Microbubbles enable super-resolution ultrasound imaging

Mayo Clinic researchers have developed systems and methods for super-resolution ultrasound imaging of microvessels (WO/2018/222724). The technique involves acquiring ultrasound data from a region-of-interest in a subject who has been administered a microbubble contrast agent. The data are acquired while the microbubbles are moving through or otherwise present in the region-of-interest, which may include microvessels or other microvasculature. Isolating, localizing, tracking and accumulating the microbubbles in the ultrasound data enables generation of super-resolution images.

Radioactive source delivers PET timing calibration

Philips has described a scheme for performing timing calibration of a PET imaging device. The approach uses a radioactive source comprising a positron-emitting radioisotope with a decay path that includes emission of two opposed 511 keV gamma rays and a cascade gamma ray at a different energy (WO/2018/202878). A timestamped detection event data set acquired from the source by the PET device is processed using energy window filtering and time window filtering. This generates a coincidence data set that includes event pairs, each consisting of two coincident 511 keV gammas, and cascade event pairs or triplets, each consisting of at least one coincident 511 keV event and a coincident cascade event at the cascade gamma ray energy. The coincidence data set is then used to generate a timing calibration, which provides offset times for the detectors of the PET imaging device.

Convolutional neural networks reduce nuclear medicine dose

A team from Stanford University has devised a method to reduce radiation dose for nuclear medicine imaging by using a convolutional network to generate a standard-dose image from a low-dose image (WO/2018/200493). The network includes N convolution neural network stages, where each stage includes M convolution layers with K x K kernels. The network extracts multi-scale and high-level features from the low-dose image to simulate a high-dose image, and adds concatenate connections to the low-dose image to preserve local information and resolution of the high-dose image. The high-dose image includes a radiotracer dose reduction factor (DRF) of one; the low-dose PET image includes a DRF of at least four.

Mesoscopic ultrasound generates brain tissue elastogram

Arizona State University has published details of a technique for creating an elastogram of brain tissue (WO/2018/227088). The elastogram is generated using mesoscopic wavelength ultrasound, composed of longitudinal waves, to produce micromechanical disturbances of brain nuclei and circuits. These tissue disturbances enable characterization of mechanical properties such as stiffness, elasticity, rigidity and viscoelasticity. The magnetic resonance elastography (MRE) system includes an MRE engine in communication with at least one transducer and an MRI device. The MRE engine controls the operation of the transducer, which emits ultrasound and receives at least one signal indicative of brain tissue displacement from the MRI device. It then generates an elastogram of the brain tissue based on the received signal(s).

Nanoparticles allow early diagnosis of Alzheimer’s disease

A team at the Chinese University of Hong Kong has created a novel nanoparticle that can cross the blood–brain barrier and bond with amyloid plaques and other related protein aggregates for detection by MRI (WO/2018/193278). The ability to image these amyloid plaques provide a non-invasive means for diagnosing Alzheimer’s disease at an early stage. According to the filing, which details the compositions and methods of making and using them, the approach employs non-toxic materials that have well established safety profiles and do not require further toxicological testing to secure regulatory approval.

Thickness measurements optimize radiography settings

To calculate the optimal exposure settings for a selected radiography exam, the acquisition geometry of the radiography system and the thickness of the patient must be known. Agfa has developed a method for accurately determining the source-image-distance (SID) and the thickness of a patient in a radiography configuration (WO/2018/184705). The SID is determined based on a method that accurately measures distances between a set of generator arrays and sensor arrays. These arrays are preferably orthogonally arranged magnetic field generators and sensors that allow distance measurement without being affected by the presence of human tissue between the generator and sensor arrays.