Deep learning aided preoperative diagnosis of primary central nervous system lymphoma

Paul Vincent Naser; Miriam Cindy Maurer; Maximilian Fischer; Kianush Karimian-Jazi; Chiraz Ben-Salah; Awais Akbar Bajwa; Martin Jakobs; Christine Jungk; Jessica Jesser; Martin Bendszus; Klaus Maier-Hein; Sandro M Krieg; Peter Neher; Jan-Oliver Neumann

doi:10.1016/j.isci.2024.109023

Deep learning aided preoperative diagnosis of primary central nervous system lymphoma

iScience. 2024 Jan 24;27(2):109023. doi: 10.1016/j.isci.2024.109023. eCollection 2024 Feb 16.

Authors

Paul Vincent Naser^{1

2

3

4}, Miriam Cindy Maurer^{5

6}, Maximilian Fischer^{2

5

7}, Kianush Karimian-Jazi^{2

8}, Chiraz Ben-Salah^{2

9}, Awais Akbar Bajwa^{1

2}, Martin Jakobs^{1

2

3}, Christine Jungk^{1

2}, Jessica Jesser^{2

8}, Martin Bendszus^{2

8}, Klaus Maier-Hein^{5

7

10

11

4}, Sandro M Krieg^{1

2}, Peter Neher^{5

7

11}, Jan-Oliver Neumann^{1

2

3}

Affiliations

¹ Heidelberg University Hospital, Department of Neurosurgery, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany.
² Heidelberg University, Medical Faculty, Grabengasse 1, 69117 Heidelberg, Germany.
³ Heidelberg University Hospital, Division of Stereotactic Neurosurgery, Department of Neurosurgery, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany.
⁴ AI Health Innovation Cluster, German Cancer Research Center (DKFZ), Heidelberg, Germany.
⁵ German Cancer Research Center (DKFZ) Heidelberg, Division of Medical Image Computing, Germany, Im Neuenheimer Feld 280, 69120 Heidelberg, Germany.
⁶ Department of Medical Informatics, University Medical Center Göttingen, Von-Siebold-Straße 3, 37075 Göttingen, Germany.
⁷ German Cancer Consortium (DKTK), partner site Heidelberg, Heidelberg, Germany.
⁸ Heidelberg University Hospital, Department of Neuroradiology, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany.
⁹ Department of Diagnostic and Interventional Radiology, University Hospital Heidelberg, Im Neuenheimer Feld 110, 69120 Heidelberg, Germany.
¹⁰ National Center for Tumor Diseases (NCT), NCT Heidelberg, a partnership between DKFZ and the University Medical Center Heidelberg, 69120 Heidelberg, Germany.
¹¹ Pattern Analysis and Learning Group, Department of Radiation Oncology, Heidelberg University Hospital, 69120 Heidelberg, Germany.

Abstract

The preoperative distinction between glioblastoma (GBM) and primary central nervous system lymphoma (PCNSL) can be difficult, even for experts, but is highly relevant. We aimed to develop an easy-to-use algorithm, based on a convolutional neural network (CNN) to preoperatively discern PCNSL from GBM and systematically compare its performance to experienced neurosurgeons and radiologists. To this end, a CNN-based on DenseNet169 was trained with the magnetic resonance (MR)-imaging data of 68 PCNSL and 69 GBM patients and its performance compared to six trained experts on an external test set of 10 PCNSL and 10 GBM. Our neural network predicted PCNSL with an accuracy of 80% and a negative predictive value (NPV) of 0.8, exceeding the accuracy achieved by clinicians (73%, NPV 0.77). Combining expert rating with automated diagnosis in those cases where experts dissented yielded an accuracy of 95%. Our approach has the potential to significantly augment the preoperative radiological diagnosis of PCNSL.

Keywords: Diagnostic technique in health technology; Health sciences; Health technology; Internal medicine; Medical specialty; Medicine; Oncology; Radiology.

Associated data

figshare/10.6084/m9.figshare.24986142