Diagnostic Accuracy of Arterial Spin-Labeling, Dynamic Contrast-Enhanced, and DSC Perfusion Imaging in the Diagnosis of Recurrent High-Grade Gliomas: A Prospective Study

Arterial Spin-Labeling and DSC Perfusion Metrics Improve Agreement in Neuroradiologists' Clinical Interpretations of Posttreatment High-Grade Glioma Surveillance MR Imaging-An Institutional Experience

BACKGROUND AND PURPOSE

MR perfusion has shown value in the evaluation of posttreatment high-grade gliomas, but few studies have shown its impact on the consistency and confidence of neuroradiologists' interpretation in routine clinical practice. We evaluated the impact of adding MR perfusion metrics to conventional contrast-enhanced MR imaging in posttreatment high-grade glioma surveillance imaging.

MATERIALS AND METHODS

This retrospective study included 45 adults with high-grade gliomas who had posttreatment perfusion MR imaging. Four neuroradiologists assigned Brain Tumor Reporting and Data System scores for each examination on the basis of the interpretation of contrast-enhanced MR imaging and then after the addition of arterial spin-labeling-CBF, DSC-relative CBV, and DSC-fractional tumor burden. Interrater agreement and rater agreement with a multidisciplinary consensus group were assessed with κ statistics. Raters used a 5-point Likert scale to report confidence scores. The frequency of clinically meaningful score changes resulting from the addition of each perfusion metric was determined.

RESULTS

Interrater agreement was moderate for contrast-enhanced MR imaging alone (κ = 0.63) and higher with perfusion metrics (arterial spin-labeling-CBF, κ = 0.67; DSC-relative CBV, κ = 0.66; DSC-fractional tumor burden, κ = 0.70). Agreement between raters and consensus was highest with DSC-fractional tumor burden (κ = 0.66-0.80). Confidence scores were highest with DSC-fractional tumor burden. Across all raters, the addition of perfusion resulted in clinically meaningful interpretation changes in 2%-20% of patients compared with contrast-enhanced MR imaging alone.

CONCLUSIONS

Adding perfusion to contrast-enhanced MR imaging improved interrater agreement, rater agreement with consensus, and rater confidence in the interpretation of posttreatment high-grade glioma MR imaging, with the highest agreement and confidence scores seen with DSC-fractional tumor burden. Perfusion MR imaging also resulted in interpretation changes that could change therapeutic management in up to 20% of patients.

MRI Treatment Response Assessment Maps (TRAMs) for differentiating recurrent glioblastoma from radiation necrosis

BACKGROUND

MRI treatment response assessment maps (TRAMs) were introduced to distinguish recurrent malignant glioma from therapy related changes. TRAMs are calculated with two contrast-enhanced T1-weighted sequences and reflect the "late" wash-out (or contrast clearance) and wash-in of gadolinium. Vital tumor cells are assumed to produce a wash-out because of their high turnover rate and the associated hypervascularization, whereas contrast medium slowly accumulates in scar tissue. To examine the real value of this method, we compared TRAMs with the pathology findings obtained after a second biopsy or surgery when recurrence was suspected.

METHODS

We retrospectively evaluated TRAMs in adult patients with histologically demonstrated glioblastoma, contrast-enhancing tissue and a pre-operative MRI between January 1, 2017, and December 31, 2022. Only patients with a second biopsy or surgery were evaluated. Volumes of the residual tumor, contrast clearance and contrast accumulation before the second surgery were analyzed.

RESULTS

Among 339 patients with mGBM who underwent MRI, we identified 29 repeated surgeries/biopsies in 27 patients 59 ± 12 (mean ± standard deviation) years of age. Twenty-eight biopsies were from patients with recurrent glioblastoma histology, and only one was from a patient with radiation necrosis. We volumetrically evaluated the 29 pre-surgery TRAMs. In recurrent glioblastoma, the ratio of wash-out volume to tumor volume was 36 ± 17% (range 1-73%), and the ratio of the wash-out volume to the sum of wash-out and wash-in volumes was 48 ± 21% (range 22-92%). For the one biopsy with radiation necrosis, the ratios were 42% and 54%, respectively.

CONCLUSIONS

Typical recurrent glioblastoma shows a > 20%ratio of the wash-out volume to the sum of wash-out and wash-in volumes. The one biopsy with radiation necrosis indicated that such necrosis can also produce high wash-out in individual cases. Nevertheless, the additional information provided by TRAMs increases the reliability of diagnosis.

The value of arterial spin labelling (ASL) perfusion MRI in the assessment of post-treatment progression in adult glioma: A systematic review and meta-analysis

Background

The distinction between viable tumor and therapy-induced changes is crucial for the clinical management of patients with gliomas. This study aims to quantitatively assess the efficacy of arterial spin labeling (ASL) biomarkers, including relative cerebral blood flow (rCBF) and absolute cerebral blood flow (CBF), for the discrimination of progressive disease (PD) and treatment-related effects.

Methods

Eight articles were included in the synthesis after searching the literature systematically. Data have been extracted and a meta-analysis using the random-effect model was subsequently carried out. Diagnostic accuracy assessment was also performed.

Results

This study revealed that there is a significant difference in perfusion measurements between groups with PD and therapy-induced changes. The rCBF yielded a standardized mean difference (SMD) of 1.25 [95% CI 0.75, 1.75] (p < .00001). The maximum perfusion indices (rCBFmax and CBFmax) both showed equivalent discriminatory ability, with SMD of 1.35 [95% CI 0.78, 1.91] (p < .00001) and 1.56 [95% CI 0.79, 2.33] (p < .0001), respectively. Similarly, accuracy estimates were comparable among ASL-derived metrices. Pooled sensitivities [95% CI] were 0.85 [0.67, 0.94], 0.88 [0.71, 0.96], and 0.93 [0.73, 0.98], and pooled specificities [95% CI] were 0.83 [0.71, 0.91], 0.83 [0.67, 0.92], 0.84 [0.67, 0.93], for rCBF, rCBFmax and CBFmax, respectively. Corresponding HSROC area under curve (AUC) [95% CI] were 0.90 [0.87, 0.92], 0.92 [0.89, 0.94], and 0.93 [0.90, 0.95].

Conclusion

These results suggest that ASL quantitative biomarkers, particularly rCBFmax and CBFmax, have the potential to discriminate between glioma progression and therapy-induced changes.