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- Geessink, Oscar G. F., et al.
(författare)
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Computer aided quantification of intratumoral stroma yields an independent prognosticator in rectal cancer
- 2019
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Ingår i: Cellular Oncology. - : SPRINGER. - 2211-3428 .- 2211-3436. ; 42:3, s. 331-341
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Tidskriftsartikel (refereegranskat)abstract
- PurposeTumor-stroma ratio (TSR) serves as an independent prognostic factor in colorectal cancer and other solid malignancies. The recent introduction of digital pathology in routine tissue diagnostics holds opportunities for automated TSR analysis. We investigated the potential of computer-aided quantification of intratumoral stroma in rectal cancer whole-slide images.MethodsHistological slides from 129 rectal adenocarcinoma patients were analyzed by two experts who selected a suitable stroma hot-spot and visually assessed TSR. A semi-automatic method based on deep learning was trained to segment all relevant tissue types in rectal cancer histology and subsequently applied to the hot-spots provided by the experts. Patients were assigned to a stroma-high or stroma-low group by both TSR methods (visual and automated). This allowed for prognostic comparison between the two methods in terms of disease-specific and disease-free survival times.ResultsWith stroma-low as baseline, automated TSR was found to be prognostic independent of age, gender, pT-stage, lymph node status, tumor grade, and whether adjuvant therapy was given, both for disease-specific survival (hazard ratio=2.48 (95% confidence interval 1.29-4.78)) and for disease-free survival (hazard ratio=2.05 (95% confidence interval 1.11-3.78)). Visually assessed TSR did not serve as an independent prognostic factor in multivariate analysis.ConclusionsThis work shows that TSR is an independent prognosticator in rectal cancer when assessed automatically in user-provided stroma hot-spots. The deep learning-based technology presented here may be a significant aid to pathologists in routine diagnostics.
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| 2. |
- Salazar, Ramon, et al.
(författare)
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Comparison of ColoPrint risk classification with clinical risk in the prospective PARSC trial
- 2014
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Ingår i: Journal of Clinical Oncology. - Inst Catala Oncol, Early Clin Res Unit, Lhospitalet Barcelona, Spain. Vall dHebron Univ Hosp, Barcelona, Spain. Kantonsspital Baden, Dept Surg, Baden, Switzerland. Akad Univ Hosp, Uppsala, Sweden. Westfries Gasthuis, Hoorn, Netherlands. Inst Canc Montpelier, Dept Pathol, Montpellier, France. Med Spectrum Twente, Enschede, Netherlands. Univ Texas MD Anderson Canc Ctr, Houston, TX 77030 USA. Med Ctr Alkmaar, Alkmaar, Netherlands. Med Univ Vienna, Vienna, Austria. Univ Oxford, Dept Oncol, Oxford, England. Wake Forest Univ, Bowman Gray Sch Med, Winston Salem, NC USA. Matsuda Hosp, Hamamatsu, Shizuoka, Japan. Acad Teaching Hosp, Linz, Austria. South Orange Cty Surg Med Grp, Laguna Hills, CA USA. Norfolk & Norwich Univ Hosp NHS FT, Norwich, Norfolk, England. Univ Hong Kong, Queen Mary Hosp, Hong Kong, Hong Kong, Peoples R China. Long Beach Mem Med Ctr, Long Beach, CA USA. Agendia, Amsterdam, Netherlands. Georgetown Univ, Lombardi Comprehens Canc Ctr, Washington, DC USA.. - 0732-183X .- 1527-7755. ; 32:15
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Tidskriftsartikel (refereegranskat)
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