Multi-modal imaging of tumor cellularity and Tryptophan metabolism in human Gliomas

Study on the Relationship Between MRI Functional Imaging and Multiple Immunohistochemical Features of Glioma: A Noninvasive and More Precise Glioma Management

Objective

To investigate the performance of diffusion-tensor imaging (DTI) and hydrogen proton magnetic resonance spectroscopy (1H-MRS) parameters in predicting the immunohistochemistry (IHC) biomarkers of glioma.

Methods

Patients with glioma confirmed by pathology from March 2015 to September 2019 were analyzed, the preoperative DTI and 1H-MRS images were collected, apparent diffusion coefficient (ADC) and fractional anisotropy (FA), in the lesion area were measured, the relative values relative ADC (rADC) and relative FA (rFA) were obtained by the ratio of them in the lesion area to the contralateral normal area. The peak of each metabolite in the lesion area of 1H-MRS image: N-acetylaspartate (NAA), choline (Cho), and creatine (Cr), and metabolite ratio: NAA/Cho, NAA/(Cho + Cr) were selected and calculated. The preoperative IHC data were collected including CD34, Ki-67, p53, S-100, syn, vimentin, NeuN, Nestin, and glial fibrillary acidic protein.

Results

One predicting parameter of DTI was screened, the rADC of the Ki-67 positive group was lower than that of the negative group. Two parameters of 1H-MRS were found to have significant reference values for glioma grades, the NAA and Cr decreased as the grade of glioma increased, moreover, Ki-67 Li was negatively correlated with NAA and Cr.

Conclusion

NAA and Cr have potential application value in predicting glioma grades and tumor proliferation activity. Only rADC has predictive value for Ki-67 expression among DTI parameters.

Glioma Imaging by O-(2-18F-Fluoroethyl)-L-Tyrosine PET and Diffusion-Weighted MRI and Correlation With Molecular Phenotypes, Validated by PET/MR-Guided Biopsies

Gliomas exhibit high intra-tumoral histological and molecular heterogeneity. Introducing stereotactic biopsy, we achieved a superior molecular analysis of glioma using O-(2-18F-fluoroethyl)-L-tyrosine (FET)-positron emission tomography (PET) and diffusion-weighted magnetic resonance imaging (DWI). Patients underwent simultaneous DWI and FET-PET scans. Correlations between biopsy-derived tumor tissue values, such as the tumor-to-background ratio (TBR) and apparent diffusion coefficient (ADC)/exponential ADC (eADC) and histopathological diagnoses and those between relevant genes and TBR and ADC values were determined. Tumor regions with human telomerase reverse transcriptase (hTERT) mutation had higher TBR and lower ADC values. Tumor protein P53 mutation correlated with lower TBR and higher ADC values. α-thalassemia/mental-retardation-syndrome-X-linked gene (ATRX) correlated with higher ADC values. 1p/19q codeletion and epidermal growth factor receptor (EGFR) mutations correlated with lower ADC values. Isocitrate dehydrogenase 1 (IDH1) mutations correlated with higher TBRmean values. No correlation existed between TBRmax/TBRmean/ADC/eADC values and phosphatase and tensin homolog mutations (PTEN) or O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation. Furthermore, TBR/ADC combination had a higher diagnostic accuracy than each single imaging method for high-grade and IDH1-, hTERT-, and EGFR-mutated gliomas. This is the first study establishing the accurate diagnostic criteria for glioma based on FET-PET and DWI.

Comparison of Amino Acid PET to Advanced and Emerging MRI Techniques for Neurooncology Imaging: A Systematic Review of the Recent Studies

Introduction

Standard neuroimaging protocols for brain tumors have well-known limitations. The clinical use of additional modalities including amino acid PET (aaPET) and advanced MRI (aMRI) techniques (including DWI, PWI, and MRS) is emerging in response to the need for more accurate detection of brain tumors. In this systematic review of the past 2 years of the literature, we discuss the most recent studies that directly compare or combine aaPET and aMRI for brain tumor imaging.

Methods

A PubMed search was conducted for human studies incorporating both aaPET and aMRI and published between July 2018 and August 2020.

Results

A total of 22 studies were found in the study period. Recent studies of aaPET with DWI showed a superiority of MET, FET, FDOPA, and AMT PET for detecting tumor, predicting recurrence, diagnosing progression, and predicting survival. Combining modalities further improved performance. Comparisons of aaPET with PWI showed mixed results about spatial correlation. However, both modalities were able to detect high-grade tumors, identify tumor recurrence, differentiate recurrence from treatment effects, and predict survival. aaPET performed better on these measures than PWI, but when combined, they had the strongest results. Studies of aaPET with MRS demonstrated that both modalities have diagnostic potential but MET PET and FDOPA PET performed better than MRS. MRS suffered from some data quality issues that limited analysis in two studies, and, in one study that combined modalities, overall performance actually decreased. Four recent studies compared aaPET with emerging MRI approaches (such as CEST imaging, MR fingerprinting, and SISTINA), but the initial results remain inconclusive.

Conclusions

aaPET outperformed the aMRI imaging techniques in most recent studies. DWI and PWI added meaningful complementary data, and the combination of aaPET with aMRI yielded the best results in most studies.

Terahertz dielectric spectroscopy of human brain gliomas and intact tissues ex vivo: double-Debye and double-overdamped-oscillator models of dielectric response

Terahertz (THz) technology offers novel opportunities in the intraoperative neurodiagnosis. Recently, the significant progress was achieved in the study of brain gliomas and intact tissues, highlighting a potential for THz technology in the intraoperative delineation of tumor margins. However, a lack of physical models describing the THz dielectric permittivity of healthy and pathological brain tissues restrains the further progress in this field. In the present work, the ex vivo THz dielectric response of human brain tissues was analyzed using relaxation models of complex dielectric permittivity. Dielectric response of tissues was parametrized by a pair of the Debye relaxators and a pair of the overdamped-oscillators - namely, the double-Debye (DD) and double-overdamped-oscillator (DO) models. Both models accurately reproduce the experimental curves for the intact tissues and the WHO Grades I-IV gliomas. While the DD model is more common for THz biophotonics, the DO model is more physically rigorous, since it satisfies the sum rule. In this way, the DO model and the sum rule were, then, applied to estimate the content of water in intact tissues and gliomas ex vivo. The observed results agreed well with the earlier-reported data, justifying water as a main endogenous label of brain tumors in the THz range. The developed models can be used to describe completely the THz-wave - human brain tissues interactions in the frameworks of classical electrodynamics, being quite important for further research and developments in THz neurodiagnosis of tumors.

11C- and 18F-labelled tryptophans as PET-tracers for imaging of altered tryptophan metabolism in age-associated disorders

The ageing of the world’s population is the result of increased life expectancy observed in almost all countries throughout the world. Consequently, a rising tide of ageing-associated disorders, like cancer and neurodegenerative diseases, represents one of the main global challenges of the 21st century. The ability of mankind to overcome these challenges is directly dependent on the capability to develop novel methods for therapy and diagnosis of age-associated diseases. One hallmark of age-related pathologies is an altered tryptophan metabolism. Numerous pathological processes including neurodegenerative and neurological diseases like epilepsy, Parkinson’s and Alzheimer’s diseases, cancer and diabetes exhibit marked changes in tryptophan metabolism. Visualization of key processes of tryptophan metabolic pathways, especially using positron emission tomography (PET) and related hybrid methods like PET/CT and PET/MRI, can be exploited to early detect the aforementioned disorders with considerable accuracy, allowing appropriate and timely treatment of patients. Here we review the published 11C- and 18F-labelled tryptophans with respect to the production and also preclinical and clinical evaluation as PET-tracers for visualization of different branches of tryptophan metabolism.

The bibliography includes 159 references.

Transcriptional signatures in histologic structures within glioblastoma tumors may predict personalized drug sensitivity and survival

Background

Glioblastoma is a rapidly fatal brain cancer that exhibits extensive intra- and intertumoral heterogeneity. Improving survival will require the development of personalized treatment strategies that can stratify tumors into subtypes that differ in therapeutic vulnerability and outcomes. Glioblastoma stratification has been hampered by intratumoral heterogeneity, limiting our ability to compare tumors in a consistent manner. Here, we develop methods that mitigate the impact of intratumoral heterogeneity on transcriptomic-based patient stratification.

Methods

We accessed open-source transcriptional profiles of histological structures from 34 human glioblastomas from the Ivy Glioblastoma Atlas Project. Principal component and correlation network analyses were performed to assess sample inter-relationships. Gene set enrichment analysis was used to identify enriched biological processes and classify glioblastoma subtype. For survival models, Cox proportional hazards regression was utilized. Transcriptional profiles from 156 human glioblastomas were accessed from The Cancer Genome Atlas to externally validate the survival model.

Results

We showed that intratumoral histologic architecture influences tumor classification when assessing established subtyping and prognostic gene signatures, and that indiscriminate sampling can produce misleading results. We identified the cellular tumor as a glioblastoma structure that can be targeted for transcriptional analysis to more accurately stratify patients by subtype and prognosis. Based on expression from cellular tumor, we created an improved risk stratification gene signature.

Conclusions

Our results highlight that biomarker performance for diagnostics, prognostics, and prediction of therapeutic response can be improved by analyzing transcriptional profiles in pure cellular tumor, which is a critical step toward developing personalized treatment for glioblastoma.

Multimodal imaging-defined subregions in newly diagnosed glioblastoma: impact on overall survival

BACKGROUND

Although glioblastomas are heterogeneous brain-infiltrating tumors, their treatment is mostly focused on the contrast-enhancing tumor mass. In this study, we combined conventional MRI, diffusion-weighted imaging (DWI), and amino acid PET to explore imaging-defined glioblastoma subregions and evaluate their potential prognostic value.

METHODS

Contrast-enhanced T1, T2/fluid attenuated inversion recovery (FLAIR) MR images, apparent diffusion coefficient (ADC) maps from DWI, and alpha-[11C]-methyl-L-tryptophan (AMT)-PET images were analyzed in 30 patients with newly diagnosed glioblastoma. Five tumor subregions were identified based on a combination of MRI contrast enhancement, T2/FLAIR signal abnormalities, and AMT uptake on PET. ADC and AMT uptake tumor/contralateral normal cortex (T/N) ratios in these tumor subregions were correlated, and their prognostic value was determined.

RESULTS

A total of 115 MRI/PET-defined subregions were analyzed. Most tumors showed not only a high-AMT uptake (T/N ratio > 1.65, N = 27) but also a low-uptake subregion (N = 21) within the contrast-enhancing tumor mass. High AMT uptake extending beyond contrast enhancement was also common (N = 25) and was associated with low ADC (r = -0.40, P = 0.05). Higher AMT uptake in the contrast-enhancing tumor subregions was strongly prognostic for overall survival (hazard ratio: 7.83; 95% CI: 1.98-31.02, P = 0.003), independent of clinical and molecular genetic prognostic variables. Nonresected high-AMT uptake subregions predicted the sites of tumor progression on posttreatment PET performed in 10 patients.

CONCLUSIONS

Glioblastomas show heterogeneous amino acid uptake with high-uptake regions often extending into non-enhancing brain with high cellularity; nonresection of these predict the site of posttreatment progression. High tryptophan uptake values in MRI contrast-enhancing tumor subregions are a strong, independent imaging marker for longer overall survival.

PET imaging of medulloblastoma with an 18F-labeled tryptophan analogue in a transgenic mouse model

In vivo positron emission tomography (PET) imaging is a key modality to evaluate disease status of brain tumors. In recent years, tremendous efforts have been made in developing PET imaging methods for pediatric brain tumors. Carbon-11 labelled tryptophan derivatives are feasible as PET imaging probes in brain tumor patients with activation of the kynurenine pathway, but the short half-life of carbon-11 limits its application. Using a transgenic mouse model for the sonic hedgehog (Shh) subgroup of medulloblastoma, here we evaluated the potential of the newly developed 1-(2-[¹⁸F]fluoroethyl)-L-tryptophan (1-L-[¹⁸F]FETrp) as a PET imaging probe for this common malignant pediatric brain tumor. 1-L-[¹⁸F]FETrp was synthesized on a PETCHEM automatic synthesizer with good chemical and radiochemical purities and enantiomeric excess values. Imaging was performed in tumor-bearing Smo/Smo medulloblastoma mice with constitutive actvation of the Smoothened (Smo) receptor using a PerkinElmer G4 PET-X-Ray scanner. Medulloblastoma showed significant and specific accumulation of 1-L-[¹⁸F]FETrp. 1-L-[¹⁸F]FETrp also showed significantly higher tumor uptake than its D-enantiomer, 1-D-[¹⁸F]FETrp. The uptake of 1-L-[¹⁸F]FETrp in the normal brain tissue was low, suggesting that 1-L-[¹⁸F]FETrp may prove a valuable PET imaging probe for the Shh subgroup of medulloblastoma and possibly other pediatric and adult brain tumors.

Automated production of 1-(2-[18F]fluoroethyl)-l-tryptophan for imaging of tryptophan metabolism

Automated production of an fluorine-18 labeled tryptophan analogue, 1-(2-[¹⁸F]fluoroethyl)-l-tryptophan (1-L-[¹⁸F]FETrp) in a current Good Manufacturing Practice facility was achieved. 1-L-[¹⁸F]FETrp was produced by a one-pot, two-step strategy with an overall synthesis time of approximately 100 min, a radiochemical yield of 20 ± 5% (decay corrected), radiochemical purity and enantiomeric excess over 90%, and a molar activity of 103 ± 15 GBq/μmol at the end of synthesis (EOS). The dose mass of 1-L-FETrp in four consecutive batches was less than 5 μg. The radiopharmaceutical product met all quality control criteria for clinical use.

Feasibility of Multimodal MRI-Based Deep Learning Prediction of High Amino Acid Uptake Regions and Survival in Patients With Glioblastoma

Purpose: Amino acid PET has shown high accuracy for the diagnosis and prognostication of malignant gliomas, however, this imaging modality is not widely available in clinical practice. This study explores a novel end-to-end deep learning framework ("U-Net") for its feasibility to detect high amino acid uptake glioblastoma regions (i.e., metabolic tumor volume) using clinical multimodal MRI sequences. Methods: T2, fluid-attenuated inversion recovery (FLAIR), apparent diffusion coefficient map, contrast-enhanced T1, and alpha-[¹¹C]-methyl-L-tryptophan (AMT)-PET images were analyzed in 21 patients with newly-diagnosed glioblastoma. U-Net system with data augmentation was implemented to deeply learn non-linear voxel-wise relationships between intensities of multimodal MRI as the input and metabolic tumor volume from AMT-PET as the output. The accuracy of the MRI- and PET-based volume measures to predict progression-free survival was tested. Results: In the augmented dataset using all four MRI modalities to investigate the upper limit of U-Net accuracy in the full study cohort, U-Net achieved high accuracy (sensitivity/specificity/positive predictive value [PPV]/negative predictive value [NPV]: 0.85/1.00/0.81/1.00, respectively) to predict PET-defined tumor volumes. Exclusion of FLAIR from the MRI input set had a strong negative effect on sensitivity (0.60). In repeated hold out validation in randomly selected subjects, specificity and NPV remained high (1.00), but mean sensitivity (0.62), and PPV (0.68) were moderate. AMT-PET-learned MRI tumor volume from this U-net model within the contrast-enhancing volume predicted 6-month progression-free survival with 0.86/0.63 sensitivity/specificity. Conclusions: These data indicate the feasibility of PET-based deep learning for enhanced pretreatment glioblastoma delineation and prognostication by clinical multimodal MRI.

Imaging tryptophan uptake with positron emission tomography in glioblastoma patients treated with indoximod

INTRODUCTION

Glioblastoma (GBM) is the most frequent and aggressive primary tumor of the central nervous system, accounting for over 50% of all primary malignant gliomas arising in the adult brain. Even after surgical resection, adjuvant radiotherapy (RT) and temozolomide (TMZ) chemotherapy, as well as tumor-treating fields, the median survival is only 15-20 months. We have identified a pathogenic mechanism that contributes to the tumor-induced immunosuppression in the form of increased indoleamine 2,3 dioxygenase 1 (IDO1) expression; an enzyme that metabolizes the essential amino acid, tryptophan (Trp), into kynurenine (Kyn). However, real-time measurements of IDO1 activity has yet to become mainstream in clinical protocols for assessing IDO1 activity in GBM patients.

METHODS

Pre-treatment and on-treatment α-[11C]-methyl-L-Trp (AMT) positron emission tomography (PET) with co-registered MRI was performed on patients with recurrent GBM treated with the IDO1 pathway inhibitor indoximod (D1-MT) and TMZ.

RESULTS

Regional intratumoral variability of AMT within enhancing and non-enhancing tumor was noted at baseline. On treatment imaging revealed decreased regional uptake suggesting IDO1 pathway modulation with treatment.

CONCLUSIONS

Here, we have validated the ability to use PET of the Trp probe, AMT, for use in visualizing and quantifying intratumoral Trp uptake in GBM patients treated with an IDO1 pathway inhibitor. These data serve as rationale to utilize AMT-PET imaging in the future evaluation of GBM patients treated with IDO1 enzyme inhibitors.

Brain Tumors: An Update on Clinical PET Research in Gliomas

A previous review published in 2012 demonstrated the role of clinical PET for diagnosis and management of brain tumors using mainly FDG, amino acid tracers, and ¹⁸F-fluorothymidine. This review provides an update on clinical PET studies, most of which are motivated by prediction of prognosis and planning and monitoring of therapy in gliomas. For FDG, there has been additional evidence supporting late scanning, and combination with ¹³N ammonia has yielded some promising results. Large neutral amino acid tracers have found widespread applications mostly based on ¹⁸F-labeled compounds fluoroethyltyrosine and fluorodopa for targeting biopsies, therapy planning and monitoring, and as outcome markers in clinical trials. ¹¹C-alpha-methyltryptophan (AMT) has been proposed as an alternative to ¹¹C-methionine, and there may also be a role for cyclic amino acid tracers. ¹⁸F-fluorothymidine has shown strengths for tumor grading and as an outcome marker. Studies using ¹⁸F-fluorocholine (FCH) and ⁶⁸Ga-labeled compounds are promising but have not yet clearly defined their role. Studies on radiotherapy planning have explored the use of large neutral amino acid tracers to improve the delineation of tumor volume for irradiation and the use of hypoxia markers, in particular ¹⁸F-fluoromisonidazole. Many studies employed the combination of PET with advanced multimodal MR imaging methods, mostly demonstrating complementarity and some potential benefits of hybrid PET/MR.

Tryptophan PET predicts spatial and temporal patterns of post-treatment glioblastoma progression detected by contrast-enhanced MRI

Amino acid PET is increasingly utilized for the detection of recurrent gliomas. Increased amino acid uptake is often observed outside the contrast-enhancing brain tumor mass. In this study, we evaluated if non-enhancing PET+ regions could predict spatial and temporal patterns of subsequent MRI progression in previously treated glioblastomas. Twelve patients with a contrast-enhancing area suspicious for glioblastoma recurrence on MRI underwent PET scanning with the amino acid radiotracer alpha-[(11)C]-methyl-L-tryptophan (AMT). Brain regions showing increased AMT uptake in and outside the contrast-enhancing volume were objectively delineated to include high uptake consistent with glioma (as defined by previous studies). Volume and tracer uptake of such non-enhancing PET+ regions were compared to spatial patterns and timing of subsequent progression of the contrast-enhancing lesion, as defined by serial surveillance MRI. Non-enhancing PET+ volumes varied widely across patients and extended up to 24 mm from the edge of MRI contrast enhancement. In ten patients with clear progression of the contrast-enhancing lesion, the non-enhancing PET+ volumes predicted the location of new enhancement, which extended beyond the PET+ brain tissue in six. In two patients, with no PET+ area beyond the initial contrast enhancement, MRI remained stable. There was a negative correlation between AMT uptake in non-enhancing brain and time to subsequent progression (r = -0.77, p = 0.003). Amino acid PET imaging could complement MRI not only for detecting glioma recurrence but also predicting the location and timing of subsequent tumor progression. This could support decisions for surgical intervention or other targeted therapies for recurrent gliomas.