Differentiation of the Intradural Extramedullary Spinal Tumors, Schwannomas, and Meningiomas Utilizing the Contrast Ratio as a Quantitative Magnetic Resonance Imaging Method

被引:1
|
作者
Nakamae, Toshio [1 ]
Kamei, Naosuke [1 ]
Tamura, Takayuki [2 ]
Maruyama, Toshiaki [1 ]
Nakao, Kazuto [1 ]
Farid, Fadlyansyah [1 ,3 ]
Fukui, Hiroki [1 ]
Adachi, Nobuo [1 ]
机构
[1] Hiroshima Univ, Grad Sch Biomed & Hlth Sci, Dept Orthopaed Surg, Hiroshima, Japan
[2] Hiroshima Univ Hosp, Dept Clin Support, Hiroshima, Japan
[3] Hasanuddin Univ, Fac Med, Dept Orthopaed & Traumatol, Makassar, Indonesia
关键词
Contrast ratio; Intradural extramedullary spinal tumor; Magnetic resonance imaging; Meningioma; Schwannoma; DESCRIPTIVE EPIDEMIOLOGY; DIFFUSION TENSOR; CORD; DIAGNOSIS; RESECTION; MENINGES;
D O I
10.1016/j.wneu.2024.05.106
中图分类号
R74 [神经病学与精神病学];
学科分类号
摘要
BACKGROUND: Schwannomas and meningiomas are the most common intradural extramedullary spinal tumors; however, differentiating between them using magnetic resonance imaging (MRI) is a frequent challenge. In this study, we aimed to investigate the use of the contrast ratio (CR) as a quantitative MRI method in the differentiation of schwannomas and meningiomas. METHODS: We analyzed the data of patients with intradural extramedullary spinal tumors who underwent surgery and were diagnosed with either schwannomas or meningiomas by histopathological analysis. Regions of interest were set for the entire spinal tumor on T2weighted sagittal MRI. To obtain the CR values of spinal tumors (CR (tumor )), we used the signal intensity (SI) values of the tumor (SI tumor ) and spinal cord (SI cord ) according to the following formula: [CR tumor [ (SI( tumo)r-SI cord )/ (SI D-tumor SI cord )]. RESULTS: The study included 50 patients (23 males and 27 females) with a mean age of 61.5 years old (11- 85 years old). Histopathological analysis revealed that 33 and 17 patients were diagnosed with schwannomas and meningiomas, respectively. The mean CR values of the schwannomas and meningiomas were 0.3040 +/- 0.1386 and 0.0173 +/- 0.1929, respectively. The CR value of the schwannomas was statistically significantly higher than that of meningiomas ( P < 0.01). The cutoff CR value obtained from the receiver operating characteristic curve was 0.143, with a specificity and sensitivity of 90.9% and 88.2%, respectively. Furthermore, the value for the area u nder the receiver operating characteristic curve was 0.925 (95% confidence interval: 0.852- 0.998). CONCLUSIONS: The evaluation of CRs by using MRI to distinguish between schwannomas and meningiomas is a beneficial quantitative tool.
引用
收藏
页码:E320 / E325
页数:6
相关论文
共 40 条
  • [31] Automatic removal of large blood vasculature for objective assessment of brain tumors using quantitative dynamic contrast-enhanced magnetic resonance imaging
    Kesari, Anshika
    Yadav, Virendra Kumar
    Gupta, Rakesh Kumar
    Singh, Anup
    NMR IN BIOMEDICINE, 2024, 37 (11)
  • [32] Quantitative Evaluation of Diffusion and Dynamic Contrast-Enhanced Magnetic Resonance Imaging for Differentiation Between Primary Central Nervous System Lymphoma and Glioblastoma
    Lu, Shanshan
    Wang, Siqi
    Gao, Qianqian
    Zhou, Minlin
    Li, Yang
    Cao, Peng
    Hong, Xunning
    Shi, Haibin
    JOURNAL OF COMPUTER ASSISTED TOMOGRAPHY, 2017, 41 (06) : 898 - 903
  • [33] Benign or Malignant Characterization of Soft-Tissue Tumors by Using Semiquantitative and Quantitative Parameters of Dynamic Contrast-Enhanced Magnetic Resonance Imaging
    Zhang, Yu
    Yue, Bin
    Zhao, Xiaodan
    Chen, Haisong
    Sun, Lingling
    Zhang, Xuexi
    Hao, Dapeng
    CANADIAN ASSOCIATION OF RADIOLOGISTS JOURNAL-JOURNAL DE L ASSOCIATION CANADIENNE DES RADIOLOGISTES, 2020, 71 (01): : 92 - 99
  • [34] Differentiation between orbital malignant and benign tumors using intravoxel incoherent motion diffusion-weighted imaging Correlation with dynamic contrast-enhanced magnetic resonance imaging
    Xu, Xiao-Quan
    Hu, Hao
    Su, Guo-Yi
    Liu, Hu
    Wu, Fei-Yun
    Shi, Hai-Bin
    MEDICINE, 2019, 98 (12)
  • [35] Value of Apparent Diffusion Coefficient (ADC) and Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) in Differentially Diagnosing Angiomatous Meningiomas and Solitary Fibrous Tumors/Hemangiopericytomas
    Chen, Chen
    Ren, Cui-Ping
    MEDICAL SCIENCE MONITOR, 2019, 25 : 5992 - 5996
  • [36] Feasibility of Intravoxel Incoherent Motion (IVIM) and Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) in Differentiation of Benign Parotid Gland Tumors
    Markiet, Karolina
    Glinska, Anna
    Nowicki, Tomasz
    Szurowska, Edyta
    Mikaszewski, Boguslaw
    BIOLOGY-BASEL, 2022, 11 (03):
  • [37] Differentiation between pilocytic astrocytoma and glioblastoma: a decision tree model using contrast-enhanced magnetic resonance imaging-derived quantitative radiomic features
    Dong, Fei
    Li, Qian
    Xu, Duo
    Xiu, Wenji
    Zeng, Qiang
    Zhu, Xiuliang
    Xu, Fangfang
    Jiang, Biao
    Zhang, Minming
    EUROPEAN RADIOLOGY, 2019, 29 (08) : 3968 - 3975
  • [38] Differentiation between pilocytic astrocytoma and glioblastoma: a decision tree model using contrast-enhanced magnetic resonance imaging-derived quantitative radiomic features
    Fei Dong
    Qian Li
    Duo Xu
    Wenji Xiu
    Qiang Zeng
    Xiuliang Zhu
    Fangfang Xu
    Biao Jiang
    Minming Zhang
    European Radiology, 2019, 29 : 3968 - 3975
  • [39] Differentiation of malignant from benign soft tissue tumors using radiomics based on pharmacokinetic parameter maps obtained from dynamic contrast-enhanced magnetic resonance imaging data
    Hao, Jingwei
    Liu, Shunli
    Wang, Tongyu
    Han, Xiaomeng
    Gao, Aixin
    Wang, Hexiang
    Hao, Dapeng
    CHINESE JOURNAL OF ACADEMIC RADIOLOGY, 2024, 7 (03) : 219 - 228
  • [40] Differentiation between Luminal A and B Molecular Subtypes of Breast Cancer Using Pharmacokinetic Quantitative Parameters with Histogram and Texture Features on Preoperative Dynamic Contrast-Enhanced Magnetic Resonance Imaging
    Luo, Hong-Bing
    Du, Ming-Ying
    Liu, Yuan-Yuan
    Wang, Min
    Qing, Hao-Miao
    Wen, Zhi-peng
    Xu, Guo-Hui
    Zhou, Peng
    Ren, Jing
    ACADEMIC RADIOLOGY, 2020, 27 (03) : E35 - E44