[P159] Design and application of a metric to perform routinely quality assurance of dose plans. (August 2018)

• Record Type: Journal Article
• Authors: Fernández, Irene; Díaz-Martín, Alba; Pérez-Molina, Juan Luis; Ruiz-Egea, Eugenio; Guirado, Damián; Tornero-López, Ana María
• Is Part Of: Physica medica. Volume 52(2018)Supplement 1
• Page Start: 144
• Publication Date: 2018-08
• Subjects: Medical physics -- Periodicals; Biophysics -- Periodicals; Biophysics -- Periodicals; Imagerie médicale -- Périodiques; Radiothérapie -- Périodiques; Rayons X -- Sécurité -- Mesures -- Périodiques; Physique -- Périodiques; Médecine -- Périodiques; 610.153
• DOI: 10.1016/j.ejmp.2018.06.461
• Languages: English
• ISSNs: 1120-1797

Abstract

Abstract : Purpose: In this work a suitable metric named dosimetric quality index (DQI) for quality assurance of dose planning performance is developed and implemented by means of statistical control process tools. We analyzed its robustness and reliability in performing good quality dosimetries while monitoring the process in order to progressively improve them. Methods: The DQI definition relies on the radiobiological concept that an optimal dosimetry should maximize the Tumor Control Probability (TCP) while minimizing the Normal Tissue Control Probability (NTCP). A series of 126 intermediate risk prostate cancer dosimetries provides the database from which distributions of minimum dose to PTV, and mean dose to rectum, bladder and femoral heads have been obtained in order to create a DQI set, assumed as the initial reference state (IRS), according to the expression: DQI = TCP Π ( 1 - NTCP ) For statistical control purposes, a lower DQI limit has been assessed by generating dosimetries of different quality levels using MC methods based on the real distributions of the aforementioned variables. We consider the dosimetries in the 5% lower quartile of the DQI probability function distribution as improvable, and we analyze its features. Results: The statistical analysis shows that dosimetries with a DQI smaller than the DQI lower limit are characterized by having more than two OR with mean doses bigger than the mean of the corresponding IRS distributions. Also, if the minimum dose to the PTV is smaller than the mean of the IRS distribution, and at least one OR is over irradiated, the dosimetry may have as well a DQI smaller than the DQI lower limit. The DQI statistical control process tool provides a time evolution visualization of the quality dosimetries. Conclusions: A radiobiological based control quality metric, DQI, has been designed and utilized to statistically perform a quality assurance of dose plans. The DQI helps to improve the dosimetry before its evaluation by the physician, and therefore may be a routinely used, time saving procedure. Better and better quality dosimetries may be achieved by progressively raising the overall DQI value and eventually, changing the IRS to a higher quality level.