An example of popliteal artery thrombosis formation caused by COVID-19 (SARS-CoV-2). Coronavirus often caused thrombus formation in the body, leading to numerous types of complications, including pulmonary embolism, stroke, heart attack, deep vein thrombosis (DVT) and ischemia or infarcts in various organs.

Related COVID ultrasound video clips: 

VIDEO: COVID Lung Ultrasound B-lines and Pleural Thickening

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This video clip is part of the examples from an RSNA journal Radiographics article on the radiology presentations and complications of the COVID virus and which modalities can best image these features. Here are links to the two articles:

Manifestations of COVID-19, Part 1: Viral Pathogenesis and Pulmonary and Vascular System Complications. 

Multisystem Imaging Manifestations of COVID-19, Part 2: From Cardiac Complications to Pediatric Manifestations

The video is from the study lead-author Margarita Revzin, M.D., MS, FSRU, FAIUM, associate professor of radiology and biomedical imaging, Yale University School of Medicine, abdominal and emergency imaging, radiologist. She explains more details in the VIDEO: Overview COVID-19 Imaging Techniques Using X-ray, CT, MRI and Ultrasound.

Find more COVID medical imaging in the PHOTO GALLERY: How COVID-19 Appears on Medical Imaging. 

Several radiology IT vendors at 2021 Healthcare Information Management Systems Society (HIMSS) conference demonstrated computed tomography (CT) imaging advanced visualization software software to help automatically identify and quantify COVID-19 pneumonia in the lungs. These tools can help speed assessment of the lung involvement and serial tracking can be used to assess the patient's progress in the hospital and during long-COVID observation. 

Examples of COVID analysis tool shown in this video include clips from booth tours at: 
   • Fujifilm
   • Siemens Healthineers 
   • Canon (Vital)

Canon received FDA clearance for its tool under and emergency use authorization (EUA).

Siemens said its tool was part of its lung analysis originally developed for cancer but modified and prioritized to aid in COVID assessments. 
 

HIMSS Related Content:

Advances in CVIS and Enterprise iImaging at HIMSS 21

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VIDEO: Importance of Body Part Labeling in Enterprise Imaging — Interview with Alex Towbin, M.D.

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Alex Towbin, M.D., Cincinnati Children’s Hospital Medical Center CMIO, Radiology Department associate chief of clinical operations and informatics, and chair of radiology informatics, spoke in an enterprise imaging session at the Healthcare Information Management Systems Society (HIMSS) 2021 meeting and highlight the importance of a standardizing body part labeling to enable imaging consumption, image sharing, greater levels of interoperability and image-based artificial intelligence (AI) research. 

He described the process by which existing body part ontologies were evaluated, how the HIMSS-SIIM Enterprise Imaging Community raised awareness of the issues caused by the lack of an industry-standard body-part ontology, and the process by which an industry standard will be selected. Finally, the speakers will discuss how the HIMSS-SIIM Enterprise Imaging Community plans to advocate for the selected ontology to be incorporated as part of existing standards such as DICOM and HL7 FHIR.

In the video he outlines three metadata elements needed to selection of a relevant comparison imaging examination. He also explains how the HIMSS-SIIM EIC convened experts to select a standard body part ontology for use in enterprise imaging
Describe the HIMSS-SIIM EIC’s plan to foster adoption of a standard body part ontology for use in enterprise imaging
 

Advances in PACS and Cardiology Information Systems at HIMSS 2021

Find more HIMSS content

This is an overview of trends and technologies in radiology artificial intelligence (AI) applications in 2021. Views were shared by 11 radiologists using AI and industry leaders, which include:

• Randy Hicks, M.D., MBA, radiologist and CEO of Reginal Medical Imaging (RMI), and an iCAD Profound AI user.

• Prof. Dr. Thomas Frauenfelder, University of Zurich, Institute for Diagnostic and Interventional Radiology, and Riverain AI user. 

• Amy Patel, M.D., medical director of Liberty Hospital Women’s Imaging, assistant professor of radiology at UMKC, and user of Kios AI for breast ultrasound. 

• Sham Sokka, Ph.D., vice president and head of innovation, precision diagnosis, Philips Healthcare.

• Ivo Dreisser, Siemens Healthineers, global marketing manager for the AI Rad Companion.

• Bill Lacey, vice president of medical informatics, Fujifilm Medical Systems USA.

• Karley Yoder, vice president and general manager, artificial intelligence, GE Healthcare.

• Georges Espada, head of Agfa Healthcare digital and computed radiography business unit.

• Pooja Rao, head of research and development and co-founder of Qure.ai.

• Jill Hamman, world-wide marketing manager at Carestream Health.

• Sebastian Nickel, Siemens Healthineers, global product manager for the AI Pathway Companion. 

There has been a change in attitudes about AI on the expo floor at the Radiological Society of North America (RSNA) over the last two years. AI conversations were originally 101 level and discussed how AI technology could be trained to sort photos of dogs and cats. However, in 2020, with numerous FDA approvals for various AI applications, the conversations at RSNA, and industry wide, have shifted to that of accepting the validity of AI. Radiologists now want to discuss how a specific AI algorithm is going to help them save time, make more accurate diagnoses and make them more efficient.

With a higher level of maturity in AI and the technology seeing wider adoption, radiologists using it say AI gives them additional confidence in their diagnoses, and can even help readers who may not be deep experts in the exam type they are being asked to read. 

With a myriad of new AI apps gaining regulatory approval from scores of imaging vendors, the biggest challenge for getting this technology into hospitals is an easy to integrate format. This has led to several vendors creating AI app stores. These allow AI apps to integrate easily into radiology workflows because the apps are already integrated as third-party software into a larger radiology vendors' IT platform.  

There are now hundreds of AI applications that do a wide variety of analysis, from data analytics, image reconstruction, disease and anatomy identification, automating measurements and advanced visualization. The AI applications can be divided into 2 basic types — AI to improve workflow, and AI for clinical decision support, such as diagnostic aids.

On the workflow side, several vendors are leveraging AI to pull together all of a patients' information, prior exams and reports in one location and to digest the information so it is easier for the radiologist to consume. Often the AI pulls only data and priors that relate to a specific question being asked, based on the imaging protocol used for the exam. One example of this is the Siemens Healthineers AI Clinical Pathway and Siemens AI integrations with PACS to automate measurements and advanced visualization.

AI is also helping simplify complex tasks and help reduce the reading time on involved exams. One example of this is in 3-D breast tomosythesis with hundreds of images, which is rapidly replacing 2-D mammography, which only produces 4 images. Another example is automated image reconstruction algorithms to significantly reduce manual work. AI also is now being integrated directly into several vendors' imaging systems to speed workflow and improve image quality.

Vendors say AI is here to stay. They explain the future of AI will be automation to help improve image quality, simplify manual processes, improved diagnostic quality, new ways to analyze data, and workflow aids that operate in the background as part of a growing number of software solutions. 

Several vendors at RSNA 2020 noted that AI's biggest impact in the coming years will be its ability to augment and speed the workflow for the small number of radiologists compared to the quickly growing elder patient populations worldwide. There also are applications in rural and developing countries were there are very low numbers of physicians or specialists.

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Here are two quick clinical examples of point-of-care ultrasound (POCUS) lung imaging and cardiac imaging using a GE Vscan Air device. The examples show an abnormal lung image with B-lines. The second clip shows a healthy heart in a parasternal color Doppler image.

The GE Healthcare Vscan Air is a cutting-edge, wireless pocket-sized ultrasound that provides crystal clear image quality, whole-body scanning capabilities, and intuitive software. The pocket-sized ultrasound system was originally introduced in 2010, and as of early 2021, there are over 30,000 Vscan systems in use. The new Vscan Air features a wireless ultrasound probe.

Read more in the article GE Healthcare Unveils Vscan Air Wireless Handheld Ultrasound

Find more POCUS news and video

Darryl B. Sneag, M.D., a radiologist and director of peripheral nerve MRI at the Hospital for Special Surgery (HSS) in New York City, explains how artificial intelligence (AI) magnetic resonance imaging (MRI) reconstruction algorithms have cut imaging times by 50 percent. This has enabled his facility to maintain the same number of patients as it did prior to the pandemic, while still having time to sterilize the scanners after each patient. 

Many radiology departments are now experiencing a backlog of cases due to COVID-19 shutdowns in 2020 and the limits on the number of patients that can be in the hospital for imaging exams due to pandemic containment precautions. Sneag said AI is now playing a role in helping streamline workflow.

HSS has 19 GE Healthcare MRI scanners and uses the Air Recon DL AI image reconstruction algorithm. This allows for shorter scan times, so the same number of patients as pre-pandemic can be imaged per day, even with deeper cleaning of the MRI bore. Sneag explains the algorithm has greatly helped with patient throughput, but the trade off is sometimes getting a ringing artifact on images.

HSS also uses GE's Air Coil flexible pad MRI coils. These can wrap around the patient to improve comfort and get the coils closer to the anatomy being imaged.

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Margarita Revzin, M.D., MS, FSRU, FAIUM, associate professor of radiology and biomedical imaging, Yale University School of Medicine, abdominal and emergency imaging, radiologist,  explains how different medical imaging modalities are used to image manifestations of the COVID-19 (SARS-CoV-2) virus in patients. She is the lead author on a two-part article in the RSNA journal Radiographics that provides a comprehensive overview of coronavirus imaging.

The articles offer numerous case images from X-ray, ultrasound, computed tomography (CT), and magnetic resonance imaging (MRI). Revzin also discusses some of the radiology presentations and complications of the virus and which modalities can best image these features. Here are links to the two articles:

Manifestations of COVID-19, Part 1: Viral Pathogenesis and Pulmonary and Vascular System Complications. 

Multisystem Imaging Manifestations of COVID-19, Part 2: From Cardiac Complications to Pediatric Manifestations

Although COVID-19 predominantly affects the respiratory system, other organs can also be involved. The authors of the articles said imaging plays an essential role in the diagnosis of all manifestations of the disease, as well as its related complications, and proper utilization and interpretation of imaging examinations is crucial. As the virus continues to spread, a comprehensive understanding of the diagnostic imaging hallmarks, imaging features, multisystemic involvement, and evolution of imaging findings is essential for effective patient management and treatment. Only a few articles had been published that comprehensively describe the multisystemic imaging manifestations of COVID-19 prior to this article series, published in the fall of 2020. The authors provide an inclusive system-by-system image-based review of this life-threatening and rapidly spreading infection. In part 1 of this article, the authors discuss general aspects of the disease, with an emphasis on virology, the pathophysiology of the virus, and clinical presentation of the disease. Part 2 focuses on key imaging features of COVID-19 that involve the cardiac, neurologic, abdominal, dermatologic and ocular, and musculoskeletal systems, as well as pediatric and pregnancy-related manifestations of the virus

Most of the images in the video are from the articles. Find more COVID medical imaging in the PHOTO GALLERY: How COVID-19 Appears on Medical Imaging.

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VIDEO: What Does COVID-19 Look Like in Lung CT Scans 

PHOTO GALLERY: How COVID-19 Appears on Medical Imaging

VIDEO: Imaging COVID-19 With Point-of-Care Ultrasound (POCUS) — Interview with Mike Stone, M.D.

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VIDEO: Use of Teleradiology During the COVID-19 Pandemic — Interview with John Kim, M.D.
 

VIDEO: Radiology Industry Responding to COVID-19 — Interview with Jeffrey Bundy, Ph.D.

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This is an example of Canon's Advanced intelligent Clear-IQ Engine (AiCE) AI-driven image reconstruction software that is now being used to improve image quality on the Canon Celesteion Prime PET/CT nuclear imaging system. The deep learning is used to enhance the iterative reconstruction used to reduce noise and sharped high contrast resolution on positron emission tomography (PET) images from the digital PET detector used on the system. 

This example is a whole-body FGD PET scan of a patient with a large BMI with lung cancer.

The Cartesion Prime PET/CT is the industry’s only air-cooled digital PET/CT, provides variable bed time (vBT) acquisition as a standard feature. This and the new FDA 510(k)-pending AiCE technology were highlighted at the 2020 Radiological Society of North America (RSNA) virtual meeting. 

Find more RSNA news

Treating cancer effectively often includes a combination of patient therapies. In recent years, technology advancements have led to a more efficient and personalized approach to treatment. Andrew Wilson, President of Oncology Informatics at Elekta, discussed the latest software advancements with ITN.

Agfa is looking to transform X-ray with new advancements in volumetric imaging, and with new mobile concepts and implementation of intelligent tools. ITN had a conversation with Georges Espada on Transforming X-ray with Intelligent Tools. 

This video shows a computed tomography (CT) scroll through showing bowel ischemia and perforation (see arrows) due to superior mesenteric artery (SMA) thrombus in COVID-19 (SARS-CoV-2) patient. Mesenteric artery thrombosis (MAT) is a condition involving occlusion of the arterial vascular supply of the intestinal system and is a severe and potentially fatal illness. 

Superior mesenteric artery thrombosis (Red arrow) complicated by bowel ischemia and perforation in a 54-year-old man who presented to the emergency department with abdominal pain and was diagnosed with COVID-19. Contrast-enhanced CT images of the abdomen and pelvis show mucosal hyperenhancement involving the small bowel (green arrows).

Read more in the article Multisystem Imaging Manifestations of COVID-19, Part 1: Viral Pathogenesis and Pulmonary and Vascular System Complications.

Case example from Margarita Revzin, M.D., associate professor of radiology and biomedical imaging, Yale School of Medicine.

VIDEO: How to Image COVID-19 and Radiological Presentations of the Virus — Interview with Margarita Revzin, M.D.,

See more medical imaging of COVID-19 in the photo gallery How COVID-19 Appears on Medical Imaging.

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Bruce Bauer, Ph.D., CEO of TAE Life Sciences. The company is developing boron neutron capture therapy (BNCT) as a new radiation therapy for cancer. A patient is first infused with a non-toxic boron-10 compound, which selectively accumulates in tumor tissue. A neutron beam is then focused on the tumor and the neutrons are captured by the boron and causes emission of alpha radiation particles within the tumor. Alpha particles have a a very short range, so this helps spare surrounding healthy tissue from radiation damage. 

Historically, BNCT clinical studies have been carried out using boronophenylalanine (BPA) and neutrons derived from the core of a nuclear reactor. While the clinical outcomes have been encouraging, the availability of better boron-10 compounds and access to a neutron source posed a significant barrier to clinical research and adoption of BNCT as a practical cancer therapy.

There is now a renaissance in BNCT with the availability of new accelerator-based neutrons sources and novel synthesis of boron-10 target drugs, allowing clinical research to expand with the goal to have BNCT available as a new treatment option for patients.

The secondary radiation reaction from BNCT, with cellular-level precision, spares more healthy tissues and can potentially treat cancers that otherwise have few treatment options.

The system requires a neutron accelerator, but this is smaller than a proton system and operates at much lower energy, so the shielding requirement is much lower, cutting construction costs.

Find more news and video on radiation therapy

GE Healthcare is highlighting artificial intelligence (AI) automation features on its Voluson Swift ultrasound platform at the 2020 Radiological Society of North America (RSNA) virtual meeting. Features of this system include semi-automated contouring, auto identification of fetal anatomy and positioning on imaging, 

The new SonoLyst AI software can auto recognize 20 standard fetal views in the second trimester protocol. The goal is to speed exam times and make the exams more accurate, even for less experienced sonographers. The AI can tell users what any image is when they freeze the frame. This can be used to help cue up measurements and appropriate annotations. The AI also can tell th user if all the required anatomical structures are in an image needed for the exam protocols.
 

Find more RSNA news and video

Professor Christiane Kuhl, M.D., director of radiology, University Hospital Aachen, Germany, explains how the COVID-19 (SARS-CoV-2) pandemic has impacted screening mammography and raised fears there will be a large increase in more advanced breast cancer cases in the near future as sizable numbers of women skip their annual exams this year. Kuhl also explains the COVID safety protocols most breast imaging centers are taking to limit any potential exposure to the virus from asymptomatic patients.

Other video interviews with Dr. Kuhl:

VIDEO: Explaining Dense Breasts

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How COVID Has Disrupted Screening Mammography and The Urgency to Resume Screenings:

Breast Imaging in the Age of Coronavirus

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Ernest Garcia, Ph.D., MASNC, FAHA, endowed professor in cardiac imaging, director of nuclear cardiology R&D laboratory, Emory University, developer of the Emory Cardiac Tool Box used in nuclear imaging and past-president of the American Society of Nuclear Cardiology (ASNC), explains the use of artificial intelligence (AI) in cardiac imaging. He said there is a tsunami of new AI applications that are starting to flood the FDA for market approval, and there are several examples of AI already in use in radiology. He spoke on this topic in a keynote session at the 2020 ASNC meeting.

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Enterprise viewers are designed to provide fast and easy access to a patient’s imaging history, and today’s modern healthcare systems require a clinical viewer capable of meeting the diverse needs of a large group of users. GE Healthcare’s Zero Footprint Viewer can quickly and easily display digital images, video clips and cine loops from any department and on many different devices.

It provides access to images and reports from anywhere, whether it’s on the hospital floor, in surgery, in clinic or at home, to allow clinicians to access and develop clinical insights that deliver patient results and drive operational efficiencies.

Learn more at https://www.gehealthcare.com/products/healthcare-it/enterprise-imaging/centricity-universal-viewer-zero-footprint

Advanced visualization company Medis recently purchased Advanced Medical Imaging Development S.r.l. (AMID), which developed software to automatically track and measure strain in echocardiograms. That technology is now being adapted for strain imaging in CT and MRI. Using this imaging data, the software also can noninvasively derive pressure gradient loops and curves, similar to using invasive pulmonary arterial (PA) hemodynamic pressure catheters. This information is useful in monitoring critically ill patients on hemodynamic support and to monitor worsening severity of heart failure. 

The technology was discussed at the 2020 Society of Cardiovascular Computed Tomography (SCCT) virtual meeting. Examples of this technology are presented in this video. 
 

Find more news and video from SCCT 2020

VIDEO: Photon Counting Detectors Will be the Next Major Advance in Computed Tomography

Todd Villines, M.D., FACC, FAHA, MSCCT, explains how artificial intelligence (AI) might be used in the near future to automatically calculate CT calcium scoring and and radiomic feature assessments. This was a key take away during the Society of Cardiovascular Computed Tomography (SCCT) 2020 virtual meeting. 

Villines is the Julian Ruffin Beckwith Professor of Medicine, Division of Cardiovascular Medicine, University of Virginia, editor-in-chief of the Journal of Cardiovascular CT (JCCT),  and SCCT past-president.

AI is already commercially used to improve CT image reconstruction to increase the diagnostic quality of the images, especially from low-dose scans. AI is now being applied to automate time-consuming tasks in CT image reads, such as manually calculated calcium scores and automated contouring and quantification of anatomy and function of the heart.

Another area that is seeing a lot of research in in radiomics, where AI is being used to sift through thousands of CT scans to look for subtle imaging traits that may indicate the early development or worsening of disease. These subtle changes may not be evident to radiologists reading the scans, but AI software can identify similarities in patients as a trend and alert researchers to look at that specific trait as a potential imaging biomarker.

Other Key Trends and Technology at SCCT:

Top 9 Cardiovascular CT Studies in Past Year 

VIDEO: Photon Counting Detectors Will be the Next Major Advance in Computed Tomography

VIDEO: Increased Use of Cardiac CT During the COVID-19 Pandemic

VIDEO: Coronary Plaque Quantification Will Become Major Risk Assessment

VIDEO: Key Cardiac CT Papers Presented at SCCT 2020

Low-attenuation Coronary Plaque Burden May Become Next Big Cardiac Risk Assessment

Impact of Cardiac CT During COVID-19

Todd Villines, M.D., FACC, FAHA, MSCCT, explains how coronary plaque assessment will become a new risk assessment tool in cardiac CT. This was a key take away during the Society of Cardiovascular Computed Tomography (SCCT) 2020 virtual meeting in July. He is the Julian Ruffin Beckwith Professor of Medicine, Division of Cardiovascular Medicine, University of Virginia; editor-in-chief of the Journal of Cardiovascular CT (JCCT), and SCCT past-president. 

While basic plaque assessments have been available for several years on CT vendor and third-party advanced visualization software, it lacked automation standardization for what various values meant and clinical evidence it was relevant. However, several speakers in SCCT sessions said that is now changing, with more specific analysis being tested clinically and automation using artificial intelligence. 

Several key opinion leaders in cardiac CT said this new information and automation lwill likely lead to a revision of the current CAD-RADS scoring system used by radiologists and cardiologists when assessing the coronary event risk of patients. They are calling for the new CAD-RADS 2.0 to include a detailed plaque assessment.  

Other Key Trends and CT Technology at SCCT:

Top 9 Cardiovascular CT Studies in Past Year 

VIDEO: Photon Counting Detectors Will be the Next Major Advance in Computed Tomography

VIDEO: Increased Use of Cardiac CT During the COVID-19 Pandemic

VIDEO: Coronary Plaque Quantification Will Become Major Risk Assessment

VIDEO: Key Cardiac CT Papers Presented at SCCT 2020

Impact of Cardiac CT During COVID-19

VIDEO: Artificial Intelligence to Automate CT Calcium Scoring and Radiomics

Pooja Rao, Ph.D., co-founder of Qure.AI and head of research and development for the company, explains how the company's artificial intelligence (AI)-based auto detection software can be used to analyze radiology images. The vendor offers a U.S. Food and Drug Administration (FDA)-cleared emergency room computed tomography (CT) scan automated AI analysis tool to immediately identify areas of suspected intracranial bleeds and cranial fractures. The software offers immediate feedback for suspected areas of interest for the attending physician or stat read radiologist. This can enable faster diagnosis and treatment in neuro imaging cases, especially in meeting door to TPA time in patients with ischemic stroke.

Qure.AI also developed AI-based lung analysis software to detect a variety of abnormalities, which is working its way through FDA review. It is being used in some developing countries for mobile lung screening programs in remote areas. The vendor developed a self-contained unit for the AI to work without a PACS system or internet connection so there is immediate feedback on the image if someone may be positive. This greatly reduces the complexities of patient call backs in low-income areas that might be without out phones or web connectivity for followup. Rao explains how the technology is being implemented in this use case. AI might have its greatest impact on developing countries that do not have adequate healthcare resources of doctors.

qER detects and prioritizes scans containing Intracranial bleeds, cranial fractures, mass effect and midline shift. Image markings, bleed subtypes and labels are not available in the United States.

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