Research priorities for the secondary prevention and management of acute rheumatic fever and rheumatic heart disease: a National Heart, Lung, and Blood Institute workshop report.

Secondary prevention of acute rheumatic fever (ARF) and rheumatic heart disease (RHD) involves continuous antimicrobial prophylaxis among affected individuals and is recognised as a cornerstone of public health programmes that address these conditions. However, several important scientific issues around the secondary prevention paradigm remain unresolved. This report details research priorities for secondary prevention that were developed as part of a workshop convened by the US National Heart, Lung, and Blood Institute in November 2021. These span basic, translational, clinical and population science research disciplines and are built on four pillars. First, we need a better understanding of RHD epidemiology to guide programmes, policies, and clinical and public health practice. Second, we need better strategies to find and diagnose people affected by ARF and RHD. Third, we urgently need better tools to manage acute RF and slow the progression of RHD. Fourth, new and existing technologies for these conditions need to be better integrated into healthcare systems. We intend for this document to be a reference point for research organisations and research sponsors interested in contributing to the growing scientific community focused on RHD prevention and control.

Improving Early Identification of Significant Weight Loss Using Clinical Decision Support System in Lung Cancer Radiation Therapy.

PURPOSE: Early identification of patients who may be at high risk of significant weight loss (SWL) is important for timely clinical intervention in lung cancer radiotherapy (RT). A clinical decision support system (CDSS) for SWL prediction was implemented within the routine clinical workflow and assessed on a prospective cohort of patients. MATERIALS AND METHODS: CDSS incorporated a machine learning prediction model on the basis of radiomics and dosiomics image features and was connected to a web-based dashboard for streamlined patient enrollment, feature extraction, SWL prediction, and physicians' evaluation processes. Patients with lung cancer (N = 37) treated with definitive RT without prior RT were prospectively enrolled in the study. Radiomics and dosiomics features were extracted from CT and 3D dose volume, and SWL probability (≥ 0.5 considered as SWL) was predicted. Two physicians predicted whether the patient would have SWL before and after reviewing the CDSS prediction. The physician's prediction performance without and with CDSS and prediction changes before and after using CDSS were compared. RESULTS: CDSS showed significantly better prediction accuracy than physicians (0.73 v 0.54) with higher specificity (0.81 v 0.50) but with lower sensitivity (0.55 v 0.64). Physicians changed their original prediction after reviewing CDSS prediction for four cases (three correctly and one incorrectly), for all of which CDSS prediction was correct. Physicians' prediction was improved with CDSS in accuracy (0.54-0.59), sensitivity (0.64-0.73), specificity (0.50-0.54), positive predictive value (0.35-0.40), and negative predictive value (0.76-0.82). CONCLUSION: Machine learning-based CDSS showed the potential to improve SWL prediction in lung cancer RT. More investigation on a larger patient cohort is needed to properly interpret CDSS prediction performance and its benefit in clinical decision making.

Rapid administration of undiluted intravenous levetiracetam.

OBJECTIVE: Operational delays have the potential to lead to suboptimal time to seizure control during status epilepticus. Levetiracetam (LEV) is an urgent control antiepileptic medication that offers relative lack of adverse effects and ease of monitoring. There are limited data published demonstrating safety and tolerability of undiluted rapid intravenous (IV) push of LEV in doses of 1000 mg or less. The purpose of this study was to evaluate the safety of IV push administration of LEV doses up to 4500 mg. METHODS: This is a retrospective, observational, cohort analysis of adult patients who received at least one dose of undiluted IV push LEV from October 15, 2019 to August 31, 2020 at a large academic medical center in Phoenix, Arizona. Outcomes of interest include safety and tolerability of rapid administration of undiluted LEV. RESULTS: There were 953 unique patients included during the study period. LEV was a new medication for witnessed or suspected seizure in 51.9% of patients, and 40.7% of patients had a documented history of epilepsy or seizure disorder. There were 8561 undiluted IV push LEV doses administered, 3674 (42.9%) of which were greater than 1000 mg. LEV was administered most often through a peripheral IV (79.1%). There were 12 patients with documented adverse drug events during the study period, with four potentially directly related to IV push LEV administration. These events were limited to local injection site reactions and included redness, burning, and loss of a peripheral IV line. SIGNIFICANCE: Rapid IV administration of undiluted LEV is both safe and tolerable in doses of up to 4500 mg, allowing for rapid drug administration, which is paramount during neurologic emergencies.

Multi-view radiomics and dosiomics analysis with machine learning for predicting acute-phase weight loss in lung cancer patients treated with radiotherapy.

We propose a multi-view data analysis approach using radiomics and dosiomics (R&D) texture features for predicting acute-phase weight loss (WL) in lung cancer radiotherapy. Baseline weight of 388 patients who underwent intensity modulated radiation therapy (IMRT) was measured between one month prior to and one week after the start of IMRT. Weight change between one week and two months after the commencement of IMRT was analyzed, and dichotomized at 5% WL. Each patient had a planning CT and contours of gross tumor volume (GTV) and esophagus (ESO). A total of 355 features including clinical parameter (CP), GTV and ESO (GTV&ESO) dose-volume histogram (DVH), GTV radiomics, and GTV&ESO dosiomics features were extracted. R&D features were categorized as first- (L1), second- (L2), higher-order (L3) statistics, and three combined groups, L1 + L2, L2 + L3 and L1 + L2 + L3. Multi-view texture analysis was performed to identify optimal R&D input features. In the training set (194 earlier patients), feature selection was performed using Boruta algorithm followed by collinearity removal based on variance inflation factor. Machine-learning models were developed using Laplacian kernel support vector machine (lpSVM), deep neural network (DNN) and their averaged ensemble classifiers. Prediction performance was tested on an independent test set (194 more recent patients), and compared among seven different input conditions: CP-only, DVH-only, R&D-only, DVH + CP, R&D + CP, R&D + DVH and R&D + DVH + CP. Combined GTV L1 + L2 + L3 radiomics and GTV&ESO L3 dosiomics were identified as optimal input features, which achieved the best performance with an ensemble classifier (AUC = 0.710), having statistically significantly higher predictability compared with DVH and/or CP features (p < 0.05). When this performance was compared to that with full R&D-only features which reflect traditional single-view data, there was a statistically significant difference (p < 0.05). Using optimized multi-view R&D input features is beneficial for predicting early WL in lung cancer radiotherapy, leading to improved performance compared to using conventional DVH and/or CP features.

Utility of a Clinical Decision Support System in Weight Loss Prediction After Head and Neck Cancer Radiotherapy.

PURPOSE: To evaluate the utility of a clinical decision support system (CDSS) using a weight loss prediction model. METHODS: A prediction model for significant weight loss (loss of greater than or equal to 7.5% of body mass at 3-month post radiotherapy) was created with clinical, dosimetric, and radiomics predictors from 63 patients in an independent training data set (accuracy, 0.78; area under the curve [AUC], 0.81) using least absolute shrinkage and selection operator logistic regression. Four physicians with varying experience levels were then recruited to evaluate 100 patients in an independent validation data set of head and neck cancer twice (ie, a pre-post design): first without and then with the aid of a CDSS derived from the prediction model. At both evaluations, physicians were asked to predict the development (yes/no) and probability of significant weight loss for each patient on the basis of patient characteristics, including pretreatment dysphagia and weight loss and information from the treatment plan. At the second evaluation, physicians were also provided with the prediction model's results for weight loss probability. Physicians' predictions were compared with actual weight loss, and accuracy and AUC were investigated between the two evaluations. RESULTS: The mean accuracy of the physicians' ability to identify patients who will experience significant weight loss (yes/no) increased from 0.58 (range, 0.47 to 0.63) to 0.63 (range, 0.58 to 0.72) with the CDSS ( P = .06). The AUC of weight loss probability predicted by physicians significantly increased from 0.56 (range, 0.46 to 0.64) to 0.69 (range, 0.63 to 0.73) with the aid of the CDSS ( P < .05). Specifically, more improvement was observed among less-experienced physicians ( P < .01). CONCLUSION: Our preliminary results demonstrate that physicians' decisions may be improved by a weight loss CDSS model, especially among less-experienced physicians. Additional study with a larger cohort of patients and more participating physicians is thus warranted for understanding the usefulness of CDSSs.

The Value of Clinical Needs Assessments for Point-of-Care Diagnostics.

Most entrepreneurial ventures fail long before the core technology can be brought to the marketplace because of disconnects in performance and usability measures such as accuracy, cost, complexity, assay stability, and time requirements between technology developers' specifications and needs of the end-users. By going through a clinical needs assessment (CNA) process, developers will gain vital information and a clear focus that will help minimize the risks associated with the development of new technologies available for use within the health care system. This article summarizes best practices of the principal investigators of the National Institute of Biomedical Imaging and Bioengineering point-of-care (POC) centers within the National Institute of Biomedical Imaging and Bioengineering POC Technologies Research Network. Clinical needs assessments are particularly important for product development areas that do not sufficiently benefit from traditional market research, such as grant-funded research and development, new product lines using cutting-edge technologies developed in start-up companies, and products developed through product development partnerships for low-resource settings. The objectives of this article were to (1) highlight the importance of CNAs for development of POC devices, (2) discuss methods applied by POC Technologies Research Network for assessing clinical needs, and (3) provide a road map for future CNAs.

Bioengineering and Imaging Research Opportunities Workshop V: a white paper on imaging and characterizing structure and function in native and engineered tissues.

The fifth Bioengineering and Image Research Opportunities Workshop (BIROW V) was held on January 18-19, 2008. As with previous BIROW meetings, the purpose of BIROW V was to identify and characterize research and engineering opportunities in biomedical engineering and imaging. The topic of this BIROW meeting was Imaging and Characterizing Structure and Function in Native and Engineered Tissues. Under this topic, four areas were explored in depth: (1) Heterogeneous single-cell measurements and their integration into tissue and organism models; (2) Functional, molecular and structural imaging of engineered tissue in vitro and in vivo; (3) New technologies for characterizing cells and tissues in situ; (4) Imaging for targeted cell, gene and drug delivery.

Bioengineering and Imaging Research Opportunities Workshop V: a summary on Imaging and Characterizing Structure and Function in Native and Engineered Tissues.

The Fifth Bioengineering and Imaging Research Opportunities Workshop (BIROW V) was held on January 18-19, 2008. As with previous BIROW meetings, the purpose of BIROW V was to identify and characterize research and engineering opportunities in biomedical engineering and imaging. The topic of this BIROW meeting was Imaging and Characterizing Structure and Function in Native and Engineered Tissues. Under this topic, four areas were explored in depth:1) Heterogeneous single-cell measurements and their integration into tissue and organism models;2) Functional, molecular, and structural imaging of engineered tissue in vitro and in vivo;3) New technologies for characterizing cells and tissues in situ;4) Imaging for targeted cell, gene, and drug delivery.

Bioengineering and imaging research opportunities workshop V: a summary.

The fifth Bioengineering and Imaging Research Opportunities Workshop (BIROW V) was held on January 18-19, 2008. As with previous BIROW meetings, the purpose of BIROW V was to identify and characterize research and engineering opportunities in biomedical engineering and imaging. The topic of this BIROW meeting was Imaging and Characterizing Structure and Function in Native and Engineered Tissues. Under this topic, four areas were explored in depth: (1) Heterogeneous single-cell measurements and their integration into tissue and organism models; (2) Functional, molecular, and structural imaging of engineered tissue in vitro and in vivo; (3) New technologies for characterizing cells and tissues in situ; (4) Imaging for targeted cell, gene, and drug delivery.

Challenges in image-guided therapy system design.

System development for image-guided therapy (IGT), or image-guided interventions (IGI), continues to be an area of active interest across academic and industry groups. This is an emerging field that is growing rapidly: major academic institutions and medical device manufacturers have produced IGT technologies that are in routine clinical use, dozens of high-impact publications are published in well regarded journals each year, and several small companies have successfully commercialized sophisticated IGT systems. In meetings between IGT investigators over the last two years, a consensus has emerged that several key areas must be addressed collaboratively by the community to reach the next level of impact and efficiency in IGT research and development to improve patient care. These meetings culminated in a two-day workshop that brought together several academic and industrial leaders in the field today. The goals of the workshop were to identify gaps in the engineering infrastructure available to IGT researchers, develop the role of research funding agencies and the recently established US-based National Center for Image Guided Therapy (NCIGT), and ultimately to facilitate the transfer of technology among research centers that are sponsored by the National Institutes of Health (NIH). Workshop discussions spanned many of the current challenges in the development and deployment of new IGT systems. Key challenges were identified in a number of areas, including: validation standards; workflows, use-cases, and application requirements; component reusability; and device interface standards. This report elaborates on these key points and proposes research challenges that are to be addressed by a joint effort between academic, industry, and NIH participants.

Biomedical imaging research opportunities at the NIH.

Biomedical imaging is a key aspect of clinical diagnosis and treatment of disease and research concerning disease genesis, progression, and therapy. The NIH offers research funding opportunities for imaging at the cellular/molecular levels and at the whole-body (diagnostic) levels. This presentation will discuss imaging programs and directions at the NIH and specific funding opportunities that encompass devices, informatics, and applications.

Modification of reference array attachment for image guided neurosurgery: direct cranial fixation.

We have modified the cranial fixation technique of the reference array used for the Stealth (Medtronics Inc., Minneapolis, MN) image guided neurosurgical workstation to avoid rigid immobilization and to accommodate patients undergoing awake procedures. The modification allows attachment of a reference array directly to the skull prior to registration, avoiding the requirement for rigid cranial fixation. The accuracy of fiducial registration for the modified reference array was compared to the conventional reference array using a phantom system yielding similar registration results and target accuracy. The successful application of the modified system to two operative cases is described.

Enhanced anatomic visualization with ultrasound-assisted intracranial image-guidance in neurosurgery.

Anatomical comparisons between ultrasound images and magnetic resonance imaging (MRI)/computed tomography (CT) preoperative images were performed in four ultrasound-assisted image-guided intracranial surgeries. An ultrasound scanner connected to a surgical navigation system allowed the neurosurgeon to acquire useful views from that integration, offering an improved method for visualization. This surgical navigation device and associated ultrasound provides real-time brain shift correction. The accuracy of navigation depends on the identification of the anatomic structures. Despite some limitations of the ultrasound images, the ability to compare preoperative MRI and intraoperative ultrasound proved useful to the surgeon.

Infrastructure for image guided surgery / 中国医学物理学杂志

Image guided surgery (IGS) requires an integrated environment for seamless acquisition, visualization,manipulation, display, registration and storage of complex data sets. The infrastructure to support IGS integrates image acquisition, networks, presurgical planning, surgical navigation, and archival storage elements. This paper describes the principal components of an integrated IGS environment and an implementation in a large academic medical center. The IGS infrastructure is illustrated for practical applications in neurosurgical case examples.

Aconito: um estudo de caso de conflito doutrinal e assimilacao na medicina cientifica / Aconite: a case study in doctrinal conflict and the meaning of scientific medicine

A historia farmacoterapeutica da raiz tuberosa dessecada Aconitum napellus oferece uma oportunidade unica para se acompanharem os passos pioneiros em sua aplicacao terapeutica, sua apropriacao por um dos sistemas medicos mais... (AU)