الفهرس 
ANATOMY OF THE PROSTATE GLANDOnly 14 pages are availabe for public view
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Abstract
Magnetic resonance imaging (MRI) assessment of prostate cancer has a number of important limitations including a restricted ability to demonstrate microscopic and early macroscopic capsular penetration in addition to its limited ability for detection of prostate cancer in the peripheral zone. Furthermore, it is not possible to use conventional imaging criteria to reliably distinguish tumors from other causes of reduced signal in the peripheral gland such as scars, hemorrhage, areas of prostatitis and treatment effects.
Also, central gland tumors are not well delineated on T2-weighted images particularly in the presence of benign prostatic hyperplasia. In addition, tumor volume is often under estimated when compared with pathological specimens. Other limitations of conventional MRI include the lack of information on tumor grade or vascularity, both of which are known to be useful predictors of patient prognosis.
To improve the diagnostic performance of MR imaging in evaluations for prostate cancer, various other techniques have been applied. These include dynamic contrast material–enhanced MR imaging, diffusion-weighted (DW) imaging, and magnetic resonance spectroscopy imaging (MRSI).
Dynamic contrast-enhanced MR imaging (DCE-MRI) has the advantage of providing direct depiction of tumor vascularity and may obviate the use of an endorectal coil. Current roles of T1-weighted techniques include tumor staging (depiction of capsular penetration and seminal vesicle invasion) and for the detection of suspected tumor recurrence following definitive treatment.
However, Limitations of the technique include inadequate lesion characterization particularly differentiating prostatitis from cancer in the peripheral gland and in distinguishing between benign prostatic hyperplasia and central gland tumors. In addition, there is as yet no consensus with regard to the best acquisition protocol and the optimal perfusion parameter for differentiating cancer from normal tissue.
Also, its role in monitoring tumor response to hormonal and radiation therapy remains to be limited.
The combination of DCE-MRI and other functional MRI techniques such as MRSI and DW-MRI, which can be performed at the same patient examination, may be able to address these current limitations.
Diffusion-weighted imaging has advantages such as short acquisition time and high contrast resolution between tumors and normal tissue. However, this technique is limited by poor spatial resolution and the potential risk of image distortion caused by postbiopsy hemorrhage, which results in magnetic field inhomogeneity.
Diffusion weighted imaging including an apparent diffusion coefficient (ADC) map should be used in conjunction with a morphological study with conventional MR imaging as well as together with complementary functional studies, such as dynamic contrast enhanced study and/or MR spectroscopy.
In conclusion, DW imaging is a relatively new functional imaging technique complementary to conventional MR imaging in the evaluation of prostate cancer. Diffusion weighted imaging is certain to become an important option for prostate cancer detection and characterization.
The advantages of MR spectroscopy are its generally accepted accuracy, its capability for depicting possible cancer in the transitional zone, and its widely proved diagnostic performance. However, the technique is disadvantaged by long acquisition time, possible variability in results dependent on post-processing or shimming, and no direct visualization of the periprostatic anatomy. Furthermore, a previous prostate biopsy may lead to spectral degradation that makes accurate interpretation of the metabolite ratios impossible.
An adequate time interval is necessary between prostatic biopsy and MR examination. In a study, investigators showed that, despite the potential risk of hemorrhage, MR spectroscopy may improve the ability to determine the presence of prostate cancer and its spatial extent when post biopsy changes hinder interpretation with the use of conventional MR images alone.
Combined use of MRI and MRSI is emerging as the most sensitive tool for the anatomical and metabolic evaluation of prostate cancer.
The addition of MRSI to MRI has further improved the accuracy of MR in prostate cancer localization, volume estimation and staging. Recent studies have confirmed that MRSI metabolic and volumetric data correlate with pathological Gleason grade and thus may help to non-invasively predict prostate cancer aggressiveness.
In clinical practice, MRI/MRSI is currently of greatest value for high-risk patients. With greater understanding of the relationship between spectroscopic data and tumor biology, it may become possible to use MRI/MRSI to assist all risk groups substantially by improving patient stratification in clinical trials, monitoring the progress of patients who select watchful waiting or other minimally aggressive cancer management options, and assisting in the guidance and assessment of emerging local prostate cancer therapies.
With the advent of newer MR modalities such as spectroscopy, diffusion, and DCE MR Imaging, the concept of ‘‘multimodal’’ MR imaging has arisen. In this scheme, morphologic assessment through T2W imaging serves as a starting point rather than an end point for tumor detection. Multiple ‘‘physiologic’’ or ‘‘functional’’ layers can be added to the morphologic scaffolding of T2W images, with information derived from spectroscopy, DCE MRI, and diffusion. In theory, these added layers of information would improve the sensitivity and specificity of MR imaging for prostate cancer depiction and staging by providing the radiologist with additional information beyond that of T2W image intensity and image texture.
Functional multi-modality MR imaging includes high resolution MR imaging, dynamic contrast- enhanced (DCE) MRI, MR-spectroscopy (MRS), and diffusion weighted MR imaging (DWI). With functional multi-modality MR imaging, it is possible to detect and exactly localize the tumor in the prostate with more than 90% accuracy.