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Co-written by Bhvita Jani, Mustafa Hassan and Simon Harris
By the end of summer 2021, the worst of the coronavirus pandemic appeared to be over. Providers were now tasked with dealing with the enormous backlog of patients whose elective procedures and screening scans were postponed because of the emergency restrictions brought in as a result of the Covid-19 pandemic. As 2022 begins, however, the threat of Covid is back with a new variant threatening to cause further disruption. Against this backdrop, medical imaging modality vendors had been performing strongly, but 2022 will see them need to offer the products and technologies that can help providers with this disruption. They will also need to look after their own houses, and make sure the global and economic volatility does not prevent them doing business. In light of that, here are five predictions that we expect to define the year ahead.
Supply chain management will be crucial
Challenges within hospitals have dramatically intensified as a result of the Covid-19 pandemic, however, there are other, global challenges that vendors must also countenance. Chief among these are the supply chain issues that are affecting companies from almost every sector, with reports from carmakers, food producers, electronics manufacturers and others all being hit.
Medical imaging systems vendors are not immune from this challenge, with almost all the major vendors noting the issue in their latest results presentations. This disruption is likely to have several significant impacts. Semiconductor chips are among the products which have been impacted most acutely. The scarcity of these chips will mean that vendors will have to prioritise their use, using them first in systems that command higher-prices and higher margins, this will drive up the average selling price of systems, compounding increases caused more directly by a shortage of supply.
Smaller vendors are likely to be most impacted by these shortages. Larger vendors have the buying power and international reach to better mitigate against shortages. They have the reserves to stockpile essential resources, and the ability to broker deals with new suppliers across the world.
This supply chain disruption and component shortage will impact every vendor, so will not, in and of itself, favour any vendor over any other. However, how vendors deal with the disruption will have a huge impact. Orderbooks are brimming, but that means naught if vendors cannot manufacture and supply the systems needed to meet them. Management of supply chains will therefore become one of the major differentiators between vendors throughout 2022.
The democratisation of medical imaging will be accelerated by larger vendors
Imaging has already started its journey out of hospital imaging departments. This transition has in many cases been driven by young vendors which mark this decentralisation as their mission. Butterfly Network is among the highest profile of these, having leveraged a new technology and new business models to quickly become one of the market leaders in handheld ultrasound, making its devices an increasingly common sight across inpatient and outpatient settings. Other new vendors, both within handheld ultrasound, such as Exo Imaging, Pulsenmore, and Vave, and elsewhere, such as Nanox, Turner Imaging Systems and Hyperfine, are hoping to imitate Butterfly Network’s success in the transition of imaging out of the hospital.
In 2022 this will change. Large imaging vendors have been a part of medical imaging’s transition away from imaging departments in the past, but this year will see those efforts intensify. This is, in many instances, a result of larger vendors having to create new markets if they are to be able to continue to deliver on their growth forecasts. Growth opportunity within hospital’s radiology departments is limited. This is compounded further by the transition of many providers to longer-term, more holistic vendor partnerships, which further limit sales opportunities for vendors looking to displace competitors.
New clinical settings can provide these sales opportunities. Vendors such as Siemens Healthineers, which late last year announced its MAGNETOM Free.Star MRI scanner are indicative of larger vendors looking to target these opportunities. Siemens, as well as other vendors such as GE Healthcare and Philips have focused on making their products more accessible, with factors such as smaller space requirements and lower infrastructure needs, as well as lower cost and facilitation of less experienced technicians all making their system’s adoption by emergency rooms, orthopaedic, paediatric departments, and outpatient centres more likely in 2022.
Vendors and providers will focus on advanced imaging systems
While there are still growth opportunities across medical imaging, with a range of different modalities performing strongly in 2021, the potential for technical development and innovation within advanced modalities such as MRI and CT means that vendors will be keen to focus on these categories in the coming year.
These modalities offer strong opportunities for growth. Innovations can represent significant steps forward and will give customers and potential customers impetus to buy new systems or replace existing systems. Vendors have responded to this opportunity, and have already been making sizeable technological leaps forward, with Philips launching a new detector-based spectral CT system early last year, and Siemens officially launching its photon-counting CT system, after it received regulatory approval in September. There were several other products launched at RSNA too, with GE, Canon and Fujifilm launching new MRI and CT products at the event.
These advanced systems will be key battlegrounds for vendors who will look to use their systems to satisfy providers’ ever-present appetite for increased image quality, and, bolstered by improved software and automation, be keen to sell the systems into more departments and clinics than ever before.
There are also other facets to this greater adoption of advanced imaging systems. Another element is the increasing uptake of hybrid systems. As clinical precision continues to play a paramount role in delivering positive patient outcomes and first-time right diagnosis, the adoption of hybrid imaging systems in high-end facilities will accelerate the convergence of different imaging modalities, offering benefits such as seamless workflows with all required imaging modalities to be easily accessible in one room. One of the more recent examples of this is Philips’ latest spectral CT system, which can be used for both CT and interventional applications, for advanced guidance during procedures.
Some of the biggest advances will be seen in medical imaging workflow
Providers’ ongoing desire to acquire better image quality means that they will continue to rely on MRI and CT imaging. However, using these systems can be relatively time consuming and resource intensive. For providers facing an unprecedented backlog of patients amidst a shortage of fully trained and experienced personnel, this could present a challenge.
However, 2022 will see this obstacle partly addressed by the increased adoption of advanced workflow tools. Providers will, for instance, adopt AI-powered workflow solutions that can be used to maximise the efficiency of medical imaging and increase patient throughput, thereby effectively resulting in a higher return on investment.
These tools, in essence, look to improve patient scheduling, increase the speed at which scans can be conducted and reduce the need for time consuming rescans. This will be achieved through the use of several types of solutions, including those which help support patient positioning; automatic and intelligent protocolling tools which ensure that the parameters of systems are set correctly for the patient to be scanned; and automatic image accept and reject tools to make sure any scans which are not of the requisite quality can be caught early.
Such tools will be particularly valuable in 2022 as providers will try to address the backlog of scans that were postponed in the midst of the Covid-19 pandemic, when many providers across the world stopped carrying out elective procedures. Such workflow tools will be critical to ensure that radiology departments can operate efficiently. These tools will also benefit vendors, with the new solutions helping convince providers to replace or upgrade existing systems.
AI will benefit the technician as well as the radiologist
AI’s use in medical imaging has, until now, predominantly focused on how the technology can help with the reading and interpretation of medical images. This year that will change, with tools increasingly being used to aid in the capture of medical images. In a climate where high staff turnover is a challenge that healthcare providers are facing, increased support at the point of image acquisition is paramount.
In some scenarios, particularly in ultrasound, this will see AI being used to guide users in the acquisition of diagnostic quality images. There have already been some steps in this direction, with the likes of Caption Health’s Caption Guidance software being offered to help novice users correctly perform cardiac ultrasound scans. This ties into the earlier prediction of enabling imaging to be more widely used outside of imaging departments, where technicians are often less experienced and more likely to benefit from guidance. In addition to helping technicians perform the scans, these tools can also be used to automatically take some quantitative measurements from patients, such as calculating the bladder volume and the ejection fraction.
In other modalities the focus will be on reducing the time it takes to capture images and improving the efficiency of radiology departments. MRI and CT scans in particular are time consuming. AI-enhanced workflow optimisations tools, such as intelligent protocolling, can help to mitigate this issue and significantly reduce the time it takes for images to be captured by analysing an initial set of images and then suggesting the most appropriate next sequences based on the initial findings. Additionally, deep‐learning models for image reconstruction in MRI are delivering high-quality images with shorter scan times, overcoming the historical trade-offs in MR between scan time and image quality.
In general radiography, AI can identify potential technical problems during imaging capture to ensure the images are suitable for interpretation and potentially avoid patient recalls when they are not. For example, CXR from annalise.ai can identify technical image factors (exposure, patient rotation etc.) and devices (lines, implants, stents etc.). Similarly, Fujifilm offers foreign body detection tools on its diagnostic X-ray products.
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