Quantitative detection of drug dose and spatial distribution in the lung revealed by Cryoslicing Imaging

AbstractAdministration of drugs via inhalation is an attractive route for pulmonary and systemic drug delivery. The therapeutic outcome of inhalation therapy depends not only on the dose of the lung-delivered drug, but also on its bioactivity and regional distribution. Fluorescence imaging has the potential to monitor these aspects already during preclinical development of inhaled drugs, but quantitative methods of analysis are lacking. In this proof-of-concept study, we demonstrate that Cryoslicing Imaging allows for 3D quantitative fluorescence imaging on ex vivo murine lungs. Known amounts of fluorescent substance (nanoparticles or fluorophore–drug conjugate) were instilled in the lungs of mice. The excised lungs were measured by Cryoslicing Imaging. Herein, white light and fluorescence images are obtained from the face of a gradually sliced frozen organ block. A quantitative representation of the fluorescence intensity throughout the lung was inferred from the images by accounting for instrument noise, tissue autofluorescence and out-of-plane fluorescence. Importantly, the out-of-plane fluorescence correction is based on the experimentally determined effective light attenuation coefficient of frozen murine lung tissue (10.0±0.6cm−1 at 716nm). The linear correlation between pulmonary total fluorescence intensity and pulmonary fluorophore dose indicates the validity of this method and allows direct fluorophore dose assessment. The pulmonary dose of a fluorescence-labeled drug (FcγR-Alexa750) could be assessed with an estimated accuracy of 9% and the limit of detection in ng regime. Hence, Cryoslicing Imaging can be used for quantitative assessment of dose and 3D distribution of fluorescence-labeled drugs or drug carriers in the lungs of mice

Simultaneous Color Imaging and Fluorescence Detection using a Single Camera Sensor

We demonstrate an imaging system intended for medical applications that allows to display simultaneously and in real-time both the reflectance image as well as the signal from up to three fluorescent dyes

Fluorescence background subtraction technique for hybrid fluorescence molecular tomography/x-ray computed tomography imaging of a mouse model of early stage lung cancer

The ability to visualize early stage lung cancer is important in the study of biomarkers and targeting agents that could lead to earlier diagnosis. The recent development of hybrid free-space 360-deg fluorescence molecular tomography (FMT) and x-ray computed tomography (XCT) imaging yields a superior optical imaging modality for three-dimensional small animal fluorescence imaging over stand-alone optical systems. Imaging accuracy was improved by using XCT information in the fluorescence reconstruction method. Despite this progress, the detection sensitivity of targeted fluorescence agents remains limited by nonspecific background accumulation of the fluorochrome employed, which complicates early detection of murine cancers. Therefore we examine whether x-ray CT information and bulk fluorescence detection can be combined to increase detection sensitivity. Correspondingly, we research the performance of a data-driven fluorescence background estimator employed for subtraction of background fluorescence from acquisition data. Using mice containing known fluorochromes ex vivo, we demonstrate the reduction of background signals from reconstructed images and sensitivity improvements. Finally, by applying the method to in vivo data from K-ras transgenic mice developing lung cancer, we find small tumors at an early stage compared with reconstructions performed using raw data. We conclude with the benefits of employing fluorescence subtraction in hybrid FMT-XCT for early detection studies

In-vivo imaging of murine tumors using complete-angle projection fluorescence molecular tomography

We interrogate the ability of free-space fluorescence tomography to image small animals in vivo using charge-coupled device (CCD) camera measurements over 360-deg noncontact projections. We demonstrate the performance of normalized dual-wavelength measurements that are essential for in-vivo use, as they account for the heterogeneous distribution of photons in tissue. In-vivo imaging is then showcased on mouse lung and brain tumors cross-validated by x-ray microcomputed tomography and histology

Visualization 1: Simultaneous real-time multicomponent fluorescence and reflectance imaging method for fluorescence-guided surgery

Injection of fluorescent dyes into tissue Originally published in Optics Letters on 15 March 2016 (ol-41-6-1173

Multiparametric Cystoscopy for Detection of Bladder Cancer Using Real-time Multispectral Imaging

Background: Various imaging modalities can be used in addition to white light (WL) to improve detection of bladder cancer (BC). Objective: To use real-time multispectral imaging (rMSI) during urethrocystoscopy to combine different imaging modalities to achieve multiparametric cystoscopy (MPC). Design, setting, and partidpants: The rMSI system consisted of a camera with a spectral filter, a multi-LED light source, a microcontroller, and a computer for display and data acquisition. MSI with this system was achieved via temporal multiplexing. Surgical procedure: MPC was performed in ten patients with a diagnosed bladder tumor. Measurements: We gathered evidence to prove the feasibility of our approach. In addition, experienced urologists performed post-interventional evaluation of images of individual lesions. Images were independently rated in a semiquantitative manner for each modality. A statistical model was built for pairwise comparisons across modalities. Results and limitations: Overall, 31 lesions were detected using the rMSI set-up. Histopathology revealed malignancy in 27 lesions. All lesions could be visualized simultaneously in five modalities: WL, enhanced vascular contrast (EVC), blue light fluorescence, protoporphyrin IX fluorescence, and autofluorescence. EVC and photodynamic diagnosis images were merged in real time into one MP image. Using the recorded images, two observers identified all malignant lesions via MPC, whereas the single modalities did not arouse substantial suspicion for some lesions. The MP images of malignant lesions were rated significantly more suspicious than the images from single imaging modalities. Conclusions: We demonstrated for the first time the application of rMSI in endourology and we established MPC for detection of BC. This approach allows existing imaging modalities to be combined, and it may significantly improve the detection of bladder cancer

Usefulness of a Darwinian system in a biotechnological application: evolution of optical window fluorescent protein variants under selective pressure.

With rare exceptions, natural evolution is an extremely slow process. One particularly striking exception in the case of protein evolution is in the natural production of antibodies. Developing B cells activate and diversify their immunoglobulin (Ig) genes by recombination, gene conversion (GC) and somatic hypermutation (SHM). Iterative cycles of hypermutation and selection continue until antibodies of high antigen binding specificity emerge (affinity maturation). The avian B cell line DT40, a cell line which is highly amenable to genetic manipulation and exhibits a high rate of targeted integration, utilizes both GC and SHM. Targeting the DT40's diversification machinery onto transgenes of interest inserted into the Ig loci and coupling selective pressure based on the desired outcome mimics evolution. Here we further demonstrate the usefulness of this platform technology by selectively pressuring a large shift in the spectral properties of the fluorescent protein eqFP615 into the highly stable and advanced optical imaging expediting fluorescent protein Amrose. The method is advantageous as it is time and cost effective and no prior knowledge of the outcome protein's structure is necessary. Amrose was evolved to have high excitation at 633 nm and excitation/emission into the far-red, which is optimal for whole-body and deep tissue imaging as we demonstrate in the zebrafish and mouse model