Improving Image Quality of Bronchial Arteries with Virtual Monochromatic Spectral CT Images

Improved digital chest tomosynthesis image quality by use of a projection-based dual-energy virtual monochromatic convolutional neural network with super resolution

We developed a novel dual-energy (DE) virtual monochromatic (VM) very-deep super-resolution (VDSR) method with an unsharp masking reconstruction algorithm (DE–VM–VDSR) that uses projection data to improve the nodule contrast and reduce ripple artifacts during chest digital tomosynthesis (DT). For estimating the residual errors from high-resolution and multiscale VM images from the projection space, the DE–VM–VDSR algorithm employs a training network (mini-batch stochastic gradient-descent algorithm with momentum) and a hybrid super-resolution (SR) image [simultaneous algebraic reconstruction technique (SART) total-variation (TV) first-iterative shrinkage–thresholding algorithm (FISTA); SART–TV–FISTA] that involves subjective reconstruction with bilateral filtering (BF) [DE–VM–VDSR with BF]. DE-DT imaging was accomplished by pulsed X-ray exposures rapidly switched between low (60 kV, 37 projection) and high (120 kV, 37 projection) tube-potential kVp by employing a 40° swing angle. This was followed by comparison of images obtained employing the conventional polychromatic filtered backprojection (FBP), SART, SART–TV–FISTA, and DE–VM–SART–TV–FISTA algorithms. The improvements in contrast, ripple artifacts, and resolution were compared using the signal-difference-to-noise ratio (SDNR), Gumbel distribution of the largest variations, radial modulation transfer function (radial MTF) for a chest phantom with simulated ground-glass opacity (GGO) nodules, and noise power spectrum (NPS) for uniform water phantom. The novel DE–VM–VDSR with BF improved the overall performance in terms of SDNR (DE–VM–VDSR with BF: 0.1603, without BF: 0.1517; FBP: 0.0521; SART: 0.0645; SART–TV–FISTA: 0.0984; and DE–VM–SART–TV–FISTA: 0.1004), obtained a Gumbel distribution that yielded good images showing the type of simulated GGO nodules used in the chest phantom, and reduced the ripple artifacts. The NPS of DE–VM–VDSR with BF showed the lowest noise characteristics in the high-frequency region (~0.8 cycles/mm). The DE–VM–VDSR without BF yielded an improved resolution relative to that of the conventional reconstruction algorithms for radial MTF analysis (0.2–0.3 cycles/mm). Finally, based on the overall image quality, DE–VM–VDSR with BF improved the contrast and reduced the high-frequency ripple artifacts and noise.

Visibility of bronchial arteries using virtual and advanced virtual monoenergetic imaging

BACKGROUND

The utility of virtual monoenergetic imaging (VMI) for fine arteries has not been well clarified.

PURPOSE

To assess bronchial artery visualization using VMI and noise-optimized advanced VMI (VMI+).

MATERIAL AND METHODS

Eighty-seven patients with esophageal cancer underwent computed tomography (CT) using a third-generation dual-source system before surgery. Tube voltages were set to 90 kVp and 150 kVp, respectively. Images were reconstructed using VMI and VMI+ with energy levels of 40-120 keV (in 10-keV increments); composite images equivalent to CT images at 105 kVp were also generated. The CT attenuation value and contrast-to-noise ratio (CNR) of bronchial arteries using VMI and VMI+ were compared with those obtained using composite imaging. Two radiologists subjectively analyzed bronchial artery visualization with reference to the composite image.

RESULTS

CT attenuation values for bronchial arteries using VMI at 40-60 keV and VMI+ at 40 keV and 50 keV were significantly higher than those obtained using composite imaging (P < 0.05). CNR using VMI at 40-60 keV was significantly higher than that obtained using composite imaging (P < 0.05), whereas no differences were noted for values obtained using composite imaging between VMI+ at 40 keV and 50 keV. In the subjective analysis, VMI at 40 keV and 50 keV yielded significantly better visibility of bronchial arteries than VMI+ (P < 0.05).

CONCLUSION

VMI and VMI+ at low voltages (40-50 keV) may be useful for bronchial artery visualization. VMI+ may be less effective for fine vessels as bronchial artery visualization.

Evaluation of the bronchial arteries: normal findings, hypertrophy and embolization in patients with hemoptysis

The enlargement of the bronchial arteries occurs in a multitude of congenital and acquired diseases and is responsible for the majority of cases of hemoptysis. In this review, we provide a simplified imaging approach to the evaluation of the bronchial arteries. We highlight the anatomy and function of the bronchial arteries, typical imaging findings, how to recognize bronchial artery dilatation, and its underlying causes. Contrast-enhanced computer tomography plays a major role in diagnosing bronchial artery enlargement and also improves treatment planning. Bronchial artery embolization has proven to be effective in controlling the potential hazardous hemoptysis.

Differential diagnosis between benign and malignant pleural effusion with dual-energy spectral CT

PURPOSE

To investigate the value of spectral CT in the differential diagnosis of benign from malignant pleural effusion.

METHOD AND MATERIALS

14 patients with benign pleural effusion and 15 patients with malignant pleural effusion underwent non-contrast spectral CT imaging. These patients were later verified by the combination of disease history, clinical signs and other information with the consensus of surgeons and radiologists. Various Spectral CT image parameters measured for the effusion were as follows: CT numbers of the polychromatic 140kVp images, monochromatic images at 40keV and 100keV, the material density contents from the water, fat and blood-based material decomposition images, the effective atomic number and the spectral curve slope. These values were statistically compared with t test and logistic regression analysis between benign and malignant pleural effusion.

RESULTS

The CT value of benign and malignant pleural effusion in the polychromatic 140kVp images showed no differences (12.61±3.39HU vs. 14.71±5.03HU) (P>0.05), however, they were statistically different on the monochromatic images at 40keV (43.15±3.79 vs. 39.42±2.60, p = 0.005) and 100keV (9.11±1.38 vs. 6.52±2.04, p<0.001). There was difference in the effective atomic number value between the benign (7.87±0.08) and malignant pleural effusion (7.90±0.02) (P = 0.02). Using 6.32HU as the threshold for CT value measurement at 100keV, one could obtain sensitivity of 100% and specificity of 66.7% with area-under-curve of 0.843 for differentiating benign from malignant effusion. In addition, age and disease history were potential confounding factors for differentiating malignant pleural effusion from benign, since the older age (61.13±12.51 year-old vs48.57±12.33 year-old) as well as longer disease history (70.00±49.28 day vs.28.36±21.64 day) were more easily to be found in the malignant pleural effusion group than those in the benign pleural effusion group. By combining above five factors, one could obtain sensitivity of 100% and specificity of 71.4% with area-under-curve of 0.933 for differentiating benign from malignant effusion.

CONCLUSION

The CT value measurement at both high and low energy levels and the effective atomic number obtained in a single spectral CT scan can assist the differential diagnosis of benign from malignant pleural effusion.Combining them with patient age and disease history can further improve diagnostic performance.

CLINICAL RELEVANCE/APPLICATION

Clinical findings and Spectral CT imaging can provide significant evidences about the nature of pleural effusion.