Retrospective comparison of direct in-bore magnetic resonance imaging (MRI)-guided biopsy and fusion-guided biopsy in patients with MRI lesions which are likely or highly likely to be clinically significant prostate cancer.

PURPOSE: To compare clinically significant prostate cancer (csPCa) detection rates between magnetic resonance imaging (MRI)-transrectal ultrasound (TRUS) fusion-guided prostate biopsy (FGB) and direct in-bore MRI-guided biopsy (MRGB). METHODS: We performed a comparison of csPCa detection rates between FGB and MRGB. Included patients had (1) at least one prior negative TRUS biopsy; (2) a Prostate Imaging Reporting and Data System (PI-RADS) 4 or 5 lesion and (3) a lesion size of ≥8 mm measured in at least one direction. We considered a Gleason score ≥7 being csPCa. Descriptive statistics with 95% confidence intervals (CI) were used to determine any differences. RESULTS: We included 51 patients with FGB (59 PI-RADS 4 and 41% PI-RADS 5) and 227 patients with MRGB (34 PI-RADS 4 and 66% PI-RADS 5). Included patients had a median age of 69 years (IQR, 65-72) and a median PSA level of 11.0 ng/ml (IQR, 7.4-15.1) and a median age of 67 years (IQR, 61-70), the median PSA 12.8 ng/ml (IQR, 9.1-19.0) within the FGB and the MRGB group, respectively. Detection rates of csPCA did not differ significantly between FGB and MRGB, 49 vs. 61%, respectively. CONCLUSION: We did not detect significant differences between FGB and MRGB in the detection of csPCa. The differences in detection ratios between both biopsy techniques are narrow with an increasing lesion size. This study warrants further studies to optimize selection of best biopsy modality.

Visibility of prostate cancer on transrectal ultrasound during fusion with multiparametric magnetic resonance imaging for biopsy.

OBJECTIVES: To determine transrectal ultrasound (TRUS) visibility of magnetic resonance (MR) lesions. METHODS: Data from 34 patients with 56 MR lesions and prostatectomy were used. Five observers localized and determined TRUS visibility during retrospective fusion. Visibility was correlated to Prostate Imaging-Reporting and Data System (PIRADS) and Gleason scores. RESULTS: TRUS visibility occurred in 43% of all MR lesions and in 62% of PIRADS 5 lesions. Visible lesions had a significantly lower localization variability. On prostatectomy, 58% of the TRUS-visible lesions had a Gleason 4 or 5 component. CONCLUSIONS: Almost half of the MR lesions were visible on TRUS. TRUS-visible lesions were more aggressive than TRUS-invisible lesions.

MR-targeted TRUS prostate biopsy using local reference augmentation: initial experience.

PURPOSE: To evaluate MR-targeted TRUS prostate biopsy using a novel local reference augmentation method. PATIENTS AND METHODS: Tracker-based MR-TRUS fusion was applied using local reference augmentation. In contrast to conventional whole gland fusion, local reference augmentation focuses the highest registration accuracy to the region surrounding the lesion to be biopsied. Pre-acquired multi-parametric MR images (mpMRI) were evaluated using PIRADS classification. T2-weighted MR images were imported on an ultrasound machine to allow for MR-TRUS fusion. Biopsies were targeted to the most suspicious lesion area identified on mpMRI. Each target was biopsied 1-5 times. For each biopsied lesion the diameter, PIRADS and Gleason scores, visibility during fusion, and representativeness were recorded. RESULTS: Included were 23 consecutive patients with 25 MR suspicious lesions, of which 11 patients had a previous negative TRUS-guided biopsy and 12 were biopsy naïve. The cancer detection rate was 64 % (Gleason score ≥6). Biopsy was negative (i.e., no Gleason score) in seven patients confirmed by follow-up in all of them (up to 18 months). After MR-TRUS fusion, 88 % of the lesions could be visualized on TRUS. The cancer detection rate increases with increasing lesion size, being 73 % for lesions larger than 10 mm. CONCLUSION: Tracker-based MR-TRUS fusion biopsy with local reference augmentation is feasible, especially for lesions with an MR maximum diameter of at least 10 mm or PIRADS 5 lesions. If this is not the case, we recommend in-bore MR-guided biopsy.

Biomechanical modeling constrained surface-based image registration for prostate MR guided TRUS biopsy.

PURPOSE: Adding magnetic resonance (MR)-derived information to standard transrectal ultrasound (TRUS) images for guiding prostate biopsy is of substantial clinical interest. A tumor visible on MR images can be projected on ultrasound (US) by using MR-US registration. A common approach is to use surface-based registration. The authors hypothesize that biomechanical modeling will better control deformation inside the prostate than a regular nonrigid surface-based registration method. The authors developed a novel method by extending a nonrigid surface-based registration algorithm with biomechanical finite element (FE) modeling to better predict internal deformations of the prostate. METHODS: Data were collected from ten patients and the MR and TRUS images were rigidly registered to anatomically align prostate orientations. The prostate was manually segmented in both images and corresponding surface meshes were generated. Next, a tetrahedral volume mesh was generated from the MR image. Prostate deformations due to the TRUS probe were simulated using the surface displacements as the boundary condition. A three-dimensional thin-plate spline deformation field was calculated by registering the mesh vertices. The target registration errors (TREs) of 35 reference landmarks determined by surface and volume mesh registrations were compared. RESULTS: The median TRE of a surface-based registration with biomechanical regularization was 2.76 (0.81-7.96) mm. This was significantly different than the median TRE of 3.47 (1.05-7.80) mm for regular surface-based registration without biomechanical regularization. CONCLUSIONS: Biomechanical FE modeling has the potential to improve the accuracy of multimodal prostate registration when comparing it to a regular nonrigid surface-based registration algorithm and can help to improve the effectiveness of MR guided TRUS biopsy procedures.

Evaluation of prostate segmentation algorithms for MRI: the PROMISE12 challenge.

Prostate MRI image segmentation has been an area of intense research due to the increased use of MRI as a modality for the clinical workup of prostate cancer. Segmentation is useful for various tasks, e.g. to accurately localize prostate boundaries for radiotherapy or to initialize multi-modal registration algorithms. In the past, it has been difficult for research groups to evaluate prostate segmentation algorithms on multi-center, multi-vendor and multi-protocol data. Especially because we are dealing with MR images, image appearance, resolution and the presence of artifacts are affected by differences in scanners and/or protocols, which in turn can have a large influence on algorithm accuracy. The Prostate MR Image Segmentation (PROMISE12) challenge was setup to allow a fair and meaningful comparison of segmentation methods on the basis of performance and robustness. In this work we will discuss the initial results of the online PROMISE12 challenge, and the results obtained in the live challenge workshop hosted by the MICCAI2012 conference. In the challenge, 100 prostate MR cases from 4 different centers were included, with differences in scanner manufacturer, field strength and protocol. A total of 11 teams from academic research groups and industry participated. Algorithms showed a wide variety in methods and implementation, including active appearance models, atlas registration and level sets. Evaluation was performed using boundary and volume based metrics which were combined into a single score relating the metrics to human expert performance. The winners of the challenge where the algorithms by teams Imorphics and ScrAutoProstate, with scores of 85.72 and 84.29 overall. Both algorithms where significantly better than all other algorithms in the challenge (p<0.05) and had an efficient implementation with a run time of 8min and 3s per case respectively. Overall, active appearance model based approaches seemed to outperform other approaches like multi-atlas registration, both on accuracy and computation time. Although average algorithm performance was good to excellent and the Imorphics algorithm outperformed the second observer on average, we showed that algorithm combination might lead to further improvement, indicating that optimal performance for prostate segmentation is not yet obtained. All results are available online at http://promise12.grand-challenge.org/.

Simulated required accuracy of image registration tools for targeting high-grade cancer components with prostate biopsies.

OBJECTIVES: To estimate the required spatial alignment accuracy for correctly grading 95 % of peripheral zone (PZ) prostate cancers using a system for multiparametric magnetic resonance (MR)-guided ultrasound (US) biopsies. METHODS: PZ prostate tumours were retrospectively annotated on multiparametric MR series using prostatectomy specimens as reference standard. Tumours were grouped based on homogeneous and heterogeneous apparent diffusion coefficient (ADC) values using an automated ADC texture analysis method. The proportion of heterogeneous tumours containing a distinct, high Gleason grade tumour focus yielding low ADC values was determined. Both overall tumour and high-grade focal volumes were calculated. All high-grade target volumes were then used in a simulated US biopsy system with adjustable accuracy to determine the hit rate. RESULTS: An ADC-determined high-grade tumour focus was found in 63 % of the PZ prostate tumours. The focal volumes were significantly smaller than the total tumour volumes (median volume of 0.3 ml and 1.1 ml respectively). To correctly grade 95 % of the aggressive tumour components the target registration error (TRE) should be smaller than 1.9 mm. CONCLUSIONS: To enable finding the high Gleason grade component in 95 % of PZ prostate tumours with MR-guided US biopsies, a technical registration accuracy of 1.9 mm is required. KEY POINTS: • MRI can identify foci of prostatic cancer with reduced apparent diffusion coefficients • Sixty-three per cent of prostatic peripheral zone tumours contain high-grade tumour low ADC foci • The median volume of such foci is 0.3 ml • Biopsy targets are significantly smaller than whole tumour volumes • Simulated registration accuracy is 1.9 mm for correctly grading 95 % of tumours.

A pattern recognition approach to zonal segmentation of the prostate on MRI.

Zonal segmentation of the prostate into the central gland and peripheral zone is a useful tool in computer-aided detection of prostate cancer, because occurrence and characteristics of cancer in both zones differ substantially. In this paper we present a pattern recognition approach to segment the prostate zones. It incorporates three types of features that can differentiate between the two zones: anatomical, intensity and texture. It is evaluated against a multi-parametric multi-atlas based method using 48 multi-parametric MRI studies. Three observers are used to assess inter-observer variability and we compare our results against the state of the art from literature. Results show a mean Dice coefficient of 0.89 +/- 0.03 for the central gland and 0.75 +/- 0.07 for the peripheral zone, compared to 0.87 +/- 0.04 and 0.76 +/- 0.06 in literature. Summarizing, a pattern recognition approach incorporating anatomy, intensity and texture has been shown to give good results in zonal segmentation of the prostate.

The alpha-motoneuron pool as transmitter of rhythmicities in cortical motor drive.

OBJECTIVE: Investigate the effectiveness and frequency dependence of central drive transmission via the alpha-motoneuron pool to the muscle. METHODS: We describe a model for the simulation of alpha-motoneuron firing and the EMG signal as response to central drive input. The transfer in the frequency domain is investigated. Coherence between stochastical central input and EMG is also evaluated. RESULTS: The transmission of central rhythmicities to the EMG signal relates to the spectral content of the latter. Coherence between central input to the alpha-motoneuron pool and the EMG signal is significant whereby the coupling strength hardly depends on the frequency in a range from 1 to 100 Hz. Common central input to pairs of alpha-motoneurons strongly increases the coherence levels. The often-used rectification of the EMG signal introduces a clear frequency dependence. CONCLUSIONS: Oscillatory phenomena are strongly transmitted via the alpha-motoneuron pool. The motoneuron firing frequencies do play a role in the transmission gain, but do not influence the coherence levels. Rectification of the EMG signal enhances the transmission gain, but lowers coherence and introduces a strong frequency dependency. We think that it should be avoided. SIGNIFICANCE: Our findings show that rhythmicities are translated into alpha-motoneuron activity without strong non-linearities.