MCMICRO: a scalable, modular image-processing pipeline for multiplexed tissue imaging

Denis Schapiro; Artem Sokolov; Clarence Yapp; Yu-An Chen; Jeremy L Muhlich; Joshua Hess; Allison L Creason; Ajit J Nirmal; Gregory J Baker; Maulik K Nariya; Jia-Ren Lin; Zoltan Maliga; Connor A Jacobson; Matthew W Hodgman; Juha Ruokonen; Samouil L Farhi; Domenic Abbondanza; Eliot T McKinley; Daniel Persson; Courtney Betts; Shamilene Sivagnanam; Aviv Regev; Jeremy Goecks; Robert J Coffey; Lisa M Coussens; Sandro Santagata; Peter K Sorger

doi:10.1038/s41592-021-01308-y

MCMICRO: a scalable, modular image-processing pipeline for multiplexed tissue imaging

Nat Methods. 2022 Mar;19(3):311-315. doi: 10.1038/s41592-021-01308-y. Epub 2021 Nov 25.

Authors

Denis Schapiro^#^{1

2

3

4}, Artem Sokolov^#^{1

2

5}, Clarence Yapp^#^{1

2

6}, Yu-An Chen^{1

2}, Jeremy L Muhlich^{1

2}, Joshua Hess⁷, Allison L Creason⁸, Ajit J Nirmal^{1

2

9}, Gregory J Baker^{1

2}, Maulik K Nariya^{1

2}, Jia-Ren Lin^{1

2}, Zoltan Maliga^{1

2}, Connor A Jacobson^{1

2}, Matthew W Hodgman^{2

10}, Juha Ruokonen^{1

2}, Samouil L Farhi³, Domenic Abbondanza³, Eliot T McKinley^{11

12}, Daniel Persson^{8

13}, Courtney Betts¹⁴, Shamilene Sivagnanam¹⁴, Aviv Regev^{3

15

16}, Jeremy Goecks^{8

13}, Robert J Coffey¹⁷, Lisa M Coussens^{13

14}, Sandro Santagata^{1

2

18}, Peter K Sorger^{19

20

21}

Affiliations

¹ Ludwig Center for Cancer Research at Harvard, Harvard Medical School, Boston, MA, USA.
² Laboratory of Systems Pharmacology, Harvard Medical School, Boston, MA, USA.
³ Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
⁴ Institute for Computational Biomedicine and Institute of Pathology, Faculty of Medicine, Heidelberg University Hospital and Heidelberg University, Heidelberg, Germany.
⁵ Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
⁶ Image and Data Analysis Core, Harvard Medical School, Boston, MA, USA.
⁷ Vaccine and Immunotherapy Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
⁸ Biomedical Engineering, Oregon Health and Science University, Portland, OR, USA.
⁹ Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA.
¹⁰ Department of Biology, Brigham Young University, Provo, UT, USA.
¹¹ Epithelial Biology Center, Vanderbilt University Medical Center, Nashville, TN, USA.
¹² Department of Cell and Developmental Biology, Vanderbilt University School of Medicine, Nashville, TN, USA.
¹³ Knight Cancer Institute, Oregon Health and Science University, Portland, OR, USA.
¹⁴ Department of Cell, Developmental and Cancer Biology, Oregon Health and Science University, Portland, OR, USA.
¹⁵ Department of Biology, Howard Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, MA, USA.
¹⁶ Genentech, South San Francisco, CA, USA.
¹⁷ Division of Gastroenterology, Hepatology, and Nutrition, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.
¹⁸ Department of Pathology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
¹⁹ Ludwig Center for Cancer Research at Harvard, Harvard Medical School, Boston, MA, USA. peter_sorger@hms.harvard.edu.
²⁰ Laboratory of Systems Pharmacology, Harvard Medical School, Boston, MA, USA. peter_sorger@hms.harvard.edu.
²¹ Department of Systems Biology, Harvard Medical School, Boston, MA, USA. peter_sorger@hms.harvard.edu.

^# Contributed equally.

Abstract

Highly multiplexed tissue imaging makes detailed molecular analysis of single cells possible in a preserved spatial context. However, reproducible analysis of large multichannel images poses a substantial computational challenge. Here, we describe a modular and open-source computational pipeline, MCMICRO, for performing the sequential steps needed to transform whole-slide images into single-cell data. We demonstrate the use of MCMICRO on tissue and tumor images acquired using multiple imaging platforms, thereby providing a solid foundation for the continued development of tissue imaging software.

Publication types

Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't

MeSH terms

Diagnostic Imaging
Humans
Image Processing, Computer-Assisted* / methods
Neoplasms* / diagnostic imaging
Neoplasms* / pathology
Software

Abstract

Publication types

MeSH terms

Grants and funding