Literature DB >> 19291709

Do we see what we think we see? The complexities of morphological assessment.

Peter W Hamilton1, Paul J van Diest, Richard Williams, Anthony G Gallagher.   

Abstract

Reliable pathological interpretation is vital to so many aspects of tissue-based research as well as being central to patient care. Understanding the complex processes involved in decision-making is the starting point to improve both diagnostic reproducibility and the definition of diagnostic groups that underpin our experiments. Unfortunately, there is a paucity of research in this field and it is encouraging to see The Journal of Pathology publishing work in this area. This review attempts to highlight the opportunities that exist in this field and the technologies that are now available to support this type of research. Key amongst these are the use of decision analysis tools such as inference networks, and virtual microscopy that allows us to simulate diagnostic decision-making. These tools have roles, not only in studying the subtleties of diagnostic decision-making, but also in delivering new methods of training and proficiency testing. Research which helps us to better understand what we see, why we see it, and standardizing interpretative reasoning in pathological classification is essential for improving the wide range of activities that pathologists support, including clinical diagnosis, teaching, training, and experimental research. 2009 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Entities:  

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Year:  2009        PMID: 19291709     DOI: 10.1002/path.2527

Source DB:  PubMed          Journal:  J Pathol        ISSN: 0022-3417            Impact factor:   7.996


  18 in total

1.  From virtual microscopy to systems pathology: a meeting report of the 1st European workshop on tissue imaging and analysis, Heidelberg, Germany, 13-14 February 2009.

Authors:  Niels Grabe; Peter Schirmacher
Journal:  Virchows Arch       Date:  2009-08-04       Impact factor: 4.064

2.  Haematology morphology teaching during the COVID-19 pandemic: a UK teaching hospital experience.

Authors:  Sarah K Westbury; Andrew Stewart
Journal:  Future Healthc J       Date:  2021-03

3.  Feasibility of fully automated classification of whole slide images based on deep learning.

Authors:  Kyung-Ok Cho; Sung Hak Lee; Hyun-Jong Jang
Journal:  Korean J Physiol Pharmacol       Date:  2020-12-20       Impact factor: 2.016

4.  The use of virtual slides in the EUROPALS examination.

Authors:  Jan G van den Tweel; Fred T Bosman
Journal:  Diagn Pathol       Date:  2011-03-30       Impact factor: 2.644

5.  What was I thinking? Eye-tracking experiments underscore the bias that architecture exerts on nuclear grading in prostate cancer.

Authors:  Dario Bombari; Braulio Mora; Stephan C Schaefer; Fred W Mast; Hans-Anton Lehr
Journal:  PLoS One       Date:  2012-05-30       Impact factor: 3.240

6.  How reliable is Ki-67 immunohistochemistry in grade 2 breast carcinomas? A QA study of the Swiss Working Group of Breast- and Gynecopathologists.

Authors:  Zsuzsanna Varga; Joachim Diebold; Corina Dommann-Scherrer; Harald Frick; Daniela Kaup; Aurelia Noske; Ellen Obermann; Christian Ohlschlegel; Barbara Padberg; Christiane Rakozy; Sara Sancho Oliver; Sylviane Schobinger-Clement; Heide Schreiber-Facklam; Gad Singer; Coya Tapia; Urs Wagner; Mauro G Mastropasqua; Giuseppe Viale; Hans-Anton Lehr
Journal:  PLoS One       Date:  2012-05-25       Impact factor: 3.240

7.  Attitude and Perception of Medical Students Towards Histology Subject at Wollo University, Ethiopia.

Authors:  Daniel Teshome
Journal:  Adv Med Educ Pract       Date:  2022-04-19

8.  Optimisation of an immunohistochemistry method for the determination of androgen receptor expression levels in circulating tumour cells.

Authors:  Jeffrey Cummings; Robert Sloane; Karen Morris; Cong Zhou; Matt Lancashire; David Moore; Tony Elliot; Noel Clarke; Caroline Dive
Journal:  BMC Cancer       Date:  2014-03-28       Impact factor: 4.430

9.  Prognostic image-based quantification of CD8CD103 T cell subsets in high-grade serous ovarian cancer patients.

Authors:  S T Paijens; A Vledder; D Loiero; E W Duiker; J Bart; A M Hendriks; M Jalving; H H Workel; H Hollema; N Werner; A Plat; G B A Wisman; R Yigit; H Arts; A J Kruse; N M de Lange; V H Koelzer; M de Bruyn; H W Nijman
Journal:  Oncoimmunology       Date:  2021-06-06       Impact factor: 8.110

10.  Do We Know Why We Make Errors in Morphological Diagnosis? An Analysis of Approach and Decision-Making in Haematological Morphology.

Authors:  Michelle Brereton; Barbara De La Salle; John Ardern; Keith Hyde; John Burthem
Journal:  EBioMedicine       Date:  2015-07-18       Impact factor: 8.143

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