Assessment and prediction of glioblastoma therapy response: challenges and opportunities.

Glioblastoma is the most aggressive type of primary adult brain tumour. The median survival of patients with glioblastoma remains approximately 15 months, and the 5-year survival rate is <10%. Current treatment options are limited, and the standard of care has remained relatively constant since 2011. Over the last decade, a range of different treatment regimens have been investigated with very limited success. Tumour recurrence is almost inevitable with the current treatment strategies, as glioblastoma tumours are highly heterogeneous and invasive. Additionally, another challenging issue facing patients with glioblastoma is how to distinguish between tumour progression and treatment effects, especially when relying on routine diagnostic imaging techniques in the clinic. The specificity of routine imaging for identifying tumour progression early or in a timely manner is poor due to the appearance similarity of post-treatment effects. Here, we concisely describe the current status and challenges in the assessment and early prediction of therapy response and the early detection of tumour progression or recurrence. We also summarize and discuss studies of advanced approaches such as quantitative imaging, liquid biomarker discovery and machine intelligence that hold exceptional potential to aid in the therapy monitoring of this malignancy and early prediction of therapy response, which may decisively transform the conventional detection methods in the era of precision medicine.

Imaging for Response Assessment in Cancer Clinical Trials.

The use of biomarkers is integral to the routine management of cancer patients, including diagnosis of disease, clinical staging and response to therapeutic intervention. Advanced imaging metrics with computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET) are used to assess response during new drug development and in cancer research for predictive metrics of response. Key components and challenges to identifying an appropriate imaging biomarker are selection of integral vs integrated biomarkers, choosing an appropriate endpoint and modality, and standardization of the imaging biomarkers for cooperative and multicenter trials. Imaging biomarkers lean on the original proposed quantified metrics derived from imaging such as tumor size or longest dimension, with the most commonly implemented metrics in clinical trials coming from the Response Evaluation Criteria in Solid Tumors (RECIST) criteria, and then adapted versions such as immune-RECIST (iRECIST) and Positron Emission Tomography Response Criteria in Solid Tumors (PERCIST) for immunotherapy response and PET imaging, respectively. There have been many widely adopted biomarkers in clinical trials derived from MRI including metrics that describe cellularity and vascularity from diffusion-weighted (DW)-MRI apparent diffusion coefficient (ADC) and Dynamic Susceptibility Contrast (DSC) or dynamic contrast enhanced (DCE)-MRI (Ktrans, relative cerebral blood volume (rCBV)), respectively. Furthermore, Fluorodexoyglucose (FDG), fluorothymidine (FLT), and fluoromisonidazole (FMISO)-PET imaging, which describe molecular markers of glucose metabolism, proliferation and hypoxia have been implemented into various cancer types to assess therapeutic response to a wide variety of targeted- and chemotherapies. Recently, there have been many functional and molecular novel imaging biomarkers that are being developed that are rapidly being integrated into clinical trials (with anticipation of being implemented into clinical workflow in the future), such as artificial intelligence (AI) and machine learning computational strategies, antibody and peptide specific molecular imaging, and advanced diffusion MRI. These include prostate-specific membrane antigen (PSMA) and trastuzumab-PET, vascular tumor burden extracted from contrast-enhanced CT, diffusion kurtosis imaging, and CD8 or Granzyme B PET imaging. Further excitement surrounds theranostic procedures such as the combination of 68Ga/111In- and 177Lu-DOTATATE to use integral biomarkers to direct care and personalize therapy. However, there are many challenges in the implementation of imaging biomarkers that remains, including understand the accuracy, repeatability and reproducibility of both acquisition and analysis of these imaging biomarkers. Despite the challenges associated with the biological and technical validation of novel imaging biomarkers, a distinct roadmap has been created that is being implemented into many clinical trials to advance the development and implementation to create specific and sensitive novel imaging biomarkers of therapeutic response to continue to transform medical oncology.

Systematic assessment of multi-echo dynamic susceptibility contrast MRI using a digital reference object.

PURPOSE: Brain tumor dynamic susceptibility contrast (DSC) MRI is adversely impacted by T1 and T2∗ contrast agent leakage effects that result in inaccurate hemodynamic metrics. While multi-echo acquisitions remove T1 leakage effects, there is no consensus on the optimal set of acquisition parameters. Using a computational approach, we systematically evaluated a wide range of acquisition strategies to determine the optimal multi-echo DSC-MRI perfusion protocol. METHODS: Using a population-based DSC-MRI digital reference object (DRO), we assessed the influence of preload dosing (no preload and full dose preload), field strength (1.5 and 3T), pulse sequence parameters (echo time, repetition time, and flip angle), and leakage correction on relative cerebral blood volume (rCBV) and flow (rCBF) accuracy. We also compared multi-echo DSC-MRI protocols with standard single-echo protocols. RESULTS: Multi-echo DSC-MRI is highly consistent across all protocols, and multi-echo rCBV (with or without use of a preload dose) had higher accuracy than single-echo rCBV. Regression analysis showed that choice of repetition time and flip angle had minimal impact on multi-echo rCBV and rCBV, indicating the potential for significant flexibility in acquisition parameters. The echo time combination had minimal impact on rCBV, though longer echo times should be avoided, particularly at higher field strengths. Leakage correction improved rCBV accuracy in all cases. Multi-echo rCBF was less biased than single-echo rCBF, although rCBF accuracy was reduced overall relative to rCBV. CONCLUSIONS: Multi-echo acquisitions were more robust than single-echo, essentially decoupling both repetition time and flip angle from rCBV accuracy. Multi-echo acquisitions obviate the need for preload dosing, although leakage correction to remove residual T2∗ leakage effects remains compulsory for high rCBV accuracy.

Assessment of renal fibrosis in murine diabetic nephropathy using quantitative magnetization transfer MRI.

PURPOSE: Renal fibrosis is a hallmark of progressive renal disease; however, current clinical tests are insufficient for assessing renal fibrosis. Here we evaluated the utility of quantitative magnetization transfer MRI in detecting renal fibrosis in a murine model of progressive diabetic nephropathy (DN). METHODS: The db/db eNOS-/- mice, a well-recognized model of progressive DN, and normal wild-type mice were imaged at 7T. The quantitative magnetization transfer data were collected in coronal plane using a 2D magnetization transfer prepared spoiled gradient echo sequence with a Gaussian-shaped presaturation pulse. Parameters were derived using a two-pool fitting model. A normal range of cortical pool size ratio (PSR) was defined as Mean±2SD of wild-type kidneys (N = 20). The cortical regions whose PSR values exceeded this threshold (threshold PSR) were assessed. The correlations between the PSR-based and histological (collagen IV or picrosirius red stain) fibrosis measurements were evaluated. RESULTS: Compared with wild-type mice, moderate increases in mean PSR values and scattered clusters of high PSR region were observed in cortex of DN mouse kidneys. Abnormally high PSR regions (% area) that were detected by the threshold PSR were significantly increased in renal cortexes of DN mice. These regions progressively increased on aging and highly correlated with histological fibrosis measures, while the mean PSR values correlated much less. CONCLUSION: Renal fibrosis in DN can be assessed by the quantitative magnetization transfer MRI and threshold analysis. This technique may be used as a novel imaging biomarker for DN and other renal diseases.

Assessment of a simplified spin and gradient echo (sSAGE) approach for human brain tumor perfusion imaging.

The goal of this study was to validate a simplified spin- and gradient-echo (sSAGE) approach to obtain T1-corrected dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) data in a clinical brain tumor population. A five-echo SAGE sequence was used to acquire DSC-MRI data (n=8 patients, 3 primary glioma, and 5 brain metastases). The ΔR2⁎ and ΔR2 time series obtained from a nonlinear fit of all echoes (SAGE) were compared to ΔR2⁎ and ΔR2 time series obtained analytically (sSAGE) using three echoes (two GEs and one SE). Through the use of multiple echoes, both methods removed T1 leakage effects from the ΔR2⁎ and ΔR2 time series, and the sSAGE ΔR2⁎ and ΔR2 time series were highly correlated with those from SAGE, with average correlations of 0.9. The resulting hemodynamic parameters included GE and SE cerebral blood volume (CBV), cerebral blood flow (CBF), mean vessel diameter (mVD), volume transfer constant (Ktrans), and volume fraction of the extravascular extracellular space (ve). For each metric, there was good correlation (>0.86) between sSAGE and SAGE, with no significant differences. The sSAGE method provides T1-corrected GE and SE DSC-MRI parameters in an efficient and clinically feasible manner.

Assessment of a combined spin- and gradient-echo (SAGE) DSC-MRI method for preclinical neuroimaging.

The goal of this study was to optimize and validate a combined spin- and gradient-echo (SAGE) sequence for dynamic susceptibility-contrast magnetic resonance imaging to obtain hemodynamic parameters in a preclinical setting. The SAGE EPI sequence was applied in phantoms and in vivo rat brain (normal, tumor, and stroke tissue). Partial and full Fourier encoding schemes were implemented and characterized. Maps of cerebral blood volume (CBV), cerebral blood flow (CBF), mean transit time (MTT), vessel size index (VSI), volume transfer constant (K(trans)), and volume fraction of the extravascular extracellular space (ve) were obtained. Partial Fourier encoding provided shortened echo times with acceptable signal-to-noise ratio and temporal stability, thus enabling reliable characterization of T2, T2(*) and T1 in both phantoms and rat brain. The hemodynamic parameters CBV, CBF, and MTT for gradient-echo and spin-echo contrast were determined in tumor and stroke; VSI, K(trans), and ve were also computed in tumor tissue. The SAGE EPI sequence allows the acquisition of multiple gradient- and spin-echoes, from which measures of perfusion, permeability, and vessel size can be obtained in a preclinical setting. Partial Fourier encoding can be used to minimize SAGE echo times and reliably quantify dynamic T2 and T2(*) changes. This acquisition provides a more comprehensive assessment of hemodynamic status in brain tissue with vascular and perfusion abnormalities.

Longitudinal assessment of mouse renal injury using high-resolution anatomic and magnetization transfer MR imaging.

The purpose of this study is to evaluate the utility of high-resolution non-invasive endogenous high-field MRI methods for the longitudinal structural and quantitative assessments of mouse kidney disease using the model of unilateral ureter obstruction (UUO). T1-weighted, T2-weighted and magnetization transfer (MT) imaging protocols were optimized to improve the regional contrast in mouse kidney. Conventional T1 and T2 weighted images were collected in UUO mice on day 0 (~3h), day 1, day 3 and day 6 after injury, on a 7 T small animal MRI system. Cortical and medullary thickness, corticomedullary contrast and Magnetization Transfer Ratio (MTR) were assessed longitudinally. Masson trichrome staining was used to histologically assess changes in tissue microstructure. Over the course of UUO progression there were significant (p<0.05) changes in thickness of cortex and outer medulla, and regional changes in T2 signal intensity and MTR values. Histological changes included tubular cell death, tubular dilation, urine retention, and interstitial fibrosis, assessed by histology. The MRI measures of renal cortical and medullary atrophy, cortical-medullary differentiation and MTR changes provide an endogenous, non-invasive and quantitative evaluation of renal morphology and tissue composition during UUO progression.