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Congress: ECR25
Poster Number: C-12171
Type: Poster: EPOS Radiologist (scientific)
DOI: 10.26044/ecr2025/C-12171
Authorblock: C. Thouly1, B. Dufour1, N. Heracleous1, D. Moreira1, D. Ribeiro1, B. Rizk1, F. Zanca2; 1Sion/CH, 2Leuven/BE
Disclosures:
Cyril Thouly: Nothing to disclose
Benoît Dufour: Nothing to disclose
Natalie Heracleous: Nothing to disclose
Daniela Moreira: Nothing to disclose
Diana Ribeiro: Nothing to disclose
Benoît Rizk: Nothing to disclose
Federica Zanca: Nothing to disclose
Keywords: Artificial Intelligence, Bones, Paediatric, Conventional radiography, Digital radiography, RIS, Computer Applications-General, Cost-effectiveness, Structured reporting, Education and training, Outcomes
Results

The shift from manual to AI-assisted reporting resulted in a significant decrease in the time required to generate a report. The mean reporting time in Phase 1 was 3.5 minutes, with a range of 1 to 13 minutes, whereas in Phase 2, the mean time decreased to 1.58 minutes, with a range of 1 to 9 minutes. This represents a 55% reduction in reporting time, demonstrating the efficiency of AI-assisted reporting (p < 0.001). Figure 1 illustrates this reduction, showing the comparison between the two phases.

Fig 1: Average Reporting Time Reduction

A statistical summary of these findings is presented in Table 1.

Table 1: Statistical Summary

Beyond efficiency improvements, AI-assisted assessment provides automated and standardized bone age interpretation, reducing the likelihood of human error and improving workflow consistency across multiple centers. Figure 2 shows an example of a BoneXpert analysis, illustrating the automated bone age determination.

Fig 2: Example of BoneXpert Analysis

GALLERY