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Purpose: MRI-targeted, 3D transrectal ultrasound (TRUS)-guided prostate biopsy aims to reduce the 21–47% false negative rate1 of clinical 2D TRUS-guided sextant biopsy, but still has a substantial false negative rate. This could be improved via biopsy needle target optimization, accounting for uncertainties due to guidance system errors and image registration errors. As an initial step toward this broader goal, we elucidated the impact of biopsy needle delivery error on the probability of obtaining tumour samples and on core involvement. These are both important parameters to patient risk stratification and treatment decision. Methods: We investigated this for cancer of all grades, and separately for intermediate/high grade (≥Gleason 4+3) cancer. We used expert-contoured gold-standard prostatectomy histology to simulate targeted biopsies using an isotropic Gaussian needle delivery error from 1 to 6 mm, and investigated the amount of cancer obtained in each biopsy core as determined by histology. Results: Needle delivery error resulted in core involvement variability that could influence treatment decisions; the presence or absence of cancer in 1/3 or more of each needle core can be attributed to needle delivery error of 4 mm (as observed in practice2). Conclusions: Repeated biopsies of the same tumour target can yield percent core involvement measures with sufficient variability to influence the decision between active surveillance and treatment. However, this may be mitigated by making more than one biopsy attempt at selected tumour targets.

Purpose: Evaluation ofin vivo prostate imaging modalities for determining the spatial distribution and aggressiveness of prostate cancer ideally requires accurate registration of images to an accepted reference standard, such as histopathological examination of radical prostatectomy specimens. Three-dimensional (3D) reconstruction of prostate histology facilitates these registration-based evaluations by reintroducing 3D spatial information lost during histology processing. Because the reconstruction accuracy may constrain the clinical questions that can be answered with these data, it is important to assess the tradeoffs between minimally disruptive methods based on intrinsic image information and potentially more robust methods based on extrinsic fiducial markers. Methods: Ex vivo magnetic resonance (MR) images and digitized whole-mount histology images from 12 radical prostatectomy specimens were used to evaluate four 3D histology reconstruction algorithms. 3D reconstructions were computed by registering each histology image to the corresponding ex vivo MR image using one of two similarity metrics (mutual information or fiducial registration error) and one of two search domains (affine transformations or a constrained subset thereof). The algorithms were evaluated for accuracy using the mean target registration error (TRE) computed from homologous intrinsic point landmarks (3–16 per histology section; 232 total) identified on histology and MR images, and for the sensitivity of TRE to rotational, translational, and scaling initialization errors. Results: The algorithms using fiducial registration error and mutual information had mean ± standard deviation TREs of 0.7 ± 0.4 and 1.2 ± 0.7 mm, respectively, and one algorithm using fiducial registration error and affine transforms had negligible sensitivities to initialization errors. The postoptimization values of the mutual information-based metric showed evidence of errors due to both the optimizer and the similarity metric, and variation of parameters of the mutual information-based metric did not improve its performance. Conclusions: The extrinsic fiducial-based algorithm had lower mean TRE and lower sensitivity to initialization than the intrinsic intensity-based algorithm using mutual information. A model relating statistical power to registration error for certain imaging validation study designs estimated that a reconstruction algorithm with a mean TRE of 0.7 mm would require 27% fewer subjects than the method used to initialize the algorithms (mean TRE 1.3 ± 0.7 mm), suggesting the choice of reconstruction technique can have a substantial impact on the design of imaging validation studies, and on their overall cost.

Purpose: An accurate determination of stage and grade from in vivo prostate cancerimaging would support improved biopsy guidance, therapy selection and, possibly, focal therapy guidance. Validation of prostate cancerimaging modalities ideally requires accurate registration of in vivo imaging to histopathology, where accurate diagnoses can be made. An important intermediate component of this registration aligns ex vivo imaging to histology. This work describes and evaluates a simplified approach, developed in our laboratory, to the registration of digital prostate histopathology to ex vivo magnetic resonance(MR)images. Our approach obviates three elements typical of existing methods: (1) guidance of specimen slicing, (2) imaging/photography of sliced tissue blocks, and (3) dependence on the appearance of salient structures within the image to guide registration. Methods: Six resected prostate specimens were marked with strand‐shaped fiducials, imaged with T1‐ and T2‐weighted MRI before and after image‐guided specimen slicing, and then processed for histology as whole mount specimens. Direct fiducial‐based registration from histology to whole specimen ex vivo MRI was performed by establishing a correspondence between fiducial cross‐sections on histology and fiducial space curves on whole specimen MRI. The target registration error (TRE) of 93 intrinsic landmarks across 21 histology images was calculated for this method, for an indirect registration using tissue block MRI and for a registration based on image‐guidance of slicing. Results: The image‐guided, indirect and direct registrations yielded TREs of 1.2 mm, 0.8 mm and 0.8 mm respectively. A two‐tail paired t‐test failed to show a significant difference between direct and indirect registration mean TREs (p = 0.8, 95% confidence interval, −0.08 to 0.10 mm), and showed that both TREs were lower than that of the image‐guided registration (p = 0.0001). Conclusions: The direct registration is a suitable replacement for existing, more complex registration methods for aligning histopathology to ex vivo imaging.

Early and accurate diagnosis of prostate cancer enables minimally invasive therapies to cure the cancer with less morbidity. The purpose of this work is to non‐rigidly register in vivo pre‐prostatectomy prostate medical images to regionally‐graded histopathology images from post‐prostatectomy specimens, seeking a relationship between the multi parametric imaging and cancer distribution and aggressiveness. Our approach orients the physical slicing of the specimen to be parallel to the in vivoimaging planes, yielding a tractable 2D registration problem solved using a thin‐plate spline method. Our technique is as follows: (1) apply a set of novel fiducial markers, visible on ex vivo MR and digital histopathology images; (2) use a magnetically tracked probe to localize the fiducials on the specimen and register the in vivoimaging plane orientation to the specimen space via a collected ex vivo MR image, specifying the insertion points of three pins on the desired specimen cutting plane; (3) use the pins to orient the specimen in a slotted forceps for slicing along the desired plane orientation. We measure slicing accuracy using a high‐resolution (12.7 micron precision) mechanically‐tracked probe. We measured a target registration error of 0.85 mm, a mean slicing plane marking error of 0.7 mm, and a mean slicing error of 0.6 mm; these results compare favourably with our 2.2 mm diagnostic MR image thickness. Qualitative evaluation of in vivoimaging‐histopathology fusion reveals excellent anatomic concordance, including alignment between suspicious regions on MR and cancerous regions on digital histopathology. Declaration of concurrent submission: A full‐length submission of this work has been made to Medical Image Computing and Computer‐Assisted Intervention (MICCAI) 2010 (which has only a 20% acceptance rate), and a reduced version to AAPM 2010. We would like to request the permission of the Scientific Program Directors to share this work with the Canadian medial physics research community at COMP 2010.

Purpose: To non‐rigidly register in vivo prostate medical images to regionally‐graded digital histopathology (DH) images in order to determine a relationship between in vivo fused multi‐parametric imaging and prostate cancer aggressiveness. This is a challenge due to varying prostate deformations induced by the different imaging modalities and distortion during formalin fixation and histological processing. Method and Materials: We are collecting in vivo MR CT and ultrasoundimages as well as whole‐mount DH images at 5 mm increments from 36 RP patients. Our approach orients the physical slicing of the specimen to be parallel to the in vivoimaging planes yielding a tractable 2D registration problem solved using a thin‐plate spline method. Our technique is as follows: (1) apply a set of novel fiducial markers visible on ex vivo MR and DH images; (2) use a magnetically tracked probe to localize the fiducials on the specimen and register the in vivoimaging plane orientation to the specimen space via a collected ex vivo MR image specifying the insertion points of three pins on the desired specimen cutting plane; (3) use the pins to orient the specimen in a slotted forceps for slicing along the desired plane orientation. We measure slicing accuracy using a high‐resolution (12.7 micron precision) mechanically‐tracked probe. Results: Qualitative evaluation reveals excellent anatomic concordance between in vivo MR images and DH images including alignment between suspicious regions on MR and confirmed cancerous regions on DH. The mean distance of the actual specimen slicing plane to the desired plane given by the inserted pins is 0.6 mm comparing favorably with the 2.2 mm in vivo MR slice thickness. Conclusion: This work suggests our method's potential to accurately orient physical specimen slicing to be parallel to in vivoimaging planes yielding useful anatomic concordance between registered in vivo and DH images.

Purpose: The usefulness of three‐dimensional (3D) high‐frequency ultrasound as a tool to monitor tumor progression in a genetically engineered mouse model of prostate cancer was investigated. Method and Materials: A genetically engineered mouse model (PSP94 gene‐directed transgenic mouse adenocarcinoma of the prostate) was used that spontaneously developed prostate tumors. Mice were imaged with a commercial high‐frequency ultrasound system including 3D imaging, power Doppler, and 3D power Doppler capabilities. Primary and metastatic tumor detection was confirmed by gross pathology and histology. Primary tumors were imaged longitudinally to monitor growth. Power Doppler was used to investigate blood vessel formation within tumors.Results: Primary tumors could be detected while still small (under 2.5 mm in diameter) and imaged repeatedly as they grew. Tumors were manually segmented in 3D images to measure volumes. Exponential growth curves fit the measured tumor volumes well (r2=0.939 to 0.986) even though the estimated growth rate constants (0.054 to 0.143 days−1) were markedly different. Examples of metastatic tumors were also detected, including a liver and a lymph node metastasis. Initial 3D power Doppler reconstructions showed intratumor vessels approximately 150 □m in diameter. Conclusion: High‐frequency ultrasound can be used for longitudinal studies of volume and vasculature development of prostate tumors in genetically engineered mice. Ultrasound is a promising technique for assessing treatment responses in preclinical trials of prostate cancer therapies. Conflict of Interest: VisualSonics, the manufacturer of the ultrasound system, has licensed 3D reconstruction, visualization, and segmentation software from our laboratory.