Advanced<scp>MR</scp>Techniques for Preoperative Glioma Characterization: Part 2

Hangel, Gilbert; Schmitz-Abecassis, Bárbara; Sollmann, Nico; Pinto, Joana; Arzanforoosh, Fatemehsadat; Barkhof, Frederik; Booth, Thomas C.; Calvo-Imirizaldu, Marta; Cassia, Guilherme de Souza e; Chmelík, Marek; Clement, Patricia; Ercan, Ece; Fernández‐Seara, María A.; Furtner, Julia; Fuster–Garcia, Elies; Grech‐Sollars, Matthew; Hatay, Gokce Hale; Karami, Golestan; Keil, Vera C.; Kim, Mina; Koekkoek, Johan A F; Kukran, Simran; Mancini, Laura; Nechifor, Ruben Emanuel; Özcan, Alpay; Öztürk-Işık, Esin; Pişkin, Şenol; Schmainda, Kathleen M.; Svensson, Siri Fløgstad; Tseng, Chih-Hsien; Unnikrishnan, Saritha; Vos, Frans M.; Warnert, Esther; Zhao, Mengjing; Jancalek, Radim; Nunes, Teresa; Hirschler, Lydiane; Smits, Marion; Petr, Jan; Emblem, Kyrre E.

doi:10.1002/jmri.28663

Cited by 17 publications

(11 citation statements)

References 121 publications

(312 reference statements)

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“…First, despite the high sensitivity and specificity of our predictive model, challenges arise in interpreting and generalizing the results due to the lack of validation from other centers and the variability of imaging data obtained from different scanning devices. Additionally, advanced techniques such as amide proton transfer (Xu et al., 2021 ), diffusion kurtosis imaging (Hempel et al., 2021 ), and arterial spin labeling (Brendle et al., 2018 ; Hangel et al., 2023 ) have demonstrated promising potential in providing valuable metabolic or functional insights into tumors, respectively. These sequences offer distinctive perspectives on tumor biology that can complement conventional anatomical imaging modalities.…”

Section: Discussionmentioning

confidence: 99%

A radiomics‐based nomogram may be useful for predicting telomerase reverse transcriptase promoter mutation status in adult glioblastoma

Li,

Chen,

Huang

et al. 2024

Brain and Behavior

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Background and purposeAs a crucial diagnostic and prognostic biomarker, telomerase reverse transcriptase (TERT) promoter mutation holds immense significance for personalized treatment of patients with glioblastoma (GBM). In this study, we developed a radiomics nomogram to determine the TERT promoter mutation status and assessed its prognostic efficacy in GBM patients.MethodsThe study retrospectively included 145 GBM patients. A comprehensive set of 3736 radiomics features was extracted from preoperative magnetic resonance imaging, including T2‐weighted imaging, T1‐weighted imaging (T1WI), contrast‐enhanced T1WI, and fluid‐attenuated inversion recovery. The construction of the radiomics model was based on integrating the radiomics signature (rad‐score)with clinical features. Receiver‐operating characteristic curve analysis was employed to evaluate the discriminative ability of the prediction model, and the risk score was used to stratify patient outcomes.ResultsThe least absolute shrinkage and selection operator classifier identified 10 robust features for constructing the prediction model, and the radiomics nomogram exhibited excellent performance in predicting TERT promoter mutation status, with area under the curve values of.906 (95% confidence interval [CI]:.850–.963) and.899 (95% CI:.708–.966) in the training and validation sets, respectively. The clinical utility of the radiomics nomogram is further supported by calibration curve and decision curve analyses. Additionally, the radiomics nomogram effectively stratified GBM patients with significantly different prognoses (HR = 1.767, p = .019).ConclusionThe radiomics nomogram holds promise as a modality for evaluating TERT promoter mutations and prognostic outcomes in patients with GBM.

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Section: Discussionmentioning

confidence: 99%

A radiomics‐based nomogram may be useful for predicting telomerase reverse transcriptase promoter mutation status in adult glioblastoma

Li,

Chen,

Huang

et al. 2024

Brain and Behavior

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“…Due to the significant overlap of the cohorts of these studies, this primarily indicates the consistency of our data evaluation and processing when compared to our 2020 paper, but to further support our hypothesis that these metabolites may be useful biomarkers, further studies including larger cohorts are required [ 6 ]. In addition, increases in tCho/tNAA have been commonly reported in the literature [ 32 , 33 ].…”

Section: Discussionmentioning

confidence: 99%

A Comparison of 7 Tesla MR Spectroscopic Imaging and 3 Tesla MR Fingerprinting for Tumor Localization in Glioma Patients

Lazen,

Lima Cardoso,

Sharma

et al. 2024

Cancers

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This paper investigated the correlation between magnetic resonance spectroscopic imaging (MRSI) and magnetic resonance fingerprinting (MRF) in glioma patients by comparing neuro-oncological markers obtained from MRSI to T1/T2 maps from MRF. Data from 12 consenting patients with gliomas were analyzed by defining hotspots for T1, T2, and various metabolic ratios, and comparing them using Sørensen–Dice similarity coefficients (DSCs) and the distances between their centers of intensity (COIDs). The median DSCs between MRF and the tumor segmentation were 0.73 (T1) and 0.79 (T2). The DSCs between MRSI and MRF were the highest for Gln/tNAA (T1: 0.75, T2: 0.80, tumor: 0.78), followed by Gly/tNAA (T1: 0.57, T2: 0.62, tumor: 0.54) and tCho/tNAA (T1: 0.61, T2: 0.58, tumor: 0.45). The median values in the tumor hotspot were T1 = 1724 ms, T2 = 86 ms, Gln/tNAA = 0.61, Gly/tNAA = 0.28, Ins/tNAA = 1.15, and tCho/tNAA = 0.48, and, in the peritumoral region, were T1 = 1756 ms, T2 = 102 ms, Gln/tNAA = 0.38, Gly/tNAA = 0.20, Ins/tNAA = 1.06, and tCho/tNAA = 0.38, and, in the NAWM, were T1 = 950 ms, T2 = 43 ms, Gln/tNAA = 0.16, Gly/tNAA = 0.07, Ins/tNAA = 0.54, and tCho/tNAA = 0.20. The results of this study constitute the first comparison of 7T MRSI and 3T MRF, showing a good correspondence between these methods.

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“…However, some experts have suggested that the clinical adoption of DSC‐derived biomarkers is restricted because of a lack of standardization, which may account for the variations in reported rCBV and rCBF thresholds. Nonetheless, recent studies have demonstrated the exceptional reproducibility, consistency across different sites, and commercial availability of carefully curated DSC quantification protocols, 40 indicating a high level of technological readiness for this technique 41 . The adoption of standardized protocols by the MR community will enhance the reliability of the DSC‐derived biomarkers and their suitability for clinical use.…”

Section: Discussionmentioning

confidence: 99%

“…Nonetheless, recent studies have demonstrated the exceptional reproducibility, consistency across different sites, and commercial availability of carefully curated DSC quantification protocols, 40 indicating a high level of technological readiness for this technique. 41 The adoption of standardized protocols by the MR community will enhance the reliability of the DSC-derived biomarkers and their suitability for clinical use.…”

Section: Discussionmentioning

confidence: 99%

Vascular differences between IDH‐wildtype glioblastoma and astrocytoma IDH‐mutant grade 4 at imaging and transcriptomic levels

et al. 2023

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Global agreement in central nervous system (CNS) tumor classification is essential for predicting patient prognosis and determining the correct course of treatment, as well as for stratifying patients for clinical trials at international level. The last update by the World Health Organization of CNS tumor classification and grading in 2021 considered, for the first time, IDH‐wildtype glioblastoma and astrocytoma IDH‐mutant grade 4 as different tumors. Mutations in the genes isocitrate dehydrogenase (IDH) 1 and 2 occur early and, importantly, contribute to gliomagenesis. IDH mutation produces a metabolic reprogramming of tumor cells, thus affecting the processes of hypoxia and vascularity, resulting in a clear advantage for those patients who present with IDH‐mutated astrocytomas. Despite the clinical relevance of IDH mutation, current protocols do not include full sequencing for every patient. Alternative biomarkers could be useful and complementary to obtain a more reliable classification. In this sense, magnetic resonance imaging (MRI)‐perfusion biomarkers, such as relative cerebral blood volume and flow, could be useful from the moment of presurgery, without incurring additional financial costs or requiring extra effort. The main purpose of this work is to analyze the vascular and hemodynamic differences between IDH‐wildtype glioblastoma and IDH‐mutant astrocytoma. To achieve this, we evaluate and validate the association between dynamic susceptibility contrast‐MRI perfusion biomarkers and IDH mutation status. In addition, to gain a deeper understanding of the vascular differences in astrocytomas depending on the IDH mutation, we analyze the transcriptomic bases of the vascular differences.

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AdvancedMRTechniques for Preoperative Glioma Characterization: Part 2

Cited by 17 publications

References 121 publications

A radiomics‐based nomogram may be useful for predicting telomerase reverse transcriptase promoter mutation status in adult glioblastoma

A radiomics‐based nomogram may be useful for predicting telomerase reverse transcriptase promoter mutation status in adult glioblastoma

A Comparison of 7 Tesla MR Spectroscopic Imaging and 3 Tesla MR Fingerprinting for Tumor Localization in Glioma Patients

Vascular differences between IDH‐wildtype glioblastoma and astrocytoma IDH‐mutant grade 4 at imaging and transcriptomic levels

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