Differentiation Between True Tumor Progression of Glioblastoma and Pseudoprogression Using Diffusion-Weighted Imaging and Perfusion-Weighted Imaging: Systematic Review and Meta-analysis

Tsakiris, Charalampos; Siempis, Timoleon; Alexiou, George Α.; Zikou, Anastasia; Sioka, Chrissa; Voulgaris, Spyridon; Argyropoulou, Maria I.

doi:10.1016/j.wneu.2020.07.218

Cited by 20 publications

(15 citation statements)

References 46 publications

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“…A prior meta-analysis has compared the utility of DWI and PWI for discriminating PsP and TTP. [33] Consistent with our results, they did not nd a signi cant difference between the two modalities. In contrast to the study by Tsakiris and colleagues, our inclusion criteria were not limited to two methods only.…”

Section: Discussionsupporting

confidence: 90%

Discriminators of pseudoprogression and true progression in high-grade gliomas: A systematic review and meta-analysis

Taylor

Ekert

Sefcikova

et al. 2022

Preprint

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BackgroundHigh-grade gliomas remain the most common primary brain tumour with limited treatments options and early recurrence rates following adjuvant treatments. However, differentiating true tumour progression (TTP) from treatment-related effects or pseudoprogression (PsP), may critically influence subsequent management options. Structural MRI is routinely employed to evaluate treatment responses, but misdiagnosis of TTP or PsP may lead to continuation of ineffective or premature cessation of effective treatments, respectively. MethodsA systematic review and meta-analysis were conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) method. The entirety of the Embase and MEDLINE databases were searched for methods differentiating PsP and TTP, and studies were selected using pre-specified eligibility criteria. The sensitivity and specificity of included studies were summarised in a forest plot. Three of the identified methods were assessed in a separate subgroup meta-analysis.ResultsTwenty-six studies assessing seven distinct neuroimaging methods in 1145 patients were included in the systematic review. 18F-fluoroethyltyrosine PET (FET PET) and amide proton transfer-weighted MRI (APTw-MRI) showed high diagnostic accuracy, but results were based on single low-powered studies. The highest performing methods in the subgroup analysis were DWI (AUC = 0.95 [0.92 – 0.96]) and DSC-pMRI (AUC = 0.94 [0.91 – 0.95]), compared to DCE-pMRI (AUC = 0.90 [0.87 – 0.93]).ConclusionsBoth DWI and DSC-pMRI performed with high sensitivity and specificity for differentiating PsP from TTP. Considering the technical parameters and feasibility of each identified method, DSC-pMRI was found to be the most promising technique.

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Section: Discussionsupporting

confidence: 90%

Discriminators of pseudoprogression and true progression in high-grade gliomas: A systematic review and meta-analysis

Taylor

Ekert

Sefcikova

et al. 2022

Preprint

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“…A number of research groups confirmed DSC-CBV to be higher in tumor recurrence/progression versus radiation necrosis [ 78 , 79 , 81 , 82 , 83 , 89 , 91 , 93 , 94 , 97 , 100 , 101 , 102 , 103 ]. These results have been accordingly strengthened by meta-analyses [ 104 , 105 , 106 , 107 ]. Chuang et al in 2016 performed a random effect model meta-analysis of ten studies evaluating CBV and found that this parameter is increased in the contrast-enhancing lesion of tumor recurrence versus radiation injury [ 105 ].…”

Section: Clinical Applications Of Hemodynamic Imaging In Gliomas—partmentioning

confidence: 97%

“…Wang et al meta-analyzed 20 studies that adopted DSC and found that the pooled sensitivity and specificity were 0.83 and 0.83 respectively, while the AUC was 0.89 [ 104 ]. A more recent study by Tsakiris evaluating the differentiation of true tumor progression versus pseudoprogression using a random effect model in five DSC studies found there to be a pooled sensitivity and specificity of 0.81 and 0.82 [ 107 ]. Some studies also found that certain histographic patterns are the best independent predictors of tumor recurrence [ 87 ].…”

Section: Clinical Applications Of Hemodynamic Imaging In Gliomas—partmentioning

confidence: 99%

“…Tsakiris et al also evaluated performance in a random effect meta-analysis of DCE in the differential diagnosis between tumor progression and pseudoprogression. They found there to be a pooled sensitivity and specificity of 0.88 and 0.77, respectively [ 107 ]. In their meta-analysis including four DCE studies, Wang et al found a pooled sensitivity and specificity of 0.73 and 0.80, and an AUC of 0.94 [ 104 ].…”

Section: Clinical Applications Of Hemodynamic Imaging In Gliomas—partmentioning

confidence: 99%

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Hemodynamic Imaging in Cerebral Diffuse Glioma—Part B: Molecular Correlates, Treatment Effect Monitoring, Prognosis, and Future Directions

Stumpo

Guida

Bellomo

et al. 2022

Cancers

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Gliomas, and glioblastoma in particular, exhibit an extensive intra- and inter-tumoral molecular heterogeneity which represents complex biological features correlating to the efficacy of treatment response and survival. From a neuroimaging point of view, these specific molecular and histopathological features may be used to yield imaging biomarkers as surrogates for distinct tumor genotypes and phenotypes. The development of comprehensive glioma imaging markers has potential for improved glioma characterization that would assist in the clinical work-up of preoperative treatment planning and treatment effect monitoring. In particular, the differentiation of tumor recurrence or true progression from pseudoprogression, pseudoresponse, and radiation-induced necrosis can still not reliably be made through standard neuroimaging only. Given the abundant vascular and hemodynamic alterations present in diffuse glioma, advanced hemodynamic imaging approaches constitute an attractive area of clinical imaging development. In this context, the inclusion of objective measurable glioma imaging features may have the potential to enhance the individualized care of diffuse glioma patients, better informing of standard-of-care treatment efficacy and of novel therapies, such as the immunotherapies that are currently increasingly investigated. In Part B of this two-review series, we assess the available evidence pertaining to hemodynamic imaging for molecular feature prediction, in particular focusing on isocitrate dehydrogenase (IDH) mutation status, MGMT promoter methylation, 1p19q codeletion, and EGFR alterations. The results for the differentiation of tumor progression/recurrence from treatment effects have also been the focus of active research and are presented together with the prognostic correlations identified by advanced hemodynamic imaging studies. Finally, the state-of-the-art concepts and advancements of hemodynamic imaging modalities are reviewed together with the advantages derived from the implementation of radiomics and machine learning analyses pipelines.

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“…When it comes to comparing DWI and PWI, a meta-analysis included 24 studies on the differentiation of PsP from TP, a meta-analysis metaanalysis including 24 studies, with a total of 900 patients, found that DWI was slightly superior to PWI in terms of sensitivity (88% vs. 85%) and specificity (85% vs. 79%). When the authors compared the overall diagnostic accuracy of the MRI modalities, using their respective AUC values (0.9156 for DWI and 0.9072 for PWI), no significant difference emerged between the two [ 49 ].…”

Section: Resultsmentioning

confidence: 99%

Pseudoprogression in Glioblastoma: Role of Metabolic and Functional MRI-Systematic Review

et al. 2022

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Background: Glioblastoma is the most frequent malignant primitive brain tumor in adults. The treatment includes surgery, radiotherapy, and chemotherapy. During follow-up, combined chemoradiotherapy can induce treatment-related changes mimicking tumor progression on medical imaging, such as pseudoprogression (PsP). Differentiating PsP from true progression (TP) remains a challenge for radiologists and oncologists, who need to promptly start a second-line treatment in the case of TP. Advanced magnetic resonance imaging (MRI) techniques such as diffusion-weighted imaging, perfusion MRI, and proton magnetic resonance spectroscopic imaging are more efficient than conventional MRI in differentiating PsP from TP. None of these techniques are fully effective, but current advances in computer science and the advent of artificial intelligence are opening up new possibilities in the imaging field with radiomics (i.e., extraction of a large number of quantitative MRI features describing tumor density, texture, and geometry). These features are used to build predictive models for diagnosis, prognosis, and therapeutic response. Method: Out of 7350 records for MR spectroscopy, GBM, glioma, recurrence, diffusion, perfusion, pseudoprogression, radiomics, and advanced imaging, we screened 574 papers. A total of 228 were eligible, and we analyzed 72 of them, in order to establish the role of each imaging modality and the usefulness and limitations of radiomics analysis.

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Differentiation Between True Tumor Progression of Glioblastoma and Pseudoprogression Using Diffusion-Weighted Imaging and Perfusion-Weighted Imaging: Systematic Review and Meta-analysis

Cited by 20 publications

References 46 publications

Discriminators of pseudoprogression and true progression in high-grade gliomas: A systematic review and meta-analysis

Discriminators of pseudoprogression and true progression in high-grade gliomas: A systematic review and meta-analysis

Hemodynamic Imaging in Cerebral Diffuse Glioma—Part B: Molecular Correlates, Treatment Effect Monitoring, Prognosis, and Future Directions

Pseudoprogression in Glioblastoma: Role of Metabolic and Functional MRI-Systematic Review

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