Poster Poster Program Therapy Physics

Dosimetric Impact of Hidden Input Parameters In Inverse Optimization Algorithms for GYN HDR Brachytherapy: A Systematic In-House Study

Abstract
Purpose

To quantify the dosimetric impact of hidden input parameters in three inverse optimization (IO) algorithms—IPSA, HIPO, and MCO—for GYN HDR brachytherapy across two applicator types.

Methods

In-house implementations of IPSA, HIPO, and MCO were developed and compared against retrospectively generated commercial TPS plans (Oncentra Brachy) using identical clinical input parameters across 24 cervical cancer cases (18 T&O; 6 T&O+Needles (T&O+N)). Each IO algorithm was tested with 1,000 combinations of hidden parameters (e.g., dwell-time modulation constraints, convergence thresholds, etc). Cumulative DVH curves and dosimetric indices (HR-CTV D98/D90, OAR D2cc) were compared to commercial plans. Standard deviations (SD) of DVH differences quantified sensitivity to hidden parameters.

Results

For HR-CTV, SD values in T&O+N cases were recorded as 23.0 Gy and 7.1 Gy for MCO and HIPO, respectively, with corresponding average values of 55.8 Gy and 19.7 Gy. In T&O cases of HR-CTV, SD values were recorded as 4.9 Gy and 3.3 Gy for HIPO and IPSA, respectively, while their average values were measured as 20.1 Gy and 8.6 Gy. MCO presented the highest sensitivity, followed by HIPO and IPSA. T&O+N presented higher sensitivity over T&O. Absolute differences in HR-CTV D90 (D98) compared with commercial algorithms reached up to 33.3 Gy (28.4) for T&O+N cases, and 10.8 Gy (8.5) for T&O cases. For OARs, absolute D2cc differences in T&O+N (T&O) cases were up to 8.6 Gy (2.3) (rectum), 17 Gy (10.2) (bladder), 14.8Gy (3.9) (sigmoid), and 7.0 Gy (8.1) (bowel).

Conclusion

Hidden input parameter settings significantly impact GYN HDR plans—up to 28.4 Gy in target coverage, regardless of the IO algorithm type for both intracavitary and intracavitary plus needle cases. The findings in this study shown considerable potential to yield improved plans through hidden input parameter optimization.

People

Related

Similar sessions

Poster Poster Program
Jul 19 · 07:00
Python-Based Automation Framework for Annual Machine QA Data Archiving In Qatrack+

Annual water-tank measurements help ensure beam characteristics remain consistent with commissioning baselines. However, the lack of a standardized processing workflow and decentralized data storage makes it difficult to analyze...

Syed Bilal Ahmad, PhD
Therapy Physics 0 people interested
Poster Poster Program
Jul 19 · 07:00
User Expectations and Current Availability of HDR Brachytherapy Audits In Europe

The aim of this work was to evaluate the need to implement more dosimetric audits in high‐dose‐rate brachytherapy (HDR-BT) in Europe and to identify which characteristics such audits should meet according to users.

Javier Vijande, PhD Laura Oliver Cañamás
Therapy Physics 0 people interested