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A Permanent Window for Investigating Cancer Metastasis to the Lung

  • Lucia Borriello
  • , Brian Traub
  • , Anouchka Coste
  • , Maja H. Oktay
  • , David Entenberg
  • Montefiore Health System
  • Albert Einstein College of Medicine

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

Abstract

Metastasis, accounting for ~90% of cancer-related mortality, involves the systemic spread of cancer cells from primary tumors to secondary sites such as the bone, brain, and lung. Although extensively studied, the mechanistic details of this process remain poorly understood. While common imaging modalities, including computed tomography (CT), positron emission tomography (PET), and magnetic resonance imaging (MRI), offer varying degrees of gross visualization, each lacks the temporal and spatial resolution necessary to detect the dynamics of individual tumor cells. To address this, numerous techniques have been described for intravital imaging of common metastatic sites. Of these sites, the lung has proven especially challenging to access for intravital imaging owing to its delicacy and critical role in sustaining life. Although several approaches have previously been described for single-cell intravital imaging of the intact lung, all involve highly invasive and terminal procedures, limiting the maximum possible imaging duration to 6-12 h. Described here is an improved technique for the permanent implantation of a minimally invasive thoracic optical Window for High-Resolution Imaging of the Lung (WHRIL). Combined with an adapted approach to microcartography, the innovative optical window facilitates serial intravital imaging of the intact lung at single-cell resolution across multiple imaging sessions and spanning multiple weeks. Given the unprecedented duration of time over which imaging data can be gathered, the WHRIL can facilitate the accelerated discovery of the dynamic mechanisms underlying metastatic progression and numerous additional biologic processes within the lung.

Original languageEnglish
Article numbere62761
JournalJournal of Visualized Experiments
Volume2021
Issue number173
DOIs
StatePublished - Jul 1 2021

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Humans
  • Lung Neoplasms/diagnostic imaging
  • Lung/diagnostic imaging
  • Magnetic Resonance Imaging
  • Neoplasms
  • Positron-Emission Tomography
  • Tomography, X-Ray Computed

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