Evidence map›Paper›PMID 41457092›Full record

ArticleNeuroradiology2026

Relaxometry assessment of meningioma consistency using quantitative magnetic resonance imaging.

Kazufumi Kikuchi, Osamu Togao, Koji Yamashita, Daichi Momosaka, Masaoki Kusunoki, Daisuke Kuga, Ryusuke Hatae, Yutaka Fujioka, Ryosuke Otsuji, Fumiya Narutomi and 2 more

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Article in Neuroradiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

12 authors.

Kazufumi KikuchiDepartment of Clinical Radiology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan. kikuchi.kazufumi.953@m.kyushu-u.ac.jp.
Osamu TogaoDepartment of Molecular Imaging & Diagnosis, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.
Koji YamashitaDepartment of Clinical Radiology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.
Daichi MomosakaDepartment of Clinical Radiology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.
Masaoki KusunokiDepartment of Clinical Radiology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.
Daisuke KugaDepartment of Neurosurgery, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.
Ryusuke HataeDepartment of Neurosurgery, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.
Yutaka FujiokaDepartment of Neurosurgery, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.
Ryosuke OtsujiDepartment of Neurosurgery, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.
Fumiya NarutomiDepartment of Anatomic Pathology, Pathological Sciences, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.
Koji YoshimotoDepartment of Neurosurgery, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.
Kousei IshigamiDepartment of Clinical Radiology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo determine whether relaxometry assessment using synthetic MRI (SyMRI) can predict meningioma consistency.

methodsEighteen patients with histologically confirmed meningioma were included, and all patients underwent quantitative MRI on a 3T MRI system using a 2D multi-dynamic multi-cho sequence. Quantitative MRI software version 11.3 (SyntheticMR AB, Linköping, Sweden) was used to generate quantitative maps of T1, T2 relaxation times and proton density (PD). Regions of interest were manually placed over all tumor slices to evaluate three parameters (T1, T2, PD). Comparing with the conventional method, relative values of the tumor-to-thalamus signal intensity ratio on the non-contrast T1-weighted image (T1R) and T2-weighted image (T2R) and apparent diffusion coefficients generated from b-values (0 and 1000 s/mm

resultsSoft meningiomas showed significantly longer T1 and T2 relaxation times and higher PDs than hard meningiomas (median value, p-value: 2701 vs. 1721 ms, p = 0.0009 for T1; 111 vs. 94 ms, p = 0.0047 for T2; 92 vs. 85%, p = 0.0092 for PD, respectively). The 90

conclusionRelaxometry assessment offers a reliable method for predicting meningioma consistency that can optimize surgical planning.

Indexed as

Magnetic Resonance ImagingMeningeal NeoplasmsMeningiomaAdultAgedFemaleHumansImage Interpretation, Computer-AssistedMaleMiddle AgedMeningioma consistencyRelaxation timeSynthetic MRI

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PMID41457092

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.