Comparison of visual and automated assessment of tumour inflammatory infiltrates in patients with colorectal cancer |
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| Affiliation: | 1. Academic Unit of Surgery, School of Medicine, University of Glasgow, Royal Infirmary, Glasgow G31 2ER, UK;2. University Department of Pathology, Southern General Hospital, Glasgow, UK;1. Department of Dermatology, Erasmus MC University Medical Center, Rotterdam, The Netherlands;2. Eindhoven Cancer Registry, Comprehensive Cancer Centre South, Eindhoven, The Netherlands;3. Department of Public Health, Erasmus MC University Medical Center, Rotterdam, The Netherlands;4. Department of Surgical Oncology, Erasmus MC University Medical Center – Daniel den Hoed Cancer Center, Rotterdam, The Netherlands;5. Department of Clinical Epidemiology, Viecuri Medical Centre, Venlo, The Netherlands;1. Department of Otolaryngology and Head & Neck Surgery, Navy General Hospital, Beijing, China;2. Department of Epidemiology, The University of Texas M.D. Anderson Cancer Center, Houston, TX 77030, USA;3. Duke Cancer Institute, Duke University Medical Center, 905 South Lasalle Street, Durham, NC 27710, USA;4. Department of Head and Neck Surgery, The University of Texas M.D. Anderson Cancer Center, Houston, TX 77030, USA;1. Children’s Cancer Research Institute, Vienna, Austria;2. Institute of Pathology, Medical University of Vienna, Austria;3. Department of Hematology, Medical University Vienna, Vienna, Austria;4. Department of Oncology, Medical University Vienna, Vienna, Austria;5. Institute of Pathology and Microbiology, Hanusch-Krankenhaus, Vienna, Austria;6. Department of Pediatrics, Medical University Vienna, Vienna, Austria;1. Department of Radiation Oncology, VU University Medical Center, Amsterdam, The Netherlands;2. William Buckland Radiation Oncology, Alfred Health, Melbourne, Australia;1. Department of Dermatology, Edouard Herriot Hospital Group, Lyon, France;2. Department of Pathology, Aristotelian University of Thessaloniki, Thessaloniki, Greece;1. Department of Genetics, Wroclaw Medical University, Wroclaw, Poland;2. Department and Clinic of Internal Medicine and Allergology, Wroclaw Medical University, Wroclaw, Poland;3. Institute of Human Genetics, Saarland University, Homburg, Germany |
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| Abstract: | BackgroundCancer-associated inflammation is increasingly recognised to be an important determinant of oncological outcome. In colorectal cancer, the presence of peri-tumoural inflammatory/lymphocytic infiltrates predicts improved survival. To date, these infiltrates, assessed visually on haematoxylin and eosin (H&E) stained sections, have failed to enter routine clinical practice, partly due to their subjective assessment and considerable inter-observer variation. The present study aims to develop an automated scoring method to enable consistent and reproducible assessment of tumour inflammatory infiltrates in colorectal cancer.Methods154 colorectal cancer patients who underwent curative resection were included in the study. The local inflammatory infiltrate was assessed using the method described by Klintrup–Makinen. H&E tumour sections were uploaded to an image analysis programme (Slidepath, Leica Biosystems). An image analysis algorithm was developed to count the inflammatory cells at the invasive margin. The manual and automated assessments of the tumour inflammatory infiltrates were then compared.ResultsThe automated inflammatory cell counts assessed using the freehand annotation method (p < 0.001) and the rectangular box method (p < 0.001) were significantly associated with both K–M score (p < 0.001) and K–M grade (p < 0.001). The inflammatory cell counts were divided using quartiles to group tumours with similar inflammatory cell densities. There was good agreement between the manual and automated scoring methods (intraclass correlation coefficient (ICC) = 0.82). Similar to the visual K–M scoring system, the automated K–M classification of the inflammatory cell counts, using quartiles, was significantly associated with venous invasion (p < 0.05) and modified Glasgow Prognostic Score (mGPS) (p ⩽ 0.05). On univariate survival analysis, both automated K–M category (p < 0.05) and automated K–M grade (p < 0.005) were associated with cancer-specific survival.ConclusionThe results of the present study demonstrate that automated assessment effectively recapitulates the clinical value of visual assessment of the local inflammatory cell infiltrate at the invasive margin of colorectal tumours. In addition, it is possible to obtain an objective assessment of tumour inflammatory infiltrates using routinely stained H&E sections. An automated, computer-based scoring method is therefore a workable and cost-effective approach to clinical assessment of local immune cell infiltrates in colorectal cancer. |
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| Keywords: | Tumour inflammatory cell infiltrate Automated assessment Colorectal cancer |
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