MRI system incorporates motion detection

Philips has developed an MRI system that contains an additional RF sensor to monitor signals from breathing and cardiac motion (WO/2019/096707). The system comprises an RF coil arrangement with a coil that transmits and/or receives an RF signal for generating an MR image and an additional RF sensor that transmits an RF transmit signal adapted to interact with the patient’s tissue. This allows sensing of signals due to patient motion simultaneously with transmitting and/or receiving the RF signal for generating the MR image. In this way, movements of a patient under examination in an MRI system may be detected in an efficient and reliable way.

Machine learning methods ease lesion analysis

Patients with known or suspected pathologies of the lungs and liver are commonly assessed using CT or MRI. Identifying and quantifying possible malignant regions in the resulting images is essential for accurate and timely diagnosis. However, careful quantitative assessment of lung and liver lesions can be tedious and time consuming. Computer aided detection software can improve accuracy and efficiency for both lesion detection and quantitative assessment. With this goal, Arterys has described an automated end-to-end pipeline for accurate lesion detection, segmentation and longitudinal identification (WO/2019/103912).

PET detector designed for combined PET/MRI scanner

Researchers at RWTH Aachen University have created a PET detector for use in a combined PET/MRI scanner (WO/2019/101909). The detector incorporates shielding against electromagnetic fields, such that fields generated by the MRI scanner are kept away from the PET detector, and fields from the PET detector’s processing electronics are kept away from the MRI scanner’s receiver coil. The PET detector is suitable for use within the MRI scanner, with the scanning unit of the PET detector is not oriented in parallel with the main axis of the MRI scanner and where the shielding of the detector has at least one slot perpendicular to the main axis of the scanner in at least one projection, to prevent induced currents.

Digital X-ray system offers automatic exposure control

IRay has described a digital X-ray system with automatic exposure control (WO/2019/105490). The system generates a pre-exposure parameter and sends it to a high-voltage generator, which performs pre-exposure imaging according to this parameter. This image is collected by a flat-panel detector and used to obtain a pre-exposure image greyscale value. According to this greyscale value, the pre-exposure X-ray dose and a set main exposure greyscale value, the system calculates a main exposure X-ray dose and generates a main exposure parameter. The high-voltage generator then performs the main exposure according to this parameter and the resulting image is collected and sent by the flat-panel detector. IRay says that this method removes the need to install an ionization chamber, has accurate exposure and low complexity, reduces system costs, decreases scrap rates in clinical applications, and reduces generation of extra radiation.

Cascaded dual-polarity waves deliver ultrafast ultrasound

Versitech Limited, the commercial arm of the University of Hong Kong, has invented a system and method for ultrafast ultrasound imaging (WO/2019/114585). The approach involves directing an array to transmit sets of cascaded titled ultrasound waves towards a tissue sample, and decoding the reflected signals through summing, subtracting and delay operations. The reflected signals can then be reconstructed to provide a final decoded output. The technique, known as “cascaded dual-polarity waves imaging” increases the signal-to-noise ratio and sensitivity in ultrafast imaging without compromising the frame rate.

3D printing creates physical models from medical images

The University of Pennsylvania has presented methods, systems and computer readable media for 3D printing from volumetric medical images, for example, MR or CT images of anatomical structures (WO/2019/113254). An example method involves receiving, from an imaging device, a multi-dimensional image of an anatomical structure. For each 2D slice of the original or resampled/processed image, voxels of the 2D slice are converted, row-by-row, into 3D printing instructions for that slice. By controlling a 3D printing extruder, a physical model based on the anatomical structure is created by printing, slice-by-slice, each 2D slice using the printing instructions.

By Tami Freeman