Summary
Background: Radiology reports are commonly written on free-text using voice recognition devices.
Structured reports (SR) have a high potential but they are usually considered more
difficult to fill-in so their adoption in clinical practice leads to a lower efficiency.
However, some studies have demonstrated that in some cases, producing SRs may require
shorter time than plain-text ones. This work focuses on the definition and demonstration
of a methodology to evaluate the productivity of software tools for producing radiology
reports. A set of SRs for breast cancer diagnosis based on BI-RADS have been developed
using this method. An analysis of their efficiency with respect to free-text reports
has been performed.
Material and Methods: The methodology proposed compares the Elapsed Time (ET) on a set of radiological
reports. Free-text reports are produced with the speech recognition devices used in
the clinical practice. Structured reports are generated using a web application generated
with TRENCADIS framework. A team of six radiologists with three different levels of
experience in the breast cancer diagnosis was recruited. These radiologists performed
the evaluation, each one introducing 50 reports for mammography, 50 for ultrasound
scan and 50 for MRI using both approaches. Also, the Relative Efficiency (REF) was
computed for each report, dividing the ET of both methods. We applied the T-Student
(T-S) test to compare the ETs and the ANOVA test to compare the REFs. Both tests were
computed using the SPSS software.
Results: The study produced three DICOM- SR templates for Breast Cancer Diagnosis on mammography,
ultrasound and MRI, using RADLEX terms based on BIRADs 5th edition. The T-S test on
radiologists with high or intermediate profile, showed that the difference between
the ET was only statistically significant for mammography and ultrasound. The ANOVA
test performed grouping the REF by modalities, indicated that there were no significant
differences between mammograms and ultrasound scans, but both have significant statistical
differences with MRI. The ANOVA test of the REF for each modality, indicated that
there were only significant differences in Mammography (ANOVA p = 0.024) and Ultrasound
(ANOVA p = 0.008). The ANOVA test for each radiologist profile, indicated that there
were significant differences on the high profile (ANOVA p = 0.028) and medium (ANOVA
p=0.045).
Conclusions: In this work, we have defined and demonstrated a methodology to evaluate the productivity
of software tools for producing radiology reports in Breast Cancer. We have evaluated
that adopting Structured Reporting in mammography and ultrasound studies in breast
cancer diagnosis improves the performance in producing reports.
Keywords
Structured reporting - DICOM-SR - BI-RADS - breast cancer
