Open-source image registration for MRI–TRUS fusion-guided prostate interventions

Abstract

Purpose We propose two software tools for non-rigid registration of MRI and transrectal ultrasound (TRUS) images of the prostate. Our ultimate goal is to develop an open-source solution to support MRI–TRUS fusion image guidance of prostate interventions, such as targeted biopsy for prostate cancer detection and focal therapy. It is widely hypothesized that image registration is an essential component in such systems. Methods The two non-rigid registration methods are: (1) a deformable registration of the prostate segmentation distance maps with B-spline regularization and (2) a finite element-based deformable registration of the segmentation surfaces in the presence of partial data. We evaluate the methods retrospectively using clinical patient image data collected during standard clinical procedures. Computation time and Target Registration Error (TRE) calculated at the expert-identified anatomical landmarks were used as quantitative measures for the evaluation. Results The presented image registration tools were capable of completing deformable registration computation within 5 min. Average TRE was approximately 3 mm for both methods, which is comparable with the slice thickness in our MRI data. Both tools are available under nonrestrictive open-source license. Conclusions We release open-source tools that may be used for registration during MRI–TRUS-guided prostate interventions. Our tools implement novel registration approaches and produce acceptable registration results. We believe these tools will lower the barriers in development and deployment of interventional research solutions and facilitate comparison with similar tools.

Interobserver Reproducibility of the PI-RADS Version 2 Lexicon: A Multicenter Study of Six Experienced Prostate Radiologists

“…The biopsy results were obtained from standard pathologic reports. Given an estimated registration error of 3-4 mm by using fusion systems for targeted prostate biopsy (20)(21)(22), any tumor within the targeted cores or within the nearest adjacent systematic core was considered to correspond with the MR-imaged lesion. Radical prostatectomy was performed in 29 patients, although none of the specimens underwent whole-mount processing.…”

In silico comparison of photons versus carbon ions in single fraction therapy of lung cancer

“…They can be accessed either using existing libraries, such as ITK [Yoo et al, 2002], or by writing designated software [Fedorov et al, 2015]. In the future, different DIR algorithms have to be implemented and tested for various anatomical sites.…”

MR-TRUS Fusion Biopsy

“…13,14 The acquisition can be 2-or 3-dimensional (2D or 3D), with improved through-plane resolution of the 3D acquisition resulting in smoother reformats but a longer acquisition time and concomitant risk of motion artifact that affects the entire image stack. 15,16 Depending on the software, the prostate and targets must be segmented on the same pulse sequence.…”