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Motion model ultrasound localization microscopy for preclinical and clinical multiparametric tumor characterization

Author

Listed:
  • Tatjana Opacic

    (University Clinic Aachen, RWTH Aachen University, CMBS)

  • Stefanie Dencks

    (Ruhr University Bochum)

  • Benjamin Theek

    (University Clinic Aachen, RWTH Aachen University, CMBS)

  • Marion Piepenbrock

    (Ruhr University Bochum)

  • Dimitri Ackermann

    (Ruhr University Bochum)

  • Anne Rix

    (University Clinic Aachen, RWTH Aachen University, CMBS)

  • Twan Lammers

    (University Clinic Aachen, RWTH Aachen University, CMBS)

  • Elmar Stickeler

    (University Clinic Aachen, RWTH Aachen University)

  • Stefan Delorme

    (German Cancer Research Center)

  • Georg Schmitz

    (Ruhr University Bochum)

  • Fabian Kiessling

    (University Clinic Aachen, RWTH Aachen University, CMBS)

Abstract

Super-resolution imaging methods promote tissue characterization beyond the spatial resolution limits of the devices and bridge the gap between histopathological analysis and non-invasive imaging. Here, we introduce motion model ultrasound localization microscopy (mULM) as an easily applicable and robust new tool to morphologically and functionally characterize fine vascular networks in tumors at super-resolution. In tumor-bearing mice and for the first time in patients, we demonstrate that within less than 1 min scan time mULM can be realized using conventional preclinical and clinical ultrasound devices. In this context, next to highly detailed images of tumor microvascularization and the reliable quantification of relative blood volume and perfusion, mULM provides multiple new functional and morphological parameters that discriminate tumors with different vascular phenotypes. Furthermore, our initial patient data indicate that mULM can be applied in a clinical ultrasound setting opening avenues for the multiparametric characterization of tumors and the assessment of therapy response.

Suggested Citation

  • Tatjana Opacic & Stefanie Dencks & Benjamin Theek & Marion Piepenbrock & Dimitri Ackermann & Anne Rix & Twan Lammers & Elmar Stickeler & Stefan Delorme & Georg Schmitz & Fabian Kiessling, 2018. "Motion model ultrasound localization microscopy for preclinical and clinical multiparametric tumor characterization," Nature Communications, Nature, vol. 9(1), pages 1-13, December.
  • Handle: RePEc:nat:natcom:v:9:y:2018:i:1:d:10.1038_s41467-018-03973-8
    DOI: 10.1038/s41467-018-03973-8
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    Cited by:

    1. Zeng Zhang & Misun Hwang & Todd J. Kilbaugh & Anush Sridharan & Joseph Katz, 2022. "Cerebral microcirculation mapped by echo particle tracking velocimetry quantifies the intracranial pressure and detects ischemia," Nature Communications, Nature, vol. 13(1), pages 1-15, December.

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