Purpose <p>This study aimed to investigate the difference in T1, T2, and proton density (PD) values derived from synthetic magnetic resonance imaging (MRI) across various meningioma subtypes and their potential as imaging biomarkers for the World Health Organization (WHO) grade classification of meningioma.</p> Materials and methods <p>This study retrospectively analyzed the data of 100 consecutive meningioma cases. Across subtypes and WHO grades, intratumoral T1, T2, PD, and apparent diffusion coefficient (ADC) values, along with tumor volume, were measured and compared, and the discriminative performance of each parameter was evaluated using the area under the receiver operating characteristic curve (AUC). Simple and multiple regression analyses were conducted to assess the associations between quantitative imaging parameters and atypical pathological features (4 ≥ mitotic findings/high power field; brain invasion; increased cellularity; small cells with high nuclear-to-cytoplasmic ratio; prominent nucleoli; sheeting; necrosis).</p> Results <p>Among all subtypes, angiomatous, microcystic, and metaplastic meningioma demonstrated remarkable high T1 and T2 values. The AUCs for differentiating these subtypes from other subtypes were 0.97 for T1 value and 0.99 for T2 value. Volume (<i>p</i> &lt; 0.001), T1 value (<i>p</i> &lt; 0.001), T2 value (<i>p</i> = 0.002), and ADC value (<i>p</i> = 0.035) were significantly higher in high grade meningioma than low grade meningioma, with an AUC of 0.83 achieved by combining volume, T1, and ADC value. Multiple regression analysis revealed that volume was significantly associated with necrosis (<i>p</i> = 0.018), whereas T1 and T2 values were significantly associated with sheeting (<i>p</i> = 0.047 and 0.025 for T1 and T2).</p> Conclusion <p>T1 and T2 mappings may serve as useful quantitative imaging biomarkers for meningioma grading.</p>

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Preoperative prediction of meningioma grade based on synthetic MRI quantitative T1 and T2 mapping

  • Tsubasa Nakano,
  • Junki Kamizono,
  • Tomohito Hasegawa,
  • Masanori Nakajo,
  • Kiyohisa Kamimura,
  • Ryota Nakanosono,
  • Hiroaki Nagano,
  • Koji Takumi,
  • Ryoji Yamagishi,
  • Fumitaka Ejima,
  • Fumiko Kanzaki,
  • Nayuta Higa,
  • Hajime Yonezawa,
  • Mari Kirishima,
  • Ikumi Kitazono,
  • Takashi Yoshiura

摘要

Purpose

This study aimed to investigate the difference in T1, T2, and proton density (PD) values derived from synthetic magnetic resonance imaging (MRI) across various meningioma subtypes and their potential as imaging biomarkers for the World Health Organization (WHO) grade classification of meningioma.

Materials and methods

This study retrospectively analyzed the data of 100 consecutive meningioma cases. Across subtypes and WHO grades, intratumoral T1, T2, PD, and apparent diffusion coefficient (ADC) values, along with tumor volume, were measured and compared, and the discriminative performance of each parameter was evaluated using the area under the receiver operating characteristic curve (AUC). Simple and multiple regression analyses were conducted to assess the associations between quantitative imaging parameters and atypical pathological features (4 ≥ mitotic findings/high power field; brain invasion; increased cellularity; small cells with high nuclear-to-cytoplasmic ratio; prominent nucleoli; sheeting; necrosis).

Results

Among all subtypes, angiomatous, microcystic, and metaplastic meningioma demonstrated remarkable high T1 and T2 values. The AUCs for differentiating these subtypes from other subtypes were 0.97 for T1 value and 0.99 for T2 value. Volume (p < 0.001), T1 value (p < 0.001), T2 value (p = 0.002), and ADC value (p = 0.035) were significantly higher in high grade meningioma than low grade meningioma, with an AUC of 0.83 achieved by combining volume, T1, and ADC value. Multiple regression analysis revealed that volume was significantly associated with necrosis (p = 0.018), whereas T1 and T2 values were significantly associated with sheeting (p = 0.047 and 0.025 for T1 and T2).

Conclusion

T1 and T2 mappings may serve as useful quantitative imaging biomarkers for meningioma grading.