ITN Contributing Editor Greg Freiherr interviews Kim Garriott, Principal Consultant, Logicalis
The rapidly expanding volume of unstructured data, exemplified by medical images, underscores the need to develop an enterprise imaging strategy, says Kim Garriott, principal consultant at Logicalis, a global provider of IT solutions and managed services.
In the accompanying video interview, Garriott explains how the combination of these two may form a convincing argument for the leadership of your organization to move forward with enterprise imaging.
On June 1, at the upcoming SIIM 2018 convention, she will co-host the continuing education session “Achieving Enterprise Imaging Maturity,” during which she and the HIMSS-SIIM Workgroup will present the new Digital Imaging Adoption Maturity Model. DIAM, as it is called, is designed to support real-time collaboration and patient-centric care by providing a method to address enterprise-wide imaging challenges.
When developing an enterprise imaging strategy, organizations must consider their specific needs, which are characterized in “use cases.” Garriott, who is the global chair of the HIMSS analytic DIAM Development team and co-chair of the HIMSS-SIIM Enterprise Imaging Workgroup, explains that these use cases constitute one very important element of the enterprise imaging strategy. Another is construction of a “data governance model.” This model is needed to guide the capture of data and is essential to the success of enterprise imaging.
Editor’s Note: This pre-SIIM video interview is the first in a series of three by ITN Contributing Editor, Greg Freiherr. The series features industry luminaries discussing key issues associated with the upcoming SIIM conference.
Related Video: ITN Associate Editor Jeff Zagoudis discusses, "Enterprise Imaging and the Digital Imaging Adoption Model" with Kim Garriott at HIMSS 2018.
Recent Videos View all 592 items
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
Photo Gallery of New Technologies at HIMSS 2021
VIDEO: Importance of Body Part Labeling in Enterprise Imaging — Interview with Alex Towbin, M.D.
HIMSS 2021 Showed What to Expect From In-person Healthcare Conferences During the COVID Pandemic
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: Examples of COVID-19 CT Scan Analysis Software
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
Photo Gallery of New Technologies at HIMSS 2021
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
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.
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
Sponsored Videos View all 163 items
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
BLOG: Exa Gateway Offers a New Way to Deliver Teleradiology
BLOG: Artificial Intelligence for Clinical Decision Support and Increased Revenues
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.
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.
Technology Reports View all 12 items
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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3 High-impact AI Market Trends in Radiology at RSNA 2019
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Find more artificial intelligence news and video
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.
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.
In Artificial Intelligence 2018: What Radiologists Need to Know About AI, ITN Contributing Editor Greg Freiherr offers an overview of artificial intelligence (AI) advances at the Radiological Society of North America (RSNA) 2018 annual meeting.
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Radiation Oncology View all 117 items
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.
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
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.
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 363 items
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
Photo Gallery of New Technologies at HIMSS 2021
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
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
BLOG: Exa Gateway Offers a New Way to Deliver Teleradiology
BLOG: Artificial Intelligence for Clinical Decision Support and Increased Revenues
Yael Eshet, M.D., MSc, a diagnostic radiology specialist at Sheba Medical Center in Israel, was the lead author on a recent study that showed COVID-19 (SARS-CoV-2) vaccine adenopathy can persist more than 6 weeks. This swelling of lymph nodes is similar to what is seen cancer and infections and the new findings show it can last longer than 7-10 weeks. The current recommended time people should delay medical imaging is 6 weeks after receiving a COVID vaccine to avoid a misdiagnosis,[2] but this new study shows there is increased inflammation shown on PET-CT imaging for much longer.
These were the findings in the Radiology published study "Prevalence of Increased FDG PET/CT Axillary Lymph Node Uptake Beyond 6 Weeks after mRNA COVID-19 Vaccination."[1]
Researchers using fluorodeoxyglucose (FDG)-positron emission tomography (PET) have found increased FDG uptake in the lymph nodes of patients 7-10 weeks past their second mRNA-based Pfizer-BioNTech COVID-19 vaccination. This new information indicates a persistent immune response that could be mistaken on imaging exams for serious conditions like lymphoma over a much longer period of time.
Recent recommendations for post-vaccine lymphadenopathy advise scheduling routine imaging, such as screening mammography, before, or at least 6 weeks after, the final vaccination dose to eliminate false positive results. However, this new research showed that avid axillary lymph node uptake was present beyond 6 weeks after the second vaccination in more than 29% of the patients in the study cohort.
The authors stated “This study shows that avid axillary lymph node uptake on FDG PET/CT can be detected in more than a quarter of our patient population even beyond 6 weeks after the second dose of the mRNA-based COVID-19 vaccination. Compared to a previous study showing normalization of FDG uptake within 40 days of receiving an inactivated H1N1 influenza vaccine, we found uptake persistence even at 70 days. Physicians should be aware of this potential pitfall.”
Some images in this video are from another Radiology study, which showed PET tracer uptake at the COVID vaccine injection site and other examples of axillary adenopathy.[3]
Related COVID Vaccine Axillary Adenapathy Content:
COVID-19 Vaccine Can Cause False Positive Cancer Diagnosis
Help Spread Awareness of Potential COVID-19 Vaccine Imaging Side-effects
VIDEO: COVID Vaccine May Cause Enlarged Lymph Nodes on Mammograms — Interview with Constance "Connie" Lehman, M.D.
COVID-19 Vaccination Axillary Adenopathy Detected During Breast Imaging
PHOTO GALLERY: How COVID-19 Appears on Medical Imaging
Find more radiology related COVID content
References:
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
Molecular Imaging View all 30 items
Yael Eshet, M.D., MSc, a diagnostic radiology specialist at Sheba Medical Center in Israel, was the lead author on a recent study that showed COVID-19 (SARS-CoV-2) vaccine adenopathy can persist more than 6 weeks. This swelling of lymph nodes is similar to what is seen cancer and infections and the new findings show it can last longer than 7-10 weeks. The current recommended time people should delay medical imaging is 6 weeks after receiving a COVID vaccine to avoid a misdiagnosis,[2] but this new study shows there is increased inflammation shown on PET-CT imaging for much longer.
These were the findings in the Radiology published study "Prevalence of Increased FDG PET/CT Axillary Lymph Node Uptake Beyond 6 Weeks after mRNA COVID-19 Vaccination."[1]
Researchers using fluorodeoxyglucose (FDG)-positron emission tomography (PET) have found increased FDG uptake in the lymph nodes of patients 7-10 weeks past their second mRNA-based Pfizer-BioNTech COVID-19 vaccination. This new information indicates a persistent immune response that could be mistaken on imaging exams for serious conditions like lymphoma over a much longer period of time.
Recent recommendations for post-vaccine lymphadenopathy advise scheduling routine imaging, such as screening mammography, before, or at least 6 weeks after, the final vaccination dose to eliminate false positive results. However, this new research showed that avid axillary lymph node uptake was present beyond 6 weeks after the second vaccination in more than 29% of the patients in the study cohort.
The authors stated “This study shows that avid axillary lymph node uptake on FDG PET/CT can be detected in more than a quarter of our patient population even beyond 6 weeks after the second dose of the mRNA-based COVID-19 vaccination. Compared to a previous study showing normalization of FDG uptake within 40 days of receiving an inactivated H1N1 influenza vaccine, we found uptake persistence even at 70 days. Physicians should be aware of this potential pitfall.”
Some images in this video are from another Radiology study, which showed PET tracer uptake at the COVID vaccine injection site and other examples of axillary adenopathy.[3]
Related COVID Vaccine Axillary Adenapathy Content:
COVID-19 Vaccine Can Cause False Positive Cancer Diagnosis
Help Spread Awareness of Potential COVID-19 Vaccine Imaging Side-effects
VIDEO: COVID Vaccine May Cause Enlarged Lymph Nodes on Mammograms — Interview with Constance "Connie" Lehman, M.D.
COVID-19 Vaccination Axillary Adenopathy Detected During Breast Imaging
PHOTO GALLERY: How COVID-19 Appears on Medical Imaging
Find more radiology related COVID content
References:
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.
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
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VIDEO: ACC Efforts to Advance Evidence-based Implementation of AI in Cardiovascular Care — Interview with John Rumsfeld, M.D.
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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.
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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
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Conference Coverage View all 474 items
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
Photo Gallery of New Technologies at HIMSS 2021
VIDEO: Importance of Body Part Labeling in Enterprise Imaging — Interview with Alex Towbin, M.D.
HIMSS 2021 Showed What to Expect From In-person Healthcare Conferences During the COVID Pandemic
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: Examples of COVID-19 CT Scan Analysis Software
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
Photo Gallery of New Technologies at HIMSS 2021
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
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.
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
Information Technology View all 269 items
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
Photo Gallery of New Technologies at HIMSS 2021
VIDEO: Importance of Body Part Labeling in Enterprise Imaging — Interview with Alex Towbin, M.D.
HIMSS 2021 Showed What to Expect From In-person Healthcare Conferences During the COVID Pandemic
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: Examples of COVID-19 CT Scan Analysis Software
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
Photo Gallery of New Technologies at HIMSS 2021
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
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.
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
Women's Health View all 77 items
Yael Eshet, M.D., MSc, a diagnostic radiology specialist at Sheba Medical Center in Israel, was the lead author on a recent study that showed COVID-19 (SARS-CoV-2) vaccine adenopathy can persist more than 6 weeks. This swelling of lymph nodes is similar to what is seen cancer and infections and the new findings show it can last longer than 7-10 weeks. The current recommended time people should delay medical imaging is 6 weeks after receiving a COVID vaccine to avoid a misdiagnosis,[2] but this new study shows there is increased inflammation shown on PET-CT imaging for much longer.
These were the findings in the Radiology published study "Prevalence of Increased FDG PET/CT Axillary Lymph Node Uptake Beyond 6 Weeks after mRNA COVID-19 Vaccination."[1]
Researchers using fluorodeoxyglucose (FDG)-positron emission tomography (PET) have found increased FDG uptake in the lymph nodes of patients 7-10 weeks past their second mRNA-based Pfizer-BioNTech COVID-19 vaccination. This new information indicates a persistent immune response that could be mistaken on imaging exams for serious conditions like lymphoma over a much longer period of time.
Recent recommendations for post-vaccine lymphadenopathy advise scheduling routine imaging, such as screening mammography, before, or at least 6 weeks after, the final vaccination dose to eliminate false positive results. However, this new research showed that avid axillary lymph node uptake was present beyond 6 weeks after the second vaccination in more than 29% of the patients in the study cohort.
The authors stated “This study shows that avid axillary lymph node uptake on FDG PET/CT can be detected in more than a quarter of our patient population even beyond 6 weeks after the second dose of the mRNA-based COVID-19 vaccination. Compared to a previous study showing normalization of FDG uptake within 40 days of receiving an inactivated H1N1 influenza vaccine, we found uptake persistence even at 70 days. Physicians should be aware of this potential pitfall.”
Some images in this video are from another Radiology study, which showed PET tracer uptake at the COVID vaccine injection site and other examples of axillary adenopathy.[3]
Related COVID Vaccine Axillary Adenapathy Content:
COVID-19 Vaccine Can Cause False Positive Cancer Diagnosis
Help Spread Awareness of Potential COVID-19 Vaccine Imaging Side-effects
VIDEO: COVID Vaccine May Cause Enlarged Lymph Nodes on Mammograms — Interview with Constance "Connie" Lehman, M.D.
COVID-19 Vaccination Axillary Adenopathy Detected During Breast Imaging
PHOTO GALLERY: How COVID-19 Appears on Medical Imaging
Find more radiology related COVID content
References:
Constance "Connie" Lehman, M.D., Ph.D., chief of breast imaging, co-director of the Avon Comprehensive Breast Evaluation Center at the Massachusetts General Hospital, and professor of radiology at Harvard Medical School, explains issues and suggested guidelines for women who receive the COVID-19 vaccine and need to get a mammogram. In the first three months since the vaccines have been released, there have been numerous case reports of the vaccine causing swollen lymph nodes. This is would usually raise a red flag for breast cancer, but is normal for many women receiving the vaccine as their body's immune system gears up against the virus.
Lehman said cases reports of axillary adenopathy have been identified on breast imaging after coronavirus disease (COVID-19) vaccination and are rising. Lehman et al. proposed a pragmatic management approach in a recent article in the American Journal of Roentgenology (AJR).[1]
In the settings of screening mammography, screening MRI and diagnostic imaging work-up of breast symptoms, with no imaging findings beyond unilateral axillary adenopathy ipsilateral to recent (prior six weeks) vaccination, they report the adenopathy as benign with no further imaging indicated if no nodes are palpable six weeks after the last vaccine dose.
For patients with palpable axillary adenopathy in the setting of ipsilateral recent vaccination, clinical follow-up of the axilla is recommended. In all these scenarios, axillary ultrasound is recommended if clinical concern persists six weeks after vaccination.
In patients with recent breast cancer diagnosis in the pre- or peri-treatment setting, prompt recommended imaging is encouraged as well as vaccination (in the thigh or contralateral arm). The recommendations align with the ACR BI-RADS Atlas and aim to: 1) reduce patient anxiety, provider burden, and costs of unnecessary evaluation of enlarged nodes in the setting of recent vaccination, and 2) avoid further delays in vaccinations and breast cancer screening during the pandemic.
Related Medical Imaging of COVID Content:
COVID-19 Vaccination Axillary Adenopathy Detected During Breast Imaging
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.
Find more radiology related COVID content
Reference:
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
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.
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