Abstract / Description of output
Aims:Tumour budding is an established prognostic feature in multiple cancers but is not routinely assessed in pathology practice. Efforts to standardise and automate assessment have shifted from haematoxylin and eosin (H&E)-stained images towards cytokeratin immunohistochemistry. In this study, we compare manual H&E and cytokeratin assessment methods with a semi-automated approach built within QuPath open-source software.
Methods and Results:Results: Budding was assessed in cores from the advancing tumour edge in a cohort of stage II/III colon cancers (n=186). The total numbers of buds detected by each method were: manual H&E (n=503), manual cytokeratin (n=2290), semi-automated (n=5138). More than four times the number of buds were detected manually using cytokeratin compared to H&E. 1734 individual buds were identified on both manual and semi-automated assessments applied to cytokeratin images, representing 75.7% of the
buds identified manually (n=2290) and 33.7% of the buds detected using the semiautomated method (n=5138). Higher semi-automated bud scores were due to any discrete area of cytokeratin immunopositivity within an accepted area range being identified as a bud, regardless of shape or crispness of definition, and to inclusion of tumour cell clusters within glandular lumina (“luminal pseudobuds”). Although absolute numbers differed, semi-automated and manual bud counts were strongly correlated across cores (ρ=0.81, p<0.0001). All methods of budding assessment demonstrated poorer survival associated with higher budding scores.
Conclusions: Conclusions: We present a new QuPath-based approach to tumour budding assessment, which compares favorably to established methods and offers a freely-available, rapid and transparent tool that is also applicable to whole slide images.
Methods and Results:Results: Budding was assessed in cores from the advancing tumour edge in a cohort of stage II/III colon cancers (n=186). The total numbers of buds detected by each method were: manual H&E (n=503), manual cytokeratin (n=2290), semi-automated (n=5138). More than four times the number of buds were detected manually using cytokeratin compared to H&E. 1734 individual buds were identified on both manual and semi-automated assessments applied to cytokeratin images, representing 75.7% of the
buds identified manually (n=2290) and 33.7% of the buds detected using the semiautomated method (n=5138). Higher semi-automated bud scores were due to any discrete area of cytokeratin immunopositivity within an accepted area range being identified as a bud, regardless of shape or crispness of definition, and to inclusion of tumour cell clusters within glandular lumina (“luminal pseudobuds”). Although absolute numbers differed, semi-automated and manual bud counts were strongly correlated across cores (ρ=0.81, p<0.0001). All methods of budding assessment demonstrated poorer survival associated with higher budding scores.
Conclusions: Conclusions: We present a new QuPath-based approach to tumour budding assessment, which compares favorably to established methods and offers a freely-available, rapid and transparent tool that is also applicable to whole slide images.
Original language | English |
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Journal | Histopathology |
Early online date | 28 Sept 2021 |
DOIs | |
Publication status | E-pub ahead of print - 28 Sept 2021 |
Keywords / Materials (for Non-textual outputs)
- tumour budding
- colorectal cancer
- cytokeratin immunohistochemistry
- machine learning
- QuPath