Rationale and objectives: Registration enables quantitative spatial correlation of features from different imaging modalities. Our objective is to register in vivo imaging with histologic sections of the human prostate so that histologic truth can be correlated with in vivo imaging features.
Materials and methods: In vivo imaging of the prostate included T2-weighted anatomic and diffusion weighted 3-T magnetic resonance imaging (MRI) as well as 11C-choline positron emission tomography (PET). In addition, ex vivo 3-T MRI of the prostate specimen, histology, and associated block face photos of the prostate specimen were obtained. A standard registration method based on mutual information (MI) and thin-plate spline (TPS) was applied. Registration among in vivo imaging modalities is well established; however, accurate registration involving histology is difficult. Our approach breaks up the difficult direct registration of histology and in vivo imaging into achievable subregistration tasks involving intermediate ex vivo modalities like block face photography and specimen MRI. Results of subregistration tasks are combined to compute the intended, final registration between in vivo imaging and histology.
Results: The methodology was applied to two patients and found to be clinically feasible. Overall registered anatomic MRI, diffusion MRI, and 11C-choline PET aligned well with histology qualitatively for both patients. There is no ground truth of registration accuracy as the scans are real patient scans. An indirect validation of the registration accuracy has been proposed comparing tumor boundary markings found in diffusion MRI and histologic sections. Registration errors for two patients between diffusion MRI and histology were 3.74 and 2.26 mm.
Conclusion: This proof of concept paper demonstrates a method based on intrinsic image information content for successfully registering in vivo imaging of the human prostate with its post-resection histology, which does not require the use of extrinsic fiducial markers. The methodology successfully mapped histology onto the in vivo imaging space, allowing the observation of how well different in vivo imaging features correspond to histologic truth. The methodology is therefore the basis for a systematic comparison of in vivo imaging for staging of human prostate cancer.