Multicentre imaging measurements for oncology and in the brain

P S Tofts, D J Collins
2011 British Journal of Radiology  
Multicentre imaging studies of brain tumours (and other tumour and brain studies) can enable a large group of patients to be studied, yet they present challenging technical problems. Differences between centres can be characterised, understood and minimised by use of phantoms (test objects) and normal control subjects. Normal white matter forms an excellent standard for some MRI parameters (e.g. diffusion or magnetisation transfer) because the normal biological range is low (,2-3%) and the
more » ... rements will reflect this, provided the acquisition sequence is controlled. MR phantoms have benefits and they are necessary for some parameters (e.g. tumour volume). Techniques for temperature monitoring and control are given. In a multicentre study or treatment trial, between-centre variation should be minimised. In a cross-sectional study, all groups should be represented at each centre and the effect of centre added as a covariate in the statistical analysis. In a serial study of disease progression or treatment effect, individual patients should receive all of their scans at the same centre; the power is then limited by the within-subject reproducibility. Sources of variation that are generic to any imaging method and analysis parameters include MR sequence mismatch, B 1 errors, CT effective tube potential, region of interest generation and segmentation procedure. Specific tissue parameters are analysed in detail to identify the major sources of variation and the most appropriate phantoms or normal studies. These include dynamic contrast-enhanced and dynamic susceptibility contrast gadolinium imaging, T 1 , diffusion, magnetisation transfer, spectroscopy, tumour volume, arterial spin labelling and CT perfusion. There have been many approaches to carrying out multicentre imaging studies. A common difficulty is a measurement made at one centre is often not reproducible at another centre and to pool measurements from several centres into a large trial reduces its statistical power. Yet there is a strong imperative to be able to carry out meaningful multicentre studies so clinical drug trials with a large number of subjects can take place in a reasonable time. Analysing the sources of intercentre variation, with insight into the MR physics aspects of the imaging process, and then reducing them where possible has allowed progress to be made. Measuring actual quantities, such as volume, relaxation time or transfer constant, has meant in principle we are able to obtain values independent of the scanner used and the particular way the measurement was carried out. Multicentre imaging studies are desirable for several reasons. 1. In clinical treatment trials, they are usually the only way of achieving the large number of patients needed to statistically power the study. 2. Measurement of good intercentre agreement demonstrates the imaging technique is good and the results of clinical or scientific research can be applied to other centres. 3. Good intercentre agreement also demonstrates that the physical factors involved in the measurement process are relatively well understood and controlled, and that the process is relatively reliable and robust and serial measurements through imager upgrades are also likely to be reliable. 4. Pharmaceutical companies will sometimes recruit a large number of clinical centres to engage with many potential buyers of the treatment (although this can actually reduce the power of the study as discussed later). Multicentre studies have considerable difficulties [1]. These are primarily related to logistics and variance. Logistical problems relate to the interfacing required by the reading centre to the many different imaging centres, which each have a potentially different imaging hardware and protocol, system of controlling and documenting the protocol, and image data format. The resources required increases approximately proportional to the number of imaging centres used. Variance problems relate to the way image measurements of a given subject can vary between centres (the between-centre variance) and how the variance can mask the effects of treatment. A small number of carefully selected and controlled centres, which give high quality data, might give better statistical power than a large number of relatively low quality centres. Minimising between-centre variance (and also within-centre variance) is at the heart of this paper. In this paper we discuss measurement variance in general terms, including how it affects cross-sectional and serial measurements. The principle sources in MR and CT measurements are identified. Concepts of quality assurance (QA) using normal human controls (healthy volunteers) and phantoms (test objects that seek to simulate
doi:10.1259/bjr/74316620 pmid:22433831 pmcid:PMC3473901 fatcat:tjmigfvftbcj7k7tbmai5swi2u