Supervised learning to quantify amyloidosis in whole brains of an Alzheimer's disease mouse model acquired with optical projection tomography

Noninvasive Visualization of Amyloid-Beta Deposits in Alzheimer's Amyloidosis Mice via Fluorescence Molecular Tomography Using Contrast Agent

Alzheimer's disease is pathologically featured by the accumulation of amyloid-beta (Aβ) plaque and neurofibrillary tangles. Compared to small animal positron emission tomography, optical imaging features nonionizing radiation, low cost, and logistic convenience. Optical detection of Aβ deposits is typically implemented by 2D macroscopic imaging and various microscopic techniques assisted with Aβ-targeted contrast agents. Here, we introduce fluorescence molecular tomography (FMT), a macroscopic 3D fluorescence imaging technique, convenient for in vivo longitudinal monitoring of the animal brain without the involvement of cranial window opening operation. This chapter aims to provide the protocols for FMT in vivo imaging of Aβ deposits in the brain of rodent model of Alzheimer's disease. The materials, stepwise method, notes, limitations of FMT, and emerging opportunities for FMT techniques are presented.

Weakly supervised learning analysis of Aβ plaque distribution in the whole rat brain

Alzheimer's disease (AD) is a great challenge for the world and hardly to be cured, partly because of the lack of animal models that fully mimic pathological progress. Recently, a rat model exhibiting the most pathological symptoms of AD has been reported. However, high-resolution imaging and accurate quantification of beta-amyloid (Aβ) plaques in the whole rat brain have not been fulfilled due to substantial technical challenges. In this paper, a high-efficiency data analysis pipeline is proposed to quantify Aβ plaques in whole rat brain through several terabytes of image data acquired by a high-speed volumetric imaging approach we have developed previously. A novel segmentation framework applying a high-performance weakly supervised learning method which can dramatically reduce the human labeling consumption is described in this study. The effectiveness of our segmentation framework is validated with different metrics. The segmented Aβ plaques were mapped to a standard rat brain atlas for quantitative analysis of the Aβ distribution in each brain area. This pipeline may also be applied to the segmentation and accurate quantification of other non-specific morphology objects.

Non-invasive visualization of amyloid-beta deposits in Alzheimer amyloidosis mice using magnetic resonance imaging and fluorescence molecular tomography

Abnormal cerebral accumulation of amyloid-beta peptide (Aβ) is a major hallmark of Alzheimer's disease. Non-invasive monitoring of Aβ deposits enables assessing the disease burden in patients and animal models mimicking aspects of the human disease as well as evaluating the efficacy of Aβ-modulating therapies. Previous in vivo assessments of plaque load have been predominantly based on macroscopic fluorescence reflectance imaging (FRI) and confocal or two-photon microscopy using Aβ-specific imaging agents. However, the former method lacks depth resolution, whereas the latter is restricted by the limited field of view preventing a full coverage of the large brain region. Here, we utilized a fluorescence molecular tomography (FMT)-magnetic resonance imaging (MRI) pipeline with the curcumin derivative fluorescent probe CRANAD-2 to achieve full 3D brain coverage for detecting Aβ accumulation in the arcAβ mouse model of cerebral amyloidosis. A homebuilt FMT system was used for data acquisition, whereas a customized software platform enabled the integration of MRI-derived anatomical information as prior information for FMT image reconstruction. The results obtained from the FMT-MRI study were compared to those from conventional planar FRI recorded under similar physiological conditions, yielding comparable time courses of the fluorescence intensity following intravenous injection of CRANAD-2 in a region-of-interest comprising the brain. In conclusion, we have demonstrated the feasibility of visualizing Aβ deposition in 3D using a multimodal FMT-MRI strategy. This hybrid imaging method provides complementary anatomical, physiological and molecular information, thereby enabling the detailed characterization of the disease status in arcAβ mouse models, which can also facilitate monitoring the efficacy of putative treatments targeting Aβ.

Statistical distortion of supervised learning predictions in optical microscopy induced by image compression

The growth of data throughput in optical microscopy has triggered the extensive use of supervised learning (SL) models on compressed datasets for automated analysis. Investigating the effects of image compression on SL predictions is therefore pivotal to assess their reliability, especially for clinical use. We quantify the statistical distortions induced by compression through the comparison of predictions on compressed data to the raw predictive uncertainty, numerically estimated from the raw noise statistics measured via sensor calibration. Predictions on cell segmentation parameters are altered by up to 15% and more than 10 standard deviations after 16-to-8 bits pixel depth reduction and 10:1 JPEG compression. JPEG formats with higher compression ratios show significantly larger distortions. Interestingly, a recent metrologically accurate algorithm, offering up to 10:1 compression ratio, provides a prediction spread equivalent to that stemming from raw noise. The method described here allows to set a lower bound to the predictive uncertainty of a SL task and can be generalized to determine the statistical distortions originated from a variety of processing pipelines in AI-assisted fields.

Nanoparticle-based colorimetric sensors to detect neurodegenerative disease biomarkers

Neurodegenerative disorders (NDDs) are progressive, incurable health conditions that primarily affect brain cells, and result in loss of brain mass and impaired function. Current sensing technologies for NDD detection are limited by high cost, long sample preparation, and/or require skilled personnel. To overcome these limitations, optical sensors, specifically colorimetric sensors, have garnered increasing attention towards the development of a cost-effective, simple, and rapid alternative approach. In this review, we evaluate colorimetric sensing strategies of NDD biomarkers (e.g. proteins, neurotransmitters, bio-thiols, and sulfide), address the limitations and challenges of optical sensor technologies, and provide our outlook on the future of this field.

High resolution optical projection tomography platform for multispectral imaging of the mouse gut

Optical projection tomography (OPT) is a powerful tool for three-dimensional imaging of mesoscopic biological samples with great use for biomedical phenotyping studies. We present a fluorescent OPT platform that enables direct visualization of biological specimens and processes at a centimeter scale with high spatial resolution, as well as fast data throughput and reconstruction. We demonstrate nearly isotropic sub-28 µm resolution over more than 60 mm3 after reconstruction of a single acquisition. Our setup is optimized for imaging the mouse gut at multiple wavelengths. Thanks to a new sample preparation protocol specifically developed for gut specimens, we can observe the spatial arrangement of the intestinal villi and the vasculature network of a 3-cm long healthy mouse gut. Besides the blood vessel network surrounding the gastrointestinal tract, we observe traces of vasculature at the villi ends close to the lumen. The combination of rapid acquisition and a large field of view with high spatial resolution in 3D mesoscopic imaging holds an invaluable potential for gastrointestinal pathology research.

Deep learning approach for quantification of organelles and misfolded polypeptide delivery within degradative compartments

Endolysosomal compartments maintain cellular fitness by clearing dysfunctional organelles and proteins from cells. Modulation of their activity offers therapeutic opportunities. Quantification of cargo delivery to and/or accumulation within endolysosomes is instrumental for characterizing lysosome-driven pathways at the molecular level and monitoring consequences of genetic or environmental modifications. Here we introduce LysoQuant, a deep learning approach for segmentation and classification of fluorescence images capturing cargo delivery within endolysosomes for clearance. LysoQuant is trained for unbiased and rapid recognition with human-level accuracy, and the pipeline informs on a series of quantitative parameters such as endolysosome number, size, shape, position within cells, and occupancy, which report on activity of lysosome-driven pathways. In our selected examples, LysoQuant successfully determines the magnitude of mechanistically distinct catabolic pathways that ensure lysosomal clearance of a model organelle, the endoplasmic reticulum, and of a model protein, polymerogenic ATZ. It does so with accuracy and velocity compatible with those of high-throughput analyses.

Optical Projection Tomography Using a Commercial Microfluidic System

Optical projection tomography (OPT) is the direct optical equivalent of X-ray computed tomography (CT). To obtain a larger depth of field, traditional OPT usually decreases the numerical aperture (NA) of the objective lens to decrease the resolution of the image. So, there is a trade-off between sample size and resolution. Commercial microfluidic systems can observe a sample in flow mode. In this paper, an OPT instrument is constructed to observe samples. The OPT instrument is combined with commercial microfluidic systems to obtain a three-dimensional and time (3D + T)/four-dimensional (4D) video of the sample. “Focal plane scanning” is also used to increase the images’ depth of field. A series of two-dimensional (2D) images in different focal planes was observed and compared with images simulated using our program. Our work dynamically monitors 3D OPT images. Commercial microfluidic systems simulate blood flow, which has potential application in blood monitoring and intelligent drug delivery platforms. We design an OPT adaptor to perform OPT on a commercial wide-field inverted microscope (Olympusix81). Images in different focal planes are observed and analyzed. Using a commercial microfluidic system, a video is also acquired to record motion pictures of samples at different flow rates. To our knowledge, this is the first time an OPT setup has been combined with a microfluidic system.