Evidence map›Paper›PMID 29871661›Full record

ArticleBreast cancer research : BCR2018

Quantitative background parenchymal uptake on molecular breast imaging and breast cancer risk: a case-control study.

Carrie B Hruska, Jennifer R Geske, Tiffinee N Swanson, Alyssa N Mammel, David S Lake, Armando Manduca, Amy Lynn Conners, Dana H Whaley, Christopher G Scott, Rickey E Carter and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Breast cancer research : BCR, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Trial
  2. Monte Carlo-derivedMedical physics · 2023
    Article
  3. Monte Carlo-derivedMedical physics · 2023
    Article
  4. Advances and Future Directions in Molecular Breast Imaging.Journal of nuclear medicine : official publication, Society of Nuclear Medicine · 2022
    Review
  5. Article
  6. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

13 authors.

Carrie B HruskaDepartment of Physiology and Biomedical Engineering, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA. hruska.carrie@mayo.edu.
Jennifer R GeskeDepartment of Health Sciences Research, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA.
Tiffinee N SwansonDepartment of Physiology and Biomedical Engineering, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA.
Alyssa N MammelDepartment of Physiology and Biomedical Engineering, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA.
David S LakeDepartment of Physiology and Biomedical Engineering, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA.
Armando ManducaDepartment of Physiology and Biomedical Engineering, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA.
Amy Lynn ConnersDepartment of Physiology and Biomedical Engineering, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA.
Dana H WhaleyDepartment of Physiology and Biomedical Engineering, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA.
Christopher G ScottDepartment of Health Sciences Research, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA.
Rickey E CarterDepartment of Health Sciences Research, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA.
Deborah J RhodesDepartment Medicine, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA.
Michael K O'ConnorDepartment of Physiology and Biomedical Engineering, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA.
Celine M VachonDepartment of Health Sciences Research, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA.

Funding

Mayo Clinic Center for Translational Science ActivitiesUL1TR000135 · NCATS · MAYO CLINIC ROCHESTER · PI KHOSLA, SUNDEEP · 2012 to 2015
$41.2M
Background parenchymal uptake (BPU) on molecular breast imaging as a novel breast cancer risk factorR21CA197752 · NCI · MAYO CLINIC ROCHESTER · PI HRUSKA, CARRIE B · 2015 to 2016
$380k
NCATS NIH HHS UL1 TR000135NCI NIH HHS R21 CA197752
6 · The paper itself

Abstract

backgroundBackground parenchymal uptake (BPU), which refers to the level of Tc-99m sestamibi uptake within normal fibroglandular tissue on molecular breast imaging (MBI), has been identified as a breast cancer risk factor, independent of mammographic density. Prior analyses have used subjective categories to describe BPU. We evaluate a new quantitative method for assessing BPU by testing its reproducibility, comparing quantitative results with previously established subjective BPU categories, and determining the association of quantitative BPU with breast cancer risk.

methodsTwo nonradiologist operators independently performed region-of-interest analysis on MBI images viewed in conjunction with corresponding digital mammograms. Quantitative BPU was defined as a unitless ratio of the average pixel intensity (counts/pixel) within the fibroglandular tissue versus the average pixel intensity in fat. Operator agreement and the correlation of quantitative BPU measures with subjective BPU categories assessed by expert radiologists were determined. Percent density on mammograms was estimated using Cumulus. The association of quantitative BPU with breast cancer (per one unit BPU) was examined within an established case-control study of 62 incident breast cancer cases and 177 matched controls.

resultsQuantitative BPU ranged from 0.4 to 3.2 across all subjects and was on average higher in cases compared to controls (1.4 versus 1.2, p < 0.007 for both operators). Quantitative BPU was strongly correlated with subjective BPU categories (Spearman's r = 0.59 to 0.69, p < 0.0001, for each paired combination of two operators and two radiologists). Interoperator and intraoperator agreement in the quantitative BPU measure, assessed by intraclass correlation, was 0.92 and 0.98, respectively. Quantitative BPU measures showed either no correlation or weak negative correlation with mammographic percent density. In a model adjusted for body mass index and percent density, higher quantitative BPU was associated with increased risk of breast cancer for both operators (OR = 4.0, 95% confidence interval (CI) 1.6-10.1, and 2.4, 95% CI 1.2-4.7).

conclusionQuantitative measurement of BPU, defined as the ratio of average counts in fibroglandular tissue relative to that in fat, can be reliably performed by nonradiologist operators with a simple region-of-interest analysis tool. Similar to results obtained with subjective BPU categories, quantitative BPU is a functional imaging biomarker of breast cancer risk, independent of mammographic density and hormonal factors.

Indexed as

Molecular ImagingAdultAgedAged, 80 and overBreastBreast DensityBreast NeoplasmsCase-Control StudiesFemaleHumansMammographyMiddle AgedParenchymal TissueRisk FactorsBreast cancer riskBreast densityMammographyMolecular breast imagingTc-99m sestamibi

Identifiers

PMID29871661
PMCPMC5989426

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.