Focused ultrasound–induced blood–brain barrier opening: A comparative analysis of permeability quantification based on Ktrans and PS
| Authors | |
|---|---|
| Year of publication | 2025 |
| Type | Article in Periodical |
| Magazine / Source | Magnetic Resonance in Medicine |
| MU Faculty or unit | |
| Citation | |
| web | https://onlinelibrary.wiley.com/doi/full/10.1002/mrm.30446 |
| Doi | https://doi.org/10.1002/mrm.30446 |
| Keywords | BBB opening; DCE-MRI; focused ultrasound; perfusion analysis; simulation |
| Description | Purpose Focused ultrasound-induced blood–brain barrier (BBB) opening is a promising method for neurotherapeutic delivery. The standard parameter for quantifying induced BBB permeability is Ktrans, which reflects both permeability and plasma flow. The influence of plasma flow can be eliminated by estimating the PS parameter; however, this parameter has been largely unexplored in this application. This study aims to compare permeability estimates based on Ktrans and PS in focused ultrasound-induced BBB opening experiments. Methods We used the extended Tofts model (ETM) and the two-compartment exchange model (2CXM) to estimate Ktrans and PS parameters, respectively. Permeability estimates were compared using simulated concentration curves, simulated DCE-MRI data, and real datasets. We also explored the influence of spatially regularized model fitting on the results. Results For opened BBB, Ktrans was minimally influenced by plasma flow under the tested conditions. However, fitting the ETM often introduced outliers in Ktrans estimates in regions with closed BBB. The 2CXM outperformed the ETM at high signal-to-noise ratios, but its higher complexity led to lower precision at low signal-to-noise ratios. Both of these issues were successfully compensated for by spatially regularized model fitting. Conclusion Both Ktrans and PS appear to be suitable options for quantifying BBB opening, and the appropriate choice depends on the specifics of the acquired DCE-MRI data. Additionally, spatial regularization has demonstrated its importance in enhancing the accuracy and reproducibility of results for both models. |
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