Anja Gwendolyn van der Kolk

Background: Gliomas, particularly astrocytomas (IDH-mutated, 1p/19q intact) and oligodendrogliomas (IDH-mutated, 1p/19q co-deleted), differ significantly in their clinical behavior and prognosis. Accurate differentiation between these subtypes is crucial for guiding therapeutic decisions. Non-invasive imaging biomarkers, such as T2-Flair mismatch sign and relative cerebral blood volume (rCBV), have shown promise in glioma classification. Methods: This retrospective multicenter study analyzed 42 patients with astrocytoma and 21 with oligodendroglioma. Demographic, histopathological, and imaging data were collected, with a focus on rCBV parameters derived from dynamic susceptibility contrast perfusion MRI. Statistical analyses were conducted to assess differences between the groups and evaluate the discriminatory power of rCBV metrics. After correction for multiple corrections, level of significance was set at p < 0.01. Results: Patients with astrocytoma and oligodendroglioma were similar in age and gender distribution (mean age and male-female-ratio; p = 0.01 respectively p = 0.04). The rCBVmax value was significantly higher in oligodendrogliomas (11.64 vs. 7.69, p < 0.001) and demonstrated a good discriminatory power (AUC = 0.764). Median and mean rCBV values showed non-significant differences between oligodendroglioma and astrocytoma ( p = 0.02 respectively p = 0.03). Conclusion: rCBVmax emerges as a potential imaging marker for differentiating oligodendrogliomas from astrocytomas. These findings can be explained by biological properties of oligodendrogliomas and thereby underscore the potential of advanced imaging techniques in non-invasive glioma classification. However, larger prospective studies are required to validate these results and standardize imaging protocols.

Background/Objectives: Neuroimaging biomarkers could offer more objective measures of the pain experience. This study investigated rT1/T2 maps of the brain as a novel biomarker for chronic pain in patients with central post-stroke pain (PSP) and persistent spinal pain syndrome type 2 (PSPS-II). Methods: Patients with PSP and PSPS-II were retrospectively included alongside healthy controls. Bias correction and intensity normalization were applied to the T1-weighted and T2-weighted images to generate the rT1/T2 maps of the brain. Subsequently, rT1/T2 maps were spatially correlated with neurotransmitter atlases derived from molecular imaging. Results: In total, 15 PSPS-II patients, 11 PSP patients, and 18 healthy controls were included. No significant differences between patient and control demographics were found. Significant decreases in rT1/T2 signal intensity (p < 0.001) were observed in the dorsal and medial part of the thalamus, left caudate nucleus, cuneus, superior frontal gyrus, and dorsal cervicomedullary junction in PSP patients. No significant changes were found in rT1/T2 signal intensity in PSPS-II patients. Significant correlations were found with CB1-, 5HT2a-, and mGluR5-receptor maps (pFDR = 0.003, 0.030, and 0.030, respectively) for the PSP patients and with CB1-, 5HT1a-, 5HT2a-, KappaOp-, and mGluR5-receptor maps (pFDR = 0.003, 0.002, 0.002, 0.003, and 0.002, respectively) in PSPS-II patients. Conclusions: These findings suggest that microstructural alterations occur in the thalamus, cuneus, and dorsal cervicomedullary junction in patients with PSP. The lack of significant findings in rT1/T2 in PSPS-II patients combined with the significant correlations with multiple neurotransmitter maps suggests varying degrees of microstructural deterioration in both chronic pain syndromes, although further research is warranted.

The neuronal tricarboxylic acid and glutamate/glutamine (Glu/Gln) cycles play important roles in brain function. These processes can be measured in vivo using dynamic ¹H–[¹³C] MRS during administration of ¹³C‐labeled glucose. Proton‐observed carbon‐edited (POCE) MRS enhances the signal‐to‐noise ratio (SNR) compared with direct ¹³C‐MRS. Ultra‐high field further boosts the SNR and increases spectral dispersion; however, even at 7 T, Glu and Gln ¹H‐resonances may overlap. Further gain can be obtained with selective POCE (selPOCE). Our aim was to create a setup for indirect dynamic ¹H–[¹³C] MRS in the human brain at 7 T. A home‐built non‐shielded transmit–receive ¹³C‐birdcage head coil with eight transmit–receive ¹H‐dipole antennas was used together with a 32‐channel ¹H‐receive array. Electromagnetic simulations were carried out to ensure that acquisitions remained within local and global head SAR limits. POCE‐MRS was performed using slice‐selective excitation with semi‐localization by adiabatic selective refocusing (sLASER) and stimulated echo acquisition mode (STEAM) localization, and selPOCE‐MRS using STEAM. Sequences were tested in a phantom containing non‐enriched Glu and Gln, and in three healthy volunteers during uniformly labeled ¹³C‐glucose infusions. In one subject the voxel position was alternated between bi‐frontal and bi‐occipital placement within one session. [4‐¹³C]Glu‐H4 and [4‐¹³C]Gln‐H4 signals could be separately detected using both STEAM‐POCE and STEAM‐selPOCE in the phantom. In vivo, [4,5‐¹³C]Glx could be detected using both sLASER‐POCE and STEAM‐POCE, with similar sensitivities, but [4,5‐¹³C]Glu and [4,5‐¹³C]Gln signals could not be completely resolved. STEAM‐POCE was alternately performed bi‐frontal and bi‐occipital within a single session without repositioning of the subject, yielding similar results. With STEAM‐selPOCE, [4,5‐¹³C]Glu and [4,5‐¹³C]Gln could be clearly separated. We have shown that with our setup indirect dynamic ¹H–[¹³C] MRS at 7 T is feasible in different locations in the brain within one session, and by using STEAM‐selPOCE it is possible to separate Glu from Gln in vivo while obtaining high quality spectra.

The role of molecular imaging with positron emission tomography (PET) for diagnosis, treatment planning and post-treatment monitoring of brain tumors has grown substantially in the last decades. In the last 25 years, almost 50 different PET agents have been developed and tested in human clinical studies. While some of these PET agents are yet to make their way into clinical practice, others have already established pivotal roles in brain tumor imaging. Although all these agents share an affinity for brain tumor cells, they target different tumor-altered molecular pathways within these cells: some agents are taken up by the cell through overexpressed transporters and become trapped, altered, or incorporated into upregulated metabolic pathways, while other agents bind to overexpressed receptors or to cells present in the tumor microenvironment. In this monograph, we explore the major genetic and molecular changes characteristic of brain tumors, how they are used by PET agents to gain access to tumor cells and their environment, and how this translates to uptake in clinical practice. Gaining insight in these processes is essential for correct image interpretation and helps to understand why some agents are more successful than others.

The role of molecular imaging with positron emission tomography (PET) for diagnosis, treatment planning and post-treatment monitoring of brain tumors has grown substantially in the last decades. In the last 25 years, almost 50 different PET agents have been developed and tested in human clinical studies. While some of these PET agents are yet to make their way into clinical practice, others have already established pivotal roles in brain tumor imaging. Although all these agents share an affinity for brain tumor cells, they target different tumor-altered molecular pathways within these cells: some agents are taken up by the cell through overexpressed transporters and become trapped, altered, or incorporated into upregulated metabolic pathways, while other agents bind to overexpressed receptors or to cells present in the tumor microenvironment. In this monograph, we explore the major genetic and molecular changes characteristic of brain tumors, how they are used by PET agents to gain access to tumor cells and their environment, and how this translates to uptake in clinical practice. Gaining insight in these processes is essential for correct image interpretation and helps to understand why some agents are more successful than others.

Introduction: Chronic pain after spinal surgery (CPSS), formerly known as failed back surgery syndrome, encompasses a variety of highly incapacitating chronic pain syndromes emerging after spinal surgery. The intractability of CPSS makes objective parameters that could aid classification and treatment essential. In this study, we investigated the use of cerebral diffusion-weighted magnetic resonance imaging. Methods: Cerebral 3T diffusion-weighted (DW-) MRI data from adult CPSS patients were assessed and compared with those of healthy controls matched by age and gender. Only imaging data without relevant artefacts or significant pathologies were included. Apparent diffusion coefficient (ADC) maps were calculated from the b0 and b1000 values using nonlinear regression. After skull stripping and affine registration of all imaging data, ADC values for fifteen anatomical regions were calculated and analyzed with independent samples T-tests. Results: A total of 32 subjects were included (sixteen CPSS patients and sixteen controls). The mean ADC value of the spinothalamic tract was found to be significantly higher in CPSS patients compared with in healthy controls (p = 0.013). The other anatomical regions did not show statistically different ADC values between the two groups. Conclusion: Our results suggest that patients suffering from CPSS are subject to microstructural changes, predominantly within the cerebral spinothalamic tract. Additional research could possibly lead to imaging biomarkers derived from ADC values in CPSS patients.

Background: Intraplaque hemorrhage (IPH) is a hallmark of atherosclerotic plaque instability. Biliverdin reductase B (BLVRB) is enriched in plasma and plaques from patients with symptomatic carotid atherosclerosis and functionally associated with IPH. Objective: We explored the biomarker potential of plasma BLVRB through (1) its correlation with IPH in carotid plaques assessed by magnetic resonance imaging (MRI), and with recurrent ischemic stroke, and (2) its use for monitoring pharmacotherapy targeting IPH in a preclinical setting. Methods: Plasma BLVRB levels were measured in patients with symptomatic carotid atherosclerosis from the PARISK study (n = 177, 5 year follow-up) with and without IPH as indicated by MRI. Plasma BLVRB levels were also measured in a mouse vein graft model of IPH at baseline and following antiangiogenic therapy targeting vascular endothelial growth factor receptor 2 (VEGFR-2). Results: Plasma BLVRB levels were significantly higher in patients with IPH (737.32 ± 693.21 vs. 520.94 ± 499.43 mean fluorescent intensity (MFI), p = 0.033), but had no association with baseline clinical and biological parameters. Plasma BLVRB levels were also significantly higher in patients who developed recurrent ischemic stroke (1099.34 ± 928.49 vs. 582.07 ± 545.34 MFI, HR = 1.600, CI [1.092–2.344]; p = 0.016). Plasma BLVRB levels were significantly reduced following prevention of IPH by anti-VEGFR-2 therapy in mouse vein grafts (1189 ± 258.73 vs. 1752 ± 366.84 MFI; p = 0.004). Conclusions: Plasma BLVRB was associated with IPH and increased risk of recurrent ischemic stroke in patients with symptomatic low- to moderate-grade carotid stenosis, indicating the capacity to monitor the efficacy of IPH-preventive pharmacotherapy in an animal model. Together, these results suggest the utility of plasma BLVRB as a biomarker for atherosclerotic plaque instability.

The post-treatment imaging surveillance of gliomas is challenged by distinguishing tumor progression (TP) from treatment-related abnormalities (TRA). Sophisticated imaging techniques, such as perfusion-weighted magnetic resonance imaging (MRI PWI) and positron-emission tomography (PET) with a variety of radiotracers, have been suggested as being more reliable than standard imaging for distinguishing TP from TRA. However, it remains unclear if any technique holds diagnostic superiority. This meta-analysis provides a head-to-head comparison of the diagnostic accuracy of the aforementioned imaging techniques. Systematic literature searches on the use of PWI and PET imaging techniques were carried out in PubMed, Embase, the Cochrane Library, ClinicalTrials.gov and the reference lists of relevant papers. After the extraction of data on imaging technique specifications and diagnostic accuracy, a meta-analysis was carried out. The quality of the included papers was assessed using the QUADAS-2 checklist. Nineteen articles, totaling 697 treated patients with glioma (431 males; mean age ± standard deviation 50.5 ± 5.1 years) were included. The investigated PWI techniques included dynamic susceptibility contrast (DSC), dynamic contrast enhancement (DCE) and arterial spin labeling (ASL). The PET-tracers studied concerned [S-methyl-¹¹C]methionine, 2-deoxy-2-[¹⁸F]fluoro-D-glucose ([¹⁸F]FDG), O-(2-[¹⁸F]fluoroethyl)-L-tyrosine ([¹⁸F]FET) and 6-[¹⁸F]-fluoro-3,4-dihydroxy-L-phenylalanine ([¹⁸F]FDOPA). The meta-analysis of all data showed no diagnostic superior imaging technique. The included literature showed a low risk of bias. As no technique was found to be diagnostically superior, the local level of expertise is hypothesized to be the most important factor for diagnostically accurate results in post-treatment glioma patients regarding the distinction of TRA from TP.

We present a fully automated method for carotid artery (CA) outer wall segmentation in black blood MRI using partially annotated data and compare it to the state-of-the-art reference model. Our model was trained and tested on multicentric data of patients (106 and 23 patients, respectively) with a carotid plaque and was validated on different MR sequences (24 patients) as well as data that were acquired with MRI systems of a different vendor (34 patients). A 3D nnU-Net was trained on pre-contrast T1w turbo spin echo (TSE) MR images. A CA centerline sliding window approach was chosen to refine the nnU-Net segmentation using an additionally trained 2D U-Net to increase agreement with manual annotations. To improve segmentation performance in areas with semantically and visually challenging voxels, Monte-Carlo dropout was used. To increase generalizability, data were augmented with intensity transformations. Our method achieves state-of-the-art results yielding a Dice similarity coefficient (DSC) of 91.7% (interquartile range (IQR) 3.3%) and volumetric intraclass correlation (ICC) with ground truth of 0.90 on the development domain data and a DSC of 91.1% (IQR 7.2%) and volumetric ICC with ground truth of 0.83 on the external domain data outperforming top-ranked methods for open-source CA segmentation. The uncertainty-based approach increases the interpretability of the proposed method by providing an uncertainty map together with the segmentation.