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Thirty-eight slices of pure trabecular bone 1-cm thickness were extracted from human proximal femurs. A pair of 1-MHz central frequency transducers was used to measure quantitative ultrasound (QUS) parameters in transmission [normalized broadband ultrasound attenuation (nBUA), speed of sound (SOS)] and in backscatter [broadband ultrasound backscatter (BUB)]. Bone mineral density (BMD) was measured using clinical x-ray quantitative computed tomography. Site-matched identical region of interest (ROIs) of 7×7 mm2 were positioned on QUS and QCT images. This procedure resulted in 605 ROIs for all the specimens data pooled together. The short-term precision of the technique expressed in terms of CV was found to be 2.3% for nBUA, 0.3% for SOS and 4.5% for BUB. Significant linear correlation between QUS and BMD were found for all the 605 ROIs pooled, with r2 values of 0.73, 0.77, and 0.58 for nBUA, SOS, and BUB, respectively (all p<0.05). For the BUB, the best regression was obtained with a polynomial fit of second order (r2=0.63). An analysis of measurements errors was developed. It showed that the residual variability of SOS is almost completely predicted by measurements errors, which is not the case for BUA and BUB, suggesting a role for micro-architecture in the determination of BUA and BUB. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study was to investigate the prognostic value of left atrioventricular coupling index (LACI) assessed by cardiac computed tomography (CT), to predict cardiovascular death in consecutive patients referred for cardiac CT with coronary analysis., Materials and Methods: Between 2010 and 2020, we conducted a single-centre study with all consecutive patients without known cardiovascular disease referred for cardiac CT. LACI was defined as the ratio of left atrial to left ventricle end-diastolic volumes. The primary outcome was cardiovascular death. Cox regressions were used to evaluate the association between LACI and primary outcome after adjustment for traditional risk factors and cardiac CT angiography findings., Results: In 1,444 patients (mean age, 70 ± 12 [standard deviation] years; 43% men), 67 (4.3%) patients experienced cardiovascular death after a median follow-up of 6.8 (Q1, Q3: 5.9, 9.1) years. After adjustment, LACI was positively associated with the occurrence of cardiovascular death (adjusted hazard ratio [HR], 1.07 [95% CI: 1.05-1.09] per 1% increment; P < 0.001), and all-cause death (adjusted HR, 1.05 [95% CI: 1.03-1.07] per 1% increment; P <0.001). After adjustment, a LACI ≥ 25% showed the best improvement in model discrimination and reclassification for predicting cardiovascular death above traditional risk factors and cardiac CT findings (C-statistic improvement: 0.27; Nnet reclassification improvement = 0.826; Integrative discrimination index =0.209, all P < 0.001; likelihood-ratio-test, P < 0.001)., Conclusion: LACI measured by cardiac CT is independently associated with cardiovascular death and all-cause death in patients without known cardiovascular disease referred for cardiac CT, with an incremental prognostic value over traditional risk factors and cardiac CT findings., Competing Interests: Declaration of Competing Interest Solenn Toupin is employee of Siemens Healthcare. The other authors declare that they have no competing interests., (Copyright © 2023. Published by Elsevier Masson SAS.)

Rationale and Objectives: Interpreting radiographs in emergency settings is stressful and a burden for radiologists. The main objective was to assess the performance of three commercially available artificial intelligence (AI) algorithms for detecting acute peripheral fractures on radiographs in daily emergency practice., Materials and Methods: Radiographs were collected from consecutive patients admitted for skeletal trauma at our emergency department over a period of 2 months. Three AI algorithms-SmartUrgence, Rayvolve, and BoneView-were used to analyze 13 body regions. Four musculoskeletal radiologists determined the ground truth from radiographs. The diagnostic performance of the three AI algorithms was calculated at the level of the radiography set. Accuracies, sensitivities, and specificities for each algorithm and two-by-two comparisons between algorithms were obtained. Analyses were performed for the whole population and for subgroups of interest (sex, age, body region)., Results: A total of 1210 patients were included (mean age 41.3 ± 18.5 years; 742 [61.3%] men), corresponding to 1500 radiography sets. The fracture prevalence among the radiography sets was 23.7% (356/1500). Accuracy was 90.1%, 71.0%, and 88.8% for SmartUrgence, Rayvolve, and BoneView, respectively; sensitivity 90.2%, 92.6%, and 91.3%, with specificity 92.5%, 70.4%, and 90.5%. Accuracy and specificity were significantly higher for SmartUrgence and BoneView than Rayvolve for the whole population (P < .0001) and for subgroups. The three algorithms did not differ in sensitivity (P = .27). For SmartUrgence, subgroups did not significantly differ in accuracy, specificity, or sensitivity. For Rayvolve, accuracy and specificity were significantly higher with age 27-36 than ≥53 years (P = .0029 and P = .0019). Specificity was higher for the subgroup knee than foot (P = .0149). For BoneView, accuracy was significantly higher for the subgroups knee than foot (P = .0006) and knee than wrist/hand (P = .0228). Specificity was significantly higher for the subgroups knee than foot (P = .0003) and ankle than foot (P = .0195)., Conclusion: The performance of AI detection of acute peripheral fractures in daily radiological practice in an emergency department was good to high and was related to the AI algorithm, patient age, and body region examined., Competing Interests: Declaration of Competing Interest Valérie Bousson is a paid consultant for Milvue starting July 1, 2022. Grégoire Attané was paid by Gleamer between March and August 2019 to label radiographs. The remaining authors declare none. The three companies, Milvue, AZmed, and Gleamer, provided the AI algorithms to our radiology department for free. None of the three companies had access to the study methodology or data during the course of the study., (Copyright © 2023 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.)

Background: Cardiovascular disease (CVD) is the main cause of mortality in patients with chronic kidney disease (CKD). Although several studies have demonstrated the consistently high prognostic value of stress cardiovascular magnetic resonance (CMR), its prognostic value in patients with CKD is not well established. We aimed to assess the safety and the incremental prognostic value of vasodilator stress perfusion CMR in consecutive symptomatic patients with known CKD., Methods: Between 2008 and 2021, we conducted a retrospective dual center study with all consecutive symptomatic patients with known stage 3 CKD, defined by estimated glomerular filtration rate (eGFR) between 30 and 60 ml/min/1.73 m 2 , referred for vasodilator stress CMR. All patients with eGFR < 30 ml/min/1.73 m 2 (n = 62) were excluded due the risk of nephrogenic systemic fibrosis. All patients were followed for the occurrence of major adverse cardiovascular events (MACE) defined as cardiac death or recurrent nonfatal myocardial infarction (MI). Cox regression analysis was used to determine the prognostic value of stress CMR parameters., Results: Of 825 patients with known CKD (71.4 ± 8.8 years, 70% men), 769 (93%) completed the CMR protocol. Follow-up was available in 702 (91%) (median follow-up 6.4 (4.0-8.2) years). Stress CMR was well tolerated without occurrence of death or severe adverse event related to the injection of gadolinium or cases of nephrogenic systemic fibrosis. The presence of inducible ischemia was associated with the occurrence of MACE (hazard ratio [HR] 12.50; 95% confidence interval [CI] 7.50-20.8; p < 0.001). In multivariable analysis, ischemia and late gadolinium enhancement were independent predictors of MACE (HR 15.5; 95% CI 7.72 to 30.9; and HR 4.67 [95% CI 2.83-7.68]; respectively, both p < 0.001). After adjustment, stress CMR findings showed the best improvement in model discrimination and reclassification above traditional risk factors (C-statistic improvement: 0.13; NRI = 0.477; IDI = 0.049)., Conclusions: In patients with known stage 3 CKD, stress CMR is safe and its findings have an incremental prognostic value to predict MACE over traditional risk factors., (© 2023. The Author(s).)

Aims: To assess the safety, feasibility, and prognostic value of stress cardiovascular magnetic resonance (CMR) in patients with pacemaker (PM)., Methods and Results: Between 2008 and 2021, we conducted a bi-centre longitudinal study with all consecutive patients with MR-conditional PM referred for vasodilator stress CMR at 1.5 T in the Institut Cardiovasculaire Paris Sud and Lariboisiere University Hospital. They were followed for the occurrence of major adverse cardiovascular events (MACE) defined as cardiac death or non-fatal myocardial infarction. Cox regression analyses were performed to determine the prognostic value of CMR parameters. The quality of CMR was rated by two observers blinded to clinical details. Of 304 patients who completed the CMR protocol, 273 patients (70% male, mean age 71 ± 9 years) completed the follow-up (median [interquartile range], 7.1 [5.4-7.5] years). Among those, 32 experienced a MACE (11.7%). Stress CMR was well tolerated with no significant change in lead thresholds or pacing parameters. Overall, the image quality was rated good or excellent in 84.9% of segments. Ischaemia and late gadolinium enhancement (LGE) were significantly associated with the occurrence of MACE (hazard ratio, HR: 11.71 [95% CI: 4.60-28.2]; and HR: 5.62 [95% CI: 2.02-16.21], both P < 0.001). After adjustment for traditional risk factors, ischaemia and LGE were independent predictors of MACE (HR: 5.08 [95% CI: 2.58-14.0]; and HR: 2.28 [95% CI: 2.05-3.76]; both P < 0.001)., Conclusion: Stress CMR is safe, feasible and has a good discriminative prognostic value in consecutive patients with PM., Competing Interests: Conflict of interest: None declared. Solenn Toupin is an employee of Siemens Healthcare., (© The Author(s) 2022. Published by Oxford University Press on behalf of the European Society of Cardiology. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Background: In patients with suspected or known coronary artery disease, traditional prognostic risk assessment is based on a limited selection of clinical and imaging findings. Machine learning (ML) methods can take into account a greater number and complexity of variables., Objectives: This study sought to investigate the feasibility and accuracy of ML using stress cardiac magnetic resonance (CMR) and clinical data to predict 10-year all-cause mortality in patients with suspected or known coronary artery disease, and compared its performance with existing clinical or CMR scores., Methods: Between 2008 and 2018, a retrospective cohort study with a median follow-up of 6.0 (IQR: 5.0-8.0) years included all consecutive patients referred for stress CMR. Twenty-three clinical and 11 stress CMR parameters were evaluated. ML involved automated feature selection by random survival forest, model building with a multiple fractional polynomial algorithm, and 5 repetitions of 10-fold stratified cross-validation. The primary outcome was all-cause death based on the electronic National Death Registry. The external validation cohort of the ML score was performed in another center., Results: Of 31,752 consecutive patients (mean age: 63.7 ± 12.1 years, and 65.7% male), 2,679 (8.4%) died with 206,453 patient-years of follow-up. The ML score (ranging from 0 to 10 points) exhibited a higher area under the curve compared with Clinical and Stress Cardiac Magnetic Resonance score, European Systematic Coronary Risk Estimation score, QRISK3 score, Framingham Risk Score, and stress CMR data alone for prediction of 10-year all-cause mortality (ML score: 0.76 vs Clinical and Stress Cardiac Magnetic Resonance score: 0.68, European Systematic Coronary Risk Estimation score: 0.66, QRISK3 score: 0.64, Framingham Risk Score: 0.63, extent of inducible ischemia: 0.66, extent of late gadolinium enhancement: 0.65; all P < 0.001). The ML score also exhibited a good area under the curve in the external cohort (0.75)., Conclusions: The ML score including clinical and stress CMR data exhibited a higher prognostic value to predict 10-year death compared with all traditional clinical or CMR scores., Competing Interests: Funding Support and Author Disclosures Dr Toupin is an employee of Siemens Healthcare. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Copyright © 2022 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)

Objective: Gitelman syndrome (GS) is the most frequent salt-wasting genetic tubulopathy and a source of hypokalaemia and hypomagnesemia. Chondrocalcinosis (CC) is a frequent feature of GS. The aim of our study was to determine the prevalence, distribution patterns, clinical phenotypes and risk factors for CC in GS., Methods: This prospective study of a cohort of 57 patients with GS included a systematic screening for CC by peripheral joint radiography, cervical spine CT and joint US. The prevalence of cervical C1-C2 CC by CT was compared between 33 GS patients and sex- and age-matched controls. Clinical and biochemical features were analysed to identify factors associated with CC., Results: Mean (s.d.) age of patients was 46.5 (12.4) years, 66.7% were women and 93.0% carried SLC12A3 mutations. Mean serum magnesium level was 0.60 (0.30) mmol/l. CC was observed in 79% of patients, with the highest prevalence at the cervical spine (81.8%) followed by the knee (52.6%), wrist (50.9%), ankle (38.6%), TM joint (36.4%), shoulder (33.3%), hip (22.8%), elbow (14.0%) and sclerochoroid (12.1%). Prevalence of CC at the C1-C2 level was higher in the GS cohort than control group (72.7% vs 9.1%) (adjusted odds ratio 21.0, 95% CI 2.8, 156.1, P = 0.003). Independent factors associated with CC were low serum magnesium level and age., Conclusion: GS was associated with widespread CC, favoured by aging and hypomagnesemia. The C1-C2 level was the most affected site. Follow-up of this unique cohort will help understanding the clinical consequences of CC, especially the precise characterization of pyrophosphate arthropathy., (© The Author(s) 2021. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For permissions, please email: journals.permissions@oup.com.)