Comparison of Prostate MRI Lesion Segmentation Agreement Between Multiple Radiologists and a Fully Automatic Deep Learning System.

Journal: RoFo : Fortschritte auf dem Gebiete der Rontgenstrahlen und der Nuklearmedizin
Published Date:

Abstract

PURPOSE:  A recently developed deep learning model (U-Net) approximated the clinical performance of radiologists in the prediction of clinically significant prostate cancer (sPC) from prostate MRI. Here, we compare the agreement between lesion segmentations by U-Net with manual lesion segmentations performed by different radiologists.

Authors

  • Patrick Schelb
    From the Department of Radiology (D.B., P.S., J.P.R., P.K., K.Y., M.F., H.P.S.), Division of Medical Image Computing (S.K., M.G., N.G., K.H.M.H.), Division of Statistics (M.W.), and Department of Medical Physics (T.A.K., F.D.), German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, Heidelberg 69120, Germany; German Cancer Consortium (DKTK), Heidelberg, Germany (D.B., H.P.S., K.H.M.H.); and Departments of Urology (J.P.R., B.H., M.H., B.A.H.) and Neuroradiology (P.K.), University of Heidelberg Medical Center, Heidelberg, Germany.
  • Anoshirwan Andrej Tavakoli
    Division of Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany.
  • Teeravut Tubtawee
    Division of Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany.
  • Thomas Hielscher
    Division of Biostatistics, German Cancer Research Center (DKFZ), Heidelberg, Germany.
  • Jan-Philipp Radtke
    Department of Urology, University of Heidelberg Medical Center, Heidelberg, Germany.
  • Magdalena Görtz
    Department of Urology, University of Heidelberg Medical Center, Heidelberg, Germany.
  • Viktoria Schütz
    Department of Urology, University of Heidelberg Medical Center, Heidelberg, Germany.
  • Tristan Anselm Kuder
    From the Department of Radiology (D.B., P.S., J.P.R., P.K., K.Y., M.F., H.P.S.), Division of Medical Image Computing (S.K., M.G., N.G., K.H.M.H.), Division of Statistics (M.W.), and Department of Medical Physics (T.A.K., F.D.), German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, Heidelberg 69120, Germany; German Cancer Consortium (DKTK), Heidelberg, Germany (D.B., H.P.S., K.H.M.H.); and Departments of Urology (J.P.R., B.H., M.H., B.A.H.) and Neuroradiology (P.K.), University of Heidelberg Medical Center, Heidelberg, Germany.
  • Lars Schimmöller
    University Dusseldorf, Medical Faculty, Department of Diagnostic and Interventional Radiology, Dusseldorf, Germany.
  • Albrecht Stenzinger
    From the Division of Radiology, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120 Heidelberg, Germany (P.S., J.P.R., P.K., H.P.S., D.B.); Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany (S.K., K.H.M.H.); Department of Urology, University of Heidelberg Medical Center, Heidelberg, Germany (J.P.R., M.H.); Division of Biostatistics, German Cancer Research Center (DKFZ), Heidelberg, Germany (M.W.); Department of Neuroradiology, University of Heidelberg Medical Center, Heidelberg, Germany (P.K.); Junior Group Medical Imaging and Radiology-Cancer Prevention, German Cancer Research Center (DKFZ), Heidelberg, Germany (S.B.); Division of Medical Physics, German Cancer Research Center (DKFZ), Heidelberg, Germany (T.A.K.); Institute of Pathology, University of Heidelberg Medical Center, Heidelberg, Germany (A.S.); and German Cancer Consortium (DKTK), Heidelberg, Germany (H.P.S., K.H.M.H., D.B.).
  • Markus Hohenfellner
    From the Department of Radiology (D.B., P.S., J.P.R., P.K., K.Y., M.F., H.P.S.), Division of Medical Image Computing (S.K., M.G., N.G., K.H.M.H.), Division of Statistics (M.W.), and Department of Medical Physics (T.A.K., F.D.), German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, Heidelberg 69120, Germany; German Cancer Consortium (DKTK), Heidelberg, Germany (D.B., H.P.S., K.H.M.H.); and Departments of Urology (J.P.R., B.H., M.H., B.A.H.) and Neuroradiology (P.K.), University of Heidelberg Medical Center, Heidelberg, Germany.
  • Heinz-Peter Schlemmer
    From the Department of Radiology (D.B., P.S., J.P.R., P.K., K.Y., M.F., H.P.S.), Division of Medical Image Computing (S.K., M.G., N.G., K.H.M.H.), Division of Statistics (M.W.), and Department of Medical Physics (T.A.K., F.D.), German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, Heidelberg 69120, Germany; German Cancer Consortium (DKTK), Heidelberg, Germany (D.B., H.P.S., K.H.M.H.); and Departments of Urology (J.P.R., B.H., M.H., B.A.H.) and Neuroradiology (P.K.), University of Heidelberg Medical Center, Heidelberg, Germany.
  • David Bonekamp
    From the Department of Radiology (D.B., P.S., J.P.R., P.K., K.Y., M.F., H.P.S.), Division of Medical Image Computing (S.K., M.G., N.G., K.H.M.H.), Division of Statistics (M.W.), and Department of Medical Physics (T.A.K., F.D.), German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, Heidelberg 69120, Germany; German Cancer Consortium (DKTK), Heidelberg, Germany (D.B., H.P.S., K.H.M.H.); and Departments of Urology (J.P.R., B.H., M.H., B.A.H.) and Neuroradiology (P.K.), University of Heidelberg Medical Center, Heidelberg, Germany.