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Advances in differentiating intracranial isolated fibromas from different grades of meningiomas based on diffusion-weighted imaging
WEI Lingzhen  ZENG Qingshi  CHEN Jinming  LI Meilin  LIU Jiahao  WANG Huaizhen 

Cite this article as: WEI L Z, ZENG Q S, CHEN J M, et al. Advances in differentiating intracranial isolated fibromas from different grades of meningiomas based on diffusion-weighted imaging[J]. Chin J Magn Reson Imaging, 2024, 15(8): 207-211. DOI:10.12015/issn.1674-8034.2024.08.033.


[Abstract] Intracranial solitary fibrous tumor (SFT) has the characteristics of easy recurrence and high probability of intraoperative hemorrhage. It must be actively carried out preoperative and intraoperative preparations and systematic postoperative treatment. In contrast, meningiomas, which are similar in imaging manifestations with SFTs, are mostly benign, less prone to intraoperative hemorrhage, and have a better prognosis. So, it is crucial to differentiate between SFTs and meningiomas before surgery or treatment accurately. Therefore, accurate differentiation between SFTs and meningiomas before surgery or treatment is crucial. This article aims to systematically review the research progress and pathophysiological mechanisms of magnetic resonance diffusion-weighted imaging in distinguishing intracranial SFT from high-grade meningiomas, low-grade meningiomas, and angiomatous meningiomas. It thoroughly explores the advantages and value of this sequence in improving diagnostic accuracy, providing reference ideas for subsequent studies. Additionally, it aims to offer effective assistance to clinicians in preoperative evaluation and intraoperative decision-making, with the goal of improving patient prognosis and quality of life.
[Keywords] intracranial solitary fibrous tumor；meningiomas；diffusion weighted imaging；magnetic resonance imaging；differential diagnosis

WEI Lingzhen1, 2   ZENG Qingshi2   CHEN Jinming2, 3   LI Meilin2   LIU Jiahao2   WANG Huaizhen4  

1 School of Clinical Medicine, Jining Medical University, Jining 272067, China

2 Department of Radiology, the First Affiliated Hospital of Shandong First Medical University, Jinan 250014, China

3 Shandong University Cheeloo College of Medicine, Jinan 250012, China

4 The First Clinical Medical College of Shandong University of Traditional Chinese Medicine, Jinan 250011, China

Corresponding author: ZENG Q S, E-mail: zengqingshi@sina.com

Conflicts of interest   None.

Received  2024-03-14
Accepted  2024-08-07
DOI: 10.12015/issn.1674-8034.2024.08.033
Cite this article as: WEI L Z, ZENG Q S, CHEN J M, et al. Advances in differentiating intracranial isolated fibromas from different grades of meningiomas based on diffusion-weighted imaging[J]. Chin J Magn Reson Imaging, 2024, 15(8): 207-211. DOI:10.12015/issn.1674-8034.2024.08.033.

[1]
LOUIS D N, PERRY A, REIFENBERGER G, et al. The 2016 World Health Organization Classification of Tumors of the Central Nervous System: a summary[J]. Acta Neuropathol, 2016, 131(6): 803-820. DOI: 10.1007/s00401-016-1545-1.
[2]
EL-ABTAH M E, MURAYI R, LEE J, et al. Radiological differentiation between intracranial meningioma and solitary fibrous tumor/hemangiopericytoma: A systematic literature review[J]. World Neurosurg, 2023, 170: 68-83. DOI: 10.1016/j.wneu.2022.11.062.
[3]
SHIN D W, KIM J H, CHONG S, et al. Intracranial solitary fibrous tumor/hemangiopericytoma: tumor reclassification and assessment of treatment outcome via the 2016 WHO classification[J]. J Neurooncol, 2021, 154(2): 171-178. DOI: 10.1007/s11060-021-03733-7.
[4]
KINSLOW C J, RAE A I, KUMAR P, et al. Risk Stratification for Management of Solitary Fibrous Tumor/Hemangiopericytoma of the Central Nervous System[J/OL]. Cancers (Basel), 2023, 15(3): 876 [2024-03-14]. http://dx.doi.org/10.3390/cancers15030876. DOI: 10.3390/cancers15030876.
[5]
GOLDBRUNNER R, STAVRINOU P, JENKINSON M D, et al. EANO guideline on the diagnosis and management of meningiomas[J]. Neuro Oncol, 2021, 23(11): 1821-1834. DOI: 10.1093/neuonc/noab150.
[6]
SATGUNASEELAN L, SY J, SHIVALINGAM B, et al. Prognostic and predictive biomarkers in central nervous system tumours: the molecular state of play[J]. Pathology, 2024, 56(2): 158-169. DOI: 10.1016/j.pathol.2023.11.003.
[7]
NAIK V, PAHWA B, SINGH M, et al. Correlation based on the WHO grading with tumor control and clinical outcome following gamma knife radiosurgery in meningiomas[J]. Neurol India, 2023, 71(Supplement): S140-S145. DOI: 10.4103/0028-3886.373628.
[8]
CHEN Z, YE N, JIANG N, et al. Deep learning model for intracranial hemangiopericytoma and meningioma classification[J/OL]. Front Oncol, 2022, 12: 839567 [2024-03-14]. http://dx.doi.org/10.3389/fonc.2022.839567. DOI: 10.3389/fonc.2022.839567.
[9]
FAN Y, LIU P, LI Y, et al. Non-invasive preoperative imaging differential diagnosis of intracranial hemangiopericytoma and angiomatous meningioma: A novel developed and validated multiparametric MRI-based clini-radiomic model[J/OL]. Front Oncol, 2021, 11: 792521 [2024-03-14]. http://dx.doi.org/10.3389/fonc.2021.792521. DOI: 10.3389/fonc.2021.792521.
[10]
KONG X, LUO Y, LI Y, et al. Preoperative prediction and histological stratification of intracranial solitary fibrous tumours by machine-learning models[J/OL]. Clin Radiol, 2023, 78(3): e204-e213 [2024-03-14]. http://dx.doi.org/10.1016/j.crad.2022.10.013. DOI: 10.1016/j.crad.2022.10.013.
[11]
FOLPE A L. "Hey! Whatever happened to hemangiopericytoma and fibrosarcoma?" An update on selected conceptual advances in soft tissue pathology which have occurred over the past 50 years[J]. Hum Pathol, 2020, 95: 113-136. DOI: 10.1016/j.humpath.2019.10.001.
[12]
KAZAZIAN K, DEMICCO E G, DE PERROT M, et al. Toward better understanding and management of solitary fibrous tumor[J]. Surg Oncol Clin N Am, 2022, 31(3): 459-483. DOI: 10.1016/j.soc.2022.03.009.
[13]
TAO X, YAN X, ZHANG Y, et al. Intracranial solitary fibrous tumor mimicking meningioma[J/OL]. J Craniofac Surg, 2023, 34(7): e688-e690 [2024-03-14]. http://dx.doi.org/10.1097/scs.0000000000009598. DOI: 10.1097/scs.0000000000009598.
[14]
ZHOU J L, LIU J L, ZHANG J, et al. Thirty-nine cases of intracranial hemangiopericytoma and anaplastic hemangiopericytoma: a retrospective review of MRI features and pathological findings[J]. Eur J Radiol, 2012, 81(11): 3504-3510. DOI: 10.1016/j.ejrad.2012.04.034.
[15]
ZHAO H Y, NI C, LUO D D, et al. The value of MRI in the grading diagnosis of intracranial solitary fibrous tumor/hemangiopericytoma[J]. J Mod Oncol, 2021, 29(20): 3632-3635. DOI: 10.3969/j.issn.1672-4992.2021.20.026.
[16]
DAVIDSON C. Histopathologic and molecular evaluation of meningioma[J]. Neurosurg Clin N Am, 2023, 34(3): 311-318. DOI: 10.1016/j.nec.2023.02.001.
[17]
BI W L, SANTAGATA S. Skull base tumors: neuropathology and clinical implications[J]. Neurosurgery, 2022, 90(3): 243-261. DOI: 10.1093/neuros/nyab209.
[18]
WANG B L, ZHAO W, DING S, et al. Study on the application value of MRI texture analysis technique in distinguishing solitary fibrous tumor (SFT) and angiomatous meningioma (AM)[J]. Chin J CT & MRI, 2022, 20(3): 14-17, 20. DOI: 10.3969/j.issn.1672-5131.2022.03.005.
[19]
LOUIS D N, PERRY A, WESSELING P, et al. The 2021 WHO Classification of Tumors of the Central Nervous System: a summary[J]. Neuro Oncol, 2021, 23(8): 1231-1251. DOI: 10.1093/neuonc/noab106.
[20]
XIAO D, SHI J, ZHOU M, et al. Tumor volume and the dural tail sign enable the differentiation of intracranial solitary fibrous tumor/hemangiopericytoma from high-grade meningioma[J/OL]. Clin Neurol Neurosurg, 2021, 207: 106769 [2024-03-14]. http://dx.doi.org/10.1016/j.clineuro.2021.106769. DOI: 10.1016/j.clineuro.2021.106769.
[21]
HOSAINEY S A M, BOUGET D, REINERTSEN I, et al. Are there predilection sites for intracranial meningioma? A population-based atlas[J]. Neurosurg Rev, 2022, 45(2): 1543-1552. DOI: 10.1007/s10143-021-01652-9.
[22]
ZHANG H M, ZHAO W, LI Z F, et al. Multifactorial analysis of MR imaging characteristics of intracranial solitary fibrous tumor and meningioma[J]. J Clin Radiol, 2018, 37(9): 1436-1440. DOI: 10.13437/j.cnki.jcr.2018.09.006.
[23]
YU Y, GU F, LUO Y L, et al. The role of tumor parenchyma and brain cortex signal intensity ratio in differentiating solitary fibrous tumors and meningiomas[J/OL]. Discov Oncol, 2024, 15(1): 32 [2024-03-14]. http://dx.doi.org/10.1007/s12672-024-00883-8. DOI: 10.1007/s12672-024-00883-8.
[24]
WIJETHILAKE N, MACCORMAC O, VERCAUTEREN T, et al. Imaging biomarkers associated with extra-axial intracranial tumors: a systematic review[J/OL]. Front Oncol, 2023, 13: 1131013 [2024-03-14]. http://dx.doi.org/10.3389/fonc.2023.1131013. DOI: 10.3389/fonc.2023.1131013.
[25]
SHROT S, KERPEL A, BELENKY J, et al. MR imaging characteristics and ADC histogram metrics for differentiating molecular subgroups of pediatric low-grade gliomas[J]. AJNR Am J Neuroradiol, 2022, 43(9): 1356-1362. DOI: 10.3174/ajnr.A7614.
[26]
MAGILL S T, NGUYEN M P, AGHI M K, et al. Postoperative diffusion-weighted imaging and neurological outcome after convexity meningioma resection[J]. J Neurosurg, 2021, 135(4): 1008-1015. DOI: 10.3171/2020.8.Jns193537.
[27]
LIU X, HAN T, WANG Y, et al. Utility of apparent diffusion coefficient histogram analysis in differentiating microcystic meningioma from intracranial solitary fibrous tumor[J/OL]. World Neurosurg, 2023: S1878-8750(23)00842-2 [2024-03-14]. http://dx.doi.org/10.1016/j.wneu.2023.06.073. DOI: 10.1016/j.wneu.2023.06.073.
[28]
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]. Eur J Radiol, 2019, 112: 186-191. DOI: 10.1016/j.ejrad.2019.01.023.
[29]
BAILO M, GAGLIARDI F, BOARI N, et al. Meningioma and other meningeal tumors[J]. Adv Exp Med Biol, 2023, 1405: 73-97. DOI: 10.1007/978-3-031-23705-8_3.
[30]
CHEN F, SHEN X J, MA L, et al. Comparison study of imaging features and differential diagnostic value of ADC values between intracranial hemangiopericytoma and atypical meningioma[J]. Chin J Magn Reson Imaging, 2016, 7(11): 813-818. DOI: 10.12015/issn.1674-8034.2016.11.004.
[31]
WANG X, DAI Y, LIN H, et al. Shape and texture analyses based on conventional MRI for the preoperative prediction of the aggressiveness of pituitary adenomas[J]. Eur Radiol, 2023, 33(5): 3312-3321. DOI: 10.1007/s00330-023-09412-7.
[32]
LIU J J, HOU M L, WU J, et al. Value of whole-volume apparent diffusion coefficient histogram in distinguishing intracranial solitary fibrous tumor/hemangiopericytoma from atypical meningioma[J]. J Clin Radiol, 2021, 40(10): 1856-1860. DOI: 10.13437/j.cnki.jcr.2021.10.004.
[33]
CHEN X T, SU C Q, PAN T, et al. Application value of combined DWI texture analysis and conventional MRI in distinguishing intracranial solitary fibrous tumor/hemangiopericytoma from atypical meningioma[J]. J Med Imaging, 2022, 32(5): 742-747.
[34]
OHBA S, MURAYAMA K, NISHIYAMA Y, et al. Clinical and radiographic features for differentiating solitary fibrous tumor/hemangiopericytoma from meningioma[J/OL]. World Neurosurg, 2019, 130: e383-e392 [2024-03-14]. http://dx.doi.org/10.1016/j.wneu.2019.06.094. DOI: 10.1016/j.wneu.2019.06.094.
[35]
TSAI Y T, HUNG K C, SHIH Y J, et al. Preoperative apparent diffusion coefficient values for differentiation between low and high grade meningiomas: An updated systematic review and meta-analysis[J/OL]. Diagnostics (Basel), 2022, 12(3): 630 [2024-03-14]. http://dx.doi.org/10.3390/diagnostics12030630. DOI: 10.3390/diagnostics12030630.
[36]
CAO T, JIANG R, ZHENG L, et al. T1 and ADC histogram parameters may be an in vivo biomarker for predicting the grade, subtype, and proliferative activity of meningioma[J]. Eur Radiol, 2023, 33(1): 258-269. DOI: 10.1007/s00330-022-09026-5.
[37]
ZHANG T, YU J M, WANG Y Q, et al. WHO grade I meningioma subtypes: MRI features and pathological analysis[J]. Life Sci, 2018, 213: 50-56. DOI: 10.1016/j.lfs.2018.08.061.
[38]
LIU X, WANG Y, WEI J, et al. Role of diffusion-weighted imaging in differentiating angiomatous meningioma from atypical meningioma[J/OL]. Clin Neurol Neurosurg, 2022, 221: 107406 [2024-03-14] . http://dx.doi.org/10.1016/j.clineuro.2022.107406. DOI: 10.1016/j.clineuro.2022.107406.
[39]
LI X, LU Y, XIONG J, et al. Presurgical differentiation between malignant haemangiopericytoma and angiomatous meningioma by a radiomics approach based on texture analysis[J]. J Neuroradiol, 2019, 46(5): 281-287. DOI: 10.1016/j.neurad.2019.05.013.
[40]
ROGN W, ZHANG X Y. MRI differentiation diagnosis of hemangiopericytoma and angioma-type meningioma[J]. Journal of Practical Radiology, 2022, 38(2): 185-187, 199. DOI: 10.3969/j.issn.1002-1671.2022.02.002.
[41]
KANAZAWA T, MINAMI Y, JINZAKI M, et al. Preoperative prediction of solitary fibrous tumor/hemangiopericytoma and angiomatous meningioma using magnetic resonance imaging texture analysis[J/OL]. World Neurosurg, 2018, 120: e1208-e1216 [2024-03-14]. http://dx.doi.org/10.1016/j.wneu.2018.09.044. DOI: 10.1016/j.wneu.2018.09.044.
[42]
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.
[43]
SCHMEEL F C. Variability in quantitative diffusion-weighted MR imaging (DWI) across different scanners and imaging sites: is there a potential consensus that can help reducing the limits of expected bias?[J]. Eur Radiol, 2019, 29(5): 2243-2245. DOI: 10.1007/s00330-018-5866-4.
[44]
EL-ALI A M, AGARWAL V, THOMAS A, et al. Clinical metric for differentiating intracranial hemangiopericytomas from meningiomas using diffusion weighted MRI[J]. Clin Imaging, 2019, 54: 1-5. DOI: 10.1016/j.clinimag.2018.10.018.
[45]
CHEN T, JIANG B, ZHENG Y, et al. Differentiating intracranial solitary fibrous tumor/hemangiopericytoma from meningioma using diffusion-weighted imaging and susceptibility-weighted imaging[J]. Neuroradiology, 2020, 62(2): 175-184. DOI: 10.1007/s00234-019-02307-9.
[46]
WANG J, HU C H, WANG X M. Differentiating intracranial solitary fibrous tumor/hemangiopericytoma and angioma-type meningioma based on ADC grayscale histogram analysis[J]. Radiol Prac, 2020, 35(2): 154-158. DOI: 10.13609/j.cnki.1000-0313.2020.02.006.
[47]
HE W L, LI X D, GUO L J, et al. ADC Whole-Tumor Histogram Analysis for Discriminating Intracranial Solitary Fibrous Tumor/Hemangiopericytoma from Angioma-Type Meningioma[J]. Radiol Prac, 2020, 35(4): 456-461. DOI: 10.13609/j.cnki.1000-0313.2020.04.012.
[48]
WEI W X, REN Y D, FU S L, et al. The diagnostic value of MRI in discriminating intracranial solitary fibrous tumor/hemangiopericytoma from angioma-type meningioma[J]. J Med Imaging, 2022, 32(2):190-194.
[49]
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 [2024-03-14]. http://dx.doi.org/10.3389/fonc.2023.1155162. DOI: 10.3389/fonc.2023.1155162.
[50]
WEI J, LI L, HAN Y, et al. Accurate preoperative distinction of intracranial hemangiopericytoma from meningioma using a multihabitat and multisequence-based radiomics diagnostic technique[J/OL]. Front Oncol, 2020, 10: 534 [2024-03-14]. http://dx.doi.org/10.3389/fonc.2020.00534. DOI: 10.3389/fonc.2020.00534.
[51]
WU H L, SU W J, LI X X, et al. Clinical Characteristics and Postoperative Recurrence Factors of Central Nervous System Solitary Fibrous Tumors[J]. Chinese Journal of Neurology and Psychiatry Disorders, 2023, 49(2): 85-91. DOI: 10.3969/j.issn.1002-0152.2023.02.003.
[52]
PENG Z, WANG Y, WANG Y, et al. Hemangiopericytoma/solitary fibrous tumor of the cranial base: a case series and literature review[J/OL]. BMC Surg, 2022, 22(1): 289 [2024-03-14]. http://dx.doi.org/10.1186/s12893-022-01718-5. DOI: 10.1186/s12893-022-01718-5.
[53]
SEO I, KIM Y S, KIM H S, et al. Hemangiopericytoma of the posterior fossa: a case report and review of the literature[J]. Brain Tumor Res Treat, 2013, 1(2): 95-98. DOI: 10.14791/btrt.2013.1.2.95.

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