Combining CT scans and pathology slides to predict ovarian cancer treatment response
Official title: Early Evaluation of Ovarian Cancer Prognosis by Fusing Radiographic and Histopathologic Imaging Information
Funded at University of Oklahoma · NIH-11256732 · Data updated 2026-11-12
This project is testing a computer-made image marker that combines CT scans and pathology slides to tell which ovarian cancer patients are likely to benefit from chemotherapy.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Oklahoma NIH-funded |
| Lab location | 1 site (Norman, United States) |
| Project start | February 15, 2022 |
| Project end | January 1, 2026 |
| Funding year | 2026 |
| Award (this year) | $190,058 |
| NIH project number | 5P20GM135009-05 |
| Project ID | NIH-11256732 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates are people with ovarian cancer who have pre-treatment CT scans and tumor tissue available for digital pathology, especially patients treated at or referred to the Stephenson Cancer Center.
✕Less likely to help
Patients who lack CT scans or digitized pathology samples, or whose tumor types differ from those included in the study, may not receive direct benefit from this project.
What this research studies
Researchers will use CT scans and digitized pathology slides from ovarian cancer patients and train a machine-learning model to find image patterns linked to chemotherapy response. They will compute quantitative features from both radiographic and histopathology images (radiomics and pathomics) and fuse them into a single image marker. The marker will be built using a retrospective patient database and then tested prospectively to see if it predicts early treatment response. If the marker works, doctors could use it to personalize chemotherapy choices sooner.
Why it matters
Potential benefit: If successful, this could help identify earlier which patients will or will not respond to specific chemotherapies, allowing more personalized treatment decisions.
How similar studies have gone: Radiomics and pathomics approaches have shown promising early results in related cancers, but combining CT and histopathology into a validated clinical marker remains relatively novel.
Where this research is happening
-
University of Oklahoma
Norman, United States Active
Researchers
- Principal investigator: Qiu, Yuchen — University of Oklahoma
- Study coordinator: Qiu, Yuchen
Related research
Other NIH-funded projects on the same topics.
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Improving ovarian cancer treatment predictions using advanced imaging techniques
This study is looking to improve how doctors predict which ovarian cancer patients will respond well to chemotherapy by using advanced computer techniques to analyze CT scans and tissue images, helping to identify the best treatment options for each patient.
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Understanding the experience of ovarian cancer after diagnosis to improve survivorship
This NIH grant funds a mixed-methods study to better understand physical and emotional challenges faced by ovarian cancer survivors and how supportive care can help them live better after diagnosis.
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Targeting quiescent ovarian cancer cells to overcome chemotherapy resistance
A study focusing on why some ovarian cancer cells pause dividing and resist chemotherapy, with the goal of finding new treatment targets for relapsed disease.
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Photodynamic lipids to boost chemotherapy for metastatic ovarian cancer
A patient-friendly approach tests a light-activated method to make ovarian cancer metastases more sensitive to chemotherapy.
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Colorectal cancer prognosis through a broad, collaborative study
A large, multi-center study follows people newly diagnosed with colorectal cancer to find biomarkers and patterns that predict outcomes and guide future care.
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Integrated framework to validate and quantify proteoforms in patient-derived ovarian cancer cells
A collaboration will combine advanced top-down proteomics with a new computational method to precisely identify and measure intact proteoforms in tiny samples from ovarian cancer cells.
About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page.