{
  "abstract": "Background Deep learning (DL) models are effective pre-screening tools for detecting mismatch repair deficiency (dMMR) in colorectal carcinoma (CRC). These models have been trained and validated on large cohorts from the Northern Hemisphere, without representation of African samples. We sought to determine the performance of a DL model in an ethnically heterogeneous cohort of patients from South Africa.Methods Our cohort comprised 197 CRC resection specimens, with scanned whole slide images tessellated and inputted into a transformer-based DL model trained on large international cohorts. Model performance was evaluated using area under the receiver operating characteristic curve (AUROC), sensitivity and specificity. The maximal Youden’s J index was calculated to determine the optimal cut-off threshold for the model prediction score.Results Our model yielded an AUROC of 0.91 (±0.05). Using a prediction score threshold of 0.620 produced an overall sensitivity of 85.7% (95% CI 73.3% to 92.9%) and a specificity of 82.4% (95% CI 75.5% to 87.7%). The false negative cases were predominantly left-sided (71.4%) and did not show the typical dMMR/microsatellite instability-high histological phenotype. Sensitivity was lower (50%–75%) in cases showing isolated PMS2 or MSH6 loss of staining. Calibrating the classification threshold to 0.470, the sensitivity was optimised to 95.6% (95% CI 86.3% to 98.9%) with a specificity of 69.6% (95% CI 61.8% to 76.4%). This would have resulted in excluding 103 cases (52.3%) from downstream immunohistochemical (IHC) or molecular testing.Conclusions Following appropriate region-specific calibration, we have shown that this model could be employed to accurately prescreen for dMMR in CRC, thereby reducing the burden of downstream IHC and molecular testing in a resource-limited setting.",
  "authors": [
    {
      "affiliations": [
        "Division of Anatomical Pathology, University of Cape Town, Observatory, South Africa",
        "JDW Pathology Inc, Cape Town, South Africa",
        "UCT MRC Genomic and Precision Medicine Research Unit, Division of Human Genetics, Department of Pathology, Institute of Infectious Diseases and Molecular Medicine, Faculty of Health Sciences and University of Cape Town, Cape Town, South Africa"
      ],
      "name": "Alessandro Pietro Aldera"
    },
    {
      "affiliations": [
        "Else Kroener Fresenius Center for Digital Health, Dresden University of Technology, Dresden, Germany"
      ],
      "name": "Didem Cifci"
    },
    {
      "affiliations": [
        "Department of Medicine, Section of Hematology/Oncology, The University of Chicago, Chicago, Illinois, USA"
      ],
      "name": "Gregory Patrick Veldhuizen"
    },
    {
      "affiliations": [
        "Division of Anatomical Pathology, University of Cape Town, Observatory, South Africa",
        "National Health Laboratory Services, Groote Schuur Hospital, Cape Town, South Africa"
      ],
      "name": "Wan-Jung Tsai"
    },
    {
      "affiliations": [
        "Division of Anatomical Pathology, University of Cape Town, Observatory, South Africa",
        "National Health Laboratory Services, Groote Schuur Hospital, Cape Town, South Africa"
      ],
      "name": "Komala Pillay"
    },
    {
      "affiliations": [
        "Division of General Surgery, Groote Schuur Hospital and University of Cape Town, Cape Town, South Africa"
      ],
      "name": "Adam Boutall"
    },
    {
      "affiliations": [
        "German Cancer Research Centre Division of Clinical Epidemiology and Aging Research, Heidelberg, Germany",
        "Division of Preventive Oncology, German Cancer Research Center (DKFZ) and National Center for Tumor Diseases (NCT), Heidelberg, Germany",
        "German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany"
      ],
      "name": "Hermann Brenner"
    },
    {
      "affiliations": [
        "German Cancer Research Centre Division of Clinical Epidemiology and Aging Research, Heidelberg, Germany"
      ],
      "name": "Michael Hoffmeister"
    },
    {
      "affiliations": [
        "Else Kroener Fresenius Center for Digital Health, Dresden University of Technology, Dresden, Germany",
        "Department of Medicine I, University Hospital Dresden, Dresden, Germany",
        "Medical Oncology, National Center for Tumour Diseases (NCT), University Hospital Heidelberg, Heidelberg, Germany"
      ],
      "name": "Jakob Nikolas Kather"
    },
    {
      "affiliations": [
        "UCT MRC Genomic and Precision Medicine Research Unit, Division of Human Genetics, Department of Pathology, Institute of Infectious Diseases and Molecular Medicine, Faculty of Health Sciences and University of Cape Town, Cape Town, South Africa"
      ],
      "name": "Raj Ramesar"
    }
  ],
  "title": "Deep learning predicts microsatellite instability status in colorectal carcinoma in an ethnically heterogeneous population in South Africa",
  "uid": "961fe8ac-0999-5eb1-b849-1fccd26d8fc1"
}