Literature DB >> 28386717

Co-registration of pre-operative CT with ex vivo surgically excised ground glass nodules to define spatial extent of invasive adenocarcinoma on in vivo imaging: a proof-of-concept study.

Mirabela Rusu1,2, Prabhakar Rajiah3,4, Robert Gilkeson4, Michael Yang4, Christopher Donatelli4, Rajat Thawani5, Frank J Jacono4,6, Philip Linden4, Anant Madabhushi7.   

Abstract

OBJECTIVE: To develop an approach for radiology-pathology fusion of ex vivo histology of surgically excised pulmonary nodules with pre-operative CT, to radiologically map spatial extent of the invasive adenocarcinomatous component of the nodule.
METHODS: Six subjects (age: 75 ± 11 years) with pre-operative CT and surgically excised ground-glass nodules (size: 22.5 ± 5.1 mm) with a significant invasive adenocarcinomatous component (>5 mm) were included. The pathologist outlined disease extent on digitized histology specimens; two radiologists and a pulmonary critical care physician delineated the entire nodule on CT (in-plane resolution: <0.8 mm, inter-slice distance: 1-5 mm). We introduced a novel reconstruction approach to localize histology slices in 3D relative to each other while using CT scan as spatial constraint. This enabled the spatial mapping of the extent of tumour invasion from histology onto CT.
RESULTS: Good overlap of the 3D reconstructed histology and the nodule outlined on CT was observed (65.9 ± 5.2%). Reduction in 3D misalignment of corresponding anatomical landmarks on histology and CT was observed (1.97 ± 0.42 mm). Moreover, the CT attenuation (HU) distributions were different when comparing invasive and in situ regions.
CONCLUSION: This proof-of-concept study suggests that our fusion method can enable the spatial mapping of the invasive adenocarcinomatous component from 2D histology slices onto in vivo CT. KEY POINTS: • 3D reconstructions are generated from 2D histology specimens of ground glass nodules. • The reconstruction methodology used pre-operative in vivo CT as 3D spatial constraint. • The methodology maps adenocarcinoma extent from digitized histology onto in vivo CT. • The methodology potentially facilitates the discovery of CT signature of invasive adenocarcinoma.

Entities:  

Keywords:  Computed tomography; Computer-assisted image processing; Lung adenocarcinoma; Multimodal imaging; Pathology

Mesh:

Year:  2017        PMID: 28386717      PMCID: PMC5630490          DOI: 10.1007/s00330-017-4813-0

Source DB:  PubMed          Journal:  Eur Radiol        ISSN: 0938-7994            Impact factor:   5.315


  15 in total

1.  elastix: a toolbox for intensity-based medical image registration.

Authors:  Stefan Klein; Marius Staring; Keelin Murphy; Max A Viergever; Josien P W Pluim
Journal:  IEEE Trans Med Imaging       Date:  2009-11-17       Impact factor: 10.048

2.  Elastic registration of multimodal prostate MRI and histology via multiattribute combined mutual information.

Authors:  Jonathan Chappelow; B Nicolas Bloch; Neil Rofsky; Elizabeth Genega; Robert Lenkinski; William DeWolf; Anant Madabhushi
Journal:  Med Phys       Date:  2011-04       Impact factor: 4.071

3.  International Association for the Study of Lung Cancer/American Thoracic Society/European Respiratory Society: international multidisciplinary classification of lung adenocarcinoma: executive summary.

Authors:  William D Travis; Elisabeth Brambilla; Masayuki Noguchi; Andrew G Nicholson; Kim Geisinger; Yasushi Yatabe; Charles A Powell; David Beer; Greg Riely; Kavita Garg; John H M Austin; Valerie W Rusch; Fred R Hirsch; James Jett; Pan-Chyr Yang; Michael Gould
Journal:  Proc Am Thorac Soc       Date:  2011-09

Review 4.  Pathologic classification of adenocarcinoma of lung.

Authors:  Paul E Van Schil; Alan D L Sihoe; William D Travis
Journal:  J Surg Oncol       Date:  2013-09-04       Impact factor: 3.454

5.  New IASLC/ATS/ERS classification and invasive tumor size are predictive of disease recurrence in stage I lung adenocarcinoma.

Authors:  Naoki Yanagawa; Satoshi Shiono; Masami Abiko; Shin-ya Ogata; Toru Sato; Gen Tamura
Journal:  J Thorac Oncol       Date:  2013-05       Impact factor: 15.609

6.  Invasive size is an independent predictor of survival in pulmonary adenocarcinoma.

Authors:  Alain C Borczuk; Fang Qian; Angeliki Kazeros; Jennifer Eleazar; Adel Assaad; Joshua R Sonett; Mark Ginsburg; Lyall Gorenstein; Charles A Powell
Journal:  Am J Surg Pathol       Date:  2009-03       Impact factor: 6.394

7.  Computerized texture analysis of persistent part-solid ground-glass nodules: differentiation of preinvasive lesions from invasive pulmonary adenocarcinomas.

Authors:  Hee-Dong Chae; Chang Min Park; Sang Joon Park; Sang Min Lee; Kwang Gi Kim; Jin Mo Goo
Journal:  Radiology       Date:  2014-08-01       Impact factor: 11.105

8.  Framework for 3D histologic reconstruction and fusion with in vivo MRI: Preliminary results of characterizing pulmonary inflammation in a mouse model.

Authors:  Mirabela Rusu; Thea Golden; Haibo Wang; Andrew Gow; Anant Madabhushi
Journal:  Med Phys       Date:  2015-08       Impact factor: 4.071

9.  Invasive pulmonary adenocarcinomas versus preinvasive lesions appearing as ground-glass nodules: differentiation by using CT features.

Authors:  Sang Min Lee; Chang Min Park; Jin Mo Goo; Hyun-Ju Lee; Jae Yeon Wi; Chang Hyun Kang
Journal:  Radiology       Date:  2013-03-06       Impact factor: 11.105

10.  Morphological factors differentiating between early lung adenocarcinomas appearing as pure ground-glass nodules measuring ≤10 mm on thin-section computed tomography.

Authors:  Wenjing Xiang; Yanfen Xing; Sen Jiang; Gang Chen; Haixia Mao; Kanchan Labh; Xiaoli Jia; Xiwen Sun
Journal:  Cancer Imaging       Date:  2014-11-20       Impact factor: 3.909

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  9 in total

Review 1.  Radiomics: an Introductory Guide to What It May Foretell.

Authors:  Stephanie Nougaret; Hichem Tibermacine; Marion Tardieu; Evis Sala
Journal:  Curr Oncol Rep       Date:  2019-06-25       Impact factor: 5.075

Review 2.  The state of the art for artificial intelligence in lung digital pathology.

Authors:  Vidya Sankar Viswanathan; Paula Toro; Germán Corredor; Sanjay Mukhopadhyay; Anant Madabhushi
Journal:  J Pathol       Date:  2022-06-20       Impact factor: 9.883

3.  Towards a better understanding of annotation tools for medical imaging: a survey.

Authors:  Manar Aljabri; Manal AlAmir; Manal AlGhamdi; Mohamed Abdel-Mottaleb; Fernando Collado-Mesa
Journal:  Multimed Tools Appl       Date:  2022-03-25       Impact factor: 2.577

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

Authors:  Jacob Antunes; Satish Viswanath; Justin T Brady; Benjamin Crawshaw; Pablo Ros; Scott Steele; Conor P Delaney; Raj Paspulati; Joseph Willis; Anant Madabhushi
Journal:  Acad Radiol       Date:  2018-01-19       Impact factor: 3.173

Review 5.  Harnessing non-destructive 3D pathology.

Authors:  Jonathan T C Liu; Adam K Glaser; Kaustav Bera; Lawrence D True; Nicholas P Reder; Kevin W Eliceiri; Anant Madabhushi
Journal:  Nat Biomed Eng       Date:  2021-02-15       Impact factor: 25.671

6.  Quantitative vessel tortuosity: A potential CT imaging biomarker for distinguishing lung granulomas from adenocarcinomas.

Authors:  Mehdi Alilou; Mahdi Orooji; Niha Beig; Prateek Prasanna; Prabhakar Rajiah; Christopher Donatelli; Vamsidhar Velcheti; Sagar Rakshit; Michael Yang; Frank Jacono; Robert Gilkeson; Philip Linden; Anant Madabhushi
Journal:  Sci Rep       Date:  2018-10-16       Impact factor: 4.379

7.  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

8.  ProsRegNet: A deep learning framework for registration of MRI and histopathology images of the prostate.

Authors:  Wei Shao; Linda Banh; Christian A Kunder; Richard E Fan; Simon J C Soerensen; Jeffrey B Wang; Nikola C Teslovich; Nikhil Madhuripan; Anugayathri Jawahar; Pejman Ghanouni; James D Brooks; Geoffrey A Sonn; Mirabela Rusu
Journal:  Med Image Anal       Date:  2020-12-17       Impact factor: 8.545

9.  Bridging cell-scale simulations and radiologic images to explain short-time intratumoral oxygen fluctuations.

Authors:  Jessica L Kingsley; James R Costello; Natarajan Raghunand; Katarzyna A Rejniak
Journal:  PLoS Comput Biol       Date:  2021-07-26       Impact factor: 4.475

  9 in total

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