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, Deborah J. Rhodes, Michael K. O'Connor, Celine M. Vachon

Research output: Contribution to journalArticle

4 Scopus citations

Abstract

Background: Background 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. Methods: Two 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. Results: Quantitative 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). Conclusion: Quantitative 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.

Original languageEnglish (US)
Article number46
JournalBreast Cancer Research
Volume20
Issue number1
DOIs
StatePublished - Jun 5 2018

Keywords

  • Breast cancer risk
  • Breast density
  • Mammography
  • Molecular breast imaging
  • Tc-99m sestamibi

ASJC Scopus subject areas

  • Oncology
  • Cancer Research

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