Biology subjects

Niedre, M.

Publications and source records attributed to Niedre, M..

7 recordsLinked to original sources

bioRxiv2026

Machine Learning Approach for Enumeration of Circulating Cells with Diffuse in vivo Flow Cytometry

SignificanceDiffuse in vivo flow cytometry (DiFC) is an emerging technique for enumerating rare, fluorescentlylabeled circulating tumor cells (CTCs) in small animals without drawing blood samples. DiFC uses detection of transient fluorescent peaks in time-series data. Previously, we used a simple amplitude threshold-based method for identifying peak candidates, but it ignores potentially useful information in peak shape that could reduce false-positive detections from instrument noise and increase detection efficiency of lower-amplitude peaks. AimTo develop a machine learning (ML)-integrated signal processing approach for improved CTC enumeration using DiFC by distinguishing CTC peaks from artifacts. ApproachWe developed an ML-integrated approach that incorporates a convolutional neural network (CNN) classifier. The CNN was trained to distinguish CTC peaks from artifacts by analyzing peak amplitude and temporal shape characteristics. Performance was validated on in-silico, control, and CTC-bearing mouse datasets. ResultsThe CNN classifier achieved accuracy, precision, sensitivity, and specificity exceeding 98% on test data. Compared with our previously published threshold-based approach, the ML-integrated method increased the number of correctly identified CTCs and their flow direction while reducing false detections across validation datasets. ConclusionsThe ML-integrated approach significantly improves DiFC CTC enumeration, enabling robustness against artifacts in noisy conditions.

bioengineering↗

bioRxiv2022

Near-Infrared Diffuse In Vivo Flow Cytometry

SignificanceDiffuse in vivo Flow Cytometry (DiFC) is an emerging technique for enumerating rare fluorescently labeled circulating cells non-invasively in the bloodstream. Thus far we have reported red and blue-green versions of DiFC. Use of near-infrared (NIR) fluorescent light would in principle allow use of DiFC in deeper tissues and would be compatible with emerging NIR fluorescence molecular contrast agents. AimIn this work, we describe the design of a NIR-DiFC instrument and demonstrate its use in optical flow phantoms in vitro and in mice in vivo. ApproachWe developed an improved optical fiber probe design for efficient collection of fluorescence from individual circulating cells, and efficient rejection of instrument autofluorescence. We built a NIR-DiFC instrument. We tested this with NIR fluorescent microspheres and cell lines labeled with OTL38 fluorescence contrast agent in a flow phantom model. We also tested NIR-DiFC in nude mice injected intravenously with OTL38-labeled L1210A cells. ResultsNIR-DiFC allowed detection of CTCs in flow phantoms with mean signal to noise ratios (SNRs) of 19 to 32 dB. In mice, fluorescently-labeled CTCs were detectable with mean SNR of 26 dB. NIR-DiFC also exhibited orders significantly lower autofluorescence and false-alarm rates than blue-green DiFC. ConclusionsNIR-DiFC allows use of emerging NIR contrast agents. This work could pave the way for future use of NIR-DiFC in humans.

bioengineering↗

bioRxiv2022

Signal and Measurement Considerations for Human Translation of Diffuse in vivo Flow Cytometry

SignificanceDiffuse in vivo flow cytometry (DiFC) is an emerging technology for fluorescence detection of rare circulating cells directly in large deep-seated blood vessels in mice. Because DiFC uses highly scattered light, in principle it could be translated to human use. However, an open question is whether fluorescent signals from single cells would be detectable in human-scale anatomies. AimSuitable blood vessels in a human wrist or forearm are at a depth of approximately 2-4 mm. The aim of this work was to study the impact of DiFC instrument geometry and wavelength on the detected DiFC signal and on the maximum depth of detection of a moving cell. ApproachWe used Monte Carlo simulations to compute Jacobian (sensitivity) matrices for a range of source-detector separations and tissue optical properties over the visible and near infrared (NIR) spectrum. We performed experimental measurements with three available versions of DiFC (488 nm, 640 nm, and 780 nm), fluorescent microspheres, and tissue mimicking optical flow phantoms. We used both computational and experimental data to estimate the maximum depth of detection at each combination of settings. Results and ConclusionsFor the DiFC detection problem, our analysis showed that for deep-seated blood vessels, the maximum sensitivity was obtained with NIR light (780 nm) and 3 mm source-and-detector separation. These results suggest that - in combination with a suitable molecularly targeted fluorescent probes - circulating cells and nanosensors could in principle be detectable in circulation in humans.

bioengineering↗

bioRxiv2020

Fluorescence Labeling of Circulating Tumor Cells with Folate Receptor Targeted Molecular Probes for Diffuse In Vivo Flow Cytometry

PurposeWe recently developed a new instrument called diffuse in vivo flow cytometry (DiFC) for enumeration of rare fluorescently-labeled circulating tumor cells (CTCs) in small animals without drawing blood samples. Until now, we have used cell lines that express fluorescent proteins, or were pre-labeled with a fluorescent dye ex-vivo. In this work, we investigated the use of two folate receptor (FR)-targeted fluorescence molecular probes for in vivo labeling of FR+ CTCs for DiFC. MethodsWe used EC-17 and Cy5-PEG-FR fluorescent probes. We studied the affinity of these probes for L1210A and KB cancer cells, both of which over-express FR. We tested the labeling specificity in cells in culture in vitro, in whole blood, and in mice in vivo. We also studied detectability of labeled cells with DiFC. ResultsBoth EC-17 and Cy5-PEG-FR probes had high affinity for FR+ CTCs in cell culture in vitro. However, only EC-17 had sufficient specificity for CTCs in whole blood. EC-17 labeled CTCs were also readily detectable in circulation in mice with DiFC. ConclusionsThis work demonstrates the feasibility of labeling CTCs for DiFC with a cell surface receptor targeted probe, greatly expanding the utility of the method for pre-clinical animal models. Because DiFC uses diffuse light, this method could be also used to enumerate CTCs in larger animal models and potentially even in humans.

bioengineering↗

bioRxiv2019

Short-term circulating tumor cell dynamics in mouse xenograft models and implications for liquid biopsy.

MotivationCirculating tumor cells (CTCs) are widely studied using liquid biopsy methods that analyze single, fractionally-small peripheral blood (PB) samples. However, little is known about fluctuations in CTC numbers that occur over short timescales in vivo, and how these may affect accurate enumeration from blood samples. MethodsWe recently developed an instrument called diffuse in vivo flow cytometry (DiFC) that allows continuous, non-invasive counting of rare, green fluorescent protein expressing CTCs in large deeply-seated blood vessels in mice. Here, we used DiFC to study short-term changes in CTC numbers in multiple myeloma and Lewis lung carcinoma xenograft models. We analyzed 35- to 50-minute data sets, with intervals corresponding to approximately 1, 5, 10 and 20% of the PB volume, as well as changes over 24-hour periods. ResultsFor rare CTCs, the use of short DiFC intervals (corresponding to small PB samples) frequently resulted in no detections. For more abundant CTCs, CTC numbers frequently varied by an order of magnitude or more over the time-scales considered. This variability far exceeded that expected by Poisson statistics, and instead was consistent with rapidly changing mean numbers of CTCs in the PB. ConclusionsBecause of these natural temporal changes, accurately enumerating CTCs from fractionally small blood samples is inherently problematic. The problem is likely to be compounded for multicellular CTC clusters or specific CTC subtypes. However, we also show that enumeration can be improved by averaging multiple samples, analysis of larger volumes, or development of new methods for enumeration of CTCs directly in vivo.

bioengineering↗

bioRxiv2019

In Vivo Monitoring of Rare Circulating Tumor Cell and Cluster Dissemination in a Multiple Myeloma Xenograft Model

We recently developed Diffuse in vivo Flow Cytometry (DiFC), a new pre-clinical research tool for enumerating extremely rare fluorescently-labeled circulating cells directly in vivo. In this paper, we developed a green fluorescent protein (GFP) compatible version of DiFC, and used it to non-invasively monitor the circulating tumor cell (CTC) burden over time in a multiple myeloma disseminated xenograft model. We show that DiFC allowed counting of CTCs at estimated concentrations below 1 cell per mL in peripheral blood with a negligible false alarm rate. DiFC also revealed the presence of CTC clusters in circulation to our knowledge for the first time in this model, and allowed us to calculate their size, kinetics, and frequency of shedding. We anticipate that the unique capabilities of DiFC will have many applications in the study of hematogenous metastasis, and as a powerful complementary methodology to liquid biopsy assays.

bioengineering↗

bioRxiv2018

In Vivo Flow Cytometry of Extremely Rare Circulating Cells

Circulating tumor cells (CTCs) are of great interest in cancer research, but methods for their enumeration remain far from optimal. We developed a new small animal research tool called \"Diffuse in vivo Flow Cytometry\" (DiFC) for detecting extremely rare fluorescently-labeled circulating cells directly in the bloodstream. The technique exploits near-infrared diffuse photons to detect and count cells flowing in large superficial arteries and veins without drawing blood samples. DiFC uses custom-designed, dual fiber optic probes that are placed in contact with the skin surface approximately above a major vascular bundle. In combination with a novel signal processing, algorithm DiFC allows counting of individual cells moving in arterial or venous directions, as well as measurement of their speed and depth. We show that DiFC allows sampling of the entire circulating blood volume of a mouse in under 10 minutes, while maintaining a false alarm rate of 0.014 per minute. Hence, the unique capabilities of DiFC are highly suited to biological applications involving very rare cell types such as the study of hematogenic cancer metastasis.

bioengineering↗