Evidence map›Paper›PMID 24342178›Full record

ArticleMicrovascular research2014

A bioimage informatics based reconstruction of breast tumor microvasculature with computational blood flow predictions.

Spyros K Stamatelos, Eugene Kim, Arvind P Pathak, Aleksander S Popel

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Microvascular research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.

0numbers the graph read from it
0cells of the map it votes in
38citing 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

38 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.

Spyros K StamatelosDepartment of Biomedical Engineering, The Johns Hopkins University, School of Medicine, USA. Electronic address: spyros@jhu.edu.
Eugene KimDepartment of Biomedical Engineering, The Johns Hopkins University, School of Medicine, USA; Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University, School of Medicine, USA.
Arvind P PathakRussell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University, School of Medicine, USA; Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University, School of Medicine, USA.
Aleksander S PopelDepartment of Biomedical Engineering, The Johns Hopkins University, School of Medicine, USA; Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University, School of Medicine, USA.

Funding

Predictive experiment-based multiscale models of the tumor immune microenvironment and immunotherapy in breast cancerR01CA138264 · NCI · JOHNS HOPKINS UNIVERSITY · PI POPEL, ALEKSANDER S. · 2009 to 2023
$8.1M
NCI NIH HHS R01 CA138264
6 · The paper itself

Abstract

Induction of tumor angiogenesis is among the hallmarks of cancer and a driver of metastatic cascade initiation. Recent advances in high-resolution imaging enable highly detailed three-dimensional geometrical representation of the whole-tumor microvascular architecture. This enormous increase in complexity of image-based data necessitates the application of informatics methods for the analysis, mining and reconstruction of these spatial graph data structures. We present a novel methodology that combines ex-vivo high-resolution micro-computed tomography imaging data with a bioimage informatics algorithm to track and reconstruct the whole-tumor vasculature of a human breast cancer model. The reconstructed tumor vascular network is used as an input of a computational model that estimates blood flow in each segment of the tumor microvascular network. This formulation involves a well-established biophysical model and an optimization algorithm that ensures mass balance and detailed monitoring of all the vessels that feed and drain blood from the tumor microvascular network. Perfusion maps for the whole-tumor microvascular network are computed. Morphological and hemodynamic indices from different regions are compared to infer their role in overall tumor perfusion.

Indexed as

MicrovesselsNeovascularization, PathologicAlgorithmsAngiogenesis InhibitorsAnimalsAntineoplastic AgentsBreast NeoplasmsCell Line, TumorComputational BiologyFemaleHemodynamicsHumansImaging, Three-DimensionalMiceMice, NudeNeoplasm TransplantationAngiogenesis InhibitorsAntineoplastic AgentsAdjacency matrixa symmetric matrix consisting of ones and zeros indicating whether or not 2 nodes are connected with a segmentBFSbreadth-first search traversal algorithm (systematic visiting of nodes and segments of the graph)Ddata structure where each element is served based on a predefined prioritydepth-first search traversal algorithm (systematic visiting of nodes and segments of the graph)DFSflow rateflow-weighted mean path lengthGhydraulic conductanceinterquartile range (measure of data dispersion)IQRLL(D)mass of tumor tissuemaximum extravascular diffusion distance of oxygenMinimum heapMPLm(tissue)MTTNPpressurePriority queueQRsegment diametersegment lengthtotal mean transit timetotal number of segmentstree-based data structure where the parent nodes have always an identity (key) smaller than their children nodesvascular length density

Identifiers

PMID24342178
PMCPMC3977934

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.