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Feng A, Li L, Huang T, Li S, He N, Huang L, Zeng M, Lyu J. Differentiating glioblastoma from primary central nervous system lymphoma of atypical manifestation using multiparametric magnetic resonance imaging: A comparative study. Heliyon 2023; 9:e15150. [PMID: 37095995 PMCID: PMC10121909 DOI: 10.1016/j.heliyon.2023.e15150] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Revised: 03/24/2023] [Accepted: 03/28/2023] [Indexed: 04/26/2023] Open
Abstract
Background The aim of this study is to evaluate the diagnostic efficiency of magnetic resonance imaging (MRI) of single parameters, unimodality, and bimodality in distinguishing glioblastoma (GBM) from atypical primary central nervous system lymphoma (PCNSL) based on diffusion-weighted imaging (DWI), dynamic susceptibility contrast (DSC) enhancement, diffusion tensor imaging (DTI), and proton magnetic resonance spectroscopy (1H-MRS) findings. Methods The cohort included 108 patients pathologically diagnosed with GBM and 54 patients pathologically diagnosed with PCNSL. Pretreatment morphological MRI, DWI, DSC, DTI and MRS were all performed on each patient. The quantitative parameters of multimodal MRI were measured and compared between the patients in the GBM and atypical PCNSL groups, and those parameters showing a significant difference (p < 0.05) between patients in the GBM and atypical PCNSL groups were used to develop one-parameters, unimodality, and bimodality models. We evaluated the efficiency of different models in distinguishing GBM from atypical PCNSL by performing receiver operating characteristic analysis (ROC). Results Atypical PCNSL had lower minimum apparent diffusion coefficient (ADCmin), mean ADC (ADCmean), relative ADC (rADC), mean relative cerebral blood volume (rCBVmean), maximum rCBV (rCBVmax), fractional anisotropy (FA), axial diffusion coefficient (DA) and radial diffusion coefficient (DR) values and higher choline/creatine (Cho/Cr) and lipid/creatine (Lip/Cr) ratios than GBM (all p < 0.05). The rCBVmax, DTI and DSC + DTI data were optimal models of single-parameter, unimodality and bimodality for differentiation of GBM from atypical PCNSL, yielding areas under the curves (AUCs) of 0.905, 0.954, and 0.992, respectively. Conclusions Models of single-parameter, unimodality and bimodality based on muti multiparameter functional MRI may help to discriminate GBM from atypical PCNSL.
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Affiliation(s)
- Aozi Feng
- Department of Clinical Research, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong 510632, China
| | - Li Li
- Department of Clinical Research, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong 510632, China
| | - Tao Huang
- Department of Clinical Research, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong 510632, China
| | - Shuna Li
- Department of Clinical Research, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong 510632, China
| | - Ningxia He
- Department of Clinical Research, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong 510632, China
| | - Liying Huang
- Department of Clinical Research, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong 510632, China
| | - Mengnan Zeng
- College of Pharmacy, Henan University of Chinese Medicine, Zhengzhou, Henan 450046, China
- Corresponding author.
| | - Jun Lyu
- Department of Clinical Research, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong 510632, China
- Guangdong Provincial Key Laboratory of Traditional Chinese Medicine Informatization, Guangzhou, Guangdong 510632, China
- Corresponding author. Department of Clinical Research, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong 510632, China.
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Differentiation of high-grade glioma and primary central nervous system lymphoma: Multiparametric imaging of the enhancing tumor and peritumoral regions based on hybrid 18F-FDG PET/MRI. Eur J Radiol 2022; 150:110235. [DOI: 10.1016/j.ejrad.2022.110235] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Revised: 02/19/2022] [Accepted: 03/03/2022] [Indexed: 12/14/2022]
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Ohba S, Murayama K, Abe M, Hasegawa M, Hirose Y. Magnetic Resonance Imaging and Proton Magnetic Resonance Spectroscopy for Differentiating Between Enhanced Gliomas and Malignant Lymphomas. World Neurosurg 2019; 127:e779-e787. [PMID: 30951915 DOI: 10.1016/j.wneu.2019.03.261] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2019] [Revised: 03/24/2019] [Accepted: 03/25/2019] [Indexed: 11/25/2022]
Abstract
BACKGROUND Although the treatment strategies for malignant lymphomas and gliomas differ, it is usually difficult to preoperatively distinguish between them. Magnetic resonance spectroscopy (MRS) was recently reported to be useful for preoperative diagnoses; however, MRS data analysis using LCModel, which is a quantitative and objective method, was performed in only a few of the existing reports. METHODS The clinical characteristics, conventional magnetic resonance imaging findings, and MRS parameters using LCModel were evaluated to identify the factors that can help distinguish between malignant lymphomas and enhanced gliomas. RESULTS In total, 59 cases were evaluated, including 13 cases of malignant lymphoma, 1 case of pilocytic astrocytoma, 5 cases of grade Ⅱ glioma, 5 cases of grade Ⅲ glioma, and 35 cases of glioblastoma. There was no correlation between clinical characteristics (sex and age) and diagnosis. Neither T1- nor T2-weighted image was useful for differentiation between the 2 forms of tumors, but the apparent diffusion coefficient minimum value was useful for distinguishing malignant lymphomas from gliomas, with an area under the curve (AUC) value of 0.852. MRS analysis using LCModel revealed differences in glutamate (Glu), N-acetylaspartate (NAA) + N-acetylaspartylglutamate (NAAG), Glu + glutamine, and Lipid (Lip) 13a + Lip13b between malignant lymphomas and gliomas. The largest AUC was 0.904, which was obtained for the Glu level, followed by 0.883 and 0.866 for NAA + NAAG and Lip13a + Lip13b, respectively. CONCLUSIONS Quantitative analysis of proton-MRS using LCModel is considered to be a valuable method for distinguishing between gliomas and malignant lymphomas.
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Affiliation(s)
- Shigeo Ohba
- Department of Neurosurgery, Fujita Health University, Toyoake, Aichi, Japan.
| | - Kazuhiro Murayama
- Department of Radiology, Fujita Health University, Toyoake, Aichi, Japan
| | - Masato Abe
- Department of Pathology, Fujita Health University, Toyoake, Aichi, Japan
| | - Mitsuhiro Hasegawa
- Department of Neurosurgery, Fujita Health University, Toyoake, Aichi, Japan
| | - Yuichi Hirose
- Department of Neurosurgery, Fujita Health University, Toyoake, Aichi, Japan
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Diagnostic performance of DWI for differentiating primary central nervous system lymphoma from glioblastoma: a systematic review and meta-analysis. Neurol Sci 2019; 40:947-956. [PMID: 30706241 DOI: 10.1007/s10072-019-03732-7] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2018] [Accepted: 01/18/2019] [Indexed: 12/23/2022]
Abstract
OBJECTIVE The purpose of this meta-analysis was to evaluate the diagnostic performance of diffusion-weighted imaging (DWI) for differentiating primary central nervous system lymphoma (PCNSL) from glioblastoma (GBM). MATERIALS AND METHODS A thorough search of the databases including PubMed, EMBASE, and Cochrane Library was carried out and the data acquired were up to November 1, 2017. The quality of the studies involved was evaluated using QUADAS-2 (Quality Assessment of Diagnostic Accuracy Studies, revised version). Multiple analytic values including sensitivity (SEN), specificity (SPE), positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and the summary receiver operating characteristic (SROC) curve were calculated and pooled for the statistical analysis. The subgroup analysis was also performed to explore the heterogeneity. RESULTS Eight retrospective studies (461 patients with 461 lesions) were included. The pooled SEN, SPE, PLR, NLR, and DOR with 95% confidence interval (CI) were 0.82 [95% CI 0.70-0.90], 0.84 [95% CI 0.75-0.90], 4.96 [95% CI 3.20-7.69], 0.22 [95% CI 0.13-0.37], and 22.85 [95% CI 10.42-50.11], respectively. The area under the curve (AUC) given by SROC curve was 0.90 [95% CI 0.87-0.92]. The subgroup analysis indicated the slice thickness of the images (> 3 mm versus ≤ 3 mm) was a significant factor affecting the heterogeneity. No existence of significant publication bias was confirmed with Deeks' test. CONCLUSIONS DWI showed moderate diagnostic performance for differentiating primary central nervous system lymphoma (PCNSL) from glioblastoma (GBM). Moreover, it is of clinical significance using DWI combined with conventional MRI to differentiate PCNSL from GBM.
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Suh CH, Kim HS, Jung SC, Park JE, Choi CG, Kim SJ. MRI as a diagnostic biomarker for differentiating primary central nervous system lymphoma from glioblastoma: A systematic review and meta-analysis. J Magn Reson Imaging 2019; 50:560-572. [PMID: 30637843 DOI: 10.1002/jmri.26602] [Citation(s) in RCA: 37] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2018] [Revised: 11/28/2018] [Accepted: 11/28/2018] [Indexed: 01/15/2023] Open
Abstract
BACKGROUND Accurate preoperative differentiation of primary central nervous system lymphoma (PCNSL) and glioblastoma is clinically crucial because the treatment strategies differ substantially. PURPOSE To evaluate the diagnostic performance of MRI for differentiating PCNSL from glioblastoma. STUDY TYPE Systematic review and meta-analysis. SUBJECTS Ovid-MEDLINE and EMBASE databases were searched to find relevant original articles up to November 25, 2018. The search term combined synonyms for "lymphoma," "glioblastoma," and "MRI." FIELD STRENGTH/SEQUENCE Patients underwent at least one MRI sequence including diffusion-weighted imaging (DWI), dynamic susceptibility-weighted contrast-enhanced imaging (DSC), dynamic contrast-enhanced imaging (DCE), arterial spin labeling (ASL), susceptibility-weighted imaging (SWI), intravoxel incoherent motion (IVIM), and magnetic resonance spectroscopy (MRS) using 1.5 or 3 T. ASSESSMENT Quality assessment was performed according to the Quality Assessment of Diagnostic Accuracy Studies-2 tool. STATISTICAL TESTS Hierarchical logistic regression modeling was used to obtain pooled sensitivity and specificity. Meta-regression was performed. RESULTS Twenty-two studies with 1182 patients were included. MRI sequences demonstrated high overall diagnostic performance with pooled sensitivity of 91% (95% confidence interval [CI], 87-93%) and specificity of 89% (95% CI, 85-93%). The area under the hierarchical summary receiver operating characteristic curve was 0.92 (95% CI, 0.90-0.94). Studies using DSC or ASL showed high diagnostic performance (sensitivity of 93% [95% CI, 89-97%] and specificity of 91% [95% CI, 86-96%]). Heterogeneity was only detected in specificity (I2 = 66.84%) and magnetic field strength was revealed to be a significant factor affecting study heterogeneity. DATA CONCLUSION MRI showed overall high diagnostic performance for differentiating PCNSL from glioblastoma, with studies using DSC or ASL showing high diagnostic performance. Therefore, MRI sequences including DSC or ASL is a potential diagnostic tool for differentiating PCNSL from glioblastoma. LEVEL OF EVIDENCE 3 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2019;50:560-572.
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Affiliation(s)
- Chong Hyun Suh
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea
| | - Ho Sung Kim
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea
| | - Seung Chai Jung
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea
| | - Ji Eun Park
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea
| | - Choong Gon Choi
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea
| | - Sang Joon Kim
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea
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Royer-Perron L, Hoang-Xuan K. Management of primary central nervous system lymphoma. Presse Med 2018; 47:e213-e244. [PMID: 30416008 DOI: 10.1016/j.lpm.2018.04.016] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/28/2018] [Revised: 03/21/2018] [Accepted: 04/09/2018] [Indexed: 12/28/2022] Open
Abstract
A rare tumor, primary central nervous system lymphoma can affect immunocompetent and immunocompromised patients. While sensitive to radiotherapy or chemotherapy crossing the blood-brain barrier, it often recurs. Modern treatment consists of high-dose methotrexate-based induction chemotherapy, often followed by consolidation with either radiotherapy or further chemotherapy. Neurotoxicity is however a concern with radiotherapy, especially for patients older than 60 years. The benefit of the addition of rituximab to chemotherapy is unclear. Targeted therapies and immunotherapy have been effective in some patients and are tested on a larger scale. Survival has improved in the last decade, but remains poor in older patients.
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Affiliation(s)
- Louis Royer-Perron
- Hôpital Pierre-Boucher, Longueuil, Canada; AP-HP, Sorbonne universités, UPMC université Paris 06, hôpitaux Universitaires La Pitié Salpêtrière, Charles Foix, service de neurologie, 2, Mazarin, 75013, Paris, France; LOC network, 75561 Paris cedex 13, France.
| | - Khê Hoang-Xuan
- Institut du Cerveau et de la Moelle épinière (ICM), Inserm U 1127, CNRS UMR 7225, Paris, France; AP-HP, Sorbonne universités, UPMC université Paris 06, hôpitaux Universitaires La Pitié Salpêtrière, Charles Foix, service de neurologie, 2, Mazarin, 75013, Paris, France; LOC network, 75561 Paris cedex 13, France
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Primary CNS Lymphomas: Challenges in Diagnosis and Monitoring. BIOMED RESEARCH INTERNATIONAL 2018; 2018:3606970. [PMID: 30035121 PMCID: PMC6033255 DOI: 10.1155/2018/3606970] [Citation(s) in RCA: 71] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/30/2017] [Revised: 04/12/2018] [Accepted: 05/17/2018] [Indexed: 12/22/2022]
Abstract
Primary Central Nervous System Lymphoma (PCNSL) is a rare neoplasm that can involve brain, eye, leptomeninges, and rarely spinal cord. PCNSL lesions most typically enhance homogeneously on T1-weighted magnetic resonance imaging (MRI) and appear T2-hypointense, but high variability in MRI features is commonly encountered. Neurological symptoms and MRI findings may mimic high grade gliomas (HGGs), tumefactive demyelinating lesions (TDLs), or infectious and granulomatous diseases. Advanced MRI techniques (MR diffusion, spectroscopy, and perfusion) and metabolic imaging, such as Fluorodeoxyglucose Positron Emission Tomography (FDG-PET) or amino acid PET (usually employing methionine), may be useful in distinguishing these different entities and monitoring the disease course. Moreover, emerging data suggest a role for cerebrospinal fluid (CSF) markers in predicting prognosis and response to treatments. In this review, we will address the challenges in PCNSL diagnosis, assessment of response to treatments, and evaluation of potential neurotoxicity related to chemotherapy and radiotherapy.
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Nagashima H, Sasayama T, Tanaka K, Kyotani K, Sato N, Maeyama M, Kohta M, Sakata J, Yamamoto Y, Hosoda K, Itoh T, Sasaki R, Kohmura E. Myo-inositol concentration in MR spectroscopy for differentiating high grade glioma from primary central nervous system lymphoma. J Neurooncol 2017; 136:317-326. [DOI: 10.1007/s11060-017-2655-x] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2017] [Accepted: 10/24/2017] [Indexed: 01/26/2023]
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Magnetic Resonance Spectroscopy and its Clinical Applications: A Review. J Med Imaging Radiat Sci 2017; 48:233-253. [PMID: 31047406 DOI: 10.1016/j.jmir.2017.06.004] [Citation(s) in RCA: 46] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2017] [Revised: 04/30/2017] [Accepted: 06/22/2017] [Indexed: 12/25/2022]
Abstract
In vivo NMR spectroscopy is known as magnetic resonance spectroscopy (MRS). MRS has been applied as both a research and a clinical tool in order to detect visible or nonvisible abnormalities. The adaptability of MRS allows a technique that can probe a wide variety of metabolic uses across different tissues. Although MRS is mostly applied for brain tissue, it can be used for detection, localization, staging, tumour aggressiveness evaluation, and tumour response assessment of breast, prostate, hepatic, and other cancers. In this article, the medical applications of MRS in the brain, including tumours, neural and psychiatric disorder studies, breast, prostate, hepatic, gastrointestinal, and genitourinary investigations have been reviewed.
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Lin X, Lee M, Buck O, Woo KM, Zhang Z, Hatzoglou V, Omuro A, Arevalo-Perez J, Thomas AA, Huse J, Peck K, Holodny AI, Young RJ. Diagnostic Accuracy of T1-Weighted Dynamic Contrast-Enhanced-MRI and DWI-ADC for Differentiation of Glioblastoma and Primary CNS Lymphoma. AJNR Am J Neuroradiol 2016; 38:485-491. [PMID: 27932505 DOI: 10.3174/ajnr.a5023] [Citation(s) in RCA: 56] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2016] [Accepted: 10/07/2016] [Indexed: 01/20/2023]
Abstract
BACKGROUND AND PURPOSE Glioblastoma and primary CNS lymphoma dictate different neurosurgical strategies; it is critical to distinguish them preoperatively. However, current imaging modalities do not effectively differentiate them. We aimed to examine the use of DWI and T1-weighted dynamic contrast-enhanced-MR imaging as potential discriminative tools. MATERIALS AND METHODS We retrospectively reviewed 18 patients with primary CNS lymphoma and 36 matched patients with glioblastoma with pretreatment DWI and dynamic contrast-enhanced-MR imaging. VOIs were drawn around the tumor on contrast-enhanced T1WI and FLAIR images; these images were transferred onto coregistered ADC maps to obtain the ADC and onto dynamic contrast-enhanced perfusion maps to obtain the plasma volume and permeability transfer constant. Histogram analysis was performed to determine the mean and relative ADCmean and relative 90th percentile values for plasma volume and the permeability transfer constant. Nonparametric tests were used to assess differences, and receiver operating characteristic analysis was performed for optimal threshold calculations. RESULTS The enhancing component of primary CNS lymphoma was found to have significantly lower ADCmean (1.1 × 10-3 versus 1.4 × 10-3; P < .001) and relative ADCmean (1.5 versus 1.9; P < .001) and relative 90th percentile values for plasma volume (3.7 versus 5.0; P < .05) than the enhancing component of glioblastoma, but not significantly different relative 90th percentile values for the permeability transfer constant (5.4 versus 4.4; P = .83). The nonenhancing portions of glioblastoma and primary CNS lymphoma did not differ in these parameters. On the basis of receiver operating characteristic analysis, mean ADC provided the best threshold (area under the curve = 0.83) to distinguish primary CNS lymphoma from glioblastoma, which was not improved with normalized ADC or the addition of perfusion parameters. CONCLUSIONS ADC was superior to dynamic contrast-enhanced-MR imaging perfusion, alone or in combination, in differentiating primary CNS lymphoma from glioblastoma.
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Affiliation(s)
- X Lin
- From the Departments of Neurology (X.L., A.O., A.A.T.).,Department of Neurology (X.L.), National Neuroscience Institute, Singapore
| | - M Lee
- Radiology (M.L., O.B., V.H., J.A.-P., A.I.H., R.J.Y.)
| | - O Buck
- Radiology (M.L., O.B., V.H., J.A.-P., A.I.H., R.J.Y.)
| | - K M Woo
- Epidemiology and Biostatistics (K.M.W., Z.Z.)
| | - Z Zhang
- Epidemiology and Biostatistics (K.M.W., Z.Z.)
| | - V Hatzoglou
- Radiology (M.L., O.B., V.H., J.A.-P., A.I.H., R.J.Y.).,The Brain Tumor Center (V.H., A.O., A.I.H., R.J.Y.), Memorial Sloan Kettering Cancer Center, New York, New York
| | - A Omuro
- From the Departments of Neurology (X.L., A.O., A.A.T.).,The Brain Tumor Center (V.H., A.O., A.I.H., R.J.Y.), Memorial Sloan Kettering Cancer Center, New York, New York
| | | | - A A Thomas
- From the Departments of Neurology (X.L., A.O., A.A.T.)
| | | | | | - A I Holodny
- Radiology (M.L., O.B., V.H., J.A.-P., A.I.H., R.J.Y.).,The Brain Tumor Center (V.H., A.O., A.I.H., R.J.Y.), Memorial Sloan Kettering Cancer Center, New York, New York
| | - R J Young
- Radiology (M.L., O.B., V.H., J.A.-P., A.I.H., R.J.Y.) .,The Brain Tumor Center (V.H., A.O., A.I.H., R.J.Y.), Memorial Sloan Kettering Cancer Center, New York, New York
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