Structures, functions and adaptations of the human LINE-1 ORF2 protein.

The LINE-1 (L1) retrotransposon is an ancient genetic parasite that has written around one-third of the human genome through a 'copy and paste' mechanism catalysed by its multifunctional enzyme, open reading frame 2 protein (ORF2p)1. ORF2p reverse transcriptase (RT) and endonuclease activities have been implicated in the pathophysiology of cancer2,3, autoimmunity4,5 and ageing6,7, making ORF2p a potential therapeutic target. However, a lack of structural and mechanistic knowledge has hampered efforts to rationally exploit it. We report structures of the human ORF2p 'core' (residues 238-1061, including the RT domain) by X-ray crystallography and cryo-electron microscopy in several conformational states. Our analyses identified two previously undescribed folded domains, extensive contacts to RNA templates and associated adaptations that contribute to unique aspects of the L1 replication cycle. Computed integrative structural models of full-length ORF2p show a dynamic closed-ring conformation that appears to open during retrotransposition. We characterize ORF2p RT inhibition and reveal its underlying structural basis. Imaging and biochemistry show that non-canonical cytosolic ORF2p RT activity can produce RNA:DNA hybrids, activating innate immune signalling through cGAS/STING and resulting in interferon production6-8. In contrast to retroviral RTs, L1 RT is efficiently primed by short RNAs and hairpins, which probably explains cytosolic priming. Other biochemical activities including processivity, DNA-directed polymerization, non-templated base addition and template switching together allow us to propose a revised L1 insertion model. Finally, our evolutionary analysis demonstrates structural conservation between ORF2p and other RNA- and DNA-dependent polymerases. We therefore provide key mechanistic insights into L1 polymerization and insertion, shed light on the evolutionary history of L1 and enable rational drug development targeting L1.

Fork Cleavage-Religation Cycle and Active Transcription Mediate Replication Restart after Fork Stalling at Co-transcriptional R-Loops.

Formation of co-transcriptional R-loops underlies replication fork stalling upon head-on transcription-replication encounters. Here, we demonstrate that RAD51-dependent replication fork reversal induced by R-loops is followed by the restart of semiconservative DNA replication mediated by RECQ1 and RECQ5 helicases, MUS81/EME1 endonuclease, RAD52 strand-annealing factor, the DNA ligase IV (LIG4)/XRCC4 complex, and the non-catalytic subunit of DNA polymerase δ, POLD3. RECQ5 disrupts RAD51 filaments assembled on stalled forks after RECQ1-mediated reverse branch migration, preventing a new round of fork reversal and facilitating fork cleavage by MUS81/EME1. MUS81-dependent DNA breaks accumulate in cells lacking RAD52 or LIG4 upon induction of R-loop formation, suggesting that RAD52 acts in concert with LIG4/XRCC4 to catalyze fork religation, thereby mediating replication restart. The resumption of DNA synthesis after R-loop-associated fork stalling also requires active transcription, the restoration of which depends on MUS81, RAD52, LIG4, and the transcription elongation factor ELL. These findings provide mechanistic insights into transcription-replication conflict resolution.

Senataxin RNA/DNA helicase promotes replication restart at co-transcriptional R-loops to prevent MUS81-dependent fork degradation.

Replication forks stalled at co-transcriptional R-loops can be restarted by a mechanism involving fork cleavage-religation cycles mediated by MUS81 endonuclease and DNA ligase IV (LIG4), which presumably relieve the topological barrier generated by the transcription-replication conflict (TRC) and facilitate ELL-dependent reactivation of transcription. Here, we report that the restart of R-loop-stalled replication forks via the MUS81-LIG4-ELL pathway requires senataxin (SETX), a helicase that can unwind RNA:DNA hybrids. We found that SETX promotes replication fork progression by preventing R-loop accumulation during S-phase. Interestingly, loss of SETX helicase activity leads to nascent DNA degradation upon induction of R-loop-mediated fork stalling by hydroxyurea. This fork degradation phenotype is independent of replication fork reversal and results from DNA2-mediated resection of MUS81-cleaved replication forks that accumulate due to defective replication restart. Finally, we demonstrate that SETX acts in a common pathway with the DEAD-box helicase DDX17 to suppress R-loop-mediated replication stress in human cells. A possible cooperation between these RNA/DNA helicases in R-loop unwinding at TRC sites is discussed.

Biochemical, biomechanical and imaging biomarkers of ischemic stroke: Time for integrative thinking.

Stroke is one of the leading causes of adult disability affecting millions of people worldwide. Post-stroke cognitive and motor impairments diminish quality of life and functional independence. There is an increased risk of having a second stroke and developing secondary conditions with long-term social and economic impacts. With increasing number of stroke incidents, shortage of medical professionals and limited budgets, health services are struggling to provide a care that can break the vicious cycle of stroke. Effective post-stroke recovery hinges on holistic, integrative and personalized care starting from improved diagnosis and treatment in clinics to continuous rehabilitation and support in the community. To improve stroke care pathways, there have been growing efforts in discovering biomarkers that can provide valuable insights into the neural, physiological and biomechanical consequences of stroke and how patients respond to new interventions. In this review paper, we aim to summarize recent biomarker discovery research focusing on three modalities (brain imaging, blood sampling and gait assessments), look at some established and forthcoming biomarkers, and discuss their usefulness and complementarity within the context of comprehensive stroke care. We also emphasize the importance of biomarker guided personalized interventions to enhance stroke treatment and post-stroke recovery.

Fast 19 F spectroscopic imaging with pseudo-spiral k-space sampling.

Fluorine MRI is finding wider acceptance in theranostics applications where imaging of 19 F hotspots of fluorinated contrast material is central. The essence of such applications is to capture ghosting-artifact-free images of the inherently low MR response under clinically viable conditions. To serve this purpose, this work introduces the balanced spiral spectroscopic imaging (BaSSI) sequence, which is implemented on a 3.0 T clinical scanner and is capable of generating 19 F hotspot images in an efficient manner. The sequence utilizes an all-phase-encoded pseudo-spiral k-space trajectory, enabling the acquisition of broadband (80 ppm) fluorine spectra free from chemical shift ghosting. BaSSI can acquire a 64 × 64 image with 1 mm × 1 mm voxels in just 14 s, significantly outperforming typical MRSI sequences used in 1 H or 31 P imaging. The study employed in silico characterization to verify essential design choices such as the excitation pulse, as well as to identify the boundaries of the parameter space explored for optimization. BaSSI's performance was further benchmarked against the 3D ultrashort-echo-time balanced steady-state free precession (3D UTE BSSFP) sequence, a well established method used in 19 F MRI, in vitro. Both sequences underwent extensive optimization through exploration of a wide parameter space on a small phantom containing 10 µL of non-diluted bulk perfluorooctylbromide (PFOB) prior to comparative experiments. Subsequent to optimization, BaSSI and 3D UTE BSSFP were employed to capture images of small non-diluted bulk PFOB samples (0.10 and 0.05 µL), with variations in the number of signal averages, and thus the total scan time, in order to assess the detection sensitivities of the sequences. In these experiments, the detection sensitivity was evaluated using the Rose criterion (Rc ), which provides a quantitative metric for assessing object visibility. The study further demonstrated BaSSI's utility as a (pre)clinical tool through postmortem imaging of polymer microspheres filled with PFOB in a BALB/c mouse. Anatomic localization of 19 F hotspots was achieved by denoising raw data obtained with BaSSI using a filter based on the Rose criterion. These data were then successfully registered to 1 H anatomical images. BaSSI demonstrated superior detection sensitivity in the benchmarking analysis, achieving Rc values approximately twice as high as those obtained with the 3D UTE BSSFP method. The technique successfully facilitated imaging and precise localization of 19 F hotspots in postmortem experiments. However, it is important to highlight that imaging 10 mM PFOB in small mice postmortem, utilizing a 48 × 48 × 48 3D scan, demanded a substantial scan time of 1 h and 45 min. Further studies will explore accelerated imaging techniques, such as compressed sensing, to enhance BaSSI's clinical utility.

Pulmonary vasculature development in congenital diaphragmatic hernia: a novel automated quantitative imaging analysis.

PURPOSE: Impaired fetal lung vasculature determines the degree of pulmonary hypertension in the congenital diaphragmatic hernia (CDH). This study aims to demonstrate the morphometric measurements that differ in pulmonary vessels of fetuses with CDH. METHODS: Nitrofen-induced CDH Sprague-Dawley rat fetuses were scanned with microcomputed tomography. The analysis of the pulmonary vascular tree was performed with artificial intelligence. RESULTS: The number of segments in CDH was significantly lower than that in the control group on the left (U = 2.5, p = 0.004) and right (U = 0, p = 0.001) sides for order 1(O1), whereas there was a significant difference only on the right side for O2 and O3. The pooled element numbers in the control group obeyed Horton's law (R2 = 0.996 left and R2 = 0.811 right lungs), while the CDH group broke it. Connectivity matrices showed that the average number of elements of O1 springing from elements of O1 on the left side and the number of elements of O1 springing from elements of O3 on the right side were significantly lower in CDH samples. CONCLUSION: According to these findings, CDH not only reduced the amount of small order elements, but also destroyed the fractal structure of the pulmonary arterial trees.

Advanced MR Techniques for Preoperative Glioma Characterization: Part 2.

Preoperative clinical MRI protocols for gliomas, brain tumors with dismal outcomes due to their infiltrative properties, still rely on conventional structural MRI, which does not deliver information on tumor genotype and is limited in the delineation of diffuse gliomas. The GliMR COST action wants to raise awareness about the state of the art of advanced MRI techniques in gliomas and their possible clinical translation. This review describes current methods, limits, and applications of advanced MRI for the preoperative assessment of glioma, summarizing the level of clinical validation of different techniques. In this second part, we review magnetic resonance spectroscopy (MRS), chemical exchange saturation transfer (CEST), susceptibility-weighted imaging (SWI), MRI-PET, MR elastography (MRE), and MR-based radiomics applications. The first part of this review addresses dynamic susceptibility contrast (DSC) and dynamic contrast-enhanced (DCE) MRI, arterial spin labeling (ASL), diffusion-weighted MRI, vessel imaging, and magnetic resonance fingerprinting (MRF). EVIDENCE LEVEL: 3. TECHNICAL EFFICACY: Stage 2.

Advanced MR Techniques for Preoperative Glioma Characterization: Part 1.

Preoperative clinical magnetic resonance imaging (MRI) protocols for gliomas, brain tumors with dismal outcomes due to their infiltrative properties, still rely on conventional structural MRI, which does not deliver information on tumor genotype and is limited in the delineation of diffuse gliomas. The GliMR COST action wants to raise awareness about the state of the art of advanced MRI techniques in gliomas and their possible clinical translation or lack thereof. This review describes current methods, limits, and applications of advanced MRI for the preoperative assessment of glioma, summarizing the level of clinical validation of different techniques. In this first part, we discuss dynamic susceptibility contrast and dynamic contrast-enhanced MRI, arterial spin labeling, diffusion-weighted MRI, vessel imaging, and magnetic resonance fingerprinting. The second part of this review addresses magnetic resonance spectroscopy, chemical exchange saturation transfer, susceptibility-weighted imaging, MRI-PET, MR elastography, and MR-based radiomics applications. Evidence Level: 3 Technical Efficacy: Stage 2.

Assessment of myelin oligodendrocyte glycoprotein antibodies and magnetic resonance spectroscopy in childhood-onset systemic lupus erythematosus.

OBJECTIVES: Systemic lupus erythematosus (SLE) is a chronic inflammatory disease characterised by the presence of various autoantibodies. Mild cognitive impairment developing in patients without significant neuropsychiatric (NP) symptoms was thought to be the result of immune-mediated myelinopathy. We aimed to determine the role of myelin oligodendrocyte glycoprotein antibody (MOG-Ab) in the neurological manifestations of childhood-onset SLE (cSLE) and if there is a correlation between various metabolite peaks in magnetic resonance spectroscopy (MRS) and myelinopathy. METHODS: MOG-Ab levels were studied in all healthy subjects (n=28) and in all patients with (NPSLE=9) and without (non-NPSLE=36) overt neuropsychiatric manifestations. Twenty patients (all had a normal-appearing brain on plain magnetic resonance) in non-NPSLE and 20 subjects in healthy group met the MRS imaging standards for evaluation in which normal appearing brain on plain MR. RESULTS: A total of 45 cSLE (36 non-NPSLE and 9 NPSLE) subjects and 28 healthy children were recruited to the study. The mean age of the SLE patients at study time was 16.22±3.22 years. MOG-Ab was not detected in cSLE or in healthy group. There was no significant difference between the non-NPSLE group and healthy subjects in terms of choline, N-acetyl aspartate (NAA), creatine, NAA/creatine, and choline/creatine. CONCLUSIONS: There was no association of MOG-Ab with cSLE, whether NP manifestations were present or not. A causal relationship between immune-mediated myelinopathy and cognitive impairment could not be suggested, since there has been no patient with positive MOG-Ab and there has been no difference in choline, choline/creatine between groups.

Identification of metabolic correlates of mild cognitive impairment in Parkinson's disease using magnetic resonance spectroscopic imaging and machine learning.

OBJECTIVE: To investigate metabolic changes of mild cognitive impairment in Parkinson's disease (PD-MCI) using proton magnetic resonance spectroscopic imaging (1H-MRSI). METHODS: Sixteen healthy controls (HC), 26 cognitively normal Parkinson's disease (PD-CN) patients, and 34 PD-MCI patients were scanned in this prospective study. Neuropsychological tests were performed, and three-dimensional 1H-MRSI was obtained at 3 T. Metabolic parameters and neuropsychological test scores were compared between PD-MCI, PD-CN, and HC. The correlations between neuropsychological test scores and metabolic intensities were also assessed. Supervised machine learning algorithms were applied to classify HC, PD-CN, and PD-MCI groups based on metabolite levels. RESULTS: PD-MCI had a lower corrected total N-acetylaspartate over total creatine ratio (tNAA/tCr) in the right precentral gyrus, corresponding to the sensorimotor network (p = 0.01), and a lower tNAA over myoinositol ratio (tNAA/mI) at a part of the default mode network, corresponding to the retrosplenial cortex (p = 0.04) than PD-CN. The HC and PD-MCI patients were classified with an accuracy of 86.4% (sensitivity = 72.7% and specificity = 81.8%) using bagged trees. CONCLUSION: 1H-MRSI revealed metabolic changes in the default mode, ventral attention/salience, and sensorimotor networks of PD-MCI patients, which could be summarized mainly as 'posterior cortical metabolic changes' related with cognitive dysfunction.

The Open Brain Consent: Informing research participants and obtaining consent to share brain imaging data.

Having the means to share research data openly is essential to modern science. For human research, a key aspect in this endeavor is obtaining consent from participants, not just to take part in a study, which is a basic ethical principle, but also to share their data with the scientific community. To ensure that the participants' privacy is respected, national and/or supranational regulations and laws are in place. It is, however, not always clear to researchers what the implications of those are, nor how to comply with them. The Open Brain Consent (https://open-brain-consent.readthedocs.io) is an international initiative that aims to provide researchers in the brain imaging community with information about data sharing options and tools. We present here a short history of this project and its latest developments, and share pointers to consent forms, including a template consent form that is compliant with the EU general data protection regulation. We also share pointers to an associated data user agreement that is not only useful in the EU context, but also for any researchers dealing with personal (clinical) data elsewhere.

Identification of IDH and TERTp mutation status using 1 H-MRS in 112 hemispheric diffuse gliomas.

BACKGROUND: There is a growing interest in noninvasively defining molecular subsets of hemispheric diffuse gliomas based on the isocitrate dehydrogenase (IDH) and telomerase reverse transcriptase gene promoter (TERTp) mutation status, which correspond to distinct tumor entities, and differ in demographics, natural history, treatment response, recurrence, and survival patterns. PURPOSE: To investigate whether metabolite levels detected with short echo time (TE) proton MR spectroscopy (1 H-MRS) at 3T can be used for noninvasive molecular classification of IDH and TERTp mutation-based subsets of gliomas. STUDY TYPE: Retrospective. SUBJECTS: In all, 112 hemispheric diffuse gliomas (70 males/42 females, mean age: 42.1 ± 13.9 years). FIELD STRENGTH/SEQUENCE: Short-TE 1 H-MRS (repetition time (TR) = 2000 msec, TE = 30 msec, number of signal averages = 192) and routine clinical brain tumor MR protocols were acquired at 3T. ASSESSMENT: 1 H-MRS data were quantified using LCModel software. TERTp and IDH1 or IDH2 (IDH1/2) mutations in the tissue were determined by either minisequencing or Sanger sequencing. STATISTICAL TESTS: Metabolic differences between IDH mutant and IDH wildtype gliomas were assessed by a Mann-Whitney U-test. A Kruskal-Wallis test followed by a Tukey-Kramer test was used to analyze metabolic differences between IDH and TERTp mutational molecular subsets of gliomas. A Spearman rank correlation coefficient was used to assess the correlations of metabolite intensities with the Ki-67 index. Furthermore, machine learning was employed to classify the IDH and TERTp mutational status of gliomas, and the accuracy, sensitivity, and specificity values were estimated. RESULTS: Short-TE 1 H-MRS classified the presence of an IDH mutation with 88.39% accuracy, 76.92% sensitivity, and 94.52% specificity, and a TERTp mutation within primary IDH wildtype gliomas with 92.59% accuracy, 83.33% sensitivity, and 95.24% specificity. DATA CONCLUSION: Short-TE 1 H-MRS could be used to identify molecular subsets of hemispheric diffuse gliomas corresponding to IDH and TERTp mutations. LEVEL OF EVIDENCE: 3 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2020;51:1799-1809.

The cerebral blood flow deficits in Parkinson's disease with mild cognitive impairment using arterial spin labeling MRI.

Parkinson's disease (PD) with mild cognitive impairment (PD-MCI) is currently diagnosed based on an arbitrarily predefined standard deviation of neuropsychological test scores, and more objective biomarkers for PD-MCI diagnosis are needed. The purpose of this study was to define possible brain perfusion-based biomarkers of not only mild cognitive impairment, but also risky gene carriers in PD using arterial spin labeling magnetic resonance imaging (ASL-MRI). Fifteen healthy controls (HC), 26 cognitively normal PD (PD-CN), and 27 PD-MCI subjects participated in this study. ASL-MRI data were acquired by signal targeting with alternating radio-frequency labeling with Look-Locker sequence at 3 T. Single nucleotide polymorphism genotyping for rs9468 [microtubule-associated protein tau (MAPT) H1/H1 versus H1/H2 haplotype] was performed using a Stratagene Mx3005p real-time polymerase chain-reaction system (Agilent Technologies, USA). There were 15 subjects with MAPT H1/H1 and 11 subjects with MAPT H1/H2 within PD-MCI, and 33 subjects with MAPT H1/H1 and 19 subjects with MAPT H1/H2 within all PD. Voxel-wise differences of cerebral blood flow (CBF) values between HC, PD-CN and PD-MCI were assessed by one-way analysis of variance followed by pairwise post hoc comparisons. Further, the subgroup of PD patients carrying the risky MAPT H1/H1 haplotype was compared with noncarriers (MAPT H1/H2 haplotype) in terms of CBF by a two-sample t test. A pattern that could be summarized as "posterior hypoperfusion" (PH) differentiated the PD-MCI group from the HC group with an accuracy of 92.6% (sensitivity = 93%, specificity = 93%). Additionally, the PD patients with MAPT H1/H1 haplotype had decreased perfusion than the ones with H1/H2 haplotype at the posterior areas of the visual network (VN), default mode network (DMN), and dorsal attention network (DAN). The PH-type pattern in ASL-MRI could be employed as a biomarker of both current cognitive impairment and future cognitive decline in PD.

Genomewide Elucidation of Drug Resistance Mechanisms for Systemically Used Antifungal Drugs Amphotericin B, Caspofungin, and Voriconazole in the Budding Yeast.

There are only a few antifungal drugs used systemically in treatment, and invasive fungal infections that are resistant to these drugs are an emerging problem in health care. In this study, we performed a high-copy-number genomic DNA (gDNA) library screening to find and characterize genes that reduce susceptibility to amphotericin B, caspofungin, and voriconazole in Saccharomyces cerevisiae We identified the PDR16 and PMP3 genes for amphotericin B, the RMD9 and SWH1 genes for caspofungin, and the MRS3 and TRI1 genes for voriconazole. The deletion mutants for PDR16 and PMP3 were drug susceptible, but the other mutants had no apparent susceptibility. Quantitative-PCR analyses suggested that the corresponding drugs upregulated expression of the PDR16, PMP3, SWH1, and MRS3 genes. To further characterize these genes, we also profiled the global expression patterns of the cells after treatment with the antifungals and determined the genes and paths that were up- or downregulated. We also cloned Candida albicans homologs of the PDR16, PMP3, MRS3, and TRI1 genes and expressed them in S. cerevisiae Heterologous expression of Candida homologs also provided reduced drug susceptibility to the budding yeast cells. Our analyses suggest the involvement of new genes in antifungal drug resistance.

MutSß-MutLß-FANCJ axis mediates the restart of DNA replication after fork stalling at cotranscriptional G4/R-loops.

Transcription-replication conflicts (TRCs) induce formation of cotranscriptional RNA:DNA hybrids (R-loops) stabilized by G-quadruplexes (G4s) on the displaced DNA strand, which can cause fork stalling. Although it is known that these stalled forks can resume DNA synthesis in a process initiated by MUS81 endonuclease, how TRC-associated G4/R-loops are removed to allow fork passage remains unclear. Here, we identify the mismatch repair protein MutSß, an MLH1-PMS1 heterodimer termed MutLß, and the G4-resolving helicase FANCJ as factors that are required for MUS81-initiated restart of DNA replication at TRC sites in human cells. This DNA repair process depends on the G4-binding activity of MutSß, the helicase activity of FANCJ, and the binding of FANCJ to MLH1. Furthermore, we show that MutSß, MutLß, and MLH1-FANCJ interaction mediate FANCJ recruitment to G4s. These data suggest that MutSß, MutLß, and FANCJ act in conjunction to eliminate G4/R-loops at TRC sites, allowing replication restart.

SurvNet: A low-complexity convolutional neural network for survival time classification of patients with glioblastoma.

Background and objective: Malignant primary brain tumors cause the greatest number of years of life lost than any other cancer. Grade 4 glioma is particularly devastating: The median survival without any treatment is less than six months and with standard-of-care treatment is only 14.6 months. Accurate identification of the overall survival time of patients with brain tumors is of profound importance in many clinical applications. Automated image analytics with magnetic resonance imaging (MRI) can provide insights into the prognosis of patients with brain tumors. Methods: In this paper, We propose SurvNet, a low-complexity deep learning architecture based on the convolutional neural network to classify the overall survival time of patients with brain tumors into long-time and short-time survival cohorts. Through the incorporation of diverse MRI modalities as inputs, we facilitate deep feature extraction at various anatomical sites, thereby augmenting the precision of predictive modeling. We compare SurvNet with the Inception V3, VGG 16 and ensemble CNN models on pre-operative magnetic resonance image datasets. We also analyzed the effect of segmented brain tumors and training data on the system performance. Results: Several measures, such as accuracy, precision, and recall, are calculated to examine the perfor-mance of SurvNet on three-fold cross-validation. SurvNet with T1 MRI modality achieved a 62.7 % accuracy, compared with 52.9 % accuracy of the Inception V3 model, 58.5 % accuracy of the VGG 16 model, and 54.9 % of the ensemble CNN model. By increasing the MRI input modalities, SurvNet becomes more accurate and achieves 76.5 % accuracy with four MRI modalities. Combining the segmented data, SurvNet achieved the highest accuracy of 82.4 %. Conclusions: The research results show that SurvNet achieves higher metrics such as accuracy and f1-score than the comparisons. Our research also proves that by using multiparametric MRI modalities, SurvNet is able to learn more image features and performs a better classification accuracy. We can conclude that SurvNet with the complete scenario, i.e., segmented data and four MRI modalities, achieved the best accuracy, showing the validity of segmentation information during the survival time prediction process.

Susceptibility-Weighted MRI for Predicting NF-2 Mutations and S100 Protein Expression in Meningiomas.

S100 protein expression levels and neurofibromatosis type 2 (NF-2) mutations result in different disease courses in meningiomas. This study aimed to investigate non-invasive biomarkers of NF-2 copy number loss and S100 protein expression in meningiomas using morphological, radiomics, and deep learning-based features of susceptibility-weighted MRI (SWI). This retrospective study included 99 patients with S100 protein expression data and 92 patients with NF-2 copy number loss information. Preoperative cranial MRI was conducted using a 3T clinical MR scanner. Tumor volumes were segmented on fluid-attenuated inversion recovery (FLAIR) and subsequent registration of FLAIR to high-resolution SWI was performed. First-order textural features of SWI were extracted and assessed using Pyradiomics. Morphological features, including the tumor growth pattern, peritumoral edema, sinus invasion, hyperostosis, bone destruction, and intratumoral calcification, were semi-quantitatively assessed. Mann-Whitney U tests were utilized to assess the differences in the SWI features of meningiomas with and without S100 protein expression or NF-2 copy number loss. A logistic regression analysis was used to examine the relationship between these features and the respective subgroups. Additionally, a convolutional neural network (CNN) was used to extract hierarchical features of SWI, which were subsequently employed in a light gradient boosting machine classifier to predict the NF-2 copy number loss and S100 protein expression. NF-2 copy number loss was associated with a higher risk of developing high-grade tumors. Additionally, elevated signal intensity and a decrease in entropy within the tumoral region on SWI were observed in meningiomas with S100 protein expression. On the other hand, NF-2 copy number loss was associated with lower SWI signal intensity, a growth pattern described as "en plaque", and the presence of calcification within the tumor. The logistic regression model achieved an accuracy of 0.59 for predicting NF-2 copy number loss and an accuracy of 0.70 for identifying S100 protein expression. Deep learning features demonstrated a strong predictive capability for S100 protein expression (AUC = 0.85 ± 0.06) and had reasonable success in identifying NF-2 copy number loss (AUC = 0.74 ± 0.05). In conclusion, SWI showed promise in identifying NF-2 copy number loss and S100 protein expression by revealing neovascularization and microcalcification characteristics in meningiomas.

Identification of IDH and TERTp mutations using dynamic susceptibility contrast MRI with deep learning in 162 gliomas.

PURPOSE: Isocitrate dehydrogenase (IDH) and telomerase reverse transcriptase gene promoter (TERTp) mutations play crucial roles in glioma biology. Such genetic information is typically obtained invasively from excised tumor tissue; however, these mutations need to be identified preoperatively for better treatment planning. The relative cerebral blood volume (rCBV) information derived from dynamic susceptibility contrast MRI (DSC-MRI) has been demonstrated to correlate with tumor vascularity, functionality, and biology, and might provide some information about the genetic alterations in gliomas before surgery. Therefore, this study aims to predict IDH and TERTp mutational subgroups in gliomas using deep learning applied to rCBV images. METHOD: After the generation of rCBV images from DSC-MRI data, classical machine learning algorithms were applied to the features obtained from the segmented tumor volumes to classify IDH and TERTp mutation subgroups. Furthermore, pre-trained convolutional neural networks (CNNs) and CNNs enhanced with attention gates were trained using rCBV images or a combination of rCBV and anatomical images to classify the mutational subgroups. RESULTS: The best accuracies obtained with classical machine learning algorithms were 83 %, 68 %, and 76 % for the identification of IDH mutational, TERTp mutational, and TERTp-only subgroups, respectively. On the other hand, the best-performing CNN model achieved 88 % accuracy (86 % sensitivity, 91 % specificity) for the IDH-mutational subgroups, 70 % accuracy (73 % sensitivity and 67 % specificity) for the TERTp-mutational subgroups, and 84 % accuracy (86 % sensitivity, 81 % specificity) for the TERTp-only subgroup using attention gates. CONCLUSIONS: DSC-MRI can be utilized to noninvasively classify IDH- and TERTp-based molecular subgroups of gliomas, facilitating preoperative identification of these genetic alterations.

Developing blood-brain barrier arterial spin labelling as a non-invasive early biomarker of Alzheimer's disease (DEBBIE-AD): a prospective observational multicohort study protocol.

INTRODUCTION: Loss of blood-brain barrier (BBB) integrity is hypothesised to be one of the earliest microvascular signs of Alzheimer's disease (AD). Existing BBB integrity imaging methods involve contrast agents or ionising radiation, and pose limitations in terms of cost and logistics. Arterial spin labelling (ASL) perfusion MRI has been recently adapted to map the BBB permeability non-invasively. The DEveloping BBB-ASL as a non-Invasive Early biomarker (DEBBIE) consortium aims to develop this modified ASL-MRI technique for patient-specific and robust BBB permeability assessments. This article outlines the study design of the DEBBIE cohorts focused on investigating the potential of BBB-ASL as an early biomarker for AD (DEBBIE-AD). METHODS AND ANALYSIS: DEBBIE-AD consists of a multicohort study enrolling participants with subjective cognitive decline, mild cognitive impairment and AD, as well as age-matched healthy controls, from 13 cohorts. The precision and accuracy of BBB-ASL will be evaluated in healthy participants. The clinical value of BBB-ASL will be evaluated by comparing results with both established and novel AD biomarkers. The DEBBIE-AD study aims to provide evidence of the ability of BBB-ASL to measure BBB permeability and demonstrate its utility in AD and AD-related pathologies. ETHICS AND DISSEMINATION: Ethics approval was obtained for 10 cohorts, and is pending for 3 cohorts. The results of the main trial and each of the secondary endpoints will be submitted for publication in a peer-reviewed journal.

Optimized multi-voxel TE-averaged PRESS for glutamate detection in the human brain at 3T.

PURPOSE: To optimize possible combinations of echo times (TE) for multi-voxel TE-averaged Point RESolved Spectroscopy (PRESS) while reducing the total number of TEs required to separate glutamate (Glu) and glutamine (Gln) within a clinically feasible scan time. METHODS: General Approach to Magnetic resonance Mathematical Analysis (GAMMA) was used to implement 2D J-resolved PRESS technique, and the spectra of 14 individual brain metabolites were simulated at 64 different TEs. Monte Carlo simulations were used for selecting the best TE combinations to separate Glu and Gln using TE-averaged PRESS with a total number of two, three, four and five TEs. Single-voxel 1H-MRS data were acquired using 64 different TEs from a healthy volunteer on a clinical 3T MR scanner to validate the echo time combinations selected with simulations. Additionally, 2D 1H-MRSI data of eight healthy volunteers were acquired on a clinical 3T MR scanner using four different TEs that were determined by Monte Carlo simulations. Optimized TE-averaged PRESS spectra were created by averaging the spectra acquired at selected TEs. LCModel was used for spectral quantification. A Wilcoxon signed-rank test was used to detect statistically significant differences in Glu/Gln ratios between 35 ms PRESS and optimized TE-averaged PRESS data. RESULTS: Glu could be clearly separated from Gln at 2.35 ppm, using optimized TE-averaged PRESS with only four TEs (35, 37, 40, and 42 ms) that were selected through Monte Carlo simulations. Glu/Gln ratios were significantly higher in the optimized TE-averaged PRESS data of healthy volunteers than in the 35 ms PRESS data (P = 0.008). CONCLUSION: Optimized multi-voxel TE-averaged PRESS enabled faster and unobstructed quantification of Glu at multiple voxels in the human brain in vivo at 3T.