Factors modulating 99m Tc-MAA planar lung dosimetry for 90 Y radioembolization.
J Appl Clin Med Phys
; 23(12): e13734, 2022 Dec.
Article
em En
| MEDLINE
| ID: mdl-35906892
PURPOSE: To investigate the accuracy and biases of predicted lung shunt fraction (LSF) and lung dose (LD) calculations via 99m Tc-macro-aggregated albumin (99m Tc-MAA) planar imaging for treatment planning of 90 Y-microsphere radioembolization. METHODS AND MATERIALS: LSFs in 52 planning and LDs in 44 treatment procedures were retrospectively calculated, in consecutive radioembolization patients over a 2 year interval, using 99m Tc-MAA planar and SPECT/CT imaging. For each procedure, multiple planar LSFs and LDs were calculated using different: (1) contours, (2) views, (3) liver 99m Tc-MAA shine-through compensations, and (4) lung mass estimations. The accuracy of each planar-based LSF and LD methodology was determined by calculating the median (range) absolute difference from SPECT/CT-based LSF and LD values, which have been demonstrated in phantom and patient studies to more accurately and reliably quantify the true LSF and LD values. RESULTS: Standard-of-care LSF using geometric mean of lung and liver contours had median (range) absolute over-estimation of 4.4 percentage points (pp) (0.9 to 11.9 pp) from SPECT/CT LSF. Using anterior views only decreased LSF errors (2.4 pp median, -1.1 to +5.7 pp range). Planar LD over-estimations decreased when using single-view versus geometric-mean LSF (1.3 vs. 2.6 Gy median and 7.2 vs. 18.5 Gy maximum using 1000 g lung mass) but increased when using patient-specific versus standard-man lung mass (2.4 vs. 1.3 Gy median and 11.8 vs. 7.2 Gy maximum using single-view LSF). CONCLUSIONS: Calculating planar LSF from lung and liver contours of a single view and planar LD using that same LSF and 1000 g lung mass was found to improve accuracy and minimize bias in planar lung dosimetry.
Palavras-chave
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Embolização Terapêutica
/
Neoplasias Hepáticas
Tipo de estudo:
Prognostic_studies
Limite:
Humans
Idioma:
En
Ano de publicação:
2022
Tipo de documento:
Article