Improving risk assessment for uncertain lung nodules using advanced AI techniques
Official title: Risk stratifying indeterminate pulmonary nodules with jointly learned features from longitudinal radiologic and clinical big data
Funded at Vanderbilt University · NIH-10871696 · Data updated 2026-11-12
This study is looking to improve how doctors determine the risk of certain lung nodules by using information from multiple CT scans and patient records, with the help of artificial intelligence, to give patients a clearer idea of whether their nodules are more likely to be harmless or serious.
Quick facts
| Grant type | Fellowship grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Vanderbilt University NIH-funded |
| Lab location | 1 site (Nashville, UNITED STATES) |
| Project start | July 1, 2023 |
| Project end | September 19, 2026 |
| Funding year | 2024 |
| Award (this year) | $53,351 |
| NIH project number | 5F30CA275020-02 |
| Project ID | NIH-10871696 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are individuals who have been identified with indeterminate pulmonary nodules and require further evaluation to determine their malignancy risk.
✕Less likely to help
Patients with clearly defined benign nodules or those who do not have pulmonary nodules may not benefit from this research.
What this research studies
This research focuses on enhancing the accuracy of risk assessment for indeterminate pulmonary nodules (IPNs) by integrating data from repeated CT scans and clinical records. By employing artificial intelligence, the study aims to develop a predictive model that can classify these nodules into low and high malignancy risk categories. This approach seeks to provide a more personalized assessment for patients, potentially leading to better management decisions and outcomes. The methodology involves analyzing dynamic changes in nodules alongside clinical factors such as smoking history and lab results.
Why it matters
Potential benefit: If successful, this research could lead to more accurate and personalized risk assessments for patients with lung nodules, improving clinical decision-making and potentially reducing unnecessary procedures.
How similar studies have gone: Previous research has shown promise in using AI for medical imaging and risk stratification, indicating that this approach could lead to significant advancements in the field.
Where this research is happening
-
Vanderbilt University
Nashville, United States Active
Researchers
- Principal investigator: Li, Thomas Zhihe — Vanderbilt University
- Study coordinator: Li, Thomas Zhihe
Related research
Other NIH-funded projects on the same topics.
-
Understanding how peer norms around alcohol and HIV prevention affect adolescents and young adults in rural Uganda
This project studies how what young people think their peers do or approve of influences drinking and HIV prevention behaviors in rural Uganda, with the goal of improving health outcomes.
-
Cancer Pain Management for Asian American Breast Cancer Survivors with Depressive Symptoms
A technology-based program helps Asian American breast cancer survivors with depressive symptoms manage chronic pain more effectively from home using a web app and mobile tools.
-
Targeted gene silencing in the brain using siRNA helpers
This grant tests a new way to turn off specific brain genes in particular CNS cell types using siRNA conjugates to help understand brain biology and disease.
-
RSELVES Study: How older couples influence daily life and function with Alzheimer’s risk
A study to understand how daily routines and support between older adults and their partners relate to the development of Alzheimer’s-related functional decline.
-
Molecular mechanisms of coat assembly and regulation in membrane trafficking
A research project seeks to understand how cellular coats organize and regulate the delivery of membrane-bound cargo, with a focus on proteins related to neurological diseases.
-
Synaptic nanostructure in neurodevelopmental disorders
This project aims to map the tiny architecture of brain synapses in native cells to understand how connections form and change in neurodevelopmental disorders.
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.