Diagnostic performance of DWI for differentiating primary central nervous system lymphoma from glioblastoma: a systematic review and meta-analysis

Lü, Xin; Xu, Weilin; Wei, Yuyu; Gao, Liansheng; Fu, Xiongjie; Yao, Yuan; Wang, Lin

doi:10.1007/s10072-019-03732-7

Cited by 19 publications

(19 citation statements)

References 35 publications

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“…Since the θ values were not significantly different between the PCNSL and GB groups, it was likely that the lower κ values might result in the lower ADC and D values and the higher f1 values observed in the PCNSLs compared to the GBs. These findings are in accordance with studies that examined the mono-exponential model, in which PCNSLs showed lower ADC values relative to GBs [3][4][5].…”

Section: Discussionsupporting

confidence: 92%

“…Several studies have indicated that advanced MRI techniques such as diffusion-weighted imaging (DWI) [3][4][5][6], dynamic susceptibility contrast perfusion-weighted imaging [6][7][8], and arterial spin labeling [9] are useful for distinguishing PCNSLs and GBs. According to those studies, PCNSLs are characterized by more restricted water diffusion and lower perfusion compared to GBs.…”

Section: Introductionmentioning

confidence: 99%

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Gamma distribution model of diffusion MRI for the differentiation of primary central nerve system lymphomas and glioblastomas

et al. 2020

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The preoperative imaging-based differentiation of primary central nervous system lymphomas (PCNSLs) and glioblastomas (GBs) is of high importance since the therapeutic strategies differ substantially between these tumors. In this study, we investigate whether the gamma distribution (GD) model is useful in this differentiation of PNCSLs and GBs. Twenty-seven patients with PCNSLs and 57 patients with GBs were imaged with diffusion-weighted imaging using 13 b-values ranging from 0 to 1000 sec/mm2. The shape parameter (κ) and scale parameter (θ) were obtained with the GD model. Fractions of three different areas under the probability density function curve (f1, f2, f3) were defined as follows: f1, diffusion coefficient (D) <1.0×10−3 mm2/sec; f2, D >1.0×10−3 and <3.0×10−3 mm2/sec; f3, D >3.0 × 10−3 mm2/sec. The GD model-derived parameters were compared between PCNSLs and GBs. Receiver operating characteristic (ROC) curve analyses were performed to assess diagnostic performance. The correlations with intravoxel incoherent motion (IVIM)-derived parameters were evaluated. The PCNSL group's κ (2.26 ± 1.00) was significantly smaller than the GB group's (3.62 ± 2.01, p = 0.0004). The PCNSL group's f1 (0.542 ± 0.107) was significantly larger than the GB group's (0.348 ± 0.132, p<0.0001). The PCNSL group's f2 (0.372 ± 0.098) was significantly smaller than the GB group's (0.508 ± 0.127, p<0.0001). The PCNSL group's f3 (0.086 ± 0.043) was significantly smaller than the GB group's (0.144 ± 0.062, p<0.0001). The combination of κ, f1, and f3 showed excellent diagnostic performance (area under the curve, 0.909). The f1 had an almost perfect inverse correlation with D. The f2 and f3 had very strong positive correlations with D and f, respectively. The GD model is useful for the differentiation of GBs and PCNSLs.

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Section: Discussionsupporting

confidence: 92%

Section: Introductionmentioning

confidence: 99%

Gamma distribution model of diffusion MRI for the differentiation of primary central nerve system lymphomas and glioblastomas

et al. 2020

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“…To our knowledge, this is the first systematic review aiming at summarizing the role of diffusion MR imaging metrics in predicting survival in GBM patients. To date, systematic studies exploring diffusion metrics applied to GBM patients aimed at evaluating the power of DWI and DTI for differentiating GBM from brain metastasis or PCNSL, or from lower grade gliomas [ 32 , 33 , 88 ]. However, analysis of survival outcomes was out of the purpose of these works.…”

Section: Discussionmentioning

confidence: 99%

Predicting Survival in Glioblastoma Patients Using Diffusion MR Imaging Metrics—A Systematic Review

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Tramontano

et al. 2020

Cancers

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Despite advances in surgical and medical treatment of glioblastoma (GBM), the medium survival is about 15 months and varies significantly, with occasional longer survivors and individuals whose tumours show a significant response to therapy with respect to others. Diffusion MRI can provide a quantitative assessment of the intratumoral heterogeneity of GBM infiltration, which is of clinical significance for targeted surgery and therapy, and aimed at improving GBM patient survival. So, the aim of this systematic review is to assess the role of diffusion MRI metrics in predicting survival of patients with GBM. According to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement, a systematic literature search was performed to identify original articles since 2010 that evaluated the association of diffusion MRI metrics with overall survival (OS) and progression-free survival (PFS). The quality of the included studies was evaluated using the QUIPS tool. A total of 52 articles were selected. The most examined metrics were associated with the standard Diffusion Weighted Imaging (DWI) (34 studies) and Diffusion Tensor Imaging (DTI) models (17 studies). Our findings showed that quantitative diffusion MRI metrics provide useful information for predicting survival outcomes in GBM patients, mainly in combination with other clinical and multimodality imaging parameters.

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“…Both entities may be centered in the corpus callosum in a butterfly pattern, but primary CNS lymphoma more frequently infiltrates the optic tracts and the basal ganglia, while HGG is typically found in the cerebral cortex. On DWI, ADC values are useful in differentiation (primary CNS lymphomas have lower ADC because of higher cellularity than HGG), especially when used in conjunction with conventional MRI ( 29 , 49 , 50 ). Ideally, imaging is performed with slice thickness <3 mm to reduce heterogeneity and artifacts ( 50 ).…”

Section: Advanced Mrimentioning

confidence: 99%

“…On DWI, ADC values are useful in differentiation (primary CNS lymphomas have lower ADC because of higher cellularity than HGG), especially when used in conjunction with conventional MRI ( 29 , 49 , 50 ). Ideally, imaging is performed with slice thickness <3 mm to reduce heterogeneity and artifacts ( 50 ). The decrease in fractional anisotropy in primary CNS lymphoma is also more marked than the decrease in glioblastoma (GBM), although this DTI metric has been described as less specific and less accurate than changes in ADC ( 38 ).…”

Section: Advanced Mrimentioning

confidence: 99%

Positron emission tomography and magnetic resonance imaging in primary central nervous system lymphoma—a narrative review

et al. 2021

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This review addresses the challenges of primary central nervous system (CNS) lymphoma diagnosis, assessment of treatment response, and detection of recurrence. Primary CNS lymphoma is a rare form of extra-nodal non-Hodgkin lymphoma that can involve brain, spinal cord, leptomeninges, and eyes. Primary CNS lymphoma lesions are most commonly confined to the white matter or deep cerebral structures such as basal ganglia and deep periventricular regions. Contrast-enhanced magnetic resonance imaging (MRI) is the standard diagnostic modality employed by neuro-oncologists. MRI often shows common morphological features such as a single or multiple uniformly well-enhancing lesions without necrosis but with moderate surrounding edema. Other brain tumors or inflammatory processes can show similar radiological patterns, making differential diagnosis difficult. [18F]-fluorodeoxyglucose (FDG) positron emission tomography (PET) has selected utility in cerebral lymphoma, especially in diagnosis. Primary CNS lymphoma can sometimes present with atypical findings on MRI and FDG PET, such as disseminated disease, non-enhancing or ring-like enhancing lesions. The complementary strengths of PET and MRI have led to the development of combined PET-MR systems, which in some cases may improve lesion characterization and detection. By highlighting active developments in this field, including advanced MRI sequences, novel radiotracers, and potential imaging biomarkers, we aim to spur interest in sophisticated imaging approaches.

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Diagnostic performance of DWI for differentiating primary central nervous system lymphoma from glioblastoma: a systematic review and meta-analysis

Cited by 19 publications

References 35 publications

Gamma distribution model of diffusion MRI for the differentiation of primary central nerve system lymphomas and glioblastomas

Gamma distribution model of diffusion MRI for the differentiation of primary central nerve system lymphomas and glioblastomas

Predicting Survival in Glioblastoma Patients Using Diffusion MR Imaging Metrics—A Systematic Review

Positron emission tomography and magnetic resonance imaging in primary central nervous system lymphoma—a narrative review

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