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Image quality and clinical usefulness of automatic tube current modulation technology in female chest computed tomography screening.

ABSTRACT: The study was aimed to evaluate the image quality and radiation dose during female chest computed tomography (CT) screening using organ-based tube current modulation technology X-ray combined applications to reduce exposure (XCARE).Five hundred sixty female individuals undergoing chest CT scan were prospectively enrolled and divided into 4 groups based on body mass index (BMI). Then they were randomly and equally divided into control and experimental subgroup and respectively accepted conventional low-dose and XCARE technology spiral CT scan with same parameters. Signal-to-noise ratio and contrast-to-noise ratio were calculated. The quality of the images was evaluated by 2 radiologists using a 5-point scale.Among experimental subgroups of the 4 BMI groups, Signal-to-noise ratios, CT dose index of volume, dose-length product, effective dose, and contrast-to-noise ratio all displayed significant differences, as well as in control subgroups (P??.05), while BMI was significantly associated with increased CT dose index of volume (P?

SUBMITTER: Li C

PROVIDER: S-EPMC7437791 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

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Image quality and clinical usefulness of automatic tube current modulation technology in female chest computed tomography screening.

Li Cheng C Qi Lin L Zhang Yusheng Y Gao Feng F Jin Xiu X Zhang Lukai L Tang Huan H Li Ming M

Medicine 20200801 33

The study was aimed to evaluate the image quality and radiation dose during female chest computed tomography (CT) screening using organ-based tube current modulation technology X-ray combined applications to reduce exposure (XCARE).Five hundred sixty female individuals undergoing chest CT scan were prospectively enrolled and divided into 4 groups based on body mass index (BMI). Then they were randomly and equally divided into control and experimental subgroup and respectively accepted convention ...[more]

PMID: 32872052

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Project description:Background: Interstitial lung disease (ILD) is a common complication in patients with systemic sclerosis (SSc), and its diagnosis contributes to early treatment decisions. Purposes: To quantify ILD associated with SSc (SSc-ILD) from chest CT images using an automatic quantification method based on the computation of the weight of interstitial lung opacities. Methods: Ninety-four patients with SSc underwent CT, forced vital capacity (FVC), and carbon monoxide diffusion capacity (DLCO) tests. Seventy-three healthy individuals without radiological evidence of lung disease served as controls. After lung and airway segmentation, the ratio between the weight of interstitial opacities [densities between -500 and +50 Hounsfield units (HU)] and the total lung weight (densities between -1,000 and +50 HU) was used as an ILD indicator (ILD[%] = 100 × [LW(-500 to +50HU)/LW(-1, 000 to +50HU)]). The cutoff of normality between controls and SSc was determined with a receiver operator characteristic curve. The severity of pulmonary involvement in SSc patients was also assessed by calculating Z scores of ILD relative to the average interstitial opacities in controls. Accordingly, SSc-ILD was classified as SSc Limited-ILD (Z score < 3) and SSc Extensive-ILD (Z score ≥ 3 or FVC < 70%). Results: Seventy-eight (83%) SSc patients were classified as presenting SSc-ILD (optimal ILD threshold of 23.4%, 0.83 sensitivity, 0.92 specificity, and 0.94 area under the receiver operator characteristic curve, 95% CI from 0.89 to 0.96, 0.93 positive predictive value, and 0.81 negative predictive value, p < 0.001) and exhibited radiological attenuations compatible with interstitial pneumonia dispersed in the lung parenchyma. Thirty-six (38%) patients were classified as SSc Extensive-ILD (ILD threshold ≥ 29.6% equivalent to a Z score ≥ 3) and 42 (45%) as SSc Limited-ILD. Eighteen (50%) patients with SSc Extensive-ILD presented FVC < 70%, being only five patients classified exclusively based on FVC. SSc Extensive-ILD also presented lower DLCO (57.9 ± 17.9% vs. 73.7 ± 19.8%; p < 0.001) and total lung volume (2,916 ± 674 vs. 4,286 ± 1,136, p < 0.001) compared with SSc Limited-ILD. Conclusion: The proposed method seems to provide an alternative to identify and quantify the extension of ILD in patients with SSc, mitigating the subjectivity of semiquantitative analyzes based on visual scores.

Project description:BackgroundThis study aimed (I) to investigate the clinical implication of computed tomography (CT) cavity volume in tuberculosis (TB) and non-tuberculous mycobacterial pulmonary disease (NTM-PD), and (II) to develop a three-dimensional (3D) nnU-Net model to automatically detect and quantify cavity volume on CT images.MethodsWe retrospectively included conveniently sampled 206 TB and 186 NTM-PD patients in a tertiary referral hospital, who underwent thin-section chest CT scans from 2012 through 2019. TB was microbiologically confirmed, and NTM-PD was diagnosed by 2007 Infectious Diseases Society of America/American Thoracic Society guideline. The reference cavities were semi-automatically segmented on CT images and a 3D nnU-Net model was built with 298 cases (240 cases for training, 20 for tuning, and 38 for internal validation). Receiver operating characteristic curves were used to evaluate the accuracy of the CT cavity volume for two clinically relevant parameters: sputum smear positivity in TB and treatment in NTM-PD. The sensitivity and false-positive rate were calculated to assess the cavity detection of nnU-Net using radiologist-detected cavities as references, and the intraclass correlation coefficient (ICC) between the reference and the U-Net-derived cavity volumes was analyzed.ResultsThe mean CT cavity volumes in TB and NTM-PD patients were 11.3 and 16.4 cm3, respectively, and were significantly greater in smear-positive TB (P<0.001) and NTM-PD necessitating treatment (P=0.020). The CT cavity volume provided areas under the curve of 0.701 [95% confidence interval (CI): 0.620-0.782] for TB sputum positivity and 0.834 (95% CI: 0.773-0.894) for necessity of NTM-PD treatment. The nnU-Net provided per-patient sensitivity of 100% (19/19) and per-lesion sensitivity of 83.7% (41/49) in the validation dataset, with an average of 0.47 false-positive small cavities per patient (median volume, 0.26 cm3). The mean Dice similarity coefficient between the manually segmented cavities and the U-Net-derived cavities was 78.9. The ICCs between the reference and U-Net-derived volumes were 0.991 (95% CI: 0.983-0.995) and 0.933 (95% CI: 0.897-0.957) on a per-patient and per-lesion basis, respectively.ConclusionsCT cavity volume was associated with sputum positivity in TB and necessity of treatment in NTM-PD. The 3D nnU-Net model could automatically detect and quantify mycobacterial cavities on chest CT, helping assess TB infectivity and initiate NTM-TB treatment.

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Image quality and clinical usefulness of automatic tube current modulation technology in female chest computed tomography screening.

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Image quality and clinical usefulness of automatic tube current modulation technology in female chest computed tomography screening.

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