Input or output interoperability
DICOM is explicitly referenced in the described input, output, or workflow.
exact submission · checked 2026-09-01The model card does not establish every supported DICOM object, transfer method, or local interface.
FDA-cleared profile
MSKai
MSKai
MSKai is an image identification, post-processing, measurement, and reporting software tool that provides qualitative viewing and quantitative spine measurements from previously-acquired T2 weighted DICOM lumbar spine Magnetic Resonance Imaging (MRI) images for users' review, evaluation and analysis. It provides the following functionality to assist users in identifying, observing, measuring and reporting measurements: - Anatomy segmentation; - Anatomy labeling; - Anatomy measurement; and - Export of measurement results to a qualitative and quantitative report for user's evaluation, amendment and authorization MSKai does not serve as a diagnostic device by providing or recommending any type of medical diagnosis or treatment. MSKai simply provides users the ability to access objective and repeatable identification, segmentation, measurement and reported measurements of the Lumbar spine. The user is responsible for the indications of preferences and settings, confirming the software generated measurements, and reviewing, confirming and approving draft reports based on their medical training. The device is intended to be used only by physicians, radiologist, hospitals and other medical institutions. Only T2 weighted DICOM images of MRI acquired from lumbar spine exams of patients aged 18 and above are acceptable input. MSKai does not support DICOM images of patients that are pregnant, have post-operational complications, tumors, infections, or complex hardware.
Evidence status: each field shows source quality, applicability, and review date. Research pending, information not established in reviewed sources, and vendor documentation pending are distinct outcomes.
Clinical fit
What this tool is for
Start with the authorized purpose, then verify how it fits your service line and reading workflow.
- Exact purpose
- MSKai is an image identification, post-processing, measurement, and reporting software tool that provides qualitative viewing and quantitative spine measurements from previously-acquired T2 weighted DICOM lumbar spine Magnetic Resonance Imaging (MRI) images for users' review, evaluation and analysis. It provides the following functionality to assist users in identifying, observing, measuring and reporting measurements: - Anatomy segmentation; - Anatomy labeling; - Anatomy measurement; and - Export of measurement results to a qualitative and quantitative report for user's evaluation, amendment and authorization MSKai does not serve as a diagnostic device by providing or recommending any type of medical diagnosis or treatment. MSKai simply provides users the ability to access objective and repeatable identification, segmentation, measurement and reported measurements of the Lumbar spine. The user is responsible for the indications of preferences and settings, confirming the software generated measurements, and reviewing, confirming and approving draft reports based on their medical training. The device is intended to be used only by physicians, radiologist, hospitals and other medical institutions. Only T2 weighted DICOM images of MRI acquired from lumbar spine exams of patients aged 18 and above are acceptable input. MSKai does not support DICOM images of patients that are pregnant, have post-operational complications, tumors, infections, or complex hardware.
Exact-submission indication text from the ACR AI Central model card. FDA labeling remains controlling.
- Intended users
- Physicians, radiologists, neurosurgeons, ortho/spine surgeons, hospitals and other medical institutions
Intended-user text reported in the exact-submission ACR model card.
- Care setting and population
- Adult
Patient-population text reported in the exact-submission ACR model card; institutional setting may still require vendor confirmation.
- Workflow role
- Segmentation or contouring
Conservative normalization of explicit wording in an exact-submission source.
- Required input
- MR images or data. Inclusion criteria: T2 weighted DICOM images of MRI acquired from lumbar spine exams of patients aged 18 and above
Conservative normalization of explicit wording in an exact-submission source.
- Output and human action
- The AI model outputs anatomy segmentation (vertebral bodies L1-S1, intervertebral discs, cord canal, dural sac, nerve roots, posterior arch), anatomy labeling, quantitative measurements (protruding disc material, intervertebral angles, vertebral body heights, disc heights, anterio-lithesis, retro-lithesis, lordotic angle, dural sac diameter), and export of measurement results to a qualitative and quantitative report for user evaluation, amendment, and authorization. Outputs are classified using alerts based on rule-based algorithms and must be confirmed by the user before being stored and reported.
Clinical output reported in the exact-submission ACR model card.
- Limitations
- Research pending
Confirm contraindications, unsupported populations, scanners, protocols, and known failure modes.
Regulatory identity
FDA record and catalog context
The FDA listing establishes the regulatory identity. It does not by itself establish local workflow fit, pricing, security, or performance in your environment.
- FDA submission
- K240793
- Modality
- MRI
Imaging modality reported in the exact-submission ACR AI Central model card.
- Anatomy
- Spine
Anatomy normalized from explicit exact-submission ACR model-card wording.
- Clearance type
- 510(k)
- Decision date
- 2024-12-16
- FDA status
- FDA-cleared
Implementation
Questions for IT, informatics, and operations
Use these fields to structure a vendor demo, security review, and implementation estimate.
- Integration
- The exact-submission ACR model card explicitly references DICOM in the described input, output, or workflow; exact interfaces, versions, and local compatibility require confirmation.
Interoperability terms explicitly reported in the exact-submission ACR model card; interface versions and local compatibility still require confirmation.
- Deployment and data flow
- On-premise
Deployment category preserved from the prior exact-submission review; hosting region, data flow, and current commercial configuration still require vendor confirmation.
- Security and privacy
- Vendor documentation pending
FDA authorization does not establish the current commercial security posture. Request data-flow diagrams, hosting and retention details, access controls, audit logging, attestations, and incident-response documentation.
- Training and support
- Vendor documentation pending
Training, onboarding, competency, and support commitments are commercial implementation details that require current vendor documentation.
- Monitoring and change control
- Vendor documentation pending
Local acceptance testing, production monitoring, drift review, update control, and incident escalation require a current vendor and site-specific governance plan.
Evidence
Performance evidence
Metrics are shown only when they are tied to a source, endpoint, population, and tested product version.
- Evidence summary
- Study type: Stand-Alone Performance. Cases: 238
Structured study metadata from the exact-submission ACR model card; this is not an independent evidence synthesis.
- Reported sensitivity
- Research pending
This field has not been curated yet.
- Reported specificity
- Research pending
This field has not been curated yet.
No contextualized exact-version metric has completed evidence review. Regulatory-document values, when available, are shown above with their limitations.
MSKai regulatory performance study summary
Stand-Alone Performance · Adult
exact submission · Tested version: Exact product version not reported; regulatory study summarized for FDA submission K240793 · n=238 · Independence not establishedK240793
ACR AI Central summarizes the regulatory study; consult the exact FDA materials before comparative use.
Economics and lifecycle
Budget and ongoing governance
These are common procurement questions; unknown values remain visible until a source supports them.
- Pricing and total cost
- Vendor documentation pending
FDA submission materials do not establish current commercial pricing. Request the pricing unit, term, minimum commitment, implementation fees, and included support from the vendor.
- Reimbursement and coding
- Research pending
Determine whether any product-specific CPT/HCPCS pathway exists and separate it from billing for the underlying imaging service.
Safety and lifecycle
Postmarket record
Recall and adverse-event records are shown only after product matching. Adverse-event reports do not establish incidence or causality.
- Postmarket safety review
- Not established in reviewed sources
No native submission-identifier match was found in the checked openFDA radiology recall snapshot. Product-name, manufacturer, and adverse-event searches remain necessary; this does not establish that no recall or safety report exists.
Buyer worksheet
Open questions to take to the vendor
- Verify limitations: Confirm contraindications, unsupported populations, scanners, protocols, and known failure modes.
- Verify security and privacy controls: FDA authorization does not establish the current commercial security posture. Request data-flow diagrams, hosting and retention details, access controls, audit logging, attestations, and incident-response documentation.
- Verify training: Training, onboarding, competency, and support commitments are commercial implementation details that require current vendor documentation.
- Verify pricing and total cost: FDA submission materials do not establish current commercial pricing. Request the pricing unit, term, minimum commitment, implementation fees, and included support from the vendor.
- Verify reimbursement and coding relevance: Determine whether any product-specific CPT/HCPCS pathway exists and separate it from billing for the underlying imaging service.
- Verify local validation and lifecycle monitoring: Local acceptance testing, production monitoring, drift review, update control, and incident escalation require a current vendor and site-specific governance plan.
- Verify recalls and postmarket safety signals: No native submission-identifier match was found in the checked openFDA radiology recall snapshot. Product-name, manufacturer, and adverse-event searches remain necessary; this does not establish that no recall or safety report exists.
Research record
What has been checked
This audit distinguishes completed source review from fields that have not yet been researched.
Exact FDA record reviewedStatus
2026-09-04Last searched
17Fields reviewed
6Source classes checked
0Unreviewed PubMed leads
0Unreviewed trial leads
0Unreviewed FDA recall leads
Exact-submission ACR model-card fields were normalized under the current provenance rules; vendor and independent-study confirmation remain distinct. Automated exact-name discovery found 0 PubMed and 0 ClinicalTrials.gov candidate records. Candidates require human product and version matching; zero candidates is not evidence that no studies exist. Native FDA recall identifiers produced 0 postmarket candidate records; 0 have been reviewed (0 published, 0 rejected) and 0 remain unreviewed.
Candidate leads remain unpublished until a human confirms the exact product and tested version.
Source classes: fda ai list, fda decision summary, acr ai central product, pubmed, clinical trials, openfda device recall
Sources
Source ledger
Sources accessed through 2026-09-02.
- K240793 FDA decision source U.S. Food and Drug Administration · 2026-08-31
- Artificial Intelligence-Enabled Medical Devices U.S. Food and Drug Administration · 2026-08-31
- MSKai model card (K240793) American College of Radiology · 2026-09-01
- PubMed biomedical literature index U.S. National Library of Medicine · 2026-09-01
- ClinicalTrials.gov study registry U.S. National Library of Medicine · 2026-09-01
- openFDA Device Recall API U.S. Food and Drug Administration · 2026-09-02
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