Establishing the basic knowledge, methodology, and technology for a framework for the continuous decoding of hand/arm movement intention was the aim of the ERC-funded project “Feel Your Reach”. In this work, we review the studies and methods we performed and implemented in the last 6 years, which build the basis for enabling severely paralyzed people to non-invasively control a robotic arm in real-time from electroencephalogram (EEG). In detail, we investigated goal-directed movement detection, decoding of executed and attempted movement trajectories, grasping correlates, error processing, and kinesthetic feedback. Although we have tested some of our approaches already with the target populations, we still need to transfer the “Feel Your Reach” framework to people with cervical spinal cord injury and evaluate the decoders’ performance while participants attempt to perform upper-limb movements. While on the one hand, we made major progress towards this ambitious goal, we also critically discuss current limitations.

/pdf/feel-your-reach-an-eeg-based-framework-to-continuously-1vhflrsq.pdf

Feel Your Reach: An EEG-Based Framework to Continuously Detect Goal-Directed Movements and Error Processing to Gate Kinesthetic Feedback Informed Artificial Arm Control

Transcatheter aortic valve implantation (TAVI) performed using femoral arterial access is now a guideline recommended treatment for severe calcific aortic stenosis (AS) in elderly patients. Technological advancements and procedural refinements have focused on making TAVI simpler, safer, more effective and durable. Myval (Meril Lifesciences) is a new generation balloon-expandable transcatheter heart valve (THV) developed in India that possesses novel features to improve deliverability and aid precise deployment. Following the first-in-human study, Myval was approved in India for commercial implantation in October 2018 and was subsequently given a CE mark in April 2019. This article reviews the science, technology and up-to-date clinical evidence for the Myval THV.

/pdf/myval-a-novel-transcatheter-heart-valve-for-the-treatment-of-1afg6m2x.pdf

Myval: A Novel Transcatheter Heart Valve for the Treatment of Severe Aortic Stenosis

Transcatheter mitral valve replacement (TMVR) is a novel and evolving field dedicated to addressing the therapeutic challenges posed by patients at high surgical risk with mitral valve disease. TMVR can be categorized into two distinct fields based on the type of device and its specific indications: TMVR with transcatheter aortic valves (TAV) and TMVR with dedicated devices. Similar to aortic stenosis, TMVR with TAV requires a rigid support structure to secure the valve in place. As a result, it is indicated for patients with failing bioprothesis or surgical rings or mitral valve disease associated with severe mitral annular calcification (MAC), which furnishes the necessary foundation for valve anchoring. While TMVR with TAV has shown promising outcomes in valve-in-valve procedures, its effectiveness remains more contentious in valve-in-ring or valve-in-MAC procedures. Conversely, TMVR with dedicated devices seeks to address native mitral regurgitation, whether accompanied by MAC or not, providing an alternative to Transcatheter Edge-to-Edge Repair (TEER) when TEER is not feasible or expected to yield unsatisfactory results. This emerging field is gradually surmounting technical challenges, including anchoring a valve in a non-calcified annulus and transitioning from the transapical route to the transeptal approach. Numerous devices are presently undergoing clinical trials. This review aims to furnish an overview of the supporting evidence for TMVR using TAV in each specific indication (valve-in-valve, valve-in-ring, valve-in-MAC). Subsequently, we will discuss the anticipated benefits of TMVR with dedicated devices over TEER, summarize the characteristics and clinical results of TMVR systems currently under investigation, and outline future prospects in this field.

Transcatheter Mitral Valve Replacement Using Transcatheter Aortic Valve or Dedicated Devices: Current Evidence and Future Prospects

Standard microarchitectural analysis of bone using micro-computed tomography produces a large number of parameters that quantify the structure of the trabecular network. Analyses that perform statistical tests on many parameters are at elevated risk of making Type I errors. However, when multiple testing correction procedures are applied, the risk of Type II errors is elevated if the parameters being tested are strongly correlated. In this article, we argue that four commonly used trabecular microarchitectural parameters (thickness, separation, number, and bone volume fraction) are interdependent and describe only two independent properties of the trabecular network. We first derive theoretical relationships between the parameters based on their geometric definitions. Then, we analyze these relationships with an aggregated in vivo dataset with 2987 images from 1434 participants and a synthetically generated dataset with 144 images using principal component analysis (PCA) and linear regression analysis. With PCA, when trabecular thickness, separation, number, and bone volume fraction are combined, we find that 92 % to 97 % of the total variance in the data is explained by the first two principal components. With linear regressions, we find high coefficients of determination (0.827–0.994) and fitted coefficients within expected ranges. These findings suggest that to maximize statistical power in future studies, only two of trabecular thickness, separation, number and bone volume fraction should be used for statistical testing. 

Statistical investigation of interdependence of trabecular microarchitectural parameters from micro-computed tomography

Automatic bone segmentation is a fundamental task supporting various clinical practices. Conventional methods in this field rely heavily on dense annotations, which incurs substantial labeling labor and expense. Recent efforts have been made to reduce the labeling workload through semi-supervised and weakly supervised learning. However, methods under these two paradigms usually assume that all objects of interest e.g., bones, are covered by labels. In this work, we explore a less studied problem setting that assumes only partially labeled bone CT data. To tackle the supervision bias brought by incomplete annotations, we design a three-stage learning method that automatically detects unlabeled bones while being robust to their various shape. Extensive experiments are conducted on the curated dataset to test the proposed method and promising performance is observed. To the best of our knowledge, this is the first work on the partially supervised bone segmentation problem.

Segment Any Bone in CT with Partial Supervision

Objective: To evaluate the safety and efficacy of transcatheter aortic valve implantation (TAVI) with the novel Prizvalve® system in treating severe aortic stenosis. Methods: This is a single-center, prospective, single-arm, observational study. A total of 11 patients with severe aortic stenosis with high risk or inappropriate for conventional surgical aortic valve replacement (SAVR) were included, and TAVI was achieved with the Prizvalve® system between March 2021 and May 2021 in West China Hospital. Transthoracic echocardiography (TTE) was performed immediately after prosthesis implantation to evaluate mean transaortic gradient and maximal transaortic velocity. The device success rate was calculated, which was defined as (1) the device being delivered via the access, deployed, implanted and withdrawn, (2) mean transaortic gradient<20 mmHg (1 mmHg=0.133 kPa) or a maximal transaortic velocity<3 m/s post TAVI, and without severe aortic regurgitation or paravalvular leak post TAVI. TTE was performed at 30 days after the surgery, and all-cause mortality as well as the major cardiovascular adverse events (including acute myocardial infarction, disabling hemorrhagic or ischemic stroke) up to 30 days post TAVI were analyzed. Results: The age of 11 included patients were (78.1±6.3) years, with 8 males. A total of 10 patients were with NYHA functional class Ⅲ or Ⅳ. Devices were delivered via the access, deployed, implanted and withdrawn successfully in all patients. Post-implant mean transaortic gradient was (7.55±4.08) mmHg and maximal transaortic velocity was (1.78±0.44) m/s, and both decreased significantly as compared to baseline levels (both P<0.05). No severe aortic regurgitation or paravalvular leak was observed post TAVI. Device success was achieved in all the 11 patients. No patient died or experienced major cardiovascular adverse events up to 30 days post TAVI. Mean transaortic gradient was (9.45±5.07) mmHg and maximal transaortic velocity was (2.05±0.42) m/s at 30 days post TAVI, which were similar as the values measured immediately post TAVI (both P>0.05). Conclusions: TAVI with the Prizvalve® system is a feasible and relatively safe procedure for patients with severe aortic stenosis and at high risk or inappropriate for SAVR. Further clinical studies could be launched to obtain more clinical experience with Prizvalve® system.

[Preliminary clinical experience of the novel transcatheter aortic valve system Prizvalve® for the treatment of severe aortic stenosis].

A prospective, single-center, single-arm, and open-design study was performed to evaluate the feasibility and safety of transseptal transcatheter mitral valve replacement in the treatment of severe mitral regurgitation. Patients with symptomatic moderate-severe or severe mitral regurgitation at high-surgical risk and anatomically appropriate for the HighLife transseptal mitral valve replacement (TSMVR) system in West China Hospital, Sichuan University from December 2021 to August 2022 were enrolled. Four patients (1 male and 3 females) with severe mitral regurgitation were included, with a median age of 68.5 (64.0-77.0) years and a median Society of Thoracic Surgeons (STS) score of 8.1% (6.4%-8.9%). Technical success was achieved in all the patients. There was no residual mitral regurgitation, paravalvular leakage, or left ventricular outflow tract obstruction. Three major cardiovascular and cerebrovascular adverse events occurred within 30 days after the procedure, including ventricular tachycardia, iatrogenic atrial septal defect closure, and heart failure readmission. The current study preliminarily demonstrates that transcatheter mitral valve replacement using the HighLife system via the transseptal approach for severe mitral regurgitation is feasible and relatively safe.

[Feasibility and safety of transseptal transcatheter mitral valve replacement for severe mitral regurgitation].

Objectives: To evaluate the feasibility and preliminary clinical results of transcatheter pulmonary valve replacement (TPVR) with the domestically-produced balloon-expandable Prizvalve system. Methods: This is a prospective single-center observational study. Patients with postoperative right ventricular outflow tract (RVOT) dysfunction, who were admitted to West China Hospital of Sichuan University from September 2021 to March 2023 and deemed anatomically suitable for TPVR with balloon-expandable valve, were included. Clinical, imaging, procedural and follow-up data were analyzed. The immediate procedural results were evaluated by clinical implant success rate, which is defined as successful valve implantation with echocardiography-assessed pulmonary regurgitation<moderate and peak trans-pulmonary pressure gradient<40 mmHg (1 mmHg=0.133 kPa). Results: A total of 5 patients were included, with 4 males, aged 14 to 37 years. The initial diagnosis included Tetralogy of Fallot (2 cases), truncus arteriosus (1 case), pulmonary atresia (1 case) and subaortic stenosis (1 case, prior Ross procedure). Four patients underwent RVOT reconstruction with homograft or artificial conduit, and one patient was treated with trans-annular patch technique. The indications of TPVR included RVOT obstruction and regurgitation (3 cases), isolated obstruction (1 case), and isolated regurgitation (1 case). Of the 4 patients with varying severity of ROVT obstruction, the average preprocedural peak jet velocity of RVOT was 3.5 m/s, and the average peak pressure gradient was 50.0 mmHg. Except for one patient, who had previously been implanted with a covered Cheatham-Platinum (CP) stent due to severe stenosis of the main pulmonary artery, other patients underwent pre-stenting with a covered CP stent before TPVR. Clinical implant success was achieved in all of the 5 patients, and there was no serious periprocedural complications. The average trans-pulmonary peak jet velocity and peak pressure gradient derived from postprocedural echocardiography was 2.3 m/s and 21.2 mmHg, respectively. All patients experienced significant symptom relief after the procedure. All patients completed 3-month follow-up, and 4 completed 6-month follow-up. There was no case of infectious endocarditis during follow-up. All patients were graded as NYHA functional class one at the latest follow-up. Conclusions: TPVR using the domestically-produced balloon-expandable Prizvalve system is safe and feasible for the treatment of patients with post-surgical RVOT dysfunction and suitable landing-zone anatomy. The safety, effectiveness, and long-term valve durability of the Prizvalve system deserve further research.目的： 初步探讨使用国产球囊扩张式瓣膜Prizvalve进行经导管肺动脉瓣置换（TPVR）的可行性及临床效果。 方法： 本研究为单中心前瞻性单组观察性研究，连续纳入2021年9月至2023年3月于四川大学华西医院就诊、经评估适合通过球囊扩张式瓣膜进行TPVR治疗的外科术后右心室流出道功能障碍患者，均使用Prizvalve进行TPVR治疗。记录患者的临床、影像和手术资料、手术效果及随访结果。即刻效果主要通过临床植入成功率评价，定义为瓣膜顺利植入且术后超声心动图评估的肺动脉瓣反流程度在中度以下、肺动脉瓣峰值压差<40 mmHg（1 mmHg=0.133 kPa）。 结果： 共纳入5例患者，其中4例男性，年龄14~37岁。初始诊断包括法洛四联症（2例）、永存动脉干（1例）、肺动脉闭锁（1例）和主动脉瓣下狭窄（1例，既往行Ross手术）；4例通过同种或人工管道行右心室流出道重建，1例通过跨瓣补片技术重建右心室流出道。干预指征包括右心室流出道-肺动脉狭窄合并反流（3例）、单纯狭窄（1例）及单纯反流（1例）。4例存在右心室流出道-肺动脉狭窄的患者术前平均右心室流出道峰值流速为3.5 m/s，平均右心室流出道峰值压差为50.0 mmHg。除1例患者既往因主肺动脉严重狭窄已植入覆膜Cheatham-Platinum（CP）支架外，其余患者在术中均先预植入覆膜CP支架再进行瓣膜植入。5例患者均临床植入成功，围术期无严重并发症出现。术后超声心动图测量平均右心室流出道-肺动脉峰值流速为2.3 m/s，平均右心室流出道-肺动脉峰值压差为21.2 mmHg。术后患者症状均明显改善，所有患者均已完成3个月随访，其中4例已完成6个月随访，随访期内无感染性心内膜炎发生，最近一次随访时评估纽约心脏病协会（NYHA）心功能均为1级。 结论： 对于解剖条件合适的外科术后右心室流出道-肺动脉功能障碍患者，通过国产球囊扩张式短瓣膜Prizvalve进行TPVR是可行的治疗方案，安全性、有效性和长期耐久性数据值得进一步研究。. 

[Preliminary experience of transcatheter pulmonary valve replacement using domestic balloon-expandable valve].

Importance Fragility fractures are a public health problem. Over 70% of women having fractures have osteopenia or normal BMD, but they remain unidentified and untreated because the definition of osteoporosis, a bone mineral density (BMD) T-Score [≤] -2.5SD, is often used to signal bone fragility.

Objective As deep learning facilitates investigation of bones multi-level hierarchical structure and soft tissue, we tested whether this approach might better identify women at risk of fracture before fracture.

Design We pooled data from three French and Swiss prospective population-based cohorts (OFELY, QUALYOR, GERICO) that collected clinical risk factors for fracture, areal BMD and distal radius measurements with high resolution peripheral quantitative tomography (HRpQCT). Using only three-dimensional images of the distal radius, ulna and soft tissue acquired by HRpQCT, an algorithm, a Structural Fragility Score-Artificial Intelligence (SFS-AI), was trained to distinguish 277 women having fractures from 1401 remaining fracture-free during 5 years and then was tested in a validation cohort of 422 women.

Setting European postmenopausal women

Participants We have studied postmenopausal women considered as representative of the general population, who were followed for a median 9.4 years in OFELY, 5.4 years in QUALYOR and 5.7 years in GERICO.

Main outcome and measure All types of incident fragility fractures

Results We used data from 2666 postmenopausal women, with age range of 42-94. In women [≥] 65 years having All Fragility Fractures or Major Fragility Fractures, SFS-AI generated an AUC of 66-70%, sensitivities of 60-68% and specificity of 71%. Sensitivities were greater than achieved by the fracture risk assessment (FRAX) with BMD or BMD (6.7-26.7%) with lower specificities than these diagnostics (~95%).

Conclusion The SFS-AI is a holistic surrogate of fracture risk that pre-emptively identifies most women needing prompt treatment to avert a first fracture.

/pdf/deep-learning-using-high-resolution-images-of-forearm-17ii05b8.pdf

Deep Learning Using High-Resolution Images of Forearm Predicts Fracture

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Y. Peng

Author Tools

Chat about Author

Papers

[Preliminary clinical experience of the novel transcatheter aortic valve system Prizvalve® for the treatment of severe aortic stenosis].

[Feasibility and safety of transseptal transcatheter mitral valve replacement for severe mitral regurgitation].

[Preliminary experience of transcatheter pulmonary valve replacement using domestic balloon-expandable valve].

Deep Learning Using High-Resolution Images of Forearm Predicts Fracture