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European Radiology

, Volume 29, Issue 2, pp 485–493 | Cite as

Risk stratification of ductal carcinoma in situ using whole-lesion histogram analysis of the apparent diffusion coefficient

  • Jin You KimEmail author
  • Jin Joo Kim
  • Ji Won Lee
  • Nam Kyung Lee
  • Geewon Lee
  • Taewoo Kang
  • Heesung Park
  • Yo Han Son
  • Robert Grimm
Breast
  • 297 Downloads

Abstract

Objectives

To investigate the value of the whole-lesion histogram apparent diffusion coefficient (ADC) metrics for differentiating low-risk from non-low-risk ductal carcinoma in situ (DCIS).

Methods

The authors identified 93 women with pure DCIS who had undergone preoperative MR imaging and diffusion-weighted imaging from 2013 to 2016. Histogram analysis of pixel-based ADC data of the whole tumour volume was performed by two radiologists using a software tool. The results were compared between low-risk and non-low-risk DCIS. Associations between quantitative ADC metrics and low-risk DCIS were evaluated by receiver operating characteristics (ROC) curve and logistic regression analyses.

Results

In whole-lesion histogram analysis, mean ADC and 5th, 50th and 95th percentiles of ADC were significantly different between low-risk and non-low-risk DCIS (1.522, 1.207, 1.536 and 1.854 × 10−3 mm2/s versus 1.270, 0.917, 1.261 and 1.657 × 10−3 mm2/s, respectively; p = .004, p = .003, p = .004 and p = .024, respectively). ROC curve analysis for differentiating low-risk DCIS revealed that 5th percentile ADC yielded the largest area under the curve (0.786) among the metrics of whole-lesion histogram, and the optimal cut-off point was 1.078 × 10−3 mm2/s (sensitivity 80%, specificity 75.9%, p = .001). Multivariate regression analysis revealed that a high 5th percentile of ADC (> 1.078× 10−3 mm2/s; odds ratio [OR] = 10.494, p = .016), small tumour size (≤ 2 cm; OR = 12.692, p = .008) and low Ki-67 status (< 14%; OR = 10.879, p = .046) were significantly associated with low-risk DCIS.

Conclusions

Assessment with whole-lesion histogram analysis of the ADC could be helpful for identifying patients with low-risk DCIS.

Key Points

• Whole-lesion histogram ADC metrics could be helpful for differentiating low-risk from non-low-risk DCIS.

• A high 5th percentile ADC was a significant factor associated with low-risk DCIS.

• Risk stratification of DCIS is important for their management.

Keywords

Breast neoplasm Magnetic resonance imaging Diffusion magnetic resonance imaging Ductal carcinoma in situ Risk 

Abbreviations

ADC

Apparent diffusion coefficient

AUC

Area under the curve

CI

Confidence interval

DCIS

Ductal carcinoma in situ

DWI

Diffusion-weighted imaging

ER

Oestrogen receptor

HER2

Human epidermal growth factor receptor 2

ICC

Intraclass correlation coefficient

OR

Odds ratio

PR

Progesterone receptor

ROC

Receiver operating characteristic

ROI

Regions of interest

Notes

Acknowledgements

This work was based on the Multi Parametric Analysis works-in-progress software package provided by Siemens Healthineers.

This study was presented at the 2017 RSNA Scientific Assembly.

Funding

The authors state that this work has not received any funding.

Compliance with ethical standards

Guarantor

The scientific guarantor of this publication is Jin You Kim.

Conflict of interest

The authors of this manuscript declare no relationships with any companies whose products or services may be related to the subject matter of the article.

Statistics and biometry

No complex statistical methods were necessary for this paper.

Informed consent

Written informed consent was waived by the institutional review board.

Ethical approval

Institutional review board approval was obtained.

Methodology

• retrospective

• observational

• performed at one institution

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Copyright information

© European Society of Radiology 2018

Authors and Affiliations

  1. 1.Department of Radiology, Pusan National University HospitalPusan National University School of Medicine and Medical Research InstituteBusanRepublic of Korea
  2. 2.Medical Research InstitutePusan National University School of MedicineBusanRepublic of Korea
  3. 3.Busan Cancer CenterPusan National University HospitalBusanRepublic of Korea
  4. 4.Siemens HealthineersSeoulKorea
  5. 5.Siemens HealthineersMR Application PredevelopmentErlangenGermany

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