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Image-guided patient-specific optimization of catheter placement for convection-enhanced nanoparticle delivery in recurrent glioblastoma.
- Source :
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Computers in biology and medicine [Comput Biol Med] 2024 Sep; Vol. 179, pp. 108889. Date of Electronic Publication: 2024 Jul 19. - Publication Year :
- 2024
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Abstract
- Background: Proper catheter placement for convection-enhanced delivery (CED) is required to maximize tumor coverage and minimize exposure to healthy tissue. We developed an image-based model to patient-specifically optimize the catheter placement for rhenium-186 ( <superscript>186</superscript> Re)-nanoliposomes (RNL) delivery to treat recurrent glioblastoma (rGBM).<br />Methods: The model consists of the 1) fluid fields generated via catheter infusion, 2) dynamic transport of RNL, and 3) transforming RNL concentration to the SPECT signal. Patient-specific tissue geometries were assigned from pre-delivery MRIs. Model parameters were personalized with either 1) individual-based calibration with longitudinal SPECT images, or 2) population-based assignment via leave-one-out cross-validation. The concordance correlation coefficient (CCC) was used to quantify the agreement between the predicted and measured SPECT signals. The model was then used to simulate RNL distributions from a range of catheter placements, resulting in a ratio of the cumulative RNL dose outside versus inside the tumor, the "off-target ratio" (OTR). Optimal catheter placement) was identified by minimizing OTR.<br />Results: Fifteen patients with rGBM from a Phase I/II clinical trial (NCT01906385) were recruited to the study. Our model, with either individual-calibrated or population-assigned parameters, achieved high accuracy (CCC > 0.80) for predicting RNL distributions up to 24 h after delivery. The optimal catheter placements identified using this model achieved a median (range) of 34.56 % (14.70 %-61.12 %) reduction on OTR at the 24 h post-delivery in comparison to the original placements.<br />Conclusions: Our image-guided model achieved high accuracy for predicting patient-specific RNL distributions and indicates value for optimizing catheter placement for CED of radiolabeled liposomes.<br />Competing Interests: Declaration of competing interest William T. Phillips discloses stock ownership and board membership in NanoTx, Inc., and is consultant for Plus Therapeutics, Inc. Andrew J. Brenner discloses financial Interests and stock ownership in NanoTx, Inc., and financial Interests and advisory role in Plus Therapeutics, Inc. Ryan T. Woodall owns stake in Cairina Inc. All other authors report no conflict of interest relevant to this article.<br /> (Copyright © 2024 Elsevier Ltd. All rights reserved.)
- Subjects :
- Humans
Brain Neoplasms diagnostic imaging
Nanoparticles chemistry
Tomography, Emission-Computed, Single-Photon methods
Catheters
Convection
Magnetic Resonance Imaging methods
Male
Female
Neoplasm Recurrence, Local diagnostic imaging
Middle Aged
Drug Delivery Systems methods
Liposomes chemistry
Glioblastoma diagnostic imaging
Rhenium therapeutic use
Subjects
Details
- Language :
- English
- ISSN :
- 1879-0534
- Volume :
- 179
- Database :
- MEDLINE
- Journal :
- Computers in biology and medicine
- Publication Type :
- Academic Journal
- Accession number :
- 39032243
- Full Text :
- https://doi.org/10.1016/j.compbiomed.2024.108889