Clinical evaluation of pulmonary quantitative computed tomography parameters for diagnosing eosinophilic chronic obstructive pulmonary disease: Characteristics and diagnostic performance.

Aims: To investigate the characteristics and diagnostic performance of quantitative computed tomography (QCT) parameters in eosinophilic chronic obstructive pulmonary disease (COPD) patients. Methods: High-resolution CT scans of COPD patients were retrospectively analyzed, and various emphysematous parenchyma measurements, including lung volume (LC), lung mean density (LMD), lung standard deviation (LSD), full-width half maximum (FWHM), and lung relative voxel number (LRVN) were performed. The QCT parameters were compared between eosinophilic and noneosinophilic COPD patients, using a definition of eosinophilic COPD as blood eosinophil values ≥ 300 cells·µL-1 on at least three times. Receiver operating characteristic curves and area under the curve (ROC-AUC) and python were used to evaluate discriminative efficacy of QCT. Results: Noneosinophilic COPD patients had a significantly lower TLMD (-846.3 ± 47.9 Hounsfield Unit [HU]) and TFWHM(162.5 ± 30.6 HU) compared to eosinophilic COPD patients (-817.8 ± 54.4, 177.3 ± 33.1 HU, respectively) (p = 0.018, 0.03, respectively). Moreover, the total LC (TLC) and TLSD were significantly lower in eosinophilic COPD group (3234.4 ± 1145.8, 183.8 ± 33.9 HU, respectively) than the noneosinophilic COPD group (5600.2 ± 1248.4, 203.5 ± 20.4 HU, respectively) (p = 0.009, 0.002, respectively). The ROC-AUC values for TLC, TLMD, TLSD, and TFWHM were 0.91 (95% confidence interval [CI], 0.828-0.936), 0.66 (95% CI, 0.546-0.761), 0.64 (95% CI, 0.524-0.742), and 0.63 (95% CI, 0.511-0.731), respectively. When the TLC value was 4110 mL, the sensitivity was 90.7% (95% CI, 79.7-96.9), specificity was 77.8% (95% CI, 57.7-91.4) and accuracy was 86.4%. Notably, TLC demonstrated the highest discriminative efficiency with an F1 Score of 0.79, diagnostic Odds Ratio of 34.3 and Matthews Correlation Coefficient of 0.69, surpassing TLMD (0.55, 3.66, 0.25), TLSD (0.56, 3.95, 0.26), and TFWHM (0.56, 4.16, 0.33). Conclusion: Eosinophilic COPD patients exhibit lower levels of emphysema and a more uniform density distribution throughout the lungs compared to noneosinophilic COPD patients. Furthermore, TLC demonstrated the highest diagnostic efficiency and may serve as a valuable diagnostic marker for distinguishing between the two groups.

To explore the mechanism of tobacco addiction using structural and functional MRI: a preliminary study of the role of the cerebellum-striatum circuit.

Previous studies have found that the striatum and the cerebellum played important roles in nicotine dependence, respectively. In heavy smokers, however, the effect of resting-state functional connectivity of cerebellum-striatum circuits in nicotine dependence remained unknown. This study aimed to explore the role of the circuit between the striatum and the cerebellum in addiction in heavy smokers using structural and functional magnetic resonance imaging. The grey matter volume differences and the resting-state functional connectivity differences in cerebellum-striatum circuits were investigated between 23 heavy smokers and 23 healthy controls. The cigarette dependence in heavy smokers and healthy controls were evaluated by using Fagerström Test. Then, we applied mediation analysis to test whether the resting-state functional connectivity between the striatum and the cerebellum mediates the relationship between the striatum morphometry and the nicotine dependence in heavy smokers. Compared with healthy controls, the heavy smokers' grey matter volumes decreased significantly in the cerebrum (bilateral), and increased significantly in the caudate (bilateral). Seed-based resting-state functional connectivity analysis showed significantly higher resting-state functional connectivity among the bilateral caudate, the left cerebellum, and the right middle temporal gyrus in heavy smokers. The cerebellum-striatum resting-state functional connectivity fully mediated the relationship between the striatum morphometry and the nicotine dependence in heavy smokers. Heavy smokers showed abnormal interactions and functional connectivity between the striatum and the cerebellum, which were associated with the striatum morphometry and nicotine dependence. Such findings could provide new insights into the neural correlates of nicotine dependence in heavy smokers.

Characterizing the Structural Pattern of Heavy Smokers Using Multivoxel Pattern Analysis.

Background: Smoking addiction is a major public health issue which causes a series of chronic diseases and mortalities worldwide. We aimed to explore the most discriminative gray matter regions between heavy smokers and healthy controls with a data-driven multivoxel pattern analysis technique, and to explore the methodological differences between multivoxel pattern analysis and voxel-based morphometry. Methods: Traditional voxel-based morphometry has continuously contributed to finding smoking addiction-related regions on structural magnetic resonance imaging. However, voxel-based morphometry has its inherent limitations. In this study, a multivoxel pattern analysis using a searchlight algorithm and support vector machine was applied on structural magnetic resonance imaging to identify the spatial pattern of gray matter volume in heavy smokers. Results: Our proposed method yielded a voxel-wise accuracy of at least 81% for classifying heavy smokers from healthy controls. The identified regions were primarily located at the temporal cortex and prefrontal cortex, occipital cortex, thalamus (bilateral), insula (left), anterior and median cingulate gyri, and precuneus (left). Conclusions: Our results suggested that several regions, which were seldomly reported in voxel-based morphometry analysis, might be latently correlated with smoking addiction. Such findings might provide insights for understanding the mechanism of chronic smoking and the creation of effective cessation treatment. Multivoxel pattern analysis can be efficient in locating brain discriminative regions which were neglected by voxel-based morphometry.

A histogram analysis of diffusion and perfusion features of cervical cancer based on intravoxel incoherent motion magnetic resonance imaging.

OBJECTIVE: To evaluate the diagnostic potential based on histogram analysis of IVIM parameters between uterine cervical cancers (CC) - normal myometrium (Myo) versus CC - gluteus maximus muscle (GM) and to study the feasibility of histogram analysis of IVIM parameters to differentiate the early from locally advanced stage CCs. METHODS: 64 patients with pathologically confirmed CC were enrolled. Histogram indices mean, median, 25th, and ð 75th percentile of apparent diffusion coefficient (ADC), true diffusion coefficient (D), pseudo-diffusion coefficient (D*), and perfusion fraction (f) value of entire tumor were statistically analyzed and compared between CC - GM versus CC - Myo, as well as between early and locally advanced stage CCs. A multivariate analysis was performed to identify indices that could best distinguish early from locally advanced stage CC. Receiver operating characteristic curves (ROC) were used to evaluate the diagnostic efficiency of every histogram parameter. RESULTS: All the tested histogram indices significantly differed between the patients with CC - GM vs. CC - Myo, nonetheless, CC - GM yielded higher range area under the curve (AUC) value of 0.8-0.99 vs. 0.6-0.99. The additional significant difference was found among all the tested histogram indices of D*, mean, median, and 75th percentile of f, mean and 75th percentile of ADC, and 75th percentile of D discriminating early from locally advanced CCs. ROC curves indicated that the 75th percentile of D* value 28.17 × 10-3 mm2/s could best differentiate early from locally advanced stage CCs, with AUC of 0.776. In the multivariate analysis, ROC indicated the 50th percentile of D* and f was the most significant with AUCs of 0.856. CONCLUSIONS: The histogram analysis of IVIM parameters depicted that gluteus maximus served better reference tissue in comparison to myometrium. The histogram index 75th percentile of ADC, D, D*, and f may serve a diagnostic biomarker to differentiate the early from locally advanced stage CCs.

Diffusion Kurtosis Imaging Combined With DWI at 3-T MRI for Detection and Assessment of Aggressiveness of Prostate Cancer.

OBJECTIVE: The objective of this study was to explore whether diffusion kurtosis imaging (DKI) combined with DWI can improve the performance of DWI in detection and assessment of aggressiveness of prostate cancer (PCa). MATERIALS AND METHODS: One hundred twenty patients with complete DK and MR images and diagnosis confirmed by prostate biopsy, including 67 patients with PCa and 53 patients with benign prostatic hyperplasia (BPH), were retrospectively analyzed. The patients with PCa were divided into a low-grade PCa group (Gleason score [GS] ≤ 3 + 3) and intermediate- and high-grade PCa group (GS ≥ 3 + 4). A DKI-derived parameter (i.e., apparent kurtosis coefficient [Kapp]) and a DWI-derived parameter (i.e., apparent diffusion coefficient [ADC]) were fitted. The intraclass correlation coefficient (ICC) test, t test, ROC curves, Delong test, and Spearman correlation were performed. RESULTS: Ninety ROIs in 67 patients with PCa were drawn, including ROIs in 37 low-grade tumors and ROIs in 53 intermediate- and high-grade tumors. PCa and intermediate- and high-grade PCa had significantly lower ADC values and significantly higher Kapp values than BPH and low-grade PCa (p < 0.01 for all). The AUCs of Kapp were significantly lower than the AUCs of ADC in the diagnosis (0.947 vs 0.978, p < 0.001) and grading (0.689 vs 0.894, p = 0.008) of PCa. The AUCs of the combination of the two metrics were significantly higher than the AUCs of Kapp for the diagnosis (0.979 vs 0.947, p = 0.013) and grading (0.934 vs 0.689, p < 0.001) of PCa and were higher than the AUCs of ADC without significance between groups (both p > 0.05). The combination of the two metrics significantly increased the specificity in grading of PCa compared with Kapp alone (0.838 vs 0.730, p = 0.035). CONCLUSION: Both ADC and Kapp can be used as quantitative parameters in detection and assessment of aggressiveness of PCa. The combination of DKI and DWI showed no significant superiority to DWI alone in detection and assessment of the aggressiveness of PCa.

Asymptomatic Human Immunodeficiency Virus Vertical Transmitted Adolescents' Brain Functional Changes: Based on Resting-State Functional Magnetic Resonance Imaging.

Perinatal HIV-infected (PHIV+) adolescents survive longer with the use of readily found combination antiretroviral therapy (cART); however, they still have the risk of developing cognitive deficits. The article aims to explore the brain functional changes in asymptomatic PHIV+ adolescents with cART based on the resting-state functional magnetic resonance imaging (rs-fMRI). rs-fMRI was performed on 20 PHIV+ adolescents and 28 PHIV- controls to evaluate the regional homogeneity (ReHo) in different brain regions by calculating the Kendall harmonious coefficient. Montreal cognitive assessment and laboratory studies (nadir CD4+ T cell counts) were also performed on all the subjects to evaluate their cognitive and immune status. Thirteen PHIV+ adolescents and 22 PHIV- controls were enrolled. There was a significant difference of ReHo values in PHIV+ adolescents compared to PHIV- controls, the areas with increased ReHo values include bilateral precentral/postcentral gyrus and right middle temporal pole. Also, the areas with decreased ReHo values locate in right putamen/pallidum/insula, left caudate/putamen/insula, right superior temporal pole/insula, right caudate/putamen, bilateral anterior cingulate cortex, and left inferior temporal pole. Furthermore, age, cognitive scores, and laboratory studies (nadir CD4+ T cell counts) did not show any significant correlation with altered ReHo values of brain regions neither in PHIV+ groups nor in PHIV- control groups. Among PHIV+ adolescents, brain areas with increased ReHo values were mainly located in the central somatic motor-sensory cortex, which might be related to the compensatory mechanism, whereas brain areas with decreased ReHo values were mainly focused on corticostriatal pathway, which might be associated with abnormal dopamine consumption. Thus, rs-fMRI could demonstrate the brain functional changes in resting state of asymptomatic PHIV+ adolescents.

Structural Covariance of Gray Matter Volume in HIV Vertically Infected Adolescents.

Human immunodeficiency virus (HIV) infection significantly affect neurodevelopmental and behavioral outcomes. We investigated whether alterations of gray matter organization and structural covariance networks with vertical HIV infection adolescents exist, by using the GAT toolbox. MRI data were analysed from 25 HIV vertically infected adolescents and 33 HIV-exposed-uninfected control participants. The gray matter volume (GMV) was calculated, and structural brain networks were reconstructed from gray matter co-variance. Gray matter losses were pronounced in anterior cingulate cortex (ACC), right pallidum, right occipital lobe, inferior parietal lobe, and bilateral cerebellum crus. The global brain network measures were not significantly different between the groups; however, the nodal alterations were most pronounced in frontal, temporal, basal ganglia, cerebellum, and temporal lobes. Brain hubs in the HIV-infected subjects increased in number and tended to shift to sensorimotor and temporal areas. In the HIV-infected subjects, decreased GMVs in ACC and bilateral cerebellum were related to lower Mini-Mental State Examination scores; the CD4 counts were positively related to the GMVs in ACC and sensorimotor areas. These findings suggest that focally reduced gray matter, disrupted nodal profiles of structural wirings, and a shift in hub distribution may represent neuroanatomical biomarkers of HIV infection on the developing brain.

A study on diffusion and kurtosis features of cervical cancer based on non-Gaussian diffusion weighted model.

OBJECTIVE: To explore the diffusion and kurtosis features of cervical cancer (CC) and study the feasibility of diffusion kurtosis imaging (DKI) based on the non-Gaussian diffusion-weighted model to differentiate the stage and grade of CC. METHODS: A total of 50 patients with pathologically confirmed CC were enrolled. MRI examinations including DKI (with 5b values 200, 500, 1000, 1500, and 2000smm-2 were performed before any treatment. The apparent coefficient (Dapp) and the apparent kurtosis value (Kapp) were derived from the non-gaussian diffusion model, and the apparent diffusion coefficient (ADC) was derived from the Gaussian model. The parameters of CC and normal tissue (myometrium) were obtained, analyzed statistically, and evaluated with respect to differentiating stage and grade between the tissue and the CC. RESULTS: ADC and Dapp values of CC were significantly lower than that of the normal myometrium (P=0.024 and P<0.001, respectively), while the Kapp value was not found to exhibit a significant difference. Compared to the well/moderately differentiated CC, poorly differentiated CC had a significantly decreased mean ADC and Dapp (P=0.018 and P=0.026, respectively); however, the mean Kapp (P=0.035) increased significantly. In the clinical staging, the DKI sequence was advantageous over conventional MRI sequences (degree of accuracy: 90% vs. 74%), Although in the quantitative analysis, these parameters did not show a significant difference. CONCLUSIONS: The pilot study demonstrated that these diffusion and kurtosis indices from DKI based on the non-Gaussian diffusion-weighted model putatively differentiated the grade and stage of CC.