Semi‐automatic deformable registration of prostate MR images to pathological slices

Abstract

Purpose: To present a semi-automatic deformable registration algorithm for co-registering T2-weighted (T2w) images of the prostate with whole-mount pathological sections of prostatectomy specimens. Materials and Methods:Twenty-four patients underwent 1.5 Tesla (T) endorectal MR imaging before radical prostatectomy with whole-mount step-section pathologic analysis of surgical specimens. For each patient, the T2w imaging containing the largest area of tumor was manually matched with the corresponding pathologic slice. The prostate was co-registered using a free-form deformation (FFD) algorithm based on B-splines. Registration quality was assessed through differences between prostate diameters measured in right-left (RL) and anteroposterior (AP) directions on T2w images and pathologic slices and calculation of the Dice similarity coefficient, D, for the whole prostate (WP), the peripheral zone (PZ) and the transition zone (TZ).Results: The mean differences in diameters measured on pathology and MR imaging in the RL direction and the AP direction were 0.49 cm and À0.63 cm, respectively, before registration and 0.10 cm and À0.11 cm, respectively, after registration. The mean D values for the WP, PZ and TZ, were 0.76, 0.65, and 0.77, respectively, before registration and increased to 0.91, 0.76, and 0.85, respectively, after registration. The improvements in D were significant for all three tissues (P < 0.001 for all). Conclusion:The proposed semi-automatic method enabled successful co-registration of anatomical prostate MR images to pathologic slices.

Imaging of prostate cancer: a platform for 3D co-registration of in-vivo MRI ex-vivo MRI and pathology

“…visual approach to correlate in-vivo images with histopathology 2 . A recent study of Mazaheri et al 12 demonstrated how to automate this process with deformable 2D image co-registration. However.…”

“…Mazaheri et al 12 developed a methodology to co-register histology sections with T2W MR acquired using an endorectal coil. This approach used a deformable algorithm and the method of moments, and reported good accuracy.…”

Computer-aided Detection of Prostate Cancer with MRI

“…Mazaheri et al. describe a semi-automatic method by using a free-form deformation (FFD) algorithm based on B-splines [125]. This method enabled successful registration of anatomical prostate MR images to pathologic slices.…”

Improved Magnetic Resonance Imaging-Pathology Correlation With Imaging-Derived, 3D-Printed, Patient-Specific Whole-Mount Molds of the Prostate

“…Secondly, we analyzed a single slice rather than the entire gland; the differences observed in that one slice may not preserve a linear relationship with the differences observed should the entire gland had been analyzed. Additionally, while PSMs pursue image registration based on direct anatomical similarity, different strategies using software-based algorithms have been proposed by other groups 23–25 and have not been compared to the PSM approach. Although we presented an example of how the cost of the technology has been decreasing, we did not objectively perform a cost analysis of this technique.…”