Of critical importance in evaluating combinatory treatment strategies involving anti-angiogenic therapies is the availability of noninvasive imaging techniques that can directly and objectively assess their effectiveness in terms of both tumor burden and vascular patency. Ideally, the quantitative parameters derived from these imaging methods would determine which patients would benefit most from a given therapy before the onset of treatment and ultimately provide clinicians with a tool for identifying the best candidates for diverse therapeutic strategies. In this study, we successfully achieved the goal of identifying a predictive biomarker for one such form of antiangiogenic therapy, the PKC-kinase inhibitor, enzastaurin, using a parameter derived from SWI. To our knowledge, this is the first time SWI has been shown to predict outcome in a population of patients with brain tumors.
The parameter %SWI-h, or the fraction of hypointense signal on an SWI in the CEL lesion, was found to be predictive of both PFS and OS in patients with newly diagnosed GBM who were receiving a treatment regime consisting of upfront radiation therapy, temozolomide, and enzastaurin. There are 2 plausible underlying mechanisms to elucidate why a larger region of hypointensity on SWI in the core of the tumor would result in a better prognosis. The most likely explanation is that tumors with a larger extent of damaged vasculature initially are more likely to benefit from a treatment regimen containing an anti-angiogenic agent that aims to normalize the existing vasculature. The more abnormal vessels present, the greater the potential effect of the anti-angiogenic agent on pruning excess vessels and decreasing the oxygen supply to the tumor or fascilitating the delivery of chemotherapy, resulting in a heightened response and improved patient outcome. To test whether this is in fact the case, future studies evaluating the ability of baseline %SWI-h to predict outcome in patients with GBM who do not receive an anti-angiogenic agent are necessary. It is also possible that SWI hypointensity is reflecting the amount of chronic hemorrhage in the tumor (subacute hemorrhage, demarcated by hyperintensity on the precontrast injection T1-weighted image, was explicitly excluded from the contrast-enhancing tumor region). More chronic hemorrhage in the CEL would indicate less active tumor, which would, in turn, result in more favorable outcome measures. If the latter is the case, the type of therapy should not influence the ability of this parameter to predict prognosis. However, findings from the literature, whereby rapid functional vascular normalization both in terms of a reduction in vessel size and overall permeability derived from dynamic susceptibility-weighted contrast-enhanced and dynamic contrast-enhanced perfusion-weighted imaging were observed in patients with GBM who received other anti-angiogenic therapies,26,34
support the former hypothesis.
In identifying robust prognostic markers from quantitative imaging metrics, the first step is to establish a relationship between the candidate parameter(s) and outcome measure. This was achieved for %SWI-h in the first section of the results, in which we showed that the %SWI-h in the CEL was significantly higher in sustained responders than in nonresponders for both time to progression and death. These differences did not exist for baseline CEL volume for either event. Univariate CoxPH models also demonstrated strong associations between %SWI-h and both PFS and OS. After a significant association is ascertained between the imaging marker and outcome measure, the relationship must also be demonstrated with high confidence when controlling for known clinical factors. Our data confirmed that an elevated %SWI-h value at baseline is a protective factor for both PFS and OS analyses, with highly significant hazard ratios. Nevertheless, the ultimate goal is to provide the clinician with a decision-making tool that can objectively determine whether a patient should be administered a given therapy (in this case, concomitant enzastaurin) based on their postsurgery, pretreatment baseline scan. To achieve this end, we implemented CART analysis to determine the optimal cutoff for deciding whether a patient is likely to benefit from anti-angiogenic therapy (in this case, enzastaurin). We found that %SWI-h best distinguished early progressors and long-term survivors, with values >38% significantly separating patients who benefited the most from enzasturin, according to both progression- and survival-based outcome measures.
Another strength of this study lies in the ability to use a quantitative measure, %SWI-h, to stratify patients noninvasively before any therapy administration, without having to wait for signs of response. Evaluating response to anti-angiogenic therapies using standard response criteria is often a challenge because of the apparent reduction in enhancing volume from transient normalization of the blood-brain barrier rather than antitumor activity. The vast majority of literature on predicting response to anti-angiogenic therapies, therefore, has focused on identifying early changes in physiological and metabolic imaging parameters that either more accurately reflect early antitumor activity of the therapeutic agent or later preclude any evidence of progression based on standard anatomical imaging. In several of these initial studies, response rate was used as the primary end point,17,26,34
which has since been shown to correlate poorly with more stable outcome measures, such as PFS and OS.22,44
The VEGF-targeting class of drugs in particular result in even higher pseudo response rates, compared with historical controls6–8,26
with only marginal improvements, if any, in survival, despite the somewhat delayed onset of progression.9–11,25,30
Our results consistently indicated that %SWI-h was more associated with OS than with PFS. This is advantageous in the current context in which the vasogenic effect of anti-angiogenic therapies often masks the presence of active tumor cells, and extended PFS does not necessarily reflect overall patient outcome, because after progression, the rate of decline often hastens and the time from progression to death is reduced.
Despite the promising impact of our findings on patient treatment, there are some potential limitations that need to be addressed. The disadvantage of using categorical response assessment is that it does not provide a continuous scale on which to measure response and to test predictive hypotheses. Although the use of RANO criteria to evaluate PFS is still limited in the evaluation of response to anti-angiogenic therapy,45
it does provide a scale for evaluating early biomarkers. While OS is likely to be a more appropriate end point in evaluating response to anti-angiogenic therapy, it is still limited by the influence of salvage treatments.45
The advantage in integrating the discrete categorical radiographic assessment of response with the continuous PFS and OS scales is that this type of analysis facilitates elucidating differences in SWI hypointensity that could accurately identify radiographic response groups and predict outcome. Despite the distinct contrast present on the SWI images, the other main source of variability in this study arises from inaccuracies of thresholding the projected SWI images, as shown in Fig. . However, this error was minimized using an automatic technique in which 65% of the patients exhibited variations of %SWI-h of <5% between methods (Fig. B). The 2 techniques were also highly correlated with a correlation coefficient of .86 (P
< .001, Spearman Rank correlation) (Fig. A), with larger differences in thresholds between methods resulting in greater changes in the %SWI-h parameter (Fig. C). Although the results reported in this article used the automatic method to remove user bias, varying the threshold had little effect on the volumes of SWI-h, and all the same findings were observed when using the visually defined thresholds.
Fig. 5. Relationship between automatic and manual thresholding. In (A), scatter plot of %SWI-h values for automatic versus manual thresholding. In (B), histogram of percentage difference between %SWI-h derived from automatic and manual thresholding across all (more ...)
In conclusion, the volume of SWI hypointensity in the CEL pretherapy was associated with both PFS and OS. These findings suggest that tumors with a larger extent of hypointense signal on SWI initially are more likely to benefit from a treatment regimen containing concomitant anti-angiogenic, cytotoxic, and radiation therapy. The ability to stratify patients on the basis of quantitative measures obtained noninvasively before therapy can aid in identifying patients who are the best candidates for different therapeutic strategies. Future studies will validate these results in other patient populations receiving alternate anti-angiogenic treatment regimens, investigate the patterns of SWI-h before progression, and incorporate functional imaging changes derived from perfusion- and diffusion-weighted imaging.