Three-dimensional echo planar spectroscopic imaging for differentiation of true progression from pseudoprogression in patients with glioblastoma

Abstract

Accurate differentiation of true progression (TP) from pseudoprogression (PsP) in patients with glioblastomas (GBMs) is essential for planning adequate treatment and for estimating clinical outcome measures and future prognosis. The purpose of this study was to investigate the utility of three-dimensional echo planar spectroscopic imaging (3D-EPSI) in distinguishing TP from PsP in GBM patients. For this institutional review board approved and HIPAA compliant retrospective study, 27 patients with GBM demonstrating enhancing lesions within six months of completion of concurrent chemo-radiation therapy were included. Of these, 18 were subsequently classified as TP and 9 as PsP based on histological features or follow-up MRI studies. Parametric maps of choline/creatine (Cho/Cr) and choline/N-acetylaspartate (Cho/NAA) were computed and co-registered with post-contrast T₁ -weighted and FLAIR images. All lesions were segmented into contrast enhancing (CER), immediate peritumoral (IPR), and distal peritumoral (DPR) regions. For each region, Cho/Cr and Cho/NAA ratios were normalized to corresponding metabolite ratios from contralateral normal parenchyma and compared between TP and PsP groups. Logistic regression analyses were performed to obtain the best model to distinguish TP from PsP. Significantly higher Cho/NAA was observed from CER (2.69 ± 1.00 versus 1.56 ± 0.51, p = 0.003), IPR (2.31 ± 0.92 versus 1.53 ± 0.56, p = 0.030), and DPR (1.80 ± 0.68 versus 1.19 ± 0.28, p = 0.035) regions in TP patients compared with those with PsP. Additionally, significantly elevated Cho/Cr (1.74 ± 0.44 versus 1.34 ± 0.26, p = 0.023) from CER was observed in TP compared with PsP. When these parameters were incorporated in multivariate regression analyses, a discriminatory model with a sensitivity of 94% and a specificity of 87% was observed in distinguishing TP from PsP. These results indicate the utility of 3D-EPSI in differentiating TP from PsP with high sensitivity and specificity.

Keywords: echo planar spectroscopic imaging; glioblastoma; proton MRS; pseudoprogression; true progression; tumor treatment response.

Figure 1

Top row, axial post‐contrast T ₁‐weighted image from a patient with TP, demonstrating a neoplasm in the right thalamus infiltrating into the lateral ventricles. The regions of interest (ROIs) are overlaid on the image, with the colors indicating the following defined regions: Yellow, CER; orange, IPR; brown, DPR. The corresponding Cho/NAA map shows areas of elevated Cho/NAA (color bar indicating the distribution of non‐normalized Cho/NAA). A photomicrograph of a histologic section (hematoxylin–eosin stain) shows areas of high tumor cellularity, pseudopalisading necrosis, endothelial proliferation, and increased mitotic activity. Bottom row, axial post‐contrast T ₁‐weighted image from a patient with PsP, demonstrating a neoplasm in the left frontal lobe. The different ROIs as defined above are overlaid on the image. The corresponding Cho/NAA map shows reduced Cho/NAA compared with that of the TP case shown above. A photomicrograph of hematoxylin–eosin stain reveals most of the tissue with treatment‐related changes, including extensive geographic necrosis and vascular fibrinoid necrosis

Figure 2

Summed ¹H MRS spectra encompassing the entire volumes of different regions of neoplasms (CER, IPR, and DPR) from the TP and PsP patients shown in Figure 1. The number of voxels for these summed spectra from TP and PsP patients was CER 55 versus 41, IPR 75 versus 46, and DPR 75 versus 128, which explains the apparent differences in the signal to noise of these spectra. Significantly higher Cho/NAA and Cho/Cr from different regions of neoplasms were observed in TP patients compared with those with PsP

Figure 3

Box‐and‐whisker plots demonstrating the distribution of Cho/NAA and Cho/Cr from the different segmented regions, distinguishing TP from PsP patients at baseline. The bottom and top edges of boxes represent the 25th percentile and the 75th percentile values. The bands within the boxes represent 50th percentile (median) values. Whiskers display the range of data distribution. Outliers are marked with open circles (values 1.5 × box length from the 75th/25th percentiles). An asterisk indicates significant difference (p < 0.05) between the two groups

Figure 4

ROC curves for individual and combinations of different metabolite ratios. Using a univariate logistic regression model, Cho/NAA from CER provided the best AUC of 0.87 in discriminating TP from PsP patients with a sensitivity of 86% and specificity of 82%. After incorporation of Cho/Cr from CER and Cho/NAA from all regions (CER, IPR, and DPR) in multivariate logistic regression analyses the best model to distinguish the two groups of patients was observed, with an AUC of 0.93, a sensitivity of 94%, and a specificity of 86%. A leave‐one‐out cross‐validation test revealed that 92% of patients were correctly classified