Rationale and Objectives
Magnetic resonance (MR) perfusion techniques and MR spectroscopy (MRS) provide specific physiological information that may allow distinction between recurrent glioma and progression from stable disease.
Materials and Methods
Forty patients underwent conventional MR imaging, dynamic contrast-enhanced T1-weighted perfusion imaging, dynamic susceptibility contrast-enhanced perfusion imaging (DSC), and multivoxel MRS. Arterial spin labeling was available in 26 of these patients. Quantitative parameters were calculated in tumor recurrences and stable disease, which were retrospectively verified on clinical and radiological follow-up. Receiver operating characteristic curves for each parameter were generated for the differentiation between recurrent glioma and stable disease. A forward discriminant analysis was undertaken to assess the power of the conjunction of MR perfusion techniques and MRS.
Results
Of the 40 patients, 23 were determined to have recurrent gliomas. Differences in arterial spin labeling between the two groups were not statistically significant ( P = .063). Sensitivities and specificities for the detection of recurrent lesions in dynamic contrast-enhanced T1-weighted perfusion imaging and DSC were 61.9% and 80% transfer constant k(trans) , 77.3% and 84.6% for cerebral blood flow, and 81% and 76.9% for cerebral blood volume, respectively. Among the parameters in MRS, the ratio of choline to normalized creatine showed the best diagnostic accuracy ( P = .014; sensitivity 70%, specificity 78.6%). When considering all perfusion modalities, diagnostic accuracy could be increased to 82.5%, adding MRS to the multiparametric approach resulted in a diagnostic accuracy of 90.0%.
Conclusions
MR perfusion techniques and MRS are useful tools that enable improved differentiation between recurrent glioma and stable disease. Among the single parameters, DSC showed the best diagnostic performance. Multiparametric assessment substantially improved the ability to differentiate the two entities.
The current therapy for high-grade gliomas includes surgical resection followed by radiotherapy and chemotherapy, but tumor recurrence or progression is often seen in the course of the disease. Furthermore, up to 30% of these patients develop treatment-related injury that can mimic tumor recurrence or progression in conventional magnetic resonance imaging (MRI) . On anatomic MRI, corpus callosum involvement and multiple enhancing lesions may suggest recurrent tumor , but this is not robustly reliable. Contrast-enhanced MRI has a low specificity in the differentiation because a breakdown of the blood–brain barrier is seen in both radiation-induced necrosis and tumor recurrence. In many cases, the peritumoral territory will contain both chemoradiation injury and possible recurrent tumor . This mixed pathology makes it impossible to dichotomize patients into either tumor recurrence or pure radionecrosis. Even histological results may contain mixed pathology, and the determination whether tumor cells after radiation are viable is often difficult . Surgical biopsy samples may not be representative of the whole lesion, especially via the minimally invasive approach. Therefore, the term “stable disease” was proposed by some authors. The clinical outcome and management strategy of patients with tumor progression differ profoundly, and functional MRI is increasingly used to monitor the therapeutic effects of combined chemoradiation schemas in treating gliomas. A reliable noninvasive methodology for the differentiation between stable disease and tumor recurrence is highly needed.
In theory, the membrane turnover, the cell density, and the vasculature expression are higher in recurrent tumors than in radiation injuries . This could be measured in metabolic and hemodynamic parameters. Functional MRI enables the assessment of several parameters using different technical approaches. Perfusion techniques including arterial spin labeling (ASL), dynamic contrast-enhanced T1-weighted imaging (DCE), and dynamic susceptibility-weighted contrast-enhanced imaging (DCS) are most frequently used and enable the assessment of perfusion parameters like cerebral blood flow (CBF), cerebral blood volume (CBV), and the transfer constant between the blood plasma and extracellular space, k(trans) . However, there is no consensus regarding which technique provides the best diagnostic accuracy for the differentiation of recurrent glioma from stable disease. In addition, MR spectroscopy (MRS) enables the quantification and comparison of metabolites including choline (Cho), creatine (Cr), and N -acetylaspartate (NAA).
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Materials and methods
Patient Population
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Imaging Protocol
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ASL Imaging
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DCE Imaging
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DCS Imaging
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MRS
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Image Evaluation
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Statistical Analysis
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Results
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Table 1
Quantitative Results
Age Gender ASL DCE MR DSC MR MRS rCBF_k(trans)_ max v(e) rCBF rCBV Cho/NAA Cho/Cr NAA/Cr(n) Cho/Cr(n) Tumor recurrence 54.7 ± 15 14 Men, 9 women 2.41 ± 1.3 0.08 ± 0.06 0.27 ± 0.12 4.01 ± 2.32 3.91 ± 2.81 2.20 ± 1.55 1.66 ± 0.72 1.01 ± 0.69 1.78 ± 1.30 Stable disease 52.1 ± 10 10 Men, 7 women 1.66 ± 0.5 0.047 ± 0.02 0.15 ± 0.17 1.66 ± 1.18 1.73 ± 1.14 1.47 ± 1.57 1.30 ± 0.68 0.51 ± 0.40 0.65 ± 0.44P -value n.s. n.s. .063 .046 .10 <.01 .01 >.01 .047 .051 .014
The table summarizes the quantitative results of the comparison of the two study groups (tumor recurrence and stable disease). The parameters k(trans) , rCBF, rCBV, Cho/Cr, and Cho/Cr(n) reach statistical significance. ASL, arterial spin labeling perfusion; DCE, dynamic contrast-enhanced T1-weighted perfusion imaging; DSC, dynamic susceptibility contrast-enhanced perfusion imaging; MR, magnetic resonance; MRS, MR spectroscopy; rCBF, normalized values for cerebral blood flow; k(trans), transfer constant; rCBV, normalized values for cerebral blood volume; Cho, choline; Cr, creatine; (n), normalized, n.s., nonsignificant.
![Figure 1, Example of tumor recurrence in a 53-year-old patient treated with surgery and radiation with recurrence of glioma. The image shows magnetic resonance (MR) perfusion (a–c) , MR spectroscopy (MRS) (d,f) , and postcontrast T1-weighted imaging (e) . The T1-weighted contrast-enhanced images (e) show the new enhancing lesion in the former surgery area. While arterial spin labeling perfusion (a) could not reliably differentiate tumor recurrence (normalized values for cerebral blood flow 1.6), dynamic contrast-enhanced T1-weighted perfusion imaging (b) and dynamic susceptibility contrast-enhanced perfusion imaging (c) show hyperperfusion of the lesion [quantification of perfusion values: maximum k(trans) 0.062/min and normalized values for cerebral blood volume >5], an indication of tumor recurrence. MRS supports the diagnosis due to the elevated ratio of choline in the lesion (f) to creatine in the healthy tissue (d) . The patient underwent resection, and tumor recurrence was confirmed by histopathology. The illustrations show the values in a descending red-green-blue color scale. (Color version of the figure is available online.)](https://storage.googleapis.com/dl.dentistrykey.com/clinical/ComparisonofThreeDifferentMRPerfusionTechniquesandMRSpectroscopyforMultiparametricAssessmentinDistinguishingRecurrentHighGradeGliomasfromStableDisease/0_1s20S107663321300411X.jpg)
![Figure 2, Example of stable disease in a 39-year-old patient treated with surgery and radiation. The image shows magnetic resonance (MR) perfusion (a–c) , MR spectroscopy (MRS) (d,f) , and postcontrast T1-weighted imaging (e) as well as T1-weighted imaging in two serial follow-up examinations (g,h) . The T1-weighted contrast-enhanced images (e) show the new enhancing lesion in the former surgical area. While arterial spin labeling perfusion (a) and dynamic contrast-enhanced T1-weighted perfusion imaging (b) indicate normal values [normalized values for cerebral blood flow 1.3 and maximum k(trans) 0.04], normalized values for cerebral blood volume are slightly elevated in dynamic susceptibility contrast-enhanced perfusion imaging (c) with a value of 2.2 ( arrow ). MRS supports the diagnosis of stable disease due to normal choline in the lesion (d) and normal ratio normalized to the healthy tissue (f) . The lesion seems to resolve in two serial follow-up examinations (g,h) , confirming the diagnosis of stable disease. The illustrations show the values in a descending red-green-blue color scale. (Color version of the figure is available online.)](https://storage.googleapis.com/dl.dentistrykey.com/clinical/ComparisonofThreeDifferentMRPerfusionTechniquesandMRSpectroscopyforMultiparametricAssessmentinDistinguishingRecurrentHighGradeGliomasfromStableDisease/1_1s20S107663321300411X.jpg)
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ASL Imaging
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DCE Imaging
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DSC Imaging
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MRS
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Combined Implementation of ASL, DCE, DSC, and MRS
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Table 2
Receiver Operating Characteristic Analysis
ASL DCE MR DSC MR MRS Scoring System rCBF_k(trans)_ max rCBF rCBV Cho/Cr Cho/Cr(n) Multiparametric Cut-off 2.18 0.058 2.24 2.15 1.12 1.07 2 Sensitivity 53.9 61.9 77.3 81.0 85.0 70.0 74 Specificity 84.6 80.0 84.6 76.9 50.0 78.6 94 Accuracy 69.2 69.4 80.0 79.4 71.9 73.5 82.5 Cut-off 100% specificity >2.46 >0.075 >4.14 >3.92 >2.33 >1.89 Not applicable Accuracy (100% specificity) 69.2 65.0 61.5 61.5 58.9 62.5
The table displays the threshold values with maximum accuracy and maximum specificity in discriminating between recurrent glioma and stable disease. ASL, arterial spin labeling perfusion; DCE, dynamic contrast-enhanced T1-weighted perfusion imaging; DSC, dynamic susceptibility contrast-enhanced perfusion imaging; MR, magnetic resonance; MRS, MR spectroscopy; rCBF, normalized values for cerebral blood flow; k(trans), transfer constant; rCBV, normalized values for cerebral blood volume; Cho, choline; Cr, creatine; (n), normalized.
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Discussion
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ASL Imaging
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DCE Imaging
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DSC Imaging
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MRS
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Multimodality Functional Imaging
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Conclusions
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