Evidence map›Paper›PMID 28042590›Full record

ArticleJournal of medical imaging (Bellingham, Wash.)2016

Breast density estimation from high spectral and spatial resolution MRI.

Hui Li, William A Weiss, Milica Medved, Hiroyuki Abe, Gillian M Newstead, Gregory S Karczmar, Maryellen L Giger

Abstract read
In one paragraph

Article in Journal of medical imaging (Bellingham, Wash.), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the 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.

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

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. 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

7 authors.

Hui LiUniversity of Chicago , Department of Radiology, 5841 South Maryland Avenue, MC 2026, Chicago, Illinois 60637, United States.
William A WeissUniversity of Chicago , Department of Radiology, 5841 South Maryland Avenue, MC 2026, Chicago, Illinois 60637, United States.
Milica MedvedUniversity of Chicago , Department of Radiology, 5841 South Maryland Avenue, MC 2026, Chicago, Illinois 60637, United States.
Hiroyuki AbeUniversity of Chicago , Department of Radiology, 5841 South Maryland Avenue, MC 2026, Chicago, Illinois 60637, United States.
Gillian M NewsteadUniversity of Chicago , Department of Radiology, 5841 South Maryland Avenue, MC 2026, Chicago, Illinois 60637, United States.
Gregory S KarczmarUniversity of Chicago , Department of Radiology, 5841 South Maryland Avenue, MC 2026, Chicago, Illinois 60637, United States.
Maryellen L GigerUniversity of Chicago , Department of Radiology, 5841 South Maryland Avenue, MC 2026, Chicago, Illinois 60637, United States.

Funding

VIRAL ONCOLOGY CORE FACILITYP30CA014599 · NCI · UNIVERSITY OF CHICAGO · PI MARK W. LINGEN · 1985 to 2026
$122.1M
Quantitative Image Analysis for Assessing Response to Breast Cancer TherapyU01CA195564 · NCI · UNIVERSITY OF CHICAGO · PI GIGER, MARYELLEN L. · 2015 to 2019
$2.5M
Assessment of Breast Cancer Risk with High Spectral and Spatial Resolution MRIR01CA167785 · NCI · UNIVERSITY OF CHICAGO · PI KARCZMAR, GREGORY S., NEWSTEAD, GILLIAN · 2013 to 2017
$2.4M
NCI NIH HHS P30 CA014599NCI NIH HHS R01 CA167785NCI NIH HHS U01 CA195564
6 · The paper itself

Abstract

A three-dimensional breast density estimation method is presented for high spectral and spatial resolution (HiSS) MR imaging. Twenty-two patients were recruited (under an Institutional Review Board--approved Health Insurance Portability and Accountability Act-compliant protocol) for high-risk breast cancer screening. Each patient received standard-of-care clinical digital x-ray mammograms and MR scans, as well as HiSS scans. The algorithm for breast density estimation includes breast mask generating, breast skin removal, and breast percentage density calculation. The inter- and intra-user variabilities of the HiSS-based density estimation were determined using correlation analysis and limits of agreement. Correlation analysis was also performed between the HiSS-based density estimation and radiologists' breast imaging-reporting and data system (BI-RADS) density ratings. A correlation coefficient of 0.91 ([Formula: see text]) was obtained between left and right breast density estimations. An interclass correlation coefficient of 0.99 ([Formula: see text]) indicated high reliability for the inter-user variability of the HiSS-based breast density estimations. A moderate correlation coefficient of 0.55 ([Formula: see text]) was observed between HiSS-based breast density estimations and radiologists' BI-RADS. In summary, an objective density estimation method using HiSS spectral data from breast MRI was developed. The high reproducibility with low inter- and low intra-user variabilities shown in this preliminary study suggest that such a HiSS-based density metric may be potentially beneficial in programs requiring breast density such as in breast cancer risk assessment and monitoring effects of therapy.

Indexed as

breast cancer screening and diagnosisbreast density measurementecho planar spectroscopic imaginghigh spatial and spectral resolution MRISENSE acceleration

Identifiers

PMID28042590
PMCPMC5193119

What OpenQuestion holds

Textmetadata
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.