Multi-channel pre-beamformed data acquisition system for research on advanced ultrasound imaging methods

The lack of open access to the pre-beamformed data of an ultrasound scanner has limited the research of novel imaging methods to a few privileged laboratories. To address this need, we have developed a pre-beamformed data acquisition (DAQ) system that can collect data over 128 array elements in parallel from the Ultrasonix series of research-purpose ultrasound scanners. Our DAQ system comprises three system-level blocks: 1) a connector board that interfaces with the array probe and the scanner through a probe connector port; 2) a main board that triggers DAQ and controls data transfer to a computer; and 3) four receiver boards that are each responsible for acquiring 32 channels of digitized raw data and storing them to the on-board memory. This system can acquire pre-beamformed data with 12-bit resolution when using a 40-MHz sampling rate. It houses a 16 GB RAM buffer that is sufficient to store 128 channels of pre-beamformed data for 8000 to 25 000 transmit firings, depending on imaging depth; corresponding to nearly a 2-s period in typical imaging setups. Following the acquisition, the data can be transferred through a USB 2.0 link to a computer for offline processing and analysis. To evaluate the feasibility of using the DAQ system for advanced imaging research, two proof-of-concept investigations have been conducted on beamforming and plane-wave B-flow imaging. Results show that adaptive beamforming algorithms such as the minimum variance approach can generate sharper images of a wire cross-section whose diameter is equal to the imaging wavelength (150 μm in our example). Also, planewave B-flow imaging can provide more consistent visualization of blood speckle movement given the higher temporal resolution of this imaging approach (2500 fps in our example). © 2012 IEEE.published_or_final_versio

Ten years of screening for congenital disorders of glycosylation in Argentina: case studies and pitfalls

Background: Congenital Disorders of Glycosylation (CDG) are genetic diseases caused by hypoglycosylation of glycoproteins and glycolipids. Most CDG are multisystem disorders with mild to severe involvement. Methods: We studied 554 patients (2007–2017) with a clinical phenotype compatible with a CDG. Screening was performed by serum transferrin isoelectric focusing. The diagnosis was confirmed by genetic testing (Sanger or exome sequencing). Results: A confirmed abnormal pattern was found in nine patients. Seven patients showed a type 1 pattern: four with PMM2-CDG, two with ALG2-CDG, and one with classical galactosemia. A type 2 pattern was found in two patients: one with a CDG-IIx and one with a transferrin protein variant. Abnormal transferrin pattern were observed in a patient with a myopathy due to a COL6A2 gene variant. Conclusions: CDG screening in Argentina from 2007 to 2017 revealed 4 PMM2-CDG patients, 2 ALG2-CDG patients with a novel homozygous gene variant and 1 CDG-IIx.Fil: Asteggiano, Carla Gabriela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; Argentina. Universidad Nacional de Córdoba. Facultad de Medicina. Centro de Estudios de las Metabolopatías Congénitas; Argentina. Universidad Católica de Córdoba; Argentina. Gobierno de la Provincia de Córdoba. Ministerio de Salud. Hospital de Niños de la Santísima Trinidad; ArgentinaFil: Papazoglu, Gabriela Magali. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; Argentina. Universidad Nacional de Córdoba. Facultad de Medicina. Centro de Estudios de las Metabolopatías Congénitas; Argentina. Gobierno de la Provincia de Córdoba. Ministerio de Salud. Hospital de Niños de la Santísima Trinidad; Argentina. Universidad Católica de Córdoba; ArgentinaFil: Bistue Millon, Maria Beatriz. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; Argentina. Universidad Nacional de Córdoba. Facultad de Medicina. Centro de Estudios de las Metabolopatías Congénitas; Argentina. Gobierno de la Provincia de Córdoba. Ministerio de Salud. Hospital de Niños de la Santísima Trinidad; Argentina. Universidad Católica de Córdoba; ArgentinaFil: Peralta, Maria Fernanda. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; Argentina. Universidad Católica de Córdoba; Argentina. Universidad Nacional de Córdoba. Facultad de Medicina. Centro de Estudios de las Metabolopatías Congénitas; Argentina. Gobierno de la Provincia de Córdoba. Ministerio de Salud. Hospital de Niños de la Santísima Trinidad; ArgentinaFil: Azar, Nydia Beatríz. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; Argentina. Universidad Nacional de Córdoba. Facultad de Medicina. Centro de Estudios de las Metabolopatías Congénitas; Argentina. Universidad Católica de Córdoba; Argentina. Gobierno de la Provincia de Córdoba. Ministerio de Salud. Hospital de Niños de la Santísima Trinidad; ArgentinaFil: Spécola, Norma. Municipalidad de La Plata. Hospital de Niños; ArgentinaFil: Guelbert, Norberto Bernardo. Gobierno de la Provincia de Córdoba. Ministerio de Salud. Hospital de Niños de la Santísima Trinidad; ArgentinaFil: Suldrup, Niels. Iaca Laboratorios; ArgentinaFil: Pereyra, Marcela. Gobierno de la Provincia de Mendoza. Hospital Pediátrico Humberto Notti; ArgentinaFil: Dodelson de Kremer, Raquel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; Argentina. Universidad Nacional de Córdoba. Facultad de Medicina. Centro de Estudios de las Metabolopatías Congénitas; Argentina. Gobierno de la Provincia de Córdoba. Ministerio de Salud. Hospital de Niños de la Santísima Trinidad; Argentina. Universidad Católica de Córdoba; Argentin