Ultra-sensitive and multiplexed tracking of single cells using whole-body PET/CT
Data files
May 13, 2024 version files 2.77 GB
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Listmode_invivo_IC.zip
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PETCT_DICOM_IC_NudeMouse1.zip
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PETCT_DICOM_IC_NudeMouse2.zip
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PETCT_DICOM_IC_NudeMouse3.zip
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PETCT_DICOM_IC_NudeMouse4.zip
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PETCT_DICOM_IC_NudeMouse5.zip
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PETCT_DICOM_IC_NudeMouse6.zip
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PETCT_DICOM_IC_Time0.zip
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PETCT_DICOM_IC_Time30.zip
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PETCT_DICOM_IC_Time60.zip
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README.md
Abstract
In vivo molecular imaging tools are crucially important for elucidating how cells move through complex biological systems, however, achieving single-cell sensitivity over the entire body remains challenging. Here, we report a highly sensitive and multiplexed approach for tracking upwards of 20 single cells simultaneously in the same subject using positron emission tomography (PET). The method relies on a statistical tracking algorithm (PEPT-EM) to achieve a sensitivity of 4 Bq/cell, and a streamlined workflow to reliably label single cells with over 50 Bq/cell of 18F-fluorodeoxyglucose (FDG). To demonstrate the potential of the method, we tracked the fate of over 70 melanoma cells after intracardiac injection and found they primarily arrested in the small capillaries of the pulmonary, musculoskeletal, and digestive organ systems. This study bolsters the evolving potential of PET in offering unmatched insights into the earliest phases of cell trafficking in physiological and pathological processes and in cell-based therapies.
README: Ultra-sensitive and multiplexed tracking of single cells using whole-body PET/CT
Access this dataset on Dryad: https://doi.org/10.5061/dryad.3bk3j9kt4
Data Description
This dataset includes PET/CT reconstructed images and raw outputs from imaging FDG-labeled single cells in vivo. We have provided PET/CT data from six Foxn1nu mice, each successfully administered with FDG-labeled single cells via intracardiac injection. Additionally, the dataset features longitudinal PET/CT observations of these single cells at 0, 30, and 60 minutes post-injection.
The PET/CT data are available in two formats: DICOM files (191 files for PET and 600 files for CT in each set) and a PET binary list-mode (.lmf) file. DICOM files can be visualized using open-source software such as AMIDE or 3D Slicer. The binary list-mode file can be accessed using our in-house tool, available in the code section.
Code/Software
We have provided MATLAB codes for 1) importing the binary list-mode files into the lines of response data, and 2) running Positron Emission Particle Tracking Expectation Maximization (PEPT-EM) to track FDG-labeled single cells following intravenous injection.