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Minimally invasive vascular interventional surgery is widely used and remote-controlled vascular interventional surgery robots (RVIRs) are being developed to reduce the occupational risk of the intervening physician in minimally invasive vascular interventional surgeries. Skilled surgeon performs surgeries mainly depending on the detection of collisions. Inaccurate force feedback will be difficult for surgeons to perform surgeries or even results in medical accidents. In addition, the surgeon cannot quickly and easily distinguish whether the proximal force exceeds the safety threshold of blood vessels or not, and thus it results in damage to the blood vessels. In this paper, we present a novel method comprising compensatory force measurement and multimodal force feedback (MFF). Calibration experiments and performance evaluation experiments were carried out. Experimental results demonstrated that the proposed method can measure the proximal force of catheter/guidewire accurately and assist surgeons to distinguish the change of proximal force more easily. This novel method is suitable for use in actual surgical operations.

Objectives To investigate the association between venous outflow (VO) profiles and outcomes among acute ischemic stroke caused by anterior circulation large vessel occlusion (AIS-LVO) patients who had undergone endovascular treatment (EVT) in the late window of 6–24 h from stroke onset. Methods This was a post-hoc analysis of our preceding RESCUE-BT trial, with findings validated in an external cohort. Baseline computed tomographic angiography (CTA) was performed to assess VO using the Cortical Vein Opacification Score (COVES). The primary clinical outcome was functional independence at 90 days (modified Rankin Scale score of 0–2). The adjusted odd ratio (aOR) and confidence interval (CI) were obtained from multivariable logistic regressions. Results A total of 440 patients were included in the present study. After identifying the cutoff of COVES by marginal effects approach, enrolled patients were divided into the favorable VO group (COVES 4–6) and the poor VO (COVES 0–3) group. Multivariable logistic regression analysis showed that favorable VO (aOR 2.25; 95% CI 1.31–3.86; p  = 0.003) was associated with functional independence. Similar results were detected in the external validation cohort. Among those with poor arterial collateralization, favorable VO was still an independent predictor of functional independence (aOR 2.09; 95% CI 1.06–4.10; p  = 0.032). Conclusion The robust VO profile indicated by COVES 4–6 could promote the frequency of functional independence among AIS-LVO patients receiving EVT in the late window, and the prognostic value of VO was independent of the arterial collateral status. Clinical relevance statement The robust venous outflow profile was a valid predictor for functional independence among AIS-LVO patients receiving EVT in the late window (6–24 h) and the predictive role of venous outflow did not rely on the status of arterial collateral circulation. Key Points Many patients undergoing EVT within 6–24   h after stroke onset have non-functionally independent outcomes . Favorable VO was associated with an increased frequency of functional independence in AIS-LVO after EVT . The predictive value of VO didn’t rely on the status of arterial collateral circulation .

In vascular interventional surgery, surgeons operate guidewires and catheters to diagnose and treat patients with the assistance of the digital subtraction angiography (DSA). Therefore, the surgeon will be exposed to X-rays for extended periods. To protect the surgeon, the development of a robot-assisted surgical system is of great significance. The displacement tracking accuracy is the most important issue to be considered in the development of the system. In this study, the active disturbance rejection control (ADRC) method is applied to guarantee displacement tracking accuracy. First, the core contents of the proportional–integral–derivative (PID) and ADRC methods are analyzed. Second, comparative evaluation experiments for incremental PID and ADRC methods are presented. The results show that the ADRC method has better performance of than that of the incremental PID method. Finally, the calibration experiments for the ADRC control method are implemented using the master–slave robotic system. These experiments demonstrate that the maximum tracking error is 0.87 mm using the ADRC method, effectively guaranteeing surgical safety.

The European Society of Cardiovascular Radiology (ESCR) is the European specialist society of cardiac and vascular imaging. This society’s highest priority is the continuous improvement, development, and standardization of education, training, and best medical practice, based on experience and evidence. The present intra-society consensus is based on the existing scientific evidence and on the individual experience of the members of the ESCR writing group on carotid diseases, the members of the ESCR guidelines committee, and the members of the executive committee of the ESCR. The recommendations published herein reflect the evidence-based society opinion of ESCR. We have produced a twin-papers consensus, indicated through the documents as respectively “Part I” and “Part II.” The first document (Part I) begins with a discussion of features, role, indications, and evidence for CT and MR imaging-based diagnosis of carotid artery disease for risk stratification and prediction of stroke (Section I). It then provides an extensive overview and insight into imaging-derived biomarkers and their potential use in risk stratification (Section II). Finally, detailed recommendations about optimized imaging technique and imaging strategies are summarized (Section III). The second part of this consensus paper (Part II) is focused on structured reporting of carotid imaging studies with CT/MR. Key Points • CT and MR imaging-based evaluation of carotid artery disease provides essential information for risk stratification and prediction of stroke. • Imaging-derived biomarkers and their potential use in risk stratification are evolving; their correct interpretation and use in clinical practice must be well-understood. • A correct imaging strategy and scan protocol will produce the best possible results for disease evaluation.

Magnetically manipulated interventional robotic systems offer outstanding advantages for improving vascular interventions, including minimizing radiation exposure to physicians and increasing the controllability of magnetic interventional devices in hard‐to‐reach vessels. However, automatic control of magnetic guidewires (MGs) is still challenging in terms of modeling of guidewires and trajectory planning. Herein, a magnetically controlled guidewire robotic system (MCGRS) with steering and propulsion capabilities is proposed based on adequate modeling and trajectory planning methods. The steering kinematics of MG is first modeled by constant curvature theory. Then, a continuum mechanics model is built to predict the deformation of the magnetic tip by combining the dipole model and the Cosserat‐rod model. Moreover, a trajectory planning algorithm is developed to navigate the MG through vessels. Furthermore, trajectory following experiments within three vascular phantoms confirm that the proposed model and algorithm are reliable and capable of navigating the MG through the desired trajectory. Finally, two extra navigation experiments are implemented in 3D vascular phantom, which show that the MCGRS can be remotely controlled to manipulate the MG to actively steer and reach the target site. The system and methods will build the foundation for automatic control of MG and help to improve the autonomy. In this study, a magnetically controlled guidewire robotic system with steering and propulsion capabilities is proposed based on adequate modeling of magnetic guidewire (MG) and trajectory planning methods. The system and methods will build the foundation for automatic control of MG, which will help to improve the autonomy of the magnetically manipulated interventional robotic systems.

Objectives Objective response rate (ORR) under mRECIST criteria after transarterial chemoembolization (TACE) is a well-perceived surrogate endpoint of overall survival (OS). However, its optimal time point remains controversial and may be influenced by tumor burden. We aim to investigate the surrogacy of initial/best ORR in relation to tumor burden. Methods A total of 1549 eligible treatment-naïve patients with unresectable hepatocellular carcinoma (HCC), Child-Pugh score ≤ 7, and performance status score ≤ 1 undergoing TACE between January 2010 and May 2016 from 17 academic hospitals were retrospectively analyzed. Based on “six-and-twelve” criteria, tumor burden was graded as low, intermediate, and high if the sum of the maximum tumor diameter and tumor number was ≤ 6, > 6 but ≤ 12, and > 12, respectively. Results Both initial and best ORRs interacted with tumor burden. Initial and best ORRs could equivalently predict and correlate with OS in low (adjusted HR, 2.55 and 2.95, respectively, both p < 0.001; R = 0.84, p = 0.035, and R = 0.97, p = 0.002, respectively) and intermediate strata (adjusted HR, 1.81 and 2.22, respectively, both p < 0.001; R = 0.74, p = 0.023, and R = 0.9, p = 0.002, respectively). For high strata, only best ORR exhibited qualified surrogacy (adjusted HR, 2.61, p < 0.001; R = 0.70, p = 0.035), whereas initial ORR was not significant (adjusted HR, 1.08, p = 0.357; R = 0.22, p = 0.54). Conclusions ORR as surrogacy of OS is associated with tumor burden. For patients with low/intermediate tumor burden, initial ORR should be preferred in its early availability upon similar sensitivity, whereas for patients with high tumor burden, best ORR has optimal sensitivity. Timing of OR assessment should be tailored according to tumor burden. Key Points • This is the first study utilizing individual patient data to comprehensively analyze the surrogacy of ORR with a long follow-up period. • Optimal timing of ORR assessment for predicting survival should be tailored according to tumor burden. • For patients with low and intermediate tumor burden, initial ORR is optimal for its timeliness upon similar sensitivity with best ORR. For patients with high tumor burden, best ORR has optimal sensitivity.

Objective The aim of this study was to assess whether aortic peak wall stress (PWS) and peak wall rupture index (PWRI) were associated with the risk of abdominal aortic aneurysm (AAA) rupture or repair (defined as AAA events) among participants with small AAAs. Methods PWS and PWRI were estimated from computed tomography angiography (CTA) scans of 210 participants with small AAAs (≥ 30 and  ≤ 50 mm) prospectively recruited between 2002 and 2016 from two existing databases. Participants were followed for a median of 2.0 (inter-quartile range 1.9, 2.8) years to record the incidence of AAA events. The associations between PWS and PWRI with AAA events were assessed using Cox proportional hazard analyses. The ability of PWS and PWRI to reclassify the risk of AAA events compared to the initial AAA diameter was examined using net reclassification index (NRI) and classification and regression tree (CART) analysis. Results After adjusting for other risk factors, one standard deviation increase in PWS (hazard ratio, HR, 1.56, 95% confidence intervals, CI 1.19, 2.06; p  = 0.001) and PWRI (HR 1.74, 95% CI 1.29, 2.34; p  < 0.001) were associated with significantly higher risks of AAA events. In the CART analysis, PWRI was identified as the best single predictor of AAA events at a cut-off value of  > 0.562. PWRI, but not PWS, significantly improved the classification of risk of AAA events compared to the initial AAA diameter alone. Conclusion PWS and PWRI predicted the risk of AAA events but only PWRI significantly improved the risk stratification compared to aortic diameter alone. Key Points • Aortic diameter is an imperfect measure of abdominal aortic aneurysm (AAA) rupture risk. • This observational study of 210 participants found that peak wall stress (PWS) and peak wall rupture index (PWRI) predicted the risk of aortic rupture or AAA repair. • PWRI, but not PWS, significantly improved the risk stratification for AAA events compared to aortic diameter alone.

Objectives It remains uncertain which embolization material is best for portal vein embolization (PVE). We investigated the various materials for effectiveness in inducing future liver remnant (FLR) hypertrophy, technical and growth success rates, and complication and resection rates. Methods A systematic review from 1998 to 2019 on embolization materials for PVE was performed on Pubmed, Embase, and Cochrane. FLR growth between the two most commonly used materials was compared in a random effects meta-analysis. In a separate analysis using local data ( n = 52), n- butyl cyanoacrylate (NBCA) was compared with microparticles regarding costs, radiation dose, and procedure time. Results In total, 2896 patients, 61.0 ± 4.0 years of age and 65% male, from 51 papers were included in the analysis. In 61% of the patients, either NBCA or microparticles were used for embolization. The remaining were treated with ethanol, gelfoam, or sclerosing agents. The FLR growth with NBCA was 49.1% ± 29.7 compared to 42.2% ± 40 with microparticles ( p = 0.037). The growth success rate with NBCA vs microparticles was 95.3% vs 90.7% respectively ( p < 0.001). There were no differences in major complications between NBCA and microparticles. In the local analysis, NBCA ( n = 41) entailed shorter procedure time and reduced fluoroscopy time ( p < 0.001), lower radiation exposure ( p < 0.01), and lower material costs ( p < 0.0001) than microparticles ( n = 11). Conclusion PVE with NBCA seems to be the best choice when combining growth of the FLR, procedure time, radiation exposure, and costs. Key Points • The meta-analysis shows that n-butyl cyanoacrylate (NBCA) is superior to microparticles regarding hypertrophy of the future liver remnant, 49.1% ± 29.7 vs 42.2% ± 40.0 (p = 0.037). • There is no significant difference in major complication rates for portal vein embolization using NBCA, 4% (24/681), compared with microparticles, 5% (25/494) (p > 0.05). • Local data shows a shorter procedure time, 215 vs 348 mins from arrival to departure at the interventional radiology unit, and fluoroscopy time, 43 vs 96 mins (p < 0.001), lower radiation dosage, 573 vs 1287 Gycm 2 (p < 0.01), and costs, €816 vs €4233 (p < 0.0001) for NBCA compared to microparticles.

Objectives We proposed a new approach to train deep learning model for aneurysm rupture prediction which only uses a limited amount of labeled data. Method Using segmented aneurysm mask as input, a backbone model was pretrained using a self-supervised method to learn deep embeddings of aneurysm morphology from 947 unlabeled cases of angiographic images. Subsequently, the backbone model was finetuned using 120 labeled cases with known rupture status. Clinical information was integrated with deep embeddings to further improve prediction performance. The proposed model was compared with radiomics and conventional morphology models in prediction performance. An assistive diagnosis system was also developed based on the model and was tested with five neurosurgeons. Result Our method achieved an area under the receiver operating characteristic curve (AUC) of 0.823, outperforming deep learning model trained from scratch (0.787). By integrating with clinical information, the proposed model’s performance was further improved to AUC = 0.853, making the results significantly better than model based on radiomics (AUC = 0.805, p = 0.007) or model based on conventional morphology parameters (AUC = 0.766, p = 0.001). Our model also achieved the highest sensitivity, PPV, NPV, and accuracy among the others. Neurosurgeons’ prediction performance was improved from AUC=0.877 to 0.945 ( p = 0.037) with the assistive diagnosis system. Conclusion Our proposed method could develop competitive deep learning model for rupture prediction using only a limited amount of data. The assistive diagnosis system could be useful for neurosurgeons to predict rupture. Key Points • A self-supervised learning method was proposed to mitigate the data-hungry issue of deep learning, enabling training deep neural network with a limited amount of data. • Using the proposed method, deep embeddings were extracted to represent intracranial aneurysm morphology. Prediction model based on deep embeddings was significantly better than conventional morphology model and radiomics model. • An assistive diagnosis system was developed using deep embeddings for case-based reasoning, which was shown to significantly improve neurosurgeons’ performance to predict rupture.

This paper proposes an operation safety early warning system based on LabView (2014, National Instruments Corporation, Austin, TX, USA) for vascular interventional surgery (VIS) robotic system. The system not only provides intuitive visual feedback information for the surgeon, but also has a safety early warning function. It is well known that blood vessels differ in their ability to withstand stress in different age groups, therefore, the operation safety early warning system based on LabView has a vascular safety threshold function that changes in real-time, which can be oriented to different age groups of patients and a broader applicable scope. In addition, the tracing performance of the slave manipulator to the master manipulator is also an important index for operation safety. Therefore, we also transformed the slave manipulator and integrated the displacement error compensation algorithm in order to improve the tracking ability of the slave manipulator to the master manipulator and reduce master–slave tracking errors. We performed experiments “in vitro” to validate the proposed system. According to previous studies, 0.12 N is the maximum force when the blood vessel wall has been penetrated. Experimental results showed that the proposed operation safety early warning system based on LabView combined with operating force feedback can effectively avoid excessive collisions between the surgical catheter and vessel wall to avoid vascular puncture. The force feedback error of the proposed system is maintained between ±20 mN, which is within the allowable safety range and meets our design requirements. Therefore, the proposed system can ensure the safety of surgery.