About 35% of patients with a type of blood cancer called diffuse large B-cell lymphoma don't respond well to standard treatment or their cancer comes back. When this happens, newer treatments like CAR T-cell therapy (using modified immune cells) or bispecific antibodies (special proteins that help the immune system fight cancer) are an option. However, these treatments are only successful in about half the patients. It is currently difficult to predict which patients will respond to these treatments or experience serious side effects. This makes it hard to choose the best treatment plan for a given patient. In this project, a special type of magnetic resonance imaging (MRI) scan will be used to track immune cells called macrophages that live around tumors. These cells can either help fight cancer or help cancer grow. By understanding how these cells behave, it may be possible to predict treatment success. The MRI technique involves injecting an iron-based substance called ferumoxytol, which can be used as an MRI contrast agent, into patients' veins. This contrast agent gets absorbed by the macrophages, making them visible on MRI scans throughout the entire body - not just one tumor spot. Sixty patients will be scanned before and after treatment (30 getting CAR T-cells, 30 getting bispecific antibodies), and results will be compared with tissue samples. The goals are to predict which patients will go into complete remission, predict who will survive longer without cancer progression, and identify patients at risk for serious side effects like cytokine release syndrome. If successful, this imaging technique could help to personalize treatment choices, potentially improving outcomes while avoiding unnecessary toxicity in patients who will not benefit from these intensive therapies.
Age range
18 Years
Sex
ALL
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Correlation between immunoMRI and M1 and M2 TAM-directed IHC
Timeframe: Through study completion, 3 years
Prediction of complete remission (CR)
Timeframe: Through study completion, 3 years
Prediction of 1-year overall survival (OS)
Timeframe: Through study completion, 3 years
Prediction of 1-year PFS
Timeframe: Through study completion, 3 years
Prediction of development of treatment toxicities (CRS, ICANS)
Timeframe: Through study completion, 3 years
Marius E Mayerhoefer, MD, PhD