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Coregistration of Preoperative MRI with Ex Vivo Mesorectal Pathology Specimens to Spatially Map Post-treatment Changes in Rectal Cancer Onto In Vivo Imaging

Posted Jun 30, 2018 Updated Apr 10, 2023
By Jacob Antunes PhD , Satish Viswanath PhD , Justin T. Brady MD , Benjamin Crawshaw MD , Pablo Ros MD , Scott Steele MD , Conor P. Delaney MD , Raj Paspulati MD , Joseph Willis MD , Anant Madabhushi PhD
9 min read

Rationale and Objectives

The objective of this study was to develop and quantitatively evaluate a radiology-pathology fusion method for spatially mapping tissue regions corresponding to different chemoradiation therapy-related effects from surgically excised whole-mount rectal cancer histopathology onto preoperative magnetic resonance imaging (MRI).

Materials and Methods

This study included six subjects with rectal cancer treated with chemoradiation therapy who were then imaged with a 3-T T2-weighted MRI sequence, before undergoing mesorectal excision surgery. Excised rectal specimens were sectioned, stained, and digitized as two-dimensional (2D) whole-mount slides. Annotations of residual disease, ulceration, fibrosis, muscularis propria, mucosa, fat, inflammation, and pools of mucin were made by an expert pathologist on digitized slide images. An expert radiologist and pathologist jointly established corresponding 2D sections between MRI and pathology images, as well as identified a total of 10 corresponding landmarks per case (based on visually similar structures) on both modalities (five for driving registration and five for evaluating alignment). We spatially fused the in vivo MRI and ex vivo pathology images using landmark-based registration. This allowed us to spatially map detailed annotations from 2D pathology slides onto corresponding 2D MRI sections.

Results

Quantitative assessment of coregistered pathology and MRI sections revealed excellent structural alignment, with an overall deviation of 1.50 ± 0.63 mm across five expert-selected anatomic landmarks (in-plane misalignment of two to three pixels at 0.67- to 1.00-mm spatial resolution). Moreover, the T2-weighted intensity distributions were distinctly different when comparing fibrotic tissue to perirectal fat (as expected), but showed a marked overlap when comparing fibrotic tissue and residual rectal cancer.

Conclusions

Our fusion methodology enabled successful and accurate localization of post-treatment effects on in vivo MRI.

Introduction

Of the 40,000 patients diagnosed with rectal cancer in 2016 , most underwent neoadjuvant chemoradiation therapy before surgery. However, histopathologic analysis of the postsurgical specimens reveals that up to 27% of these patients had pathologic complete response to treatment , indicating they could have potentially avoided aggressive surgery. Current preoperative standard-of-care assessment is primarily based on T2-weighted (T2w) magnetic resonance imaging (MRI) for evaluation of treatment response and extent of tumor regression in vivo. Radiologists attempt to restage the tumor based on visual differences in grayscale contrast of soft tissue regions within and around the rectum. Although fibrotic tissue and rectal cancer may be different from a physiological perspective (different T2 relaxation times) , regions of benign treatment effects such as fibrosis, inflammation, and mucin pools typically have indistinguishable intensities from residual cancer on T2w MRI ( Fig 1 ) . Thus, experts tend to struggle in identifying patients with complete response (no residual disease and only fibrosis) via MRI, leading to possible overstaging in patients with rectal cancer .

Figure 1, Radiology and pathology images for a patient with rectal cancer who underwent chemoradiation therapy before surgical resection of the mesorectum. (a) 3-T T2-weighted magnetic resonance image of the rectum acquired after chemoradiation. (b) Expert radiologist delineation of estimated residual rectal cancer based on visual changes in magnetic resonance imaging pre- and post treatment. (c) Two-dimensional pathology slide of the same patient obtained after surgical removal of the rectum and surrounding the rectal tissue. (d) Expert pathologist delineation of varied treatment effects seen on the pathology image, which are not visually discernible on T2-weighted magnetic resonance imaging. Pathology report indicated that the patient had complete tumor response to radiation therapy (no residual rectal cancer).

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Materials and Methods

Data Description

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Acquisition of In Vivo MRI

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Digitization of Surgical Specimens and Annotation of Treatment Effects

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Identification of Corresponding Slices and Landmarks Between MRI and Pathology Sections

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Figure 2, Visualization and labeling of corresponding landmarks between modalities: (a) pathologist identification of anatomic landmarks on pathology section based on edges and folds along the inner or outer rectal wall, and (b) radiologist localization of corresponding edge and boundary landmarks on magnetic resonance imaging section (indicated by matching pairs of colored circles ). (Color version of figure is available online.)

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Coregistration of Radiology-Pathology to Spatially Map Detailed Annotations onto MRI

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Figure 3, Overall workflow for radiology-pathology coregistration to map pathologic annotations of chemoradiation treatment effects and residual disease onto magnetic resonance imaging.

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Evaluation of Coregistration Accuracy

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Figure 4, Strategy to qualitatively and quantitatively evaluate coregistration. Corresponding landmarks on (a) pathology slide and (b) T2w slices selected to drive coregistration. Independent set of five evaluation landmarks on (c) registered pathology and (d) T2w slice, with corresponding labels 1–5. Qualitative inspection of coregistration result involves (e) examining registered pathology slide image overlaid onto T2w slice image for alignment of known structures, (f) spatial comparison of corresponding landmarks used for (h) computing TRE, as well as (g) overlay of registered pathology annotations onto the T2w slice image, which was examined to ensure fidelity of mapped annotations. TRE, target registration error; T2w, T2-weighted.

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Results

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Figure 5, Results of coregistration for four different patients (one per row). (a, e, i, m) Original pathology slides with landmarks used for registration in different colors . (b, f, j, n) T2w slices and landmarks used for registration (in different colors ), corresponding to the pathology slide in the extreme left column. (c, g, k, o) Registered pathology image overlaid onto the T2w slice. (d, h, l, p) Detailed pathology annotations (with region labels in legend) spatially mapped onto the T2w slice . T2w, T2-weighted. (Color version of figure is available online.)

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Figure 6, (a) T2w image intensity distributions for annotated perirectal fat regions for all six patients (in different colors ). Five of the six patients show relatively similar fat intensity distributions, which suggest a successful spatial mapping of perirectal fat from pathology onto radiology. (b) Bar plots of average TREs across five evaluation landmarks for each patient, with error bars showing standard deviations. TRE, target registration error; T2w, T2-weighted. (Color version of figure is available online.)

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Figure 7, Side-by-side violin plots comparing T2w signal intensity distributions from the fibrosis region ( red ) and rectal cancer ( green ) to the perirectal fat region ( blue ) across all patients. The fibrosis region appears to have a signal intensity that is markedly different from that in the fat region, reflective of the accuracy in spatially mapping the pathology annotations onto the T2w images. This difference in signal intensities appears to be harder to discriminate in cases of poor response to treatment ( extreme right ) compared to complete response to treatment ( extreme left ). Additionally, the spatially mapped rectal cancer and fibrotic tissue annotations exhibit overlapping T2w signal intensity distributions, reflecting their overlapping visual appearance on T2w MRI. T2w, T2-weighted. (Color version of figure is available online.)

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Discussion

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TABLE 1

Comparison of Radiology-Pathology Coregistration Results to Relevant Literature

Reference Organ Fused Modalities Coregistration Method Number of Registration Landmarks (per Case) Number of Evaluation Landmarks (per Case) TRE (mm) Kimm et al. (2012) Prostate Ex vivo MRI-histology (2D) Injected fiducials 3 10–25 1.24 ± 0.59 Gibson et al. (2012) Prostate Ex vivo MRI-histology (2D) Injected fiducials 10 3–7 0.71 ± 0.38 Litjens et al. (2014) Prostate In vivo MRI-histology (2D) Thin-plate spline 7 Not performed Not performed Rusu et al. (2017) Lung nodules In vivo CT-histology reconstruction (3D) Rigid + nonrigid N/A 5–7 1.06 ± 0.40 This work Rectum In vivo MRI-histology (2D) Thin-plate spline 5–7 5 1.50 ± 0.63

2D, two-dimensional; 3D, three-dimensional; CT, computed tomography; MRI, magnetic resonance imaging; TRE, target registration error.

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Supplementary Data

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Figure S1

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Academic Radiology, Volume 25, Issue 7
Journals General Radiology
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