Ultralow-dose CT with knowledge-based iterative model reconstruction (IMR) in evaluation of pulmonary tuberculosis: comparison of radiation dose and image quality

CT and 18F-FDG PET abnormalities in contacts with recent tuberculosis infections but negative chest X-ray

Close contacts of individuals with pulmonary tuberculosis are at risk for tuberculosis infection and the development of active tuberculosis. In current contact investigations, immunologic tests (the tuberculin skin test and interferon-gamma release assay) and chest X-ray examinations are used to dichotomize contacts with Mycobacterium tuberculosis infections into those with active (X-ray abnormalities) versus latent tuberculosis (normal radiographs). This article is a critical review of computed tomographic (CT) and 18-fluorodeoxyglucose positron emission tomographic (PET) findings of incipient tuberculosis without X-ray abnormalities based on a systematic literature review of twenty-five publications. The CT and 18-fluorodeoxyglucose PET studies revealed minimal pauci-nodular infiltrations in the lung parenchyma and mediastinal lymph nodes abnormalities with metabolic uptake in approximately one-third of asymptomatic close contacts with negative chest radiographic and bacteriological/molecular results for active tuberculosis. Tuberculosis with minimal changes challenge the validity of simply dichotomizing cases of recent M. tuberculosis infections in contacts depending on the presence of X-ray abnormalities as the recent infections may spontaneously regress, remain stagnant, or progress to active tuberculosis in human and nonhuman primate studies. Whether contacts with tuberculosis with minimal changes are interpreted as having active tuberculosis or latent tuberculosis has clinical implications in terms of specific benefits and harms under the current contact management. Advanced imaging tools may help further stratify contacts intensely exposed to M. tuberculosis on a continuous spectrum from latent tuberculosis to incipient, subclinical and active tuberculosis. Identifying incipient tuberculosis would provide an opportunity for earlier and tailored treatment before active tuberculosis is established.

Cycle-Consistent Generative Adversarial Network: Effect on Radiation Dose Reduction and Image Quality Improvement in Ultralow-Dose CT for Evaluation of Pulmonary Tuberculosis

Objective

To investigate the image quality of ultralow-dose CT (ULDCT) of the chest reconstructed using a cycle-consistent generative adversarial network (CycleGAN)-based deep learning method in the evaluation of pulmonary tuberculosis.

Materials and Methods

Between June 2019 and November 2019, 103 patients (mean age, 40.8 ± 13.6 years; 61 men and 42 women) with pulmonary tuberculosis were prospectively enrolled to undergo standard-dose CT (120 kVp with automated exposure control), followed immediately by ULDCT (80 kVp and 10 mAs). The images of the two successive scans were used to train the CycleGAN framework for image-to-image translation. The denoising efficacy of the CycleGAN algorithm was compared with that of hybrid and model-based iterative reconstruction. Repeated-measures analysis of variance and Wilcoxon signed-rank test were performed to compare the objective measurements and the subjective image quality scores, respectively.

Results

With the optimized CycleGAN denoising model, using the ULDCT images as input, the peak signal-to-noise ratio and structural similarity index improved by 2.0 dB and 0.21, respectively. The CycleGAN-generated denoised ULDCT images typically provided satisfactory image quality for optimal visibility of anatomic structures and pathological findings, with a lower level of image noise (mean ± standard deviation [SD], 19.5 ± 3.0 Hounsfield unit [HU]) than that of the hybrid (66.3 ± 10.5 HU, p < 0.001) and a similar noise level to model-based iterative reconstruction (19.6 ± 2.6 HU, p > 0.908). The CycleGAN-generated images showed the highest contrast-to-noise ratios for the pulmonary lesions, followed by the model-based and hybrid iterative reconstruction. The mean effective radiation dose of ULDCT was 0.12 mSv with a mean 93.9% reduction compared to standard-dose CT.

Conclusion

The optimized CycleGAN technique may allow the synthesis of diagnostically acceptable images from ULDCT of the chest for the evaluation of pulmonary tuberculosis.

Ultra-low-dose CT reconstructed with ASiR-V using SmartmA for pulmonary nodule detection and Lung-RADS classifications compared with low-dose CT

AIM

To evaluate the accuracy of ultra-low-dose computed tomography (ULDCT) with ASiR-V using a noise index (SmartmA) for pulmonary nodule detection and Lung CT Screening Reporting And Data System (Lung-RADS) classifications compared with low-dose CT (LDCT).

MATERIALS AND METHODS

Two-hundred and ten patients referred for lung cancer screening underwent conventional chest LDCT (0.80 ± 0.28 mSv) followed immediately by ULDCT (0.16 ± 0.03 mSv). ULDCT was scanned using 120 kV/SmartmA with a noise index of 28 HU and reconstructed with ASiR-V70%. The types and diameters of all nodules were recorded. The attenuation of pure ground-glass nodules (pGGNs) was measured on LDCT. All nodules were further classified using Lung-RADS. Sensitivities of nodule detection on ULDCT were analysed using LDCT as the reference standard. Logistic regression was used to establish a prediction model for the sensitivity of nodules.

RESULTS

LDCT revealed 362 nodules and the overall sensitivity on ULDCT was 90.1%. The sensitivity for solid nodules (SNs) of ≥1 mm diameter was 96.6% (228/236) and 100% (26/26) for SNs of ≥6 mm diameter. For pGGNs of ≥6 mm, the overall sensitivity was 93% (40/43) and 100% (29/29) for nodules with a attenuation value -700 HU or more. The agreement of Lung-RADS classification between two scans was good. On logistic regression, diameter was the only independent predictor for sensitivity of SNs (p<0.05). Diameter and attenuation value were predictors for pGGNs (p<0.05).

CONCLUSION

ULDCT with ASiR-V using SmartmA is suitable for lung-cancer screening in people with a BMI ≤35 kg/m² as it has a low radiation dose of 0.16 mSv, high sensitivity for nodule detection and good performance of Lung-RADS classifications.

3T magnetic resonance for evaluation of adult pulmonary tuberculosis

OBJECTIVES

To evaluate image quality and detection rate of four 3T magnetic resonance imaging (MRI) sequences and MRI performances in pulmonary tuberculosis (TB) when compared to computed tomography (CT).

METHODS

Forty patients with pulmonary tuberculosis separately underwent CT and 3T-MRI with T1-weighted free-breathing star-volumetric interpolated breath-hold examination (Star-VIBE) and standard VIBE, T2-weighted two-dimensional fast BLADE turbo spin-echo (2D-fBLADE TSE) and three-dimensional isotropic turbo spin-echo (3D-SPACE). Four MRI sequences were compared in terms of detection rate and image quality, which consisted of signal to noise ratio (SNR), contrast to noise ratio (CNR) and 5-point scoring scale. The total sensitivity was also compared between CT and MRI. Inter-observer agreement on 5-point scoring scale was calculated by Cohen's kappa (k). SNR, CNR and 5-point scoring scale were compared using two-tailed pared t-test. Using CT as a reference, the MRI detection rate of pulmonary abnormality was evaluated by Pearson's Chi-square test. Furthermore, the sizes of the nodules (≥5 mm) were compared using intraclass correlation coefficient.

RESULTS

In this study, Free-breathing Star-VIBE had significantly better SNR and identical CNR compared with standard VIBE. 2D-fBLADE TSE had statistically higher SNR but uniform or inferior CNR compared with 3D-SPACE. Inter-observers showed excellent agreement on 5-point scoring scale. The average score of Star-VIBE and VIBE had no difference. The average score of 2D-fBLADE TSE was higher than 3D-SPACE. There were no statistical differences in the detection rates of non-calcified parenchymal lesions between Star-VIBE and standard VIBE, 2D-fBALDE TSE and 3D-SPACE. MRI is comparable to CT in detecting consolidation, cavity, non-calcified nodules of ≥5 mm and tree-in-bud signs compared to CT. MRI detected non-calcified nodules of ＜5 mm, 5-10 mm, ≥10 mm and calcified nodules with sensitivity of 69.6%, 90.6%, 100% and 89.5% respectively. In addition, the sizes of the nodules (≥5 mm) had statistical consistency. MRI is more sensitive in detecting caseous necrosis, liquefaction, active cavity, abnormalities of lymph nodes and pleura.

CONCLUSIONS

T1-weighted free-breathing Star-VIBE and T2-weighted 2D-fBLADE TSE, both with satisfactory image quality, are suitable for patients with pulmonary TB who need long-term follow-ups in clinical routine, especially for children, young women and pregnant women.