IMPA-Net: Interpretable Multi-Part Attention Network for Trustworthy Brain Tumor Classification from MRI.

Deep learning (DL) networks have shown attractive performance in medical image processing tasks such as brain tumor classification. However, they are often criticized as mysterious "black boxes". The opaqueness of the model and the reasoning process make it difficult for health workers to decide whether to trust the prediction outcomes. In this study, we develop an interpretable multi-part attention network (IMPA-Net) for brain tumor classification to enhance the interpretability and trustworthiness of classification outcomes. The proposed model not only predicts the tumor grade but also provides a global explanation for the model interpretability and a local explanation as justification for the proffered prediction. Global explanation is represented as a group of feature patterns that the model learns to distinguish high-grade glioma (HGG) and low-grade glioma (LGG) classes. Local explanation interprets the reasoning process of an individual prediction by calculating the similarity between the prototypical parts of the image and a group of pre-learned task-related features. Experiments conducted on the BraTS2017 dataset demonstrate that IMPA-Net is a verifiable model for the classification task. A percentage of 86% of feature patterns were assessed by two radiologists to be valid for representing task-relevant medical features. The model shows a classification accuracy of 92.12%, of which 81.17% were evaluated as trustworthy based on local explanations. Our interpretable model is a trustworthy model that can be used for decision aids for glioma classification. Compared with black-box CNNs, it allows health workers and patients to understand the reasoning process and trust the prediction outcomes.

Generalizing the Enhanced-Deep-Super-Resolution neural network to brain MR images: a retrospective study on the Cam-CAN dataset.

The Enhanced-Deep-Super-Resolution (EDSR) model is a state-of-art convolutional neural network suitable for improving image spatial resolution. It was previously trained with general-purpose pictures and then, in this work, tested on biomedical Magnetic Resonance (MR) images, comparing the network outcomes with traditional up-sampling techniques. We explored possible changes in the model response when different MR sequences were analyzed. T1w and T2w MR brain images of 70 human healthy subjects (F:M 40:30) from the Cambridge Centre for Ageing and Neuroscience (Cam-CAN) repository were down-sampled and then up-sampled using EDSR model and BiCubic (BC) interpolation. Several reference metrics were used to quantitatively assess the performance of up-sampling operations (RMSE, pSNR, SSIM and HFEN). Two-dimensional and three-dimensional reconstructions were evaluated. Different brain tissues were analyzed individually. The EDSR model was superior to BC interpolation on the selected metrics, both for two- and three- dimensional reconstructions. The reference metrics showed higher quality of EDSR over BC reconstructions for all the analyzed images, with a significant difference of all the criteria in T1w images and of the perception-based SSIM and HFEN in T2w images. The analysis per tissue highlights differences in EDSR performance related to the gray-level values, showing a relative lack of out-performance in reconstructing hyper-intense areas. The EDSR model, trained on general-purpose images, better reconstructs MR T1w and T2w images than BC, without any re-training or fine-tuning. These results highlight the excellent generalization ability of the network and lead to possible applications on other MR measurements.Significance Statement Super resolution applications in biomedical images may help in reducing acquisition scan time and concurrently improving the quality of the exam. Neural networks have been shown to work better than traditional up-sampling techniques, even though ad hoc training experiments need to be performed for specific kind of data. In this work, we used a model previously trained with general-purpose images and we directly applied to magnetic resonance human brain ones; we verified its ability of reconstructing new kind of images, comparing the results with traditional up-sampling techniques. Our analysis highlights the excellent generalization capabilities of the model over the images tested, without need of specific re-training, suggesting that such results might be reproduced on images from other acquisition systems.

Magnetic resonance imaging scoring system of the lower limbs in adult patients with suspected idiopathic inflammatory myopathy.

PURPOSE: We aim to propose a visual quantitative score for muscle edema in lower limb MRI to contribute to the diagnosis of idiopathic inflammatory myopathy (IIM). MATERIAL AND METHODS: We retrospectively evaluated 85 consecutive patients (mean age 57.4 ± 13.9 years; 56.5% female) with suspected IIM (muscle weakness and/or persistent hyper-CPK-emia with/without myalgia) who underwent MRI of lower limbs using T2-weighted fast recovery-fast spin echo images and fat-sat T2 echo planar images. Muscle inflammation was evaluated bilaterally in 11 muscles of the thigh and eight muscles of the leg. Edema in each muscle was graded according to a four-point Likert-type scale adding up to 114 points ([11 + 8)] × 3 × 2). Diagnostic accuracy of the total edema score was explored by assessing sensitivity and specificity using the area under the ROC curve. Final diagnoses were made by a multidisciplinary Expert Consensus Panel applying the Bohan and Peter diagnostic criteria whenever possible. RESULTS: Of the 85 included patients, 34 (40%) received a final diagnosis of IIM (IIM group) while 51 (60%) received an alternative diagnosis (non-IIM group). A cutoff score ≥ 18 was able to correctly classify patients having an IIM with an area under the curve of 0.85, specificity of 96%, and sensitivity of 52.9%. CONCLUSION: Our study demonstrates that a quantitative MRI score for muscle edema in the lower limbs (thighs and legs) aids in distinguishing IIM from conditions that mimic it.

Active mobility and mental health: A scoping review towards a healthier world.

Research has proven that engaging in active mobility (AM), namely walking and cycling for transportation, significantly enhances physical activity levels, leading to better physical health. It is still unclear whether AM could also offer any mental health benefits. This scoping review aims to provide a comprehensive understanding of the current knowledge on the relationship between AM and mental health, given its crucial role in public health. The authors searched online databases to isolate primary studies written in English involving an adult sample (16 or over). AM was the exposure factor. Many mental health elements were included as outcomes (depression, anxiety, self-esteem, self-efficacy, stress, psychological and subjective well-being, resilience, loneliness and social support, quality of life, mood, life satisfaction and sleep). The results were organised in a narrative summary per each outcome selected, graphical syntheses and an overview of gaps to be further examined. The authors identified a total of 55 papers as relevant. The results show inconsistency in study designs, definition and operationalisation of the variables, approach and methodologies used. A cross-sectional design was the dominant choice, primarily examining data from national public health surveys. Nonetheless, there has been improvement in outcomes of interests, initially mainly the quality of life and affect. Lately, authors have focused on a broader range of mental health-related factors (such as travel satisfaction). The experimental studies showed promising mental health improvements in those who used active modes more than those who used motorised vehicles. It creates a rationale for further research towards implementing a unified theoretical and methodological framework to study the link between AM and mental health. The ultimate goal is to generate solid conclusions that could support building societies and cities through public health promotion and sustainable strategies, like walking and cycling as a means of transport.

Association between Physical Activity and Reduced Mortality in Inoperable Lung Cancer.

We examined device-measured physical activity (PA) and sedentary behaviour at the time of diagnosis in people with inoperable lung cancer and investigated their associations with 12-month mortality. The people with inoperable lung cancer wore an accelerometer for seven days prior to the treatment commencement. The analysed PA/sedentary behaviour variables included light-intensity PA, moderate-to-vigorous-intensity PA (MVPA), step count, the total time spent sedentary, and the usual sedentary bout duration. The data on the disease stage, clinical covariates and 12-month mortality were extracted from medical records. Cox regression models were used to estimate the association between the PA measures and 12-month mortality, and the sedentary behaviour measures and 12-month mortality. The models were adjusted for the stage and neutrophil-to-lymphocyte ratio. All the PA and sedentary behaviour variables were dichotomised at their medians for analysis. Eighty-nine participants (70 ± 10 years; 55 [62%] males) contributed valid data. The twelve-month mortality was 30% (n = 27). Compared to the participants who spent ≤4.6 min/day in MVPA (n = 45), those who spent >4.6 min/day (n = 44) had a relative risk of 12-month mortality reduced by 60% (hazard ratio, 0.40; 95% CI, 0.16 to 0.96; 18 versus nine deaths, respectively). The other variables of PA/sedentary behaviour were not associated with 12-month mortality. Higher device-measured MVPA was associated with reduced 12-month mortality in people who were newly diagnosed with inoperable lung cancer.

Assessing robustness of quantitative susceptibility-based MRI radiomic features in patients with multiple sclerosis.

Multiple Sclerosis (MS) is an autoimmune demyelinating disease characterised by changes in iron and myelin content. These biomarkers are detectable by Quantitative Susceptibility Mapping (QSM), an advanced Magnetic Resonance Imaging technique detecting magnetic properties. When analysed with radiomic techniques that exploit its intrinsic quantitative nature, QSM may furnish biomarkers to facilitate early diagnosis of MS and timely assessment of progression. In this work, we explore the robustness of QSM radiomic features by varying the number of grey levels (GLs) and echo times (TEs), in a sample of healthy controls and patients with MS. We analysed the white matter in total and within six clinically relevant tracts, including the cortico-spinal tract and the optic radiation. After optimising the number of GLs (n = 64), at least 65% of features were robust for each Volume of Interest (VOI), with no difference (p > .05) between left and right hemispheres. Different outcomes in feature robustness among the VOIs depend on their characteristics, such as volume and variance of susceptibility values. This study validated the processing pipeline for robustness analysis and established the reliability of QSM-based radiomics features against GLs and TEs. Our results provide important insights for future radiomics studies using QSM in clinical applications.

Methods of diffusion MRI tractography for localization of the anterior optic pathway: A systematic review of validated methods.

The anterior optic pathway (AOP) is a system of three structures (optic nerves, optic chiasma, and optic tracts) that convey visual stimuli from the retina to the lateral geniculate nuclei. A successful reconstruction of the AOP using tractography could be helpful in several clinical scenarios, from presurgical planning and neuronavigation of sellar and parasellar surgery to monitoring the stage of fiber degeneration both in acute (e.g., traumatic optic neuropathy) or chronic conditions that affect AOP structures (e.g., amblyopia, glaucoma, demyelinating disorders or genetic optic nerve atrophies). However, its peculiar anatomy and course, as well as its surroundings, pose a serious challenge to obtaining successful tractographic reconstructions. Several AOP tractography strategies have been adopted but no standard procedure has been agreed upon. We performed a systematic review of the literature according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) 2020 guidelines in order to find the combinations of acquisition and reconstruction parameters that have been performed previously and have provided the highest rate of successful reconstruction of the AOP, in order to promote their routine implementation in clinical practice. For this purpose, we reviewed data regarding how the process of anatomical validation of the tractographies was performed. The Cochrane Handbook for Systematic Reviews of Interventions was used to assess the risk of bias and thus the study quality We identified thirty-nine studies that met our inclusion criteria, and only five were considered at low risk of bias and achieved over 80% of successful reconstructions. We found a high degree of heterogeneity in the acquisition and analysis parameters used to perform AOP tractography and different combinations of them can achieve satisfactory levels of anterior optic tractographic reconstruction both in real-life research and clinical scenarios. One thousand s/mm2 was the most frequently used b value, while both deterministic and probabilistic tractography algorithms performed morphological reconstruction of the tract satisfactorily, although probabilistic algorithms estimated a more realistic percentage of crossing fibers (45.6%) in healthy subjects. A wide heterogeneity was also found regarding the method used to assess the anatomical fidelity of the AOP reconstructions. Three main strategies can be found: direct visual direct visual assessment of the tractography superimposed to a conventional MR image, surgical evaluation, and computational methods. Because the latter is less dependent on a priori knowledge of the anatomy by the operator, computational methods of validation of the anatomy should be considered whenever possible.

Proposed quality indicators and recommended standard reporting items in performance of EBUS bronchoscopy: An official World Association for Bronchology and Interventional Pulmonology Expert Panel consensus statement.

BACKGROUND: Since their introduction, both linear and radial endobronchial ultrasound (EBUS) have become an integral component of the practice of Pulmonology and Thoracic Oncology. The quality of health care can be measured by comparing the performance of an individual or a health service with an ideal threshold or benchmark. The taskforce sought to evaluate quality indicators in EBUS bronchoscopy based on clinical relevance/importance and on the basis that observed significant variation in outcomes indicates potential for improvement in health care outcomes. METHODS: A comprehensive literature review informed the composition of a comprehensive list of candidate quality indicators in EBUS. A multiple-round modified Delphi consensus process was subsequently performed with the aim of reaching consensus over a final list of quality indicators and performance targets for these indicators. Standard reporting items were developed, with a strong preference for items where evidence demonstrates a relationship with quality indicator outcomes. RESULTS: Twelve quality Indicators are proposed, with performance targets supported by evidence from the literature. Standardized reporting items for both radial and linear EBUS are recommended, with evidence supporting their utility in assessing procedural outcomes presented. CONCLUSION: This statement is intended to provide a framework for individual proceduralists to assess the quality of EBUS they provide their patients through the identification of clinically relevant, feasible quality measures. Emphasis is placed on outcome measures, with a preference for consistent terminology to allow communication and benchmarking between centres.

Sedentary Behaviour, Physical Activity, and Their Associations with Health Outcomes at the Time of Diagnosis in People with Inoperable Lung Cancer.

This study aimed to examine sedentary behaviour (SB), physical activity (PA) and their associations with health-related measures at the time of diagnosis in people with inoperable lung cancer. People newly diagnosed with inoperable lung cancer were invited to participate in the study and asked to wear an accelerometer for seven consecutive days. Variables analysed included time spent in SB, light intensity PA (LIPA) and moderate-to-vigorous intensity PA (MVPA). Daily steps were also recorded. Data on symptoms, health-related quality of life (HRQoL), hand grip force, comorbidities and lung function were collected. Of the 120 patients referred to the study, 89 (74%) consented to participate, and SB/PA data were available for 79 (age 71 ± 11 years; 29 females). Participants spent 71% of their waking time in SB, 28% in LIPA and 1% in MVPA. Regression models demonstrated that increased SB was associated with more symptoms of fatigue and dyspnoea (p ≤ 0.02 for both), poorer HRQoL (general health and physical component score; p ≤ 0.02 for all) and lower hand grip force. For PA variables, higher daily step count was associated with better scores in all health-related measures (p < 0.05 for all). LIPA was associated with more health-related outcomes than MVPA. These findings may guide future interventions in this population.

Convolutional Neural Network Techniques for Brain Tumor Classification (from 2015 to 2022): Review, Challenges, and Future Perspectives.

Convolutional neural networks (CNNs) constitute a widely used deep learning approach that has frequently been applied to the problem of brain tumor diagnosis. Such techniques still face some critical challenges in moving towards clinic application. The main objective of this work is to present a comprehensive review of studies using CNN architectures to classify brain tumors using MR images with the aim of identifying useful strategies for and possible impediments in the development of this technology. Relevant articles were identified using a predefined, systematic procedure. For each article, data were extracted regarding training data, target problems, the network architecture, validation methods, and the reported quantitative performance criteria. The clinical relevance of the studies was then evaluated to identify limitations by considering the merits of convolutional neural networks and the remaining challenges that need to be solved to promote the clinical application and development of CNN algorithms. Finally, possible directions for future research are discussed for researchers in the biomedical and machine learning communities. A total of 83 studies were identified and reviewed. They differed in terms of the precise classification problem targeted and the strategies used to construct and train the chosen CNN. Consequently, the reported performance varied widely, with accuracies of 91.63-100% in differentiating meningiomas, gliomas, and pituitary tumors (26 articles) and of 60.0-99.46% in distinguishing low-grade from high-grade gliomas (13 articles). The review provides a survey of the state of the art in CNN-based deep learning methods for brain tumor classification. Many networks demonstrated good performance, and it is not evident that any specific methodological choice greatly outperforms the alternatives, especially given the inconsistencies in the reporting of validation methods, performance metrics, and training data encountered. Few studies have focused on clinical usability.

Impact of low-dose computed tomography (LDCT) screening on lung cancer-related mortality.

BACKGROUND: Lung cancer is the most common cause of cancer-related death in the world, however lung cancer screening has not been implemented in most countries at a population level. A previous Cochrane Review found limited evidence for the effectiveness of lung cancer screening with chest radiography (CXR) or sputum cytology in reducing lung cancer-related mortality, however there has been increasing evidence supporting screening with low-dose computed tomography (LDCT).  OBJECTIVES: To determine whether screening for lung cancer using LDCT of the chest reduces lung cancer-related mortality and to evaluate the possible harms of LDCT screening. SEARCH METHODS: We performed the search in collaboration with the Information Specialist of the Cochrane Lung Cancer Group and included the Cochrane Lung Cancer Group Trial Register, Cochrane Central Register of Controlled Trials (CENTRAL, the Cochrane Library, current issue), MEDLINE (accessed via PubMed) and Embase in our search. We also searched the clinical trial registries to identify unpublished and ongoing trials. We did not impose any restriction on language of publication. The search was performed up to 31 July 2021.  SELECTION CRITERIA: Randomised controlled trials (RCTs) of lung cancer screening using LDCT and reporting mortality or harm outcomes.  DATA COLLECTION AND ANALYSIS: Two review authors were involved in independently assessing trials for eligibility, extraction of trial data and characteristics, and assessing risk of bias of the included trials using the Cochrane RoB 1 tool. We assessed the certainty of evidence using GRADE. Primary outcomes were lung cancer-related mortality and harms of screening. We performed a meta-analysis, where appropriate, for all outcomes using a random-effects model. We only included trials in the analysis of mortality outcomes if they had at least 5 years of follow-up. We reported risk ratios (RRs) and hazard ratios (HRs), with 95% confidence intervals (CIs) and used the I2 statistic to investigate heterogeneity.  MAIN RESULTS: We included 11 trials in this review with a total of 94,445 participants. Trials were conducted in Europe and the USA in people aged 40 years or older, with most trials having an entry requirement of ≥ 20 pack-year smoking history (e.g. 1 pack of cigarettes/day for 20 years or 2 packs/day for 10 years etc.). One trial included male participants only. Eight trials were phase three RCTs, with two feasibility RCTs and one pilot RCT. Seven of the included trials had no screening as a comparison, and four trials had CXR screening as a comparator. Screening frequency included annual, biennial and incrementing intervals. The duration of screening ranged from 1 year to 10 years. Mortality follow-up was from 5 years to approximately 12 years.  None of the included trials were at low risk of bias across all domains. The certainty of evidence was moderate to low across different outcomes, as assessed by GRADE. In the meta-analysis of trials assessing lung cancer-related mortality, we included eight trials (91,122 participants), and there was a reduction in mortality of 21% with LDCT screening compared to control groups of no screening or CXR screening (RR 0.79, 95% CI 0.72 to 0.87; 8 trials, 91,122 participants; moderate-certainty evidence). There were probably no differences in subgroups for analyses by control type, sex, geographical region, and nodule management algorithm. Females appeared to have a larger lung cancer-related mortality benefit compared to males with LDCT screening. There was also a reduction in all-cause mortality (including lung cancer-related) of 5% (RR 0.95, 95% CI 0.91 to 0.99; 8 trials, 91,107 participants; moderate-certainty evidence).  Invasive tests occurred more frequently in the LDCT group (RR 2.60, 95% CI 2.41 to 2.80; 3 trials, 60,003 participants; moderate-certainty evidence). However, analysis of 60-day postoperative mortality was not significant between groups (RR 0.68, 95% CI 0.24 to 1.94; 2 trials, 409 participants; moderate-certainty evidence).  False-positive results and recall rates were higher with LDCT screening compared to screening with CXR, however there was low-certainty evidence in the meta-analyses due to heterogeneity and risk of bias concerns. Estimated overdiagnosis with LDCT screening was 18%, however the 95% CI was 0 to 36% (risk difference (RD) 0.18, 95% CI -0.00 to 0.36; 5 trials, 28,656 participants; low-certainty evidence). Four trials compared different aspects of health-related quality of life (HRQoL) using various measures. Anxiety was pooled from three trials, with participants in LDCT screening reporting lower anxiety scores than in the control group (standardised mean difference (SMD) -0.43, 95% CI -0.59 to -0.27; 3 trials, 8153 participants; low-certainty evidence). There were insufficient data to comment on the impact of LDCT screening on smoking behaviour.  AUTHORS' CONCLUSIONS: The current evidence supports a reduction in lung cancer-related mortality with the use of LDCT for lung cancer screening in high-risk populations (those over the age of 40 with a significant smoking exposure). However, there are limited data on harms and further trials are required to determine participant selection and optimal frequency and duration of screening, with potential for significant overdiagnosis of lung cancer. Trials are ongoing for lung cancer screening in non-smokers.

Multishell Diffusion MR Tractography Yields Morphological and Microstructural Information of the Anterior Optic Pathway: A Proof-of-Concept Study in Patients with Leber's Hereditary Optic Neuropathy.

Tractography based on multishell diffusion-weighted magnetic resonance imaging (DWI) can be used to estimate the course of myelinated white matter tracts and nerves, yielding valuable information regarding normal anatomy and variability. DWI is sensitive to the local tissue microstructure, so tractography can be used to estimate tissue properties within nerve tracts at a resolution of millimeters. This study aimed to test the applicability of the method using a disease with a well-established pattern of myelinated nerve involvement. Eight patients with LHON and 13 age-matched healthy controls underwent tractography of the anterior optic pathway. Diffusion parameters were compared between groups, and for the patient group correlated with clinical/ophthalmological parameters. Tractography established the course of the anterior optic pathway in both patients and controls. Localized changes in fractional anisotropy were observed, and related to estimates of different tissue compartments within the nerve and tract. The proportion of different compartments correlated with markers of disease severity. The method described allows both anatomical localization and tissue characterization in vivo, permitting both visualization of variation at the individual level and statistical inference at the group level. It provides a valuable adjunct to ex vivo anatomical and histological study of normal variation and disease processes.

Steroid Therapy and Outcome of Parapneumonic Pleural Effusions (STOPPE): A Pilot Randomized Clinical Trial.

Rationale: Pleural effusion commonly complicates community-acquired pneumonia and is associated with intense pleural inflammation. Whether antiinflammatory treatment with corticosteroids improves outcomes is unknown. Objectives: To assess the effects of corticosteroids in an adult population with pneumonia-related pleural effusion. Methods: The STOPPE (Steroid Therapy and Outcome of Parapneumonic Pleural Effusions) trial was a pilot, multicenter, double-blinded, placebo-controlled, randomized trial involving six Australian centers. Patients with community-acquired pneumonia and pleural effusion were randomized (2:1) to intravenous dexamethasone (4 mg twice daily for 48 h) or placebo and followed for 30 days. Given the diverse effects of corticosteroids, a comprehensive range of clinical, serological, and imaging outcomes were assessed in this pilot trial (ACTRN12618000947202). Measurements and Main Results: Eighty patients were randomized (one withdrawn before treatment) and received dexamethasone (n = 51) or placebo (n = 28). This pilot trial found no preliminary evidence of benefits of dexamethasone in improving time to sustained (>12 h) normalization of vital signs (temperature, oxygen saturations, blood pressure, heart, and respiratory rates): median, 41.0 (95% confidence interval, 32.3-54.5) versus 27.8 (15.4-49.5) hours in the placebo arm (hazard ratio, 0.729 [95% confidence interval, 0.453-1.173]; P = 0.193). Similarly, no differences in C-reactive protein or leukocyte counts were observed, except for a higher leukocyte count in the dexamethasone group at Day 3. Pleural drainage procedures were performed in 49.0% of dexamethasone-treated and 42.9% of placebo-treated patients (P = 0.60). Radiographic pleural opacification decreased over time with no consistent intergroup differences. Mean duration of antibiotic therapy (22.4 [SD, 15.4] vs. 20.4 [SD, 13.8] d) and median hospitalization (6.0 [interquartile range, 5.0-10.0] vs. 5.5 [interquartile range, 5.0-8.0] d) were similar between the dexamethasone and placebo groups. Serious adverse events occurred in 25.5% of dexamethasone-treated and 21.4% of placebo-treated patients. Transient hyperglycemia more commonly affected the dexamethasone group (15.6% vs. 7.1%). Conclusions: Systemic corticosteroids showed no preliminary benefits in adults with parapneumonic effusions. Clinical trial registered with www.anzctr.org.au (ACTRN12618000947202).

Molecular biomarkers correlate with brain grey and white matter changes in patients with mitochondrial m.3243A > G mutation.

INTRODUCTION: The mitochondrial DNA (mtDNA) m.3243A > G mutation in the MT-TL1 gene results in a multi-systemic disease, that is commonly associated with neurodegenerative changes in the brain. METHODS: Seventeen patients harboring the m3243A > G mutation were enrolled (age 43.1 ± 11.4 years, 10 M/7F). A panel of plasma biomarkers including lactate acid, alanine, L-arginine, fibroblast growth factor 21 (FGF-21), growth/differentiation factor 15 (GDF-15) and circulating cell free -mtDNA (ccf-mtDNA), as well as blood, urine and muscle mtDNA heteroplasmy were evaluated. Patients also underwent a brain standardized MR protocol that included volumetric T1-weighted images and diffusion-weighted MRI. Twenty sex- and age-matched healthy controls were included. Voxel-wise analysis was performed on T1-weighted and diffusion imaging, respectively with VBM (voxel-based morphometry) and TBSS (Tract-based Spatial Statistics). Ventricular lactate was also evaluated by 1H-MR spectroscopy. RESULTS: A widespread cortical gray matter (GM) loss was observed, more severe (p < 0.001) in the bilateral calcarine, insular, frontal and parietal cortex, along with infratentorial cerebellar cortex. High urine mtDNA mutation load, high levels of plasma lactate and alanine, low levels of plasma arginine, high levels of serum FGF-21 and ventricular lactate accumulation significantly (p < 0.05) correlated with the reduced brain GM density. Widespread microstructural alterations were highlighted in the white matter, significantly (p < 0.05) correlated with plasma alanine and arginine levels, with mtDNA mutation load in urine, with high level of serum GDF-15 and with high content of plasma ccf-mtDNA. CONCLUSIONS: Our results suggest that the synergy of two pathogenic mechanisms, mtDNA-related mitochondrial respiratory deficiency and defective nitric oxide metabolism, contributes to the brain neurodegeneration in m.3243A > G patients.

Brain Structure and Degeneration Staging in Friedreich Ataxia: Magnetic Resonance Imaging Volumetrics from the ENIGMA-Ataxia Working Group.

OBJECTIVE: Friedreich ataxia (FRDA) is an inherited neurological disease defined by progressive movement incoordination. We undertook a comprehensive characterization of the spatial profile and progressive evolution of structural brain abnormalities in people with FRDA. METHODS: A coordinated international analysis of regional brain volume using magnetic resonance imaging data charted the whole-brain profile, interindividual variability, and temporal staging of structural brain differences in 248 individuals with FRDA and 262 healthy controls. RESULTS: The brainstem, dentate nucleus region, and superior and inferior cerebellar peduncles showed the greatest reductions in volume relative to controls (Cohen d = 1.5-2.6). Cerebellar gray matter alterations were most pronounced in lobules I-VI (d = 0.8), whereas cerebral differences occurred most prominently in precentral gyri (d = 0.6) and corticospinal tracts (d = 1.4). Earlier onset age predicted less volume in the motor cerebellum (rmax  = 0.35) and peduncles (rmax  = 0.36). Disease duration and severity correlated with volume deficits in the dentate nucleus region, brainstem, and superior/inferior cerebellar peduncles (rmax  = -0.49); subgrouping showed these to be robust and early features of FRDA, and strong candidates for further biomarker validation. Cerebral white matter abnormalities, particularly in corticospinal pathways, emerge as intermediate disease features. Cerebellar and cerebral gray matter loss, principally targeting motor and sensory systems, preferentially manifests later in the disease course. INTERPRETATION: FRDA is defined by an evolving spatial profile of neuroanatomical changes beyond primary pathology in the cerebellum and spinal cord, in line with its progressive clinical course. The design, interpretation, and generalization of research studies and clinical trials must consider neuroanatomical staging and associated interindividual variability in brain measures. ANN NEUROL 2021;90:570-583.

A deep learning approach for magnetic resonance fingerprinting: Scaling capabilities and good training practices investigated by simulations.

MR fingerprinting (MRF) is an innovative approach to quantitative MRI. A typical disadvantage of dictionary-based MRF is the explosive growth of the dictionary as a function of the number of reconstructed parameters, an instance of the curse of dimensionality, which determines an explosion of resource requirements. In this work, we describe a deep learning approach for MRF parameter map reconstruction using a fully connected architecture. Employing simulations, we have investigated how the performance of the Neural Networks (NN) approach scales with the number of parameters to be retrieved, compared to the standard dictionary approach. We have also studied optimal training procedures by comparing different strategies for noise addition and parameter space sampling, to achieve better accuracy and robustness to noise. Four MRF sequences were considered: IR-FISP, bSSFP, IR-FISP-B1, and IR-bSSFP-B1. A comparison between NN and the dictionary approaches in reconstructing parameter maps as a function of the number of parameters to be retrieved was performed using a numerical brain phantom. Results demonstrated that training with random sampling and different levels of noise variance yielded the best performance. NN performance was at least as good as the dictionary-based approach in reconstructing parameter maps using Gaussian noise as a source of artifacts: the difference in performance increased with the number of estimated parameters because the dictionary method suffers from the coarse resolution of the parameter space sampling. The NN proved to be more efficient in memory usage and computational burden, and has great potential for solving large-scale MRF problems.

Feasibility, tolerance and effects of adding impact loading exercise to pulmonary rehabilitation in people with chronic obstructive pulmonary disease: study protocol for a pilot randomised controlled trial.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a disorder linked with a multitude of extra pulmonary manifestations (also known as treatable traits), including low bone mineral density (BMD). To date, no specific guidelines exist for the management of BMD in this population. Impact loading exercise has been identified as an intervention that improves or maintains BMD in other populations. However, the feasibility of and tolerance to impact loading exercise has not been tested in people with COPD. The aim of the proposed study will be to investigate the feasibility and tolerance of adding impact loading exercise to a standard pulmonary rehabilitation programme (PRP) in people with COPD and report its effects on bone health, balance and falls risk. METHODS: This is a protocol for a pilot feasibility and tolerance randomised controlled trial (RCT). Fifty-eight people with COPD will be randomly allocated, on a 1:1 ratio, to either the experimental or control group. Initially, participants in both groups will complete a standard 8-week (twice-weekly) PRP followed by a 32-week period of maintenance exercises. Over the initial 8-week period, participants allocated to the experimental group will also undertake targeted lower limb resistance exercises and commence a programme of impact loading exercises (e.g. bounding and drop jumps). On completion of the initial 8-week PRP, in addition to the standard maintenance exercises, participants in the experimental group will continue with home-based impact loading exercises, four times a week, for the extra 32 weeks. The primary outcome of this study is feasibility of and tolerance to impact loading exercises. Feasibility will be measured using data collected pertaining to recruitment, withdrawal and completion. Adherence to the exercises will be collected using exercise logs. Tolerance to the exercises will be determined using outcomes to assess pain, recording any adverse effects such as a fall and feedback from the participants in semi-structured interviews on completing of the trial. The effects of the 40-week experimental intervention on bone health, balance and falls risk will be reported. DISCUSSION: This pilot RCT will test the feasibility and tolerance of an intervention that has never been trialed in people with COPD. It will also provide initial information regarding the size of the effect this intervention has on outcomes such as BMD, balance and falls risk. These data will be critical when designing a definitive RCT to advance this area of research. TRIAL REGISTRATION: Australian and New Zealand Clinical Trials Registry (ANZCTR): 12620001085965 (20/10/2020).

The optimal timing of FDG-PET/CT in non-small cell lung cancer diagnosis and staging in an Australian centre.

BACKGROUND: Clinical practice guidelines and re-imbursement schedules vary in the recommended timing of FDG-PET/CT in the diagnostic evaluation of suspected or confirmed lung cancer. The aim was to estimate the probability of requiring more than one invasive test to complete diagnosis and staging in non-small cell lung cancer if FDG-PET/CT was used prior to initial biopsy (FDG-PET/CT First) compared to current Australian funding criteria (CT First). METHODS: Single-centre retrospective study of individuals with pathologically confirmed NSCLC without evidence of metastatic disease on baseline computed tomography (CT) of the chest. Decision tree analysis based on diagnosis and staging approaches estimated the probability of requiring more than one invasive biopsy. A Monte Carlo analysis with 1000 simulations was used to estimate decision tree precision. RESULTS: After exclusions, 115 patients were included with median (IQR) age of 71 (63-79) and 55.6% were male. The majority of cases were early stage (Stage I 43.5%, Stage II 19.1%) and adenocarcinoma (65.2%) histological subtype. The estimated probability of requiring more than one invasive biopsy with FDG-PET/CT prior was 0.12 compared to 0.19 when using the base case CT First scenario. Using the Monte Carlo analysis, the mean (95% CI) probability using the FDG-PET First approach was 0.15 (95%CI 0.12-0.20) versus 0.20 (95% CI 0.15-0.27) for the CT First approach. Only 7.8% had CT Chest-occult metastatic disease on FDG-PET that was accessible by percutaneous biopsy. CONCLUSION: FDG-PET/CT performed prior to initial biopsy may reduce the proportion of people with NSCLC who require more than one biopsy attempt, but the clinical significance and overall cost-utility requires evaluation.

The Combination of Metabolic Posterior Cingulate Cortical Abnormalities and Structural Asymmetries Improves the Differential Diagnosis Between Primary Progressive Aphasia and Alzheimer's Disease.

Differential diagnosis between primary progressive aphasia (PPA) and Alzheimer's disease (AD) could be difficult if based on clinical grounds alone. We evaluated the combination of proton MR spectroscopy of posterior cingulate cortex (PCC) and quantitative structural imaging asymmetries to differentiate PPA from AD patients. A greater left-lateralized temporo-parietal atrophy (higher accuracy for the PCC, 81.4%) and metabolic neurodegenerative changes in PCC (accuracy 76.8%) was demonstrated in PPA versus AD. The combined multiparametric approach increased the accuracy to 94%in the differential diagnosis between these two neurodegenerative diseases.