» Articles » PMID: 33458354

Evaluation of Automated Pre-treatment and Transit In-vivo Dosimetry in Radiotherapy Using Empirically Determined Parameters

Overview
Specialty Oncology
Date 2021 Jan 18
PMID 33458354
Citations 22
Authors
Affiliations
Soon will be listed here.
Abstract

Background And Purpose: First reports on clinical use of commercially automated systems for Electronic Portal Imaging Device (EPID)-based dosimetry in radiotherapy showed the capability to detect important changes in patient setup, anatomy and external device position. For this study, results for more than 3000 patients, for both pre-treatment verification and in-vivo transit dosimetry were analyzed.

Materials And Methods: For all Volumetric Modulated Arc Therapy (VMAT) plans, pre-treatment quality assurance (QA) with EPID images was performed. In-vivo dosimetry using transit EPID images was analyzed, including causes and actions for failed fractions for all patients receiving photon treatment (2018-2019). In total 3136 and 32,632 fractions were analyzed with pre-treatment and transit images respectively. Parameters for gamma analysis were empirically determined, balancing the rate between detection of clinically relevant problems and the number of false positive results.

Results: Pre-treatment and in-vivo results depended on machine type. Causes for failed in-vivo analysis included deviations in patient positioning (32%) and anatomy change (28%). In addition, errors in planning, imaging, treatment delivery, simulation, breath hold and with immobilization devices were detected. Actions for failed fractions were mostly to repeat the measurement while taking extra care in positioning (54%) and to intensify imaging procedures (14%). Four percent initiated plan adjustments, showing the potential of the system as a basis for adaptive planning.

Conclusions: EPID-based pre-treatment and in-vivo transit dosimetry using a commercially available automated system efficiently revealed a wide variety of deviations and showed potential to serve as a basis for adaptive planning.

Citing Articles

A commissioning protocol for portal imaging-based radiotherapy in vivo dosimetry systems.

Esposito M, Baldoni R, Bossuyt E, Bresciani S, Clark C, Jones M Phys Imaging Radiat Oncol. 2024; 32:100666.

PMID: 39624392 PMC: 11609462. DOI: 10.1016/j.phro.2024.100666.


A Preliminary Investigation of Radiation-Sensitive Ultrasound Contrast Agents for Photon Dosimetry.

Carlier B, Heymans S, Nooijens S, Collado-Lara G, Toumia Y, Delombaerde L Pharmaceuticals (Basel). 2024; 17(5).

PMID: 38794199 PMC: 11125270. DOI: 10.3390/ph17050629.


Systematic evaluation of spatial resolution and gamma criteria for quality assurance with detector arrays in stereotactic radiosurgery.

Stedem A, Tutty M, Chofor N, Langhans M, Kleefeld C, Schonfeld A J Appl Clin Med Phys. 2024; 25(2):e14274.

PMID: 38265979 PMC: 10860444. DOI: 10.1002/acm2.14274.


Multi-institutional generalizability of a plan complexity machine learning model for predicting pre-treatment quality assurance results in radiotherapy.

Claessens M, De Kerf G, Vanreusel V, Mollaert I, Hernandez V, Saez J Phys Imaging Radiat Oncol. 2024; 29:100525.

PMID: 38204910 PMC: 10776441. DOI: 10.1016/j.phro.2023.100525.


Validation of an in vivo transit dosimetry algorithm using Monte Carlo simulations and ionization chamber measurements.

Sanchez-Artunedo D, Pie-Padro S, Hermida-Lopez M, Duch-Guillen M, Beltran-Vilagrasa M J Appl Clin Med Phys. 2023; 25(2):e14187.

PMID: 37890864 PMC: 10860462. DOI: 10.1002/acm2.14187.


References
1.
Olch A, OMeara K, Wong K . First Report of the Clinical Use of a Commercial Automated System for Daily Patient QA Using EPID Exit Images. Adv Radiat Oncol. 2019; 4(4):722-728. PMC: 6817722. DOI: 10.1016/j.adro.2019.04.001. View

2.
Mijnheer B, Gonzalez P, Olaciregui-Ruiz I, Rozendaal R, Van Herk M, Mans A . Overview of 3-year experience with large-scale electronic portal imaging device-based 3-dimensional transit dosimetry. Pract Radiat Oncol. 2015; 5(6):e679-87. DOI: 10.1016/j.prro.2015.07.001. View

3.
Persoon L, Nijsten S, Wilbrink F, Podesta M, Snaith J, Lustberg T . Interfractional trend analysis of dose differences based on 2D transit portal dosimetry. Phys Med Biol. 2012; 57(20):6445-58. DOI: 10.1088/0031-9155/57/20/6445. View

4.
Bojechko C, Ford E . Quantifying the performance of in vivo portal dosimetry in detecting four types of treatment parameter variations. Med Phys. 2015; 42(12):6912-8. DOI: 10.1118/1.4935093. View

5.
Zhuang A, Olch A . Sensitivity study of an automated system for daily patient QA using EPID exit dose images. J Appl Clin Med Phys. 2018; 19(3):114-124. PMC: 5978566. DOI: 10.1002/acm2.12303. View