Patient-specific organ dose and in-vivo image quality assessment in clinical CT.

PURPOSE: To develop and characterize individualized dose and quality measures at organ level compared to their generic counterparts across a clinical CT dataset. MATERIALS AND METHODS: The study included 9801 chest-abdomen-pelvis and abdomen-pelvis CT exams (7,763 patients, mean age, 56 ± 17 years; 4113 women) representing 20 unique protocols. For each exam, patient-specific organ dose of all radiosensitive organs was estimated using a validated method by generating personalized computational phantoms and Monte Carlo simulations. Effective dose (EOD) was calculated by weighted sum of the organ doses. Liver dose, ODliver, noise in the liver, Nliver, and observer model detectability, d', were assessed within the liver as examples of individualized, organ-based image assessment measurements. The organ-based measurements (ODliver, EOD, and Nliver) were compared to their generic counterparts: ssize-specific ddose estimates (SSDE), effective dose based on dose length product (EDLP), and whole-body noise (Nglobal), respectively. RESULTS: Generic dose values were substantially higher than individualized estimates for SSDE vs. ODliver (median of all exams: 51.2 %, p < 0.001) and EDLP vs. EDOD (median: 41.0 %, p < 0.001). Nglobal was generally lower than Nliver (median: -7.2 %, p < 0.001). The correlation relationships of EOD and d' were substantially varied (R2 range: 0-0.5) for different patient sizes and scan parameters. CONCLUSIONS: Demonstrated across a population of exams, individualized organ-based measurements of dose and quality are feasible. Generic measures cannot fully represent individualized organ-based values. The correlation relationships between individualized dose and image quality values varies for different vendors and protocols, implying imaging optimization is best when done semi-independently for each factor using individualized measurements.

Duke Scholars

Author William Paul Segars Radiology

Author Francesco Ria Radiology

Author Justin Solomon Radiology

Author Aiping Ding Radiology