Evidence map›Paper›PMID 28286871›Full record

ArticleTomography (Ann Arbor, Mich.)2016

Semiautomated Workflow for Clinically Streamlined Glioma Parametric Response Mapping.

Lauren Keith, Brian D Ross, Craig J Galbán, Gary D Luker, Stefanie Galbán, Binsheng Zhao, Xiaotao Guo, Thomas L Chenevert, Benjamin A Hoff

Open access · goldAbstract read
In one paragraph

Article in Tomography (Ann Arbor, Mich.), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.6field-weighted citation impact, top 27% 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

3 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Article
  3. 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

9 authors at 3 institutions in 1 country.

Lauren KeithImbio, LLC, Minneapolis, Minnesota.
Brian D RossDepartment of Radiology, Center for Molecular Imaging, University of Michigan, Ann Arbor, Michigan.
Craig J GalbánDepartment of Radiology, Center for Molecular Imaging, University of Michigan, Ann Arbor, Michigan.
Gary D LukerDepartment of Radiology, Center for Molecular Imaging, University of Michigan, Ann Arbor, Michigan.
Stefanie GalbánDepartment of Radiology, Center for Molecular Imaging, University of Michigan, Ann Arbor, Michigan.
Binsheng ZhaoDepartment of Radiology, Columbia University College of Physicians and Surgeons, New York, New York.
Xiaotao GuoDepartment of Radiology, Columbia University College of Physicians and Surgeons, New York, New York.
Thomas L ChenevertDepartment of Radiology, Center for Molecular Imaging, University of Michigan, Ann Arbor, Michigan.
Benjamin A HoffDepartment of Radiology, Center for Molecular Imaging, University of Michigan, Ann Arbor, Michigan.
University of Michigan–Ann Arbor · USColumbia University · USImbio (United States) · US

Funding

TREATMENT VERIFICATION AND TREATMENT PLAN REFINEMENTP01CA059827 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI BALTER, JAMES M, LAWRENCE, THEODORE S · 1993 to 2018
$37.9M
QUANTITATION OF HUMAN BRAIN TUMOR THERAPY RESPONSE BY MRP01CA085878 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI CHENEVERT, THOMAS L · 2001 to 2017
$31.9M
Small Animal Imaging CoreP50CA093990 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI ROSS, BRIAN D. · 2002 to 2012
$19.0M
Presurgical Planning with Optimized Verbalized Speech Activation Studies inP01CA087634 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI BLAND, PEYTON H · 2002 to 2013
$14.8M
Imaging of Hematologic and Oncologic DisordersR35CA197701 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI ROSS, BRIAN D. · 2016 to 2022
$5.9M
Michigan Small Animal Imaging Resource (MSAIR)R24CA083099 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI ROSS, BRIAN D. · 1999 to 2006
$4.2M
Quantitative DW-MRI for Early Breast Cancer Treatment Response AssessmentU01CA166104 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI CHENEVERT, THOMAS L, GALBAN, CRAIG J · 2012 to 2019
$4.1M
NCI NIH HHS P01 CA059827NCI NIH HHS P01 CA085878NCI NIH HHS P01 CA087634NCI NIH HHS P50 CA093990NCI NIH HHS R24 CA083099NCI NIH HHS R35 CA197701NCI NIH HHS U01 CA166104
6 · The paper itself

Abstract

Management of glioblastoma multiforme remains a challenging problem despite recent advances in targeted therapies. Timely assessment of therapeutic agents is hindered by the lack of standard quantitative imaging protocols for determining targeted response. Clinical response assessment for brain tumors is determined by volumetric changes assessed at 10 weeks post-treatment initiation. Further, current clinical criteria fail to use advanced quantitative imaging approaches, such as diffusion and perfusion magnetic resonance imaging. Development of the parametric response mapping (PRM) applied to diffusion-weighted magnetic resonance imaging has provided a sensitive and early biomarker of successful cytotoxic therapy in brain tumors while maintaining a spatial context within the tumor. Although PRM provides an earlier readout than volumetry and sometimes greater sensitivity compared with traditional whole-tumor diffusion statistics, it is not routinely used for patient management; an automated and standardized software for performing the analysis and for the generation of a clinical report document is required for this. We present a semiautomated and seamless workflow for image coregistration, segmentation, and PRM classification of glioblastoma multiforme diffusion-weighted magnetic resonance imaging scans. The software solution can be integrated using local hardware or performed remotely in the cloud while providing connectivity to existing picture archive and communication systems. This is an important step toward implementing PRM analysis of solid tumors in routine clinical practice.

Indexed as

diffusiongliomaparametric response mapping

Identifiers

PMID28286871
PMCPMC5345939
OpenAlexW2587967952

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.