Thanh-Tai Duong: A Novel Framework for Predicting TRT Doses Prior to Treatment
Thanh-Tai Duong

Thanh-Tai Duong: A Novel Framework for Predicting TRT Doses Prior to Treatment

Thanh-Tai Duong, Therapeutic Medical Physicist at Abben Cancer Center – Spencer Hospital, shared a short summary of his recent research:

“While personalized dosimetry is crucial for optimizing Targeted Radioligand Therapy (TRT), its clinical implementation remains a challenge due to the logistical burden of multiple post-treatment SPECT/CT scans. This proof-of-concept study introduces a novel framework for predicting therapeutic radiation doses prior to treatment.

By utilizing dynamic 18F-DCFPyL PET/CT scans from prostate cancer patients, we demonstrated that pre-treatment diagnostic imaging can reliably estimate voxel-based absorbed doses for 177Lu-PSMA-617.

This approach enables clinicians to optimize treatment planning and potentially integrate TRT with other modalities, such as external beam radiation therapy, moving us closer to truly personalized, multi-modal cancer care.”

Title: A proof-of-concept study of personalized dosimetry for targeted radioligand therapy using pre-treatment diagnostic dynamic PET/CT and Monte Carlo simulation

Authors: Thanh Tai Duong, Danny De Sarno, Hatim Fakir, Glenn Bauman, Martin Martinov, Rowan M. Thomson, Ting-Yim Lee

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Thanh-Tai Duong: A Novel Framework for Predicting TRT Doses Prior to Treatment

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Thanh-Tai Duong: A Novel Framework for Predicting TRT Doses Prior to Treatment