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

 

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

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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

 

Photo Gallery of New Imaging Technologies at RSNA 2019

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VIDEO: AI-Assisted Automatic Ejection Fraction for Point-of-Care Ultrasound

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Northwestern Medicine Introduces Artificial Intelligence to Improve Ultrasound Imaging

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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

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.

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.

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

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

Find more RSNA news and video

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

Other video interviews with Dr. Kuhl:

VIDEO: Explaining Dense Breasts

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

 

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

Breast Imaging in the Age of Coronavirus

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

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

Hologic and Sheryl Crow Begin Back to Screening Campaign

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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

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GE Highlights New Echocardiography Technologies at ASE 2020

Other ASE news and video

 

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

 

 

 

Todd Villines, M.D., FACC, FAHA, MSCCT, explains some of more influential cardiac CT clinical papers from the past year at the Society of Cardiovascular Computed Tomography (SCCT) 2020 virtual meeting. Among these were the ISCHEMIA Trial, others showing the value of CT is assessing chest pain patients and its ability to act as a gate keeper to the cath lab, and the 2019 European Society of Cardiology (ESC) guidelines that now list cardiac as a preferred imaging modality.

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: 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

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

 

Todd Villines, M.D., FACC, FAHA, MSCCT, explains some of the discussion on CT used for COVID-19 patients at 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. 

Early on in the COVID-19 pandemic in China, CT emerged as a key imaging modality and was found to be able to detect COVID ground glass lesions in the lungs sometimes prior to positive genetic PCR test results. Supporters of CT say the modality offers a way to get detailed anatomical and functional information using a short exam time and limits the exposure of staff to potential or known COVID-19 positive patients.

One area where cardiac CT is seeing a lot of increased his is for the evaluation of thrombus in the left atrial appendage (LAA). This is traditionally done using trans esophageal echo (TEE), but it required very close contact with the patient and direct exposure of staff to bodily fluids and potential viral shed from the patient exhaling with each breath.

 

Related CT During COVID-19 Content:

Cardiac Imaging Best Practices During the COVID-19 Pandemic

VIDEO: CT and POCUS Emerge As Frontline Cardiac Imaging Modalities in COVID-19 Era — Interview with Geoffrey Rose, M.D.,

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

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

 

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: 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

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."

 

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.

EIZO medical monitors were showcased recently at RSNA 2019. Learn how the EIZO approach streamlines the effectiveness of your readings. From the NEW 30.9 inch, super-high-resolution, 12 megapixel multi-modality Radiforce RX1270, to the EIZO built-in features such as Point-and-Focus, EIZO holds to the ideal to harmoniously combine performance, ease-of-use and comfort. Learn the Shape of Comfort with EIZO.  Stop by and visit with us at HIMSS, booth #4087.

ProFound AI is an FDA-cleared artificial intelligence (AI) system for reading 3-D breast tomosynthesis images. At RSNA19, ITN Contributing Editor Greg Freiherr spoke with iCad Chairman and CEO Michael Klein about the system, which has been clinically proven in a large reader study to produce an 8% average improvement in sensitivity, 7.2% average reduction in recall rate and 52.7% reduction in average radiologist reading time. 

GE Healthcare's iCenter is a cloud-based management software that provides 24/7 visibility to customers' visual and operational data. In this Conversations video, Contributing Editor Greg Freiherr discusses iCenter with GE and Microsoft Executives at RSNA 2019.

Elizabeth M. Hecht, M.D., professor of radiology, Columbia University, New York, explains the latest advances to help visualize the difficult to image pancreas. She was a moderator of a session on pancreatic imaging advances at the 2019 Radiological Society of North America (RSNA) meeting.

She explained computed tomography is the front line imaging modality, followed by MRI for more detailed examination of the soft tissue details. MRI tissue elastography can also help to differentiate pancreatitis from pancreatic cancer. Hecht also said PET-CT and endoscopic ultrasound also play roles in pancreatic imaging. She said new software is helping automate measurements and artificial intelligence (AI) is in development to help improve pancreatic imaging and to find new radiomic markers that might be missed by the human eye to better detect disease or risk stratify patients.

Find more news and video from RSNA

 

 

An experienced technologist and two Agfa executives talk about what distinguishes the new Agfa 100s. Three key highlights include the quality of images that users can get out of the system for the certainty of the diagnostic; more flexibility that has been designed around the user; and its revolutionary platform.

Hitachi announced the FDA clearance of its newest CT – Scenaria View – at RSNA2019. The View offers an 80 cm wide bore, 550 lb table capacity and powerful 84 kW generator as well as a 200 mm lateral shifting table. Installs in Georgia, Ohio and Florida are underway with more to come in the new year.