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Objectives: Chemical exchange saturation transfer (CEST) imaging has emerged as a promising imaging biomarker, but its reliability for clinical practice remains uncertain. This study aimed to investigate the robustness of CEST parameters in healthy volunteers and patients with brain tumours., Methods: A total of n = 52 healthy volunteers and n = 52 patients with histologically confirmed glioma underwent two consecutive 3-T MRI scans separated by a 1-min break. The CEST measurements were reconstructed using two models: with and without fluid suppression and included the evaluation of both amide (amidePTw) and amine (aminePTw) offsets. Mean intensity values in healthy volunteers were compared from volumetric segmentations (VOI) of grey matter, white matter, and the whole brain. Mean intensity values in brain tumour patients were assessed from VOI of the contrast-enhancing, non-enhancing and whole tumour, as well as from the normal-appearing white matter. Test-retest reliability was assessed using ICC and Bland-Altman plots., Results: The amidePTw/aminePTw signal intensity distribution was significantly affected by fluid suppression (p < 0.001 for each VOI). Test-retest reliability in healthy volunteers showed fair to excellent agreement (ICC = 0.53-0.74), with the highest signal intensity values observed by amidePTw (ICC = 0.73-0.74). In patients, an excellent agreement of both amidePTw and aminePTw measurements was observed across different tumour regions (ICC = 0.76-0.89), with the highest ICC for contrast-enhancing tumour measurements. Bland-Altman analysis indicated negligible systematic bias and no proportional bias in measurement errors., Conclusion: Measurements from amide/aminePTw imaging obtained from an adequately powered test-retest study yield consistent and reproducible results in glioma patients, as a prerequisite for robust imaging biomarker discovery in neuro-oncology., Key Points: Question The clinical reliability of chemical exchange saturation transfer imaging remains uncertain, necessitating further investigation to establish its robustness as a biomarker in neuro-oncology. Findings This study demonstrates that amide/amine proton transfer imaging provides repeatable, high-agreement measurements in glioma patients, particularly in contrast-enhancing tumour regions. Clinical relevance This test-retest study demonstrates that chemical exchange saturation transfer imaging using two models and assessing amide and amine offsets yield consistent and repeatable results in glioma patients, as a prerequisite for robust imaging biomarker discovery for neuro-oncology studies and clinical practice., Competing Interests: Compliance with ethical standards. Guarantor: The scientific guarantor of this publication is Prof. Philipp Vollmuth. Conflict of interest: The authors of this manuscript declare relationships with the following companies: S.C. and C.P. are employees of Olea Medical. P.L. is an employee of Siemens Healthcare Gmbh. The remaining authors declare no conflicts of interest. Statistics and biometry: One of the authors has significant statistical expertise (Rouven Behnisch). Informed consent: Written informed consent was obtained from all subjects (patients) in this study. Ethical approval: Institutional Review Board approval was obtained. Study subjects or cohorts overlap: Study subjects or cohorts have never been previously reported. Methodology: Prospective Case-control study Performed at one institution, (© 2024. The Author(s), under exclusive licence to European Society of Radiology.)

Objectives: Recurrent glioma is highly treatment resistant due to its metabolic, cellular, and molecular heterogeneity and invasiveness. Tumor monitoring by conventional MRI has shortcomings to assess these key glioma characteristics. Recent studies introduced chemical exchange saturation transfer for metabolic imaging in oncology and assessed its diagnostic value for newly diagnosed glioma. This prospective study investigates amide proton transfer-weighted (APTw) MRI at 3 T as an imaging biomarker to elucidate the molecular heterogeneity and invasion patterns of recurrent glioma in comparison to pseudoprogression (PsPD)., Materials and Methods: We performed a monocenter, prospective trial and screened 371 glioma patients who received tumor monitoring between August 2021 and March 2024 at our institution. The study included IDH wildtype astrocytoma and IDH mutant astrocytoma and oligodendroglioma, graded according to the WHO 2021 classification. Patients had received clinical standard of care treatment including surgical resection and radiochemotherapy prior to study inclusion. Patients were monitored by 3 monthly MRI follow-up imaging, and response assessment was performed according to the RANO criteria. Within this cohort, we identified 30 patients who presented with recurrent glioma and 12 patients with PsPD. In addition to standard anatomical sequences (FLAIR and T1-w Gd-enhanced sequences), MRI included APTw imaging. After sequence co-registration, semiautomated segmentation was performed of the FLAIR lesion, CE lesion, resection cavity, and the contralateral normal-appearing white matter, and APTw signals were quantified in these regions of interest., Results: APTw values were highest in solid, Gd-enhancing tumor parts as compared with the nonenhancing FLAIR lesion (APTw: 1.99% vs 1.36%, P = 0.001), whereas there were no detectable APTw alterations in the normal-appearing white matter (APTw: 0.005%, P < 0.001 compared with FLAIR). Patients with progressive disease had higher APTw levels compared with patients with PsPD (APTw: 1.99% vs 1.26%, P = 0.008). Chemical exchange saturation transfer identified heterogeneity within the FLAIR lesion that was not detectable by conventional sequences. There were also focal APTw signal peaks within contrast enhancing lesions as putative metabolic hotspots within recurrent glioma. The resection cavity developed an APTw increase at recurrence that was not detectable prior to recurrence nor in patients with PsPD (APTw before recurrence: 0.6% vs 2.68% at recurrence, P = 0.03)., Conclusions: Our study shows that APTw imaging can differentiate PD and PsPD. We identify previously undetectable imaging patterns during glioma recurrence, which include alterations within resection cavity associated with disease progression. Our work highlights the clinical potential of APTw imaging for glioma monitoring and further establishes it as an imaging biomarker in neuro-oncology., Competing Interests: Conflicts of interest and sources of funding: none declared., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)

The translation of AI-generated brain metastases (BM) segmentation into clinical practice relies heavily on diverse, high-quality annotated medical imaging datasets. The BraTS-METS 2023 challenge has gained momentum for testing and benchmarking algorithms using rigorously annotated internationally compiled real-world datasets. This study presents the results of the segmentation challenge and characterizes the challenging cases that impacted the performance of the winning algorithms. Untreated brain metastases on standard anatomic MRI sequences (T1, T2, FLAIR, T1PG) from eight contributed international datasets were annotated in stepwise method: published UNET algorithms, student, neuroradiologist, final approver neuroradiologist. Segmentations were ranked based on lesion-wise Dice and Hausdorff distance (HD95) scores. False positives (FP) and false negatives (FN) were rigorously penalized, receiving a score of 0 for Dice and a fixed penalty of 374 for HD95. The mean scores for the teams were calculated. Eight datasets comprising 1303 studies were annotated, with 402 studies (3076 lesions) released on Synapse as publicly available datasets to challenge competitors. Additionally, 31 studies (139 lesions) were held out for validation, and 59 studies (218 lesions) were used for testing. Segmentation accuracy was measured as rank across subjects, with the winning team achieving a LesionWise mean score of 7.9. The Dice score for the winning team was 0.65 ± 0.25. Common errors among the leading teams included false negatives for small lesions and misregistration of masks in space. The Dice scores and lesion detection rates of all algorithms diminished with decreasing tumor size, particularly for tumors smaller than 100 mm3. In conclusion, algorithms for BM segmentation require further refinement to balance high sensitivity in lesion detection with the minimization of false positives and negatives. The BraTS-METS 2023 challenge successfully curated well-annotated, diverse datasets and identified common errors, facilitating the translation of BM segmentation across varied clinical environments and providing personalized volumetric reports to patients undergoing BM treatment., Competing Interests: Conflicts of Interest No conflicts of interest to disclose.

Background: To date, fiber tractography (FT) is predominantly based on diffusion tensor imaging (DTI). High angular resolution diffusion imaging (HARDI)-based reconstructions have become a focus of interest, enabling the resolution of intravoxel fiber crossing. However, experience with high resolution tractography (HRFT) for neurosurgical applications is still limited to a few reports. This prospectively designed feasibility study shares our initial experience using an analytical q-ball approach (QBI) for FT of language-associated pathways in comparison with DTI-FT, focussing on a quantitative analysis and evaluation of its applicability in clinical routine., Methods: Probabilistic QBI-, and DTI-FT were performed for the major components of the language-associated fiber bundles (superior longitudinal fasciculus, inferior fronto-occipital fasciculus, medial/inferior longitudinal faciculus) in 11 patients with eloquent gliomas. The data was derived from a routine DWI sequence (b=1000s/mm 2 , 64 gradient directions). Quantitative analysis evaluated tract volume (TV), tract length (TL) and tract density (TD). Results were correlated to tumor and edema size., Results: Quantitative analysis showed larger TV and TL of the overall fiber object using QBI-FT compared with DTI-FT (TV: 16.45±1.85 vs. 10.07±1.15cm 3 ; P<0.0001; TL: 81.95±6.14 vs. 72.06±6.92 mm; P=0.0011). Regarding overall TD, DTI delivered significantly higher values (40.57±6.59 vs. 60.98±15.94 points/voxel; P=0.0118). Bland-Altman analysis illustrated a systematic advantage to yield lager TV and TL via QBI compared with DTI for all reconstructed pathways. The results were independent of tumor or edema volume., Conclusions: QBI proved to be suitable for an application in the neurosurgical setting without additional expense for the patient. Quantitative analysis of FT reveals larger overall TV, longer TL with lower TD using QBI compared with DTI, suggesting the better depiction of marginal and terminal fibers according to neuroanatomical knowledge. This emphasizes the known limitation of DTI to underestimate the dimensions of a pathway. Rather than relying on DTI, sophisticated HRFT techniques should be considered for preoperative planning and intraoperative guidance in selected cases of eloquent glioma surgery.

Purpose: Fiber tracking (FT) is used in neurosurgical planning for the resection of lesions in proximity to fiber pathways, as it contributes to a substantial amelioration of postoperative neurological impairments. Currently, diffusion-tensor imaging (DTI)-based FT is the most frequently used technique; however, sophisticated techniques such as Q-ball (QBI) for high-resolution FT (HRFT) have suggested favorable results. Little is known about the reproducibility of both techniques in the clinical setting. Therefore, this study aimed to examine the intra- and interrater agreement for the depiction of white matter pathways such as the corticospinal tract (CST) and the optic radiation (OR)., Methods: Nineteen patients with eloquent lesions in the proximity of the OR or CST were prospectively enrolled. Two different raters independently reconstructed the fiber bundles by applying probabilistic DTI- and QBI-FT. Interrater agreement was evaluated from the comparison between results obtained by the two raters on the same data set acquired in two independent iterations at different timepoints using the Dice Similarity Coefficient (DSC) and the Jaccard Coefficient (JC). Likewise, intrarater agreement was determined for each rater comparing individual results., Results: DSC values showed substantial intrarater agreement based on DTI-FT (rater 1: mean 0.77 (0.68-0.85); rater 2: mean 0.75 (0.64-0.81); p = 0.673); while an excellent agreement was observed after the deployment of QBI-based FT (rater 1: mean 0.86 (0.78-0.98); rater 2: mean 0.80 (0.72-0.91); p = 0.693). In contrast, fair agreement was observed between both measures for the repeatability of the OR of each rater based on DTI-FT (rater 1: mean 0.36 (0.26-0.77); rater 2: mean 0.40 (0.27-0.79), p = 0.546). A substantial agreement between the measures was noted by applying QBI-FT (rater 1: mean 0.67 (0.44-0.78); rater 2: mean 0.62 (0.32-0.70), 0.665). The interrater agreement was moderate for the reproducibility of the CST and OR for both DSC and JC based on DTI-FT (DSC and JC ≥ 0.40); while a substantial interrater agreement was noted for DSC after applying QBI-based FT for the delineation of both fiber tracts (DSC > 0.6)., Conclusions: Our findings suggest that QBI-based FT might be a more robust tool for the visualization of the OR and CST adjacent to intracerebral lesions compared with the common standard DTI-FT. For neurosurgical planning during the daily workflow, QBI appears to be feasible and less operator-dependent., (© 2023. The Author(s).)

Background: Reliable detection and precise volumetric quantification of brain metastases (BM) on MRI are essential for guiding treatment decisions. Here we evaluate the potential of artificial neural networks (ANN) for automated detection and quantification of BM., Methods: A consecutive series of 308 patients with BM was used for developing an ANN (with a 4:1 split for training/testing) for automated volumetric assessment of contrast-enhancing tumors (CE) and non-enhancing FLAIR signal abnormality including edema (NEE). An independent consecutive series of 30 patients was used for external testing. Performance was assessed case-wise for CE and NEE and lesion-wise for CE using the case-wise/lesion-wise DICE-coefficient (C/L-DICE), positive predictive value (L-PPV) and sensitivity (C/L-Sensitivity)., Results: The performance of detecting CE lesions on the validation dataset was not significantly affected when evaluating different volumetric thresholds (0.001-0.2 cm 3 ; P = .2028). The median L-DICE and median C-DICE for CE lesions were 0.78 (IQR = 0.6-0.91) and 0.90 (IQR = 0.85-0.94) in the institutional as well as 0.79 (IQR = 0.67-0.82) and 0.84 (IQR = 0.76-0.89) in the external test dataset. The corresponding median L-Sensitivity and median L-PPV were 0.81 (IQR = 0.63-0.92) and 0.79 (IQR = 0.63-0.93) in the institutional test dataset, as compared to 0.85 (IQR = 0.76-0.94) and 0.76 (IQR = 0.68-0.88) in the external test dataset. The median C-DICE for NEE was 0.96 (IQR = 0.92-0.97) in the institutional test dataset as compared to 0.85 (IQR = 0.72-0.91) in the external test dataset., Conclusion: The developed ANN-based algorithm (publicly available at www.github.com/NeuroAI-HD/HD-BM) allows reliable detection and precise volumetric quantification of CE and NEE compartments in patients with BM., (© The Author(s) 2022. Published by Oxford University Press, the Society for Neuro-Oncology and the European Association of Neuro-Oncology.)

Objective: Fiber tractography (FT) has become an important noninvasive tool to ensure maximal safe tumor resection in eloquent glioma surgery. Intraoperatively applied FT is still predominantly based on diffusion tensor imaging (DTI). However, reconstruction schemes of high angular resolution diffusion imaging data for high-resolution FT (HRFT) are gaining increasing attention. The aim of this prospective study was to compare the accuracy of sophisticated HRFT models compared with DTI-FT., Methods: Ten patients with eloquent gliomas underwent surgery under awake craniotomy conditions. The localization of acquisition points, representing deteriorations during intraoperative electrostimulation (IOM) and neuropsychological mapping, were documented. The offsets of acquisition points to the respective fiber bundle were calculated. Probabilistic Q-ball imaging (QBI) and constrained spherical deconvolution (CSD)-FT were compared with DTI-FT for the major language-associated fiber bundles (superior longitudinal fasciculus [SLF] II-IV, inferior fronto-occipital fasciculus, and inferior longitudinal fasciculus/medial longitudinal fasciculus)., Results: Among 186 offset values, 46% were located closer than 10 mm to the estimated fiber bundle (CSD, 36%; DTI, 40% and QBI, 60%). Moreover, only 10 offsets were further away than 30 mm (5%). Lowest mean minimum offsets (SLF, 7.7 ± 7.9 mm; inferior fronto-occipital fasciculus, 12.7 ± 8.3 mm; inferior longitudinal fasciculus/medial longitudinal fasciculus, 17.7 ± 6.7 mm) were found for QBI, indicating a significant advantage compared with CSD or DTI (P < 0.001), respectively. No significant differences were found between CSD-FT and DTI-FT offsets (P = 0.105), albeit for the compound SLF exclusively (P < 0.001)., Conclusions: Comparing HRFT techniques QBI and CSD with DTI, QBI delivered significantly better results with lowest offsets and good correlation to IOM results. Besides, QBI-FT was feasible for neurosurgical preoperative and intraoperative applications. Our findings suggest that a combined approach of QBI-FT and IOM under awake craniotomy is considerable for best preservation of neurological function in the presented setting. Overall, the implementation of selected HRFT models into neuronavigation systems seems to be a promising tool in glioma surgery., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Background: Gadolinium-based contrast agents (GBCAs) are widely used to enhance tissue contrast during MRI scans and play a crucial role in the management of patients with cancer. However, studies have shown gadolinium deposition in the brain after repeated GBCA administration with yet unknown clinical significance. We aimed to assess the feasibility and diagnostic value of synthetic post-contrast T1-weighted MRI generated from pre-contrast MRI sequences through deep convolutional neural networks (dCNN) for tumour response assessment in neuro-oncology., Methods: In this multicentre, retrospective cohort study, we used MRI examinations to train and validate a dCNN for synthesising post-contrast T1-weighted sequences from pre-contrast T1-weighted, T2-weighted, and fluid-attenuated inversion recovery sequences. We used MRI scans with availability of these sequences from 775 patients with glioblastoma treated at Heidelberg University Hospital, Heidelberg, Germany (775 MRI examinations); 260 patients who participated in the phase 2 CORE trial (1083 MRI examinations, 59 institutions); and 505 patients who participated in the phase 3 CENTRIC trial (3147 MRI examinations, 149 institutions). Separate training runs to rank the importance of individual sequences and (for a subset) diffusion-weighted imaging were conducted. Independent testing was performed on MRI data from the phase 2 and phase 3 EORTC-26101 trial (521 patients, 1924 MRI examinations, 32 institutions). The similarity between synthetic and true contrast enhancement on post-contrast T1-weighted MRI was quantified using the structural similarity index measure (SSIM). Automated tumour segmentation and volumetric tumour response assessment based on synthetic versus true post-contrast T1-weighted sequences was performed in the EORTC-26101 trial and agreement was assessed with Kaplan-Meier plots., Findings: The median SSIM score for predicting contrast enhancement on synthetic post-contrast T1-weighted sequences in the EORTC-26101 test set was 0·818 (95% CI 0·817-0·820). Segmentation of the contrast-enhancing tumour from synthetic post-contrast T1-weighted sequences yielded a median tumour volume of 6·31 cm 3 (5·60 to 7·14), thereby underestimating the true tumour volume by a median of -0·48 cm 3 (-0·37 to -0·76) with the concordance correlation coefficient suggesting a strong linear association between tumour volumes derived from synthetic versus true post-contrast T1-weighted sequences (0·782, 0·751-0·807, p<0·0001). Volumetric tumour response assessment in the EORTC-26101 trial showed a median time to progression of 4·2 months (95% CI 4·1-5·2) with synthetic post-contrast T1-weighted and 4·3 months (4·1-5·5) with true post-contrast T1-weighted sequences (p=0·33). The strength of the association between the time to progression as a surrogate endpoint for predicting the patients' overall survival in the EORTC-26101 cohort was similar when derived from synthetic post-contrast T1-weighted sequences (hazard ratio of 1·749, 95% CI 1·282-2·387, p=0·0004) and model C-index (0·667, 0·622-0·708) versus true post-contrast T1-weighted MRI (1·799, 95% CI 1·314-2·464, p=0·0003) and model C-index (0·673, 95% CI 0·626-0·711)., Interpretation: Generating synthetic post-contrast T1-weighted MRI from pre-contrast MRI using dCNN is feasible and quantification of the contrast-enhancing tumour burden from synthetic post-contrast T1-weighted MRI allows assessment of the patient's response to treatment with no significant difference by comparison with true post-contrast T1-weighted sequences with administration of GBCAs. This finding could guide the application of dCNN in radiology to potentially reduce the necessity of GBCA administration., Funding: Deutsche Forschungsgemeinschaft., Competing Interests: Declaration of interests SH reports grants from the German Research Council and Dietmar-Hopp Foundation, outside of the submitted work. JD reports grants from ViewRay, the Clinical Research Institute, Accuray, RaySearch Laboratories, Vision RT, Merck, Astellas Pharma, AstraZeneca, Siemens Healthcare, Solution Akademie, Egomed, Quintiles, Pharmaceutical Research Association, Boehringer Ingelheim, PTW-Freiburg, and Nanobiotix, outside of the submitted work. MP reports non-financial support from Pfizer, and grants and personal fees from Bayer, outside of the submitted work. MP also has a licensed patent for IDH1 vaccines, a patent H3 vaccine pending, and a patent AHR inhibitor with royalties paid to Bayer. AI reports grants and travel funding from Carthera; research grants from Transgene, Sanofi, Air Liquide, and Nutritheragene; travel funding from Leo Pharma; and is on the advisory board for Novocure and Leo Pharma, outside the submitted work. MjvdB reports personal fees from Roche, Cellgene, Bristol Myers Squibb, Agios, Merck Sharpe & Dohme, and Boehringer Ingelheim; and grants and personal fees from AbbVie, outside of the submitted work. BN is on the scientific advisory board for Karyopharm and BTG Pharmaceuticals and is on the data safety and monitoring board for the University of Pennsylvania (Philadelphia, PA, USA), outside of the submitted work. J-CT reports personal fees from BrainLab and carThera, outside of the submitted work. WW reports grants from Apogenix, Boehringer Ingelheim, and Pfizer; grants and personal fees from Merck Sharp and Dohme and Roche; and personal fees from Bristol Myers Squibb and Celldex, outside of the submitted work. MB reports personal fees from Boehringer Ingelheim, Merck, Bayer, Teva, B Braun, Springer, and Vascular Dynamics; grants and personal fees from Novartis, Codman, and Guerbet; and grants from Siemens, Hopp Foundation, the German Research Council, the EU, Stryker, and Medtronic, outside of the submitted work. All other authors declare no competing interests., (Copyright © 2021 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Tryptophan (Trp)-catabolic enzymes (TCEs) produce metabolites that activate the aryl hydrocarbon receptor (AHR) and promote tumor progression and immunosuppression in glioblastoma. As therapies targeting TCEs or AHR become available, a better understanding of Trp metabolism is required. Methods: The combination of LC-MS/MS with chemical isobaric labeling enabled the simultaneous quantitative comparison of Trp and its amino group-bearing metabolites in multiple samples. We applied this method to the sera of a cohort of 43 recurrent glioblastoma patients and 43 age- and sex-matched healthy controls. Tumor volumes were measured in MRI data using an artificial neural network-based approach. MALDI MSI visualized Trp and its direct metabolite N -formylkynurenine (FK) in glioblastoma tissue. Analysis of scRNA-seq data was used to detect the presence of Trp metabolism and AHR activity in different cell types in glioblastoma. Results: Compared to healthy controls, glioblastoma patients showed decreased serum Trp levels. Surprisingly, the levels of Trp metabolites were also reduced. The decrease became smaller with more enzymatic steps between Trp and its metabolites, suggesting that Trp availability controls the levels of its systemic metabolites. High tumor volume associated with low systemic metabolite levels and low systemic kynurenine levels associated with worse overall survival. MALDI MSI demonstrated heterogeneity of Trp catabolism across glioblastoma tissues. Analysis of scRNA-seq data revealed that genes involved in Trp metabolism were expressed in almost all the cell types in glioblastoma and that most cell types, in particular macrophages and T cells, exhibited AHR activation. Moreover, high AHR activity associated with reduced overall survival in the glioblastoma TCGA dataset. Conclusion: The novel techniques we developed could support the identification of patients that may benefit from therapies targeting TCEs or AHR activation., Competing Interests: Competing Interests: A.S., S.T. and C.A.O. are listed as inventors on WO/2020/201825, C.A.O., M.P. and W.W. are listed as inventors on WO/2013/034685, S.K., M.P., P.S.K., I.P. and C.A.O. are listed as inventors on WO/2017/072368. S.K., V.F., S.J., K.K., S.Se., P.S.K. and I.P. have been employed or are employed by Proteome Sciences. W.W. receives trial funding from Apogenix, Boehringer Ingelheim, Pfizer and Roche to the institution. He serves on advisory boards for Agios, Bayer, MSD, Novartis, Roche with compensation paid to the institution. The authors not listed above declare that they have no competing interests., (© The author(s).)

Background: This study validated a previously described diffusion MRI phenotype as a potential predictive imaging biomarker in patients with recurrent glioblastoma receiving bevacizumab (BEV)., Methods: A total of 396/596 patients (66%) from the prospective randomized phase II/III EORTC-26101 trial (with n = 242 in the BEV and n = 154 in the non-BEV arm) met the inclusion criteria with availability of anatomical and diffusion MRI sequences at baseline prior treatment. Apparent diffusion coefficient (ADC) histograms from the contrast-enhancing tumor volume were fitted to a double Gaussian distribution and the mean of the lower curve (ADClow) was used for further analysis. The predictive ability of ADClow was assessed with biomarker threshold models and multivariable Cox regression for overall survival (OS) and progression-free survival (PFS)., Results: ADClow was associated with PFS (hazard ratio [HR] = 0.625, P = 0.007) and OS (HR = 0.656, P = 0.031). However, no (predictive) interaction between ADClow and the treatment arm was present (P = 0.865 for PFS, P = 0.722 for OS). Independent (prognostic) significance of ADClow was retained after adjusting for epidemiological, clinical, and molecular characteristics (P ≤ 0.02 for OS, P ≤ 0.01 PFS). The biomarker threshold model revealed an optimal ADClow cutoff of 1241*10-6 mm2/s for OS. Thereby, median OS for BEV-patients with ADClow ≥ 1241 was 10.39 months versus 8.09 months for those with ADClow < 1241 (P = 0.004). Similarly, median OS for non-BEV patients with ADClow ≥ 1241 was 9.80 months versus 7.79 months for those with ADClow < 1241 (P = 0.054)., Conclusions: ADClow is an independent prognostic parameter for stratifying OS and PFS in patients with recurrent glioblastoma. Consequently, the previously suggested role of ADClow as predictive imaging biomarker could not be confirmed within this phase II/III trial., (© The Author(s) 2020. Published by Oxford University Press on behalf of the Society for Neuro-Oncology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background Relevance of antiangiogenic treatment with bevacizumab in patients with glioblastoma is controversial because progression-free survival benefit did not translate into an overall survival (OS) benefit in randomized phase III trials. Purpose To perform longitudinal characterization of intratumoral angiogenesis and oxygenation by using dynamic susceptibility contrast agent-enhanced (DSC) MRI and evaluate its potential for predicting outcome from administration of bevacizumab. Materials and Methods In this secondary analysis of the prospective randomized phase II/III European Organization for Research and Treatment of Cancer 26101 trial conducted between October 2011 and December 2015 in 596 patients with first recurrence of glioblastoma, the subset of patients with availability of anatomic MRI and DSC MRI at baseline and first follow-up was analyzed. Patients were allocated into those administered bevacizumab (hereafter, the BEV group; either bevacizumab monotherapy or bevacizumab with lomustine) and those not administered bevacizumab (hereafter, the non-BEV group with lomustine monotherapy). Contrast-enhanced tumor volume, noncontrast-enhanced T2 fluid-attenuated inversion recovery (FLAIR) signal abnormality volume, Gaussian-normalized relative cerebral blood volume (nrCBV), Gaussian-normalized relative blood flow (nrCBF), and tumor metabolic rate of oxygen (nTMRO 2 ) was quantified. The predictive ability of these imaging parameters was assessed with multivariable Cox regression and formal interaction testing. Results A total of 254 of 596 patients were evaluated (mean age, 57 years ± 11; 155 men; 161 in the BEV group and 93 in non-BEV group). Progression-free survival was longer in the BEV group (3.7 months; 95% confidence interval [CI]: 3.0, 4.2) compared with the non-BEV group (2.5 months; 95% CI: 1.5, 2.9; P = .01), whereas OS was not different ( P = .15). The nrCBV decreased for the BEV group (-16.3%; interquartile range [IQR], -39.5% to 12.0%; P = .01), but not for the non-BEV group (1.2%; IQR, -17.9% to 23.3%; P = .19) between baseline and first follow-up. An identical pattern was observed for both nrCBF and nTMRO 2 values. Contrast-enhanced tumor and noncontrast-enhanced T2 FLAIR signal abnormality volumes decreased for the BEV group (-66% [IQR, -83% to -35%] and -33% [IQR, -71% to -5%], respectively; P < .001 for both), whereas they increased for the non-BEV group (30% [IQR, -17% to 98%], P = .001; and 10% [IQR, -13% to 82%], P = .02, respectively) between baseline and first follow-up. None of the assessed MRI parameters were predictive for OS in the BEV group. Conclusion Bevacizumab treatment decreased tumor volumes, angiogenesis, and oxygenation, thereby reflecting its effectiveness for extending progression-free survival; however, these parameters were not predictive of overall survival (OS), which highlighted the challenges of identifying patients that derive an OS benefit from bevacizumab. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Dillon in this issue.

Objective: As a result of the resolution of intravoxel fiber crossing, high-resolution fiber tractography (HRFT) provides advantages over conventional diffusion tensor imaging (DTI) for fiber tractography (FT). Nevertheless, neurosurgically applied FT is still predominantly based on DTI. Although the application of HRFT is evolving, there is still a lack of data about which method should be preferred. With this prospectively designed study, we present our initial experience comparing an analytical Q-ball imaging (QBI) approach with constrained spherical deconvolution (CSD) and conventional DTI-FT considering a particularly neurosurgical perspective., Methods: For 18 patients with eloquent gliomas in the dominant hemisphere, probabilistic FT based on QBI, CSD, and DTI was performed for the major components of the language-associated pathways using a routine diffusion-weighted sequence. Quantitative analysis evaluated tract density, tract volume (TV), tract length (TL), number of fibers, and tract surface (TS) of the fiber object., Results: Both HRFT models showed a significantly larger mean TV, TL, and TS compared with DTI (for QBI vs. DTI: TV (P = 0.0000), TL (P = 0.0048), and TS (P = 0.0129); for CSD vs. DTI: TV (P = 0.0000), TL (P = 0.0008), and TS (P = 0.0010)). However, results of QBI versus CSD did not differ significantly for these variables: TV (P = 0.1415), TL (P = 0.2837), and TS (P = 0.3692). Bland-Altman analysis supports these findings, suggesting systematically higher values for TV, TL, and TS with HRFT but no relevant differences of either QBI or CSD. Neither tumor volume nor peritumoral edema influenced FT results., Conclusions: Our quantitative analysis showed no significant differences regarding TV, TL, and TS for the HRFT methods; however, it suggested advantages over DTI-FT in terms of the display of marginal and terminal fibers. In our recently established setting, QBI-FT shows greater potential for integration into the clinical workflow., (Copyright © 2019 Elsevier Inc. All rights reserved.)