Exploring MRI Characteristics of Brain Diffuse Midline Gliomas With the H3 K27M Mutation Using Radiomics

Li, Qian; Dong, Fei; Jiang, Biao; Zhang, Minming

doi:10.3389/fonc.2021.646267

Cited by 13 publications

(19 citation statements)

References 35 publications

(49 reference statements)

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“…Historically, MR images have been primarily used for a qualitative and objective assessment of the tumor by clinicians. However, recent neuroimaging advances have contributed to the development of quantitative and molecular MRI techniques (17)(18)(19), which have the potential to transform the interpretation and application of imaging results into routine clinical practice. Nonetheless, research into fully quantitative MRIbased biomarkers of glioma is still very much an ongoing endeavor.…”

Section: Introductionmentioning

confidence: 99%

Multispectral fluorine-19 MRI enables longitudinal and noninvasive monitoring of tumor-associated macrophages

et al. 2022

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High-grade gliomas, the most common and aggressive primary brain tumors, are characterized by a complex tumor microenvironment (TME). Among the immune cells infiltrating the glioma TME, tumor-associated microglia and macrophages (TAMs) constitute the major compartment. In patients with gliomas, increased TAM abundance is associated with more aggressive disease. Alterations in TAM phenotypes and functions have been reported in preclinical models of multiple cancers during tumor development and after therapeutic interventions, including radiotherapy and molecular targeted therapies. These findings indicate that it is crucial to evaluate TAM abundance and dynamics over time. Current techniques to quantify TAMs in patients rely mainly on histological staining of tumor biopsies. Although informative, these techniques require an invasive procedure to harvest the tissue sample and typically only result in a snapshot of a small region at a single point in time. Fluorine isotope 19 MRI ( 19 F MRI) represents a powerful means to noninvasively and longitudinally monitor myeloid cells in pathological conditions by intravenously injecting perfluorocarbon-containing nanoparticles (PFC-NP). In this study, we demonstrated the feasibility and power of 19 F MRI in preclinical models of gliomagenesis, breast-to-brain metastasis, and breast cancer and showed that the major cellular source of 19 F signal consists of TAMs. Moreover, multispectral 19 F MRI with two different PFC-NP allowed us to identify spatially and temporally distinct TAM niches in radiotherapy-recurrent murine gliomas. Together, we have imaged TAMs noninvasively and longitudinally with integrated cellular, spatial, and temporal resolution, thus revealing important biological insights into the critical functions of TAMs, including in disease recurrence.

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Section: Introductionmentioning

confidence: 99%

Multispectral fluorine-19 MRI enables longitudinal and noninvasive monitoring of tumor-associated macrophages

et al. 2022

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“…The model had an AUC of 0.791 in the training set and 0.737 in the test set, and the AC of the model was 73% in the test set. Furthermore, Li et al ( 34 ) explored visually accessible MRI features of 30 patients with DMGs with and without the H3 K27M mutation using principal component analysis based on radiomics and found that T2w sequences may be more valuable and that cystic formation may be a biomarker for diagnosing DMGs with an H3 K27M mutation.…”

Section: Discussionmentioning

confidence: 99%

Non-Invasive Prediction of Survival Time of Midline Glioma Patients Using Machine Learning on Multiparametric MRI Radiomics Features

Deng

Liao²,

Zhou

et al. 2022

Front. Neurol.

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ObjectivesTo explore the feasibility of predicting overall survival (OS) of patients with midline glioma using multi-parameter magnetic resonance imaging (MRI) features.MethodsData of 84 patients with midline gliomas were retrospectively collected, including 40 patients with OS > 12 months (28 cases were adults, 14 cases were H3 K27M-mutation) and 44 patients with OS < 12 months (29 cases were adults, 31 cases were H3 K27M-mutation). Features were extracted from the largest slice of tumors, which were manually segmented on T2-weighted (T2w), T2 fluid-attenuated inversion recovery (T2 FLAIR), and contrast-enhanced T1-weighted (T1c) images. Data were randomly divided into training (70%) and test cohorts (30%) and normalized and standardized using Z-scores. Feature dimensionality reduction was performed using the variance method and maximum relevance and minimum redundancy (mRMR) algorithm. We used the logistic regression algorithm to construct three models for T2w, T2 FLAIR, and T1c images as well as one combined model. The test cohort was used to evaluate the models, and receiver operating characteristic (ROC) curves, areas under the curve (AUCs), sensitivity, specificity, and accuracy were calculated. The nomogram of the combined model was built and evaluated using a calibration curve. Decision curve analysis (DCA) was used to evaluate the clinical application value of the four models.ResultsA total of 1,316 features were extracted from T2w, T2 FLAIR, and T1c images, respectively. And then the best non-redundant features were selected from the extracted features using the variance method and mRMR. Finally, five features were extracted each from T2w, T2 FLAIR, and T1c images, and 12 features were extracted for the combined model. Four models were established using the optimal features. In the test cohort, the combined model performed the best out of all models. The AUCs of the T2w, T2 FLAIR, T1c, and combined models were 0.73, 0.78, 0.74, and 0.87, respectively, and accuracies were 0.72, 0.76, 0.72, and 0.84, respectively. The ROC curves and DCA showed that the combined model had the highest efficiency and most favorable clinical benefits.ConclusionThe combined radiomics model based on multi-parameter MRI features provided a reliable non-invasive method for the prognostic prediction of midline gliomas.

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“…The majority of studies assessed MRI appearances, with or without CT. Two series (one publication each for H3 K27-altered and H3 G34-mutant gliomas) assessed PET (positron emission tomography) using the amino acid tracer FET (fluorine-18-fluoroethyl-L-tyrosine) [13,15]. Three recent papers assessed the use of MRI radiomics for predicting H3 K27 status [38,46,47].…”

Section: Data Synthesismentioning

confidence: 99%

“…There were notable differences in tumor location depending on the age group studied. The thalami were the most common location in cohorts which either largely or exclusively assessed adult patients [22,25,28,46,48]. In contrast, the brainstem was the most common overall location in studies targeting a pediatric population [10,13,31,51].…”

Section: Tumor Locationmentioning

confidence: 99%

Imaging features associated with H3 K27-altered and H3 G34-mutant gliomas: a narrative systematic review

et al. 2022

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Background Advances in molecular diagnostics accomplished the discovery of two malignant glioma entities harboring alterations in the H3 histone: diffuse midline glioma, H3 K27-altered and diffuse hemispheric glioma, H3 G34-mutant. Radiogenomics research, which aims to correlate tumor imaging features with genotypes, has not comprehensively examined histone-altered gliomas (HAG). The aim of this research was to synthesize the current published data on imaging features associated with HAG. Methods A systematic search was performed in March 2022 using PubMed and the Cochrane Library, identifying studies on the imaging features associated with H3 K27-altered and/or H3 G34-mutant gliomas. Results Forty-seven studies fulfilled the inclusion criteria, the majority on H3 K27-altered gliomas. Just under half (21/47) were case reports or short series, the remainder being diagnostic accuracy studies. Despite heterogeneous methodology, some themes emerged. In particular, enhancement of H3 K27M-altered gliomas is variable and can be less than expected given their highly malignant behavior. Low apparent diffusion coefficient values have been suggested as a biomarker of H3 K27-alteration, but high values do not exclude this genotype. Promising correlations between high relative cerebral blood volume values and H3 K27-alteration require further validation. Limited data on H3 G34-mutant gliomas suggest some morphologic overlap with 1p/19q-codeleted oligodendrogliomas. Conclusions The existing data are limited, especially for H3 G34-mutant gliomas and artificial intelligence techniques. Current evidence indicates that imaging-based predictions of HAG are insufficient to replace histological assessment. In particular, H3 K27-altered gliomas should be considered when occurring in typical midline locations irrespective of enhancement characteristics.

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Exploring MRI Characteristics of Brain Diffuse Midline Gliomas With the H3 K27M Mutation Using Radiomics

Cited by 13 publications

References 35 publications

Multispectral fluorine-19 MRI enables longitudinal and noninvasive monitoring of tumor-associated macrophages

Multispectral fluorine-19 MRI enables longitudinal and noninvasive monitoring of tumor-associated macrophages

Non-Invasive Prediction of Survival Time of Midline Glioma Patients Using Machine Learning on Multiparametric MRI Radiomics Features

Imaging features associated with H3 K27-altered and H3 G34-mutant gliomas: a narrative systematic review

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