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Brain Microstructural Damage as Potential Biomarker of Immune Cell-Associated Neurotoxicity Syndrome
Caterina Lapucci1, Massimiliano Gambella2, Emilio Cipriano3
1IRCCS Ospedale Policlinico San Martino, Genoa, Italy.
Background And Purpose:
Chimeric antigen receptor-engineered T-cell (CAR-T) therapy in hematological malignancies may be associated with severe complications, as Cytokine Release Syndrome (CRS) and Immune effector Cell-Associated Neurotoxicity Syndrome (ICANS). The aim of the study is to investigate MRI-derived macrostructural and microstructural features potentially able to identify patients at higher ICANS risk.
Methods:
Forty-two patients treated with CAR-T from October 2020 to June 2025 performed brain MRIs before CAR-T administration, including diffusion-weighted imaging. A general linear model was used to compare patients who developed ICANS, CRS, or neither at baseline in terms of MRI macro- and microstructural features. A binary logistic regression analysis was performed to evaluate the role of microstructural features in predicting the risk of developing ICANS.
Results:
Mean age 59.2 ± 13 years, 59.5% male; 21 (50%) patients received tisagenlecleucel, 21 (50%), axicabtagene ciloleucel or brexucabtagene autoleucel; 14 (33%) and 31 (73.8%) patients developed ICANS and CRS, respectively. At baseline MRI, fluid-attenuated inversion recovery (FLAIR) white matter (WM) hyperintensities were detected in 41/42 (97.6%). No significant differences between patients who developed ICANS, CRS and neither both were observed in terms of FLAIR hyperintensities nor total brain volume at baseline. Fractional anisotropy extracted from FLAIR hyperintensities and WM areas without macroscopic abnormalities was a predictor of ICANS in the logistic regression model (p = 0.03 and 0.02, respectively).
Conclusions:
FLAIR hyperintensities and brain volume prior to CAR-T were not informative, whereas the severity of WM microstructural (axonal) damage predicted ICANS risk. Greater axonal damage was associated with a higher likelihood of ICANS.
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