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Updated: Jun 4, 2025
Modeling Brain Metastases Through Intracranial Injection and Magnetic Resonance Imaging
Published on: June 7, 2020
Metastasis Detection Using True and Artificial T1-Weighted Postcontrast Images in Brain MRI
Robert Haase1, Thomas Pinetz, Erich Kobler
1From the Department of Diagnostic and Interventional Neuroradiology, University Hospital Bonn, Venusberg-Campus 1, Bonn, Germany (R.H., E.K., Z.B., D.P., R.C., A.R., K.D.); Institute of Applied Mathematics, Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn, Germany (T.P., A.E.); Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA (D.P.); Division of Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany (D.P., H.-P.S.); Department of Diagnostic and Interventional Radiology With Nuclear Medicine, Thoraxklinik at University Hospital Heidelberg, Heidelberg, Germany (M.F.-D., K.S., G.H., C.P.H.); Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany (M.F.-D.); Department of Diagnostic and Interventional Radiology, University Hospital Heidelberg, Heidelberg, Germany (V.W., C.P.H.); Translational Lung Research Center Heidelberg, Member of the German Center of Lung Research (DZL), Heidelberg, Germany (C.P.H.); Praxisnetz, Radiology and Nuclear Medicine, Bonn, Germany (M.V.); Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Venusberg-Campus 1, Bonn, Germany (J.A.L.); Chair of Civil Law, Data Protection Law, Law of Data Economy, Digitalization and AI Law, Faculty of Law, Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn, Germany (L.S.-R.); and German Center for Neurodegenerative Diseases (DZNE), Helmholtz Association of German Research Centers, Venusberg-Campus 1, Bonn, Germany (A.R., K.D.).
Objectives:
Small lesions are the limiting factor for reducing gadolinium-based contrast agents in brain magnetic resonance imaging (MRI). The purpose of this study was to compare the sensitivity and precision in metastasis detection on true contrast-enhanced T1-weighted (T1w) images and artificial images synthesized by a deep learning method using low-dose images.
Materials And Methods:
In this prospective, multicenter study (5 centers, 12 scanners), 917 participants underwent brain MRI between October 2021 and March 2023 including T1w low-dose (0.033 mmol/kg) and full-dose (0.1 mmol/kg) images. Forty participants with metastases or unremarkable brain findings were evaluated in a reading (mean age ± SD, 54.3 ± 15.1 years; 24 men). True and artificial T1w images were assessed for metastases in random order with 4 weeks between readings by 2 neuroradiologists. A reference reader reviewed all data to confirm metastases. Performances were compared using mid- P McNemar tests for sensitivity and Wilcoxon signed rank tests for false-positive findings.
Results:
The reference reader identified 97 metastases. The sensitivity of reader 1 did not differ significantly between sequences (sensitivity [precision]: true, 66.0% [98.5%]; artificial, 61.9% [98.4%]; P = 0.38). With a lower precision than reader 1, reader 2 found significantly more metastases using true images (sensitivity [precision]: true, 78.4% [87.4%]; artificial, 60.8% [80.8%]; P < 0.001). There was no significant difference in sensitivity for metastases ≥5 mm. The number of false-positive findings did not differ significantly between sequences.
Conclusions:
One reader showed a significantly higher overall sensitivity using true images. The similar detection performance for metastases ≥5 mm is promising for applying low-dose imaging in less challenging diagnostic tasks than metastasis detection.
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