scholarly journals The Role of Diffusion-Weighted Imaging and the Apparent Diffusion Coefficient (ADC) Values for Breast Tumors

2007 ◽  
Vol 8 (5) ◽  
pp. 390 ◽  
Author(s):  
Mi Jung Park ◽  
Eun Suk Cha ◽  
Bong Joo Kang ◽  
Yon Kwon Ihn ◽  
Jun Hyun Baik
Keyword(s):  
Diffusion Coefficient ◽  
Apparent Diffusion Coefficient ◽  
Diffusion Weighted Imaging ◽  
Breast Tumors ◽  
Diffusion Weighted ◽  
Apparent Diffusion ◽  
Adc Values

Effects of contrast-enhancement on diffusion weighted imaging and apparent diffusion coefficient measurements in 3-T magnetic resonance imaging of breast lesions

2017 ◽  
Vol 59 (8) ◽  
pp. 902-908
Author(s):  
Valentina Cipolla ◽  
Daniele Guerrieri ◽  
Giacomo Bonito ◽  
Simone Celsa ◽  
Carlo de Felice
Keyword(s):  
Diffusion Coefficient ◽  
Apparent Diffusion Coefficient ◽  
Diffusion Weighted Imaging ◽  
Breast Lesions ◽  
Post Contrast ◽  
Diffusion Weighted ◽  
Signed Rank ◽  
Apparent Diffusion ◽  
Malignant Breast ◽  
Adc Values

Background The effect of gadolinium-based contrast agents on diffusion-weighted imaging (DWI) measurements of breast lesions is still not clear. Purpose To investigate gadolinium effects on DWI and apparent diffusion coefficient (ADC) in breast lesions and normal parenchyma with 3 Tesla contrast-enhanced MRI. Material and Methods Pre- and post-contrast DWI (b = 0 and b = 1000 s/mm2) were acquired in 47 patients. Measured ADC values, pre- and post-contrast T2 signal intensity (T2 SI) and contrast-to-noise ratio (CNR) were compared with Wilcoxon signed-rank and rank-sum test ( P < 0.05). Results Post-contrast ADC was reduced only in malignant lesions (−34%), T2 SI was reduced both in malignant (−50%) and benign (−36%) lesions. Post-contrast CNR was reduced in all groups except for benign lesions. Conclusion Gadolinium-based contrast agent causes a significant reduction in ADC values of malignant breast lesions.

scholarly journals Diffusion-Weighted Imaging Reflects Tumor Grading and Microvascular Invasion in Hepatocellular Carcinoma

Liver Cancer ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 10-24
Author(s):  
Alexey Surov ◽  
Maciej Pech ◽  
Jazan Omari ◽  
Frank Fischbach ◽  
Robert Damm ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Diffusion Coefficient ◽  
Diffusion Weighted Imaging ◽  
Microvascular Invasion ◽  
Data Bases ◽  
Tumor Grading ◽  
Diffusion Weighted ◽  
Apparent Diffusion ◽  
Adc Values

<b><i>Background:</i></b> To date, there are inconsistent data about relationships between diffusion-weighted imaging (DWI) and tumor grading/microvascular invasion (MVI) in hepatocellular carcinoma (HCC). Our purpose was to systematize the reported results regarding the role of DWI in prediction of tumor grading/MVI in HCC. <b><i>Method:</i></b> MEDLINE library, Scopus, and Embase data bases were screened up to December 2019. Overall, 29 studies with 2,715 tumors were included into the analysis. There were 20 studies regarding DWI and tumor grading, 8 studies about DWI and MVI, and 1 study investigated DWI, tumor grading, and MVI in HCC. <b><i>Results:</i></b> In 21 studies (1,799 tumors), mean apparent diffusion coefficient (ADC) values (ADC<sub>mean</sub>) were used for distinguishing HCCs. ADC<sub>mean</sub> of G1–3 lesions overlapped significantly. In 4 studies (461 lesions), minimum ADC (ADC<sub>min</sub>) was used. ADC<sub>min</sub> values in G1/2 lesions were over 0.80 × 10<sup>−3</sup> mm<sup>2</sup>/s and in G3 tumors below 0.80 × 10<sup>−3</sup> mm<sup>2</sup>/s. In 4 studies (241 tumors), true diffusion (<i>D</i>) was reported. A significant overlapping of <i>D</i> values between G1, G2, and G3 groups was found. ADC<sub>mean</sub> and MVI were analyzed in 9 studies (1,059 HCCs). ADC<sub>mean</sub> values of MIV+/MVI− lesions overlapped significantly. ADC<sub>min</sub> was used in 4 studies (672 lesions). ADC<sub>min</sub> values of MVI+ tumors were in the area under 1.00 × 10<sup>−3</sup> mm<sup>2</sup>/s. In 3 studies (227 tumors), <i>D</i> was used. Also, <i>D</i> values of MVI+ lesions were predominantly in the area under 1.00 × 10<sup>−3</sup> mm<sup>2</sup>/s. <b><i>Conclusion:</i></b> ADC<sub>min</sub> reflects tumor grading, and ADC<sub>min</sub> and <i>D</i> predict MVI in HCC. Therefore, these DWI parameters should be estimated for every HCC lesion for pretreatment tumor stratification. ADC<sub>mean</sub> cannot predict tumor grading/MVI in HCC.

scholarly journals Quantitative Evaluation of apparent diffusion coefficient in a large multi-unit institution using the QIBA diffusion phantom.

2020 ◽  
Author(s):  
Joshua P Yung ◽  
Yao Ding ◽  
Ken-Pin Hwang ◽  
Carlos E Cardenas ◽  
Hua Ai ◽  
...  
Keyword(s):  
Diffusion Coefficient ◽  
Apparent Diffusion Coefficient ◽  
Coefficient Of Variation ◽  
Diffusion Weighted Imaging ◽  
Diffusion Weighted ◽  
Apparent Diffusion Coefficient Values ◽  
Wide Range ◽  
Apparent Diffusion ◽  
Adc Values ◽  
The One

Purpose: The purpose of this study was to determine the quantitative variability of diffusion weighted imaging and apparent diffusion coefficient values across a large fleet of MR systems. Using a NIST traceable magnetic resonance imaging diffusion phantom, imaging was reproducible and the measurements were quantitatively compared to known values. Methods: A fleet of 23 clinical MRI scanners was investigated in this study. A NIST/QIBA DWI phantom was imaged with protocols provided with the phantom. The resulting images were analyzed and ADC maps were generated. User-directed region-of-interests on each of the different vials provided ADC measurements among a wide range of known ADC values. Results: Three diffusion phantoms were used in this study and compared to one another. From the one-way analysis of the variance, the mean and standard deviation of the percent errors from each phantom were not significantly different from one another. The low ADC vials showed larger errors and variation and appear directly related to SNR. Across all the MR systems and data, the coefficient of variation was calculated and Bland-Altman analysis was performed. ADC measurements were similar to one another except for the vials with the lower ADC values, which had a higher coefficient of variation. Conclusion: ADC values among the three phantoms showed good agreement and were not significantly different from one another. The large percent errors seen primarily at the low ADC values were shown to be a consequence of the SNR dependence and very little bias was observed between magnetic strengths and manufacturers. ADC values between diffusion phantoms were not statistically significant. Future investigations will be performed to study differences in magnetic field strength, vendor, MR system models, gradients, and bore size. More data across different MR platforms would facilitate quantitative measurements for multi-platform and multi-site imaging studies. With the increasing usage of diffusion weighted imaging in the clinic, the characterization of ADC variability for MR systems provides an improved quality control over the MR systems.

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