Int J Med Sci 2022; 19(7):1110-1117. doi:10.7150/ijms.73319 This issue Cite

Research Paper

The value of quantitative magnetic resonance imaging signal intensity in distinguishing between spinal meningiomas and schwannomas

Nguyen Duy Hung1,2,#✉, Le Thanh Dung2,3, Dang Khanh Huyen1, Ngo Quang Duy4, Dong-Van He5, Nguyen Minh Duc6,#

1. Department of Radiology, Hanoi Medical University, Hanoi, Vietnam.
2. Department of Radiology, Viet Duc Hospital, Hanoi, Vietnam.
3. Department of Radiology, VNU University of Medicine and Pharmacy, Vietnam National University, Hanoi, Vietnam.
4. Department of Radiology, Ha Giang General Hospital, Ha Giang, Vietnam.
5. Department of Neurosurgery, Viet Duc Hospital, Hanoi, Vietnam.
6. Department of Radiology, Pham Ngoc Thach University of Medicine, Ho Chi Minh City, Vietnam.
# These authors contributed equally to this article as co-first authors

Citation:
Hung ND, Dung LT, Huyen DK, Duy NQ, He DV, Duc NM. The value of quantitative magnetic resonance imaging signal intensity in distinguishing between spinal meningiomas and schwannomas. Int J Med Sci 2022; 19(7):1110-1117. doi:10.7150/ijms.73319. https://www.medsci.org/v19p1110.htm
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Abstract

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Background: Prior studies have suggested a number of the subjective visual characteristics that help distinguish between spinal meningiomas and schwannomas on magnetic resonance imaging and computed tomography; however, objective quantification of the signal intensity can be useful information. This study assessed whether quantitative magnetic resonance imaging (MRI) signal intensity (SI) measurements could distinguish intradural-extramedullary schwannomas from meningiomas.

Methods: From July 2019 to September 2021, 54 patients with intradural-extramedullary tumors (37 meningiomas and 17 schwannomas) underwent surgery, and tumors were verified pathologically. Defined regions of interest were used to quantify SI values on T1- (T1W) and T2-weighted images (T2W). Receiver operating characteristic curve analysis was used to obtain cutoff values and calculate the area under the curve (AUC), sensitivity (SE), specificity (SP), positive predictive value (PPV), and negative predictive value (NPV).

Results: Both Maximum (T2max) and mean (T2mean) T2W SI values demonstrated outstanding (AUC: 0.91) abilities to differentiate meningiomas from schwannomas with Se, Sp, PPV, and NPV values of 94.6%, 70.6%, 87.5%, and 85.7%, respectively, for T2max and 81.1%, 88.2%, 93.8%, and 68.2% for T2mean. The maximum SI value on contrast-enhanced T1W (T1CEmax) and the T2W tumor: fat SI ratio (rTF) demonstrated acceptable abilities (AUC: 0.73 and 0.79, respectively) to differentiate meningiomas from schwannomas with Se, Sp, PPV, and NPV values of 94.6%, 70.6%, 87.5%, and 85.7%, respectively, for T1CEmax and 81.1%, 88.2%, 93.8%, and 68.2% for rTF.

Conclusions: Quantitative SI values (T2max, T2mean, T2min, T1CEmax, rTF) can be used to differentiate intradural-extramedullary schwannomas from meningiomas.

Keywords: spinal tumor, meningioma, schwannoma, quantitative measurement, magnetic resonance imaging


Citation styles

APA
Hung, N.D., Dung, L.T., Huyen, D.K., Duy, N.Q., He, D.V., Duc, N.M. (2022). The value of quantitative magnetic resonance imaging signal intensity in distinguishing between spinal meningiomas and schwannomas. International Journal of Medical Sciences, 19(7), 1110-1117. https://doi.org/10.7150/ijms.73319.

ACS
Hung, N.D.; Dung, L.T.; Huyen, D.K.; Duy, N.Q.; He, D.V.; Duc, N.M. The value of quantitative magnetic resonance imaging signal intensity in distinguishing between spinal meningiomas and schwannomas. Int. J. Med. Sci. 2022, 19 (7), 1110-1117. DOI: 10.7150/ijms.73319.

NLM
Hung ND, Dung LT, Huyen DK, Duy NQ, He DV, Duc NM. The value of quantitative magnetic resonance imaging signal intensity in distinguishing between spinal meningiomas and schwannomas. Int J Med Sci 2022; 19(7):1110-1117. doi:10.7150/ijms.73319. https://www.medsci.org/v19p1110.htm

CSE
Hung ND, Dung LT, Huyen DK, Duy NQ, He DV, Duc NM. 2022. The value of quantitative magnetic resonance imaging signal intensity in distinguishing between spinal meningiomas and schwannomas. Int J Med Sci. 19(7):1110-1117.

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