Search

We greatly appreciate Dr. Stummer's and Dr. Thomas's interest in our study and their important comments [...].

For patients with presumed glioblastoma, essential tumor characteristics are determined from preoperative MR images to optimize the treatment strategy. This procedure is time-consuming and subjective, if performed by crude eyeballing or manually. The standardized GSI-RADS aims to provide neurosurgeons with automatic tumor segmentations to extract tumor features rapidly and objectively. In this study, we improved automatic tumor segmentation and compared the agreement with manual raters, describe the technical details of the different components of GSI-RADS, and determined their speed. Two recent neural network architectures were considered for the segmentation task: nnU-Net and AGU-Net. Two preprocessing schemes were introduced to investigate the tradeoff between performance and processing speed. A summarized description of the tumor feature extraction and standardized reporting process is included. The trained architectures for automatic segmentation and the code for computing the standardized report are distributed as open-source and as open-access software. Validation studies were performed on a dataset of 1594 gadolinium-enhanced T1-weighted MRI volumes from 13 hospitals and 293 T1-weighted MRI volumes from the BraTS challenge. The glioblastoma tumor core segmentation reached a Dice score slightly below 90%, a patientwise F1-score close to 99%, and a 95th percentile Hausdorff distance slightly below 4.0 mm on average with either architecture and the heavy preprocessing scheme. A patient MRI volume can be segmented in less than one minute, and a standardized report can be generated in up to five minutes. The proposed GSI-RADS software showed robust performance on a large collection of MRI volumes from various hospitals and generated results within a reasonable runtime.

Treatment decisions for patients with presumed glioblastoma are based on tumor characteristics available from a preoperative MR scan. Tumor characteristics, including volume, location, and resectability, are often estimated or manually delineated. This process is time consuming and subjective. Hence, comparison across cohorts, trials, or registries are subject to assessment bias. In this study, we propose a standardized Glioblastoma Surgery Imaging Reporting and Data System (GSI-RADS) based on an automated method of tumor segmentation that provides standard reports on tumor features that are potentially relevant for glioblastoma surgery. As clinical validation, we determine the agreement in extracted tumor features between the automated method and the current standard of manual segmentations from routine clinical MR scans before treatment. In an observational consecutive cohort of 1596 adult patients with a first time surgery of a glioblastoma from 13 institutions, we segmented gadolinium-enhanced tumor parts both by a human rater and by an automated algorithm. Tumor features were extracted from segmentations of both methods and compared to assess differences, concordance, and equivalence. The laterality, contralateral infiltration, and the laterality indices were in excellent agreement. The native and normalized tumor volumes had excellent agreement, consistency, and equivalence. Multifocality, but not the number of foci, had good agreement and equivalence. The location profiles of cortical and subcortical structures were in excellent agreement. The expected residual tumor volumes and resectability indices had excellent agreement, consistency, and equivalence. Tumor probability maps were in good agreement. In conclusion, automated segmentations are in excellent agreement with manual segmentations and practically equivalent regarding tumor features that are potentially relevant for neurosurgical purposes. Standard GSI-RADS reports can be generated by open access software.

The prediction of the individual prognosis of low-grade glioma (LGG) patients is limited in routine clinical practice. Nowadays, 5-aminolevulinic acid (5-ALA) fluorescence is primarily applied for improved intraoperative visualization of high-grade gliomas. However, visible fluorescence is also observed in rare cases despite LGG histopathology and might be an indicator for aggressive tumor behavior. The aim of this study was thus to investigate the value of intraoperative 5-ALA fluorescence for prognosis in LGG patients. We performed a retrospective analysis of patients with newly diagnosed histopathologically confirmed LGG and preoperative 5-ALA administration at two independent specialized centers. In this cohort, we correlated the visible intraoperative fluorescence status with progression-free survival (PFS), malignant transformation-free survival (MTFS) and overall survival (OS). Altogether, visible fluorescence was detected in 7 (12%) of 59 included patients in focal intratumoral areas. At a mean follow-up time of 5.3 ± 2.9 years, patients with fluorescing LGG had significantly shorter PFS (2.3 ± 0.7 vs. 5.0 ± 0.4 years; p = 0.01), MTFS (3.9 ± 0.7 vs. 8.0 ± 0.6 years; p = 0.03), and OS (5.4 ± 1.0 vs. 10.3 ± 0.5 years; p = 0.01) than non-fluorescing tumors. Our data indicate that visible 5-ALA fluorescence during surgery of pure LGG might be an already intraoperatively available marker of unfavorable patient outcome and thus close imaging follow-up might be considered.

Diffusely infiltrating gliomas are characterized by a variable clinical course, and thus novel prognostic biomarkers are needed. The heme biosynthesis cycle constitutes a fundamental metabolic pathway and might play a crucial role in glioma biology. The aim of this study was thus to investigate the role of the heme biosynthesis mRNA expression signature on prognosis in a large glioma patient cohort. Glioma patients with available sequencing data on heme biosynthesis expression were retrieved from The Cancer Genome Atlas (TCGA). In each patient, the heme biosynthesis mRNA expression signature was calculated and categorized into low, medium, and high expression subgroups. Differences in progression-free and overall survival between these subgroups were investigated including a multivariate analysis correcting for WHO grade, tumor subtype, and patient age and sex. In a total of 693 patients, progression-free and overall survival showed a strictly monotonical decrease with increasing mRNA expression signature subgroups. In detail, median overall survival was 134.2 months in the low, 79.9 months in the intermediate, and 16.5 months in the high mRNA expression signature subgroups, respectively. The impact of mRNA expression signature on progression-free and overall survival was independent of the other analyzed prognostic factors. Our data indicate that the heme biosynthesis mRNA expression signature might serve as an additional novel prognostic marker in patients with diffusely infiltrating gliomas to optimize postoperative management.

5-Aminolevulinic acid (5-ALA) is a fluorescent dye that after metabolization to Protoporphyrin IX (PpIX) by the heme biosynthesis pathway typically leads to visible fluorescence in WHO grade IV but not grade II gliomas. The exact mechanism for high PpIX levels in WHO grade IV gliomas and low PpIX levels in WHO grade II gliomas is not fully clarified. To detect relevant changes in mRNA expression, we performed an in-silico analysis of WHO grade II and IV glioma sequencing datasets provided by The Cancer Genome Atlas (TCGA) to investigate mRNA expression levels of relevant heme biosynthesis genes: Solute Carrier Family 15 Member 1 and 2 (SLC15A1 and SLC15A2), Aminolevulinate-Dehydratase (ALAD), Hydroxymethylbilane-Synthase (HMBS), Uroporphyrinogen-III-Synthase (UROS), Uroporphyrinogen-Decarboxylase (UROD), Coproporphyrinogen-Oxidase (CPOX), Protoporphyrinogen-Oxidase (PPOX), ATP-binding Cassette Subfamily B Member 6 (ABCB6)/G Member 2 (ABCG2) and Ferrochelatase (FECH). Altogether, 258 WHO grade II and 166 WHO grade IV samples were investigated. The mRNA expression levels showed significant differences in 8 of 11 examined genes between WHO grade II and IV gliomas. Significant differences in mRNA expression included increases of HMBS, UROD, FECH and PPOX as well as decreases of SLC15A2, ALAD, UROS and ABCB6 in WHO IV gliomas. Since the majority of changes was found in directions that might actually impair PpIX accumulation in WHO grade IV gliomas, additional studies are needed to analyze the corresponding factors of the heme biosynthesis also on protein level.