Evidence map›Paper›PMID 35314635›Full record

ArticleTomography (Ann Arbor, Mich.)2022

Impact of Alternate

Savannah C Partridge, Jon Steingrimsson, David C Newitt, Jessica E Gibbs, Helga S Marques, Patrick J Bolan, Michael A Boss, Thomas L Chenevert, Mark A Rosen, Nola M Hylton

Registry-linked trialAbstract readMulticenter Study
In one paragraph

Article in Tomography (Ann Arbor, Mich.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT01564368 (Diffusion Weighted MR Imaging Biomarkers for Assessment of Breast Cancer Response to Neoadjuvant Treatment), which is not on this map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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.

NCT01564368 nacompletednot on this map

Diffusion Weighted MR Imaging Biomarkers for Assessment of Breast Cancer Response to Neoadjuvant Treatment: A Sub-study of the I-SPY 2 TRIAL (Investigation of Serial Studies to Predict Your Therapeutic Response With Imaging And MoLecular Analysis)

TypeinterventionalSponsorAmerican College of Radiology Imaging NetworkRan2012 to 2020Enrolled406ConditionsBreast CancerArmsdiffusion-weighted magnetic resonance imaging
3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Quantitative [Journal of nuclear medicine : official publication, Society of Nuclear Medicine · 2025
    Article
  6. Article
  7. 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

10 authors.

Savannah C PartridgeDepartment of Radiology, University of Washington, Seattle, WA 98195, USA.ORCID 0000-0001-6370-9111
Jon SteingrimssonDepartment of Biostatistics and Center for Statistical Sciences, Brown University, Providence, RI 02912, USA.
David C NewittDepartment of Radiology and Biomedical Imaging, University of California, San Francisco, CA 94143, USA.
Jessica E GibbsDepartment of Radiology and Biomedical Imaging, University of California, San Francisco, CA 94143, USA.ORCID 0000-0003-1785-0899
Helga S MarquesDepartment of Biostatistics and Center for Statistical Sciences, Brown University, Providence, RI 02912, USA.ORCID 0000-0003-2029-9241
Patrick J BolanCenter for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN 55455, USA.
Michael A BossCenter for Research and Innovation, American College of Radiology, Philadelphia, PA 19103, USA.ORCID 0000-0002-9492-767X
Thomas L ChenevertUniversity of Michigan, Ann Arbor, MI 48109, USA.
Mark A RosenUniversity of Pennsylvania, Philadelphia, PA 19104, USA.
Nola M HyltonDepartment of Radiology and Biomedical Imaging, University of California, San Francisco, CA 94143, USA.

Funding

ARRA - ADOPT New Technologies for RDC/CDMSU01CA080098 · NCI · AMERICAN COLLEGE OF RADIOLOGY · PI SCHNALL, MITCHELL D. · 1999 to 2011
$182.7M
Project-006U10CA180820 · NCI · ECOG-ACRIN MEDICAL RESEARCH FOUNDATION · PI Peter J ODwyer · 2014 to 2026
$167.6M
Statistics CoreU10CA180794 · NCI · DANA-FARBER CANCER INST · PI PAUL J CATALANO, CONSTANTINE A. GATSONIS · 2014 to 2026
$111.2M
BIOSTATISTICS DATA MANAGEMENT CENTER FOR ACROINU01CA079778 · NCI · BROWN UNIVERSITY · PI GATSONIS, CONSTANTINE A. · 1999 to 2011
$48.6M
TRD4 - Ultrahigh Field Engineering and SafetyP41EB027061 · NIBIB · UNIVERSITY OF MINNESOTA · PI Gregory John Metzger, KAMIL UGURBIL · 2019 to 2026
$11.7M
Elimination of Instrumental Bias for Quantitative Diffusion Imaging in Clinical Oncology TrialsR01CA190299 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI MALYARENKO, DARIYA I. · 2015 to 2025
$6.4M
Real-time In Vivo MRI Biomarkers for Breast Cancer Pre-Operative Treatment TrialsR01CA132870 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI HYLTON-WATSON, NOLA M., NEWITT, DAVID C · 2008 to 2019
$4.8M
Quantitative Imaging for Assessing Breast Cancer Response to TreatmentU01CA225427 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI HYLTON-WATSON, NOLA M. · 2018 to 2022
$3.2M
Multicenter Quantitative MRI Assessment of Breast Cancer Therapy ResponseR01CA248192 · NCI · WILLIAM BEAUMONT HOSPITAL RESEARCH INST · PI WEI HUANG, James H Holmes · 2021 to 2026
$2.8M
Validation and Standardization of the Apparent Diffusion Coefficient as a Quantitative Imaging Biomarker in Breast CancerR01CA207290 · NCI · UNIVERSITY OF WASHINGTON · PI PARTRIDGE, SAVANNAH CORRINA · 2017 to 2022
$2.2M
MR Diffusion Tensor Imaging for Detection and Characterization of Breast LesionsR01CA151326 · NCI · UNIVERSITY OF WASHINGTON · PI PARTRIDGE, SAVANNAH CORRINA · 2010 to 2014
$1.3M
NCI NIH HHS R01 CA132870NCI NIH HHS R01 CA151326NCI NIH HHS R01 CA190299NCI NIH HHS R01 CA207290NCI NIH HHS R01 CA248192NCI NIH HHS U01 CA079778NCI NIH HHS U01 CA080098NCI NIH HHS U01 CA225427NCI NIH HHS U10 CA180794NCI NIH HHS U10 CA180820NIBIB NIH HHS P41 EB027061
6 · The paper itself

Abstract

In diffusion-weighted MRI (DW-MRI), choice of b-value influences apparent diffusion coefficient (ADC) values by probing different aspects of the tissue microenvironment. As a secondary analysis of the multicenter ECOG-ACRIN A6698 trial, the purpose of this study was to investigate the impact of alternate b-value combinations on the performance and repeatability of tumor ADC as a predictive marker of breast cancer treatment response. The final analysis included 210 women who underwent standardized 4-b-value DW-MRI (b = 0/100/600/800 s/mm2) at multiple timepoints during neoadjuvant chemotherapy treatment and a subset (n = 71) who underwent test−retest scans. Centralized tumor ADC and perfusion fraction (fp) measures were performed using variable b-value combinations. Prediction of pathologic complete response (pCR) based on the mid-treatment/12-week percent change in each metric was estimated by area under the receiver operating characteristic curve (AUC). Repeatability was estimated by within-subject coefficient of variation (wCV). Results show that two-b-value ADC calculations provided non-inferior predictive value to four-b-value ADC calculations overall (AUCs = 0.60−0.61 versus AUC = 0.60) and for HR+/HER2− cancers where ADC was most predictive (AUCs = 0.75−0.78 versus AUC = 0.76), p < 0.05. Using two b-values (0/600 or 0/800 s/mm2) did not reduce ADC repeatability over the four-b-value calculation (wCVs = 4.9−5.2% versus 5.4%). The alternate metrics ADCfast (b ≤ 100 s/mm2), ADCslow (b ≥ 100 s/mm2), and fp did not improve predictive performance (AUCs = 0.54−0.60, p = 0.08−0.81), and ADCfast and fp demonstrated the lowest repeatability (wCVs = 6.71% and 12.4%, respectively). In conclusion, breast tumor ADC calculated using a simple two-b-value approach can provide comparable predictive value and repeatability to full four-b-value measurements as a marker of treatment response.

Indexed as

Breast NeoplasmsDiffusion Magnetic Resonance ImagingBenchmarkingFemaleHumansNeoadjuvant TherapyROC CurveTumor Microenvironmentapparent diffusion coefficient (ADC)breast cancerdiffusion-weighted MRI (DW-MRI)quantitative imaging biomarker alliance (QIBA)repeatabilityreproducibilitytreatment response

Identifiers

PMID35314635
PMCPMC8938828

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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.