Standardized volume-rendering of contrast-enhanced renal magnetic resonance angiography

Visual grading regression: analysing data from visual grading experiments with regression models

For visual grading experiments, which are an easy and increasingly popular way of studying image quality, hitherto used data analysis methods are often inadequate. Visual grading analysis makes assumptions that are not statistically appropriate for ordinal data, and visual grading characteristic curves are difficult to apply in more complex experimental designs. The approach proposed in this paper, visual grading regression (VGR), consists of an established statistical technique, ordinal logistic regression, applied to data from single-image and image-pair experiments with visual grading scores selected on an ordinal scale. The approach is applicable for situations in which, for example, the effects of the choice of imaging equipment and post-processing method are to be studied simultaneously, while controlling for potentially confounding variables such as patient and observer identity. The analysis can be performed with standard statistical software packages using straightforward coding of the data. We conclude that the proposed statistical technique is useful in a wide range of visual grading studies.

Standardized volume rendering for magnetic resonance angiography measurements in the abdominal aorta

PURPOSE

To compare three methods for standardizing volume rendering technique (VRT) protocols by studying aortic diameter measurements in magnetic resonance angiography (MRA) datasets.

MATERIAL AND METHODS

Datasets from 20 patients previously examined with gadolinium-enhanced MRA and with digital subtraction angiography (DSA) for abdominal aortic aneurysm were retrospectively evaluated by three independent readers. The MRA datasets were viewed using VRT with three different standardized transfer functions: the percentile method (Pc-VRT), the maximum-likelihood method (ML-VRT), and the partial range histogram method (PRH-VRT). The aortic diameters obtained with these three methods were compared with freely chosen VRT parameters (F-VRT) and with maximum intensity projection (MIP) concerning inter-reader variability and agreement with the reference method DSA.

RESULTS

F-VRT parameters and PRH-VRT gave significantly higher diameter values than DSA, whereas Pc-VRT gave significantly lower values than DSA. The highest interobserver variability was found for F-VRT parameters and MIP, and the lowest for Pc-VRT and PRH-VRT. All standardized VRT methods were significantly superior to both MIP and F-VRT in this respect. The agreement with DSA was best for PRH-VRT, which was the only method with a mean error below 1 mm and which also had the narrowest limits of agreement (95% of cases between 2.1 mm below and 3.1 mm above DSA).

CONCLUSION

All the standardized VRT methods compare favorably with MIP and VRT with freely selected parameters as regards interobserver variability. The partial range histogram method, although systematically overestimating vessel diameters, gives results closest to those of DSA.