European radiology · 2022
Comparison of detection of trauma-related injuries using combined "all-in-one" fused images and conventionally reconstructed images in acute trauma CT.
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Higashigaito Kai, Fischer Gioia, Jungblut Lisa, Blüthgen Christian, Schwyzer Moritz, Eberhard Matthias, Dos Santos Daniel Pinto, Baessler Bettina, Vuylsteke Pieter, Soons Joris A M, Frauenfelder Thomas
Аннотация
OBJECTIVES: To compare the accuracy of lesion detection of trauma-related injuries using combined "all-in-one" fused (AIO) and conventionally reconstructed images (CR) in acute trauma CT.
METHODS: In this retrospective study, trauma CT of 66 patients (median age 47 years, range 18-96 years; 20 female (30.3%)) were read using AIO and CR. Images were independently reviewed by 4 blinded radiologists (two residents and two consultants) for trauma-related injuries in 22 regions. Sub-analyses were performed to analyze the influence of experience (residents vs. consultants) and body region (chest, abdomen, skeletal structures) on lesion detection. Paired t-test was used to compare the accuracy of lesion detection. The effect size was calculated (Cohen's d). Linear mixed-effects model with patients as the fixed effect and random forest models were used to investigate the effect of experience, reconstruction/image processing, and body region on lesion detection.
RESULTS: Reading time of residents was significantly faster using AIO (AIO: 266 ± 72 s, CR: 318 ± 113 s; p < 0.001; d = 0.46) while no significant difference was observed in the accuracy of lesion detection (AIO: 93.5 ± 6.0%, CR: 94.6 ± 6.0% p = 0.092; d = - 0.21). Reading time of consultants showed no significant difference (AIO: 283 ± 82 s, CR: 274 ± 95 s; p = 0.067; d = 0.16). Accuracy was significantly higher using CR; however, the difference and effect size were very small (AIO 95.1 ± 4.9%, CR: 97.3 ± 3.7%, p = 0.002; d = - 0.39). The linear mixed-effects model showed only minor effect of image processing/reconstruction for lesion detection.
CONCLUSIONS: Residents at the emergency department might benefit from faster reading time without sacrificing lesion detection rate using AIO for trauma CT.
KEY POINTS: • Image fusion techniques decrease the reading time of acute trauma CT without sacrificing diagnostic accuracy.
METHODS: In this retrospective study, trauma CT of 66 patients (median age 47 years, range 18-96 years; 20 female (30.3%)) were read using AIO and CR. Images were independently reviewed by 4 blinded radiologists (two residents and two consultants) for trauma-related injuries in 22 regions. Sub-analyses were performed to analyze the influence of experience (residents vs. consultants) and body region (chest, abdomen, skeletal structures) on lesion detection. Paired t-test was used to compare the accuracy of lesion detection. The effect size was calculated (Cohen's d). Linear mixed-effects model with patients as the fixed effect and random forest models were used to investigate the effect of experience, reconstruction/image processing, and body region on lesion detection.
RESULTS: Reading time of residents was significantly faster using AIO (AIO: 266 ± 72 s, CR: 318 ± 113 s; p < 0.001; d = 0.46) while no significant difference was observed in the accuracy of lesion detection (AIO: 93.5 ± 6.0%, CR: 94.6 ± 6.0% p = 0.092; d = - 0.21). Reading time of consultants showed no significant difference (AIO: 283 ± 82 s, CR: 274 ± 95 s; p = 0.067; d = 0.16). Accuracy was significantly higher using CR; however, the difference and effect size were very small (AIO 95.1 ± 4.9%, CR: 97.3 ± 3.7%, p = 0.002; d = - 0.39). The linear mixed-effects model showed only minor effect of image processing/reconstruction for lesion detection.
CONCLUSIONS: Residents at the emergency department might benefit from faster reading time without sacrificing lesion detection rate using AIO for trauma CT.
KEY POINTS: • Image fusion techniques decrease the reading time of acute trauma CT without sacrificing diagnostic accuracy.