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ItemFat fraction quantification of bone marrow in the lumbar spine using the LiverLab assessment tool in healthy adult volunteers and patients with Gaucher diseaseGan, C ; Robertson, PL ; Lai, JKC ; Szer, J (WILEY, 2023-07)BACKGROUND: Magnetic Resonance Imaging is used for evaluation of bone in Gaucher disease (GD), but a widely available quantitative scoring method remains elusive. AIMS: The study purpose was to assess the reproducibility of the LiverLab tool for assessing bone marrow fat fraction (FF) and determine whether it could differentiate GD patients from healthy subjects. METHODS: Ten healthy volunteers and 18 GD patients were prospectively recruited. FF was calculated at L3, L4 and L5. GD patient bone marrow burden (BMB) score assessed by one observer. Inter and intra-rater agreement assessed with Bland-Altman data plots. Differences in FF between healthy volunteers versus GD patients and between subjects treated versus not treated assessed using two-sample t-tests. In GD patients, the relationship between FF, BMB and glucosylsphingosine was determined using the Pearson's correlation coefficient. RESULTS: Healthy volunteer mean FF was 0.36, standard deviation (SD) 0.10 (range 0.20-0.57). Intra and inter-rater SD were both 0.02. GD patient mean FF was 0.40, SD 0.13 (range 0.09-0.57). No statistical difference was shown between healthy volunteers and GD patients (P = 0.447) or between GD patients whether on enzyme replacement therapy or not (P = 0.090). No significant correlation between mean FF and total BMB (r = -0.525, P = 0.253) or between FF and glucosylsphingosine levels (r = 0.287, P = 0.248). CONCLUSION: Excellent reproducibility of LiverLab FF measurements across studies and observers is comparable to Dixon quantitative chemical shift imaging (QCSI). Lack of statistical difference between GD patients and controls may be explained by limited patient numbers, active treatment or mild disease severity in untreated patients.
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ItemSensorimotor network dynamics predict decline in upper and lower limb function in people with multiple sclerosisStrik, M ; Eijlers, AJC ; Dekker, I ; Broeders, TAA ; Douw, L ; Killestein, J ; Kolbe, SC ; Geurts, JJG ; Schoonheim, MM (SAGE PUBLICATIONS LTD, 2022-09-30)BACKGROUND: Upper and lower limb disabilities are hypothesized to have partially independent underlying (network) disturbances in multiple sclerosis (MS). OBJECTIVE: This study investigated functional network predictors and longitudinal network changes related to upper and lower limb progression in MS. METHODS: Two-hundred fourteen MS patients and 58 controls underwent functional magnetic resonance imaging (fMRI), dexterity (9-Hole Peg Test) and mobility (Timed 25-Foot Walk) measurements (baseline and 5 years). Patients were stratified into progressors (>20% decline) or non-progressors. Functional network efficiency was calculated using static (over entire scan) and dynamic (fluctuations during scan) approaches. Baseline measurements were used to predict progression; significant predictors were explored over time. RESULTS: In both limbs, progression was related to supplementary motor area and caudate efficiency (dynamic and static, respectively). Upper limb progression showed additional specific predictors; cortical grey matter volume, putamen static efficiency and posterior associative sensory (PAS) cortex, putamen, primary somatosensory cortex and thalamus dynamic efficiency. Additional lower limb predictors included motor network grey matter volume, caudate (dynamic) and PAS (static). Only the caudate showed a decline in efficiency over time in one group (non-progressors). CONCLUSION: Disability progression can be predicted using sensorimotor network measures. Upper and lower limb progression showed unique predictors, possibly indicating different network disturbances underlying these types of progression in MS.
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ItemInterpretable surface-based detection of focal cortical dysplasias: a Multi-centre Epilepsy Lesion Detection studySpitzer, H ; Ripart, M ; Whitaker, K ; D'Arco, F ; Mankad, K ; Chen, AA ; Napolitano, A ; De Palma, L ; De Benedictis, A ; Foldes, S ; Humphreys, Z ; Zhang, K ; Hu, W ; Mo, J ; Likeman, M ; Davies, S ; Guttler, C ; Lenge, M ; Cohen, NT ; Tang, Y ; Wang, S ; Chari, A ; Tisdall, M ; Bargallo, N ; Conde-Blanco, E ; Pariente, JC ; Pascual-Diaz, S ; Delgado-Martinez, I ; Perez-Enriquez, C ; Lagorio, I ; Abela, E ; Mullatti, N ; O'Muircheartaigh, J ; Vecchiato, K ; Liu, Y ; Caligiuri, ME ; Sinclair, B ; Vivash, L ; Willard, A ; Kandasamy, J ; McLellan, A ; Sokol, D ; Semmelroch, M ; Kloster, AG ; Opheim, G ; Ribeiro, L ; Yasuda, C ; Rossi-Espagnet, C ; Hamandi, K ; Tietze, A ; Barba, C ; Guerrini, R ; Gaillard, WD ; You, X ; Wang, I ; Gonzalez-Ortiz, S ; Severino, M ; Striano, P ; Tortora, D ; Kalviainen, R ; Gambardella, A ; Labate, A ; Desmond, P ; Lui, E ; O'Brien, T ; Shetty, J ; Jackson, G ; Duncan, JS ; Winston, GP ; Pinborg, LH ; Cendes, F ; Theis, FJ ; Shinohara, RT ; Cross, JH ; Baldeweg, T ; Adler, S ; Wagstyl, K (OXFORD UNIV PRESS, 2022-11-21)One outstanding challenge for machine learning in diagnostic biomedical imaging is algorithm interpretability. A key application is the identification of subtle epileptogenic focal cortical dysplasias (FCDs) from structural MRI. FCDs are difficult to visualize on structural MRI but are often amenable to surgical resection. We aimed to develop an open-source, interpretable, surface-based machine-learning algorithm to automatically identify FCDs on heterogeneous structural MRI data from epilepsy surgery centres worldwide. The Multi-centre Epilepsy Lesion Detection (MELD) Project collated and harmonized a retrospective MRI cohort of 1015 participants, 618 patients with focal FCD-related epilepsy and 397 controls, from 22 epilepsy centres worldwide. We created a neural network for FCD detection based on 33 surface-based features. The network was trained and cross-validated on 50% of the total cohort and tested on the remaining 50% as well as on 2 independent test sites. Multidimensional feature analysis and integrated gradient saliencies were used to interrogate network performance. Our pipeline outputs individual patient reports, which identify the location of predicted lesions, alongside their imaging features and relative saliency to the classifier. On a restricted 'gold-standard' subcohort of seizure-free patients with FCD type IIB who had T1 and fluid-attenuated inversion recovery MRI data, the MELD FCD surface-based algorithm had a sensitivity of 85%. Across the entire withheld test cohort the sensitivity was 59% and specificity was 54%. After including a border zone around lesions, to account for uncertainty around the borders of manually delineated lesion masks, the sensitivity was 67%. This multicentre, multinational study with open access protocols and code has developed a robust and interpretable machine-learning algorithm for automated detection of focal cortical dysplasias, giving physicians greater confidence in the identification of subtle MRI lesions in individuals with epilepsy.
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ItemA pilot study investigating the role of F-18-FDG-PET in the early identification of chemoradiotherapy response in anal cancerSmith, D ; Joon, DL ; Knight, K ; Sim, J ; Schneider, M ; Lau, E ; Foroudi, F ; Khoo, V (WILEY, 2022-07-30)INTRODUCTION: Anal cancer (AC) is 18 F-FDG-PET avid and has been used to evaluate treatment response several months after chemoradiotherapy. This pilot study aimed to assess the utility of semi-automated contouring methods and quantitative measures of treatment response using 18 F-FDG-PET imaging at the early time point of 1-month post-chemoradiotherapy. METHODS: Eleven patients with AC referred for chemoradiotherapy were prospectively enrolled into this study, with 10 meeting eligibility requirements. 18 F-FDG-PET imaging was obtained pre-chemoradiotherapy (TP1), and then 1-month (TP2), 3-6 months (TP3) and 9-12 months (TP4) post-chemoradiotherapy. Manual and semi-automated (Threshold) contouring methods were used to define the primary tumour on all 18 F-FDG-PET images. Resultant contours from each method were interrogated using quantitative measures, including volume, response index (RI), total lesion glycolysis (TLG), SUVmax , SUVmedian and SUVmean . Response was assessed quantitatively as reductions in these measures and also qualitatively against established criteria. RESULTS: Nine patients were qualitatively classified as complete metabolic responders at TP2 and all 10 at TP3. All quantitative measures demonstrated significant (P < 0.05) reductions at TP2 for both Manual and Threshold methods. All reduced further at TP3 and again at TP4 for Threshold methods. TLG showed the highest reduction at all post-chemoradiotherapy time points and classified the most responders for each method at each time point. All patients are recurrence-free at minimum 4-year follow-up. CONCLUSION: Based on our small sample size, semi-automated methods of disease definition using 18 F-FDG-PET imaging are feasible and appear to facilitate quantitative response classification of AC as early as 1-month post-chemoradiotherapy. Early identification of treatment response may potentially improve disease management.
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ItemIodinated contrast media shortage: Insights and guidance from two major public hospitals.Amukotuwa, SA ; Bammer, R ; Jackson, DM ; Sutherland, T (Wiley, 2022-10)Global shortage of iodinated contrast medium (ICM) is the latest health care ripple-effect from the COVID-19 pandemic. Some public hospitals in Australia have less than a week's supply. Strategies are, therefore, urgently needed to conserve ICM for those diagnostic tests and interventions, which are time-critical, and without which patients would suffer death or significant morbidity. A plan is also required to continue providing best possible care to patients in the worst-case scenario of exhausted ICM supplies. This document, by representatives from two major public hospitals, will provide some guidance that is tailored to the Australian context.
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ItemPathological predictors of F-18-DCFPyL prostate-specific membrane antigen-positive recurrence after radical prostatectomyPerry, E ; Talwar, A ; Taubman, K ; Ng, M ; Wong, L-M ; Sutherland, TR (WILEY, 2022-06)OBJECTIVES: To assess the correlation of pathological radical prostatectomy (RP) specimen features and prostate-specific antigen (PSA) characteristics to imaging findings on subsequent 18 F-DCFPyL positron emission tomography/computed tomography (PET/CT) in patients with biochemical failure (BF). PATIENTS AND METHODS: Retrospective analysis of combined 18 F-DCFPyL PET/CT database of patients from centres in Australia and New Zealand was performed. A total of 205 patients presenting with BF after RP were included in this study. Imaging findings on 18 F-DCFPyL PET/CT were recorded and correlated with the PSA characteristics at BF and pathological features of the original tumour. RESULTS: Of the 205 patients, 120 (58.5%) had evidence of abnormal prostate-specific membrane antigen (PSMA) expression compatible with recurrent prostate cancer. Increasing PSA velocity (P = 0.01), International Society of Urological Pathology (ISUP) Grade Group (P = 0.02), lymphovascular invasion (P = 0.05) and nodal positivity (P = 0.02) at the time of RP were more likely to demonstrate PSMA positivity. Multivariable logistic regression revealed a higher PSA level prior to PSMA PET/CT (P < 0.01), adjuvant radiotherapy (P = 0.09), Gleason score ≥8 (P < 0.01) and nodal positivity (P = 0.05) were all predictive of PSMA positivity. CONCLUSION: 18 F-DCFPyL PET/CT positivity, both generally and site specific, correlates with PSA and RP pathological factors. Our results echo cohorts focussing on post-RP patients, those imaged with 68 Ga-PSMA and those concerning biochemical persistence. Nomograms that include risk factors for 'PSMA-positive recurrence' in the BF population may increase the catchment of patients with disease confined to the prostate bed or pelvis who have a greater probability of prolonged disease-free survival.
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ItemEvent-based modeling in temporal lobe epilepsy demonstrates progressive atrophy from cross-sectional dataLopez, SM ; Aksman, LM ; Oxtoby, NP ; Vos, SB ; Rao, J ; Kaestner, E ; Alhusaini, S ; Alvim, M ; Bender, B ; Bernasconi, A ; Bernasconi, N ; Bernhardt, B ; Bonilha, L ; Caciagli, L ; Caldairou, B ; Caligiuri, ME ; Calvet, A ; Cendes, F ; Concha, L ; Conde-Blanco, E ; Davoodi-Bojd, E ; de Bezenac, C ; Delanty, N ; Desmond, PM ; Devinsky, O ; Domin, M ; Duncan, JS ; Focke, NK ; Foley, S ; Fortunato, F ; Galovic, M ; Gambardella, A ; Gleichgerrcht, E ; Guerrini, R ; Hamandi, K ; Ives-Deliperi, V ; Jackson, GD ; Jahanshad, N ; Keller, SS ; Kochunov, P ; Kotikalapudi, R ; Kreilkamp, BAK ; Labate, A ; Lariviere, S ; Lenge, M ; Lui, E ; Malpas, C ; Martin, P ; Mascalchi, M ; Medland, SE ; Meletti, S ; Morita-Sherman, ME ; Owen, TW ; Richardson, M ; Riva, A ; Ruber, T ; Sinclair, B ; Soltanian-Zadeh, H ; Stein, DJ ; Striano, P ; Taylor, PN ; Thomopoulos, SI ; Thompson, PM ; Tondelli, M ; Vaudano, AE ; Vivash, L ; Wang, Y ; Weber, B ; Whelan, CD ; Wiest, R ; Winston, GP ; Yasuda, CL ; McDonald, CR ; Alexander, DC ; Sisodiya, SM ; Altmann, A (WILEY, 2022-08)OBJECTIVE: Recent work has shown that people with common epilepsies have characteristic patterns of cortical thinning, and that these changes may be progressive over time. Leveraging a large multicenter cross-sectional cohort, we investigated whether regional morphometric changes occur in a sequential manner, and whether these changes in people with mesial temporal lobe epilepsy and hippocampal sclerosis (MTLE-HS) correlate with clinical features. METHODS: We extracted regional measures of cortical thickness, surface area, and subcortical brain volumes from T1-weighted (T1W) magnetic resonance imaging (MRI) scans collected by the ENIGMA-Epilepsy consortium, comprising 804 people with MTLE-HS and 1625 healthy controls from 25 centers. Features with a moderate case-control effect size (Cohen d ≥ .5) were used to train an event-based model (EBM), which estimates a sequence of disease-specific biomarker changes from cross-sectional data and assigns a biomarker-based fine-grained disease stage to individual patients. We tested for associations between EBM disease stage and duration of epilepsy, age at onset, and antiseizure medicine (ASM) resistance. RESULTS: In MTLE-HS, decrease in ipsilateral hippocampal volume along with increased asymmetry in hippocampal volume was followed by reduced thickness in neocortical regions, reduction in ipsilateral thalamus volume, and finally, increase in ipsilateral lateral ventricle volume. EBM stage was correlated with duration of illness (Spearman ρ = .293, p = 7.03 × 10-16 ), age at onset (ρ = -.18, p = 9.82 × 10-7 ), and ASM resistance (area under the curve = .59, p = .043, Mann-Whitney U test). However, associations were driven by cases assigned to EBM Stage 0, which represents MTLE-HS with mild or nondetectable abnormality on T1W MRI. SIGNIFICANCE: From cross-sectional MRI, we reconstructed a disease progression model that highlights a sequence of MRI changes that aligns with previous longitudinal studies. This model could be used to stage MTLE-HS subjects in other cohorts and help establish connections between imaging-based progression staging and clinical features.
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ItemIntellectual enrichment and genetic modifiers of cognition and brain volume in Huntington's disease.Papoutsi, M ; Flower, M ; Hensman Moss, DJ ; Holmans, P ; Estevez-Fraga, C ; Johnson, EB ; Scahill, RI ; Rees, G ; Langbehn, D ; Tabrizi, SJ ; Track-HD Investigators, (Oxford University Press (OUP), 2022)An important step towards the development of treatments for cognitive impairment in ageing and neurodegenerative diseases is to identify genetic and environmental modifiers of cognitive function and understand the mechanism by which they exert an effect. In Huntington's disease, the most common autosomal dominant dementia, a small number of studies have identified intellectual enrichment, i.e. a cognitively stimulating lifestyle and genetic polymorphisms as potential modifiers of cognitive function. The aim of our study was to further investigate the relationship and interaction between genetic factors and intellectual enrichment on cognitive function and brain atrophy in Huntington's disease. For this purpose, we analysed data from Track-HD, a multi-centre longitudinal study in Huntington's disease gene carriers and focused on the role of intellectual enrichment (estimated at baseline) and the genes FAN1, MSH3, BDNF, COMT and MAPT in predicting cognitive decline and brain atrophy. We found that carrying the 3a allele in the MSH3 gene had a positive effect on global cognitive function and brain atrophy in multiple cortical regions, such that 3a allele carriers had a slower rate of cognitive decline and atrophy compared with non-carriers, in agreement with its role in somatic instability. No other genetic predictor had a significant effect on cognitive function and the effect of MSH3 was independent of intellectual enrichment. Intellectual enrichment also had a positive effect on cognitive function; participants with higher intellectual enrichment, i.e. those who were better educated, had higher verbal intelligence and performed an occupation that was intellectually engaging, had better cognitive function overall, in agreement with previous studies in Huntington's disease and other dementias. We also found that intellectual enrichment interacted with the BDNF gene, such that the positive effect of intellectual enrichment was greater in Met66 allele carriers than non-carriers. A similar relationship was also identified for changes in whole brain and caudate volume; the positive effect of intellectual enrichment was greater for Met66 allele carriers, rather than for non-carriers. In summary, our study provides additional evidence for the beneficial role of intellectual enrichment and carrying the 3a allele in MSH3 in cognitive function in Huntington's disease and their effect on brain structure.
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ItemHPV status represents dominant trait driving delineation of survival-associated gene co-expression networks in head and neck cancerMehdi, AM ; Zhou, C ; Turrell, G ; Walpole, E ; Porceddu, S ; Frazer, IH ; Chandra, J (SPRINGERNATURE, 2022-12-27)Integration of high-dimensional tumor gene expression data with clinicopathological data can increase our understanding of disease diversity, enable retrospective patient stratification, and identify new potential biomarkers and therapeutic targets. Using a systems biology approach, we provide a holistic overview of gene co-expression networks in head and neck squamous cell carcinomas (HNSCC). Weighted gene co-expression network analysis of HNSCC RNA sequencing data from 519 patients from The Cancer Genome Atlas (TCGA) was used to determine correlates of 5-year survival, using regression tree-based optimal threshold calculations. Survival-associated gene sets were transformed to gene set scores that were assessed for correlation with clinicopathological data. We identified 8 gene co-expression modules for HNSCC tumors, each of which contained co-expressed genes associated significantly with 5-year survival. Survival-associated co-expression gene signatures correlated dominantly with tumor HPV and p16 status. Network analysis identified that survival was associated with signaling networks of infection, immunity, epithelial-mesenchymal transition (EMT), hypoxia, glycolysis, focal adhesion, extracellular matrix, MYC signaling, autophagy and transcriptional regulation. EMT-associated gene signatures were expressed dominantly in fibroblasts, and cancer-associated fibroblasts were inversely correlated with immune activity. Interestingly, a high Immune Suppression Score based on expression of 21 genes associated with immune inhibition and including immune checkpoints, cytokines and regulatory T cell factors, was also associated with increased survival probability, and was significantly higher in HPV+ HNSCC. Networks associated with HNSCC survival were further associated with survival in cervical cancer, melanoma and lung cancer. This study defines 5129 genes associated with HNSCC survival, organized into co-expressed networks, their correlation with clinicopathological data, and with gene expression data from other malignant diseases, and provides a source for the discovery of biomarkers and novel therapies for HNSCC.
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ItemNo Preview AvailableCortico-Striatal Activity Characterizes Human Safety Learning via Pavlovian Conditioned InhibitionLaing, PAF ; Steward, T ; Davey, CG ; Felmingham, KL ; Fullana, MA ; Vervliet, B ; Greaves, MD ; Moffat, B ; Glarin, RK ; Harrison, BJ (SOC NEUROSCIENCE, 2022-06-22)Safety learning generates associative links between neutral stimuli and the absence of threat, promoting the inhibition of fear and security-seeking behaviors. Precisely how safety learning is mediated at the level of underlying brain systems, particularly in humans, remains unclear. Here, we integrated a novel Pavlovian conditioned inhibition task with ultra-high field (7 Tesla) fMRI to examine the neural basis of safety learning in 49 healthy participants. In our task, participants were conditioned to two safety signals: a conditioned inhibitor that predicted threat omission when paired with a known threat signal (A+/AX-), and a standard safety signal that generally predicted threat omission (BC-). Both safety signals evoked equivalent autonomic and subjective learning responses but diverged strongly in terms of underlying brain activation (PFDR whole-brain corrected). The conditioned inhibitor was characterized by more prominent activation of the dorsal striatum, anterior insular, and dorsolateral PFC compared with the standard safety signal, whereas the latter evoked greater activation of the ventromedial PFC, posterior cingulate, and hippocampus, among other regions. Further analyses of the conditioned inhibitor indicated that its initial learning was characterized by consistent engagement of dorsal striatal, midbrain, thalamic, premotor, and prefrontal subregions. These findings suggest that safety learning via conditioned inhibition involves a distributed cortico-striatal circuitry, separable from broader cortical regions involved with processing standard safety signals (e.g., CS-). This cortico-striatal system could represent a novel neural substrate of safety learning, underlying the initial generation of "stimulus-safety" associations, distinct from wider cortical correlates of safety processing, which facilitate the behavioral outcomes of learning.SIGNIFICANCE STATEMENT Identifying safety is critical for maintaining adaptive levels of anxiety, but the neural mechanisms of human safety learning remain unclear. Using 7 Tesla fMRI, we compared learning-related brain activity for a conditioned inhibitor, which actively predicted threat omission, and a standard safety signal (CS-), which was passively unpaired with threat. The inhibitor engaged an extended circuitry primarily featuring the dorsal striatum, along with thalamic, midbrain, and premotor/PFC regions. The CS- exclusively involved cortical safety-related regions observed in basic safety conditioning, such as the vmPFC. These findings extend current models to include learning-specific mechanisms for encoding stimulus-safety associations, which might be distinguished from expression-related cortical mechanisms. These insights may suggest novel avenues for targeting dysfunctional safety learning in psychopathology.