Clinical investigation survival prediction in high-grade gliomas by MRI perfusion before and during early stage of RT

Evolving concepts in margin strategies and adaptive radiotherapy for glioblastoma: A new future is on the horizon

Chemoradiotherapy is the standard treatment after maximal safe resection for glioblastoma (GBM). Despite advances in molecular profiling, surgical techniques, and neuro-imaging, there have been no major breakthroughs in radiotherapy (RT) volumes in decades. Although the majority of recurrences occur within the original gross tumor volume (GTV), treatment of a clinical target volume (CTV) ranging from 1.5 to 3.0 cm beyond the GTV remains the standard of care. Over the past 15 years, the incorporation of standard and functional MRI sequences into the treatment workflow has become a routine practice with increasing adoption of MR simulators, and new integrated MR-Linac technologies allowing for daily pre-, intra- and post-treatment MR imaging. There is now unprecedented ability to understand the tumor dynamics and biology of GBM during RT, and safe CTV margin reduction is being investigated with the goal of improving the therapeutic ratio. The purpose of this review is to discuss margin strategies and the potential for adaptive RT for GBM, with a focus on the challenges and opportunities associated with both online and offline adaptive workflows. Lastly, opportunities to biologically guide adaptive RT using non-invasive imaging biomarkers and the potential to define appropriate volumes for dose modification will be discussed.

Integrating multi-modal imaging in radiation treatments for glioblastoma

Advances in diagnostic and treatment technology along with rapid developments in translational research may now allow the realization of precision radiotherapy. Integration of biologically informed multimodality imaging to address the spatial and temporal heterogeneity underlying treatment resistance in glioblastoma is now possible for patient care, with evidence of safety and potential benefit. Beyond their diagnostic utility, several candidate imaging biomarkers have emerged in recent early-phase clinical trials of biologically based radiotherapy, and their definitive assessment in multicenter prospective trials is already in development. In this review, the rationale for clinical implementation of candidate advanced magnetic resonance imaging and positron emission tomography imaging biomarkers to guide personalized radiotherapy, the current landscape, and future directions for integrating imaging biomarkers into radiotherapy for glioblastoma are summarized. Moving forward, response-adaptive radiotherapy using biologically informed imaging biomarkers to address emerging treatment resistance in rational combination with novel systemic therapies may ultimately permit improvements in glioblastoma outcomes and true individualization of patient care.

Treatment of Central Nervous System Tumors on Combination MR-Linear Accelerators: Review of Current Practice and Future Directions

Magnetic resonance imaging (MRI) provides excellent visualization of central nervous system (CNS) tumors due to its superior soft tissue contrast. Magnetic resonance-guided radiotherapy (MRgRT) has historically been limited to use in the initial treatment planning stage due to cost and feasibility. MRI-guided linear accelerators (MRLs) allow clinicians to visualize tumors and organs at risk (OARs) directly before and during treatment, a process known as online MRgRT. This novel system permits adaptive treatment planning based on anatomical changes to ensure accurate dose delivery to the tumor while minimizing unnecessary toxicity to healthy tissue. These advancements are critical to treatment adaptation in the brain and spinal cord, where both preliminary MRI and daily CT guidance have typically had limited benefit. In this narrative review, we investigate the application of online MRgRT in the treatment of various CNS malignancies and any relevant ongoing clinical trials. Imaging of glioblastoma patients has shown significant changes in the gross tumor volume over a standard course of chemoradiotherapy. The use of adaptive online MRgRT in these patients demonstrated reduced target volumes with cavity shrinkage and a resulting reduction in radiation dose to uninvolved tissue. Dosimetric feasibility studies have shown MRL-guided stereotactic radiotherapy (SRT) for intracranial and spine tumors to have potential dosimetric advantages and reduced morbidity compared with conventional linear accelerators. Similarly, dosimetric feasibility studies have shown promise in hippocampal avoidance whole brain radiotherapy (HA-WBRT). Next, we explore the potential of MRL-based multiparametric MRI (mpMRI) and genomically informed radiotherapy to treat CNS disease with cutting-edge precision. Lastly, we explore the challenges of treating CNS malignancies and special limitations MRL systems face.

Advances in Radiotherapy for Brain Metastases

Radiotherapy remains a cornerstone treatment of brain metastases. With new treatment advances, patients with brain metastases are living longer, and finding solutions for mitigating treatment-related neurotoxicity and improving quality of life is important. Historically, whole-brain radiation therapy (WBRT) was widely used but treatment options such as hippocampal sparing WBRT and stereotactic radiosurgery (SRS) have emerged as promising alternatives. Herein, we discuss the recent advances in radiotherapy for brain metastases including the sparing of critical structures that may improve long-term neurocognitive outcomes (eg, hippocampus, fornix) that may improve long-term neurocognitive outcome, evidence supporting preoperative and fractionated-SRS, and treatment strategies for managing radiation necrosis.

Dynamic Susceptibility Contrast MRI May Contribute in Prediction of Stereotactic Radiosurgery Outcome in Brain Metastases

Background

Following stereotactic radiosurgery (SRS), predicting treatment response is not possible at an early stage using structural imaging alone. Hence, the current study aims at investigating whether dynamic susceptibility contrast (DSC)-MRI estimated prior to SRS can provide predictive biomarkers in response to SRS treatment and characterize vascular characteristics of pseudo-progression.

Methods

In this retrospective study, perfusion-weighted DSC-MRI image data acquired with a temporal resolution of 1.45 seconds were collected from 41 patients suffering from brain metastases. Outcome was defined based on lesion volume changes in time (determined on structural images) or death. Motion correction and manual lesion delineation were performed prior to semi-automated, voxel-wise perfusion analysis. Statistical testing was performed using linear regression and a significance threshold at P = .05. Age, sex, primary cancers (pulmonary cancer and melanoma), lesion volume, and dichotomized survival time were added as covariates in the linear regression models (ANOVA).

Results

Relative cerebral blood volume (rCBV) and relative cerebral blood flow (rCBF) were found to be significantly lower prior to SRS treatment in patients with increasing lesion volume or early death post-SRS (P ≤ .01).

Conclusion

Unfavorable treatment outcome may be linked to low perfusion prior to SRS. Pseudo-progression may be preceded by a transient rCBF increase post-SRS. However, results should be verified in different or larger patient material.

Differentiation of progressive disease from pseudoprogression using MRI histogram analysis in patients with treated glioblastoma

PURPOSE

Conventional magnetic resonance imaging (MRI) technics are insufficient in the differentiation of tumor progression from post-treatment changes in patients with treated glioblastoma. Previous studies have suggested that histogram analysis is a useful tool in the assessment of treatment response in different cancer types. The aim of the study was to to evaluate the effectiveness of MRI histogram analysis in the differentiation of tumor progression from pseudoprogression in patients with treated glioblastoma.

METHODS

Forty-six patients with glioblastoma who newly developed enhancing lesions following chemoradiation treatment were included in this retrospective study. Histogram analysis was performed from new enhancing lesions on T1-weighted contrast-enhanced MRI. Histogram analysis findings of patients with progression (23) and pseudoprogression (23) were compared.

RESULTS

Mean, minimum, median, maximum, standard deviation, variance, entropy, skewness, uniformity values were found to be significantly higher in progressive disease (p < 0.05). A receiver-operating characteristic (ROC) curve analysis was performed for mean value, and area under the curve (AUC) was found as 0.975. When the threshold value was selected as 528.86, two groups could be differentiated with 95.7% sensitivity and 87.0% specificity.

CONCLUSION

MRI histogram analysis can be used for the differentiation of progressive disease from pseudoprogression.

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.

Medical Imaging Biomarker Discovery and Integration Towards AI-Based Personalized Radiotherapy

Intensity-modulated radiation therapy (IMRT) has been used for high-accurate physical dose distribution sculpture and employed to modulate different dose levels into Gross Tumor Volume (GTV), Clinical Target Volume (CTV) and Planning Target Volume (PTV). GTV, CTV and PTV can be prescribed at different dose levels, however, there is an emphasis that their dose distributions need to be uniform, despite the fact that most types of tumour are heterogeneous. With traditional radiomics and artificial intelligence (AI) techniques, we can identify biological target volume from functional images against conventional GTV derived from anatomical imaging. Functional imaging, such as multi parameter MRI and PET can be used to implement dose painting, which allows us to achieve dose escalation by increasing doses in certain areas that are therapy-resistant in the GTV and reducing doses in less aggressive areas. In this review, we firstly discuss several quantitative functional imaging techniques including PET-CT and multi-parameter MRI. Furthermore, theoretical and experimental comparisons for dose painting by contours (DPBC) and dose painting by numbers (DPBN), along with outcome analysis after dose painting are provided. The state-of-the-art AI-based biomarker diagnosis techniques is reviewed. Finally, we conclude major challenges and future directions in AI-based biomarkers to improve cancer diagnosis and radiotherapy treatment.

Prediction of the effects of radiation therapy in esophageal cancer using diffusion and perfusion MRI

Chemoradiation therapy (CRT) of locally advanced esophageal cancer (LAEC), although improving outcomes of patients, still results in 50% of local failure. An early prediction could identify patients at high risk of poor response for individualized adaptive treatment. We aimed to investigate physiological changes in LAEC using diffusion and perfusion magnetic resonance imaging (MRI) for early prediction of treatment response. In the study, 115 LAEC patients treated with CRT were enrolled (67 in the discovery cohort and 48 in the validation cohort). MRI scans were performed before radiotherapy (pre‐RT) and at week 3 during RT (mid‐RT). Gross tumor volume (GTV) of primary tumor was delineated on T2‐weighted images. Within the GTV, the hypercellularity volume (V_HC) and high blood volume (V_HBV) were defined based on the analysis of ADC and fractional plasma volume (Vp) histogram distributions within the tumors in the discovery cohort. The median GTVs were 28 cc ± 2.2 cc at pre‐RT and 16.7 cc ± 1.5 cc at mid‐RT. Respectively, V_HC and V_HBV decreased from 4.7 cc ± 0.7 cc and 5.7 cc ± 0.7 cc at pre‐RT to 2.8 cc ± 0.4 cc and 3.5 cc ± 0.5 cc at mid‐RT. Smaller V_HC at mid‐RT (area under the curve [AUC] = 0.67, P = .05; AUC = 0.66, P = .05) and further decrease in V_HC at mid‐RT (AUC = 0.7, P = .01; AUC = 0.69, P = .03) were associated with longer progression‐free survival (PFS) in both discovery and validation cohort. No significant predictive effects were shown in GTV and V_HBV at any time point. In conclusion, we demonstrated that V_HC represents aggressive subvolumes in LAEC. Further analysis will be carried out to confirm the correlations between the changes in image‐phenotype subvolumes and local failure to determine the radiation‐resistant tumor subvolumes, which may be useful for dose escalation.

Precision Radiotherapy for Gliomas: Implementing Novel Imaging Biomarkers to Improve Outcomes With Patient-Specific Therapy

ABSTRACT

Gliomas are the most common primary brain cancer, yet are extraordinarily challenging to treat because they can be aggressive and infiltrative, locally recurrent, and resistant to standard treatments. Furthermore, the treatments themselves, including radiation therapy, can affect patients' neurocognitive function and quality of life. Noninvasive imaging is the standard of care for primary brain tumors, including diagnosis, treatment planning, and monitoring for treatment response. This article explores the ways in which advanced imaging has and will continue to transform radiation treatment for patients with gliomas, with a focus on cognitive preservation and novel biomarkers, as well as precision radiotherapy and treatment adaptation. Advances in novel imaging techniques continue to push the field forward, to more precisely guided treatment planning, radiation dose escalation, measurement of therapeutic response, and understanding of radiation-associated injury.

A Phase 2 Study of Dose-intensified Chemoradiation Using Biologically Based Target Volume Definition in Patients With Newly Diagnosed Glioblastoma

PURPOSE

We hypothesized that dose-intensified chemoradiation therapy targeting adversely prognostic hypercellular (TVHCV) and hyperperfused (TVCBV) tumor volumes would improve outcomes in patients with glioblastoma.

METHODS AND MATERIALS

This single-arm, phase 2 trial enrolled adult patients with newly diagnosed glioblastoma. Patients with a TVHCV/TVCBV >1 cm3, identified using high b-value diffusion-weighted magnetic resonance imaging (MRI) and dynamic contrast-enhanced perfusion MRI, were treated over 30 fractions to 75 Gy to the TVHCV/TVCBV with temozolomide. The primary objective was to estimate improvement in 12-month overall survival (OS) versus historical control. Secondary objectives included evaluating the effect of 3-month TVHCV/TVCBV reduction on OS using Cox proportional-hazard regression and characterizing coverage (95% isodose line) of metabolic tumor volumes identified using correlative 11C-methionine positron emission tomography. Clinically meaningful change was assessed for quality of life by the European Organisation for the Research and Treatment of Cancer Quality of Life Questionnaire C30, for symptom burden by the MD Anderson Symptom Inventory for brain tumor, and for neurocognitive function (NCF) by the Controlled Oral Word Association Test, the Trail Making Test, parts A and B, and the Hopkins Verbal Learning Test-Revised.

RESULTS

Between 2016 and 2018, 26 patients were enrolled. Initial patients were boosted to TVHCV alone, and 13 patients were boosted to both TVHCV/TVCBV. Gross or subtotal resection was performed in 87% of patients; 22% were O6-methylguanine-DNA methyltransferase (MGMT) methylated. With 26-month follow-up (95% CI, 19-not reached), the 12-month OS rate among patients boosted to the combined TVHCV/TVCBV was 92% (95% CI, 78%-100%; P = .03) and the median OS was 20 months (95% CI, 18-not reached); the median OS for the whole study cohort was 20 months (95% CI, 14-29 months). Patients whose 3-month TVHCV/TVCBV decreased to less than the median volume (3 cm3) had superior OS (29 vs 12 months; P = .02). Only 5 patients had central or in-field failures, and 93% (interquartile range, 59%-100%) of the 11C-methionine metabolic tumor volumes received high-dose coverage. Late grade 3 neurologic toxicity occurred in 2 patients. Among non-progressing patients, 1-month and 7-month deterioration in quality of life, symptoms, and NCF were similar in incidence to standard therapy.

CONCLUSIONS

Dose intensification against hypercellular/hyperperfused tumor regions in glioblastoma yields promising OS with favorable outcomes for NCF, symptom burden, and quality of life, particularly among patients with greater tumor reduction 3 months after radiation therapy.

Transformational Role of Medical Imaging in (Radiation) Oncology

Simple Summary

Onboard, imaging techniques have brought about a huge transformation in the ability to deliver targeted radiation therapies. Each generation of these technologies enables us to better visualize where to deliver lethal doses of radiation and thus allows the shrinking of necessary geometric margins leading to reduced toxicities. Alongside improvements in treatment delivery, advances in medical imaging have also allowed us to better define the volumes we wish to target. The development of imaging techniques that can capture aspects of the tumor’s biology before, during and after therapy is transforming how treatment can be delivered. Technological changes have further made these biological imaging techniques available in real-time providing the opportunity to monitor a patient’s response to treatment closely and often before any volume changes are visible on conventional radiological images. Here we discuss the development of robust quantitative imaging biomarkers and how they can personalize therapy towards meaningful clinical endpoints.

Abstract

Onboard, real-time, imaging techniques, from the original megavoltage planar imaging devices, to the emerging combined MRI-Linear Accelerators, have brought a huge transformation in the ability to deliver targeted radiation therapies. Each generation of these technologies enables lethal doses of radiation to be delivered to target volumes with progressively more accuracy and thus allows shrinking of necessary geometric margins, leading to reduced toxicities. Alongside these improvements in treatment delivery, advances in medical imaging, e.g., PET, and MRI, have also allowed target volumes themselves to be better defined. The development of functional and molecular imaging is now driving a conceptually larger step transformation to both better understand the cancer target and disease to be treated, as well as how tumors respond to treatment. A biological description of the tumor microenvironment is now accepted as an essential component of how to personalize and adapt treatment. This applies not only to radiation oncology but extends widely in cancer management from surgical oncology planning and interventional radiology, to evaluation of targeted drug delivery efficacy in medical oncology/immunotherapy. Here, we will discuss the role and requirements of functional and metabolic imaging techniques in the context of brain tumors and metastases to reliably provide multi-parametric imaging biomarkers of the tumor microenvironment.

Novel Radiation Approaches

The standard of care treatment for glioblastoma is surgical resection followed by radiotherapy to 60 Gy with concurrent and adjuvant temozolomide with or without tumor-treating fields. Advanced imaging techniques are under evaluation to better guide radiotherapy target volume delineation and allow for dose escalation. Particle therapy, in the form of protons, carbon ions, and boron neutron capture therapy, are being assessed as strategies to improve the radiotherapeutic ratio. Stereotactic, hypofractionated, pulsed-reduced dose-rate, and particle radiotherapy are re-irradiation techniques each uniquely suited for different clinical scenarios. Novel radiotherapy approaches, such as FLASH, represent promising advancements in radiotherapy for glioblastoma.

Advanced Imaging Techniques for Radiotherapy Planning of Gliomas

The accuracy of target delineation in radiation treatment (RT) planning of cerebral gliomas is crucial to achieve high tumor control, while minimizing treatment-related toxicity. Conventional magnetic resonance imaging (MRI), including contrast-enhanced T1-weighted and fluid-attenuated inversion recovery (FLAIR) sequences, represents the current standard imaging modality for target volume delineation of gliomas. However, conventional sequences have limited capability to discriminate treatment-related changes from viable tumors, owing to the low specificity of increased blood-brain barrier permeability and peritumoral edema. Advanced physiology-based MRI techniques, such as MR spectroscopy, diffusion MRI and perfusion MRI, have been developed for the biological characterization of gliomas and may circumvent these limitations, providing additional metabolic, structural, and hemodynamic information for treatment planning and monitoring. Radionuclide imaging techniques, such as positron emission tomography (PET) with amino acid radiopharmaceuticals, are also increasingly used in the workup of primary brain tumors, and their integration in RT planning is being evaluated in specialized centers. This review focuses on the basic principles and clinical results of advanced MRI and PET imaging techniques that have promise as a complement to RT planning of gliomas.

Response assessment during chemoradiation using a hypercellular/hyperperfused imaging phenotype predicts survival in patients with newly diagnosed glioblastoma

BACKGROUND

Adversely prognostic hypercellular and hyperperfused regions of glioblastoma (GBM) predict progression-free survival, and are a novel target for dose-intensified chemoradiation (chemoRT) recently implemented in a phase II clinical trial. As a secondary aim, we hypothesized that dose-intensified chemoRT would induce greater mid-treatment response of hypercellular/hyperperfused tumor regions vs standard chemoradiation, and that early response would improve overall survival (OS).

METHODS

Forty-nine patients with newly diagnosed GBM underwent prospective, multiparametric high b value diffusion-weighted MRI (DW-MRI) and perfusion dynamic contrast-enhanced MRI (DCE-MRI) pre-RT and 3-4 weeks into RT. The hypercellular tumor volume (TVHCV, mean contralateral normal brain + 2SD) and hyperperfused tumor volume (TVCBV, contralateral normal frontal gray matter + 1SD) were generated using automated thresholding. Twenty-six patients were enrolled on a dose-escalation trial targeting TVHCV/TVCBV with 75 Gy in 30 fractions, and 23 non-trial patients comprised the control group. OS was estimated using the Kaplan-Meier method and compared using the log-rank test. The effect of TVHCV/TVCBV and Gd-enhanced tumor volume on OS was assessed using multivariable Cox proportional-hazard regression.

RESULTS

Most patients had gross total (47%) or subtotal resection (37%), 25% were MGMT-methylated. Patients treated on the dose-escalation trial had significantly greater reduction in TVHCV/TVCBV (41% reduction, IQR 17%-75%) vs non-trial patients (6% reduction, IQR 6%-22%, P = .002). An increase in TVHCV/TVCBV during chemoRT was associated with worse OS (adjusted hazard ratio [aHR] 1.2, 95%CI 1.0-1.4, P = .02), while pre-treatment tumor volumes (P > .5) and changes in Gd-enhanced volume (P = .9) were not.

CONCLUSIONS

Multiparametric MRI permits identification of therapeutic resistance during chemoRT and supports adaptive strategies in future trials.

A feasibility study to evaluate early treatment response of brain metastases one week after stereotactic radiosurgery using perfusion weighted imaging

Background

To explore if early perfusion-weighted magnetic resonance imaging (PWI) may be a promising imaging biomarker to predict local recurrence (LR) of brain metastases after stereotactic radiosurgery (SRS).

Methods

This is a prospective pilot study of adult brain metastasis patients who were treated with SRS and imaged with PWI before and 1 week later. Relative cerebral blood volume (rCBV) parameter maps were calculated by normalizing to the mean value of the contralateral white matter on PWI. Cox regression was conducted to explore factors associated with time to LR, with Bonferroni adjusted p<0.0006 for multiple testing correction. LR rates were estimated with the Kaplan-Meier method and compared using the log-rank test.

Results

Twenty-three patients were enrolled from 2013 through 2016, with 22 evaluable lesions from 16 patients. After a median follow-up of 13.1 months (range: 3.0–53.7), 5 lesions (21%) developed LR after a median of 3.4 months (range: 2.3–5.7). On univariable analysis, larger tumor volume (HR 1.48, 95% CI 1.02–2.15, p = 0.04), lower SRS dose (HR 0.45, 95% CI 0.21–0.97, p = 0.04), and higher rCBV at week 1 (HR 1.07, 95% CI 1.003–1.14, p = 0.04) had borderline association with shorter time to LR. Tumors >2.0cm³ had significantly higher LR than if ≤2.0cm³: 54% vs 0% at 1 year, respectively, p = 0.008. A future study to confirm the association of early PWI and LR of the high-risk cohort of lesions >2.0cm³ is estimated to require 258 patients.

Conclusions

PWI at week 1 after SRS may have borderline association with LR. Tumors <2.0cm³ have low risk of LR after SRS and may be low-yield for predictive biomarker studies. Information regarding sample size and potential challenges for future imaging biomarker studies may be gleaned from this pilot study.

[99mTc]-Bis-Methionine-DTPA Single-Photon Emission Computed Tomography Impacting Glioma Management: A Sensitive Indicator for Postsurgical/Chemoradiotherapy Response Assessment

Background: The present study evaluated the prognostic value of [^99mTc]MDM (bis-methionine-DTPA) follow-up single-photon emission computed tomography (SPECT) imaging for response assessment to chemoradiotherapy in glioma postoperatively. Materials and Methods: One hundred fourteen glioma patients (80 M:34 F) were followed postoperatively by sequential [^99mTc]MDM SPECT, dynamic susceptibility contrast-enhanced (DSCE)-MRI, and magnetic resonance spectroscopy (MRS) at baseline, 6, 12, and 22.5 months postchemoradiotherapy. The quantitative imaging results and the clinical outcome were used for response assessment and for the final diagnosis. The quantitative parameter of [^99mTc]MDM SPECT were also used for survival analysis. Results: A significantly (p = 0.001) lower target to nontarget (T/NT) ratio was observed in responders than in nonresponders. The sensitivity and specificity of [^99mTc]MDM-SPECT for identifying tumor recurrence from radiation necrosis at a cutoff ratio of 1.90 were estimated at 97.9% and 92%. Whereas, the sensitivity and specificity of DSCE-MRI with the normalized cerebral blood volume (nCBV) cutoff of 3.32 for this differentiation was found to be 84.6% and 93.0%. MRS intensity ratios of Cho/NAA and Cho/Cr provided comparatively lower sensitivity of 81.0% and 85.3% and specificity of 73.0% and 73.7%. T/NT ratios correlated with nCBV (r = 0.775, p < 0.001) and to a moderate extent with Cho/NAA ratios (r = 0.467, p = 0.001). [^99mTc]MDM SPECT and DSCE-MRI provided comparable results for predicting response assessment to chemoradiotherapy. There was a final diagnosis in 72 patients, of which 47 cases were tumor recurrence and 25 were radiation necrosis. The Kaplan-Meier analysis indicated that patients with T/NT ratio <1.9 showed prolonged survival (53.8 months) as compared (37.2 months) with those who demonstrated T/NT ratio >1.9 (p = 0.0001). Conclusion: Thus, this low-cost SPECT technique in combination with DSCE-MRI can be used accurately for mapping the disease activity, response assessment, and survival in glioma. [^99mTc]MDM SPECT and DSCE-MRI had the same diagnostic efficacy to detect recurrent/residual tumor and radiation necrosis while MRS was inferior to both the techniques.

BRAINSTORM: A Multi-Institutional Phase 1/2 Study of RRx-001 in Combination With Whole Brain Radiation Therapy for Patients With Brain Metastases

PURPOSE

To determine the recommended phase 2 dose of RRx-001, a radiosensitizer with vascular normalizing properties, when used with whole-brain radiation therapy (WBRT) for brain metastases and to assess whether quantitative changes in perfusion magnetic resonance imaging (MRI) after RRx-001 correlate with response.

METHODS AND MATERIALS

Five centers participated in this phase 1/2 trial of RRx-001 given once pre-WBRT and then twice weekly during WBRT. Four dose levels were planned (5 mg/m², 8.4 mg/m², 16.5 mg/m², 27.5 mg/m²). Dose escalation was managed by the time-to-event continual reassessment method algorithm. Linear mixed models were used to correlate change in 24-hour T1, Ktrans (capillary permeability), and fractional plasma volume with change in tumor volume.

RESULTS

Between 2015 and 2017, 31 patients were enrolled. Two patients dropped out before any therapy. Median age was 60 years (range, 30-76), and 12 were male. The most common tumor types were melanoma (59%) and non-small cell lung cancer (18%). No dose limiting toxicities were observed. The most common severe adverse event was grade 3 asthenia (6.9%, 2 of 29). The median intracranial response rate was 46% (95% confidence interval, 24-68) and median overall survival was 5.2 months (95% confidence interval, 4.5-9.4). No neurologic deaths occurred. Among 10 patients undergoing dynamic contrast-enhanced MRI, a reduction in Vp 24 hours after RRx-001 was associated with reduced tumor volume at 1 and 4 months (P ≤ .01).

CONCLUSIONS

The addition of RRx-001 to WBRT is well tolerated with favorable intracranial response rates. Because activity was observed across all dose levels, the recommended phase 2 dose is 10 mg twice weekly. A reduction in fractional plasma volume on dynamic contrast-enhanced MRI 24 hours after RRx-001 suggests antiangiogenic activity associated with longer-term tumor response.

Developing a Pipeline for Multiparametric MRI-Guided Radiation Therapy: Initial Results from a Phase II Clinical Trial in Newly Diagnosed Glioblastoma

Quantitative mapping of hyperperfused and hypercellular regions of glioblastoma has been proposed to improve definition of tumor regions at risk for local recurrence following conventional radiation therapy. As the processing of the multiparametric dynamic contrast-enhanced (DCE-) and diffusion-weighted (DW-) magnetic resonance imaging (MRI) data for delineation of these subvolumes requires additional steps that go beyond the standard practices of target definition, we sought to devise a workflow to support the timely planning and treatment of patients. A phase II study implementing a multiparametric imaging biomarker for tumor hyperperfusion and hypercellularity consisting of DCE-MRI and high b-value DW-MRI to guide intensified (75 Gy/30 fractions) radiation therapy (RT) in patients with newly diagnosed glioblastoma was launched. In this report, the workflow and the initial imaging outcomes of the first 12 patients are described. Among all the first 12 patients, treatment was initiated within 6 weeks of surgery and within 2 weeks of simulation. On average, the combined hypercellular volume and high cerebral blood volume/tumor perfusion volume were 1.8 times smaller than the T1 gadolinium abnormality and 10 times smaller than the FLAIR abnormality. Hypercellular volume and high cerebral blood volume/tumor perfusion volume each identified largely distinct regions and showed 57% overlap with the enhancing abnormality, and minimal-to-no extension outside of the FLAIR. These results show the feasibility of implementing a workflow for multiparametric magnetic resonance-guided radiation therapy into clinical trials with a coordinated multidisciplinary team, and the unique and complementary tumor subregions identified by the combination of high b-value DW-MRI and DCE-MRI.

Metabolic Tumor Volume Response Assessment Using (11)C-Methionine Positron Emission Tomography Identifies Glioblastoma Tumor Subregions That Predict Progression Better Than Baseline or Anatomic Magnetic Resonance Imaging Alone

Purpose

To evaluate whether response assessment of newly diagnosed glioblastoma at 3 months using ¹¹C-methionine-positron emission tomography (MET-PET) is better associated with patient outcome compared with baseline MET-PET or anatomic magnetic resonance imaging alone.

Methods and Materials

Patients included were participants in a phase I/II trial of dose-escalated chemoradiation based on anatomic magnetic resonance imaging. Automated segmentation of metabolic tumor volume (MTV) was performed at a threshold of 1.5 times mean cerebellar uptake. Progression-free (PFS) and overall survival were estimated with the Kaplan-Meier method and compared with log-rank tests. Multivariate analysis for PFS and overall survival was performed using Cox proportional hazards, and spatial overlap between imaging and recurrence volumes were analyzed.

Results

Among 37 patients, 15 had gross total resection, of whom 10 (67%) had residual MTV, 16 subtotal resection, and 6 biopsy alone. Median radiation therapy dose was 75 Gy (range, 66-81). Median baseline T1 Gd-enhanced tumor volume (GTV-Gd) was 38.0 cm³ (range, 8.0-81.5). Median pre-CRT MTV was 4.9 cm³ (range, 0-43.8). Among 25 patients with 3-month MET-PET, MTV was only 2.4 cm³ (range, 0.004-18.0) in patients with uptake. Patients with MTV = 0 cm³ at 3 months had superior PFS (18.2 vs 10.1 months, P = .03). On multivariate analysis, larger 3-month MTV (hazard ratio [HR] 2.4, 95% confidence interval [CI], 1.4-4.3, P = .03), persistent MET-PET subvolume (overlap of pre-CRT and 3 month MTV; HR 2.0, 95% CI, 1.2-3.4, P = .06), and increase in MTV (HR 1.8, 95% CI, 1.1-3.1, P = .09) were the only imaging factors significant for worse PFS. GTV-Gd at recurrence encompassed 97% of the persistent MET-PET subvolume (interquartile range 72%-100%), versus 71% (interquartile range 39%-93%) of baseline MTV, 54% of baseline GTV-Gd (18%-87%), and 78% of 3-month MTV (47%-95%).

Conclusions

The majority of patients with apparent gross total resection of glioblastoma have measurable postoperative MTV. Total and persisting MTV 3 months post-CRT were significant predictors of PFS, and persistent MET-PET subvolume was the strongest predictor for localizing tumor recurrence.

Emerging Functional Imaging Biomarkers of Tumour Responses to Radiotherapy

Tumour responses to radiotherapy are currently primarily assessed by changes in size. Imaging permits non-invasive, whole-body assessment of tumour burden and guides treatment options for most tumours. However, in most tumours, changes in size are slow to manifest and can sometimes be difficult to interpret or misleading, potentially leading to prolonged durations of ineffective treatment and delays in changing therapy. Functional imaging techniques that monitor biological processes have the potential to detect tumour responses to treatment earlier and refine treatment options based on tumour biology rather than solely on size and staging. By considering the biological effects of radiotherapy, this review focusses on emerging functional imaging techniques with the potential to augment morphological imaging and serve as biomarkers of early response to radiotherapy.

The Role of Standard and Advanced Imaging for the Management of Brain Malignancies From a Radiation Oncology Standpoint

Radiation therapy (RT) plays a critical role in the overall management of many central nervous system (CNS) tumors. Advances in RT treatment planning, with techniques such as intensity modulated radiation therapy, volumetric modulated arc therapy, and stereotactic radiosurgery, now allow the delivery of highly conformal dose with great precision. These techniques rely on high-resolution 3-dimensional anatomical imaging modalities such as computed tomography or magnetic resonance imaging (MRI) scans to accurately and reliably define CNS targets and normal tissue avoidance structures. The integration of cross-sectional imaging into radiation oncology has directly translated into improvements in the therapeutic window of RT, and the union between radiation oncology and imaging is only expected to grow stronger. In addition, advanced imaging modalities including diffusion, perfusion, and spectroscopic MRIs as well as positron emission tomography (PET) scans with novel tracers are being utilized to provide additional insight into tumor biology and behavior beyond anatomy. Together, these standard and advanced imaging modalities hold significant potential to improve future RT delivery and response assessment. In this review, we will discuss the current utilization of standard/advanced imaging for CNS tumors from a radiation oncology perspective as well as the implications of novel MRI and PET modalities currently under investigation.

Stereotactic Radiosurgery and Hypofractionated Radiotherapy for Glioblastoma

Glioblastoma is the most common primary brain tumor in adults. Standard therapy depends on patient age and performance status but principally involves surgical resection followed by a 6-wk course of radiation therapy given concurrently with temozolomide chemotherapy. Despite such treatment, prognosis remains poor, with a median survival of 16 mo. Challenges in achieving local control, maintaining quality of life, and limiting toxicity plague treatment strategies for this disease. Radiotherapy dose intensification through hypofractionation and stereotactic radiosurgery is a promising strategy that has been explored to meet these challenges. We review the use of hypofractionated radiotherapy and stereotactic radiosurgery for patients with newly diagnosed and recurrent glioblastoma.

Radiomics in Brain Tumor: Image Assessment, Quantitative Feature Descriptors, and Machine-Learning Approaches

Radiomics describes a broad set of computational methods that extract quantitative features from radiographic images. The resulting features can be used to inform imaging diagnosis, prognosis, and therapy response in oncology. However, major challenges remain for methodologic developments to optimize feature extraction and provide rapid information flow in clinical settings. Equally important, to be clinically useful, predictive radiomic properties must be clearly linked to meaningful biologic characteristics and qualitative imaging properties familiar to radiologists. Here we use a cross-disciplinary approach to highlight studies in radiomics. We review brain tumor radiologic studies (eg, imaging interpretation) through computational models (eg, computer vision and machine learning) that provide novel clinical insights. We outline current quantitative image feature extraction and prediction strategies with different levels of available clinical classes for supporting clinical decision-making. We further discuss machine-learning challenges and data opportunities to advance radiomic studies.

Tumor image signatures and habitats: a processing pipeline of multimodality metabolic and physiological images

To create tumor "habitats" from the "signatures" discovered from multimodality metabolic and physiological images, we developed a framework of a processing pipeline. The processing pipeline consists of six major steps: (1) creating superpixels as a spatial unit in a tumor volume; (2) forming a data matrix [Formula: see text] containing all multimodality image parameters at superpixels; (3) forming and clustering a covariance or correlation matrix [Formula: see text] of the image parameters to discover major image "signatures;" (4) clustering the superpixels and organizing the parameter order of the [Formula: see text] matrix according to the one found in step 3; (5) creating "habitats" in the image space from the superpixels associated with the "signatures;" and (6) pooling and clustering a matrix consisting of correlation coefficients of each pair of image parameters from all patients to discover subgroup patterns of the tumors. The pipeline was applied to a dataset of multimodality images in glioblastoma (GBM) first, which consisted of 10 image parameters. Three major image "signatures" were identified. The three major "habitats" plus their overlaps were created. To test generalizability of the processing pipeline, a second image dataset from GBM, acquired on the scanners different from the first one, was processed. Also, to demonstrate the clinical association of image-defined "signatures" and "habitats," the patterns of recurrence of the patients were analyzed together with image parameters acquired prechemoradiation therapy. An association of the recurrence patterns with image-defined "signatures" and "habitats" was revealed. These image-defined "signatures" and "habitats" can be used to guide stereotactic tissue biopsy for genetic and mutation status analysis and to analyze for prediction of treatment outcomes, e.g., patterns of failure.

Response Assessment in Neuro-Oncology criteria, contrast enhancement and perfusion MRI for assessing progression in glioblastoma

PURPOSE

The purpose of the study was to evaluate Response Assessment in Neuro-Oncology (RANO) criteria in glioblastoma multiforme (GBM), with respect to the Macdonald criteria and changes in contrast-enhancement (CE) volume. Related variations in relative cerebral blood volume (rCBV) were investigated.

METHODS

Forty-three patients diagnosed between 2006 and 2010 were included. All underwent surgical resection, followed by temozolomide-based chemoradiation. MR images were retrospectively reviewed. Times to progression (TTPs) according to RANO criteria, Macdonald criteria and increased CE volume (CE-3D) were compared, and the percentage change in the 75th percentile of rCBV (rCBV75) was evaluated.

RESULTS

After a median follow-up of 22.7 months, a total of 39 patients had progressed according to RANO criteria, 32 according to CE-3D, and 42 according to Macdonald. Median TTPs were 6.4, 9.3, and 6.6 months, respectively. Overall agreement was 79.07% between RANO and CE-3D and 93.02% between RANO and Macdonald. The mean percentage change in rCBV75 at RANO progression onset was over 73% in 87.5% of patients.

CONCLUSIONS

In conclusion, our findings suggest that CE-3D criterion is not yet suitable to assess progression in routine clinical practice. Indeed, the accurate threshold is still not well defined. To date, in our opinion, early detection of disease progression by RANO combined with advanced MRI imaging techniques like MRI perfusion and diffusion remains the best way to assess disease progression. Further investigations that would examine the impact of treatment modifications after progression determined by different criteria on overall survival would be of great value.

MR-guided radiation therapy: transformative technology and its role in the central nervous system

This review article describes advancement of magnetic resonance imaging technologies in radiation therapy planning, guidance, and adaptation of brain tumors. The potential for MR-guided radiation therapy to improve outcomes and the challenges in its adoption are discussed.

Posttreatment DSC-MRI is Predictive of Early Treatment Failure in Children with Supratentorial High-Grade Glioma Treated with Erlotinib

BACKGROUND AND PURPOSE

The role of perfusion imaging in the management of pediatric high grade glioma is unclear. We evaluated the ability of dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) to determine grade, evaluate post-treatment response and predict treatment failure.

MATERIAL AND METHODS

In this study 22 patients with high-grade glioma underwent biopsy and were treated with concurrent and sequential radiotherapy and erlotinib as part of a phase I/II clinical trial (NCT00124657). Preradiotherapy, immediate postradiotherapy, 6‑month and treatment failure DSC MR images were reviewed, registered, and processed for the ratio of cerebral blood flow (CBF) and cerebral blood volume (CBV). Processed, derived perfusion, and T1-weighted images (T1WI), T2WI, and fluid attenuation inversion recovery (FLAIR) MRI sequences were used for segmentation and extraction of tumor perfusion parameters at all time points. Patient, tumor, treatment, and outcome data were summarized and related to perfusion data.

RESULTS

Regional CBF in tumors increased from diagnosis to postradiotherapy, while they decreased to levels below those at diagnosis from postradiotherapy to 6‑month follow-up. At 6 months, the median regional CBF was higher in tumors that progressed (median 1.16) than in those that did not (median, 0.95; P < 0.05). Patients with regional CBF ratios above 1.4 at diagnosis had shorter survival times than did those with regional CBF ratios below 1.4 (P = 0.77). Tumors with a regional CBV above 1.15 at the postradiotherapy (1-3 months) follow-up scan were associated with an earlier time to death than that of tumors with a regional CBV below 1.15 (P < 0.05).

CONCLUSION

Posttreatment perfusion characteristics are prognostic and may help predict survival. Overall, perfusion MRI is useful for managing pediatric high-grade glioma and should be incorporated into future clinical trials.

Dynamic Susceptibility Contrast MR Imaging in Glioma: Review of Current Clinical Practice

Dynamic susceptibility contrast (DSC) MR imaging, a perfusion-weighted MR imaging technique typically used in neuro-oncologic applications for estimating the relative cerebral blood volume within brain tumors, has demonstrated much potential for determining prognosis, predicting therapeutic response, and assessing early treatment response of gliomas. This review highlights recent developments using DSC-MR imaging and emphasizes the need for technical standardization and validation in prospective studies in order for this technique to become incorporated into standard-of-care imaging for patients with brain tumors.

Quantitative correlational study of microbubble-enhanced ultrasound imaging and magnetic resonance imaging of glioma and early response to radiotherapy in a rat model

PURPOSE

Radiotherapy remains a major treatment method for malignant tumors. Magnetic resonance imaging (MRI) is the standard modality for assessing glioma treatment response in the clinic. Compared to MRI, ultrasound imaging is low-cost and portable and can be used during intraoperative procedures. The purpose of this study was to quantitatively compare contrast-enhanced ultrasound (CEUS) imaging and MRI of irradiated gliomas in rats and to determine which quantitative ultrasound imaging parameters can be used for the assessment of early response to radiation in glioma.

METHODS

Thirteen nude rats with U87 glioma were used. A small thinned skull window preparation was performed to facilitate ultrasound imaging and mimic intraoperative procedures. Both CEUS and MRI with structural, functional, and molecular imaging parameters were performed at preradiation and at 1 day and 4 days postradiation. Statistical analysis was performed to determine the correlations between MRI and CEUS parameters and the changes between pre- and postradiation imaging.

RESULTS

Area under the curve (AUC) in CEUS showed significant difference between preradiation and 4 days postradiation, along with four MRI parameters, T2, apparent diffusion coefficient, cerebral blood flow, and amide proton transfer-weighted (APTw) (all p < 0.05). The APTw signal was correlated with three CEUS parameters, rise time (r = - 0.527, p < 0.05), time to peak (r = - 0.501, p < 0.05), and perfusion index (r = 458, p < 0.05). Cerebral blood flow was correlated with rise time (r = - 0.589, p < 0.01) and time to peak (r = - 0.543, p < 0.05).

CONCLUSIONS

MRI can be used for the assessment of radiotherapy treatment response and CEUS with AUC as a new technique and can also be one of the assessment methods for early response to radiation in glioma.

Mitotic Activity in Glioblastoma Correlates with Estimated Extravascular Extracellular Space Derived from Dynamic Contrast-Enhanced MR Imaging

BACKGROUND AND PURPOSE

A number of parameters derived from dynamic contrast-enhanced MR imaging and separate histologic features have been identified as potential prognosticators in high-grade glioma. This study evaluated the relationships between dynamic contrast-enhanced MRI-derived parameters and histologic features in glioblastoma multiforme.

MATERIALS AND METHODS

Twenty-eight patients with newly presenting glioblastoma multiforme underwent preoperative imaging (conventional imaging and T1 dynamic contrast-enhanced MRI). Parametric maps of the initial area under the contrast agent concentration curve, contrast transfer coefficient, estimate of volume of the extravascular extracellular space, and estimate of blood plasma volume were generated, and the enhancing fraction was calculated. Surgical specimens were used to assess subtype and were graded (World Health Organization classification system) and were assessed for necrosis, cell density, cellular atypia, mitotic activity, and overall vascularity scores. Quantitative assessment of endothelial surface area, vascular surface area, and a vascular profile count were made by using CD34 immunostaining. The relationships between MR imaging parameters and histopathologic features were examined.

RESULTS

High values of contrast transfer coefficient were associated with the presence of frank necrosis (P = .005). High values of the estimate of volume of the extravascular extracellular space were associated with a fibrillary histologic pattern (P < .01) and with increased mitotic activity (P < .05). No relationship was found between mitotic activity and histologic pattern, suggesting that the correlation between the estimate of volume of the extravascular extracellular space and mitotic activity was independent of the histologic pattern.

CONCLUSIONS

A correlation between the estimate of volume of the extravascular extracellular space and mitotic activity is reported. Further work is warranted to establish how dynamic contrast-enhanced MRI parameters relate to more quantitative histologic measurements, including markers of proliferation and measures of vascular endothelial growth factor expression.

Identification of a candidate biomarker from perfusion MRI to anticipate glioblastoma progression after chemoradiation

OBJECTIVE

To identify relevant relative cerebral blood volume biomarkers from T2* dynamic-susceptibility contrast magnetic resonance imaging to anticipate glioblastoma progression after chemoradiation.

METHODS

Twenty-five patients from a prospective study with glioblastoma, primarily treated by chemoradiation, were included. According to the last follow-up MRI confirmed status, patients were divided into: relapse group (n = 13) and control group (n = 12). The time of last MR acquisition was t_end; MR acquisitions performed at t_end-2M, t_end-4M and t_end-6M (respectively 2, 4 and 6 months before t_end) were analyzed to extract relevant variations among eleven perfusion biomarkers (B). These variations were assessed through R(B), as the absolute value of the ratio between ∆B from t_end-4M to t_end-2M and ∆B from t_end-6M to t_end-4M. The optimal cut-off for R(B) was determined using receiver-operating-characteristic curve analysis.

RESULTS

The fraction of hypoperfused tumor volume (F_hP_g) was a relevant biomarker. A ratio R(F_hP_g) ≥ 0.61 would have been able to anticipate relapse at the next follow-up with a sensitivity/specificity/accuracy of 92.3 %/63.6 %/79.2 %. High R(F_hPg) (≥0.61) was associated with more relapse at t_end compared to low R(F_hPg) (75 % vs 12.5 %, p = 0.008).

CONCLUSION

Iterative analysis of F_hP_g from consecutive examinations could provide surrogate markers to predict progression at the next follow-up.

KEY POINTS

• Related rCBV biomarkers from DSC were assessed to anticipate GBM progression. • Biomarkers were assessed through their patterns of variation during the follow-up. • The fraction of hypoperfused tumour volume (F_hP _g ) seemed to be a relevant biomarker. • An innovative ratio R(F_hP _g ) could be an early surrogate marker of relapse. • A significant time gain could be achieved in the management of GBM patients.

Pre-Operative Perfusion Skewness and Kurtosis Are Potential Predictors of Progression-Free Survival after Partial Resection of Newly Diagnosed Glioblastoma

Objective

To determine whether pre-operative perfusion skewness and kurtosis derived from normalized cerebral blood volume (nCBV) histograms are associated with progression-free survival (PFS) of patients after partial resection of newly diagnosed glioblastoma.

Materials and Methods

A total of 135 glioblastoma patients who had undergone partial resection of tumor (resection of < 50% of pre-operative tumor volume or surgical biopsy) confirmed with immediate postsurgical MRI and examined with both conventional MRI and dynamic susceptibility contrast (DSC) perfusion MRI before the surgery were retrospectively reviewed in this study. They had been followed up post-surgical chemoradiotherapy for tumor progression. Using histogram analyses of nCBV derived from pre-operative DSC perfusion MRI, patients were sub-classified into the following four groups: positive skewness and leptokurtosis (group 1); positive skewness and platykurtosis (group 2); negative skewness and leptokurtosis (group 3); negative skewness and platykurtosis (group 4). Kaplan-Meier analysis and multivariable Cox proportional hazards regression analysis were performed to determine whether clinical and imaging covariates were associated with PFS or overall survival (OS) of these patients.

Results

According to the Kaplan-Meier method, median PFS of group 1, 2, 3, and 4 was 62, 51, 39, and 41 weeks, respectively, with median OS of 82, 77, 77, and 72 weeks, respectively. In multivariable analyses with Cox proportional hazards regression, pre-operative skewness/kurtosis pattern (hazard ratio: 2.98 to 4.64; p < 0.001), Karnofsky performance scale score (hazard ratio: 1.04; p = 0.003), and post-operative tumor volume (hazard ratio: 1.04; p = 0.02) were independently associated with PFS but not with OS.

Conclusion

Higher skewness and kurtosis of nCBV histogram before surgery were associated with longer PFS in patients with newly diagnosed glioblastoma after partial tumor resection.

Treating recurrent glioblastoma: an update

Glioblastoma, the most aggressive of the gliomas, has a high recurrence and mortality rate. The nature of this poor prognosis resides in the molecular heterogeneity and phenotypic features of this tumor. Despite research advances in understanding the molecular biology, it has been difficult to translate this knowledge into effective treatment. Nearly all will have tumor recurrence, yet to date very few therapies have established efficacy as salvage regimens. This challenge is further complicated by imaging confounders and to an even greater degree by the ever increasing molecular heterogeneity that is thought to be both sporadic and treatment-induced. The development of novel clinical trial designs to support the development and testing of novel treatment regimens and drug delivery strategies underscore the need for more precise techniques in imaging and better surrogate markers to help determine treatment response. This review summarizes recent approaches to treat patients with recurrent glioblastoma and considers future perspectives.

Physiologic MRI for assessment of response to therapy and prognosis in glioblastoma

Aside from bidimensional measurements from conventional contrast-enhanced MRI, there are no validated or FDA-qualified imaging biomarkers for high-grade gliomas. However, advanced functional MRI techniques, including perfusion- and diffusion-weighted MRI, have demonstrated much potential for determining prognosis, predicting therapeutic response, and assessing early treatment response. They may also prove useful for differentiating pseudoprogression from true progression after temozolomide chemoradiation and pseudoresponse from true response after anti-angiogenic therapy. This review will highlight recent developments using these techniques and emphasize the need for technical standardization and validation in prospective studies in order for these methods to become incorporated into standard-of-care imaging for brain tumor patients.

Development of a Multiparametric Voxel-Based Magnetic Resonance Imaging Biomarker for Early Cancer Therapeutic Response Assessment

Quantitative magnetic resonance imaging (MRI)-based biomarkers, which capture physiological and functional tumor processes, were evaluated as imaging surrogates of early tumor response following chemoradiotherapy in glioma patients. A multiparametric extension of a voxel-based analysis, referred as the parametric response map (PRM), was applied to quantitative MRI maps to test the predictive potential of this metric for detecting response. Fifty-six subjects with newly diagnosed high-grade gliomas treated with radiation and concurrent temozolomide were enrolled in a single-site prospective institutional review board-approved MRI study. Apparent diffusion coefficient (ADC) and relative cerebral blood volume (rCBV) maps were acquired before therapy and 3 weeks after therapy was initiated. Multiparametric PRM (mPRM) was applied to both physiological MRI maps and evaluated as an imaging biomarker of patient survival. For comparison, single-biomarker PRMs were also evaluated in this study. The simultaneous analysis of ADC and rCBV by the mPRM approach was found to improve the predictive potential for patient survival over single PRM measures. With an array of quantitative imaging parameters being evaluated as biomarkers of therapeutic response, mPRM shows promise as a new methodology for consolidating physiologically distinct imaging parameters into a single interpretable and quantitative metric.

Early changes in perfusion of glioblastoma during radio- and chemotherapy evaluated by T1-dynamic contrast enhanced magnetic resonance imaging

BACKGROUND

The survival times of patients with glioblastoma differ widely and biomarkers that would enable individualized treatment are needed. The objective of this study was to measure changes in the vascular physiology of tumor using T1-dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) in patients with glioblastoma during early stages of radio- and chemotherapy (Tx) and explore possible correlations with treatment outcomes.

MATERIAL AND METHODS

An exploratory prospective study was planned. Patients underwent DCE-MRI at baseline, after approximately one and six weeks of Tx and three and six months post-Tx. DCE-MRI at three Tesla generated maps of blood flow (BF), blood volume (BV), permeability (Ki) and volume of distribution (Vd) using a combination of model-free deconvolution and Patlak plots. Regions of interest in contrast enhancing tumor and in normal appearing white matter were contoured. Progression-free survival (PFS) was the primary clinical outcome. Patients with PFS > 6 months were compared with those with PFS < 6 months. Parameters of vascular physiology and changes in these during Tx were compared for these two groups at all time points using non-parametric statistics.

RESULTS

Eleven eligible patients were included and 46 DCE-MRI examinations were carried out. BF in tumor increased for all patients early during Tx (p = 0.005) and then fell to a level below baseline at post-Tx examinations (p = 0.016). A similar but non-significant trend was seen for tumor BV. There was no detectable difference between patients with PFS > 6 months versus PFS < 6 months with regards to baseline values or changes during and after Tx.

CONCLUSIONS

Although no correlations to outcomes were found, the results of this exploratory study may be hypothesis generating and will be examined in a larger patient group.

Emerging techniques and technologies in brain tumor imaging

The purpose of this report is to describe the state of imaging techniques and technologies for detecting response of brain tumors to treatment in the setting of multicenter clinical trials. Within currently used technologies, implementation of standardized image acquisition and the use of volumetric estimates and subtraction maps are likely to help to improve tumor visualization, delineation, and quantification. Upon further development, refinement, and standardization, imaging technologies such as diffusion and perfusion MRI and amino acid PET may contribute to the detection of tumor response to treatment, particularly in specific treatment settings. Over the next few years, new technologies such as 2(3)Na MRI and CEST imaging technologies will be explored for their use in expanding the ability to quantitatively image tumor response to therapies in a clinical trial setting.

Automatic brain tumour detection and neovasculature assessment with multiseries MRI analysis

In this paper a novel multi-stage automatic method for brain tumour detection and neovasculature assessment is presented. First, the brain symmetry is exploited to register the magnetic resonance (MR) series analysed. Then, the intracranial structures are found and the region of interest (ROI) is constrained within them to tumour and peritumoural areas using the Fluid Light Attenuation Inversion Recovery (FLAIR) series. Next, the contrast-enhanced lesions are detected on the basis of T1-weighted (T1W) differential images before and after contrast medium administration. Finally, their vascularisation is assessed based on the Regional Cerebral Blood Volume (RCBV) perfusion maps. The relative RCBV (rRCBV) map is calculated in relation to a healthy white matter, also found automatically, and visualised on the analysed series. Three main types of brain tumours, i.e. HG gliomas, metastases and meningiomas have been subjected to the analysis. The results of contrast enhanced lesions detection have been compared with manual delineations performed independently by two experts, yielding 64.84% sensitivity, 99.89% specificity and 71.83% Dice Similarity Coefficient (DSC) for twenty analysed studies of subjects with brain tumours diagnosed.

Pixel-by-Pixel Comparison of Volume Transfer Constant and Estimates of Cerebral Blood Volume from Dynamic Contrast-Enhanced and Dynamic Susceptibility Contrast-Enhanced MR Imaging in High-Grade Gliomas

BACKGROUND AND PURPOSE

Estimates of blood volume and volume transfer constant are parameters commonly used to characterize hemodynamic properties of brain lesions. The purposes of this study were to compare values of volume transfer constant and estimates of blood volume in high-grade gliomas on a pixel-by-pixel basis to comprehend whether they provide different information and to compare estimates of blood volume obtained by dynamic contrast-enhanced MR imaging and dynamic susceptibility contrast-enhanced MR imaging.

MATERIALS AND METHODS

Thirty-two patients with biopsy-proved grade IV gliomas underwent dynamic contrast-enhanced MR imaging and dynamic susceptibility contrast-enhanced MR imaging, and parametric maps of volume transfer constant, plasma volume, and CBV maps were calculated. The Spearman rank correlation coefficients among matching values of CBV, volume transfer constant, and plasma volume were calculated on a pixel-by-pixel basis. Comparison of median values of normalized CBV and plasma volume was performed.

RESULTS

Weak-but-significant correlation (P < .001) was noted for all comparisons. Spearman rank correlation coefficients were as follows: volume transfer constant versus CBV, ρ = 0.113; volume transfer constant versus plasma volume, ρ = 0.256; CBV versus plasma volume, ρ = 0.382. We found a statistically significant difference (P < .001) for the estimates of blood volume obtained by using dynamic contrast-enhanced MR imaging (mean normalized plasma volume, 13.89 ± 11.25) and dynamic susceptibility contrast-enhanced MR imaging (mean normalized CBV, 4.37 ± 4.04).

CONCLUSIONS

The finding of a very weak correlation between estimates of microvascular density and volume transfer constant suggests that they provide different information. Estimates of blood volume obtained by using dynamic contrast-enhanced MR imaging are significantly higher than those obtained by dynamic susceptibility contrast-enhanced MR imaging in human gliomas, most likely due to the effect of contrast leakage.

Early Cerebral Blood Volume Changes Predict Progression After Convection-Enhanced Delivery of Topotecan for Recurrent Malignant Glioma

OBJECTIVE

To assess whether early changes in enhancing tumor volume (eTV) and relative cerebral blood volume (rCBV) 1 month after convection-enhanced delivery of topotecan in patients with recurrent malignant glioma correlated with 6-month disease progression status.

METHODS

Sixteen patients were enrolled in a Phase Ib trial of convection-enhanced delivery of topotecan for recurrent malignant glioma. Each patient was evaluated with serial follow-up magnetic resonance imaging at baseline and at 4- to 8-week intervals. Changes at 1 month compared with baseline in eTV and rCBV were evaluated as potential predictors of 6-month progression status, classified as either progressive disease or nonprogressive disease. Relationships between percent changes in eTV and rCBV at 1 month with the probability of progressive disease at 6 months were estimated by the use of logistic regression analysis. Receiver operating characteristic curves for varying percent change thresholds in eTV and rCBV were evaluated by the use of 6-month progressive disease as the reference.

RESULTS

There was a significant difference in the percent change in rCBV at 1 month in patients with progressive disease compared with those with nonprogressive disease at 6 months (+12% vs. -29%, P = 0.02). Logistic regression analysis demonstrated on average that a 10% increase in rCBV at 1 month after convection-enhanced delivery of topotecan was associated with 1.7 times the odds of developing progressive disease at 6 months (95% confidence interval [CI] 1.0-2.9 P = 0.05). Receiver operating characteristic analysis for determining progressive disease at 6 months showed a greater area under the curve with rCBV (0.867; 95% CI 0.66-1.00) than with change in enhancing tumor volume (0.767; 95% CI 0.51-1.00).

CONCLUSION

In this selected population of patients with recurrent malignant glioma treated with convection-enhanced delivery of topotecan, early changes in rCBV at 4 weeks after therapy may help predict progression status at 6 months.

Multimodality functional imaging in radiation therapy planning: relationships between dynamic contrast-enhanced MRI, diffusion-weighted MRI, and 18F-FDG PET

OBJECTIVES

Biologically guided radiotherapy needs an understanding of how different functional imaging techniques interact and link together. We analyse three functional imaging techniques that can be useful tools for achieving this objective.

MATERIALS AND METHODS

The three different imaging modalities from one selected patient are ADC maps, DCE-MRI, and 18F-FDG PET/CT, because they are widely used and give a great amount of complementary information. We show the relationship between these three datasets and evaluate them as markers for tumour response or hypoxia marker. Thus, vascularization measured using DCE-MRI parameters can determine tumour hypoxia, and ADC maps can be used for evaluating tumour response.

RESULTS

ADC and DCE-MRI include information from 18F-FDG, as glucose metabolism is associated with hypoxia and tumour cell density, although 18F-FDG includes more information about the malignancy of the tumour. The main disadvantage of ADC maps is the distortion, and we used only low distorted regions, and extracellular volume calculated from DCE-MRI can be considered equivalent to ADC in well-vascularized areas.

CONCLUSION

A dataset for achieving the biologically guided radiotherapy must include a tumour density study and a hypoxia marker. This information can be achieved using only MRI data or only PET/CT studies or mixing both datasets.