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In Vivo Quantitative Imaging of Gliomas

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A special issue of Cancers (ISSN 2072-6694). This special issue belongs to the section "Methods and Technologies Development".

Deadline for manuscript submissions: closed (1 May 2022) | Viewed by 21297

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Special Issue Editor

Dr. Ovidiu Andronesi

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Guest Editor

Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA.
Interests: glioma metabolism; IDH mutations; clinical translation of targeted therapy; metabolic imaging; development of fast and high resolution MRSI; deep learning

Special Issue Information

Dear Colleagues,

In vivo imaging has great value for brain studies because it can be done non-invasively, can sample the entire brain including both tumor and healthy brain tissue, and can be easily repeated. These features are difficult to achieve in brain when using other means, such as biopsies. Hence, there is high motivation for advancing glioma imaging, which is growing at a fast pace fueled by advances in aspects of imaging platforms including hardware, software, and imaging agents.

Quantitative imaging is being translated into the clinical workflow, where it enables precision oncology in glioma patients, and is being recognized and requested by neurooncologists and neurosurgeons toward improving outcomes for these patients.

For this Special Issue, we would like to invite papers that cover the entire breath of in vivo imaging for glioma—from technical development to clinical applications and from animal to human studies.

We are interested in technical development research articles presenting new imaging hardware platforms, imaging software methods for acquisition/reconstruction/analysis/reporting enhanced by deep learning, and molecular imaging agents. Methods that combine and leverage advances in multiple fields such as imaging genomics, (radiogenomics), artificial intelligence, therapy, and diagnostics have great potential to have a significant impact in clinical arena.

We seek to promote clinical applications related to diagnosis, treatment planning, and treatment response assessment of novel targeted treatments in glioma patients performed first in either human or large multi-center studies. In addition, we value research articles that bring new understanding of the mechanisms of tumor formation, response, and relapse either in animal models or human studies.

In addition to non-invasive imaging methods based on CT, MRI, PET, SPECT, and US, we welcome intraoperative imaging methods such as fluorescence (5-ALA) and Raman spectroscopy applied in glioma surgery.

We look forward to receiving submissions of cutting-edge and breakthrough research that will improve the outcomes and clinical needs of glioma patients.

Dr. Ovidiu Andronesi
Guest Editor

Manuscript Submission Information

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Keywords

glioma mechanisms & metabolism
treatment planning & guidance & response
quantitative multi-modal/parametric imaging
molecular imaging
imaging genomics
radiogenomics
radiomics
artificial intelligence
clinical translation
precision oncology

Published Papers (9 papers)

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Research

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13 pages, 1530 KiB

Open AccessArticle

Validation Study for Non-Invasive Prediction of IDH Mutation Status in Patients with Glioma Using In Vivo ¹H-Magnetic Resonance Spectroscopy and Machine Learning

by Elisabeth Bumes, Claudia Fellner, Franz A. Fellner, Karin Fleischanderl, Martina Häckl, Stefan Lenz, Ralf Linker, Tim Mirus, Peter J. Oefner, Christian Paar, Martin Andreas Proescholdt, Markus J. Riemenschneider, Katharina Rosengarth, Serge Weis, Christina Wendl, Sibylle Wimmer, Peter Hau, Wolfram Gronwald and Markus Hutterer

Cancers 2022, 14(11), 2762; https://doi.org/10.3390/cancers14112762 - 02 Jun 2022

Cited by 4 | Viewed by 2147

Abstract

The isocitrate dehydrogenase (IDH) mutation status is an indispensable prerequisite for diagnosis of glioma (astrocytoma and oligodendroglioma) according to the WHO classification of brain tumors 2021 and is a potential therapeutic target. Usually, immunohistochemistry followed by sequencing of tumor tissue is performed for this purpose. In clinical routine, however, non-invasive determination of IDH mutation status is desirable in cases where tumor biopsy is not possible and for monitoring neuro-oncological therapies. In a previous publication, we presented reliable prediction of IDH mutation status employing proton magnetic resonance spectroscopy (¹H-MRS) on a 3.0 Tesla (T) scanner and machine learning in a prospective cohort of 34 glioma patients. Here, we validated this approach in an independent cohort of 67 patients, for which ¹H-MR spectra were acquired at 1.5 T between 2002 and 2007, using the same data analysis approach. Despite different technical conditions, a sensitivity of 82.6% (95% CI, 61.2–95.1%) and a specificity of 72.7% (95% CI, 57.2–85.0%) could be achieved. We concluded that our ¹H-MRS based approach can be established in a routine clinical setting with affordable effort and time, independent of technical conditions employed. Therefore, the method provides a non-invasive tool for determining IDH status that is well-applicable in an everyday clinical setting. Full article

(This article belongs to the Special Issue In Vivo Quantitative Imaging of Gliomas)

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29 pages, 5495 KiB

Open AccessArticle

Deep Learning for Reaction-Diffusion Glioma Growth Modeling: Towards a Fully Personalized Model?

by Corentin Martens, Antonin Rovai, Daniele Bonatto, Thierry Metens, Olivier Debeir, Christine Decaestecker, Serge Goldman and Gaetan Van Simaeys

Cancers 2022, 14(10), 2530; https://doi.org/10.3390/cancers14102530 - 20 May 2022

Cited by 2 | Viewed by 2205

Abstract

Reaction-diffusion models have been proposed for decades to capture the growth of gliomas, the most common primary brain tumors. However, ill-posedness of the initialization at diagnosis time and parameter estimation of such models have restrained their clinical use as a personalized predictive tool. In this work, we investigate the ability of deep convolutional neural networks (DCNNs) to address commonly encountered pitfalls in the field. Based on 1200 synthetic tumors grown over real brain geometries derived from magnetic resonance (MR) data of six healthy subjects, we demonstrate the ability of DCNNs to reconstruct a whole tumor cell-density distribution from only two imaging contours at a single time point. With an additional imaging contour extracted at a prior time point, we also demonstrate the ability of DCNNs to accurately estimate the individual diffusivity and proliferation parameters of the model. From this knowledge, the spatio-temporal evolution of the tumor cell-density distribution at later time points can ultimately be precisely captured using the model. We finally show the applicability of our approach to MR data of a real glioblastoma patient. This approach may open the perspective of a clinical application of reaction-diffusion growth models for tumor prognosis and treatment planning. Full article

(This article belongs to the Special Issue In Vivo Quantitative Imaging of Gliomas)

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18 pages, 19445 KiB

Open AccessArticle

Diagnostic and Prognostic Value of pH- and Oxygen-Sensitive Magnetic Resonance Imaging in Glioma: A Retrospective Study

by Jingwen Yao, Akifumi Hagiwara, Talia C. Oughourlian, Chencai Wang, Catalina Raymond, Whitney B. Pope, Noriko Salamon, Albert Lai, Matthew Ji, Phioanh L. Nghiemphu, Linda M. Liau, Timothy F. Cloughesy and Benjamin M. Ellingson

Cancers 2022, 14(10), 2520; https://doi.org/10.3390/cancers14102520 - 20 May 2022

Cited by 2 | Viewed by 1814

Abstract

Characterization of hypoxia and tissue acidosis could advance the understanding of glioma biology and improve patient management. In this study, we evaluated the ability of a pH- and oxygen-sensitive magnetic resonance imaging (MRI) technique to differentiate glioma genotypes, including isocitrate dehydrogenase (IDH) mutation, 1p/19q co-deletion, and epidermal growth factor receptor (EGFR) amplification, and investigated its prognostic value. A total of 159 adult glioma patients were scanned with pH- and oxygen-sensitive MRI at 3T. We quantified the pH-sensitive measure of magnetization transfer ratio asymmetry (MTR_asym) and oxygen-sensitive measure of R₂’ within the tumor region-of-interest. IDH mutant gliomas showed significantly lower MTR_asym × R₂’ (p < 0.001), which differentiated IDH mutation status with sensitivity and specificity of 90.0% and 71.9%. Within IDH mutants, 1p/19q codeletion was associated with lower tumor acidity (p < 0.0001, sensitivity 76.9%, specificity 91.3%), while IDH wild-type, EGFR-amplified gliomas were more hypoxic (R₂’ p = 0.024, sensitivity 66.7%, specificity 76.9%). Both R₂’ and MTR_asym × R₂’ were significantly associated with patient overall survival (R₂’: p = 0.045; MTR_asym × R₂’: p = 0.002) and progression-free survival (R₂’: p = 0.010; MTR_asym × R₂’: p < 0.0001), independent of patient age, treatment status, and IDH status. The pH- and oxygen-sensitive MRI is a clinically feasible and potentially valuable imaging technique for distinguishing glioma subtypes and providing additional prognostic value to clinical practice. Full article

(This article belongs to the Special Issue In Vivo Quantitative Imaging of Gliomas)

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12 pages, 2128 KiB

Open AccessArticle

Quantification of Tissue Compression Identifies High-Grade Glioma Patients with Reduced Survival

by Elies Fuster-Garcia, Ivar Thokle Hovden, Siri Fløgstad Svensson, Christopher Larsson, Jonas Vardal, Atle Bjørnerud and Kyrre E. Emblem

Cancers 2022, 14(7), 1725; https://doi.org/10.3390/cancers14071725 - 28 Mar 2022

Cited by 2 | Viewed by 1780

Abstract

The compression of peritumoral healthy tissue in brain tumor patients is considered a major cause of the life-threatening neurologic symptoms. Although significant deformations caused by the tumor growth can be observed radiologically, the quantification of minor tissue deformations have not been widely investigated. In this study, we propose a method to quantify subtle peritumoral deformations. A total of 127 MRI longitudinal studies from 23 patients with high-grade glioma were included. We estimate longitudinal displacement fields based on a symmetric normalization algorithm and we propose four biomarkers. We assess the interpatient and intrapatient association between proposed biomarkers and the survival based on Cox analyses, and the potential of the biomarkers to stratify patients according to their survival based on Kaplan–Meier analysis. Biomarkers show a significant intrapatient association with survival (p < 0.05); however, only compression biomarkers show the ability to stratify patients between those with higher and lower overall survival (AUC = 0.83, HR = 6.30, p < 0.05 for CompCH). The compression biomarkers present three times higher Hazard Ratios than those representing only displacement. Our study provides a robust and automated method for quantifying and delineating compression in the peritumoral area. Based on the proposed methodology, we found an association between lower compression in the peritumoral area and good prognosis in high-grade glial tumors. Full article

(This article belongs to the Special Issue In Vivo Quantitative Imaging of Gliomas)

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13 pages, 1541 KiB

Open AccessArticle

Matching Quantitative MRI Parameters with Histological Features of Treatment-Naïve IDH Wild-Type Glioma

by Gabriele D. Maurer, Julia Tichy, Patrick N. Harter, Ulrike Nöth, Lutz Weise, Johanna Quick-Weller, Ralf Deichmann, Joachim P. Steinbach, Oliver Bähr and Elke Hattingen

Cancers 2021, 13(16), 4060; https://doi.org/10.3390/cancers13164060 - 12 Aug 2021

Cited by 6 | Viewed by 2454

Abstract

Quantitative MRI allows to probe tissue properties by measuring relaxation times and may thus detect subtle changes in tissue composition. In this work we analyzed different relaxation times (T1, T2, T2* and T2′) and histological features in 321 samples that were acquired from 25 patients with newly diagnosed IDH wild-type glioma. Quantitative relaxation times before intravenous application of gadolinium-based contrast agent (GBCA), T1 relaxation time after GBCA as well as the relative difference between T1 relaxation times pre-to-post GBCA (T1rel) were compared with histopathologic features such as the presence of tumor cells, cell and vessel density, endogenous markers for hypoxia and cell proliferation. Image-guided stereotactic biopsy allowed for the attribution of each tissue specimen to its corresponding position in the respective relaxation time map. Compared to normal tissue, T1 and T2 relaxation times and T1rel were prolonged in samples containing tumor cells. The presence of vascular proliferates was associated with higher T1rel values. Immunopositivity for lactate dehydrogenase A (LDHA) involved slightly longer T1 relaxation times. However, low T2′ values, suggesting high amounts of deoxyhemoglobin, were found in samples with elevated vessel densities, but not in samples with increased immunopositivity for LDHA. Taken together, some of our observations were consistent with previous findings but the correlation of quantitative MRI and histologic parameters did not confirm all our pathophysiology-based assumptions. Full article

(This article belongs to the Special Issue In Vivo Quantitative Imaging of Gliomas)

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17 pages, 12239 KiB

Open AccessArticle

Hypoxia and Microvascular Alterations Are Early Predictors of IDH-Mutated Anaplastic Glioma Recurrence

by Andreas Stadlbauer, Stefan Oberndorfer, Gertraud Heinz, Max Zimmermann, Thomas M. Kinfe, Arnd Doerfler, Michael Buchfelder, Natalia Kremenevski and Franz Marhold

Cancers 2021, 13(8), 1797; https://doi.org/10.3390/cancers13081797 - 09 Apr 2021

Cited by 2 | Viewed by 1713

Abstract

Anaplastic gliomas (AG) represents aggressive brain tumors that often affect young adults. Although isocitrate-dehydrogenase (IDH) gene mutation has been identified as a more favorable prognostic factor, most IDH-mutated AG patients are confronted with tumor recurrence. Hence, increased knowledge about pathophysiological precursors of AG recurrence is urgently needed in order to develop precise diagnostic monitoring and tailored therapeutic approaches. In this study, 142 physiological magnetic resonance imaging (phyMRI) follow-up examinations in 60 AG patients after standard therapy were evaluated and magnetic resonance imaging (MRI) biomarker maps for microvascular architecture and perfusion, neovascularization activity, oxygen metabolism, and hypoxia calculated. From these 60 patients, 34 patients developed recurrence of the AG, and 26 patients showed no signs for AG recurrence during the study period. The time courses of MRI biomarker changes were analyzed regarding early pathophysiological alterations over a one-year period before radiological AG recurrence or a one-year period of stable disease for patients without recurrence, respectively. We detected intensifying local tissue hypoxia 250 days prior to radiological recurrence which initiated upregulation of neovascularization activity 50 to 70 days later. These changes were associated with a switch from an avascular infiltrative to a vascularized proliferative phenotype of the tumor cells another 30 days later. The dynamic changes of blood perfusion, microvessel density, neovascularization activity, and oxygen metabolism showed a close physiological interplay in the one-year period prior to radiological recurrence of IDH-mutated AG. These findings may path the wave for implementing both new MR-based imaging modalities for routine follow-up monitoring of AG patients after standard therapy and furthermore may support the development of novel, tailored therapy options in recurrent AG. Full article

(This article belongs to the Special Issue In Vivo Quantitative Imaging of Gliomas)

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Review

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14 pages, 900 KiB

Open AccessReview

Magnetic Resonance Spectroscopy in Diagnosis and Follow-Up of Gliomas: State-of-the-Art

by Malik Galijasevic, Ruth Steiger, Stephanie Mangesius, Julian Mangesius, Johannes Kerschbaumer, Christian Franz Freyschlag, Nadja Gruber, Tanja Janjic, Elke Ruth Gizewski and Astrid Ellen Grams

Cancers 2022, 14(13), 3197; https://doi.org/10.3390/cancers14133197 - 29 Jun 2022

Cited by 7 | Viewed by 3395

Abstract

Preoperative grade prediction is important in diagnostics of glioma. Even more important can be follow-up after chemotherapy and radiotherapy of high grade gliomas. In this review we provide an overview of MR-spectroscopy (MRS), technical aspects, and different clinical scenarios in the diagnostics and follow-up of gliomas in pediatric and adult populations. Furthermore, we provide a recap of the current research utility and possible future strategies regarding proton- and phosphorous-MRS in glioma research. Full article

(This article belongs to the Special Issue In Vivo Quantitative Imaging of Gliomas)

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16 pages, 2192 KiB

Open AccessReview

In Vivo Quantitative Imaging of Glioma Heterogeneity Employing Positron Emission Tomography

by Cristina Barca, Claudia Foray, Bastian Zinnhardt, Alexandra Winkeler, Ulrich Herrlinger, Oliver M. Grauer and Andreas H. Jacobs

Cancers 2022, 14(13), 3139; https://doi.org/10.3390/cancers14133139 - 27 Jun 2022

Cited by 3 | Viewed by 2158

Abstract

Glioblastoma is the most common primary brain tumor, highly aggressive by being proliferative, neovascularized and invasive, heavily infiltrated by immunosuppressive glioma-associated myeloid cells (GAMs), including glioma-associated microglia/macrophages (GAMM) and myeloid-derived suppressor cells (MDSCs). Quantifying GAMs by molecular imaging could support patient selection for GAMs-targeting immunotherapy, drug target engagement and further assessment of clinical response. Magnetic resonance imaging (MRI) and amino acid positron emission tomography (PET) are clinically established imaging methods informing on tumor size, localization and secondary phenomena but remain quite limited in defining tumor heterogeneity, a key feature of glioma resistance mechanisms. The combination of different imaging modalities improved the in vivo characterization of the tumor mass by defining functionally distinct tissues probably linked to tumor regression, progression and infiltration. In-depth image validation on tracer specificity, biological function and quantification is critical for clinical decision making. The current review provides a comprehensive overview of the relevant experimental and clinical data concerning the spatiotemporal relationship between tumor cells and GAMs using PET imaging, with a special interest in the combination of amino acid and translocator protein (TSPO) PET imaging to define heterogeneity and as therapy readouts. Full article

(This article belongs to the Special Issue In Vivo Quantitative Imaging of Gliomas)

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Other

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20 pages, 1222 KiB

Open AccessSystematic Review

A Systematic Review of the Current Status and Quality of Radiomics for Glioma Differential Diagnosis

by Valentina Brancato, Marco Cerrone, Marialuisa Lavitrano, Marco Salvatore and Carlo Cavaliere

Cancers 2022, 14(11), 2731; https://doi.org/10.3390/cancers14112731 - 31 May 2022

Cited by 14 | Viewed by 2642

Abstract

Radiomics is a promising tool that may increase the value of imaging in differential diagnosis (DDx) of glioma. However, implementation in clinical practice is still distant and concerns have been raised regarding the methodological quality of radiomic studies. Therefore, we aimed to systematically review the current status of radiomic studies concerning glioma DDx, also using the radiomics quality score (RQS) to assess the quality of the methodology used in each study. A systematic literature search was performed to identify original articles focused on the use of radiomics for glioma DDx from 2015. Methodological quality was assessed using the RQS tool. Spearman’s correlation (ρ) analysis was performed to explore whether RQS was correlated with journal metrics and the characteristics of the studies. Finally, 42 articles were selected for the systematic qualitative analysis. Selected articles were grouped and summarized in terms of those on DDx between glioma and primary central nervous system lymphoma, those aiming at differentiating glioma from brain metastases, and those based on DDx of glioma and other brain diseases. Median RQS was 8.71 out 36, with a mean RQS of all studies of 24.21%. Our study revealed that, despite promising and encouraging results, current studies on radiomics for glioma DDx still lack the quality required to allow its introduction into clinical practice. This work could provide new insights and help to reach a consensus on the use of the radiomic approach for glioma DDx. Full article

(This article belongs to the Special Issue In Vivo Quantitative Imaging of Gliomas)

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