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Mice MR Images (lungs and pulmonary metastases)

Authors: Edgar Lefevre; Emmanuel Bouilhol; Antoine Chauvière; Wilfried Souleyreau; Marie-Alix Derieppe; Aurélien J Trotier; Sylvain Miraux; +3 Authors

Mice MR Images (lungs and pulmonary metastases)

Abstract

55 mice were imaged after injection on a 7T Bruker BioSpec system equipped with a gradient coil of 660 mT/m maximum strength and 110 μs rise time. 27 mice with Crispr/Cas9 il34 KO gene and 28 controls. Animals were imaged every week: from day 6 to day 32 post-implantation for control mice and from day 8 till their condition deteriorated (up to day 141 at most) for il34 mice. Two additional healthy mice were scanned 3 times, two times without repositioning and one time after waking them up in order to evaluate the reproducibility of the lungs’ segmentations. The balanced Steady State Free Precession (bSSFP) sequence was chosen, as it has previously been shown that high tumor contrast can be obtained in the brain and in the liver (https://doi.org/10.1002/jmri.21449 ; https://doi.org/10.1002/jmri.22593 ; https://doi.org/10.1002/jmri.24688). Combined with the Self-Gating (SG) method, it enables to delete echoes affected by motion and consequently obtain abdominal images without motion artifact (https://doi.org/10.1002/jmri.24688). Corresponding masks were manually drawn around the lungs on every slice of 185 3D images; masks were manually drawn around the pulmonary metastases on every slice of 62 3D images containing metastases. Both tasks were performed by two different investigators.

Related Organizations
Keywords

Mice, Lungs, Metastases, MRI

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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