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• Clinical Article •
Differential diagnosis of angiomatous meningioma and atypical meningioma based on contrast enhanced T1-weighted images histogram analysis
HAN Tao  LIU Xianwang  JIANG Jian  ZHOU Fengyu  DONG Wenjie  ZHANG Bin  ZHOU Junlin 

Cite this article as: HAN T, LIU X W, JIANG J, et al. Differential diagnosis of angiomatous meningioma and atypical meningioma based on contrast enhanced T1-weighted images histogram analysis[J]. Chin J Magn Reson Imaging, 2024, 15(3): 37-42. DOI:10.12015/issn.1674-8034.2024.03.007.


[Abstract] Objective To investigate the value of structural MRI features and enhanced T1-weighted images histogram analysis in the differential diagnosis of atypical meningioma (AtM) and angiomatous meningioma (AnM).Materials and Methods The clinical, imaging and pathological data of AtM (n=40) and AnM (n=30) were collected retrospectively. The tumor was delineated layer-by-layer on axial enhanced T1-weighted images by MaZda software and histogram parameters of tumor enhancement areas were obtained. Structural MRI characteristics were compared using the chi-square test or Fisher's exact test. Histogram parameters were compared between the two groups using independent samples t-tests or Mann-Whitney U-tests, and diagnostic efficacy between the two groups was assessed by receiver operating characteristic (ROC) curves.Results The incidence of tumor necrosis was significantly higher in the AtM group (75.0%) than in the AnM group (36.7%) (P=0.001). The mean (P=0.003), 1st percentile (P<0.001), 10th percentile (P=0.001), and 50th percentile (P=0.009) of the AnM were greater than those of the AtM. ROC curve analysis showed that tumor necrosis + combined histogram parameters had the optimal differential diagnostic efficacy between the two, with area under the curve, sensitivity, specificity, accuracy, positive predictive value, and negative predictive value of 0.858 (0.753-0.930), 95.00%, 66.67%, 82.86%, 79.20%, and 90.90%.Conclusions The conventional MRI features and histogram analysis based on enhanced T1-weighted images is helpful in the preoperative non-invasive differentiation of AnM and AtM, of which the diagnostic efficacy is highest in the tumor necrosis + combined histogram parameters.
[Keywords] meningioma；angiomatous meningioma；atypical meningioma；magnetic resonance imaging；histogram analysis

HAN Tao1, 2, 3, 4   LIU Xianwang1, 2, 3, 4   JIANG Jian1, 2, 3, 4   ZHOU Fengyu1, 2, 3, 4   DONG Wenjie1, 2, 3, 4   ZHANG Bin1, 2, 3, 4   ZHOU Junlin1, 3, 4*  

1 Department of Radiology, Lanzhou University Second Hospital, Lanzhou 730030, China

2 Second Clinical School, Lanzhou University, Lanzhou 730030, China

3 Key Laboratory of Medical Imaging of Gansu Province, Lanzhou 730030, China

4 Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou 730030, China

Corresponding author: ZHOU J L, E-mail: lzuzjl601@163.com

Conflicts of interest   None.

Received  2023-09-12
Accepted  2024-01-31
DOI: 10.12015/issn.1674-8034.2024.03.007
Cite this article as: HAN T, LIU X W, JIANG J, et al. Differential diagnosis of angiomatous meningioma and atypical meningioma based on contrast enhanced T1-weighted images histogram analysis[J]. Chin J Magn Reson Imaging, 2024, 15(3): 37-42. DOI:10.12015/issn.1674-8034.2024.03.007.

[1]
ZHANG J, YAO K, LIU P, et al. A radiomics model for preoperative prediction of brain invasion in meningioma non-invasively based on MRI: A multicentre study[J/OL]. EBioMedicine, 2020, 58: 102933 [2023-09-12]. https://pubmed.ncbi.nlm.nih.gov/32739863/. DOI: 10.1016/j.ebiom.2020.102933.
[2]
OSTROM Q T, CIOFFI G, GITTLEMAN H, et al. CBTRUS Statistical Report: Primary Brain and Other Central Nervous System Tumors Diagnosed in the United States in 2012-2016[J/OL]. Neuro Oncol, 2019, 21(Suppl 5): v1-v100 [2023-09-12]. https://pubmed.ncbi.nlm.nih.gov/31675094/. DOI: 10.1093/neuonc/noz150.
[3]
RAMAN S G, PRAKASH P, SUMIT J, et al. Clinical outcome and recurrence after meningioma surgery: An experience from a developing country, Nepal[J/OL]. World Neurosurg, 2021, 148: e138-e144 [2023-09-12].https://pubmed.ncbi.nlm.nih.gov/33359878/. DOI: 10.1016/j.wneu.2020.12.079.
[4]
HORTOBÁGYI T, BENCZE J, VARKOLY G, et al. Meningioma recurrence[J]. Open Med (Wars), 2016, 11(1): 168-173. DOI: 10.1515/med-2016-0032.
[5]
HAN T, ZHANG J, LIU X, et al. Differentiating atypical meningioma from anaplastic meningioma using diffusion weighted imaging[J/OL]. Clin Imaging, 2022, 82: 237-243 [2023-09-12]. https://pubmed.ncbi.nlm.nih.gov/32739863/. DOI: 10.1016/j.clinimag.2021.12.004.
[6]
OGASAWARA C, PHILBRICK B D, ADAMSON D C. Meningioma: A review of epidemiology, pathology, diagnosis, treatment, and future directions[J/OL]. Biomedicines, 2021, 9(3): 319 [2023-09-12]. https://pubmed.ncbi.nlm.nih.gov/33801089/. DOI: 10.3390/biomedicines9030319.
[7]
KIM L. A narrative review of targeted therapies in meningioma[J/OL]. Chin Clin Oncol, 2020, 9(6): 76 [2023-09-12]. https://pubmed.ncbi.nlm.nih.gov/33353364/. DOI: 10.21037/cco-2020-mbt-01.
[8]
PELLERINO A, BRUNO F, PALMIERO R, et al. Clinical significance of molecular alterations and systemic therapy for meningiomas: Where do we stand?[J/OL]. Cancers, 2022, 14(9): 2256. [2023-09-12]. https://pubmed.ncbi.nlm.nih.gov/35565385/. DOI: 10.3390/cancers14092256.
[9]
HE W, XIAO X, LI X, et al. Whole-tumor histogram analysis of apparent diffusion coefficient in differentiating intracranial solitary fibrous tumor/hemangiopericytoma from angiomatous meningioma[J/OL]. Eur J Radiol, 2019, 112: 186-191 [2023-09-12]. https://pubmed.ncbi.nlm.nih.gov/30777209/. DOI: 10.1016/j.ejrad.2019.01.023.
[10]
GIHR G A, HORVATH D, KOHLHLF P, et al. Histogram profiling of postcontrast T1-weighted MRI gives valuable insights into tumor biology and enables prediction of growth kinetics and prognosis in meningiomas[J]. Transl Oncol, 2018, 11(4): 957-961. DOI: 10.1016/j.tranon.2018.05.009.
[11]
CHEN X, ZHANG G Q, RUAN X H, et al. Post-contrast enhanced T1WI histogram analysis in prediction the status of glioblastoma multiforme[J/OL]. Radiology Practice, 2020, 35(4):452-455. DOI: 10.13609/j.cnki.1000-0313.2020.04.011.
[12]
ZHANG S, LI Y L, HUANG S. Post contrast-enhanced T1WI histogram analysis for differentiating glioblastom from solitary brain metastasis[J]. Chin J Med Imaging, 2017, 25(2): 89-92. DOI: 10.3969/j.issn.1005-5185.2017.02.003.
[13]
MEYER H J, WIENKE A, SUROV A. ADC values of benign and high grade meningiomas and associations with tumor cellularity and proliferation - A systematic review and meta-analysis[J/OL]. J Neurol Sci, 2020, 415: 116975 [2023-09-12]. https://pubmed.ncbi.nlm.nih.gov/32535250/. DOI: 10.1016/j.jns.2020.116975.
[14]
WANG G, ZHOU J. The value of whole-volume apparent diffusion coefficient histogram analysis in preoperatively distinguishing intracranial solitary fibrous tumor and transitional meningioma[J/OL]. Front Oncol, 2023, 13: 1155162 [2023-09-12]. https://pubmed.ncbi.nlm.nih.gov/37260978/. DOI: 10.3389/fonc.2023.1155162.
[15]
LIU X, HAN T, WANG Y, et al. Differentiating angiomatous meningioma from atypical meningioma using histogram analysis of apparent diffusion coefficient maps[J]. Quant Imaging Med Surg, 2023, 13(7): 4160-4170. DOI: 10.21037/qims-22-1224.
[16]
ZHANG X L, LIU X W, WEI J Y, et al. The value of MRI diffusion-weighted imaging for differential diagnosis of angiomatous meningioma and atypical meningioma[J]. J Chin Clin Med Imag, 2023, 34(9): 615-619. DOI: 10.12117/jccmi.2023.09.002.
[17]
GOLDBRUNNER R, MINNITI G, PREUSSER M, et al. EANO guidelines for the diagnosis and treatment of meningiomas[J/OL]. Lancet Oncol, 2016, 17(9): e383-e391 [2023-09-12]. https://pubmed.ncbi.nlm.nih.gov/27599143/. DOI: 10.1016/S1470-2045(16)30321-7.
[18]
LIU X, DENG J, SUN Q, et al. Differentiation of intracranial solitary fibrous tumor/hemangiopericytoma from atypical meningioma using apparent diffusion coefficient histogram analysis[J]. Neurosurg Rev, 2022, 45(3): 2449-2456. DOI: 10.1007/s10143-022-01771-x.
[19]
XUE C, ZHOU Q, ZHANG P, et al. MRI histogram analysis of tumor-infiltrating CD8+ T cell levels in patients with glioblastoma[J/OL]. Neuroimage Clin, 2023, 37: 103353 [2023-09-12]. https://pubmed.ncbi.nlm.nih.gov/9958466/. DOI: 10.1016/j.nicl.2023.103353.
[20]
SUROV A, HAMERLA G, MEYER H J, et al. Whole lesion histogram analysis of meningiomas derived from ADC values. Correlation with several cellularity parameters, proliferation indexKI 67, nucleic content, and membrane permeability[J/OL]. Magn Reson Imaging. 2018, 51: 158-162 [2023-09-12]. https://pubmed.ncbi.nlm.nih.gov/29782920/. DOI: 10.1016/j.mri.2018.05.009.
[21]
NAGANO H, SAKAI K, TAZOE J, et al. Whole-tumor histogram analysis of DWI and QSI for differentiating between meningioma and schwannoma: a pilot study[J]. Jpn J Radiol, 2019, 37(10): 694-700. DOI: 10.1007/s11604-019-00862-y.
[22]
OZTURK M, POLAT A V, SELCUK M B. Whole-lesion ADC histogram analysis versus single-slice ADC measurement for the differentiation of benign and malignant soft tissue tumors[J/OL]. Eur J Radiol, 2021, 143: 109934 [2023-09-12]. https://pubmed.ncbi.nlm.nih.gov/34500411/. DOI: 10.1016/j.ejrad.2021.109934.
[23]
PAYABVASH S, TIHAN T, CHA S. Volumetric voxelwise apparent diffusion coefficient histogram analysis for differentiation of the fourth ventricular tumors[J]. Neuroradiol J, 2018, 31(6): 554-564. DOI: 10.1177/1971400918800803.
[24]
LI X, MIAO Y, HAN L, et al. Meningioma grading using conventional MRI histogram analysis based on 3D tumor measurement[J/OL]. Eur J Radiol, 2019, 110: 45-53 [2023-09-12]. https://pubmed.ncbi.nlm.nih.gov/30599872/. DOI: 10.1016/j.ejrad.2018.11.016.
[25]
LIU X W, XIE Y J, HAN T, et al. Value of preoperative prediction of meningioma brain invasion with whole-tumor histogram analysis based on enhanced T1WI[J]. J Chin Clin Med Imaging, 2022, 33(10): 691-695. DOI: 10.12117/jccmi.2022.10.002.
[26]
WANG B L, ZHAO W, DING S, et al. Study on the value of MRI texture analysis in the differential diagnosis of solitary fibroma (SFT) and hemangiomatous meningioma (AM)[J]. Chin J CT & MRI, 2022, 20(3): 14-17, 20. DOI: 10.3969/j.issn.1672-5131.2022.03.005.
[27]
ZHANG R, BAI Y, WEI W, et al. Whole-tumor histogram analysis of enhanced T1-weighted images for differentiating diagnosis meningioma from choroid plexus papilloma in ventricle[J]. Chin J Magn Reson Imaging, 2020, 11(3): 171-176. DOI: 10.12015/issn.1674-8034.2020.03.003.
[28]
HAN L, WANG S, MIAO Y, et al. MRI texture analysis based on 3D tumor measurement reflects the IDH1 mutations in gliomas - A preliminary study[J/OL]. Eur J Radiol, 2019, 112: 169-179 [2023-09-12]. https://pubmed.ncbi.nlm.nih.gov/30777207/. DOI: 10.1016/j.ejrad.2019.01.025.
[29]
XUE C, LIU S, DENG J, et al. Apparent diffusion coefficient histogram analysis for the preoperative evaluation of Ki-67 expression in pituitary macroadenoma[J]. Clin Neuroradiol, 2022, 32(1): 269-276. DOI: 10.1007/s00062-021-01134-x.
[30]
YANG H, LIU X, JIANG J, et al. Apparent diffusion coefficient histogram analysis to preoperative evaluate intracranial solitary fibrous tumor: Relationship to Ki-67 proliferation index[J/OL]. Clin Neurol Neurosurg, 2022, 220: 107364 [2023-09-12]. https://pubmed.ncbi.nlm.nih.gov/35872434/. DOI: 10.1016/j.clineuro.2022.107364.
[31]
SCHOB S, MEYER H J, DIECKOW J, et al. Histogram analysis of diffusion weighted imaging at 3T is useful for prediction of lymphatic metastatic spread, proliferative activity, and cellularity in thyroid cancer[J/OL]. Int J Mol Sci, 2017, 18(4): 821 [2023-09-12]. https://pubmed.ncbi.nlm.nih.gov/28417929/. DOI: 10.3390/ijms18040821.

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