Clinical Presentation, Management, and Outcome in Neurolymphomatosis: A Systematic Review.

BACKGROUND AND OBJECTIVES: Neurolymphomatosis (NL) refers to lymphomatous infiltration of the peripheral nervous system (PNS). NL diagnosis and treatment are challenging given the broad differential diagnosis of peripheral neuropathy, the lack of larger cohorts, and the subsequent unavailability of prognostic factors or consensus therapy. This study aimed to define characteristics and prognostic factors of NL. METHODS: A systematic review of the literature (2004-2023) was performed using PubMed and Scopus databases and reported following PRISMA guidelines. Studies reporting individual patient data on cases with definitive NL diagnosis were included. Clinical, radiologic, pathologic, and outcome information were extracted. Univariable and multivariable survival analyses were performed using log-rank tests and Cox proportional hazard models. RESULTS: A total of 459 NL cases from 264 studies were accumulated. NL was the first manifestation of malignancy (primary NL) in 197 patients. PNS relapse of known non-Hodgkin lymphoma (secondary NL) occurred in 262 cases after a median 12 months. NL predominantly presented with rapidly deteriorating, asymmetric painful polyneuropathy. Infiltrated structures included peripheral nerves (56%), nerve roots (52%), plexus (33%), and cranial nerves (32%). Diagnosis was established at a median of 3 months after symptom onset with substantial delays in primary NL. It mainly relied on PNS biopsy or FDG-PET, which carried high diagnostic yields (>90%). Postmortem diagnoses were rare (3%). Most cases were classified as B-cell (90%) lymphomas. Tumor-directed therapy was administered in 96% of patients and typically consisted of methotrexate or rituximab-based polychemotherapy. The median overall survival was 18 months. Primary NL without concurrent systemic disease outside the nervous system (hazard ratio [HR]: 0.44; 95% CI 0.25-0.78; p = 0.005), performance status (ECOG <2, HR: 0.30; 95% CI 0.18-0.52; p < 0.0001), and rituximab-based treatment (HR: 0.46; 95% CI 0.28-0.73; p = 0.001) were identified as favorable prognostic markers on multivariable analysis when adjusting for clinical and sociodemographic parameters. DISCUSSION: Advances in neuroimaging modalities, particularly FDG-PET, facilitate NL diagnosis and offer a high diagnostic yield. Yet, diagnostic delays in primary NL remain common. Rituximab-based therapy improves NL outcome. Findings may assist clinicians in early recognition, prognostic stratification, and treatment of NL.

"I didn't even wonder why I was on the floor" - mixed methods exploration of stroke awareness and help-seeking behaviour at stroke symptom onset.

INTRODUCTION: To better target stroke awareness efforts (pre and post first stroke) and thereby decrease the time window for help-seeking, this study aims to assess quantitatively whether stroke awareness is associated with appropriate help-seeking at symptom onset, and to investigate qualitatively why this may (not) be the case. METHODS: This study conducted in a German regional stroke network comprises a convergent quantitative-dominant, hypothesis-driven mixed methods design including 462 quantitative patient questionnaires combined with qualitative interviews with 28 patients and seven relatives. Quantitative associations were identified using Pearson's correlation analysis. Open coding was performed on interview transcripts before the quantitative results were used to further focus qualitative analysis. Joint display analysis was conducted to mix data strands. Cooperation with the Patient Council of the Department of Neurology ensured patient involvement in the study. RESULTS: Our hypothesis that stroke awareness would be associated with appropriate help-seeking behaviour at stroke symptom onset was partially supported by the quantitative data, i.e. showing associations between some dimensions of stroke awareness and appropriate help-seeking, but not others. For example, knowing stroke symptoms is correlated with recognising one's own symptoms as stroke (r = 0.101; p = 0.030*; N = 459) but not with no hesitation before calling help (r = 0.003; p = 0.941; N = 457). A previous stroke also makes it more likely to recognise one's own symptoms as stroke (r = 0.114; p = 0.015*; N = 459), but not to be transported by emergency ambulance (r = 0.08; p = 0.872; N = 462) or to arrive at the hospital on time (r = 0.02; p = 0.677; N = 459). Qualitative results showed concordance, discordance or provided potential explanations for quantitative findings. For example, qualitative data showed processes of denial on the part of patients and the important role of relatives in initiating appropriate help-seeking behaviour on patients' behalf. CONCLUSIONS: Our study provides insights into the complexities of the decision-making process at stroke symptom onset. As our findings suggest processes of denial and inabilities to translate abstract disease knowledge into correct actions, we recommend to address relatives as potential saviours of loved ones, increased use of specific situational examples (e.g. lying on the bathroom floor) and the involvement of patient representatives in the preparation of informational resources and campaigns. Future research should include mixed methods research from one sample and more attention to potential reporting inconsistencies.

Tumor biomechanics as a novel imaging biomarker to assess response to immunotherapy in a murine glioma model.

Glioblastoma is the most common and aggressive primary malignant brain tumor with poor prognosis. Novel immunotherapeutic approaches are currently under investigation. Even though magnetic resonance imaging (MRI) is the most important imaging tool for treatment monitoring, response assessment is often hampered by therapy-related tissue changes. As tumor and therapy-associated tissue reactions differ structurally, we hypothesize that biomechanics could be a pertinent imaging proxy for differentiation. Longitudinal MRI and magnetic resonance elastography (MRE) were performed to monitor response to immunotherapy with a toll-like receptor 7/8 agonist in orthotopic syngeneic experimental glioma. Imaging results were correlated to histology and light sheet microscopy data. Here, we identify MRE as a promising non-invasive imaging method for immunotherapy-monitoring by quantifying changes in response-related tumor mechanics. Specifically, we show that a relative softening of treated compared to untreated tumors is linked to the inflammatory processes following therapy-induced re-education of tumor-associated myeloid cells. Mechanistically, combined effects of myeloid influx and inflammation including extracellular matrix degradation following immunotherapy form the basis of treated tumors being softer than untreated glioma. This is a very early indicator of therapy response outperforming established imaging metrics such as tumor volume. The overall anti-tumor inflammatory processes likely have similar effects on human brain tissue biomechanics, making MRE a promising tool for gauging response to immunotherapy in glioma patients early, thereby strongly impacting patient pathway.

Tumoral Interferon Beta Induces an Immune-Stimulatory Phenotype in Tumor-Associated Macrophages in Melanoma Brain Metastases.

Type I interferons (IFN) are immune-stimulatory cytokines involved in antiviral and antitumor immune responses. They enhance the efficacy of immunogenic anticancer therapies such as radiotherapy by activating both innate and adaptive immune cells. Macrophages are one of the most abundant innate immune cells in the immune microenvironment of melanoma brain metastases (MBMs) and can exert potent immune-suppressive functions. Here, we investigate the potential of tumoral type I IFNs to re-polarize tumor-associated macrophages (TAMs) in two murine MBM models and assess the effects of radiotherapy-induced type I IFNs on TAMs in a transcriptomic MBM patient dataset. In mice, we describe a pro-inflammatory M1-like TAM phenotype induced by tumoral IFNß and identify a myeloid type I IFN-response signature associated with a high M1/M2-like TAM ratio. Following irradiation, patients with MBMs displaying a myeloid type I IFN-response signature showed increased overall survival, providing evidence that tumoral IFNß supports an effective antitumor immune response by re-educating immune-regulatory TAMs. These findings uncover type I IFN-inducing therapies as a potential macrophage-targeting therapeutic approach and provide a rationale for combining radiotherapy with concomitant immunotherapy to improve treatment response in patients with MBM.

Whole-Brain Vascular Architecture Mapping Identifies Region-Specific Microvascular Profiles in Vivo.

BACKGROUND AND PURPOSE: The novel MR imaging technique of vascular architecture mapping allows in vivo characterization of local changes in cerebral microvasculature, but reference ranges for vascular architecture mapping parameters in healthy brain tissue are lacking, limiting its potential applicability as an MR imaging biomarker in clinical practice. We conducted whole-brain vascular architecture mapping in a large cohort to establish vascular architecture mapping parameter references ranges and identify region-specific cortical and subcortical microvascular profiles. MATERIALS AND METHODS: This was a single-center examination of adult patients with unifocal, stable low-grade gliomas with multiband spin- and gradient-echo EPI sequence at 3T using parallel imaging. Voxelwise plotting of resulting values for gradient-echo (R2*) versus spin-echo (R2) relaxation rates during contrast agent bolus administration generates vessel vortex curves that allow the extraction of vascular architecture mapping parameters representative of, eg, vessel type, vessel radius, or CBV in the underlying voxel. Averaged whole-brain parametric maps were calculated for 9 parameters, and VOI analysis was conducted on the basis of a standardized brain atlas and individual cortical GM and WM segmentation. RESULTS: Prevalence of vascular risk factors among subjects (n = 106; mean age, 39.2 [SD, 12.5] years; 56 women) was similar to those in the German population. Compared with WM, we found cortical GM to have larger mean vascular calibers (5.80 [SD, 0.59] versus 4.25 [SD, 0.62] P < .001), increased blood volume fraction (20.40 [SD, 4.49] s-1 versus 11.05 [SD, 2.44] s-1; P < .001), and a dominance of venous vessels. Distinct microvascular profiles emerged for cortical GM, where vascular architecture mapping vessel type indicator differed, eg, between the thalamus and cortical GM (mean, -2.47 [SD, 4.02] s-2 versus -5.41 [SD, 2.84] s-2; P < .001). Intraclass correlation coefficient values indicated overall high test-retest reliability for vascular architecture mapping parameter mean values when comparing multiple scans per subject. CONCLUSIONS: Whole-brain vascular architecture mapping in the adult brain reveals region-specific microvascular profiles. The obtained parameter reference ranges for distinct anatomic and functional brain areas may be used for future vascular architecture mapping studies on cerebrovascular pathologies and might facilitate early discovery of microvascular changes, in, eg, neurodegeneration and neuro-oncology.

Unraveling glioblastoma diversity: Insights into methylation subtypes and spatial relationships.

Background: The purpose of this study was to elucidate the relationship between distinct brain regions and molecular subtypes in glioblastoma (GB), focusing on integrating modern statistical tools and molecular profiling to better understand the heterogeneity of Isocitrate Dehydrogenase wild-type (IDH-wt) gliomas. Methods: This retrospective study comprised 441 patients diagnosed with new IDH-wt glioma between 2009 and 2020 at Heidelberg University Hospital. The diagnostic process included preoperative magnetic resonance imaging and molecular characterization, encompassing IDH-status determination and subclassification, through DNA-methylation profiling. To discern and map distinct brain regions associated with specific methylation subtypes, a support-vector regression-based lesion-symptom mapping (SVR-LSM) was employed. Lesion maps were adjusted to 2 mm³ resolution. Significance was assessed with beta maps, using a threshold of P < .005, with 10 000 permutations and a cluster size minimum of 100 voxels. Results: Of 441 initially screened glioma patients, 423 (95.9%) met the inclusion criteria. Following DNA-methylation profiling, patients were classified into RTK II (40.7%), MES (33.8%), RTK I (18%), and other methylation subclasses (7.6%). Between molecular subtypes, there was no difference in tumor volume. Using SVR-LSM, distinct brain regions correlated with each subclass were identified: MES subtypes were associated with left-hemispheric regions involving the superior temporal gyrus and insula cortex, RTK I with right frontal regions, and RTK II with 3 clusters in the left hemisphere. Conclusions: This study linked molecular diversity and spatial features in glioblastomas using SVR-LSM. Future studies should validate these findings in larger, independent cohorts to confirm the observed patterns.

No benefit from TMZ treatment in GB with truly unmethylated MGMT promoter: Reanalysis of the CE.6 and the pooled Nordic/NOA-08 trials in elderly GB patients.

BACKGROUND: The treatment of elderly/ frail patients with glioblastoma is a balance between avoiding undue toxicity, while not withholding effective treatment. It remains debated, whether these patients should receive combined chemo-radiotherapy with temozolomide (RT/TMZ➜TMZ) regardless of the O6-methylguanine DNA methyltransferase gene promoter (MGMTp) methylation status. MGMT is a well-known resistance factor blunting the treatment effect of TMZ, by repairing the most genotoxic lesion. Epigenetic silencing of the MGMTp sensitizes glioblastoma to TMZ. For risk adapted treatment, it is of utmost importance to accurately identify patients, who will not benefit from TMZ treatment. METHODS: Here, we present a reanalysis of the clinical trials CE.6 and the pooled NOA-08 and Nordic trials in elderly glioblastoma patients that compared RT to RT/TMZ➜TMZ, or RT to TMZ, respectively. For 687 patients with available MGMTp methylation data, we applied a cutoff discerning truly unmethylated glioblastoma, established in a pooled analysis of four clinical trials for glioblastoma, with RT/TMZ➜TMZ treatment, using the same quantitative methylation specific MGMTp PCR assay. RESULTS: When applying this restricted cutoff to the elderly patient population, we confirmed that glioblastoma with truly unmethylated MGMTp derived no benefit from TMZ treatment. In the Nordic/NOA-08 trials RT was better than TMZ, suggesting little or no benefit from TMZ. CONCLUSION: For evidence-based treatment of glioblastoma patients validated MGMTp methylation assays should be used that accurately identify truly unmethylated patients. Respective stratified management of patients will reduce toxicity without compromising outcome and allow testing of more promising treatment options.

Incorporating Supramaximal Resection into Survival Stratification of IDH-Wildtype Glioblastoma: A Refined Multi-institutional Recursive Partitioning Analysis.

PURPOSE: To propose a novel recursive partitioning analysis (RPA) classification model in patients with IDH-wildtype glioblastomas that incorporates the recently expanded conception of the extent of resection (EOR) in terms of both supramaximal and total resections. EXPERIMENTAL DESIGN: This multicenter cohort study included a developmental cohort of 622 patients with IDH-wildtype glioblastomas from a single institution (Severance Hospital) and validation cohorts of 536 patients from three institutions (Seoul National University Hospital, Asan Medical Center, and Heidelberg University Hospital). All patients completed standard treatment including concurrent chemoradiotherapy and underwent testing to determine their IDH mutation and MGMTp methylation status. EORs were categorized into either supramaximal, total, or non-total resections. A novel RPA model was then developed and compared to a previous RTOG RPA model. RESULTS: In the developmental cohort, the RPA model included age, MGMTp methylation status, KPS, and EOR. Younger patients with MGMTp methylation and supramaximal resections showed a more favorable prognosis (class I: median overall survival [OS] 57.3 months), while low-performing patients with non-total resections and without MGMTp methylation showed the worst prognosis (class IV: median OS 14.3 months). The prognostic significance of the RPA was subsequently confirmed in the validation cohorts, which revealed a greater separation between prognostic classes for all cohorts compared to the previous RTOG RPA model. CONCLUSIONS: The proposed RPA model highlights the impact of supramaximal versus total resections and incorporates clinical and molecular factors into survival stratification. The RPA model may improve the accuracy of assessing prognostic groups.

Patient, Relative and Staff Experiences of Clinical Trial Participation in Neurooncology: "Maybe You Can Also Show the Positive, No Matter How It Ends".

Purpose: There is a lack of evidence regarding how patients with malignant brain tumor and their relatives experience participation in neurooncological clinical trials. Similarly, insights from the perspective of trial staff caring for this group of patients are missing. This study aims to investigate patient, relative and trial staff experiences regarding participation in clinical neurooncological trials. Methods: Within a qualitative exploratory study, 29 semi-structured interviews with brain tumor patients, relatives and trial staff were conducted and analyzed using reflexive thematic analysis (RTA) by Braun and Clarke. A patient researcher and patient council were involved in data analysis and interpretation. Results: Four themes were developed reflecting significant aspects of the trial experience: 1. "It all revolves around hope"; 2. "Trial participation: experiencing unique medical care"; 3. "Everyone's roles are changing"; 4. "Communication as a possible area of conflict". Experiencing trial participation and general medical treatment were found to be interconnected to such a degree that they were often not meaningfully distinguished by patients and relatives. Conclusion: In addition to assessing traditional endpoints for patient outcomes, we recommend increased emphasis on investigating the impact of the "soft" components constituting trial participation. Due to the interconnectedness of medical treatment and trial participation, we recommend further investigation in comparison to experiences in regular care. A deeper understanding of trial participation is needed to inform improvements for patient experiences and staff satisfaction alongside medical and scientific progress.

The treatment options available to patients with (malignant) brain tumors are currently very limited. Therefore, patients are sometimes offered to participate in a clinical trial. This means that they receive an experimental treatment (eg new medicine) for which it is not yet clear whether it works better than regular medical care. Currently, little is known about how this group of patients, their relatives and the hospital staff who care for them experience the participation in these clinical trials ­ which is what we aimed to explore in our study reported here. Based on interviews with patients, relatives and staff, we found that: trial participation mainly revolves around hope;trial participation entails experiencing unique medical care;trial participation significantly changes the previous roles of patients, relatives and staff;trial participation intensifies communication as a possible area of conflict. By providing information on how patients, relatives and staff make sense of their trial experiences, this study constitutes an important addition to the traditional focus of clinical trials on medical and scientific endpoints (eg progression-free survival). This may help clinicians and researchers involved in cancer research and treatment to understand why "unsuccessful" trials can still be perceived as positive by patients or how hopeful communication may support their patients even when perceived as "unrealistic" from the clinicians' perspective. An in depth understanding of trial participation from the perspective of those affected is needed for improved care experiences alongside medical and scientific progress for cancer treatment.

A Neuroradiologist's Guide to Operationalizing the Response Assessment in Neuro-Oncology (RANO) Criteria Version 2.0 for Gliomas in Adults.

Radiographic assessment plays a crucial role in the management of patients with central nervous system (CNS) tumors, aiding in treatment planning and evaluation of therapeutic efficacy by quantifying response. Recently, an updated version of the Response Assessment in Neuro-Oncology (RANO) criteria (RANO 2.0) was developed to improve upon prior criteria and provide an updated, standardized framework for assessing treatment response in clinical trials for gliomas in adults. This article provides an overview of significant updates to the criteria including (1) the use of a unified set of criteria for high and low grade gliomas in adults; (2) the use of the post-radiotherapy MRI scan as the baseline for evaluation in newly diagnosed high-grade gliomas; (3) the option for the trial to mandate a confirmation scan to more reliably distinguish pseudoprogression from tumor progression; (4) the option of using volumetric tumor measurements; and (5) the removal of subjective non-enhancing tumor evaluations in predominantly enhancing gliomas (except for specific therapeutic modalities). Step-by-step pragmatic guidance is hereby provided for the neuroradiologist and imaging core lab involved in operationalization and technical execution of RANO 2.0 in clinical trials, including the display of representative cases and in-depth discussion of challenging scenarios.ABBREVIATIONS: BTIP = Brain Tumor Imaging Protocol; CE = Contrast-Enhancing; CNS = Central Nervous System; CR = Complete Response; ECOG = Eastern Cooperative Oncology Group; HGG = High-Grade Glioma; IDH = Isocitrate Dehydrogenase; IRF = Independent Radiologic Facility; LGG = Low-Grade Glioma; KPS = Karnofsky Performance Status; MR = Minor Response; mRANO = Modified RANO; NANO = Neurological Assessment in Neuro-Oncology; ORR = Objective Response Rate; OS = Overall Survival; PD = Progressive Disease; PFS = Progression-Free Survival; PR = Partial Response; PsP = Pseudoprogression; RANO = Response Assessment in Neuro-Oncology; RECIST = Response Evaluation Criteria In Solid Tumors; RT = Radiation Therapy; SD = Stable Disease; Tx = Treatment.

Evolution of peripheral nerve changes in early multiple sclerosis-a longitudinal MR neurography study.

Objectives: Multiple sclerosis (MS) is a demyelinating disorder of the central nervous system. Increasing evidence indicates additional peripheral nerve involvement in early and chronic disease stages. To investigate the evolution of peripheral nerve changes in patients first diagnosed with MS using quantitative MR neurography. Materials and methods: This prospective study included 19 patients with newly diagnosed MS according to the revised McDonald criteria (16 female, mean 30.2 ± 7.1 years) and 19 age-/sex-matched healthy volunteers. High-resolution 3 T MR neurography of the sciatic nerve using a quantitative T2-relaxometry sequence was performed, which yielded the biomarkers of T2 relaxation time (T2app) and proton spin density (PSD). Follow-up scans of patients were performed after median of 12 months (range 7-16). Correlation analyses considered clinical symptoms, intrathecal immunoglobulin synthesis, nerve conduction study, and lesion load on brain and spine MRI. Results: Patients showed increased T2app and decreased PSD compared to healthy controls at initial diagnosis and follow-up (p < 0.001 each). Compared to the initial scan, T2app further increased in patients at follow-up (p = 0.003). PSD further declined by at least 10% in 9/19 patients and remained stable in another 9/19 patients. Correlation analyses did not yield significant results. Conclusion: Peripheral nerve involvement in MS appears at initial diagnosis and continues to evolve within 1 year follow-up with individual dynamics. Quantitative MRN provides non-invasive biomarkers to detect and monitor peripheral nerve changes in MS.

Plasma extracellular vesicles in meningioma patients following radiotherapy as liquid biopsy- a prospective explorative biomarker study (ARO 2023-05/AG-NRO-07).

BACKGROUND: While surgical resection remains the primary treatment approach for symptomatic or growing meningiomas, radiotherapy represents an auspicious alternative in patients with meningiomas not safely amenable to surgery. Biopsies are often omitted in light of potential postoperative neurological deficits, resulting in a lack of histological grading and (molecular) risk stratification. In this prospective explorative biomarker study, extracellular vesicles in the bloodstream will be investigated in patients with macroscopic meningiomas to identify a biomarker for molecular risk stratification and disease monitoring. METHODS: In total, 60 patients with meningiomas and an indication of radiotherapy (RT) and macroscopic tumor on the planning MRI will be enrolled. Blood samples will be obtained before the start, during, and after radiotherapy, as well as during clinical follow-up every 6 months. Extracellular vesicles will be isolated from the blood samples, quantified and correlated with the clinical treatment response or progression. Further, nanopore sequencing-based DNA methylation profiles of plasma EV-DNA will be generated for methylation-based meningioma classification. DISCUSSION: This study will explore the dynamic of plasma EVs in meningioma patients under/after radiotherapy, with the objective of identifying potential biomarkers of (early) tumor progression. DNA methylation profiling of plasma EVs in meningioma patients may enable molecular risk stratification, facilitating a molecularly-guided target volume delineation and adjusted dose prescription during RT treatment planning.

Epigenetic landscape reorganization and reactivation of embryonic development genes are associated with malignancy in IDH-mutant astrocytoma.

Accurate grading of IDH-mutant gliomas defines patient prognosis and guides the treatment path. Histological grading is however difficult and, apart from CDKN2A/B homozygous deletions in IDH-mutant astrocytomas, there are no other objective molecular markers used for grading. Experimental Design: RNA-sequencing was conducted on primary IDH-mutant astrocytomas (n=138) included in the prospective CATNON trial, which was performed to assess the prognostic effect of adjuvant and concurrent temozolomide. We integrated the RNA sequencing data with matched DNA-methylation and NGS data. We also used multi-omics data from IDH-mutant astrocytomas included in the TCGA dataset and validated results on matched primary and recurrent samples from the GLASS-NL study. We used the DNA-methylation profiles to generate a Continuous Grading Coefficient (CGC) that is based on classification scores derived from a CNS-tumor classifier. We found that the CGC was an independent predictor of survival outperforming current WHO-CNS5 and methylation-based classification. Our RNA-sequencing analysis revealed four distinct transcription clusters that were associated with i) an upregulation of cell cycling genes; ii) a downregulation of glial differentiation genes; iii) an upregulation of embryonic development genes (e.g. HOX, PAX and TBX) and iv) an upregulation of extracellular matrix genes. The upregulation of embryonic development genes was associated with a specific increase of CpG island methylation near these genes.

Advancing noninvasive glioma classification with diffusion radiomics: Exploring the impact of signal intensity normalization.

Background: This study investigates the influence of diffusion-weighted Magnetic Resonance Imaging (DWI-MRI) on radiomic-based prediction of glioma types according to molecular status and assesses the impact of DWI intensity normalization on model generalizability. Methods: Radiomic features, compliant with image biomarker standardization initiative standards, were extracted from preoperative MRI of 549 patients with diffuse glioma, known IDH, and 1p19q-status. Anatomical sequences (T1, T1c, T2, FLAIR) underwent N4-Bias Field Correction (N4) and WhiteStripe normalization (N4/WS). Apparent diffusion coefficient (ADC) maps were normalized using N4 or N4/z-score. Nine machine-learning algorithms were trained for multiclass prediction of glioma types (IDH-mutant 1p/19q codeleted, IDH-mutant 1p/19q non-codeleted, IDH-wild type). Four approaches were compared: Anatomical, anatomical + ADC naive, anatomical + ADC N4, and anatomical + ADC N4/z-score. The University of California San Francisco (UCSF)-glioma dataset (n = 409) was used for external validation. Results: Naïve-Bayes algorithms yielded overall the best performance on the internal test set. Adding ADC radiomics significantly improved AUC from 0.79 to 0.86 (P = .011) for the IDH-wild-type subgroup, but not for the other 2 glioma subgroups (P > .05). In the external UCSF dataset, the addition of ADC radiomics yielded a significantly higher AUC for the IDH-wild-type subgroup (P ≤ .001): 0.80 (N4/WS anatomical alone), 0.81 (anatomical + ADC naive), 0.81 (anatomical + ADC N4), and 0.88 (anatomical + ADC N4/z-score) as well as for the IDH-mutant 1p/19q non-codeleted subgroup (P < .012 each). Conclusions: ADC radiomics can enhance the performance of conventional MRI-based radiomic models, particularly for IDH-wild-type glioma. The benefit of intensity normalization of ADC maps depends on the type and context of the used data.

3D volume growth rate evaluation in the EORTC-BTG-1320 clinical trial for recurrent WHO grade 2 and 3 meningiomas.

BACKGROUND: We previously reported that tumor 3D volume growth rate (3DVGR) classification could help in the assessment of drug activity in patients with meningioma using 3 main classes and a total of 5 subclasses: class 1: decrease; 2: stabilization or severe slowdown; 3: progression. The EORTC-BTG-1320 clinical trial was a randomized phase II trial evaluating the efficacy of trabectedin for recurrent WHO 2 or 3 meningioma. Our objective was to evaluate the discriminative value of 3DVGR classification in the EORTC-BTG-1320. METHODS: All patients with at least 1 available MRI before trial inclusion were included. 3D volume was evaluated on consecutive MRI until progression. 2D imaging response was centrally assessed by MRI modified Macdonald criteria. Clinical benefit was defined as neurological or functional status improvement or steroid decrease or discontinuation. RESULTS: Sixteen patients with a median age of 58.5 years were included. Best 3DVGR classes were: 1, 2A, 3A, and 3B in 2 (16.7%), 4 (33.3%), 2 (16.7%), and 4 (33.3%) patients, respectively. All patients with progression-free survival longer than 6 months had best 3DVGR class 1 or 2. 3DVGR classes 1 and 2 (combined) had a median overall survival of 34.7 months versus 7.2 months for class 3 (P = .061). All class 1 patients (2/2), 75% of class 2 patients (3/4), and only 10% of class 3 patients (1/10) had clinical benefit. CONCLUSIONS: Tumor 3DVGR classification may be helpful to identify early signals of treatment activity in meningioma clinical trials.

A clinically applicable connectivity signature for glioblastoma includes the tumor network driver CHI3L1.

Tumor microtubes (TMs) connect glioma cells to a network with considerable relevance for tumor progression and therapy resistance. However, the determination of TM-interconnectivity in individual tumors is challenging and the impact on patient survival unresolved. Here, we establish a connectivity signature from single-cell RNA-sequenced (scRNA-Seq) xenografted primary glioblastoma (GB) cells using a dye uptake methodology, and validate it with recording of cellular calcium epochs and clinical correlations. Astrocyte-like and mesenchymal-like GB cells have the highest connectivity signature scores in scRNA-sequenced patient-derived xenografts and patient samples. In large GB cohorts, TM-network connectivity correlates with the mesenchymal subtype and dismal patient survival. CHI3L1 gene expression serves as a robust molecular marker of connectivity and functionally influences TM networks. The connectivity signature allows insights into brain tumor biology, provides a proof-of-principle that tumor cell TM-connectivity is relevant for patients' prognosis, and serves as a robust prognostic biomarker.

Deep-learning-based reconstruction of undersampled MRI to reduce scan times: a multicentre, retrospective, cohort study.

BACKGROUND: The extended acquisition times required for MRI limit its availability in resource-constrained settings. Consequently, accelerating MRI by undersampling k-space data, which is necessary to reconstruct an image, has been a long-standing but important challenge. We aimed to develop a deep convolutional neural network (dCNN) optimisation method for MRI reconstruction and to reduce scan times and evaluate its effect on image quality and accuracy of oncological imaging biomarkers. METHODS: In this multicentre, retrospective, cohort study, MRI data from patients with glioblastoma treated at Heidelberg University Hospital (775 patients and 775 examinations) and from the phase 2 CORE trial (260 patients, 1083 examinations, and 58 institutions) and the phase 3 CENTRIC trial (505 patients, 3147 examinations, and 139 institutions) were used to develop, train, and test dCNN for reconstructing MRI from highly undersampled single-coil k-space data with various acceleration rates (R=2, 4, 6, 8, 10, and 15). Independent testing was performed with MRIs from the phase 2/3 EORTC-26101 trial (528 patients with glioblastoma, 1974 examinations, and 32 institutions). The similarity between undersampled dCNN-reconstructed and original MRIs was quantified with various image quality metrics, including structural similarity index measure (SSIM) and the accuracy of undersampled dCNN-reconstructed MRI on downstream radiological assessment of imaging biomarkers in oncology (automated artificial intelligence-based quantification of tumour burden and treatment response) was performed in the EORTC-26101 test dataset. The public NYU Langone Health fastMRI brain test dataset (558 patients and 558 examinations) was used to validate the generalisability and robustness of the dCNN for reconstructing MRIs from available multi-coil (parallel imaging) k-space data. FINDINGS: In the EORTC-26101 test dataset, the median SSIM of undersampled dCNN-reconstructed MRI ranged from 0·88 to 0·99 across different acceleration rates, with 0·92 (95% CI 0·92-0·93) for 10-times acceleration (R=10). The 10-times undersampled dCNN-reconstructed MRI yielded excellent agreement with original MRI when assessing volumes of contrast-enhancing tumour (median DICE for spatial agreement of 0·89 [95% CI 0·88 to 0·89]; median volume difference of 0·01 cm3 [95% CI 0·00 to 0·03] equalling 0·21%; p=0·0036 for equivalence) or non-enhancing tumour or oedema (median DICE of 0·94 [95% CI 0·94 to 0·95]; median volume difference of -0·79 cm3 [95% CI -0·87 to -0·72] equalling -1·77%; p=0·023 for equivalence) in the EORTC-26101 test dataset. Automated volumetric tumour response assessment in the EORTC-26101 test dataset yielded an identical median time to progression of 4·27 months (95% CI 4·14 to 4·57) when using 10-times-undersampled dCNN-reconstructed or original MRI (log-rank p=0·80) and agreement in the time to progression in 374 (95·2%) of 393 patients with data. The dCNN generalised well to the fastMRI brain dataset, with significant improvements in the median SSIM when using multi-coil compared with single-coil k-space data (p<0·0001). INTERPRETATION: Deep-learning-based reconstruction of undersampled MRI allows for a substantial reduction of scan times, with a 10-times acceleration demonstrating excellent image quality while preserving the accuracy of derived imaging biomarkers for the assessment of oncological treatment response. Our developments are available as open source software and hold considerable promise for increasing the accessibility to MRI, pending further prospective validation. FUNDING: Deutsche Forschungsgemeinschaft (German Research Foundation) and an Else Kröner Clinician Scientist Endowed Professorship by the Else Kröner Fresenius Foundation.