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Portrait of Sophia Zackrisson. Photo

Sophia Zackrisson

Research group manager, Principal investigator, Professor, MD

Portrait of Sophia Zackrisson. Photo

Prediction of Ki-67 expression of breast cancer with a multiparametric model using MRI parameters from ultrafast DCE-MRI and DWI

Author

  • Akane Ohashi
  • Masako Kataoka
  • Mami Iima
  • Maya Honda
  • Rie Ota
  • Yuta Urushibata
  • Marcel Dominik Nickel
  • Masakazu Toi
  • Sophia Zackrisson
  • Yuji Nakamoto

Editor

  • Hilde Bosmans
  • Nicholas Marshall
  • Chantal Van Ongeval

Summary, in English

The purpose of this study is to investigate the prediction of Ki-67 expression of breast cancers using MRI parameters from ultrafast (UF) DCE-MRI, DWI, T2WI, and the lesion size. Breast MRI was performed with a 3T scanner using dedicated breast coils. UF DCE-MRI was obtained using Compressed Sensing-VIBE (prototype sequence). As a kinetic parameter of UF DCE-MRI, maximum slope (MS) was defined as percentage relative enhancement (%/s), and time to enhance (TTE) was defined as the time interval between the aorta and lesion enhancement. The apparent diffusion coefficient (ADC) was derived from DWI. Two radiologists measured each MR parameter, and inter-rater agreement was evaluated. Univariate and multivariate logistic regression analyses were perfomed to predict low Ki-67 (< 14%) and high Ki-67 (≥ 14%) expression using MS, TTE, ADC, T2-signal intensity (SI), and lesion size. The significant parameters (p-values of < 0.05) were selected for the prediction model, and the diagnostic performance of the model was evaluated using ROC curve analysis. A total of 191 invasive carcinomas defined as mass lesions were included (72 low Ki-67/ 119 high Ki-67 lesions). The inter-rater agreements of all parameters were excellent. After univariate and multivariate logistic regression analysis, ADC and lesion size remained significant parameters. Using these significant parameters, the multi-parametric prediction model yielded an AUC of 0.77 (95%CI of 0.70-0.84) (sensitivity 72.3%, specificity 76.4%, and PPV 83.5%, and NPV 62.5%). DWI parameter (ADC) may be more valuable than UF DCE-MRI parameters (MS, TTE) to predict high Ki-67 in mass-shaped invasive breast carcinoma.

Department/s

  • Radiology Diagnostics, Malmö
  • LUCC: Lund University Cancer Centre
  • LTH Profile Area: Photon Science and Technology
  • EpiHealth: Epidemiology for Health

Publishing year

2022

Language

English

Publication/Series

Proceedings of SPIE - The International Society for Optical Engineering

Volume

12286

Document type

Conference paper

Publisher

SPIE

Topic

  • Radiology and Medical Imaging

Keywords

  • ADC
  • Breast Cancer
  • Breast MRI
  • DWI
  • Image based estimation of prognostic factor
  • Ki-67
  • UF DCE-MRI

Conference name

16th International Workshop on Breast Imaging, IWBI 2022

Conference date

2022-05-22 - 2022-05-25

Conference place

Leuven, Belgium

Status

Published

Research group

  • Radiology Diagnostics, Malmö

ISBN/ISSN/Other

  • ISSN: 0277-786X
  • ISSN: 1996-756X
  • ISBN: 9781510655843