Keywords: Tumors (Pre-Treatment), Translational Studies, Treatment response, Survival prediction, Glioblastoma (GBM), Perfusion, Quantitative Imaging

Motivation: Quantitative measurements at baseline, prior to chemoradiation, can inform prognosis and optimal treatment strategies for patients with glioblastoma (GBM), however, such measurements using ASL are currently lacking. 

Goal(s): To investigate ASL measured quantitative perfusion prior to chemoradiation for survival prediction in GBM patients. 

Approach: Twenty-three newly diagnosed GBM patients were enrolled in this prospective IRB-approved study. Baseline scans with ASL and survival information were obtained. 

Results: ASL measured baseline perfusion aids in survival prediction and stratification between groups with long (mean: 717 days) and short (mean: 361 days) survival in GBM. 

Impact: Early and accurate survival stratification by ASL measured perfusion prior to chemoradiation treatment provides valuable opportunities for therapeutic interventions, including personalized and biologically driven radiation treatment planning and strategic discontinuation of traditional treatments for enrollment in promising clinical trials.

Keywords: Tumors (Pre-Treatment), Brain

Motivation: Identifying brain regions where glioblastoma is associated with epilepsy or neurological deficits could help recognize patients with a higher risk of developing neurological symptoms based on MRI.

Goal(s): We aim to correlate clinical and radiological findings to improve diagnostic evaluation of pre-treatment glioblastoma patients.

Approach: MRIs from 557 patients with de-novo glioblastoma were analyzed retrospectively. We used NANO scale to report neurological deficits and analyzed lesion-frequency-maps for identifying deficits-associated regions.

Results: There was a significant correlation between the NANO scale and lesion volume. For each investigated domain with the NANO scale, radiologically correlated brain regions could be identified.

Impact: We showed that MRI examinations of pre-treatment glioblastoma patients can provide clinicians and patients valuable information regarding risk of developing certain neurological deficits and symptoms. Furthermore, NANO scale and epilepsy-status can provide information regarding the characteristics of the tumor lesion.

Keywords: Tumors (Pre-Treatment), Tumor

Motivation: Edema tissue in glioblastoma is not included in surgical resection, even though tumor cells infiltration could be mediated by it.

Goal(s): The aim of the study is to investigate the heterogeneity of edema.

Approach: Clustering analysis within edema is performed on the orientation dispersion index derived from diffusion magnetic resonance imaging. Then, a non-parametric statistical test is carried out to assess the difference between the resulting edema sub-tissues (e.g., clusters).

Results: Two spatially separated clusters are found for all subjects. Statistically significant differences are observed between each couple of resulting clusters.

Impact: Edema is not a healthy tissue and the possibility of identifying sub-tissues within it could aid clinical practice and pre-surgical planning. This study works at single-subject level, allowing the focus on the specific glioblastoma cases.

Keywords: Tumors (Pre-Treatment), DSC & DCE Perfusion, Glioblastoma, PCNSL, dynamic contrast-enhanced, tracer kinetic model

Motivation: The overlapping radiographical features between glioblastoma and primary central nervous system lymphoma (PCNSL) make it difficult to distinguish the two clinically.

Goal(s): This study aimed to compare values of conventional and advanced tracer kinetic models based on dynamic contrast enhanced (DCE)-MRI in differentiating glioblastoma and lymphoma.

Approach: Patients diagnosed as glioblastoma or lymphoma were examined using dynamic contrast-enhanced MRI. Imaging data were analyzed using tracer kinetic models.

Results: Permeability parameters of DP model attained best performance in differential diagnosis, with dominant features comprising significantly higher PS and E in the tumor region of lymphoma than in that of glioblastoma.

Impact: Distributed parameter (DP) model demonstrated excellent performance in differentiating PCNSL and glioblastoma and permeability parameters of advanced tracer kinetic models such as PS and E could be promising imaging biomarkers.

Keywords: Tumors (Pre-Treatment), Tumor, glioblastoma; magnetic resonance imaging; apparent diffusion coefficient; CD8+ T cells

Motivation: Tumor-infiltrating CD8+ T cells play a key role in glioblastoma development, malignant progression, and recurrence.

Goal(s): The aim of the study was to establish nomograms based on the VASARI features of multiparametric MRI to determine the expression levels of CD8+ T cells in patients with glioblastoma.

Approach: 140 patients with glioblastoma confirmed by surgery and pathology were retrospectively analyzed. Patients were divided into high and low CD8 expression groups. The MRI images of patients with glioblastoma were analyzed using the VASARI scoring system.

Results: The features with the greatest predictive power for CD8 expression levels were, cystic, hemorrhage, and ependymal extension.

Impact: The VASARI feature-based nomogram model can shows promise to predict the level of infiltrative CD8 expression in GB tumors noninvasively for earlier tissue diagnosis and more aggressive treatment.

Keywords: Tumors (Pre-Treatment), Brain, Neuro

Motivation: Noninvasive measurement of the MGMT methylation status has great clinical significance for making a tailored treatment plan and prognosis assessment.
 

Goal(s): This study aimed to establish and validate a radiomics nomogram with robust radiomics features from ADC and ISO-CE-T1-weighted images. 

Approach: The radiomics features were selected using LASSO regression. A radiomics nomogram combined radiomics signature and clinical factors were established with multivariate logistic regression analysis.

Results: The radiomics nomogram is a promising method. The Hosmer-Lemeshow test concluded that the radiomics nomogram showed goodness of fit. The decision curve showed that the addition of clinical characteristics to the nomogram showed incremental predictive value.

Impact: The multiparametric MRI-based radiomics nomogram was a promising method to preoperatively predict the MGMT mpromoter ethylation status noninvasively. Besides, the nomogram transformed the prediction signature into a visual and readable graph, making it easier to understand.

Keywords: Tumors (Pre-Treatment), Brain, Glioma, PET/MRI

Motivation: The biological behavior and prognosis between low- and high-grade gliomas (HGG) are different, it is important to preoperatively judge the grading in clinical practice.

Goal(s): Multiple parameters derived from hybrid ¹⁸F-FDG PET/MRI of the solid component and peritumoral zone (PTZ) can potentially improve the accuracy of glioma grading.

Approach: We employed multiparametric simultaneous hybrid ¹⁸F-FDG PET/MRI including PET, ASL, and DWI from the solid component and PTZ of glioma to differentiate HGG from LGG. 

Results: The combination of multiple parameters from hybrid PET/MRI in tumor and PBZ can provide better diagnostic efficacy than a single parameter alone.

Impact: Incorporating multiple tumoral regions into multiparameter from simultaneous 18F-FDG PET/MRI can optimize the workflow efficiency for glioma grading, and aid treatment decision-making to offer appropriate, patient-tailored precision medicine, and reduce the risk of unnecessary or inappropriate treatments.

Keywords: Tumors (Pre-Treatment), DSC & DCE Perfusion, Telomerase reverse transcriptase

Motivation: This study aims to predict the TERTp mutation status noninvasively before surgery, which is crucial for determining treatment strategies and prognosis in GBM patients.

Goal(s): Investigate the predictive value of DCE-MRI and IVIM for TERTp mutation status in GBM patients.

Approach: 68 GBM patients were enrolled according to the 2021 WHO classification, and divided into TERTp mutant group and TERTp wild group. Compare DCE-MRI and IVIM parameters between the two groups.

Results: The DCE-MRI parameter Vp was significantly higher in the TERTp mutation group (AUC=0.708), indicating its potential as a predictor for TERTp mutation status.

Impact: This study suggests that Vp, a DCE-MRI parameter, can predict TERTp mutation status noninvasively. This has important implications for targeted therapy and prognosis prediction in GBM patients.

Keywords: Tumors (Pre-Treatment), Brain, Blood vessels

Motivation: Echo planar based SWI (SWI-EPI) can provide better contrast of vasculature and higher spatial resolution compared to SWI and at shorter acquisition time. However, its potential in glioma grading has not been explored well.

Goal(s): To evaluate the potential of SWI-EPI for automatic segmentation and quantification of tumor vasculature for glioma grading.

Approach: Tumor vasculature for both SWI and SWI-EPI images were segmented and quantified. T-test and ROC curve  analysis was used to determine statistical significance and grading accuracy.

Results: Tumor vasculature features automatically computed from SWI-EPI provided improved glioma grading accuracy compared to conventional SWI based features.

Impact: SWI-EPI offers advantages over SWI images in terms of image resolution and shorter acquistion time. It was found to have improved glioma grading accuracy and has the potential to be used as a routine imaging sequence in clinical settings.

Keywords: Tumors (Pre-Treatment), Tumor, MRS

Motivation: challenges emerge at ultra-high fields when measuring metabolites using ¹H-MRS. 

Goal(s): To investigate how well the high SNR and high bandwidth spin echo (HISE) technique performs at 5.0T for detecting target metabolites in brain tumors.

Approach: 26 Subjects suspected of having brain tumors were enrolled. HISE and point-resolved spectroscopy (PRESS) single-voxel spectroscopy (SVS) scans were collected with a 5.0T clinical scanner with an intermediate echo time (TE=144ms).

Results: HISE outperformed the clinical standard PRESS technique in detecting target metabolites of brain tumors at 5.0T, particularly Lac and Ala.

Impact: In a recently developed whole-body 5.0T clinical scanner, the HISE technique has been demonstrated to be more preferable than PRESS for the clinical diagnosis of brain tumors. 

Keywords: Tumors (Pre-Treatment), Diffusion/other diffusion imaging techniques

Motivation: Time-diffusion-dependent diffusion MRI (t-dMRI)provides quantitative imaging of cellular microstructure; however, its value in diagnosing molecular subtypes of IDH in gliomas remains unknown.<stork-writing-assistant></stork-writing-assistant><stork-writing-assistant></stork-writing-assistant>

Goal(s): Molecular subtypes of IDH were diagnosed using quantitative time-dependent diffusion imaging parameters.<stork-writing-assistant></stork-writing-assistant><stork-writing-assistant></stork-writing-assistant>

Approach: t-dMRI was acquired using OGSE and PGSE sequences, and quantitative parameters were then fitted using the Imaging Microstructural Parameters Using Limited spectrally edited diffusion(IMPULSED) method and evaluated for diagnostic potency for molecular subtypes of IDH in gliomas. <stork-writing-assistant></stork-writing-assistant><stork-writing-assistant></stork-writing-assistant>

Results: t-dMRI can identify IDH genotypes, and intracellular fraction (fin) reflects the actual state of tumor cells.<stork-writing-assistant></stork-writing-assistant><stork-writing-assistant></stork-writing-assistant>

Impact: t-dMRI can non-invasively identify IDH genotype.<stork-writing-assistant></stork-writing-assistant><stork-writing-assistant></stork-writing-assistant>

Keywords: Tumors (Pre-Treatment), DSC & DCE Perfusion

Motivation: To evaluate dynamic contrast enhanced (DCE) MRI for assessing heterogeneity in glioma IDH genotyping and derive a combined map.
 

Goal(s): To predict specific tumor areas and to guide biopsy and precision molecular typing therapy. 

Approach: Whole tumor volumes were delineated on DCE images, and voxel-wise clustering of each quantitative imaging map identified five combined physiologic MRI habitats.

Results: DCE-Ktrans within necrosis subregion (mask1) emerged as the best parameter to identify IDH status (AUC=0.824, p＜0.001), while DCE-Ktrans within mild reinforcement region (mask 2) was positively correlated with Ki-67(r=0.473, p=0.001) and DCE-Ve of middle reinforcement (mask 4) was positively correlated with microvessel density (MVD)(r=-0.549, p＜0.001).

Impact: Based on the habitat analysis of MR perfusion imaging, glioma was divided into different sub-regions, which reflected biological information such as necrosis, hypoxia, and angiogenesis, predicted molecular classification and guided clinical biopsy or surgical sampling accurately to guide precision therapy.

Keywords: Tumors (Pre-Treatment), MR-Guided Interventions, Glioma, Ki67, transmembrane water-efflux rate, Aquaporins4.

Motivation: Cell proliferation abnormalities (e.g., Ki67 status) are key features of glioma. Conventional biopsy is used to characterize Ki67 expression levels in vivo, but it lacks spatial and temporal information because of intratumorally heterogeneity.

Goal(s): To identify MRI parameters representing the intracellular water-efflux rate regulated by aquaporin-4, a noninvasive biomarker sensitive to Ki67 quantitative expression, in glioma.

Approach: Human tumors, animal models, and cell lines were investigated by water-exchange DCE-MRI and immunohistochemistry.

Results: Ki67 and transmembrane water-efflux rate showed a strong linear relationship. The underlying mechanism was the close symbiotic expression pattern between aquaporin-4 and Ki67.

Impact: Transmembrane water-efflux rate is a sensitive biomarker of Ki67 because rapidly growing cells upregulate aquaporin-4 expression for enhanced transmembrane transport.

Keywords: Tumors (Pre-Treatment), Arterial spin labelling

Motivation: Blood brain barrier arterial spin labeling (BBB-ASL) could assess BBB integrity. However, the assumption of homogeneous T2 in data fitting might be broken in gliomas.

Goal(s):  To evaluate the BBB integrity in gliomas with regional tissue-specific T2.

Approach: A mono-exponential T2 fitting was used to obtain tissue-specific T2 values to estimate time of water exchange (Tex) and perfusion (CBF) in the tumor, normal-appearing white (NAWM), and gray matter (NAGM) using ExploreASL.

Results: Higher Tex in NAWM, and lower Tex in the tumor and NAGM were observed and the tumor heterogeneity was better depicted when tissue-specific T2 values were used.

Impact:  Water exchange and perfusion maps are highly affected by the tissue T2 value used in BBB-ASL data processing. Applying tissue-specific T2 correction has resulted in a more reliable evaluation of BBB integrity in gliomas. 

Keywords: Tumors (Pre-Treatment), Tumor, Glioma; Amide proton transfer imaging; apparent diffusion coefficient; Gene

Motivation: To the best of our knowledge, no study has explored the predictive ability of APT for ATRX mutations in gliomas.

Goal(s): Investigating APT and ADC's predictive capacities for ATRX mutations in WHO grade 2/3 gliomas with IDH mutations, we conducted a retrospective analysis.

Approach: We retrospectively analyzed data from these patients and extracted features for modeling.

Results: The results revealed the APT-median became the key diagnostic parameter, and the model developed showed the highest diagnostic efficiency. The histogram analysis method based on APT and ADC is an effective non-invasive tool for predicting ATRX gene status.

Impact: Our study, to our knowledge, pioneered the use of APT in predicting ATRX mutations in gliomas and established histogram analysis of APT and ADC as an effective non-invasive tool for ATRX gene prediction in IDH mutant WHO grade 2/3 gliomas.

Keywords: Tumors (Pre-Treatment), Tumor, Glioma, Glioblastoma

Motivation: Non-invasive prediction of GBM’s pMGMT methylation status is still challenging despite recent advancements of image analysis. 

Goal(s): This study explored a clinically feasible imaging biomarker that represents GBM’s pMGMT methylation status with external validation. 

Approach: Two qualitative imaging features, namely the “Thickened structure” and the “Methylated contrast phenotype,” were identified as valuable to this means. 

Results: GBMs presenting both imaging features exhibited a significantly high odds ratio, favoring pMGMT methylation in the exploratory and validation cohorts with a sensitivity and specificity of approximately 0.3-0.4 and 0.8. The easy clinical application of the proposed imaging features is expected to facilitate better preoperative GBM characterization. 
 

Impact: GBMs presenting both imaging features, namely the “Thickened structure” and the “Methylated contrast phenotype,” exhibited a significantly high odds ratio, favoring pMGMT methylation in the exploratory and validation cohorts with a sensitivity and specificity of approximately 0.3-0.4 and 0.8.