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Department of Radiation Oncology: Artificial Intelligence in Medicine Seminar Series

 

Radka Stoyanova, Ph.D., Professor and Director of Imaging and Biomarkers Research, Department of Radiation Oncology, University of Miami
"Radiogenomic Characterization of mpMRI Habitats for Effective Management of Prostate Cancer"

 

Abstract: Prostate cancer clinical prognostic factors explain only a fraction of the observed variations in clinical outcomes. While genomic classifiers have been introduced to help in the clinical management of patients with prostate cancer, both histopathological and genomic assessment are subject to biopsy sampling error. The “habitats” concept was introduced in imaging to characterize and map tumor heterogeneity and in the prostate, imaging “habitats” refer to areas with similar quantitative characteristics on multiparametric (mp)MRI. We used the perfusion and diffusion mpMRI sequences to devise the Habitat Risk Score (HRS), an algorithm that associates a quantitative measure on a pixel-by-pixel basis for the risk of malignancy. HRS is represented as a heat map overlaid on MRI, depicting tumor heterogeneity. We have implemented HRS in MRI/Ultrasound-fused targeted biopsies and automatic delineation of the intraprostatic tumor volume for focal delivery of radiation boost. The radiomics and genomic features associated with the habitats are used in building predictive models for better selection of patients for active surveillance or radiation response. In addition, changes in habitat characteristics (delta radiomics) are used to monitor response to treatment.

 

Bio: Dr. Stoyanova has an extensive background in developing approaches to best utilize imaging techniques in cancer research, diagnosis, and treatment. She has more than 100 publications on the development of approaches for analysis, mining, and interpretation of “big data” generated by high-throughput approaches such as genomics, proteomics, metabolomics, and radiomics. Having been working in a clinical department for a considerable part of her career, Dr. Stoyanova has directed her research toward the development and implementation of tailored techniques for addressing significant clinical questions. Her research focuses on the delineation of tumor heterogeneity via image-defined “habitats”. To map tumor heterogeneity in the prostate, her team has devised a Habitat Risk Score system based on mpMRI data – a pixel-by-pixel 10-grade score system in increasing the order of aggressiveness. The resulting heat-maps are integrated into the MRI/Ultrasound fusion system to assign prostate biopsy targets and in the Radiation Treatment Planning System – to define the volumes for radiation boost. The habitats are further characterized using radiomics for developing prognostic and predictive models. Dr. Stoyanova’s overarching goal is to develop a multifaceted approach, whereby combining data about habitat directed biopsies, biopsy tissue biomarkers, and in vivo imaging (functional and metabolic) can lead to the informed design of effective treatment for improved tumor control and reduced toxicity.

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