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Abstract #2342

SLICs Algorithm for Non-Invasive Response Evaluation in Osteosarcoma with Multiparametric MR Imaging

Amit Mehndiratta1, Esha Badiya Kayal1, Sneha Patil 1, Sameer Bakhshi2, Raju Sharma3, and Devasenathipathy Kandasamy3

1Centre for Biomedical Engineering, Indian Institute of Technology Delhi, New Delhi, India, 2Medical Oncology, IRCH, All India Institute of Medical Sciences, New Delhi, India, 3Radio Diagnosis, All India Institute of Medical Sciences, New Delhi, India

Osteosarcoma is a highly morbid bone-tumor with poor prognosis. Neoadjuvant-chemotherapy(NACT) is the current standard of care. The response of NACT is judged on Histopathology-examination(HPE) after surgical resection of tumor. However, a non-invasive and accurate methods for evaluation of treatment response during the course of therapy is highly desirable. In this research, a Simple-linear-iterative-clustering supervoxels(SLICs) algorithm based methodology using multiparametric MRI (T2,DWI and ADC) has been developed for identification of sub-parts of tumor (active-tumor, necrosis). The volume of active-tumor and necrosis were estimated using this novel approach in patients with OS, before NACT(baseline) and after 3 cycles of NACT(follow-up). The level of necrosis estimated using SLICs and measure with HPE showed a close match. SLICs based estimation of necrosis level is a non-invassive technique that can be useful in response evaluation of cancer imaging.

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