The most significant finding in this study is that the measured DTI anisotropy parameter (FA) and diffusivity parameter (MD) had higher sensitivity and diagnostic accuracy in evaluation of the aggressiveness of prostate cancer in correlation with Gleason score, pathological scoring system, and PSA levels.
This study was carried out on 50 patients. The highest prevalence of prostate cancer among this study population was between (70 and 79 years old); this copes with the recorded age incidence of prostate cancer [8, 17]. Clinically speaking, age is considered a significant non-modifiable risk factor for PCa [18, 19]. Some risk factors of PCa can be affected by aging, such as immunity, cholesterol metabolism, obesity, free testosterone levels, and genetic effects .
In prostate cancer, FA and MD vary because of altered diffusivity and disorganization of the fibers. (MD) has been used to describe the strength of diffusion in biological tissues which is valid only for homogeneous fluid with free diffusion, diffusion can be hindered or restricted, and result in decreased MD .
Fractional anisotropy defines the degree of anisotropy and reflects the degree of alignment of cellular structures and measures the total magnitude of water directional movement along the fibers . In this study, to be more accurate in determination of the FA and MD, especially in large heterogonous lesions, we used the ROI in the portion of the tumor showing the highest SI on DWi and the lowest SI on ADC map, compared with the signal from the adjacent tumoral tissue. . We used the ellipse ROI, as it was suggested to be a simpler and appropriate method for MD measurement in PCa .
In this study, the mean FA detected among the control group (N = 20) was (0.219 ± 0.028); however, the mean FA among the patient group (N = 50) was (0.327 ± 0.065) with the cutoff point of FA value among the 70 male included in this study was (≥ 0.245) above which the detected lesion is considered a cancer lesion with 84% sensitivity and 80% specificity.
The mean MD value was detected among control group (N = 20) (1.69 ± 0.183 × 10–3 mm2/sec); however, MD value detected among the patient group (N = 50) was (0.745 ± 0.180 × 10–3 mm2/sec). The cutoff point of MD value among the 70 males included at this study was (≤ 1.075) below which the detected lesion is considered a cancer.
The greater FA values of cancer lesions than FA values of normal tissues as well as the lesser mean cancerous tissue MD values than the normal values coincide with Onya A., et al. who reported on 2017 that FA of cancerous tissue is higher than of normal tissues . This also agreed with Li L., et al. who concluded on 2015 that elevated FA values and reduced MD values in prostate cancer at 3 T MRI machine .
Gholizadeh N., et al. also on 2019 showed reduced diffusivity (MD) and elevated fractional anisotropy (FA) values of cancer foci from several DTI maps suggesting increased cellularity or overcrowded cancerous tissues . This can be explained as the increased intracellular viscosity and the number of cell membranes in cancerous tissues leads to diffusion directionality and restricted diffusion, whereas water diffusion in benign tissue is fairly isotropic with low FA and high MD .
This is partially contradicted to the results by Manenti G., et al. on 2007 who detected significant reduction in MD and FA measurements in PZ prostate cancer compared to healthy areas . He related the decreased FA value to the nature of tumorous tissues, which were described as areas of absent or reduced fibers. This can be explained by a shift of the adjacent healthy tissues “fibers.” FA values were reduced in the tumor area, contrary to the surrounding healthy tissue, because of the disorganized structure of the tumor itself (tumoral necrosis or degeneration) .
High-grade tumors having high cellularity with packed cells this will have elevated levels of FA; on the other hand, tumors of low grade showing decreased cellularity with cells that are randomly arranged will have decreased FA [3, 7]. Diffusion is more restricted and hindered in the cases of poorly formed/fused/cribriform glands that significantly reduce MD values in high-grade tumors .
PSA level showed decreased specificity in prostate cancer diagnosis, because of its false positive results in benign diseases as prostatitis and BPH; consequently, increased PSA does not essentially demonstrate the presence of PCa . Moreover, its normal level does not rule out the presence of PCa. On the other hand, evaluation of PSA is still utilized because of absence effective biomarkers in detection of PCa [28, 29]. This coincides with our results as PSA showed a statically insignificant very low positive correlation with FA, and a statistically significant negative correlation with MD.
In this study, we found that the FA showed high positive correlation with Gleason score (p value < 0.001) which is statically significant. Furthermore, we found that MD showed negative correlation with Glasson score with statistically significant results (p value = 0.013). These alterations may be because of the progressively dense arrangement of cells in the tumors of high grades; additionally, the extracellular space decreases . This coincides with Tian W, et al.  who found nearly the same results.
This is not consistent with Wang S, et al. who reported a negative correlation between the values of FA and Gleason scores, signifying that an elevation in Gleason scores will lead to a slowly decrease in the value of FA . Nezzo M, et al. documented no correlation between the value of FA and Gleason score. This conflict in FA correlation with prostate cancerous tissues may be related to the difference in the parameters of acquisition protocols and/or post-processing techniques .
The limitations of this study could be summarized in the small number of patients enrolled in the study, together with absence of follow-up DTI for the patients. No fusion or cognitive biopsy on the suspected lesion was observed. Another limitation of this study was carried out in a single-center study, on one type of MRI scanner. It is well known that diffusion imaging, including DTI, is very dependent on the scanner type as well as the imaging protocol and modeling.