Literature DB >> 30069968

A system using patient-specific 3D-printed molds to spatially align in vivo MRI with ex vivo MRI and whole-mount histopathology for prostate cancer research.

Holden H Wu1,2, Alan Priester2,3, Pooria Khoshnoodi1, Zhaohuan Zhang1,2, Sepideh Shakeri1, Sohrab Afshari Mirak1, Nazanin H Asvadi1, Preeti Ahuja1, Kyunghyun Sung1,2, Shyam Natarajan2,3, Anthony Sisk4, Robert Reiter3, Steven Raman1,3, Dieter Enzmann1.   

Abstract

BACKGROUND: Patient-specific 3D-printed molds and ex vivo MRI of the resected prostate have been two important strategies to align MRI with whole-mount histopathology (WMHP) for prostate cancer (PCa) research, but the combination of these two strategies has not been systematically evaluated.
PURPOSE: To develop and evaluate a system that combines patient-specific 3D-printed molds with ex vivo MRI (ExV) to spatially align in vivo MRI (InV), ExV, and WMHP in PCa patients. STUDY TYPE: Prospective cohort study. POPULATION: Seventeen PCa patients who underwent 3T MRI and robotic-assisted laparoscopic radical prostatectomy (RALP). FIELD STRENGTH/SEQUENCES: T2 -weighted turbo spin-echo sequences at 3T. ASSESSMENT: Immediately after RALP, the fresh whole prostate specimens were imaged in patient-specific 3D-printed molds by 3T MRI and then sectioned to create WMHP slides. The time required for ExV was measured to assess impact on workflow. InV, ExV, and WMHP images were registered. Spatial alignment was evaluated using: slide offset (mm) between ExV slice locations and WMHP slides; overlap of the 3D prostate contour on InV versus ExV using Dice's coefficient (0 to 1); and 2D target registration error (TRE, mm) between corresponding landmarks on InV, ExV, and WMHP. Data are reported as mean ± standard deviation (SD). STATISTICAL TESTING: Differences in 2D TRE before versus after registration were compared using the Wilcoxon signed-rank test (P < 0.05 considered significant).
RESULTS: ExV (duration 115 ± 15 min) was successfully incorporated into the workflow for all cases. Absolute slide offset was 1.58 ± 1.57 mm. Dice's coefficient was 0.865 ± 0.035. 2D TRE was significantly reduced after registration (P < 0.01) with mean (±SD of per patient means) of 1.9 ± 0.6 mm for InV versus ExV, 1.4 ± 0.5 mm for WMHP versus ExV, and 2.0 ± 0.5 mm for WMHP versus InV. DATA
CONCLUSION: The proposed system combines patient-specific 3D-printed molds with ExV to achieve spatial alignment between InV, ExV, and WMHP with mean 2D TRE of 1-2 mm. LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2019;49:270-279.
© 2018 International Society for Magnetic Resonance in Medicine.

Entities:  

Keywords:  3D-printed molds; MRI-pathology correlation; ex vivo MRI; prostate MRI

Mesh:

Year:  2018        PMID: 30069968     DOI: 10.1002/jmri.26189

Source DB:  PubMed          Journal:  J Magn Reson Imaging        ISSN: 1053-1807            Impact factor:   4.813


  14 in total

1.  High-Resolution Ex Vivo Microstructural MRI After Restoring Ventricular Geometry via 3D Printing.

Authors:  Tyler E Cork; Luigi E Perotti; Ilya A Verzhbinsky; Michael Loecher; Daniel B Ennis
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2.  Selective identification and localization of indolent and aggressive prostate cancers via CorrSigNIA: an MRI-pathology correlation and deep learning framework.

Authors:  Indrani Bhattacharya; Arun Seetharaman; Christian Kunder; Wei Shao; Leo C Chen; Simon J C Soerensen; Jeffrey B Wang; Nikola C Teslovich; Richard E Fan; Pejman Ghanouni; James D Brooks; Geoffrey A Sonn; Mirabela Rusu
Journal:  Med Image Anal       Date:  2021-11-06       Impact factor: 8.545

3.  Head-to-Head Comparison of 68Ga-PSMA-11 PET/CT and mpMRI with a Histopathology Gold Standard in the Detection, Intraprostatic Localization, and Determination of Local Extension of Primary Prostate Cancer: Results from a Prospective Single-Center Imaging Trial.

Authors:  Ida Sonni; Ely R Felker; Andrew T Lenis; Anthony E Sisk; Shadfar Bahri; Martin Allen-Auerbach; Wesley R Armstrong; Voraparee Suvannarerg; Teeravut Tubtawee; Tristan Grogan; David Elashoff; Matthias Eiber; Steven S Raman; Johannes Czernin; Robert E Reiter; Jeremie Calais
Journal:  J Nucl Med       Date:  2021-10-14       Impact factor: 11.082

4.  3D Registration of pre-surgical prostate MRI and histopathology images via super-resolution volume reconstruction.

Authors:  Rewa R Sood; Wei Shao; Christian Kunder; Nikola C Teslovich; Jeffrey B Wang; Simon J C Soerensen; Nikhil Madhuripan; Anugayathri Jawahar; James D Brooks; Pejman Ghanouni; Richard E Fan; Geoffrey A Sonn; Mirabela Rusu
Journal:  Med Image Anal       Date:  2021-01-23       Impact factor: 8.545

5.  Multi-colour extrusion fused deposition modelling: a low-cost 3D printing method for anatomical prostate cancer models.

Authors:  Michael Y Chen; Jacob Skewes; Maria A Woodruff; Prokar Dasgupta; Nicholas J Rukin
Journal:  Sci Rep       Date:  2020-06-19       Impact factor: 4.379

6.  Three-dimensional printing versus conventional machining in the creation of a meatal urethral dilator: development and mechanical testing.

Authors:  Michael Y Chen; Jacob Skewes; Ryan Daley; Maria A Woodruff; Nicholas J Rukin
Journal:  Biomed Eng Online       Date:  2020-07-01       Impact factor: 2.819

7.  Evaluation of metronomic chemotherapy response using diffusion and dynamic contrast-enhanced MRI.

Authors:  Mehran Baboli; Kerryanne V Winters; Melanie Freed; Jin Zhang; Sungheon Gene Kim
Journal:  PLoS One       Date:  2020-11-25       Impact factor: 3.240

8.  Registration of presurgical MRI and histopathology images from radical prostatectomy via RAPSODI.

Authors:  Mirabela Rusu; Wei Shao; Christian A Kunder; Jeffrey B Wang; Simon J C Soerensen; Nikola C Teslovich; Rewa R Sood; Leo C Chen; Richard E Fan; Pejman Ghanouni; James D Brooks; Geoffrey A Sonn
Journal:  Med Phys       Date:  2020-07-18       Impact factor: 4.071

9.  Liver-specific 3D sectioning molds for correlating in vivo CT and MRI with tumor histopathology in woodchucks (Marmota monax).

Authors:  Andrew S Mikhail; Michal Mauda-Havakuk; Ari Partanen; John W Karanian; William F Pritchard; Bradford J Wood
Journal:  PLoS One       Date:  2020-03-26       Impact factor: 3.240

10.  Variability in accuracy of prostate cancer segmentation among radiologists, urologists, and scientists.

Authors:  Michael Y Chen; Maria A Woodruff; Prokar Dasgupta; Nicholas J Rukin
Journal:  Cancer Med       Date:  2020-08-18       Impact factor: 4.452

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