Topogram-based automated selection of the tube potential and current in thoraco-abdominal trauma CT - a comparison to fixed kV with mAs modulation alone.

OBJECTIVE: To investigate the impact of automated attenuation-based tube potential selection on image quality and exposure parameters in polytrauma patients undergoing contrast-enhanced thoraco-abdominal CT. METHODS: One hundred patients were examined on a 16-slice device at 120 kV with 190 ref.mAs and automated mA modulation only. Another 100 patients underwent 128-slice CT with automated mA modulation and topogram-based automated tube potential selection (autokV) at 100, 120 or 140 kV. Volume CT dose index (CTDI(vol)), dose-length product (DLP), body diameters, noise, signal-to-noise ratio (SNR) and subjective image quality were compared. RESULTS: In the autokV group, 100 kV was automatically selected in 82 patients, 120 kV in 12 patients and 140 kV in 6 patients. Patient diameters increased with higher kV settings. The median CTDI(vol) (8.3 vs. 12.4 mGy; -33%) and DLP (594 vs. 909 mGy cm; -35%) in the entire autokV group were significantly lower than in the group with fixed 120 kV (p < 0.05 for both). Image quality remained at a constantly high level at any selected kV level. CONCLUSION: Topogram-based automated selection of the tube potential allows for significant dose savings in thoraco-abdominal trauma CT while image quality remains at a constantly high level. KEY POINTS: • Automated kV selection in thoraco-abdominal trauma CT results in significant dose savings • Most patients benefit from a 100-kV protocol with relevant DLP reduction • Constantly good image quality is ensured • Image quality benefits from higher kV when arms are positioned downward.

Diagnostic accuracy of late iodine-enhancement dual-energy computed tomography for the detection of chronic myocardial infarction compared with late gadolinium-enhancement 3-T magnetic resonance imaging.

OBJECTIVES: The purpose of the study was to compare the performance of late iodine-enhancement (LIE) dual-energy computed tomography (DECT) linear blending and selective myocardial iodine mapping for the detection of chronic myocardial infarction (CMI) with late gadolinium-enhancement (LGE) 3-T magnetic resonance imaging. MATERIALS AND METHODS: This study was approved by the institutional review board, and the patients gave informed consent. A total of 20 patients with a history of CMI underwent cardiac LIE-DECT and LGE-MRI. Images of the LIE-DECT were reconstructed as 100 kilovolt (peak) (kV[p]), 140 kV(p), and weighted-average (WA; linear blending) images from low- and high-kilovoltage peak data using 3 different weighting factors (0.8, 0.6, 0.3). Additional color-coded myocardial iodine distribution maps were calculated. The images were reviewed for the presence of late enhancement, transmural extent, signal characteristics, infarct volume, and subjective image quality. RESULTS: Segmental analysis of LIE-DECT data from 100 kV(p), WA of 0.8, and WA of 0.6 showed identical results for the identification of CMI (89% sensitivity, 98% specificity, 96% accuracy) and correctly identified all segments with transmural scarring detected through LGE-MRI. Weighted average of 0.6 received the best subjective image quality rating (15/20 votes) and average measured infarct size correlated best with LGE-MRI (5.7% difference). In comparison with LGE-MRI, iodine distribution maps were susceptible to false-positive and false-negative findings (52% sensitivity, 88% specificity, 81% accuracy), overestimating quantity of transmural scars by 78% while underestimating infarct volume by 55%. CONCLUSIONS: Late iodine enhancement cardiac dual-energy computed tomography correlates well with LGE-MRI for detecting CMI, whereas iodine distribution analysis provides inferior accuracy. Linear blending further improves image quality and enables more precise estimation of scar volume.