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

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 ca...

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Autores principales: Hruska, Carrie B., Geske, Jennifer R., Swanson, Tiffinee N., Mammel, Alyssa N., Lake, David S., Manduca, Armando, Conners, Amy Lynn, Whaley, Dana H., Scott, Christopher G., Carter, Rickey E., Rhodes, Deborah J., O’Connor, Michael K., Vachon, Celine M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5989426/
https://www.ncbi.nlm.nih.gov/pubmed/29871661
http://dx.doi.org/10.1186/s13058-018-0973-3
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author Hruska, Carrie B.
Geske, Jennifer R.
Swanson, Tiffinee N.
Mammel, Alyssa N.
Lake, David S.
Manduca, Armando
Conners, Amy Lynn
Whaley, Dana H.
Scott, Christopher G.
Carter, Rickey E.
Rhodes, Deborah J.
O’Connor, Michael K.
Vachon, Celine M.
author_facet Hruska, Carrie B.
Geske, Jennifer R.
Swanson, Tiffinee N.
Mammel, Alyssa N.
Lake, David S.
Manduca, Armando
Conners, Amy Lynn
Whaley, Dana H.
Scott, Christopher G.
Carter, Rickey E.
Rhodes, Deborah J.
O’Connor, Michael K.
Vachon, Celine M.
author_sort Hruska, Carrie B.
collection PubMed
description 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13058-018-0973-3) contains supplementary material, which is available to authorized users.
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spelling pubmed-59894262018-06-20 Quantitative background parenchymal uptake on molecular breast imaging and breast cancer risk: a case-control study Hruska, Carrie B. Geske, Jennifer R. Swanson, Tiffinee N. Mammel, Alyssa N. Lake, David S. Manduca, Armando Conners, Amy Lynn Whaley, Dana H. Scott, Christopher G. Carter, Rickey E. Rhodes, Deborah J. O’Connor, Michael K. Vachon, Celine M. Breast Cancer Res Research Article 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13058-018-0973-3) contains supplementary material, which is available to authorized users. BioMed Central 2018-06-05 2018 /pmc/articles/PMC5989426/ /pubmed/29871661 http://dx.doi.org/10.1186/s13058-018-0973-3 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Hruska, Carrie B.
Geske, Jennifer R.
Swanson, Tiffinee N.
Mammel, Alyssa N.
Lake, David S.
Manduca, Armando
Conners, Amy Lynn
Whaley, Dana H.
Scott, Christopher G.
Carter, Rickey E.
Rhodes, Deborah J.
O’Connor, Michael K.
Vachon, Celine M.
Quantitative background parenchymal uptake on molecular breast imaging and breast cancer risk: a case-control study
title Quantitative background parenchymal uptake on molecular breast imaging and breast cancer risk: a case-control study
title_full Quantitative background parenchymal uptake on molecular breast imaging and breast cancer risk: a case-control study
title_fullStr Quantitative background parenchymal uptake on molecular breast imaging and breast cancer risk: a case-control study
title_full_unstemmed Quantitative background parenchymal uptake on molecular breast imaging and breast cancer risk: a case-control study
title_short Quantitative background parenchymal uptake on molecular breast imaging and breast cancer risk: a case-control study
title_sort quantitative background parenchymal uptake on molecular breast imaging and breast cancer risk: a case-control study
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5989426/
https://www.ncbi.nlm.nih.gov/pubmed/29871661
http://dx.doi.org/10.1186/s13058-018-0973-3
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