Apparent Diffusion Coefficient Value Is Not Dependent on Magnetic Resonance Systems and Field Strength Under Fixed Imaging Parameters in Brain

Ogura, Akio; Tamura, Takayuki; Ozaki, Masanori; Doi, Tsukasa; Fujimoto, Koji; Miyati, Tosiaki; Ito, Yukiko; Maeda, Fumie; Tarewaki, Hiroyuki; Takahashi, M

doi:10.1097/rct.0000000000000266

Cited by 33 publications

(15 citation statements)

References 37 publications

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“…It would be better to conduct a study using an identical scanner, even though the diffusion signal decay does not depend on the field strength. 27,28 Finally, in this study, no significant difference was observed between Frac < 0.3 and Frac < 0.5. Further investigation to identify the parameter that is most suitable for the discrimination of tumor grades is needed.…”

Section: Discussioncontrasting

confidence: 56%

Analysis of Diffusion-weighted MR Images Based on a Gamma Distribution Model to Differentiate Prostate Cancers with Different Gleason Score

et al. 2020

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Prostate cancer management includes identification of clinically significant cancers that may require curative treatment. Statistical models based on gamma distribution can describe diffusion signal decay curves of prostate cancer. The purpose of this study was to evaluate the ability of parameters obtained with the gamma model in differentiating prostate cancers with different Gleason score values. Methods: This study included 155 patients with prostate cancer who underwent multiparametric magnetic resonance imaging prior to prostate biopsy (127 patients) or radical prostatectomy (28 patients) between January 2015 and June 2017; 159 foci of prostate cancer were included in our study. We compared cases scored as Gleason score (GS) 3 + 3 and GS ≥ 3 + 4, and analyzed cases scored as GS ≤ 3+ 4 and GS ≥ 4 + 3 based on the gamma model (Frac < 1.0, Frac < 0.8, Frac < 0.5, Frac < 0.3, and Frac > 3.0), and apparent diffusion coefficient (ADC). Results: Among 159 cancerous lesions in 155 patients, 13 (8.2%) were GS 3 + 3 prostate cancers, 51 (32.0%) were GS 3 + 4 prostate cancers, 30 (18.2%) were GS 4 + 3 cancers, and 65 (40.9%) were GS ≥ 4 + 4 cancers. Frac < 0.3, Frac < 0.5, Frac < 0.8, and Frac < 1.0 were significantly higher and ADC values were significantly lower in GS ≥ 4 + 3 cancers than in GS ≤ 3 + 4 cancers (P < 0.01, P < 0.01, P < 0.01, P = 0.01, and P < 0.01, respectively). With receiver operating characteristic (ROC) analysis, Frac < 0.3 and Frac < 0.5 had significantly greater area under the ROC curve for discriminating GS ≥ 4 + 3 cancers from GS ≤ 3 + 4 cancers than ADC (P = 0.03, P < 0.01, respectively). Conclusion: Frac < 0.3 and Frac < 0.5 showed higher diagnostic performance than ADC for differentiating GS ≥ 4 + 3 from GS ≤ 3 + 4 cancers. The gamma model may add additional value in discrimination of tumor grades.

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Section: Discussioncontrasting

confidence: 56%

Analysis of Diffusion-weighted MR Images Based on a Gamma Distribution Model to Differentiate Prostate Cancers with Different Gleason Score

et al. 2020

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“…It should be noticed that our MR scanners with different field strengths were from different vendors. Contradicting results of how ADCs of the liver parenchyma, [ 10 , 12 , 30 ] some other organs of the abdomen, and the brain [ 25 , 31 , 32 ] were affected by different field strengths have been reported in literatures. For instance, Dale et al [ 30 ] found that hepatic ADCs at 3.0T MR were higher than those at 1.5T MR and assumed that the noise floor issues from lower signal-to-noise ratio (SNR) reduced ADC values.…”

Section: Discussionmentioning

confidence: 96%

“…[ 31 , 33 ] As ADC value was affected by SNR of high b values in liver, it is important for 3.0T MR scanners to have high SNR with improved imaging techniques and reasonable diffusion-weighted parameters to get precise ADC values. [ 11 , 32 ]…”

Section: Discussionmentioning

confidence: 99%

Apparent diffusion coefficient normalization of normal liver

Zhang¹,

Gao²,

Li³

et al. 2017

Medicine

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Apparent diffusion coefficient (ADC) measurement in diffusion-weighted imaging (DWI) has been reported to be a helpful biomarker for detection and characterization of lesion. In view of the importance of ADC measurement reproducibility, the aim of this study was to probe the variability of the healthy hepatic ADC values measured at 3 MR scanners from different vendors and with different field strengths, and to investigate the reproducibility of normalized ADC (nADC) value with the spleen as the reference organ. Thirty enrolled healthy volunteers received DWI with GE 1.5T, Siemens 1.5T, and Philips 3.0T magnetic resonance (MR) systems on liver and spleen (session 1) and were imaged again after 10 to 14 days using only GE 1.5T MR and Philips 3.0T MR systems (session 2). Interscan agreement and reproducibility of ADC measurements of liver and the calculated nADC values (ADCliver/ADCspleen) were statistically evaluated between 2 sessions. In session 1, ADC and nADC values of liver were evaluated for the scanner-related variability by 2-way analysis of variance and intraclass correlation coefficients (ICCs). Coefficients of variation (CVs) of ADCs and nADCs of liver were calculated for both 1.5 and 3.0-T MR system. Interscan agreement and reproducibility of ADC measurements of liver and related nADCs between 2 sessions were found to be satisfactory with ICC values of 0.773 to 0.905. In session 1, the liver nADCs obtained from different scanners were consistent (P = 0.112) without any significant difference in multiple comparison (P = 0.117 to >0.99) by using 2-way analysis of variance with post-hoc analysis of Bonferroni method, although the liver ADCs varied significantly (P < 0.001). nADCs measured by 3 scanners were in good interscanner agreements with ICCs of 0.685 to 0.776. The mean CV of nADCs of both 1.5T MR scanners (9.6%) was similar to that of 3.0T MR scanner (8.9%). ADCs measured at 3 MR scanners with different field strengths and vendors could not be compared directly. Normalization of ADCs, however, may provide better reproducibility by overcoming these potential issues.

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“…Another potential limitation is MRI acquisition in two different field strengths and on various scanners, though this should not substantially affect ADC values obtained with repetition time >3000 ms and b value of 1000 sec/mm 2 . 16 Manual segmentation of the solid segments of tumor and visual assessment of the tumor morphology can limit the generalization of the results. In addition, the ADC maps were not coregistered and resliced before segmentation.…”

Section: Discussionmentioning

confidence: 99%

Differentiation of Cerebellar Hemisphere Tumors: Combining Apparent Diffusion Coefficient Histogram Analysis and Structural MRI Features

Payabvash

Tihan

2018

Journal of Neuroimaging

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In pretreatment differentiation of cerebellar tumors, the ADC histogram analysis is particularly helpful for distinction of medulloblastomas from other subtypes, and differentiation of the two most common adult tumors (ie, metastases and hemangioblastomas) from each other. Combination of structural imaging features and ADC histogram analysis can help with pretreatment differentiation of cerebellar tumors.

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Apparent Diffusion Coefficient Value Is Not Dependent on Magnetic Resonance Systems and Field Strength Under Fixed Imaging Parameters in Brain

Abstract: The variance in the ADC values for different MR scanners is reasonably small if appropriate scanning parameters (repetition time, >3000 ms; echo time, minimum; and high enough signal-to-noise ratio of high-b diffusion-weighted image) are used.

Cited by 33 publications

References 37 publications

Analysis of Diffusion-weighted MR Images Based on a Gamma Distribution Model to Differentiate Prostate Cancers with Different Gleason Score

Analysis of Diffusion-weighted MR Images Based on a Gamma Distribution Model to Differentiate Prostate Cancers with Different Gleason Score

Apparent diffusion coefficient normalization of normal liver

Differentiation of Cerebellar Hemisphere Tumors: Combining Apparent Diffusion Coefficient Histogram Analysis and Structural MRI Features

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