Mapping of Transrectal Ultrasonographic Prostate Biopsies

Mozer, Pierre; Baumann, Michaël; Chevreau, Grégoire; Moreau–Gaudry, Alexandre; Bart, S.; Renard-Penna, Raphaële; Compérat, Eva; Conort, Pierre; Bitker, Marc‐Olivier; Chartier‐Kastler, Emmanuel; Richard, François; Troccaz, Jocelyne

doi:10.7863/jum.2009.28.4.455

Cited by 40 publications

(7 citation statements)

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“…12,28 The robot can assist in image navigation since it can steadily hold and manipulate the imaging device (TRUS probe) accurately to generate a 3-D reconstruction image of the prostate. 13 Robotic assistance can improve biopsy targeting, while potentially decreasing false-negative results by geometrically consistent sampling.…”

Section: Discussionmentioning

confidence: 99%

“…In addition, only a few groups have addressed the distribution of biopsy cores and its relationship to the cancer detection rate. 10–12 Therefore, we studied the efficacy of freehand TRUS guided biopsy and compared it with that of a robot-assisted biopsy approach. We first developed a biopsy simulation system to accurately assess the position of biopsy cores in vitro.…”

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Geometric Evaluation of Systematic Transrectal Ultrasound Guided Prostate Biopsy

et al. 2012

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Purpose Transrectal ultrasound guided prostate biopsy results rely on physician ability to target the gland according to the biopsy schema. However, to our knowledge it is unknown how accurately the freehand, transrectal ultrasound guided biopsy cores are placed in the prostate and how the geometric distribution of biopsy cores may affect the prostate cancer detection rate. Materials and Methods To determine the geometric distribution of cores, we developed a biopsy simulation system with pelvic mock-ups and an optical tracking system. Mock-ups were biopsied in a freehand manner by 5 urologists and by our transrectal ultrasound robot, which can support and move the transrectal ultrasound probe. We compared 1) targeting errors, 2) the accuracy and precision of repeat biopsies, and 3) the estimated significant prostate cancer (0.5 cm3 or greater) detection rate using a probability based model. Results Urologists biopsied cores in clustered patterns and under sampled a significant portion of the prostate. The robot closely followed the predefined biopsy schema. The mean targeting error of the urologists and the robot was 9.0 and 1.0 mm, respectively. Robotic assistance significantly decreased repeat biopsy errors with improved accuracy and precision. The mean significant prostate cancer detection rate of the urologists and the robot was 36% and 43%, respectively (p <0.0001). Conclusions Systematic biopsy with freehand transrectal ultrasound guidance does not closely follow the sextant schema and may result in suboptimal sampling and cancer detection. Repeat freehand biopsy of the same target is challenging. Robotic assistance with optimized biopsy schemas can potentially improve targeting, precision and accuracy. A clinical trial is needed to confirm the additional benefits of robotic assistance.

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Section: Discussionmentioning

confidence: 99%

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confidence: 99%

Geometric Evaluation of Systematic Transrectal Ultrasound Guided Prostate Biopsy

et al. 2012

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“…In clinical practice, the total targeting error equates to the sum of these two errors [16]. All biopsy strategies were performed with a range of applied error, from 1 mm to 10 mm (Fig.…”

Section: Methodsmentioning

confidence: 99%

Prostate Cancer Risk Inflation as a Consequence of Image-targeted Biopsy of the Prostate: A Computer Simulation Study

Robertson¹,

Hu²,

Ahmed³

et al. 2014

European Urology

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BackgroundProstate biopsy parameters are commonly used to attribute cancer risk. A targeted approach to lesions found on imaging may have an impact on the risk attribution given to a man.ObjectiveTo evaluate whether, based on computer simulation, targeting of lesions during biopsy results in reclassification of cancer risk when compared with transrectal ultrasound (TRUS) guided biopsy.Design, setting, and participantsA total of 107 reconstructed three-dimensional models of whole-mount radical prostatectomy specimens were used for computer simulations. Systematic 12-core TRUS biopsy was compared with transperineal targeted biopsies using between one and five cores. All biopsy strategies incorporated operator and needle deflection error. A target was defined as any lesion ≥0.2 ml. A false-positive magnetic resonance imaging identification rate of 34% was applied.Outcome measurements and statistical analysisSensitivity was calculated for the detection of all cancer and clinically significant disease. Cases were designated as high risk based on achieving ≥6 mm cancer length and/or ≥50% positive cores. Statistical significance (p values) was calculated using both a paired Kolmogorov-Smirnov test and the t test.Results and limitationsWhen applying a widely used biopsy criteria to designate risk, 12-core TRUS biopsy classified only 24% (20 of 85) of clinically significant cases as high risk, compared with 74% (63 of 85) of cases using 4 targeted cores. The targeted strategy reported a significantly higher proportion of positive cores (44% vs 11%; p < 0.0001) and a significantly greater mean maximum cancer core length (7.8 mm vs 4.3 mm; p < 0.0001) when compared with 12-core TRUS biopsy. Computer simulations may not reflect the sources of errors encountered in clinical practice. To mitigate this we incorporated all known major sources of error to maximise clinical relevance.ConclusionsImage-targeted biopsy results in an increase in risk attribution if traditional criteria, based on cancer core length and the proportion of positive cores, are applied. Targeted biopsy strategies will require new risk stratification models that account for the increased likelihood of sampling the tumour.

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“…The shrinkage of AZ can be modeled prior to follow-up biopsy and incorporated in a US-guided sampling system 54 . A recent study evocated the benefit of a TRUS-MRI fusion platform that corrects for deformation on ultrasound due to the probe insertion, as compared to "cognitive registration" 55 .…”

Section: Discussionmentioning

confidence: 99%

3D Registration of mpMRI for Assessment of Prostate Cancer Focal Therapy

et al. 2017

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Purpose To assess a novel method of 3D co-registration of prostate MRI exams performed before and after prostate cancer focal therapy. Material and method We developed a software platform for automatic 3D deformable coregistration of prostate MRI at different time points and applied this method to ten patients who underwent focal ablative therapy. MRI exams were performed preoperatively, as well as one week and six months posttreatment. Rigid registration served as reference for assessing coregistration accuracy and precision. Results Segmentation of preoperative and postoperative prostate revealed a significant post-operative volume decrease of the gland that averaged 6.49 cc (p=0.017). Applying deformable transformation based upon Mutual Information (MI) from 120 pairs of MRI slices, we refined by 2.9 mm (max 6.25mm) the alignment of the ablation zone (AZ), segmented from contrastenhanced images on the one-week post-operative exam, to the 6-month postoperative T2-weighted images. This represented a 500% improvement over the rigid approach (p=0.001), corrected by volume. The dissimilarity by Dice index of the mapped AZ using deformable transformation vs. rigid control was significantly (p=0.04) higher at the ablation site compared to the whole gland. Conclusion Our findings illustrate our method's ability to correct for deformation at the ablation site. The preliminary analysis suggests that deformable transformation computed from MI of preoperative and follow-up MRI is accurate in co-registration of MRI exams performed before and after focal therapy. The ability to localize the previously ablated tissue in 3D space may improve targeting for image-guided follow-up biopsy within focal therapy protocols.

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Mapping of Transrectal Ultrasonographic Prostate Biopsies

Abstract: In addition to being a useful tool to improve the distribution of prostate biopsies, the potential of this system is above all the preparation of a detailed "map" of each patient showing biopsy zones without substantial changes in routine clinical practices.

Cited by 40 publications

References 7 publications

Geometric Evaluation of Systematic Transrectal Ultrasound Guided Prostate Biopsy

Geometric Evaluation of Systematic Transrectal Ultrasound Guided Prostate Biopsy

Prostate Cancer Risk Inflation as a Consequence of Image-targeted Biopsy of the Prostate: A Computer Simulation Study

3D Registration of mpMRI for Assessment of Prostate Cancer Focal Therapy

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