Diffusion kurtosis imaging for characterizing tumor heterogeneity in an intracranial rat glioblastoma model

An End-to-end In-Silico and In-Vitro Drug Repurposing Pipeline for Glioblastoma

Our study aims to address the challenges in drug development for glioblastoma, a highly aggressive brain cancer with poor prognosis. We propose a computational framework that utilizes machine learning-based propensity score matching to estimate counterfactual treatment effects and predict synergistic effects of drug combinations. Through our in-silico analysis, we identified promising drug candidates and drug combinations that warrant further investigation. To validate these computational findings, we conducted in-vitro experiments on two GBM cell lines, U87 and T98G. The experimental results demonstrated that some of the identified drugs and drug combinations indeed exhibit strong suppressive effects on GBM cell growth. Our end-to-end pipeline showcases the feasibility of integrating computational models with biological experiments to expedite drug repurposing and discovery efforts. By bridging the gap between in-silico analysis and in-vitro validation, we demonstrate the potential of this approach to accelerate the development of novel and effective treatments for glioblastoma.

Diffusion kurtosis imaging detects subclinical white matter abnormalities in Phenylketonuria

OBJECTIVE

Phenylketonuria (PKU) is an autosomal recessive disorder whereby deficiencies in phenylalanine metabolism cause progressive neurological dysfunction. Managing PKU is challenging, with disease monitoring focussed on short-term phenylalanine control rather than measures of neuronal damage. Conventional imaging lacks sensitivity, however diffusion kurtosis imaging (DKI), a new MRI method may reveal subclinical white matter structural changes in PKU.

METHODS

This cohort study involved adults with PKU recruited during routine clinical care. MRI, neurocognitive assessment and historical phenylalanine (Phe) levels were collected. A hypothesis-generating case study comparing diet-compliant and non-compliant siblings confirmed that DKI metrics are sensitive to dietary adherence and prompted a candidate metric (K_rad/K_FA ratio). We then tested this metric in a Replication cohort (PKU = 20; controls = 43).

RESULTS

Both siblings scored outside the range of controls for all DKI-based metrics, with severe changes in the periventricular white matter and a gradient of severity toward the cortex. K_rad/K_FA provided clear separation by diagnosis in the Replication cohort (p < 0.001 in periventricular, deep and pericortical compartments). The ratio also correlated negatively with attention (r = -0.51 & -0.50, p < 0.05) and positively with 3-year mean Phe (r = 0.45 & 0.58, p < 0.01).

CONCLUSION

DKI reveals regionally-specific, progressive abnormalities of brain diffusion characteristics in PKU, even in the absence of conspicuous clinical signs or abnormalities on conventional MRI. A DKI-based marker derived from these scores (K_rad/K_FA ratio) was sensitive to cognitive impairment and PKU control over the medium term and may provide a meaningful subclinical biomarker of end-organ damage.

Disparate volumetric fluid shifts across cerebral tissue compartments with two different anesthetics

Background

Large differences in glymphatic system transport—similar in magnitude to those of the sleep/wake cycle—have been observed during anesthesia with dexmedetomidine supplemented with low dose isoflurane (DEXM-I) in comparison to isoflurane (ISO). However, the biophysical and bioenergetic tissue status underlying glymphatic transport differences between anesthetics remains undefined. To further understand biophysical characteristics underlying these differences we investigated volume status across cerebral tissue compartments, water diffusivity, and T2* values in rats anesthetized with DEXM-I in comparison to ISO.

Methods

Using a crossover study design, a group of 12 Sprague Dawley female rats underwent repetitive magnetic resonance imaging (MRI) under ISO and DEXM-I. Physiological parameters were continuously measured. MRI included a proton density weighted (PDW) scan to investigate cerebrospinal fluid (CSF) and parenchymal volumetric changes, a multigradient echo scan (MGE) to calculate T2* maps as a measure of ‘bioenergetics’, and a diffusion scan to quantify the apparent diffusion coefficient (ADC).

Results

The heart rate was lower with DEXM-I in comparison to ISO, but all other physiological variables were similar across scans and groups. The PDW images revealed a 1% parenchymal volume increase with ISO compared to DEXM-I comprising multiple focal tissue areas scattered across the forebrain. In contrast, with DEXM-I the CSF compartment was enlarged by ~ 6% in comparison to ISO at the level of the basal cisterns and peri-arterial conduits which are main CSF influx routes for glymphatic transport. The T2* maps showed brain-wide increases in T2* in ISO compared to DEXM-I rats. Diffusion-weighted images yielded no significant differences in ADCs across the two anesthesia groups.

Conclusions

We demonstrated CSF volume expansion with DEXM-I (in comparison to ISO) and parenchymal (GM) expansion with ISO (in comparison to DEXM-I), which may explain the differences in glymphatic transport. The T2* changes in ISO are suggestive of an increased bioenergetic state associated with excess cellular firing/bursting when compared to DEXM-I.