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01-02-2017 | Research Article

Multiparametric evaluation of preoperative MRI in early stage breast cancer: prognostic impact of peri-tumoral fat

Authors: J.-P. Obeid, R. Stoyanova, D. Kwon, M. Patel, K. Padgett, J. Slingerland, C. Takita, N. Alperin, M. Yepes, Y. H. Zeidan

Published in: Clinical and Translational Oncology | Issue 2/2017

Abstract

Purpose

Obesity is associated with adverse outcomes in breast cancer patients. Fat-specific cytokines (adipokines) have been proposed as key drivers of breast cancer progression, invasion, and metastasis. We aimed at assessing correlations between peri-tumoral fat, quantified on magnetic resonance imaging (MRI) and pathologic factors potentially impacting therapy recommendations.

Methods

We retrospectively reviewed records of 63 patients with early stage breast cancer who underwent preoperative MRI imaging using appropriately weighted series for breast and tumor contouring. Fat volumes were generated through voxel intensity filtering. The peri-tumoral region was defined as the intersection of a 1-cm spherical extension around the tumor and the breast contour. Peri-tumoral fat was defined as the fraction of a fat content in this volume. Surgical pathology records were used to extract clinical data. Statistical analyses were conducted using Pearson and Spearman correlation coefficients.

Results

Among reviewed patients, 45 had T1 tumors (1.22 ± 0.85 cm diameter) and 18 had T2 tumors (2.08 ± 1.06 cm). Axillary lymph nodes were dissected in 31 and positive in 17 patients analyzed. Peri-tumoral fat ratio ranged between 25 and 99 %. Peri-tumoral fat ratio significantly correlated with the nodal-positive ratio of positive axillary lymph nodes (r = 0.532). Peri-tumoral fat ratio demonstrated optimally prominent correlation among obese patients upon body mass index categorical stratification.

Conclusions

In women with early stage breast cancer, peri-tumoral fat correlates positively with the ratio of pathologically involved axillary nodes. This work highlights a novel method for quantitating peri-tumoral fat content. Preoperative breast MRI may be utilized to predict extent of axillary disease.

Gallagher EJ, LeRoith D. Obesity and diabetes: the increased risk of cancer and cancer-related mortality. Physiol Rev. 2015;95(3):727–48. doi:10.1152/physrev.00030.2014.CrossRefPubMedPubMedCentral

Goodwin PJ, Ambrosone CB, Hong CC. Modifiable lifestyle factors and breast cancer outcomes: current controversies and research recommendations. Adv Exp Med Biol. 2015;862:177–92. doi:10.1007/978-3-319-16366-6_12.CrossRefPubMed

Rota M, Rumi F, Bagnardi V, Dal Maso L, Zucchetto A, Levi F, et al. Modelling body mass index and endometrial cancer risk in a pooled-analysis of three case–control studies. BJOG. 2015. doi:10.1111/1471-0528.13717.PubMed

Secord AA, Hasselblad V, Von Gruenigen VE, Gehrig PA, Modesitt SC, Bae-Jump V, et al. Body mass index and mortality in endometrial cancer: a systematic review and meta-analysis. Gynecol Oncol. 2015. doi:10.1016/j.ygyno.2015.10.020.

Gati A, Kouidhi S, Marrakchi R, El Gaaied A, Kourda N, Derouiche A, et al. Obesity and renal cancer: role of adipokines in the tumor-immune system conflict. Oncoimmunology. 2014;3(1):e27810. doi:10.4161/onci.27810.CrossRefPubMedPubMedCentral

Amor S, Iglesias-de la Cruz MC, Ferrero E, Garcia-Villar O, Barrios V, Fernandez N, et al. Peritumoral adipose tissue as a source of inflammatory and angiogenic factors in colorectal cancer. Int J Colorectal Dis. 2015. doi:10.1007/s00384-015-2420-6.PubMed

Zhang X, Wu K, Giovannucci EL, Ma J, Colditz GA, Fuchs CS, et al. Early life body fatness and risk of colorectal cancer in U.S. women and men—results from two large cohort studies. Cancer Epidemiol Biomark Prev. 2015;24(4):690–7. doi:10.1158/1055-9965.EPI-14-0909-T.CrossRef

Chan DS, Vieira AR, Aune D, Bandera EV, Greenwood DC, McTiernan A, et al. Body mass index and survival in women with breast cancer-systematic literature review and meta-analysis of 82 follow-up studies. Ann Oncol. 2014;25(10):1901–14. doi:10.1093/annonc/mdu042.CrossRefPubMedPubMedCentral

Gilbert CA, Slingerland JM. Cytokines, obesity, and cancer: new insights on mechanisms linking obesity to cancer risk and progression. Annu Rev Med. 2013;64:45–57. doi:10.1146/annurev-med-121211-091527.CrossRefPubMed

10.

Diedrich J, Gusky HC, Podgorski I. Adipose tissue dysfunction and its effects on tumor metabolism. Horm Mol Biol Clin Investig. 2015;21(1):17–41. doi:10.1515/hmbci-2014-0045.PubMedPubMedCentral

11.

Gregor MF, Hotamisligil GS. Thematic review series: adipocyte biology. Adipocyte stress: the endoplasmic reticulum and metabolic disease. J Lipid Res. 2007;48(9):1905–14. doi:10.1194/jlr.R700007-JLR200.CrossRefPubMed

12.

Gregor MF, Hotamisligil GS. Inflammatory mechanisms in obesity. Annu Rev Immunol. 2011;29:415–45. doi:10.1146/annurev-immunol-031210-101322.CrossRefPubMed

13.

Picon-Ruiz M, Pan C, Drews-Elger K, Jang K, Besser AH, Zhao D, et al. Interactions between adipocytes and breast cancer cells stimulate cytokine production and drive Src/Sox2/miR-302b-mediated malignant progression. Cancer Res. 2016;76(2):491–504. doi:10.1158/0008-5472.CAN-15-0927.CrossRefPubMed

14.

Park J, Morley TS, Kim M, Clegg DJ, Scherer PE. Obesity and cancer—mechanisms underlying tumour progression and recurrence. Nat Rev Endocrinol. 2014;10(8):455–65. doi:10.1038/nrendo.2014.94.CrossRefPubMedPubMedCentral

15.

Lambin P, Rios-Velazquez E, Leijenaar R, Carvalho S, van Stiphout RG, Granton P, et al. Radiomics: extracting more information from medical images using advanced feature analysis. Eur J Cancer. 2012;48(4):441–6. doi:10.1016/j.ejca.2011.11.036.CrossRefPubMedPubMedCentral

16.

Uematsu T, Kasami M, Yuen S. Triple-negative breast cancer: correlation between MR imaging and pathologic findings. Radiology. 2009;250(3):638–47. doi:10.1148/radiol.2503081054.CrossRefPubMed

17.

Youk JH, Son EJ, Chung J, Kim JA, Kim EK. Triple-negative invasive breast cancer on dynamic contrast-enhanced and diffusion-weighted MR imaging: comparison with other breast cancer subtypes. Eur Radiol. 2012;22(8):1724–34. doi:10.1007/s00330-012-2425-2.CrossRefPubMed

18.

Loiselle C, Eby PR, Kim JN, Calhoun KE, Allison KH, Gadi VK, et al. Preoperative MRI improves prediction of extensive occult axillary lymph node metastases in breast cancer patients with a positive sentinel lymph node biopsy. Acad Radiol. 2014;21(1):92–8. doi:10.1016/j.acra.2013.10.001.CrossRefPubMedPubMedCentral

19.

Loiselle CR, Eby PR, DeMartini WB, Peacock S, Bittner N, Lehman CD, et al. Dynamic contrast-enhanced MRI kinetics of invasive breast cancer: a potential prognostic marker for radiation therapy. Int J Radiat Oncol Biol Phys. 2010;76(5):1314–9. doi:10.1016/j.ijrobp.2009.03.053.CrossRefPubMed

20.

Tafreshi NK, Gillies RJ, Morse DL. Molecular imaging of breast cancer lymph node metastasis. Eur J Radiol. 2012;81(Suppl 1):S160–1. doi:10.1016/S0720-048X(12)70067-0.CrossRefPubMedPubMedCentral

21.

Edge SB, Compton CC. The American Joint Committee on Cancer: the 7th edition of the AJCC cancer staging manual and the future of TNM. Ann Surg Oncol. 2010;17(6):1471–4. doi:10.1245/s10434-010-0985-4.CrossRefPubMed

22.

Jauffret C, Houvenaeghel G, Classe JM, Garbay JR, Giard S, Charitansky H, et al. Lobular invasive breast cancer prognostic factors: about 940 patients. Gynecol Obstet Fertil. 2015. doi:10.1016/j.gyobfe.2015.09.007.PubMed

23.

Wang X, He YJ, Ying M, Li JF, Xie YT, Wang TF, et al. Impact of response of positive axillary nodes to neoadjuvant chemotherapy on breast cancer survival. Zhonghua Yi Xue Za Zhi. 2011;91(30):2116–9.PubMed

24.

Cunliffe A, Armato SG 3rd, Castillo R, Pham N, Guerrero T, Al-Hallaq HA. Lung texture in serial thoracic computed tomography scans: correlation of radiomics-based features with radiation therapy dose and radiation pneumonitis development. Int J Radiat Oncol Biol Phys. 2015;91(5):1048–56. doi:10.1016/j.ijrobp.2014.11.030.CrossRefPubMedPubMedCentral

25.

Hong R, Dai Z, Zhu W, Xu B. Association between lymph node ratio and disease specific survival in breast cancer patients with one or two positive lymph nodes stratified by different local treatment modalities. PLoS One. 2015;10(10):e0138908. doi:10.1371/journal.pone.0138908.CrossRefPubMedPubMedCentral

26.

Veronesi U, Orecchia R, Zurrida S, Galimberti V, Luini A, Veronesi P, et al. Avoiding axillary dissection in breast cancer surgery: a randomized trial to assess the role of axillary radiotherapy. Ann Oncol. 2005;16(3):383–8. doi:10.1093/annonc/mdi089.CrossRefPubMed

27.

Golshan M, Smith B. Prevention and management of arm lymphedema in the patient with breast cancer. J Support Oncol. 2006;4(8):381–6.PubMed

28.

Kuehn T, Klauss W, Darsow M, Regele S, Flock F, Maiterth C, et al. Long-term morbidity following axillary dissection in breast cancer patients—clinical assessment, significance for life quality and the impact of demographic, oncologic and therapeutic factors. Breast Cancer Res Treat. 2000;64(3):275–86.CrossRefPubMed

29.

Madsen RJ, Esmonde NO, Ramsey KL, Hansen JE. Axillary lymph node dissection is a risk factor for major complications after immediate breast reconstruction. Ann Plast Surg. 2015. doi:10.1097/SAP.0000000000000653.

30.

Giuliano AE, McCall L, Beitsch P, Whitworth PW, Blumencranz P, Leitch AM, et al. Locoregional recurrence after sentinel lymph node dissection with or without axillary dissection in patients with sentinel lymph node metastases: the American College of Surgeons Oncology Group Z0011 randomized trial. Ann Surg. 2010;252(3):426–32. doi:10.1097/SLA.0b013e3181f08f32 (discussion 32–3).PubMed

31.

James FR, Wootton S, Jackson A, Wiseman M, Copson ER, Cutress RI. Obesity in breast cancer—what is the risk factor? Eur J Cancer. 2015;51(6):705–20. doi:10.1016/j.ejca.2015.01.057.CrossRefPubMed

32.

Strong AL, Strong TA, Rhodes LV, Semon JA, Zhang X, Shi Z, et al. Obesity associated alterations in the biology of adipose stem cells mediate enhanced tumorigenesis by estrogen dependent pathways. Breast Cancer Res. 2013;15(5):R102. doi:10.1186/bcr3569.CrossRefPubMedPubMedCentral

33.

Khan S, Shukla S, Sinha S, Meeran SM. Role of adipokines and cytokines in obesity-associated breast cancer: therapeutic targets. Cytokine Growth Factor Rev. 2013;24(6):503–13. doi:10.1016/j.cytogfr.2013.10.001.CrossRefPubMed

Title: Multiparametric evaluation of preoperative MRI in early stage breast cancer: prognostic impact of peri-tumoral fat
Authors: J.-P. Obeid
R. Stoyanova
D. Kwon
M. Patel
K. Padgett
J. Slingerland
C. Takita
N. Alperin
M. Yepes
Y. H. Zeidan
Publication date: 01-02-2017
Publisher: Springer International Publishing
Published in: Clinical and Translational Oncology / Issue 2/2017
Print ISSN: 1699-048X
Electronic ISSN: 1699-3055
DOI: https://doi.org/10.1007/s12094-016-1526-9

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