Evidence map›Paper›PMID 34201654›Full record

ArticleTomography (Ann Arbor, Mich.)2021

Characterizing Errors in Pharmacokinetic Parameters from Analyzing Quantitative Abbreviated DCE-MRI Data in Breast Cancer.

Kalina P Slavkova, Julie C DiCarlo, Anum S Kazerouni, John Virostko, Anna G Sorace, Debra Patt, Boone Goodgame, Thomas E Yankeelov

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Tomography (Ann Arbor, Mich.), 2021. 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

8 authors.

Kalina P SlavkovaDepartment of Physics, The University of Texas at Austin, Austin, TX 78712, USA.ORCID 0000-0003-4311-2355
Julie C DiCarloLivestrong Cancer Institutes, The University of Texas at Austin, Austin, TX 78712, USA.ORCID 0000-0002-6965-3611
Anum S KazerouniDepartment of Radiology, The University of Washington, Seattle, WA 98195, USA.ORCID 0000-0002-4200-534X
John VirostkoLivestrong Cancer Institutes, The University of Texas at Austin, Austin, TX 78712, USA.
Anna G SoraceDepartment of Radiology, The University of Alabama at Birmingham, Birmingham, AL 35294, USA.ORCID 0000-0002-3640-3966
Debra PattTexas Oncology, Austin, TX 78731, USA.
Boone GoodgameSeton Hospital, Austin, TX 78712, USA.
Thomas E YankeelovLivestrong Cancer Institutes, The University of Texas at Austin, Austin, TX 78712, USA.ORCID 0000-0001-6201-3913

Funding

Quantitative MRI for Predicting Response of Breast Cancer to Neoadjuvant TherapyU01CA142565 · NCI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI KARCZMAR, GREGORY S., NANDA, RITA · 2010 to 2019
$4.5M
INTEGRATING OMICS AND QUANTITATIVE IMAGING DATA IN CO-CLINICAL TRIALS TO PREDICT TREATMENT RESPONSE IN TRIPLE NEGATIVE BREAST CANCERU24CA226110 · NCI · BAYLOR COLLEGE OF MEDICINE · PI LEWIS, MICHAEL T., RUBIN, DANIEL L · 2019 to 2023
$3.2M
Image Driven Multi-Scale Modeling to Predict Treatment Response in Breast CancerU01CA174706 · NCI · VANDERBILT UNIVERSITY · PI QUARANTA, VITO, YANKEELOV, THOMAS E · 2013 to 2018
$2.5M
Using label-free Raman microscopy to predict therapeutic resistance of TNBC cellsU01CA253540 · NCI · UNIVERSITY OF TEXAS AT AUSTIN · PI BROCK, AMY, YANKEELOV, THOMAS E · 2020 to 2024
$2.1M
Personalizing immunotherapy in HER2+ breast cancer through quantitative imagingR01CA240589 · NCI · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI SORACE, ANNA C · 2020 to 2023
$1.6M
NCI NIH HHS R01 CA240589NCI NIH HHS U01 CA142565NCI NIH HHS U01 CA174706NCI NIH HHS U01 CA253540NCI NIH HHS U24 CA226110
6 · The paper itself

Abstract

This study characterizes the error that results when performing quantitative analysis of abbreviated dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) data of the breast with the Standard Kety-Tofts (SKT) model and its Patlak variant. More specifically, we used simulations and patient data to determine the accuracy with which abbreviated time course data could reproduce the pharmacokinetic parameters,

Indexed as

Breast NeoplasmsContrast MediaFemaleHumansMagnetic Resonance ImagingContrast Mediaabbreviated breast MRIdynamic contrast-enhanced MRIKety–ToftsPatlakquantitative MRI

Identifiers

PMID34201654
PMCPMC8293327

What OpenQuestion holds

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Read underepoch 390

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.