Search: WFRF:(Bokhorst John Melle) >
Deep learning based...
-
Smit, Marloes A.Department of Surgery, Leiden University Medical Center, Leiden, The Netherlands
(author)
Deep learning based tumor–stroma ratio scoring in colon cancer correlates with microscopic assessment
- Article/chapterEnglish2023
Publisher, publication year, extent ...
-
Elsevier B.V.2023
-
printrdacarrier
Numbers
-
LIBRIS-ID:oai:DiVA.org:liu-200781
-
https://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-200781URI
-
https://doi.org/10.1016/j.jpi.2023.100191DOI
Supplementary language notes
-
Language:English
-
Summary in:English
Part of subdatabase
Classification
-
Subject category:ref swepub-contenttype
-
Subject category:art swepub-publicationtype
Notes
-
Background: The amount of stroma within the primary tumor is a prognostic parameter for colon cancer patients. This phenomenon can be assessed using the tumor–stroma ratio (TSR), which classifies tumors in stroma-low (≤50% stroma) and stroma-high (>50% stroma). Although the reproducibility for TSR determination is good, improvement might be expected from automation. The aim of this study was to investigate whether the scoring of the TSR in a semi- and fully automated method using deep learning algorithms is feasible. Methods: A series of 75 colon cancer slides were selected from a trial series of the UNITED study. For the standard determination of the TSR, 3 observers scored the histological slides. Next, the slides were digitized, color normalized, and the stroma percentages were scored using semi- and fully automated deep learning algorithms. Correlations were determined using intraclass correlation coefficients (ICCs) and Spearman rank correlations. Results: 37 (49%) cases were classified as stroma-low and 38 (51%) as stroma-high by visual estimation. A high level of concordance between the 3 observers was reached, with ICCs of 0.91, 0.89, and 0.94 (all P < .001). Between visual and semi-automated assessment the ICC was 0.78 (95% CI 0.23–0.91, P-value 0.005), with a Spearman correlation of 0.88 (P < .001). Spearman correlation coefficients above 0.70 (N=3) were observed for visual estimation versus the fully automated scoring procedures. Conclusion: Good correlations were observed between standard visual TSR determination and semi- and fully automated TSR scores. At this point, visual examination has the highest observer agreement, but semi-automated scoring could be helpful to support pathologists. © 2023 The Authors
Subject headings and genre
Added entries (persons, corporate bodies, meetings, titles ...)
-
Ciompi, FrancescoDepartment of Pathology, Radboud University Medical Center, Nijmegen, the Netherlands
(author)
-
Bokhorst, John-MelleDepartment of Pathology, Radboud University Medical Center, Nijmegen, the Netherlands
(author)
-
van Pelt, Gabi W.Department of Surgery, Leiden University Medical Center, Leiden, The Netherlands
(author)
-
Geessink, Oscar G.F.Department of Pathology, Radboud University Medical Center, Nijmegen, the Netherlands
(author)
-
Putter, HeinDepartment of Medical Statistics, Leiden University Medical Center, Leiden, The Netherlands
(author)
-
Tollenaar, Rob A.E.M.Department of Surgery, Leiden University Medical Center, Leiden, The Netherlands
(author)
-
van Krieken, J. Han J.M.Department of Pathology, Radboud University Medical Center, Nijmegen, the Netherlands
(author)
-
Mesker, Wilma E.Department of Surgery, Leiden University Medical Center, Leiden, The Netherlands
(author)
-
van der Laak, Jeroen,1967-Linköpings universitet,Avdelningen för diagnostik och specialistmedicin,Medicinska fakulteten,Centrum för medicinsk bildvetenskap och visualisering, CMIV,Region Östergötland, Klinisk patologi,Department of Pathology, Radboud University Medical Center, Nijmegen, the Netherlands(Swepub:liu)jerva26
(author)
-
Department of Surgery, Leiden University Medical Center, Leiden, The NetherlandsDepartment of Pathology, Radboud University Medical Center, Nijmegen, the Netherlands
(creator_code:org_t)
Related titles
-
In:Journal of Pathology Informatics: Elsevier B.V.142229-50892153-3539
Internet link
Find in a library
To the university's database
- By the author/editor
-
Smit, Marloes A.
-
Ciompi, Francesc ...
-
Bokhorst, John-M ...
-
van Pelt, Gabi W ...
-
Geessink, Oscar ...
-
Putter, Hein
-
show more...
-
Tollenaar, Rob A ...
-
van Krieken, J. ...
-
Mesker, Wilma E.
-
van der Laak, Je ...
-
show less...
- About the subject
-
- MEDICAL AND HEALTH SCIENCES
-
MEDICAL AND HEAL ...
-
and Clinical Medicin ...
-
and Cancer and Oncol ...
- Articles in the publication
-
Journal of Patho ...
- By the university
-
Linköping University