Ester Bonmati1, Yipeng Hu1, Barbara Villarini1,2, Rachael Rodell1, Paul Martin1, Lianghao Han1,3, Ian Donaldson4, Hashim U Ahmed4,5,6, Caroline M Moore4, Mark Emberton4, Dean C Barratt1. 1. Department of Medical Physics & Biomedical Engineering, UCL Centre for Medical Image Computing, University College London, Gower Street, London, WC1E 6BT, UK. 2. Department of Computer Science, University of Westminster, 115 New Cavendish Street, London, W1W 6UW, UK. 3. School of Medicine, Shanghai East Hospital, Tongji University, 1239 Siping Road, Shanghai, China. 4. Division of Surgery and Interventional Science, University College London, UCL Medical School Building, 21 University Street, London, WC1E 6AU, UK. 5. Division of Surgery, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, Charing Cross Hospital Campus, Fulham Palace Road, London, W6 8RF, UK. 6. Imperial Urology, Charing Cross Hospital, Imperial College Healthcare NHS Trust, Imperial College London, Charing Cross Hospital Campus, Fulham Palace Road, London, W6 8RF, UK.
Abstract
PURPOSE: Image-guided systems that fuse magnetic resonance imaging (MRI) with three-dimensional (3D) ultrasound (US) images for performing targeted prostate needle biopsy and minimally invasive treatments for prostate cancer are of increasing clinical interest. To date, a wide range of different accuracy estimation procedures and error metrics have been reported, which makes comparing the performance of different systems difficult. METHODS: A set of nine measures are presented to assess the accuracy of MRI-US image registration, needle positioning, needle guidance, and overall system error, with the aim of providing a methodology for estimating the accuracy of instrument placement using a MR/US-guided transperineal approach. RESULTS: Using the SmartTarget fusion system, an MRI-US image alignment error was determined to be 2.0 ± 1.0 mm (mean ± SD), and an overall system instrument targeting error of 3.0 ± 1.2 mm. Three needle deployments for each target phantom lesion was found to result in a 100% lesion hit rate and a median predicted cancer core length of 5.2 mm. CONCLUSIONS: The application of a comprehensive, unbiased validation assessment for MR/US guided systems can provide useful information on system performance for quality assurance and system comparison. Furthermore, such an analysis can be helpful in identifying relationships between these errors, providing insight into the technical behavior of these systems.
PURPOSE: Image-guided systems that fuse magnetic resonance imaging (MRI) with three-dimensional (3D) ultrasound (US) images for performing targeted prostate needle biopsy and minimally invasive treatments for prostate cancer are of increasing clinical interest. To date, a wide range of different accuracy estimation procedures and error metrics have been reported, which makes comparing the performance of different systems difficult. METHODS: A set of nine measures are presented to assess the accuracy of MRI-US image registration, needle positioning, needle guidance, and overall system error, with the aim of providing a methodology for estimating the accuracy of instrument placement using a MR/US-guided transperineal approach. RESULTS: Using the SmartTarget fusion system, an MRI-US image alignment error was determined to be 2.0 ± 1.0 mm (mean ± SD), and an overall system instrument targeting error of 3.0 ± 1.2 mm. Three needle deployments for each target phantom lesion was found to result in a 100% lesion hit rate and a median predicted cancer core length of 5.2 mm. CONCLUSIONS: The application of a comprehensive, unbiased validation assessment for MR/US guided systems can provide useful information on system performance for quality assurance and system comparison. Furthermore, such an analysis can be helpful in identifying relationships between these errors, providing insight into the technical behavior of these systems.
Authors: Christopher Antonio Febres-Aldana; Sarah Alghamdi; Thomas A Weppelmann; Emilio Lastarria; Akshay Bhandari; Yumna Omarzai; Robert J Poppiti Journal: Urol Ann Date: 2020-10-15
Authors: Sami Hamid; Ian A Donaldson; Yipeng Hu; Rachael Rodell; Barbara Villarini; Ester Bonmati; Pamela Tranter; Shonit Punwani; Harbir S Sidhu; Sarah Willis; Jan van der Meulen; David Hawkes; Neil McCartan; Ingrid Potyka; Norman R Williams; Chris Brew-Graves; Alex Freeman; Caroline M Moore; Dean Barratt; Mark Emberton; Hashim U Ahmed Journal: Eur Urol Date: 2018-12-06 Impact factor: 20.096