CT ​EvaLuation ​by ​ARtificial ​Intelligence ​For ​Atherosclerosis, Stenosis and Vascular ​MorphologY ​(CLARIFY): ​A ​Multi-center, international study

Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.BACKGROUND: Atherosclerosis evaluation by coronary computed tomography angiography (CCTA) is promising for coronary artery disease (CAD) risk stratification, but time consuming and requires high expertise. Artificial Intelligence (AI) applied to CCTA for comprehensive CAD assessment may overcome these limitations. We hypothesized AI aided analysis allows for rapid, accurate evaluation of vessel morphology and stenosis. METHODS: This was a multi-site study of 232 patients undergoing CCTA. Studies were analyzed by FDA-cleared software service that performs AI-driven coronary artery segmentation and labeling, lumen and vessel wall determination, plaque quantification and characterization with comparison to ground truth of consensus by three L3 readers. CCTAs were analyzed for: % maximal diameter stenosis, plaque volume and composition, presence of high-risk plaque and Coronary Artery Disease Reporting & Data System (CAD-RADS) category. RESULTS: AI performance was excellent for accuracy, sensitivity, specificity, positive predictive value and negative predictive value as follows: >70% stenosis: 99.7%, 90.9%, 99.8%, 93.3%, 99.9%, respectively; >50% stenosis: 94.8%, 80.0%, 97.0, 80.0%, 97.0%, respectively. Bland-Altman plots depict agreement between expert reader and AI determined maximal diameter stenosis for per-vessel (mean difference -0.8%; 95% CI 13.8% to -15.3%) and per-patient (mean difference -2.3%; 95% CI 15.8% to -20.4%). L3 and AI agreed within one CAD-RADS category in 228/232 (98.3%) exams per-patient and 923/924 (99.9%) vessels on a per-vessel basis. There was a wide range of atherosclerosis in the coronary artery territories assessed by AI when stratified by CAD-RADS distribution. CONCLUSIONS: AI-aided approach to CCTA interpretation determines coronary stenosis and CAD-RADS category in close agreement with consensus of L3 expert readers. There was a wide range of atherosclerosis identified through AI.proofpublishe

Patient education for individuals with Interstitial Lung Disease: A scoping review. [version 1; peer review: 1 approved, 2 approved with reservations]

Objectives Interstitial Lung Disease (ILD) is a severe and rapidly progressing disease with a high fatality rate. Patient education (PE) has been demonstrated to promote long-term adherence to exercise and lifestyle improvements by assisting patients in developing self-management techniques. Our scoping review's goal was to chart out the prevailing level of research about the content, processes, and effectiveness of PE for patients with ILD. Methods The relevant databases were searched using the rules provided by Arksey and O'Malley in 2005 and the Joanna Briggs Institute reviewers' manual 2015: an approach for JBI scoping reviews. Individuals with ILD, published in English between the years of inception and 2020, and describing PE administered by various healthcare practitioners were among the 355 studies found and reviewed. Thirteen studies met these criteria. Results PE delivery process, delivery techniques, quality of life assessments, common PE themes, and healthcare professional participation were all recognized and cataloged. Conclusion Despite the fact that healthcare professionals (physicians, nurses, and physiotherapists) provide PE to patients with ILD regularly, the PE provided varies greatly (contents of PE, process of delivery and delivery techniques). During the scoping review, a significant variation in the themes was addressed. They could not provide any evidence-based specific recommendations for all healthcare practitioners due to the studies' heterogeneity and lack of effectiveness measures

a CLARIFY trial sub-study

Publisher Copyright: © 2022Background: The difference between expert level (L3) reader and artificial intelligence (AI) performance for quantifying coronary plaque and plaque components is unknown. Objective: This study evaluates the interobserver variability among expert readers for quantifying the volume of coronary plaque and plaque components on coronary computed tomographic angiography (CCTA) using an artificial intelligence enabled quantitative CCTA analysis software as a reference (AI-QCT). Methods: This study uses CCTA imaging obtained from 232 patients enrolled in the CLARIFY (CT EvaLuation by ARtificial Intelligence For Atherosclerosis, Stenosis and Vascular MorphologY) study. Readers quantified overall plaque volume and the % breakdown of noncalcified plaque (NCP) and calcified plaque (CP) on a per vessel basis. Readers categorized high risk plaque (HRP) based on the presence of low-attenuation-noncalcified plaque (LA-NCP) and positive remodeling (PR; ≥1.10). All CCTAs were analyzed by an FDA-cleared software service that performs AI-driven plaque characterization and quantification (AI-QCT) for comparison to L3 readers. Reader generated analyses were compared among readers and to AI-QCT generated analyses. Results: When evaluating plaque volume on a per vessel basis, expert readers achieved moderate to high interobserver consistency with an intra-class correlation coefficient of 0.78 for a single reader score and 0.91 for mean scores. There was a moderate trend between readers 1, 2, and 3 and AI with spearman coefficients of 0.70, 0.68 and 0.74, respectively. There was high discordance between readers and AI plaque component analyses. When quantifying %NCP v. %CP, readers 1, 2, and 3 achieved a weighted kappa coefficient of 0.23, 0.34 and 0.24, respectively, compared to AI with a spearman coefficient of 0.38, 0.51, and 0.60, respectively. The intra-class correlation coefficient among readers for plaque composition assessment was 0.68. With respect to HRP, readers 1, 2, and 3 achieved a weighted kappa coefficient of 0.22, 0.26, and 0.17, respectively, and a spearman coefficient of 0.36, 0.35, and 0.44, respectively. Conclusion: Expert readers performed moderately well quantifying total plaque volumes with high consistency. However, there was both significant interobserver variability and high discordance with AI-QCT when quantifying plaque composition.publishersversionpublishe

Interobserver Variability Among Expert Readers Quantifying Plaque Volume and Plaque Characteristics on Coronary CT Angiography: A CLARIFY Trial Sub-Study

Background: The difference between expert level (L3) reader and artificial intelligence (AI) performance for quantifying coronary plaque and plaque components is unknown. Objective: This study evaluates the interobserver variability among expert readers for quantifying the volume of coronary plaque and plaque components on coronary computed tomographic angiography (CCTA) using an artificial intelligence enabled quantitative CCTA analysis software as a reference (AI-QCT). Methods: This study uses CCTA imaging obtained from 232 patients enrolled in the CLARIFY (CT EvaLuation by ARtificial Intelligence For Atherosclerosis, Stenosis and Vascular MorphologY) study. Readers quantified overall plaque volume and the % breakdown of noncalcified plaque (NCP) and calcified plaque (CP) on a per vessel basis. Readers categorized high risk plaque (HRP) based on the presence of low-attenuation-noncalcified plaque (LA-NCP) and positive remodeling (PR; ≥1.10). All CCTAs were analyzed by an FDA-cleared software service that performs AI-driven plaque characterization and quantification (AI-QCT) for comparison to L3 readers. Reader generated analyses were compared among readers and to AI-QCT generated analyses. Results: When evaluating plaque volume on a per vessel basis, expert readers achieved moderate to high interobserver consistency with an intra-class correlation coefficient of 0.78 for a single reader score and 0.91 for mean scores. There was a moderate trend between readers 1, 2, and 3 and AI with spearman coefficients of 0.70, 0.68 and 0.74, respectively. There was high discordance between readers and AI plaque component analyses. When quantifying %NCP v. %CP, readers 1, 2, and 3 achieved a weighted kappa coefficient of 0.23, 0.34 and 0.24, respectively, compared to AI with a spearman coefficient of 0.38, 0.51, and 0.60, respectively. The intra-class correlation coefficient among readers for plaque composition assessment was 0.68. With respect to HRP, readers 1, 2, and 3 achieved a weighted kappa coefficient of 0.22, 0.26, and 0.17, respectively, and a spearman coefficient of 0.36, 0.35, and 0.44, respectively. Conclusion: Expert readers performed moderately well quantifying total plaque volumes with high consistency. However, there was both significant interobserver variability and high discordance with AI-QCT when quantifying plaque composition

Design and integration of current-mode on -chip interconnect signaling in nanometer technologies

As feature sizes progress into nanometer realms, on-chip interconnects play an increasing role in the overall performance and power consumption of high-performance integrated circuits. Three novel on-chip interconnect communication techniques are presented; (i) differential current-transfer sensing, (ii) multi-level current signaling, (iii) swing-limited interconnect communication; silicon implementation and an integration methodology in conventional CAD flow are proposed. The differential current-transfer sense amplifier ( DCTSA), is a new static-power mitigated receiver for conventional differential current-sensing. It is compared with the conventional differential current sense amplifier (DCSA) and standard repeaters. Results in 130nm, 65nm and 45nm show that DCTSA outperforms repeaters for wires with activity of 50% and higher and length longer than 4mm. The multi-level current signaling technique with novel driver and receiver circuits is proposed which encode two bits on one interconnect using current levels. This multi-level system is compared with conventional repeaters for process technologies including 130nm, 90nm, 65nm and 45nm. The impact of process induced parameter variations was analyzed and a process tolerant driver was presented. Compared to repeaters, multi-level current signaling is attractive for wires longer than 4mm and with activity factors more than 40%. A swing-limited interconnect current-mode technique is proposed with a novel low-swing receiver circuit, which achieves energy efficient transmission for on-chip interconnects over repeaters. This swing-limited interconnect system is compared with repeaters in a 65nm industrial CMOS technology. With this signaling technique there is a 56% energy reduction and 21% delay reduction compared to repeaters. Delay savings increase by 8% at supply of 1.4v at iso energy. A total area savings of 86% is obtained in device width with this technique. A methodology and tool for the integration of current-mode interconnect techniques into conventional design flow was presented. The methodology and tool called Network-on-Chip Interconnect Calculator provides results in terms of delay and power for interconnects, and illustrates the effects of delay and power on input parameters in plots. It hides the circuit level details of the proposed current-mode techniques and provides a simple library that can be used by conventional CAD flow. The proposed signaling techniques along with conventional repeater insertion method have been implemented in silicon in IBM 130nm technology through MOSIS for different wirelengths showing proof-of-concept. The test chip is fully functional and the measurement results closely followed the simulated results, thus verifying the validity of the proposed techniques and their benefit over existing techniques for on-chip interconnects

Shining a Light on Hidden Thyroids: A Case Exploring the Potential of Technetium Imaging for Lingual Thyroid Diagnosis

Ectopic thyroid, the presence of thyroid tissue in locations other than the normal anterior neck region between the second and fourth tracheal cartilages, is the most common form of thyroid dysgenesis. A 32-year-old female patient sought medical attention at the Otolaryngology Department with a foreign body sensation in her throat. To ensure an accurate diagnosis, hereby, the authors conducted a comprehensive diagnostic work-up, which included Technetium-99 (Tc-99m) scanning. Remarkably, the scanning results revealed radiotracer uptake in the base of the tongue while indicating an absence of uptake in the thyroid bed. By shedding light on present captivating case, the present report offers valuable insights into the usage of Technetium imaging in diagnosing doubtful Lingual Thyroid (LT) cases