European radiology · 2025
Crowd-sourcing optimized abdomen CT protocols from 908,000 examinations in a large radiation dose registry.
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Smith-Bindman Rebecca, Kang Taewoon, Stewart Carly, Chu Philip W, Wang Yifei, Szczykutowicz Timothy P
Аннотация
OBJECTIVES: Identify routine diagnostic abdomen CT protocols in adults that achieve lower radiation doses, crowd-sourced from a large CT dose registry.
MATERIALS AND METHODS: We retrospectively captured acquisition parameters, patient diameter, and patient size-adjusted and unadjusted radiation dose (CTDIvol and DLP). A protocol was defined as a unique combination of facility, scanner make/model, CT indication, and protocol name. We used k-means clustering to classify protocols into clusters based on similarity of average acquisition parameters (mAs, pitch, kV, collimation, scan length, phase count), each representing a distinct pattern of protocol design choices. For each cluster, we summarized the mean technical parameters and dose metrics of its constituent protocols.
RESULTS: Analyses included 907,992 exams from 1767 protocols at 132 facilities, grouped in 9 clusters. The number of protocols and exams within each cluster ranged from 62 to 508 and 15,317 to 381,457, respectively. Mean size-adjusted DLP varied threefold across clusters, ranging from 486 to 1382 mGy-cm, with no difference in patient diameter. Lowest-dosed clusters 1 and 2 minimized radiation primarily through low kV (around 100). Cluster 8 had the highest acquisition techniques (mean mAs = 338 and kV = 125), and cluster 9 had the highest dose due to phase (mean = 3.3, versus 1.1-1.6 for the remaining clusters).
CONCLUSION: The clustering approach offers a new framework for identifying optimized protocols, while highlighting variation in practice and worst-in-class technique, e.g., using three phases for routine abdomen. These findings may guide clinicians in protocol design, by providing best-practice protocols from a large registry, as well as a method for analyzing data within their own health system.
KEY POINTS: Question Can we identify best-practice imaging protocols from a large CT registry, to offer clinicians a blueprint for optimizing radiation dose in routine abdomen CT? Findings Protocols were grouped into clusters using average acquisition parameters. Across clusters, patient size-adjusted radiation dose varied 486-1382 mGy-cm. Lowest-dosed protocols had one phase and low kVp. Clinical relevance We used crowd-sourcing and k-means clustering to identify routine abdomen CT protocols that achieve lowest radiation dose, offering a playbook for protocol design from real clinical practice. Non-indicated phases were the greatest driver of excessive radiation dose.
MATERIALS AND METHODS: We retrospectively captured acquisition parameters, patient diameter, and patient size-adjusted and unadjusted radiation dose (CTDIvol and DLP). A protocol was defined as a unique combination of facility, scanner make/model, CT indication, and protocol name. We used k-means clustering to classify protocols into clusters based on similarity of average acquisition parameters (mAs, pitch, kV, collimation, scan length, phase count), each representing a distinct pattern of protocol design choices. For each cluster, we summarized the mean technical parameters and dose metrics of its constituent protocols.
RESULTS: Analyses included 907,992 exams from 1767 protocols at 132 facilities, grouped in 9 clusters. The number of protocols and exams within each cluster ranged from 62 to 508 and 15,317 to 381,457, respectively. Mean size-adjusted DLP varied threefold across clusters, ranging from 486 to 1382 mGy-cm, with no difference in patient diameter. Lowest-dosed clusters 1 and 2 minimized radiation primarily through low kV (around 100). Cluster 8 had the highest acquisition techniques (mean mAs = 338 and kV = 125), and cluster 9 had the highest dose due to phase (mean = 3.3, versus 1.1-1.6 for the remaining clusters).
CONCLUSION: The clustering approach offers a new framework for identifying optimized protocols, while highlighting variation in practice and worst-in-class technique, e.g., using three phases for routine abdomen. These findings may guide clinicians in protocol design, by providing best-practice protocols from a large registry, as well as a method for analyzing data within their own health system.
KEY POINTS: Question Can we identify best-practice imaging protocols from a large CT registry, to offer clinicians a blueprint for optimizing radiation dose in routine abdomen CT? Findings Protocols were grouped into clusters using average acquisition parameters. Across clusters, patient size-adjusted radiation dose varied 486-1382 mGy-cm. Lowest-dosed protocols had one phase and low kVp. Clinical relevance We used crowd-sourcing and k-means clustering to identify routine abdomen CT protocols that achieve lowest radiation dose, offering a playbook for protocol design from real clinical practice. Non-indicated phases were the greatest driver of excessive radiation dose.