Correlative assessment of tumor microcirculation using contrast‐enhanced perfusion MRI and intravoxel incoherent motion diffusion‐weighted MRI: is there a link between them?

Bisdas, Sotirios; Braun, Christian; Skardelly, Marco; Schittenhelm, Jens; Teo, Tze Hern; Thng, Choon Hua; Klose, Uwe; Koh, Tong San

doi:10.1002/nbm.3172

Cited by 52 publications

(49 citation statements)

References 42 publications

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“…In the liver perfusion parameters from IVIM do not correlate with those from model-free DCE-MRI (12). Additionally, Bisdas et al (11) also reported no evident correlation between perfusion parameters from IVIM and DSC- or DCE-MRI in patients with cerebral glioma. Our current results are very similar to these results, emphasizing no significant correlation between perfusion parameters from IVIM and DCE-MRI.…”

Section: Discussionmentioning

confidence: 99%

“…Whether the perfusion parameters from IVIM could be surrogate markers to the established perfusion markers from perfusion MRI in tumor imaging is unclear (1112131415222324). In terms of the head and neck, several studies have investigated the correlation between IVIM and DCE-MRI parameters.…”

Section: Discussionmentioning

confidence: 99%

“…Recently, several studies demonstrated the correlation between parameters from IVIM and those from DCE-MRI in the brain, liver, uterine cervix, and in the head and neck (1112131415). Among these studies, the correlation between IVIM and DCE-MRI parameters in the head and neck was studied either by focusing on nasopharyngeal cancer or using a two-compartment model for DCE-MRI analysis (1415).…”

Section: Introductionmentioning

confidence: 99%

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Intravoxel Incoherent Motion MR Imaging in the Head and Neck: Correlation with Dynamic Contrast-Enhanced MR Imaging and Diffusion-Weighted Imaging

Choi

Sung

et al. 2016

Korean J Radiol

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ObjectiveTo investigate the correlation between perfusion- and diffusion-related parameters from intravoxel incoherent motion (IVIM) and those from dynamic contrast-enhanced MR imaging (DCE-MRI) and diffusion-weighted imaging in tumors and normal muscles of the head and neck.Materials and MethodsWe retrospectively enrolled 20 consecutive patients with head and neck tumors with MR imaging performed using a 3T MR scanner. Tissue diffusivity (D), pseudo-diffusion coefficient (D*), and perfusion fraction (f) were derived from bi-exponential fitting of IVIM data obtained with 14 different b-values in three orthogonal directions. We investigated the correlation between D, f, and D* and model-free parameters from the DCE-MRI (wash-in, Tmax, Emax, initial AUC60, whole AUC) and the apparent diffusion coefficient (ADC) value in the tumor and normal masseter muscle using a whole volume-of-interest approach. Pearson's correlation test was used for statistical analysis.ResultsNo correlation was found between f or D* and any of the parameters from the DCE-MRI in all patients or in patients with squamous cell carcinoma (p > 0.05). The ADC was significantly correlated with D values in the tumors (p < 0.001, r = 0.980) and muscles (p = 0.013, r = 0.542), despite its significantly higher value than D. The difference between ADC and D showed significant correlation with f values in the tumors (p = 0.017, r = 0.528) and muscles (p = 0.003, r = 0.630), but no correlation with D* (p > 0.05, respectively).ConclusionIntravoxel incoherent motion shows no significant correlation with model-free perfusion parameters derived from the DCE-MRI but is feasible for the analysis of diffusivity in both tumors and normal muscles of the head and neck.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Intravoxel Incoherent Motion MR Imaging in the Head and Neck: Correlation with Dynamic Contrast-Enhanced MR Imaging and Diffusion-Weighted Imaging

Choi

Sung

et al. 2016

Korean J Radiol

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“…21 D* is dependent on both blood velocity and mean capillary segment length, 13 which are heterogeneous in the tortuous tumor vasculature. Indeed, we observed poor repeatability for D* in HCC lesions, which is consistent with recent studies on repeatability of IVIM-DWI metrics in liver and HCC 18 and in liver metastases.…”

Section: Discussionmentioning

confidence: 99%

Intravoxel incoherent motion diffusion‐weighted imaging of hepatocellular carcinoma: Is there a correlation with flow and perfusion metrics obtained with dynamic contrast‐enhanced MRI?

Hectors

Wagner

Besa

et al. 2016

Magnetic Resonance Imaging

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Purpose To assess the correlation between intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) metrics in hepatocellular carcinoma (HCC) and liver parenchyma. Materials and Methods Twenty-five patients with HCC (M/F 23/2, mean age 58 years) underwent abdominal MRI at 1.5 or 3.0T, including IVIM-DWI (with 16 b-values) and DCE-MRI (3D FLASH sequence, mean temporal resolution of 2.3 sec). IVIM-DWI parameters (pseudodiffusion coefficient, D*, diffusion coefficient, D, and perfusion fraction, PF) were quantified in HCC lesions and liver parenchyma using a Bayesian fitting algorithm. DCE-MRI parameters (arterial flow, Fa, portal flow, Fp, total flow, Ft, mean transit time, MTT, distribution volume, DV, and arterial fraction, ART) were quantified using a dual-input single-compartment model. Correlations between IVIM-DWI and DCE-MRI parameters were assessed using a Spearman correlation test. Results Thirty-three HCC lesions (average size 5.0 ± 3.6 cm) were analyzed. D, D*, and PF were all significantly lower in HCC vs. liver (P < 0.05). Significantly higher Fa and ART and lower Fp were observed in HCC vs. liver (P < 0.001). Significant moderate to strong negative correlations were observed between ART and D* (r = −0.443, P = 0.028), ART and PF (r = −0.536, P = 0.006), ART and PFxD* (r = −0.655, P < 0.001), Fa and PF (r = 0.455, P = 0.023), and Fa and PFxD* (r = −0.475, P = 0.018) in liver parenchyma. There was no significant correlation between IVIM-DWI and DCE-MRI metrics in HCC lesions. Conclusion IVIM-DWI and DCE-MRI provide nonredundant information in HCC, while they correlate in liver parenchyma. These findings may be secondary to predominant portal inflow in the liver and tortuous vasculature and tissue heterogeneity in tumors.

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“…The fast ADC-bi values of the tumor and the normal rectal wall were much bigger than fast ADC-mono values of both, which showed that the IVIM-bi model may overestimate the proportion of perfusion in water diffusivity. Moreover, some studies21242526 found that there was no or weak correlation between fast-ADC and CBF, f value and CBV, which meant that fast-ADC and f value might not represent the true perfusion in the tumor. The AUC of fast-ADC was smaller than that of slow-ADC, which demonstrated the lower diagnostic efficiency of fast-ADC in the discriminating malignant lesions and normal tissue.…”

Section: Discussionmentioning

confidence: 99%

Comparison of non-Gaussian and Gaussian diffusion models of diffusion weighted imaging of rectal cancer at 3.0 T MRI

Zhang

Wang

Wen

et al. 2016

Sci Rep

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Water molecular diffusion in vivo tissue is much more complicated. We aimed to compare non-Gaussian diffusion models of diffusion-weighted imaging (DWI) including intra-voxel incoherent motion (IVIM), stretched-exponential model (SEM) and Gaussian diffusion model at 3.0 T MRI in patients with rectal cancer, and to determine the optimal model for investigating the water diffusion properties and characterization of rectal carcinoma. Fifty-nine consecutive patients with pathologically confirmed rectal adenocarcinoma underwent DWI with 16 b-values at a 3.0 T MRI system. DWI signals were fitted to the mono-exponential and non-Gaussian diffusion models (IVIM-mono, IVIM-bi and SEM) on primary tumor and adjacent normal rectal tissue. Parameters of standard apparent diffusion coefficient (ADC), slow- and fast-ADC, fraction of fast ADC (f), α value and distributed diffusion coefficient (DDC) were generated and compared between the tumor and normal tissues. The SEM exhibited the best fitting results of actual DWI signal in rectal cancer and the normal rectal wall (R2 = 0.998, 0.999 respectively). The DDC achieved relatively high area under the curve (AUC = 0.980) in differentiating tumor from normal rectal wall. Non-Gaussian diffusion models could assess tissue properties more accurately than the ADC derived Gaussian diffusion model. SEM may be used as a potential optimal model for characterization of rectal cancer.

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Correlative assessment of tumor microcirculation using contrast‐enhanced perfusion MRI and intravoxel incoherent motion diffusion‐weighted MRI: is there a link between them?

Cited by 52 publications

References 42 publications

Intravoxel Incoherent Motion MR Imaging in the Head and Neck: Correlation with Dynamic Contrast-Enhanced MR Imaging and Diffusion-Weighted Imaging

Intravoxel Incoherent Motion MR Imaging in the Head and Neck: Correlation with Dynamic Contrast-Enhanced MR Imaging and Diffusion-Weighted Imaging

Intravoxel incoherent motion diffusion‐weighted imaging of hepatocellular carcinoma: Is there a correlation with flow and perfusion metrics obtained with dynamic contrast‐enhanced MRI?

Comparison of non-Gaussian and Gaussian diffusion models of diffusion weighted imaging of rectal cancer at 3.0 T MRI

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