###### Abstract  
Computed tomography (CT) is a widely utilized diagnostic imaging modality in medicine. However, the potential risks associated with radiation exposure necessitate investigating CT exams to minimize unnecessary radiation. The objective of this study is to evaluate how patient-related parameters impact the CT dose indices for different CT exams. In this study, a dataset containing CT dose information for a cohort of 333 patients categorized into four CT exams, chest, cardiac angiogram, cardiac calcium score and abdomen/pelvis, was collected and retrospectively analyzed. Regression analysis and Pearson correlation were applied to estimate the relationships between patient-related factors, namely body mass index (BMI), weight and age as input variables, and CT dose indices, namely the volume CT dose index (CTD\({}_{\text{vol}}\)), dose length product (DLP), patient effective dose (ED) and size-specific dose estimate (SSDE), as output variables. Moreover, the study investigated the correlation between the different CT dose indices. Using linear regression models and Pearson correlation, the study found that all CT dose indices correlate with BMI and weight in all CT exams with varying degrees as opposed to age, which did not demonstrate any significant correlation with any of the CT dose indices across all CT exams. Moreover, it was found that using multiple regression models where multiple input variables are considered resulted in a higher correlation with the output variables than when simple regression was used. Investigating the relationships between the different dose indices, statistically significant relationships were found between all dose indices. A stronger linear relationship was noticed between CTD\({}_{\text{vol}}\) and DLP compared to the relationships between each pair of the other dose indices. The findings of this study contribute to understanding the relationships between patient-related parameters and CT dose indices, aiding in the development of optimized CT exams that ensure patient safety while maintaining the diagnostic efficacy of CT imaging. radiation dose; computed tomography; regression and correlation analysis 20  
Dose indices vary between various X-ray-based imaging modalities such as mammography [6] and CT [7; 8]. For instance, the volume CT dose index (CTDI\({}_{\text{vol}}\)) and dose length product (DLP) are two commonly used dose indices in CT [7]. CTDI\({}_{\text{vol}}\) provides information about the dose intensity in a specific slice, while DLP quantity accounts for the scan length coverage by roughly multiplying CTDI\({}_{\text{vol}}\) with the scan length. In contrast, the effective dose (ED) integrates the dose contributions from various exposed organs or tissues, providing a comprehensive measure of radiation impact [9]. ED is used to assess the radiation absorbed by the patient's body. It is calculated as the sum of the organ-equivalent doses multiplied by the organ-weighting factors proposed by the International Commission on Radiological Protection (ICRP) [10]. ED takes into account the varying sensitivities of different tissues and organs to radiation, recognizing that the absorption during, for instance, an abdomen CT scan differs from that during a head CT scan [11]. Clinical scientists, radiologists and CT technologists consider these indices to optimize CT exams, striking a balance between dose and image quality while minimizing risks [12]. The correlation between CTDI\({}_{\text{vol}}\), DLP and ED depends on factors such as scan acquisition parameters, patient characteristics and dosimetric models used for calculation [12]. The SSDE index is another dose index that indicates that patient size (i.e., weight) was taken into consideration, unlike the CT dose index of CTDI\({}_{\text{vol}}\), resulting generally in more accurate dose estimates [13]. For more detail, the reader is referred to the American Association of Physicists in Medicine (AAPM) task group report no. 204 [14].