OBJECTIVE: To compare 2 previously presented algorithms for extracting parameters from intravoxel incoherent motion (IVIM) studies and investigate them in the context of tissue differentiation. METHODS: Magnetic resonance imaging (MRI) was performed in 23 patients without histologically proven prostate carcinoma (PCa) and 27 patients with histologically proven PCa. Two methods were used to determine IVIM parameters (f, D, D*). Receiver operating characteristic analysis was performed for IVIM parameters and apparent diffusion coefficient for discrimination of prostate tissue. RESULTS: The IVIM parameters showed no significant difference between patients without PCa and normal areas in patients with PCa (r = 0.46-0.99). Results for D were not significantly different for both methods (P = 0.22), whereas f from method 1 was significantly higher than the f from method 2 (P < 0.05). The diffusion parameters D (both methods) and apparent diffusion coefficient could discriminate between tumor and normal areas (receiver operating characteristic analysis, area under the curve, ≥0.90). Additionally, in subgroup analysis, only D was able to discriminate between low- and high-grade PCa. CONCLUSIONS: For tumor detection, IVIM diffusion does not yield a clear added value, but the perfusion-free diffusion constant D may hold potential for improved image-based tumor grading.
OBJECTIVE: To compare 2 previously presented algorithms for extracting parameters from intravoxel incoherent motion (IVIM) studies and investigate them in the context of tissue differentiation. METHODS: Magnetic resonance imaging (MRI) was performed in 23 patients without histologically proven prostate carcinoma (PCa) and 27 patients with histologically proven PCa. Two methods were used to determine IVIM parameters (f, D, D*). Receiver operating characteristic analysis was performed for IVIM parameters and apparent diffusion coefficient for discrimination of prostate tissue. RESULTS: The IVIM parameters showed no significant difference between patients without PCa and normal areas in patients with PCa (r = 0.46-0.99). Results for D were not significantly different for both methods (P = 0.22), whereas f from method 1 was significantly higher than the f from method 2 (P < 0.05). The diffusion parameters D (both methods) and apparent diffusion coefficient could discriminate between tumor and normal areas (receiver operating characteristic analysis, area under the curve, ≥0.90). Additionally, in subgroup analysis, only D was able to discriminate between low- and high-grade PCa. CONCLUSIONS: For tumor detection, IVIM diffusion does not yield a clear added value, but the perfusion-free diffusion constant D may hold potential for improved image-based tumor grading.
Authors: Filippo Pesapane; Francesca Patella; Enrico Maria Fumarola; Silvia Panella; Anna Maria Ierardi; Giovanni Guido Pompili; Giuseppe Franceschelli; Salvatore Alessio Angileri; Alberto Magenta Biasina; Gianpaolo Carrafiello Journal: Med Oncol Date: 2017-01-31 Impact factor: 3.064
Authors: Pelin Aksit Ciris; Jr-Yuan George Chiou; Daniel I Glazer; Tzu-Cheng Chao; Clare M Tempany-Afdhal; Bruno Madore; Stephan E Maier Journal: Invest Radiol Date: 2019-04 Impact factor: 6.016
Authors: Casey Vieni; Benjamin Ades-Aron; Bettina Conti; Eric E Sigmund; Peter Riviello; Timothy M Shepherd; Yvonne W Lui; Dmitry S Novikov; Els Fieremans Journal: Neuroimage Date: 2019-09-30 Impact factor: 6.556
Authors: Yin Xi; Alexander Liu; Franklin Olumba; Parker Lawson; Daniel N Costa; Qing Yuan; Gaurav Khatri; Takeshi Yokoo; Ivan Pedrosa; Robert E Lenkinski Journal: Quant Imaging Med Surg Date: 2018-07