Microwave Imaging System Based on Signal Analysis in a Planar Environment for Detection of Abdominal Aortic Aneurysms.

A proof-of-concept of a microwave imaging system for the fast detection of abdominal aortic aneurysms is shown. This experimental technology seeks to overcome the factors hampering the fast screening for these aneurysms with the usual equipment, such as high cost, long-time operation or hazardous exposure to chemical substances. The hardware system is composed of 16 twin antennas mastered by a microcontroller through a switching network, which connects the antennas to the measurement instrument for sequential measurement. The software system is run by a computer, mastering the whole system, automatizing the measurement process and running the signal processing and medical image generation algorithms. Two image generation algorithms are tested: Delay-and-Sum (DAS) and Improved Delay-and-Sum (IDAS). Own-modified versions of these algorithms adapted to the requirements of our system are proposed. The system is carefully calibrated and fine-tuned with known objects placed at known distances. An experimental proof-of-concept is shown with a human torso phantom, including an aorta phantom and an aneurysm phantom placed in different positions. The results show good imaging capabilities with the potential for detecting and locating possible abdominal aortic aneurysms and reporting acceptable errors.

Non-Invasive Microwave-Based Imaging System for Early Detection of Breast Tumours.

This work introduces a microwave-based system able to detect tumours in breast phantoms in a non-invasive way. The data acquisition system is composed of a hardware system which involves high-frequency components (antennas, switches and cables), a microcontroller, a vector network analyser used as measurement instrument and a computer devoted to the control and automation of the operation of the system. Concerning the software system, the computer runs a Python script which is in charge of mastering and automatising all the required stages for the data acquisition, from initialisation of the hardware system to performing and saving the measurements. We also report on the design of the high-performance broadband antenna used to carry out the measurements, as well as on the algorithm employed to build the final medical images, based on an adapted version of the so-called Improved Delay-and-Sum (IDAS) algorithm improved by a Hamming window filter and averaging preprocessing. The calibration and start-up of the system are also described. The experimental validation includes the use of different tumour models with different dielectric properties inside the breast phantom. The results show promising tumour detection capabilities, even when there is low dielectric contrast between the tumoural and healthy tissues, as is the usual case for dense breasts in young women.

Validation of an RF Image System for Real-Time Tracking Neurosurgical Tools.

A radio frequency (RF)-based system for surgical navigation is presented. Surgical navigation technologies are widely used nowadays for aiding the surgical team with many interventions. However, the currently available options still pose considerable limitations, such as line-of-sight occlusion prevention or restricted materials and equipment allowance. In this work, we suggest a different approach based on a microwave broadband antenna system. We combine techniques from microwave medical imaging, which can overcome the current limitations in surgical navigation technologies, and we propose methods to develop RF-based systems for real-time tracking neurosurgical tools. The design of the RF system to perform the measurements is shown and discussed, and two methods (Multiply and Sum and Delay Multiply and Sum) for building the medical images are analyzed. From these measurements, a surgical tool's position tracking system is developed and experimentally assessed in an emulated surgical scenario. The reported results are coherent with other approaches found in the literature, while overcoming their main practical limitations. The discussion of the results discloses some hints on the validity of the system, the optimal configurations depending on the requirements, and the possibilities for future enhancements.

Impact of Gestational COVID-19 on Neonatal Outcomes: Is Vertical Infection Possible?

BACKGROUND: The vertical transmission of severe acute respiratory coronavirus-2 (SARS-CoV-2) remains highly debated. Here, we evaluated SARS-CoV-2-transmission in newborns with intrauterine conditions. METHODS: This was a prospective, observational and multicentric study involving 13 Spanish hospitals included in the GEStational and NEOnatal-COVID cohort. Pregnant women with microbiologically confirmed SARS-CoV-2 infection during any trimester of pregnancy or delivery and their newborns were included from March to November 2020. Demographic, clinical and microbiological data were also obtained. Viral loads were analyzed in different maternal and newborn biological samples (placenta, breast milk and maternal blood; urine, meconium and newborn blood). RESULTS: A total of 177 newborns exposed to SARS-CoV-2 were included. Newborns were tested by reverse transcriptase-polymerase chain reaction using nasopharyngeal swabs within the first 24-48 hours of life and at 14 days of life. In total 5.1% were considered to have SARS-CoV-2 infection in the neonatal period, with 1.7% considered intrauterine and 3.4% intrapartum or early postnatal transmission cases. There were no differences in the demographic and clinical characteristics of the pregnant women and their newborns' susceptibility to infections in their perinatal history or background. CONCLUSIONS: Intrauterine transmission of SARS-CoV-2 is possible, although rare, with early postnatal transmission occurring more frequently. Most infected newborns remained asymptomatic or had mild symptoms that evolved well during follow-up. We did not find any maternal characteristics predisposing infants to neonatal infection. All infected newborn mothers had acute infection at delivery.Although there was no presence of SARS-CoV2 in cord blood or breast milk samples, SARS-CoV-2 viral load was detected in urine and meconium samples from infected newborns.