Evidence map›Paper›PMID 32307271›Full record

ArticleAcademic radiology2021

Breast Cancer Conspicuity on Computed Versus Acquired High b-Value Diffusion-Weighted MRI.

Michaela R DelPriore, Debosmita Biswas, Daniel S Hippe, Mladen Zecevic, Sana Parsian, John R Scheel, Habib Rahbar, Savannah C Partridge

Open access · greenAbstract read
In one paragraph

Article in Academic radiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
2.2field-weighted citation impact, top 10% 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

16 citing papers in PubMed, 29 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Comparison of synthesized and acquired high b-value diffusion-weighted MRI for detection of prostate cancer.Cancer imaging : the official publication of the International Cancer Imaging Society · 2024
    Article
  5. Non-contrast Breast MR Imaging.Radiologic clinics of North America · 2024
    Review
  6. Article
  7. Update on DWI for Breast Cancer Diagnosis and Treatment Monitoring.AJR. American journal of roentgenology · 2024
    Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Observational
  14. Article
  15. Article
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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

8 authors at 1 institution in 1 country.

Michaela R DelPrioreDepartment of Radiology, University of Washington, Seattle, Washington.
Debosmita BiswasDepartment of Radiology, University of Washington, Seattle, Washington.
Daniel S HippeDepartment of Radiology, University of Washington, Seattle, Washington.
Mladen ZecevicDepartment of Radiology, University of Washington, Seattle, Washington.
Sana ParsianDepartment of Radiology, University of Washington, Seattle, Washington; Breast Imaging, Seattle Cancer Care Alliance, 1144 Eastlake Ave E, LG2-200, Seattle, WA 98109.
John R ScheelDepartment of Radiology, University of Washington, Seattle, Washington; Breast Imaging, Seattle Cancer Care Alliance, 1144 Eastlake Ave E, LG2-200, Seattle, WA 98109.
Habib RahbarDepartment of Radiology, University of Washington, Seattle, Washington; Breast Imaging, Seattle Cancer Care Alliance, 1144 Eastlake Ave E, LG2-200, Seattle, WA 98109.
Savannah C PartridgeDepartment of Radiology, University of Washington, Seattle, Washington; Breast Imaging, Seattle Cancer Care Alliance, 1144 Eastlake Ave E, LG2-200, Seattle, WA 98109. Electronic address: scp3@uw.edu.
University of Washington · US

Funding

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
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
MRI Characterization of Biological Risk of Ductal Carcinoma in SituR01CA203883 · NCI · UNIVERSITY OF WASHINGTON · PI RAHBAR, HABIBOLLAH · 2017 to 2021
$1.8M
NCI NIH HHS R01 CA207290NCI NIH HHS U01 CA225427
6 · The paper itself

Abstract

RATIONALE AND

objectivesOn unenhanced diffusion-weighted imaging (DWI), computing or synthesizing high b-value images from lower b-value acquisitions can enhance breast cancer visibility. This study aimed to evaluate relative lesion conspicuity on computed versus acquired diffusion-weighted images and investigate clinical characteristics influencing optimal b-values. MATERIALS AND

methodsWomen with newly diagnosed breast cancer were prospectively enrolled and underwent 3T breast MRI with DWI. Lesion contrast-to-noise ratio (CNR) was measured across a range of b-values (0-2500 s/mm

resultsThe study included 30 women (median age, 48 years); 28 with invasive carcinoma, 2 DCIS. Lesion CNR was higher on acquired versus computed images (p = 0.018), while lesion visibility by reader assessment was not different (p = 0.36). Optimal b-values selected by readers (mean, b = 1411 ± 383 s/mm

conclusionLesion CNR on computed high b-value images was slightly reduced versus acquired images, but our study suggests that this did not significantly impact lesion visibility. Computing high b-value images offers extra flexibility to adjust b-value during interpretation.

Indexed as

Breast NeoplasmsAgedBreastDiffusion Magnetic Resonance ImagingFemaleHumansMagnetic Resonance ImagingMiddle AgedRetrospective StudiesBreast cancerb-valueDiffusion-weighted imaging (DWI)Lesion conspicuityMagnetic resonance imaging (MRI)

Identifiers

PMID32307271
PMCPMC7572480
OpenAlexW3016956547

What OpenQuestion holds

Textmetadata
LicenceTDM
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.