The STRAT-PARK cohort: A personalized initiative to stratify Parkinson's disease.

The STRAT-PARK initiative aims to provide a platform for stratifying Parkinson's disease (PD) into biological subtypes, using a bottom-up, multidisciplinary biomarker-based and data-driven approach. PD is a heterogeneous entity, exhibiting high interindividual clinicopathological variability. This diversity suggests that PD may encompass multiple distinct biological entities, each driven by different molecular mechanisms. Molecular stratification and identification of disease subtypes is therefore a key priority for understanding and treating PD. STRAT-PARK is a multi-center longitudinal cohort aiming to recruit a total of 2000 individuals with PD and neurologically healthy controls from Norway and Canada, for the purpose of identifying molecular disease subtypes. Clinical assessment is performed annually, whereas biosampling, imaging, and digital and neurophysiological phenotyping occur every second year. The unique feature of STRAT-PARK is the diversity of collected biological material, including muscle biopsies and platelets, tissues particularly useful for mitochondrial biomarker research. Recruitment rate is ∼150 participants per year. By March 2023, 252 participants were included, comprising 204 cases and 48 controls. STRAT-PARK is a powerful stratification initiative anticipated to become a global research resource, contributing to personalized care in PD.

Neurobiological mechanisms of ECT and TMS treatment in depression: study protocol of a multimodal magnetic resonance investigation.

BACKGROUND: Noninvasive neurostimulation treatments are increasingly being used to treat major depression, which is a common cause of disability worldwide. While electroconvulsive therapy (ECT) and transcranial magnetic stimulation (TMS) are both effective in treating depressive episodes, their mechanisms of action are, however, not completely understood. ECT is given under general anesthesia, where an electrical pulse is administered through electrodes placed on the patient's head to trigger a seizure. ECT is used for the most severe cases of depression and is usually not prescribed before other options have failed. With TMS, brain stimulation is achieved through rapidly changing magnetic fields that induce electric currents underneath a ferromagnetic coil. Its efficacy in depressive episodes has been well documented. This project aims to identify the neurobiological underpinnings of both the effects and side effects of the neurostimulation techniques ECT and TMS. METHODS: The study will utilize a pre-post case control longitudinal design. The sample will consist of 150 subjects: 100 patients (bipolar and major depressive disorder) who are treated with either ECT (N = 50) or TMS (N = 50) and matched healthy controls (N = 50) not receiving any treatment. All participants will undergo multimodal magnetic resonance imaging (MRI) as well as neuropsychological and clinical assessments at multiple time points before, during and after treatment. Arterial spin labeling MRI at baseline will be used to test whether brain perfusion can predict outcomes. Signs of brain disruption, potentiation and rewiring will be explored with resting-state functional MRI, magnetic resonance spectroscopy and multishell diffusion weighted imaging (DWI). Clinical outcome will be measured by clinician assessed and patient reported outcome measures. Memory-related side effects will be investigated, and specific tests of spatial navigation to test hippocampal function will be administered both before and after treatment. Blood samples will be stored in a biobank for future analyses. The observation time is 6 months. Data will be explored in light of the recently proposed disrupt, potentiate and rewire (DPR) hypothesis. DISCUSSION: The study will contribute data and novel analyses important for our understanding of neurostimulation as well as for the development of enhanced and more personalized treatment. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT05135897.

Similarities and differences between intermittent and continuous resting-state fMRI.

Introduction: Functional Magnetic Resonance Imaging (fMRI) block-design experiments typically include active ON-blocks with presentation of cognitive tasks which are contrasted with OFF- blocks with no tasks presented. OFF-blocks in between ON-blocks can however, also be seen as a proxy for intermittent periods of resting, inducing temporary resting-states. We still do not know if brain activity during such intermittent periods reflects the same kind of resting-state activity as that obtained during a continuous period, as is typically the case in studies of the classic Default Mode Network (DMN). The purpose of the current study was therefore to investigate both similarities and differences in brain activity between intermittent and continuous resting conditions. Methods: There were 47 healthy participants in the 3T fMRI experiment. Data for the intermittent resting-state condition were acquired from resting-periods in between active task-processing periods in a standard ON-OFF block design, with three different cognitive tasks presented during ON-blocks. Data for the continuous resting-state condition were acquired during a 5 min resting period after the task-design had been presented. Results and discussion: The results showed that activity was overall similar in the two conditions, but with some differences. These differences were within the DMN network, and for the interaction of DMN with other brain networks. DMN maps showed weak overlap between conditions in the medial prefrontal cortex (MPFC), and in particular for the intermittent compared to the continuous resting-state condition. Moreover, DMN showed strong connectivity with the salience network (SN) in the intermittent resting-state condition, particularly in the anterior insula and the supramarginal gyrus. The observed differences may reflect a "carry-over" effect from task-processing to the next resting-state period, not present in the continuous resting-state condition, causing interference from the ON-blocks. Further research is needed to fully understand the extent of differences between intermittent and continuous resting-state conditions.

Electroconvulsive therapy triggers a reversible decrease in brain N-acetylaspartate.

Introduction: Based on previous research on electroconvulsive therapy (ECT) we have proposed a model where disruption, potentiation, and rewiring of brain networks occur in sequence and serve as the underlying therapeutic mechanism of ECT. This model implies that a temporary disturbance of neuronal networks (disruption) is followed by a trophic effect (potentiation), which enables the rewiring of neuronal circuits to a more euthymic functioning brain. We hypothesized that disruption of neuronal networks could trigger biochemical alterations leading to a temporary decrease in N-acetylaspartate (tNAA, considered a marker of neuronal integrity), while choline (a membrane component), myo-Inositol (mI, astroglia marker), and glutamate/glutamine (Glx, excitatory neurotransmitter) were postulated to increase. Previous magnetic resonance spectroscopy studies, reporting diverse findings, have used two different referencing methods - creatine ratios and tissue corrected values referenced to water - for the quantification of brain metabolites. Changes in creatine during ECT have also been reported, which may confound estimates adopting this as an internal reference. Methods: Using MR spectroscopy, we investigated 31 moderately to severely depressed patients and 19 healthy controls before, during, and after ECT or at similar time points (for controls). We tested whether biochemical alterations in tNAA, choline, mI, and Glx lend support to the disrupt, potentiate, and rewire hypothesis. We used both creatine ratios and water-scaled values for the quantification of brain metabolites to validate the results across referencing methods. Results: Levels of tNAA in the anterior cingulate cortex decreased after an ECT treatment series (average 10.6 sessions) by 6% (p = 0.007, creatine ratio) and 3% (p = 0.02, water referenced) but returned to baseline 6 months after ECT. Compared to after treatment series tNAA levels at 6-month follow-up had increased in both creatine ratio (+6%, p < 0.001) and water referenced data (+7%, p < 0.001). Findings for other brain metabolites varied and could not be validated across referencing methods. Discussion: Our findings suggest that prior research must be interpreted with care, as several referencing and processing methods have been used in the past. Yet, the results for tNAA were robust across quantification methods and concur with relevant parts of the disrupt, potentiate, and rewire model.

Microstructural changes precede depression in patients with relapsing-remitting Multiple Sclerosis.

BACKGROUND: Multiple Sclerosis lesions in the brain and spinal cord can lead to different symptoms, including cognitive and mood changes. In this study we explore the temporal relationship between early microstructural changes in subcortical volumes and cognitive and emotional function in a longitudinal cohort study of patients with relapsing-remitting Multiple Sclerosis. METHODS: In vivo imaging in forty-six patients with relapsing-remitting Multiple Sclerosis was performed annually over 3 years magnetic resonance imaging. Microstructural changes were estimated in subcortical structures using the free water fraction, a diffusion-based MRI metric. In parallel, patients were assessed with the Hospital Anxiety and Depression Scale amongst other tests. Predictive structural equation modeling was set up to further explore the relationship between imaging and the assessment scores. In a general linear model analysis, the cohort was split into patients with higher and lower depression scores. RESULTS: Nearly all subcortical diffusion microstructure estimates at the baseline visit correlate with the depression score at the 2 years follow-up. The predictive nature of baseline free water estimates and depression subscores after 2 years are confirmed in the predictive structural equation modeling analysis with the thalamus showing the greatest effect size. The general linear model analysis shows patterns of MRI free water differences in the thalamus and amygdala/hippocampus area between participants with high and low depression score. CONCLUSIONS: Our data suggests a relationship between higher levels of free-water in the subcortical structures in an early stage of Multiple Sclerosis and depression symptoms at a later stage of the disease.

Signals between the brain and spinal cord are disrupted in people with Multiple Sclerosis. For those with relapsing-remitting Multiple Sclerosis (RRMS), symptoms get periodically better and worse over time. We looked at whether changes in the brain of people with RRMS were associated with changes in their mood over time. People who had more changes in certain areas of the brain at the start of the study were more likely to have symptoms of depression later. This work suggests that early changes in the brain may be linked to increased symptoms of depression over time in people with RRMS. We believe this could be an opportunity to provide care to those suffering from RRMS to lessen the impact of severe depression symptoms before they arise.

Patterns of inflammation, microstructural alterations, and sodium accumulation define multiple sclerosis subtypes after 15 years from onset.

Introduction: Conventional MRI is routinely used for the characterization of pathological changes in multiple sclerosis (MS), but due to its lack of specificity is unable to provide accurate prognoses, explain disease heterogeneity and reconcile the gap between observed clinical symptoms and radiological evidence. Quantitative MRI provides measures of physiological abnormalities, otherwise invisible to conventional MRI, that correlate with MS severity. Analyzing quantitative MRI measures through machine learning techniques has been shown to improve the understanding of the underlying disease by better delineating its alteration patterns. Methods: In this retrospective study, a cohort of healthy controls (HC) and MS patients with different subtypes, followed up 15 years from clinically isolated syndrome (CIS), was analyzed to produce a multi-modal set of quantitative MRI features encompassing relaxometry, microstructure, sodium ion concentration, and tissue volumetry. Random forest classifiers were used to train a model able to discriminate between HC, CIS, relapsing remitting (RR) and secondary progressive (SP) MS patients based on these features and, for each classification task, to identify the relative contribution of each MRI-derived tissue property to the classification task itself. Results and discussion: Average classification accuracy scores of 99 and 95% were obtained when discriminating HC and CIS vs. SP, respectively; 82 and 83% for HC and CIS vs. RR; 76% for RR vs. SP, and 79% for HC vs. CIS. Different patterns of alterations were observed for each classification task, offering key insights in the understanding of MS phenotypes pathophysiology: atrophy and relaxometry emerged particularly in the classification of HC and CIS vs. MS, relaxometry within lesions in RR vs. SP, sodium ion concentration in HC vs. CIS, and microstructural alterations were involved across all tasks.

Brief international cognitive assessment for MS (BICAMS) and global brain volumes in early stages of MS - A longitudinal correlation study.

BACKGROUND: Cognitive impairment is common in patients with multiple sclerosis, even in the early stages of the disease. The Brief International Cognitive Assessment for multiple sclerosis (BICAMS) is a short screening tool developed to assess cognitive function in everyday clinical practice. OBJECTIVE: To investigate associations between volumetric brain measures derived from a magnetic resonance imaging (MRI) examination and performance on BICAMS subtests in early stages of multiple sclerosis (MS). METHODS: BICAMS was used to assess cognitive function in 49 MS patients at baseline and after one and two years. The patients were separated into two groups (with or without cognitive impairment) based on their performances on BICAMSs subtests. MRI data were analysed by a software tool (MSMetrix), yielding normalized measures of global brain volumes and lesion volumes. Associations between cognitive tests and brain MRI measures were analysed by running correlation analyses, and differences between subgroups and changes over time with independent and paired samples tests, respectively. RESULTS: The strongest baseline correlations were found between the BICAMS subtests and normalized whole brain volume (NBV) and grey matter volume (NGV); processing speed r = 0.54/r = 0.48, verbal memory r = 0.49/ r = 0.42, visual memory r = 0.48 /r = 0.39. Only the verbal memory test had significant correlations with T2 and T1 lesion volumes (LV) at both time points; T2LV r = 0.39, T1LV r = 0.38. There were significant loss of grey matter and white matter volume overall (NGV p<0.001, NWV p = 0.003), as well as an increase in T1LV (p = 0.013). The longitudinally defined confirmed cognitively impaired (CCI) and preserved (CCP) patients showed significant group differences on all MRI volume measures at both time points, except for NWV. Only the CCI subgroup showed significant white matter atrophy (p = 0.006) and increase in T2LV (p = 0.029). CONCLUSIONS: The present study found strong correlations between whole brain and grey matter volumes and performance on the BICAMS subtests as well as significant changes in global volumes from baseline to follow-up with clear differences between patients defined as cognitively impaired and preserved at both baseline and follow-up.

Predicting Survival in Patients with Brain Tumors: Current State-of-the-Art of AI Methods Applied to MRI.

Given growing clinical needs, in recent years Artificial Intelligence (AI) techniques have increasingly been used to define the best approaches for survival assessment and prediction in patients with brain tumors. Advances in computational resources, and the collection of (mainly) public databases, have promoted this rapid development. This narrative review of the current state-of-the-art aimed to survey current applications of AI in predicting survival in patients with brain tumors, with a focus on Magnetic Resonance Imaging (MRI). An extensive search was performed on PubMed and Google Scholar using a Boolean research query based on MeSH terms and restricting the search to the period between 2012 and 2022. Fifty studies were selected, mainly based on Machine Learning (ML), Deep Learning (DL), radiomics-based methods, and methods that exploit traditional imaging techniques for survival assessment. In addition, we focused on two distinct tasks related to survival assessment: the first on the classification of subjects into survival classes (short and long-term or eventually short, mid and long-term) to stratify patients in distinct groups. The second focused on quantification, in days or months, of the individual survival interval. Our survey showed excellent state-of-the-art methods for the first, with accuracy up to ∼98%. The latter task appears to be the most challenging, but state-of-the-art techniques showed promising results, albeit with limitations, with C-Index up to ∼0.91. In conclusion, according to the specific task, the available computational methods perform differently, and the choice of the best one to use is non-univocal and dependent on many aspects. Unequivocally, the use of features derived from quantitative imaging has been shown to be advantageous for AI applications, including survival prediction. This evidence from the literature motivates further research in the field of AI-powered methods for survival prediction in patients with brain tumors, in particular, using the wealth of information provided by quantitative MRI techniques.

Imaging Glioblastoma Metabolism by Using Hyperpolarized [1-13C]Pyruvate Demonstrates Heterogeneity in Lactate Labeling: A Proof of Principle Study.

Purpose To evaluate glioblastoma (GBM) metabolism by using hyperpolarized carbon 13 (13C) MRI to monitor the exchange of the hyperpolarized 13C label between injected [1-13C]pyruvate and tumor lactate and bicarbonate. Materials and Methods In this prospective study, seven treatment-naive patients (age [mean ± SD], 60 years ± 11; five men) with GBM were imaged at 3 T by using a dual-tuned 13C-hydrogen 1 head coil. Hyperpolarized [1-13C]pyruvate was injected, and signal was acquired by using a dynamic MRI spiral sequence. Metabolism was assessed within the tumor, in the normal-appearing brain parenchyma (NABP), and in healthy volunteers by using paired or unpaired t tests and a Wilcoxon signed rank test. The Spearman ρ correlation coefficient was used to correlate metabolite labeling with lactate dehydrogenase A (LDH-A) expression and some immunohistochemical markers. The Benjamini-Hochberg procedure was used to correct for multiple comparisons. Results The bicarbonate-to-pyruvate (BP) ratio was lower in the tumor than in the contralateral NABP (P < .01). The tumor lactate-to-pyruvate (LP) ratio was not different from that in the NABP (P = .38). The LP and BP ratios in the NABP were higher than those observed previously in healthy volunteers (P < .05). Tumor lactate and bicarbonate signal intensities were strongly correlated with the pyruvate signal intensity (ρ = 0.92, P < .001, and ρ = 0.66, P < .001, respectively), and the LP ratio was weakly correlated with LDH-A expression in biopsy samples (ρ = 0.43, P = .04). Conclusion Hyperpolarized 13C MRI demonstrated variation in lactate labeling in GBM, both within and between tumors. In contrast, bicarbonate labeling was consistently lower in tumors than in the surrounding NABP. Keywords: Hyperpolarized 13C MRI, Glioblastoma, Metabolism, Cancer, MRI, Neuro-oncology Supplemental material is available for this article. Published under a CC BY 4.0 license.

Sodium accumulation in breast cancer predicts malignancy and treatment response.

BACKGROUND: Breast cancer remains a leading cause of death in women and novel imaging biomarkers are urgently required. Here, we demonstrate the diagnostic and treatment-monitoring potential of non-invasive sodium (23Na) MRI in preclinical models of breast cancer. METHODS: Female Rag2-/- Il2rg-/- and Balb/c mice bearing orthotopic breast tumours (MDA-MB-231, EMT6 and 4T1) underwent MRI as part of a randomised, controlled, interventional study. Tumour biology was probed using ex vivo fluorescence microscopy and electrophysiology. RESULTS: 23Na MRI revealed elevated sodium concentration ([Na+]) in tumours vs non-tumour regions. Complementary proton-based diffusion-weighted imaging (DWI) linked elevated tumour [Na+] to increased cellularity. Combining 23Na MRI and DWI measurements enabled superior classification accuracy of tumour vs non-tumour regions compared with either parameter alone. Ex vivo assessment of isolated tumour slices confirmed elevated intracellular [Na+] ([Na+]i); extracellular [Na+] ([Na+]e) remained unchanged. Treatment with specific inward Na+ conductance inhibitors (cariporide, eslicarbazepine acetate) did not affect tumour [Na+]. Nonetheless, effective treatment with docetaxel reduced tumour [Na+], whereas DWI measures were unchanged. CONCLUSIONS: Orthotopic breast cancer models exhibit elevated tumour [Na+] that is driven by aberrantly elevated [Na+]i. Moreover, 23Na MRI enhances the diagnostic capability of DWI and represents a novel, non-invasive biomarker of treatment response with superior sensitivity compared to DWI alone.

High-Grade Glioma Treatment Response Monitoring Biomarkers: A Position Statement on the Evidence Supporting the Use of Advanced MRI Techniques in the Clinic, and the Latest Bench-to-Bedside Developments. Part 1: Perfusion and Diffusion Techniques.

Objective: Summarize evidence for use of advanced MRI techniques as monitoring biomarkers in the clinic, and highlight the latest bench-to-bedside developments. Methods: Experts in advanced MRI techniques applied to high-grade glioma treatment response assessment convened through a European framework. Current evidence regarding the potential for monitoring biomarkers in adult high-grade glioma is reviewed, and individual modalities of perfusion, permeability, and microstructure imaging are discussed (in Part 1 of two). In Part 2, we discuss modalities related to metabolism and/or chemical composition, appraise the clinic readiness of the individual modalities, and consider post-processing methodologies involving the combination of MRI approaches (multiparametric imaging) or machine learning (radiomics). Results: High-grade glioma vasculature exhibits increased perfusion, blood volume, and permeability compared with normal brain tissue. Measures of cerebral blood volume derived from dynamic susceptibility contrast-enhanced MRI have consistently provided information about brain tumor growth and response to treatment; it is the most clinically validated advanced technique. Clinical studies have proven the potential of dynamic contrast-enhanced MRI for distinguishing post-treatment related effects from recurrence, but the optimal acquisition protocol, mode of analysis, parameter of highest diagnostic value, and optimal cut-off points remain to be established. Arterial spin labeling techniques do not require the injection of a contrast agent, and repeated measurements of cerebral blood flow can be performed. The absence of potential gadolinium deposition effects allows widespread use in pediatric patients and those with impaired renal function. More data are necessary to establish clinical validity as monitoring biomarkers. Diffusion-weighted imaging, apparent diffusion coefficient analysis, diffusion tensor or kurtosis imaging, intravoxel incoherent motion, and other microstructural modeling approaches also allow treatment response assessment; more robust data are required to validate these alone or when applied to post-processing methodologies. Conclusion: Considerable progress has been made in the development of these monitoring biomarkers. Many techniques are in their infancy, whereas others have generated a larger body of evidence for clinical application.

The NADPARK study: A randomized phase I trial of nicotinamide riboside supplementation in Parkinson's disease.

We conducted a double-blinded phase I clinical trial to establish whether nicotinamide adenine dinucleotide (NAD) replenishment therapy, via oral intake of nicotinamide riboside (NR), is safe, augments cerebral NAD levels, and impacts cerebral metabolism in Parkinson's disease (PD). Thirty newly diagnosed, treatment-naive patients received 1,000 mg NR or placebo for 30 days. NR treatment was well tolerated and led to a significant, but variable, increase in cerebral NAD levels-measured by 31phosphorous magnetic resonance spectroscopy-and related metabolites in the cerebrospinal fluid. NR recipients showing increased brain NAD levels exhibited altered cerebral metabolism, measured by 18fluoro-deoxyglucose positron emission tomography, and this was associated with mild clinical improvement. NR augmented the NAD metabolome and induced transcriptional upregulation of processes related to mitochondrial, lysosomal, and proteasomal function in blood cells and/or skeletal muscle. Furthermore, NR decreased the levels of inflammatory cytokines in serum and cerebrospinal fluid. Our findings nominate NR as a potential neuroprotective therapy for PD, warranting further investigation in larger trials.

Hyperpolarized 13C-Pyruvate Metabolism as a Surrogate for Tumor Grade and Poor Outcome in Renal Cell Carcinoma-A Proof of Principle Study.

Differentiating aggressive clear cell renal cell carcinoma (ccRCC) from indolent lesions is challenging using conventional imaging. This work prospectively compared the metabolic imaging phenotype of renal tumors using carbon-13 MRI following injection of hyperpolarized [1-13C]pyruvate (HP-13C-MRI) and validated these findings with histopathology. Nine patients with treatment-naïve renal tumors (6 ccRCCs, 1 liposarcoma, 1 pheochromocytoma, 1 oncocytoma) underwent pre-operative HP-13C-MRI and conventional proton (1H) MRI. Multi-regional tissue samples were collected using patient-specific 3D-printed tumor molds for spatial registration between imaging and molecular analysis. The apparent exchange rate constant (kPL) between 13C-pyruvate and 13C-lactate was calculated. Immunohistochemistry for the pyruvate transporter (MCT1) from 44 multi-regional samples, as well as associations between MCT1 expression and outcome in the TCGA-KIRC dataset, were investigated. Increasing kPL in ccRCC was correlated with increasing overall tumor grade (ρ = 0.92, p = 0.009) and MCT1 expression (r = 0.89, p = 0.016), with similar results acquired from the multi-regional analysis. Conventional 1H-MRI parameters did not discriminate tumor grades. The correlation between MCT1 and ccRCC grade was confirmed within a TCGA dataset (p < 0.001), where MCT1 expression was a predictor of overall and disease-free survival. In conclusion, metabolic imaging using HP-13C-MRI differentiates tumor aggressiveness in ccRCC and correlates with the expression of MCT1, a predictor of survival. HP-13C-MRI may non-invasively characterize metabolic phenotypes within renal cancer.

Effects of Multi-Shell Free Water Correction on Glioma Characterization.

Diffusion MRI is a useful tool to investigate the microstructure of brain tumors. However, the presence of fast diffusing isotropic signals originating from non-restricted edematous fluids, within and surrounding tumors, may obscure estimation of the underlying tissue characteristics, complicating the radiological interpretation and quantitative evaluation of diffusion MRI. A multi-shell regularized free water (FW) elimination model was therefore applied to separate free water from tissue-related diffusion components from the diffusion MRI of 26 treatment-naïve glioma patients. We then investigated the diagnostic value of the derived measures of FW maps as well as FW-corrected tensor-derived maps of fractional anisotropy (FA). Presumed necrotic tumor regions display greater mean and variance of FW content than other parts of the tumor. On average, the area under the receiver operating characteristic (ROC) for the classification of necrotic and enhancing tumor volumes increased by 5% in corrected data compared to non-corrected data. FW elimination shifts the FA distribution in non-enhancing tumor parts toward higher values and significantly increases its entropy (p ≤ 0.003), whereas skewness is decreased (p ≤ 0.004). Kurtosis is significantly decreased (p < 0.001) in high-grade tumors. In conclusion, eliminating FW contributions improved quantitative estimations of FA, which helps to disentangle the cancer heterogeneity.

Multiparametric MRI of early tumor response to immune checkpoint blockade in metastatic melanoma.

BACKGROUND: Immune checkpoint inhibitors are now standard of care treatment for many cancers. Treatment failure in metastatic melanoma is often due to tumor heterogeneity, which is not easily captured by conventional CT or tumor biopsy. The aim of this prospective study was to investigate early microstructural and functional changes within melanoma metastases following immune checkpoint blockade using multiparametric MRI. METHODS: Fifteen treatment-naïve metastatic melanoma patients (total 27 measurable target lesions) were imaged at baseline and following 3 and 12 weeks of treatment on immune checkpoint inhibitors using: T2-weighted imaging, diffusion kurtosis imaging, and dynamic contrast-enhanced MRI. Treatment timepoint changes in tumor cellularity, vascularity, and heterogeneity within individual metastases were evaluated and correlated to the clinical outcome in each patient based on Response Evaluation Criteria in Solid Tumors V.1.1 at 1 year. RESULTS: Differential tumor growth kinetics in response to immune checkpoint blockade were measured in individual metastases within the same patient, demonstrating significant intertumoral heterogeneity in some patients. Early detection of tumor cell death or cell loss measured by a significant increase in the apparent diffusivity (Dapp) (p<0.05) was observed in both responding and pseudoprogressive lesions after 3 weeks of treatment. Tumor heterogeneity, as measured by apparent diffusional kurtosis (Kapp), was consistently higher in the pseudoprogressive and true progressive lesions, compared with the responding lesions throughout the first 12 weeks of treatment. These preceded tumor regression and significant tumor vascularity changes (Ktrans, ve, and vp) detected after 12 weeks of immunotherapy (p<0.05). CONCLUSIONS: Multiparametric MRI demonstrated potential for early detection of successful response to immune checkpoint inhibitors in metastatic melanoma.

Imaging and treatment of brain tumors through molecular targeting: Recent clinical advances.

Molecular imaging techniques have rapidly progressed over recent decades providing unprecedented in vivo characterization of metabolic pathways and molecular biomarkers. Many of these new techniques have been successfully applied in the field of neuro-oncological imaging to probe tumor biology. Targeting specific signaling or metabolic pathways could help to address several unmet clinical needs that hamper the management of patients with brain tumors. This review aims to provide an overview of the recent advances in brain tumor imaging using molecular targeting with positron emission tomography and magnetic resonance imaging, as well as the role in patient management and possible therapeutic implications.

Combined 23 Na and 13 C imaging at 3.0 Tesla using a single-tuned large FOV birdcage coil.

PURPOSE: An unmet need in carbon-13 (13 C)-MRI is a transmit system that provides uniform excitation across a large FOV and can accommodate patients of wide-ranging body habitus. Due to the small difference between the resonant frequencies, sodium-23 (23 Na) coil developments can inform 13 C coil design while being simpler to assess due to the higher naturally abundant 23 Na signal. Here we present a removable 23 Na birdcage, which also allows operation as a 13 C abdominal coil. METHODS: We demonstrate a quadrature-driven 4-rung 23 Na birdcage coil of 50 cm in length for both 23 Na and 13 C abdominal imaging. The coil transmit efficiencies and B1+ maps were compared to a linearly driven 13 C Helmholtz-based (clamshell) coil. SNR was investigated with 23 Na and 13 C data using an 8-channel 13 C receive array within the 23 Na birdcage. RESULTS: The 23 Na birdcage longitudinal FOV was > 40 cm, whereas the 13 C clamshell was < 32 cm. The transmit efficiency of the birdcage at the 23 Na frequency was 0.65 µT/sqrt(W), similar to the clamshell for 13 C. However, the coefficient of variation of 23 Na- B1+ was 16%, nearly half that with the 13 C clamshell. The 8-channel 13 C receive array combined with the 23 Na birdcage coil generated a greater than twofold increase in 23 Na-SNR from the central abdomen compared with the birdcage alone. DISCUSSION: This 23 Na birdcage coil has a larger FOV and improved B1+ uniformity when compared to the widely used clamshell coil design while also providing similar transmit efficiency. The coil has the potential to be used for both 23 Na and 13 C imaging.

Investigating the relationship between diffusion kurtosis tensor imaging (DKTI) and histology within the normal human brain.

Measurements of water diffusion with MRI have been used as a biomarker of tissue microstructure and heterogeneity. In this study, diffusion kurtosis tensor imaging (DKTI) of the brain was undertaken in 10 healthy volunteers at a clinical field strength of 3 T. Diffusion and kurtosis metrics were measured in regions-of-interest on the resulting maps and compared with quantitative analysis of normal post-mortem tissue histology from separate age-matched donors. White matter regions showed low diffusion (0.60 ± 0.04 × 10-3 mm2/s) and high kurtosis (1.17 ± 0.06), consistent with a structured heterogeneous environment comprising parallel neuronal fibres. Grey matter showed intermediate diffusion (0.80 ± 0.02 × 10-3 mm2/s) and kurtosis (0.82 ± 0.05) values. An important finding is that the subcortical regions investigated (thalamus, caudate and putamen) showed similar diffusion and kurtosis properties to white matter. Histological staining of the subcortical nuclei demonstrated that the predominant grey matter was permeated by small white matter bundles, which could account for the similar kurtosis to white matter. Quantitative histological analysis demonstrated higher mean tissue kurtosis and vector standard deviation values for white matter (1.08 and 0.81) compared to the subcortical regions (0.34 and 0.59). Mean diffusion on DKTI was positively correlated with tissue kurtosis (r = 0.82, p < 0.05) and negatively correlated with vector standard deviation (r = -0.69, p < 0.05). This study demonstrates how DKTI can be used to study regional structural variations in the cerebral tissue microenvironment and could be used to probe microstructural changes within diseased tissue in the future.

High-Grade Glioma Treatment Response Monitoring Biomarkers: A Position Statement on the Evidence Supporting the Use of Advanced MRI Techniques in the Clinic, and the Latest Bench-to-Bedside Developments. Part 2: Spectroscopy, Chemical Exchange Saturation, Multiparametric Imaging, and Radiomics.

Objective: To summarize evidence for use of advanced MRI techniques as monitoring biomarkers in the clinic, and to highlight the latest bench-to-bedside developments. Methods: The current evidence regarding the potential for monitoring biomarkers was reviewed and individual modalities of metabolism and/or chemical composition imaging discussed. Perfusion, permeability, and microstructure imaging were similarly analyzed in Part 1 of this two-part review article and are valuable reading as background to this article. We appraise the clinic readiness of all the individual modalities and consider methodologies involving machine learning (radiomics) and the combination of MRI approaches (multiparametric imaging). Results: The biochemical composition of high-grade gliomas is markedly different from healthy brain tissue. Magnetic resonance spectroscopy allows the simultaneous acquisition of an array of metabolic alterations, with choline-based ratios appearing to be consistently discriminatory in treatment response assessment, although challenges remain despite this being a mature technique. Promising directions relate to ultra-high field strengths, 2-hydroxyglutarate analysis, and the use of non-proton nuclei. Labile protons on endogenous proteins can be selectively targeted with chemical exchange saturation transfer to give high resolution images. The body of evidence for clinical application of amide proton transfer imaging has been building for a decade, but more evidence is required to confirm chemical exchange saturation transfer use as a monitoring biomarker. Multiparametric methodologies, including the incorporation of nuclear medicine techniques, combine probes measuring different tumor properties. Although potentially synergistic, the limitations of each individual modality also can be compounded, particularly in the absence of standardization. Machine learning requires large datasets with high-quality annotation; there is currently low-level evidence for monitoring biomarker clinical application. Conclusion: Advanced MRI techniques show huge promise in treatment response assessment. The clinical readiness analysis highlights that most monitoring biomarkers require standardized international consensus guidelines, with more facilitation regarding technique implementation and reporting in the clinic.

Characterization and correction of center-frequency effects in X-nuclear eddy current compensations on a clinical MR system.

PURPOSE: The aim of the study was to investigate whether incorrectly compensated eddy currents are the source of persistent X-nuclear spectroscopy and imaging artifacts, as well as methods to correct this. METHODS: Pulse-acquire spectra were collected for 1 H and X-nuclei (23 Na or 31 P) using the minimum TR permitted on a 3T clinical MRI system. Data were collected in 3 orientations (axial, sagittal, and coronal) with the spoiler gradient at the end of the TR applied along the slice direction for each. Modifications to system calibration files to tailor eddy current compensation for each X-nucleus were developed and applied, and data were compared with and without these corrections for: slice-selective MRS (for 23 Na and 31 P), 2D spiral trajectories (for 13 C), and 3D cones trajectories (for 23 Na). RESULTS: Line-shape distortions characteristic of eddy currents were demonstrated for X-nuclei, which were not seen for 1 H. The severity of these correlated with the amplitude of the eddy current frequency compensation term applied by the system along the axis of the applied spoiler gradient. A proposed correction to eddy current compensation, taking account of the gyromagnetic ratio, was shown to dramatically reduce these distortions. The same correction was also shown to improve data quality of non-Cartesian imaging (2D spiral and 3D cones trajectories). CONCLUSION: A simple adaptation of the default compensation for eddy currents was shown to eliminate a range of artifacts detected on X-nuclear spectroscopy and imaging.