Spatial and Temporal Characterization of Gliomas Using Radiomic Analysis

Condition(s) studied

Investigational drug(s) / intervention(s)

Radiomic analysis of imaging - MRI, PET, CT: Radiomic analysis of imaging will be undertaken as a standard of care to develop computational algorithms for patients treated in our institution.

Study summary

Glioma are type of primary brain tumors arising within the substance of brain. Different type of gliomas are seen which are classified depending upon pathological examination and advanced molecular techniques, which help to determine the aggressiveness of the tumor and outcomes. Artificial intelligence uses advanced analytical process aided by computer which can be undertaken on the medical images. We plan to use artificial intelligence techniques to identify the abnormal areas within the brain representing tumor from the radiological images. Also, similar approach will be undertaken to classify gliomas with good or bad prognosis, to differentiate glioma from other type of brain tumors, and to detect response after treatment.

Eligibility

Primary outcome measure(s)

• Autosegmentation of tumor — 3 years
  The correlation of tumor region between manual segmentation and artificial intelligence-based autosegmentation model will be assessed using the Dice coefficient of similarity.
• Prognostication of gliomas — 3 years
  Radiomic signature in prognostication of gliomas with estimation of progression-free survival and overall survival using Kaplan Meier plots and radiomics score-based nomograms.

Trial sites (1)

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