Treatment Response and Prognosis Evaluation in High-Grade Glioma: An Imaging Review Based on MRI

Progression/Recurrence of Meningioma: An Imaging Review Based on Magnetic Resonance Imaging

Meningiomas are the most common primary central nervous system tumors. The preferred treatment is maximum safe resection, and the heterogeneity of meningiomas results in a variable prognosis. Progression/recurrence (P/R) can occur at any grade of meningioma and is a common adverse outcome after surgical treatment and a major cause of postoperative rehospitalization, secondary surgery, and mortality. Early prediction of P/R plays an important role in postoperative management, further adjuvant therapy, and follow-up of patients. Therefore, it is essential to thoroughly analyze the heterogeneity of meningiomas and predict postoperative P/R with the aid of noninvasive preoperative imaging. In recent years, the development of advanced magnetic resonance imaging technology and machine learning has provided new insights into noninvasive preoperative prediction of meningioma P/R, which helps to achieve accurate prediction of meningioma P/R. This narrative review summarizes the current research on conventional magnetic resonance imaging, functional magnetic resonance imaging, and machine learning in predicting meningioma P/R. We further explore the significance of tumor microenvironment in meningioma P/R, linking imaging features with tumor microenvironment to comprehensively reveal tumor heterogeneity and provide new ideas for future research.

Advancements in Image-Based Models for High-Grade Gliomas Might Be Accelerated

The first half of 2022 saw the publication of several major research advances in image-based models and artificial intelligence applications to optimize treatment strategies for high-grade gliomas, the deadliest brain tumors. We review them and discuss the barriers that delay their entry into clinical practice; particularly, the small sample size and the heterogeneity of the study designs and methodologies used. We will also write about the poor and late palliation that patients suffering from high-grade glioma can count on at the end of life, as well as the current legislative instruments, with particular reference to Italy. We suggest measures to accelerate the gradual progress in image-based models and end of life care for patients with high-grade glioma.

Cerebrospinal Fluid Liquid Biopsies in the Evaluation of Adult Gliomas

PURPOSE OF REVIEW

This review aims to discuss recent research regarding the biomolecules explored in liquid biopsies and their potential clinical uses for adult-type diffuse gliomas.

RECENT FINDINGS

Evaluation of tumor biomolecules via cerebrospinal fluid (CSF) is an emerging technology in neuro-oncology. Studies to date have already identified various circulating tumor DNA, extracellular vesicle, micro-messenger RNA and protein biomarkers of interest. These biomarkers show potential to assist in multiple avenues of central nervous system (CNS) tumor evaluation, including tumor differentiation and diagnosis, treatment selection, response assessment, detection of tumor progression, and prognosis. In addition, CSF liquid biopsies have the potential to better characterize tumor heterogeneity compared to conventional tissue collection and CNS imaging. Current imaging modalities are not sufficient to establish a definitive glioma diagnosis and repeated tissue sampling via conventional biopsy is risky, therefore, there is a great need to improve non-invasive and minimally invasive sampling methods. CSF liquid biopsies represent a promising, minimally invasive adjunct to current approaches which can provide diagnostic and prognostic information as well as aid in response assessment.

Utility of 1.5 Tesla MRI Scanner in the Management of Small Sample Sizes Driven from 3D Breast Cell Culture

The aim of this work was to use and optimize a 1.5 Tesla magnetic resonance imaging (MRI) system for three-dimensional (3D) images of small samples obtained from breast cell cultures in vitro. The basis of this study was to design MRI equipment to enable imaging of MCF-7 breast cancer cell cultures (about 1 million cells) in 1.5 and 2 mL glass tubes and/or bioreactors with an external diameter of less than 20 mm. Additionally, the development of software to calculate longitudinal and transverse relaxation times is described. Imaging tests were performed using a clinical MRI scanner OPTIMA 360 manufactured by GEMS. Due to the size of the tested objects, it was necessary to design additional receiving circuits allowing for the study of MCF-7 cell cultures placed in glass bioreactors. The examined sample's volume did not exceed 2.0 mL nor did the number of cells exceed 1 million. This work also included a modification of the sequence to allow for the analysis of T1 and T2 relaxation times. The analysis was performed using the MATLAB package (produced by MathWorks). The created application is based on medical MR images saved in the DICOM3.0 standard which ensures that the data analyzed are reliable and unchangeable in an unintentional manner that could affect the measurement results. The possibility of using 1.5 T MRI systems for cell culture research providing quantitative information from in vitro studies was realized. The scanning resolution for FOV = 5 cm and the matrix was achieved at a level of resolution of less than 0.1 mm/pixel. Receiving elements were built allowing for the acquisition of data for MRI image reconstruction confirmed by images of a phantom with a known structure and geometry. Magnetic resonance sequences were modified for the saturation recovery (SR) method, the purpose of which was to determine relaxation times. An application in MATLAB was developed that allows for the analysis of T1 and T2 relaxation times. The relaxation times of cell cultures were determined over a 6-week period. In the first week, the T1 time value was 1100 ± 40 ms, which decreased to 673 ± 59 ms by the sixth week. For T2, the results were 171 ± 10 ms and 128 ± 12 ms, respectively.

Post-treatment imaging of gliomas: challenging the existing dogmas

Gliomas are the commonest malignant central nervous system tumours in adults and imaging is the cornerstone of diagnosis, treatment, and post-treatment follow-up of these patients. With the ever-evolving treatment strategies post-treatment imaging and interpretation in glioma remains challenging, more so with the advent of anti-angiogenic drugs and immunotherapy, which can significantly alter the appearance in this setting, thus making interpretation of routine imaging findings such as contrast enhancement, oedema, and mass effect difficult to interpret. This review details the various methods of management of glioma including the upcoming novel therapies and their impact on imaging findings, with a comprehensive description of the imaging findings in conventional and advanced imaging techniques. A systematic appraisal for the existing and emerging techniques of imaging in these settings and their clinical application including various response assessment guidelines and artificial intelligence based response assessment will also be discussed.

Tumor Multiregional Mean Apparent Propagator (MAP) Features in Evaluating Gliomas-A Comparative Study With Diffusion Kurtosis Imaging (DKI)

BACKGROUND

Glioma classification affects treatment and prognosis. Reliable imaging methods for preoperatively evaluating gliomas are essential.

PURPOSE

To evaluate tumor multiregional mean apparent propagator (MAP) features in glioma diagnosis and to compare those with diffusion-kurtosis imaging (DKI).

STUDY TYPE

Retrospective study.

SUBJECTS

70 untreated glioma patients (31 LGGs (low-grade gliomas), 34 women; mean age, 47 ± 12 years, training (60%, n = 42) and testing cohorts (40%, n = 28)).

FIELD STRENGTH/SEQUENCE

3-T, diffusion-MRI using q-space Cartesian grid sampling with 11 different b-values.

ASSESSMENT

Tumor multiregional MAP (mean squared displacement (MSD); q-space inverse variance (QIV); non-Gaussianity (NG); axial/radial non-Gaussianity (NGAx, NGRad); return-to-origin/axis/plane probability (RTOP, RTAP, and RTPP)); and DKI metrics (axial/mean/radial kurtosis (AK, MK, and RK)) on tumor parenchyma (TP) and peritumoral areas (PT) in histopathologically gliomas grading and genotyping were assessed.

STATISTICAL TESTS

Mann-Whitney U; Kruskal-Wallis; Benjamini-Hochberg; Bonferroni-correction; receiver operating curve (ROC) and area under curve (AUC); DeLong's test; Random Forest (RF). P value<0.05 was considered statistically significant after multiple comparisons correction.

RESULTS

Compared with LGGs, MSD, and QIV were significantly lower in TP, whereas NG, NGAx, NGRad, RTOP, RTAP, RTPP, and DKI metrics were significantly higher in HGGs (high-grade gliomas) (P ≤ 0.007), as well as in isocitrate-dehydrogenase (IDH)-mutated than IDH-wildtype gliomas (P ≤ 0.039). These trends were reversed for PT (tumor grades, P ≤ 0.011; IDH-mutation status, P ≤ 0.012). ROC analysis showed that, in TP, DKI metrics performed best in TP (AUC 0.83), whereas in PT, RTPP performed best (AUC 0.77) in glioma grading. AK performed best in TP (AUC 0.77), whereas MSD and RTPP performed best in PT (AUC 0.73) in IDH genotyping. Further RF analysis with DKI and MAP demonstrated good performance in grading (AUC 0.91, Accuracy 82%) and IDH genotyping (AUC 0.87, Accuracy 79%).

DATA CONCLUSION

Tumor multiregional MAP features could effectively evaluate gliomas. The performance of MAP may be similar to DKI in TP, while in PT, MAP may outperform DKI.

LEVEL OF EVIDENCE

4 TECHNICAL EFFICACY: Stage 2.

Diagnostic Accuracy of PET with 18F-Fluciclovine ([18F]FACBC) in Detecting High-Grade Gliomas: A Systematic Review and Meta-Analysis

BACKGROUND

18F-Fluciclovine ([18F]FACBC) has been recently proposed as a synthetic radiolabeled amino acid for positron emission tomography (PET) imaging in patients with brain neoplasms. Our aim is to evaluate the diagnostic performance of [18F]FACBC PET in high-grade glioma (HGG) patients, taking into account the literature data.

METHODS

A comprehensive literature search was performed. We included original articles evaluating [18F]FACBC PET in the detection of HGG before therapy and for the suspicion of tumor recurrence. Pooled sensitivity, specificity, positive and negative likelihood ratios (LR+ and LR-), and diagnostic odds ratios (DOR), including 95% confidence intervals (95% CI), were measured. Statistical heterogeneity and publication bias were also assessed.

RESULTS

ten studies were included in the review and eight in the meta-analysis (113 patients). Regarding the identification of HGG, the sensitivity of [18F]FACBC PET ranged between 85.7% and 100%, with a pooled estimate of 92.9% (95% CI: 84.4-96.9%), while the specificity ranged from 50% to 100%, with a pooled estimate of 70.7% (95% CI: 47.5-86.5%). The pooled LR+, LR-, and DOR of [18F]FACBC PET were 2.5, 0.14, and 37, respectively. No significant statistical heterogeneity or publication bias were found.

CONCLUSIONS

evidence-based data demonstrate the good diagnostic accuracy of [18F]FACBC PET for HGG detection. Due to the still limited data, further studies are warranted to confirm the promising role of [18F]FACBC PET in this context.

TXNDC12 knockdown promotes ferroptosis by modulating SLC7A11 expression in glioma

Ferroptosis is an iron-dependent cell death process mainly triggered by reactive oxygen species (ROS) and lipid peroxidation. Thioredoxin domain protein 12 (TXNDC12) promotes the development of some tumors; however, its function in tumor ferroptosis remains unclear. In this study, we found that knockdown of TXNDC12 promoted erastin-induced increase in ROS, lipid peroxidation, and Fe2+ levels, and decreased glutathione content. TXNDC12 is involved in ferroptosis by regulating SLC7A11. Further studies showed that TXNDC12 knockdown promoted an erastin-induced decrease in glioma cell viability. Overall, TXNDC12 played a significant role in ferroptosis by modulating SLC7A11 expression. Thus, TXNDC12 and ferroptosis may provide new targets for the treatment of gliomas.

Differential Susceptibility of Ex Vivo Primary Glioblastoma Tumors to Oncolytic Effect of Modified Zika Virus

Glioblastoma (GBM), the most common primary malignant brain tumor, is a highly lethal form of cancer with a very limited set of treatment options. High heterogeneity in the tumor cell population and the invasive nature of these cells decrease the likely efficacy of traditional cancer treatments, thus requiring research into novel treatment options. The use of oncolytic viruses as potential therapeutics has been researched for some time. Zika virus (ZIKV) has demonstrated oncotropism and oncolytic effects on GBM stem cells (GSCs). To address the need for safe and effective GBM treatments, we designed an attenuated ZIKV strain (ZOL-1) that does not cause paralytic or neurological diseases in mouse models compared with unmodified ZIKV. Importantly, we found that patient-derived GBM tumors exhibited susceptibility (responders) and non-susceptibility (non-responders) to ZOL-1-mediated tumor cell killing, as evidenced by differential apoptotic cell death and cell viability upon ZOL-1 treatment. The oncolytic effect observed in responder cells was seen both in vitro in neurosphere models and in vivo upon xenograft. Finally, we observed that the use of ZOL-1 as combination therapy with multiple PI3K-AKT inhibitors in non-responder GBM resulted in enhanced chemotherapeutic efficacy. Altogether, this study establishes ZOL-1 as a safe and effective treatment against GBM and provides a foundation to conduct further studies evaluating its potential as an effective adjuvant with other chemotherapies and kinase inhibitors.

Preoperative Systemic Immune-Inflammation Index is a Potential Biomarker in Adult Patients with High-Grade Gliomas Undergoing Radical Resection

Background

Increasing evidence has highlighted that systemic immune-inflammation index (SII), a recently developed prognostic biomarker that utilizes peripheral platelet, lymphocyte and neutrophil counts, is associated with unfavorable prognosis in various tumors. Nevertheless, the prognostic significance of SII in high-grade gliomas patients undergoing radical resection remains unclear. Therefore, the present study aimed to assess the potential of SII as a prognostic biomarker in this patient population.

Methods

A total of 111 adult patients with high-grade gliomas who underwent radical resection were consecutively enrolled in this investigation. The study involved the categorization of patients into high and low SII groups using predetermined cut-off values. Subsequently, forward stepwise logistic regression was employed to identify autonomous predictors for early gliomas recurrence. To mitigate the impact of confounding factors, a propensity score matching (PSM) analysis was performed between high and low SII patients. Finally, the Kaplan-Meier approach was utilized to compare the progression-free survival (PFS) and overall survival (OS) of the two groups.

Results

The study involved the categorization of patients into two groups based on their SII levels, namely high SII (> 604.8) and low SII (≤ 604.8) groups. Forward stepwise logistic regression revealed that high SII (p < 0.001) and tumor size ≥ 50 mm (p < 0.001) were significantly related to early recurrence of gliomas. Furthermore, the results indicate that PFS and OS were significantly shorter in the high SII group compared to the low SII group, both before and after PSM (p < 0.05).

Conclusion

Preoperative biomarker SII can serve as a prognostic biomarker for early recurrence and prognosis in patients with high-grade gliomas undergoing radical resection. Furthermore, the combination of tumor size and SII demonstrates a robust predictive capacity for early recurrence and prognosis in this patient population.

Performance of deep learning algorithms to distinguish high-grade glioma from low-grade glioma: A systematic review and meta-analysis

This study aims to evaluate deep learning (DL) performance in differentiating low- and high-grade glioma. Search online database for studies continuously published from 1st January 2015 until 16th August 2022. The random-effects model was used for synthesis, based on pooled sensitivity (SE), specificity (SP), and area under the curve (AUC). Heterogeneity was estimated using the Higgins inconsistency index (I²). 33 were ultimately included in the meta-analysis. The overall pooled SE and SP were 94% and 93%, with an AUC of 0.98. There was great heterogeneity in this field. Our evidence-based study shows DL achieves high accuracy in glioma grading. Subgroup analysis reveals several limitations in this field: 1) Diagnostic trials require standard method for data merging for AI; 2) small sample size; 3) poor-quality image preprocessing; 4) not standard algorithm development; 5) not standard data report; 6) different definition of HGG and LGG; and 7) poor extrapolation.

Multiple Cell Cultures for MRI Analysis

Magnetic resonance imaging (MRI) is an imaging method that enables diagnostics. In recent years, this technique has been widely used for research using cell cultures used in pharmaceutical science to understand the distribution of various drugs in a variety of biological samples, from cellular models to tissues. MRI's dynamic development in recent years, in addition to diagnostics, has allowed the method to be implemented to assess response to applied therapies. Conventional MRI imaging provides anatomical and pathological information. Due to advanced technology, MRI provides physiological information. The use of cell cultures is very important in the process of testing new synthesized drugs, cancer research, and stem cell research, among others. Two-dimensional (2D) cell cultures conducted under laboratory conditions, although they provide a lot of information, do not reflect the basic characteristics of the tumor. To replicate the tumor microenvironment in science, a three-dimensional (3D) culture of tumor cells was developed. This makes it possible to reproduce in vivo conditions where, in addition, there is a complex and dynamic process of cell-to-cell communication and cell-matrix interaction. In this work, we reviewed current research in 2D and 3D cultures and their use in MRI studies. Articles for each section were collected from PubMed, ScienceDirect, Web of Science, and Google Scholar.

Tumor-derived small extracellular vesicles: potential roles and mechanism in glioma

Small extracellular vesicles (SEVs) are extracellular vesicles containing DNA, RNA, and proteins and are involved in intercellular communication and function, playing an essential role in the growth and metastasis of tumors. SEVs are present in various body fluids and can be isolated and extracted from blood, urine, and cerebrospinal fluid. Under both physiological and pathological conditions, SEVs can be released by some cells, such as immune, stem, and tumor cells, in a cytosolic manner. SEVs secreted by tumor cells are called tumor-derived exosomes (TEXs) because of their origin in the corresponding parent cells. Glioma is the most common intracranial tumor, accounting for approximately half of the primary intracranial tumors, and is characterized by insidious onset, high morbidity, and high mortality rate. Complete removal of tumor tissues by surgery is difficult. Chemotherapy can improve the survival quality of patients to a certain extent; however, gliomas are prone to chemoresistance, which seriously affects the prognosis of patients. In recent years, TEXs have played a vital role in the occurrence, development, associated immune response, chemotherapy resistance, radiation therapy resistance, and metastasis of glioma. This article reviews the role of TEXs in glioma progression, drug resistance, and clinical diagnosis.

PSMA Radioligand Uptake as a Biomarker of Neoangiogenesis in Solid Tumours: Diagnostic or Theragnostic Factor?

Due to its overexpression on the surface of prostate cancer cells, prostate-specific membrane antigen (PSMA) is a relatively novel effective target for molecular imaging and radioligand therapy (RLT) in prostate cancer. Recent studies reported that PSMA is expressed in the neovasculature of various types of cancer and regulates tumour cell invasion as well as tumour angiogenesis. Several authors explored the role of diagnostic and therapeutic PSMA radioligands in various malignancies. In this narrative review, we describe the current status of the literature on PSMA radioligands' application in solid tumours other than prostate cancer to explore their potential role as diagnostic or therapeutic agents, with particular regard to the relevance of PSMA radioligand uptake as neoangiogenetic biomarker. Hence, a comprehensive review of the literature was performed to find relevant articles on the applications of PSMA radioligands in non-prostate solid tumours. Data on the general, methodological and clinical aspects of all included studies were collected. Forty full-text papers were selected for final review, 8 of which explored PSMA radioligand PET/CT performances in gliomas, 3 in salivary gland malignancies, 6 in thyroid cancer, 2 in breast cancer, 16 in renal cell carcinoma and 5 in hepatocellular carcinoma. In the included studies, PSMA radioligand PET showed promising performance in patients with non-prostate solid tumours. Further studies are needed to better define its potential role in oncological patients management, especially in those undergoing antineoangiogenic therapies, and to assess the efficacy of PSMA-RLT in this clinical context.

Diagnostic Accuracy of PET/CT or PET/MRI Using PSMA-Targeting Radiopharmaceuticals in High-Grade Gliomas: A Systematic Review and a Bivariate Meta-Analysis

Background: Several studies proposed the use of positron emission tomography (PET) with Prostate Specific Membrane Antigen (PSMA)-targeting radiopharmaceuticals in brain tumors. Our aim is to calculate the diagnostic accuracy of these methods in high-grade gliomas (HGG) with a bivariate meta-analysis. Methods: A comprehensive literature search of studies on the diagnostic accuracy of PET/CT or PET/MRI with PSMA-targeting radiopharmaceuticals in HGG was performed. Original articles evaluating these imaging methods both in the differential diagnosis between HGG and low-grade gliomas (LGG) and in the assessment of suspicious HGG recurrence were included. Pooled sensitivity, specificity, positive and negative likelihood ratios (LR+ and LR-), and diagnostic odds ratio (DOR) including 95% confidence intervals (95% CI) were calculated. Statistical heterogeneity was also assessed using the I² test. Results: The meta-analysis of six selected studies (157 patients) provided the following results about PET/CT or PET/MRI with PSMA-targeting radiopharmaceuticals in the diagnosis of HGG: sensitivity 98.2% (95% CI: 75.3–99.9%), specificity 91.2% (95% CI: 68.4–98.1%), LR+ 4.5 (95% CI: 2.2–9.3), LR− 0.07 (95% CI: 0.04–0.15), and DOR 70.1 (95% CI: 19.6–250.9). No significant statistical heterogeneity among the included studies was found (I² = 0%). Conclusions: the quantitative data provided demonstrate the high diagnostic accuracy of PET/CT or PET/MRI with PSMA-targeting radiopharmaceuticals for HGG detection. However, more studies are needed to confirm the promising role of PSMA-targeted PET in this clinical setting.