Volumetric analysis of IDH-mutant lower-grade glioma: a natural history study of tumor growth rates before and after treatment

Cerebrospinal fluid D-2-hydroxyglutarate for IDH-mutant glioma: utility for detection versus monitoring

BACKGROUND

Imaging-based monitoring of gliomas is limited by treatment-related changes. D-2-hydroxyglutarate (D-2-HG), produced by the isocitrate dehydrogenase (IDH) mutation, is detectable in cerebrospinal fluid (CSF) that can be accessed from various anatomic compartments. We evaluated CSF D-2-HG as a serially accessible biomarker for IDH-mutant gliomas.

METHODS

A CLIA-approved gas chromatography mass spectrometry assay was developed for CSF D- and L-2-HG. Lumbar and cranial CSF samples were collected from patients with IDH-mutant gliomas or IDH-wild-type brain tumors and non-tumor pathologies via surgical field collection, lumbar punctures, Ommaya reservoirs, and ventriculoperitoneal shunts.

RESULTS

CSF D-2-HG was significantly higher in cranial than lumbar samples from IDH-mutant glioma patients (median lumbar=0.20 μM, cranial = 1.72 μM; p<0.0001). Cranial, but not lumbar, CSF D-2-HG distinguished primary IDH-mutant gliomas from IDH-wild type lesions (cranial AUC= 0.89, 95% confidence interval (CI)= 0.80-0.97); lumbar AUC= 0.52, 95% CI=0.28-0.76). When evaluated in recurrent lesions as a separate validation cohort, this finding was also reproduced in this group (cranial AUC=0.97, 95% CI= 0.94-1.00; lumbar AUC=0.60, 95% CI=0.38-0.83). Cranial CSF D-2-HG levels decreased to 0.54x of baseline with resection in seventeen patients (p=0.0129) but did not decrease significantly with chemoradiation in five patients (p=0.6250). Longitudinal anatomical changes, such as cavity collapse, influenced serial sample interpretation. In grade 4 IDH-mutant astrocytomas, serial cranial CSF D-2-HG increased with disease progression and differentiated stability from pseudoprogression when tumor-CSF contact was sufficient.

CONCLUSIONS

Serial cranial CSF D-2-HG shows promise as a monitoring biomarker in patients with IDH-mutant gliomas when anatomic variables remain constant.

KEY POINTS

Cranial CSF D-2-HG levels exceed that of lumbar CSF in patients with IDH-mutant gliomas.Cranial CSF D-2-HG may discriminate disease stability vs. treatment effects, although post-resection anatomical changes can impact monitoring.

IMPORTANCE OF THE STUDY

Improved glioma monitoring is needed due to challenges distinguishing disease progression from treatment-related changes on imaging. Toward this goal, we evaluated CSF D-2-HG as a biomarker of IDH-mutant gliomas using a CLIA-approved assay. This study answers whether D-2-HG can identify IDH-mutant gliomas via either cranial or lumbar CSF. Importantly, in seventeen patients, we demonstrate that CSF D-2-HG is responsive to cytoreduction via resection, but not chemoradiation in five patients. This is also the first study to demonstrate that longitudinal anatomical changes can impact evaluation of CSF D-2-HG as a monitoring biomarker. Finally, the study demonstrates that serial CSF D-2-HG can increase with disease progression, but not pseudoprogression or stable disease, in five patients with grade 4 IDH-mutant astrocytomas. These findings support the potential of CSF D-2-HG as a monitoring biomarker in patients with IDH-mutant gliomas, particularly when there are minimal changes to the anatomy of the resection cavity.

The role of vorasidenib in the treatment of isocitrate dehydrogenase-mutant glioma

Isocitrate dehydrogenase (IDH)-mutant gliomas are the most common malignant primary brain tumors in young adults. This condition imposes a substantial burden on patients and their caregivers, marked by neurocognitive deficits and high mortality rates due to tumor progression, coupled with significant morbidity from current treatment modalities. Although surgery, radiation therapy, and chemotherapy improve survival, these treatments can adversely affect cognitive function, quality of life, finances, employment status, and overall independence. Consequently, there is an urgent need for innovative strategies that delay progression and the use of radiation therapy and chemotherapy. The recent Federal Drug Administration (FDA) approval of vorasidenib, a brain-penetrant small molecule targeting mutant IDH1/2 proteins, heralds a shift in the therapeutic landscape for IDH-mutant gliomas. In this review, we address the role of vorasidenib in the treatment of IDH-mutant gliomas, providing a roadmap for its incorporation into daily practice. We discuss ongoing clinical trials with vorasidenib and other IDH inhibitors, as single-agent or in combination with other therapies, as well as current challenges and future directions.

Progression-free survival versus post-progression survival and overall survival in WHO grade 2 gliomas

BACKGROUND AND PURPOSE

Progression-free survival (PFS) remains to be validated as an outcome measure for diffuse WHO grade 2 gliomas, and knowledge about the relationships between PFS, post-progression survival (PPS), and overall survival (OS) in this subset of tumors is limited. We sought to assess correlations between PFS and OS, and identify factors associated with PFS, PPS, and OS in patients treated for diffuse supratentorial WHO grade 2 gliomas.

MATERIAL AND METHODS

We included 319 patients from three independent observational cohorts. The correlation between PFS and OS was analyzed using independent exponential distributions for PFS and time from progression to death. Cox proportional hazards models were used to determine the effects of covariates on PFS, PPS, and OS.

RESULTS

The overall correlation between PFS and OS was rs0.31. The correlation was rs 0.37 for astrocytomas and rs 0.19 for oligodendrogliomas. Longer PFS did not predict longer PPS. Patients with astrocytomas had shorter PFS, PPS, and OS. Larger preoperative tumor volume was a risk factor for shorter PFS, while older age was a risk factor for shorter PPS and OS. Patients who received early radio- and chemotherapy had longer PFS, but shorter PPS and OS.

INTERPRETATION

We found a weak correlation between PFS and OS in WHO grade 2 gliomas, with the weakest correlation observed in oligodendrogliomas. Our analyses did not demonstrate any association between PFS and PPS. Critically, predictors of PFS are not necessarily predictors of OS. There is a need for validation of PFS as an endpoint in diffuse WHO grade 2 gliomas.

The biological significance of tumor grade, age, enhancement, and extent of resection in IDH-mutant gliomas: How should they inform treatment decisions in the era of IDH inhibitors?

The 2016 and 2021 World Health Organization 2021 Classification of central nervous system tumors have resulted in a major improvement in the classification of isocitrate dehydrogenase (IDH)-mutant gliomas. With more effective treatments many patients experience prolonged survival. However, treatment guidelines are often still based on information from historical series comprising both patients with IDH wild-type and IDH-mutant tumors. They provide recommendations for radiotherapy and chemotherapy for so-called high-risk patients, usually based on residual tumor after surgery and age over 40. More up-to-date studies give a better insight into clinical, radiological, and molecular factors associated with the outcome of patients with IDH-mutant glioma. These insights should be used today for risk stratification and for treatment decisions. In many patients with IDH-mutant grades 2 and 3 glioma, if carefully monitored postponing radiotherapy and chemotherapy is safe, and will not jeopardize the overall outcome of patients. With the INDIGO trial showing patient benefit from the IDH inhibitor vorasidenib, there is a sizable population in which it seems reasonable to try this class of agents before recommending radio-chemotherapy with its delayed adverse event profile affecting quality of survival. Ongoing trials should help to further identify the patients that are benefiting from this treatment.

IDH inhibition in gliomas: from preclinical models to clinical trials

Gliomas are the most common malignant primary brain tumours in adults and cannot usually be cured with standard cancer treatments. Gliomas show intratumoural and intertumoural heterogeneity at the histological and molecular levels, and they frequently contain mutations in the isocitrate dehydrogenase 1 (IDH1) or IDH2 gene. IDH-mutant adult-type diffuse gliomas are subdivided into grade 2, 3 or 4 IDH-mutant astrocytomas and grade 2 or 3 IDH-mutant, 1p19q-codeleted oligodendrogliomas. The product of the mutated IDH genes, D-2-hydroxyglutarate (D-2-HG), induces global DNA hypermethylation and interferes with immunity, leading to stimulation of tumour growth. Selective inhibitors of mutant IDH, such as ivosidenib and vorasidenib, have been shown to reduce D-2-HG levels and induce cellular differentiation in preclinical models and to induce MRI-detectable responses in early clinical trials. The phase III INDIGO trial has demonstrated superiority of vorasidenib, a brain-penetrant pan-mutant IDH inhibitor, over placebo in people with non-enhancing grade 2 IDH-mutant gliomas following surgery. In this Review, we describe the pathway of development of IDH inhibitors in IDH-mutant low-grade gliomas from preclinical models to clinical trials. We discuss the practice-changing implications of the INDIGO trial and consider new avenues of investigation in the field of IDH-mutant gliomas.

Tumor Volume Growth Rates and Doubling Times during Active Surveillance of IDH-mutant Low-Grade Glioma

PURPOSE

Isocitrate dehydrogenase-mutant (IDH-mt) gliomas are incurable primary brain tumors characterized by a slow-growing phase over several years followed by a rapid-growing malignant phase. We hypothesized that tumor volume growth rate (TVGR) on MRI may act as an earlier measure of clinical benefit during the active surveillance period.

EXPERIMENTAL DESIGN

We integrated three-dimensional volumetric measurements with clinical, radiologic, and molecular data in a retrospective cohort of IDH-mt gliomas that were observed after surgical resection in order to understand tumor growth kinetics and the impact of molecular genetics.

RESULTS

Using log-linear mixed modeling, the entire cohort (n = 128) had a continuous %TVGR per 6 months of 10.46% [95% confidence interval (CI), 9.11%-11.83%] and a doubling time of 3.5 years (95% CI, 3.10-3.98). High molecular grade IDH-mt gliomas, defined by the presence of homozygous deletion of CDKN2A/B, had %TVGR per 6 months of 19.17% (95% CI, 15.57%-22.89%) which was significantly different from low molecular grade IDH-mt gliomas with a growth rate per 6 months of 9.54% (95% CI, 7.32%-11.80%; P < 0.0001). Using joint modeling to comodel the longitudinal course of TVGR and overall survival, we found each one natural logarithm tumor volume increase resulted in more than a 3-fold increase in risk of death (HR = 3.83; 95% CI, 2.32-6.30; P < 0.0001).

CONCLUSIONS

TVGR may be used as an earlier measure of clinical benefit and correlates well with the WHO 2021 molecular classification of gliomas and survival. Incorporation of TVGR as a surrogate endpoint into future prospective studies of IDH-mt gliomas may accelerate drug development.

Identifying IDH-mutant and 1p/19q noncodeleted astrocytomas from nonenhancing gliomas: Manual recognition followed by artificial intelligence recognition

Background

The T2-FLAIR mismatch sign (T2FM) has nearly 100% specificity for predicting IDH-mutant and 1p/19q noncodeleted astrocytomas (astrocytomas). However, only 18.2%-56.0% of astrocytomas demonstrate a positive T2FM. Methods must be considered for distinguishing astrocytomas from negative T2FM gliomas. In this study, positive T2FM gliomas were manually distinguished from nonenhancing gliomas, and then a support vector machine (SVM) classification model was used to distinguish astrocytomas from negative T2FM gliomas.

Methods

Nonenhancing gliomas (regardless of pathological type or grade) diagnosed between January 2022 and October 2022 (N = 300) and November 2022 and March 2023 (N = 196) will comprise the training and validation sets, respectively. Our method for distinguishing astrocytomas from nonenhancing gliomas was examined and validated using the training set and validation set.

Results

The specificity of T2FM for predicting astrocytomas was 100% in both the training and validation sets, while the sensitivity was 42.75% and 67.22%, respectively. Using a classification model of SVM based on radiomics features, among negative T2FM gliomas, the accuracy was above 85% when the prediction score was greater than 0.70 in identifying astrocytomas and above 95% when the prediction score was less than 0.30 in identifying nonastrocytomas.

Conclusions

Manual screening of positive T2FM gliomas, followed by the SVM classification model to differentiate astrocytomas from negative T2FM gliomas, may be a more effective method for identifying astrocytomas in nonenhancing gliomas.

Impact of Frontline Ivosidenib on Volumetric Growth Patterns in Isocitrate Dehydrogenase-mutant Astrocytic and Oligodendroglial Tumors

PURPOSE

Isocitrate dehydrogenase (IDH)-mutant gliomas are usually treated with radiotherapy and chemotherapy, which increases the risk for neurocognitive sequelae during patients' most productive years. We report our experience using off-label first-in-class mutant IDH1 inhibitor ivosidenib and its impact on tumor volume in IDH-mutant gliomas.

EXPERIMENTAL DESIGN

We retrospectively analyzed patients ages ≥18 years with radiation/chemotherapy-naïve, mutant IDH1, nonenhancing, radiographically active, grade 2/3 gliomas, and ≥2 pretreatment and ≥2 on-treatment ivosidenib MRIs. T2/FLAIR-based tumor volumes, growth rates, and progression-free survival (PFS) were analyzed. log-linear mixed-effect modeling of growth curves adjusted for grade, histology, and age was performed.

RESULTS

We analyzed 116 MRIs of 12 patients [10 males, median age 46 years (range: 26-60)]: 8 astrocytomas (50% grade 3) and 4 grade 2 oligodendrogliomas. Median on-drug follow-up was 13.2 months [interquartile range (IQR): 9.7-22.2]. Tolerability was 100%. A total of 50% of patients experienced ≥20% tumor volume reduction on-treatment and absolute growth rate was lower during treatment (-1.2 ± 10.6 cc/year) than before treatment (8.0 ± 7.7 cc/year; P ≤ 0.05). log-linear models in the Stable group (n = 9) showed significant growth before treatment (53%/year; P = 0.013), and volume reduction (-34%/year; P = 0.037) after 5 months on treatment. After treatment, volume curves were significantly lower than before treatment (after/before treatment ratio 0.5; P < 0.01). Median time-to-best response was 11.2 (IQR: 1.7-33.4) months, and 16.8 (IQR: 2.6-33.5) months in patients on drug for ≥1 year. PFS at 9 months was 75%.

CONCLUSIONS

Ivosidenib was well tolerated and induced a high volumetric response rate. Responders had significant reduction in tumor growth rates and volume reductions observed after a 5-month delay. Thus, ivosidenib appears useful to control tumor growth and delay more toxic therapies in IDH-mutant nonenhancing indolently growing gliomas. See related commentary by Lukas and Horbinski, p. 4709.

Evaluation of RANO Criteria for the Assessment of Tumor Progression for Lower-Grade Gliomas

PURPOSE

The Response Assessment in Neuro-Oncology (RANO) criteria for lower-grade gliomas (LGGs) define tumor progression as ≥25% change in the T2/FLAIR signal area based on an operator's discretion of the perpendicular diameter of the largest tumor cross-section. Potential sources of error include acquisition inconsistency of 2D slices, operator selection variabilities in both representative tumor cross-section and measurement line locations, and the inability to quantify infiltrative tumor margins and satellite lesions. Our goal was to assess the accuracy and reproducibility of RANO in LG.

MATERIALS AND METHODS

A total of 651 FLAIR MRIs from 63 participants with LGGs were retrospectively analyzed by three blinded attending physicians and three blinded resident trainees using RANO criteria, 2D visual assessment, and computer-assisted 3D volumetric assessment.

RESULTS

RANO product measurements had poor-to-moderate inter-operator reproducibility (r² = 0.28-0.82; coefficient of variance (CV) = 44-110%; mean percent difference (diff) = 0.4-46.8%) and moderate-to-excellent intra-operator reproducibility (r² = 0.71-0.88; CV = 31-58%; diff = 0.3-23.9%). When compared to 2D visual ground truth, the accuracy of RANO compared to previous and baseline scans was 66.7% and 65.1%, with an area under the ROC curve (AUC) of 0.67 and 0.66, respectively. When comparing to volumetric ground truth, the accuracy of RANO compared to previous and baseline scans was 21.0% and 56.5%, with an AUC of 0.39 and 0.55, respectively. The median time delay at diagnosis was greater for false negative cases than for false positive cases for the RANO assessment compared to previous (2.05 > 0.50 years, p = 0.003) and baseline scans (1.08 > 0.50 years, p = 0.02).

CONCLUSION

RANO-based assessment of LGGs has moderate reproducibility and poor accuracy when compared to either visual or volumetric ground truths.

Incidental diffuse low-grade gliomas: A systematic review and meta-analysis of treatment results with correction of lead-time and length-time biases

Background

Better overall survival (OS) reported in patients with incidental diffuse low-grade glioma (iLGG) in comparison to symptomatic LGG (sLGG) may be overestimated by lead-time and length-time.

Methods

We performed a systematic review and meta-analysis of studies on adult hemispheric iLGGs according to the PRISMA statement to adjust for biases in their outcomes. Survival data were extracted from Kaplan-Meier curves. Lead-time was estimated by 2 methods: Pooled data of time to become symptomatic (LTs) and time calculated from the tumor growth model (LTg).

Results

We selected articles from PubMed, Ovid Medline, and Scopus since 2000. Five compared OS between patients with iLGG (n = 287) and sLGG (n = 3117). The pooled hazard ratio (pHR) for OS of iLGG to sLGG was 0.40 (95% confidence interval [CI] {0.27-0.61}). The estimated mean LTs and LTg were 3.76 years (n = 50) and 4.16-6.12 years, respectively. The corrected pHRs were 0.64 (95% CI [0.51-0.81]) by LTs and 0.70 (95% CI [0.56-0.88]) by LTg. In patients with total removal, the advantage of OS in iLGG was lost after the correction of lead-time. Patients with iLGG were more likely to be female pooled odds ratio (pOR) 1.60 (95% CI [1.25-2.04]) and have oligodendrogliomas (pOR 1.59 [95% CI {1.05-2.39}]). Correction of the length-time bias, which increased the pHR by 0.01 to 0.03, preserved the statistically significant difference in OS.

Conclusions

The reported outcome in iLGG was biased by lead-time and length-time. Although iLGG had a longer OS after correction of biases, the difference was less than previously reported.

Prognostic and predictive impact of abnormal signal volume evolution early after chemoradiotherapy in glioblastoma

INTRODUCTION

This study was designed to explore the feasibility of semiautomatic measurement of abnormal signal volume (ASV) in glioblastoma (GBM) patients, and the predictive value of ASV evolution for the survival prognosis after chemoradiotherapy (CRT).

METHODS

This retrospective trial included 110 consecutive patients with GBM. MRI metrics, including the orthogonal diameter (OD) of the abnormal signal lesions, the pre-radiation enhancement volume (PRRCE), the volume change rate of enhancement (rCE), and fluid attenuated inversion recovery (rFLAIR) before and after CRT were analyzed. Semi-automatic measurements of ASV were done through the Slicer software.

RESULTS

In logistic regression analysis, age (HR = 2.185, p = 0.012), PRRCE (HR = 0.373, p < 0.001), post CE volume (HR = 4.261, p = 0.001), rCE_1m (HR = 0.519, p = 0.046) were the significant independent predictors of short overall survival (OS) (< 15.43 months). The areas under the receiver operating characteristic curve (AUCs) for predicting short OS with rFLAIR_3m and rCE_1m were 0.646 and 0.771, respectively. The AUCs of Model 1 (clinical), Model 2 (clinical + conventional MRI), Model 3 (volume parameters), Model 4 (volume parameters + conventional MRI), and Model 5 (clinical + conventional MRI + volume parameters) for predicting short OS were 0.690, 0.723, 0.877, 0.879, 0.898, respectively.

CONCLUSION

Semi-automatic measurement of ASV in GBM patients is feasible. The early evolution of ASV after CRT was beneficial in improving the survival evaluation after CRT. The efficacy of rCE_1m was better than that of rFLAIR_3m in this evaluation.

Isocitrate dehydrogenase (IDH) mutant gliomas: A Society for Neuro-Oncology (SNO) consensus review on diagnosis, management, and future directions

Isocitrate dehydrogenase (IDH) mutant gliomas are the most common adult, malignant primary brain tumors diagnosed in patients younger than 50, constituting an important cause of morbidity and mortality. In recent years, there has been significant progress in understanding the molecular pathogenesis and biology of these tumors, sparking multiple efforts to improve their diagnosis and treatment. In this consensus review from the Society for Neuro-Oncology (SNO), the current diagnosis and management of IDH-mutant gliomas will be discussed. In addition, novel therapies, such as targeted molecular therapies and immunotherapies, will be reviewed. Current challenges and future directions for research will be discussed.

Change in volumetric tumor growth rate after cytotoxic therapy is predictive of overall survival in recurrent glioblastoma

Background

Alterations in tumor growth rate (TGR) in recurrent glioblastoma (rGBM) after treatment may be useful for identifying therapeutic activity. The aim of this study was to assess the impact of volumetric TGR alterations on overall survival (OS) in rGBM treated with chemotherapy with or without radiation therapy (RT).

Methods

Sixty-one rGBM patients treated with chemotherapy with or without concomitant radiation therapy (RT) at 1st or 2nd recurrence were retrospectively examined. Pre- and post-treatment contrast enhancing volumes were computed. Patients were considered "responders" if they reached progression-free survival at 6 months (PFS6) and showed a decrease in TGR after treatment and "non-responders" if they didn't reach PFS6 or if TGR increased.

Results

Stratification by PFS6 and based on TGR resulted in significant differences in OS both for all patients and for patients without RT (P < 0.05). A decrease of TGR (P = 0.009), smaller baseline tumor volume (P = 0.02), O6-methylguanine-DNA methyltransferase promoter methylation (P = 0.048) and fewer number of recurrences (P = 0.048) were significantly associated with longer OS after controlling for age, sex and concomitant RT.

Conclusion

A decrease in TGR in patients with PFS6, along with smaller baseline tumor volume, were associated with a significantly longer OS in rGBM treated with chemotherapy with or without radiation. Importantly, all patients that exhibited PFS6 also showed a measurable decrease in TGR.

NS-HGlio: A generalizable and repeatable HGG segmentation and volumetric measurement AI algorithm for the longitudinal MRI assessment to inform RANO in trials and clinics

Background

Accurate and repeatable measurement of high-grade glioma (HGG) enhancing (Enh.) and T2/FLAIR hyperintensity/edema (Ed.) is required for monitoring treatment response. 3D measurements can be used to inform the modified Response Assessment in Neuro-oncology criteria. We aim to develop an HGG volumetric measurement and visualization AI algorithm that is generalizable and repeatable.

Methods

A single 3D-Convoluted Neural Network, NS-HGlio, to analyze HGG on MRIs using 5-fold cross validation was developed using retrospective (557 MRIs), multicentre (38 sites) and multivendor (32 scanners) dataset divided into training (70%), validation (20%), and testing (10%). Six neuroradiologists created the ground truth (GT). Additional Internal validation (IV, three institutions) using 70 MRIs, and External validation (EV, single institution) using 40 MRIs through measuring the Dice Similarity Coefficient (DSC) of Enh., Ed. ,and Enh. + Ed. (WholeLesion/WL) tumor tissue and repeatability testing on 14 subjects from the TCIA MGH-QIN-GBM dataset using volume correlations between timepoints were performed.

Results

IV Preoperative median DSC Enh. 0.89 (SD 0.11), Ed. 0.88 (0.28), WL 0.88 (0.11). EV Preoperative median DSC Enh. 0.82 (0.09), Ed. 0.83 (0.11), WL 0.86 (0.06). IV Postoperative median DSC Enh. 0.77 (SD 0.20), Ed 0.78. (SD 0.09), WL 0.78 (SD 0.11). EV Postoperative median DSC Enh. 0.75 (0.21), Ed 0.74 (0.12), WL 0.79 (0.07). Repeatability testing; Intraclass Correlation Coefficient of 0.95 Enh. and 0.92 Ed.

Conclusion

NS-HGlio is accurate, repeatable, and generalizable. The output can be used for visualization, documentation, treatment response monitoring, radiation planning, intra-operative targeting, and estimation of Residual Tumor Volume among others.

Future development of chimeric antigen receptor T cell therapies for patients suffering from malignant glioma

PURPOSE OF REVIEW

Chimeric antigen receptor (CAR) T cell therapy has been successful in some haematologic malignancies, but the central nervous system (CNS) presents unique obstacles to its use against tumours arising therein. This review discusses recent improvements in the delivery and design of these cells to improve the efficacy and safety of this treatment against malignant gliomas.

RECENT FINDINGS

The immunosuppressive environment of the CNS affects the functionality of CAR T cells, but recent developments using metabolic manipulation and cytokine delivery have shown that the performance of CAR T cells can be improved in this environment. Emerging techniques can improve the delivery of CAR T cells to the CNS parenchyma, which is normally well protected from peripheral immune cells. The implementation of novel antigens and CAR-expression regulation strategies will improve the specificity and efficacy of these cells. Finally, although autologous T cells have historically been the standard, recent developments have made the use of allogeneic T cells or natural killer (NK) cells more clinically feasible.

SUMMARY

The discoveries highlighted in this review will aid the development of CAR cells that are safer, more resilient against immunosuppressive signals in the CNS, and able to specifically target intracranial tumour cells.

Balancing Risk and Efficiency in Drug Development for Rare and Challenging Tumors: A New Paradigm for Glioma

The process of developing cancer therapies is well established and has enabled the incorporation of many new drugs and classes of agents into the standard of care for common cancers. Clinical drug development is fundamentally different for rare and difficult-to-treat solid tumors, such as glioma or pancreatic cancer. The failure to develop effective new agents for the latter diseases has discouraged the development of therapeutics for these cancers. Using glioma as an example, we describe a process toward obtaining more reliable early-stage signals of drug activity and a process toward translating those signals into clinical benefits with more efficient late-stage development. If linked together, these processes should increase the likelihood of benefit in late-stage settings at a lower cost and encourage more drug development for patients with rare and difficult-to-treat cancers.

Novel Clinical Trial Designs in Neuro-Oncology

Scientific and technologic advances have led to a boon of candidate therapeutics for patients with malignancies of the central nervous system. The path from drug development to clinical use has generally followed a regimented order of sequential clinical trial phases. The recent increase in novel therapies, however, has strained the regulatory process and unearthed limitations of the current system, including significant cost, prolonged development time, and difficulties in testing therapies for rarer tumors. Novel clinical trial designs have emerged to increase efficiencies in clinical trial conduct to better evaluate and bring impactful drugs to patients in a timely manner. In order to better capture meaningful benefits for brain tumor patients, new endpoints to complement or replace traditional endpoints are also an increasingly important consideration. This review will explore the current challenges in the current clinical trial landscape and discuss novel clinical trial concepts, including consideration of limitations and risks of novel trial designs, within the context of neuro-oncology.

T2-Fluid-Attenuated Inversion Recovery (FLAIR) Mismatch as a Novel Specific MRI Marker for Adult Low-Grade Glioma (LGG): A Case Report

Astrocytic tumors are primary central nervous system tumors. They are the most common tumors arising from glial cells. In the new WHO classification 2021, adult-type diffuse astrocytic gliomas subdivide into isocitrate dehydrogenase (IDH)-mutant astrocytoma, IDH-mutant and 1p/19q-codeleted oligodendroglioma, and IDH-wildtype glioblastoma. The T2-fluid-attenuated inversion recovery (FLAIR) mismatch sign describes the MRI appearance of IDH-mutant astrocytoma, it is considered a highly specific radiogenomic signature for diffuse astrocytoma, as opposed to other lower-grade. MRI is the first and most accurate diagnostic tool for low-grade gliomas (LGGs). It is particularly helpful in distinguishing a diffuse astrocytoma from an oligodendroglioma that will not demonstrate T2-FLAIR mismatch. The tumor displays a hyperintense signal on T2-weighted images and a hypointense signal on T2-weighted FLAIR images, which distinguishes it from other types of diffuse gliomas. We report a case of a 29-year-old female patient who was diagnosed with IDH-mutant 1p/19q-non-codeleted diffuse astrocytoma based on MRI T-2 FLAIR mismatch sign, which is confirmed by the molecular analysis in the pathology lab. Our aim of this report is to confirm the power of the MRI findings in the diagnosis of glioma genotypes and to assess neurosurgeons in the preoperative surgical planning.

Hypothetical generalized framework for a new imaging endpoint of therapeutic activity in early phase clinical trials in brain tumors

Imaging response assessment is a cornerstone of patient care and drug development in oncology. Clinicians/clinical researchers rely on tumor imaging to estimate the impact of new treatments and guide decision making for patients and candidate therapies. This is important in brain cancer, where associations between tumor size/growth and emerging neurological deficits are strong. Accurately measuring the impact of a new therapy on tumor growth early in clinical development, where patient numbers are small, would be valuable for decision making regarding late-stage development activation. Current attempts to measure the impact of a new therapy have limited influence on clinical development, as determination of progression, stability or response does not currently account for individual tumor growth kinetics prior to the initiation of experimental therapies. Therefore, we posit that imaging-based response assessment, often used as a tool for estimating clinical effect, is incomplete as it does not adequately account for growth trajectories or biological characteristics of tumors prior to the introduction of an investigational agent. Here, we propose modifications to the existing framework for evaluating imaging assessment in primary brain tumors that will provide a more reliable understanding of treatment effects. Measuring tumor growth trajectories prior to a given intervention may allow us to more confidently conclude whether there is an anti-tumor effect. This updated approach to imaging-based tumor response assessment is intended to improve our ability to select candidate therapies for later-stage development, including those that may not meet currently sought thresholds for "response" and ultimately lead to identification of effective treatments.

AI-Driven Image Analysis in Central Nervous System Tumors-Traditional Machine Learning, Deep Learning and Hybrid Models

The interpretation of imaging in medicine in general and in oncology specifically remains problematic due to several limitations which include the need to incorporate detailed clinical history, patient and disease-specific history, clinical exam features, previous and ongoing treatment, and account for the dependency on reproducible human interpretation of multiple factors with incomplete data linkage. To standardize reporting, minimize bias, expedite management, and improve outcomes, the use of Artificial Intelligence (AI) has gained significant prominence in imaging analysis. In oncology, AI methods have as a result been explored in most cancer types with ongoing progress in employing AI towards imaging for oncology treatment, assessing treatment response, and understanding and communicating prognosis. Challenges remain with limited available data sets, variability in imaging changes over time augmented by a growing heterogeneity in analysis approaches. We review the imaging analysis workflow and examine how hand-crafted features also referred to as traditional Machine Learning (ML), Deep Learning (DL) approaches, and hybrid analyses, are being employed in AI-driven imaging analysis in central nervous system tumors. ML, DL, and hybrid approaches coexist, and their combination may produce superior results although data in this space is as yet novel, and conclusions and pitfalls have yet to be fully explored. We note the growing technical complexities that may become increasingly separated from the clinic and enforce the acute need for clinician engagement to guide progress and ensure that conclusions derived from AI-driven imaging analysis reflect that same level of scrutiny lent to other avenues of clinical research.

Real-time PACS-integrated longitudinal brain metastasis tracking tool provides comprehensive assessment of treatment response to radiosurgery

Background

Treatment of brain metastases can be tailored to individual lesions with treatments such as stereotactic radiosurgery. Accurate surveillance of lesions is a prerequisite but challenging in patients with multiple lesions and prior imaging studies, in a process that is laborious and time consuming. We aimed to longitudinally track several lesions using a PACS-integrated lesion tracking tool (LTT) to evaluate the efficiency of a PACS-integrated lesion tracking workflow, and characterize the prevalence of heterogenous response (HeR) to treatment after Gamma Knife (GK).

Methods

We selected a group of brain metastases patients treated with GK at our institution. We used a PACS-integrated LTT to track the treatment response of each lesion after first GK intervention to maximally seven diagnostic follow-up scans. We evaluated the efficiency of this tool by comparing the number of clicks necessary to complete this task with and without the tool and examined the prevalence of HeR in treatment.

Results

A cohort of eighty patients was selected and 494 lesions were measured and tracked longitudinally for a mean follow-up time of 374 days after first GK. Use of LTT significantly decreased number of necessary clicks. 81.7% of patients had HeR to treatment at the end of follow-up. The prevalence increased with increasing number of lesions.

Conclusions

Lesions in a single patient often differ in their response to treatment, highlighting the importance of individual lesion size assessments for further treatment planning. PACS-integrated lesion tracking enables efficient lesion surveillance workflow and specific and objective result reports to treating clinicians.

Metabolic Signature-Based Subtypes May Pave Novel Ways for Low-Grade Glioma Prognosis and Therapy

Metabolic signatures are frequently observed in cancer and are starting to be recognized as important regulators for tumor progression and therapy. Because metabolism genes are involved in tumor initiation and progression, little is known about the metabolic genomic profiles in low-grade glioma (LGG). Here, we applied bioinformatics analysis to determine the metabolic characteristics of patients with LGG from the Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA). We also performed the ConsensusClusterPlus, the CIBERSORT algorithm, the Estimate software, the R package "GSVA," and TIDE to comprehensively describe and compare the characteristic difference between three metabolic subtypes. The R package WGCNA helped us to identify co-expression modules with associated metabolic subtypes. We found that LGG patients were classified into three subtypes based on 113 metabolic characteristics. MC1 patients had poor prognoses and MC3 patients obtained longer survival times. The different metabolic subtypes had different metabolic and immune characteristics, and may have different response patterns to immunotherapy. Based on the metabolic subtype, different patterns were exhibited that reflected the characteristics of each subtype. We also identified eight potential genetic markers associated with the characteristic index of metabolic subtypes. In conclusion, a comprehensive understanding of metabolism associated characteristics and classifications may improve clinical outcomes for LGG.

Isocitrate Dehydrogenase Mutant Grade II and III Glial Neoplasms

Mutations in isocitrate dehydrogenase (IDH) 1 or IDH2 occur in most of the adult low-grade gliomas and, less commonly, in cholangiocarcinoma, chondrosarcoma, acute myeloid leukemia, and other human malignancies. Cancer-associated mutations alter the function of the enzyme, resulting in production of R(-)-2-hydroxyglutarate and broad epigenetic dysregulation. Small molecule IDH inhibitors have received regulatory approval for the treatment of IDH mutant (mIDH) leukemia and are under development for the treatment of mIDH solid tumors. This article provides a current view of mIDH adult astrocytic and oligodendroglial tumors, including their clinical presentation and treatment, and discusses novel approaches and challenges toward improving the treatment of these tumors.

Imaging Advances for Central Nervous System Tumors

This article reviews recent advances in the use of standard and advanced imaging techniques for diagnosis and treatment of central nervous system (CNS) tumors, including glioma and brain metastasis. Following the recent transition from a histology-based approach in classifying CNS tumors to one that integrates histology with the molecular information of tumor, the approaches for imaging CNS tumors have also been adapted to this new framework. Some challenges related to the diagnosis and treatment of CNS tumors, such as differentiating tumor from treatment-related imaging changes, require further progress to implement advanced imaging for clinical use.