18 research outputs found
3D renal model for surgical planning of partial nephrectomy: A way to improve surgical outcomes
to evaluate the impact of 3D model for a comprehensive assessment of surgical planning and quality of partial nephrectomy (PN)
Primary mitochondrial myopathy: Clinical features and outcome measures in 118 cases from Italy
Objective: To determine whether a set of functional tests, clinical scales, patient-reported questionnaires, and specific biomarkers can be considered reliable outcome measures in patients with primary mitochondrial myopathy (PMM), we analyzed a cohort of Italian patients. Methods: Baseline data were collected from 118 patients with PMM, followed by centers of the Italian network for mitochondrial diseases. We used the 6-Minute Walk Test (6MWT), Timed Up-and-Go Test (x3) (3TUG), Five-Times Sit-To-Stand Test (5XSST), Timed Water Swallow Test (TWST), and Test of Masticating and Swallowing Solids (TOMASS) as functional outcome measures; the Fatigue Severity Scale and West Haven-Yale Multidimensional Pain Inventory as patient-reported outcome measures; and FGF21, GDF15, lactate, and creatine kinase (CK) as biomarkers. Results: A total of 118 PMM cases were included. Functional outcome measures (6MWT, 3TUG, 5XSST, TWST, and TOMASS) and biomarkers significantly differed from healthy reference values and controls. Moreover, functional measures correlated with patients' perceived fatigue and pain severity. Patients with either mitochondrial or nuclear DNA point mutations performed worse in functional measures than patients harboring single deletion, even if the latter had an earlier age at onset but similar disease duration. Both the biomarkers FGF21 and GDF15 were significantly higher in the patients compared with a matched control population; however, there was no relation with severity of disease. Conclusions: We characterized a large cohort of PMM by evaluating baseline mitochondrial biomarkers and functional scales that represent potential outcome measures to monitor the efficacy of treatment in clinical trials; these outcome measures will be further reinvestigated longitudinally to define the natural history of PMM
Effectiveness of Radiomic ZOT Features in the Automated Discrimination of Oncocytoma from Clear Cell Renal Cancer
Background: Benign renal tumors, such as renal oncocytoma (RO), can be erroneously
diagnosed as malignant renal cell carcinomas (RCC), because of their similar imaging features.
Computer-aided systems leveraging radiomic features can be used to better discriminate benign renal
tumors from the malignant ones. The purpose of this work was to build a machine learning model to
distinguish RO from clear cell RCC (ccRCC). Method: We collected CT images of 77 patients, with
30 cases of RO (39%) and 47 cases of ccRCC (61%). Radiomic features were extracted both from the
tumor volumes identified by the clinicians and from the tumor’s zone of transition (ZOT). We used a
genetic algorithm to perform feature selection, identifying the most descriptive set of features for the
tumor classification. We built a decision tree classifier to distinguish between ROs and ccRCCs. We
proposed two versions of the pipeline: in the first one, the feature selection was performed before the
splitting of the data, while in the second one, the feature selection was performed after, i.e., on the
training data only. We evaluated the efficiency of the two pipelines in cancer classification. Results:
The ZOT features were found to be the most predictive by the genetic algorithm. The pipeline
with the feature selection performed on the whole dataset obtained an average ROC AUC score of
0.87 ± 0.09. The second pipeline, in which the feature selection was performed on the training data
only, obtained an average ROC AUC score of 0.62 ± 0.17. Conclusions: The obtained results confirm
the efficiency of ZOT radiomic features in capturing the renal tumor characteristics. We showed
that there is a significant difference in the performances of the two proposed pipelines, highlighting
how some already published radiomic analyses could be too optimistic about the real generalization
capabilities of the models
Whole exome sequencing highlights rare variants in CTCF, DNMT1, DNMT3A, EZH2 and SUV39H1 as associated with FSHD
Introduction: Despite the progress made in the study of Facioscapulohumeral Dystrophy (FSHD), the wide heterogeneity of disease complicates its diagnosis and the genotype-phenotype correlation among patients and within families. In this context, the present work employed Whole Exome Sequencing (WES) to investigate known and unknown genetic contributors that may be involved in FSHD and may represent potential disease modifiers, even in presence of a D4Z4 Reduced Allele (DRA).Methods: A cohort of 126 patients with clinical signs of FSHD were included in the study, which were characterized by D4Z4 sizing, methylation analysis and WES. Specific protocols were employed for D4Z4 sizing and methylation analysis, whereas the Illumina® Next-Seq 550 system was utilized for WES. The study included both patients with a DRA compatible with FSHD diagnosis and patients with longer D4Z4 alleles. In case of patients harboring relevant variants from WES, the molecular analysis was extended to the family members.Results: The WES data analysis highlighted 20 relevant variants, among which 14 were located in known genetic modifiers (SMCHD1, DNMT3B and LRIF1) and 6 in candidate genes (CTCF, DNMT1, DNMT3A, EZH2 and SUV39H1). Most of them were found together with a permissive short (4–7 RU) or borderline/long DRA (8–20 RU), supporting the possibility that different genes can contribute to disease heterogeneity in presence of a FSHD permissive background. The segregation and methylation analysis among family members, together with clinical findings, provided a more comprehensive picture of patients.Discussion: Our results support FSHD pathomechanism being complex with a multigenic contribution by several known (SMCHD1, DNMT3B, LRIF1) and possibly other candidate genes (CTCF, DNMT1, DNMT3A, EZH2, SUV39H1) to disease penetrance and expressivity. Our results further emphasize the importance of extending the analysis of molecular findings within the proband’s family, with the purpose of providing a broader framework for understanding single cases and allowing finer genotype-phenotype correlations in FSHD-affected families
Redox Homeostasis in Muscular Dystrophies
In recent years, growing evidence has suggested a prominent role of oxidative stress in the pathophysiology of several early- and adult-onset muscle disorders, although effective antioxidant treatments are still lacking. Oxidative stress causes cell damage by affecting protein function, membrane structure, lipid metabolism, and DNA integrity, thus interfering with skeletal muscle homeostasis and functionality. Some features related to oxidative stress, such as chronic inflammation, defective regeneration, and mitochondrial damage are shared among most muscular dystrophies, and Nrf2 has been shown to be a central player in antagonizing redox imbalance in several of these disorders. However, the exact mechanisms leading to overproduction of reactive oxygen species and deregulation in the cellular antioxidants system seem to be, to a large extent, disease-specific, and the clarification of these mechanisms in vivo in humans is the cornerstone for the development of targeted antioxidant therapies, which will require testing in appropriately designed clinical trials
Beyond 10 years of levodopa intestinal infusion experience: Analysis of mortality and its predictors
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Muscle fibrosis as a prognostic biomarker in facioscapulohumeral muscular dystrophy: a retrospective cohort study
Abstract Facioscapulohumeral muscular dystrophy (FSHD) is an autosomal dominant epigenetic disorder with highly variable muscle involvement and disease progression. Ongoing clinical trials, aimed at counteracting muscle degeneration and disease progression in FSHD patients, increase the need for reliable biomarkers. Muscle magnetic resonance imaging (MRI) studies showed that the appearance of STIR-positive (STIR+) lesions in FSHD muscles represents an initial stage of muscle damage, preceding irreversible adipose changes. Our study aimed to investigate fibrosis, a parameter of muscle degeneration undetectable by MRI, in relation to disease activity and progression of FSHD muscles. We histologically evaluated collagen in FSHD1 patients’ (STIR+ n = 27, STIR− n = 28) and healthy volunteers’ (n = 12) muscles by picrosirius red staining. All patients (n = 55) performed muscle MRI before biopsy, 45 patients also after 1 year and 36 patients also after 2 years. Fat content (T1 signal) and oedema/inflammation (STIR signal) were evaluated at baseline and at 1- and 2-year MRI follow-up. STIR+ muscles showed significantly higher collagen compared to both STIR− (p = 0.001) and healthy muscles (p < 0.0001). STIR− muscles showed a higher collagen content compared to healthy muscles (p = 0.0194). FSHD muscles with a worsening in fatty infiltration during 1- (P = 0.007) and 2-year (P < 0.0001) MRI follow-up showed a collagen content of 3.6- and 3.7-fold higher compared to FSHD muscles with no sign of progression. Moreover, the fibrosis was significantly higher in STIR+ muscles who showed a worsening in fatty infiltration in a timeframe of 2 years compared to both STIR− (P = 0.0006) and STIR+ muscles with no sign of progression (P = 0.02). Fibrosis is a sign of muscle degeneration undetectable at MRI never deeply investigated in FSHD patients. Our data show that 23/27 of STIR+ and 12/28 STIR− muscles have a higher amount of collagen deposition compared to healthy muscles. Fibrosis is higher in FSHD muscles with a worsening in fatty infiltration thus suggesting that its evaluation with innovative non-invasive techniques could be a candidate prognostic biomarker for FSHD, to be used to stratify patients and to evaluate the efficacy of therapeutic treatments
Differential diagnosis of vacuolar muscle biopsies: use of p62, LC3 and LAMP2 immunohistochemistry
Botulinum toxin for Pisa syndrome: An MRI-, ultrasound- and electromyography-guided pilot study
Artificial Intelligence for Evaluation of Retinal Vasculopathy in Facioscapulohumeral Dystrophy Using OCT Angiography: A Case Series
Facioscapulohumeral muscular dystrophy (FSHD) is a slowly progressive muscular dystrophy with a wide range of manifestations including retinal vasculopathy. This study aimed to analyse retinal vascular involvement in FSHD patients using fundus photographs and optical coherence tomography-angiography (OCT-A) scans, evaluated through artificial intelligence (AI). Thirty-three patients with a diagnosis of FSHD (mean age 50.4 +/- 17.4 years) were retrospectively evaluated and neurological and ophthalmological data were collected. Increased tortuosity of the retinal arteries was qualitatively observed in 77% of the included eyes. The tortuosity index (TI), vessel density (VD), and foveal avascular zone (FAZ) area were calculated by processing OCT-A images through AI. The TI of the superficial capillary plexus (SCP) was increased (p < 0.001), while the TI of the deep capillary plexus (DCP) was decreased in FSHD patients in comparison to controls (p = 0.05). VD scores for both the SCP and the DCP results increased in FSHD patients (p = 0.0001 and p = 0.0004, respectively). With increasing age, VD and the total number of vascular branches showed a decrease (p = 0.008 and p < 0.001, respectively) in the SCP. A moderate correlation between VD and EcoRI fragment length was identified as well (r = 0.35, p = 0.048). For the DCP, a decreased FAZ area was found in FSHD patients in comparison to controls (t (53) = -6.89, p = 0.01). A better understanding of retinal vasculopathy through OCT-A can support some hypotheses on the disease pathogenesis and provide quantitative parameters potentially useful as disease biomarkers. In addition, our study validated the application of a complex toolchain of AI using both ImageJ and Matlab to OCT-A angiograms