No abstract

Objective: To evaluate phantomless assessment of volumetric bone mineral density (vBMD) based on virtual non-contrast images of arterial (VNCa) and venous phase (VNCv) derived from spectral detector CT in comparison to true non-contrast (TNC) images and adjusted venous phase conventional images (CIV(adjusted)). Methods: 104 consecutive patients who underwent triphasic spectral detector CT between January 2018 and April 2019 were retrospectively included. TNC, VNCa, VNCv and venous phase images (CIV) were reconstructed. vBMD was obtained by two radiologists using an FDA/CE-cleared software. Average vBMD of the first three lumbar vertebrae was determined in each reconstruction; vBMD of CIV was adjusted for contrast enhancement as suggested earlier. Results: vBMD values obtained from CIV(adjusted) are comparable to vBMD values derived from TNC images (91.79 ± 36.52 vs 90.16 ± 41.71 mg/cm3, p = 1.00); however, vBMD values derived from VNCa and VNCv (42.20 ± 22.50 and 41.98 ± 23.3 mg/cm3 respectively) were significantly lower as compared to vBMD values from TNC and CIV(adjusted) (all p ≤ 0.01). Conclusion: Spectral detector CT-derived virtual non-contrast images systematically underestimate vBMD and therefore should not be used without appropriate adjustments. Adjusted venous phase images provide reliable results and may be utilized for an opportunistic BMD screening in CT examinations. Advances in knowledge: Adjustments of venous phase images facilitate opportunistic assessment of vBMD, while spectral detector CT-derived VNC images systematically underestimate vBMD.

No abstract

Objective The aim of the study was to evaluate the effect of slice thickness, iterative reconstruction (IR) algorithm, and kernel selection on measurement accuracy and interobserver variability for semiautomated renal cortex volumetry (RCV) with multislice computed tomography (CT). Methods Ten patients (62.4 ± 17.2 years) undergoing abdominal biphasic multislice computed tomography were enrolled in this retrospective study. Computed tomography data sets were reconstructed at 1-, 2-, and 5-mm slice thickness with 2 different IR algorithms (iDose, IMRST) and 2 different kernels (IMRS and IMRR) (Philips, the Netherlands). Two readers independently performed semiautomated RCV for each reconstructed data set to calculate left kidney volume (LKV) and split renal function (SRF). Statistics were calculated using analysis of variance with Geisser-Greenhouse correction, followed by Tukey multiple comparisons post hoc test. Statistical significance was defined as P ≤ 0.05. Results Semiautomated RCV of 120 data sets (240 kidneys) was successfully performed by both readers. Semiautomated RCV provides comparable results for LKV and SRF with 3 different slice thicknesses, 2 different IR algorithms, and 2 different kernels. Only the 1-mm slice thickness showed significant differences for LKV between IMRR and IMRS (P = 0.02, mean difference = 4.28 bb) and IMRST versus IMRS (P = 0.02, mean difference = 4.68 cm3) for reader 2. Interobserver variability was low between both readers irrespective of slice thickness and reconstruction algorithm (0.82 ≥ P ≥ 0.99). Conclusions Semiautomated RCV measurements of LKV and SRF are independent of slice thickness, IR algorithm, and kernel selection. These findings suggest that comparisons between studies using different slice thicknesses and reconstruction algorithms for RCV are valid.