Finding the Optimal Timing for Repair of Standard Tetralogy of Fallot: Analysis of Cardiac Magnetic Resonance and Echocardiography Parameters Related to Intermediate Term Outcomes in a Pediatric Population.

Introduction: Right ventricular (RV) dilatation is the determining prognostic factor in the long-term follow up of patients with repaired Tetralogy of Fallot (TOF). The objective of this study is to analyze whether the results vary depending on the timing of the complete repair and on the surgical technique applied.

Material-methods: This is a retrospective longitudinal study in which patients with standard TOF were divided into 3 groups depending on their age at surgical repair: group 1 = Early repair (n = 12,1-8 months), group 2 = Late repair (n = 26, > 8 months), and group 3 = Late repair with previous palliative surgery (n = 17, > 8 months).

Evaluation of Cerebrospinal Fluid Neurofilament Light Chain as a Routine Biomarker in a Memory Clinic.

Systematic evaluation of biomarkers in representative populations is needed to validate their clinical utility. In this work, we assessed the diagnostic performance of cerebrospinal fluid (CSF) neurofilament light chain (NfL) in a neurocognitive clinical setting. A total of 51 patients with different cognitive clinical syndromes and 11 cognitively normal individuals were evaluated in a memory clinic in Argentina.

Multicentre evaluation of the INTERPRET decision support system 2.0 for brain tumour classification.

In a previous study, we have shown the added value of (1) H MRS for the neuroradiological characterisation of adult human brain tumours. In that study, several methods of MRS analysis were used, and a software program, the International Network for Pattern Recognition of Tumours Using Magnetic Resonance Decision Support System 1.0 (INTERPRET DSS 1.

Compatibility between 3T 1H SV-MRS data and automatic brain tumour diagnosis support systems based on databases of 1.5T 1H SV-MRS spectra.

Object: This study demonstrates that 3T SV-MRS data can be used with the currently available automatic brain tumour diagnostic classifiers which were trained on databases of 1.5T spectra. This will allow the existing large databases of 1.