State-of-the-art imaging for glioma surgery

Non-hemorrhagic cerebellar contrast enhancement on intraoperative MRI during a supratentorial glioma resection: Concerning finding of no significance

Intraoperative magnetic resonance imaging (iMRI) is a powerful tool used to verify maximal safe resection of gliomas. However, unsuspected new or incidental findings can present difficult clinical scenarios. Here we present a case of a large supratentorial glioma resection where new, incidental bilateral cerebellar hemispheric enhancement was noted on iMRI. A 52-year-old male with a large intra-axial mass spanning the right temporal and parietal lobes underwent a craniotomy for tumor resection utilizing iMRI. Imaging displayed new, remote, bilateral cerebellar enhancement. Upon completion of surgery, the patient was extubated and was at his neurological baseline. An immediate CT scan showed no abnormalities in the cerebellum, and the duration of his hospital stay was unaffected by this finding. An MRI 24 hours after the procedure demonstrated complete resolution of the enhancement. New, remote contrast enhancement in the cerebellum raises concerns for the potentially emergent, well-defined pathology known as remote cerebellar hemorrhage (RCH). However, here we describe a case where these findings turned out to be clinically insignificant, CT-negative, and self-limiting. Therefore, here we call this finding remote non-hemorrhagic cerebellar contrast enhancement (RNHCCE) to differentiate it from RCE, and we discuss nuances and management considerations for differentiating the two.

Radiomics and visual analysis for predicting success of transplantation of heterotopic glioblastoma in mice with MRI

BACKGROUND

Quantifying tumor growth and treatment response noninvasively poses a challenge to all experimental tumor models. The aim of our study was, to assess the value of quantitative and visual examination and radiomic feature analysis of high-resolution MR images of heterotopic glioblastoma xenografts in mice to determine tumor cell proliferation (TCP).

METHODS

Human glioblastoma cells were injected subcutaneously into both flanks of immunodeficient mice and followed up on a 3 T MR scanner. Volumes and signal intensities were calculated. Visual assessment of the internal tumor structure was based on a scoring system. Radiomic feature analysis was performed using MaZda software. The results were correlated with histopathology and immunochemistry.

RESULTS

21 tumors in 14 animals were analyzed. The volumes of xenografts with high TCP (H-TCP) increased, whereas those with low TCP (L-TCP) or no TCP (N-TCP) continued to decrease over time (p < 0.05). A low intensity rim (rim sign) on unenhanced T1-weighted images provided the highest diagnostic accuracy at visual analysis for assessing H-TCP (p < 0.05). Applying radiomic feature analysis, wavelet transform parameters were best for distinguishing between H-TCP and L-TCP / N-TCP (p < 0.05).

CONCLUSION

Visual and radiomic feature analysis of the internal structure of heterotopically implanted glioblastomas provide reproducible and quantifiable results to predict the success of transplantation.

Intraoperative rapid molecular diagnosis aids glioma subtyping and guides precise surgical resection

OBJECTIVE

The molecular era of glioma diagnosis and treatment has arrived, and a single rapid histopathology is no longer sufficient for surgery. This study sought to present an automatic integrated gene detection system (AIGS), which enables rapid intraoperative detection of IDH/TERTp mutations.

METHODS

A total of 78 patients with gliomas were included in this study. IDH/TERTp mutations were detected intraoperatively using AIGS in 41 of these patients, and they were guided to surgical resection (AIGS detection group). The remaining 37 underwent histopathology-guided conventional surgical resection (non-AIGS detection group). The clinical utility of this technique was evaluated by comparing the accuracy of glioma subtype diagnosis before and after TERTp mutation results were obtained by pathologists and the extent of resection (EOR) and patient prognosis for molecular pathology-guided glioma surgery.

RESULTS

With NGS/Sanger sequencing and chromosome detection as the gold standard, the accuracy of AIGS results was 100%. And the timing was well matched to the intraoperative rapid pathology report. After obtaining the TERTp mutation detection results, the accuracy of the glioma subtype diagnosis made by the pathologists increased by 19.51%. Molecular pathology-guided surgical resection of gliomas significantly increased EOR (99.06% vs. 93.73%, p < 0.0001) and also improved median OS (26.77 vs. 13.47 months, p = 0.0289) and median PFS (15.90 vs. 10.57 months, p = 0.0181) in patients with glioblastoma.

INTERPRETATION

Using AIGS intraoperatively to detect IDH/TERTp mutations to accurately diagnose glioma subtypes can help achieve maximum safe resection of gliomas, which in turn improves the survival prognosis of patients.

Beyond conventional imaging: Advancements in MRI for glioma malignancy prediction and molecular profiling

This review examines the advancements in magnetic resonance imaging (MRI) techniques and their pivotal role in diagnosing and managing gliomas, the most prevalent primary brain tumors. The paper underscores the importance of integrating modern MRI modalities, such as diffusion-weighted imaging and perfusion MRI, which are essential for assessing glioma malignancy and predicting tumor behavior. Special attention is given to the 2021 WHO Classification of Tumors of the Central Nervous System, emphasizing the integration of molecular diagnostics in glioma classification, significantly impacting treatment decisions. The review also explores radiogenomics, which correlates imaging features with molecular markers to tailor personalized treatment strategies. Despite technological progress, MRI protocol standardization and result interpretation challenges persist, affecting diagnostic consistency across different settings. Furthermore, the review addresses MRI's capacity to distinguish between tumor recurrence and pseudoprogression, which is vital for patient management. The necessity for greater standardization and collaborative research to harness MRI's full potential in glioma diagnosis and personalized therapy is highlighted, advocating for an enhanced understanding of glioma biology and more effective treatment approaches.

Hypnosis-Assisted Awake Craniotomy for Eloquent Brain Tumors: Advantages and Pitfalls

BACKGROUND

Awake craniotomy (AC) is recommended for the resection of tumors in eloquent areas. It is traditionally performed under monitored anesthesia care (MAC), which relies on hypnotics and opioids. Hypnosis-assisted AC (HAAC) is an emerging technique that aims to provide psychological support while reducing the need for pharmacological sedation and analgesia. We aimed to compare the characteristics and outcomes of patients who underwent AC under HAAC or MAC.

METHODS

We retrospectively analyzed the clinical, anesthetic, surgical, and neuropsychological data of patients who underwent awake surgical resection of eloquent brain tumors under HAAC or MAC. We used Mann-Whitney U tests, Wilcoxon signed-rank tests, and repeated-measures analyses of variance to identify statistically significant differences at the 0.05 level.

RESULTS

A total of 22 patients were analyzed, 14 in the HAAC group and 8 in the MAC group. Demographic, radiological, and surgical characteristics as well as postoperative outcomes were similar. Patients in the HAAC group received less remifentanil (p = 0.047) and propofol (p = 0.002), but more dexmedetomidine (p = 0.025). None of them received ketamine as a rescue analgesic. Although patients in the HAAC group experienced higher levels of perioperative pain (p < 0.05), they reported decreasing stress levels (p = 0.04) and greater levels of satisfaction (p = 0.02).

CONCLUSION

HAAC is a safe alternative to MAC as it reduces perioperative stress and increases overall satisfaction. Further research is necessary to assess whether hypnosis is clinically beneficial.

Significance of navigated transcranial magnetic stimulation and tractography to preserve motor function in patients undergoing surgery for motor eloquent gliomas

Resection of gliomas in or close to motor areas is at high risk for morbidity and development of surgery-related deficits. Navigated transcranial magnetic stimulation (nTMS) including nTMS-based tractography is suitable for presurgical planning and risk assessment. The aim of this study was to investigate the association of postoperative motor status and the spatial relation to motor eloquent brain tissue in order to increase the understanding of postoperative motor deficits. Patient data, nTMS examinations and imaging studies were retrospectively reviewed, corticospinal tracts (CST) were reconstructed with two different approaches of nTMS-based seeding. Postoperative imaging and nTMS-augmented preoperative imaging were merged to identify the relation between motor positive cortical and subcortical areas and the resection cavity. 38 tumor surgeries were performed in 36 glioma patients (28.9% female) aged 55.1 ± 13.8 years. Mean distance between the CST and the lesion was 6.9 ± 5.1 mm at 75% of the patient-individual fractional anisotropy threshold and median tumor volume reduction was 97.7 ± 11.6%. The positive predictive value for permanent deficits after resection of nTMS positive areas was 66.7% and the corresponding negative predictive value was 90.6%. Distances between the resection cavity and the CST were higher in patients with postoperative stable motor function. Extent of resection and distance between resection cavity and CST correlated well. The present study strongly supports preoperative nTMS as an important surgical tool for preserving motor function in glioma patients at risk.

Imaging Role in Diagnosis, Prognosis, and Treatment Response Prediction Associated with High-grade Glioma

Background

Glioma is one of the most drug and radiation-resistant tumors. Gliomas suffer from inter- and intratumor heterogeneity which makes the outcome of similar treatment protocols vary from patient to patient. This article is aimed to overview the potential imaging markers for individual diagnosis, prognosis, and treatment response prediction in malignant glioma. Furthermore, the correlation between imaging findings and biological and clinical information of glioma patients is reviewed.

Materials and Methods

The search strategy in this study is to select related studies from scientific websites such as PubMed, Scopus, Google Scholar, and Web of Science published until 2022. It comprised a combination of keywords such as Biomarkers, Diagnosis, Prognosis, Imaging techniques, and malignant glioma, according to Medical Subject Headings.

Results

Some imaging parameters that are effective in glioma management include: ADC, FA, Ktrans, regional cerebral blood volume (rCBV), cerebral blood flow (CBF), ve, Cho/NAA and lactate/lipid ratios, intratumoral uptake of 18F-FET (for diagnostic application), RD, ADC, ve, vp, Ktrans, CBFT1, rCBV, tumor blood flow, Cho/NAA, lactate/lipid, MI/Cho, uptakes of 18F-FET, 11C-MET, and 18F-FLT (for prognostic and predictive application). Cerebral blood volume and Ktrans are related to molecular markers such as vascular endothelial growth factor (VEGF). Preoperative ADCmin value of GBM tumors is associated with O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation status. 2-hydroxyglutarate metabolite and dynamic 18F-FDOPA positron emission tomography uptake are related to isocitrate dehydrogenase (IDH) mutations.

Conclusion

Parameters including ADC, RD, FA, rCBV, Ktrans, vp, and uptake of 18F-FET are useful for diagnosis, prognosis, and treatment response prediction in glioma. A significant correlation between molecular markers such as VEGF, MGMT, and IDH mutations with some diffusion and perfusion imaging parameters has been identified.

Canine glioblastoma-derived extracellular vesicles as precise carriers for glioblastoma imaging: Targeting across the blood-brain barrier

The treatment of glioblastoma (GBM) faces significant challenges due to the difficulty of delivering drugs through the blood-brain barrier (BBB). Extracellular vesicles (EVs) have emerged as potential carriers for targeted drug delivery to brain tumors. However, their use and distribution in the presence of an intact BBB and their ability to target GBM tissue are still under investigation. This study explored the use of EVs for GBM targeting across the BBB. Canine plasma EVs from healthy dogs and dogs with glioma were isolated, characterized, and loaded with diagnostic agents. Biodistribution studies were conducted in healthy murine models and a novel intranasal model that preserved BBB integrity while initiating early-stage GBM growth. This model assessed EVs' potential for delivering the contrast agent gadoteric acid to intracranial tumors. Imaging techniques, such as bioluminescence and MRI, confirmed EVs' targeting and delivery capabilities thus revealing a selective accumulation of canine glioma-derived EVs in brain tissue under physiological conditions. In the model of brain tumor, MRI experiments demonstrated the ability of EVs to accumulate gadoteric acid within GBM to enhance contrast of the tumoral mass, even when BBB integrity is maintained. This study underscores the potential of EVs derived from glioma for the targeted delivery of drugs to glioblastoma. EVs from dogs with glioma showed capacity to traverse the BBB and selectively accumulate within the brain tumor. Overall, this research represents a foundation for the application of autologous EVs to precision glioblastoma treatment, addressing the challenge of BBB penetration and targeting specificity in brain cancer therapy.

A transferrin receptor targeting dual-modal MR/NIR fluorescent imaging probe for glioblastoma diagnosis

The prognosis of glioblastoma (GBM) remains challenging, primarily due to the lack of a precise, effective imaging technique for comprehensively characterization. Addressing GBM diagnostic challenges, our study introduces an innovative dual-modal imaging that merges near-infrared (NIR) fluorescent imaging with magnetic resonance imaging (MRI). This method employs superparamagnetic iron oxide nanoparticles coated with NIR fluorescent dyes, specifically Cyanine 7, and targeted peptides. This synthetic probe facilitates MRI functionality through superparamagnetic iron oxide nanoparticles, provides NIR imaging capability via Cyanine 7 and enhances tumor targeting trough peptide interactions, offering a comprehensive diagnostic tool for GBM. Notably, the probe traverses the blood-brain barrier, targeting GBM in vivo via peptides, producing clear and discernible images in both modalities. Cytotoxicity and histopathology assessments confirm the probe's favorable safety profile. These findings suggest that the dual-modal MR\NIR fluorescent imaging probe could revolutionize GBM prognosis and survival rates, which can also be extended to other tumors type.

The Role of Genetic Analysis in Distinguishing Multifocal and Multicentric Glioblastomas: An Illustrative Case

Introduction

Glioblastomas can manifest as multiple, simultaneous, noncontiguous lesions. We genetically analyzed multiple glioblastomas and discuss their etiological origins in this report.

Case Presentation

We present the case of a 47-year-old woman who presented with memory impairment and left partial paralysis. Radiographic imaging revealed three apparently noncontiguous lesions in the right temporal and parietal lobes extending into the corpus callosum, leading to diagnosis of multicentric glioblastomas. All three lesions were excised. Genetic analysis of the lesions revealed a TERT promoter C228T mutation, a roughly equivalent amplification of EGFR, and homozygous deletion of CDKN2A/B exclusively in the two contrast-enhanced lesions. Additionally, the contrast-enhanced lesions exhibited the same two-base pair mutations of PTEN, whereas the non-enhanced lesion showed a partially distinct 13-base pair mutation. The other genetic characteristics were consistent. Rather than each having arisen de novo, we believe that they had developed by infiltration and are therefore best classified as multifocal glioblastomas.

Conclusion

Our findings underscore anew the possibility of infiltration by glioblastomas, even within regions devoid of signal alterations on T2-weighted images or fluid-attenuated inversion recovery images. Genetic analysis can play a crucial role in differentiating whether multiple glioblastomas are multifocal or multicentric.

Hyperspectral imaging benchmark based on machine learning for intraoperative brain tumour detection

Brain surgery is one of the most common and effective treatments for brain tumour. However, neurosurgeons face the challenge of determining the boundaries of the tumour to achieve maximum resection, while avoiding damage to normal tissue that may cause neurological sequelae to patients. Hyperspectral (HS) imaging (HSI) has shown remarkable results as a diagnostic tool for tumour detection in different medical applications. In this work, we demonstrate, with a robust k-fold cross-validation approach, that HSI combined with the proposed processing framework is a promising intraoperative tool for in-vivo identification and delineation of brain tumours, including both primary (high-grade and low-grade) and secondary tumours. Analysis of the in-vivo brain database, consisting of 61 HS images from 34 different patients, achieve a highest median macro F1-Score result of 70.2 ± 7.9% on the test set using both spectral and spatial information. Here, we provide a benchmark based on machine learning for further developments in the field of in-vivo brain tumour detection and delineation using hyperspectral imaging to be used as a real-time decision support tool during neurosurgical workflows.

Modern preoperative imaging and functional mapping in patients with intracranial glioma

Magnetic resonance imaging (MRI) in therapy-naïve intracranial glioma is paramount for neuro-oncological diagnostics, and it provides images that are helpful for surgery planning and intraoperative guidance during tumor resection, including assessment of the involvement of functionally eloquent brain structures. This study reviews emerging MRI techniques to depict structural information, diffusion characteristics, perfusion alterations, and metabolism changes for advanced neuro-oncological imaging. In addition, it reflects current methods to map brain function close to a tumor, including functional MRI and navigated transcranial magnetic stimulation with derived function-based tractography of subcortical white matter pathways. We conclude that modern preoperative MRI in neuro-oncology offers a multitude of possibilities tailored to clinical needs, and advancements in scanner technology (e. g., parallel imaging for acceleration of acquisitions) make multi-sequence protocols increasingly feasible. Specifically, advanced MRI using a multi-sequence protocol enables noninvasive, image-based tumor grading and phenotyping in patients with glioma. Furthermore, the add-on use of preoperatively acquired MRI data in combination with functional mapping and tractography facilitates risk stratification and helps to avoid perioperative functional decline by providing individual information about the spatial location of functionally eloquent tissue in relation to the tumor mass. KEY POINTS::   · Advanced preoperative MRI allows for image-based tumor grading and phenotyping in glioma.. · Multi-sequence MRI protocols nowadays make it possible to assess various tumor characteristics (incl. perfusion, diffusion, and metabolism).. · Presurgical MRI in glioma is increasingly combined with functional mapping to identify and enclose individual functional areas.. · Advancements in scanner technology (e. g., parallel imaging) facilitate increasing application of dedicated multi-sequence imaging protocols.. CITATION FORMAT: · Sollmann N, Zhang H, Kloth C et al. Modern preoperative imaging and functional mapping in patients with intracranial glioma. Fortschr Röntgenstr 2023; 195: 989 - 1000.

Intraoperative Imaging and Optical Visualization Techniques for Brain Tumor Resection: A Narrative Review

Advancements in intraoperative visualization and imaging techniques are increasingly central to the success and safety of brain tumor surgery, leading to transformative improvements in patient outcomes. This comprehensive review intricately describes the evolution of conventional and emerging technologies for intraoperative imaging, encompassing the surgical microscope, exoscope, Raman spectroscopy, confocal microscopy, fluorescence-guided surgery, intraoperative ultrasound, magnetic resonance imaging, and computed tomography. We detail how each of these imaging modalities contributes uniquely to the precision, safety, and efficacy of neurosurgical procedures. Despite their substantial benefits, these technologies share common challenges, including difficulties in image interpretation and steep learning curves. Looking forward, innovations in this field are poised to incorporate artificial intelligence, integrated multimodal imaging approaches, and augmented and virtual reality technologies. This rapidly evolving landscape represents fertile ground for future research and technological development, aiming to further elevate surgical precision, safety, and, most critically, patient outcomes in the management of brain tumors.

Classification of IDH wild-type glioblastoma tumorspheres into low- and high-invasion groups based on their transcriptional program

BACKGROUND

Glioblastoma (GBM), one of the most lethal tumors, exhibits a highly infiltrative phenotype. Here, we identified transcription factors (TFs) that collectively modulate invasion-related genes in GBM.

METHODS

The invasiveness of tumorspheres (TSs) were quantified using collagen-based 3D invasion assays. TF activities were quantified by enrichment analysis using GBM transcriptome, and confirmed by cell-magnified analysis of proteome imaging. Invasion-associated TFs were knocked down using siRNA or shRNA, and TSs were orthotopically implanted into mice.

RESULTS

After classifying 23 patient-derived GBM TSs into low- and high-invasion groups, we identified active TFs in each group-PCBP1 for low invasion, and STAT3 and SRF for high invasion. Knockdown of these TFs reversed the phenotype and invasion-associated-marker expression of GBM TSs. Notably, MRI revealed consistent patterns of invasiveness between TSs and the originating tumors, with an association between high invasiveness and poor prognosis. Compared to controls, mice implanted with STAT3- or SRF-downregulated GBM TSs showed reduced normal tissue infiltration and tumor growth, and prolonged survival, indicating a therapeutic response.

CONCLUSIONS

Our integrative transcriptome analysis revealed three invasion-associated TFs in GBM. Based on the relationship among the transcriptional program, invasive phenotype, and prognosis, we suggest these TFs as potential targets for GBM therapy.

The application of decision tree model based on clinicopathological risk factors and pre-operative MRI radiomics for predicting short-term recurrence of glioblastoma after total resection: a retrospective cohort study

To develop a decision tree model based on clinical information, molecular genetics information and pre-operative magnetic resonance imaging (MRI) radiomics-score (Rad-score) to investigate its predictive value for the risk of recurrence of glioblastoma (GBM) within one year after total resection. Patients with pathologically confirmed GBM at Huashan Hospital, Fudan University between November 2017 and June 2020 were retrospectively analyzed, and the enrolled patients were randomly divided into training and test sets according to the ratio of 3:1. The relevant clinical and MRI data of patients before, after surgery and follow-up were collected, and after feature extraction on preoperative MRI, the LASSO filter was used to filter the features and establish the Rad-score. Using the training set, a decision tree model for predicting recurrence of GBM within one year after total resection was established by the C5.0 algorithm, and scatter plots were generated to evaluate the prediction accuracy of the decision tree during model testing. The prediction performance of the model was also evaluated by calculating area under the receiver operating characteristic (ROC) curve (AUC), ACC, Sensitivity (SEN), Specificity (SPE) and other indicators. Besides, two external validation datasets from Wuhan union hospital and the second affiliated hospital of Xuzhou Medical University were used to verify the reliability and accuracy of the prediction model. According to the inclusion and exclusion criteria, 134 patients with GBM were finally identified for inclusion in the study, and 53 patients recurred within one year after total resection, with a mean recurrence time of 5.6 months. According to the importance of the predictor variables, a decision tree model for predicting recurrence based on five important factors, including patient age, Rad-score, O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation, pre-operative Karnofsky Performance Status (KPS) and Telomerase reverse transcriptase (TERT) promoter mutation, was developed. The AUCs of the model in the training and test sets were 0.850 and 0.719, respectively, and the scatter plot showed excellent consistency. In addition, the prediction model achieved AUCs of 0.810 and 0.702 in two external validation datasets from Wuhan union hospital and the second affiliated hospital of Xuzhou Medical University, respectively. The decision tree model based on clinicopathological risk factors and preoperative MRI Rad-score can accurately predict the risk of recurrence of GBM within one year after total resection, which can further guide the clinical optimization of patient treatment decisions, as well as refine the clinical management of patients and improve their prognoses to a certain extent.

Toward a theranostic device for gliomas

BACKGROUND

In the surgical management of glioblastoma, a highly aggressive and incurable type of brain cancer, identification and treatment of residual tissue is the most common site of disease recurrence. Monitoring and localized treatment are achieved with engineered microbubbles (MBs) by combining ultrasound and fluorescence imaging with actively targeted temozolomide (TMZ) delivery.

METHODS

The MBs were conjugated with a near-infrared fluorescence probe CF790, cyclic pentapeptide bearing the RGD sequence and a carboxyl-temozolomide, TMZA. The efficiency of adhesion to HUVEC cells was assessed in vitro in realistic physiological conditions of shear rate and vascular dimensions. Cytotoxicity of TMZA-loaded MBs on U87 MG cells and IC50 were assessed by MTT tests.

RESULTS

We report on the design of injectable poly(vinyl alcohol) echogenic MBs designed as a platform with active targeting ability to tumor tissues, by tethering on the surface a ligand having the tripeptide sequence, RGD. The biorecognition of RGD-MBs onto HUVEC cells is quantitatively proved. Efficient NIR emission from the CF790-decorated MBs was successfully detected. The conjugation on the MBs surface of a specific drug as TMZ is achieved. The pharmacological activity of the coupled-to-surface drug is preserved by controlling the reaction conditions.

CONCLUSIONS

We present an improved formulation of PVA-MBs to achieve a multifunctional device with adhesion ability, cytotoxicity on glioblastoma cells and supporting imaging.

Multifunctional nanotheranostics for near infrared optical imaging-guided treatment of brain tumors

Malignant brain tumors, a heterogeneous group of primary and metastatic neoplasms in the central nervous system (CNS), are notorious for their highly invasive and devastating characteristics, dismal prognosis and low survival rate. Recently, near-infrared (NIR) optical imaging modalities including fluorescence imaging (FLI) and photoacoustic imaging (PAI) have displayed bright prospect in innovation of brain tumor diagnoses, due to their merits, like noninvasiveness, high spatiotemporal resolution, good sensitivity and large penetration depth. Importantly, these imaging techniques have been widely used to vividly guide diverse brain tumor therapies in a real-time manner with high accuracy and efficiency. Herein, we provide a systematic summary of the state-of-the-art NIR contrast agents (CAs) for brain tumors single-modal imaging (e.g., FLI and PAI), dual-modal imaging (e.g., FLI/PAI, FLI/magnetic resonance imaging (MRI) and PAI/MRI) and triple-modal imaging (e.g., MRI/FLI/PAI and MRI/PAI/computed tomography (CT) imaging). In addition, we update the most recent progress on the NIR optical imaging-guided therapies, like single-modal (e.g., photothermal therapy (PTT), chemotherapy, surgery, photodynamic therapy (PDT), gene therapy and gas therapy), dual-modal (e.g., PTT/chemotherapy, PTT/surgery, PTT/PDT, PDT/chemotherapy, PTT/chemodynamic therapy (CDT) and PTT/gene therapy) and triple-modal (e.g., PTT/PDT/chemotherapy, PTT/PDT/surgery, PTT/PDT/gene therapy and PTT/gene/chemotherapy). Finally, we discuss the opportunities and challenges of the CAs and nanotheranostics for future clinic translation.

Is intraoperative ultrasound more efficient than magnetic resonance in neurosurgical oncology? An exploratory cost-effectiveness analysis

Objective

Intraoperative imaging is a chief asset in neurosurgical oncology, it improves the extent of resection and postoperative outcomes. Imaging devices have evolved considerably, in particular ultrasound (iUS) and magnetic resonance (iMR). Although iUS is regarded as a more economically convenient and yet effective asset, no formal comparison between the efficiency of iUS and iMR in neurosurgical oncology has been performed.

Methods

A cost-effectiveness analysis comparing two single-center prospectively collected surgical cohorts, classified according to the intraoperative imaging used. iMR (2013-2016) and iUS (2021-2022) groups comprised low- and high-grade gliomas, with a maximal safe resection intention. Units of health gain were gross total resection and equal or increased Karnofsky performance status. Surgical and health costs were considered for analysis. The incremental cost-effectiveness ratio (ICER) was calculated for the two intervention alternatives. The cost-utility graphic and the evolution of surgical duration with the gained experience were also analyzed.

Results

50 patients followed an iMR-assisted operation, while 17 underwent an iUS-guided surgery. Gross total resection was achieved in 70% with iMR and in 60% with iUS. Median postoperative Karnofsky was similar in both group (KPS 90). Health costs were € 3,220 higher with iMR, and so were surgical-related costs (€ 1,976 higher). The ICER was € 322 per complete resection obtained with iMR, and € 644 per KPS gained or maintained with iMR. When only surgical-related costs were analyzed, ICER was € 198 per complete resection with iMR and € 395 per KPS gained or maintained.

Conclusion

This is an unprecedented but preliminary cost-effectiveness analysis of the two most common intraoperative imaging devices in neurosurgical oncology. iMR, although being costlier and time-consuming, seems cost-effective in terms of complete resection rates and postoperative performance status. However, the differences between both techniques are small. Possibly, iMR and iUS are complementary aids during the resection: iUS real-time images assist while advancing towards the tumor limits, informing about the distance to relevant landmarks and correcting neuronavigation inaccuracy due to brain shift. Yet, at the end of resection, it is the iMR that reliably corroborates whether residual tumor remains.

Fast intraoperative histology-based diagnosis of gliomas with third harmonic generation microscopy and deep learning

Management of gliomas requires an invasive treatment strategy, including extensive surgical resection. The objective of the neurosurgeon is to maximize tumor removal while preserving healthy brain tissue. However, the lack of a clear tumor boundary hampers the neurosurgeon's ability to accurately detect and resect infiltrating tumor tissue. Nonlinear multiphoton microscopy, in particular higher harmonic generation, enables label-free imaging of excised brain tissue, revealing histological hallmarks within seconds. Here, we demonstrate a real-time deep learning-based pipeline for automated glioma image analysis, matching video-rate image acquisition. We used a custom noise detection scheme, and a fully-convolutional classification network, to achieve on average 79% binary accuracy, 0.77 AUC and 0.83 mean average precision compared to the consensus of three pathologists, on a preliminary dataset. We conclude that the combination of real-time imaging and image analysis shows great potential for intraoperative assessment of brain tissue during tumor surgery.

Sedoheptulose Kinase SHPK Expression in Glioblastoma: Emerging Role of the Nonoxidative Pentose Phosphate Pathway in Tumor Proliferation

Glioblastoma (GBM) is the most common form of malignant brain cancer and is considered the deadliest human cancer. Because of poor outcomes in this disease, there is an urgent need for progress in understanding the molecular mechanisms of GBM therapeutic resistance, as well as novel and innovative therapies for cancer prevention and treatment. The pentose phosphate pathway (PPP) is a metabolic pathway complementary to glycolysis, and several PPP enzymes have already been demonstrated as potential targets in cancer therapy. In this work, we aimed to evaluate the role of sedoheptulose kinase (SHPK), a key regulator of carbon flux that catalyzes the phosphorylation of sedoheptulose in the nonoxidative arm of the PPP. SHPK expression was investigated in patients with GBM using microarray data. SHPK was also overexpressed in GBM cells, and functional studies were conducted. SHPK expression in GBM shows a significant correlation with histology, prognosis, and survival. In particular, its increased expression is associated with a worse prognosis. Furthermore, its overexpression in GBM cells confirms an increase in cell proliferation. This work highlights for the first time the importance of SHPK in GBM for tumor progression and proposes this enzyme and the nonoxidative PPP as possible therapeutic targets.

Effect of 3D Slicer Preoperative Planning and Intraoperative Guidance with Mobile Phone Virtual Reality Technology on Brain Glioma Surgery

Objective

To explore the effect of 3D Slicer preoperative planning and intraoperative guidance with mobile phone virtual reality (VR) technology on brain glioma surgery.

Methods

By means of retrospective study, the data of 77 brain glioma patients treated in the neurosurgery departments at The Second Affiliated Hospital of Wannan Medical College and Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine from January 2015 to January 2022 were analyzed, and the patients were divided into the experimental group (EG, n = 38) and the control group (CG, n = 39) according to the surgical modalities. Before surgery, all patients received positron emission tomography-computed tomography (PET/CT) scanning and magnetic resonance imaging (MRI) examination. For patients in EG, the DICOM format images acquired from PET-CT and MRI examinations were imported with the 3D Slicer software for 3D visual fusion reconstruction, acquiring VR images, and developing detailed preoperative planning. Then, the reconstructed images were imported into the Sina software on a mobile phone, and the surgery was performed with the assistance of VR technology; for patients in CG, traditional 2D images were used for tumor contour drawing by the subjective visual method, and the craniotomy was performed under a traditional microscope. Patients' surgery indicators and Karnofsky Performance Scale (KPS) scores were compared between the two groups.

Results

The number of cases with total resection, rate of total resection, hospital stay after surgery, and surgery time were significantly better in EG than in CG (P < 0.05); after treatment, the KPS score was significantly higher in EG than in CG (75.66 ± 4.01 vs 65.36 ± 5.23, P < 0.001).

Conclusion

Combining 3D Slicer preoperative planning with intraoperative mobile phone VR technology can promote the accuracy of brain glioma surgery, which is conducive to effectively removing tumors while protecting patients' neural function.

An Integrated Immune-Related Bioinformatics Analysis in Glioma: Prognostic Signature’s Identification and Multi-Omics Mechanisms’ Exploration

As the traditional treatment for glioma, the most common central nervous system malignancy with poor prognosis, the efficacy of high-intensity surgery combined with radiotherapy and chemotherapy is not satisfactory. The development of individualized scientific treatment strategy urgently requires the guidance of signature with clinical predictive value. In this study, five prognosis-related differentially expressed immune-related genes (PR-DE-IRGs) (CCNA2, HMGB2, CASP3, APOBEC3C, and BMP2) highly associated with glioma were identified for a prognostic model through weighted gene co-expression network analysis, univariate Cox and lasso regression. Kaplan-Meier survival curves, receiver operating characteristic curves and other methods have shown that the model has good performance in predicting the glioma patients’ prognosis. Further combined nomogram provided better predictive performance. The signature’s guiding value in clinical treatment has also been verified by multiple analysis results. We also constructed a comprehensive competing endogenous RNA (ceRNA) regulatory network based on the protective factor BMP2 to further explore its potential role in glioma progression. Numerous immune-related biological functions and pathways were enriched in a high-risk population. Further multi-omics integrative analysis revealed a strong correlation between tumor immunosuppressive environment/IDH1 mutation and signature, suggesting that their cooperation plays an important role in glioma progression.

Hemodynamic Imaging in Cerebral Diffuse Glioma-Part A: Concept, Differential Diagnosis and Tumor Grading

Diffuse gliomas are the most common primary malignant intracranial neoplasms. Aside from the challenges pertaining to their treatment-glioblastomas, in particular, have a dismal prognosis and are currently incurable-their pre-operative assessment using standard neuroimaging has several drawbacks, including broad differentials diagnosis, imprecise characterization of tumor subtype and definition of its infiltration in the surrounding brain parenchyma for accurate resection planning. As the pathophysiological alterations of tumor tissue are tightly linked to an aberrant vascularization, advanced hemodynamic imaging, in addition to other innovative approaches, has attracted considerable interest as a means to improve diffuse glioma characterization. In the present part A of our two-review series, the fundamental concepts, techniques and parameters of hemodynamic imaging are discussed in conjunction with their potential role in the differential diagnosis and grading of diffuse gliomas. In particular, recent evidence on dynamic susceptibility contrast, dynamic contrast-enhanced and arterial spin labeling magnetic resonance imaging are reviewed together with perfusion-computed tomography. While these techniques have provided encouraging results in terms of their sensitivity and specificity, the limitations deriving from a lack of standardized acquisition and processing have prevented their widespread clinical adoption, with current efforts aimed at overcoming the existing barriers.

Surgical Neuro-Oncology

Gliomas are the most common intrinsic brain tumor in adults. Although maximal tumor resection improves survival, this must be balanced with preservation of neurologic function. Technological advancements have greatly expanded our ability to safely maximize tumor resection and design innovative therapeutic trials that take advantage of intracavitary delivery of therapeutic agents after resection. In this article, we review the role of surgical intervention for both low-grade and high-grade gliomas and the innovations that are driving and expanding the role of surgery in this therapeutically challenging group of malignancies.

Intraoperative MR Imaging during Glioma Resection

One of the major issues in the surgical treatment of gliomas is the concern about maximizing the extent of resection while minimizing neurological impairment. Thus, surgical planning by carefully observing the relationship between the glioma infiltration area and eloquent area of the connecting fibers is crucial. Neurosurgeons usually detect an eloquent area by functional MRI and identify a connecting fiber by diffusion tensor imaging. However, during surgery, the accuracy of neuronavigation can be decreased due to brain shift, but the positional information may be updated by intraoperative MRI and the next steps can be planned accordingly. In addition, various intraoperative modalities may be used to guide surgery, including neurophysiological monitoring that provides real-time information (e.g., awake surgery, motor-evoked potentials, and sensory evoked potential); photodynamic diagnosis, which can identify high-grade glioma cells; and other imaging techniques that provide anatomical information during the surgery. In this review, we present the historical and current context of the intraoperative MRI and some related approaches for an audience active in the technical, clinical, and research areas of radiology, as well as mention important aspects regarding safety and types of devices.

Advanced Imaging Techniques for Newly Diagnosed and Recurrent Gliomas

Management of gliomas following initial diagnosis requires thoughtful presurgical planning followed by regular imaging to monitor treatment response and survey for new tumor growth. Traditional MR imaging modalities such as T1 post-contrast and T2-weighted sequences have long been a staple of tumor diagnosis, surgical planning, and post-treatment surveillance. While these sequences remain integral in the management of gliomas, advances in imaging techniques have allowed for a more detailed characterization of tumor characteristics. Advanced MR sequences such as perfusion, diffusion, and susceptibility weighted imaging, as well as PET scans have emerged as valuable tools to inform clinical decision making and provide a non-invasive way to help distinguish between tumor recurrence and pseudoprogression. Furthermore, these advances in imaging have extended to the operating room and assist in making surgical resections safer. Nevertheless, surgery, chemotherapy, and radiation treatment continue to make the interpretation of MR changes difficult for glioma patients. As analytics and machine learning techniques improve, radiomics offers the potential to be more quantitative and personalized in the interpretation of imaging data for gliomas. In this review, we describe the role of these newer imaging modalities during the different stages of management for patients with gliomas, focusing on the pre-operative, post-operative, and surveillance periods. Finally, we discuss radiomics as a means of promoting personalized patient care in the future.

[Radiological biomarkers of brain gliomas]

The most important objective of modern neuroimaging is comparison of data on genotype and phenotype of brain gliomas. Radiogenomics as a new branch of science is devoted to searching for such relationships based on MRI and PET/CT parameters. The 2021 WHO classification of tumors of the central nervous system poses the most important tasks for physicians in assessment of biological behavior of tumors and their response to combined treatment. The review demonstrates the possibilities and prospects of preoperative MRI and PET/CT with amino acids in assessing the genetic profile of brain gliomas.

Malignant Tumor Purity Reveals the Driven and Prognostic Role of CD3E in Low-Grade Glioma Microenvironment

The tumor microenvironment (TME) contributes to the initiation and progression of many neoplasms. However, the impact of low-grade glioma (LGG) purity on carcinogenesis remains to be elucidated. We selected 509 LGG patients with available genomic and clinical information from the TCGA database. The percentage of tumor infiltrating immune cells and the tumor purity of LGG were evaluated using the ESTIMATE and CIBERSORT algorithms. Stromal-related genes were screened through Cox regression, and protein-protein interaction analyses and survival-related genes were selected in 487 LGG patients from GEO database. Hub genes involved in LGG purity were then identified and functionally annotated using bioinformatics analyses. Prognostic implications were validated in 100 patients from an Asian real-world cohort. Elevated tumor purity burden, immune scores, and stromal scores were significantly associated with poor outcomes and increased grade in LGG patients from the TCGA cohort. In addition, CD3E was selected with the most significant prognostic value (Hazard Ratio=1.552, P<0.001). Differentially expressed genes screened according to CD3E expression were mainly involved in stromal related activities. Additionally, significantly increased CD3E expression was found in 100 LGG samples from the validation cohort compared with adjacent normal brain tissues. High CD3E expression could serve as an independent prognostic indicator for survival of LGG patients and promotes malignant cellular biological behaviors of LGG. In conclusion, tumor purity has a considerable impact on the clinical, genomic, and biological status of LGG. CD3E, the gene for novel membrane immune biomarker deeply affecting tumor purity, may help to evaluate the prognosis and develop individual immunotherapy strategies for LGG patients. Evaluating the ratio of differential tumor purity and CD3E expression levels may provide novel insights into the complex structure of the LGG microenvironment and targeted drug development.

[Magnetic resonance relaxometry in high-grade glioma subregion assessment - neuroimaging and morphological correlates]

OBJECTIVE

To analyze the differences of high-grade glioma subregions using magnetic resonance relaxometry with compilation of images (MAGiC) and arterial spin labeling (ASL), as well as to compare quantitative measurements of these techniques with morphological data.

MATERIAL AND METHODS

The study enrolled 35 patients with newly diagnosed supratentorial gliomas (23 - grade IV, 12 - grade III). We measured relaxometric values (T1, T2, proton density), tumor blood flow (TBF) in glioma subregions and normal-appearing brain matter. Neuronavigation was intraoperatively used to obtain tissue samples from active tumor growth zone, perifocal infiltrative edema zone and adjacent brain matter along surgical approach.

RESULTS

ASL perfusion revealed higher tumor blood flow (TBF) in active tumor growth region compared to perifocal infiltrative edema zone (p<0.01). Relaxometric values (T1, T2, proton density) in perifocal zone were higher (p<0.01) compared to adjacent intact white matter along surgical approach. However, there were no differences in TBF between these zones. Proton density in tumor-adjacent intact white matter was higher (p<0.01) compared to normal-appearing white matter in ipsilateral hemisphere. There was inverse correlation between T2 and TBF in active tumor growth zone (Spearman rank R= -0.58; p=0.0016). We found inverse correlation between T2 and Ki67 proliferative index and direct correlation between TBF and Ki67 in this zone. Nevertheless, these relationships were insignificant after multiple test adjustment.

CONCLUSION

Our study advocates for complementary power of ASL perfusion and MR relaxometry in assessment of high-grade brain glioma subregions. More malignant tumor zones tend to have higher TBF and shorter T2. Further investigation is needed to prove the capability of MAGiC to reveal foci of increased relaxometric values in tumor-adjacent normal-appearing white matter.

5-ALA in Suspected Low-Grade Gliomas: Current Role, Limitations, and New Approaches

Radiologically suspected low-grade gliomas (LGG) represent a special challenge for the neurosurgeon during surgery due to their histopathological heterogeneity and indefinite tumor margin. Therefore, new techniques are required to overcome these current surgical drawbacks. Intraoperative visualization of brain tumors with assistance of 5-aminolevulinic acid (5-ALA) induced protoporphyrin IX (PpIX) fluorescence is one of the major advancements in the neurosurgical field in the last decades. Initially, this technique was exclusively applied for fluorescence-guided surgery of high-grade glioma (HGG). In the last years, the use of 5-ALA was also extended to other indications such as radiologically suspected LGG. Here, we discuss the current role of 5-ALA for intraoperative visualization of focal malignant transformation within suspected LGG. Furthermore, we discuss the current limitations of the 5-ALA technology in pure LGG which usually cannot be visualized by visible fluorescence. Finally, we introduce new approaches based on fluorescence technology for improved detection of pure LGG tissue such as spectroscopic PpIX quantification fluorescence lifetime imaging of PpIX and confocal microscopy to optimize surgery.

Visualizing Glioma Infiltration by the Combination of Multimodality Imaging and Artificial Intelligence, a Systematic Review of the Literature

The aim of this study was to systematically review the literature concerning the integration of multimodality imaging with artificial intelligence methods for visualization of tumor cell infiltration in glioma patients. The review was performed in accordance with the preferred reporting items for systematic reviews and meta-analysis (PRISMA) guidelines. The literature search was conducted in PubMed, Embase, The Cochrane Library and Web of Science and yielded 1304 results. 14 studies were included in the qualitative analysis. The reference standard for tumor infiltration was either histopathology or recurrence on image follow-up. Critical assessment was performed according to the Quality Assessment of Diagnostic Accuracy Studies (QUADAS2). All studies concluded their findings to be of significant value for future clinical practice. Diagnostic test accuracy reached an area under the curve of 0.74–0.91 reported in six studies. There was no consensus with regard to included image modalities, models or training and test strategies. The integration of artificial intelligence with multiparametric imaging shows promise for visualizing tumor cell infiltration in glioma patients. This approach can possibly optimize surgical resection margins and help provide personalized radiotherapy planning.

Advanced imaging techniques for neuro-oncologic tumor diagnosis, with an emphasis on PET-MRI imaging of malignant brain tumors

PURPOSE OF REVIEW

This review will explore the latest in advanced imaging techniques, with a focus on the complementary nature of multiparametric, multimodality imaging using magnetic resonance imaging (MRI) and positron emission tomography (PET).

RECENT FINDINGS

Advanced MRI techniques including perfusion-weighted imaging (PWI), MR spectroscopy (MRS), diffusion-weighted imaging (DWI), and MR chemical exchange saturation transfer (CEST) offer significant advantages over conventional MR imaging when evaluating tumor extent, predicting grade, and assessing treatment response. PET performed in addition to advanced MRI provides complementary information regarding tumor metabolic properties, particularly when performed simultaneously. 18F-fluoroethyltyrosine (FET) PET improves the specificity of tumor diagnosis and evaluation of post-treatment changes. Incorporation of radiogenomics and machine learning methods further improve advanced imaging. The complementary nature of combining advanced imaging techniques across modalities for brain tumor imaging and incorporating technologies such as radiogenomics has the potential to reshape the landscape in neuro-oncology.