Timely diagnosis of brain death (BD) is critical as it prevents unethical and futile continuation of support of vital organ functions when the patient has passed. Furthermore, it helps with avoiding the unnecessary use of resources and provides early opportunity for precious organ donation. The diagnosis of BD is mainly based on careful neurological assessment of patients with an established underlying diagnosis of neurological catastrophe capable of causing BD.

Ancillary testing, however, is tremendously helpful in situations when the presence of confounders prevents or delays comprehensive neurological assessment. Traditionally, four-vessel digital subtraction angiography and computed tomography angiography have been used for blood flow (BF) examinations of the brain. The lack of BF in the intracranial arteries constitutes conclusive evidence that the brain is dead. However, there is an apparent discrepancy between the BF and sufficient cerebral perfusion; several studies have shown that in 15% of patients with confirmed clinical diagnosis of BD, BF is still preserved. In these patients, cerebral perfusion is significantly impaired. Hence, measurement of cerebral perfusion rather than BF will provide a more precise assessment of the brain function.

In this review article, we discuss a brief history of BD, our understanding of its complex pathophysiology, current Canadian guidelines for the clinical diagnosis of BD, and the ancillary tests-specifically CT perfusion of the brain that help us with the prompt and timely diagnosis of BD.

This study provides a detailed description of the development of the gastrointestinal tract (GIT) of farmed red deer (Cervus elaphus) calves over the first 12 months of age. GIT development was measured using a combination of computerised tomography (CT) scanning and traditional slaughter plus dissection techniques. Red deer calves of a known birth date were randomly assigned to two treatment groups. A group of five animals were repeatedly CT scanned at 31, 63, 92, 135, 207, 275 and 351 days of age to identify GIT organs and determine their volume. From a group of 20 animals, subsets of four individuals were also scanned at corresponding ages (except 135 days of age). They were immediately euthanised and dissected after CT scanning to compare CT-scanned results with actual anatomical measurements. Individual organ weights were compared with their respective organ volumes determined by CT scanning and were found to have a strong, positive relationship. The combined rumen and reticulum (RR) CT-scanned volume was compared with its volume determined by the water-displacement technique and this also showed good correlation between the two techniques (R = 0.92). The allometric growth rates of organs, relative to animal live weight gains, in descending order, were the rumen, omasum, reticulum, abomasum, caecum blind sac, kidneys, spleen and liver. The red deer GIT was continuing to grow and develop when the last measurement was taken at 351 days of age. The greatest growth of the RR, when expressed in terms of empty weight, was between 31 and 92 days of age. Compared with sheep and cattle, it appears that the red deer have a similar or greater rate of RR development up until approximately 60 to 90 days of age; however, the final increments of GIT maturity in deer may take longer to complete, with the empty weight of the RR gaining 7.5 g/day between 275 and 351 days of age. CT scanning was validated in this study as a viable technique to follow GIT development in the same animals over time, and it provided novel information on allometric organ growth. The success of CT scanning highlights the potential future use of diagnostic imaging for GIT development studies.

This paper describes an investigation of the use of computer tomography (CT) to genetically improve carcass composition and conformation in Scottish Blackface sheep. After 5 years of selection on an index designed to improve both composition and conformation (the ‘CT index’), a large response was observed in the CT index, with genetic progress equivalent to 0.11 phenotypic standard deviations per year. Heritabilities for the index and for the component traits of average CT-assessed muscle area, ultrasonic muscle depth and ultrasonic fat depth were 0.41 (s.e. 0.08), 0.38 (s.e. 0.07), 0.41 (s.e. 0.05) and 0.30 (s.e. 0.05), respectively. The index was positively genetically correlated with ultrasonic muscle depth and carcass weight and negatively genetically correlated with fat class. The genetic and phenotypic correlations among ultrasonic measurements were positive and moderate. However, many of the genetic correlations tended to have large standard errors. Selection on the CT index moderately improved conformation and was successful at decreasing fat class of the carcass. Equivalent selection on live weight at ultrasound scanning would improve carcass and slaughter weight, and total price received, but would have a slightly deleterious impact on conformation score. The results of this study demonstrate that genetic improvement of carcass quality can be achieved in hill sheep using CT assessed traits.

In this paper we study some topics of interest to specialists in computer tomography. These are the following. (a) The Radon transform and its applications to computer tomography. (b) Problems of computer tomography with partially known data. Estimates of stability will be given for different types of distance in the space of probability distributions. We consider the problem with partially known tomographic data as a stability problem for appropriately chosen distances. This approach allows us to give a solution of the so-called computer tomography paradox. (c) The relation of quantum mechanics to computer tomography. An intriguing method for ‘measuring' wavefunctions by tomographic methods (CAT scans) opens a new approach to various problems in quantum mechanics. Using the method outlined for the solution of the computer tomography paradox, we derive inequalities that estimate the amount of information on the wavefunctions resulting from real CAT scans, i.e. CAT scans based on the finite number of measured marginals (projections) of the Wigner distributions. In conclusion, we propose a new version of the mathematical justification of CAT scans.