Deep intravital brain tumor imaging enabled by tailored three-photon microscopy and analysis.

Intravital 2P-microscopy enables the longitudinal study of brain tumor biology in superficial mouse cortex layers. Intravital microscopy of the white matter, an important route of glioblastoma invasion and recurrence, has not been feasible, due to low signal-to-noise ratios and insufficient spatiotemporal resolution. Here, we present an intravital microscopy and artificial intelligence-based analysis workflow (Deep3P) that enables longitudinal deep imaging of glioblastoma up to a depth of 1.2 mm. We find that perivascular invasion is the preferred invasion route into the corpus callosum and uncover two vascular mechanisms of glioblastoma migration in the white matter. Furthermore, we observe morphological changes after white matter infiltration, a potential basis of an imaging biomarker during early glioblastoma colonization. Taken together, Deep3P allows for a non-invasive intravital investigation of brain tumor biology and its tumor microenvironment at subcortical depths explored, opening up opportunities for studying the neuroscience of brain tumors and other model systems.

Shape matters: unsupervised exploration of IDH-wildtype glioma imaging survival predictors.

OBJECTIVES: This study examines clustering based on shape radiomic features and tumor volume to identify IDH-wildtype glioma phenotypes and assess their impact on overall survival (OS). MATERIALS AND METHODS: This retrospective study included 436 consecutive patients diagnosed with IDH-wt glioma who underwent preoperative MR imaging. Alongside the total tumor volume, nine distinct shape radiomic features were extracted using the PyRadiomics framework. Different imaging phenotypes were identified using partition around medoids (PAM) clustering on the training dataset (348/436). The prognostic efficacy of these phenotypes in predicting OS was evaluated on the test dataset (88/436). External validation was performed using the public UCSF glioma dataset (n = 397). A decision-tree algorithm was employed to determine the relevance of features associated with cluster affiliation. RESULTS: PAM clustering identified two clusters in the training dataset: Cluster 1 (n = 233) had a higher proportion of patients with higher sphericity and elongation, while Cluster 2 (n = 115) had a higher proportion of patients with higher maximum 3D diameter, surface area, axis lengths, and tumor volume (p < 0.001 for each). OS differed significantly between clusters: Cluster 1 showed a median OS of 23.8 compared to 11.4 months of Cluster 2 in the holdout test dataset (p = 0.002). Multivariate Cox regression showed improved performance with cluster affiliation over clinical data alone (C index 0.67 vs 0.59, p = 0.003). Cluster-based models outperformed the models with tumor volume alone (evidence ratio: 5.16-5.37). CONCLUSION: Data-driven clustering reveals imaging phenotypes, highlighting the improved prognostic power of combining shape-radiomics with tumor volume, thereby outperforming predictions based on tumor volume alone in high-grade glioma survival outcomes. CLINICAL RELEVANCE STATEMENT: Shape-radiomics and volume-based cluster analyses of preoperative MRI scans can reveal imaging phenotypes that improve the prediction of OS in patients with IDH-wild type gliomas, outperforming currently known models based on tumor size alone or clinical parameters. KEY POINTS: Shape radiomics and tumor volume clustering in IDH-wildtype gliomas are investigated for enhanced prognostic accuracy. Two distinct phenotypic clusters were identified with different median OSs. Integrating shape radiomics and volume-based clustering enhances OS prediction in IDH-wildtype glioma patients.

T2-relaxometry in a large cohort of hereditary transthyretin amyloidosis with polyneuropathy.

BACKGROUND: Previously, T2-relaxation time (T2app) and proton spin density (ρ) detected nerve injury in a small group of ATTRv amyloidosis. Here, we aim to quantify peripheral nerve impairment in a large cohort of symptomatic and asymptomatic ATTRv amyloidosis and correlate T2-relaxometry markers with clinical parameters and nerve conduction studies (NCS). METHODS: Eighty participants with pathologic variants of the transthyretin gene (TTRv) and 40 controls prospectively underwent magnetic resonance neurography. T2-relaxometry was performed, allowing to calculate tibial ρ, T2app and cross-sectional-area (CSA). Detailed clinical examinations and NCS of tibial and peroneal nerves were performed. RESULTS: Forty participants were classified as asymptomatic TTRv-carriers, 40 as symptomatic patients with polyneuropathy. ρ, T2app and CSA were significantly higher in symptomatic ATTRv amyloidosis (484.2 ± 14.8 a.u.; 70.6 ± 1.8 ms; 25.7 ± 0.9 mm2) versus TTRv-carriers (413.1 ± 9.4 a.u., p < 0.0001; 62.3 ± 1.3 ms, p = 0.0002; 19.0 ± 0.8 mm2, p < 0.0001) and versus controls (362.6 ± 7.5 a.u., p < 0.0001; 59.5 ± 1.0 ms, p < 0.0001; 15.4 ± 0.5 mm2, p < 0.0001). Only ρ and CSA differentiated TTRv-carriers from controls. ρ and CSA correlated with NCS in TTRv-carriers, while T2app correlated with NCS in symptomatic ATTRv amyloidosis. Both ρ and T2app correlated with clinical score. CONCLUSION: ρ and CSA can detect early nerve injury and correlate with electrophysiology in asymptomatic TTRv-carriers. T2app increases only in symptomatic ATTRv amyloidosis in whom it correlates with clinical scores and electrophysiology. Our results suggest that T2-relaxometry can provide biomarkers for disease- and therapy-monitoring in the future.

Automated peripheral nerve segmentation for MR-neurography.

BACKGROUND: Magnetic resonance neurography (MRN) is increasingly used as a diagnostic tool for peripheral neuropathies. Quantitative measures enhance MRN interpretation but require nerve segmentation which is time-consuming and error-prone and has not become clinical routine. In this study, we applied neural networks for the automated segmentation of peripheral nerves. METHODS: A neural segmentation network was trained to segment the sciatic nerve and its proximal branches on the MRN scans of the right and left upper leg of 35 healthy individuals, resulting in 70 training examples, via 5-fold cross-validation (CV). The model performance was evaluated on an independent test set of one-sided MRN scans of 60 healthy individuals. RESULTS: Mean Dice similarity coefficient (DSC) in CV was 0.892 (95% confidence interval [CI]: 0.888-0.897) with a mean Jaccard index (JI) of 0.806 (95% CI: 0.799-0.814) and mean Hausdorff distance (HD) of 2.146 (95% CI: 2.184-2.208). For the independent test set, DSC and JI were lower while HD was higher, with a mean DSC of 0.789 (95% CI: 0.760-0.815), mean JI of 0.672 (95% CI: 0.642-0.699), and mean HD of 2.118 (95% CI: 2.047-2.190). CONCLUSION: The deep learning-based segmentation model showed a good performance for the task of nerve segmentation. Future work will focus on extending training data and including individuals with peripheral neuropathies in training to enable advanced peripheral nerve disease characterization. RELEVANCE STATEMENT: The results will serve as a baseline to build upon while developing an automated quantitative MRN feature analysis framework for application in routine reading of MRN examinations. KEY POINTS: Quantitative measures enhance MRN interpretation, requiring complex and challenging nerve segmentation. We present a deep learning-based segmentation model with good performance. Our results may serve as a baseline for clinical automated quantitative MRN segmentation.

Assessment of Tumor Cell Invasion and Radiotherapy Response in Experimental Glioma by Magnetic Resonance Elastography.

BACKGROUND: Gliomas are highly invasive brain neoplasms. MRI is the most important tool to diagnose and monitor glioma but has shortcomings. In particular, the assessment of tumor cell invasion is insufficient. This is a clinical dilemma, as recurrence can arise from MRI-occult glioma cell invasion. HYPOTHESIS: Tumor cell invasion, tumor growth and radiotherapy alter the brain parenchymal microstructure and thus are assessable by diffusion tensor imaging (DTI) and MR elastography (MRE). STUDY TYPE: Experimental, animal model. ANIMAL MODEL: Twenty-three male NMRI nude mice orthotopically implanted with S24 patient-derived glioma cells (experimental mice) and 9 NMRI nude mice stereotactically injected with 1 µL PBS (sham-injected mice). FIELD STRENGTH/SEQUENCE: 2D and 3D T2-weighted rapid acquisition with refocused echoes (RARE), 2D echo planar imaging (EPI) DTI, 2D multi-slice multi-echo (MSME) T2 relaxometry, 3D MSME MRE at 900 Hz acquired at 9.4 T (675 mT/m gradient strength). ASSESSMENT: Longitudinal 4-weekly imaging was performed for up to 4 months. Tumor volume was assessed in experimental mice (n = 10 treatment-control, n = 13 radiotherapy). The radiotherapy subgroup and 5 sham-injected mice underwent irradiation (3 × 6 Gy) 9 weeks post-implantation/sham injection. MRI-/MRE-parameters were assessed in the corpus callosum and tumor core/injection tract. Imaging data were correlated to light sheet microscopy (LSM) and histology. STATISTICAL TESTS: Paired and unpaired t-tests, a P-value ≤0.05 was considered significant. RESULTS: From week 4 to 8, a significant callosal stiffening (4.44 ± 0.22 vs. 5.31 ± 0.29 kPa) was detected correlating with LSM-proven tumor cell invasion. This was occult to all other imaging metrics. Histologically proven tissue destruction in the tumor core led to an increased T2 relaxation time (41.65 ± 0.34 vs. 44.83 ± 0.66 msec) and ADC (610.2 ± 12.27 vs. 711.2 ± 13.42 × 10-6 mm2/s) and a softening (5.51 ± 0.30 vs. 4.24 ± 0.29 kPa) from week 8 to 12. Radiotherapy slowed tumor progression. DATA CONCLUSION: MRE is promising for the assessment of key glioma characteristics. EVIDENCE LEVEL: NA TECHNICAL EFFICACY: Stage 2.

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.

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.

Diffusion tensor imaging in anisotropic tissues: application of reduced gradient vector schemes in peripheral nerves.

BACKGROUND: In contrast to the brain, fibers within peripheral nerves have distinct monodirectional structure questioning the necessity of complex multidirectional gradient vector schemes for DTI. This proof-of-concept study investigated the diagnostic utility of reduced gradient vector schemes in peripheral nerve DTI. METHODS: Three-Tesla magnetic resonance neurography of the tibial nerve using 20-vector DTI (DTI20) was performed in 10 healthy volunteers, 12 patients with type 2 diabetes, and 12 age-matched healthy controls. From the full DTI20 dataset, three reduced datasets including only two or three vectors along the x- and/or y- and z-axes were built to calculate major parameters. The influence of nerve angulation and intraneural connective tissue was assessed. The area under the receiver operating characteristics curve (ROC-AUC) was used for analysis. RESULTS: Simplified datasets achieved excellent diagnostic accuracy equal to DTI20 (ROC-AUC 0.847-0.868, p ≤ 0.005), but compared to DTI20, the reduced models yielded mostly lower absolute values of DTI scalars: median fractional anisotropy (FA) ≤ 0.12; apparent diffusion coefficient (ADC) ≤ 0.25; axial diffusivity ≤ 0.96, radial diffusivity ≤ 0.07). The precision of FA and ADC with the three-vector model was closest to DTI20. Intraneural connective tissue was negatively correlated with FA and ADC (r ≥ -0.49, p < 0.001). Small deviations of nerve angulation had little effect on FA accuracy. CONCLUSIONS: In peripheral nerves, bulk tissue DTI metrics can be approximated with only three predefined gradient vectors along the scanner's main axes, yielding similar diagnostic accuracy as a 20-vector DTI, resulting in substantial scan time reduction. RELEVANCE STATEMENT: DTI bulk tissue parameters of peripheral nerves can be calculated with only three predefined gradient vectors at similar diagnostic performance as a standard DTI but providing a substantial scan time reduction. KEY POINTS: • In peripheral nerves, DTI parameters can be approximated using only three gradient vectors. • The simplified model achieves a similar diagnostic performance as a standard DTI. • The simplified model allows for a significant acceleration of image acquisition. • This can help to introduce multi-b-value DTI techniques into clinical practice.

Phase angle of bioelectrical impedance analysis as an indicator for diabetic polyneuropathy in type 2 diabetes mellitus.

CONTEXT: Due to the heterogenous clinical symptoms and deficits, the diagnosis of diabetic polyneuropathy (DPN) is still difficult in clinical routine leading to increased morbidity and mortality. OBJECTIVE: We studied the correlation of phase angle (PhA) of bioelectrical impedance analysis (BIA) with clinical, laboratory and physical markers of DPN to evaluate PhA as possible diagnostic method for DPN. MATERIALS AND METHODS: In this cross-sectional observational study as part of the Heidelberg Study on Diabetes and Complications we examined 104 healthy individuals and 205 patients with type 2 diabetes mellitus (T2D), amongst which 63 had DPN. The PhA was calculated from multi-frequency BIA. Nerve conduction studies (NCS), quantitative sensory testing (QST) and diffusion-weighted magnetic resonance neurography (MRN) to determine fractional anisotropy (FA) reflecting peripheral nerve integrity were performed. RESULTS: T2D patients with DPN had lower PhA values (5.71 ± 0.10) compared to T2D patients without DPN (6.07 ± 0.08, p = 0.007, + 6.1%) and healthy controls (6.18 ± 0.08, p < 0.001, + 7.9%). Confounder-adjusted analyses showed correlations of the PhA with conduction velocities and amplitudes of the peroneal (ß=0.28; ß=0.31, p < 0.001) and tibial nerves (ß=0.28; ß=0.32, p < 0.001), Z-scores of QST (thermal detection ß=0.30, p < 0.05) and the FA (ß=0.60, p < 0.001). ROC analysis showed similar performance of PhA in comparison to mentioned diagnostic methods. CONCLUSION: The study shows that PhA is in comparison to other test systems used, at least an equally good and much easier to handle, investigator independent marker for detection of DPN.

Magnetic resonance neurography in spinal cord injury: Imaging findings and clinical significance.

BACKGROUND AND PURPOSE: It is unknown whether changes to the peripheral nervous system following spinal cord injury (SCI) are relevant for functional recovery or the development of neuropathic pain below the level of injury. Magnetic resonance neurography (MRN) at 3 T allows detection and localization of structural and functional nerve damage. This study aimed to combine MRN and clinical assessments in individuals with chronic SCI and nondisabled controls. METHODS: Twenty participants with chronic SCI and 20 controls matched for gender, age, and body mass index underwent MRN of the L5 dorsal root ganglia (DRG) and the sciatic nerve. DRG volume, sciatic nerve mean cross-sectional area (CSA), fascicular lesion load, and fractional anisotropy (FA), a marker for functional nerve integrity, were calculated. Results were correlated with clinical assessments and nerve conduction studies. RESULTS: Sciatic nerve CSA and lesion load were higher (21.29 ± 5.82 mm2 vs. 14.08 ± 4.62 mm2 , p < 0.001; and 8.70 ± 7.47% vs. 3.60 ± 2.45%, p < 0.001) in individuals with SCI compared to controls, whereas FA was lower (0.55 ± 0.11 vs. 0.63 ± 0.08, p = 0.022). DRG volumes were larger in individuals with SCI who suffered from neuropathic pain compared to those without neuropathic pain (223.7 ± 53.08 mm3 vs. 159.7 ± 55.66 mm3 , p = 0.043). Sciatic MRN parameters correlated with electrophysiological results but did not correlate with the extent of myelopathy or clinical severity of SCI. CONCLUSIONS: Individuals with chronic SCI are subject to a decline of structural peripheral nerve integrity that may occur independently from the clinical severity of SCI. Larger volumes of DRG in SCI with neuropathic pain support existing evidence from animal studies on SCI-related neuropathic pain.

Magnetization transfer ratio of the sciatic nerve differs between patients in type 1 and type 2 diabetes.

BACKGROUND: Previous studies on magnetic resonance neurography (MRN) found different patterns of structural nerve damage in type 1 diabetes (T1D) and type 2 diabetes (T2D). Magnetization transfer ratio (MTR) is a quantitative technique to analyze the macromolecular tissue composition. We compared MTR values of the sciatic nerve in patients with T1D, T2D, and healthy controls (HC). METHODS: 3-T MRN of the right sciatic nerve at thigh level was performed in 14 HC, 10 patients with T1D (3 with diabetic neuropathy), and 28 patients with T2D (10 with diabetic neuropathy). Results were subsequently correlated with clinical and electrophysiological data. RESULTS: The sciatic nerve's MTR was lower in patients with T2D (0.211 ± 0.07, mean ± standard deviation) compared to patients with T1D (T1D 0.285 ± 0.03; p = 0.015) and HC (0.269 ± 0.05; p = 0.039). In patients with T1D, sciatic MTR correlated positively with tibial nerve conduction velocity (NCV; r = 0.71; p = 0.021) and negatively with hemoglobin A1c (r = - 0.63; p < 0.050). In patients with T2D, we found negative correlations of sciatic nerve's MTR peroneal NCV (r = - 0.44; p = 0.031) which remained significant after partial correlation analysis controlled for age and body mass index (r = 0.51; p = 0.016). CONCLUSIONS: Lower MTR values of the sciatic nerve in T2D compared to T1D and HC and diametrical correlations of MTR values with NCV in T1D and T2D indicate that there are different macromolecular changes and pathophysiological pathways underlying the development of neuropathic nerve damage in T1D and T2D. TRIAL REGISTRATION: https://classic. CLINICALTRIALS: gov/ct2/show/NCT03022721 . 16 January 2017. RELEVANCE STATEMENT: Magnetization transfer ratio imaging may serve as a non-invasive imaging method to monitor the diseases progress and to encode the pathophysiology of nerve damage in patients with type 1 and type 2 diabetes. KEY POINTS: • Magnetization transfer imaging detects distinct macromolecular nerve lesion patterns in diabetes patients. • Magnetization transfer ratio was lower in type 2 diabetes compared to type 1 diabetes. • Different pathophysiological mechanisms drive nerve damage in type 1 and 2 diabetes.

Association of Small Fiber Function with Microvascular Perfusion of Peripheral Nerves in Patients with Type 2 Diabetes : Study using Quantitative Sensory Testing and Magnetic Resonance Neurography.

INTRODUCTION/AIMS: Diabetic small fiber neuropathy (SFN) is caused by damage to thinly myelinated A­fibers (δ) and unmyelinated C­fibers. This study aimed to assess associations between quantitative sensory testing (QST) and parameters of peripheral nerve perfusion obtained from dynamic contrast enhanced (DCE) magnetic resonance neurography (MRN) in type 2 diabetes patients with and without SFN. METHODS: A total of 18 patients with type 2 diabetes (T2D, 8 with SFN, 10 without SFN) and 10 healthy controls (HC) took part in this cross-sectional single-center study and underwent QST of the right leg and DCE-MRN of the right thigh with subsequent calculation of the sciatic nerve constant of capillary permeability (Ktrans), extravascular extracellular volume fraction (Ve), and plasma volume fraction (Vp). RESULTS: The Ktrans (HC 0.031 min-1 ± 0.009, T2D 0.043 min-1 ± 0.015; p = 0.033) and Ve (HC 1.2% ± 1.5, T2D: 4.1% ± 5.1; p = 0.027) were lower in T2D patients compared to controls. In T2D patients, compound z­scores of thermal and mechanical detection correlated with Ktrans (r = 0.73; p = 0.001, and r = 0.57; p = 0.018, respectively) and Ve (r = 0.67; p = 0.002, and r = 0.69; p = 0.003, respectively). Compound z­scores of thermal pain and Vp (r = -0.57; p = 0.015) correlated negatively. DISCUSSION: The findings suggest that parameters of peripheral nerve microcirculation are related to different symptoms in SFN: A reduced capillary permeability may result in a loss of function related to insufficient nutritional supply, whereas increased capillary permeability may be accompanied by painful symptoms related to a gain of function.

Iatrogenic Air Embolisms During Endovascular Interventions: Impact of Origin and Number of Air Bubbles on Cerebral Infarctions.

PURPOSE: Cerebral infarctions caused by air embolisms (AE) are a feared risk in endovascular procedures; however, the relevance and pathophysiology of these AEs is still largely unclear. The objective of this study was to investigate the impact of the origin (aorta, carotid artery or right atrium) and number of air bubbles on cerebral infarctions in an experimental in vivo model. METHODS: In 20 rats 1200 or 2000 highly calibrated micro air bubbles (MAB) with a size of 85 µm were injected at the aortic valve (group Ao), into the common carotid artery (group CA) or into the right atrium (group RA) using a microcatheter via a transfemoral access, resembling endovascular interventions in humans. Magnetic resonance imaging (MRI) using a 9.4T system was performed 1 h after MAB injection followed by finalization. RESULTS: The number (5.5 vs. 5.5 median) and embolic patterns of infarctions did not significantly differ between groups Ao and CA. The number of infarctions were significantly higher comparing 2000 and 1200 injected MABs (6 vs. 4.5; p < 0.001). The infarctions were significantly larger for group CA (median infarction volume: 0.41 mm3 vs. 0.19 mm3; p < 0.001). In group RA and in the control group no infarctions were detected. Histopathological analyses showed early signs of ischemic stroke. CONCLUSION: Iatrogenic AEs originating at the ascending aorta cause a similar number and pattern of cerebral infarctions compared to those with origin at the carotid artery. These findings underline the relevance and potential risk of AE occurring during endovascular interventions at the aortic valve and ascending aorta.

Microstructural changes of peripheral nerves in early multiple sclerosis: A prospective magnetic resonance neurography study.

BACKGROUND AND PURPOSE: Multiple sclerosis (MS) is a demyelinating disorder of the central nervous system (CNS). However, there is increasing evidence of peripheral nerve involvement. This study aims to characterize the pattern of peripheral nerve changes in patients with newly diagnosed MS using quantitative magnetic resonance (MR) neurography. METHODS: In this prospective study, 25 patients first diagnosed with MS according to the revised McDonald criteria (16 female, mean age = 32.8 ± 10.6 years) and 14 healthy controls were examined with high-resolution 3-T MR neurography of the sciatic nerve using diffusion kurtosis imaging (DKI; 20 diffusional directions, b = 0, 700, 1200 s/mm2 ) and magnetization transfer imaging (MTI). In total, 15 quantitative MR biomarkers were analyzed and correlated with clinical symptoms, intrathecal immunoglobulin synthesis, electrophysiology, and lesion load on brain and spine MR imaging. RESULTS: Patients showed decreased fractional anisotropy (mean = 0.51 ± 0.04 vs. 0.56 ± 0.03, p < 0.001), extra-axonal tortuosity (mean = 2.32 ± 0.17 vs. 2.49 ± 0.17, p = 0.008), and radial kurtosis (mean = 1.40 ± 0.23 vs. 1.62 ± 0.23, p = 0.014) and higher radial diffusivity (mean = 1.09 ∙ 10-3 mm2 /s ± 0.16 vs. 0.98 ± 0.11 ∙ 10-3 mm2 /s, p = 0.036) than controls. Groups did not differ in MTI. No significant association was found between MR neurography markers and clinical/laboratory parameters or CNS lesion load. CONCLUSIONS: This study provides further evidence of peripheral nerve involvement in MS already at initial diagnosis. The characteristic pattern of DKI parameters indicates predominant demyelination and suggests a primary coaffection of the peripheral nervous system in MS. This first human study using DKI for peripheral nerves shows its potential and clinical feasibility in providing novel biomarkers.

A diminished sciatic nerve structural integrity is associated with distinct peripheral sensory phenotypes in individuals with type 2 diabetes.

AIMS/HYPOTHESIS: Quantitative sensory testing (QST) allows the identification of individuals with rapid progression of diabetic sensorimotor polyneuropathy (DSPN) based on certain sensory phenotypes. Hence, the aim of this study was to investigate the relationship of these phenotypes with the structural integrity of the sciatic nerve among individuals with type 2 diabetes. METHODS: Seventy-six individuals with type 2 diabetes took part in this cross-sectional study and underwent QST of the right foot and high-resolution magnetic resonance neurography including diffusion tensor imaging of the right distal sciatic nerve to determine the sciatic nerve fractional anisotropy (FA) and cross-sectional area (CSA), both of which serve as markers of structural integrity of peripheral nerves. Participants were then assigned to four sensory phenotypes (participants with type 2 diabetes and healthy sensory profile [HSP], thermal hyperalgesia [TH], mechanical hyperalgesia [MH], sensory loss [SL]) by a standardised sorting algorithm based on QST. RESULTS: Objective neurological deficits showed a gradual increase across HSP, TH, MH and SL groups, being higher in MH compared with HSP and in SL compared with HSP and TH. The number of participants categorised as HSP, TH, MH and SL was 16, 24, 17 and 19, respectively. There was a gradual decrease of the sciatic nerve's FA (HSP 0.444, TH 0.437, MH 0.395, SL 0.382; p=0.005) and increase of CSA (HSP 21.7, TH 21.5, MH 25.9, SL 25.8 mm2; p=0.011) across the four phenotypes. Further, MH and SL were associated with a lower sciatic FA (MH unstandardised regression coefficient [B]=-0.048 [95% CI -0.091, -0.006], p=0.027; SL B=-0.062 [95% CI -0.103, -0.020], p=0.004) and CSA (MH ß=4.3 [95% CI 0.5, 8.0], p=0.028; SL B=4.0 [95% CI 0.4, 7.7], p=0.032) in a multivariable regression analysis. The sciatic FA correlated negatively with the sciatic CSA (r=-0.35, p=0.002) and markers of microvascular damage (high-sensitivity troponin T, urine albumin/creatinine ratio). CONCLUSIONS/INTERPRETATION: The most severe sensory phenotypes of DSPN (MH and SL) showed diminishing sciatic nerve structural integrity indexed by lower FA, likely representing progressive axonal loss, as well as increasing CSA of the sciatic nerve, which cannot be detected in individuals with TH. Individuals with type 2 diabetes may experience a predefined cascade of nerve fibre damage in the course of the disease, from healthy to TH, to MH and finally SL, while structural changes in the proximal nerve seem to precede the sensory loss of peripheral nerves and indicate potential targets for the prevention of end-stage DSPN. TRIAL REGISTRATION: ClinicalTrials.gov NCT03022721.

Cluster-based prognostication in glioblastoma: Unveiling heterogeneity based on diffusion and perfusion similarities.

BACKGROUND: While the association between diffusion and perfusion magnetic resonance imaging (MRI) and survival in glioblastoma is established, prognostic models for patients are lacking. This study employed clustering of functional imaging to identify distinct functional phenotypes in untreated glioblastomas, assessing their prognostic significance for overall survival. METHODS: A total of 289 patients with glioblastoma who underwent preoperative multimodal MR imaging were included. Mean values of apparent diffusion coefficient normalized relative cerebral blood volume and relative cerebral blood flow were calculated for different tumor compartments and the entire tumor. Distinct imaging patterns were identified using partition around medoids (PAM) clustering on the training dataset, and their ability to predict overall survival was assessed. Additionally, tree-based machine-learning models were trained to ascertain the significance of features pertaining to cluster membership. RESULTS: Using the training dataset (231/289) we identified 2 stable imaging phenotypes through PAM clustering with significantly different overall survival (OS). Validation in an independent test set revealed a high-risk group with a median OS of 10.2 months and a low-risk group with a median OS of 26.6 months (P = 0.012). Patients in the low-risk cluster had high diffusion and low perfusion values throughout, while the high-risk cluster displayed the reverse pattern. Including cluster membership in all multivariate Cox regression analyses improved performance (P ≤ 0.004 each). CONCLUSIONS: Our research demonstrates that data-driven clustering can identify clinically relevant, distinct imaging phenotypes, highlighting the potential role of diffusion, and perfusion MRI in predicting survival rates of glioblastoma patients.

Quantitative magnetic resonance neurography in chronic inflammatory demyelinating polyradiculoneuropathy: A longitudinal study over 6 years.

OBJECTIVE: To evaluate magnetic resonance neurography (MRN) for the longitudinal assessment of patients with chronic inflammatory demyelinating polyradiculoneuropathy (CIDP). METHODS: Prospective examination of twelve CIDP patients by neurological assessment, MRN, and nerve conduction studies in 2016 and 6 years later in 2022. Imaging parameters were compared with matched healthy controls and correlated with clinical and electrophysiological markers. The MRN protocol included T2-weighted imaging, diffusion tensor imaging (DTI), T2 relaxometry, and magnetization transfer imaging (MTI). RESULTS: Nerve cross-sectional area (CSA) was increased in CIDP patients compared to controls (plexus: p = 0.003; sciatic nerve: p < 0.001). Over 6 years, nerve CSA decreased in CIDP patients, most pronounced at the lumbosacral plexus (p = 0.015). Longitudinally, changes in CSA correlated with changes in the inflammatory neuropathy cause and treatment validated overall disability sum score (INCAT/ODSS) (p = 0.006). High initial nerve CSA was inversely correlated with changes in the INCAT/ODSS over 6 years (p < 0.05). The DTI parameter fractional anisotropy (FA) showed robust correlations with electrodiagnostic testing both cross-sectionally and longitudinally (p < 0.05). MTI as a newly added imaging technique revealed a significantly reduced magnetization transfer ratio (MTR) in CIDP patients (p < 0.01), suggesting underlying changes in macromolecular tissue composition, and correlated significantly with electrophysiological parameters of demyelination (p < 0.05). INTERPRETATION: This study provides evidence that changes in nerve CSA and FA reflect the clinical and electrophysiological course of CIDP patients. Initial nerve hypertrophy might predict a rather benign course or better therapy response.

An AI-based segmentation and analysis pipeline for high-field MR monitoring of cerebral organoids.

Cerebral organoids recapitulate the structure and function of the developing human brain in vitro, offering a large potential for personalized therapeutic strategies. The enormous growth of this research area over the past decade with its capability for clinical translation makes a non-invasive, automated analysis pipeline of organoids highly desirable. This work presents a novel non-invasive approach to monitor and analyze cerebral organoids over time using high-field magnetic resonance imaging and state-of-the-art tools for automated image analysis. Three specific objectives are addressed, (I) organoid segmentation to investigate organoid development over time, (II) global cysticity classification and (III) local cyst segmentation for organoid quality assessment. We show that organoid growth can be monitored reliably over time and cystic and non-cystic organoids can be separated with high accuracy, with on par or better performance compared to state-of-the-art tools applied to brightfield imaging. Local cyst segmentation is feasible but could be further improved in the future. Overall, these results highlight the potential of the pipeline for clinical application to larger-scale comparative organoid analysis.

In vivo nanoparticle-based T cell imaging can predict therapy response towards adoptive T cell therapy in experimental glioma.

Rationale: Intrinsic brain tumors, such as gliomas are largely resistant to immunotherapies including immune checkpoint blockade. Adoptive cell therapies (ACT) including chimeric antigen receptor (CAR) or T cell receptor (TCR)-transgenic T cell therapy targeting glioma-associated antigens are an emerging field in glioma immunotherapy. However, imaging techniques for non-invasive monitoring of adoptively transferred T cells homing to the glioma microenvironment are currently lacking. Methods: Ultrasmall iron oxide nanoparticles (NP) can be visualized non-invasively by magnetic resonance imaging (MRI) and dedicated MRI sequences such as T2* mapping. Here, we develop a protocol for efficient ex vivo labeling of murine and human TCR-transgenic and CAR T cells with iron oxide NPs. We assess labeling efficiency and T cell functionality by flow cytometry and transmission electron microscopy (TEM). NP labeled T cells are visualized by MRI at 9.4 T in vivo after adoptive T cell transfer and correlated with 3D models of cleared brains obtained by light sheet microscopy (LSM). Results: NP are incorporated into T cells in subcellular cytoplasmic vesicles with high labeling efficiency without interfering with T cell viability, proliferation and effector function as assessed by cytokine secretion and antigen-specific killing assays in vitro. We further demonstrate that adoptively transferred T cells can be longitudinally monitored intratumorally by high field MRI at 9.4 Tesla in a murine glioma model with high sensitivity. We find that T cell influx and homogenous spatial distribution of T cells within the TME as assessed by T2* imaging predicts tumor response to ACT whereas incomplete T cell coverage results in treatment resistance. Conclusion: This study showcases a rational for monitoring adoptive T cell therapies non-invasively by iron oxide NP in gliomas to track intratumoral T cell influx and ultimately predict treatment outcome.

Iatrogenic air embolism: influence of air bubble size on cerebral infarctions in an experimental in vivo and numerical simulation model.

BACKGROUND: Cerebral infarctions resulting from iatrogenic air embolism (AE), mainly caused by small air bubbles, are a well-known and often overlooked event in endovascular interventions. Despite their significance, the underlying pathophysiology remains largely unclear. METHODS: In 24 rats, AEs were induced using a microcatheter, positioned in the carotid artery via femoral access. Rats were divided into two study groups, based on the size of the bubbles (85 and 120 µm) and two sub-groups, differing in air volume (0.39 and 0.64 µl). Ultra-high-field magnetic resonance imaging (MRI) was performed 1.5 hours after intervention. MRI findings including the number, single volume and total volume of the infarctions were assessed. A software-based numerical simulation was performed to qualitatively assess the microvascular pathomechanisms. RESULTS: In the study groups 22 of 24 rats (92%) revealed cerebral infarctions. The number of infarctions per rat was higher for the smaller bubbles, for the lower (medians: 5 vs 3; p=0.049) and higher air volume sub-groups (medians: 6 vs 4; p=0.012). Correspondingly, total infarction volume was higher for the smaller bubbles (1.67 vs 0.5 mm³; p=0.042). Simulations confirmed the results of the experiments and suggested that fusion of microbubbles to larger bubbles is the underlying pathomechanism of vascular occlusions. CONCLUSION: In iatrogenic AE, the size of the bubbles can have a major impact on the number and total volume of cerebral infarctions. These findings can help to better understand the pathophysiology of this frequent, often underestimated adverse event in endovascular interventions.