Lymphomas and glioblastomas: Differences in the apparent diffusion coefficient evaluated with high b-value diffusion-weighted magnetic resonance imaging at 3 T

Doskaliyev, Aidos; Yamasaki, Fumiyuki; Ohtaki, Megu; Kajiwara, Yoshinori; Takeshima, Yukio; Watanabe, Y.; Takayasu, Takeshi; Amatya, Vishwa Jeet; Akiyama, Yuji; Sakamoto, Kazuhiko; Kurisu, Kaoru

doi:10.1016/j.ejrad.2010.11.005

Cited by 101 publications

(76 citation statements)

References 21 publications

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“…In our study, we used a b-value of 1000 s mm 22 to minimize the influence of microperfusion on ADC and FA. Although one study 25 showed that the minimum apparent diffusion coefficient (ADC min ) at a b-value of 4000 s mm 22 was associated with tumour cellularity more significantly than ADC min at a b-value of 1000 s mm 22 in brain tumours, no similar studies in the breast have been reported; extremely high b-values in the breast will reduce the signal of the breast tissue and lesions. Therefore, no b-values .1000 s mm 22 were used in our study.…”

Section: Discussionmentioning

confidence: 98%

Diffusion tensor imaging of breast lesions: evaluation of apparent diffusion coefficient and fractional anisotropy and tissue cellularity

Jiang

Hua

et al. 2016

BJR

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Section: Discussionmentioning

confidence: 98%

Diffusion tensor imaging of breast lesions: evaluation of apparent diffusion coefficient and fractional anisotropy and tissue cellularity

Jiang

Hua

et al. 2016

BJR

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“…Although some papers have focused on diŠerentiating high-grade gliomas and lymphoma, whose cellularities are diŠerent, 53,[56][57][58][59][60] ADC values overlap between gliomas and lymphoma. 61 Murakami's team reported that use of the ADC can improve accuracy in grading astrocytic tumors, using a combination of minimum ADCs and ADC diŠerence values (2-parameter method).…”

Section: Neoplasms Of the Brain And Spinementioning

confidence: 99%

Visualizing Non-Gaussian Diffusion: Clinical Application of q-Space Imaging and Diffusional Kurtosis Imaging of the Brain and Spine

et al. 2012

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Recently, non-Gaussian diŠusion-weighted imaging (DWI) techniques, including qspace imaging (QSI) and diŠusional kurtosis imaging (DKI), have emerged as advanced methods to evaluate tissue microstructure in vivo using water diŠusion. QSI and DKI have shown promising results in clinical applications, such as in the evaluation of brain tumors (e.g., grading gliomas), degenerative diseases (e.g., speciˆc diagnosis of Parkinson disease), demyelinating diseases (e.g., assessment of normal-appearing tissue of multiple sclerosis), and cerebrovascular diseases (e.g., assessment of the microstructural environment of fresh infarctions). Representative metrics in clinical use are the full width at half maximum, also known as the mean displacement of the probability density function curve, which is derived from QSI, and diŠusional kurtosis, which is derived from DKI. These new metrics may provide information on tissue structure in addition to that provided by conventional Gaussian DWI investigations that use the apparent diŠusion coe‹cient and fractional anisotropy, recognized indices for evaluating disease and normal development in the brain and spine. In some clinical situations, sensitivity for detecting pathological conditions is higher using QSI and DKI than conventional DWI and diŠusion tensor imaging (DTI) because DWI and DTI calculations are based on the assumption that water molecules follow a Gaussian distribution, whereas hindrance of the distribution of water molecules by complex and restricted structures in actual neural tissues produces distributions that are far from Gaussian. We review the technical aspects and clinical applications of QSI and DKI, focusing on clinical use and in vivo studies and highlighting diŠerences from conventional diŠusional metrics.

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“…A differential diagnostic advantage of higher b-valuebased DWI in many CNS diseases, including malignant lymphomas, has been reported. 6 Although we found that b-4000-based DWI was superior to b-1000-based DWI, it was not possible to differentiate all malignant lymphomas from gliomas even with the higher b value.…”

Section: High Lipid Levels In Malignant Lymphoma On 1 H-mrsmentioning

confidence: 57%

“…6,10,15,20,32,35,37 The sensitivity and specificity of the ADC for discriminating between malignant lymphomas and gliomas are approximately 80%-90%. However, some studies reported no statistically significant difference in the ADCs of glioblastomas and malignant lymphomas, although the ADCs of malignant lymphomas were lower than those of highgrade gliomas.…”

Section: High Lipid Levels In Malignant Lymphoma On 1 H-mrsmentioning

confidence: 99%

Magnetic resonance spectroscopy detection of high lipid levels in intraaxial tumors without central necrosis: a characteristic of malignant lymphoma

Yamasaki¹,

Takayasu²,

Nosaka³

et al. 2015

JNS

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Primary CNS lymphomas, a rare malignant form of non-Hodgkin's lymphoma, account for 3%-6% of all primary brain neoplasms. 4 There has been an increase in the incidence of malignant lymphoma in the last 3 decades. The differentiation of malignant lymphomas from gliomas or malignant gliomas by conventional MRI can be difficult. Malignant lymphomas and glioblastomas require different treatments; glioblastomas are treated by extensive resection, whereas malignant lymphomas are usually addressed by biopsy. Therefore, a differential diagnosis is of high clinical relevance. Moreover, even with advanced MRI techniques that yield physiological inabbreviatioNs ADC = apparent diffusion coefficient; ADCMIN = minimum absolute ADC; b-n = b value of n sec/mm 2 ; cho = choline; Cr = creatine; DWI = diffusionweighted imaging; FLAIR = fluid-attenuated inversion recovery;1 H-MRS = proton MR spectroscopy; mI = myoinositol; MRS = MR spectroscopy; NAA = N-acetyl aspartate; ROI = region of interest; VOI = volume(s) of interest. submitted January 10, 2014. accepted September 10, 2014. iNclude wheN citiNg Published online March 6, 2015; DOI: 10.3171/2014.9.JNS14106. disclosure The authors report no conflict of interest concerning the materials or methods used in this study or the findings specified in this paper. The following grants funded this study: grant-in-aid nos. 25462262 and 23592091 from the Japan Society for the Promotion of Science Grant-in-Aid for Scientific Research. H-MRS at 3 T, and the diagnoses were histologically confirmed. results Using a short echo time 1 H-MRS, large lipid peaks were observed in all 17 patients with a malignant lymphoma, in 39 patients (79.6%) with a Grade IV glioma, and in 10 patients (30.3%) with a Grade III glioma. A focus on homogeneously enhanced tumors revealed large lipid peaks in 15 malignant lymphomas that were free of central necrosis on Gd-enhanced T1-weighted images. Conversely, in the 7 homogeneously enhanced gliomas (glioblastoma and anaplastic astrocytoma, n = 2 each; anaplastic oligodendroglioma, diffuse astrocytoma, and pilomyxoid astrocytoma, n = 1 each), lipid peaks were small or absent. coNclusioNs Large lipid peaks on 1 H-MRS images of tumors without central necrosis were characteristic of malignant lymphomas. Conversely, small or absent lipid peaks in intraaxial tumors without central necrosis were strongly suggestive of glioma.

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Lymphomas and glioblastomas: Differences in the apparent diffusion coefficient evaluated with high b-value diffusion-weighted magnetic resonance imaging at 3 T

Cited by 101 publications

References 21 publications

Diffusion tensor imaging of breast lesions: evaluation of apparent diffusion coefficient and fractional anisotropy and tissue cellularity

Diffusion tensor imaging of breast lesions: evaluation of apparent diffusion coefficient and fractional anisotropy and tissue cellularity

Visualizing Non-Gaussian Diffusion: Clinical Application of q-Space Imaging and Diffusional Kurtosis Imaging of the Brain and Spine

Magnetic resonance spectroscopy detection of high lipid levels in intraaxial tumors without central necrosis: a characteristic of malignant lymphoma

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