BACKGROUND AND PURPOSE: To analyse the results of routine EPID measurements for individualised patient dosimetry. MATERIALS AND METHODS: Calibrated camera-based EPIDs were used to measure the central field dose, which was compared with a dose prediction at the EPID level. For transit dosimetry, dose data were calculated using patient transmission and scatter, and compared with measured values. Furthermore, measured transit dose data were back-projected to an in vivo dose value at 5 cm depth in water (D(5)) and directly compared with D(5) from the treatment planning system. Dose differences per treatment session were calculated by weighting dose values with the number of monitor units per beam. Reported errors were categorised and analysed for approximately 37,500 images from 2511 patients during a period of 24 months. RESULTS: Pre-treatment measurements showed a mean dose difference per treatment session of 0.0+/-1.7% (1 SD). Transfer errors were detected and corrected prior to the first treatment session. An accelerator output variation of about 4% was found between two weekly QC measurements. Patient dosimetry showed mean transit and D(5) dose differences of -0.7+/-5.2% (1 SD) and -0.3+/-5.6% (1 SD) per treatment session, respectively. Dose differences could be related to set-up errors, organ motion, erroneous density corrections and changes in patient anatomy. CONCLUSIONS: EPIDs can be used routinely to accurately verify treatment parameter transfer and machine output. By applying transit and in vivo dosimetry, more insight can be obtained with respect to the different error sources influencing dose delivery to a patient.
BACKGROUND AND PURPOSE: To analyse the results of routine EPID measurements for individualised patient dosimetry. MATERIALS AND METHODS: Calibrated camera-based EPIDs were used to measure the central field dose, which was compared with a dose prediction at the EPID level. For transit dosimetry, dose data were calculated using patient transmission and scatter, and compared with measured values. Furthermore, measured transit dose data were back-projected to an in vivo dose value at 5 cm depth in water (D(5)) and directly compared with D(5) from the treatment planning system. Dose differences per treatment session were calculated by weighting dose values with the number of monitor units per beam. Reported errors were categorised and analysed for approximately 37,500 images from 2511 patients during a period of 24 months. RESULTS: Pre-treatment measurements showed a mean dose difference per treatment session of 0.0+/-1.7% (1 SD). Transfer errors were detected and corrected prior to the first treatment session. An accelerator output variation of about 4% was found between two weekly QC measurements. Patient dosimetry showed mean transit and D(5) dose differences of -0.7+/-5.2% (1 SD) and -0.3+/-5.6% (1 SD) per treatment session, respectively. Dose differences could be related to set-up errors, organ motion, erroneous density corrections and changes in patient anatomy. CONCLUSIONS: EPIDs can be used routinely to accurately verify treatment parameter transfer and machine output. By applying transit and in vivo dosimetry, more insight can be obtained with respect to the different error sources influencing dose delivery to a patient.
Authors: Philippe Lambin; Ruud G P M van Stiphout; Maud H W Starmans; Emmanuel Rios-Velazquez; Georgi Nalbantov; Hugo J W L Aerts; Erik Roelofs; Wouter van Elmpt; Paul C Boutros; Pierluigi Granone; Vincenzo Valentini; Adrian C Begg; Dirk De Ruysscher; Andre Dekker Journal: Nat Rev Clin Oncol Date: 2012-11-20 Impact factor: 66.675
Authors: A Piermattei; F Greco; M Grusio; S Menna; L Azario; G Stimato; E Placidi; S Teodoli; S Cilla; A Porcelli; L Alberico; A Fidanzio Journal: Med Biol Eng Comput Date: 2018-04-23 Impact factor: 2.602
Authors: Hugo J W L Aerts; Angela A W van Baardwijk; Steven F Petit; Claudia Offermann; Judith van Loon; Ruud Houben; Anne-Marie C Dingemans; Rinus Wanders; Liesbeth Boersma; Jacques Borger; Gerben Bootsma; Wiel Geraedts; Cordula Pitz; Jean Simons; Bradly G Wouters; Michel Oellers; Philippe Lambin; Geert Bosmans; Andre L A J Dekker; Dirk De Ruysscher Journal: Radiother Oncol Date: 2009-03-28 Impact factor: 6.280
Authors: Angelo Piermattei; Andrea Fidanzio; Luigi Azario; Francesca Greco; Alessandra Mameli; Savino Cilla; Luca Grimaldi; Guido D'Onofrio; Boris Giuseppe Augelli; Gerardina Stimato; Diego Gaudino; Sara Ramella; Rolando D'Angelillo; Francesco Cellini; Lucio Trodella Journal: Med Biol Eng Comput Date: 2009-02-17 Impact factor: 2.602
Authors: T C Harris; J Seco; D Ferguson; M Lehmann; P Huber; M Shi; M Jacobson; I Valencia Lozano; M Myronakis; P Baturin; R Fueglistaller; D Morf; R Berbeco Journal: Phys Med Biol Date: 2020-12-07 Impact factor: 4.174