Journal Article
. 2012 Mar;22(7).
doi: 10.1007/s00330-012-2403-8.

Correlations between diffusion-weighted imaging and breast cancer biomarkers

Laura Martincich 1 Veronica Deantoni  Ilaria Bertotto  Stefania Redana  Franziska Kubatzki  Ivana Sarotto  Valentina Rossi  Michele Liotti  Riccardo Ponzone  Massimo Aglietta  Daniele Regge  Filippo Montemurro  
  • PMID: 22411304
  •     48 References
  •     68 citations


Objective: We evaluated whether the apparent diffusion coefficient (ADC) provided by diffusion-weighted imaging (DWI) varies according to biological features in breast cancer.

Methods: DWI was performed in 190 patients undergoing dynamic contrast-enhanced magnetic resonance imaging (MRI) for local staging. For each of the 192 index cancers we studied the correlation between ADC and classical histopathological and immunohistochemical breast tumour features (size, histological type, grade, oestrogen receptor [ER] and Ki-67 expression, HER2 status). ADC was compared with immunohistochemical surrogates of the intrinsic subtypes (Luminal A; Luminal B; HER2-enriched; triple-negative). Correlations were analysed using the Mann-Whitney U and Kruskal-Wallis H tests.

Results: A weak, statistically significant correlation was observed between ADC values and the percentage of ER-positive cells (-0.168, P = 0.020). Median ADC values were significantly higher in ER-negative than in ER-positive tumours (1.110 vs 1.050 × 10(-3) mm(2)/s, P = 0.015). HER2-enriched tumours had the highest median ADC value (1.190 × 10(-3) mm(2)/s, range 0.950-2.090). Multiple comparisons showed that this value was significantly higher than that of Luminal A (1.025 × 10(-3) mm(2)/s [0.700-1.340], P = 0.004) and Luminal B/HER2-negative (1.060 × 10(-3) mm(2)/s [0.470-2.420], P = 0.008) tumours. A trend towards statistical significance (P = 0.018) was seen with Luminal B/HER2-positive tumours.

Conclusions: ADC values vary significantly according to biological tumour features, suggesting that cancer heterogeneity influences imaging parameters.

Key Points: DWI may identify biological heterogeneity of breast neoplasms. • ADC values vary significantly according to biological features of breast cancer. • Compared with other types, HER2-enriched tumours show highest median ADC value. • Knowledge of biological heterogeneity of breast neoplasm may improve imaging interpretation.

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Front Oncol, 2019 Jul 02; 9. PMID: 31259153    Free PMC article.
Diagnostic value of diffusion-weighted imaging-derived apparent diffusion coefficient and its association with histological prognostic factors in breast cancer.
Congcong Ren, Yu Zou, Xiaodan Zhang, Kui Li.
Oncol Lett, 2019 Aug 28; 18(3). PMID: 31452808    Free PMC article.
Prediction of the clinicopathological subtypes of breast cancer using a fisher discriminant analysis model based on radiomic features of diffusion-weighted MRI.
Ming Ni, Xiaoming Zhou, +4 authors, Zhiming Li.
BMC Cancer, 2020 Nov 11; 20(1). PMID: 33167903    Free PMC article.
Diffusion-weighted imaging of the breast: current status as an imaging biomarker and future role.
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BJR Open, 2019 Mar 08; 1(1). PMID: 33178933    Free PMC article.
A machine learning approach to radiogenomics of breast cancer: a study of 922 subjects and 529 DCE-MRI features.
Ashirbani Saha, Michael R Harowicz, +4 authors, Maciej A Mazurowski.
Br J Cancer, 2018 Jul 24; 119(4). PMID: 30033447    Free PMC article.
Preoperative elevated neutrophil-to-lymphocyte ratio (NLR) and derived NLR are associated with poor prognosis in patients with breast cancer: A meta-analysis.
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Medicine (Baltimore), 2018 Dec 14; 97(49). PMID: 30544398    Free PMC article.
Correlation between apparent diffusion coefficient of magnetic resonance imaging and tumor-infiltrating lymphocytes in breast cancer.
Marco Fogante, Corrado Tagliati, +3 authors, Andrea Giovagnoni.
Radiol Med, 2019 Feb 27; 124(7). PMID: 30806920
Hypoxia and perfusion in breast cancer: simultaneous assessment using PET/MR imaging.
Julia C Carmona-Bozo, Roido Manavaki, +8 authors, Fiona J Gilbert.
Eur Radiol, 2020 Jul 30; 31(1). PMID: 32725330    Free PMC article.
Can MRI Biomarkers Predict Triple-Negative Breast Cancer?
Giuliana Moffa, Francesca Galati, +4 authors, Federica Pediconi.
Diagnostics (Basel), 2020 Dec 19; 10(12). PMID: 33333733    Free PMC article.
Diffusion-Weighted Magnetic Resonance Imaging of the Breast: Standardization of Image Acquisition and Interpretation.
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[Multimodal, multiparametric and genetic breast imaging].
Roberto LoGullo, Joao Horvat, Jeffrey Reiner, Katja Pinker.
Radiologe, 2021 Jan 20; 61(2). PMID: 33464404
Dynamic contrast enhanced-MRI and diffusion-weighted image as predictors of lymphovascular invasion in node-negative invasive breast cancer.
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World J Surg Oncol, 2021 Mar 17; 19(1). PMID: 33722246    Free PMC article.
Quantitative diffusion-weighted MRI parameters and human papillomavirus status in oropharyngeal squamous cell carcinoma.
C S Schouten, P de Graaf, +6 authors, R de Bree.
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An analysis of Ki-67 expression in stage 1 invasive ductal breast carcinoma using apparent diffusion coefficient histograms.
Maolin Xu, Qi Tang, +2 authors, Fang Li.
Quant Imaging Med Surg, 2021 Apr 06; 11(4). PMID: 33816188    Free PMC article.