{"id":50682,"date":"2023-09-30T10:52:21","date_gmt":"2023-09-30T10:52:21","guid":{"rendered":"https:\/\/biomedpharmajournal.org\/?p=50682"},"modified":"2023-10-07T11:13:17","modified_gmt":"2023-10-07T11:13:17","slug":"influence-of-body-mass-index-and-abdominal-circumference-on-radiation-dose-during-abdominopelvic-computed-tomography","status":"publish","type":"post","link":"https:\/\/biomedpharmajournal.org\/staging\/vol16no3\/influence-of-body-mass-index-and-abdominal-circumference-on-radiation-dose-during-abdominopelvic-computed-tomography\/","title":{"rendered":"Influence of Body Mass Index and Abdominal Circumference on Radiation Dose During Abdominopelvic Computed Tomography"},"content":{"rendered":"\n<p class=\"wp-block-paragraph\"><strong>Introduction<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Computed tomography is an essential imaging modality that produces tomographic images of specific areas to diagnose various pathologies. In the US, it is estimated that around 62 million CT scans are done annually <sup>1<\/sup>. Due to the rapid advances in imaging technology, such as faster scan times, advanced multi-planar reconstruction techniques, reduced artefacts, improved contrast, and spatial and temporal resolution, there has been a dramatic increase in CT scans <sup>2,3<\/sup>. Compared to the more common conventional x-ray examinations, CT alone involves larger radiation doses, with the majority resulting from examinations of the chest, abdomen, and pelvis <sup>1,4-6<\/sup>. Moreover, the wide use of multidetector-row CT scanners can increase abdominal CT examinations. Despite its advantages in imaging, concerns have been raised regarding radiation exposure. A study conducted by Gonzalez and Darby reported a 0.6-3.2 % risk of cancer from all diagnostic procedures using x-rays <sup>7<\/sup>. Contrast-enhanced examinations of the abdomen region have a greater radiation exposure due to the multiphase abdominal CT protocols. Risk can be best quantified by effective dose. An effective dose can be defined as the weighted sum of all the equivalent doses in all tissues and organs <sup>8,9<\/sup>. The effective dose can vary depending on the scanner design, exposure factors set, scan range and patient size <sup>10<\/sup>. The effective dose can be reduced by choosing the appropriate scan volume and adjusting scan parameters like pitch, kVp, mAs, rotation time, slice width, slice gap, and dose modulation techniques. Automatic tube current modulation was first introduced in 1998. Various methods of automatic tube current modulation (ATCM) are currently used. The longitudinal tube current modulation adjusts the mA on the z-axis, and the angular tube current modulation adjusts the mA on the x and y-axis. The angular-longitudinal (x, y, z) tube current modulation adjusts mA in all three planes. Automatic tube current modulation is known to reduce radiation dose and maintain or improve image quality for abdominal CT. <sup>11-13<\/sup>. However, automatic tube current modulation can increase radiation dose for individuals with a larger body habitus. <sup>10,11,13,14<\/sup>. Most clinicians prefer to obtain a constant image quality and, therefore, utilise the same noise index and reference mAs; this, in turn, can increase the radiation dose to oversized patients. Therefore, the study aims to determine how body mass index and abdominal circumference affect the effective dose for routine contrast-enhanced abdomen and pelvis scans using a 128-slice CT scanner with ATCM.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Materials and Methods<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">A total of 160 participants above the age of 18 years referred for routine CECT abdomen and pelvis were included in the study. Study approval was obtained from the institutional ethics committee. Prior to the scan, data on patient characteristics such as height, weight, BMI and abdominal circumference were collected. The BMI was categorised as underweight (&lt;18.5 kg\/m2), normal (18.5- 24.9 kg\/m2), overweight (25-29.9 kg\/m2) and obese (\u226530 kg\/m2) as per the WHO classification <sup>15<\/sup>. The 160 patients were divided according to their BMI into four groups, with 40 patients in each group. All scans were performed on a Philips 128-Slice Incisive CT scanner. A standard triple-phase abdomen and pelvis protocol was used for imaging. The scanning parameters for the protocol is shown in table 1. Tube current was controlled by a 3D dose modulation technique that adjusts the angular and longitudinal mA according to the body habitus and the DRI (dose right index). The area coverage for the CT abdomen and pelvis extended from the domes of the diaphragm to the symphysis pubis.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Table 1: Routine protocol for CECT Abdomen and pelvis<\/strong><\/p>\n\n\n<table style=\"width: 95%;\" border=\"1\" cellspacing=\"0\" cellpadding=\"4\">\n<tbody>\n<tr>\n<td width=\"164\">\n<p style=\"text-align: center;\"><strong>Scanning parameters<\/strong><\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"416\">\n<p><strong>Abdomen and pelvis<\/strong><\/p>\n<\/td>\n<\/tr>\n<tr>\n<td style=\"text-align: center;\" width=\"164\">\n<p>kVp<\/p>\n<\/td>\n<td width=\"416\">\n<p style=\"text-align: center;\">120<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td width=\"164\">\n<p style=\"text-align: center;\">Reference mA<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"416\">\n<p>80-250<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td style=\"text-align: center;\" width=\"164\">\n<p>Slice thickness<\/p>\n<\/td>\n<td width=\"416\">\n<p style=\"text-align: center;\">5 mm<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td width=\"164\">\n<p style=\"text-align: center;\">Rotaion time<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"416\">\n<p>0.5<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td style=\"text-align: center;\" width=\"164\">\n<p>Collimation<\/p>\n<\/td>\n<td width=\"416\">\n<p style=\"text-align: center;\">64 X 0.625<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td width=\"164\">\n<p style=\"text-align: center;\">Pitch<\/p>\n<\/td>\n<td width=\"416\">\n<p style=\"text-align: center;\">1.10<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\n\n<p class=\"wp-block-paragraph\"><strong>Radiation dose<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The dose information on the CT console was used to write the dose length\nproduct for each series. The effective dose was then found by multiplying the\ndose length product (8,10) by the region-specific conversion factor (0.015).<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Statistical\nanalysis<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">All statistical analysis was performed using the EZR software. Baseline\ncharacteristics (age, abdominal circumference), scanning parameters (mA, mAs,\nscan length, and scan time) and <\/p>\n\n\n\n<p class=\"wp-block-paragraph\">the effective dose was summarised using descriptive characteristics for\neach BMI group. One-way ANOVA was done to evaluate the difference in effective\ndose between the groups.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Results <\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">A total of 40 patients were included in each BMI group. The underweight group included 14 females and 26 males. The normal group included 10 females and 30 males, the overweight group included 16 females and 24 males, and the obese group included 24 females and 16 males. The patients&#8217; characteristics for each BMI group are summarised in table 2. One-way ANOVA showed no significant difference in age among the groups (p=0.163) and a significant difference in abdominal circumference among the groups (p&lt;0.001).<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Table 2: Mean and standard deviation of age and abdominal circumference among various BMI groups for triple phase CECT abdomen and pelvis scan<\/strong>.<\/p>\n\n\n<table style=\"width: 95%;\" border=\"1\" cellspacing=\"0\" cellpadding=\"4\">\n<tbody>\n<tr>\n<td width=\"250\">\n<p style=\"text-align: center;\"><strong>BMI Categories<\/strong><\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"250\">\n<p><strong>Age (years)<\/strong><\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"251\">\n<p><strong>Mean abdominal circumference (mm)<\/strong><\/p>\n<\/td>\n<\/tr>\n<tr>\n<td style=\"text-align: center;\" width=\"250\">\n<p>Underweight<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"250\">\n<p>44.8 \u00b1 19<\/p>\n<\/td>\n<td width=\"251\">\n<p style=\"text-align: center;\">739.2\u00b159<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td width=\"250\">\n<p style=\"text-align: center;\">Normal<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"250\">\n<p>49.2\u00b1 18<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"251\">\n<p>886.7\u00b1101<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td style=\"text-align: center;\" width=\"250\">\n<p>Overweight<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"250\">\n<p>50.9\u00b1 17<\/p>\n<\/td>\n<td width=\"251\">\n<p style=\"text-align: center;\">1016.8\u00b158<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td width=\"250\">\n<p style=\"text-align: center;\">Obese<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"250\">\n<p>53.5\u00b113.7<\/p>\n<\/td>\n<td width=\"251\">\n<p style=\"text-align: center;\">1167\u00b1 97<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\n\n<p class=\"wp-block-paragraph\"><strong>Scanning\/exposure\nparameters<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The scanning\/exposure parameters for various BMI groups for all series in a CECT abdomen and pelvis scan are depicted in tables 3, 4, 5 &amp; 6. The results reported a significant difference in mAs and mA among all groups for all series in a triple-phase CECT abdomen and pelvis (p&lt;0.05). For scan length, the results showed a significant difference in scan length among all groups for the plain, arterial, Porto venous, and delayed series in a triple-phase CECT abdomen and pelvis (p&lt;0.05). However, they showed no significant difference in the scanogram among the groups. The results also reported a substantial difference in scan time among all groups for scanogram, plain, arterial, and Porto-venous phases (p&lt;0.05). However, they showed no significant difference in the delayed phases among the groups.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Table 3: Mean mA among various BMI groups for triple phase CECT abdomen and pelvis scan<\/strong><\/p>\n\n\n<table style=\"width: 95%;\" border=\"1\" cellspacing=\"0\" cellpadding=\"4\">\n<tbody>\n<tr>\n<td rowspan=\"2\" width=\"136\">\n<p style=\"text-align: center;\"><strong>Abdominal series<\/strong><\/p>\n<\/td>\n<td style=\"text-align: center;\" colspan=\"5\" width=\"581\">\n<p><strong>mA<\/strong><\/p>\n<\/td>\n<\/tr>\n<tr>\n<td style=\"text-align: center;\" width=\"130\">\n<p><strong>Underweight<\/strong><\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"109\">\n<p><strong>Normal<\/strong><\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"127\">\n<p><strong>Overweight<\/strong><\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"109\">\n<p><strong>Obese<\/strong><\/p>\n<\/td>\n<td width=\"105\">\n<p style=\"text-align: center;\"><strong>p-value<\/strong><\/p>\n<\/td>\n<\/tr>\n<tr>\n<td width=\"136\">\n<p style=\"text-align: center;\"><strong>Plain<\/strong><\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"130\">\n<p>151.8\u00b1 15.4<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"109\">\n<p>184\u00b132.5<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"127\">\n<p>195\u00b141.8<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"109\">\n<p>217\u00b18.9<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"105\">\n<p>&lt;0.001<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td style=\"text-align: center;\" width=\"136\">\n<p><strong>Arterial<\/strong><\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"130\">\n<p>177.2\u00b110.2<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"109\">\n<p>188.4\u00b111.2<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"127\">\n<p>191.1\u00b120.5<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"109\">\n<p>201.2\u00b139.9<\/p>\n<\/td>\n<td width=\"105\">\n<p style=\"text-align: center;\">&lt;0.001<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td width=\"136\">\n<p style=\"text-align: center;\"><strong>Porto-venous<\/strong><\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"130\">\n<p>178.2\u00b19.7<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"109\">\n<p>186.9\u00b19.3<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"127\">\n<p>189.4\u00b115.3<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"109\">\n<p>197.6\u00b128<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"105\">\n<p>&lt;0.001<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td style=\"text-align: center;\" width=\"136\">\n<p><strong>Delayed<\/strong><\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"130\">\n<p>176.8\u00b17.3<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"109\">\n<p>179.5\u00b17.9<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"127\">\n<p>182.2\u00b111<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"109\">\n<p>207.1\u00b151.4<\/p>\n<\/td>\n<td width=\"105\">\n<p style=\"text-align: center;\">&lt;0.001<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\n\n<p class=\"wp-block-paragraph\"><strong>Table 4: Mean mAs among various BMI groups for triple phase CECT abdomen and pelvis scan<\/strong><\/p>\n\n\n<table style=\"width: 95%;\" border=\"1\" cellspacing=\"0\" cellpadding=\"4\">\n<tbody>\n<tr>\n<td rowspan=\"2\" width=\"136\">\n<p style=\"text-align: center;\"><strong>Abdominal series<\/strong><\/p>\n<\/td>\n<td style=\"text-align: center;\" colspan=\"5\" width=\"581\">\n<p><strong>mAs<\/strong><\/p>\n<\/td>\n<\/tr>\n<tr>\n<td width=\"130\">\n<p style=\"text-align: center;\"><strong>Underweight<\/strong><\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"109\">\n<p><strong>Normal<\/strong><\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"127\">\n<p><strong>Overweight<\/strong><\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"109\">\n<p><strong>Obese<\/strong><\/p>\n<\/td>\n<td width=\"105\">\n<p style=\"text-align: center;\"><strong>p-value<\/strong><\/p>\n<\/td>\n<\/tr>\n<tr>\n<td style=\"text-align: center;\" width=\"136\">\n<p><strong>Plain<\/strong><\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"130\">\n<p>70.7\u00b1 4.1<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"109\">\n<p>85.8\u00b112.8<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"127\">\n<p>97.1\u00b1 12.9<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"109\">\n<p>114.5\u00b123.8<\/p>\n<\/td>\n<td width=\"105\">\n<p style=\"text-align: center;\">&lt;0.001<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td width=\"136\">\n<p style=\"text-align: center;\"><strong>Arterial<\/strong><\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"130\">\n<p>90.7\u00b11.6<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"109\">\n<p>91.9\u00b1 3.9<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"127\">\n<p>95.4\u00b15.6<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"109\">\n<p>111.7\u00b122.2<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"105\">\n<p>&lt;0.001<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td style=\"text-align: center;\" width=\"136\">\n<p><strong>Porto-venous<\/strong><\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"130\">\n<p>90.8\u00b11.7<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"109\">\n<p>91.1\u00b12.5<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"127\">\n<p>93.3\u00b13.8<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"109\">\n<p>106.4\u00b118.5<\/p>\n<\/td>\n<td width=\"105\">\n<p style=\"text-align: center;\">&lt;0.001<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td width=\"136\">\n<p style=\"text-align: center;\"><strong>Delayed<\/strong><\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"130\">\n<p>87.8\u00b11.6<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"109\">\n<p>88.7\u00b13.2<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"127\">\n<p>90.8\u00b15.2<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"109\">\n<p>107\u00b122.2<\/p>\n<\/td>\n<td width=\"105\">\n<p style=\"text-align: center;\">&lt;0.001<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\n\n<p class=\"wp-block-paragraph\"><strong>Table 5: Mean Scan length among various BMI groups for triple phase CECT abdomen and pelvis scan<\/strong><\/p>\n\n\n<table style=\"width: 95%;\" border=\"1\" cellspacing=\"0\" cellpadding=\"4\">\n<tbody>\n<tr>\n<td rowspan=\"2\" width=\"136\">\n<p style=\"text-align: center;\"><strong>Abdominal series<\/strong><\/p>\n<\/td>\n<td style=\"text-align: center;\" colspan=\"5\" width=\"581\">\n<p><strong>Scan length<\/strong><\/p>\n<\/td>\n<\/tr>\n<tr>\n<td style=\"text-align: center;\" width=\"130\">\n<p><strong>Underweight<\/strong><\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"124\">\n<p><strong>Normal<\/strong><\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"127\">\n<p><strong>Overweight<\/strong><\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"109\">\n<p><strong>Obese<\/strong><\/p>\n<\/td>\n<td width=\"90\">\n<p style=\"text-align: center;\"><strong>p-value<\/strong><\/p>\n<\/td>\n<\/tr>\n<tr>\n<td width=\"136\">\n<p style=\"text-align: center;\"><strong>Scano<\/strong><\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"130\">\n<p>520\u00b1 68.1<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"124\">\n<p>532.2\u00b1 55.8<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"127\">\n<p>540.4\u00b1 62.8<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"109\">\n<p>550.9\u00b167.4<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"90\">\n<p>0.1<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td style=\"text-align: center;\" width=\"136\">\n<p><strong>Plain<\/strong><\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"130\">\n<p>493\u00b1 35.7<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"124\">\n<p>495.2\u00b139.6<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"127\">\n<p>520.3\u00b1 56.7<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"109\">\n<p>521.7\u00b152.6<\/p>\n<\/td>\n<td width=\"90\">\n<p style=\"text-align: center;\">0.005<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td width=\"136\">\n<p style=\"text-align: center;\"><strong>Arterial<\/strong><\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"130\">\n<p>492\u00b1 37.8<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"124\">\n<p>492.4\u00b1 39.7<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"127\">\n<p>515.2\u00b149.7<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"109\">\n<p>526.4\u00b149.4<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"90\">\n<p>0.001<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td style=\"text-align: center;\" width=\"136\">\n<p><strong>Porto-venous<\/strong><\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"130\">\n<p>493.7 \u00b1 37.2<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"124\">\n<p>498.1\u00b138.7<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"127\">\n<p>521.3\u00b156.2<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"109\">\n<p>526.8\u00b148.2<\/p>\n<\/td>\n<td width=\"90\">\n<p style=\"text-align: center;\">0.002<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td width=\"136\">\n<p style=\"text-align: center;\"><strong>Delayed<\/strong><\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"130\">\n<p>281.6\u00b153.4<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"124\">\n<p>287.8\u00b143.9<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"127\">\n<p>299.6\u00b156.4<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"109\">\n<p>311.6\u00b132.1<\/p>\n<\/td>\n<td width=\"90\">\n<p style=\"text-align: center;\">0.02<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\n\n<p class=\"wp-block-paragraph\"><strong>Table 6: Mean Scan time among various BMI groups for triple phase CECT abdomen and pelvis scan<\/strong><\/p>\n\n\n<table style=\"width: 95%;\" border=\"1\" cellspacing=\"0\" cellpadding=\"4\">\n<tbody>\n<tr>\n<td rowspan=\"2\" width=\"136\">\n<p style=\"text-align: center;\"><strong>Abdominal series<\/strong><\/p>\n<\/td>\n<td style=\"text-align: center;\" colspan=\"5\" width=\"581\">\n<p><strong>Scan time<\/strong><\/p>\n<\/td>\n<\/tr>\n<tr>\n<td style=\"text-align: center;\" width=\"130\">\n<p><strong>Underweight<\/strong><\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"109\">\n<p><strong>Normal<\/strong><\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"127\">\n<p><strong>Overweight<\/strong><\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"109\">\n<p><strong>Obese<\/strong><\/p>\n<\/td>\n<td width=\"105\">\n<p style=\"text-align: center;\"><strong>p-value<\/strong><\/p>\n<\/td>\n<\/tr>\n<tr>\n<td width=\"136\">\n<p style=\"text-align: center;\"><strong>Scano<\/strong><\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"130\">\n<p>5.1\u00b1 0.6<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"109\">\n<p>5.1\u00b1 0.5<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"127\">\n<p>5.3 \u00b1 0.6<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"109\">\n<p>5.4\u00b10.6<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"105\">\n<p>0.04<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td style=\"text-align: center;\" width=\"136\">\n<p><strong>Plain<\/strong><\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"130\">\n<p>6.2\u00b1 0.4<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"109\">\n<p>6.2\u00b10.5<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"127\">\n<p>6.5\u00b1 0.6<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"109\">\n<p>6.6\u00b10.6<\/p>\n<\/td>\n<td width=\"105\">\n<p style=\"text-align: center;\">0.009<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td width=\"136\">\n<p style=\"text-align: center;\"><strong>Arterial<\/strong><\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"130\">\n<p>6.8\u00b10.5<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"109\">\n<p>6.8\u00b1 0.5<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"127\">\n<p>7.1\u00b1 0.6<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"109\">\n<p>7.3\u00b10.6<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"105\">\n<p>0.001<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td style=\"text-align: center;\" width=\"136\">\n<p><strong>Porto-venous<\/strong><\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"130\">\n<p>6.9\u00b10.4<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"109\">\n<p>6.9\u00b10.5<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"127\">\n<p>7.1\u00b10.7<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"109\">\n<p>7.3\u00b10.6<\/p>\n<\/td>\n<td width=\"105\">\n<p style=\"text-align: center;\">&lt;0.001<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td width=\"136\">\n<p style=\"text-align: center;\"><strong>Delayed<\/strong><\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"130\">\n<p>4.3\u00b10.9<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"109\">\n<p>4.4\u00b10.5<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"127\">\n<p>4.4\u00b1 0.7<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"109\">\n<p>4.6\u00b1 0.4<\/p>\n<\/td>\n<td width=\"105\">\n<p style=\"text-align: center;\">0.2<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\n\n<p class=\"wp-block-paragraph\"><strong>Radiation dose<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The mean effective dose and dose length product across all BMI groups for the CECT abdomen and pelvis is demonstrated in Table 7. The study results showed increased DLP and effective dose with increasing BMI. One-way ANOVA showed a significant difference in DLP and effective dose among the groups (p=&lt;0.001), as shown in figure 1.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Table 7: Descriptive statistics showing mean and standard deviation of DLP and Effective dose for each BMI group<\/strong><\/p>\n\n\n<table style=\"width: 95%;\" border=\"1\" cellspacing=\"0\" cellpadding=\"4\">\n<tbody>\n<tr>\n<td width=\"250\">\n<p style=\"text-align: center;\"><strong>BMI group<\/strong><\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"250\">\n<p><strong>Dose length product mGy*cm<\/strong><\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"251\">\n<p><strong>Effective dose (mSv)<\/strong><\/p>\n<\/td>\n<\/tr>\n<tr>\n<td style=\"text-align: center;\" width=\"250\">\n<p><strong>Underweight<\/strong><\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"250\">\n<p>1431.3\u00b1 136<\/p>\n<\/td>\n<td width=\"251\">\n<p style=\"text-align: center;\">21.47 \u00b12<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td width=\"250\">\n<p style=\"text-align: center;\"><strong>Normal<\/strong><\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"250\">\n<p>1516.6 \u00b1 155<\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"251\">\n<p>22.75 \u00b12.3<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td style=\"text-align: center;\" width=\"250\">\n<p><strong>Overweight<\/strong><\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"250\">\n<p>1668.1 \u00b1 191<\/p>\n<\/td>\n<td width=\"251\">\n<p style=\"text-align: center;\">25.02\u00b12.8<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td width=\"250\">\n<p style=\"text-align: center;\"><strong>Obese<\/strong><\/p>\n<\/td>\n<td style=\"text-align: center;\" width=\"250\">\n<p>1984.6 \u00b1 448<\/p>\n<\/td>\n<td width=\"251\">\n<p style=\"text-align: center;\">29.7\u00b16.7<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<table style=\"width: 70%;\" border=\"1\" cellpadding=\"5\">\n<tbody>\n<tr>\n<td><img decoding=\"async\" class=\"alignnone size-thumbnail wp-image-50697\" src=\"https:\/\/biomedpharmajournal.org\/wp-content\/uploads\/2023\/07\/Vol16No3_Inf_Nit_Fig1-150x150.jpg\" alt=\"\" width=\"150\" height=\"150\" srcset=\"https:\/\/biomedpharmajournal.org\/staging\/wp-content\/uploads\/2023\/07\/Vol16No3_Inf_Nit_Fig1-150x150.jpg 150w, https:\/\/biomedpharmajournal.org\/staging\/wp-content\/uploads\/2023\/07\/Vol16No3_Inf_Nit_Fig1-256x256.jpg 256w, https:\/\/biomedpharmajournal.org\/staging\/wp-content\/uploads\/2023\/07\/Vol16No3_Inf_Nit_Fig1.jpg 686w\" sizes=\"(max-width: 150px) 100vw, 150px\" \/><\/td>\n<td>\n<p><strong>Figure 1: Bar diagram with error bars. Bars depict the mean ED across various BMI groups and Error bars represent the<\/strong><strong> standard deviation.<\/strong><\/p>\n<p><\/p>\n<p><a href=\"https:\/\/biomedpharmajournal.org\/wp-content\/uploads\/2023\/07\/Vol16No3_Inf_Nit_Fig1.jpg\" target=\"_blank\" rel=\"noopener noreferrer\">Click here to view Figure<\/a><\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\n\n<p class=\"wp-block-paragraph\"><strong>Discussion<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Radiation dose in CT has always been a cause of concern due to its associated radiation dose. With the advancements in CT scanners, various strategies have been developed to optimise the radiation dose. Along with optimising exposure factors based on body habitus, the introduction of automatic tube current modulation (ATCM) has contributed to dose reduction while maintaining the diagnostic quality of images. Various studies have reported a decrease in radiation dose while utilising the ATCM technique <sup>15,16,17<\/sup>. As per the study by Livingstone et al., the use of the dose modulation technique resulted in a dose reduction of 16-28%. Although tube current modulation can reduce the overall radiation dose, various studies have reported a potential risk of increased radiation dose in oversized or obese patients due to the higher tube current used to maintain constant image quality <sup>12,18<\/sup>. A study conducted by Schindera et al. on a phantom that was adjusted for three patient sizes demonstrated an increase in abdominal organ doses by 528 % in larger patients. Similarly, the present study reported a 32.39% increase in effective doses for obese patients. This increase in dose is due to the increase in scan parameters like mAs, mA and scan length to achieve consistent image quality. Another study conducted by Chan VO et al. reported a mean effective dose of 7.3 \u00b1 0.9 mSv, 8.9 \u00b1 1 mSv and 12\u00b12.8 mSv for low, normal and high BMI, respectively <sup>10<\/sup>. The present study reported much higher values of effective dose for low BMI (21.47 \u00b1 2), normal BMI (22.7 \u00b1 2.3), overweight (25 \u00b1 2.8) and obese (29.7 \u00b16.7) <sup>10<\/sup>. This could also be because the dose reported in the present study was the total dose obtained during the entire CECT abdomen and pelvis that included triple-phase like arterial, Porto-venous, and delayed phases rather than computing the dose from a single series. Nevertheless, dose optimisation techniques should be extended to obese patients as well, mainly because an increase in BMI is associated with an increase in effective dose. A study by Israel G M et al. reported that radiation given to a 100 kg patient is three times more when compared to a 60 kg patient, resulting in an organ dose that is twice as high <sup>19<\/sup>. Similarly, a study conducted by Chan VO et al. showed that for every kilogram of weight, there is an increase of 0.13 mSv of effective dose <sup>10<\/sup>. Therefore, more research can be done to investigate the usage of low kVp techniques for obese patients to optimise the dose. Also, a study conducted by Qurashi AA et al. showed that obese patients might benefit from fat deposition around their organs as it may improve inherent tissue contrast between the organs <sup>20<\/sup>. With more advancements in iterative reconstruction algorithms, there is scope for reducing the dose whilst maintaining the image quality. Although there are no dose limits for patients, establishing local, regional, or national DRLs may aid in radiation dose optimisation and thus reduce the risk of stochastic effects.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Conclusion<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">As obesity is a growing concern and since the CECT abdomen and pelvis\nplay an essential role in diagnosing various pathologies, dose optimisation\ntechniques must be extended for obese patients. The study results showed an\nincrease in DLP and effective dose with increasing BMI and a 32.39 % increase\nin effective doses for obese patients. Therefore, designing protocols based on\npatient size, clinical indication, and system capability can help reduce\nradiation exposure to patients undergoing abdominopelvic examinations.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Acknowledgement<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The authors would like to acknowledge, Kasturba hospital and Manipal\nCollege of health professions for their support to undertake this study. We\nalso extend our heartfelt gratitude to the faculties and Head of the department of Radio-diagnosis and imaging for\ntheir cooperation during data collection.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Conflicts of Interest<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">We declare there is no conflict of interest regarding the publication of\nthis paper<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Funding Source<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">There is no funding sources<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>References<\/strong><\/p>\n\n\n\n<ol class=\"wp-block-list\"><li>Brenner DJ, Hall EJ. 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Radiat Prot Dosimetry. 2019 Nov 30;185(1):17-26. <br><a href=\"https:\/\/doi.org\/10.1093\/rpd\/ncy212\" target=\"_blank\" rel=\"noreferrer noopener\" aria-label=\" CrossRef  (opens in a new tab)\"> CrossRef <\/a><\/li><\/ol>\n","protected":false},"excerpt":{"rendered":"<p>Introduction Computed tomography is an essential imaging modality that produces  [&#8230;]<\/p>\n","protected":false},"author":15,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[109],"tags":[],"class_list":["post-50682","post","type-post","status-publish","format-standard","hentry","category-vol16no3"],"_links":{"self":[{"href":"https:\/\/biomedpharmajournal.org\/staging\/wp-json\/wp\/v2\/posts\/50682","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/biomedpharmajournal.org\/staging\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/biomedpharmajournal.org\/staging\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/biomedpharmajournal.org\/staging\/wp-json\/wp\/v2\/users\/15"}],"replies":[{"embeddable":true,"href":"https:\/\/biomedpharmajournal.org\/staging\/wp-json\/wp\/v2\/comments?post=50682"}],"version-history":[{"count":5,"href":"https:\/\/biomedpharmajournal.org\/staging\/wp-json\/wp\/v2\/posts\/50682\/revisions"}],"predecessor-version":[{"id":52640,"href":"https:\/\/biomedpharmajournal.org\/staging\/wp-json\/wp\/v2\/posts\/50682\/revisions\/52640"}],"wp:attachment":[{"href":"https:\/\/biomedpharmajournal.org\/staging\/wp-json\/wp\/v2\/media?parent=50682"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/biomedpharmajournal.org\/staging\/wp-json\/wp\/v2\/categories?post=50682"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/biomedpharmajournal.org\/staging\/wp-json\/wp\/v2\/tags?post=50682"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}