Integrated Registration and Harmonization Framework for Quantitative T2-weighted MRI Analysis following Prostate Cancer Radiotherapy
Motivation: The reliable evaluation of T2-weighted MRI (T2w) signal change in prostate cancer following radiotherapy (RT) is challenging due to deformations (physiological and RT-related) and scanner/protocol acquisition variability. Goal(s): To develop an automated and reproducible methodology for quantification of T2w signal change in longitudinal studies following RT. Approach: The methodology includes T2w image intensity harmonization and deformable registration of post-RT to pre-RT images for automated detection of prostate, peripheral zone and tumor volume. Results: The repeatability in T2w intensity estimation improved following the automatic registration relative to manual contours; and the quantitative changes of T2w reached significance when pre- and post-RT series were compared. Impact: The developed methodology allows to automatically detect ROIs in post-RT MRI exams, reduces data acquisition-related variation and improves imaging features’ repeatability, thereby enables the quantitative characterization of RT-induced changes in T2w.
Authors
- Radka Stoyanova (ORCID: https://orcid.org/0000-0002-1301-3228)
- Matthew K. Abramowitz (ORCID: https://orcid.org/0000-0001-6984-9799)
- Sanoj Punnen (ORCID: https://orcid.org/0000-0002-0383-7311)
- Ahmad Algohary (ORCID: https://orcid.org/0000-0003-1286-3164)
- Evangelia I. Zacharaki (ORCID: https://orcid.org/0000-0001-8228-0437)
- Adrian Breto (ORCID: https://orcid.org/0000-0002-4958-2991)
- Veronica Wallaengen
- Alan Pollack
Publication Details
- Journal
- Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
- Published
- 2024-11-26
- DOI
- https://doi.org/10.58530/2024/0543
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00