UNBIASED ESTIMATION OF HUMAN-BODY COMPOSITION BY THE CAVALIERI METHODUSING MAGNETIC-RESONANCE-IMAGING

The classical methods for estimating the volume of human body compartm ents in vivo (e.g. skin-fold thickness for fat, radioisotope counting for different compartments, etc.) are generally indirect and rely on e ssentially empirical relationships-hence they are biased to unknown de grees. The advent of modem non-invasive scanning techniques, such as X -ray computed tomography (CT) and magnetic resonance imaging (MRI) is now widening the scope of volume quantification, especially in combina tion with stereological methods. Apart from its superior soft tissue c ontrast, MRI enjoys the distinct advantage of not using ionizing radia tions. By a proper landmarking and control of the scanner couch, an ad ult male volunteer was scanned exhaustively into parallel systematic M R 'sections'. Four compartments were defined, namely bone, muscle, org ans and fat (which included the skin), and their corresponding volumes were easily and efficiently estimated by the Cavalieri method: the to tal section area of a compartment times the section interval estimates the volume of the compartment without bias. Formulae and nomograms ar e given to predict the errors and to optimize the design. To estimate an individual's muscle volume with a 5% coefficient of error, 10 secti ons and less than 10 min point counting (to estimate the relevant sect ion areas) are required. Bone and fat require about twice as much work . To estimate the mean muscle volume of a population with the same err or contribution, from a random sample of six subjects, the workload pe r subject can be divided by square-root 6, namely.4 min per subject. F or a given number of sections planimetry would be as accurate but far more time consuming than point counting.