• Saudi Med J · Mar 2021

    Prediction of squamous cell carcinoma cases from squamous cell hyperplasia in throat lesions using CT radiomics model.

    • Osama A Khodrog, Fengzhi Cui, Nannan Xu, Qinghe Han, Jianhua Liu, Tingting Gong, and Qinghai Yuan.
    • From the Department of Radiology (Khodrog, Cui, Xu, Han, Liu, Gong, Yuan), the Second Hospital of Jilin University, Changchun, China and from the Department of Medical Imaging (Khodrog), Faculty of Applied Medical Health, Palestine Ahliya University, Bethlehem, Palestine.
    • Saudi Med J. 2021 Mar 1; 42 (3): 284-292.

    ObjectivesTo differentiate squamous cell hyperplasia (SCH) (benign) from squamous cell carcinoma (SCC) malignant) using textural features extracted from CT images and thereby, facilitate the preoperative medical diagnosis and treatment of throat cancers without the need for sample biopsies.MethodsIn total, 100 throat cancer patients were selected for this retrospective study. The cases were collected from the Second Hospital of Jilin University, Changchun, China, from June 2017 to January 2019. The patients were separated into a training and validation cohort consisting of 70 and 30 cases, respectively. The Artificial Intelligence Kit software (A.K. software) was used to extract the radiomics features from the CT images. These features were further processed using the minimum redundancy maximum relevance (mRMR) and least absolute shrinkage and selection operator (LASSO) methods to obtain a subset of optimal features. The radiomics model was validated based on area-under-the-curve (AUC) values, accuracy, specificity, and sensitivity using the R-studio software.ResultsThe diagnostic accuracy, specificity, PPV, NPV, and AUC values obtained for the training cohort was 0.91, 0.9, 0.93, 0.9, and 0.96 CT angiography (CTA), 0.93, 0.93, 0.95, 0.90, and 0.96 computed tomography normal (CTN), and 0.92, 0.87, 0.91, 0.96, and 0.96 CT venogram (CTV). These values were subsequently confirmed in the validation cohort.ConclusionThe radiomics-based prediction model proposed in this study successfully differentiated between SCH and SCC throat cancers using CT imaging, thereby facilitating the development of accurate preoperative diagnosis based on specific biomarkers and cancer phenotypes.Copyright: © Saudi Medical Journal.

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