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Predicting metastasis in clinically negative axillary lymph nodes with minimum apparent diffusion coefficient value in luminal A-like breast cancer

  • Fumi KatoEmail author
  • Kohsuke Kudo
  • Hiroko Yamashita
  • Motoi Baba
  • Ai Shimizu
  • Noriko Oyama-Manabe
  • Rumiko Kinoshita
  • Ruijiang Li
  • Hiroki Shirato
Original Article
  • 64 Downloads

Abstract

Background

We investigated the usefulness of the minimum ADC value of primary breast lesions for predicting axillary lymph node (LN) status in luminal A-like breast cancers with clinically negative nodes in comparison with the mean ADC.

Methods

Forty-four luminal A-like breast cancers without axillary LN metastasis at preoperative clinical evaluation, surgically resected with sentinel LN biopsy, were retrospectively studied. Mean and minimum ADC values of each lesion were measured and statistically compared between LN positive (n = 12) and LN negative (n = 32) groups. An ROC curve was drawn to determine the best cutoff value to differentiate LN status. Correlations between mean and minimum ADC values and the number of metastatic axillary LNs were investigated.

Results

Mean and minimum ADC values of breast lesions with positive LN were significantly lower than those with negative LN (mean 839.9 ± 110.9 vs. 1022.2 ± 250.0 × 10− 6 mm2/s, p = 0.027, minimum 696.7 ± 128.0 vs. 925.0 ± 257.6 × 10− 6 mm2/s, p = 0.004). The sensitivity and NPV using the best cutoff value from ROC using both mean and minimum ADC were 100%. AUC of the minimum ADC (0.784) was higher than that of the mean ADC (0.719). Statistically significant negative correlations were observed between both mean and minimum ADCs and number of positive LNs, with stronger correlation to minimum ADC than mean ADC.

Conclusions

The minimum ADC value of primary breast lesions predicts axillary LN metastasis in luminal A-like breast cancer with clinically negative nodes, with high sensitivity and high NPV.

Keywords

Breast cancer Axillary lymph node metastasis Magnetic resonance imaging Diffusion-weighed imaging 

Abbreviations

ADC

Apparent diffusion coefficient

DWI

Diffusion-weighted imaging

ER

Estrogen receptor

HER2

Human epidermal growth factor receptor 2

LN

Lymph node

MRI

Magnetic resonance imaging

NPV

Negative predictive value

PgR

Progesterone receptor

PPV

Positive predictive value

ROC

Receiver operating characteristic

Notes

Acknowledgements

This study was supported in part by Japan Society for the Promotion of Science (JSPS) KAKENHI (Grant numbers 26860962 and 17K10389) and supported by Global Station for Quantum Medical Science and Engineering, a project of Global Institution for Collaborative Research and Education at Hokkaido University.

Compliance with ethical standards

Conflict of interest

K. Kudo received research grants from Hitachi Ltd and Philips Medical systems, as well as lecture fees from Hitachi Ltd, GE Healthcare, Siemens Healthcare, and Toshiba Medical Systems. The other authors have no conflict of interest to declare.

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Copyright information

© The Japanese Breast Cancer Society 2019

Authors and Affiliations

  • Fumi Kato
    • 1
    Email author
  • Kohsuke Kudo
    • 1
    • 2
  • Hiroko Yamashita
    • 3
  • Motoi Baba
    • 3
  • Ai Shimizu
    • 4
  • Noriko Oyama-Manabe
    • 1
  • Rumiko Kinoshita
    • 5
  • Ruijiang Li
    • 6
  • Hiroki Shirato
    • 2
    • 7
  1. 1.Department of Diagnostic and Interventional RadiologyHokkaido University HospitalSapporoJapan
  2. 2.Global Station for Quantum Medical Science and Engineering, Global Institution for Collaborative Research and EducationHokkaido UniversitySapporoJapan
  3. 3.Department of Breast SurgeryHokkaido University HospitalSapporoJapan
  4. 4.Department of Surgical PathologyHokkaido University HospitalSapporoJapan
  5. 5.Department of Radiation OncologyHokkaido University HospitalSapporoJapan
  6. 6.Department of Radiation OncologyStanford University School of MedicinePalo AltoUSA
  7. 7.Department of Radiation MedicineHokkaido University Graduate School of MedicineSapporoJapan

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