The purpose of this retrospective study was to simulate a daily pre-alignment strategy to mitigate systematic positioning errors in image-guided pediatric hadron therapy. All pediatric patients (32 patients, 853 fractions) treated from December 2021 and September 2022 at our Institution were retrospectively considered. For all fractions, daily correction vectors (CVs) resulting from image registration for patient positioning were retrieved in the form of txt files from the hospital database. For each fraction, an adjusted correction vector (V ') was then computed as the difference between the actual one (V) and the algebraic average of the previous ones, as to simulate patient pre-alignment before imaging. The Euclidean norm of each V ' was computed and normalized with respect to that of the corresponding V to derive N. Pre-correcting all the coordinate values led to a 46% average reduction (min 20%, max 60%) in CVs, considering the first 27 fractions (average value in this cohort of patients). Such a potential improvement (N < 1) was observed for the most patients' fractions (781/853, 91.6%). For the remaining 72/853 cases (8.4%), a remarkable worsening (N > 2) involved only 7/853 (0.82%) fractions. The presented strategy shows promising outcomes in order to ameliorate pediatric patient setup before imaging. However, further investigations to identify patients most likely to benefit from this approach are warranted.
Personalized Setup Optimization Strategies to Improve Clinical Workflow in Image-Guided Pediatric Particle Therapy
Pella, Andrea;Paganelli, Chiara;Baroni, Guido
2024-01-01
Abstract
The purpose of this retrospective study was to simulate a daily pre-alignment strategy to mitigate systematic positioning errors in image-guided pediatric hadron therapy. All pediatric patients (32 patients, 853 fractions) treated from December 2021 and September 2022 at our Institution were retrospectively considered. For all fractions, daily correction vectors (CVs) resulting from image registration for patient positioning were retrieved in the form of txt files from the hospital database. For each fraction, an adjusted correction vector (V ') was then computed as the difference between the actual one (V) and the algebraic average of the previous ones, as to simulate patient pre-alignment before imaging. The Euclidean norm of each V ' was computed and normalized with respect to that of the corresponding V to derive N. Pre-correcting all the coordinate values led to a 46% average reduction (min 20%, max 60%) in CVs, considering the first 27 fractions (average value in this cohort of patients). Such a potential improvement (N < 1) was observed for the most patients' fractions (781/853, 91.6%). For the remaining 72/853 cases (8.4%), a remarkable worsening (N > 2) involved only 7/853 (0.82%) fractions. The presented strategy shows promising outcomes in order to ameliorate pediatric patient setup before imaging. However, further investigations to identify patients most likely to benefit from this approach are warranted.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.