Evidence map›Paper›PMID 36494493›Full record

ReviewNature protocols2023

Micro-CT acquisition and image processing to track and characterize pulmonary nodules in mice.

May Zaw Thin, Christopher Moore, Thomas Snoeks, Tammy Kalber, Julian Downward, Axel Behrens

Abstract readReview
PubMed Publisher
In one paragraph

Review in Nature protocols, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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 registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed.

  1. Article
  2. Review
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  13. Frontiers in medicine · 2024
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

May Zaw Thin *Cancer Stem Cell Laboratory, Institute of Cancer Research, London, UK. may.zawthin@icr.ac.uk.ORCID 0000-0003-0036-2776
Christopher Moore *Oncogene Biology Laboratory, The Francis Crick Institute, London, UK.
Thomas SnoeksImaging Research Facility, The Francis Crick Institute, London, UK.
Tammy KalberCentre for Advanced Biomedical Imaging (CABI), University College London, London, UK.
Julian DownwardOncogene Biology Laboratory, The Francis Crick Institute, London, UK. Julian.Downward@crick.ac.uk.ORCID 0000-0002-2331-4729
Axel BehrensCancer Stem Cell Laboratory, Institute of Cancer Research, London, UK.ORCID 0000-0002-1557-1143

Funding

Cancer Research UKMedical Research CouncilWellcome Trust FC001039
6 · The paper itself

Abstract

X-ray computed tomography is a reliable technique for the detection and longitudinal monitoring of pulmonary nodules. In preclinical stages of diagnostic or therapeutic development, the miniaturized versions of the clinical computed tomography scanners are ideally suited for carrying out translationally-relevant research in conditions that closely mimic those found in the clinic. In this Protocol, we provide image acquisition parameters optimized for low radiation dose, high-resolution and high-throughput computed tomography imaging using three commercially available micro-computed tomography scanners, together with a detailed description of the image analysis tools required to identify a variety of lung tumor types, characterized by specific radiological features. For each animal, image acquisition takes 4-8 min, and data analysis typically requires 10-30 min. Researchers with basic training in animal handling, medical imaging and software analysis should be able to implement this protocol across a wide range of lung cancer models in mice for investigating the molecular mechanisms driving lung cancer development and the assessment of diagnostic and therapeutic agents.

Indexed as

Lung NeoplasmsAnimalsImage Processing, Computer-AssistedMiceSoftwareX-Ray Microtomography

Identifiers

What OpenQuestion holds

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Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.