Prostate: Registration of Digital Histopathologic Images to in Vivo MR Images Acquired by Using Endorectal Receive Coil

Ward, Aaron D.; Crukley, Cathie; McKenzie, Charles A.; Montreuil, Jacques; Gibson, Eli; Romagnoli, Cesare; Gómez, José A.; Moussa, Madeleine; Chin, Joseph L.; Bauman, Glenn; Fenster, Aaron

doi:10.1148/radiol.12102294

Cited by 65 publications

(79 citation statements)

References 27 publications

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“…The works [6], [7] involve placement of fiducial markers into the ex vivo specimen, in order to guide its sectioning along the imaging plane with a magnetically tracked probe, while [8] employs such markers to fit affine transformations between histological slices and the specimen. These methods achieve good registration results, but require a special setup, and additional clinical time and approvals that may not be available in practice.…”

Section: B Related Workmentioning

confidence: 99%

Registration of Whole-Mount Histology and Volumetric Imaging of the Prostate Using Particle Filtering

Nir

Sahebjavaher

Kozłowski

et al. 2014

IEEE Trans. Med. Imaging

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Registration of histological slices to volumetric imaging of the prostate is an important task that can be used to optimize imaging for cancer detection. Such registration is challenging due to physical changes of the specimen during excision and fixation, and misalignment of the histological slices during preparation and digital scanning. In this work, we consider a multi-slice to volume registration method in which a stack of sparse, unaligned 2-D whole-mount histological slices is registered to a 3-D volumetric imaging of the prostate. We propose a particle filtering framework to contend with the high dimensionality of the search space and multimodal nature of the optimization. Such framework allows modeling of the uncertainty in the pose of the slices and in the imaged information, in order to derive optimal registration parameters in a Bayesian approach. Intensity-, region-, and point-based similarity metrics were incorporated into the registration algorithm to account for different imaging modalities. We demonstrate and evaluate our method on a diverse set of data that includes a synthetic volume, ex vivo and in vivo magnetic resonance imaging, and in vivo ultrasound.

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Section: B Related Workmentioning

confidence: 99%

Registration of Whole-Mount Histology and Volumetric Imaging of the Prostate Using Particle Filtering

Nir

Sahebjavaher

Kozłowski

et al. 2014

IEEE Trans. Med. Imaging

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“…Currently, this information can only be definitively determined after a total mesorectal excision of the rectum and surrounding fat, when histologic slides of the rectal tissue are evaluated for residual disease and treatment effects (7). If one could coregister these pathologic specimens with corresponding preoperative MRI and bring them into spatial correspondence (8), different pathologic regions (eg, fibrosis, inflammation, and residual disease) could be rigorously mapped onto MRI. This method could, in turn, be utilized to build a definitive “learning set” for machine-based learning of computerized imaging features, which could enable accurate post-treatment evaluation of tumor regression on MRI.…”

Section: Introductionmentioning

confidence: 99%

“…The use of spatial coregistration methods for mapping pathologic annotations onto imaging has been previously performed by several groups, most popularly in the context of prostate cancer. Applications explored have included mapping disease extent onto diagnostic MRI (8,11–14), as well as mapping treatment effects and residual disease onto post-treatment MRI (15). …”

Section: Introductionmentioning

confidence: 99%

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

Antunes¹,

Viswanath²,

Brady³

et al. 2018

Academic Radiology

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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.

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“…5 Whole-mount histopathology has been used to acquire crosssectional images of complete breast 6 and prostate 7,8 specimens, and several semiautomated methods for reconstructing 3-D prostate histology volumes have been proposed. [9][10][11] We are particularly interested in generating 3-D volumes from breast tumor specimens as it is known that 3-D features such as tumor margin, focality, and extent all have prognostic significance. 5 This is, however, a significantly more challenging task than in the prostate for two main reasons.…”

Section: Introductionmentioning

confidence: 99%

Optimized SIFTFlow for registration of whole-mount histology to reference optical images

Shojaii

Martel

2016

J. Med. Imag

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Abstract. The registration of two-dimensional histology images to reference images from other modalities is an important preprocessing step in the reconstruction of three-dimensional histology volumes. This is a challenging problem because of the differences in the appearances of histology images and other modalities, and the presence of large nonrigid deformations which occur during slide preparation. This paper shows the feasibility of using densely sampled scale-invariant feature transform (SIFT) features and a SIFTFlow deformable registration algorithm for coregistering whole-mount histology images with blockface optical images. We present a method for jointly optimizing the regularization parameters used by the SIFTFlow objective function and use it to determine the most appropriate values for the registration of breast lumpectomy specimens. We demonstrate that tuning the regularization parameters results in significant improvements in accuracy and we also show that SIFTFlow outperforms a previously described edge-based registration method. The accuracy of the histology images to blockface images registration using the optimized SIFTFlow method was assessed using an independent test set of images from five different lumpectomy specimens and the mean registration error was 0.32 AE 0.22 mm. © The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

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Prostate: Registration of Digital Histopathologic Images to in Vivo MR Images Acquired by Using Endorectal Receive Coil

Abstract: This method for the registration of prostate digital histopathologic images to in vivo MR images acquired by using an endorectal receive coil was sufficiently accurate for coregistering the smallest clinically important lesions with 95% confidence.

Cited by 65 publications

References 27 publications

Registration of Whole-Mount Histology and Volumetric Imaging of the Prostate Using Particle Filtering

Registration of Whole-Mount Histology and Volumetric Imaging of the Prostate Using Particle Filtering

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

Optimized SIFTFlow for registration of whole-mount histology to reference optical images

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