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PERSPECTIVES |
1 Anaesthesia, Critical Care and Pain Medicine, Royal Infirmary, Edinburgh, UK Email: g.b.drummond{at}ed.ac.uk
The dimensions, shapes and movements of the lung are complex. Scintigraphic methods developed in the 1960s first allowed measurements of the function of different parts of the lung. The studies used large detectors of radioactive gases such as133Xe that could be inhaled, or dissolved and injected. They distinguished large regions, such as ‘upper’, ‘middle’ and ‘lower’ (West & Dollery, 1960; Ball et al. 1962). A primary finding of these ‘broad brush’ imaging methods was the effect of gravity, and the interaction between gravity and the mechanical properties of the lung (Milic-Emili et al. 1966). These findings were explained with simple concepts, perhaps sustained too long because of their simplicity (Galvin et al. 2007). Even at that time, invasive methods showed that there were considerable differences in ventilation within small units of the lung (Engel et al. 1974). Non-invasive methods now give improved resolution: static computed tomography imaging of hyperpolarized 3He can track the distribution of a single breath (Gast et al. 2002).
In this issue of The Journal of Physiology, Robertson and colleagues (Robertson et al. 2007) have used simultaneous labelling of vessels and airways, using fluorescent particles, to accurately align measures of blood flow and ventilation, within 2 cm lung cubes. These measurements allow a unique insight into the factors that affect the efficiency of gas exchange, which requires the accurate matching of gas and blood entry into functional lung units.
Weibel (1991) suggested that the inner surface of the lung has more than two dimensions, but not as many as three: the inner surface is crumpled, not smooth. Describing this type of shape is not easy, but fractal geometry is a useful concept. In fractal systems, the form or pattern of the structure appears the same, irrespective of the scale. This appears to be true in the lung, both for the airways and the vessels. Both systems branch in a predictable but non-uniform way. Thus, the structure determines a variation in the end result, the distribution of ventilation and of perfusion, in specific units of lung tissue, irrespective of the size of the unit considered. When we consider the important relationship between ventilation and perfusion in these units, it is possible that additional variation, in the relationship between the two factors, could result in even more variation. However, the opposite seems to be the case. The matching between ventilation and blood flow appears to be better than random. The result is that gas exchange is better than expected because matching of ventilation to blood flow is better than random (Glenny et al. 2000). Furthermore, although the individual components, ventilation and blood flow distribution, vary over time, the variation of the resultant matching appears to be suppressed.
To examine the process of gas exchange, lung can be modelled into a number of smaller units (typically 50) to ‘explain’ the retention and excretion of infused test gases, chosen to have a large range of blood/gas partition coefficients (Hlastala, 1984). However, these are ‘imaginary’ compartments, just as the original concept of three compartments consisting of ideal function, blood flow without ventilation, and ventilation without blood flow. The ‘solution’ given by this conceptual model is not unique. In particular, the resolution is limited: only two modes of 
distribution can be determined, and the temporal resolution of this method is limited by the need to obtain a steady state of retention and excretion. It is not clear how complex the regional and temporal variation in lung gas exchange can be, but these new data provided by Robertson et al. show that temporal variations are considerable.
The dangers of slow sample rates when making discrete measurements of a continuously changing variable are well known. Problems such as aliasing can occur. It isn't clear what was happening to the blood flow and ventilation in the 20 min between each measurement. I hope that these challenging and important findings, that track co-ordinated time-related changes in local ventilation and perfusion, will trigger further studies in several directions. How fast are these changes? What controls the congruence of the changes? Can the matching be upset in disease, or during interventions such as anaesthesia? The authors make several reasonable suggestions, some of which are able to be directly tested. We may be on the verge of a new era of understanding the coordination of pulmonary gas exchange efficiency.
References
Ball WCJ, Stewart PB, Newsham LGS & Bates DV (1962). J Clin Invest 41, 519–531.[Medline]
Engel LA, Utz G, Wood LDH & Macklem PT (1974). J Appl Physiol 37, 194–200.
Galvin I, Drummond GB & Nirmalan M (2007). Br J Anaesthesia 98, 420–428.
Gast KK, Puderbach MU, Rodriguez I, Eberle B, Markstaller K, Hanke AT, Schmiedeskamp J, Weiler N, Lill J, Schreiber WG, Thelen M & Kauczor HU (2002). Invest Radiol 37, 126–134.[CrossRef][Medline]
Glenny RW, Bernard SL & Robertson HT (2000). J Appl Physiol 89, 742–748.
Hlastala MP (1984). J Appl Physiol 56, 1–7.
Milic-Emili J, Henderson JAM, Dolovich MB, Trop D & Kaneko K (1966). J Appl Physiol 21, 749–759.
Robertson HT, Neradilek B, Polissar NL & Glenny RW (2007). J Physiol 583, 743–752.
Rodarte JR, Chaniotakis M & Wilson TA (1989). J Appl Physiol 67, 226–231.
Weibel ER (1991). Am J Physiol Lung Cell Mol Physiol 261, L361–L369.
West JB & Dollery CT (1960). J Appl Physiol 15, 405–410.
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