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Determination of Height, Weight, Body Mass Index, and Body Surface Area with a Single Abdominal CT Image¹

¹ From the Department of Radiology, University of California Davis Medical Center, 4701 X St, Sacramento, CA 95817-2205. Received February 21, 2002; revision requested April 18; final revision received October 29; accepted November 5. Address correspondence to J.M.B. (e-mail: jmboone@ucdavis.edu).

View larger version (94K): [in a new window]   Figure 1. Diagrammatic representation of outlined ROIs and other measured anthropometric parameters. Outermost tracing represents the circumference of the body. Interior to that is the outline defined as intraabdominal area. Spinal canal is circumscribed, and its widest transverse dimension is used as the dorsal cutoff for tracing of the first lumbar vertebral body. BAPD = anteroposterior body diameter, BTD = transverse body diameter, L1APD = greatest L1 vertebral anteroposterior diameter, L1TD = greatest L1 transverse diameter.

View larger version (24K): [in a new window]   Figure 2a. Scatterplots show the relationship between the patient’s actual height and calculated height derived from predictive equations (black squares). Calculated values where the balance of the data comprised the training set (gray circles) are also represented. Correlation coefficient from the multiple linear regression analysis is reported. Line of identity is depicted, and the SD is presented as calculated from the leave-one-out analysis. (a) Graph shows height in women. Predictive equation for height in women, or heightW, is as follows: heightW = -0.103177 + (0.0254 · SCA) - (0.000696 · age) + (0.015441 · BTD) + (0.196566 · L1TD) + (0.117566 · L1APD), where height is measured in meters. (b) Graph shows height in men. Predictive equation for height in men, or heightM, is as follows: heightM = 1.134047 + (0.083556 · L1A) + (0.143212 · SCA) - (0.004139 · age) - (0.171034 · L1TD), where height is measured in meters.

View larger version (28K): [in a new window]   Figure 2b. Scatterplots show the relationship between the patient’s actual height and calculated height derived from predictive equations (black squares). Calculated values where the balance of the data comprised the training set (gray circles) are also represented. Correlation coefficient from the multiple linear regression analysis is reported. Line of identity is depicted, and the SD is presented as calculated from the leave-one-out analysis. (a) Graph shows height in women. Predictive equation for height in women, or heightW, is as follows: heightW = -0.103177 + (0.0254 · SCA) - (0.000696 · age) + (0.015441 · BTD) + (0.196566 · L1TD) + (0.117566 · L1APD), where height is measured in meters. (b) Graph shows height in men. Predictive equation for height in men, or heightM, is as follows: heightM = 1.134047 + (0.083556 · L1A) + (0.143212 · SCA) - (0.004139 · age) - (0.171034 · L1TD), where height is measured in meters.

View larger version (28K): [in a new window]   Figure 3a. Scatterplots show good correlation between the actual patient weight derived from hospital medical records and the calculated weight derived from predictive equations. Black squares are parameter calculated with equations derived from all data points, and gray circles are parameter calculated with leave-one-out method. (a) Graph shows weight in women. Predictive equation for weight in women, or weightW, is as follows: weightW = -71.039024 + (1.520375 · BC) - (0.223321 · age) + (3.958301 · L1APD), where weight is measured in kilograms. (b) Graph shows weight in men. Predictive equation for weight in men, or weightM, is as follows: weightM = -54.856007 + (1.985658 · L1A) + (3.784671 · SCA) + (0.103460 · SQA) - (0.302853 · age) + (2.987843 · BTD), where weight is measured in kilograms.

View larger version (29K): [in a new window]   Figure 3b. Scatterplots show good correlation between the actual patient weight derived from hospital medical records and the calculated weight derived from predictive equations. Black squares are parameter calculated with equations derived from all data points, and gray circles are parameter calculated with leave-one-out method. (a) Graph shows weight in women. Predictive equation for weight in women, or weightW, is as follows: weightW = -71.039024 + (1.520375 · BC) - (0.223321 · age) + (3.958301 · L1APD), where weight is measured in kilograms. (b) Graph shows weight in men. Predictive equation for weight in men, or weightM, is as follows: weightM = -54.856007 + (1.985658 · L1A) + (3.784671 · SCA) + (0.103460 · SQA) - (0.302853 · age) + (2.987843 · BTD), where weight is measured in kilograms.

View larger version (25K): [in a new window]   Figure 4a. Scatterplots show correlation between actual BMI when calculated from the patient’s height and weight versus calculated BMI derived from predictive equations with CT data. Black squares are parameter calculated with equations derived from all data points, and gray circles are parameter calculated with leave-one-out method. (a) Graph shows BMI in women. Predictive equation for BMI in women, or BMIW, is as follows: BMIW = -9.163352 + (0.252992 · BC) + (10.621081 · SQR) - (0.080649 · age) + (0.597135 · BAPD), where BMI is measured in kilograms per square meter. (b) Graph shows BMI in men. Predictive equation for BMI in men, or BMIM, is as follows: BMIM = 2.069055 + (0.037443 · SQA) - (0.050594 · age) + (0.984937 · BTD) - (2.647949 · L1APD), where BMI is measured in kilograms per square meter.

View larger version (26K): [in a new window]   Figure 4b. Scatterplots show correlation between actual BMI when calculated from the patient’s height and weight versus calculated BMI derived from predictive equations with CT data. Black squares are parameter calculated with equations derived from all data points, and gray circles are parameter calculated with leave-one-out method. (a) Graph shows BMI in women. Predictive equation for BMI in women, or BMIW, is as follows: BMIW = -9.163352 + (0.252992 · BC) + (10.621081 · SQR) - (0.080649 · age) + (0.597135 · BAPD), where BMI is measured in kilograms per square meter. (b) Graph shows BMI in men. Predictive equation for BMI in men, or BMIM, is as follows: BMIM = 2.069055 + (0.037443 · SQA) - (0.050594 · age) + (0.984937 · BTD) - (2.647949 · L1APD), where BMI is measured in kilograms per square meter.

View larger version (25K): [in a new window]   Figure 5a. Scatterplots show relationship between the actual BSA as calculated from patient height and weight versus BSA derived from predictive equations. Black squares are parameter calculated with equations derived from all data points, and gray circles are parameter calculated with leave-one-out method. (a) Graph shows BSA in women. Predictive equation for BSA in women, or BSAW, is as follows: BSAW = -0.724995 + (0.019472 · BC) - (0.003817 · age) +(0.231837 · L1TD), where BSA is measured in square meters. (b) Graph shows BSA in men. Predictive equation for BSA in men, or BSAM, is as follows: BSAM = -0.615293 + (0.041699 · L1A) + (0.088085 · SCA) - (0.006687 · age) + (0.062063 · BTD), where BSA is measured in square meters.

View larger version (27K): [in a new window]   Figure 5b. Scatterplots show relationship between the actual BSA as calculated from patient height and weight versus BSA derived from predictive equations. Black squares are parameter calculated with equations derived from all data points, and gray circles are parameter calculated with leave-one-out method. (a) Graph shows BSA in women. Predictive equation for BSA in women, or BSAW, is as follows: BSAW = -0.724995 + (0.019472 · BC) - (0.003817 · age) +(0.231837 · L1TD), where BSA is measured in square meters. (b) Graph shows BSA in men. Predictive equation for BSA in men, or BSAM, is as follows: BSAM = -0.615293 + (0.041699 · L1A) + (0.088085 · SCA) - (0.006687 · age) + (0.062063 · BTD), where BSA is measured in square meters.