JMIR Publications

ABSTRACT

Background:

Despite the existing evidence that waist circumference (WC) provides independent and additive information to body mass index for predicting morbidity and mortality, this measurement is not routinely obtained in clinical practice. Using CT scan images, mobile health (mHealth) has the potential to make WC parameter easily available even in retrospective studies.

Objective:

This study aimed to develop a mobile app as a tool for facilitating the measurement of WC, based on a cross-sectional CT image.

Methods:

The development process included three stages: determination of principles of WC measurement on CT images; app prototype design and prototype validation. We performed a preliminary validity study, in which we compared waist circumference measurements obtained both by the conventional method using a tape measurement in a standing position and by the mobile app using the last abdominal CT slice not showing the iliac bone. Pearson’s correlation, Student’s t tests, Q-Q and Bland-Altman plots were used for statistical analysis. Moreover, in order to perform a diagnostic test evaluation, we also analysed the accuracy of the app in detecting abdominal obesity.

Results:

We developed a prototype of the app “Measure It” capable of estimating the WC from a single cross-sectional CT image. We used an estimation based on an ellipse formula adjusted to gender of the patient. The validity study was proposed to 20 patients, including 10 men and 10 women. There was a good correlation between both measurements (Pearson R =0,906). The student t test showed there were no significant differences between the two measurements (P=0,978). Both Q-Q dispersion plot and Bland-Altman analysis graphs showed good overlapping with some dispersion of extreme values. The diagnostic test evaluation showed an accuracy of 83% when using the mobile app to detect abdominal obesity.

Conclusions:

This app is a simple and accessible mHealth tool with the purpose of routinely including WC as a valuable obesity parameter in clinical and research practice. Usability and validity evaluation among medical teams will be the next step prior to its use in clinical trials and multicentric studies.