Using computer tools to read brain scans after glioblastoma treatment
Original title: AI-driven radiomics and radiogenomics: supporting the assessment and differentiation of pseudoprogression in cellular immunotherapy for glioblastoma.
How far along is this research?
- Lab cells
- Animals
- Review
- Tested in people
This looks across many earlier studies rather than running a new one.
This is an expert review of ideas, not a tool doctors can use yet.
The short version
Experts looked at how computer tools might help doctors tell real tumor growth from harmless changes on scans.
What was studied. This is a review of past research, not a new study. It looked at computer tools that study MRI brain scans in people with glioblastoma: A glioma that is given grade 4, the highest grade. It grows fast. Treatment usually starts soon after it is found. It often means surgery, then radiation and chemotherapy. See the glossary who get immune treatments.
What they found. After treatment, a scan can make a tumor look like it is growing when it is not. This is called pseudoprogression: A scan after treatment that looks worse because of the treatment itself, not because the tumor has grown. Telling the two apart can take another scan. See the glossary. It can lead doctors to stop a treatment too soon or add treatment that is not needed. The authors say computer tools that use many kinds of scans, blood tests, gene data, and health records may help tell the two apart. But the research so far has problems, like small groups of patients and results not yet checked by other teams.
What this means, and what it doesn't
What it could mean: Someday these tools might help doctors read scans more clearly after treatment. That could help people stay on a treatment that is working, or change course sooner when it is not.
What it doesn't mean: This is not a new result. It is a summary of where the science is heading. These tools are not ready for everyday care, and many more studies are needed to check them. This is not a cure and does not treat the tumor.
Source: PubMed, September 2, 2026 · Read the original
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