Prediction of pathologic complete response to neoadjuvant systemic therapy in triple negative breast cancer using deep learning on multiparametric MRI.

Journal: Scientific reports
PMID: 36670144

Abstract

Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer. Neoadjuvant systemic therapy (NAST) followed by surgery are currently standard of care for TNBC with 50-60% of patients achieving pathologic complete response (pCR). We investigated ability of deep learning (DL) on dynamic contrast enhanced (DCE) MRI and diffusion weighted imaging acquired early during NAST to predict TNBC patients' pCR status in the breast. During the development phase using the images of 130 TNBC patients, the DL model achieved areas under the receiver operating characteristic curves (AUCs) of 0.97 ± 0.04 and 0.82 ± 0.10 for the training and the validation, respectively. The model achieved an AUC of 0.86 ± 0.03 when evaluated in the independent testing group of 32 patients. In an additional prospective blinded testing group of 48 patients, the model achieved an AUC of 0.83 ± 0.02. These results demonstrated that DL based on multiparametric MRI can potentially differentiate TNBC patients with pCR or non-pCR in the breast early during NAST.

Authors

  • Zijian Zhou
    State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics and Center for Molecular Imaging and Translational Medicine, School of Public Health, Xiamen University, Xiamen, 361102, China.
  • Beatriz E Adrada
    Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
  • Rosalind P Candelaria
    Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
  • Nabil A Elshafeey
    Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
  • Medine Boge
    Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
  • Rania M Mohamed
    Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
  • Sanaz Pashapoor
    Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
  • Jia Sun
    State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, Hubei 430079, China.
  • Zhan Xu
    Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, 1400 Pressler St., Unit 1472, Houston, TX, 77030, USA.
  • Bikash Panthi
    Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, 1400 Pressler St., Unit 1472, Houston, TX, 77030, USA.
  • Jong Bum Son
    From the Department of Imaging Physics (Z.Z., J.W.S., J.B.S., J.M.), Medical Physics Graduate Program, UTHealth Graduate School of Biomedical Sciences (J.W.S.), Department of Diagnostic Radiology (J.M.J., M.K.G., M.M.C.), Department of Radiation Physics (T.M.B.), Department of Radiation Oncology (Y.W., J.L.), and Department of Cancer Systems Imaging (M.D.P.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030.
  • Mary S Guirguis
    Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
  • Miral M Patel
    Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
  • Gary J Whitman
    From the Department of Breast Imaging, University of Texas MD Anderson Cancer Center, Unit 1350, 1155 Pressler St, Houston, TX 77030-3721.
  • Tanya W Moseley
    From the Department of Breast Imaging, University of Texas MD Anderson Cancer Center, Unit 1350, 1155 Pressler St, Houston, TX 77030-3721.
  • Marion E Scoggins
    Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
  • Jason B White
    Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
  • Jennifer K Litton
    Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
  • Vicente Valero
    Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
  • Kelly K Hunt
  • Debu Tripathy
    Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
  • Wei Yang
    Key Laboratory of Structure-Based Drug Design and Discovery (Shenyang Pharmaceutical University), Ministry of Education, School of Traditional Chinese Materia Medica, Shenyang Pharmaceutical University, Wenhua Road 103, Shenyang 110016, PR China. Electronic address: 421063202@qq.com.
  • Peng Wei
    School of Basic Medicine, Guizhou University of Traditional Chinese Medicine, Guiyang, Guizhou, China.
  • Clinton Yam
    Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
  • Mark D Pagel
    Department of Cancer Systems Imaging, University of Texas MD Anderson Cancer Center, Houston, Texas.
  • Gaiane M Rauch
    Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX, USA. gmrauch@mdanderson.org.
  • Jingfei Ma
    Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA.

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