Integration of preoperative anatomic and metabolic physiologic imaging of newly diagnosed glioma

Abstract

Purpose: To integrate standard anatomic magnetic resonance imaging in conjunction with uniformly acquired physiologic imaging biomarkers of untreated glioma with different histological grades with the goal of generating an algorithm that can be applied for patient management.

Methods: A total of 143 patients with previously untreated glioma were scanned immediately before surgical resection using conventional anatomical MR imaging, and with uniform acquisition of perfusion-weighted imaging, diffusion-weighted imaging, and proton MR spectroscopic imaging. Regions of interest corresponding to anatomic and metabolic lesions were identified to assess tumor burden. MR parameters that had been found to be predictive of survival in patients with grade IV glioma were evaluated as a function of tumor grade and histological sub-type. Based on these finding both anatomic and physiologic imaging parameters were then integrated to generate an algorithm for management of patients with newly diagnosed presumed glioma.

Results: Histological analysis indicated that the population comprised 56 patients with grade II, 31 with grade III, and 56 with grade IV glioma. Based on standard anatomic imaging, the presence of hypointense necrotic regions in post-Gadolinium T1-weighted images and the percentage of the T2 hyperintense lesion that was either enhancing or necrotic were effective in identifying patients with grade IV glioma. The individual parameters of diffusion and perfusion parameters were significantly different for patients with grade II astrocytoma versus oligodendroglioma sub-types. All tumors had regions with elevated choline to N-acetylasparate index (CNI). Lactate was higher for grade III and grade IV glioma and lipid was significantly elevated for grade IV glioma. These results were integrated into a proposed management algorithm for newly diagnosed glioma that will need to be prospectively tested in future studies.

Conclusion: Metabolic and physiologic imaging characteristics provide information about tumor heterogeneity that may be important for assisting the surgeon to ensure acquisition of representative histology. Correlation of these integrated MR parameters with clinical features will need to be assessed with respect to their role in predicting outcome and stratifying patients into risk groups for clinical trials. Future studies will use image directed tissue sampling to confirm the biological interpretation of these parameters and to assess how they change in response to therapy.

Fig. 1

T1-weighted post-Gadolinium and T2-weighted images of Grade II (a, b), III (c) and IV (d, e) glioma. The volumes of the overall T2 hyperintensity are large in all three cases, but the T1-weighted images shows larger contrast enhancement and/or hypointense necrotic regions for the grade IV glioma, no enhancement for the grade II lesion and marginal or no enhancement for the grade III gliomas

Fig. 2

Frequency distribution of the parameter % (CEL + NEC) versus tumor grade. Note that the vertical scale has been modified for the grade III lesions by a factor of 56/31 to facilitate direct comparisons between grades

Fig. 3

A comparison of the distributions and different ranges of ADC values for sub-types of grade II glioma. The green area represents ADC values characteristic of normal appearing white matter, the pink regions ADC values that are characteristic of oligiodendroglioma (a) and the blue values are characteristic of astrocytoma (b). Note that the mixed subtype oligoastocytoma (c) has a mixture of pink and blue regions

Fig. 4

Patient with an ACII: a is a post-Gadolinium T1-weighted image, b is a FSE image, c is a FLAIR image, d is an ADC map, and e is a map of nPH. The lactate edited spectra correspond to the sum (choline, creatine, NAA, and lipid if it is present) and the difference (which would show lactate if present). Light blue voxels show 2 < CNI <3 and dark blue voxels show CNI >3

Fig. 5

Patient with an ACII: a is a post-Gadolinium T1-weighted image, b is a FSE image, c is a FLAIR image, d is an ADC map, and e is a map of nPH. The lactate edited spectra correspond to the sum (choline, creatine, NAA, and lipid if it is present) and the difference (which would show lactate if present). Light blue voxels show 2 < CNI <3 and dark blue voxels show CNI >3. Note the low nPH and high relatively uniform nADC

Fig. 6

Patient with an ODII: a is a post-Gadolinium T1-weighted image, b is a FSE image, c is a FLAIR image, d is an ADC map, and e is a map of nPH. The lactate edited spectra correspond to the sum (choline, creatine, NAA, and lipid if it is present) and the difference (which would show lactate if present). Light blue voxels show 2 < CNI <3 and dark blue voxels show CNI >3. Note the elevated nPH, lower nADC values and the large number of voxels with visible but low lactate (green)

Fig. 7

Patient with an OAIII: a is a post-Gadolinium T1-weighted image, b is a FSE image, c is a FLAIR image, d is an ADC map, and e is a map of nPH. The lactate edited spectra correspond to the sum (choline, creatine, NAA, and lipid if it is present) and the difference (which would show lactate if present). Light blue voxels show 2 < CNI <3 and dark blue voxels show CNI >3. Note the low nPH, lower nADC values and the voxels with visible but low lactate (green)

Fig. 8

Patient with a grade IV glioma: a is a post-Gadolinium T1-weighted image, b is a FSE image, c is a FLAIR image, d is an ADC map, and e is a map of nPH. The lactate edited spectra correspond to the sum (choline, creatine, NAA, and lipid if it is present) and the difference (which would show lactate if present). Light blue voxels show CNI >2 and red voxels show CNI >2 and elevated lipid, yellow voxels show low CNI with elevated lipid and green voxels show elevated latcate. Note the low nPH in the necrosis and the variable nADC values. Survival = 139 days

Fig. 9

Patient with a grade III glioma: a is a post-Gadolinium T1-weighted image, b is a FSE image, c is a FLAIR image, d is an ADC map, and e is a map of nPH. The lactate edited spectra correspond to the sum (choline, creatine, NAA, and lipid if it is present) and the difference (which would show lactate if present). Light blue voxels show CNI >2 and red voxels show CNI >2 and elevated lipid and the green voxels show elevated latcate. Note the low nPH in the lesion and the variable nADC values. Survival = 610 days

Fig. 10

Patient with an atypical grade IV glioma: a is a post-Gadolinium T1-weighted image, b is a FSE image, c is a FLAIR image, d is an ADC map, and e is a map of nPH. The lactate edited spectra correspond to the sum (choline, creatine, NAA, and lipid if it is present) and the difference (which would show lactate if present). Light blue voxels show 3 > CNI >2 and the dark blue show CNI >3. Note the intermediate levels of nPH in the lesion and low nADC values. Survival = 985 days