IQ-AI subsidiary sees tech installed at important tumour centre
By Josh White
Date: Tuesday 11 Dec 2018
(Sharecast News) - IQ-AI subsidiary Imaging Biometrics (IB) announced on Tuesday that Barrow Neurological Institute: Dignity Health, St. Joseph's Hospital and Medical Center (BNI) has installed a new 'IB Rad Tech' software platform, to help assess treatment response for patients with brain tumours.
The London-listed company said BNI had "led the way" in the development of top diagnosis, treatment, and neurosurgical procedures for patients with brain tumours.
It said that each year, Barrow treated thousands of patients with brain tumours, including some of the most difficult cases in the world.
IB Rad Tech was reportedly chosen for its ability to efficiently generate quantitative maps of enhancing regions of tumour, and fractional tumour burden.
IB's perfusion-derived fractional tumour burden maps had been shown to aid clinicians in distinguishing tumour from non-tumour tissue.
The company said IB Rad Tech offered custom workflows that automated the generation of sophisticated maps, output quality assurance indices, and could allow manual acknowledgement and intervention during intermediate processing steps.
For example, one workflow used in generating quantitative Delta T1 and fractional tumour burden maps relied on an exclusive machine-learned calibration technology termed 'standardisation', which worked for all platforms and field strengths.
That step had proven superior to conventional normalisation techniques, IB said, as it eliminated the need for the manual placement of regions of interest by radiology staff or physicians, thus reducing error and improving workflow efficiencies.
"Using this automated normalisation algorithm within an IB Rad Tech workflow enables objective longitudinal assessment and can help assess whether a certain treatment protocol is working for brain tumour patients," siad Imaging Biometrics chief executive officer David Smith.
"Removing the variability of the manually-placed regions of interest is a more repeatable and faster method to do inter- and intra-study comparisons for multi-centre clinical trials as well."
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