Perfusion MRI-Based Fractional Tumor Burden Differentiates between Tumor and Treatment Effect in Recurrent Glioblastomas and Informs Clinical Decision-Making

Multisite Benchmark Study for Standardized Relative CBV in Untreated Brain Metastases Using the DSC-MRI Consensus Acquisition Protocol

BACKGROUND AND PURPOSE

A national consensus recommendation for the collection of DSC-MRI perfusion data, used to create maps of relative CBV (rCBV), has been recently established for primary and metastatic brain tumors. The goal was to reduce intersite variability and improve ease of comparison across time and sites, fostering widespread use of this informative measure. To translate this goal into practice, the prospective collection of consensus DSC-MRI data and characterization of derived rCBV maps in brain metastases is needed. The purpose of this multisite study was to determine rCBV in untreated brain metastases in comparison to glioblastoma (GBM) and normal-appearing brain by using the national consensus protocol.

MATERIALS AND METHODS

Subjects from 3 sites with untreated enhancing brain metastases underwent DSC-MRI according to a recommended option that uses a midrange flip angle, GRE-EPI acquisition, and the administration of both a preload and second DSC-MRI dose of 0.1 mmol/kg gadolinium-based contrast agent. Quantitative maps of standardized relative CBV (srCBV) were generated and enhancing lesion ROIs determined from postcontrast T1-weighted images alone or calibrated difference maps, termed Δ T1 (dT1) maps. Mean srCBV for metastases were compared with normal-appearing white matter (NAWM) and GBM from a previous study. Comparisons were performed by using either the Wilcoxon signed-rank test for paired comparisons or the Mann-Whitney U nonparametric test for unpaired comparisons.

RESULTS

Forty-nine patients with a primary histology of lung (n = 25), breast (n = 6), squamous cell carcinoma (n = 1), melanoma (n = 5), gastrointestinal (GI) (n = 3), and genitourinary (GU) (n = 9) were included in comparison to GBM (n = 31). The mean srCBV of all metastases (1.83±1.05) were significantly lower (P = .0009) than mean srCBV for GBM (2.67 ± 1.34) with both statistically greater (P < .0001) than NAWM (0.68 ± 0.18). Histologically distinct metastases are each statistically greater than NAWM (P < .0001) with lung (P = .0002) and GU (P = .02) srCBV being significantly different from GBM srCBV.

CONCLUSIONS

Using the consensus DSC-MRI protocol, mean srCBV values were determined for treatment-naïve brain metastases in comparison to normal-appearing white matter and GBM thus setting the benchmark for all subsequent studies adherent to the national consensus recommendation.

Identification of a Single-Dose, Low-Flip-Angle-Based CBV Threshold for Fractional Tumor Burden Mapping in Recurrent Glioblastoma

BACKGROUND AND PURPOSE

DSC-MR imaging can be used to generate fractional tumor burden (FTB) maps via application of relative CBV thresholds to spatially differentiate glioblastoma recurrence from posttreatment radiation effects (PTRE). Image-localized histopathology was previously used to validate FTB maps derived from a reference DSC-MR imaging protocol by using preload, a moderate flip angle (MFA, 60°), and postprocessing leakage correction. Recently, a DSC-MR imaging protocol with a low flip angle (LFA, 30°) with no preload was shown to provide leakage-corrected relative CBV (rCBV) equivalent to the reference protocol. This study aimed to identify the rCBV thresholds for the LFA protocol that generate the most accurate FTB maps, concordant with those obtained from the reference MFA protocol.

MATERIALS AND METHODS

Fifty-two patients with grade-IV glioblastoma who had prior surgical resection and received chemotherapy and radiation therapy were included in the study. Two sets of DSC-MR imaging data were collected sequentially first by using LFA protocol with no preload, which served as the preload for the subsequent MFA protocol. Standardized relative CBV maps (sRCBV) were obtained for each patient and coregistered with the anatomic postcontrast T1-weighted images. The reference MFA-based FTB maps were computed by using previously published sRCBV thresholds (1.0 and 1.56). A receiver operating characteristics (ROC) analysis was conducted to identify the optimal, voxelwise LFA sRCBV thresholds, and the sensitivity, specificity, and accuracy of the LFA-based FTB maps were computed with respect to the MFA-based reference.

RESULTS

The mean sRCBV values of tumors across patients exhibited strong agreement (concordance correlation coefficient = 0.99) between the 2 protocols. Using the ROC analysis, the optimal lower LFA threshold that accurately distinguishes PTRE from tumor recurrence was found to be 1.0 (sensitivity: 87.77%; specificity: 90.22%), equivalent to the ground truth. To identify aggressive tumor regions, the ROC analysis identified an upper LFA threshold of 1.37 (sensitivity: 90.87%; specificity: 91.10%) for the reference MFA threshold of 1.56.

CONCLUSIONS

For LFA-based FTB maps, an sRCBV threshold of 1.0 and 1.37 can differentiate PTRE from recurrent tumors. FTB maps aid in surgical planning, guiding pathologic diagnosis and treatment strategies in the recurrent setting. This study further confirms the reliability of single-dose LFA-based DSC-MR imaging.

How to evaluate perfusion imaging in post-treatment glioma: a comparison of three different analysis methods

INTRODUCTION

Dynamic susceptibility contrast (DSC) perfusion weighted (PW)-MRI can aid in differentiating treatment related abnormalities (TRA) from tumor progression (TP) in post-treatment glioma patients. Common methods, like the 'hot spot', or visual approach suffer from oversimplification and subjectivity. Using perfusion of the complete lesion potentially offers an objective and accurate alternative. This study aims to compare the diagnostic value and assess the subjectivity of these techniques.

METHODS

50 Glioma patients with enhancing lesions post-surgery and chemo-radiotherapy were retrospectively included. Outcome was determined by clinical/radiological follow-up or biopsy. Imaging analysis used the 'hot spot', volume of interest (VOI) and visual approach. Diagnostic accuracy was compared using receiving operator characteristics (ROC) curves for the VOI and 'hot spot' approach, visual assessment was analysed with contingency tables. Inter-operator agreement was determined with Cohens kappa and intra-class coefficient (ICC).

RESULTS

29 Patients suffered from TP, 21 had TRA. The visual assessment showed poor to substantial inter-operator agreement (κ = -0.72 - 0.68). Reliability of the 'hot spot' placement was excellent (ICC = 0.89), while reference placement was variable (ICC = 0.54). The area under the ROC (AUROC) of the mean- and maximum relative cerebral blood volume (rCBV) (VOI-analysis) were 0.82 and 0.72, while the rCBV-ratio ('hot spot' analysis) was 0.69. The VOI-analysis had a more balanced sensitivity and specificity compared to visual assessment.

CONCLUSIONS

VOI analysis of DSC PW-MRI data holds greater diagnostic accuracy in single-moment differentiation of TP and TRA than 'hot spot' or visual analysis. This study underlines the subjectivity of visual placement and assessment.

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.

Neuroimaging features of primary central nervous system post-transplantation lymphoproliferative disorder following hematopoietic stem cell transplant in patients with β-thalassemia: a case series and review of literature

PURPOSE

Primary central nervous system post-transplantation lymphoproliferative disorder (PCNS-PTLD) is a rare but serious complication of hematopoietic stem cell transplantation (HSCT) in patients with severe β-thalassemia. This study aimed to assess the clinical presentation, pathological characteristics, neuroimaging findings, and treatment strategies in patients with β-thalassemia who developed PCNS-PTLD and to compare a case series from our transplant center to reported cases from literature.

METHODS

We retrospectively reviewed our hospital database and identified four cases of pathologically confirmed PCNS-PTLD without a history of systemic PTLD in patients with severe β-thalassemia after HSCT. We also performed a relevant literature review on PCNS-PTLD.

RESULTS

The median time from transplantation to diagnosis of PCNS-PTLD was 5.5 months. Intracerebral lesions were usually multiple involving both supratentorial and infratentorial regions with homogeneous or rim enhancement. All patients had pathologically confirmed PCNS-PTLD with three patients having diffuse large B-cell lymphoma and the fourth patient having plasmacytic hyperplasia. There was low response to treatment with a median survival of 83 days.

CONCLUSION

PCNS-PTLD should be considered in the differential diagnosis of patients with β-thalassemia who had an intracranial lesion on neuroimaging after HSCT.

CRITICAL RELEVANCE STATEMENT

This case series with a comprehensive review of neuroimaging and clinical characteristics of children with primary central nervous system post-transplantation lymphoproliferative disorder should advance our understanding and improve management of this rare yet severe complication following transplant for β-thalassemia.

KEY POINTS

• We assessed clinical presentation, treatment strategies, and neuroimaging characteristics of PCNS-PTLD in patients with β-thalassemia after transplantation. • Patients with β-thalassemia may have post-transplantation lymphoproliferative disorder presenting as brain lesions on neuroimaging. • Neuroimaging findings of the brain lesions are helpful for prompt diagnosis and proper management.

Tumor treating fields increases blood-brain barrier permeability and relative cerebral blood volume in patients with glioblastoma

BACKGROUND AND OBJECTIVE

200 kHz tumor treating fields (TTFields) is clinically approved for newly-diagnosed glioblastoma (nGBM). Because its effects on conventional surveillance MRI brain scans are equivocal, we investigated its effects on perfusion MRI (pMRI) brain scans.

METHODS

Each patient underwent institutional standard pMRI: dynamic contrast-enhanced (DCE) and dynamic susceptibility contrast (DSC) pMRI at three time points: baseline, 2-, and 6-months on-adjuvant therapy. At each timepoint, the difference between T1 pre- versus post-contrast tumor volume (ΔT1) and these pMRI metrics were evaluated: normalized and standardized relative cerebral blood volume (nRCBV, sRCBV); fractional plasma volume (Vp), volume of extravascular extracellular space (EES) per volume of tissue (Ve), blood-brain barrier (BBB) permeability (Ktrans), and time constant for gadolinium reflux from EES back into the vascular system (Kep). Between-group comparisons were performed using rank-sum analysis, and bootstrapping evaluated likely reproducibility of the results.

RESULTS

Among 13 pMRI datasets (11 nGBM, 2 recurrent GBM), therapies included temozolomide-only (n = 9) and temozolomide + TTFields (n = 4). No significant differences were found in patient or tumor characteristics. Compared to temozolomide-only, temozolomide + TTFields did not significantly affect the percent-change in pMRI metrics from baseline to 2 months. But during the 2- to 6-month period, temozolomide + TTFields significantly increased the percent-change in nRCBV (+26.9% [interquartile range 55.1%] vs -39.1% [37.0%], p = 0.049), sRCBV (+9.5% [39.7%] vs -30.5% [39.4%], p = 0.049), Ktrans (+54.6% [1768.4%] vs -26.9% [61.2%], p = 0.024), Ve (+111.0% [518.1%] vs -13.0% [22.5%], p = 0.048), and Vp (+98.8% [2172.4%] vs -24.6% [53.3%], p = 0.024) compared to temozolomide-only.

CONCLUSION

Using pMRI, we provide initial in-human validation of pre-clinical studies regarding the effects of TTFields on tumor blood volume and BBB permeability in GBM.

Identification of single-dose, dual-echo based CBV threshold for fractional tumor burden mapping in recurrent glioblastoma

Background

Relative cerebral blood volume (rCBV) obtained from dynamic susceptibility contrast (DSC) MRI is widely used to distinguish high grade glioma recurrence from post treatment radiation effects (PTRE). Application of rCBV thresholds yield maps to distinguish between regional tumor burden and PTRE, a biomarker termed the fractional tumor burden (FTB). FTB is generally measured using conventional double-dose, single-echo DSC-MRI protocols; recently, a single-dose, dual-echo DSC-MRI protocol was clinically validated by direct comparison to the conventional double-dose, single-echo protocol. As the single-dose, dual-echo acquisition enables reduction in the contrast agent dose and provides greater pulse sequence parameter flexibility, there is a compelling need to establish dual-echo DSC-MRI based FTB mapping. In this study, we determine the optimum standardized rCBV threshold for the single-dose, dual-echo protocol to generate FTB maps that best match those derived from the reference standard, double-dose, single-echo protocol.

Methods

The study consisted of 23 high grade glioma patients undergoing perfusion scans to confirm suspected tumor recurrence. We sequentially acquired single dose, dual-echo and double dose, single-echo DSC-MRI data. For both protocols, we generated leakage-corrected standardized rCBV maps. Standardized rCBV (sRCBV) thresholds of 1.0 and 1.75 were used to compute single-echo FTB maps as the reference for delineating PTRE (sRCBV < 1.0), tumor with moderate angiogenesis (1.0 < sRCBV < 1.75), and tumor with high angiogenesis (sRCBV > 1.75) regions. To assess the sRCBV agreement between acquisition protocols, the concordance correlation coefficient (CCC) was computed between the mean tumor sRCBV values across the patients. A receiver operating characteristics (ROC) analysis was performed to determine the optimum dual-echo sRCBV threshold. The sensitivity, specificity, and accuracy were compared between the obtained optimized threshold (1.64) and the standard reference threshold (1.75) for the dual-echo sRCBV threshold.

Results

The mean tumor sRCBV values across the patients showed a strong correlation (CCC = 0.96) between the two protocols. The ROC analysis showed maximum accuracy at thresholds of 1.0 (delineate PTRE from tumor) and 1.64 (differentiate aggressive tumors). The reference threshold (1.75) and the obtained optimized threshold (1.64) yielded similar accuracy, with slight differences in sensitivity and specificity which were not statistically significant (1.75 threshold: Sensitivity = 81.94%; Specificity: 87.23%; Accuracy: 84.58% and 1.64 threshold: Sensitivity = 84.48%; Specificity: 84.97%; Accuracy: 84.73%).

Conclusions

The optimal sRCBV threshold for single-dose, dual-echo protocol was found to be 1.0 and 1.64 for distinguishing tumor recurrence from PTRE; however, minimal differences were observed when using the standard threshold (1.75) as the upper threshold, suggesting that the standard threshold could be used for both protocols. While the prior study validated the agreement of the mean sRCBV values between the protocols, this study confirmed that their voxel-wise agreement is suitable for reliable FTB mapping. Dual-echo DSC-MRI acquisitions enable robust single-dose sRCBV and FTB mapping, provide pulse sequence parameter flexibility and should improve reproducibility by mitigating variations in preload dose and incubation time.

Case report: Fractional brain tumor burden magnetic resonance mapping to assess response to pulsed low-dose-rate radiotherapy in newly-diagnosed glioblastoma

Background

Pulsed low-dose-rate radiotherapy (pLDR) is a commonly used reirradiation technique for recurrent glioma, but its upfront use with temozolomide (TMZ) following primary resection of glioblastoma is currently under investigation. Because standard magnetic resonance imaging (MRI) has limitations in differentiating treatment effect from tumor progression in such applications, perfusion-weighted MRI (PWI) can be used to create fractional tumor burden (FTB) maps to spatially distinguish active tumor from treatment-related effect.

Methods

We performed PWI prior to re-resection in four patients with glioblastoma who had undergone upfront pLDR concurrent with TMZ who had radiographic suspicion for tumor progression at a median of 3 months (0-5 months or 0-143 days) post-pLDR. The pathologic diagnosis was compared to retrospectively-generated FTB maps.

Results

The median patient age was 55.5 years (50-60 years). All were male with IDH-wild type (n=4) and O6-methylguanine-DNA methyltransferase (MGMT) hypermethylated (n=1) molecular markers. Pathologic diagnosis revealed treatment effect (n=2), a mixture of viable tumor and treatment effect (n=1), or viable tumor (n=1). In 3 of 4 cases, FTB maps were indicative of lesion volumes being comprised predominantly of treatment effect with enhancing tumor volumes comprised of a median of 6.8% vascular tumor (6.4-16.4%).

Conclusion

This case series provides insight into the radiographic response to upfront pLDR and TMZ and the role for FTB mapping to distinguish tumor progression from treatment effect prior to redo-surgery and within 20 weeks post-radiation.

Metabolic and physiologic magnetic resonance imaging in distinguishing true progression from pseudoprogression in patients with glioblastoma

Pseudoprogression (PsP) refers to treatment-related clinico-radiologic changes mimicking true progression (TP) that occurs in patients with glioblastoma (GBM), predominantly within the first 6 months after the completion of surgery and concurrent chemoradiation therapy (CCRT) with temozolomide. Accurate differentiation of TP from PsP is essential for making informed decisions on appropriate therapeutic intervention as well as for prognostication of these patients. Conventional neuroimaging findings are often equivocal in distinguishing between TP and PsP and present a considerable diagnostic dilemma to oncologists and radiologists. These challenges have emphasized the need for developing alternative imaging techniques that may aid in the accurate diagnosis of TP and PsP. In this review, we encapsulate the current state of knowledge in the clinical applications of commonly used metabolic and physiologic magnetic resonance (MR) imaging techniques such as diffusion and perfusion imaging and proton spectroscopy in distinguishing TP from PsP. We also showcase the potential of promising imaging techniques, such as amide proton transfer and amino acid-based positron emission tomography, in providing useful information about the treatment response. Additionally, we highlight the role of "radiomics", which is an emerging field of radiology that has the potential to change the way in which advanced MR techniques are utilized in assessing treatment response in GBM patients. Finally, we present our institutional experiences and discuss future perspectives on the role of multiparametric MR imaging in identifying PsP in GBM patients treated with "standard-of-care" CCRT as well as novel/targeted therapies.

Conventional and Advanced Imaging Techniques in Post-treatment Glioma Imaging

Despite decades of advancement in the diagnosis and therapy of gliomas, the most malignant primary brain tumors, the overall survival rate is still dismal, and their post-treatment imaging appearance remains very challenging to interpret. Since the limitations of conventional magnetic resonance imaging (MRI) in the distinction between recurrence and treatment effect have been recognized, a variety of advanced MR and functional imaging techniques including diffusion-weighted imaging (DWI), diffusion tensor imaging (DTI), perfusion-weighted imaging (PWI), MR spectroscopy (MRS), as well as a variety of radiotracers for single photon emission computed tomography (SPECT) and positron emission tomography (PET) have been investigated for this indication along with voxel-based and more quantitative analytical methods in recent years. Machine learning and radiomics approaches in recent years have shown promise in distinguishing between recurrence and treatment effect as well as improving prognostication in a malignancy with a very short life expectancy. This review provides a comprehensive overview of the conventional and advanced imaging techniques with the potential to differentiate recurrence from treatment effect and includes updates in the state-of-the-art in advanced imaging with a brief overview of emerging experimental techniques. A series of representative cases are provided to illustrate the synthesis of conventional and advanced imaging with the clinical context which informs the radiologic evaluation of gliomas in the post-treatment setting.

DSC Perfusion MRI-Derived Fractional Tumor Burden and Relative CBV Differentiate Tumor Progression and Radiation Necrosis in Brain Metastases Treated with Stereotactic Radiosurgery

BACKGROUND AND PURPOSE

Differentiation between tumor and radiation necrosis in patients with brain metastases treated with stereotactic radiosurgery is challenging. We hypothesized that MR perfusion and metabolic metrics can differentiate radiation necrosis from progressive tumor in this setting.

MATERIALS AND METHODS

We retrospectively evaluated MRIs comprising DSC, dynamic contrast-enhanced, and arterial spin-labeling perfusion imaging in subjects with brain metastases previously treated with stereotactic radiosurgery. For each lesion, we obtained the mean normalized and standardized relative CBV and fractional tumor burden, volume transfer constant, and normalized maximum CBF, as well as the maximum standardized uptake value in a subset of subjects who underwent FDG-PET. Relative CBV thresholds of 1 and 1.75 were used to define low and high fractional tumor burden.

RESULTS

Thirty subjects with 37 lesions (20 radiation necrosis, 17 tumor) were included. Compared with radiation necrosis, tumor had increased mean normalized and standardized relative CBV (P = .002) and high fractional tumor burden (normalized, P = .005; standardized, P = .003) and decreased low fractional tumor burden (normalized, P = .03; standardized, P = .01). The area under the curve showed that relative CBV (normalized = 0.80; standardized = 0.79) and high fractional tumor burden (normalized = 0.77; standardized = 0.78) performed the best to discriminate tumor and radiation necrosis. For tumor prediction, the normalized relative CBV cutoff of ≥1.75 yielded a sensitivity of 76.5% and specificity of 70.0%, while the standardized cutoff of ≥1.75 yielded a sensitivity of 41.2% and specificity of 95.0%. No significance was found with the volume transfer constant, normalized CBF, and standardized uptake value.

CONCLUSIONS

Increased relative CBV and high fractional tumor burden (defined by a threshold relative CBV of ≥1.75) best differentiated tumor from radiation necrosis in subjects with brain metastases treated with stereotactic radiosurgery. Performance of normalized and standardized approaches was similar.

Advanced MRI Protocols to Discriminate Glioma From Treatment Effects: State of the Art and Future Directions

In the follow-up treatment of high-grade gliomas (HGGs), differentiating true tumor progression from treatment-related effects, such as pseudoprogression and radiation necrosis, presents an ongoing clinical challenge. Conventional MRI with and without intravenous contrast serves as the clinical benchmark for the posttreatment surveillance imaging of HGG. However, many advanced imaging techniques have shown promise in helping better delineate the findings in indeterminate scenarios, as posttreatment effects can often mimic true tumor progression on conventional imaging. These challenges are further confounded by the histologic admixture that can commonly occur between tumor growth and treatment-related effects within the posttreatment bed. This review discusses the current practices in the surveillance imaging of HGG and the role of advanced imaging techniques, including perfusion MRI and metabolic MRI.

Reproducibility of volume analysis of dynamic susceptibility contrast perfusion-weighted imaging in untreated glioblastomas

PURPOSE

Despite a high variability, the hotspot method is widely used to calculate the cerebral blood volume (CBV) of glioblastomas on DSC-MRI. Our aim was to investigate inter- and intra-observer reproducibility of parameters calculated with the hotspot or a volume method and that of an original parameter assessing the fraction of pixels in the tumour volume displaying rCBV > 2: %rCBV > 2.

METHODS

Twenty-seven consecutive patients with untreated glioblastoma (age: 63, women: 11) were retrospectively included. Three observers calculated the maximum tumour CBV value (rCBVmax) normalized with a reference ROI in the contralateral white matter (CBVWM) with (i) the hotspot method and (ii) with a volume method following tumour segmentation on 3D contrast-enhanced T1-WI. From this volume method, %rCBV > 2 was also assessed. After 8-12 weeks, one observer repeated all delineations. Intraclass (ICC) and Lin's (LCC) correlation coefficients were used to determine reproducibility.

RESULTS

Inter-observer reproducibility of rCBVmax was fair with the hotspot and good with the volume method (ICC = 0.46 vs 0.65, p > 0.05). For CBVWM, it was fair with the hotspot and excellent with the volume method (0.53 vs 0.84, p < 0.05). Reproducibility of one pairwise combination of observers was significantly better for both rCBVmax and CBVWM (LCC = 0.33 vs 0.75; 0.52 vs 0.89, p < 0.05). %rCBV > 2 showed excellent inter- and intra-observer reproducibility (ICC = 0.94 and 0.91).

CONCLUSION

Calculated in glioblastomas with a volume method, rCBVmax and CBVWM yielded good to excellent reproducibility but only fair with the hotspot method. Overall, the volume analysis offers a highly reproducible parameter, %rCBV > 2, that could be promising during the follow-up of such heterogeneous tumours.

Combined Diagnostic Accuracy of Diffusion and Perfusion MR Imaging to Differentiate Radiation-Induced Necrosis from Recurrence in Glioblastoma

We aimed to use quantitative values derived from perfusion and diffusion-weighted MR imaging (PWI and DWI) to differentiate radiation-induced necrosis (RIN) from tumor recurrence in Glioblastoma (GBM) and investigate the best parameters for improved diagnostic accuracy and clinical decision-making. Methods: A retrospective analysis of follow-up MRI with new enhancing observations was performed in histopathologically confirmed subjects of post-treated GBM, who underwent re-surgical exploration. Quantitative estimation of rCBV (relative cerebral blood volume) from PWI and three methods of apparent diffusion coefficient (ADC) estimation were performed, namely ADC R1 (whole cross-sectional area of tumor), ADC R2 (only solid enhancing lesion), and ADC R3 (central necrosis). ROC curve and logistic regression analysis was completed. A confusion matrix table created using Excel provided the best combination parameters to ameliorate false-positive and false-negative results. Results: Forty-four subjects with a mean age of 46 years (range, 19−70 years) underwent re-surgical exploration with RIN in 28 (67%) and recurrent tumor in 16 (33%) on histopathology. rCBV threshold of >3.4 had the best diagnostic accuracy (AUC = 0.93, 81% sensitivity and 89% specificity). A multiple logistic regression model showed significant contributions from rCBV (p < 0.001) and ADC R3 (p = 0.001). After analysis of confusion matrix ADC R3 > 2032 × 10−6 mm2 achieved 100% specificity with gain in sensitivity (94% vs. 56%). Conclusions: A combination of parameters had better diagnostic performance, and a stepwise combination of rCBV and ADC R3 obviated unnecessary biopsies in 10% (3/28), leading to improved clinical decision-making.

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

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.

High-Grade Glioma Treatment Response Monitoring Biomarkers: A Position Statement on the Evidence Supporting the Use of Advanced MRI Techniques in the Clinic, and the Latest Bench-to-Bedside Developments. Part 1: Perfusion and Diffusion Techniques

Objective

Summarize evidence for use of advanced MRI techniques as monitoring biomarkers in the clinic, and highlight the latest bench-to-bedside developments.

Methods

Experts in advanced MRI techniques applied to high-grade glioma treatment response assessment convened through a European framework. Current evidence regarding the potential for monitoring biomarkers in adult high-grade glioma is reviewed, and individual modalities of perfusion, permeability, and microstructure imaging are discussed (in Part 1 of two). In Part 2, we discuss modalities related to metabolism and/or chemical composition, appraise the clinic readiness of the individual modalities, and consider post-processing methodologies involving the combination of MRI approaches (multiparametric imaging) or machine learning (radiomics).

Results

High-grade glioma vasculature exhibits increased perfusion, blood volume, and permeability compared with normal brain tissue. Measures of cerebral blood volume derived from dynamic susceptibility contrast-enhanced MRI have consistently provided information about brain tumor growth and response to treatment; it is the most clinically validated advanced technique. Clinical studies have proven the potential of dynamic contrast-enhanced MRI for distinguishing post-treatment related effects from recurrence, but the optimal acquisition protocol, mode of analysis, parameter of highest diagnostic value, and optimal cut-off points remain to be established. Arterial spin labeling techniques do not require the injection of a contrast agent, and repeated measurements of cerebral blood flow can be performed. The absence of potential gadolinium deposition effects allows widespread use in pediatric patients and those with impaired renal function. More data are necessary to establish clinical validity as monitoring biomarkers. Diffusion-weighted imaging, apparent diffusion coefficient analysis, diffusion tensor or kurtosis imaging, intravoxel incoherent motion, and other microstructural modeling approaches also allow treatment response assessment; more robust data are required to validate these alone or when applied to post-processing methodologies.

Conclusion

Considerable progress has been made in the development of these monitoring biomarkers. Many techniques are in their infancy, whereas others have generated a larger body of evidence for clinical application.

Magnetic Resonance Imaging Mapping of Brain Tumor Burden: Clinical Implications for Neurosurgical Management: Case Report

BACKGROUND AND IMPORTANCE

Distinction of brain tumor progression from treatment effect on postcontrast magnetic resonance imaging (MRI) is an ongoing challenge in the management of brain tumor patients. A newly emerging MRI biomarker called fractional tumor burden (FTB) has demonstrated the ability to spatially distinguish high-grade brain tumor from treatment effect with important implications for surgical management and pathological diagnosis.

CLINICAL PRESENTATION

A 58-yr-old male with glioblastoma was treated with standard concurrent chemoradiotherapy (CRT) after initial resection. Throughout follow-up imaging, the distinction of tumor progression from treatment effect was of concern. The surgical report from a redo resection indicated recurrent glioblastoma, while the tissue sent for pathological diagnosis revealed no tumor. Presurgical FTB maps confirmed the spatial variation of tumor and treatment effect within the contrast-agent enhancing lesion. Unresected lesion, shown to be an active tumor on FTB, was the site of substantial tumor growth postresection.

CONCLUSION

This case report introduces the idea that a newly developed MRI biomarker, FTB, can provide information of tremendous benefit for surgical management, pathological diagnosis as well as subsequent treatment management decisions in high-grade glioma.

The Prognostic Value of ctDNA and bTMB on Immune Checkpoint Inhibitors in Human Cancer

Background

Circulating tumor DNA (ctDNA) levels and blood tumor mutation burden (bTMB) have a significant impact on the prognosis of tumor patients. However, their prognostic role in immune checkpoint inhibitors (ICIs) in cancer patients is still unclear.

Methods

We used the Review Manager software (version 5.3) to perform a meta-analysis based on the published literature to explore the prognostic value of ctDNA and bTMB in patients receiving immunotherapy. We extracted the hazard ratios (HRs) of progression-free survival (PFS) and overall survival (OS) for each included study and their respective 95% confidence intervals (CIs) and p-values for analysis.

Results

Thirteen studies were included in the meta-analysis. Higher ctDNA levels were significantly associated with shorter OS (HR = 3.35, 95%CI = 2.49–4.51, p < 0.00001) and PFS (HR = 3.28, 95%CI = 2.47–4.35, p < 0.00001). The results of ctDNA subgroup analysis showed that high posttreatment ctDNA levels significantly correlated with shorter OS in cancer patients receiving ICIs (HR = 5.09, 95%CI = 1.43–18.07, p = 0.01). Moreover, patients with ctDNA clearance had better OS (HR = 4.94, 95%CI = 2.96–8.26, p < 0.00001). Patients with high posttreatment ctDNA levels had shorter PFS (HR = 3.00, 95%CI = 2.02–4.46, p < 0.00001) and those with ctDNA clearance had longer PFS (HR = 4.61, 95%CI = 2.78–7.65, p < 0.00001). However, there was no statistically significant difference in the OS benefits between a high and a low bTMB after ICI therapy (HR = 0.68, 95%CI = 0.33–1.37, p = 0.28).

Conclusions

The host immune system and tumor burden together determine whether cancer patients can benefit from ICI therapy. Our systematic review and meta-analysis revealed for the first time that the levels of pretreatment and posttreatment ctDNA and the clearance of ctDNA can independently be used as prognostic factors for antitumor immunotherapy, while bTMB cannot. In conclusion, ctDNA levels have great potential as an assistant tool for radiological assessments to make clinical therapeutic decisions. The prognostic utility of bTMB still requires further exploration.

Advanced Imaging and Computational Techniques for the Diagnostic and Prognostic Assessment of Malignant Gliomas

ABSTRACT

Advanced imaging techniques provide a powerful tool to assess the intratumoral and intertumoral heterogeneity of gliomas. Advances in the molecular understanding of glioma subgroups may allow improved diagnostic assessment combining imaging and molecular tumor features, with enhanced prognostic utility and implications for patient treatment. In this article, a comprehensive overview of the physiologic basis for conventional and advanced imaging techniques is presented, and clinical applications before and after treatment are discussed. An introduction to the principles of radiomics and the advanced integration of imaging, clinical outcomes, and genomic data highlights the future potential for this field of research to better stratify and select patients for standard as well as investigational therapies.

Performance of Standardized Relative CBV for Quantifying Regional Histologic Tumor Burden in Recurrent High-Grade Glioma: Comparison against Normalized Relative CBV Using Image-Localized Stereotactic Biopsies

BACKGROUND AND PURPOSE

Perfusion MR imaging measures of relative CBV can distinguish recurrent tumor from posttreatment radiation effects in high-grade gliomas. Currently, relative CBV measurement requires normalization based on user-defined reference tissues. A recently proposed method of relative CBV standardization eliminates the need for user input. This study compares the predictive performance of relative CBV standardization against relative CBV normalization for quantifying recurrent tumor burden in high-grade gliomas relative to posttreatment radiation effects.

MATERIALS AND METHODS

We recruited 38 previously treated patients with high-grade gliomas (World Health Organization grades III or IV) undergoing surgical re-resection for new contrast-enhancing lesions concerning for recurrent tumor versus posttreatment radiation effects. We recovered 112 image-localized biopsies and quantified the percentage of histologic tumor content versus posttreatment radiation effects for each sample. We measured spatially matched normalized and standardized relative CBV metrics (mean, median) and fractional tumor burden for each biopsy. We compared relative CBV performance to predict tumor content, including the Pearson correlation (r), against histologic tumor content (0%-100%) and the receiver operating characteristic area under the curve for predicting high-versus-low tumor content using binary histologic cutoffs (≥50%; ≥80% tumor).

RESULTS

Across relative CBV metrics, fractional tumor burden showed the highest correlations with tumor content (0%-100%) for normalized (r = 0.63, P < .001) and standardized (r = 0.66, P < .001) values. With binary cutoffs (ie, ≥50%; ≥80% tumor), predictive accuracies were similar for both standardized and normalized metrics and across relative CBV metrics. Median relative CBV achieved the highest area under the curve (normalized = 0.87, standardized = 0.86) for predicting ≥50% tumor, while fractional tumor burden achieved the highest area under the curve (normalized = 0.77, standardized = 0.80) for predicting ≥80% tumor.

CONCLUSIONS

Standardization of relative CBV achieves similar performance compared with normalized relative CBV and offers an important step toward workflow optimization and consensus methodology.