PURPOSE: The aim of this study was to use intravoxel incoherent motion diffusion-weighted imaging to discriminate subtypes of renal neoplasms and to assess agreement between intravoxel incoherent motion (perfusion fraction, fp) and dynamic contrast-enhanced magnetic resonance imaging (MRI) metrics of tumor vascularity. SUBJECTS AND METHODS: In this Health Insurance Portability and Accountability Act-compliant, institutional review board-approved prospective study, 26 patients were imaged at 1.5-T MRI using dynamic contrast-enhanced MRI with high temporal resolution and diffusion-weighted imaging using 8 b values (range, 0-800 s/mm). Perfusion fraction (fp), tissue diffusivity (Dt), and pseudodiffusivity (Dp) were calculated using biexponential fitting of the diffusion data. Apparent diffusion coefficient (ADC) was calculated with monoexponential fit using 3 b values of 0, 400, and 800 s/mm. Dynamic contrast-enhanced data were processed with a semiquantitative method to generate model-free parameter cumulative initial area under the curve of gadolinium concentration at 60 seconds (CIAUC60). Perfusion fraction, Dt, Dp, ADC, and CIAUC60 were compared between different subtypes of renal lesions. Perfusion fraction was correlated with CIAUC60. RESULTS: We examined 14 clear cell, 4 papillary, 5 chromophobe, and 3 cystic renal cell carcinomas (RCCs). Although fp had higher accuracy (area under the curve, 0.74) for a diagnosis of clear cell RCC compared with Dt or ADC, the combination of fp and Dt had the highest accuracy (area under the curve, 0.78). The combination of fp and Dt diagnosed papillary RCC and cystic RCC with 100% accuracy, and clear cell RCC and chromophobe RCC, with 86.5% accuracy. There was significant strong correlation between fp and CIAUC60 (r = 0.82; P < 0.001). CONCLUSION: Intravoxel incoherent motion parameters fp and Dt can discriminate renal tumor subtypes. Perfusion fraction demonstrates good correlation with CIAUC60 and can assess degree of tumor vascularity without the use of exogenous contrast agent.
PURPOSE: The aim of this study was to use intravoxel incoherent motion diffusion-weighted imaging to discriminate subtypes of renal neoplasms and to assess agreement between intravoxel incoherent motion (perfusion fraction, fp) and dynamic contrast-enhanced magnetic resonance imaging (MRI) metrics of tumor vascularity. SUBJECTS AND METHODS: In this Health Insurance Portability and Accountability Act-compliant, institutional review board-approved prospective study, 26 patients were imaged at 1.5-T MRI using dynamic contrast-enhanced MRI with high temporal resolution and diffusion-weighted imaging using 8 b values (range, 0-800 s/mm). Perfusion fraction (fp), tissue diffusivity (Dt), and pseudodiffusivity (Dp) were calculated using biexponential fitting of the diffusion data. Apparent diffusion coefficient (ADC) was calculated with monoexponential fit using 3 b values of 0, 400, and 800 s/mm. Dynamic contrast-enhanced data were processed with a semiquantitative method to generate model-free parameter cumulative initial area under the curve of gadolinium concentration at 60 seconds (CIAUC60). Perfusion fraction, Dt, Dp, ADC, and CIAUC60 were compared between different subtypes of renal lesions. Perfusion fraction was correlated with CIAUC60. RESULTS: We examined 14 clear cell, 4 papillary, 5 chromophobe, and 3 cystic renal cell carcinomas (RCCs). Although fp had higher accuracy (area under the curve, 0.74) for a diagnosis of clear cell RCC compared with Dt or ADC, the combination of fp and Dt had the highest accuracy (area under the curve, 0.78). The combination of fp and Dt diagnosed papillary RCC and cystic RCC with 100% accuracy, and clear cell RCC and chromophobe RCC, with 86.5% accuracy. There was significant strong correlation between fp and CIAUC60 (r = 0.82; P < 0.001). CONCLUSION: Intravoxel incoherent motion parameters fp and Dt can discriminate renal tumor subtypes. Perfusion fraction demonstrates good correlation with CIAUC60 and can assess degree of tumor vascularity without the use of exogenous contrast agent.
Authors: Thomas Hauser; Marco Essig; Alexandra Jensen; Lars Gerigk; Frederik Bernd Laun; Marc Münter; Dirk Simon; Bram Stieltjes Journal: Neuroradiology Date: 2013-02-17 Impact factor: 2.804
Authors: Behzad Ebrahimi; Naveen Rihal; John R Woollard; James D Krier; Alfonso Eirin; Lilach O Lerman Journal: Invest Radiol Date: 2014-10 Impact factor: 6.016