Body weight is an indispensable parameter for determination of the dose of contrast media, appropriate drug dosing, or management of radiation dose. In this study, the predicted body weight, by applying a deep learning technique to chest and abdominal CT scout images, was found to be highly correlated with the actual body weight. Our models showed the MAE within 5.0 kg in both chest and abdominal datasets, even with a relatively modest training dataset size.
To the best of our knowledge, this is the first attempt to predict the body weight from CT scout images by applying a deep learning technique. In contrast, previous studies have required diagnostic abdominal CT images or effective mAs from whole body scan data for body weight estimation. This indicates that our CNN-based method can predict the patient body weight, even when non-contrast CT images do not exist. In clinical radiology, we frequently perform contrast-enhanced CT immediately after the first “scout” or “localizer” acquisition without acquiring non-contrast CT images. Thus, our method could be applicable to more cases than previous proposed methods.
Fernandes et al. reported that patients’ own weight estimates are likely to be more accurate than those of physicians or nurses, if weight measurement on an accurate scale is impractical. However, patients in emergency care often have difficulty in reporting their own body weight. A bedside method using supine thigh and abdominal circumference measurements by Buckley et al. yielded greater accuracy compared to visual body weight estimates made by physicians and nurses, but deviations > ± 10 kg from measured body weight were still noted in 15% of male patients and 27% of female patients. An equation based on effective mAs by Gascho et al. revealed strong correlation (r = 0.969) between measured and predicted body weight for both women and men with a postmortem interval < 4 days. The present study showed that deviations > ± 10 kg from the actual body weight were noted in only 1.6% for chest and 8.7% for abdomen. The correlations between the actual and predicted body weight were strong (r > 0.9) in both the chest and abdomen. These results suggest that our CNN-based method shows potential use in predicting patient body weight accurately in the adult population with unknown body weight.
In this study, better correlation was observed in chest scout images than in abdominal scout images. One possible reason was that the dataset size of abdominal scout images was less compared to that of chest scout images. Conversely, a previous study by Fukunaga et al. has shown a similar tendency to the present study, in which a better correlation between body weight and effective diameter was found in chest CT compared to abdominal CT. Surprisingly, it seems that body weight should be therefore estimated not from the abdominal region but from the chest region, if the scan range includes the chest region.
There were several limitations in our study. First, sex was not considered in creating models due to a limited number of datasets. An equation by Gascho et al. has considered sex in body weight estimation, according to the multivariate linear regression analysis. Therefore, performance of our models could be improved by considering sex. Second, we only trained and tested our models on CT scout images of medical checkup subjects, and our results may not generalize to some clinical settings. The performance of our models should be assessed in patients who are unable to raise their hand or have metallic implants. Third, this was a retrospective study with the training and test sets from a single institution, and the ability of the models to generalize to CT scout images obtained at external institutions with other machines is unknown. Finally, we only created our models on chest and abdominal regions. However, we could apply our models to different scan ranges, such as neck to pelvis, chest to pelvis, and abdomen to pelvis by cropping the chest or abdominal regions.
In conclusion, our CNN-based method can predict body weight from chest and abdominal CT scout images. There would be a possibility that appropriate contrast medium dosing and CT dose management are achieved in adult patients with unknown body weight.