Daisuke Sakabe

Purpose: To investigate whether virtual-monoenergetic images (VMI) from dual-layer spectral-detector computed tomography (DLCT) improve right adrenal vein (RAV) assessment before adrenal venous sampling (AVS), and portal-venous-phase (PVP) images alone can replace conventional multiphase CT combining late-arterial phase (LAP) and PVP. Methods: Sixty-three patients with primary aldosteronism who underwent LAP and PVP DLCT before AVS were retrospectively analyzed. Conventional polyenergetic-images (PEI) and VMI at 40–70 keV (VMI _40–70 ) were reconstructed. Image noise and contrast-to-noise ratio (CNR) of RAV were quantified. VMI with the highest CNR was predefined as the best-VMI. Two radiologists evaluated four image series (PEI and best-VMI at LAP and PVP) separately for RAV visibility, accessory hepatic vein (AHV) assessability, and image noise using five-point scales (1 = worst, 5 = best). RAV detection and AHV assessability rates were compared among image series. Results: In both enhancement phases, VMI _40–70 showed lower image noise and VMI _40–60 higher CNR than PEI (all p < 0.05), with VMI ₄₀ providing the highest CNR and being designated as the best VMI. Compared to PEI at LAP, CNR was lower with PEI at PVP but higher with VMI ₄₀ at PVP (both, p < 0.001). In subjective analysis, VMI ₄₀ showed better scores than PEI for image noise (LAP: 4.0 ± 0.5 vs. 2.4 ± 0.6; PVP: 4.0 ± 0.6 vs. 2.5 ± 0.5) and RAV visibility (LAP: 4.5 ± 0.8 vs. 3.5 ± 0.8; PVP: 3.7 ± 1.0 vs. 2.6 ± 0.9) (all p < 0.001). With PEI, the RAV detection rate was lower at PVP than at LAP (54.8% vs. 89.7%, p < 0.001). Use of VMI ₄₀ at PVP achieved the same detection rate as PEI at LAP (89.7%, p = 1.0) and higher AHV assessability rate than PEI at PVP (96.8% vs. 80.2%, p < 0.001). Conclusion: DLCT-VMI improved RAV assessments before AVS. Using VMI ₄₀ for PVP provided RAV depiction equivalent to PEI at LAP and superior AHV assessability to PEI at PVP, suggesting its potential as a surrogate for dedicated multiphase CT.

To assess the diagnostic performance of unenhanced electrocardiogram (ECG)-gated cardiac computed tomography (CT) for detecting myocardial edema, using MRI T2 mapping as the reference standard. This retrospective study protocol was approved by our institutional review board, which waived the requirement for written informed consent. Between December 2017 to February 2019, consecutive patients who had undergone T2 mapping for myocardial tissue characterization were identified. We excluded patients who did not undergo unenhanced ECG-gated cardiac CT within 3 months from MRI T2 mapping or who had poor CT image quality. All patients underwent unenhanced ECG-gated cardiac CT with an axial scan using a third-generation, 320 × 0.5 mm detector-row CT unit. Two radiologists together drew regions of interest (ROIs) in the interventricular septum on the unenhanced ECG-gated cardiac CT images. Using T2 mapping as the reference standard, the diagnostic performance of unenhanced cardiac CT for detecting myocardial edema was evaluated by using the area under the receiver operating characteristic curve with sensitivity and specificity. Youden index was used to find an optimal sensitivity-specificity cutoff point. A cardiovascular radiologist independently performed the measurements, and interobserver reliability was assessed using intraclass correlation coefficients for CT value measurements. A P value of <.05 was considered statistically significant. We included 257 patients who had undergone MRI T2 mapping. Of the 257 patients, 35 patients underwent unenhanced ECG-gated cardiac CT. One patient was excluded from the study because of poor CT image quality. Finally, 34 patients (23 men; age 64.7 ± 14.6 years) comprised our study group. Using T2 mapping, we identified myocardial edema in 19 patients. Mean CT and T2 values for 34 patients were 46.3 ± 2.7 Hounsfield unit and 49.0 ± 4.9 ms, respectively. Mean CT values moderately correlated with mean T2 values (Rho = –0.41; P < .05). Mean CT values provided a sensitivity of 63.2% and a specificity of 93.3% for detecting myocardial edema, with a cutoff value of ≤45.0 Hounsfield unit (area under the receiver operating characteristic curve = 0.77; P < .01). Inter-observer reproducibility in measuring mean CT values was excellent (intraclass correlation coefficient = 0.93; [95% confidence interval: 0.86, 0.96]). Myocardial edema could be detected by CT value of myocardium in unenhanced ECG-gated cardiac CT.

Objective: We compared the effect of a dual-region-of-interest (ROI) bolus-tracking technique on interpatient variability of arterial contrast enhancement with that of the conventional bolus-tracking technique in coronary computed tomographic angiography (CTA) on a 320-row scanner. Methods: This study included 100 patients who underwent coronary CTA using one of two protocols: (1) 50 patients underwent scanning using a conventional single-ROI bolus-tracking technique (P-single) with an ROI placed in the ascending aorta, and (2) 50 patients underwent scanning using a dual-ROI technique (P-dual) with two ROIs placed in the pulmonary trunk and the ascending aorta. CT attenuation in the ascending aorta and coronary arteries, and the interpatient variability were compared between the two scanning protocols. Results: The mean CT attenuation of the ascending aorta and coronary arteries tended to be higher for P-dual than for P-single, but the difference was not significant (p = 0.08–0.30). The interpatient variability of contrast enhancement (SD of the CT attenuation) was significantly smaller for P-dual than for P-single (p < 0.01). Conclusion: The dual-ROI bolus-tracking technique can reduce interpatient variability of arterial contrast enhancement in coronary CTA on a 320-row scanner. Advances in knowledge: The use of a dual-ROI bolus-tracking technique can provide sufficient and consistent arterial enhancement of coronary CTA.