Validation of a Muscle-Specific Tissue Image Analysis Tool for Quantitative Assessment of Dystrophin Staining in Frozen Muscle Biopsies
| Autor: | Johannes Dworzak, Daniel G. Rudmann, Famke Aeffner, Kristin Wilson, Crystal Faelan, Suzanne Kanaly, Manish Ranjitkar, Holger Lange, J Kris Piper, Steven A. Moore, Joshua C. Black, Anthony J. Milici, D. Frank, Jay S. Charleston, G. David Young, Alexander Moody |
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| Rok vydání: | 2018 |
| Předmět: |
Male
0301 basic medicine Pathology medicine.medical_specialty Neuromuscular disease Adolescent Biopsy Duchenne muscular dystrophy Article Pathology and Forensic Medicine Dystrophin 03 medical and health sciences 0302 clinical medicine Image Interpretation Computer-Assisted Quantitative assessment medicine Frozen Sections Humans Muscular dystrophy Child Muscle Skeletal Frozen section procedure biology medicine.diagnostic_test business.industry General Medicine Middle Aged medicine.disease Staining Muscular Dystrophy Duchenne Medical Laboratory Technology 030104 developmental biology Child Preschool 030220 oncology & carcinogenesis biology.protein Female business |
| Zdroj: | Archives of Pathology & Laboratory Medicine. 143:197-205 |
| ISSN: | 1543-2165 0003-9985 |
| DOI: | 10.5858/arpa.2017-0536-oa |
| Popis: | Context.—Duchenne muscular dystrophy is a rare, progressive, and fatal neuromuscular disease caused by dystrophin protein loss. Common investigational treatment approaches aim at increasing dystrophin expression in diseased muscle. Some clinical trials include assessments of novel dystrophin production as a surrogate biomarker of efficacy, which may predict a clinical benefit from treatment.Objectives.—To establish an immunofluorescent scanning and digital image analysis workflow that provides an objective approach for staining intensity assessment of the immunofluorescence dystrophin labeling and determination of the percentage of biomarker-positive fibers in muscle cryosections.Design.—Optimal and repeatable digital image capture was achieved by a rigorously qualified fluorescent scanning process. After scanning qualification, the MuscleMap (Flagship Biosciences, Westminster, Colorado) algorithm was validated by comparing high-power microscopic field total and dystrophin-positive fiber counts obtained by trained pathologists to data derived by MuscleMap. Next, the algorithm was tested on whole-slide images of immunofluorescent-labeled muscle sections from Duchenne muscular dystrophy, Becker muscular dystrophy, and control patients.Results.—When used under the guidance of a trained pathologist, the digital image analysis tool met predefined validation criteria and demonstrated functional and statistical equivalence with manual assessment. This work is the first, to our knowledge, to qualify and validate immunofluorescent scanning and digital tissue image-analysis workflow, respectively, with the rigor required to support the clinical trial environments.Conclusions.—MuscleMap enables analysis of all fibers within an entire muscle biopsy section and provides data on a fiber-by-fiber basis. This will allow future clinical trials to objectively investigate myofibers' dystrophin expression at a greater level of consistency and detail. |
| Databáze: | OpenAIRE |
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