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Cancer is one of the main causes of death throughout the world. Diagnosis of cancer is usually based on imaging diagnosis, such as magnetic resonance imaging (MRI) and computed tomography (CT). Since most patients cannot endure repeated CT examination and MRI is expensive, radiomics could be a new method to guide cancer treatment. We conducted a systematic review of literature of computer-aided diagnosis based on radiomics. Relevant studies were identified from PubMed and Embase from the date of inception to May 2019. Quality assessment was performed using QUADAS-2. Meta-analysis was used to make a summary of sensitivity, specificity, diagnostic threshold, area under the receiver operating characteristic curves (AUC), and median of sensitivity and specificity. From the initial 3627 records, we included 19 studies that reported data of 7047 patients. The sensitivity ranged from 0.53 to 0.96 and specificity from 0.63 to 0.97. With a minimum of 10 and a maximum of 300 patients in a single study, the pooled sensitivity of radiomics was 0.87, and the pooled specificity was 0.93. An AUC of 0.87 was reported from one study. No relevant side effects were observed in the reviewed studies. Radiomics can be used to diagnose and predict prognosis in cancer patients, including esophageal cancer, gastrointestinal cancer, rectal cancer, breast cancer, lung cancer, and non-small cell lung cancer. Studies of radiomics in lung, oropharyngeal and hypopharyngeal carcinoma, bladder cancer, and prostate cancer are still scarce. Although radiomics may have great potential in cancer diagnosis and treatment, it requires caution because of the poor quality of the studies.
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