic regression analysis and Cox proportional hazard regression analysis were used to screen clinical risk factors. Clinical (C), radiomics (R), and combined (C + R) nomograms were constructed in models predicting short-term efficacy and intracranial progression-free survival (iPFS), respectively. Calibration curves, Harrell's concordance index (C-index), and decision curve analysis (DCA) were used to evaluate the performance of models.

RESULTS

Overall response rate (ORR) was 57.3% and median iPFS was 12.67 months. The C + R nomograms were more effective. In the short-term efficacy model, the C-indexes of C + R nomograms in training cohort and validation cohort were 0.860 (0.820-0.901, 95%CI) and 0.843 (0.783-0.904, 95%CI). In iPFS model, the C-indexes of C + R nomograms in training cohort and validation cohort were 0.837 (0.751-0.923, 95%CI) and 0.850 (0.763-0.937, 95%CI).

CONCLUSION

The C + R nomograms were more effective in predicting EGFR-TKI efficacy of EGFR-mutant NSCLC patients with brain metastases than single clinical or radiomics nomograms.

Evaluation of screening performance of first-trimester competing-risks prediction model for small-for-gestational age in Asian population

OBJECTIVE

To examine the external validity of the Fetal Medicine Foundation (FMF) competing-risks model for the prediction of small-for-gestational age (SGA) at 11-14 weeks' gestation in an Asian population.

METHODS

This was a secondary analysis of a multicenter prospective cohort study in 10 120 women with a singleton pregnancy undergoing routine assessment at 11-14 weeks' gestation. We applied the FMF competing-risks model for the first-trimester prediction of SGA, combining maternal characteristics and medical history with measurements of mean arterial pressure (MAP), uterine artery pulsatility index (UtA-PI) and serum placental growth factor (PlGF) concentration. We calculated risks for different cut-offs of birth-weight percentile (< 10th , < 5th or < 3rd percentile) and gestational age at delivery (< 37 weeks (preterm SGA) or SGA at any gestational age). Predictive performance was examined in terms of discrimination and calibration.

RESULTS

The predictive performance of the competing-risks model for SGA was similar to that reported in the original FMF study. Specifically, the combination of maternal factors with MAP, UtA-PI and PlGF yielded the best performance for the prediction of preterm SGA with birth weight < 10th percentile (SGA < 10th ) and preterm SGA with birth weight < 5th percentile (SGA < 5th ), with areas under the receiver-operating-characteristics curve (AUCs) of 0.765 (95% CI, 0.720-0.809) and 0.789 (95% CI, 0.736-0.841), respectively. Combining maternal factors with MAP and PlGF yielded the best model for predicting preterm SGA with birth weight < 3rd percentile (SGA < 3rd ) (AUC, 0.797 (95% CI, 0.744-0.850)). After excluding cases with pre-eclampsia, the combination of maternal factors with MAP, UtA-PI and PlGF yielded the best performance for the prediction of preterm SGA < 10th and preterm SGA < 5th , with AUCs of 0.743 (95% CI, 0.691-0.795) and 0.762 (95% CI, 0.700-0.824), respectively. However, the best model for predicting preterm SGA < 3rd without pre-eclampsia was the combination of maternal factors and PlGF (AUC, 0.786 (95% CI, 0.723-0.849)). The FMF competing-risks model including maternal factors, MAP, UtA-PI and PlGF achieved detection rates of 42.2%, 47.3% and 48.1%, at a fixed false-positive rate of 10%, for the prediction of preterm SGA < 10th , preterm SGA < 5th and preterm SGA < 3rd , respectively. The calibration of the model was satisfactory.

CONCLUSION

The screening performance of the FMF first-trimester competing-risks model for SGA in a large, independent cohort of Asian women is comparable with that reported in the original FMF study in a mixed European population. © 2023 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

The restoration ability of a short nap after sleep deprivation on the brain cognitive function: A dynamic functional connectivity analysis

AIMS

The brain function impairment induced by sleep deprivation (SD) is temporary and can be fully reversed with sufficient sleep. However, in many cases, long-duration recovery sleep is not feasible. Thus, this study aimed to investigate whether a short nap after SD is sufficient to restore brain function.

METHODS

The data of 38 subjects, including resting state functional magnetic resonance imaging data collected at three timepoints (before SD, after 30 h of SD, and after a short nap following SD) and psychomotor vigilance task (PVT) data, were collected. Dynamic functional connectivity (DFC) analysis was used to evaluate changes in brain states among three timepoints, and four DFC states were distinguished across the three timepoints.

RESULTS

Before SD, state 2 (a resting-like FC matrix) was dominant (48.26%). However, after 30 h SD, the proportion of state 2 dramatically decreased, and state 3 (still resting-like, but FCs were weakened) became dominant (40.92%). The increased proportion of state 3 positively correlated with a larger PVT "lapse" time. After a nap, the proportions of states 2 and 3 significantly increased and decreased, respectively, and the change in proportion of state 2 negatively correlated with the change in PVT "lapse" time.

CONCLUSIONS

Taken together, the results indicated that, after a nap, the cognitive function impairment caused by SD may be reversed to some extent. Additionally, DFC differed among timepoints, which was also associated with the extent of cognitive function impairment after SD (state 3) and the extent of recovery therefrom after a nap (state 2).

White matter structural topologic efficiency predicts individual resistance to sleep deprivation

BACKGROUND

Sleep deprivation (SD) is commonplace in modern society and there are large individual differences in the vulnerability to SD. We aim to identify the structural network differences based on diffusion tensor imaging (DTI) that contribute to the individual different vulnerability to SD.

METHODS

The number of psychomotor vigilance task (PVT) lapses was used to classify 49 healthy subjects on the basis of whether they were vulnerable or resistant to SD. DTI and graph theory approaches were used to investigate the topologic organization differences of the brain structural connectome between SD-vulnerable and -resistant individuals. We measured the level of global efficiency and clustering in rich club and non-rich club organizations.

RESULTS

We demonstrated that participants vulnerable to SD had less global efficiency, network strength, and local efficiency but longer shortest path length compared with participants resistant to SD. Lower efficiency was mainly distributed in the right insula, bilateral thalamus, bilateral frontal, temporal, and temporal lobes. Furthermore, a disrupted subnetwork was observed that consisted of widespread connections. Moreover, the vulnerable group showed significantly decreased strength of the rich club compared with the resistant group. The strength of rich club connectivity was found to be correlated negatively with PVT performance (r = -0.395, p = 0.005). We further tested the reliability of the results.

CONCLUSION

The findings revealed that individual differences in resistance to SD are related to disrupted topologic efficiency connectome pattern, and our study may provide potential connectome-based biomarkers for the early detection of the vulnerable degree to SD.

Neurological prognosis in surgically treated acute aortic dissection with brain computed tomography perfusion

OBJECTIVES

The aim of this study was to explore the prognostic value of brain computed tomography perfusion (CTP) for postoperative new stroke in acute type A aortic dissection (ATAAD) patients.

METHODS

Patients with ATAAD and suspected cerebral malperfusion who underwent brain CTP and surgical repair were retrospectively analysed. Brain perfusion was quantified mainly with the averaged cerebral blood flow. Significant clinical and imaging findings were identified through univariable and multivariable regression analysis. Furthermore, the added prognostic benefit of perfusion parameters was confirmed with the receiver operating characteristic curves in the entire cohort and subgroup analysis.

RESULTS

The incidence of postoperative new stroke was 30.8% (44/143). The independent adjusted predictors of postoperative new stroke included an impaired averaged cerebral blood flow (ml/100 ml/min) (odds ratio: 0.889; P < 0.001), severe stenosis (odds ratio: 5.218; P = 0.011) or occlusion (odds ratio: 14.697; P = 0.048) of the true lumen in common carotid artery (CCA), hypotension on admission (odds ratio: 9.644; P = 0.016) and a longer surgery time (odds ratio: 1.593; P = 0.021). The area under the receiver operating characteristic curves significantly improved after adding perfusion parameters to clinical and computed tomography angiography characteristics (P = 0.048). This benefit was more pronounced in patients with severe stenosis or occlusion in CCA true lumen (P = 0.004).

CONCLUSIONS

Brain CTP could be a useful prognostic tool for surgically treated ATAAD patients and especially beneficial in patients with severe stenosis or occlusion of the CCA true lumen.

Cognitive impairment after sleep deprivation: The role of precuneus related connectivity on the intra-individual variability changes

OBJECTIVE

Intra-individual variability (IIV) in cognitive performance is thought to reflect the efficiency with which attentional resources are allocated in different circumstances requiring cognitive control. IIV in cognitive performance is associated with the strength of the negative correlation between task-positive network and default mode network (DMN) activity. In this study, we investigated the impact of sleep deprivation (SD) on functional connectivity (FC) between the DMN and psychomotor vigilance task-related network (PVT-RN), and its relationship with IIV in cognitive performance.

METHODS

Two analyses, network-level independent component analysis (NL-ICA) and region-level (RL)-ICA, were employed to compare the coefficient of variation (CV) of the PVT between normal sleep and SD conditions across 67 healthy participants.

RESULTS

After SD, in NL-ICA, the FC between the PVT-RN and DMN was positively correlated with the CV of the PVT, as well as the changes therein, compared with normal sleep. Using a mask derived from the DMN and PVT-RN, the RL-ICA revealed that 12 edges/connections between DMN and PVT independent components were associated with the CV of the PVT, with nine of these connections involving the precuneus.

CONCLUSIONS

These findings suggest that the precuneus may play a crucial role in the interactions of various brain functions during the PVT, with the connections between the precuneus and frontoparietal and somatosensory networks being significantly altered after SD. Moreover, following SD, weakened negative FC between the precuneus and bilateral inferior parietal lobule may disrupt the balance between cognitive and executive control functions, leading to a decline in cognitive performance.

Association of Objective Sleep Characteristics and Incident Angina Pectoris: A Longitudinal Analysis from the Sleep Heart Health Study

Purpose

While prior research has highlighted a significant association between sleep characteristics and angina pectoris (AP) incidence, the link between sleep efficiency (SE) and angina remains unexplored. This study seeks to elucidate the relationship between AP and objectively quantified SE.

Patients and Methods

We examined a cohort of 2990 participants (1320 males and 1670 females; mean age 63.69 ± 13.2 years) from the Sleep Heart Health Study. The main exposure variable was SE, as determined by baseline home polysomnography, while the primary outcome was the first incidence of angina pectoris (AP) during the period between the baseline polysomnography and the end of follow-up. A multivariate Cox regression model was utilized, controlling for factors such as age, gender, BMI, smoking and alcohol consumption habits, diabetes, hypertension, sleep duration, triglycerides, cholesterol, high-density lipoprotein, apnea-hypopnea index, nocturnal oxygen saturation, to analyze the relationship between SE and AP.

Results

During an average follow-up of 11 years, 284 patients developed AP. The unadjusted Kaplan-Meier analysis identified the 2nd quartile of SE as having the lowest AP risk. The multivariate Cox proportional hazards model demonstrated a higher risk of AP in quartile 1 (HR, 1.679; 95% CI, 1.109-2.542; P <0.014) and quartile 3 (HR, 1.503; 95% CI, 1.037-2.179; P <0.031), compared to quartile 2 of SE. Upon stratified analysis, this relationship was particularly pronounced in hypertensive individuals.

Conclusion

Our results highlight the critical role of optimal sleep efficiency in mitigating the risk of angina pectoris, especially among hypertensive individuals.

Risk prediction of preoperative acute ischemic stroke in acute type A aortic dissection

OBJECTIVES

To predict preoperative acute ischemic stroke (AIS) in acute type A aortic dissection (ATAAD).

METHODS

In this multi-center retrospective study, 508 consecutive patients diagnosed as ATAAD between April 2020 and March 2021 were considered for inclusion. The patients were divided into a development cohort and two validation cohorts based on time periods and centers. Clinical data and imaging findings obtained were analyzed. Univariable and multivariable logistic regression analyses were performed to identify predictors associated with preoperative AIS. The performance of resulting nomogram was evaluated in discrimination and calibration on all cohorts.

RESULTS

A total of 224 patients were in the development cohort, 94 in the temporal validation cohort, and 118 in the geographical validation cohort. Six predictors were identified: age, syncope, D-dimer, moderate to severe aortic valve insufficiency, diameter ratio of true lumen in ascending aorta  < 0.33, and common carotid artery dissection. The nomogram established showed good discrimination (area under the receiver operating characteristic curve [AUC], 0.803; 95% CI: 0.742, 0.864) and calibration (Hosmer-Lemeshow test p = 0.300) in the development cohort. External validation showed good discrimination and calibration abilities in both temporal (AUC, 0.778; 95% CI: 0.671, 0.885; Hosmer-Lemeshow test p = 0.161) and geographical cohort (AUC, 0.806; 95% CI: 0.717, 0.895; Hosmer-Lemeshow test p = 0.100).

CONCLUSIONS

A nomogram, based on simple imaging and clinical variables collected on admission, showed good discrimination and calibration abilities in predicting preoperative AIS for ATAAD patients.

KEY POINTS

• A nomogram based on simple imaging and clinical findings may predict preoperative acute ischemic stroke in patients with acute type A aortic dissection in emergencies. • The nomogram showed good discrimination and calibration abilities in validation cohorts.

Prognostic value of coronary CT angiography and CT myocardial perfusion imaging among patients with and without Diabetes

OBJECTIVES

Whether stress CT myocardial perfusion imaging (CT-MPI) improves risk assessment in patients with diabetes mellitus (DM) remains unexplored. We aimed to evaluate the prognostic value of coronary CT angiography (CCTA) and stress CT-MPI in suspected coronary artery disease (CAD) patients with and without DM.

METHODS

A total of 334 patients with suspected CAD who underwent CCTA and stress CT-MPI from May 2020 to July 2021 were retrospectively analyzed. The endpoint was major adverse cardiovascular events (MACEs). Multivariable Cox regression analysis was used to evaluate the risk factors for MACEs, including clinical risk factors, CCTA characteristics and CT-MPI characteristics.

RESULTS

After a median follow-up of 21 months,15 patients of the DM group and 16 patients of the non-DM group experienced MACEs. Multivariate Cox stepwise regression analysis showed that abnormal perfusion myocardial segments ratio was associated with MACEs after adjusting for clinical risk factors and CCTA characteristics in all patients (HR:1.023, p < 0.001), DM group (HR:1.024, p = 0.008) and non-DM group (HR:1.028, p = 0.003). By adding CT-MPI characteristics to CCTA characteristics and clinical risk factors, the global chi-square for predicting MACEs increased from 62.24 to 78.84 in all patients (p < 0.001), from 19.18 to 27.30 in DM group (p = 0.004) and from 39.51 to 48.65 in non-DM group (p = 0.003); the increment of C-index in all patients, DM group and non-DM group were 0.018, 0.054 and 0.019, respectively.

CONCLUSION

In all patients and those with and without DM, CT-MPI has incremental prognostic value over clinical risk factors alone or combined with CCTA characteristics in predicting MACEs.

Treatment of Severe Pulmonary Regurgitation in Enlarged Native Right Ventricular Outflow Tracts: Transcatheter Pulmonary Valve Replacement with Three-Dimensional Printing Guidance

BACKGROUND

Severe pulmonary regurgitation (PR) often occurs following a transannular patch repair of tetralogy of Fallot, resulting in an enlarged native right ventricular outflow tract (nRVOT) with varying shapes.

METHODS

We conducted a single-center study with eight patients having severe PR and enlarged nRVOT (diameters ≥ 29 mm). Transcatheter pulmonary valve replacement (TPVR) was performed using the self-expanding PT-Valve. Preoperative evaluation included echocardiography, computed tomography, and magnetic resonance imaging. A 3D-printed model of the nRVOT was used for preoperative assessment. Follow-up data were collected in 1-year follow-up.

RESULTS

PT-Valve was successfully implanted in all patients, resulting in immediate improvement of severe PR. Pulmonary artery diastolic pressure increased significantly (p < 0.001). No deaths or coronary compression occurred during the procedure. Over a 1-year follow-up, no stent displacement or fracture occurred. Only two patients had trace paravalvular leaks. Magnetic resonance imaging revealed a reversal of right ventricular remodeling, with a significant reduction in right ventricular end-diastolic volume index (p < 0.001) and improved right ventricular ejection fraction (p < 0.001). All patients achieved primary endpoints.

CONCLUSION

3D printing-guided PT-Valve implantation in enlarged nRVOT for severe PR is safe and effective, expanding TPVR indications and offering potential treatment for a broader patient population.

Efficacy of spesolimab for the treatment of generalized pustular psoriasis flares across pre-specified patient subgroups in the Effisayil 1 study

Effisayil 1 was a multicentre, randomized, double-blind, placebo-controlled study of the anti-interleukin (IL)-36 receptor monoclonal antibody, spesolimab, in patients presenting with a generalized pustular psoriasis (GPP) flare. Previously published data from this study revealed that within 1 week, rapid pustular and skin clearance were observed in patients receiving spesolimab versus placebo. In this pre-specified subgroup analysis, the efficacy of spesolimab was evaluated according to patient demographic and clinical characteristics at baseline in patients receiving spesolimab (n = 35) or placebo (n = 18) on Day 1. Efficacy was by assessed by achievement of primary endpoint (Generalized Pustular Psoriasis Physician Global Assessment [GPPGA] pustulation subscore of 0 at Week 1) and key secondary endpoint (GPPGA total score of 0 or 1 at Week 1). Safety was assessed at Week 1. Spesolimab was found to be efficacious and had a consistent and favourable safety profile in patients presenting with a GPP flare, regardless of patient demographics and clinical characteristics at baseline.

[Feasibility and safety of one-stage bilateral video-assisted thoracic surgery for resection of bilateral multiple pulmonary nodules]

OBJECTIVE

To evaluate the feasibility and safety of one- stage bilateral video-assisted thoracic surgery (VATS) for resection of bilateral multiple pulmonary nodules (BMPNs).

METHODS

We analyzed the clinical characteristics, pathological features, perioperative outcomes and follow-up data of 41 patients with BMPNs undergoing one-stage bilateral VATS from July, 2011 to August, 2021.

RESULTS

One-stage bilateral VATS was performed uneventfully in 40 of the patients, and conversion to open surgery occurred in 1 case. The surgical approaches included bilateral lobectomy (4.9%), lobar-sublobar resection (36.6%) and sublobar-sublobar resection (58.5%) with a mean operative time of 196.3±54.5 min, a mean blood loss of 224.6±139.5 mL, a mean thoracic drainage duration of 4.7±1.1 days and a mean hospital stay of 14±3.8 days. Pathological examination revealed bilateral primary lung cancer in 15 cases, unilateral primary lung cancer in 21 cases and bilateral benign lesions in 5 cases. A total of 112 pulmonary nodules were resected, including 67 malignant and 45 benign lesions. Postoperative complications included pulmonary infection (5 cases), respiratory failure (2 cases), asthma attack (2 cases), atrial fibrillation (2 cases), and drug-induced liver injury (1 case). No perioperative death occurred in these patients, who had a 1-year survival rate of 97.6%.

CONCLUSION

With appropriate preoperative screening and perioperative management, one-stage bilateral VATS is feasible and safe for resection of BMPNs.

Lack of Incremental Prognostic Value of Pericoronary Adipose Tissue Computed Tomography Attenuation Beyond Coronary Artery Disease Reporting and Data System for Major Adverse Cardiovascular Events in Patients With Acute Chest Pain

BACKGROUND

Pericoronary adipose tissue (PCAT) and Coronary Artery Disease Reporting and Data System (CAD-RADS) category had prognostic values for major adverse cardiovascular events (MACEs). However, little is known about the difference between CAD-RADS and PCAT computed tomography (CT) attenuation for predicting MACEs. This study was to compare the prognostic value of PCAT and CAD-RADS for MACEs in patients with acute chest pain.

METHODS

Between January 2010 and December 2021, all consecutive emergency patients with acute chest pain referred for coronary computed tomography angiography were enrolled in this retrospective study. MACEs included unstable angina requiring hospitalization, coronary revascularization, nonfatal myocardial infarction, and all-cause death. Patients' clinical characteristics, CAD-RADS, and PCAT CT attenuation were used to evaluate risk factors of MACEs using multivariable Cox regression analysis.

RESULTS

A total of 1313 patients were evaluated (mean age, 57.13±12.57 years; 782 men). During a median follow-up of 38 months, 142 of the 1313 patients (10.81%) experienced MACEs. Multivariable Cox regression analysis showed that CAD-RADS categories 2, 3, 4, 5 (hazard ratio range, 2.286-8.325; all P<0.005) and right coronary artery PCAT CT attenuation (hazard ratio, 1.033; P=0.006) were independent predictors of MACEs after adjusting for clinical risk factors. The C statistics revealed that CAD-RADS improved risk stratification compared with PCAT CT alone (C-index, 0.760 versus 0.712; P=0.036). However, the benefit of right coronary artery PCAT CT attenuation combined with CAD-RADS was not significant compared with CAD-RADS alone (0.777 versus 0.760; P=0.129).

CONCLUSIONS

Right coronary artery PCAT CT attenuation and CAD-RADS were independent predictors of MACEs. However, no incremental prognostic value of right coronary artery PCAT CT attenuation beyond CAD-RADS was detected for MACEs in patients with acute chest pain.

Nonalcoholic fatty liver disease is associated with myocardial ischemia by CT myocardial perfusion imaging, independent of clinical and coronary CT angiography characteristics

OBJECTIVE

The aim of this study was to evaluate whether patients with nonalcoholic fatty liver disease (NAFLD) have more myocardial malperfusion on CT myocardial perfusion imaging (CT-MPI), as well as to further assess if NAFLD is a predictor of myocardial ischemia independently.

METHODS

A total of 310 consecutive patients were included for analysis. All patients were divided into two groups according to the presence or absence of NAFLD, which was diagnosed by noncontrast cardiac CT partially covered liver and spleen. Clinical characteristics as well as imaging features including coronary artery calcium score, CCTA, and CT-MPI findings were analyzed. Univariable and multivariable logistic regression analyses were used to find out the relationship between NAFLD and myocardial ischemia.

RESULTS

NAFLD (unadjusted hazard ratio [HR]: 2.4, 95% confidence interval [CI]: 1.2 to 4.4, p = 0.008), male (HR: 2.6, 95% CI: 1.5 to 4.5, p = 0.001), obstructive CAD (HR: 2.3, 95% CI: 1.3 to 4.2, p = 0.004), and FAI ≥ -70.1 HU (HR: 3.1, 95% CI: 1.8 to 5.5, p < 0.001) were associated with myocardial ischemia in univariable analysis. After adjusting for traditional CAD risk factors and CT characteristics in the multivariable regression analysis, NAFLD (HR: 2.3, 95% CI: 1.2 to 4.4, p = 0.016) was an independent predictor of myocardial ischemia.

CONCLUSION

Our data suggest that myocardial ischemia was more prevalent in patients with NAFLD, and NAFLD is a predictor of myocardial ischemia independent of traditional cardiovascular risk factors and CCTA characteristics.

KEY POINTS

• NAFLD patients had higher calcium score, incidence of obstructive coronary artery disease, grade of CAD-RADS, quantitative plaque characteristics, and incidence of fat attenuation index ≥ -70.1 HU. • NAFLD patients had a higher incidence of myocardial ischemia, myocardial hypoperfusion, and hypoperfusion myocardial segments ratio. • NAFLD was a predictor of myocardial ischemia, independent of traditional cardiovascular risk factors, and CCTA characteristics.

Coronary Computed Tomography Angiography-derived Fractional Flow Reserve: An Expert Consensus Document of Chinese Society of Radiology

Invasive fractional flow reserve (FFR) measured by a pressure wire is a reference standard for evaluating functional stenosis in coronary artery disease. Coronary computed tomography angiography-derived fractional flow reserve (CT-FFR) uses advanced computational analysis methods to noninvasively obtain FFR results from a single conventional coronary computed tomography angiography data to evaluate the hemodynamic significance of coronary artery disease. More and more evidence has found good correlation between the results of noninvasive CT-FFR and invasive FFR. CT-FFR has proven its potential in optimizing patient management, improving risk stratification and prognosis, and reducing total health care costs. However, there is still a lack of standardized interpretation of CT-FFR technology in real-world clinical settings. This expert consensus introduces the principle, workflow, and interpretation of CT-FFR; summarizes the state-of-the-art application of CT-FFR; and provides suggestions and recommendations for the application of CT-FFR with the aim of promoting the standardized application of CT-FFR in clinical practice.

The burden of end-stage osteoarthritis in Australia: a population-based study on the incidence of total knee replacement attributable to overweight/obesity

OBJECTIVES

To determine the risk of total knee replacement (TKR) for primary osteoarthritis (OA) associated with overweight/obesity in the Australian population.

METHODS

This population-based study analyzed 191,723 cases of TKR collected by the Australian Orthopaedic Association National Joint Registry and population data from the Australian Bureau of Statistics. The time-trend change in incidence of TKR relating to BMI was assessed between 2015 and 2018. The influence of obesity on the incidence of TKR in different age and gender groups was determined. The population attributable fraction (PAF) was then calculated to estimate the effect of obesity reduction on TKR incidence.

RESULTS

The greatest increase in incidence of TKR was seen in patients from obese class III. The incidence rate ratio for having a TKR for obesity class III was 28.683 at those aged 18-54 years but was 2.029 at those aged >75 years. Females in obesity class III were 1.7 times more likely to undergo TKR compared to similarly classified males. The PAFs of TKR associated with overweight or obesity was 35%, estimating 14,287 cases of TKR attributable to obesity in 2018. The proportion of TKRs could be reduced by 20% if overweight and obese population move down one category.

CONCLUSIONS

Obesity has resulted in a significant increase in the incidence of TKR in the youngest population in Australia. The impact of obesity is greatest in the young and the female population. Effective strategies to reduce the national obese population could potentially reduce 35% of the TKR, with over 10,000 cases being avoided.

P-517 Validating reference gene expression stability in human ovarian follicles, oocytes, cumulus cells, ovarian medulla, and ovarian cortex tissue

Study question

How does the expression stability of commonly used reference genes (RG) vary in different human ovarian cells and tissues?

Summary answer

The RG stability differed among human ovarian cell types and tissues, but an RG with high stability was identified for each cell and tissue type.

What is known already

The expression of RGs used to normalize RT-qPCR may vary between different tissues, cell types, and experimental conditions. Hence, selecting the most appropriate RGs is critical in any experimental design to interpret data generated by RT-qPCR with the best accuracy. Human ovarian cells are phenotypically very different and often only available in limited amounts. In several animal species RG expression stability has been validated in oocytes and other ovarian cells, however, the suitability of a single universal RG in the different human ovarian cells and tissues has not been determined.

Study design, size, duration

This is an experimental study performed at a university hospital from January 2021 to September 2021.

Participants/materials, setting, methods

The freely available NormFinder software was used to analyze the expression stability of five commonly used RGs (GAPDH, B2M, RPLP0, ACTB, and PPIA) in human oocytes (n = 160), preantral follicles (n = 160), cumulus cells (n = 13), ovarian medulla (n = 8), and ovarian cortex tissue (n = 60). Samples were collected from 29 patients (aged 28 years on average; range 14–36) undergoing unilateral oophorectomy and ovarian tissue cryopreservation for fertility preservation.

Main results and the role of chance

The Normfinder software identified ACTB as the best RG for oocytes and cumulus cells; and B2M for medulla tissue and isolated follicles. Overall, comparisons of the cycle threshold (Ct) values demonstrated a wide variation among the RGs within the same group of samples (P &lt; 0.05), especially for oocytes and preantral follicles with normalized RNA. The genes ACTB and RPLP0 showed the highest levels of expression and PPIA the lowest levels of expression in all types of samples, except for cortex tissue, where PPIA had the highest level of expression and B2M the lowest. These results infer that different results could be obtained when using different RGs for data normalization. The combination of two RGs only marginally increased stability, indicating that using a single validated RG would be sufficient when the available testing material is limited. For cultured ovarian cortex culture, GAPDH or ACTB were found to be the most stable genes depending on culture conditions.

Limitations, reasons for caution

Since human oocytes are scarce and contain a small amount of RNA, only five RGs were evaluated. Moreover, only germinal vesicle (GV) oocytes and preantral follicles (60-80 µm) were tested. Future studies may validate other genes and investigate the effect of oocyte maturation and follicle growth on RG stability.

Wider implications of the findings

Our findings highlight the importance of validating RGs for each cell type or tissue and culture condition. Hence, our results can be of use as guidance for future studies involving gene expression analyses in human ovarian cells and tissues, including oocytes and preantral follicles.

Trial registration number

Not applicable

AB0864 A nomogram model combining inflammatory factors and MRI radiomics to assess the disease activity of the patients with axSpA in a prospective study

Background

Clinical and magnetic resonance imaging (MRI) disease activity score (DAS) are measuring different aspects of axial spondyloarthritis (axSpA), they are essential in disease activity assessment. The radiomics was on facilitating readings by clinical specialists via enhancing the medical images in which subtle data differences could be distinguished.

Objectives

If the additional information of MRI imaging can be considered as a predictor for axSpA disease activity? In this study, we sought to construct a nomogram integrating the sacroiliac joint (SIJ)- MRI radiomics features and the inflammatory biomarkers to assess disease activity and compare it with clinical disease acitivity index in axSpA patients.

Methods

203 patients data were collected prospectively and confirmed as axSpA were randomly divided into training (n = 143) and validation cohorts (n = 60). 1316 radiomics features were extracted from the 3.0T SIJ-MRI. A Nomogram model was constructed using multivariate logistic regression analysis Incorporating independent clinical factors and radiomics features score (Rad-score). The performance of clinics, Rad-score and nomogram models were evaluated by ROC analysis, calibration curve and decision curve analysis (DCA), and compared with the disease activity index(Ankylosing Spondylitis DAS (ASDAS)-C reactive protein (CRP), ASDAS-erythrocyte sedimentation rate (ESR), Bath Ankylosing Spondylitis Disease Activity Index (BASDAI), Bath Ankylosing Spondylitis Functional Index (BASFI)) and Spondyloarthritis Research Consortium of Canada (SPARCC) MRI scoring system.

Results

The Rad-score allowed a good discrimination in the training (AUC, 0.91; 95% CI, 0.85-0.96) and the validation cohort (AUC, 0.84; 95% CI, 0.73-0.96). The CRP-radiomics nomogram model also showed favorable discrimination in the training (AUC, 0.96; 95% CI, 0.93-0.99) and the validation cohort (AUC, 0.89; 95% CI, 0.80-0.98), better than BASDAI(AUC, 0.58), ASDAS-CRP(AUC, 0.72), ASDAS-ESR(AUC, 0.77), ESR(AUC, 0.72), CRP(AUC, 0.77) and BASFI(AUC, 0.73), had no statistical difference with SPARCC(AUC, 0.87). Calibration curves and DCA demonstrated the nomogram fit well (p > 0.05) and was useful for activity evaluation.

Conclusion

Rad-score showed good discriminative ability to assess disease activity in axSpA. The nomogram can increase the efficacy for assessment axSpA disease activity, which might simplify clinical evaluation.

Figure 1.

Comparison of ROC curve analyses in prediction models. ROC curves of the clinical features (green curve), radiomics signature model (blue curve), and hybrid model (gold curve) of axSpA in the training cohort (A) and validation cohort (B), respectively. In addition, there are AUC of ASDAS-CRP(pink curve), ASDAS-ESR(brown curve), BASDAI(purple curve), BASFI(azure curve) and SPARCC scoring system(yellow curve) in the validation cohort (B), respectively. AUC: area under the curve; ROC: receiver operating characteristic; SPARCC: Spondyloarthritis Research Consortium of Canada; BASDAI: Bath Ankylosing Spondylitis Disease Activity Index; ASDAS: Ankylosing Spondylitis Disease Activity Score; CRP: C reactive protein; ESR: erythrocyte sedimentation rate; BASFI: Bath Ankylosing Spondylitis Disease Activity Index.

References

[1]Lee KH, Choi ST, Lee GY, Ha YJ, Choi SI. Method for Diagnosing the Bone Marrow Edema of Sacroiliac Joint in Patients with Axial Spondyloarthritis Using Magnetic Resonance Image Analysis Based on Deep Learning. Diagnostics (Basel). 2021;11(7).

[2]Zheng Q, Liu W, Huang Y, Gao Z, Wu Y, Wang X, et al. Predictive Value of Active Sacroiliitis in MRI for Flare Among Chinese Patients with Axial Spondyloarthritis in Remission. Rheumatol Ther. 2021;8(1):411-24.

Acknowledgements

No conflict of interest

Disclosure of Interests

None declared

AB0890 Deucravacitinib, an Oral, Selective Tyrosine Kinase 2 Inhibitor, in Moderate to Severe Plaque Psoriasis: 52-Week Efficacy Results From the Phase 3 POETYK PSO-1 and POETYK PSO-2 Trials

Background

Tyrosine kinase 2 (TYK2) is an intracellular kinase that mediates signaling of key cytokines (eg, interleukin [IL]-23 and Type I interferons) involved in the pathogenesis of immune-mediated diseases including plaque psoriasis and psoriatic arthritis (PsA). Deucravacitinib is a novel, oral, selective, allosteric inhibitor of TYK2 that achieves high selectivity by uniquely binding to the regulatory domain of the enzyme, rather than to the more conserved active domain. Deucravacitinib showed superior efficacy compared with placebo at 16 weeks in a Phase 2 trial in patients with PsA (NCT03881059). Results from the 16-week, placebo-controlled periods of two 52-week, Phase 3 trials in psoriasis (POETYK PSO-1 and POETYK PSO-2) previously showed that deucravacitinib was significantly more efficacious than placebo and apremilast based on the coprimary endpoints of ≥75% reduction from baseline in Psoriasis Area and Severity Index (PASI 75) and a static Physician’s Global Assessment (sPGA) score of 0 or 1 (clear or almost clear) at Week 16.

Objectives

To evaluate the efficacy of deucravacitinib over 52 weeks in the POETYK PSO-1 and POETYK PSO-2 trials.

Methods

POETYK PSO-1 (NCT03624127) and PSO-2 (NCT03611751) were double-blinded trials that randomised patients with moderate to severe plaque psoriasis (body surface area involvement ≥10%, PASI ≥12, sPGA score ≥3) 2:1:1 to deucravacitinib 6 mg once daily, placebo, or apremilast 30 mg twice daily. Patients receiving placebo were switched to deucravacitinib at Week 16 in both trials. Patients randomised to deucravacitinib in PSO-1 received deucravacitinib continuously through Week 52. PSO-2 included a randomised withdrawal phase in which patients originally randomised to deucravacitinib who had achieved PASI 75 response at Week 24 were rerandomised 1:1 to placebo or deucravacitinib, whereas those who did not achieve PASI 75 response at Week 24 continued receiving deucravacitinib. The proportions of patients achieving PASI 75 and sPGA 0/1 responses were evaluated up to Week 52. Secondary efficacy endpoints evaluated over this period included PASI 90, PASI 100, percentage change from baseline in PASI, sPGA 0 (clear), change from baseline in the Psoriasis Symptoms and Signs Diary (PSSD) symptom score, and Dermatology Life Quality Index (DLQI) 0/1 (no impact on patient’s life).

Results

A total of 666 and 1020 patients were randomised in PSO-1 and PSO-2, respectively. Demographic and baseline disease characteristics were balanced across treatment groups; mean age was 46.6 years, mean disease duration was 18.6 years, 18.4% of patients had PsA, and 34.8% had previously used biologic therapy. PASI 75, PASI 90, and PASI 100 responses were maintained from Week 16 to Week 52 in PSO-1 (Figure 1). Additionally, sPGA responses were maintained during this period (sPGA 0/1: 53.6% to 52.7%; sPGA 0: 17.5% to 23.5%, respectively). Patients who switched from placebo to deucravacitinib at Week 16 demonstrated PASI 75 and sPGA 0/1 responses at Week 52 (68.3% and 53.8%, respectively) comparable to those observed in patients who received continuous deucravacitinib treatment from Day 1 (65.1% and 52.7%, respectively). In PSO-2, among deucravacitinib-treated patients who achieved PASI 75 at Week 24 and were rerandomised to continue treatment, responses were maintained at Week 52 in the majority of patients (PASI 75, 80.4% [119/148]; sPGA 0/1, 70.3% [83/118]). Results for percentage change from baseline in PASI, change from baseline in the PSSD symptom score, and DLQI 0/1 were consistent with those reported for PASI and sPGA responses.

Conclusion

Results from the Phase 3 POETYK PSO-1 and PSO-2 trials demonstrated that deucravacitinib was efficacious through 52 weeks in patients with moderate to severe plaque psoriasis. Clinical responses were maintained in patients who received continuous deucravacitinib treatment and were improved in patients who switched from placebo at Week 16 to deucravacitinib treatment.

Acknowledgements

This study was sponsored by Bristol Myers Squibb. Professional medical writing assistance was provided by Julianne Hatfield, PhD at Peloton Advantage, LLC, an OPEN Health company, Parsippany, NJ, USA, and funded by Bristol Myers Squibb.

Disclosure of Interests

Richard B. Warren Consultant of: Consulting fees: AbbVie, Almirall, Amgen, Biogen, Boehringer Ingelheim, Celgene, DiCE, Eli Lilly, Janssen, Leo Pharma, Novartis, Pfizer, Sanofi, UCB, Biogen, and UNION., Grant/research support from: Research grants: AbbVie, Almirall, Amgen, Celgene, Eli Lilly, Janssen, Leo Pharma, Novartis, Pfizer, and UCB;, April Armstrong Grant/research support from: Grants and personal fees: AbbVie, Bristol Myers Squibb, Eli Lilly, Janssen, Leo Pharma, and Novartis; Personal fees: Boehringer Ingelheim/Parexel, Celgene, Dermavant, Genentech, GlaxoSmithKline, Menlo Therapeutics, Merck, Modernizing Medicine, Ortho Dermatologics, Pfizer, Regeneron, Sanofi Genzyme, Science 37, Sun Pharma, and Valeant; Grants: Dermira, Kyowa Hakko Kirin, and UCB, outside the submitted work., Melinda Gooderham Consultant of: Advisory board, principal investigator, and lecture fees: Arcutis, Galderma, Leo Pharma, Pfizer, and Regeneron; Principal investigator and consulting fees: Akros Pharma and Kyowa Kirin; Advisory board, principal investigator, lecture fees, and consulting fees: AbbVie, Amgen, Boehringer Ingelheim, Celgene, Eli Lilly, Janssen, Novartis, Sanofi Genzyme, and Valeant; Principal investigator: Aslan, Bristol Myers Squibb, Dermavant, Dermira, GlaxoSmithKline, MedImmune, Merck, Roche Laboratories, and UCB., Bruce Strober Consultant of: Consultant (honoraria): AbbVie, Almirall, Amgen, Arcutis, Arena, Aristea, Asana, Boehringer Ingelheim, Immunic Therapeutics, Bristol Myers Squibb, Connect Biopharma, Dermavant, Eli Lilly, Equillium, Janssen, Leo Pharma, Maruho, Meiji Seika Pharma, Mindera, Novartis, Pfizer, GlaxoSmithKline, Ortho Dermatologics, Regeneron, Sanofi Genzyme, Sun Pharma, UCB, Ventyxbio, and vTv Therapeutics; Speaker: AbbVie, Eli Lilly, Janssen, and Sanofi Genzyme; Co-Scientific Director (consulting fee): CorEvitas’ Psoriasis Registry; Investigator: AbbVie, Cara, CorEvitas’ Psoriasis Registry, Dermavant, Dermira, and Novartis., Diamant Thaçi Speakers bureau: Advisory board, principal investigator, and lecture fees: AbbVie, Almirall, Amgen, Biogen Idec, Boehringer Ingelheim, Bristol Myers Squibb, Celgene, DS Pharma, Eli Lilly, Galapagos, Galderma, Janssen-Cilag, Leo Pharma, Novartis, Pfizer, Regeneron, Roche-Posay, Samsung, Sandoz-Hexal, Sanofi, and UCB., Shinichi Imafuku Grant/research support from: Grants and personal fees: AbbVie, Eisai, Kyowa Kirin, Taiho, Maruho, Tanabe Mitsubishi, Leo Pharma, Janssen, Sun Pharma, Torii, and Yakuhin; Personal fees: Amgen, Bristol Myers Squibb, Daiichi Sankyo, Eli Lilly, Novartis, and UCB., Howard Sofen Consultant of: Clinical Investigator: AbbVie, Amgen, Boehringer Ingelheim, Bristol Myers Squibb, Eli Lilly, Janssen, Leo Pharma, Novartis, and Sun Pharma., Lynda Spelman Consultant of: Consultant, paid investigator, and/or speaker: AbbVie, Amgen, Anacor, Ascend, Astellas, AstraZeneca, Blaze Bioscience, Boehringer Ingelheim, Botanix, Bristol Myers Squibb, Celgene, Dermira, Eli Lilly, Galderma, Genentech, GlaxoSmithKline, Hexima, Janssen, Leo Pharma, Mayne, Medimmune, Merck, Merck-Serono, Novartis, Otsuka, Pfizer, Phosphagenics, Photon MD, Regeneron, Roche, Samumed, Sanofi Genzyme, SHR, Sun Pharma, Trius, UCB, and Zai Lab., Neil J Korman Speakers bureau: Advisory board, consulting fees: AbbVie, Boehringer Ingelheim, Bristol Myers Squibb, Celgene, Eli Lilly, Janssen, Leo Pharma, Novartis, Principia, Regeneron, Sanofi Genzyme, Sun Pharma, and UCB; Speaker: AbbVie, Eli Lilly, Janssen, Novartis, Regeneron, and Sanofi Genzyme., Consultant of: AbbVie, Boehringer Ingelheim, Bristol Myers Squibb, Celgene, Eli Lilly, Janssen, Leo Pharma, Novartis, Principia, Regeneron, Sanofi Genzyme, Sun Pharma, and UCB, Grant/research support from: Grant support/principal investigator: AbbVie, Amgen, Argenx, Bristol Myers Squibb, Celgene, Chemocentryx, Eli Lilly, Galderma, Kyowa Hakko Kirin, Leo Pharma, Menlo, Principia, Prothena, Rhizen, Syntimmune, Trevi, and Xbiotech., Min Zheng Speakers bureau: AbbVie, Boehringer Ingelheim, Bristol Myers Squibb, Eli Lilly China, Leo Pharma China, Novartis China, Pfizer, Sanofi China, and Xian-Janssen., Consultant of: AbbVie, Boehringer Ingelheim, Bristol Myers Squibb, Eli Lilly China, Leo Pharma China, Novartis China, Pfizer, Sanofi China, and Xian-Janssen., Grant/research support from: AbbVie, Boehringer Ingelheim, Bristol Myers Squibb, Eli Lilly China, Leo Pharma China, Novartis China, Pfizer, Sanofi China, and Xian-Janssen., Elizabeth Colston Shareholder of: Bristol Myers Squibb, Employee of: Bristol Myers Squibb, John Throup Shareholder of: Bristol Myers Squibb, Employee of: Bristol Myers Squibb, Sudeep Kundu Shareholder of: Bristol Myers Squibb, Employee of: Bristol Myers Squibb, Renata Kisa Shareholder of: Bristol Myers Squibb, Employee of: Bristol Myers Squibb, Subhashis Banerjee Shareholder of: Employees and shareholders: Bristol Myers Squibb, Employee of: Employees and shareholders: Bristol Myers Squibb, Andrew Blauvelt Consultant of: Scientific advisor and/or clinical study investigator: AbbVie, Abcentra, Aligos, Almirall, Amgen, Arcutis, Arena, Aslan, Athenex, Boehringer Ingelheim, Bristol Myers Squibb, Dermavant, EcoR1, Eli Lilly, Evommune, Forte, Galderma, Incyte, Janssen, Landos, Leo Pharma, Novartis, Pfizer, Rapt, Regeneron, Sanofi Genzyme, Sun Pharma, UCB, and Vibliome. 

POS0962 CAN RADIOMICS REPLACE SPARCC SCORING SYSTEM IN EVALUATING BONE MARROW OEDEMA OF THE SACROILIAC JOINTS IN AXIAL SPONDYLOARTHRITIS?

Background

Bone marrow oedema (BMO) of the sacroiliac joints (SIJs) is evaluated to diagnose, classify and monitor disease activity in patients with axial spondyloarthritis (axSpA). Available quantitative methodologies rely on human visual assessment, and errors can’t be completely avoided. Radiomics can extract and select discriminative and quantified features from regions of interest (ROIs), making a more accurate and objective description of BMO.

Objectives

To develop a more objective and efficient method based on radiomics to evaluate BMO of the SIJs by magnetic resonance imaging (MRI) in patients with axSpA in comparison with Spondyloarthritis Research Consortium of Canada (SPARCC) scoring system.

Methods

From September 2013 to July 2021, 523 patients with axSpA underwent 3.0T SIJ-MRI were included, who were randomly classified as training cohort(n=367) and validation cohort(n=156). The optimal radiomics features, selected from the 3.0T SIJ-MRI in the training cohort, were included to build the radiomics model. Four clinical risk predictors were adopted to build the clinical model. The performance of the clinical and radiomics models was evaluated by ROC analysis and decision curve analysis (DCA). Rad-scores were calculated by the radiomics model and SPARCC scores were performed to quantify the BMO of SIJs. We also assessed the correlation between Rad-score and SPARCC score.

Results

The radiomics model, built by 15 optimal features, showed favorable discrimination about SPARCC score <2 or ≥2 both in the training (AUC, 0.91; 95% CI: 0.88-0.94) and the validation cohort (AUC, 0.89; 95% CI, 0.84-0.94). DCA confirmed that the radiomics model was clinically useful. Furthermore, Rad-score has significant correlation with SPARCC score for scoring the status of BMO (rs=0.78, P< 0.001), and moderation correlation for scoring the change (r=0.40, P=0.005).

Conclusion

The radiomics can accurately assess the BMO of the SIJs in axSpA, providing an alternative to SPARCC scoring system. There was a positive correlation between Rad-score and SPARCC score.

References

[1]van der Heijde D, Sieper J, Maksymowych WP, Lambert RG, Chen S, Hojnik M, et al. Clinical and MRI remission in patients with nonradiographic axial spondyloarthritis who received long-term open-label adalimumab treatment: 3-year results of the ABILITY-1 trial. Arthritis Res Ther. 2018;20(1):61.

[2]Landewé RB, Hermann KG, van der Heijde DM, Baraliakos X, Jurik AG, Lambert RG, et al. Scoring sacroiliac joints by magnetic resonance imaging. A multiple-reader reliability experiment. The Journal of rheumatology. 2005;32(10):2050-5.

[3]Cereser L, Zabotti A, Zancan G, Quartuccio L, Cicciò C, Giovannini I, et al. Magnetic resonance imaging assessment of ASAS-defined active sacroiliitis in patients with inflammatory back pain and suspected axial spondyloarthritis: a study of reliability. Clinical and experimental rheumatology. 2021.

[4]Maksymowych WP, Inman RD, Salonen D, Dhillon SS, Williams M, Stone M, et al. Spondyloarthritis research Consortium of Canada magnetic resonance imaging index for assessment of sacroiliac joint inflammation in ankylosing spondylitis. Arthritis Rheum. 2005;53(5):703-9.

[5]Gillies RJ, Kinahan PE, Hricak H. Radiomics: Images Are More than Pictures, They Are Data. Radiology. 2016;278(2):563-77.

Table 1.

Rad-scores corresponding to different SPARCC score intervals about the status of SIJ-BMO.

SPARCC scorenRad-scoreMean(sd)Median (iqr)Range0-1170-1.31(1.64)-1.39(2.16)-6.46, 2.352-61250.73(1.86)0.62(2.12)-3.08, 8.487-11552.25(1.80)2.36(1.79)-1.17, 8.3612-16432.65(2.14)2.66(3.21)-0.76, 7.3917-21383.31(2.05)3.25(2.88)-0.88, 7.5522-26263.08(1.55)3.38(2.12)-1.00, 5.3827-31253.77(1.36)3.77(1.59)0.40, 6.27>31414.10(1.51)4.32(2.28)1.00, 6.96

Disclosure of Interests

None declared

Influence of Different Segmentations on the Diagnostic Performance of Pericoronary Adipose Tissue

Objective

To investigate the influence of different segmentations on the diagnostic performance of pericoronary adipose tissue (PCAT) CT attenuation and radiomics features for the prediction of ischemic coronary artery stenosis.

Methods

From June 2016 to December 2018, 108 patients with 135 vessels were retrospectively analyzed in the present study. Vessel-based PCAT was segmented along the 40 mm-long proximal segments of three major epicardial coronary arteries, while lesion-based PCAT was defined around coronary lesions. CT attenuation and radiomics features derived from two segmentations were calculated and extracted. The diagnostic performance of PCAT CT attenuation or radiomics models in predicting ischemic coronary stenosis were also compared between vessel-based and lesion-based segmentations.

Results

The mean PCAT CT attenuation was −75.7 ± 9.1 HU and −76.1 ± 8.1 HU (p = 0.395) for lesion-based and vessel-based segmentations, respectively. A strong correlation was found between vessel-based and lesion-based PCAT CT attenuation for all cohort and subgroup analyses (all p < 0.01). A good agreement for all cohort and subgroup analyses was also detected between two segmentations. The diagnostic performance was comparable between vessel-based and lesion based PCAT CT attenuation in predicting ischemic stenosis. The radiomics features of PCAT based on vessel or lesion segmentation can both adequately identify the ischemic stenosis. However, no significant difference was detected between the two segmentations.

Conclusions

The quantitative evaluation of PCAT can be reliably measured both from vessel-based and lesion-based segmentation. Furthermore, the radiomics analysis of PCAT may potentially help predict hemodynamically significant coronary artery stenosis.

Predicting Attentional Vulnerability to Sleep Deprivation: A Multivariate Pattern Analysis of DTI Data

BACKGROUND

Large individual differences exist in sleep deprivation (SD) induced sustained attention deterioration. Several brain imaging studies have suggested that the activities within frontal-parietal network, cortico-thalamic connections, and inter-hemispheric connectivity might underlie the neural correlates of vulnerability/resistance to SD. However, those traditional approaches are based on average estimates of differences at the group level. Currently, a neuroimaging marker that can reliably predict this vulnerability at the individual level is lacking.

METHODS

Efficient transfer of information relies on the integrity of white matter (WM) tracts in the human brain, we therefore applied machine learning approach to investigate whether the WM diffusion metrics can predict vulnerability to SD. Forty-nine participants completed the psychomotor vigilance task (PVT) both after resting wakefulness (RW) and after 24 h of sleep deprivation (SD). The number of PVT lapse (reaction time > 500 ms) was calculated for both RW condition and SD condition and participants were categorized as vulnerable (24 participants) or resistant (25 participants) to SD according to the change in the number of PVT lapses between the two conditions. Diffusion tensor imaging were acquired to extract four multitype WM features at a regional level: fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity. A linear support vector machine (LSVM) learning approach using leave-one-out cross-validation (LOOCV) was performed to assess the discriminative power of WM features in SD-vulnerable and SD-resistant participants.

RESULTS

LSVM analysis achieved a correct classification rate of 83.67% (sensitivity: 87.50%; specificity: 80.00%; and area under the receiver operating characteristic curve: 0.85) for differentiating SD-vulnerable from SD-resistant participants. WM fiber tracts that contributed most to the classification model were primarily commissural pathways (superior longitudinal fasciculus), projection pathways (posterior corona radiata, anterior limb of internal capsule) and association pathways (body and genu of corpus callosum). Furthermore, we found a significantly negative correlation between changes in PVT lapses and the LSVM decision value.

CONCLUSION

These findings suggest that WM fibers connecting (1) regions within frontal-parietal attention network, (2) the thalamus to the prefrontal cortex, and (3) the left and right hemispheres contributed the most to classification accuracy.

Sleep Stage Classification Based on Multi-Centers: Comparison Between Different Ages, Mental Health Conditions and Acquisition Devices

PURPOSE

To investigate the general sleep stage classification performance of deep learning networks, three datasets, across different age groups, mental health conditions, and acquisition devices, comprising adults (SHHS) and children without mental health conditions (CCSHS), and subjects with mental health conditions (XJ), were included in this study.

METHODS

A long short-term memory (LSTM) network was used to evaluate the effect of different ages, mental health conditions, and acquisition devices on the sleep stage classification performance and the general performance.

RESULTS

Results showed that the age and different mental health conditions may affect the sleep stage classification performance of the network. The same acquisition device using different parameters may not have an obvious effect on the classification performance. When using a single dataset and two datasets for training, the network performed better only on the training dataset. When training was conducted with three datasets, the network performed well for all datasets with a Cohen's Kappa of 0.8192 and 0.8472 for the SHHS and CCSHS, respectively, but performed relatively worse (0.6491) for the XJ, which indicated the complexity effect of different mental health conditions on the sleep stage classification task. Moreover, the performance of the network trained using three datasets was similar for each dataset to that of the network trained using a single dataset and tested on the same dataset.

CONCLUSION

These results suggested that when more datasets across different age groups, mental health conditions, and acquisition devices (ie, more datasets with different feature distributions for each sleep stage) are used for training, the general performance of a deep learning network will be superior for sleep stage classification tasks with varied conditions.

The Construction of a Risk Prediction Model Based on Neural Network for Pre-operative Acute Ischemic Stroke in Acute Type A Aortic Dissection Patients

Objective: To establish a pre-operative acute ischemic stroke risk (AIS) prediction model using the deep neural network in patients with acute type A aortic dissection (ATAAD). Methods: Between January 2015 and February 2019, 300 ATAAD patients diagnosed by aorta CTA were analyzed retrospectively. Patients were divided into two groups according to the presence or absence of pre-operative AIS. Pre-operative AIS risk prediction models based on different machine learning algorithm was established with clinical, transthoracic echocardiography (TTE) and CTA imaging characteristics as input. The performance of the difference models was evaluated using the receiver operating characteristic (ROC), precision-recall curve (PRC) and decision curve analysis (DCA). Results: Pre-operative AIS was detected in 86 of 300 patients with ATAAD (28.7%). The cohort was split into a training (211, 70% patients) and validation cohort (89, 30% patients) according to stratified sampling strategy. The constructed deep neural network model had the best performance on the discrimination of AIS group compare with other machine learning model, with an accuracy of 0.934 (95% CI: 0.891-0.963), 0.921 (95% CI: 0.845-0.968), sensitivity of 0.934, 0.960, specificity of 0.933, 0.906, and AUC of 0.982 (95% CI: 0.967-0.997), 0.964 (95% CI: 0.932-0.997) in the training and validation cohort, respectively. Conclusion: The established risk prediction model based on the deep neural network method may have the big potential to evaluate the risk of pre-operative AIS in patients with ATAAD.

Inhibition of Aspergillus flavus growth and aflatoxin B1 production by natamycin

Aspergillus flavus causes huge crop losses, reduces crop quality and has adverse effects on human and animal health. A large amount of food contaminated with aflatoxin can greatly increase the risk of liver cancer. Therefore, prevention and control of aflatoxin production have aroused attention of research in various countries. Natamycin extracted from Streptomyces spp. has been widely used in production practice due to its good specificity and safety. Here, we found that natamycin could significantly inhibit fungal growth, conidia germination, ergosterol and AFB1 production by A. flavus in a dose-dependent manner. Scanning electron microscope analysis indicated that the number of conidia was decreased, the outer wall of conidia was destroyed, and the mycelia were shrivelled and tangled by natamycin. RNA-Seq data indicated that natamycin inhibited fungal growth and conidia development of A. flavus by significantly down-regulating some genes involved in ergosterol biosynthesis, such as Erg13, HMG1 and HMG2. It inhibited conidia germination by significantly down-regulating some genes related to conidia development, such as FluG and VosA. After natamycin exposure, the decreased ratio of aflS/aflR caused by the down-regulation of all the structural genes, which subsequently resulted in the suppression of AFB1 production. In conclusion, this study served to reveal the inhibitory mechanisms of natamycin on fungal growth and AFB1 biosynthesis in A. flavus and to provide solid evidence for its application in controlling AFB1 contamination.

Predicting haemodynamic significance of coronary stenosis with radiomics-based pericoronary adipose tissue characteristics

AIM

To investigate the diagnostic performance of the radiomics features of pericoronary adipose tissue (PCAT) in determining haemodynamically significant coronary artery stenosis as evaluated by fractional flow reserve (FFR).

MATERIALS AND METHODS

A total of 92 patients with clinically suspected coronary artery disease who underwent coronary computed tomography (CT) angiography (CCTA), invasive coronary angiography (ICA), and FFR examination within 1 month were included retrospectively, and 121 lesions were randomly assigned to the training and testing set. Based on manual segmentation of PCAT, 1,116 radiomics features were computed. After radiomics robustness assessment and feature selection, radiomics models were established using the different machine-learning algorithms. The area under the receiver operating characteristic (ROC) curve (AUC) and net reclassification index (NRI) were analysed to compare the discrimination and reclassification abilities of radiomics models.

RESULTS

Two radiomics features were selected after exclusions, and both were significantly higher in coronary arteries with FFR ≤0.8 than those with FFR >0.8. ROC analysis showed that the combination of CCTA and decision tree radiomics model achieved significantly higher diagnostic performance (AUC: 0.812) than CCTA alone (AUC: 0.599, p=0.015). Furthermore, the NRI of the combined model was 0.820 and 0.775 in the training and testing sets, respectively, suggesting the radiomics features of PCAT had were effective in classifying the haemodynamic significance of coronary stenosis.

CONCLUSIONS

Adding PCAT radiomics features to CCTA enabled identification of haemodynamically significant coronary artery stenosis.

Clinical progress and advanced research of red blood cells based drug delivery system

Red blood cells (RBCs) are biocompatible carriers that can be employed to deliver different bioactive substances. In the past few decades, many strategies have been developed to encapsulate or attach drugs to RBCs. Osmotic-based encapsulation methods have been industrialized recently, and some encapsulated RBC formulations have reached the clinical stage for treating tumors and neurological diseases. Inspired by the intrinsic properties of intact RBCs, some advanced delivery strategies have also been proposed. These delivery systems combine RBCs with other novel systems to further exploit and expand the application of RBCs. This review summarizes the clinical progress of drugs encapsulated into intact RBCs, focusing on the loading and clinical trials. It also introduces the latest advanced research based on developing prospects and limitations of intact RBCs drug delivery system (DDS), hoping to provide a reference for related research fields and further application potential of intact RBCs based drug delivery system.

The Clinical and MRI Effect of TNF-α Inhibitors in Spondyloarthritis Patients With Hip Involvement: A Real-World Observational Clinical Study

Objectives

Hip involvement is an important cause of disability and poor prognosis in patients with spondyloarthritis (SpA). Tumor necrosis factor (TNF)-α inhibitor treatment has been demonstrated to be effective in SpA patients with hip arthritis; however, quantitative assessment using MRI in long-term follow-up needs further application and observation.

Methods

A total of 239 patients were involved in this study. Methotrexate and sulfasalazine were given as basic treatment. In total, 165 patients received TNF-α inhibitors plus basic treatment, and 74 received basic treatment only, as controls. Clinical symptoms were assessed at baseline and at weeks 12, 24, and 52. MRI performances of hip arthritis, including bone marrow edema (BME) and synovitis, were quantitatively assessed using the Hip Inflammation MRI Scoring System (HIMRISS).

Results

The clinical values of erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), Bath Ankylosing Spondylitis Disease Activity Index (BASDAI), Harris hip score, and Ankylosing Spondylitis Disease Activity Score (ASDAS)-ESR in both groups showed significant clinical remission at week 52 (p < 0.001). However, the change in disease activity levels at week 52 in the control group was significantly worse than in the TNF-α inhibitor group. At week 52, MRI showed a significant remission trend in the TNF-α inhibitor group versus baseline, and total HIMRISS scores were significantly decreased (26.49 ± 10.37 vs. 20.59 ± 9.41, p < 0.001); the control group only had slight improvement (p < 0.05).

Conclusions

TNF-α inhibitors could significantly improve clinical and MRI manifestations of hip involvement in patients with SpA. Quantitative MRI assessment combined with clinical assessment can be used to accurately evaluate the treatment effect of TNF-α in SpA patients with hip involvement to help guide targeted treatment.

Classifying Vulnerability to Sleep Deprivation Using Resting-State Functional MRI Graph Theory Metrics

Sleep deprivation (SD) has become very common in contemporary society, where people work around the clock. SD-induced cognitive deficits show large inter-individual differences and are trait-like with known neural correlates. However, few studies have used neuroimaging to predict vulnerability to SD. Here, resting state functional magnetic resonance imaging (fMRI) data and psychomotor vigilance task (PVT) data were collected from 60 healthy subjects after resting wakefulness and after one night of SD. The number of PVT lapses was then used to classify participants on the basis of whether they were vulnerable or resilient to SD. We explored the viability of graph-theory-based degree centrality to accurately classify vulnerability to SD. Compared with during resting wakefulness, widespread changes in degree centrality (DC) were found after SD, indicating significant reorganization of sleep homeostasis with respect to activity in resting state brain network architecture. Support vector machine (SVM) analysis using leave-one-out cross-validation achieved a correct classification rate of 84.75% [sensitivity 82.76%, specificity 86.67%, and area under the receiver operating characteristic curve (AUC) 0.94] for differentiating vulnerable subjects from resilient subjects. Brain areas that contributed most to the classification model were mainly located within the sensorimotor network, default mode network, and thalamus. Furthermore, we found a significantly negative correlation between changes in PVT lapses and DC in the thalamus after SD. These findings suggest that resting-state network measures combined with a machine learning algorithm could have broad potential applications in screening vulnerability to SD.

Pericoronary adipose tissue CT attenuation and volume: Diagnostic performance for hemodynamically significant stenosis in patients with suspected coronary artery disease

OBJECTIVES

The aim of this study was to investigate the diagnostic abilities of both pericoronary adipose tissue (PCAT) CT attenuation and volume for the predication hemodynamic significance of coronary artery stenosis as evaluated by fractional flow reserve (FFR).

METHODS

Patients with ≥ 30 % in at least 1 major epicardial coronary artery were retrospectively included. Furthermore, all eligible patients underwent coronary computed tomography angiography (CCTA) and invasive coronary angiography (ICA) as well as FFR within 1 month. PCAT CT attenuation and volume around ischemic and non-ischemic coronary stenosis were measured and compared. The diagnostic accuracy of PCAT CT attenuation and volume for the identification of hemodynamically significant stenosis was determined against the reference standard of FFR ≤ 0.80.

RESULTS

A total of 61 patients (mean age, 57.8 years ± 11.8) with 77 vessels were included. Average PCAT CT attenuation of all vessels was -70.3 ± 7.4 HU. PCAT CT attenuation in coronary arteries with hemodynamically significant stenosis (FFR ≤ 0.80) (-65.6 ± 5.9 HU) was significantly higher than those with FFR > 0.80 (-75.3 ± 5.4 HU; p = 0.000). There was a strong correlation between FFR and PCAT CT attenuation (r = 0.64, p < 0.001). However, no significant difference in PCAT volume was observed between FFR ≤ 0.8 (5.0 ± 3.5 cm³) and FFR > 0.80 (5.5 ± 3.7 cm³, p = 0.511). The diagnostic accuracy was significantly higher in the combination of CCTA and PCAT CT attenuation compared with CCTA alone (area under the curve: 0.869 vs. 0.569, p < 0.001).

CONCLUSIONS

PCAT CT attenuation but not volume was related to the hemodynamic significance of coronary artery stenosis. For the patients with suspected coronary artery disease, after adding of PCAT CT attenuation to CCTA, the diagnostic ability for the identification of ischemic coronary stenosis was significantly improved.

[Analysis on prediction power of HIV infection risk assessment tool in men who have sex with men in Guizhou province]

Objective: To evaluate the prediction power of HIV infection risk assessment tool and the applicability in MSM in Guizhou province. Methods: MSM were recruited through snowball sampling method. Questionnaire surveys were conducted among the MSM using HIV infection risk assessment tool, and combined with HIV serologic test results, the risk prediction power of HIV infection risk assessment tool was evaluated. Results: A total of 3 379 MSM were recruited from January 2018 to December 2019 in Guizhou. The HIV infection rate was 3.3%(111/3 379). The mean risk scores of HIV positive and HIV negative MSM were (12.15±3.08) and (12.07±3.07), respectively. The difference in risk score was significant between MSM with different HIV status (t=8.69, P<0.001). According to the principle of decision tree, individual risk scores were divided into following three categories: ≤11.96, 11.97-14.80 and >14.80, the HIV infection rate was 0.8%, 4.3% and 8.6% respectively, suggesting that the higher the individual risk score was, the higher the HIV infection rate was (trend χ²=88.18, P<0.001). Multivariate logistic regression analysis showed that the higher the individual risk score was, the higher the risk of HIV infection was. Compared to the total score ≤11.96, the aOR values at total scores of 11.97-14.80 and >14.80 were 6.34 (95%CI: 3.38-11.88) and 14.07(95%CI: 7.44-26.61), respectively. The risk of HIV infection in Miao ethnic group was higher than that in Han ethnic group (aOR=1.83, 95%CI:1.04-3.21), and the risk of HIV infection in those with education level of primary school and below was higher than that in undergraduates or those with education level of junior college and above (aOR=2.50, 95%CI:1.06-5.88), and the risk of HIV infection was higher in those who had bisexual behaviors than in those who had homosexual behaviors (aOR=1.95, 95%CI:1.19-3.19). The risk of HIV infection was higher in those who had never received HIV testing (aOR=1.53, 95%CI:1.01-2.33). The area under the receiver operating characteristic (ROC) curve and area under ROC (AUC) for HIV infection prediction was 0.751 (95%CI:0.710-0.792, P<0.001). The maximum Youden's index was individual risk score of 12.56, and the sensitivity of the risk assessment tool was 0.838, and its specificity was 0.412. Conclusions: The results of HIV infection risk assessment tool in Guizhou indicated that in MSM the higher the individual risk score, the higher the risk of HIV infection is. The tool can be used to evaluate the risk of HIV infection in MSM, but the specificity should be improved.