Artificial intelligence for automated detection and measurements of carpal instability signs on conventional radiographs.

OBJECTIVES: To develop and validate an artificial intelligence (AI) system for measuring and detecting signs of carpal instability on conventional radiographs. MATERIALS AND METHODS: Two case-control datasets of hand and wrist radiographs were retrospectively acquired at three hospitals (hospitals A, B, and C). Dataset 1 (2178 radiographs from 1993 patients, hospitals A and B, 2018-2019) was used for developing an AI system for measuring scapholunate (SL) joint distances, SL and capitolunate (CL) angles, and carpal arc interruptions. Dataset 2 (481 radiographs from 217 patients, hospital C, 2017-2021) was used for testing, and with a subsample (174 radiographs from 87 patients), an observer study was conducted to compare its performance to five clinicians. Evaluation metrics included mean absolute error (MAE), sensitivity, and specificity. RESULTS: Dataset 2 included 258 SL distances, 189 SL angles, 191 CL angles, and 217 carpal arc labels obtained from 217 patients (mean age, 51 years ± 23 [standard deviation]; 133 women). The MAE in measuring SL distances, SL angles, and CL angles was respectively 0.65 mm (95%CI: 0.59, 0.72), 7.9 degrees (95%CI: 7.0, 8.9), and 5.9 degrees (95%CI: 5.2, 6.6). The sensitivity and specificity for detecting arc interruptions were 83% (95%CI: 74, 91) and 64% (95%CI: 56, 71). The measurements were largely comparable to those of the clinicians, while arc interruption detections were more accurate than those of most clinicians. CONCLUSION: This study demonstrates that a newly developed automated AI system accurately measures and detects signs of carpal instability on conventional radiographs. CLINICAL RELEVANCE STATEMENT: This system has the potential to improve detections of carpal arc interruptions and could be a promising tool for supporting clinicians in detecting carpal instability.

Cognitive functioning in untreated glioma patients: The limited predictive value of clinical variables.

BACKGROUND: Previous research identified many clinical variables that are significantly related to cognitive functioning before surgery. It is not clear whether such variables enable accurate prediction for individual patients' cognitive functioning because statistical significance does not guarantee predictive value. Previous studies did not test how well cognitive functioning can be predicted for (yet) untested patients. Furthermore, previous research is limited in that only linear or rank-based methods with small numbers of variables were used. METHODS: We used various machine learning models to predict preoperative cognitive functioning for 340 patients with glioma across 18 outcome measures. Predictions were made using a comprehensive set of clinical variables as identified from the literature. Model performances and optimized hyperparameters were interpreted. Moreover, Shapley additive explanations were calculated to determine variable importance and explore interaction effects. RESULTS: Best-performing models generally demonstrated above-random performance. Performance, however, was unreliable for 14 out of 18 outcome measures with predictions worse than baseline models for a substantial number of train-test splits. Best-performing models were relatively simple and used most variables for prediction while not relying strongly on any variable. CONCLUSIONS: Preoperative cognitive functioning could not be reliably predicted across cognitive tests using the comprehensive set of clinical variables included in the current study. Our results show that a holistic view of an individual patient likely is necessary to explain differences in cognitive functioning. Moreover, they emphasize the need to collect larger cross-center and multimodal data sets.

Regulatory Oversight of Cell, Tissue, and Gene Therapy Products in Singapore.

The Health Sciences Authority of Singapore has implemented a fit-for-purpose regulatory framework for Cell, Tissue, and Gene Therapy Products (CTGTPs) on 1 March 2021. A total of 11 pieces of subsidiary legislation for CTGTP are gazetted under the Health Products Act as Health Products (CTGTP) Regulations 2021. The CTGTPs are stratified into lower-risk Class 1 CTGTP or moderate- to higher-risk Class 2 CTGTP based on their degree of manipulation, intended use, and if they are combined or used with therapeutic products or medical devices. The regulatory controls are calibrated to the different risk profiles of the products. This risk-based regulatory approach aims to facilitate successful product development and registration in Singapore for innovative CTGTP with a least burdensome regulatory framework while ensuring reasonable safeguards on the safety, quality, and efficacy of the products. This chapter describes the regulatory oversight of CTGTP in Singapore.

Sickle Cell Virtual Support Group Program for Adults: An Implementation Evaluation.

Sickle cell disease (SCD) is associated with medical and psychosocial challenges. SCD in adulthood is characterized by increased morbidity and mortality, vulnerability, inadequate self-management preparation, and limited social support. This study evaluated the implementation of a virtual support group during the COVID-19 pandemic using an intervention parameters framework evaluation. Participants included six adults living with SCD. Content analysis was conducted for each of the six intervention parameters, and satisfaction scores were summarized. Participants positively evaluated all intervention parameters of the virtual support group. Findings confirmed that a community-engaged intervention supports self-management and establishes key social networks for adult participants.

Musculoskeletal radiologist-level performance by using deep learning for detection of scaphoid fractures on conventional multi-view radiographs of hand and wrist.

OBJECTIVES: To assess how an artificial intelligence (AI) algorithm performs against five experienced musculoskeletal radiologists in diagnosing scaphoid fractures and whether it aids their diagnosis on conventional multi-view radiographs. METHODS: Four datasets of conventional hand, wrist, and scaphoid radiographs were retrospectively acquired at two hospitals (hospitals A and B). Dataset 1 (12,990 radiographs from 3353 patients, hospital A) and dataset 2 (1117 radiographs from 394 patients, hospital B) were used for training and testing a scaphoid localization and laterality classification component. Dataset 3 (4316 radiographs from 840 patients, hospital A) and dataset 4 (688 radiographs from 209 patients, hospital B) were used for training and testing the fracture detector. The algorithm was compared with the radiologists in an observer study. Evaluation metrics included sensitivity, specificity, positive predictive value (PPV), area under the characteristic operating curve (AUC), Cohen's kappa coefficient (κ), fracture localization precision, and reading time. RESULTS: The algorithm detected scaphoid fractures with a sensitivity of 72%, specificity of 93%, PPV of 81%, and AUC of 0.88. The AUC of the algorithm did not differ from each radiologist (0.87 [radiologists' mean], p ≥ .05). AI assistance improved five out of ten pairs of inter-observer Cohen's κ agreements (p < .05) and reduced reading time in four radiologists (p < .001), but did not improve other metrics in the majority of radiologists (p ≥ .05). CONCLUSIONS: The AI algorithm detects scaphoid fractures on conventional multi-view radiographs at the level of five experienced musculoskeletal radiologists and could significantly shorten their reading time. KEY POINTS: • An artificial intelligence algorithm automatically detects scaphoid fractures on conventional multi-view radiographs at the same level of five experienced musculoskeletal radiologists. • There is preliminary evidence that automated scaphoid fracture detection can significantly shorten the reading time of musculoskeletal radiologists.

Tumor-targeting albumin nanoparticles as an efficacious drug delivery system and potential diagnostic tool in non-muscle-invasive bladder cancer therapy.

Current intravesical chemotherapy for non-muscle invasive bladder cancer (NMIBC) has limited efficacy due to loss of the instilled agent from urine voiding and the agent's lack of specificity for the tumors. We developed a nanocarrier (txCD47-HNP, ∼100 nm) based on human serum albumin conjugated with a peptide that targets the cluster of differentiation 47 receptor overexpressed on bladder cancer (BC) cells. The IC50 of gemcitabine elaidate (GEM) loaded in the txCD47-HNP was almost an order of magnitude lower than that of free GEM. In a mouse orthotopic BC model, GEM loaded in txCD47-HNP effectively reduced the tumor burden. Tumor cells in BC patients' urine can also be targeted by fluorescence-labeled txCD47-HNP resulting in >83 % of the cells exhibiting fluorescence. Thus, txCD47-HNP can potentially be a theranostic agent in NMIBC management by serving as a targeted drug delivery vehicle as well as an alternative to urine cytology.

Prayers and Mindfulness in Relation to Mental Health among First-Generation Immigrant and Refugee Muslim Women in the USA: An Exploratory Study.

The goal of our study was to explore how first-generation immigrant/refugee Muslim women experience prayer and mindfulness in relation to their mental health. Participants were nine women from an urban city in the Midwestern USA. The women completed a structured demographic survey and a virtual semi-structured interview in a focus group. Using qualitative thematic analysis, we obtained four overarching themes from the data: (a) Prayer helps to build community, (b) Prayer promotes wellbeing, (c) Prayer increases faith, and (d) Prayer encourages intentional awareness. The findings demonstrate that prayer involves awareness and has a strong influence on the mental health of the women participants.

Predicting vasovagal reactions to a virtual blood donation using facial image analysis.

BACKGROUND: People with needle fear experience not only anxiety and stress but also vasovagal reactions (VVR), including nausea, dizziness, sweating, pallor changes, or even fainting. However, the mechanism behind needle fear and the VVR response are not yet well understood. The aim of our study was to explore whether fluctuations in facial temperature in several facial regions are related to the level of experienced vasovagal reactions, in a simulated blood donation. STUDY DESIGN AND METHODS: We recruited 45 students at Tilburg University and filmed them throughout a virtual blood donation procedure using an Infrared Thermal Imaging (ITI) camera. Participants reported their fear of needles and level of experienced vasovagal reactions. ITI data pre-processing was completed on each video frame by detecting facial landmarks and image alignment before extracting the mean temperature from the six regions of interest. RESULTS: Temperatures of the chin and left and right cheek areas increased during the virtual blood donation. Mixed-effects linear regression showed a significant association between self-reported vasovagal reactions and temperature fluctuations in the area below the nose. DISCUSSION: Our results suggest that the area below the nose may be an interesting target for measuring vasovagal reactions using video imaging techniques. This is the first in a line of studies, which assess whether it is possible to automatically detect levels of fear and vasovagal reactions using facial imaging, from which the development of e-health solutions and interventions can benefit.

Development and Validation of a Convolutional Neural Network for Automated Detection of Scaphoid Fractures on Conventional Radiographs.

PURPOSE: To compare the performance of a convolutional neural network (CNN) to that of 11 radiologists in detecting scaphoid bone fractures on conventional radiographs of the hand, wrist, and scaphoid. MATERIALS AND METHODS: At two hospitals (hospitals A and B), three datasets consisting of conventional hand, wrist, and scaphoid radiographs were retrospectively retrieved: a dataset of 1039 radiographs (775 patients [mean age, 48 years ± 23 {standard deviation}; 505 female patients], period: 2017-2019, hospitals A and B) for developing a scaphoid segmentation CNN, a dataset of 3000 radiographs (1846 patients [mean age, 42 years ± 22; 937 female patients], period: 2003-2019, hospital B) for developing a scaphoid fracture detection CNN, and a dataset of 190 radiographs (190 patients [mean age, 43 years ± 20; 77 female patients], period: 2011-2020, hospital A) for testing the complete fracture detection system. Both CNNs were applied consecutively: The segmentation CNN localized the scaphoid and then passed the relevant region to the detection CNN for fracture detection. In an observer study, the performance of the system was compared with that of 11 radiologists. Evaluation metrics included the Dice similarity coefficient (DSC), Hausdorff distance (HD), sensitivity, specificity, positive predictive value (PPV), and area under the receiver operating characteristic curve (AUC). RESULTS: The segmentation CNN achieved a DSC of 97.4% ± 1.4 with an HD of 1.31 mm ± 1.03. The detection CNN had sensitivity of 78% (95% CI: 70, 86), specificity of 84% (95% CI: 77, 92), PPV of 83% (95% CI: 77, 90), and AUC of 0.87 (95% CI: 0.81, 0.91). There was no difference between the AUC of the CNN and that of the radiologists (0.87 [95% CI: 0.81, 0.91] vs 0.83 [radiologist range: 0.79-0.85]; P = .09). CONCLUSION: The developed CNN achieved radiologist-level performance in detecting scaphoid bone fractures on conventional radiographs of the hand, wrist, and scaphoid.Keywords: Convolutional Neural Network (CNN), Deep Learning Algorithms, Machine Learning Algorithms, Feature Detection-Vision-Application Domain, Computer-Aided DiagnosisSee also the commentary by Li and Torriani in this issue.Supplemental material is available for this article.©RSNA, 2021.

Complementary and Alternative Medicine Mind-Body Approaches Used Among Racially and Ethnically Diverse Adolescents.

PURPOSE: The aim of this paper is to examine complementary and alternative medicine (CAM) use among racially and ethnically diverse adolescents. Greater understanding of CAM use among this group is warranted to better inform health care providers in delivering a culturally relevant health promotion approach. DESIGN AND METHODS: A secondary data analysis was conducted using the 2012 Child Complementary and Alternative Medicine Supplement of the National Health Interview Survey (CAM-NHIS) data, which was collected from a national sample of adolescents aged 12-17 years. A logistic regression test was employed to investigate the predictors associated with CAM use among racially and ethnically diverse adolescents. RESULTS: While Black and Hispanic adolescents were the least likely to use CAM compared to their White counterparts, families with higher incomes, higher education attainment, and adolescents who experienced pain were more likely to use CAM. CONCLUSIONS: Findings suggest the need for future research to gain a greater understanding of CAM use among racially and ethnically diverse adolescents, and insights into how health disparities impact CAM use. Greater understanding of how CAM use intersects with health beliefs and outcomes is also warranted. PRACTICE IMPLICATIONS: Based on the CAM-NHIS survey, few racially and ethnically diverse adolescents have reported use of CAM. Development of culturally appropriate instruments and methods to assess CAM use among racially and ethnically diverse adolescents may yield specific data for this population. Informed health care providers can advocate for improved access to CAM for minority adolescents and alter disparate use.

Neural induction: Historical views and application to pluripotent stem cells.

Embryonic stem (ES) cells are a useful experimental material to recapitulate the differentiation steps of early embryos, which are usually invisible and inaccessible from outside of the body, especially in mammals. ES cells have greatly facilitated the analyses of gene expression profiles and cell characteristics. In addition, understanding the mechanisms during neural differentiation is important for clinical purposes, such as developing new therapeutic methods or regenerative medicine. As neurons have very limited regenerative ability, neurodegenerative diseases are usually intractable, and patients suffer from the disease throughout their lifetimes. The functional cells generated from ES cells in vitro could replace degenerative areas by transplantation. In this review, we will first demonstrate the historical views and widely accepted concepts regarding the molecular mechanisms of neural induction and positional information to produce the specific types of neurons in model animals. Next, we will describe how these concepts have recently been applied to the research in the establishment of the methodology of neural differentiation from mammalian ES cells. Finally, we will focus on examples of the applications of differentiation systems to clinical purposes. Overall, the discussion will focus on how historical developmental studies are applied to state-of-the-art stem cell research.

Multi-audience tracking with RGB-D camera on digital signage.

Digital signage is widely utilized in digital-out-of-home (DOOH) advertising for marketing and business. Recently, the combination of the digital camera and digital signage enables the advertiser to gather the audience demographic for audience measurement. Audience measurement is useful for the advertiser to understand the audience's behavior and improve their business strategies. When an audience is facing the digital display, the vision-based DOOH system will process the audience's face and broadcast a personalized advertisement. Most of the digital signage is available in an uncontrolled environment of public areas. Thus, it poses two main challenges for the vision-based DOOH system to track the audience's movement, which are multiple adjacent faces and occlusion by passer-by. In this paper, a new framework is proposed to combine the digital signage with a depth camera for tracking multi-face in the three-dimensional (3D) environment. The proposed framework extracts the audience's face centroid position (x, y) and depth information (z) and plots into the aerial map to simulate the audience's movement that is corresponding to the real-world environment. The advertiser can further measure the advertising effectiveness through the audience's behavior.

Multicell migration tracking within angiogenic networks by deep learning-based segmentation and augmented Bayesian filtering.

Cell migration is a key feature for living organisms. Image analysis tools are useful in studying cell migration in three-dimensional (3-D) in vitro environments. We consider angiogenic vessels formed in 3-D microfluidic devices (MFDs) and develop an image analysis system to extract cell behaviors from experimental phase-contrast microscopy image sequences. The proposed system initializes tracks with the end-point confocal nuclei coordinates. We apply convolutional neural networks to detect cell candidates and combine backward Kalman filtering with multiple hypothesis tracking to link the cell candidates at each time step. These hypotheses incorporate prior knowledge on vessel formation and cell proliferation rates. The association accuracy reaches 86.4% for the proposed algorithm, indicating that the proposed system is able to associate cells more accurately than existing approaches. Cell culture experiments in 3-D MFDs have shown considerable promise for improving biology research. The proposed system is expected to be a useful quantitative tool for potential microscopy problems of MFDs.

Automated tracking and quantification of angiogenic vessel formation in 3D microfluidic devices.

Angiogenesis, the growth of new blood vessels from pre-existing vessels, is a critical step in cancer invasion. Better understanding of the angiogenic mechanisms is required to develop effective antiangiogenic therapies for cancer treatment. We culture angiogenic vessels in 3D microfluidic devices under different Sphingosin-1-phosphate (S1P) conditions and develop an automated vessel formation tracking system (AVFTS) to track the angiogenic vessel formation and extract quantitative vessel information from the experimental time-lapse phase contrast images. The proposed AVFTS first preprocesses the experimental images, then applies a distance transform and an augmented fast marching method in skeletonization, and finally implements the Hungarian method in branch tracking. When applying the AVFTS to our experimental data, we achieve 97.3% precision and 93.9% recall by comparing with the ground truth obtained from manual tracking by visual inspection. This system enables biologists to quantitatively compare the influence of different growth factors. Specifically, we conclude that the positive S1P gradient increases cell migration and vessel elongation, leading to a higher probability for branching to occur. The AVFTS is also applicable to distinguish tip and stalk cells by considering the relative cell locations in a branch. Moreover, we generate a novel type of cell lineage plot, which not only provides cell migration and proliferation histories but also demonstrates cell phenotypic changes and branch information.

Detecting cell division of Pseudomonas aeruginosa bacteria from bright-field microscopy images with hidden conditional random fields.

An approach to automatically detect bacteria division with temporal models is presented. To understand how bacteria migrate and proliferate to form complex multicellular behaviours such as biofilms, it is desirable to track individual bacteria and detect cell division events. Unlike eukaryotic cells, prokaryotic cells such as bacteria lack distinctive features, causing bacteria division difficult to detect in a single image frame. Furthermore, bacteria may detach, migrate close to other bacteria and may orientate themselves at an angle to the horizontal plane. Our system trains a hidden conditional random field (HCRF) model from tracked and aligned bacteria division sequences. The HCRF model classifies a set of image frames as division or otherwise. The performance of our HCRF model is compared with a Hidden Markov Model (HMM). The results show that a HCRF classifier outperforms a HMM classifier. From 2D bright field microscopy data, it is a challenge to separate individual bacteria and associate observations to tracks. Automatic detection of sequences with bacteria division will improve tracking accuracy.

Regulatory Oversight of Cell- and Tissue-Based Therapeutic Products and Gene Therapy Products in Singapore.

The regulatory environment for cell- and tissue-based therapeutic products and gene therapy products is rapidly evolving and drug regulatory agencies are working towards establishing a risk-based system in the regulatory framework. Similarly in Singapore, a risk-based tiered approach has been applied whereby clinical trials and product licence of high-risk cell- and tissue-based therapeutic products (substantially manipulated products, products intended for nonhomologous use or combined products) and gene therapy products are regulated as medicinal products under the Medicines Act. There is no legal definition for cell- and tissue-based therapeutic and gene therapy products. The current working definition for a cell- and tissue-based therapeutic product is an article containing or consisting of an autologous or allogeneic human cell or tissue that are used for or administered to, or intended to be used for or administered to, human beings for the diagnosis, treatment, or prevention of human diseases or conditions. Gene therapy products are included under the current biological medicinal product definition.

In vivo label-free quantification of liver microcirculation using dual-modality microscopy.

Microcirculation lesion is a common symptom of chronic liver diseases in the form of vasculature deformation and circulation alteration. In acute to chronic liver diseases such as biliary atresia, microcirculation lesion can have an early onset. Detection of microcirculation lesion is meaningful for studying the progression of liver disease. We have combined wide-field fluorescence microscopy and a laser speckle contrast technique to characterize hepatic microcirculation in vivo without labeling in a bile-duct ligation rat fibrosis model of biliary atresia. Through quantitative image analysis of four microcirculation parameters, we observed significant microcirculation lesion in the early to middle stages of fibrosis. This bimodal imaging method is useful to assess hepatic microcirculation lesion for the study of liver diseases.

Formation of elongated fascicle-inspired 3D tissues consisting of high-density, aligned cells using sacrificial outer molding.

The majority of muscles, nerves, and tendons are composed of fiber-like fascicle morphology. Each fascicle has a) elongated cells highly aligned with the length of the construct, b) a high volumetric cell density, and c) a high length-to-width ratio with a diameter small enough to facilitate perfusion. Fiber-like fascicles are important building blocks for forming tissues of various sizes and cross-sectional shapes, yet no effective technology is currently available for producing long and thin fascicle-like constructs with aligned, high-density cells. Here we present a method for molding cell-laden hydrogels that generate cylindrical tissue structures that are ~100 µm in diameter with an extremely high length to diameter ratio (>100 : 1). Using this method we have successfully created skeletal muscle tissue with a high volumetric density (~50%) and perfect cell alignment along the axis. A new molding technique, sacrificial outer molding, allows us to i) create a long and thin cylindrical cavity of the desired size in a sacrificial mold that is solid at a low temperature, ii) release gelling agents from the sacrificial mold material after the cell-laden hydrogel is injected into fiber cavities, iii) generate a uniform axial tension between anchor points at both ends that promotes cell alignment and maturation, and iv) perfuse the tissue effectively by exposing it to media after melting the sacrificial outer mold at 37 °C. The effects of key parameters and conditions, including initial cavity diameter, axial tension, and concentrations of the hydrogel and gelling agent upon tissue compaction, volumetric cell density, and cell alignment are presented.