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Research ArticleBrain Tumor Imaging

Preoperative Assessment of Meningioma Consistency Using a Combination of MR Elastography and DTI

Yuting Bao, Suhao Qiu, Zhenyu Li, Guangzhong Yang, Yuan Feng and Qi Yue
American Journal of Neuroradiology November 2024, 45 (11) 1755-1761; DOI: https://doi.org/10.3174/ajnr.A8385
Yuting Bao
aFrom the Department of Neurosurgery (Y.B., Z.L., Q.Y.), Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
bNational Center for Neurological Disorders (Y.B., Z.L., Q.Y.), Shanghai, China
cShanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration (Y.B., Z.L., Q.Y.), Fudan University, Shanghai, China
dNeurosurgical Institute of Fudan University (Y.B., Z.L., Q.Y.), Shanghai, China
eShanghai Clinical Medical Center of Neurosurgery (Y.B., Z.L., Q.Y.), Shanghai, China
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Suhao Qiu
fSchool of Biomedical Engineering (S.Q., G.Y., Y.F.), Shanghai Jiao Tong University, Shanghai, China
gInstitute of Medical Robotics (S.Q., G.Y., Y.F.), Shanghai Jiao Tong University, Shanghai, China
hNational Engineering Research Center of Advanced Magnetic Resonance Technologies for Diagnosis and Therapy (NERC-AMRT) (S.Q., G.Y., Y.F.), Shanghai Jiao Tong University, Shanghai, China
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Zhenyu Li
aFrom the Department of Neurosurgery (Y.B., Z.L., Q.Y.), Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
bNational Center for Neurological Disorders (Y.B., Z.L., Q.Y.), Shanghai, China
cShanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration (Y.B., Z.L., Q.Y.), Fudan University, Shanghai, China
dNeurosurgical Institute of Fudan University (Y.B., Z.L., Q.Y.), Shanghai, China
eShanghai Clinical Medical Center of Neurosurgery (Y.B., Z.L., Q.Y.), Shanghai, China
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Guangzhong Yang
fSchool of Biomedical Engineering (S.Q., G.Y., Y.F.), Shanghai Jiao Tong University, Shanghai, China
gInstitute of Medical Robotics (S.Q., G.Y., Y.F.), Shanghai Jiao Tong University, Shanghai, China
hNational Engineering Research Center of Advanced Magnetic Resonance Technologies for Diagnosis and Therapy (NERC-AMRT) (S.Q., G.Y., Y.F.), Shanghai Jiao Tong University, Shanghai, China
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Yuan Feng
fSchool of Biomedical Engineering (S.Q., G.Y., Y.F.), Shanghai Jiao Tong University, Shanghai, China
gInstitute of Medical Robotics (S.Q., G.Y., Y.F.), Shanghai Jiao Tong University, Shanghai, China
hNational Engineering Research Center of Advanced Magnetic Resonance Technologies for Diagnosis and Therapy (NERC-AMRT) (S.Q., G.Y., Y.F.), Shanghai Jiao Tong University, Shanghai, China
iDepartment of Radiology (Y.F.), Ruijin Hospital affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
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  • ORCID record for Yuan Feng
Qi Yue
aFrom the Department of Neurosurgery (Y.B., Z.L., Q.Y.), Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
bNational Center for Neurological Disorders (Y.B., Z.L., Q.Y.), Shanghai, China
cShanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration (Y.B., Z.L., Q.Y.), Fudan University, Shanghai, China
dNeurosurgical Institute of Fudan University (Y.B., Z.L., Q.Y.), Shanghai, China
eShanghai Clinical Medical Center of Neurosurgery (Y.B., Z.L., Q.Y.), Shanghai, China
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Abstract

BACKGROUND AND PURPOSE: Preoperative assessment of meningioma consistency is beneficial for optimizing surgical strategy and prognosis of patients. We aim to develop a noninvasive prediction model for meningioma consistency utilizing MR elastography and DTI.

MATERIALS AND METHODS: Ninety-four patients (52 ± 22 years old, 69 women, 25 men) diagnosed with meningioma were recruited in the study. Each patient underwent preoperative T1WI, T2WI, DTI, and MR elastography. Combined MR elastography–DTI model was developed based on multiple logistic regression. Intraoperative tumor descriptions served as clinical criteria for evaluating meningioma consistency. The diagnostic efficacy in determining meningioma consistency was evaluated by using a receiver operating characteristic curve. Further validation was conducted in 27 stereotactic biopsies by using indentation tests and underlying mechanism was investigated by histologic analysis.

RESULTS: Among all the imaging modalities, MR elastography demonstrated the highest efficacy with the shear modulus magnitude (|G*|) achieving an area under the curve (AUC) of 0.81 (95% CI: 0.699–0.929). When combined with DTI, the diagnostic accuracy further increased (AUC: 0.88, 95% CI: 0.784–0.971), surpassing any technique alone. Indentation measurement based on stereotactic biopsies further demonstrated that the MR elastography–DTI model was suitable for predicting intratumor consistency. Histologic analysis suggested that meningioma consistency may be correlated with tumor cell density and fibrous content.

CONCLUSIONS: The MR elastography–DTI combined model is effective in noninvasive prediction of meningioma consistency.

ABBREVIATIONS:

AUC
area under the curve
FA
fractional anisotropy
MD
mean diffusivity
ROC
receiver operating characteristic
SI
signal intensity
|G*|
shear modulus magnitude
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Cite this article
Yuting Bao, Suhao Qiu, Zhenyu Li, Guangzhong Yang, Yuan Feng, Qi Yue
Preoperative Assessment of Meningioma Consistency Using a Combination of MR Elastography and DTI
American Journal of Neuroradiology Nov 2024, 45 (11) 1755-1761; DOI: 10.3174/ajnr.A8385

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Meningioma Consistency via MR Elastography
Yuting Bao, Suhao Qiu, Zhenyu Li, Guangzhong Yang, Yuan Feng, Qi Yue
American Journal of Neuroradiology Nov 2024, 45 (11) 1755-1761; DOI: 10.3174/ajnr.A8385
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