Intra-axial primary brain tumor differentiation: comparing large language models on structured MRI reports vs. radiologists on images - Takeaways - MDSpire

Intra-axial primary brain tumor differentiation: comparing large language models on structured MRI reports vs. radiologists on images

  • By

  • Takeshi Nakaura

  • Hiroyuki Uetani

  • Naofumi Yoshida

  • Naoki Kobayashi

  • Yasunori Nagayama

  • Masafumi Kidoh

  • Jun-Ichiro Kuroda

  • Akitake Mukasa

  • Toshinori Hirai

  • August 22, 2025

  • 0 min

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  • 1

    Intra-axial primary brain tumors present diagnostic challenges due to overlapping imaging characteristics, making accurate diagnosis critical in neuroradiology.

  • 2

    Structured MRI reports provide standardized descriptions that may enhance AI-assisted diagnosis of brain tumors, serving as a proxy for image interpretation.

  • 3

    This study evaluated the performance of large language models (LLMs) in differentiating intra-axial primary brain tumors using structured MRI reports.

  • 4

    A total of 137 patients with surgically confirmed intra-axial primary brain tumors were included in the analysis after a rigorous selection process.

  • 5

    Various prominent LLMs were tested for their ability to generate ranked differential diagnoses based on structured MRI report data.

Original Source(s)

Intra-axial primary brain tumor differentiation: comparing large language models on structured MRI reports vs. radiologists on images

  • by Takeshi Nakaura, Hiroyuki Uetani, Naofumi Yoshida, Naoki Kobayashi, Yasunori Nagayama, Masafumi Kidoh, Jun-Ichiro Kuroda, Akitake Mukasa, Toshinori Hirai

  • August 22, 2025

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