Region-by-region analysis of PET, MRI, and histology in en bloc-resected oligodendrogliomas reveals intra-tumoral heterogeneity

Abstract

Purpose: Oligodendrogliomas are heterogeneous tumors in terms of imaging appearance, and a deeper understanding of the histopathological tumor characteristics in correlation to imaging parameters is needed. We used PET-to-MRI-to-histology co-registration with the aim of studying intra-tumoral ¹¹C-methionine (MET) uptake in relation to tumor perfusion and the protein expression of histological cell markers in corresponding areas.

Methods: Consecutive histological sections of four tumors covering the entire en bloc-removed tumor were immunostained with antibodies against IDH1-mutated protein (tumor cells), Ki67 (proliferating cells), and CD34 (blood vessels). Software was developed for anatomical landmarks-based co-registration of subsequent histological images, which were overlaid on corresponding MET PET scans and MRI perfusion maps. Regions of interest (ROIs) on PET were selected throughout the entire tumor volume, covering hot spot areas, areas adjacent to hot spots, and tumor borders with infiltrating zone. Tumor-to-normal tissue (T/N) ratios of MET uptake and mean relative cerebral blood volume (rCBV) were measured in the ROIs and protein expression of histological cell markers was quantified in corresponding regions. Statistical correlations were calculated between MET uptake, rCBV, and quantified protein expression.

Results: A total of 84 ROIs were selected in four oligodendrogliomas. A significant correlation (p < 0.05) between MET uptake and tumor cell density was demonstrated in all tumors separately. In two tumors, MET correlated with the density of proliferating cells and vessel cell density. There were no significant correlations between MET uptake and rCBV, and between rCBV and histological cell markers.

Conclusions: The MET uptake in hot spots, outside hotspots, and in infiltrating tumor edges unanimously reflects tumor cell density. The correlation between MET uptake and vessel density and density of proliferating cells is less stringent in infiltrating tumor edges and is probably more susceptible to artifacts caused by larger blood vessels surrounding the tumor. Although based on a limited number of samples, this study provides histological proof for MET as an indicator of tumor cell density and for the lack of statistically significant correlations between rCBV and histological cell markers in oligodendrogliomas.

Keywords: 11C-methionine PET; Co-registration; Perfusion MR; Proliferation; Vascularization.

Fig. 1

Patient 1. a T2-weighted FLAIR MRI shows a hyperintense slightly heterogeneous tumor in the right frontal lobe. b MET PET shows the hotspot region of the tumor. c DSC perfusion MRI with rCBV greyscale map shows predominantly low or normal perfusion in the region corresponding to the PET hotspot. d Co-registration of MRI, PET and corresponding histological images with defined ROIs (ROI₁, red and orange; ROI₂ yellow, ROI₃ green)

Fig. 2

Patient 2. a T2-weighted FLAIR MRI shows a hyperintense tumor with small cystic regions in the left frontal lobe. b MET PET shows the hotspot region of the tumor. c DSC perfusion MRI with rCBV greyscale map shows higher perfusion in the region corresponding to the PET hotspot. d Co-registration of MRI, PET, and corresponding histological images with defined ROIs (ROI₁, red and orange; ROI₂ yellow, ROI₃ green)

Fig. 3

Patient 3. a T2-weighted FLAIR MRI shows a hyperintense tumor in the left frontal lobe. b MET PET shows the hotspot regions of the tumor. c DSC perfusion MRI with rCBV greyscale map shows low or normal perfusion in the region corresponding to the PET hotspot. d Co-registration of MRI, PET, and corresponding histological images with defined ROIs (ROI₁, red and orange; ROI₂ yellow). There was no identifiable ROI₃ in this sequence

Fig. 4

Patient 4. a T2-weighted FLAIR MRI shows a left frontal hyperintense tumor with minimal contrast enhancement on T1-weighted images (not shown). b MET PET shows a large hotspot region in the tumor. c DSC perfusion MRI with rCBV greyscale map shows areas with low, normal, and high perfusion in the region corresponding to the PET hotspot. d Co-registration of MRI, PET, and corresponding histological images with defined ROIs (ROI₁, red and orange; ROI₂ yellow). There was no identifiable ROI₃ in this sequence. As shown, ROI₁ covers almost the entire tumor volume

Fig. 5

Illustration of the study design. Step 1: En bloc tumor resection of 8–12 tissue slices of 6–8 mm thickness. Steps 2–3: Development of software for anatomical landmark-based co-registration of consecutive microsections (4 μm) for immunohistochemical staining of for tumor cells (IDH1), proliferating cells (Ki67), and blood vessels (CD34). Step 4: Quantification of protein expression in each histological sub-image (500 × 500 pixels). The original image of CD34 protein expression (left) was overlaid with the identified objects (red) in CellProfiler. Steps 5–7: Manual co-registration of MRI, PET, perfusion maps and corresponding histological images. Selection of ROIs on PET covering hot spot areas (ROI₁), areas outside hot spots (ROI₂) and tumor periphery (ROI₃). Analysis of correlations between MET uptake and quantified protein expression, MET uptake and rCBV, and rCBV and quantified protein expression. Note: ROIs in the figures indicate their specific location but not their exact volume