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The relationship between body height and body weight has been described by using various terms. Notable among them is the body mass index, body surface area, body shape index and body surface index. In clinical setting the first descriptive parameter is the BMI scale, which provides information about whether an individual body weight is proportionate to the body height. Since the development of BMI, two other body parameters have been developed in an attempt to determine the relationship between body height and weight. These are the body surface area (BSA) and body surface index (BSI). Generally, these body parameters are described as clinical health indicators that described how healthy an individual body response to the other internal organs. The aim of the study is to discuss the use of BSI as a better clinical health indicator for preclinical assessment of body-organ/tissue relationship. Hence organ health condition as against other body composition. In addition the study is `also to determine the best body parameter the best predict other parameters for clinical application. The model parameters are presented as; modeled height and weight; modelled BSI and BSA, BSI and BMI and modeled BSA and BMI. The models are presented as clinical application software for comfortable working process and designed as GUI and CAD for use in clinical application.

The quantities that determine the relative image noise level by either increasing or reducing its value are photon quality (kVp) and photon quantity (mAs). This study is to determine the effect of LET, energy and particle fluence on the renal surface area during abdominal CT scan. The method involve extracting three exposure parameters from image data using MVL DICOM application software including: kVp, mA and scan time. The kVp or the photon peak energy which is applied in the A-P direction during abdominal CT scan was used to estimate linear energy transfer. While the particle fluence and the energy fluence were estimated from the effective mAs and the kVp on the total renal surface respectively. The effective mAs were estimated by dividing the mAs by the average pitch factor of approximately 0.813. In all the examinations, the average protocol setting in terms of exposure time and kilovolts peak were 500s and 120keV respectively. While the average protocol in all the centers recorded a mean effective milliamp second (mAs) of 59.27 mAs and tube current of 94.22A. The influence of these parameters on abdominal scan depends on the scan time, scan scope, the size of the renal surface area (RSA) which has varied values. The effects of effective mean mAs per unit mean renal surface area, described as mean effective particle fluence were 1.32mAs/cm2 and 1.50 mAs/cm2 for male and female respectively. The energy fluence, which is the photon energy per unit renal surface area estimated to have a mean value of 4.02 keVcm-2 and 4.51 keVcm-2 for male and female respectively. In addition, the maximum and minimum variations of all the measured parameters. The LET, which described the lost in photon energy as it traverses across the renal tissues in the A-P direction was estimated, with a mean value of 2.60 keV/µm and 2.67 keV/µm for male and female respectively. The maximum and minimum LET values were 4.49 keV/µm and 1.90 keV/µm for male and 5.26 keV/µm and 1.98 keV/µm for female respectively. The maximum measured values were below the critical LET values estimated to be between 15 to 20 keV/µm. These estimated risk parameters were used to predict the effect on abdominal and kidney tissues using the various modeled equations.