Diffusion MR Imaging in Glioma: Does It Have Any Role in the Pre-operation Determination of Grading of Glioma?

doi:10.1053/crad.2001.0741

Clinical Radiology

Volume 57, Issue 3, March 2002, Pages 219-225

https://doi.org/10.1053/crad.2001.0741 Get rights and content

Abstract

AIM: To investigate the role of the diffusion MR weighted sequence in the pre-operative grading of gliomas, and its application in defining the different components of these tumours. MATERIALS AND METHODS: Seventeen patients with gliomas (eight high grade, nine low grade) had diffusion weighted imaging. Apparent diffusion coefficients (ADCs) of different components of tumours were measured. RESULTS: ADC of the cystic portion of the tumour was significantly higher than ADCs of the enhanced tumour, non-enhanced tumour and perifocal oedema (P < 0.01). No significant difference in ADC values between low grade and high grade glioma (P > 0.7) was found nor was there any difference between oligoglioma and non-oligoglioma (P > 0.29). CONCLUSION: ADC value was useful to differentiate the cystic from the solid components of the tumours. However, it was not useful in pre-operative grading of glioma. Lam, W. W. M., Poon, W. S. and Metreweli, C. (2002). Clinical Radiology57, 219–225.

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To retrospectively assess if diffusion-weighted MR imaging (DWI) and quantitative apparent–diffusion coefficient (ADC) maps could be used to differentiate between low-grade gliomas (LGGs) and mixed neuronal–glial tumors (MNGTs including Dysembryoplastic Neuroepithelial Tumor and Ganglioglioma).
We retrospectively searched the clinical, pathological, and radiological databases for a span of 9 years and identified 24 patients with biopsy proven LGG. This included WHO (fourth edition) grade I and II tumors including astrocytoma, oligoastrocytoma and oligodendrogliomas. We also identified 22 patients with MNGTs (WHO grade I) including 13 patients with DNET and 9 patients with Ganglioglioma. All patients with pathologically confirmed tumors who had MRI including DWI sequence were included in the study. Regions of interest (ROIs) of 0.1–0.15 cm² were manually positioned on the ADC maps and multiple values (10⁻⁶ mm²/s) were obtained including the ADCmean. Optimal thresholds of ADC values and ADC ratios for distinguishing low-grade gliomas from mixed neuronal–glial tumors were determined by receiver operating characteristic (ROC) curve analysis.
All the four ADC measurement variables, including the minimum (ADC min), the (ADC max) maximum, the mean of ADC values (ADC mean) and the ADC ratios (ADC mean/ADCnormal) showed significant difference between the MNGTs and LGGs. The most significant difference was seen with the maximum ADC value (ADC max) of the tumor where the values for LGGs were 1317 ± 314 whereas the values for MNGTs were 2134 ± 438. In both subsets of patients with MNGTs (DNET and Ganglioglioma), this difference was statistically significant (P = .015 and P = .0066, respectively). However, there was no significant difference between the ADC values of these subtypes of MNGTs.
The ADC values of MNGTs are significantly higher compared to LGGs and can be helpful in radiological demarcation of these two conditions. The high ADC of MNGTs may be attributable to the presence of large extracellular spaces and their cellularity, which is much lower than that of pure glial neoplasms.
Imaging of malignant astrocytomas
2022, Handbook of Neuro-Oncology Neuroimaging
Astrocytomas represent the vast majority of gliomas and are classified as low- and high-grade tumours. High-grade or malignant astrocytomas are the most common primary malignant brain tumours. Anaplastic astrocytomas and glioblastomas represent the vast majority of malignant astrocytomas. Computed tomography and magnetic resonance imaging (MRI) represent the most commonly used modalities with MRI being the modality of choice. Anatomic detail can be acquired with conventional structural imaging, but newer approaches also add capabilities to interrogate image-derived physiologic characteristics of central nervous system neoplasms such as tissue blood flow (perfusion), water motion (diffusion) and tissue metabolism (spectroscopy and positron emission tomography). These advanced imaging techniques are increasingly employed to generate biomarkers that better reflect tumour burden and therapy response. It is important to be aware of imaging changes associated with the different tumour treatments so that progression or recurrence can reliably be differentiated from treatment-related changes.
The utility of APT and IVIM in the diagnosis and differentiation of squamous cell carcinoma of the cervix: A pilot study
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This study aimed to investigate whether amide proton transfer (APT) imaging, compared with intravoxel incoherent motion (IVIM) imaging-derived parameters, can differentiate squamous cell carcinoma of the cervix (SCCC) from the normal cervical stroma and distinguish poorly differentiated SCCC from well-moderately differentiated SCCC.
This prospective study enrolled 32 patients, comprising 20 patients with well-moderately differentiated SCCC and 12 patients with poorly differentiated SCCC. 20 healthy volunteers were enrolled as a control group. A bi-exponential model (BEM) analysis was performed to derive ADC, pure molecular diffusion coefficient (D), pseudo-diffusion coefficient (D*) and perfusion fraction (f). The APT signal intensity (APT SI), ADC, D, D* and f were measured. The parameters between the groups were compared with independent t-tests. Diagnostic performance was evaluated with a ROC analysis.
The APT SI of SCCC (2.92 ± 0.24%) was higher than that of normal cervical stroma (2.72 ± 0.36%) with P = 0.020. The comparison of the AUCs for the diagnosis of SCCC was ADC > f > APT SI > D* > D. A significant difference was found in the APT SI between the well-moderately differentiated SCCC group (2.82 ± 0.15%) and the poorly differentiated SCCC group (3.09 ± 0.27%) with P = 0.006. Except for D (P = 0.012), the ADC, D* and f values were not significantly different between the groups (P > 0.05). The comparison of the AUCs for distinguishing poorly differentiated SCCC was APT SI > D > ADC > D* = f.
APT imaging may be a useful technique in the diagnosis and predicting the differentiation of SCCC.
Diffusion kurtosis imaging as an imaging biomarker for predicting prognosis of the patients with high-grade gliomas
2019, Magnetic Resonance Imaging
Citation Excerpt :
In addition, the reality, that complex intracellular and extracellular in vivo environments cause the diffusion of water molecules to deviate considerably from this pattern, is ignored [9]. Thus, this deviation results in an inaccurate reflection of tissue microstructure [10,11]. Diffusional kurtosis imaging (DKI), an advanced diffusion imaging model, has been increasingly implemented for providing more precise information of tissue characteristics based on quantifying non-Gaussian behavior of water molecules in brain tissue [12].
To retrospectively explore the utilization of MR diffusion kurtosis imaging (DKI) in predicting prognosis of the patients with high-grade gliomas.
Thirty-three consecutive patients with cerebral gliomas underwent pretreatment DKI and diffusion-weighted imaging examination on a 3.0-T MR scanner. Diffusion parameters, including conventional tensor parameters, kurtosis metrics (mean kurtosis [MK], radial kurtosis [AK], and axial kurtosis [RK]), and minimum apparent diffusion coefficient (minADC), were obtained and normalized to the contralateral normal-appearing white matter. Correlations among each diffusion parameter and overall survival were analyzed by a Spearman method. The diagnostic efficiency of each parameter in predicting survival for patients with high-grade gliomas was assessed by a receiver operating characteristic curve. The favorable prognostic imaging biomarkers were further analyzed by using a Kaplan-Meier method with log-rank test.
In 33 patients, 17 patients reached overall survival >15 months (long survival group), whereas 16 showed overall survival <15 months (short survival group). Negative correlations between kurtosis metrics (MK, AK, and RK) and overall survival were obtained by using Spearman analysis (r = −0.63, −0.57, and −0.61, respectively, all P < 0.01), whereas minADC was positively correlated with overall survival (r = 0.56, P < 0.01). The kurtosis parameters of the long survival group were significantly lower than that of the short survival group (P < 0.001), while the minADC of the long survival group was significantly higher than that of the short survival group (P = 0.002). Among these diffusion parameters, the optimal cut-off value of MK (0.688) provided the best combination of sensitivity (93.75%) and specificity (76.47%) for differentiation of patients with long survival from those with short survival. High kurtosis metrics and low minADC were significant predictors of poor outcome. (P < 0.05).
Both kurtosis metrics and minADC have the potential to predict survival for the patients with high-grade gliomas. The preoperative kurtosis parameters, especially MK, can be taken as a preoperative prognostic biomarker to predict prognosis in patients with high-grade gliomas.
Diffusion weighted imaging may help differentiate intracranial hemangiopericytoma from meningioma
2019, Journal of Neuroradiology
Hemangiopericytoma and meningioma appear similar on routine diagnostic imaging and hence are difficult to distinguish. The purpose of our study was to examine the diffusion weighted imaging (DWI) characteristics of these two types of tumours.
In a retrospective study, each patient with hemangiopericytoma was matched with two meningioma patients based on tumour location and size. Minimum and mean apparent diffusion coefficients (ADC) were measured in the tumour and the contralateral normal-appearing white matter (NAWM). A normalized ADC was calculated. The two tumour types were subjectively assessed for heterogeneity on ADC maps.
Of the 14 patients with histopathological proven hemangiopericytoma, only 7 had available DWI for analysis. These 7 patients were matched based on tumour location and size with 14 patients out of the 209 meningioma patients screened. Hemangiopericytomas were more heterogeneous on ADC maps (P < 0.001) and had a higher mean ADC compared to that of meningiomas (P < 0.001).
Hemangiopericytomas showed heterogeneity on DWI and significantly higher ADC compared to that of meningiomas in our small study. These observations need to be confirmed in future studies with larger sample sizes.
Grading and proliferation assessment of diffuse astrocytic tumors with monoexponential, biexponential, and stretched-exponential diffusion-weighted imaging and diffusion kurtosis imaging
2018, European Journal of Radiology
To compare the main parameters derived from monoexponential, biexponential and stretched-exponential diffusion-weighted imaging (DWI) and diffusion kurtosis imaging (DKI) with respect to diagnostic performance for tumor grading and proliferation assessment in diffuse astrocytic tumors (DATs).
Fifty-eight pathologically confirmed DAT patients who underwent DWI and DKI on a 3-T scanner were prospectively collected and retrospectively reviewed. Measurements including the apparent diffusion coefficient (ADC), true diffusion coefficient (D), pseudodiffusion coefficient (D^*), perfusion fraction (f), distributed diffusion coefficient (DDC), heterogeneity index (α), mean diffusivity (MD), fractional anisotropy (FA), and mean kurtosis (MK) were compared between tumor grades (Ⅱ, Ⅲ, and Ⅳ) by using a Jonckheere-Terpstra test. Receiver operating characteristic (ROC) curves were used to assess the diagnostic efficacy of these parameters. Spearman’s rho with the Ki-67 labeling index (LI) was calculated for each parameter.
MK values differed significantly between all DAT subtypes and increased with grade. The ADC, D, f, DDC, α and MD values were significantly higher in grade Ⅱ tumors than in grade Ⅲ/Ⅳ tumors. D^* values were significantly lower in grade Ⅱ tumors than in grade Ⅳ tumors (all P < 0.05). In discriminating between grade Ⅱ and Ⅲ tumors, α, MK, MD, D and f had significantly greater area under the ROC curve (AUC) values than D^* and FA (0.927, 0.901, 0.896, 0.895, and 0.889, respectively vs 0.659 and 0.598, respectively, P < 0.05). In discriminating between grade Ⅲ and Ⅳ tumors, only MK demonstrated acceptable discrimination (AUC = 0.711). MK and D showed a strong correlation with the Ki-67 LI (ρ = 0.791 and -0.789, respectively, P < 0.001). D^*, f, MD, ADC, DDC and α showed a moderate correlation (|ρ| ranged from 0.415 to 0.698, P < 0.05).
MK and D have considerable potential to predict the degree of proliferation of DATs. MK could effectively characterize microstructural changes throughout the malignant transformation of DATs and provided useful complementary information for grading.

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^f1: Author for correspondence and guarantor of study: W. W. M. Lam, Department of Diagnostic Radiology and Organ Imaging, Faculty of Medicine, Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, New Territories, Hong Kong. Fax: +852 2636 0012; E-mail: [email protected]

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Regular ArticleDiffusion MR Imaging in Glioma: Does It Have Any Role in the Pre-operation Determination of Grading of Glioma?

Abstract

MR diffusion imaging of cerebral infarction in humans

Am J Neuroradiol

Fast magnetic resonance diffusion weighted imaging of acute human stroke

Neurology

Spin diffusion measurements: spin echoes in the presence of a time dependent field gradient

J Chem Phys

Diffusion weighted MR imaging of the brain: value of differentiating between extraaxial cysts and epidermoid tumours

Am J Neuroradiol

Role of diffusion weighted echo planar MRU in distinguishing between brain abscess and tumour: a preliminary report

Neuroradiology

Regular Article
Diffusion MR Imaging in Glioma: Does It Have Any Role in the Pre-operation Determination of Grading of Glioma?