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68Ga-PSMA-11 PET/CT Features Extracted from Different Radiomic Zones Predict Response to Androgen Deprivation Therapy
Vuong Thuy Tran1, Shu-Ju Tu1,2,3, Jing-Ren Tseng4,5
1Department of Medical Imaging and Radiological Sciences, College of Medicine, Chang Gung University, Tao-Yuan 333, Taiwan.
Radiomic features from prostate zones on 68Ga-PSMA-11 PET/CT scans can predict response to androgen deprivation therapy (ADT) in advanced prostate cancer (PCa) patients. This aids in personalized treatment selection before therapy begins.
Area of Science:
- Oncology
- Radiology
- Medical Imaging
Background:
- Predicting treatment response to androgen deprivation therapy (ADT) for advanced prostate cancer (PCa) is challenging.
- Personalized medicine approaches are needed to optimize ADT efficacy.
Purpose of the Study:
- To investigate the utility of 68Ga-PSMA-11 PET/CT radiomic features from distinct prostate zones in predicting ADT response.
- To identify pre-treatment imaging biomarkers for ADT responders versus non-responders in advanced PCa.
Main Methods:
- 35 advanced PCa patients underwent 68Ga-PSMA-11 PET/CT scans before (PET-1) and after 3 months of ADT (PET-2).
- The prostate was segmented into three radiomic zones: metabolic tumor zone (zone-1), proximal peripheral tumor zone (zone-2), and extended peripheral tumor zone (zone-3).
- Radiomic features were extracted from each zone to differentiate responders (reduction ratio > 30%) from non-responders.
Main Results:
- Specific radiomic features from zone-1 (e.g., glcm_idmn, shape_MeshVolume), zone-2 (e.g., gldm_sdlgle), and zone-3 (e.g., diagnostics_Mask-interpolated_Minimum) distinguished ADT responders from non-responders.
- The shape_SurfaceVolumeRatio feature was consistently identified across all three zones as a predictive marker.
Conclusions:
- Radiomic features derived from different prostatic zones on pre-treatment 68Ga-PSMA-11 PET/CT scans show potential for predicting ADT response in advanced PCa.
- These imaging biomarkers could facilitate personalized treatment strategies by identifying patients likely to benefit from ADT prior to initiation.
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