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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.).

Investigative Radiology
|December 17, 2024
PubMed
Summary

This study compared brain MRI metastasis detection using low-dose contrast agents and artificial images. While one reader showed higher sensitivity with true images, both methods performed similarly for larger metastases.

Keywords:
convolutional neural networkdeep learningdose reductiongadolinium-based contrast agentlow-dosemagnetic resonance imagingmetastasis detectionvirtual contrast

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Area of Science:

  • Radiology
  • Medical Imaging
  • Artificial Intelligence

Background:

  • Reducing gadolinium-based contrast agents in brain MRI is crucial.
  • Small lesion detection is a key challenge in brain MRI.

Purpose of the Study:

  • To compare metastasis detection sensitivity and precision using true contrast-enhanced T1-weighted (T1w) images versus artificial T1w images synthesized from low-dose brain MRI.
  • To evaluate the efficacy of deep learning in generating artificial images for metastasis detection.

Main Methods:

  • Prospective, multicenter study with 917 participants undergoing brain MRI.
  • Comparison of low-dose (0.033 mmol/kg) and full-dose (0.1 mmol/kg) T1w images.
  • Two neuroradiologists assessed metastasis detection on true and artificial T1w images; a reference reader confirmed findings.

Main Results:

  • One reader demonstrated significantly higher sensitivity using true images (78.4%) compared to artificial images (60.8%).
  • No significant difference in sensitivity was observed for metastases ≥5 mm.
  • False-positive findings did not significantly differ between true and artificial images.

Conclusions:

  • Deep learning-synthesized artificial images show potential for certain diagnostic tasks in brain MRI.
  • Low-dose contrast imaging may be suitable for less demanding diagnostic tasks than metastasis detection.
  • Further research is needed to optimize artificial image generation for sensitive metastasis detection.