Role of endorectal MR imaging and MR spectroscopic imaging in defining treatable intraprostatic tumor foci in prostate cancer: quantitative analysis of imaging contour compared to whole-mount histopathology

Abstract

Purpose: To investigate the role of endorectal MR imaging and MR spectroscopic imaging in defining the contour of treatable intraprostatic tumor foci in prostate cancer, since targeted therapy requires accurate target volume definition.

Materials and methods: We retrospectively identified 20 patients with prostate cancer who underwent endorectal MR imaging and MR spectroscopic imaging prior to radical prostatectomy and subsequent creation of detailed histopathological tumor maps from whole-mount step sections. Two experienced radiologists independently reviewed all MR images and electronically contoured all suspected treatable (≥0.5 cm(3)) tumor foci. Deformable co-registration in MATLAB was used to calculate the margin of error between imaging and histopathological contours at both capsular and non-capsular surfaces and the treatment margin required to ensure at least 95% tumor coverage.

Results: Histopathology showed 17 treatable tumor foci in 16 patients, of which 8 were correctly identified by both readers and an additional 2 were correctly identified by reader 2. For all correctly identified lesions, both readers accurately identified that tumor contacted the prostatic capsule, with no error in contour identification. On the non-capsular border, the median distance between the imaging and histopathological contour was 1.4mm (range, 0-12). Expanding the contour by 5mm at the non-capsular margin included 95% of tumor volume not initially covered within the MR contour.

Conclusions: Endorectal MR imaging and MR spectroscopic imaging can be used to accurately contour treatable intraprostatic tumor foci; adequate tumor coverage is achieved by expanding the treatment contour at the non-capsular margin by 5mm.

Keywords: Dominant intraprostatic lesion; Dose escalation; Focal therapy; MRI; MRSI; Prostate cancer.

Figure 1

Figure 1A: Photomontage of axial T2-weighted MR image, overlaid MR spectral grid, and corresponding MR spectra array in a 62 year old with recently diagnosed Gleason 4+3 prostate cancer and a baseline serum prostate specific antigen level of 6.3 ng/mL. A large mass-like focus of reduced T2 signal intensity in the peripheral zone of the right mid-gland is associated with multiple voxels demonstrating high choline peaks (white arrows). This was considered a treatable tumor focus by both readers. The electronic contour generated by reader 1 is shown on the axial T2-weighted image. Figure 1B: Photomontage of whole mount step section slide, with tumor focus outlined, and the corresponding axial image from Figure 1A. Selected pairs of matching points have been selected along the outline of the prostate on both histopathological and MR images in MATLAB. Figure 1C: Photomontage of digitally extracted and matched tumor outlines on after deformable co-registration of histopathological and axial T2 images. The first image shows the histopathological tumor outline, the second image shows the MR tumor outline, and the final image shows the differences betlackween the two outlines (white indicates areas where the MR outline overestimated the tumor and white indicates areas where the MR outline underestimated the tumor). Figure 1D: Photomontage illustrating quantification of contour differences between histopathological and MR contours. Figure 1E: Quantification of differences in MRI and Path contours as a function of capsular and non-capsular borders.

Figure 2

This figure shows the distribution of the absolute error between the non-capsular border as drawn on MRI and delineated on the corresponding path slice, color-coded by patient. 647 arcs along the non-capsular edge are plotted, with 267 corresponding to points of MRI undercall. To encompass 95% of these 267 points, a margin of 5 mm on the non-capsular border is needed.