Artificial intelligence (AI) applications are making waves across industries. But in healthcare, we frequently find ourselves fighting against being left behind when it comes to new technology adoption. While the field inherently necessitates more caution when implementing emerging technologies into workflows that impact patient outcomes and human lives, AI is proving to be beneficial in offloading administrative, repetitive, and easily manageable tasks from an overburdened healthcare workforce.
When it comes to medical imaging, AI applications are accelerating time to diagnoses and improving accuracy by going much further than any human can. AI-driven insights and machine learning capabilities are able to mine hundreds of body scans in a matter of minutes for differences that the human eye can miss. With these new applications of AI in medical imaging, there is the potential for hospitals and health systems to detect problems earlier, track patients through their care journey more accurately, and offer more lifesaving treatment to patients at the time they need it.
The storage and retrieval of digital images is an integral component of any digital imaging system. A picture archiving and communication system (PACS) turns data into actionable insights by displaying, storing, and retrieving important imaging data used for the diagnosis and treatment of complex conditions. A PACS can also ensure long-term data retention and reduce physical storage needs, offering substantial cost savings, when they are running on the right system and platform that optimizes performance.
This means that seamless digital imaging processing systems are paramount to patient and provider success. When running on a platform or service that might slow down a PACS, providers are losing valuable time and patient outcomes may be impacted. Health systems are then left scrambling for something better, which in this case can mean the difference between life and death for patients with complex conditions.
The Golden Hour of Critical Care Is Impacted by Slow Operating Systems
Founded in 1907, Adventist Healthcare is one of the longest-serving healthcare systems in Maryland and delivers comprehensive care at over 50 locations across the Washington D.C. area. Adventist Healthcare delivers high-quality care across specialties but is primarily known for its expertise in cardiology, maternity, orthopedics, and mental health.
Like most health systems, we at Adventist have been trying to keep pace with the digitization of our industry and the fast-paced adoption of emerging tech, while remaining stable and scalable to meet organizational goals and patient needs. We were facing challenges that were delaying diagnoses, adding to physician workloads, and leaving patient information not as secure as it could be. Our life-saving services, including acute-care hospitals, primary care and imaging centers, home health services and more, could not be left up to chance– so we looked at strategic tech investments and partnerships to advance our operations and ensure that we are meeting the needs of patients and providers across the Maryland and D.C. region.
In an environment where every second matters, the underlying technology supporting critical healthcare systems must keep pace with growth. Our PACS and the storage needed to keep it operational and insightful directly influence our ability to save lives. For instance, when it comes to heart attack and stroke diagnoses and recovery, the ability to pull up prior patient images to make quick comparisons within the “golden hour” of an episode greatly increases the chance of patient recovery. When the storage behind our PACS began to experience performance issues, we had to look for solutions to leverage in order to gain speed, stability, and security, while cutting costs and complexity from our current data storage infrastructure to allow for better operations and room for business growth.
By Amanda Jerelyn, health sciences tutor, Academist Help.
Almost all innovations are capable of making health maintenance cost-effective and efficient. It modifies the approach used by health professionals for delivering healthcare services. Secondly, it mostly uses applied science to develop a new kind of output and medication. Thirdly, it develops bright businesses exemplary.
According to expert analysis, the health sector has experienced exponential growth and has headed towards innovation at a high pace. It is vital to have a closer look at a few of the most exciting healthcare innovations that engineers and scientists have managed to come up within these years.
Customer Observant
Modernization in the delivery of health management will lead to more productive, more active, and cheaper medicines for this time, which will continuously improve the healthcare system. For instance, less costly and accessible health services will encourage more individuals to engage in their healthcare. This can allow participants to take control of their intimate health management expenses or a lively program.
Importance of Technological Advancements
The goal of improved access to medication, cost-effective treatment, and less medical errors can be achieved with technological advancements. As an exemplification, infix sensors may allow patients to track their condition more efficiently. IT developments can connect numerous atoll of information to health management organization which can significantly improve decision making and timely delivery of care without any delays. Moreover, the probability of duplication of healthcare services also reduced, which results in cost savings for patients and their families.
The Strength Influencing Innovation
There are several players similar to the health indulgent industries, owning a purpose. Such barnstormers have the support and the ability to impact the policies. Hospitals often curse mechanization driven merchandise ground-breaker for the considerable amount of the healthcare department. American Medical Association (AMA) and the trial attorneys, formidable rivals on the problem of medical malpractice, have worked together on legislation to concede consumers who have been refused medication to sue managed care assurance policies. If innovators consider and seek to deal with the diverse desires of the different parties, they can see their attempts thwarted.
With the continued spread of COVID-19, it’s more important than ever for healthcare organizations to continue implementing ways to keep employees and patients safe, while improving patient care and keeping patient data secure. Many healthcare organizations are turning to KVM (keyboard, video and mouse) solutions to help with the increasing need for smarter and safer healthcare solutions.
A few examples:
Remote IT admins – IT admins can access critical servers when working remotely. Remote desktops only allow one connection to one server at a time, but a KVM provides a Windows explorer view of ANY server connected to that KVM.
Remote lab automation – Employees can stay safely away from contaminated areas using a KVM over IP device to access devices in lab areas.
Remote nurse station monitoring – video extenders and KVM extenders allow nurses to obtain real-time patient data from a remote station without being physically inside the room with the patient. This allows for a controlled, clean and secure environment.
Command and control through security and surveillance – Security employees can monitor all entry ways, control opening/closing and locking or unlocking doors from a distance.
Trends in Smart Healthcare
A few trends driving the need for these solutions include:
IoMT and Connected, Integrated Smart Healthcare Systems
The Internet of Medical Things (IoMT) is a connected infrastructure of medical devices, software applications and health systems and services. Integrating different healthcare delivery systems into one mechanism has created the concept of smart healthcare. Not only has this pushed the focus from just caring for the sick to promoting the general health and well-being of people, but it has driven technological advances that connect various health IT systems for ease of control and communication.
Smart technologies, such as virtual health, wearables, sensors and biometrics are already driving this transition to new healthcare delivery models that focus on streamlining processes and making use of cutting-edge digital innovations and information systems. Such developments, including those in artificial intelligence, cognitive technology and robotics are accelerating automation, while telehealth, digital medicine and remote monitoring are already part of larger connected, integrated smart healthcare systems.
Increasing Demand for High-Precision Medical Imaging
Reliable video has always been an important component to healthcare IT, predominantly related to the exponential growth in picture archiving and communication systems (PACS) used to securely store and digitally transmit electronic images and clinical reports. As the volume of digital medical images grows, and data analytics of those images becomes more prevalent, the demand for video at the highest possible resolutions for the most detailed images continues to increase.
The seamless and stable transmission of high-resolution video has become a prerequisite that medical imaging systems are expected to handle (up to 4K), and delivery must be low latency across long distances with no signal degradation. In addition to high-precision audio video signal extension devices, other infrastructure equipment, such as KVM switches, must be able to support the required resolutions and refresh rates.
Digitization Driving Demand for Increased Security
The move toward patient-centered healthcare models and medical information systems is requiring unprecedented levels of security and data protection. Alongside the digitization of healthcare records of electronic medical records (EMRs) is the push for paperless hospitals and the increasing government regulations surrounding data management and patient privacy. Secure KVM switches that are commonly seen in government and military environments are now enabling medical staff to easily switch between sensitive patient data and non-private applications on the hospital network.
Healthcare Use Cases
Medical Imaging: Live Surgery, Remote Monitoring and MRI Diagnostics
A hospital decides to implement a state-of-the-art medical imaging transmission system to enable doctors to perform surgeries and real-time diagnoses more effectively. The solution needs to transmit content, such as live surgery video from the doctors’ head-mounted cameras, patient vitals, medical records, MRI equipment and a picture archiving and communication system (PACS), accessible from various locations inside the hospital.
The challenges:
Medical imaging needs to be instantly accessible from various locations throughout the hospital.
Requires clear and stable video images for monitoring.
Compatibility with a wide range of medical equipment in a hospital environment.
A tailored solution for medical-grade applications with easy-to-use media distribution management software.
The solution: Integrating seamless switching will deliver instant and stable video over long distances over a single cable, while converting various resolutions to ensure top quality. Additionally, adding HDBaseT KVM extenders will allow MRI equipment to be accessed and operated with zero latency while uncompressed video with pixel-to-pixel quality is reliably delivered to the operator’s room for real-time diagnosis.
A foundational research roadmap for artificial intelligence (AI) in medical imaging was published this week in the journal Radiology. The report was based on outcomes from a workshop to explore the future of AI in medical imaging, featuring experts in medical imaging, and hosted at the National Institutes of Health in Bethesda, Maryland. The workshop was co-sponsored by the National Institute of Biomedical Imaging and Bioengineering, the Radiological Society of North America, the American College of Radiology, and the Academy for Radiology and Biomedical Imaging Research.
The collaborative report underscores the commitment by standards bodies, professional societies, governmental agencies, and private industry to work together to accomplish a set of shared goals in service of patients, who stand to benefit from the potential of AI to bring about innovative imaging technologies.
The report describes innovations that would help to produce more publicly available, validated and reusable data sets against which to evaluate new algorithms and techniques, noting that to be useful for machine learning these data sets require methods to rapidly create labeled or annotated imaging data. The roadmap of priorities for AI in medical imaging research includes:
new image reconstruction methods that efficiently produce images suitable for human interpretation from source data,
automated image labeling and annotation methods, including information extraction from the imaging report, electronic phenotyping, and prospective structured image reporting,
new machine learning methods for clinical imaging data, such as tailored, pre-trained model architectures, and distributed machine learning methods,
machine learning methods that can explain the advice they provide to human users (so-called explainable artificial intelligence), and
validated methods for image de-identification and data sharing to facilitate wide availability of clinical imaging data sets.
Article
Langlotz, CP, et al. A Roadmap for Foundational Research on Artificial Intelligence in Medical Imaging: From the 2018 NIH/RSNA/ACR/The Academy Workshop. Radiology. April 16, 2019.
Co-authors of the report with Curtis P. Langlotz were Bibb Allen, M.D.; Bradley J. Erickson, M.D., Ph.D.; Jayashree Kalpathy-Cramer, Ph.D.; Keith Bigelow, B.A.; Tessa S. Cook, M.D., Ph.D.; Adam E. Flanders, M.D.; Matthew P. Lungren, M.D., M.P.H.; David S. Mendelson, M.D.; Jeffrey D. Rudie, M.D., Ph.D.; Ge Wang, Ph.D.; and Krishna Kandarpa, M.D., Ph.D.
To the average person, holography is the stuff of science fiction. Many people were first exposed to the concept of practical holography in the original “Star Wars” film, released in 1977. Although the apparent 3D images represented in the film were of relatively low resolution, the possibilities were undeniably intriguing — and undoubtedly inspirational to a generation of budding scientists. Subsequent portrayals of the inherent possibilities of this technology were explored on television series, such as “Star Trek: The Next Generation,” in the late 1980s and early 1990s.
Holography: From Science Fiction to Scientific Fact
In that imagined world, holography was vastly superior to the grainy, static-filled images portrayed in “Star Wars.” Entire interactive worlds were recreated in a special space. The unimaginably advanced technology was primarily used for recreation. This fictional technology more closely resembled the 3D interactive “worlds” promised by various recently introduced virtual reality (VR) systems. Although actual VR technology is arguably in its infancy, and interactive content is still largely lacking, these systems come closest to reproducing the experience of entering a “holodeck,” where fully realized, interactive, imagined worlds can be explored at will.
A Brief History
Of course, none of these imagined uses of holographic technology reflect present, real-world applications. That’s not to say holography doesn’t exist. It does, and has done since before the time of the original “Star Trek” series, which debuted in 1966. Although that seminal science fiction series made no mention of holography, the technology already existed in the real world, having begun conceptual development as early as the 1940s. In 1971, a Hungarian-British physicist was awarded the Nobel Prize in Physics for his invention of the holographic method. His success with optical holography was only made possible by the invention of the laser, in 1960.
In essence, a hologram is a photographic recording of a light field. The recording is subsequently projected to create a faithful 3D representation of the holographed subject. Technically speaking, it involves the encoding of a light field as an interference pattern. The pattern diffracts light to create a reproduction of the original light field. Any objects present in that original light field appear to be present, viewable from any angle.
Depth cures — such as parallax and perspective — are retained, changing as expected, depending on the viewpoint of the observer. Holograms have been compared to sound recordings. When a musician performs, the vibrations he produces are encoded, recorded, stored and later reproduced to evoke the original vibrations a listener would have experienced.
Of course, other forms of practical holography have been in common usage for decades. The so-called embossed hologram, which appears on many credit cards and even paper checks, was widely introduced in the mid-1980s. National Geographic magazine, which featured an image of a holographic eagle on its cover in 1984, marks the event among its most notable milestones.
The 2D embossed hologram image retains some of the characteristics of a traditional hologram, in that the image changes somewhat depending on one’s angle of view. It’s primarily used as a security measure, or as a marketing novelty (these mass-produced holograms have even appeared on boxes of children’s cereal). However, these illusions are not true holograms. While the National Geographic eagle was impressive, one could not simply examine the animal from any conceivable angle.
Guest post by Karen Holzberger, vice president and general manager, diagnostic solutions, Nuance Healthcare.
Karen Holzberger
A few years ago, there was a witty car commercial advertising an alert feature that took the guesswork out of filling your tires by gently beeping to signal the appropriate pressure had been reached. It featured a series of vignettes where the car horn would beep, cautioning the owner to reconsider just as he was about to overdo something (for instance, betting all of his money on one roll of the dice). The concept of getting a reminder at the point of a decision is a compelling one, particularly if it can save you time or aggravation and guide you to do the right thing. In healthcare, any technology that can provide that level of support will have a profound impact on patient care.
Albeit humorous, that car commercial wasn’t far off the mark with healthcare challenges. Unnecessary medical imaging exposes patients to additional radiation doses and results in approximately $12 billion wasted each year, but it has also has another unintended downstream effect. It has fueled a culture of medical certainty, where tests are ordered in hopes of shedding light on some of the grey areas of diagnostic imaging, including incidental findings. The reality is that incidental findings are almost always a given, but not always a problem. So how do you know what to test further and what to monitor? And while one radiologist may choose the former option with a patient who has an incidental node finding, another might decide to go with the latter option, so who is right?
Beep! It’s important
It is important that when a radiologist sees a nodule and it has certain characteristics, he or she makes recommendation for follow-up imaging, which is why the American College of Radiology (ACR) has released clinical guidelines on incidental findings. By offering standard clinical decision support on findings covering eleven organs, the ACR is helping radiologists protect their patients through established best practices for diagnostic testing.
This is a great step forward for the industry, but some hospitals are taking it one step further. Massachusetts General Hospital (MGH) is using its radiology reporting platform to provide real-time quality guidance at the point-of-care to drive better patient care. Now, when a radiologist is reading a report and notes an incidental finding, the system will automatically ping her with evidence-based recommendations for that finding. For instance, if the node is a certain size, it should be tested further.
The results of having this information at the radiologists’ fingertips are impressive. In fact, studies show that when these clinical guidelines are built into existing workflows, 90 percent of radiologists align with them, as opposed to alternative methods, such as paper print outs, which result in 50 percent concordance.
By Amanda Jerelyn, health sciences tutor, 
