Reliability of 3D image analysis and influence of contrast medium administration on measurement of Hounsfield unit values of the proximal femur

Abstract

Purpose: To evaluate the reliability of 3D image analysis and the effect of an iodine contrast agent on the computed tomography (CT) Hounsfield unit (HU) values of the proximal femur.

Materials and methods: Fifty female patients (mean age, 61.3 years; age range, 50-79 years) who underwent both pre- and post-enhancement abdominopelvic CT scans were included in this retrospective study. Whole 3D volumes of the left proximal femur from the head to the lesser trochanter were extracted using the regional growth technique with commercial 3D software. Total volume, mean HU, and HU histogram analysis (HUHA) values of the extracted femur were calculated. HUHA distribution was classified into HUHAfat for the assumed fatty marrow (percentage of negative HU values) and HUHAdense-bone (percentage of HU values ≥ 126 HU). Reliability was assessed by calculating intra- and interobserver correlation coefficients (ICCs) and by drawing Bland-Altman plots. The effect of contrast medium administration was evaluated by the paired t-test.

Results: All intra- and interobserver ICCs of 3D volume measurements showed excellent reproducibility (all ICCs > 0.90). On Bland-Altman analysis of two observers' 3D volume measurements, the differences in the mean total volume, HUHAfat, HUHAdense-bone, and mean HU were 2.4 cm3, 0.17%, 0.6%, and 1.9 HU, respectively. The mean difference in HU after contrast agent administration (-2.2 HU) was not significant (P = 0.27). The mean difference in HUHAfat and HUHAdense-bone after contrast agent administration were -1.1% and -2.2%, respectively, on the Bland-Altman plot. HUHAfat and HUHAdense-bone showed significant differences (P < 0.05). The 95% limits of agreement for HUHAfat, HUHAdense-bone, and mean HU were -3.6% to 1.3%, -6.5% to 2.1%, and -30.0 to 25.5 HU, respectively.

Conclusion: Image analysis based on 3D volume measurement of the proximal femur showed excellent reliability, with the contrast agent administration showing negligible influence on the mean HU.

Fig 1. Flowchart of patient selection.

APCT = abdominopelvic CT.

Fig 2. 3D volume of interest (VOI) image analysis.

3D multiplanar reconstructions and volume-rendered image analysis were performed using commercial 3D software (Aquarius iNtuition v4.4.12^®). The femur was selected on the volume-rendered image using the regional growth method by checking all 2D multiplanar reconstructed images. The entire bone of the proximal femur from the femoral head to the inferior margin of the lesser trochanter was extracted and analyzed. The total volume (cm³), mean HU (HU), and HU histogram analysis (HUHA) were automatically calculated. Each HUHA is shown as both a volume (cm³) and as a percentage of the VOI (%). The HUHA_fat (yellow box), which reflects the percentage of HU values of zero or less in the entire VOI, represents the fatty marrow. The HUHA_dense-bone (red box), which reflects the percentage of HU values of 126 or above in the entire VOI, represents dense cortical bone.

Fig 3. Bland–Altman plots of inter-rater agreement.

Bland–Altman plots of measures of the total volume (A), the HUHA_fat (B), the HUHA_dense-bone (C), and the mean HU (D) show the relationships among measurements made by the two observers. Differences (y-axis) between duplicate measurements are plotted against the mean values (x-axis) of those measurements. Solid blue lines indicate mean differences. The top and bottom dashed lines correspond to the upper and lower margins of the 95% limits of agreement. At a probability of 95%, differences in normalized scores lie between the upper and lower limits of agreement (mean ± variability estimate = 1.96 standard deviations [SDs]).

Fig 4. Bland–Altman comparisons of data derived from pre- and postcontrast enhancement CT scans.

Bland–Altman plots for measurement of the HUHA_fat (A), the HUHA_dense-bone (B), and the mean HU (C) show mean differences with contrast agent administration. Differences (y-axis) are plotted against mean values (x-axis). Solid blue lines indicate mean differences. The top and bottom dashed lines are the upper and lower margins of the 95% limits of agreement. At a probability of 95%, differences in the normalized scores lie between the upper and lower limits (mean ± variability estimate = 1.96 standard deviations [SDs]).