Applications of artificial intelligence and advanced imaging in pediatric diffuse midline glioma.

Journal: Neuro-oncology
Published Date: Jul 30, 2025

Abstract

Diffuse midline glioma (DMG) is a rare, aggressive, and fatal tumor that largely occurs in the pediatric population. To improve outcomes, it is important to characterize DMGs, which can be performed via magnetic resonance imaging (MRI) assessment. Recently, artificial intelligence (AI) and advanced imaging have demonstrated their potential to improve the evaluation of various brain tumors, gleaning more information from imaging data than is possible without these methods. This narrative review compiles the existing literature on the intersection of MRI-based AI use and DMG tumors. The applications of AI in DMG revolve around classification and diagnosis, segmentation, radiogenomics, and prognosis/survival prediction. Currently published articles have utilized a wide spectrum of AI algorithms, from traditional machine learning and radiomics to neural networks. Challenges include the lack of cohorts of DMG patients with publicly available, multi-institutional, multimodal imaging and genomics datasets as well as the overall rarity of the disease. As an adjunct to AI, advanced MRI techniques, including diffusion-weighted imaging, perfusion-weighted imaging, and Magnetic Resonance Spectroscopy (MRS), as well as positron emission tomography (PET), provide additional insights into DMGs. Establishing AI models in conjunction with advanced imaging modalities has the potential to push clinical practice toward precision medicine.

Authors

  • Atlas Haddadi Avval
    School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
  • Suneel Banerjee
    Medical Scientist Training Program (MSTP), University of California San Diego (UCSD), San Diego, California, USA.
  • John Zielke
    Department of Radiation Oncology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.
  • Benjamin H Kann
    Artificial Intelligence in Medicine (AIM) Program, Harvard Medical School, Boston, Massachusetts, USA.
  • Sabine Mueller
    From the Artificial Intelligence in Medicine (AIM) Program, Mass General Brigham, Harvard Medical School, Boston, Mass (A.B., Z.Y., Y.Z., A.Z., H.H., R.C., H.J.W.L.A., B.H.K.); Department of Radiation Oncology (A.B., Z.Y., M.C.T., Y.Z., A.Z., H.H., R.C., K.X.L., D.A.H.K., H.J.W.L.A., B.H.K.) and Department of Radiology (H.J.W.L.A.), Brigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School, 75 Francis St, Boston, MA 02115; Department of Radiology, Boston Children's Hospital, Harvard Medical School, Boston, Mass (S.P.P., S.V., T.Y.P.); Department of Biostatistics and Computational Biology, Harvard T.H. Chan School of Public Health, Boston, Mass (P.J.C.); Center for Data-Driven Discovery in Biomedicine (D3b) (A.N., A.C.R.) and Department of Neurosurgery (A.C.R.), Children's Hospital of Philadelphia, Philadelphia, Pa; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pa (A.N.); Departments of Neurology, Pediatrics, and Neurologic Surgery, University of California, San Francisco, San Francisco, Calif (S.M.); and Department of Radiology and Nuclear Medicine, CARIM & GROW, Maastricht University, Maastricht, the Netherlands (H.J.W.L.A.).
  • Andreas M Rauschecker
    Department of Radiology, Hospital of the University of Pennsylvania, 3400 Spruce St, Philadelphia, PA 19104 (J.D.R., L.X., A.K., J.M.E., T.C., I.M.N., S.M., J.C.G.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (J.D.R., A.M.R.); Penn Image Computing and Science Laboratory, University of Pennsylvania, Philadelphia, Pa (X.L., J.W.); University of Pennsylvania Perelman School of Medicine, Philadelphia, Pa (M.T.D.); Mecklenburg Radiology Associates, Charlotte, NC (E.J.B.); Department of Radiology, University of Texas, Austin, Tex (R.N.B.); and Division of Nuclear Medicine and Clinical Molecular Imaging, Department of Radiology, University of Pennsylvania, Philadelphia, Pa (I.M.N.).

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