Objective: In the differential diagnosis between uterine fibroids and uterine sarcomas, realworld magnetic resonance imaging (MRI) diagnostic information is scarce; furthermore, high diagnostic sensitivity is important in clinical practice. We previously developed a diagnostic algorithm to detect uterine sarcoma with high sensitivity using simple MRI images and serum lactate dehydrogenase (LDH) levels. In this multicenter study, we investigated the preoperative diagnosis of sarcoma in the real world and further validated the usefulness of our diagnostic algorithm. Methods: Of 154 uterine sarcomas and 154 uterine fibroids treated at 15 centers between January 2006 and December 2020, 139 sarcomas (16 smooth muscle tumors of uncertain malignant potential) and 141 fibroids with diffusion-weighted imaging information were included in the analysis. The diagnostic algorithm was validated by 3 radiologists who were blinded to the clinical information and pathologic diagnoses and who read the MRIs. Results: The sensitivity/specificity of preoperative diagnosis was 77.7%/92.9% for the preoperative report; 92.1%/72.3% for algorithm A; and 82.0%/85.8% for algorithm B (McNemar’s test p<0.05). Comparison of overall survival rates among 3 groups (Group 1: negative A, Group 2: positive A and negative B; Group 3: positive B) using algorithms A and B showed p=0.012. On multivariate analysis, stage, and serum LDH level were independent prognostic factors. Conclusion MRI is useful for preoperative diagnosis of uterine sarcoma, and the sarcoma diagnostic algorithm presented in this study is an option for diagnosing sarcoma with greater sensitivity. This information should be shared with patients.

Objective: Instructions contained in over-the-counter medicine package inserts can be hard to read because of the limited printing space.  Pictograms are one means of helping users to understand important information.  However, few pictogram systems have been reliably and validly evaluated.  Therefore, a new method was developed to improve the clarity of each illustration and the legitimacy as a pictogram for conveying information important.
Methods: Four creators developed 69 illustrations, each of which expressed one of 24 instructions in the package insert of an H2 blocker.  In a survey, participants (449 university undergraduate and graduate students and 103 pharmacy users) were asked to describe the possible meaning of each illustration and to provide their personal suggestions for improvement.  To evaluate comprehension of information, each instruction was broken into two or three different parts.  Comprehension level was calculated by: (number of people who answered correctly) × 100 / (total number of respondents).  Existing pictograms were included to compare comprehension levels for the same instructions.
Results: Using 67% as the minimum standard for comprehension, we classified each illustration into one of three categories: “no need for improvement,” “need for partial improvement,” and “need for total improvement.”  The students and pharmacy users tended to accurately interpret the possible meanings of illustrations that were familiar to them.
Conclusion: Breaking one instruction of the package insert into a few important pieces of information was useful for determining the level of improvement needed for each illustration.  Evaluating how well each illustration conveys important information in the instructions through two steps was also beneficial, which are to improve the illustration’s clarity with students and its legitimacy among pharmacy users for fulfilling the intended functions of a pictogram.