scholarly journals Artificial Intelligence (AI)-Empowered Echocardiography Interpretation: A State-of-the-Art Review

2021 ◽  
Vol 10 (7) ◽  
pp. 1391
Author(s):  
Zeynettin Akkus ◽  
Yousof H. Aly ◽  
Itzhak Z. Attia ◽  
Francisco Lopez-Jimenez ◽  
Adelaide M. Arruda-Olson ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Clinical Medicine ◽  
State Of The Art ◽  
Imaging Modality ◽  
Learning Ability ◽  
Imaging Features ◽  
Clinical Workflow ◽  
Imaging Tool ◽  
Image Quality Control ◽  
And Function

Echocardiography (Echo), a widely available, noninvasive, and portable bedside imaging tool, is the most frequently used imaging modality in assessing cardiac anatomy and function in clinical practice. On the other hand, its operator dependability introduces variability in image acquisition, measurements, and interpretation. To reduce these variabilities, there is an increasing demand for an operator- and interpreter-independent Echo system empowered with artificial intelligence (AI), which has been incorporated into diverse areas of clinical medicine. Recent advances in AI applications in computer vision have enabled us to identify conceptual and complex imaging features with the self-learning ability of AI models and efficient parallel computing power. This has resulted in vast opportunities such as providing AI models that are robust to variations with generalizability for instantaneous image quality control, aiding in the acquisition of optimal images and diagnosis of complex diseases, and improving the clinical workflow of cardiac ultrasound. In this review, we provide a state-of-the art overview of AI-empowered Echo applications in cardiology and future trends for AI-powered Echo technology that standardize measurements, aid physicians in diagnosing cardiac diseases, optimize Echo workflow in clinics, and ultimately, reduce healthcare costs.

Top 100 most-cited articles on medical imaging applications of artificial intelligence: a bibliometric analysis (Preprint)

2020 ◽  
Author(s):  
Ying Liu ◽  
Ziyan Yu ◽  
Shuolan Jing ◽  
Honghu Jiang ◽  
Chunxia Wang
Keyword(s):  
Artificial Intelligence ◽  
Medical Imaging ◽  
Bibliometric Analysis ◽  
Clinical Medicine ◽  
Medical Physics ◽  
Medical Image Analysis ◽  
The United States ◽  
Independent Learning ◽  
Learning Ability ◽  
Core Technology

BACKGROUND Artificial intelligence (AI) has penetrated into almost every aspect of our lives and is rapidly changing our way of life. Recently, the new generation of AI taking machine learning and particularly deep convolutional neural network theories as the core technology, has stronger learning ability and independent learning evolution ability, combined with a large amount of learning data, breaks through the bottleneck limit of model accuracy, and makes the model efficient use. OBJECTIVE To identify the 100 most cited papers in artificial intelligence in medical imaging, we performed a comprehensive bibliometric analysis basing on the literature search on Web of Science Core Collection (WoSCC). METHODS The 100 top-cited articles published in “AI, Medical imaging” journals were identified using the Science Citation Index Database. The articles were further reviewed, and basic information was collected, including the number of citations, journals, authors, publication year, and field of study. RESULTS The highly cited articles in AI were cited between 72 and 1,554 times. The majority of them were published in three major journals: IEEE Transactions on Medical Imaging, Medical Image Analysis and Medical Physics. The publication year ranged from 2002 to 2019, with 66% published in a three-year period (2016 to 2018). Publications from the United States (56%) were the most heavily cited, followed by those from China (15%) and Netherlands (10%). Radboud University Nijmegen from Netherlands, Harvard Medical School in USA, and The Chinese University of Hong Kong in China produced the highest number of publications (n=6). Computer science (42%), clinical medicine (35%), and engineering (8%) were the most common fields of study. CONCLUSIONS Citation analysis in the field of artificial intelligence in medical imaging reveals interesting information about the topics and trends negotiated by researchers and elucidates which characteristics are required for a paper to attain a “classic” status. Clinical science articles published in highimpact specialized journals are most likely to be cited in the field of artificial intelligence in medical imaging.

scholarly journals Introduction of Cardiac Magnetic Resonance Imaging in Kosovo: First Fifty Consecutive Patients Registry Report

2021 ◽  
Vol 9 (B) ◽  
pp. 417-425
Author(s):  
Ted Trajcheski ◽  
Lulzim Brovina ◽  
Biljana Zafirova ◽  
Lada Trajceska
Keyword(s):  
Cardiac Magnetic Resonance ◽  
Magnetic Resonance ◽  
Heart Valves ◽  
Heart Diseases ◽  
Imaging Modality ◽  
Gadolinium Contrast ◽  
Myocardial Perfusion Study ◽  
Imaging Tool ◽  
Gadolinium Contrast Agent ◽  
And Function

BACKGROUND: Cardiac magnetic resonance (CMR) as advanced diagnostic tool for the heart has been introduced in our institution since September 2019. AIM: We report on the first fifty consecutive patients using this imaging modality. METHODS AND MATERIALS: Strict protocol for CMR procedure, imaging quality assessment, contraindications, and informed consent were established. Patients selected for CMR were enrolled in a prospective registry. Visualizing the heart chambers, heart muscle and heart valves, resulted in acquiring complex imaging of the heart structure and function. When applicable, patients received gadolinium contrast agent for Late Gadolinium Enhancement (LGE). Adenosine was used for stress induced myocardial perfusion study. In this study, we report on the initial CMR procedures in the first 15 months. RESULTS: The age of the patients ranges from 17 to 82 and the number of male and female patients was well balanced. No absolute contraindications were met in any patient. Relative contraindications were noted but did not prevent from performing the scan. Different cardiac pathologies were encountered in the examined patients. Most common was the ischemic heart disease – 19 (38%). We had 15 (30%) out of 46 (92%) CMR procedures with LGE showing fibrotic scaring. Quality image assessment was scaled from poor to excellent. Most of the assessments were graded very good and good (46% and 48%), no poor, and very poor noted. CONCLUSION: CMR has been successfully introduced in Kosovo as excellent imaging tool for diagnosing and characterizing a nearly exhaustive spectrum of heart diseases.

scholarly journals Magnetic Resonance Imaging of Non-ischemic Cardiomyopathies: A Pictorial Essay

2015 ◽  
Vol 5 ◽  
pp. 37 ◽  
Author(s):  
Cristina I Olivas-Chacon ◽  
Carola Mullins ◽  
Kevan Stewart ◽  
Nassim Akle ◽  
Jesus E Calleros ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Systemic Disease ◽  
Left Ventricular ◽  
Imaging Features ◽  
Resonance Imaging ◽  
Imaging Tool ◽  
Pictorial Essay ◽  
And Function

Non-ischemic cardiomyopathies are defined as either primary or secondary diseases of the myocardium resulting in cardiac dysfunction. While primary cardiomyopathies are confined to the heart and can be genetic or acquired, secondary cardiomyopathies show involvement of the heart as a manifestation of an underlying systemic disease including metabolic, inflammatory, granulomatous, infectious, or autoimmune entities. Non-ischemic cardiomyopathies are currently classified as hypertrophic, dilated, restrictive, or unclassifiable, including left ventricular non-compaction. Cardiovascular Magnetic Resonance Imaging (CMRI) not only has the capability to assess cardiac morphology and function, but also the ability to detect edema, hemorrhage, fibrosis, and intramyocardial deposits, providing a valuable imaging tool in the characterization of non-ischemic cardiomyopathies. This pictorial essay shows some of the most important non-ischemic cardiomyopathies with an emphasis on magnetic resonance imaging features.

scholarly journals Applications of Machine Learning and Deep Learning in Ultrasound Imaging

2020 ◽  
pp. 90-102
Author(s):  
Siddhika Arunachalam
Keyword(s):  
Machine Learning ◽  
Deep Learning ◽  
Imaging Modality ◽  
Cost Effective ◽  
Disease Diagnosis ◽  
Clinical Workflow ◽  
Cross Sectional ◽  
Computational Capability ◽  
Image Quality Control ◽  
Applications Of Machine Learning

Ultrasound (US) imaging (sonography) is the most frequently performed cross-sectional diagnostic imaging modality in the field of medicine. It is non-ionizing, portable, cost-effective, and capable of real-time image acquisition and display. US is a rapidly evolving technology with substantial opportunities and challenges. Challenges include limited image quality control and high inter- and intra-operator variability. As US devices become smaller, due to progressive miniaturization of US devices in the last decade, increased computational capability can contribute significantly to decreasing variability through advanced image processing. In this paper, leading Machine Learning (ML) and Deep Learning (DL) approaches and research directions in US, with an emphasis on recent ML and DL advances is discussed. An outlook on future opportunities for ML and DL techniques to further improve clinical workflow and US-based disease diagnosis and characterization is also presented.

Myxofibrosarcoma: clinical and prognostic value of MRI features

2020 ◽  
Vol 16 ◽  
Author(s):  
Paolo Spinnato ◽  
Andrea Sambri ◽  
Tomohiro Fujiwara ◽  
Luca Ceccarelli ◽  
Roberta Clinca ◽  
...  
Keyword(s):  
Soft Tissue ◽  
Local Recurrence ◽  
Contrast Enhancement ◽  
Imaging Modality ◽  
Soft Tissue Sarcomas ◽  
The Elderly ◽  
High Rate ◽  
Imaging Features ◽  
High Grade ◽  
Mri Features

: Myxofibrosarcoma is one of the most common soft tissue sarcomas in the elderly. It is characterized by an extremely high rate of local recurrence, higher than other soft tissue tumors, and a relatively low risk of distant metastases.Magnetic resonance imaging (MRI) is the imaging modality of choice for the assessment of myxofibrosarcoma and plays a key role in the preoperative setting of these patients.MRI features associated with high risk of local recurrence are: high myxoid matrix content (water-like appearance of the lesions), high grade of contrast enhancement, presence of an infiltrative pattern (“tail sign”). On the other hand, MRI features associated with worse sarcoma specific survival are: large size of the lesion, deep location, high grade of contrast enhancement. Recognizing the above-mentioned imaging features of myxofibrosarcoma may be helpful to stratify the risk for local recurrence and disease-specific survival. Moreover, the surgical planning should be adjusted according to the MRI features

scholarly journals Significance of Mast Cell Formed Extracellular Traps in Microbial Defense

2021 ◽  
Author(s):  
Daniel Elieh Ali Komi ◽  
Wolfgang M. Kuebler
Keyword(s):  
State Of The Art ◽  
Extracellular Dna ◽  
Cellular Mechanisms ◽  
Extracellular Traps ◽  
Synthetic Chemicals ◽  
Dna Strands ◽  
Associated Proteins ◽  
Microbial Defense ◽  
And Function ◽  
Insight Into

AbstractMast cells (MCs) are critically involved in microbial defense by releasing antimicrobial peptides (such as cathelicidin LL-37 and defensins) and phagocytosis of microbes. In past years, it has become evident that in addition MCs may eliminate invading pathogens by ejection of web-like structures of DNA strands embedded with proteins known together as extracellular traps (ETs). Upon stimulation of resting MCs with various microorganisms, their products (including superantigens and toxins), or synthetic chemicals, MCs become activated and enter into a multistage process that includes disintegration of the nuclear membrane, release of chromatin into the cytoplasm, adhesion of cytoplasmic granules on the emerging DNA web, and ejection of the complex into the extracellular space. This so-called ETosis is often associated with cell death of the producing MC, and the type of stimulus potentially determines the ratio of surviving vs. killed MCs. Comparison of different microorganisms with specific elimination characteristics such as S pyogenes (eliminated by MCs only through extracellular mechanisms), S aureus (removed by phagocytosis), fungi, and parasites has revealed important aspects of MC extracellular trap (MCET) biology. Molecular studies identified that the formation of MCET depends on NADPH oxidase-generated reactive oxygen species (ROS). In this review, we summarize the present state-of-the-art on the biological relevance of MCETosis, and its underlying molecular and cellular mechanisms. We also provide an overview over the techniques used to study the structure and function of MCETs, including electron microscopy and fluorescence microscopy using specific monoclonal antibodies (mAbs) to detect MCET-associated proteins such as tryptase and histones, and cell-impermeant DNA dyes for labeling of extracellular DNA. Comparing the type and biofunction of further MCET decorating proteins with ETs produced by other immune cells may help provide a better insight into MCET biology in the pathogenesis of autoimmune and inflammatory disorders as well as microbial defense.

scholarly journals From Exosome Glycobiology to Exosome Glycotechnology, the Role of Natural Occurring Polysaccharides

2021 ◽  
Vol 2 (2) ◽  
pp. 311-338
Author(s):  
Giulia Della Rosa ◽  
Clarissa Ruggeri ◽  
Alessandra Aloisi
Keyword(s):  
State Of The Art ◽  
Cell Communication ◽  
Pathological Conditions ◽  
New Findings ◽  
Cell Type Specific ◽  
New Perspective ◽  
And Function ◽  
And Personalized Medicine ◽  
Innate Ability

Exosomes (EXOs) are nano-sized informative shuttles acting as endogenous mediators of cell-to-cell communication. Their innate ability to target specific cells and deliver functional cargo is recently claimed as a promising theranostic strategy. The glycan profile, actively involved in the EXO biogenesis, release, sorting and function, is highly cell type-specific and frequently altered in pathological conditions. Therefore, the modulation of EXO glyco-composition has recently been considered an attractive tool in the design of novel therapeutics. In addition to the available approaches involving conventional glyco-engineering, soft technology is becoming more and more attractive for better exploiting EXO glycan tasks and optimizing EXO delivery platforms. This review, first, explores the main functions of EXO glycans and associates the potential implications of the reported new findings across the nanomedicine applications. The state-of-the-art of the last decade concerning the role of natural polysaccharides—as targeting molecules and in 3D soft structure manufacture matrices—is then analysed and highlighted, as an advancing EXO biofunction toolkit. The promising results, integrating the biopolymers area to the EXO-based bio-nanofabrication and bio-nanotechnology field, lay the foundation for further investigation and offer a new perspective in drug delivery and personalized medicine progress.

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