Page 79 - SDIR5 Abstract book 21 12 2021.

POSTER PRESENTATIONS

P39

An Adapted One-dimensional Computational Approach for Irregular ROI Analysis Improves
Osteosarcoma Classification

3
2
Goran J. Djuričić ,*, Helmut Ahammer , Jelena P. Sopta , Jelena Djokić Kovač , Zorica Milošević , Jelena
1
5
4
6
6
Milovanović and Marko Radulovic ,*
1 Department of Radiology, University Children's Hospital, School of Medicine, University of Belgrade, 11000
Belgrade, Serbia.
2 Division of Biophysics, GSRC, Medical University of Graz, 8010 Graz, Austria
3 Institute of Pathology, School of Medicine, University of Belgrade, 11000 Belgrade, Serbia
4 Center for Radiology, Clinical Center Serbia, School of Medicine, University of Belgrade, 11000 Belgrade, Serbia
5 Clinic for Radiation Oncology and Radiology, Institute for Oncology & Radiology of Serbia, 11000 Belgrade, Serbia.
6
Department of Experimental Oncology, Institute for Oncology & Radiology of Serbia, 11000 Belgrade, Serbia.

Background: The analysis of irregularly shaped tumour ROIs is hindered by the fact that most image analysis
methods apart from first-order statistics are compatible only with rectangular ROIs. We thus aimed for the
first implementation and testing of the 1-D MRI image analysis method that is fully compatible with
irregular ROIs. Material and methods: The retrospective prediction model of osteosarcoma
chemoresponsiveness included T2-weighted MRI scans obtained before OsteoSa MAP neoadjuvant
cytotoxic chemotherapy. Osteosarcoma morphology was quantified by calculating the one- and two-
dimensional (1-D, 2-D) Higuchi dimensions (Dh), directionally and non-directionally. Results: The non-
directional 1-D Dh reached a predictive AUC of 0.88, while the directional 1-D analysis along 180 radial lines
robustly improved the predictive performance, reaching an AUC of 0.95, P<0.001 that is widely considered
o
o
as nearly ideal. The optimal directional range was between 90 and 97 . Conclusions: We report the first
validity testing of the 1-D analysis approach that is fully compatible with irregular ROIs. Such analytical
adaptation to ROI shape in MRI has enhanced the osteosarcoma prediction performance over the
previously reported standard 2-D analyses. The clinical importance of the early chemoresponsiveness
prediction rests on its potential to prolong the survival of chemoresistant patients through personalised
treatment adjustments.

66