51. Tissue microarray design and construction for scientific, industrial and diagnostic use
- Author
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Maurizio Falavigna, Ida Biunno, Emanuele Martella, Daniela Pilla, Stefano Faggi, Simone Borghesi, Roberto Marotta, Paolo Forlani, Pasquale De Blasio, Giorgio Cattoretti, Francesca Maria Bosisio, Pilla, D, Bosisio, F, Marotta, R, Faggi, S, Forlani, P, Falavigna, M, Biunno, I, Martella, E, De Blasio, P, Borghesi, S, and Cattoretti, G
- Subjects
Matching (statistics) ,Process (engineering) ,Computer science ,virtual slide ,Health Informatics ,Sample (statistics) ,Context (language use) ,lcsh:Computer applications to medicine. Medical informatics ,computer.software_genre ,Pathology and Forensic Medicine ,lcsh:Pathology ,High throughput technology ,tissue micro array ,Diagnostic ,Throughput (business) ,Virtual slide ,tissue microarray ,MED/08 - ANATOMIA PATOLOGICA ,Computer Science Applications ,Virtual image ,whole slide image ,lcsh:R858-859.7 ,Original Article ,pathology ,Data mining ,computer ,Diagnostic, pathology, tissue microarray, tissue micro array, virtual slide, whole slide image ,lcsh:RB1-214 - Abstract
Context: In 2013 the high throughput technology known as Tissue Micro Array (TMA) will be fifteen years old. Its elements (design, construction and analysis) are intuitive and the core histopathology technique is unsophisticated, which may be a reason why has eluded a rigorous scientific scrutiny. The source of errors, particularly in specimen identification and how to control for it is unreported. Formal validation of the accuracy of segmenting (also known as de-arraying) hundreds of samples, pairing with the sample data is lacking. Aims: We wanted to address these issues in order to bring the technique to recognized standards of quality in TMA use for research, diagnostics and industrial purposes. Results: We systematically addressed the sources of error and used barcode-driven data input throughout the whole process including matching the design with a TMA virtual image and segmenting that image back to individual cases, together with the associated data. In addition we demonstrate on mathematical grounds that a TMA design, when superimposed onto the corresponding whole slide image, validates on each and every sample the correspondence between the image and patient′s data. Conclusions: High throughput use of the TMA technology is a safe and efficient method for research, diagnosis and industrial use if all sources of errors are identified and addressed.
- Published
- 2012