Sensitivity of Contrast-Enhanced Breast MRI vs X-ray Mammography Based on Cancer Histology, Tumor Grading, Receptor Status, and Molecular Subtype: A Supplemental Analysis of 2 Large Phase III Studies

Jan Endrikat, Gilda Schmidt, Daniel Haverstock, Olaf Weber, Zuzana Jirakova Trnkova, Jörg Barkhausen, Jan Endrikat, Gilda Schmidt, Daniel Haverstock, Olaf Weber, Zuzana Jirakova Trnkova, Jörg Barkhausen

Abstract

Background: The impact of certain tumor parameters on the sensitivity of imaging tools is unknown. The purpose was to study the impact of breast cancer histology, tumor grading, single receptor status, and molecular subtype on the sensitivity of contrast-enhanced breast magnetic resonance imaging (CE-BMRI) vs X-ray mammography (XRM) to detect breast cancer.

Materials and methods: We ran a supplemental analysis of 2 global Phase III studies which recruited patients with histologically proven breast cancers. The sensitivity of CE-BMRI vs XRM to detect cancer lesions with different histologies, tumor grading, single receptor status, and molecular subtype was compared. Six blinded readers for each study evaluated the images. Results were summarized as the "Mean Reader." For each reader, sensitivity was defined as the proportion of detected lesions vs the total number of lesions identified by the standard of reference. Two-sided 95% confidence intervals were calculated for within-group proportions, and for the difference between CE-BMRI and XRM, using a normal approximation to the binomial distribution.

Results: In 778 patients, 1273 cancer lesions were detected. A total of 435 patients had 1 lesion, 254 had 2 lesions, and 77 had 3 or more lesions. The sensitivity of CE-BMRI was significantly higher compared with XRM irrespective of the histology. The largest difference was seen for invasive lobular carcinoma (22.3%) and ductal carcinoma in situ (19%). Across all 3 tumor grades, the sensitivity advantage of CE-BMRI over XRM ranged from 15.7% to 18.5%. Contrast-enhanced breast magnetic resonance imaging showed higher sensitivity compared with XRM irrespective of single receptor expressions (15.3%-19.4%). The sensitivities for both imaging methods were numerically higher for the more aggressive ER- (estrogen receptor), PR- (progesterone receptor), and HER2+ (human epidermal growth factor receptor 2) tumors. Irrespective of molecular subtype, sensitivity of CE-BMRI was 14.8% to 18.9% higher compared with XRM.

Conclusions: Contrast-enhanced breast magnetic resonance imaging showed significantly higher sensitivity compared with XRM independent of tumor histology, tumor grading, single receptor status, and molecular subtype.Trial Registration: ClinicalTrials.gov: NCT01067976 and NCT01104584.

Keywords: Breast cancer; X-ray mammography; breast MRI; histology; hormone receptors; molecular type; tumor grading.

Conflict of interest statement

Declaration of Conflicting Interests: The author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: GS and JB declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. JE, DH, OW and ZJT are Bayer employees.

© The Author(s) 2022.

Figures

Figure 1.
Figure 1.
Sensitivities of CE-BMRI vs XRM by tumor histology (n = 1231 cancer lesions) (% [±95% CI]). *95% CIs do not overlap. CE-BMRI indicates contrast-enhanced breast magnetic resonance imaging; CI, confidence interval; DCIS, ductal carcinoma in situ; IDC, invasive ductal carcinoma; ILC, invasive lobular carcinoma; XRM, X-ray mammography.
Figure 2.
Figure 2.
Sensitivities of CE-BMRI vs XRM by tumor grading (% [±95% CI]). *95% CIs do not overlap. CE-BMRI indicates contrast-enhanced breast magnetic resonance imaging; CI, confidence interval; XRM, X-ray mammography.
Figure 3.
Figure 3.
Sensitivities of CE-BMRI vs XRM by molecular subtype (% [±95% CI]). *95% CIs do not overlap. CE-BMRI indicates contrast-enhanced breast magnetic resonance imaging; CI, confidence interval; HER2, human epidermal growth factor receptor 2; TN, triple negative; XRM, X-ray mammography.

References

    1. Strand F, Zackrisson S. Breast cancer imaging—a rapidly evolving discipline. Breast. 2019;46:58-63.
    1. Smetana GW, Elmore JG, Lee CI, Burns RB. Should this woman with dense breasts receive supplemental breast cancer screening? Grand rounds discussion from Beth Israel Deaconess Medical Center. Ann Intern Med. 2018;169:474-484.
    1. Renz DM, Durmus T, Bottcher J, et al.. Comparison of gadoteric acid and gadobutrol for detection as well as morphologic and dynamic characterization of lesions on breast dynamic contrast-enhanced magnetic resonance imaging. Invest Radiol. 2014;49:474-484.
    1. Clauser P, Baltzer PAT, Kapetas P, et al.. Synthetic 2-dimensional mammography can replace digital mammography as an adjunct to wide-angle digital breast tomosynthesis. Invest Radiol. 2019;54:83-88.
    1. Kuhl CK, Strobel K, Bieling H, Leutner C, Schild HH, Schrading S. Supplemental breast MR imaging screening of women with average risk of breast cancer. Radiology. 2017;283:361-370.
    1. Sardanelli F, Newstead GM, Putz B, et al.. Gadobutrol-enhanced magnetic resonance imaging of the breast in the preoperative setting: results of 2 prospective international multicenter phase III studies. Invest Radiol. 2016;51:454-461.
    1. Mann RM, Kuhl CK, Moy L. Contrast-enhanced MRI for breast cancer screening. J Magn Reson Imaging. 2019;50:377-390.
    1. Berg WA, Zhang Z, Lehrer D, et al.. Detection of breast cancer with addition of annual screening ultrasound or a single screening MRI to mammography in women with elevated breast cancer risk. JAMA. 2012;307:1394-1404.
    1. Kuhl CK, Schrading S, Bieling HB, et al.. MRI for diagnosis of pure ductal carcinoma in situ: a prospective observational study. Lancet. 2007;370:485-492.
    1. Kuhl CK. Abbreviated magnetic resonance imaging (MRI) for breast cancer screening: rationale, concept, and transfer to clinical practice. Annu Rev Med. 2019;70:501-519.
    1. Saadatmand S, Geuzinge HA, Rutgers EJT, et al.. MRI versus mammography for breast cancer screening in women with familial risk (FaMRIsc): a multicentre, randomised, controlled trial. Lancet Oncol. 2019;20:1136-1147.
    1. Comstock CE, Gatsonis C, Newstead GM, et al.. Comparison of abbreviated breast MRI vs digital breast tomosynthesis for breast cancer detection among women with dense breasts undergoing screening. JAMA. 2020;323:746-756.
    1. O’Flynn EA, Ledger AE, deSouza NM. Alternative screening for dense breasts: MRI. AJR Am J Roentgenol. 2015;204:W141-W149.
    1. Houssami N, Ciatto S, Macaskill P, et al.. Accuracy and surgical impact of magnetic resonance imaging in breast cancer staging: systematic review and meta-analysis in detection of multifocal and multicentric cancer. J Clin Oncol. 2008;26:3248-3258.
    1. Brennan ME, Houssami N, Lord S, et al.. Magnetic resonance imaging screening of the contralateral breast in women with newly diagnosed breast cancer: systematic review and meta-analysis of incremental cancer detection and impact on surgical management. J Clin Oncol. 2009;27:5640-5649.
    1. Peters NH, van Esser S, van den Bosch MA, et al.. Preoperative MRI and surgical management in patients with nonpalpable breast cancer: the MONET—randomised controlled trial. Eur J Cancer. 2011;47:879-886.
    1. Pettit K, Swatske ME, Gao F, et al.. The impact of breast MRI on surgical decision-making: are patients at risk for mastectomy? J Surg Oncol. 2009;100:553-558.
    1. Sardanelli F, Boetes C, Borisch B, et al.. Magnetic resonance imaging of the breast: recommendations from the EUSOMA working group. Eur J Cancer. 2010;46:1296-1316.
    1. Monticciolo DL, Newell MS, Moy L, Niell B, Monsees B, Sickles EA. Breast cancer screening in women at higher-than-average risk: recommendations from the ACR. J Am Coll Radiol. 2018;15:408-414.
    1. ACR practice parameter for the performance of contrast enhanced magnetic resonance imaging (MRI) of the breast, Amended 2014. (Resolution 39),
    1. Park EK, Seo BK, Kwon M, et al.. Low-dose perfusion computed tomography for breast cancer to quantify tumor vascularity: correlation with prognostic biomarkers. Invest Radiol. 2019;54:273-281.
    1. Scott LJ. Gadobutrol: a review in contrast-enhanced MRI and MRA. Clin Drug Investig. 2018;38:773-784.
    1. Pediconi F, Kubik-Huch R, Chilla B, Schwenke C, Kinkel K. Intra-individual randomised comparison of gadobutrol 1.0 M versus gadobenate dimeglumine 0.5 M in patients scheduled for preoperative breast MRI. Eur Radiol. 2013;23:84-92.
    1. Escribano F, Sentis M, Oliva JC, et al.. Dynamic magnetic resonance imaging of the breast: comparison of gadobutrol vs. Gd-DTPA. Radiologia (Engl Ed). 2018;60:49-56.
    1. Fallenberg EM, Renz DM, Karle B, et al.. Intraindividual, randomized comparison of the macrocyclic contrast agents gadobutrol and gadoterate meglumine in breast magnetic resonance imaging. Eur Radiol. 2015;25:837-849.
    1. Schwenke C, Busse R. Analysis of differences in proportions from clustered data with multiple measurements in diagnostic studies. Methods Inf Med. 2007;46:548-552.
    1. Barkhausen J, Bischof A, Haverstock D, et al.. Diagnostic efficacy of contrast-enhanced breast MRI versus X-ray mammography in women with different degrees of breast density. Acta Radiol. 2021;62:586-593.
    1. Oluogun WA, Adedokun KA, Oyenike MA, Adeyeba OA. Histological classification, grading, staging, and prognostic indexing of female breast cancer in an African population: a 10-year retrospective study. Int J Health Sci (Qassim). 2019;13:3-9.
    1. Vuong D, Simpson PT, Green B, Cummings MC, Lakhani SR. Molecular classification of breast cancer. Virchows Arch. 2014;465:1-14.
    1. Riedl CC, Ponhold L, Flory D, et al.. Magnetic resonance imaging of the breast improves detection of invasive cancer, preinvasive cancer, and premalignant lesions during surveillance of women at high risk for breast cancer. Clin Cancer Res. 2007;13:6144-6152.
    1. Preibsch H, Beckmann J, Pawlowski J, et al.. Accuracy of breast magnetic resonance imaging compared to mammography in the preoperative detection and measurement of pure ductal carcinoma in situ: a retrospective analysis. Acad Radiol. 2019;26:760-765.
    1. Kriege M, Brekelmans CT, Peterse H, et al.. Tumor characteristics and detection method in the MRISC screening program for the early detection of hereditary breast cancer. Breast Cancer Res Treat. 2007;102:357-363.
    1. Sung JS, Stamler S, Brooks J, et al.. Breast cancers detected at screening MR imaging and mammography in patients at high risk: method of detection reflects tumor histopathologic results. Radiology. 2016;280:716-722.
    1. Rakha EA, Reis-Filho JS, Baehner F, et al.. Breast cancer prognostic classification in the molecular era: the role of histological grade. Breast Cancer Res. 2010;12:207.
    1. Kunc M, Biernat W, Senkus-Konefka E. Estrogen receptor-negative progesterone receptor-positive breast cancer—“nobody’s land” or just an artifact? Cancer Treat Rev. 2018;67:78-87.
    1. Hayes DF. HER2 and breast cancer—a phenomenal success story. N Engl J Med. 2019;381:1284-1286.
    1. El Hachem G, Gombos A, Awada A. Recent advances in understanding breast cancer and emerging therapies with a focus on luminal and triple-negative breast cancer. F1000Res. 2019;8:591.
    1. Howlader N, Cronin KA, Kurian AW, Andridge R. Differences in breast cancer survival by molecular subtypes in the United States. Cancer Epidemiol Biomarkers Prev. 2018;27:619-626.
    1. Darlix A, Louvel G, Fraisse J, et al.. Impact of breast cancer molecular subtypes on the incidence, kinetics and prognosis of central nervous system metastases in a large multicentre real-life cohort. Br J Cancer. 2019;121:991-1000.
    1. Harbeck N, Salem M, Nitz U, Gluz O, Liedtke C. Personalized treatment of early-stage breast cancer: present concepts and future directions. Cancer Treat Rev. 2010;36:584-594.
    1. Li Y, Zhang X, Qiu J, Pang T, Huang L, Zeng Q. Comparisons of p53, KI67 and BRCA1 expressions in patients with different molecular subtypes of breast cancer and their relationships with pathology and prognosis. J BUON. 2019;24:2361-2368.
    1. Wu M, Ma J. Association between imaging characteristics and different molecular subtypes of breast cancer. Acad Radiol. 2017;24:426-434.
    1. Comes MC, Fanizzi A, Bove S, et al.. Early prediction of neoadjuvant chemotherapy response by exploiting a transfer learning approach on breast DCE-MRIs. Sci Rep. 2021;11:14123.
    1. Comes MC, La Forgia D, Didonna V, et al.. Early prediction of breast cancer recurrence for patients treated with neoadjuvant chemotherapy: a transfer learning approach on DCE-MRIs. Cancers (Basel). 2021;13:2298.
    1. Song SE, Bae MS, Chang JM, Cho N, Ryu HS, Moon WK. MR and mammographic imaging features of HER2-positive breast cancers according to hormone receptor status: a retrospective comparative study. Acta Radiol. 2017;58:792-799.
    1. Avanzo M, Porzio M, Lorenzon L, et al.. Artificial intelligence applications in medical imaging: a review of the medical physics research in Italy. Phys Med. 2021;83:221-241.
    1. Massafra R, Bove S, Lorusso V, et al.. Radiomic feature reduction approach to predict breast cancer by contrast-enhanced spectral mammography images. Diagnostics (Basel). 2021;11:684.

Source: PubMed

3
Abonnieren