1. Diseño
3.9 Matriz de validación de la propuesta
For a tumor, one critical factor that affects development, growth, invasiveness, and progression into the metastatic form is the ability of the tumor to generate new blood vessels. Angiogenesis, the sprouting of new capillaries from existing blood vessels, and vasculogenesis, the de novo generation of new blood vessels, are the two primary methods of vascular expansion by which nutrient supply to tumor tissue is adjusted to match physiologic needs49. Tumor growth beyond 1 to 2 mm in solid tissues cannot
occur without vascular support50. The importance of angiogenesis in PCa is
well established. The angiogenic process is a complex multistep sequence involving many growth factors and interactions between varieties of cell
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G ra d in g o f p ro st at e c an ce r u si ng D if fu si on -W ei gh te d M R I m ag in g (D W I)Concentration-time curves are mathematically fitted by using one of many described pharmokinetic models, and quantitative kinetic parameters are derived. These include (1) transfer constant of the contrast agent (Ktrans); (2)
rate constant (kep); and (3) interstitial extravascular extracellular space (Ve)60. Uncertainties exist with regard to the reliability of kinetic parameters
estimates derived from the application of kinetic models to T1-weighted DCE-MRI datasets. The vascular input function used in the calculations also affects the reliability of the data obtained. Robust methods for measuring the arterial input function are essential. Currently, these methods are emerging but are still not widely available61.
Currently, there are no FDA-approved DCE-MRI post-processing software packages available. Every institution is using its own developed software for analyzing these large datasets. Some companies are developing these packages for data evaluation; however, too little data are available for discussion. Furthermore, quantitative evaluation of the kinetic parameters has not been performed. There are no thresholds available, like in MR spectroscopy, for differentiation between benign and malignant tissue. This is probably caused by the inter-patient variability (variable vascular anatomy, atherosclerosis, cardiac output). Almost all imaging data in literature are evaluated based on qualitative assessment rather than quantitative thresholds. Functional dynamic imaging parameters are estimated as follows: each MR imaging signal enhancement–time curve is first fitted to a general exponential signal intensity model. Consequently, the curve is reduced to a model with five parameters (t0, time-to-peak, peak enhancement, and washin-washout gradient or plateau). The reduced signal enhancement– time curve is converted to a reduced tracer concentration–time curve (with the tracer concentration in millimoles per milliliter) such that peak enhancement is effectively converted to gadolinium concentration. In the authors’ institution, the reduced plasma concentration–time curve is estimated by using a reference tissue method. Deconvolution of the plasma profile and estimation of the pharmacokinetic parameters conformed to the theoretic derivations but are implemented in the reduced signal space as Ktrans=V
e x kep, where Ve is an estimate of the extracellular volume (expressed
as a percentage); Ktrans is the volume transfer constant (1 per minute); and k ep
is the rate constant (1 per minute) between the extracellular extravascular space and the plasma space.
kd) is the most common imaging method for evaluating human tumor vascular function in vivo55. Insights into these physiologic processes are
obtained qualitatively by characterizing kinetic enhancement curves or quantitatively by applying complex compartmental modeling techniques56.
Data reflecting the tissue perfusion (blood flow, blood volume, and mean transit time), the microvessel permeability, and the extra-cellular leakage space can be obtained.
MR imaging sequences can be designed to be sensitive to the vascular phase of contrast me- dium delivery, so-called ‘‘susceptibility-weighted (T2*- weighted) DCE-MRI’’, which reflects tissue perfusion and blood volume; or to the presence of contrast agent, so-called T1-weighted DCE-MRI, which reflects the perfused microvessel area, permeability, and extravascular extracellular leakage space57,58. Only the latter technique is discussed
because this is by far the most common method used. Low-molecular-weight extravascular and extracellular contrast agents (gadolinium chelates) shorten the T1 relaxation of water and results in an increase in signal intensity on T1-weighted MR images. One essential aspect of DCE-MRI includes the dynamic MR imaging, referring to the temporal component, with complete coverage of the prostate with a fast T1-weighted sequence, which is required before, during, and after the bolus injection of a low-mo- lecular-weight contrast agent (see Appendix 2, DCE-MRI protocol). DCE-MRI findings are related to differences in microvascular characteristics observed between normal and malignant prostatic tissues51. The obtained T1-weighted
DCE MR imaging data can be assessed in two ways.
The first is a semi-quantitative approach describing signal intensity changes by using a number of parameters, such as (1) the onset time of the signal intensity curve (t0=time from appearance in an artery to the arrival of contrast agent in the tissue of interest); (2) the slope and height of the enhancement curve (time-to-peak); (3) maximum signal intensity (peak enhancement); and (4) wash- in-washout gradient or plateau phase59. These
parameters are limited by the fact that they may not accurately reflect contrast agent concentration in tissues and can be influenced by the MR imaging scanner settings (including gain and scaling factors).
The second is a quantitative approach using pharmokinetic modeling, which is usually applied to changes in the contrast agent concentrations in tissue.
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Ch ap te r 4 G ra d in g o f p ro st at e c an ce r u si ng D if fu si on -W ei gh te d M R I m ag in g (D W I)additional value of DCE-MRI in local staging, such imaging does seem to improve local staging performance. With the use of DCE-MRI the staging performance of the less experienced showed a significant improvement of the AUC compared with T2-weighted imaging alone (0.66 and 0.82, respectively; p<0.01)48.
The application of DCE-MRI for detection of local recurrence after RP or external beam radiation therapy is increasingly being used. Haider and colleagues64 found that DCE-MRI performs better than T2-weighted imaging
for the detection and localization of PCa in the PZ after external beam radiotherapy. DCE-MRI had significantly better sensitivity (72% versus 38%), positive predictive value (PPV) (46% versus 24%), and negative predictive value (NPV) (95% versus 88%) compared with T2-weighted imaging. Sciarra et al.65 reported the use of DCE-MRI and MR spectroscopic
imaging for the detection of local recurrence in patients post-RP, and they concluded that the combination of these techniques is accurate for identification of local prostate cancer recurrence with biochemical failure (87% sensitivity and 94% specificity). This information could be helpful in the planning of salvage therapy.