Grading Astrocytic Tumors by Using Apparent Diffusion Coefficient Parameters: Superiority of a One- versus Two-Parameter Pilot Method

Murakami, Ryuji; Hirai, Toshinori; Sugahara, Takeshi; Fukuoka, Hirofumi; Toya, Ryo; Nishimura, Shin‐Ichiro; Kitajima, Mika; Okuda, Tomoko; Nakamura, Hideo; Oya, Natsuo; Kuratsu, Jun Ichi; Yamashita, Yasuyuki

doi:10.1148/radiol.2513080899

Cited by 167 publications

(125 citation statements)

References 18 publications

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“…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). 62 However, the clinical usefulness of this technique remains limited because of overlap in the regional Fig. 7.…”

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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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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“…For instance, low-grade gliomas, high-grade gliomas, and lymphomas can be distinguished thanks to the measurement of the minimal ADC (19). The difference between minimal ADC and maximal ADC may also help to grade gliomas (20). Our study shows that such a measurement is technically feasible.…”

Section: Discussionmentioning

confidence: 73%

Interobserver and intraobserver variability of the apparent diffusion coefficient in treated malignant hepatic lesions on a 3.0T machine: Measurements in the whole lesion versus in the area with the most restricted diffusion

Meuli

Marques‐Vidal

et al. 2010

Magnetic Resonance Imaging

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Purpose: To assess the inter/intraobserver variability of apparent diffusion coefficient (ADC) measurements in treated hepatic lesions and to compare ADC measurements in the whole lesion and in the area with the most restricted diffusion (MRDA). Materials and Methods:Twenty-five patients with treated malignant liver lesions were examined on a 3.0T machine. After agreeing on the best ADC image, two readers independently measured the ADC values in the whole lesion and in the MRDA. These measurements were repeated 1 month later. The Bland-Altman method, Spearman correlation coefficients, and the Wilcoxon signed-rank test were used to evaluate the measurements. Conclusion: A limited variability in ADC measurements does exist, and it should be considered when interpreting ADC values of hepatic malignancies. This is especially true for the measurements of the minimal ADC.

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“…[1][2][3][4][5][6][7][8][9][10] Although these parameters are thought to correlate inversely with tumor cellularity, their clinical value remains controversial because of the significant overlap in ADC values among different tumors and different grades of malignancy. 6 -10 Although earlier studies set scanning parameters as identically as possible to ensure comparability of the instruments, they pointed to interimager variability in ADC values.…”

Section: Discussionmentioning

confidence: 99%

“…In addition, consensus measurements for ADC values must be established because potential observer bias may affect reported ADC values. 9,17 To eliminate interobserver variability in this study, a single observer measured ADC values. Technical improvements and diagnostic training may result in the acquisition of identical ADC values.…”

Section: ¹6mentioning

confidence: 99%

“…[1][2][3][4][5][6][7][8][9][10] However, earlier studies that measured the ADC values of white and gray matter encountered significant variability related to instrument vendors, imagers, coil systems, and field strengths used during magnetic resonance (MR) imaging. [11][12][13] In 2008, Sasaki and associates 12 reported approximately 15% lower ADC values generated by imagers from one vendor than other vendors.…”

Section: Introductionmentioning

confidence: 99%

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Interimager Variability in ADC Measurement of the Human Brain

et al. 2014

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Purpose: Routine clinical practice involves the application of diverse scanning parameters that can affect apparent diffusion coefficient (ADC) values. We evaluated interimager variability in ADC values with respect to their potential effect in clinical applications.Methods: In 7 healthy volunteers, we obtained diffusion-weighted (DW) images using routine clinical parameters and 1.5-(n = 9) and 3-tesla (n = 3) magnetic resonance (MR) imagers from 5 different vendors, performing 84 MR imaging studies. To evaluate the differences in ADC values among the imagers, vendors, and magnetic field strengths, we measured the mean pixel values of the frontal white matter and thalamus (gray matter) in both cerebral hemispheres of the 7 volunteers and used repeated-measures analysis of variance for multiple comparisons.Results: The laterality of ADC values in the bilateral structures ranged from one to 3% for the 12 imagers. Although the relative difference in ADC values of white matter was 7% for scanners yielding the highest and lowest mean ADC values (P < 0.01), it was within 2 to 4% for instruments from the same vendors. For gray matter, the interimager difference was 4 to 12%, even among the same vendors (P < 0.05). Among the 3T imagers, the difference for white and gray matter was approximately 3%.Conclusions: There were significant interimager differences in ADC values, especially with respect to gray matter. Taking into consideration the existing laterality, however, the differences among our 3T imagers may be acceptable despite the use of diverse scanning parameters. In routine clinical practice, the existing variability must be considered imager by imager.

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Grading Astrocytic Tumors by Using Apparent Diffusion Coefficient Parameters: Superiority of a One- versus Two-Parameter Pilot Method

Abstract: Using a combination of minimum ADCs and ADC difference values (the two-parameter method) facilitates the accurate grading of astrocytic tumors.

Cited by 167 publications

References 18 publications

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

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

Interobserver and intraobserver variability of the apparent diffusion coefficient in treated malignant hepatic lesions on a 3.0T machine: Measurements in the whole lesion versus in the area with the most restricted diffusion

Interimager Variability in ADC Measurement of the Human Brain

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