A new study, published in the journal Radiology: Artificial Intelligence, suggests researchers can now predict which cancer patients will respond to chemotherapy by using radiomics to see beyond what’s visible in CT images alone. Radiomics enables technicians to extract quantitative data from CT images that can reveal disease characteristics. The study looked at the role of radiomic texture features – both within and around the lung tumor – in predicting time to progression and overall survival, as well as response to chemotherapy. Results showed that the radiomic features were able to distinguish patients who responded to chemotherapy and those who did not.
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The HealthMyne Platform is the only commercial system that calculates a comprehensive radiomic profile for every lesion and saves that data to a discoverable database. These metrics include simple data such as the long and short and evidence-based metrics as well complex radiomics such as texture and spiculation. All are easily mineable and available for inclusion in precision medicine initiatives including predictive prognoses such as those discussed in the above paper.