Evidence map›Paper›PMID 30753240›Full record

ArticlePloS one2019

Cardio-Respiratory synchronized bSSFP MRI for high throughput in vivo lung tumour quantification.

Ana L Gomes, Paul Kinchesh, Stuart Gilchrist, Philip D Allen, Luiza Madia Lourenço, Anderson J Ryan, Sean C Smart

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.2field-weighted citation impact, top 21% of its field
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

7 citing papers in PubMed, 8 citations in OpenAlex.

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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

7 authors at 1 institution in 1 country.

Ana L GomesCancer Research UK and Medical Research Council Oxford Institute for Radiation Oncology, Department of Oncology, University of Oxford, Oxford, United Kingdom.ORCID 0000-0002-4796-6537
Paul KincheshCancer Research UK and Medical Research Council Oxford Institute for Radiation Oncology, Department of Oncology, University of Oxford, Oxford, United Kingdom.
Stuart GilchristCancer Research UK and Medical Research Council Oxford Institute for Radiation Oncology, Department of Oncology, University of Oxford, Oxford, United Kingdom.
Philip D AllenCancer Research UK and Medical Research Council Oxford Institute for Radiation Oncology, Department of Oncology, University of Oxford, Oxford, United Kingdom.
Luiza Madia LourençoCancer Research UK and Medical Research Council Oxford Institute for Radiation Oncology, Department of Oncology, University of Oxford, Oxford, United Kingdom.
Anderson J RyanCancer Research UK and Medical Research Council Oxford Institute for Radiation Oncology, Department of Oncology, University of Oxford, Oxford, United Kingdom.
Sean C SmartCancer Research UK and Medical Research Council Oxford Institute for Radiation Oncology, Department of Oncology, University of Oxford, Oxford, United Kingdom.
Cancer Research UK · GB

Funding

Cancer Research UK C2522/A10339Cancer Research UK C5255/A12678Medical Research Council MC_PC_12006Medical Research Council MC_UU_00001/6
6 · The paper itself

Abstract

The identification and measurement of tumours is a key requirement in the study of tumour development in mouse models of human cancer. Disease burden in autochthonous tumours, such as those arising in the lung, can be seen with non-invasive imaging, but cannot be accurately measured using standard tools such as callipers. Lung imaging is further complicated in the mouse due to instabilities arising from the rapid but cyclic cardio-respiratory motions, and the desire to use free-breathing animals. Female A/JOlaHsd mice were either injected (i.p.) with PBS 0.1ml/10g body weight (n = 6), or 10% urethane/PBS 0.1ml/10g body weight (n = 12) to induce autochthonous lung tumours. Cardio-respiratory synchronised bSSFP MRI, at 200 μm isotropic resolution was performed at 8, 13 and 18 weeks post induction. Images from the same mouse at different time points were aligned using threshold-based segmented masks of the lungs (ITK-SNAP and MATLAB) and tumour volumes were determined via threshold-based segmentation (ITK-SNAP).Scan times were routinely below 10 minutes and tumours were readily identifiable. Image registration allowed serial measurement of tumour volumes as small as 0.056 mm3. Repetitive imaging did not lead to mouse welfare issues. We have developed a motion desensitised scan that enables high sensitivity MRI to be performed with high throughput capability of greater than 4 mice/hour. Image segmentation and registration allows serial measurement of individual, small tumours. This allows fast and highly efficient volumetric lung tumour monitoring in cohorts of 30 mice per imaging time point. As a result, adaptive trial study designs can be achieved, optimizing experimental and welfare outcomes.

Indexed as

LungLung NeoplasmsMagnetic Resonance ImagingMotionNeoplasms, ExperimentalTumor BurdenAnimalsFemaleMice

Identifiers

PMID30753240
PMCPMC6372180
OpenAlexW2911875416

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.