Characterization of prostate cancer using diffusion tensor imaging: A new perspective. Issue 110 (January 2019) - Gholizadeh, Neda; Greer, Peter B.; Simpson, John; Denham, Jim; Lau, Peter; Dowling, Jason; Hondermarck, Hubert; Ramadan, Saadallah
Highlights: Novel DTI parameters provide improved sensitivity and specificity in characterization and discrimination of prostate cancer tissues in vivo. Quantitative DTI parameters have the potential to provide imaging biomarkers in the detection and characterization of prostate cancer with perineural invasion. Using DTI tractography, higher fiber tract density was observed in advanced prostate cancer in vivo, in agreement with ex vivo neurogenesis. Abstract: Purpose: This study is aimed at evaluating the potential role of quantitative magnetic resonance diffusion tensor imaging (DTI) and tractography parameters in the detection and characterization of peripheral zone prostate cancer with a particular attention for fiber tract density. Materials and methods: DTI was acquired from eleven high risk, transrectal ultrasound (TRUS)-guided biopsy proven prostate cancers with perineural invasion (histological Gleason score ≥ 7) on a 3 T magnet. Twenty parameters derived from DTI were quantified in cancer and healthy regions of the prostate. In addition, fiber tract density in normal versus cancer tissues was also calculated using DTI tractography. Support vector machine with a radial basis function kernel and area under receiver operator characteristic (ROC) were used to describe and compare the diagnostic performance of combined fractional anisotropy (FA) and mean diffusivity (MD) and other statistically significant DTI parameters. Spearman correlation analysis between DTI parameters and Gleason scores was conducted. Results: Eighteen DTI parameters yielded statistically significant differences between cancer and healthy regions (p-value < 0.05). The ROC curve of all statistically significant DTI parameters between cancer and healthy regions was higher than the area under ROC curve using FA + MD alone (95% confidence interval = 0.988, range = 0.975–1.00) vs (95% confidence interval = 0.935, range = 0.898-0.999), respectively (p-value < 0.05). Fiber tract density was also found to be higher in cancer than in healthy tissues (+38.22%, p-value = 0.010) and may be related to the increase in nerve and vascular density reported in prostate cancer. The linear and relative anisotropy were highly correlated with Gleason score (Spearman correlation factor r = 0.655, p-value = 0.001 and r = 0.667, p-value < 0.001, respectively). Conclusions: DTI has the potential to provide imaging biomarkers in the detection and characterization of prostate cancer. Novel quantitative parameters derived from DTI and DTI tractography, including fiber tract density, support the use of DTI in the assessment of high grade prostate cancer.