Dataset Information

MR image-guided delivery of cisplatin-loaded brain-penetrating nanoparticles to invasive glioma with focused ultrasound.

ABSTRACT: Systemically administered chemotherapeutic drugs are often ineffective in the treatment of invasive brain tumors due to poor therapeutic index. Within gliomas, despite the presence of heterogeneously leaky microvessels, dense extracellular matrix and high interstitial pressure generate a "blood-tumor barrier" (BTB), which inhibits drug delivery and distribution. Meanwhile, beyond the contrast MRI-enhancing edge of the tumor, invasive cancer cells are protected by the intact blood-brain barrier (BBB). Here, we tested whether brain-penetrating nanoparticles (BPN) that possess dense surface coatings of polyethylene glycol (PEG) and are loaded with cisplatin (CDDP) could be delivered across both the blood-tumor and blood-brain barriers with MR image-guided focused ultrasound (MRgFUS), and whether this treatment could control glioma growth and invasiveness. To this end, we first established that MRgFUS is capable of significantly enhancing the delivery of ~60nm fluorescent tracer BPN across the blood-tumor barrier in both the 9L (6-fold improvement) gliosarcoma and invasive F98 (28-fold improvement) glioma models. Importantly, BPN delivery across the intact BBB, just beyond the tumor edge, was also markedly increased in both tumor models. We then showed that a CDDP loaded BPN formulation (CDDP-BPN), composed of a blend of polyaspartic acid (PAA) and heavily PEGylated polyaspartic acid (PAA-PEG), was highly stable, provided extended drug release, and was effective against F98 cells in vitro. These CDDP-BPN were delivered from the systemic circulation into orthotopic F98 gliomas using MRgFUS, where they elicited a significant reduction in tumor invasiveness and growth, as well as improved animal survival. We conclude that this therapy may offer a powerful new approach for the treatment invasive gliomas, particularly for preventing and controlling recurrence.

SUBMITTER: Timbie KF

PROVIDER: S-EPMC5593770 | biostudies-literature | 2017 Oct

REPOSITORIES: biostudies-literature

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MR image-guided delivery of cisplatin-loaded brain-penetrating nanoparticles to invasive glioma with focused ultrasound.

Timbie Kelsie F KF Afzal Umara U Date Abhijit A Zhang Clark C Song Ji J Wilson Miller G G Suk Jung Soo JS Hanes Justin J Price Richard J RJ

Journal of controlled release : official journal of the Controlled Release Society 20170311

Systemically administered chemotherapeutic drugs are often ineffective in the treatment of invasive brain tumors due to poor therapeutic index. Within gliomas, despite the presence of heterogeneously leaky microvessels, dense extracellular matrix and high interstitial pressure generate a "blood-tumor barrier" (BTB), which inhibits drug delivery and distribution. Meanwhile, beyond the contrast MRI-enhancing edge of the tumor, invasive cancer cells are protected by the intact blood-brain barrier ( ...[more]

PMID: 28288892

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Project description:Background and purposeTranscranial MR imaging-guided focused ultrasound is a promising novel technique to treat multiple disorders and diseases. Planning for transcranial MR imaging-guided focused ultrasound requires both a CT scan for skull density estimation and treatment-planning simulation and an MR imaging for target identification. It is desirable to simplify the clinical workflow of transcranial MR imaging-guided focused ultrasound treatment planning. The purpose of this study was to examine the feasibility of deep learning techniques to convert MR imaging ultrashort TE images directly to synthetic CT of the skull images for use in transcranial MR imaging-guided focused ultrasound treatment planning.Materials and methodsThe U-Net neural network was trained and tested on data obtained from 41 subjects (mean age, 66.4 ± 11.0 years; 15 women). The derived neural network model was evaluated using a k-fold cross-validation method. Derived acoustic properties were verified by comparing the whole skull-density ratio from deep learning synthesized CT of the skull with the reference CT of the skull. In addition, acoustic and temperature simulations were performed using the deep learning CT to predict the target temperature rise during transcranial MR imaging-guided focused ultrasound.ResultsThe derived deep learning model generates synthetic CT of the skull images that are highly comparable with the true CT of the skull images. Their intensities in Hounsfield units have a spatial correlation coefficient of 0.80 ± 0.08, a mean absolute error of 104.57 ± 21.33 HU, and a subject-wise correlation coefficient of 0.91. Furthermore, deep learning CT of the skull is reliable in the skull-density ratio estimation (r = 0.96). A simulation study showed that both the peak target temperatures and temperature distribution from deep learning CT are comparable with those of the reference CT.ConclusionsThe deep learning method can be used to simplify workflow associated with transcranial MR imaging-guided focused ultrasound.

Dataset Information

MR image-guided delivery of cisplatin-loaded brain-penetrating nanoparticles to invasive glioma with focused ultrasound.

Publications

MR image-guided delivery of cisplatin-loaded brain-penetrating nanoparticles to invasive glioma with focused ultrasound.

Similar Datasets

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