Real‐time registration of 3D to 2D ultrasound images for image‐guided prostate biopsy. Issue 9 (8th August 2017)

• Record Type: Journal Article
• Authors: Gillies, Derek J.; Gardi, Lori; De Silva, Tharindu; Zhao, Shuang‐ren; Fenster, Aaron
• Is Part Of: Medical physics. Volume 44:Issue 9(2017)
• Page Start: 4708
• Page End: 4723
• Publication Date: 2017-08-08
• Subjects: 2D‐3D transrectal ultrasound‐guided prostate biopsy -- prostate cancer -- prostate motion compensation -- real‐time image registration; Medical physics -- Periodicals; Medical physics; Geneeskunde; Natuurkunde; Toepassingen; Biophysics; Periodicals; Periodicals; Electronic journals; 610.153
• DOI: 10.1002/mp.12441
• Languages: English
• ISSNs: 0094-2405

Abstract

Abstract : Purpose: During image‐guided prostate biopsy, needles are targeted at tissues that are suspicious of cancer to obtain specimen for histological examination. Unfortunately, patient motion causes targeting errors when using an MR‐transrectal ultrasound (TRUS) fusion approach to augment the conventional biopsy procedure. This study aims to develop an automatic motion correction algorithm approaching the frame rate of an ultrasound system to be used in fusion‐based prostate biopsy systems. Two modes of operation have been investigated for the clinical implementation of the algorithm: motion compensation using a single user initiated correction performed prior to biopsy, and real‐time continuous motion compensation performed automatically as a background process. Methods: Retrospective 2D and 3D TRUS patient images acquired prior to biopsy gun firing were registered using an intensity‐based algorithm utilizing normalized cross‐correlation and Powell's method for optimization. 2D and 3D images were downsampled and cropped to estimate the optimal amount of image information that would perform registrations quickly and accurately. The optimal search order during optimization was also analyzed to avoid local optima in the search space. Error in the algorithm was computed using target registration errors (TREs) from manually identified homologous fiducials in a clinical patient dataset. The algorithm was evaluated for real‐time performance using the two different modes of clinical implementations by way of user initiated and continuous motion compensation methods on a tissue mimicking prostate phantom. Results: After implementation in a TRUS‐guided system with an image downsampling factor of 4, the proposed approach resulted in a mean ± std TRE and computation time of 1.6 ± 0.6 mm and 57 ± 20 ms respectively. The user initiated mode performed registrations with in‐plane, out‐of‐plane, and roll motions computation times of 108 ± 38 ms, 60 ± 23 ms, and 89 ± 27 ms, respectively, and corresponding registration errors of 0.4 ± 0.3 mm, 0.2 ± 0.4 mm, and 0.8 ± 0.5°. The continuous method performed registration significantly faster ( P < 0.05) than the user initiated method, with observed computation times of 35 ± 8 ms, 43 ± 16 ms, and 27 ± 5 ms for in‐plane, out‐of‐plane, and roll motions, respectively, and corresponding registration errors of 0.2 ± 0.3 mm, 0.7 ± 0.4 mm, and 0.8 ± 1.0°. Conclusions: The presented method encourages real‐time implementation of motion compensation algorithms in prostate biopsy with clinically acceptable registration errors. Continuous motion compensation demonstrated registration accuracy with submillimeter and subdegree error, while performing < 50 ms computation times. Image registration technique approaching the frame rate of an ultrasound system offers a key advantage to be smoothly integrated to the clinical workflow. In addition, this technique could be used further for a variety of image‐guided interventional procedures to treat and diagnose patients by improving targeting accuracy.