Tumor biomechanics as a novel imaging biomarker to assess response to immunotherapy in a murine glioma model.

Glioblastoma is the most common and aggressive primary malignant brain tumor with poor prognosis. Novel immunotherapeutic approaches are currently under investigation. Even though magnetic resonance imaging (MRI) is the most important imaging tool for treatment monitoring, response assessment is often hampered by therapy-related tissue changes. As tumor and therapy-associated tissue reactions differ structurally, we hypothesize that biomechanics could be a pertinent imaging proxy for differentiation. Longitudinal MRI and magnetic resonance elastography (MRE) were performed to monitor response to immunotherapy with a toll-like receptor 7/8 agonist in orthotopic syngeneic experimental glioma. Imaging results were correlated to histology and light sheet microscopy data. Here, we identify MRE as a promising non-invasive imaging method for immunotherapy-monitoring by quantifying changes in response-related tumor mechanics. Specifically, we show that a relative softening of treated compared to untreated tumors is linked to the inflammatory processes following therapy-induced re-education of tumor-associated myeloid cells. Mechanistically, combined effects of myeloid influx and inflammation including extracellular matrix degradation following immunotherapy form the basis of treated tumors being softer than untreated glioma. This is a very early indicator of therapy response outperforming established imaging metrics such as tumor volume. The overall anti-tumor inflammatory processes likely have similar effects on human brain tissue biomechanics, making MRE a promising tool for gauging response to immunotherapy in glioma patients early, thereby strongly impacting patient pathway.

Experimental Validation of Enhanced Magnetic Resonance Imaging (EMRI) Using Particle Image Velocimetry (PIV).

Flow-sensitive four-dimensional Cardiovascular Magnetic Resonance Imaging (4D Flow CMR) has increasingly been utilised to characterise patients' blood flow, in association with patiens' state of health and disease, even though spatial and temporal resolutions still constitute a limit. Computational fluid dynamics (CFD) is a powerful tool that could expand these information and, if integrated with experimentally-obtained velocity fields, would enable to derive a large variety of the flow descriptors of interest. However, the accuracy of the flow parameters is highly influenced by the quality of the input data such as the anatomical model and boundary conditions typically derived from medical images including 4D Flow CMR. We previously proposed a novel approach in which 4D Flow CMR and CFD velocity fields are integrated to obtain an Enhanced 4D Flow CMR (EMRI), allowing to overcome the spatial-resolution limitation of 4D Flow CMR, and enable an accurate quantification of flow. In this paper, the proposed approach is validated in a U bend channel, an idealised model of the human aortic arch. The flow patterns were studied with 4D Flow CMR, CFD and EMRI, and compared with high resolution 2D PIV experiments obtained in pulsatile conditions. The main strengths and limitations of 4D Flow CMR and CFD were illustrated by exploiting the accuracy of PIV by comparing against PIV velocity fields. EMRI flow patterns showed a better qualitative and quantitative agreement with PIV results than the other techniques. EMRI enables to overcome the experimental limitations of MRI-based velocity measurements and the modelling simplifications of CFD, allowing an accurate prediction of complex flow patterns observed experimentally, while satisfying mass and momentum balance equations.

Sensitivity Enhancement of Förster Resonance Energy Transfer Immunoassays by Multiple Antibody Conjugation on Quantum Dots.

Quantum dots (QDs) are not only advantageous for color-tuning, improved brightness, and high stability, but their nanoparticle surfaces also allow for the attachment of many biomolecules. Because IgG antibodies (AB) are in the same size range of biocompatible QDs and the AB orientation after conjugation to the QD is often random, it is difficult to predict if few or many AB per QD will lead to an efficient AB-QD conjugate. This is particularly true for homogeneous Förster resonance energy transfer (FRET) sandwich immunoassays, for which the AB on the QD must bind a biomarker that needs to bind a second AB-FRET-conjugate. Here, we investigate the performance of Tb-to-QD FRET immunoassays against total prostate specific antigen (TPSA) by changing the number of AB per QD while leaving all the other assay components unchanged. We first characterize the AB-QD conjugation by various spectroscopic, microscopic, and chromatographic techniques and then quantify the TPSA immunoassay performance regarding sensitivity, limit of detection, and dynamic range. Our results show that an increasing conjugation ratio leads to significantly enhanced FRET immunoassays. These findings will be highly important for developing QD-based immunoassays in which the concentrations of both AB and QDs can significantly influence the assay performance.