MRI Monitoring of Cerebral Blood Flow after the Delivery of Nanocombretastatin across the Blood Brain Tumor Barrier

Perfusion-weighted software written in Python for DSC-MRI analysis

Introduction

Dynamic susceptibility-weighted contrast-enhanced (DSC) perfusion studies in magnetic resonance imaging (MRI) provide valuable data for studying vascular cerebral pathophysiology in different rodent models of brain diseases (stroke, tumor grading, and neurodegenerative models). The extraction of these hemodynamic parameters via DSC-MRI is based on tracer kinetic modeling, which can be solved using deconvolution-based methods, among others. Most of the post-processing software used in preclinical studies is home-built and custom-designed. Its use being, in most cases, limited to the institution responsible for the development. In this study, we designed a tool that performs the hemodynamic quantification process quickly and in a reliable way for research purposes.

Methods

The DSC-MRI quantification tool, developed as a Python project, performs the basic mathematical steps to generate the parametric maps: cerebral blood flow (CBF), cerebral blood volume (CBV), mean transit time (MTT), signal recovery (SR), and percentage signal recovery (PSR). For the validation process, a data set composed of MRI rat brain scans was evaluated: i) healthy animals, ii) temporal blood-brain barrier (BBB) dysfunction, iii) cerebral chronic hypoperfusion (CCH), iv) ischemic stroke, and v) glioblastoma multiforme (GBM) models. The resulting perfusion parameters were then compared with data retrieved from the literature.

Results

A total of 30 animals were evaluated with our DSC-MRI quantification tool. In all the models, the hemodynamic parameters reported from the literature are reproduced and they are in the same range as our results. The Bland-Altman plot used to describe the agreement between our perfusion quantitative analyses and literature data regarding healthy rats, stroke, and GBM models, determined that the agreement for CBV and MTT is higher than for CBF.

Conclusion

An open-source, Python-based DSC post-processing software package that performs key quantitative perfusion parameters has been developed. Regarding the different animal models used, the results obtained are consistent and in good agreement with the physiological patterns and values reported in the literature. Our development has been built in a modular framework to allow code customization or the addition of alternative algorithms not yet implemented.

Redox-responsive glycosylated combretastatin A-4 derivative as novel tubulin polymerization inhibitor for glioma and drug delivery

Combretastatin A-4 (CA4), a tubulin inhibitor, binds to the colchicine site of tubulin, inhibits tubulin polymerization, and leads to the apoptosis of tumor cells. However, the poor hydrophilicity and blood-brain barrier (BBB) penetration ability of CA4 hampers its application in the treatment of glioma. In this study, a novel combretastatin A-4 derivative (CA4D) was designed and developed, which was further conjugated with glucose via disulfide-bond-bridged (CA4D-SS-Glu) to enhance the BBB penetration capacity. The obtained CA4D-SS-Glu conjugate displayed a suitable water partition coefficient and the superior ability across BBB in vitro and in vivo. In addition, the CA4D-SS-Glu exhibited rapid redox-responsive drug release in the presence of glutathione, enhanced in vitro cytotoxicity, and cell apoptosis. Our data further confirmed that CA4D-SS-Glu inhibited proliferation, and restrained migration via affecting microtubule stabilization. Additionally, the conjugate also showed the highest antiproliferative and antitumor action on glioma in vivo as compared to CA4D and CA4. Taken together, the novel CA4D-SS-Glu conjugate possess improved physicochemical property and BBB penetration ability, reduction triggered release of CA4D, and efficient antiproliferative activity. These results provided a novel and effective entry to the treatment of glioma.

Acute-stage MRI cerebral oxygen consumption biomarkers predict 24-hour neurological outcome in a rat cardiac arrest model

Brain injury following cardiac arrest (CA) is thought to be caused by a sudden loss of blood flow resulting in disruption in oxygen delivery, neural function and metabolism. However, temporal trajectories of the brain's physiology in the first few hours following CA have not been fully characterized. Furthermore, the extent to which these early measures can predict future neurological outcomes has not been determined. The present study sought to perform dynamic measurements of cerebral blood flow (CBF), oxygen extraction fraction (OEF) and cerebral metabolic rate of oxygen (CMRO₂ ) with MRI in the first 3 hours following the return of spontaneous circulation (ROSC) in a rat CA model. It was found that CBF, OEF and CMRO₂ all revealed a time-dependent increase during the first 3 hours after the ROSC. Furthermore, the temporal trajectories of CBF and CMRO₂ , but not OEF, were different across rats and related to neurologic outcomes at a later time (24 hours after the ROSC) (P < .001). Rats who manifested better outcomes revealed faster increases in CBF and CMRO₂ during the acute stage. When investigating physiological parameters measured at a single time point, CBF (ρ = 0.82, P = .004) and CMRO₂ (ρ = 0.80, P = .006) measured at ~ 3 hours post-ROSC were positively associated with neurologic outcome scores at 24 hours. These findings shed light on brain physiological changes following CA, and suggest that MRI measures of brain perfusion and metabolism may provide a potential biomarker to guide post-CA management.

Glioblastoma: Targeting Angiogenesis and Tyrosine Kinase Pathways

Angiogenesis is a hallmark of glioblastoma (GBM) and remains an important therapeutic target in its treatment, especially for recurrent GBM. GBMs are characterized by the release of vascular endothelial growth factor (VEGF), an important regulator and promoter of angiogenesis. Therefore, antiangiogenic therapies (AATs) targeting VEGF or VEGF receptors (VEGFRs) were designed and thought to be an effective tool for controlling the growth of GBM. However, recent results of different clinical trials using humanized monoclonal antibodies against VEGF (bevacizumab), as well as tyrosine kinase inhibitors (TKIs) that target different VEGFRs alone or in combination with other therapeutic agents demonstrated mixed results, with the majority of reports indicating that GBM developed resistance against antiangiogenic treatments.