Skip to content

UCL Spin-out SmartTarget Guides Prostate Cancer Treatment

Katie Konyn

in News

A UCL spin-out is helping improve the accuracy of prostate cancer treatment, with medical software to guide needle biopsy and minimise invasive surgical procedures.

  • The company has spun out from a well-established collaboration between the UCL Centre for Medical Image Computing, the Department of Medical Physics & Biomedical Engineering and urologists, radiologists and pathologists at UCLH, working to improve imaging of the prostate during surgery.

    Deformable 3D prostate model registered (aligned) with a 3D ultrasound image

    The prostate normally cannot be distinguished on ultrasound image, the standard method for guiding biopsy and a number of minimally-invasive treatments. Targeting ‘invisible’ tumours with a high degree of accuracy is extremely difficult, even for a skilled urologist. Dean Barratt (UCL CMIC) lead a Royal Academy of Engineering/EPSRC Postdoctoral Research Fellowship project to align MRI and ultrasound images, allowing information on prostate tumour location, size, and shape derived from MRI scans to be superimposed onto ultrasound scans obtained during surgical procedures, such as needle biopsy.

    The SmartTarget software fuses a three-dimensional computer model which describes the size and shape of a patient’s prostate, together the disease within it, with three-dimensional ultrasound images acquired during a surgical procedure. The result – an ultrasound image with a coloured graphical overlay of the tumour – is then displayed on the software user interface and used in place of the original ultrasound image to provide realtime feedback on the location of needles (and needle-like therapy delivery instruments) in relation to a target tumour. In this way, the targeting accuracy can be maximised, which for biopsy has the advantage that far fewer needles and tissue samples (<5) are required to confirm the presence of (clinically significant) cancer compared with the 12-15 normally used, resulting in a shorter procedure and lower pathology costs.

    In the case of prostate cancer treatment, the same technique enables new tissue-preserving therapy strategies to be developed, which rely on accurate tumour targeted to deliver energy precisely to a tumour and minimise the damage to surrounding tissue.

  • This approach, known as focal therapy, offer the potential benefits of a lower risk of complications compared to established “whole gland” treatments, such as surgical removal of the prostate gland and radiotherapy, and present a promising alternative treatment option for men with low-intermediate risk prostate cancer.

  • A key feature of the technology is the ability to automatically compensate for prostate movement and changes in the shape of the prostate that commonly occur between MRI and ultrasound scans, primarily due to the insertion of a transrectal ultrasound (TRUS) imaging probe into the rectum. This physically distorts the prostate and makes direct comparison with the MRI images complicated.

    SmartTarget overcomes this problem by implementing advanced biomechanical and statistical modelling techniques to learn how prostates deform when a TRUS probe is inserted, and uses this information to correct for it, leading to maximum targeting accuracy. The use of a 3D model also substantially reduces the time required to manually process TRUS images during a procedure, which is particularly important in time-critical surgical environments, where even modest savings in time by minimising human-technology interaction and adopting an easy-to-use workflow can have large implications by reducing healthcare costs.

    The development and clinical evaluation of the SmartTarget® software has been acknowledged by two recent awards for multidisciplinary clinical research: BMJ Innovation Award (2015) and an NIHR CREST Award.

    SmartTarget comprises of Dr. Dean Barratt, Dr. Yipeng Hu, Rachael Rodell, Paul Martin, and Prof. David Hawkes (all affiliated with the UCL Centre for Medical Image Computing and the Department of Medical Physics & Biomedical Engineering); Marina Santilli (UCL Business); Mark Kirby (CEO – non-UCL)

    The research relied upon the input and support of urologists, radiologists, and pathologists at UCL/UCLH, including:
    Prof. Mark Emberton, Mr. Hashim Ahmed, Mrs. Caroline Moore (UCL Surgery and Interventional Science)
    Dr. Shonit Punwani, Dr. Clare Allen, and Dr. Alex Kirkham (UCL Centre for Medical Imaging and UCLH Radiology)
    Dr. Alex Freeman (UCL Histopathology).

    Further reading is available from the UCLB website and UCL central website