4.1 Introduction
The global thresholding method represents another quantitative technique developed in an
attempt to provide better reproducibility and speed than with manual outlining (Wicks et al,
1992). The method has previously required three observer dependant stages:
1. Identification of the optimum intensity threshold that segments hyper-intense lesions
from background.
2. Deletion of those areas not corresponding to a lesion.
3. Addition of any lesions that were of lower intensity than the threshold (and had therefore
not been segmented).
The necessity to perform of all these steps inevitably leads to loss of automation, reproducibility and speed. The operator-dependant choice of an intensity threshold is a subjective process and
represents a major determinant of the derived lesion volume (Filippi et al, 1996e).
Reproducibility has been shown to improve when a single threshold is chosen by consensus
(Filippi et al, 1995d). However, a different threshold must be chosen for each scan in serial
studies due to the variations in scanner sensitivity that occur over time (arising, for example from differences in coil loading, receiver attenuation setting and scanner pre-amplifier gain). A more objective method for determination of the threshold is therefore a priority.
The histogram matching algorithm corrects for changes in scanner sensitivity over time, by
process involves two stages; (i) windowing of the image histograms to eliminate the influence of background signal, and (ii) minimising the windowed squares of the residual differences
between the two matched histograms (Wang et al, 1997a).
The aim of this study was to determine whether histogram matching would allow a single global threshold to be applied across multiple scans. Furthermore, post threshold editing is currently required to both delete non-lesion areas and add those lesions missed by the threshold. This process also leads to a loss of reproducibility and speed. The proportion of spurious non-lesion regions increases with a lower threshold choice, but the use of a relatively low threshold has been advocated since it reduces the requirement for adding lesions missed by the threshold (Filippi
et al, 1996e). Without such post threshold editing, the calculated lesion volumes will inevitably
include areas of hyper-intensity not corresponding to a lesion. However, if these areas were
consistently included over serial studies, any change in lesion volume over time should still be
detected.
These issues were therefore addressed by comparing Tj lesion volumes derived by the histogram corrected global threshold method against contour-derived lesion volumes, both cross sectionally and longitudinally. The contour method was used as a gold standard as it yields lesion volumes similar to manual outlining with better reproducibility, as discussed in chapter 3.
4,2 Patients and Methods
The baseline and month 9 MRI scans of 8 patients with clinically definite relapsing remitting or
secondary progressive MS fulfilling Poser criteria (Poser et al, 1983) were selected. All MRI
scans were obtained on a 1.5 T imager with 28 contiguous 5 mm axial slices from foramen magnum to vertex. A CSE sequence was used with the following imaging parameters; TR 2000
ms, TEs 34 and 90 ms, matrix 256x256, FOV 25 cm. Non-uniformity corrections were applied
to all of the images using an oil-phantom based correction (Wicks et al, 1993).
Image analysis was performed on a Sun workstation (Sun Microsystems, Mountain View, CA).
The contouring method (Plummer, 1992; Grimaud et al, 1996) has been described in Chapter
3. The author performed the lesion quantification on all the images using the contour method. The baseline and follow up scans were analysed on separate occasions and without reference to each other. In order to measure intra-rater reproducibility, the author repeated the lesion quantification on the same MRI dataset after a delay of at least one week. Analysis was also performed by a second rater, to obtain a measure of inter rater reproducibility. Lesions were identified independently by the two raters from the electronic data and segmented from the shorter TE images.
The histogram matching correction was first applied to the baseline short TE images using a randomly chosen scan as reference. For each patient, the follow up scan was then histogram matched to its corresponding corrected baseline scan in order to obtain the best possible match between the serial scans. Assessment of the effectiveness of the correction was performed by identifying and comparing the mean signal intensity of an area of NAWM in the deep left frontal lobe before and after the correction for the baseline and serial scans.
The global thresholding technique was then applied to the reference scan. This involves two stages; (i) application of an automated algorithm that performs cranial extra cerebral tissue extraction using thresholding and a knowledge of the 3-D structure of the brain, and (ii) identification of the intensity threshold that best separates hyper-intense MS lesions from
visible lesions were above the threshold and therefore included in the total lesion volume. This same threshold was then applied to the other 15 histogram matched scans.
Finally, the regions included by the global threshold were reviewed and manual editing was performed to delete any segmented regions that did not represent lesion. This involved both complete removal of non-lesion regions, and manual editing to amend regions that contained both lesion and non-lesion areas. After a delay of at least a week, this process was repeated on the baseline scans in order to provide a measure of reproducibility.
4.2.1 Statistics
The inter rater reproducibility for the contour method was assessed by comparison of the first set of measurements of the author and the single set of volumes obtained by the second observer, using Co Vs, having confirmed that the size of individual Co Vs was independent of the mean lesion volume. The intra-rater reproducibility was similarly described using Co Vs for the two sets of measurements of observer one.
In order to assess the agreement between the lesion volumes obtained with global thresholding and contouring methods, the mean of the three contour derived lesion volumes on each scan was compared with the volume obtained using the global threshold (before and after manual editing). Agreement between the techniques was calculated for both baseline lesion volumes and change over time as an ICC (Armitage & Berry, 1994; Streiner & Norman, 1995). The differences between the volumes measured with these techniques were also used to calculate the limits of agreement and bias. In 95% of the measurements, there should be agreement to within mean ±2 standard deviations of the differences (Bland & Altman, 1986).
4.3 Results
4.3.1 Effectiveness o f the histogram matching correction
The mean absolute percentage difference in signal intensity of the NAWM area between the reference scan and the other seven baseline studies was 15.2% before histogram matching and only 3.8% after the correction. For the serial scans the mean absolute differences in NAWM intensity between the baseline and follow up scans before and after the correction were 11.9% and 2.1% respectively.
4.3.2 Reproducibility and time consumption o f the contour method
The median intra and inter-rater Co Vs for measurements on the baseline scans were 2.4% and 7.5% respectively. The median time per person taken to perform the contour method was 44 minutes.
4.3.3 Global threshold volumes before editing
The ICC for agreement between absolute lesion volumes derived by the global thresholding and contouring was only 0.46 and the limits of agreement were wide at 46.6cm^ ± 118.9cm^. This bias of 46.6cm^ reflects the larger volumes obtained with the global threshold and the agreement is clearly poor. The differences between the two techniques are displayed graphically in Figure 4.1. The ICC for the changes in lesion volumes detected with the two techniques was only 0.17 and the limits of agreement were again wide at 25.5cm^ ± 88.8 cm^.
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□ Global Threshold vol. pre editing 0 Global Threshold w l. post editing □ Contour derived lesion volume