Evidence map›Paper›PMID 26843246›Full record

ArticleMedical physics2016

A novel perfused Bloch-McConnell simulator for analyzing the accuracy of dynamic hyperpolarized MRS.

Christopher M Walker, Yunyun Chen, Stephen Y Lai, James A Bankson

Erratum issuedAbstract read
In one paragraph

Article in Medical physics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.4field-weighted citation impact, top 21% 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

9 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
  2. The effect of transmit BMedical physics · 2021
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  4. Virtual clinical trials in medical imaging: a review.Journal of medical imaging (Bellingham, Wash.) · 2020
    Review
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

Christopher M WalkerDepartment of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030.
Yunyun ChenDepartment of Head and Neck Surgery, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030.
Stephen Y LaiDepartment of Head and Neck Surgery, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030.
James A BanksonDepartment of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030.
The University of Texas MD Anderson Cancer Center · US

Funding

Tumor Evolution and Metastasis ProgramP30CA016672 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Scott Kopetz · 1985 to 2026
$290.8M
Optimizing Radiosensitization in Anaplastic Thyroid Cancer with Metabolic ImagingR21CA178450 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI LAI, STEPHEN Y · 2014 to 2015
$383k
NCI NIH HHS P30 CA016672NCI NIH HHS P30-CA016672NCI NIH HHS R21 CA178450NCI NIH HHS R21-CA178450
6 · The paper itself

Abstract

purposeMagnetic resonance spectroscopy of hyperpolarized agents allows real-time detection of metabolism in vivo. However, the nonrenewable nature of these signals necessitates data acquisitions that differ significantly from conventional magnetic resonance imaging. Signal evolution is permanently altered by the data acquisition scheme, potentially leading to sequence parameter-dependent bias in quantification. The authors have developed a novel simulation environment to characterize the effects of sequence parameters on magnetic resonance spectroscopy-based chemical exchange measurements using hyperpolarized pyruvate.

methodsConventional Bloch-McConnell equations were coupled with a pharmacokinetic model for perfusion to allow realistic simulation of in vivo dynamic hyperpolarized signal evolution. In this study, simulations were conducted to explore effects of excitation angle and repetition time on the observed signal and subsequent parametric analysis. Both high and low apparent exchange rates were modeled under assumption of both perfused and closed systems. Bias due to sampling strategy bias was subsequently tested in vivo.

resultsSimulation of dynamic magnetic resonance spectroscopy studies using hyperpolarized pyruvate demonstrated that for closed systems, accurate measurement of the apparent exchange rate was possible over a wide range of sequence parameters. This was true for both high and low apparent exchange rates, although a low exchange rate was associated with larger errors when excitation angles were high. When effects of perfusion were included to account for pyruvate delivery, a more restricted range of settings led to accurate quantification of exchange rates. Perfusion alleviated some of the errors seen at high excitation angles for low exchange rates. Residuals from parametric analysis did not generally correlate with fit accuracy, implying that the quality of the analysis model was not a major driver of error. Animal studies acquired with sequence parameters that are predicted to impart bias showed a significant under estimation of exchange rates (P < 0.035) compared to parameter combinations that are not expected to bias measurements.

conclusionsThe authors' results suggest that great care must be taken when measuring dynamic processes by magnetic resonance spectroscopy of hyperpolarized substrates. When comparing apparent exchange rates, choice of sequence parameters will affect the results. Bias introduced by parameters of more advanced acquisition and reconstruction schemes will likely increase compared to the relatively simple dynamic spectroscopy methods tested herein. The modified Bloch-McConnell equations the authors describe will be crucial tools for characterizing and optimizing the performance of these more advanced techniques.

Indexed as

AnimalsCell Transformation, NeoplasticLactic AcidMagnetic Resonance SpectroscopyMiceModels, BiologicalPerfusionPyruvic AcidSignal-To-Noise RatioThyroid NeoplasmsLactic AcidPyruvic Acid

Identifiers

PMID26843246
PMCPMC4723412
OpenAlexW2297759636

What OpenQuestion holds

Textmetadata
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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.