Assessment of image registration accuracy in three‐dimensional transrectal ultrasound guided prostate biopsy

Karnik, Vaishali; Fenster, Aaron; Bax, Jeffrey; Cool, Derek W.; Gardi, Lori; Gyacskov, Igor; Romagnoli, Cesare; Ward, Aaron D.

doi:10.1118/1.3298010

Cited by 62 publications

(84 citation statements)

References 34 publications

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“…For those patients with suspicious lesions on MP-MRI, Fn-Bx was performed prior to Std-Bx, with 1-3 samples collected per lesion. MRI-TRUS fusion was performed using cool et al 23,24 to align the pre-biopsy 3D TRUS volume to the intra-biopsy 3D TRUS image. All MRI lesions were then mapped through the fusion pipeline and displayed on the intra-biopsy 3D TRUS platform for needle guidance.…”

Section: Mri-3d Trus Fusion Biopsymentioning

confidence: 99%

Comparison of prostate MRI-3D transrectal ultrasound fusion biopsy for first-time and repeat biopsy patients with previous atypical small acinar proliferation

Cool

Romagnoli

Izawa

et al. 2016

CUAJ

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Introduction: This study evaluates the clinical benefit of magnetic resonance-transrectal ultrasound (MR-TRUS) fusion biopsy over systematic biopsy between first-time and repeat prostate biopsy patients with prior atypical small acinar proliferation (ASAP). Materials: 100 patients were enrolled in a single-centre prospective cohort study: 50 for first biopsy, 50 for repeat biopsy with prior ASAP. Multiparameteric magnetic resonance imaging (MP-MRI) and standard 12-core ultrasound biopsy (Std-Bx) were performed on all patients. Targeted biopsy using MRI-TRUS fusion (Fn-Bx) was performed f suspicious lesions were identified on the prebiopsy MP-MRI. Classification of clinically significant disease was assessed independently for the Std-Bx vs. Fn-Bx cores to compare the two approaches. Results: Adenocarcinoma was detected in 49/100 patients (26 first biopsy, 23 ASAP biopsy), with 25 having significant disease (17 first, 8 ASAP). Fn-Bx demonstrated significantly higher per-core cancer detection rates, cancer involvement, and Gleason scores for first-time and ASAP patients. However, Fn-Bx was significantly more likely to detect significant cancer missed on Std-Bx for ASAP patients than first-time biopsy patients. The addition of Fn-Bx to Std-Bx for ASAP patients had a 166.7% relative risk reduction for missing Gleason ≥ 3 + 4 disease (number needed to image with MP-MRI=10 patients) compared to 6.3% for first biopsy (number to image=50 patients). Negative predictive value of MP-MRI for negative biopsy was 79% for first-time and 100% for ASAP patients, with median followup of 32.1 ± 15.5 months. Conclusions: MR-TRUS Fn-Bx has a greater clinical impact for repeat biopsy patients with prior ASAP than biopsy-naïve patients by detecting more significant cancers that are missed on Std-Bx.

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Section: Mri-3d Trus Fusion Biopsymentioning

confidence: 99%

Comparison of prostate MRI-3D transrectal ultrasound fusion biopsy for first-time and repeat biopsy patients with previous atypical small acinar proliferation

Cool

Romagnoli

Izawa

et al. 2016

CUAJ

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“…The Dice Similarity Coefficient (DSC) value for the total gland was reported as 0:91 and the fiducial registration error was 2.3 ± 1.8 mm for 16 cases. The accuracies of surface-based and image-based registration methods to register intra-session 3D TRUS-TRUS volumes were evaluated by Karnik et al (2010). The surfacebased registration involved a rigid registration using the iterative closest point algorithm (Besl and McKay, 1992) and the non-rigid registration was based on TPS.…”

Section: Related Workmentioning

confidence: 99%

“…Natarajan et al (2011) also proposed elastic warping of MR volume to match the TRUS volume acquired for targeted prostate biopsy. The fusion method involves rigid alignment of the two volumes using manually selected anatomical landmarks and thereafter, the methods of Narayanan et al (2009) and Karnik et al (2010) were used for surface deformation. The MR-fusion based targeted biopsy was performed on 47 patients where a 33% biopsy-positivity rate was found versus a 7% positivity rate for systematic biopsy.…”

Section: Related Workmentioning

confidence: 99%

A spline-based non-linear diffeomorphism for multimodal prostate registration

Mitra

Kató

Martí

et al. 2012

Medical Image Analysis

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This paper presents a novel method for non-rigid registration of transrectal ultrasound and magnetic resonance prostate images based on a non-linear regularized framework of point correspondences obtained from a statistical measure of shape-contexts. The segmented prostate shapes are represented by shape-contexts and the Bhattacharyya distance between the shape representations is used to find the point correspondences between the 2D fixed and moving images. The registration method involves parametric estimation of the non-linear diffeomorphism between the multimodal images and has its basis in solving a set of non-linear equations of thin-plate splines. The solution is obtained as the least-squares solution of an over-determined system of non-linear equations constructed by integrating a set of non-linear functions over the fixed and moving images. However, this may not result in clinically acceptable transformations of the anatomical targets. Therefore, the regularized bending energy of the thin-plate splines along with the localization error of established correspondences should be included in the system of equations. The registration accuracies of the proposed method are evaluated in 20 pairs of prostate mid-gland ultrasound and magnetic resonance images. The results obtained in terms of Dice similarity coefficient show an average of 0.980±0.004, average 95% Hausdorff distance of 1.63±0.48 mm and mean target registration and target localization errors of 1.60±1.17 mm and 0.15±0.12 mm respectively.

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“…Thus, an efficient and accurate prostate segmentation method for both 3-D MR and TRUS images is highly desired for the surface-based MR to 3-D TRUS registration [6], [7]. In addition, prostate segmentation from 3-D TRUS and MRI plays a key role in clinical decision making process.…”

mentioning

confidence: 99%

Prostate Segmentation: An Efficient Convex Optimization Approach With Axial Symmetry Using 3-D TRUS and MR Images

Qiu

Yuan

Ukwatta

et al. 2014

IEEE Trans. Med. Imaging

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We propose a novel global optimization-based approach to segmentation of 3-D prostate transrectal ultrasound (TRUS) and T2 weighted magnetic resonance (MR) images, enforcing inherent axial symmetry of prostate shapes to simultaneously adjust a series of 2-D slice-wise segmentations in a "global" 3-D sense. We show that the introduced challenging combinatorial optimization problem can be solved globally and exactly by means of convex relaxation. In this regard, we propose a novel coherent continuous max-flow model (CCMFM), which derives a new and efficient duality-based algorithm, leading to a GPU-based implementation to achieve high computational speeds. Experiments with 25 3-D TRUS images and 30 3-D T2w MR images from our dataset, and 50 3-D T2w MR images from a public dataset, demonstrate that the proposed approach can segment a 3-D prostate TRUS/MR image within 5-6 s including 4-5 s for initialization, yielding a mean Dice similarity coefficient of 93.2%±2.0% for 3-D TRUS images and 88.5%±3.5% for 3-D MR images. The proposed method also yields relatively low intra- and inter-observer variability introduced by user manual initialization, suggesting a high reproducibility, independent of observers.

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Assessment of image registration accuracy in three‐dimensional transrectal ultrasound guided prostate biopsy

Abstract: Our results compare favorably with a clinical need for a TRE of less than 2.5 mm, and suggest that image-based registration is superior to surface-based registration for 3D TRUS-guided prostate biopsies, since it does not require segmentation.

Cited by 62 publications

References 34 publications

Comparison of prostate MRI-3D transrectal ultrasound fusion biopsy for first-time and repeat biopsy patients with previous atypical small acinar proliferation

Comparison of prostate MRI-3D transrectal ultrasound fusion biopsy for first-time and repeat biopsy patients with previous atypical small acinar proliferation

A spline-based non-linear diffeomorphism for multimodal prostate registration

Prostate Segmentation: An Efficient Convex Optimization Approach With Axial Symmetry Using 3-D TRUS and MR Images

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