Evidence map›Paper›PMID 38108384›Full record

ArticleJournal of visualized experiments : JoVE2023

A Computational Modeling Approach to Investigate the Influence of Hyperthermia on the Tumor Microenvironment.

Anna Bottiglieri, Rahul A Sheth, Punit Prakash

Abstract readVideo-Audio Media
In one paragraph

Article in Journal of visualized experiments : JoVE, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

3 authors.

Anna BottiglieriDepartment of Electrical and Computer Engineering, Kansas State University; aabottiglieri@ksu.edu.
Rahul A ShethDepartment of Interventional Radiology, The University of Texas MD Anderson Cancer Center.
Punit PrakashDepartment of Electrical and Computer Engineering, Kansas State University.

Funding

An image-guided immunotherapy and hyperthermia delivery device to overcome barriers to tumor immunity for advanced hepatocellular carcinomaR37CA269622 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Rahul Anil Sheth · 2023 to 2026
$1.8M
NCI NIH HHS R37 CA269622
6 · The paper itself

Abstract

The biophysical properties of the tumor microenvironment differ substantially from normal tissues. A constellation of features, including decreased vascularity, lack of lymphatic drainage, and elevated interstitial pressure, diminishes the penetration of therapeutics into tumors. Local hyperthermia within the tumor can alter microenvironmental properties, such as interstitial fluid pressure, potentially leading to improvements in drug penetration. In this context, multi-physics computational models can provide insight into the interplay between the biophysical parameters within the tumor microenvironment and can guide the design and interpretation of experiments that test the bioeffects of local hyperthermia. This paper describes a step-by-step workflow for a computational model coupling partial differential equations describing electrical current distribution, bioheat transfer, and fluid dynamics. The main objective is to study the effects of hyperthermia delivered by a bipolar radiofrequency device on the interstitial fluid pressure within the tumor. The system of mathematical expressions linking electrical current distribution, bioheat transfer, and interstitial fluid pressure is presented, emphasizing the changes in the distribution of the interstitial fluid pressure that could be induced by the thermal intervention.

Indexed as

Hyperthermia, InducedNeoplasmsComputer SimulationHumansTumor Microenvironment

Identifiers

PMID38108384
PMCPMC12083881

What OpenQuestion holds

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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.