Advances in Quantitative Imaging of Genetic and Acquired Myopathies: Clinical Applications and Perspectives

In the last years, magnetic resonance imaging (MRI) has become fundamental for the diagnosis and monitoring of myopathies given its ability to show the severity and distribution of pathology, to identify specific patterns of damage distribution and to properly interpret a number of genetic variants. The advances in MR techniques and post-processing software solutions have greatly expanded the potential to assess pathological changes in muscle diseases, and more specifically of myopathies; a number of features can be studied and quantified, ranging from composition, architecture, mechanical properties, perfusion, and function, leading to what is known as quantitative MRI (qMRI). Such techniques can effectively provide a variety of information beyond what can be seen and assessed by conventional MR imaging; their development and application in clinical practice can play an important role in the diagnostic process and in assessing disease course and treatment response. In this review, we briefly discuss the current role of muscle MRI in diagnosing muscle diseases and describe in detail the potential and perspectives of the application of advanced qMRI techniques in this field

Late and Severe Myopathy in a Patient With Glycogenosis VII Worsened by Cyclosporine and Amiodarone

Glycogenosis VII (GSD VII) is a rare autosomal recessive glycogen storage disorder caused by mutations in the PFKM gene encoding the phosphofructokinase (PFK) enzyme. A classical form with exercise intolerance, contractures, and myoglobinuria, a severe multisystem infantile form, an hemolytic variant and a late-onset form usually presenting with muscle pain and mild fixed proximal weakness have been reported. We describe a 65-year-old man affected by muscle PFK deficiency who, since the age of 33, presented with exercise intolerance and myoglobinuria. Muscle biopsy showed a vacuolar myopathy with glycogen storage. The biochemical assay of PFK-M showed very low residual activity (6%). Genetic analysis of PFKM gene evidenced the presence of the heterozygote c.1817A>C (p.Asp543Ala) and c.488 G>A (p.Arg100Gln) pathogenic mutations. In his fifth decade, he started cyclosporine after liver transplantation for hepatocellular carcinoma and, then, amiodarone because of atrial fibrillation. In the following years, he developed a progressive and severe muscle weakness, mainly involving lower limbs, up to a loss of independent walking. Muscle MRI showed adipose substitution of both anterior and posterior thigh muscles with selective sparing of the medial compartment. Marked signs of adipose substitution were also documented in the legs with a selective replacement of gemelli and peroneus muscles. The temporal relationship between the patient's clinical worsening and chronic treatment with cyclosporine and amiodarone suggests an additive toxic damage by these two potentially myotoxic drugs determining such an unusually severe phenotype, also confirmed by muscle MRI findings

Deep Anatomical Federated Network (Dafne): an open client/server framework for the continuous collaborative improvement of deep-learning-based medical image segmentation

Semantic segmentation is a crucial step to extract quantitative information from medical (and, specifically, radiological) images to aid the diagnostic process, clinical follow-up. and to generate biomarkers for clinical research. In recent years, machine learning algorithms have become the primary tool for this task. However, its real-world performance is heavily reliant on the comprehensiveness of training data. Dafne is the first decentralized, collaborative solution that implements continuously evolving deep learning models exploiting the collective knowledge of the users of the system. In the Dafne workflow, the result of each automated segmentation is refined by the user through an integrated interface, so that the new information is used to continuously expand the training pool via federated incremental learning. The models deployed through Dafne are able to improve their performance over time and to generalize to data types not seen in the training sets, thus becoming a viable and practical solution for real-life medical segmentation tasks.Comment: 10 pages (main body), 5 figures. Work partially presented at the 2021 RSNA conference and at the 2023 ISMRM conference In this new version: added author and change in the acknowledgmen

Virtual brain simulations reveal network-specific parameters in neurodegenerative dementias

INTRODUCTION: Neural circuit alterations lay at the core of brain physiopathology, and yet are hard to unveil in living subjects. The Virtual Brain (TVB) modeling, by exploiting structural and functional magnetic resonance imaging (MRI), yields mesoscopic parameters of connectivity and synaptic transmission. METHODS: We used TVB to simulate brain networks, which are key for human brain function, in Alzheimer's disease (AD) and frontotemporal dementia (FTD) patients, whose connectivity and synaptic parameters remain largely unknown; we then compared them to healthy controls, to reveal novel in vivo pathological hallmarks. RESULTS: The pattern of simulated parameter differed between AD and FTD, shedding light on disease-specific alterations in brain networks. Individual subjects displayed subtle differences in network parameter patterns that significantly correlated with their individual neuropsychological, clinical, and pharmacological profiles. DISCUSSION: These TVB simulations, by informing about a new personalized set of networks parameters, open new perspectives for understanding dementias mechanisms and design personalized therapeutic approaches

Muscle quantitative MRI as a novel biomarker in hereditary transthyretin amyloidosis with polyneuropathy: a cross-sectional study

BACKGROUND: The development of reproducible and sensitive outcome measures has been challenging in hereditary transthyretin (ATTRv) amyloidosis. Recently, quantification of intramuscular fat by magnetic resonance imaging (MRI) has proven as a sensitive marker in patients with other genetic neuropathies. The aim of this study was to investigate the role of muscle quantitative MRI (qMRI) as an outcome measure in ATTRv. METHODS: Calf- and thigh-centered multi-echo T2-weighted spin-echo and gradient-echo sequences were obtained in patients with ATTRv amyloidosis with polyneuropathy (n = 24) and healthy controls (n = 12). Water T2 (wT2) and fat fraction (FF) were calculated. Neurological assessment was performed in all ATTRv subjects. Quantitative MRI parameters were correlated with clinical and neurophysiological measures of disease severity. RESULTS: Quantitative imaging revealed significantly higher FF in lower limb muscles in patients with ATTRv amyloidosis compared to controls. In addition, wT2 was significantly higher in ATTRv patients. There was prominent involvement of the posterior compartment of the thighs. Noticeably, FF and wT2 did not exhibit a length-dependent pattern in ATTRv patients. MRI biomarkers correlated with previously validated clinical outcome measures, Polyneuropathy Disability scoring system, Neuropathy Impairment Score (NIS) and NIS-lower limb, and neurophysiological parameters of axonal damage regardless of age, sex, treatment and TTR mutation. CONCLUSIONS: Muscle qMRI revealed significant difference between ATTRv and healthy controls. MRI biomarkers showed high correlation with clinical and neurophysiological measures of disease severity making qMRI as a promising tool to be further investigated in longitudinal studies to assess its role at monitoring onset, progression, and therapy efficacy for future clinical trials on this treatable condition

RFC1 expansions are a common cause of idiopathic sensory neuropathy

After extensive evaluation, one-third of patients affected by polyneuropathy remain undiagnosed and are labelled as having chronic idiopathic axonal polyneuropathy, which refers to a sensory or sensory-motor, axonal, slowly progressive neuropathy of unknown origin. Since a sensory neuropathy/neuronopathy is identified in all patients with genetically confirmed RFC1 cerebellar ataxia, neuropathy, vestibular areflexia syndrome, we speculated that RFC1 expansions could underlie a fraction of idiopathic sensory neuropathies also diagnosed as chronic idiopathic axonal polyneuropathy. We retrospectively identified 225 patients diagnosed with chronic idiopathic axonal polyneuropathy (125 sensory neuropathy, 100 sensory-motor neuropathy) from our general neuropathy clinics in Italy and the UK. All patients underwent full neurological evaluation and a blood sample was collected for RFC1 testing. Biallelic RFC1 expansions were identified in 43 patients (34%) with sensory neuropathy and in none with sensory-motor neuropathy. Forty-two per cent of RFC1-positive patients had isolated sensory neuropathy or sensory neuropathy with chronic cough, while vestibular and/or cerebellar involvement, often subclinical, were identified at examination in 58%. Although the sensory ganglia are the primary pathological target of the disease, the sensory impairment was typically worse distally and symmetric, while gait and limb ataxia were absent in two-thirds of the cases. Sensory amplitudes were either globally absent (26%) or reduced in a length-dependent (30%) or non-length dependent pattern (44%). A quarter of RFC1-positive patients had previously received an alternative diagnosis, including Sj\uf6gren's syndrome, sensory chronic inflammatory demyelinating polyneuropathy and paraneoplastic neuropathy, while three cases had been treated with immune therapies

Differential diagnosis of neurodegenerative dementias with the explainable MRI based machine learning algorithm MUQUBIA

Biomarker-based differential diagnosis of the most common forms of dementia is becoming increasingly important. Machine learning (ML) may be able to address this challenge. The aim of this study was to develop and interpret a ML algorithm capable of differentiating Alzheimer's dementia, frontotemporal dementia, dementia with Lewy bodies and cognitively normal control subjects based on sociodemographic, clinical, and magnetic resonance imaging (MRI) variables. 506 subjects from 5 databases were included. MRI images were processed with FreeSurfer, LPA, and TRACULA to obtain brain volumes and thicknesses, white matter lesions and diffusion metrics. MRI metrics were used in conjunction with clinical and demographic data to perform differential diagnosis based on a Support Vector Machine model called MUQUBIA (Multimodal Quantification of Brain whIte matter biomArkers). Age, gender, Clinical Dementia Rating (CDR) Dementia Staging Instrument, and 19 imaging features formed the best set of discriminative features. The predictive model performed with an overall Area Under the Curve of 98%, high overall precision (88%), recall (88%), and F1 scores (88%) in the test group, and good Label Ranking Average Precision score (0.95) in a subset of neuropathologically assessed patients. The results of MUQUBIA were explained by the SHapley Additive exPlanations (SHAP) method. The MUQUBIA algorithm successfully classified various dementias with good performance using cost-effective clinical and MRI information, and with independent validation, has the potential to assist physicians in their clinical diagnosis

SPIR MRI usefulness for steroid treatment management in Tolosa-Hunt syndrome

A 40-year-old man underwent surgery for a right middle ear cholesteatoma. One month later, he presented with a subacute ocular pain that was followed one day later by the appearance of vertical diplopia attributable to a right superior rectus paresis, lid ptosis and hypoaesthesia in the territory of the I and the II right trigeminal branches. A fat-suppressed (selective partial inversion recovery, SPIR) gadolinium-enhanced MRI favours the detection of inflammatory pathological tissue inside the right cavernous sinus, and in this patient it suggested a diagnosis of Tolosa-Hunt syndrome. The pain disappeared quickly after steroid treatment was started whereas the ocular nerve involvement improved only slightly during the first week of treatment. After two months, the patient only complained of diplopia on up-gaze, but the therapy was discontinued two months later on the basis of both clinical signs and MRI findings. SPIR MRI may be useful not only to support a diagnosis of Tolosa-Hunt syndrome, but also to follow-up the disease course and to manage steroid treatment