Journal of Pathology Informatics Journal of Pathology Informatics
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RESEARCH ARTICLE
Year : 2018  |  Volume : 9  |  Issue : 1  |  Page : 45

Computer-aided laser dissection: A microdissection workflow leveraging image analysis tools


1 Laboratory of Pathology, National Cancer Institute, Bethesda, MD; Google Inc., Mountain View, CA, USA
2 Winthrop P. Rockefeller Cancer Institute, University of Arkansas for Medical Sciences, Little Rock, AR, USA
3 Laboratory of Pathology, National Cancer Institute, Bethesda, MD; Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD, USA
4 Department of Biomedical Engineering, Center for Computational Imaging and Personalized Diagnostics, Case Western Reserve University, Cleveland, OH, USA
5 Inspirata Inc., Tampa, FL, USA
6 Department of Pathology, University of Michigan, Ann Arbor, MI, USA
7 Laboratory of Pathology, National Cancer Institute, Bethesda; Medimmune, LLC, Gaithersburg, MD, USA
8 Google Inc., Mountain View, CA, USA
9 Laboratory of Pathology, National Cancer Institute, Bethesda, MD; Division of Translational Pathology, Rutgers Cancer Institute of New Jersey, New Brunswick, NJ, USA
10 Laboratory of Pathology, National Cancer Institute, Bethesda, MD; Department of Pathology, Johns Hopkins School of Medicine, Baltimore, MD, USA
11 Laboratory of Pathology, National Cancer Institute, Bethesda, MD, USA
12 Laboratory of Pathology, National Cancer Institute, Bethesda, MD; Avoneaux Medical Institute, LLC, Baltimore, MD, USA
13 Laboratory of Pathology, National Cancer Institute, Bethesda; Alvin and Lois Lapidus Cancer Institute, Sinai Hospital of Baltimore, LifeBridge Health, Baltimore, MD, USA

Correspondence Address:
Dr. Michael A Tangrea
Alvin and Lois Lapidus Cancer Institute, Sinai Hospital of Baltimore, Lifebridge Health, 2401 W. Belvedere Ave, Schapiro Building, Room 203 Baltimore, MD 21215
USA
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/jpi.jpi_60_18

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Introduction: The development and application of new molecular diagnostic assays based on next-generation sequencing and proteomics require improved methodologies for procurement of target cells from histological sections. Laser microdissection can successfully isolate distinct cells from tissue specimens based on visual selection for many research and clinical applications. However, this can be a daunting task when a large number of cells are required for molecular analysis or when a sizeable number of specimens need to be evaluated. Materials and Methods: To improve the efficiency of the cellular identification process, we describe a microdissection workflow that leverages recently developed and open source image analysis algorithms referred to as computer-aided laser dissection (CALD). CALD permits a computer algorithm to identify the cells of interest and drive the dissection process. Results: We describe several “use cases” that demonstrate the integration of image analytic tools probabilistic pairwise Markov model, ImageJ, spatially invariant vector quantization (SIVQ), and eSeg onto the ThermoFisher Scientific ArcturusXT and Leica LMD7000 microdissection platforms. Conclusions: The CALD methodology demonstrates the integration of image analysis tools with the microdissection workflow and shows the potential impact to clinical and life science applications.


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