{
  "abstract": "Background Ischaemic stroke due to cancer is becoming more common with high mortality rate. There is an unmet need to predict cancer aetiology in patients with stroke using brain imaging alone, to facilitate early diagnosis and treatment.Aims To describe unique brain imaging patterns of cancer-related stroke and thereby develop a predictive model for diagnosis of stroke due to cancer. Our hypothesis was that such imaging patterns would be more closely associated with metastatic cancer.Methods Retrospective cohort study at two neighbouring sites in Australia from 2014 to 2022. The cohort group included patients with acute ischaemic stroke due to active cancer. The control group consisted of conventional stroke aetiologies and no active cancer diagnosis. Brain imaging using MRI diffusion-weighted imaging sequences classified lesions by distribution, vascular territories, lesion number and whether multifocal, crossed territories or scattered. Statistical analysis used adjusted logistic regression models. Machine learning-based predictive modelling evaluated the predictive capacity on a diagnosis of metastatic cancer.Results There were 138 patients available for analysis. A three-territory sign was the only significant imaging predictor for cancer aetiology in the multivariable analysis (OR 20.79; 95% CI 2.44 to 177.47, p=0.006). In the machine learning modelling, both logistic regression and support vector machines models predicted the presence of metastatic cancer well with a balanced accuracy of 75% and 79%, respectively, and area under the curve (receiver operating characteristic area) scores of 0.85 and 0.87, respectively.Conclusions Brain imaging alone might potentially predict cancer aetiology with good accuracy in patients with stroke, especially in metastatic cancer.",
  "authors": [
    {
      "affiliations": [
        "The University of Newcastle, Newcastle, New South Wales, Australia",
        "The University of Newcastle Hunter Medical Research Institute, New Lambton, New South Wales, Australia"
      ],
      "name": "Shyam Gangadharan"
    },
    {
      "affiliations": [
        "The University of Newcastle, Newcastle, New South Wales, Australia",
        "John Hunter Hospital Department of Neurology, Newcastle, New South Wales, Australia"
      ],
      "name": "Christopher Levi"
    },
    {
      "affiliations": [
        "John Hunter Hospital Department of Neurology, Newcastle, New South Wales, Australia",
        "Liverpool Hospital, Liverpool, New South Wales, Australia"
      ],
      "name": "Mark Parsons"
    },
    {
      "affiliations": [
        "The University of Newcastle, Newcastle, New South Wales, Australia",
        "John Hunter Hospital Department of Neurology, Newcastle, New South Wales, Australia"
      ],
      "name": "Neil Spratt"
    },
    {
      "affiliations": [
        "The University of Newcastle, Newcastle, New South Wales, Australia",
        "John Hunter Hospital Department of Neurology, Newcastle, New South Wales, Australia"
      ],
      "name": "Carlos Garcia Esperon"
    },
    {
      "affiliations": [
        "The University of Newcastle, Newcastle, New South Wales, Australia"
      ],
      "name": "Sarah Johnson"
    },
    {
      "affiliations": [
        "The University of Newcastle, Newcastle, New South Wales, Australia"
      ],
      "name": "Md Golam Hasnain"
    },
    {
      "affiliations": [
        "The University of Queensland, Brisbane, Queensland, Australia"
      ],
      "name": "Raka Datta"
    },
    {
      "affiliations": [
        "John Hunter Hospital Department of Neurology, Newcastle, New South Wales, Australia"
      ],
      "name": "Beng Lim Alvin Chew"
    }
  ],
  "title": "Predicting cancer aetiology in patients with stroke using brain imaging alone",
  "uid": "2576481d-d24f-5511-8abf-c4c81603e4c6"
}