Since 1975, global obesity has nearly tripled, reports the World Health Organization (2020).
In 2016, more than 1.9 billion adults aged 18 years and older were overweight and more than 650 million of them were obese (World Health Organization, 2020). In Slovenia, 58.1% of the adult population aged 18 years and older is considered overweight or obese (Statistical Office of the Republic of Slovenia, 2020). Overweight and obesity are defined as excessive fat accumulation that can have harmful effects on health. To determine the nutritional status in adults, we use the classification of body mass index (BMI). It is defined as a person's weight in kilograms divided by their height in meters squared. The BMI classification is divided into six groups based on the effect of excessive body fat on health and well related to obesity (Table 1). This classification was developed as a risk indicator for disease, i.e. as BMI increases, so does the risk of disease (World Health Organization/Europe, 2021).
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Table 1: BMI classification (World Health Organization/Europe, 2021) BMI Nutritional status radiographers need to adjust the procedures based on issues arising from both technical and patient care, such as patients exceeding imaging equipment weight limits, potential motion artefacts due to increased exposure parameters that also increase exposure time, inadequate image detector coverage, and difficulty palpating anatomic landmarks. It also compromises the balance between adequate radiation exposure and minimizing dose (Le et al., 2015).
Previous studies (Efthymiou et al., 2020; Zalokar et al., 2020; Metaxas et al., 2018; Chan et al., 2012; Yanch et al., 2009), investigated the effect of BMI on the radiation dose received in overweight and obese patients. These studies reported an increase in the radiation dose received by these patient groups when compared to those with normal weight, taking into account BMI classification. Chan et al. (2012) found in their study that for each kilogram of weight, there was an increase in effective dose for computed tomography (CT) of the abdomen and pelvis of 0.13 mSv, equivalent to 6.5 chest X-rays per CT examination, and for an increase in BMI of 5 kg/m2, there was an increase in effective dose of 1.95 mSv, equivalent to 97.5 chest X-rays per CT examination.
Zalokar et al., 2020 report that in their research, during pelvic AP X-ray examination, DAP increased in a group of overweight patients for 52% and for 135% in a group of obese patients in comparison to the group of patients with normal weight. The increase of effective dose was 46% in overweight patients and 123% in obese patients, both compared to the normal-weight patients. The increase of dose on individual organs was similar to the effective dose, 37% and 107%, respectively. They found image quality differences between normal and overweight group of patients, but not between groups of normal and obese or overweight and obese patients. They also concluded that DAP and effective dose are strongly
related to BMI and that BMI has a very strong effect on the dose received by the patients during X-ray imaging, so the patients with higher BMI can receive several times higher dose than those with normal body weight (Zalokar et al., 2020).
Alzyoud et al. (2019) performed a study on an anthropomorphic phantom to estimate how increasing body thickness affects radiographic quality and effective dose during pelvic imaging. Within this work the authors simulated fat on the aforementioned phantom, by using commercially available catering lard. The results showed that it is important to adjust the exposure parameters when performing pelvic X-ray examinations in obese patients. They found that the best image quality was obtained when using a tube potential of 70 kV at all fat thicknesses, while when using high tube potentials, 105 and 110 kV, the quality of the X-ray image decreased by about 68%. The effective dose was increased by 856% at 15 cm fat thickness at 80 kV. At 110 kV, the effective dose was lowest for all thicknesses. For all thicknesses used, there were characteristic differences in effective dose when different tube potentials were used, such that the radiation dose increased exponentially with increasing thickness of the imaging object. Acceptable image quality was achieved with a range of imaging parameters, but the optimal tube potential was reached at 70 and 75 kV for all fat thicknesses. This is actually contrary to professional practice, where radiographers usually tend to increase the tube potential with increasing patient thickness. However, the authors suggest that if the primary factor is radiation dose, higher tube potential could be used in pelvic radiography as patient thickness increases (Alzyoud et al., 2019).
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2 PURPOSE
The purpose of this study is to determine whether the radiation dose and image quality differ between two different erect pelvic radiographic procedures, with and without fat tissue removal. Based on the above, this study seeks to determine how much of a difference there is between the radiation doses received by the patient and how does the tissue removal technique affect the resultant images based on established image quality criteria. This study will compare the acquired images and the radiation doses received between patients who will move the fat tissue from the region of interest (pelvis) and those who do not.
Based on the literature review the following research questions have been established:
Q1: How does fat tissue removal during erect pelvic imaging affect the resultant dose area product?
Q2: How does fat tissue removal during erect pelvic imaging affect the patient's entrance skin dose?
Q3: How does fat tissue removal during erect pelvic imaging affect the patient’s effective dose?
Q4: How does fat tissue removal during erect pelvic imaging affect image quality?
3 METHODS
The measurements were divided into two parts. In the first part, measurements were performed on an anthropomorphic phantom, and in the second part, the experimental methods were performed on 60 patients referred for pelvic imaging in the erect position. The participants were randomly divided into two equal groups, half of them where imaged removing the fat tissue from the region of interest (n=30) and the other group did not remove the tissue from the ROI (n=30).
The exact sample size was calculated based on a preliminary result using the GPower 3.1 analysis tool. The calculated total number of patients was 56, with 28 participants in each group. Based on the calculated sample size, this study has a power of 95% to detect a difference in image quality and doses received between two groups of patients.