Efficacy Analysis of 1-Dimensional Water Tank for Clinical Physicist Practice
Abstract
Purpose
One-dimensional (1D) water tanks are widely used in clinical practice due to their efficiency and reduced setup complexity; however, measurement accuracy can be influenced by operational parameters selected during data acquisition. This study presents an efficacy-focused process analysis of a 1D water tank system, emphasizing the clinical impact of parameter selection on workflow efficiency and dosimetric accuracy.
Methods
A Sun Nuclear 1D water tank system was evaluated with emphasis on tank setup, water filling workflow, and PDD measurement procedures. Water filling was performed using a Venturi-effect-based apparatus derived from Bernoulli’s principle, designed to minimize physical effort and setup time. Following tank filling to approximately 30 cm depth, automated water surface detection was used to establish a 100 cm source-to-surface distance. A measurement chamber and reference chamber were connected to a PC Electrometer, with motion and data acquisition controlled via the manufacturer’s software. PDD scans were acquired for a 10 × 10 cm² field while varying chamber motion speeds and data filtering parameters.
Results
Procedure demonstrated that the Venturi-based filling approach reduced operator travel and physical workload by approximately an order of magnitude, improving procedural efficiency and safety. During PDD acquisition, chamber motion speed was identified as a critical parameter affecting dosimetric accuracy. Variations in scan speed from 0.1 mm/s to 2.0 mm/s produced shifts of up to 4 mm in the depth of maximum dose, highlighting the sensitivity of PDD measurements to temporal acquisition settings.
Conclusion
The 1D water tank provides an efficient and clinically practical solution for routine QA when appropriate scan parameters are selected. Optimization of chamber motion speed is essential to balance measurement efficiency and dosimetric precision. Future investigations should incorporate chamber volume effects, reference signal noise, and additional system variables to further standardize operational procedures and support robust clinical QA implementation.