Evidence map›Paper›PMID 34823506›Full record

ArticleBMC biotechnology2021

Computational modeling of PET tracer distribution in solid tumors integrating microvasculature.

Niloofar Fasaeiyan, M Soltani, Farshad Moradi Kashkooli, Erfan Taatizadeh, Arman Rahmim

Open access · goldAbstract read
In one paragraph

Article in BMC biotechnology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.4field-weighted citation impact, top 18% 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

5 citing papers in PubMed, 11 citations in OpenAlex.

  1. Review
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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 at 3 institutions in 2 countries.

Niloofar FasaeiyanDepartment of Mechanical Engineering, K. N. Toosi University of Technology, Tehran, Tehran Province, Iran.
M SoltaniDepartment of Mechanical Engineering, K. N. Toosi University of Technology, Tehran, Tehran Province, Iran. msoltani@uwaterloo.ca.
Farshad Moradi KashkooliDepartment of Mechanical Engineering, K. N. Toosi University of Technology, Tehran, Tehran Province, Iran.
Erfan TaatizadehDepartment of Mechanical Engineering, K. N. Toosi University of Technology, Tehran, Tehran Province, Iran.
Arman RahmimSchool of Biomedical Engineering, University of British Columbia, Vancouver, BC, Canada.
K.N.Toosi University of Technology · IRUniversity of British Columbia · CAPolytechnique Montréal · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWe present computational modeling of positron emission tomography radiotracer uptake with consideration of blood flow and interstitial fluid flow, performing spatiotemporally-coupled modeling of uptake and integrating the microvasculature. In our mathematical modeling, the uptake of fluorodeoxyglucose F-18 (FDG) was simulated based on the Convection-Diffusion-Reaction equation given its high accuracy and reliability in modeling of transport phenomena. In the proposed model, blood flow and interstitial flow are solved simultaneously to calculate interstitial pressure and velocity distribution inside cancer and normal tissues. As a result, the spatiotemporal distribution of the FDG tracer is calculated based on velocity and pressure distributions in both kinds of tissues.

resultsInterstitial pressure has maximum value in the tumor region compared to surrounding tissue. In addition, interstitial fluid velocity is extremely low in the entire computational domain indicating that convection can be neglected without effecting results noticeably. Furthermore, our results illustrate that the total concentration of FDG in the tumor region is an order of magnitude larger than in surrounding normal tissue, due to lack of functional lymphatic drainage system and also highly-permeable microvessels in tumors. The magnitude of the free tracer and metabolized (phosphorylated) radiotracer concentrations followed very different trends over the entire time period, regardless of tissue type (tumor vs. normal).

conclusionOur spatiotemporally-coupled modeling provides helpful tools towards improved understanding and quantification of in vivo preclinical and clinical studies.

Indexed as

NeoplasmsComputer SimulationHumansMicrovesselsPositron-Emission TomographyReproducibility of ResultsConvection–Diffusion-Reaction modelingFDG radiotracerMicrovascular networkPositron Emission Tomography (PET)Solid tumor

Identifiers

PMID34823506
PMCPMC8620574
OpenAlexW3217804184

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.