ArticleTomography (Ann Arbor, Mich.)2025
Deep Learning-Based Tumor Segmentation of Murine Magnetic Resonance Images of Prostate Cancer Patient-Derived Xenografts.
Satvik Nayak, Henry Salkever, Ernesto Diaz, Avantika Sinha, Nikhil Deveshwar, Madeline Hess, Matthew Gibbons, Sule Sahin, Abhejit Rajagopal, Peder E Z Larson and 1 more
Abstract read
In one paragraphArticle in Tomography (Ann Arbor, Mich.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
2 · The registryThe trial behind it
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4 · The recordCorrections and comments
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5 · Who and what moneyAuthors and funding
11 authors.
Satvik NayakDepartment of Radiology and Biomedical Imaging, University of California-San Francisco, San Francisco, CA 94158, USA.ORCID 0009-0009-9139-1783 Henry SalkeverDepartment of Radiology and Biomedical Imaging, University of California-San Francisco, San Francisco, CA 94158, USA.
Ernesto DiazDepartment of Radiology and Biomedical Imaging, University of California-San Francisco, San Francisco, CA 94158, USA.ORCID 0000-0002-3716-7758 Avantika SinhaDepartment of Radiology and Biomedical Imaging, University of California-San Francisco, San Francisco, CA 94158, USA.ORCID 0000-0002-9349-6345 Nikhil DeveshwarDepartment of Radiology and Biomedical Imaging, University of California-San Francisco, San Francisco, CA 94158, USA.ORCID 0000-0002-5516-3769 Madeline HessDepartment of Radiology and Biomedical Imaging, University of California-San Francisco, San Francisco, CA 94158, USA.
Matthew GibbonsDepartment of Radiology and Biomedical Imaging, University of California-San Francisco, San Francisco, CA 94158, USA.ORCID 0000-0003-4108-6157 Sule SahinDepartment of Radiology and Biomedical Imaging, University of California-San Francisco, San Francisco, CA 94158, USA.ORCID 0000-0002-7006-4793 Abhejit RajagopalDepartment of Radiology and Biomedical Imaging, University of California-San Francisco, San Francisco, CA 94158, USA.
Peder E Z LarsonDepartment of Radiology and Biomedical Imaging, University of California-San Francisco, San Francisco, CA 94158, USA.ORCID 0000-0003-4183-3634 Renuka SriramDepartment of Radiology and Biomedical Imaging, University of California-San Francisco, San Francisco, CA 94158, USA.ORCID 0000-0003-3505-2479 Funding
TR&D3: Open-Source Tools for Processing Hyperpolarized MR DataP41EB013598 · NIBIB · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Daniel B Vigneron · 2011 to 2026
$19.9MPreclinical imaging characterization and resource development of PDX SCNC prostate cancer murine modelsU24CA253377 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI KURHANEWICZ, JOHN, PEEHL, DONNA M. · 2020 to 2024
$3.4MNCI NIH HHS U24 CA253377NCI NIH HHS U24CA253377NIBIB NIH HHS P41 EB013598NIBIB NIH HHS P41EB013598
6 · The paper itselfAbstract
BACKGROUND/
objectiveLongitudinal in vivo studies of murine xenograft models are widely utilized in oncology to study cancer biology and develop therapies. Magnetic resonance imaging (MRI) of these tumors is an invaluable tool for monitoring tumor growth and characterizing the tumors as well.
methodsIn this work, a pipeline for automating the segmentation of xenografts in mouse models was developed. T RESULTS AND
conclusionsThe slice classifier network achieved 90% accuracy in identifying slices containing tumors. Among the various segmentation architectures tested, the dense residual recurrent U-Net achieved the highest performance in kidney tumors. When evaluated across the kidneys, tibia, and liver, this architecture performed the best when trained on all data as compared to training on only data from a single site (and inferring on a multi-site tumor images), achieving a Dice score of 0.924 across the test set.
Indexed as
Deep LearningImage Processing, Computer-AssistedMagnetic Resonance ImagingProstatic NeoplasmsAlgorithmsAnimalsDisease Models, AnimalHeterograftsHumansKidneyLiverMaleMiceTibiadeep learningmagnetic resonance imagingpatient-derived xenograftsprostate cancertumor segmentation
Identifiers
PMID40137561
PMCPMC11946206
What OpenQuestion holds
Textmetadata
LicenceCC BY
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