Carbohydrate Estimation Supported by the GoCARB System in Individuals With Type 1 Diabetes

Background

For individuals with type 1 diabetes (T1D) the current gold standard to evaluate the carbohydrate (CHO) amount of a meal is by carefully weighing its different components and calculating the CHO content using reference nutritional tables. The resulting CHO amount is then used to define the insulin dose needed to avoid an abnormal postprandial glucose profile. Since this is a cumbersome procedure in real life, diabetic individuals often estimate the CHO amount based on their personal experience. Especially for food served on a plate CHO estimates are often significantly over or underestimated leading to high variation in postprandial blood glucose. Besides the immediate risk of hypoglycaemia, there is emerging evidence that suboptimal control of postprandial glucose is affiliated with increased risk for long-term complications (e.g. diabetic micro- and macro-vascular diseases).

The effect of CHO counting in T1D control has been increasingly recognized and investigated. A meta-analysis including five studies on individuals with T1D has shown, that improved CHO counting accuracy reduces the HbA1c significantly (0.64% reduction in HbA1c compared to a control group). Teaching adult individuals with T1D to count CHO reduces HbA1c significantly and also leads to an improvement in quality of life. Similar findings are reported in children, in whom higher CHO counting accuracy is associated with a lower HbA1c. Even a short educational intervention of 4 weeks can still result in a significant and sustained effect on HbA1c reduction 9 months after without having an increase in hypoglycaemia. Lower CHO counting accuracy is a significant predictor of prolonged time in hyperglycaemic state. In one study with adults only 31% of the participants estimated the CHO content with an error of less than 20 grams per day and accurate CHO estimation were correlated with the lowest HbA1c values. In line with these findings another study has shown that individuals on intensive insulin therapy count CHO content of meals with an average error in the order of 16 grams or 21%. In general there is overestimation of small meals and a substantial underestimation of large meals. While breakfast (+8.5%) and snacks (-5%) were estimated fairly accurately, lunch (-28%) and dinner (-23%) are more prone to errors leading to an underestimation in the order of 30 grams. In children, an inaccuracy of ±10grams does not deteriorate the postprandial glycaemic control, whereas a ±20 grams variation significantly impacts the postprandial glycaemia.

The debate how to optimally estimate CHO intake is on-going and controversial. Fact is that even well trained diabetic individuals find it difficult to estimate CHO precisely and that especially meals served on a plate are prone to false estimations underlining an emergent need for novel approaches to CHO estimation. The investigators hypothesize that computer vision supported CHO estimation can have a beneficial impact on postprandial glucose control, ultimately leading to reduced episodes of hypoglycaemia and reduction in long term complications.

The recent advances in smartphone technologies and computer vision permitted the development of applications for the automatic dietary assessment through meal image analysis. The applications are using either a number of images or a short video of the upcoming meal, as captured by the user's smartphone. Although several systems have been proposed in the past decade, none of them is designed for individuals with diabetes, while they rely on strong assumptions, which often do not hold in real life, or require too much user input. The GoCARB system provides CHO estimations to individuals with T1D, by using only two meal images. The current version GoCARB has been designed to deal with