Skip to main content
Top
Published in: European Radiology 1/2020

Open Access 01-01-2020 | Magnetic Resonance Imaging | Breast

Peritumoral ADC values in breast cancer: region of interest selection, associations with hyaluronan intensity, and prognostic significance

Authors: Tiia Kettunen, Hidemi Okuma, Päivi Auvinen, Mazen Sudah, Satu Tiainen, Anna Sutela, Amro Masarwah, Markku Tammi, Raija Tammi, Sanna Oikari, Ritva Vanninen

Published in: European Radiology | Issue 1/2020

Login to get access

Abstract

Objectives

We aimed to evaluate the differences in peritumoral apparent diffusion coefficient (ADC) values by four different ROI selection methods and to validate the optimal method. Furthermore, we aimed to evaluate if the peritumor-tumor ADC ratios are correlated with axillary lymph node positivity and hyaluronan accumulation.

Methods

Altogether, 22 breast cancer patients underwent 3.0-T breast MRI, histopathological evaluation, and hyaluronan assay. Paired t and Friedman tests were used to compare minimum, mean, and maximum values of tumoral and peritumoral ADC by four methods: (M1) band ROI, (M2) whole tumor surrounding ROI, (M3) clockwise multiple ROI, and (M4) visual assessment of ROI selection. Subsequently, peritumor/tumor ADC ratios were compared with hyaluronan levels and axillary lymph node status by the Mann-Whitney U test.

Results

No statistically significant differences were found among the four ROI selection methods regarding minimum, mean, or maximum values of tumoral and peritumoral ADC. Visual assessment ROI measurements represented the less time-consuming evaluation method for the peritumoral area, and with sufficient accuracy. Peritumor/tumor ADC ratios obtained by all methods except the clockwise ROI (M3) showed a positive correlation with hyaluronan content (M1, p = 0.004; M2, p = 0.012; M3, p = 0.20; M4, p = 0.025) and lymph node metastasis (M1, p = 0.001; M2, p = 0.007; M3, p = 0.22; M4, p = 0.015), which are established factors for unfavorable prognosis.

Conclusions

Our results suggest that the peritumor/tumor ADC ratio could be a readily applicable imaging index associated with axillary lymph node metastasis and extensive hyaluronan accumulation. It could be related to the biological aggressiveness of breast cancer and therefore might serve as an additional prognostic factor.

Key Points

• Out of four different ROI selection methods for peritumoral ADC evaluation, measurements based on visual assessment provided sufficient accuracy and were the less time-consuming method.
• The peritumor/tumor ADC ratio can provide an easily applicable supplementary imaging index for breast cancer assessment.
• A higher peritumor/tumor ADC ratio was associated with axillary lymph node metastasis and extensive hyaluronan accumulation and might serve as an additional prognostic factor.
Literature
1.
go back to reference Torre LA, Bray F, Siegel RL, Ferlay J, Lortet-Tieulent J, Jemal A (2015) Global cancer statistics, 2012. CA Cancer J Clin 65:87–108CrossRef Torre LA, Bray F, Siegel RL, Ferlay J, Lortet-Tieulent J, Jemal A (2015) Global cancer statistics, 2012. CA Cancer J Clin 65:87–108CrossRef
2.
go back to reference Remsik J, Fedr R, Navratil J et al (2018) Plasticity and intratumoural heterogeneity of cell surface antigen expression in breast cancer. Br J Cancer 118:813–819CrossRef Remsik J, Fedr R, Navratil J et al (2018) Plasticity and intratumoural heterogeneity of cell surface antigen expression in breast cancer. Br J Cancer 118:813–819CrossRef
3.
go back to reference Zardavas D, Irrthum A, Swanton C, Piccart M (2015) Clinical management of breast cancer heterogeneity. Nat Rev Clin Oncol 12:381–394CrossRef Zardavas D, Irrthum A, Swanton C, Piccart M (2015) Clinical management of breast cancer heterogeneity. Nat Rev Clin Oncol 12:381–394CrossRef
4.
go back to reference Nelson DA, Tan TT, Rabson AB, Anderson D, Degenhardt K, White E (2004) Hypoxia and defective apoptosis drive genomic instability and tumorigenesis. Genes Dev 18:2095–2107CrossRef Nelson DA, Tan TT, Rabson AB, Anderson D, Degenhardt K, White E (2004) Hypoxia and defective apoptosis drive genomic instability and tumorigenesis. Genes Dev 18:2095–2107CrossRef
5.
go back to reference Polyak K, Kalluri R (2010) The role of the microenvironment in mammary gland development and cancer. Cold Spring Harb Perspect Biol 2:a003244CrossRef Polyak K, Kalluri R (2010) The role of the microenvironment in mammary gland development and cancer. Cold Spring Harb Perspect Biol 2:a003244CrossRef
6.
go back to reference Soysal SD, Tzankov A, Muenst SE (2015) Role of the tumor microenvironment in breast cancer. Pathobiology 82:142–152CrossRef Soysal SD, Tzankov A, Muenst SE (2015) Role of the tumor microenvironment in breast cancer. Pathobiology 82:142–152CrossRef
7.
go back to reference Tammi MI, Oikari S, Pasonen-Seppanen S, Rilla K, Auvinen P, Tammi RH (2019) Activated hyaluronan metabolism in the tumor matrix - causes and consequences. Matrix Biol 78-79:147–164CrossRef Tammi MI, Oikari S, Pasonen-Seppanen S, Rilla K, Auvinen P, Tammi RH (2019) Activated hyaluronan metabolism in the tumor matrix - causes and consequences. Matrix Biol 78-79:147–164CrossRef
8.
go back to reference Sironen RK, Tammi M, Tammi R, Auvinen PK, Anttila M, Kosma VM (2011) Hyaluronan in human malignancies. Exp Cell Res 317:383–391CrossRef Sironen RK, Tammi M, Tammi R, Auvinen PK, Anttila M, Kosma VM (2011) Hyaluronan in human malignancies. Exp Cell Res 317:383–391CrossRef
9.
go back to reference Hunger J, Bernecker A, Bakker HJ, Bonn M, Richter RP (2012) Hydration dynamics of hyaluronan and dextran. Biophys J 103:L10–L12CrossRef Hunger J, Bernecker A, Bakker HJ, Bonn M, Richter RP (2012) Hydration dynamics of hyaluronan and dextran. Biophys J 103:L10–L12CrossRef
10.
go back to reference Tammi RH, Kultti A, Kosma VM, Pirinen R, Auvinen P, Tammi MI (2008) Hyaluronan in human tumors: pathobiological and prognostic messages from cell-associated and stromal hyaluronan. Semin Cancer Biol 18:288–295CrossRef Tammi RH, Kultti A, Kosma VM, Pirinen R, Auvinen P, Tammi MI (2008) Hyaluronan in human tumors: pathobiological and prognostic messages from cell-associated and stromal hyaluronan. Semin Cancer Biol 18:288–295CrossRef
12.
go back to reference Auvinen P, Tammi R, Kosma VM et al (2013) Increased hyaluronan content and stromal cell CD44 associate with HER2 positivity and poor prognosis in human breast cancer. Int J Cancer 132:531–539CrossRef Auvinen P, Tammi R, Kosma VM et al (2013) Increased hyaluronan content and stromal cell CD44 associate with HER2 positivity and poor prognosis in human breast cancer. Int J Cancer 132:531–539CrossRef
13.
go back to reference Auvinen P, Tammi R, Parkkinen J et al (2000) Hyaluronan in peritumoral stroma and malignant cells associates with breast cancer spreading and predicts survival. Am J Pathol 156:529–536CrossRef Auvinen P, Tammi R, Parkkinen J et al (2000) Hyaluronan in peritumoral stroma and malignant cells associates with breast cancer spreading and predicts survival. Am J Pathol 156:529–536CrossRef
14.
go back to reference Arponen O, Masarwah A, Sutela A et al (2016) Incidentally detected enhancing lesions found in breast MRI: analysis of apparent diffusion coefficient and T2 signal intensity significantly improves specificity. Eur Radiol 26:4361–4370CrossRef Arponen O, Masarwah A, Sutela A et al (2016) Incidentally detected enhancing lesions found in breast MRI: analysis of apparent diffusion coefficient and T2 signal intensity significantly improves specificity. Eur Radiol 26:4361–4370CrossRef
15.
go back to reference Arponen O, Sudah M, Masarwah A et al (2015) Diffusion-weighted imaging in 3.0 tesla breast MRI: diagnostic performance and tumor characterization using small subregions vs. whole tumor regions of interest. PLoS One 10:e0138702CrossRef Arponen O, Sudah M, Masarwah A et al (2015) Diffusion-weighted imaging in 3.0 tesla breast MRI: diagnostic performance and tumor characterization using small subregions vs. whole tumor regions of interest. PLoS One 10:e0138702CrossRef
16.
go back to reference Hamstra DA, Rehemtulla A, Ross BD (2007) Diffusion magnetic resonance imaging: a biomarker for treatment response in oncology. J Clin Oncol 25:4104–4109CrossRef Hamstra DA, Rehemtulla A, Ross BD (2007) Diffusion magnetic resonance imaging: a biomarker for treatment response in oncology. J Clin Oncol 25:4104–4109CrossRef
17.
go back to reference Koh DM, Collins DJ (2007) Diffusion-weighted MRI in the body: applications and challenges in oncology. AJR Am J Roentgenol 188:1622–1635CrossRef Koh DM, Collins DJ (2007) Diffusion-weighted MRI in the body: applications and challenges in oncology. AJR Am J Roentgenol 188:1622–1635CrossRef
18.
go back to reference Fan M, He T, Zhang P, Zhang J, Li L (2017) Heterogeneity of diffusion-weighted imaging in tumours and the surrounding stroma for prediction of Ki-67 proliferation status in breast cancer. Sci Rep 7:2875CrossRef Fan M, He T, Zhang P, Zhang J, Li L (2017) Heterogeneity of diffusion-weighted imaging in tumours and the surrounding stroma for prediction of Ki-67 proliferation status in breast cancer. Sci Rep 7:2875CrossRef
19.
go back to reference McLaughlin RL, Newitt DC, Wilmes LJ et al (2014) High resolution in vivo characterization of apparent diffusion coefficient at the tumor-stromal boundary of breast carcinomas: a pilot study to assess treatment response using proximity-dependent diffusion-weighted imaging. J Magn Reson Imaging 39:1308–1313CrossRef McLaughlin RL, Newitt DC, Wilmes LJ et al (2014) High resolution in vivo characterization of apparent diffusion coefficient at the tumor-stromal boundary of breast carcinomas: a pilot study to assess treatment response using proximity-dependent diffusion-weighted imaging. J Magn Reson Imaging 39:1308–1313CrossRef
20.
go back to reference Mori N, Mugikura S, Takasawa C et al (2016) Peritumoral apparent diffusion coefficients for prediction of lymphovascular invasion in clinically node-negative invasive breast cancer. Eur Radiol 26:331–339CrossRef Mori N, Mugikura S, Takasawa C et al (2016) Peritumoral apparent diffusion coefficients for prediction of lymphovascular invasion in clinically node-negative invasive breast cancer. Eur Radiol 26:331–339CrossRef
21.
go back to reference Shin HJ, Park JY, Shin KC et al (2016) Characterization of tumor and adjacent peritumoral stroma in patients with breast cancer using high-resolution diffusion-weighted imaging: correlation with pathologic biomarkers. Eur J Radiol 85:1004–1011CrossRef Shin HJ, Park JY, Shin KC et al (2016) Characterization of tumor and adjacent peritumoral stroma in patients with breast cancer using high-resolution diffusion-weighted imaging: correlation with pathologic biomarkers. Eur J Radiol 85:1004–1011CrossRef
22.
go back to reference Oikari S, Kettunen T, Tiainen S et al (2018) UDP-sugar accumulation drives hyaluronan synthesis in breast cancer. Matrix Biol 67:63–74CrossRef Oikari S, Kettunen T, Tiainen S et al (2018) UDP-sugar accumulation drives hyaluronan synthesis in breast cancer. Matrix Biol 67:63–74CrossRef
23.
go back to reference Hiltunen EL, Anttila M, Kultti A et al (2002) Elevated hyaluronan concentration without hyaluronidase activation in malignant epithelial ovarian tumors. Cancer Res 62:6410–6413PubMed Hiltunen EL, Anttila M, Kultti A et al (2002) Elevated hyaluronan concentration without hyaluronidase activation in malignant epithelial ovarian tumors. Cancer Res 62:6410–6413PubMed
24.
go back to reference Landis JR, Koch GG (1977) The measurement of observer agreement for categorical data. Biometrics 33:159–174CrossRef Landis JR, Koch GG (1977) The measurement of observer agreement for categorical data. Biometrics 33:159–174CrossRef
25.
go back to reference Fan M, He T, Zhang P et al (2018) Diffusion-weighted imaging features of breast tumours and the surrounding stroma reflect intrinsic heterogeneous characteristics of molecular subtypes in breast cancer. NMR Biomed 31 Fan M, He T, Zhang P et al (2018) Diffusion-weighted imaging features of breast tumours and the surrounding stroma reflect intrinsic heterogeneous characteristics of molecular subtypes in breast cancer. NMR Biomed 31
26.
go back to reference Huang M, Liao B, Xu P et al (2018) Prediction of microvascular invasion in hepatocellular carcinoma: preoperative Gd-EOB-DTPA-dynamic enhanced MRI and histopathological correlation. Contrast Media Mol Imaging 2018:9674565PubMedPubMedCentral Huang M, Liao B, Xu P et al (2018) Prediction of microvascular invasion in hepatocellular carcinoma: preoperative Gd-EOB-DTPA-dynamic enhanced MRI and histopathological correlation. Contrast Media Mol Imaging 2018:9674565PubMedPubMedCentral
27.
go back to reference Deng L, Wang QP, Yan R et al (2018) The utility of measuring the apparent diffusion coefficient for peritumoral zone in assessing infiltration depth of endometrial cancer. Cancer Imaging 18:23CrossRef Deng L, Wang QP, Yan R et al (2018) The utility of measuring the apparent diffusion coefficient for peritumoral zone in assessing infiltration depth of endometrial cancer. Cancer Imaging 18:23CrossRef
28.
go back to reference Arponen O, Sudah M, Sutela A et al (2018) Gadoterate meglumine decreases ADC values of breast lesions depending on the b value combination. Sci Rep 8:87CrossRef Arponen O, Sudah M, Sutela A et al (2018) Gadoterate meglumine decreases ADC values of breast lesions depending on the b value combination. Sci Rep 8:87CrossRef
29.
go back to reference Padhani AR, Liu G, Koh DM et al (2009) Diffusion-weighted magnetic resonance imaging as a cancer biomarker: consensus and recommendations. Neoplasia 11:102–125CrossRef Padhani AR, Liu G, Koh DM et al (2009) Diffusion-weighted magnetic resonance imaging as a cancer biomarker: consensus and recommendations. Neoplasia 11:102–125CrossRef
30.
go back to reference Schmeel FC (2019) Variability in quantitative diffusion-weighted MR imaging (DWI) across different scanners and imaging sites: is there a potential consensus that can help reducing the limits of expected bias? Eur Radiol 29:2243–2245CrossRef Schmeel FC (2019) Variability in quantitative diffusion-weighted MR imaging (DWI) across different scanners and imaging sites: is there a potential consensus that can help reducing the limits of expected bias? Eur Radiol 29:2243–2245CrossRef
31.
go back to reference Baltzer PA, Yang F, Dietzel M et al (2010) Sensitivity and specificity of unilateral edema on T2w-TSE sequences in MR-mammography considering 974 histologically verified lesions. Breast J 16:233–239CrossRef Baltzer PA, Yang F, Dietzel M et al (2010) Sensitivity and specificity of unilateral edema on T2w-TSE sequences in MR-mammography considering 974 histologically verified lesions. Breast J 16:233–239CrossRef
32.
go back to reference Cheon H, Kim HJ, Kim TH et al (2018) Invasive breast cancer: prognostic value of peritumoral edema identified at preoperative MR imaging. Radiology 287:68–75CrossRef Cheon H, Kim HJ, Kim TH et al (2018) Invasive breast cancer: prognostic value of peritumoral edema identified at preoperative MR imaging. Radiology 287:68–75CrossRef
33.
go back to reference Costantini M, Belli P, Distefano D et al (2012) Magnetic resonance imaging features in triple-negative breast cancer: comparison with luminal and HER2-overexpressing tumors. Clin Breast Cancer 12:331–339CrossRef Costantini M, Belli P, Distefano D et al (2012) Magnetic resonance imaging features in triple-negative breast cancer: comparison with luminal and HER2-overexpressing tumors. Clin Breast Cancer 12:331–339CrossRef
Metadata
Title
Peritumoral ADC values in breast cancer: region of interest selection, associations with hyaluronan intensity, and prognostic significance
Authors
Tiia Kettunen
Hidemi Okuma
Päivi Auvinen
Mazen Sudah
Satu Tiainen
Anna Sutela
Amro Masarwah
Markku Tammi
Raija Tammi
Sanna Oikari
Ritva Vanninen
Publication date
01-01-2020
Publisher
Springer Berlin Heidelberg
Published in
European Radiology / Issue 1/2020
Print ISSN: 0938-7994
Electronic ISSN: 1432-1084
DOI
https://doi.org/10.1007/s00330-019-06361-y

Other articles of this Issue 1/2020

European Radiology 1/2020 Go to the issue