OncoAI Suite (BrainTumor AI)
Overview
The OncoAI Suite, developed by Carina AI, is an AI-native oncology imaging suite designed for cancer detection, segmentation, measurement, and longitudinal tracking across various imaging modalities including CT, MRI, and PET/CT. The BrainTumor AI module within this suite focuses specifically on segmenting and volumetrically tracking gliomas, brain metastases, and vestibular schwannomas using multi-parametric MRI. The OncoAI Suite is currently in clinical use for BrainTumor AI, with other modules like LymphNode AI on the 510(k) pathway and LungNodule AI in clinical research use. The platform is built with an on-premise architecture, ensuring that patient data remains within the institution’s network and aligns with HIPAA regulations.
Reviewed by Pouyan Golshani, MD — Interventional Radiologist
Key Features
- AI-driven tumor segmentation
- Volumetric tracking across visits
- Multi-parametric MRI analysis
- Detection of glioma, brain metastasis, and vestibular schwannoma
- On-premise deployment
- Integration with existing PACS and workflows
- Audit-ready logging of transformations
- No outbound PHI
- Three-stage AI pipeline for cancer imaging
- Peer-reviewed AI methods
Use Cases
- Brain tumor detection and segmentation
- Longitudinal tracking of brain tumors
- Assisting in radiation oncology planning (indirectly, through data for research)
- Clinical research in neuro-oncology
- Reducing manual segmentation workload in research settings
- Improving consistency in tumor assessment for research
Details
| Category | Oncology AI |
| Pricing | Contact for pricing |
| Deployment | On-premise |
| Compliance | |
| BAA Available | Unknown AI-estimated |
| HIPAA Compliant | Yes AI-estimated |
| FDA Status | Not applicable AI-estimated |
| Integrations | |
| EHR | Not specified |
| Specialties | Neurosurgery, Oncology, Radiology |
What the Web Says
OncoAI Suite (BrainTumor AI) by Carina AI is an AI-native oncology imaging suite designed for the detection, segmentation, and longitudinal tracking of various cancer types. The BrainTumor AI module is currently in clinical use and focuses on segmenting gliomas, brain metastases, and vestibular schwannomas with volumetric tracking across visits. The suite aims to streamline cancer care by providing multiple AI engines under a single viewer for different imaging modalities like CT, MRI, and PET/CT.
Overall: MixedStrengths
- Accurate identification of brain tumor subtypes (95% accuracy for a similar AI tool).
- Provides detection, segmentation, and longitudinal tracking across cancer types.
- Supports multiple imaging modalities (CT, MRI, PET/CT) within a single user interface.
- BrainTumor AI module is validated and in clinical use.
- Can help doctors make more informed decisions and optimize care.
- Potential to be especially valuable in under-resourced communities lacking genetic sequencing technology.
Limitations
- Limited information available from independent reviews by physicians, healthcare IT, or tech reviewers.
- High upfront costs for integration into clinical workflows can be a roadblock.
- Potential for inconsistent performance after deployment and biases in algorithm development.
- AI tools may not have access to enough high-quality data for less common brain tumors.
- AI should not be used for triaging acute symptoms or mapping out treatment plans.
- Lack of independent reviews on platforms like Reddit, G2, or Capterra.
- Limited FDA regulatory guidelines for AI in oncology.
Based on reviews from: Carina AI, National Institutes of Health (NIH), Nature Medicine
Last updated: 2026-10-03
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