Evidence map›Paper›PMID 34310608›Full record

ArticlePLoS computational biology2021

Bridging cell-scale simulations and radiologic images to explain short-time intratumoral oxygen fluctuations.

Jessica L Kingsley, James R Costello, Natarajan Raghunand, Katarzyna A Rejniak

Abstract read
In one paragraph

Article in PLoS computational biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 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

4 authors.

Jessica L KingsleyDepartment of Integrated Mathematical Oncology, H. Lee Moffitt Cancer Center & Research Institute, Tampa, Florida, United States of America.
James R CostelloDepartment of Radiology, H. Lee Moffitt Cancer Center & Research Institute, Tampa, Florida, United States of America.
Natarajan RaghunandDepartment of Cancer Physiology, H. Lee Moffitt Cancer Center & Research Institute, Tampa, Florida, United States of America.ORCID 0000-0002-8893-7687
Katarzyna A RejniakDepartment of Integrated Mathematical Oncology, H. Lee Moffitt Cancer Center & Research Institute, Tampa, Florida, United States of America.ORCID 0000-0003-2093-2422

Funding

TRANSLATIONAL RESEARCHP30CA076292 · NCI · UNIVERSITY OF SOUTH FLORIDA · PI Christine O'Connell · 1998 to 2026
$93.5M
Physical Dynamics of Cancer Response to Chemotherapy in 3D MicroenvironmentsU01CA202229 · NCI · VANDERBILT UNIVERSITY · PI MARKOV, DMITRY, MCCAWLEY, LISA JOY · 2015 to 2019
$3.0M
NCI NIH HHS P30 CA076292NCI NIH HHS U01 CA202229
6 · The paper itself

Abstract

Radiologic images provide a way to monitor tumor development and its response to therapies in a longitudinal and minimally invasive fashion. However, they operate on a macroscopic scale (average value per voxel) and are not able to capture microscopic scale (cell-level) phenomena. Nevertheless, to examine the causes of frequent fast fluctuations in tissue oxygenation, models simulating individual cells' behavior are needed. Here, we provide a link between the average data values recorded for radiologic images and the cellular and vascular architecture of the corresponding tissues. Using hybrid agent-based modeling, we generate a set of tissue morphologies capable of reproducing oxygenation levels observed in radiologic images. We then use these in silico tissues to investigate whether oxygen fluctuations can be explained by changes in vascular oxygen supply or by modulations in cellular oxygen absorption. Our studies show that intravascular changes in oxygen supply reproduce the observed fluctuations in tissue oxygenation in all considered regions of interest. However, larger-magnitude fluctuations cannot be recreated by modifications in cellular absorption of oxygen in a biologically feasible manner. Additionally, we develop a procedure to identify plausible tissue morphologies for a given temporal series of average data from radiology images. In future applications, this approach can be used to generate a set of tissues comparable with radiology images and to simulate tumor responses to various anti-cancer treatments at the tissue-scale level.

Indexed as

Models, BiologicalCell HypoxiaComputational BiologyComputer SimulationHumansMathematical ConceptsNeoplasmsOxygenRadiographySystems AnalysisTumor HypoxiaTumor MicroenvironmentOxygen

Identifiers

PMID34310608
PMCPMC8341701

What OpenQuestion holds

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LicenceCC BY
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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.