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Talking Trends with Bayer: Transforming Radiology with Digital Solutions

Artificial Intelligence | August 18, 2022

Digital solutions like AI and the cloud are driving innovation and transforming the way radiologists and imaging centers approach their work. ITN recently spoke with Alexandre Salvador, vice president and global head of digital business solutions for Bayer's radiology business, about Calantic Digital Solutions, Bayer's new cloud-based platform providing AI applications integrated into the clinical workflow of the radiology department. 

Information Technology

Artificial Intelligence | August 18, 2022

Digital solutions like AI and the cloud are driving innovation and transforming the way radiologists and imaging centers approach their work. ITN recently spoke with Alexandre Salvador, vice president and global head of digital business solutions for Bayer's radiology business, about Calantic Digital Solutions, Bayer's new cloud-based platform providing AI applications integrated into the clinical workflow of the radiology department. 

PACS | March 14, 2022

Software automation can help improve many processes, including verifying eligibility for patient exams, navigating the patient responsibility landscape, and meeting the upcoming CDSM mandate for Appropriate Use CriteriaITN recently spoke with with Kevin Borden, Vice President of Product, HCIT, for Konica Minolta Healthcare Americas about how Konica Minolta is leveraging automation to enhance productivity and efficiency in these areas. 

Related content:

New Exa Platform Functionality Automates Decision Support, Insurance-Related Tasks for Enhanced Productivity and Profitability

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Radiation Oncology | February 02, 2022

Douglas E. Holt, M.D., a radiation oncologist at Eastern Idaho Regional Medical Center, explains the use of 3-D virtual reality volumetric imaging review to help improve cancer patients’ understanding of their disease and treatment. Pictures are worth a thousand words, and moving pictures inside a patient's body even more. Holt said using virtual reality to go through the patient's anatomy in 3D and to show them what is wrong and how it will be treated offers a new level of understanding that is not possible using a discussion or a couple still images from their medical imaging.

Holt presented this study as a late-breaker at the 2021 American Society of Radiation Oncology (ASTRO) annual meeting.

Find more ASTRO videos and news

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Enterprise Imaging | January 27, 2022

Rik Primo, principle at Primo Medical Imaging Informatics Consultants and former health IT developer with Siemens, Philips and Agfa, explains the difference cloud-native versus cloud-enabled PACS and radiology enterprise imaging systems. He spoke with ITN during RSNA 2021.the Radiological Society of North America (RSNA) 2021 annual meeting.

Find more RSNA news and video

Related content on enterprise imaging

 

Artificial Intelligence | January 27, 2022

Emanuel Kanal, M.D., FACR, FISMRM, AANG, director of the department of emergency radiology and teleradiology, director of MRI services, and professor of radiology and neuroradiology at the University of Pittsburgh, explains artificial intelligence (AI) is the biggest over all trend in radiology at  the Radiological Society of North America (RSNA) 2021 annual meeting.

VIDEO: Artificial Intelligence Trends in Medical Imaging — Interview with Sanjay Parekh, Ph.D.

VIDEO: Examples of Artificial Intelligence Pulmonary Embolism Response Team Apps

Technology Report: Artificial Intelligence in Radiology 2021

Find more AI news

Find more RSNA news and video

Computed Tomography (CT) | January 27, 2022

Cynthia McCollough, Ph.D., director of Mayo Clinic's CT Clinical Innovation Center,  explains how photon-counting computed tomography (CT) detectors work and why it is a better technology over conventional CT systems. She helped Siemens develop the Naeotom Alpha, the first photo-counting CT system to be approved by the FDA in the fall of 2021. She spoke to ITN at the Radiological Society of North America (RSNA) 2021 annual meeting.

Read more about the first commercial photon-counting scanner 

The device uses the emerging CT technology of photon-counting detectors, which can measure each individual X-ray photon that passes through a patient's body, as opposed to current systems which use detectors that measure the total energy contained in many X-rays at once. By "counting" each individual X-ray photon, more detailed information about the patient can be obtained and used to create images with less information that is not useful, such as image noise. 

Current CT technology uses a two-step conversion process to convert X-ray photons into visible light using a scintillator layer in the detector. Then, photo diode light sensors turn the visible light into a digital signal. Due to this intermediate step, important information about the energy of the X-rays is lost and no longer available to aid in diagnosis. Also, contrast is reduced and images are not as clear.

Photon-counting detectors use a single step of direct conversion of X-rays into electrical current, and skips the step of converting X-rays into visible light. This allows the energy thresholds of each pulse to be collected and binned based on different kilovolt (kV) energy levels. This creates data to improve contrast and enable dual-energy, spectral imaging. The direct conversion also helps improve image quality without information loss. This improves image sharpness and contrast.

Photon-counting detectors have already been used for several years in high-energy physics and nuclear imaging. However, these previously generation photon-counting detectors could not be used with a clinical CT scanner because they could not keep up with the high higher rate of photons reaching the detector. The detector on the Naeotom Alpha was designed for this increased speed.

Related Photon-counting CT Content:

Mayo Clinic Begins Use of Third-Generation Photon-counting CT Clinical Research Detector

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Artificial Intelligence | January 13, 2022

Here are two examples of artificial intelligence (AI) driven pulmonary embolism (PE) response team apps featured by vendors Aidoc and Viz.AI at the 2021 Radiological Society of North America (RSNA) 2021 meeting.

The AI scans computed tomography (CT) image datasets as they came off the imaging system and looked for evidence of PE. If detected by the algorithm, it immediately sends an alert to the stroke care team members via smartphone messaging. This is done before the images are even loaded into the PACS. The radiologist on the team can use a link on the app to open the CT dataset and has basic tools for scrolling, windowing and leveling to determine if there is a PE and the severity. The team can then use the app to send messages, access patient information, imaging and reports. This enabled them all to be on the same page and can communicate quickly via mobile devices, rather than being required to use dedicated workstations in the hospital. 

Both vendors showed similar apps for stroke at RSNA 2019. That idea for rapid alerts, diagnosis and communications for acute care teams has now expanded to PE and also for aortic dissection and abdominal aortic aneurysms (AAA). AI.Viz and Aidoc are looking at expanding this type of technology for other acute care team rolls, including heart failure response. 

Read more about this technology in the article AI Can Facilitate Automated Activation of Pulmonary Embolism Response Teams.

Find more AI news

Find more RSNA news and video

Enterprise Imaging | January 13, 2022

Steve Holloway, company director at Signify Research, explains the trends he has seen over the past couple years in enterprise imaging. He spoke to ITN at the 2021 Radiological Society of North America meeting.

Holloway shared how medical imaging systems are expanding to include all departments in healthcare system enterprises that generate data, images and waveforms, so these items can be stored in a central location, rather than disparate silos or in separate systems requiring multiple logins or specific workstations. Most of these systems are are web enabled or web based, allowing users to work from anywhere as long as they have an internet connection. Most enterprise imaging systems also use a web-based vendor neutral archive, allowing DICOM and non-DICOM images to be stored there. All of these features allow easier and faster access to patient information and images.

He said these systems are becoming more inclusive of ologies outside of radiology and cardiology. Most notably is digital pathology, which was featured by many enterprise imaging vendors at RSNA 2021. 

Enterprise imaging systems are also accepting point-of-care ultrasound (POCUS), which has exploded in use over the past two years with COVID, Holloway said.

Find more RSNA news and video

VIDEO: Trends in Radiology IT seen at RSNA 2021 — Interview with Jef Williams, Paragon Consultants

VIDEO: Artificial Intelligence Trends in Medical Imaging — Interview with Sanjay Parekh, Ph.D, from Signify Research

VIDEO: Examples of Improved PACS Workflow to Aid Speed and Efficiency 

VIDEO: The New Normal of Home Workstations, Teleradiology and Remote Reading — Interview with Elizabeth Hawk, M.D.

Technology Report: Artificial Intelligence in Radiology 2021

Technology Report: Enterprise Imaging 2019
 

 

Enterprise Imaging | January 06, 2022

Jef Williams, MBA, PMP, CIIP, managing partner, Paragon Consulting Partners LLC, explains trends he saw at the 2021 Radiological Society of North America (RSNA) meeting. These include radiology IT trends in the evolution of enterprise imaging, increasing use of artificial intelligence (AI) and the movement to web-based systems.

VIDEO: Artificial Intelligence Trends in Medical Imaging — Interview with Sanjay Parekh, Ph.D, from Signify Research

VIDEO: Trends in Enterprise Imaging From Signify Research — Interview with Steve Holloway, Signify Research

Technology Report: Artificial Intelligence in Radiology 2021

Technology Report: Enterprise Imaging 2019

VIDEO: Examples of Improved PACS Workflow to Aid Speed and Efficiency 

VIDEO: The New Normal of Home Workstations, Teleradiology and Remote Reading — Interview with Elizabeth Hawk, M.D.

VIDEO: Mammography Trends and Advances at RSNA 2021 — Interview with Stamatia Destounis, M.D.

Find more RSNA news and video

Teleradiology | December 10, 2021

Elizabeth Hawk, M.D., Ph.D., director of innovation Engagement at Rad Partners, a regional president for Matrix Teleradiology, and assistant professor of medicine at Stanford, explains how the COVID-19 pandemic has helped advance home reading and changed radiology.

While teleradiology and remote reading is not new, its expansion was greatly accelerated in 2020-2021 due to COVID. Early in the pandemic, hospitals tried to get as many of their employees as possible to work remotely, and radiologists who wanted to read from home were allowed to do so in large numbers. The past two years has taught many people that remote reading from home is possible and it also can aid the balance between work and family life. Hawk said remote reading will likely be the new normal even after the pandemic.

Hawk presented in a session on this topic at the 2021 Radiological Society of North America (RSNA) annual meeting. She said many radiologists from her practice were already reading from home prior to the pandemic, so they had the experience to quickly ramp up expansion during COVID. She offers advice to hospitals that want to introduce or expand home radiology reading. 

Find more teleradiology news

Find more RSNA news and video

Artificial Intelligence | December 08, 2021

Sanjay Parekh, Ph.D., Signify Research senior market analyst, explains some of the recent trends in the application of artificial intelligence (AI) in radiology at the 2021 Radiological Society of North America (RSNA) meeting.

He discusses three trends in AI at RSNA, including:
   • AI-based critical care team tools for rapid communication and assessment of patient imaging. This is activated by an AI first pass review of the images. This includes response team alerts for pulmonary embolism (PE), stroke, aortic dissection and acute heart failure.
   • AI systems now offering numerous algorithms to perform multiple tasks, rather than a single function, adding greater valve for those AI apps.
   • Greater integration of AI apps into PACS so it fits into the radiology workflow.

Find more AI news

Find more RSNA news and video

Oncology Information Management Systems (OIMS) | November 12, 2021

An example of the Varian Noona software used by clinicians to interface with oncology patients demonstrated at the American Society of Radiation Oncology (ASTRO) 2021 meeting. It allows bi-direction communication between the care team and the patient’s smartphone. This included reporting complains about side effects, pain, questions for the physician and surveys. The data the interfaces with the patient record so anyone on the care team can access it or reach out to the patient.

Photo Gallery of Technologies at ASTRO 2021

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Enterprise Imaging | September 03, 2021

ITN Editor Dave Fornell collected numerous examples of how PACS and enterprise imaging vendors are improving the speed and workflow of their systems during booth demonstrations at the 2021 Healthcare Information Management Systems Society (HIMSS). The 11 minute video condenses down the highlights of workflow efficiencies seen during two days o vendor booth tours.

There was a clear trend of many vendors moving to new platforms that leverage more modern cloud-platform interfaces. This enables faster study loading speeds over web connections. These platforms are also using deeper integration of third-party applications and artificial intelligence (AI) software that do not require separate logins or workflows. Read more about these key trends observed at HIMSS 2021.

Vendors also showed various ways they have speed up radiology workflows. These included easier to customize hanging protocols, automated fetching of prior exams, synchronizing views and scrolling between a current a prior exams, use of timeline views of patient priors and procedures to make it easier to find relevant images and reports, and integration of all types of images into one unified viewer. 

Specific examples in this video include: 
   • Visage Imaging: Example of high speed cloud PACS access to 3D mammograms and and priors. This first video clip shows a demonstration of opening large datasets in a matter of a couple seconds over a network connection from a tethered cellphone.
   • Visage Imaging: Ability to access multiple modalities on one PACS viewer
   • GE Healthcare: Examples of fast access to priors and location on screen 
   • GE Healthcare: Example of deep integration of third-party AI software
   • Siemens: Overview of its Lung AI Pathway Companion workflow  
   • Change Healthcare: Enabling fast ability to free rotate around lung anatomy rather than going slice by slice manually 
   • Change Healthcare: Color-coded bar shows loading progress of an image or data set
   • Infinitt: Hanging protocol automation to find same view on prior and link for synchronized scrolling   
   • Infinitt: Use of timeline to get quick view of prior reports and images without needing to open whole exam 
   • Siemens: Example of deeper integration with third-party apps, in this case Epsilon strain echo analysis  
   • Fujifilm: Integrated advanced visualization in the radiology workflow for liver segmentation used for surgical or embolization planning 
   • Fujifilm: Example of life-like cinematic rendering of a CT scan offers new ways to view anatomy and explain it to a patient 
   • Visage Imaging: Example of enterprise platform able to bring in full original format advanced visualization reconstructed images on a single platform viewer

Related Medical Imaging IT Content From HIMSS 2021:

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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VIDEO: Examples of COVID-19 CT Scan Analysis Software

 

 

Coronavirus (COVID-19) | August 31, 2021

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.

VIDEO: Coordinating Followup for Radiology Incidental Findings — Interview with David Danhauer, M.D.

VIDEO: Cardiology AI Aggregates Patient Data and Enables Interactive Risk Assessments

VIDEO: Example of Epsilon Strain Imaging Deep Integration With Siemens CVIS

 

Information Technology | August 30, 2021

David Danhauer, M.D., FAAP, FHIMSS, chief medical information officer, Owensboro Health, Owensboro, Ky., explains the implementation of healthcare information technology (IT) to coordinate followup on incidental radiology findings. He presented on this topic in a session at the Healthcare Information Management Systems Society (HIMSS) 2021 meeting. 

Their system starts with key words being identified to flag incidental findings by the voice recognition system used to enter radiology report information. IT interfaces with the electronic medical record create a list of patients that need followup and what departments the incidental findings relate to so a coordinator can connect the patient with the proper subspecialty.

Danhauer said many of the incidental findings at his center include lung nodules and abdominal aortic aneurisms. In the past, many of these were lost to followup, but the new system now promotes follow through to get the patient the care they need. This has helped increase revenue, improve patient care and lowers the health system's liability profile. 

The system experienced several patient safety events due to gaps in care coordination with incidental findings documented in the radiology report, but missed by referring physicians. A patient safety initiative he helped implement automating the workflow resulted in a nine-fold increase in identifying and communicating incidental findings for improved patient safety. 

Read about more advances in PACS and enterprise imaging at HIMSS 21.

Photo Gallery of New Technologies at HIMSS 2021

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

 

 

 

Enterprise Imaging | August 27, 2021

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

Enterprise Imaging | August 06, 2021

Integrated Speech recognition solutions are becoming a necessary part of radiology reporting platforms. Konica Minolta recently announced a partnership with nVoq to integrate a speech to text solution into their Exa Platform

ITN recently spoke with Kevin Borden, Vice President of Product, Healthcare IT for Konica Minolta and Chad Hiner, Vice President of Customer Experience for nVoq, to talk about how this integration is improving the Exa user experience.

Related enterprise imaging content:

Talking Trends with Konica Minolta

BLOG: Zero-footprint Viewer with Server-side Rendering Pushes Imaging Forward During Pandemic

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BLOG: Artificial Intelligence for Clinical Decision Support and Increased Revenues

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Artificial Intelligence | July 22, 2021

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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Magnetic Resonance Imaging (MRI) | March 19, 2021

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.

 

Related MRI and COVID Content:

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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.

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.

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

 

 

 

 

 

Artificial Intelligence | October 26, 2020

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

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

Remote Viewing Systems | September 09, 2020

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

Ultrasound Imaging | August 13, 2020

This is a tutorial video on how to perform an artificial intelligence (AI) automated cardiac ejection fraction measurement using the GE Healthcare Vscan Extend point-of-care ultrasound (POCUS) system and the LVivo EF app, developed and licensed by DiA Imaging Analysis. This FDA-cleared app enables an automated edge detection of left ventricular endocardium and calculates end-diastolic, end-systolic volumes and ejection fraction, using apical 4-chamber view.

the LVivo EF app was showcased by GE Healthcare in its virtual booth at the American Society of Echocardiography (ASE) 2020 virtual meeting. POCUS imaging has emerged as a primary imaging modality for bedside assessment of COVID-19 patients in 2020.

 

Related ASE News and POCUS Content:

VIDEO: Automated Cardiac Ejection Fraction for Point-of-care-ultrasound Using Artificial Intelligence

LVivo EF Comparable to MRI, Contrast Echo in Assessing Ejection Fraction

GE Highlights New Echocardiography Technologies at ASE 2020

Other ASE news and video

Cardiac Imaging | August 12, 2020

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

Computed Tomography (CT) | August 12, 2020

 

Todd Villines, M.D., FACC, FAHA, MSCCT, said photon counting CT detectors were a key new technology discussed at the Society of Cardiovascular Computed Tomography (SCCT) 2020 virtual meeting. He said the technology will likely replace conventional CT detectors in the next decade. Advantages of photon counting detectors include the ability to enhance image quality at the detector level with much clearer details than conventional CT technology.

These new detectors also can take a single scan and bin the various energies to reconstruct a range of mono-energtic scan renderings similar to dual-energy CT, but on a wider spectrum of kV levels. This spectral aspect of photon counting also allows material decomposition based on the chemical elements that make up various materials in the scan, including calcium and metals that make up stents, orthopedic implants and replacement heart valves. This enables easier, automated removal of metal blooming artifacts and the ability to clearly image inside calcified arteries.

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.

 

Other Key Trends and CT Technology at SCCT:

Top 9 Cardiovascular CT Studies in Past Year 

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

VIDEO: Artificial Intelligence to Automate CT Calcium Scoring and Radiomics

 

 

 

Artificial Intelligence | August 12, 2020

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

 

CT Angiography (CTA) | August 11, 2020

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

 

Artificial Intelligence | July 31, 2020

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.

Related Radiology AI Related Content:

Qure.ai Receives Industry's First 4-in-1 FDA Clearance for Medical Imaging AI

Technology Report: Artificial Intelligence at RSNA 2019

The Radiology AI Evolution at RSNA 2019

Artificial Intelligence Pinpoints Nine Different Abnormalities in Head Scans

Nanox Partners With Qure.ai to Integrate AI-based Algorithms for Medical Imaging

Qure.ai Launches Solutions to Help Tackle COVID19
 

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.

Coronavirus (COVID-19) | March 27, 2020

Regina Druz, M.D., FASNC, a member of the American Society of Nuclear Cardiology (ASNC) Board of Directors, chairwomen of the American College of Cardiology (ACC) Healthcare Innovation Section, and a cardiologist at Integrative Cardiology Center of Long Island, N.Y., explains the rapid expansion of telemedicine with the U.S. spread of novel coronavirus (COVID-19, SARS-CoV-2).

Druz spoke on the unprecedented expansion of telemedicine in the U.S. under COVID-19, seeing more use in the last two months, as opposed to the past two decades. The Centers for Medicare and Medicaid Services (CMS) previously only reimbursed for Telehealth in rural areas it determined had a shortage of doctors. However, in early March 2020, CMS dropped the geographic requirements and allowed Telehealth usage across th country as a way to mitigate person-to-person contact and keep vulnerable, older patients at home for routine check ups with doctors.

Druz has subspecialty certifications in nuclear cardiology, adult echocardiography and cardiac computed tomography (CT) and explains how Telehealth can be used to pre-screen patients and get patient sign off on procedures prior to coming in for an exam, helping speed the process in the hospital and limit personal contact.

Concerns about the rpaid spread of COVID-19 also has driven many radiology departments to convert to wider use of teleradiology to allow more radiologists to work from home and reduce person-to-person contact within the hospitals. 

Watch the related VIDEO: Use of Teleradiology During the COVID-19 Pandemic — an interview with John Kim, M.D., chairman, Department of Radiology, THR Presbyterian Plano, Texas, and chief technology officer at Texas Radiology Associates.

 

Related COVID-19 Content:

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

Study Looks at CT Findings of COVID-19 Through Recovery

Experts Stress Radiology Preparedness for COVID-19

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

 

 

 

Teleradiology | March 26, 2020

John Kim, M.D., chairman, Department of Radiology, THR Presbyterian Plano, Texas, and chief technology officer at Texas Radiology Associates, explains the use of teleradiology during the novel coronavirus (COVID-19) outbreak in the U.S. The radiology group is part of Collaborative Imaging, a radiologist owned teleradiology alliance that enables radiologists to read studies using secure web links and an app.

The rapid spread of coronavirus has increased the value telemedicine solutions to help prevent person-to-person contact and take some clinicians out of the hospitals to work at home or office locations. This includes the use of teleradiology tools to read images and communicate with referring physicians.

Telemedicine allows for the continuity of care within healthcare facilities and patients and allows for safe distance without sacrificing the quality of care. It also saves patients from spreading germs to others, like while on public transportation or in the doctor’s waiting room, and to the healthcare providers who tend to them. Televisits also only last an average of 10 minutes, allowing physicians to assess patients more quickly and easily. 

Coronavirus (COVID-19) | March 25, 2020

Jilan Liu, M.D., MHA, CEO for the HIMSS Greater China, explains how health information technology (HIT) was leveraged in China to help fight the outbreak of novel coronavirus (COVID-19, SARS-CoV-2). Her discussion includes use of artificial intelligence, telemedicine to reduce contact between people, using the electronic medical record to help record and track people COVID-19 patients had contact with, apps, internet hospitals, and how 5G networks helped speed up IT systems.

She was previously principal and consulting director of the Greater China Joint Commission International (JCI). As chief executive for HIMSS Greater China, Liu and her team made a significant breakthroughs with hospitals and the HIT industry in the greater China region to embrace international HIT standards, certification requirements and to rethink prudent approaches to IT investments and operations. 

Read the the related article by Liu, "Deployment of Health IT in China’s Fight Against the COVID-19 Epidemic."

 

Enterprise Imaging | March 02, 2020

At RSNA19, Philips discussed with ITN Contributing Editor Greg Freiherr how its IntelliSpace Enterprise Edition fits into the Philips portfolio, and how the corporate acquisition of Carestream Health IT might affect the company. The video also discusses how Philips will help prospective customers acquire its products.

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