Technical Note: Error metrics for estimating the accuracy of needle/instrument placement during transperineal magnetic resonance/ultrasound‐guided prostate interventions. Issue 4 (9th March 2018)

• Record Type: Journal Article
• Authors: Bonmati, Ester; Hu, Yipeng; Villarini, Barbara; Rodell, Rachael; Martin, Paul; Han, Lianghao; Donaldson, Ian; Ahmed, Hashim U.; Moore, Caroline M.; Emberton, Mark; Barratt, Dean C.
• Is Part Of: Medical physics. Volume 45:Issue 4(2018)
• Page Start: 1408
• Page End: 1414
• Publication Date: 2018-03-09
• Subjects: accuracy validation -- focal therapy -- image‐guided interventions -- needle placement -- prostate cancer -- targeted biopsy; Medical physics -- Periodicals; Medical physics; Geneeskunde; Natuurkunde; Toepassingen; Biophysics; Periodicals; Periodicals; Electronic journals; 610.153
• DOI: 10.1002/mp.12814
• Languages: English
• ISSNs: 0094-2405

Abstract

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.