Yipeng Hu

Characterizing Clinically Significant Prostate Cancer Using Template Prostate Mapping Biopsy

PURPOSE Definitions of prostate cancer risk are limited since accurate attribution of the cancer grade and burden is not possible due to the random and systematic errors associated with transrectal ultrasound guided biopsy. Transperineal prostate mapping biopsy may have a role in accurate risk stratification. We defined the transperineal prostate mapping biopsy characteristics of clinically significant disease. MATERIALS AND METHODS A 3-dimensional model of each gland and individual cancer was reconstructed using 107 radical whole mount specimens. We performed 500 transperineal prostate mapping simulations per case by varying needle targeting errors to calculate sensitivity, specificity, and negative and positive predictive value to detect lesions 0.2 ml or greater, or 0.5 ml or greater. Definitions of clinically significant cancer based on a combination of Gleason grade and cancer burden (cancer core length) were derived. RESULTS Mean±SD patient age was 61±6.4 years (range 44 to 74) and mean prostate specific antigen was 9.7±5.9 ng/ml (range 0.8 to 36.2). We reconstructed 665 foci. The total cancer core length from all positive biopsies for a particular lesion that detected more than 95% of lesions 0.5 ml or greater and 0.2 ml or greater was 10 mm or greater and 6 mm or greater, respectively. The maximum cancer core length that detected more than 95% of lesions 0.5 ml or greater and 0.2 ml or greater was 6 mm or greater and 4 mm or greater, respectively. We combined these cancer burden thresholds with dominant and nondominant Gleason pattern 4 to derive 2 definitions of clinically significant disease. CONCLUSIONS Transperineal prostate mapping may provide an effective method to risk stratify men with localized prostate cancer. The definitions that we present require prospective validation.

The Accuracy of Different Biopsy Strategies for the Detection of Clinically Important Prostate Cancer: A Computer Simulation

PURPOSE The true accuracy of different biopsy strategies for detecting clinically significant prostate cancer is unknown, given the positive evaluation bias required for verification by radical prostatectomy. To evaluate how well different biopsy strategies perform at detecting clinically significant prostate cancer we used computer simulation in cystoprostatectomy cases with cancer. MATERIALS AND METHODS A computer simulation study was performed on prostates acquired at radical cystoprostatectomy. A total of 346 prostates were processed and examined for prostate cancer using 3 mm whole mount slices. The 96 prostates that contained cancer were digitally reconstructed. Biopsy simulations incorporating various degrees of random localization error were performed using the reconstructed 3-dimensional prostate computer model. Each biopsy strategy was simulated 500 times. Two definitions of clinically significant prostate cancer were used to define the reference standard, including definition 1--Gleason score 7 or greater, and/or lesion volume 0.5 ml or greater and definition 2--Gleason score 7 or greater, and/or lesion volume 0.2 ml or greater. RESULTS A total of 215 prostate cancer foci were present. The ROC AUC to detect and rule out definition 1 prostate cancer was 0.69, 0.75, 0.82 and 0.91 for 12-core transrectal ultrasound biopsy with a random localization error of 15 and 10 mm, 14-core transrectal ultrasound biopsy and template prostate mapping using a 5 mm sampling frame, respectively. CONCLUSIONS To our knowledge our biopsy simulation study is the first to evaluate the performance of different sampling strategies to detect clinically important prostate cancer in a population that better reflects the demographics of a screened cohort. Compared to other strategies standard transrectal ultrasound biopsy performs poorly for detecting clinically important cancer. Marginal improvement can be achieved using additional cores placed anterior but the performance attained by template prostate mapping is optimal.

A biopsy simulation study to assess the accuracy of several transrectal ultrasonography (TRUS)‐biopsy strategies compared with template prostate mapping biopsies in patients who have undergone radical prostatectomy

Study Type – Diagnostic (validating cohort)

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

Background Prostate 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. Objective To 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 participants A 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 analysis Sensitivity 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 limitations When 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. Conclusions Image-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.

Modelling Prostate Motion for Data Fusion During Image-Guided Interventions

There is growing clinical demand for image registration techniques that allow multimodal data fusion for accurate targeting of needle biopsy and ablative prostate cancer treatments. However, during procedures where transrectal ultrasound (TRUS) guidance is used, substantial gland deformation can occur due to TRUS probe pressure. In this paper, the ability of a statistical shape/motion model, trained using finite element simulations, to predict and compensate for this source of motion is investigated. Three-dimensional ultrasound images acquired on five patient prostates, before and after TRUS-probe-induced deformation, were registered using a nonrigid, surface-based method, and the accuracy of different deformation models compared. Registration using a statistical motion model was found to outperform alternative elastic deformation methods in terms of accuracy and robustness, and required substantially fewer target surface points to achieve a successful registration. The mean final target registration error (based on anatomical landmarks) using this method was 1.8 mm. We conclude that a statistical model of prostate deformation provides an accurate, rapid and robust means of predicting prostate deformation from sparse surface data, and is therefore well-suited to a number of interventional applications where there is a need for deformation compensation.

The PICTURE study — Prostate Imaging (multi-parametric MRI and Prostate HistoScanning™) Compared to Transperineal Ultrasound guided biopsy for significant prostate cancer Risk Evaluation

OBJECTIVE The primary objective of the PICTURE study is to assess the negative predictive value of multi-parametric MRI (mp-MRI) and Prostate HistoScanning™ (PHS) in ruling-out clinically significant prostate cancer. PATIENTS AND METHODS PICTURE is a prospective diagnostic validating cohort study conforming to level 1 evidence. PICTURE will assess the diagnostic performance of multi-parametric Magnetic Resonance Imaging (mp-MRI) and Prostate HistoScanning™ (PHS) ultrasound. PICTURE will involve validating both index tests against a reference test, transperineal Template Prostate Mapping (TPM) biopsies, which can be applied in all men under evaluation. Men will be blinded to the index test results and both index tests will be reported prospectively prior to the biopsies being taken to ensure reporter blinding. Paired analysis of each of the index tests to the reference test will be done at patient level. Those men with an imaging lesion will undergo targeted biopsies to assess the clinical utility of sampling only suspicious areas. The study is powered to assess the negative predictive value of these imaging modalities in ruling-out clinically significant prostate cancer. DISCUSSION The PICTURE study aims to assess the performance characteristics of two imaging modalities (mp-MRI and Prostate HistoScanning) for their utility in the prostate cancer pathway. PICTURE aims to identify if either imaging test may be useful for ruling out clinically significant disease in men under investigation, and also to examine if either imaging modality is useful for the detection of disease. Recruitment is underway and expected to complete in 2014.

Image‐directed, tissue‐preserving focal therapy of prostate cancer: a feasibility study of a novel deformable magnetic resonance‐ultrasound (MR‐US) registration system

To evaluate the feasibility of using computer‐assisted, deformable image registration software to enable three‐dimensional (3D), multi‐parametric (mp) magnetic resonance imaging (MRI)‐derived information on tumour location and extent, to inform the planning and conduct of focal high‐intensity focused ultrasound (HIFU) therapy.

MR to Ultrasound Image Registration for Guiding Prostate Biopsy and Interventions

A method is described for registering preoperative magnetic resonance (MR) to intraoperative transrectal ultrasound (TRUS) images of the prostate gland. A statistical motion model (SMM) of the prostate is first built using training data provided by biomechanical simulations of the motion of a patient-specific finite element model, derived from a preoperative MR image. The SMM is then registered to a 3D TRUS image by maximising the likelihood of the shape of an SMM instance given a voxel-intensity-based feature, which represents an estimate of normal vector at the surface of the prostate gland. Using data acquired from 7 patients, the accuracy of registering T2 MR to 3D TRUS images was evaluated using anatomical landmarks inside the gland. The results show that the proposed registration method has a root-mean-square target registration error of 2.66 mm.

The PICTURE study: diagnostic accuracy of multiparametric MRI in men requiring a repeat prostate biopsy

Background:Transrectal prostate biopsy has limited diagnostic accuracy. Prostate Imaging Compared to Transperineal Ultrasound-guided biopsy for significant prostate cancer Risk Evaluation (PICTURE) was a paired-cohort confirmatory study designed to assess diagnostic accuracy of multiparametric magnetic resonance imaging (mpMRI) in men requiring a repeat biopsy.Methods:All underwent 3 T mpMRI and transperineal template prostate mapping biopsies (TTPM biopsies). Multiparametric MRI was reported using Likert scores and radiologists were blinded to initial biopsies. Men were blinded to mpMRI results. Clinically significant prostate cancer was defined as Gleason ⩾4+3 and/or cancer core length ⩾6 mm.Results:Two hundred and forty-nine had both tests with mean (s.d.) age was 62 (7) years, median (IQR) PSA 6.8 ng ml (4.98–9.50), median (IQR) number of previous biopsies 1 (1–2) and mean (s.d.) gland size 37 ml (15.5). On TTPM biopsies, 103 (41%) had clinically significant prostate cancer. Two hundred and fourteen (86%) had a positive prostate mpMRI using Likert score ⩾3; sensitivity was 97.1% (95% confidence interval (CI): 92–99), specificity 21.9% (15.5–29.5), negative predictive value (NPV) 91.4% (76.9–98.1) and positive predictive value (PPV) 46.7% (35.2–47.8). One hundred and twenty-nine (51.8%) had a positive mpMRI using Likert score ⩾4; sensitivity was 80.6% (71.6–87.7), specificity 68.5% (60.3–75.9), NPV 83.3% (75.4–89.5) and PPV 64.3% (55.4–72.6).Conclusions:In men advised to have a repeat prostate biopsy, prostate mpMRI could be used to safely avoid a repeat biopsy with high sensitivity for clinically significant cancers. However, such a strategy can miss some significant cancers and overdiagnose insignificant cancers depending on the mpMRI score threshold used to define which men should be biopsied.

NiftySim: A GPU-based nonlinear finite element package for simulation of soft tissue biomechanics

PurposeNiftySim, an open-source finite element toolkit, has been designed to allow incorporation of high-performance soft tissue simulation capabilities into biomedical applications. The toolkit provides the option of execution on fast graphics processing unit (GPU) hardware, numerous constitutive models and solid-element options, membrane and shell elements, and contact modelling facilities, in a simple to use library.MethodsThe toolkit is founded on the total Lagrangian explicit dynamics (TLEDs) algorithm, which has been shown to be efficient and accurate for simulation of soft tissues. The base code is written in C