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Registration of in vivo prostate MRI and pseudo‐whole mount histology using Local Affine Transformations guided by Internal Structures (LATIS)
Author(s) -
Kalavagunta Chaitanya,
Zhou Xiangmin,
Schmechel Stephen C.,
Metzger Gregory J.
Publication year - 2015
Publication title -
journal of magnetic resonance imaging
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.563
H-Index - 160
eISSN - 1522-2586
pISSN - 1053-1807
DOI - 10.1002/jmri.24629
Subject(s) - magnetic resonance imaging , image registration , affine transformation , prostate , sørensen–dice coefficient , computer science , prostate cancer , landmark , artificial intelligence , gold standard (test) , medicine , nuclear medicine , radiology , cancer , segmentation , image segmentation , mathematics , pure mathematics , image (mathematics)
Purpose To present a novel registration approach called LATIS (Local Affine Transformation guided by Internal Structures) for coregistering post prostatectomy pseudo ‐whole mount (PWM) pathological sections with in vivo MRI (magnetic resonance imaging) images. Materials and Methods Thirty‐five patients with biopsy‐proven prostate cancer were imaged at 3T with an endorectal coil. Excised prostate specimens underwent quarter mount step‐section pathologic processing, digitization, annotation, and assembly into a PWM. Manually annotated macro‐structures on both pathology and MRI were used to assist registration using a relaxed local affine transformation approximation. Registration accuracy was assessed by calculation of the Dice similarity coefficient (DSC) between transformed and target capsule masks and least‐square distance between transformed and target landmark positions. Results LATIS registration resulted in a DSC value of 0.991 ± 0.004 and registration accuracy of 1.54 ± 0.64 mm based on identified landmarks common to both datasets. Image registration performed without the use of internal structures led to an 87% increase in landmark‐based registration error. Derived transformation matrices were used to map regions of pathologically defined disease to MRI. Conclusion LATIS was used to successfully coregister digital pathology with in vivo MRI to facilitate improved correlative studies between pathologically identified features of prostate cancer and multiparametric MRI. J. Magn. Reson. Imaging 2015;41:1104–1114 . © 2014 Wiley Periodicals, Inc .