The first half of 2022 is now a wrap, and it was another big one within medical imaging. Here are some of the top storylines from the last 6 months and some things to keep in mind as we head into 2022’s second half:
- Imaging Goes Home – Healthcare’s major shift into patient homes seemed to be bringing imaging along with it in H1, leading to new vendor-side efforts focused on at-home ultrasound (e.g. Caption’s home echo program, GE’s Pulsenmore investment), more providers expanding their mobile imaging capabilities, and new research efforts focused on patient-performed exams and mobile imaging operations.
- AI Shakeup – Everyone who has been predicting AI consolidation got to take a victory lap in H1, which brought at least two strategic pivots (MaxQ AI & Kheiron) and the acquisitions of Aidence and Quantib (by RadNet) and Nines (by Sirona). This kind of consolidation is normal for an emerging segment, but it wouldn’t be surprising if the difficult funding climate leads to above-normal consolidation in H2.
- Photon Counting Reality – The momentum from Siemens’ photon counting CT launch in late 2021 carried into this year, leading to a series of studies suggesting that PCCT might be as good as anticipated, the launch of Samsung NeuroLogica’s own head/neck PCCT system, and increased photon counting R&D and marketing efforts from the other major CT OEMs.
- The Patient Engagement Push – The first half seemed to bring a surge in patient engagement activity, including new investments from the major image sharing vendors, increased pressure from radiology leaders to finally achieve universal image sharing, and new efforts to make radiology reports more accessible and understandable.
- The Platform Pathway – The trend towards AI platforms heated up in H1, as new vendors launched or expanded their AI platforms, the major PACS players increased their AI integration efforts, and startups and radiology teams increasingly embraced AI platforms as a solution to their narrow AI challenges.
- Incidental Action – The detection and management of incidentals seemed to take big strides in H1, as more studies highlighted incidentals’ population health potential, more vendors and research teams developed AI-based approaches for incidental detection, and incidental follow-up workflows continued to evolve.
