AI Health Index: Radiology & Imaging AI changes https://aihealthindex.io/categories/radiology-and-imaging-ai Material product changes at Radiology & Imaging AI vendors, tracked by AI Health Index. Every entry is dated and cited to a public source. en-us Free to reuse with a visible link to aihealthindex.io. Terms: https://aihealthindex.io/use-this-data Wed, 23 Sep 2026 12:00:00 GMT 720 https://aihealthindex.io/icon-192.png AI Health Index: Radiology & Imaging AI changes https://aihealthindex.io/categories/radiology-and-imaging-ai Aidoc received FDA Breakthrough Device Designation for CARE Chest X-Ray Triage, built on its CARE foundation model, covering triage of… https://aihealthindex.io/changelog/aidoc aihealthindex.io:change:6ab85e9bd92e5616ac6dc814 Wed, 23 Sep 2026 12:00:00 GMT Regulatory / FDA Radiology & Imaging AI Clinical Decision Support Health System AI Platforms Aidoc received FDA Breakthrough Device Designation for CARE Chest X-Ray Triage, built on its CARE foundation model, covering triage of pneumomediastinum and lobar or lung collapse. It is Aidoc's third breakthrough designation in just over a year, after CARE Multi-Triage Body CT and CARE First Read for Chest X-Ray. The 510(k) is under FDA review and the product is not yet available for sale in the United States.

Why it matters: A breakthrough designation can speed FDA review but does not clear the product. Radiology groups interested in foundation model triage for chest films should treat this as a roadmap signal and ask Aidoc for expected clearance timing.

Impact: Medium. Verification: Verified. Type: Regulatory / FDA.

Evidence: Vendor announcement

Source: AI Health Index change log. Free to reuse with a link back. Terms.

]]> DeepHealth received FDA 510(k) clearance for Chest XRay, a computer aided detection tool built on a foundation model that detects and… https://aihealthindex.io/changelog/deephealth aihealthindex.io:change:6aaeaddaaaa02078636c9caa Fri, 18 Sep 2026 12:00:00 GMT Regulatory / FDA Radiology & Imaging AI Health System AI Platforms Hospital & Unit Operations DeepHealth received FDA 510(k) clearance for Chest XRay, a computer aided detection tool built on a foundation model that detects and localizes abnormalities on chest radiographs. It is the next version of the technology DeepHealth acquired with Gleamer, it is commercially available in the US now, and existing customers are eligible for the update.

Why it matters: A foundation model clearance matters because one model covers many findings, rather than one narrow algorithm per finding. Radiology groups should ask exactly which findings the 510(k) covers, since marketing for foundation models tends to run ahead of the cleared indications.

Impact: High. Verification: Partially Verified. Type: Regulatory / FDA.

Evidence: Trade press

Source: AI Health Index change log. Free to reuse with a link back. Terms.

]]> AZmed received its sixth FDA clearance, for AZchest to detect and localize pneumothorax and pleural effusion on chest radiographs. https://aihealthindex.io/changelog/azmed aihealthindex.io:change:6aaeaddaaaa02078636c9cae Tue, 15 Sep 2026 12:00:00 GMT Regulatory / FDA Radiology & Imaging AI Clinical Decision Support AZmed received its sixth FDA clearance, for AZchest to detect and localize pneumothorax and pleural effusion on chest radiographs. That brings its Rayvolve suite to eight FDA cleared findings, and AZchest can now flag up to five findings on a single chest image.

Why it matters: Pneumothorax is a time critical miss, which is why this clearance matters more than the count. AZmed cites reading time reductions of up to 31 percent for readers outside thoracic radiology; that is the group to test it with, since specialist readers gain least.

Impact: High. Verification: Verified. Type: Regulatory / FDA.

Evidence: Vendor announcement

Source: AI Health Index change log. Free to reuse with a link back. Terms.

]]> Mercy and Aidoc released a white paper, commissioned by AVIA, reporting on five months of AI deployment across the Mercy health system. https://aihealthindex.io/changelog/aidoc aihealthindex.io:change:6a92e5ef75bbcbbe469c6fee Tue, 25 Aug 2026 12:00:00 GMT Clinical evidence Radiology & Imaging AI Clinical Decision Support Health System AI Platforms Mercy and Aidoc released a white paper, commissioned by AVIA, reporting on five months of AI deployment across the Mercy health system. The review documents more than 50,000 new clinical findings surfaced in that window and tracks the associated changes in speed of diagnosis and time to treatment. The scale is the notable part: this is a multi hospital deployment reporting aggregate output rather than a single site pilot.

Why it matters: A five month figure from a named health system gives buyers something to model against, which vendor accuracy claims do not. The number to interrogate is what counts as a new clinical finding, since that definition determines whether 50,000 represents meaningful catches or a high volume of flags a radiologist would have reached anyway. AVIA commissioning the work makes it more independent than a vendor case study and less independent than peer review, which is roughly where its evidentiary weight should sit.

Impact: Medium. Verification: Partially Verified. Type: Clinical evidence.

Evidence: Trade press

Source: AI Health Index change log. Free to reuse with a link back. Terms.

]]> A study was published evaluating what happened when Brainomix 360 Stroke was implemented in a high volume stroke system that already used… https://aihealthindex.io/changelog/brainomix aihealthindex.io:change:6a92e5ef75bbcbbe469c6fed Mon, 24 Aug 2026 12:00:00 GMT Clinical evidence Radiology & Imaging AI Clinical Decision Support A study was published evaluating what happened when Brainomix 360 Stroke was implemented in a high volume stroke system that already used routine perfusion imaging. The finding is that the platform improved the efficiency of the acute stroke pathway even in a setting that was not imaging constrained to begin with. The design matters here, because it is an implementation study in an operating service rather than a retrospective accuracy comparison against a reference standard.

Why it matters: Most stroke AI evidence measures whether the algorithm agrees with an expert reader, which tells a buyer very little about whether the service gets faster. This one measures the pathway, which is the thing hospital leaders are actually purchasing. The high volume, routine perfusion setting is the harder test case, since those centers have the least headroom for an AI tool to add value, so a positive result there travels further than one from an under resourced site.

Impact: Medium. Verification: Verified. Type: Clinical evidence.

Evidence: Vendor announcement

Source: AI Health Index change log. Free to reuse with a link back. Terms.

]]> A retrospective single-center study published in Diagnostics externally validated several CE-certified AI systems, including Milvue's… https://aihealthindex.io/changelog/milvue aihealthindex.io:change:6a808db25e3cc8842da0dc3e Fri, 14 Aug 2026 12:00:00 GMT Clinical evidence Radiology & Imaging AI Clinical Decision Support A retrospective single-center study published in Diagnostics externally validated several CE-certified AI systems, including Milvue's TechCare Kids, for automated bone age assessment. The researchers found no significant differences in accuracy between TechCare Kids and the other evaluated AI systems for 90% of the clinically relevant pediatric cohort.

Why it matters: Prospective buyers evaluating pediatric bone age AI tools can use this independent clinical validation as evidence that Milvue's TechCare Kids performs competitively alongside other commercial solutions. The findings provide clinical reassurance of the model's reliability in standard use cases.

Impact: Medium. Verification: Verified. Type: Clinical evidence.

Evidence: Peer-reviewed publication

Source: AI Health Index change log. Free to reuse with a link back. Terms.

]]> MEDICAL IP: A retrospective study published in PLOS ONE validated MEDIP PRO's ability to segment orbital structures on CT imaging to assess Thyroid… https://aihealthindex.io/changelog/medical-ip aihealthindex.io:change:6a808db25e3cc8842da0dc30 Mon, 10 Aug 2026 12:00:00 GMT Clinical evidence Radiology & Imaging AI Workforce & Training A retrospective study published in PLOS ONE validated MEDIP PRO's ability to segment orbital structures on CT imaging to assess Thyroid Eye Disease (TED) activity. The software was used to perform semi-automatic segmentation of extraocular muscles, intraorbital fat, and lacrimal glands. The resulting quantitative metrics successfully differentiated active from inactive TED, demonstrating an area under the curve (AUC) of 0.938 when combined with clinical parameters.

Why it matters: Published validation provides concrete evidence of the platform's segmentation accuracy and reliability for complex orbital anatomy. Health systems evaluating the solution can point to this study as proof of its capability to extract clinically meaningful, disease-specific biomarkers from routine imaging.

Impact: Medium. Verification: Verified. Type: Clinical evidence.

Evidence: Peer-reviewed publication

Source: AI Health Index change log. Free to reuse with a link back. Terms.

]]> HOPPR expanded its vision-language model portfolio with the release of a new 2D Mammography Narrative Model. https://aihealthindex.io/changelog/hoppr aihealthindex.io:change:6a7739f386781bb15a7c68db Thu, 06 Aug 2026 12:00:00 GMT Model / architecture Radiology & Imaging AI HOPPR expanded its vision-language model portfolio with the release of a new 2D Mammography Narrative Model. The foundation model is designed to support AI development and narrative generation specifically for 2D mammography imaging.

Why it matters: This release allows healthcare organizations and developers to build and fine-tune AI applications for breast imaging. It expands the platform's clinical utility beyond chest X-rays and CT scans into women's health workflows.

Impact: Medium. Verification: Partially Verified. Type: Model / architecture.

Evidence: Trade press

Source: AI Health Index change log. Free to reuse with a link back. Terms.

]]> Circle Cardiovascular Imaging released cvi42 v6.5, introducing automated phase offset correction, anti-aliasing, and pre-segmentation for… https://aihealthindex.io/changelog/circle-cardiovascular-imaging aihealthindex.io:change:6a7739f386781bb15a7c68d3 Wed, 05 Aug 2026 12:00:00 GMT Product / capability Radiology & Imaging AI Clinical Decision Support Circle Cardiovascular Imaging released cvi42 v6.5, introducing automated phase offset correction, anti-aliasing, and pre-segmentation for 4D Flow. The update also adds editable plaque segmentation, expanded calcium scoring references, improved motion correction for quantitative perfusion, and a new Plaque Education Report.

Why it matters: These workflow automations reduce the manual preparation time required for 4D Flow and CT analysis, allowing clinicians to interpret studies faster. The addition of the Plaque Education Report and direct PDF printing also streamlines communication with referring physicians and patients.

Impact: High. Verification: Verified. Type: Product / capability.

Evidence: Vendor announcement

Source: AI Health Index change log. Free to reuse with a link back. Terms.

]]> TeraRecon released TeraRecon Neuro, a new software package designed to assist clinicians in diagnosing and treating neurovascular… https://aihealthindex.io/changelog/terarecon aihealthindex.io:change:6a7739f386781bb15a7c68d0 Tue, 04 Aug 2026 12:00:00 GMT Product / capability Radiology & Imaging AI TeraRecon released TeraRecon Neuro, a new software package designed to assist clinicians in diagnosing and treating neurovascular emergencies such as stroke. The application processes brain perfusion images from CT or MRI scanners to calculate perfusion parameters and generate 2D and 3D visualizations, including penumbra and umbra maps.

Why it matters: Radiology departments and stroke centers can deploy this dedicated neurovascular tool to accelerate clinical decision-making during time-critical emergencies. The automated generation of detailed parametric maps directly supports rapid triage and treatment planning for stroke patients.

Impact: High. Verification: Partially Verified. Type: Product / capability.

Evidence: Trade press

Source: AI Health Index change log. Free to reuse with a link back. Terms.

]]> Overjet received FDA clearance for its IRIS Real-time Image Quality Checking system. https://aihealthindex.io/changelog/overjet aihealthindex.io:change:6a7739f386781bb15a7c68cd Tue, 04 Aug 2026 12:00:00 GMT Regulatory / FDA Radiology & Imaging AI Clinical Decision Support RCM & Prior Auth AI Overjet received FDA clearance for its IRIS Real-time Image Quality Checking system. The AI-powered tool flags eight image quality issues, such as cone cuts, overlapping contacts, and missed coverage, immediately after an X-ray is captured.

Why it matters: Dental practices can catch and correct imaging errors while the patient is still in the chair, reducing the need for later retakes and consolidating imaging software and diagnostic AI into a single system.

Impact: High. Verification: Verified. Type: Regulatory / FDA.

Evidence: Vendor announcement

Source: AI Health Index change log. Free to reuse with a link back. Terms.

]]> Caristo Diagnostics: The FDA granted De Novo authorization (DEN250042) for CaRi-Heart, which quantifies coronary inflammation from routine coronary CT… https://aihealthindex.io/changelog/caristo-diagnostics aihealthindex.io:change:6ab95ec98120c43419d035cd Wed, 29 Jul 2026 12:00:00 GMT Regulatory / FDA Radiology & Imaging AI Clinical Decision Support Diagnostics & Genomics The FDA granted De Novo authorization (DEN250042) for CaRi-Heart, which quantifies coronary inflammation from routine coronary CT angiography and estimates a 10 year cardiovascular mortality risk. Caristo announced it on 29 July and plans a US commercial launch in the third quarter, expanding through the fourth. It joins CaRi-Plaque, cleared in February 2025, so plaque and inflammation can be read from one scan.

Why it matters: Until July, CaRi-Heart was limited to investigational use in the US. The company has not yet published the US indication or any conditions attached to the authorization, so ask for both before using the risk estimate in care. Category III CPT codes 0992T and 0993T, effective 1 January 2026, give practices a way to code it.

Impact: High. Verification: Verified. Type: Regulatory / FDA.

Evidence: Vendor announcement

Source: AI Health Index change log. Free to reuse with a link back. Terms.

]]> Heartflow PCI Navigator entered commercial use outside of clinical trials, with The Valley Hospital becoming the first U.S. institution to… https://aihealthindex.io/changelog/heartflow aihealthindex.io:change:6a6e7c13d9213f7e7baf7ca4 Mon, 27 Jul 2026 12:00:00 GMT Product / capability Radiology & Imaging AI Clinical Decision Support Diagnostics & Genomics Heartflow PCI Navigator entered commercial use outside of clinical trials, with The Valley Hospital becoming the first U.S. institution to deploy the software. The AI-powered tool provides interventional cardiologists with a personalized 3D model detailing vessel sizing, plaque buildup, and blood flow to plan coronary angioplasty and stent placement before entering the catheterization lab.

Why it matters: This marks the commercial availability of Heartflow's percutaneous coronary intervention planning capability, expanding the platform's utility from non-invasive diagnostics into interventional cardiology. Buyers can now evaluate this tool to gain pre-procedural insights, allowing clinical teams to establish treatment strategies and select device sizes before the procedure begins.

Impact: Medium. Verification: Partially Verified. Type: Product / capability.

Evidence: Trade press

Source: AI Health Index change log. Free to reuse with a link back. Terms.

]]> Researchers from VUNO published a peer-reviewed study in the American Journal of Neuroradiology validating a machine learning algorithm… https://aihealthindex.io/changelog/vuno aihealthindex.io:change:6a6e7c13d9213f7e7baf7ca7 Fri, 24 Jul 2026 12:00:00 GMT Clinical evidence Clinical Decision Support Remote Monitoring & Chronic Care Radiology & Imaging AI Researchers from VUNO published a peer-reviewed study in the American Journal of Neuroradiology validating a machine learning algorithm that uses automated brain MRI volumetry to differentiate frontotemporal dementia from Alzheimer's disease. The model, trained on 758 subjects and externally validated on 89 subjects, achieved 91.4 percent accuracy internally and significantly reduced interpretation time for experienced radiologists.

Why it matters: Clinical leaders and radiology buyers evaluating dementia triage solutions gain peer-reviewed validation of VUNO's MRI volumetry approach. The demonstrated time savings and diagnostic accuracy support the commercial deployment of such models in clinical workflows to separate overlapping neurodegenerative presentations.

Impact: Medium. Verification: Verified. Type: Clinical evidence.

Evidence: Peer-reviewed publication

Source: AI Health Index change log. Free to reuse with a link back. Terms.

]]> Subtle Medical received FDA clearance for SubtleHD (PET), a next generation AI PET image enhancement product for PET/CT and PET/MR systems. https://aihealthindex.io/changelog/subtle-medical aihealthindex.io:change:6a5d427dc37f509b9f489066 Wed, 27 May 2026 12:00:00 GMT Regulatory / FDA Radiology & Imaging AI Subtle Medical received FDA clearance for SubtleHD (PET), a next generation AI PET image enhancement product for PET/CT and PET/MR systems. The company states it supports all FDA approved radiotracers, enables up to 75 percent faster PET imaging on existing scanners, improves SUVmax quantitation accuracy, allows radiologist adjustable denoising levels, and incorporates anatomical CT data into reconstruction. It extends prior clearances covering SubtlePET and SubtleHD (MR).

Why it matters: PET scanner capacity is a hard constraint for most imaging programs, and acquisition acceleration is one of the few levers that adds throughput without capital equipment. The material detail for buyers is radiotracer compatibility: support across all FDA approved radiotracers, rather than 18F-FDG alone, is what makes this usable in theranostics and advanced molecular imaging programs where the older generation was limited. Two caveats worth carrying into procurement: the acceleration figure is a vendor claim and should be validated against your own protocols and reader acceptance, and adjustable denoising means image appearance becomes a configurable parameter, which needs a documented standard rather than per radiologist preference drift.

Impact: Medium. Verification: Verified. Type: Regulatory / FDA.

Evidence: Trade press

Source: AI Health Index change log. Free to reuse with a link back. Terms.

]]> The FDA cleared Aidoc's comprehensive abdomen CT triage solution, powered by its self developed CARE foundation model, bringing 11 newly… https://aihealthindex.io/changelog/aidoc aihealthindex.io:change:6a5d4a29fdd2ff3590934a75 Wed, 21 Jan 2026 12:00:00 GMT Regulatory / FDA Radiology & Imaging AI Clinical Decision Support Health System AI Platforms The FDA cleared Aidoc's comprehensive abdomen CT triage solution, powered by its self developed CARE foundation model, bringing 11 newly cleared indications together with three previously cleared into a single 14 indication workflow. The company states this is the first FDA clearance of a double digit set of acute indications powered by one foundation model. In the FDA reviewed pivotal study the new indications reported a mean sensitivity of 97 percent and mean specificity of 98 percent, and the company reports roughly an order of magnitude reduction in false alerts compared with leading single condition tools.

Why it matters: The operationally decisive number here is not the sensitivity, it is the false alert rate. Triage AI fails in practice when radiologists learn to ignore it, and single condition tools deployed side by side compound that problem because each one alerts independently. A reported order of magnitude reduction in false alerts, if it holds in a buyer's own case mix, is what determines whether the tool survives past month three. Two things to establish in evaluation: that the cleared indications match the acute findings actually driving delays in your emergency department, and how the platform governs models it did not build, since aiOS also hosts third party AI and the governance layer is doing work across all of them.

Impact: High. Verification: Verified. Type: Regulatory / FDA.

Evidence: Vendor announcement

Source: AI Health Index change log. Free to reuse with a link back. Terms.

]]> Pearl received FDA clearance extending Second Opinion to panoramic radiographs, covering detection of suspected caries, periapical… https://aihealthindex.io/changelog/pearl aihealthindex.io:change:6a5d427dc37f509b9f489067 Thu, 18 Dec 2025 12:00:00 GMT Regulatory / FDA Radiology & Imaging AI Pearl received FDA clearance extending Second Opinion to panoramic radiographs, covering detection of suspected caries, periapical radiolucencies, and impacted third molars. The clearance was supported by a standalone performance study and a fully crossed multi reader, multi case study, with the company reporting stable performance across gender, geography, and imaging device subgroups. With this clearance the platform spans bitewing, periapical, panoramic, and CBCT imaging.

Why it matters: The clinically interesting part is the study design, not the clearance itself. A fully crossed multi reader, multi case study is the appropriate design for a reader assistance claim, because it measures whether clinicians perform better with the tool rather than whether the model performs well alone, and relatively few AI vendors in any specialty run one. The reported stability of performance across gender, geography, and imaging device subgroups is also a genuine fairness disclosure, which remains the emptiest axis across this index. Buyers should still confirm that the imaging devices in their own practice are represented in the validation population.

Impact: Medium. Verification: Verified. Type: Regulatory / FDA.

Evidence: Vendor announcement

Source: AI Health Index change log. Free to reuse with a link back. Terms.

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