Automatic quantification of subarachnoid hemorrhage on noncontrast CT

Abstract

Background and purpose: Quantification of blood after SAH on initial NCCT is an important radiologic measure to predict patient outcome and guide treatment decisions. In current scales, hemorrhage volume and density are not accounted for. The purpose of this study was to develop and validate a fully automatic method for SAH volume and density quantification.

Materials and methods: The automatic method is based on a relative density increase due to the presence of blood from different brain structures in NCCT. The method incorporates density variation due to partial volume effect, beam-hardening, and patient-specific characteristics. For validation, automatic volume and density measurements were compared with manual delineation on NCCT images of 30 patients by 2 radiologists. The agreement with the manual reference was compared with interobserver agreement by using the intraclass correlation coefficient and Bland-Altman analysis for volume and density.

Results: The automatic measurement successfully segmented the hemorrhage of all 30 patients and showed high correlation with the manual reference standard for hemorrhage volume (intraclass correlation coefficient = 0.98 [95% CI, 0.96-0.99]) and hemorrhage density (intraclass correlation coefficient = 0.80 [95% CI, 0.62-0.90]) compared with intraclass correlation coefficient = 0.97 (95% CI, 0.77-0.99) and 0.98 (95% CI, 0.89-0.99) for manual interobserver agreement. Mean SAH volume and density were, respectively, 39.3 ± 31.5 mL and 62.2 ± 5.9 Hounsfield units for automatic measurement versus 39.7 ± 32.8 mL and 61.4 ± 7.3 Hounsfield units for manual measurement. The accuracy of the automatic method was excellent, with limits of agreement of -12.9-12.1 mL and -7.6-9.2 Hounsfield units.

Conclusions: The automatic volume and density quantification is very accurate compared with manual assessment. As such, it has the potential to provide important determinants in clinical practice and research.

Fig 1.

Illustration of differentiation between partial volume effect and hemorrhage in the vicinity of the skull. A, Calculation of the density gradient of an NCCT image with high hypodensities near the skull. High gradients are expected to be caused by partial volume effects in contrast to hemorrhages, which result in low gradients as seen in B and C. The pixels corresponding to low gradients (blue) are excluded from further segmentation. The white arrows mark the areas with high gradients present in the CSF image.

Fig 2.

Illustration of the correction for patient-specific density differences. A, Each section of a specific tissue type (here CSF) is divided into 64 tiles, and the SDs of the density were calculated. B, Green tiles represent those with a low SD of the density and are expected to be free of a substantial amount of extravasated blood and therefore mainly consist of healthy brain tissue, whereas tiles with a high SD (red tiles) are more likely to contain hemorrhage. The densities in the green tiles were included in the calculation of the mean density of that tissue type. Comparison with the mean density of that tissue type in the reference image resulted in a density offset, which was corrected.

Fig 3.

The accuracy of the volume measurement of the automatic method compared with that in observer 1. A, Accuracy depicted as a scatterplot. B, Accuracy shown by the Bland-Altman plot. Interobserver variability of the manual hemorrhage volume measurement depicted as C, scatterplot, and D, Bland-Altman analysis.

Fig 4.

Correlation of the Hijdra score and Fisher score with hemorrhage volume after SAH assessed with scatterplots. A, The Fisher score with automatic volume measurement (blue) and manual volume measurement (red). B, The Hijdra score with automatic volume measurement (blue) and manual volume measurement (red).

Fig 5.

Example of the results of the automatic segmentation of extravasated blood after SAH and manual measurement. A, NCCT image, shown in red, with results of the automatic method of a relatively small hemorrhage. B, The same NCCT image and hemorrhage as delineated by observer 1 (blue). C, NCCT image with beam-hardening in an extreme degree. The automatic method, in red, shows deviations of the hemorrhage volume as delineated by observer 1 (D) in blue.