Videos | Artificial Intelligence | October 26, 2020

VIDEO: AI Features on the GE Voluson Swift Ultrasound System

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

Recent Videos View all 582 items

Coronavirus (COVID-19) | February 09, 2021

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.

 

Related Medical Imaging of COVID Content:

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.

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.

CT in a Box Helps Rapidly Boost Imaging Capability at COVID Surge Hospitals

VIDEO: How China Leveraged Health IT to Combat COVID-19 — Interview with Jilan Liu, M.D.,

Coronavirus (COVID-19) | January 26, 2021

This is an example of a COVID-19 (SARS-CoV-2) positive patient's lung computed tomography (CT) scan. The video scrolls through the image slices of the scan and shows the typical white, ground glass opacities (GGO) caused by COVID pneumonia. The pneumonia typically appears along the walls of each lobe of the lung, especially the chest wall and the lower portions of the lungs. This scan is from a Canon Aquilion Prime SP CT scanner and used Advanced intelligent Clear-IQ Engine (AiCE), an artificial intelligence-driven image reconstruction software to improve image quality of lower-dose scans. This was shown by Canon Medical as an exmaple of CT image quality for the virus at the 2020 Radiological Society of North American (RSNA) meeting. 

Read more about this system and its launch in 2020 to address COVID, Canon Medical Launches CT Solution for Patients with Viral Infectious Diseases.

VIDEO: How to Image COVID-19 and Radiological Presentations of the Virus interview with Margarita Revzin, M.D., associate professor of radiology and biomedical imaging, Yale School of Medicine.

Find more radiology clinical images of coronavirus in this photo gallery.

Find more radiology related COVID news and video

PET-CT | December 04, 2020

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

 

Artificial Intelligence | December 02, 2020

Kirti Magudia, M.D., Ph.D., an abdominal imaging and ultrasound fellow at the University of California San Francisco, explains how an automated deep learning analysis of abdominal computed tomography (CT) images can produce a more precise measurement of body composition and better predicts major cardiovascular events, such as heart attack and stroke, better than overall weight or body mass index (BMI). This was according to a study she presented at the 2020 Radiological Society of North America (RSNA) virtual meeting.

Unlike BMI, which is based on height and weight, a single axial CT slice of the abdomen visualizes the volume of subcutaneous fat area, visceral fat area and skeletal muscle area. However, manually measuring these individual areas is time intensive and costly. A multidisciplinary team of researchers, including radiologists, a data scientist and biostatistician, developed a fully automated artificial intelligence (AI) method to determine body composition metrics from abdominal CT images.

Statistical analysis demonstrated that visceral fat area was independently associated with future heart attack and stroke. BMI was not associated with heart attack or stroke.

Read more about this study

Find more RSNA news

Sponsored Videos View all 162 items

Information Technology | December 01, 2020

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.

X-Ray | November 28, 2020

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.

Enterprise Imaging | November 23, 2020

Fujifilm's next generation secure server-side viewer platform extends across enterprise imaging areas to bring together radiology, mammography and cardiology into a single zero footprint platform. Bill Lacy, vice president of medical informatics for Fujifilm Medical Systems USA recently talked with ITN about their Synapse 7x platform.

PACS | June 29, 2020

Kevin Borden, Vice President of Product, Healthcare IT for Konica Minolta, talks about Improving Access and Aiding Workflow with itnTV. He explains how the server-side rendering and zero-footprint viewer in its Exa PACS make it well-suited for remote reading.

Technology Reports View all 11 items

Artificial Intelligence | February 21, 2020

In Artificial Intelligence at RSNA 2019, ITN Contributing Editor Greg Freiherr offers an overview of artificial intelligence (AI) advances at the Radiological Society of North America (RSNA) 2019 annual meeting.

Enterprise Imaging | February 21, 2020

In Enterprise Imaging at RSNA 2019, ITN Contributing Editor Greg Freiherr offers an overview of enterprise imaging advances at the Radiological Society of North America (RSNA) 2019 annual meeting.

Conference Coverage View all 467 items

Coronavirus (COVID-19) | January 26, 2021

This is an example of a COVID-19 (SARS-CoV-2) positive patient's lung computed tomography (CT) scan. The video scrolls through the image slices of the scan and shows the typical white, ground glass opacities (GGO) caused by COVID pneumonia. The pneumonia typically appears along the walls of each lobe of the lung, especially the chest wall and the lower portions of the lungs. This scan is from a Canon Aquilion Prime SP CT scanner and used Advanced intelligent Clear-IQ Engine (AiCE), an artificial intelligence-driven image reconstruction software to improve image quality of lower-dose scans. This was shown by Canon Medical as an exmaple of CT image quality for the virus at the 2020 Radiological Society of North American (RSNA) meeting. 

Read more about this system and its launch in 2020 to address COVID, Canon Medical Launches CT Solution for Patients with Viral Infectious Diseases.

VIDEO: How to Image COVID-19 and Radiological Presentations of the Virus interview with Margarita Revzin, M.D., associate professor of radiology and biomedical imaging, Yale School of Medicine.

Find more radiology clinical images of coronavirus in this photo gallery.

Find more radiology related COVID news and video

Artificial Intelligence | December 02, 2020

Kirti Magudia, M.D., Ph.D., an abdominal imaging and ultrasound fellow at the University of California San Francisco, explains how an automated deep learning analysis of abdominal computed tomography (CT) images can produce a more precise measurement of body composition and better predicts major cardiovascular events, such as heart attack and stroke, better than overall weight or body mass index (BMI). This was according to a study she presented at the 2020 Radiological Society of North America (RSNA) virtual meeting.

Unlike BMI, which is based on height and weight, a single axial CT slice of the abdomen visualizes the volume of subcutaneous fat area, visceral fat area and skeletal muscle area. However, manually measuring these individual areas is time intensive and costly. A multidisciplinary team of researchers, including radiologists, a data scientist and biostatistician, developed a fully automated artificial intelligence (AI) method to determine body composition metrics from abdominal CT images.

Statistical analysis demonstrated that visceral fat area was independently associated with future heart attack and stroke. BMI was not associated with heart attack or stroke.

Read more about this study

Find more RSNA news

Information Technology | December 01, 2020

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.

Remote Viewing Systems | November 28, 2020

Konica Minolta’s theme for RSNA 2020 is Depth of Vision. ITN recently talked with David Widmann, President and CEO of Konica Minolta Healthcare Americas, about this focus and their key messages for customers and RSNA attendees.

Radiation Oncology View all 116 items

Information Technology | December 01, 2020

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.

Radiation Therapy | November 15, 2020

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

 

Contrast Media Injectors | May 22, 2020

At this year’s RSNA ITN sat down with Dennis Durmis, Senior Vice President, Bayer Radiology to discuss Radiology trends. Discussion topics centered around three key areas where Bayer Radiology is responding to trends; including digitalization, workflow efficiencies and efforts to bring more focus to the Radiology patient experience. During the interview Dennis discussed Bayer’s digital strategy, features and benefits of their new injector, the MEDRAD® Stellant FLEX Injector and Bayer’s education efforts of the imaging needs of women with Dense Breast.

Artificial Intelligence | February 21, 2020

In Artificial Intelligence at RSNA 2019, ITN Contributing Editor Greg Freiherr offers an overview of artificial intelligence (AI) advances at the Radiological Society of North America (RSNA) 2019 annual meeting.

Radiology Imaging View all 357 items

Coronavirus (COVID-19) | February 09, 2021

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.

 

Related Medical Imaging of COVID Content:

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.

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.

CT in a Box Helps Rapidly Boost Imaging Capability at COVID Surge Hospitals

VIDEO: How China Leveraged Health IT to Combat COVID-19 — Interview with Jilan Liu, M.D.,

Coronavirus (COVID-19) | January 26, 2021

This is an example of a COVID-19 (SARS-CoV-2) positive patient's lung computed tomography (CT) scan. The video scrolls through the image slices of the scan and shows the typical white, ground glass opacities (GGO) caused by COVID pneumonia. The pneumonia typically appears along the walls of each lobe of the lung, especially the chest wall and the lower portions of the lungs. This scan is from a Canon Aquilion Prime SP CT scanner and used Advanced intelligent Clear-IQ Engine (AiCE), an artificial intelligence-driven image reconstruction software to improve image quality of lower-dose scans. This was shown by Canon Medical as an exmaple of CT image quality for the virus at the 2020 Radiological Society of North American (RSNA) meeting. 

Read more about this system and its launch in 2020 to address COVID, Canon Medical Launches CT Solution for Patients with Viral Infectious Diseases.

VIDEO: How to Image COVID-19 and Radiological Presentations of the Virus interview with Margarita Revzin, M.D., associate professor of radiology and biomedical imaging, Yale School of Medicine.

Find more radiology clinical images of coronavirus in this photo gallery.

Find more radiology related COVID news and video

PET-CT | December 04, 2020

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

 

Artificial Intelligence | December 02, 2020

Kirti Magudia, M.D., Ph.D., an abdominal imaging and ultrasound fellow at the University of California San Francisco, explains how an automated deep learning analysis of abdominal computed tomography (CT) images can produce a more precise measurement of body composition and better predicts major cardiovascular events, such as heart attack and stroke, better than overall weight or body mass index (BMI). This was according to a study she presented at the 2020 Radiological Society of North America (RSNA) virtual meeting.

Unlike BMI, which is based on height and weight, a single axial CT slice of the abdomen visualizes the volume of subcutaneous fat area, visceral fat area and skeletal muscle area. However, manually measuring these individual areas is time intensive and costly. A multidisciplinary team of researchers, including radiologists, a data scientist and biostatistician, developed a fully automated artificial intelligence (AI) method to determine body composition metrics from abdominal CT images.

Statistical analysis demonstrated that visceral fat area was independently associated with future heart attack and stroke. BMI was not associated with heart attack or stroke.

Read more about this study

Find more RSNA news

Molecular Imaging View all 29 items

PET-CT | December 04, 2020

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

 

Artificial Intelligence | September 25, 2020

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.

 

Related Artificial Intelligence in Cardiology Content:

VIDEO: Machine Learning for Diagnosis and Risk Prediction in Nuclear Cardiology — Interview with Piotr J. Slomka, Ph.D.,

Artificial Intelligence Applications in Cardiology

VIDEO: Artificial Intelligence May Improve Cath Lab Interventions — Interview with Nick West, M.D., Abbott CMO

How Artificial Intelligence Will Change Medical Imaging

VIDEO: Artificial Intelligence for Echocardiography at Mass General — Interview with Judy Hung, M.D.

VIDEO: ACC Efforts to Advance Evidence-based Implementation of AI in Cardiovascular Care — Interview with John Rumsfeld, M.D.

VIDEO: Overview of Artificial Intelligence and its Use in Cardiology — Interview with Anthony Chang, M.D.

For more AI in cardiology content

Coronavirus (COVID-19) | April 18, 2020

Stephen Bloom, M.D., FASNC, director of noninvasive cardiology (cardiac CT, nuclear cardiology and echocardiography) at Midwest Heart and Vascular Associates, Overland Park, Kansas. He is also a member of the American Society of Nuclear Cardiology (ASNC) Board of Directors, explains some of the issues involved and protocols used for cardiac imaging during the COVID-19 pandemic. His discussion includes computed tomography, cardiac ultrasound and nuclear imaging.

Right now, Bloom said it is difficult to test everybody and there is a shortage of masks, gowns and other personal protective equipment (PPE), and the imaging equipment needs to be sanitized each time it is used. He said it is just is not possible to image all the patients who need imaging right now. Hospitals also are trying to limit the number of healthy people people coming into hospitals for routine visits and tests to reduce their potential exposure to the novel coronavirus (COVID-19, SARS-CoV-2) and help containment efforts. 

"The tests should be done, very simply, if it changes the care of the patient. If it doesn't change the care of the patient, and it can be postponed, it should be postponed," Bloom explained. "I would say 80 percent of our cardiac imaging exams have stopped. It has been very dramatic."

 

Related Imaging Precautions During COVID-19 Content:

Cardiac Imaging Best Practices During the COVID-19 Pandemic

Best Practices for Nuclear Cardiology Laboratories During the Coronavirus (COVID-19) Pandemic

ASE Guidelines for the Protection of Echocardiography Providers During the COVID-19 Outbreak 

VIDEO: Best Practices for Nuclear Cardiology During the COVID-19 Pandemic — Interview with Hicham Skali, M.D.

VIDEO: Cancelling Non-essential Cardiac Procedures During the COVID-19 Outbreak — Interview with Ehtisham Mahmud, M.D. 

VIDEO: 9 Cardiologists Share COVID-19 Takeaways From Across the U.S.  

VIDEO: Telemedicine in Cardiology and Medical Imaging During COVID-19 — Interview with Regina Druz, M.D.

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

Study Looks at CT Findings of COVID-19 Through Recovery

Experts Stress Radiology Preparedness for COVID-19

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

VIDEO: How China Leveraged Health IT to Combat COVID-19 — Interview with Jilan Liu, M.D., CEO for the HIMSS Greater China

ACR Recommendations for the Use of Chest Radiography and CT for Suspected COVID-19 Cases

VIDEO: What Cardiologists Need to Know about COVID-19 — Interview with Thomas Maddox, M.D.

The Cardiac Implications of Novel Coronavirus

Coronavirus (COVID-19) | April 04, 2020

Hicham Skali, M.D., a staff cardiologist and member of the Non-invasive Cardiovascular Imaging Program at Brigham and Women’s Hospital (BWH), and at Brigham and Women’s / Massachusetts General Health Care Center at Foxborough, explains the new recommendations from the American Society of Nuclear Cardiology (ASNC) and from imagers in China and Singapore. The ASNC created a best practices document for nuclear cardiology laboratories during the novel coronavirus (COVID-19, SARS-CoV-2) pandemic. The suggestions in the guidelines can ally to any imaging modality, including computed tomography (CT), MRI and ultrasound. 

Skali elaborates on the following points in his discussion, which are specific recommendations in the ASNC and SNMMI COVID-19 guidance document:
   • Rescheduling non-urgent visits
   • Rescheduling elective surgeries and procedures
   • Using separate spaces for patients with known or suspected COVID-19 to prevent spread
   • Ensuring supplies are available
   • Promoting use of telehealth
   • Screen staff, patients and visitors before they enter the department
   • Minimize non-essential visitors into the department
   • Record symptoms at the start of the shift
   • Use personal protective equipment (PPE)for healthcare personnel
   • If available, use PPE for patients due to concern of asymptomatic transmission of COVID-19
   • Maintain strict hand hygiene
   • Maintain 6 feet distance in all patient/staff interactions when possible
   • Work remotely whenever feasible, especially with ready studies
   • Rotating staff schedules for on-site and off-site work
   • Use of rest only studies if possible
   • Use of half-time SPECT to speed exam times
   • Use of PET if available to speed exam times

Skali served as the moderator in for the ASNC on demand webinar COVID-19 Preparedness for Nuclear Cardiology Labs: Insights from the US, China and Singapore.

VIDEO: Telemedicine in Cardiology and Medical Imaging During COVID-19 — Interview with Regina Druz, M.D., an ASNC Board member and also a speaker during the ASNC webinar.

Find more news and video on relating to COVID-19 and its impact on radiology

Information Technology View all 262 items

PET-CT | December 04, 2020

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

 

Artificial Intelligence | December 02, 2020

Kirti Magudia, M.D., Ph.D., an abdominal imaging and ultrasound fellow at the University of California San Francisco, explains how an automated deep learning analysis of abdominal computed tomography (CT) images can produce a more precise measurement of body composition and better predicts major cardiovascular events, such as heart attack and stroke, better than overall weight or body mass index (BMI). This was according to a study she presented at the 2020 Radiological Society of North America (RSNA) virtual meeting.

Unlike BMI, which is based on height and weight, a single axial CT slice of the abdomen visualizes the volume of subcutaneous fat area, visceral fat area and skeletal muscle area. However, manually measuring these individual areas is time intensive and costly. A multidisciplinary team of researchers, including radiologists, a data scientist and biostatistician, developed a fully automated artificial intelligence (AI) method to determine body composition metrics from abdominal CT images.

Statistical analysis demonstrated that visceral fat area was independently associated with future heart attack and stroke. BMI was not associated with heart attack or stroke.

Read more about this study

Find more RSNA news

Information Technology | December 01, 2020

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.

Remote Viewing Systems | November 28, 2020

Konica Minolta’s theme for RSNA 2020 is Depth of Vision. ITN recently talked with David Widmann, President and CEO of Konica Minolta Healthcare Americas, about this focus and their key messages for customers and RSNA attendees.

Women's Health View all 75 items

Artificial Intelligence | November 11, 2020

Artificial Intelligence (AI) is becoming more common place in radiology practices, and emerging technologies are providing radiologists with sophisticated detection software to aid their reading and provide support for a busy workflow. With the progression of AI technology, vendors must look not only at what AI can do for the radiologist, but how the radiologist and the technician interact with that technology –  the goal should be increasing accuracy while also positively improving workflow. GE Healthcare is working to improve radiology AI workflow in its Centricity Universal Viewer.

Three key opinion leaders offers their views on what is needed to make AI more valauble and accessible to radiologists. These include:

   • Amy Patel, M.D., breast radiologist, medical director, Liberty Hospital Women's Imaging, assistant professor of radiology, University of Missouri-Kansas City.

   • Prof. Dr. Thomas Frauenfelder, M.D., vice chairman and professor of thoracic radiology, Institute for Diagnostic and Interventional Radiology, University of Zurich.

   • Randy Hicks, M.D., chief executive officer, Regional Medical Imaging.

 

Learn more about the Centricity Universal Viewer in the VIDEO: How GE Healthcare’s Zero Footprint Remote Image Viewer Supports Clinical Care

 

 

 

 

 

MRI Breast | October 14, 2020

Professor Christiane Kuhl, M.D., director of radiology, University Hospital Aachen, Germany, explains how breast magnetic resonance imaging (MRI) can be used to clearly identify breast cancers in women with dense breast tissue. In women with dense breasts, it can be very difficult to detect many cancers on standard mammograms because the cancers and dense tissue both appear white. MRI can help clearly define tumors and identify which nodules are cancer and which are benign, which can help greatly reduce the need for biopsies.

Kuhl is an expert in breast imaging and breast MRI. She helped develop an a shortened MRI protocol that allows breast MR images to be created in 3 minutes or less, rather than standard protocols that can take up to 30 minutes. In the interview she shows patient case examples of standard mammograms and the MRI supplemental imaging for the same patient to show the hidden tumors. 

She also explains the differences between standard 2-d mammography, the current standard of care, and the newer 3-D mammogram tomosythnesis technology, breast ultrasound and breast MRI technologies.

Read the related article Use of Breast MRI Screening in Women With Dense Breasts, which includes case examples comparing mammograms to the patients' breast MRIs.

Other video interviews with Dr. Kuhl:

VIDEO: Explaining Dense Breasts

VIDEO: The Impact of COVID-19 on Breast Imaging

 

Related Breast MRI Content:

Abbreviated MRI Outperforms 3-D Mammograms at Finding Cancer in Dense Breasts

VIDEO: Explaining Dense Breasts — Interview with Christiane Kuhl, M.D.

VIDEO: Use of Breast MRI Improved Cancer Detection in Dense Breasts in Dutch Study — Interview with Gillian Newstead, M.D.

Technologies to Watch in Breast Imaging

Screening MRI Detects BI-RADS 3 Breast Cancer in High-risk Patients

Rapid Breast MRI Screening Improves Cancer Detection in Dense Breasts

Breast MRI in Cancer Diagnosis
 

Coronavirus (COVID-19) | October 14, 2020

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

VIDEO: Use of Breast MRI Screening in Women With Dense Breasts

 

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

Breast Imaging in the Age of Coronavirus

How COVID-19 Appears on Medical Imaging — Photo Gallery

Half of Breast Cancer Survivors Had Delays in Care Due to COVID-19

Insight on the Impact of COVID-19 on Medical Imaging

Delay in Breast Cancer Operations Appears Non Life-threatening for Early-stage Disease

Hologic and Sheryl Crow Begin Back to Screening Campaign

A Slow Return to Normalcy in Breast Imaging

Breast Density | October 13, 2020

Professor Christiane Kuhl, M.D., director of radiology, University Hospital Aachen, Germany, explains what it means to have dense breasts and how density can hide cancers in mammograms. She offers an explanation describing dense breast tissue and that this occurs in about half of women. Density is itself a risk factor for breast cancer and the fact that dense tissue hides cancers on mammography means that supplemental imaging is needed to accurately diagnose these patients and avoid false positives, or needless tissue biopsies. Breast ultrasound and breast magnetic resonance imaging (MRI) can be used to see through dense tissue to better identify cancers and avoid the need for many biopsies.

Other video interviews with Dr. Kuhl:

VIDEO: Use of Breast MRI Screening in Women With Dense Breasts

VIDEO: The Impact of COVID-19 on Breast Imaging

 

Related Dense Breast Content:

Breast Density Explained

Animation to Bring Clarity to Dense Breasts

Improving Clinical Image Quality for Breast Imaging

Breast Imaging in the Age of Coronavirus

Abbreviated MRI Outperforms 3-D Mammograms at Finding Cancer in Dense Breasts

VIDEO: Use of Breast MRI Improved Cancer Detection in Dense Breasts in Dutch Study — Interview with Gillian Newstead, M.D.

Technologies to Watch in Breast Imaging

Screening MRI Detects BI-RADS 3 Breast Cancer in High-risk Patients