Evidence map›Paper›PMID 27533303›Full record

ArticlePloS one2016

A Multimodal Imaging Approach for Longitudinal Evaluation of Bladder Tumor Development in an Orthotopic Murine Model.

Chantal Scheepbouwer, Sandra Meyer, Maroeska J Burggraaf, Jithin Jose, Carla F M Molthoff

Abstract read
In one paragraph

Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

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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

5 authors.

Chantal ScheepbouwerDepartment of Radiology & Nuclear Medicine, VU University Medical Center, Amsterdam, The Netherlands.ORCID http://orcid.org/0000-0003-4243-0095
Sandra MeyerFUJIFILM VisualSonics Inc., Amsterdam, The Netherlands.
Maroeska J BurggraafDepartment of Radiology & Nuclear Medicine, VU University Medical Center, Amsterdam, The Netherlands.
Jithin JoseFUJIFILM VisualSonics Inc., Amsterdam, The Netherlands.
Carla F M MolthoffDepartment of Radiology & Nuclear Medicine, VU University Medical Center, Amsterdam, The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Bladder cancer is the fourth most common malignancy amongst men in Western industrialized countries with an initial response rate of 70% for the non-muscle invasive type, and improving therapy efficacy is highly needed. For this, an appropriate, reliable animal model is essential to gain insight into mechanisms of tumor growth for use in response monitoring of (new) agents. Several animal models have been described in previous studies, but so far success has been hampered due to the absence of imaging methods to follow tumor growth non-invasively over time. Recent developments of multimodal imaging methods for use in animal research have substantially strengthened these options of in vivo visualization of tumor growth. In the present study, a multimodal imaging approach was addressed to investigate bladder tumor proliferation longitudinally. The complementary abilities of Bioluminescence, High Resolution Ultrasound and Photo-acoustic Imaging permit a better understanding of bladder tumor development. Hybrid imaging modalities allow the integration of individual strengths to enable sensitive and improved quantification and understanding of tumor biology, and ultimately, can aid in the discovery and development of new therapeutics.

Indexed as

AnimalsCell Line, TumorCell ProliferationDisease Models, AnimalFemaleLongitudinal StudiesMiceMice, Inbred C57BLMultimodal ImagingMycobacterium bovisNeoplasm TransplantationPhotoacoustic TechniquesUltrasonographyUrinary Bladder Neoplasms

Identifiers

PMID27533303
PMCPMC4988778

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Registered trials

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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.