Extent of resection is a major prognostic factor in brain tumor patients. Furthermore, accurate identification during surgery of the more malignant regions of tumor is important for subsequent neuropathologic diagnosis, which determines the chemo- and radiotherapeutic regime and patient prognosis. Image guidance can help the neurosurgeon to better delineate the tumor margins for surgical removal and subsequent neuropathologic assessment. Nevertheless, image guidance suffers from intraoperative brain shift and deformation, which degrade and limit navigational accuracy.6–12
The major clinical implementations of FGR have used only subjective assessments of intraoperative fluorescence (i.e., negative or positive visible fluorescence). One major limitation of this approach is that subjective FGR suffers from interobserver variability in correctly assessing low levels of fluorescence. A further limitation of subjective ALA-induced PpIX FGR is its inability to detect fluorescence, which may be obscured by physical effects such as variation in tissue optical properties (i.e., optical absorption and transport scattering properties) and camera orientation to the resection cavity. The tissue optical absorption in particular varies among tissue sites and can greatly impact the resultant subjective fluorescence assessment. This can lead to tumor tissue that contains high levels of accumulated PpIX biomarker but is incorrectly identified (i.e., nonvisibly fluorescent); (Fig. ). In a recent study we used a fiber-optic approach that takes into account tissue optical properties to quantify PpIX concentrations in vivo and showed that significant levels of PpIX concentrations are present in a variety of intracranial tumor histologies below the threshold of visual detection.23
In this study we have shown that CPpIX evaluated in specimens resected during surgery is identified with regions of increasing malignancy assessed histologically in low- and high-grade gliomas beyond the capabilities of current fluorescence imaging. As expected, a statistically significant difference in CPpIX occurred between tissues with no visual fluorescence (−F) intraoperatively and those with positive visual fluorescence (+F). A significant trend also occurred between CPpIX and the subjective fluorescence levels observed intraoperatively, which produced a positive correlation. All but 2 nontumor tissue specimens contained CPpIX levels below 0.1 µg/mL, whereas ~40% of nonvisibly fluorescent tumor tissues were above this threshold (Fig. D). These results suggest that improvements in the detection of fluorescence intraoperatively is likely to identify more tumor tissue (especially in low-grade glioma) and if quantitative detection of CPpIX can be achieved during surgery, it may be possible to define a threshold that maximizes the diagnostic performance of PpIX fluorescence for tumor resection.
Although the exact mechanism(s) that leads to preferential accumulation of PpIX in tumor tissue is not well known, cellular proliferation, cell density, mitochondrial content, vascular proliferation, structural changes, and enzymatic up-/downregulation (e.g., ferrochelatase)34–37
have been suggested as contributing factors. Since all of these factors correlate with the degree of tissue malignancy, we also assessed relationships between PpIX fluorescence and measures of tissue malignancy quantified with a MIB-1 PI using Ki-67 antigen as the biomarker. We found a statistically significant difference in PI between nonfluorescent (−F) and positively fluorescent (+F) biopsies (Fig. ), as well as a strong correlation between PI and subjective levels of fluorescence. Furthermore, the results assessing a difference in CPpIX
levels and PI across histopathologic scores and visible fluorescence levels (i.e., Kruskal–Wallis analyses) show that CPpIX
levels and PI display similar trends of statistically significant differences between groups. These data support our hypothesis that quantitative levels of CPpIX
can serve as a useful biomarker to ascertain tumor regions of more proliferative and anaplastic tissue.
In addition, we show that quantitative ex vivo measurements of CPpIX
correlate with quantitative histopathologic measures of tissue malignancy by showing a strong, statistically significant correlation between PI and CPpIX
(Fig. A). However, “proliferation index” is a relative term quantifying the percentage of abnormal cells over the total number of cells in a given tissue—it does not fully relate measures of tissue malignancy to accumulation of CPpIX
. To further elucidate the quantitative relationship between ex vivo measurements of PpIX and tissue malignancy, we determined the correlation between cell density and number of abnormal, proliferating cells as additional factors affecting accumulation of PpIX in tissue. We found a statistically significant correlation (Fig. B and C) between CPpIX
and total number of cells as well as between CPpIX
and total number of abnormal cells. More importantly, these results as well as similarly strong correlations between CPpIX
= 0.72) and PI (r
= 0.61) with tissue histopathologic score indicate the ability of CPpIX
to differentiate between varying degrees of tissue malignancy at the microscopic level comparable to the gold standard, i.e., the Ki-67 PI. The predictive value of both qualitative levels of visible fluorescence and CPpIX
levels for predicting phenotype (e.g., proliferation, histopathologic grade) is provided by our correlation coefficients, i.e., the r
-values, which show a statistically significant, strong correlation between CPpIX
and cellular proliferation (r
= 0.70) and histopathologic score (r
= 0.72). Previous studies have shown that MIB index, although not an absolute marker of tumor malignancy, is positively correlated with WHO grade in gliomas as well as negatively correlated with prognosis.38–41
As such, in this study we have focused on gliomas, as we present a quantitative approach to identifying areas of more aggressive, highly proliferative tissue in the resection of gliomas. We have also shown a positive correlation between cell density and CPpIX
, but here we show a stronger correlation between CPpIX
and cellular proliferation, which argues that the latter is a stronger, more significant predictor of CPpIX
levels in glioma tissue.
Our findings also show that a quantitative and more sensitive determination of PpIX concentration can be used to identify microscopic levels of increasing tumor cell proliferation and, thus, regions of increasing malignancy. More importantly, quantitative measurements of CPpIX can be used as tissue biomarkers to accurately identify nonvisibly fluorescent, proliferative tumor tissue. Quantitative assessments open the door for more sensitive intraoperative determination of tumor malignancy in both visibly fluorescent and, perhaps more importantly, nonvisibly fluorescent tissue (e.g., nonfluorescing regions of anaplastic astrocytomas). Such biomarker determinations can guide the neurosurgeon in representative biopsy sampling to achieve a more accurate neuropathological diagnosis and inform patient treatment. For example, it is important to note that all WHO grade III tumors in this study were heterogeneous with anaplastic foci. This point is of importance to our study, since our results show a correlation between increased proliferation and CPpIX, arguing that such anaplastic foci in heterogeneous gliomas could be more easily identified by noting increased levels of CPpIX.
Previous work suggests that blood–brain barrier status is a contributing factor to observable levels of PpIX fluorescence.15,18,42
Stummer et al. showed a strong association between postoperative contrast enhancement on MR imaging and levels of red visible fluorescence at the end of surgery. Further, we have recently shown a significant association between intraoperative levels of PpIX fluorescence and 2 MR imaging metrics of contrast enhancement. These studies are inconclusive, since they suffer from brain shift, which degrades the accuracy of associating tissue fluorescence and MR imaging. Furthermore, to our knowledge, no study has undertaken a quantitative assessment unaffected by brain shift (e.g., brain biopsy cases) and correlated histopathologic and imaging findings with quantitative levels of PpIX. It is important to note that the strong positive correlation of r
= 0.70, P
< .0001 observed in this study for PI and PpIX accumulation argues that (1) PpIX accumulation in gliomas is strongly dependent on cellular proliferation status (i.e., cellular proliferation status in gliomas is a strong predictor of PpIX accumulation); (2) despite the strong correlation observed between CPpIX
and cellular proliferation, PpIX accumulation is a multifaceted biological process that cannot be accounted for solely on the basis of cellular proliferation; and (3) the strong correlation presented here suggests the predictive power of CPpIX
for tissue proliferation. These conclusions are in agreement with previous studies showing that PpIX accumulation is dependent upon factors such as enzymatic up- and downregulation, cellular proliferation, oxygenation status, and mitochondrial content, among others.42–44
The current study investigated the relationship specifically between cellular proliferation and PpIX accumulation in gliomas. The relationship between PpIX accumulation and blood–brain barrier status is of great importance to the field but is beyond the scope of this study.
A limitation of the study is that CPpIX
measurements were performed ex vivo, which for purposes of intraoperative guidance is impractical. Utsuki et al.45
report on a spectroscopy device for real-time feedback of fluorescence signal that shows improved detection of tumor with no visible fluorescence. Spectroscopic devices are known to improve detection of fluorescence signals from tissue due to geometries optimized for excitation and light collection, which maximize detection of fluorescent light while minimizing bleed-through of extraneous signals.42
Despite improved detection of low levels of fluorescence or fluorescence not visible by a modified surgical microscope, these other fluorescence spectroscopic devices are still limited in their ability to quantitatively determine absolute levels of PpIX. More specifically, the system by Utsuki et al. is limited by its ability to accurately quantify absolute fluorescence that may be obscured by physical effects such as variation in tissue optical properties (i.e., optical absorption and transport scattering properties). The tissue optical absorption in particular varies among tissue sites and can greatly impact the resultant fluorescence assessment.24,46–48
We have reported on an intraoperative fiber-optic system that measures CPpIX
levels in vivo and accounts for such variations in tissue optical properties, thus providing significantly improved diagnostic performance compared with other fluorescence spectroscopy. This probe is able to quantify the absolute levels of CPpIX
in tissue despite variations in tissue optical properties.23,24
The results presented in this study are a proof-of-principle of the value of CPpIX
measurements for detection of more malignant, proliferative regions of tissue in gliomas. Since the ability to quantify PpIX levels in tissue for the ex vivo assay correlates with the in vivo quantitative probe, the results from this study are translatable to a real-time in vivo quantification procedure that can be implemented using the quantitative probe. One important observation and possible limitation to this study is the validity of operating on recurrent gliomas with the assumption that CPpIX
positively correlates with cellular proliferation. Recurrent gliomas following chemotherapy are known to contain significant levels of inflammatory cells, which in turn are known to have increased levels of CPpIX
This fact could be a confounding factor leading to increased CPpIX
levels in recurrent glioma as a result of inflammatory cell presence and not increased proliferation. In our study, no recurrent glioma specimen contained any significant component of inflammatory cells, which were either diffusely infiltrated with rare tumor cells and had low levels of CPpIX
or were densely infiltrated by tumor cells with high levels of CPpIX
. Future studies will further inform the surgeon regarding the utility of CPpIX
determination for the resection of recurrent gliomas. Another limitation of this study is a possible sampling error when dividing the biopsy specimens into 3 parts for histopathologic and biochemical analyses, though generally samples are quite small (less than 0.5 cm in greatest dimension), and the 3 parts should have similar pathology.
The findings reported here provide a rationale for developing the improved PpIX fluorescence detection needed to achieve better sensitivity and quantification of the biomarker in tissue. Quantitative and more sensitive detection of PpIX fluorescence would better enable the neurosurgeon to achieve a more informed real-time assessment of the surgical field, leading to optimal tumor resection.