Journal of Thoracic Imaging最新文献

Purpose: This study investigated the prognostic value and risk reclassification ability of coronary atherosclerosis progression through serial coronary computed tomography angiography (CCTA).

Materials and methods: This study enrolled patients with suspected or confirmed coronary artery disease who underwent serial CCTA. Coronary atherosclerosis progression was represented by coronary artery calcium score (CACS) and segment stenosis score (SSS) progression. The baseline and follow-up CCTA characteristics and coronary atherosclerosis progression were compared. Furthermore, the incremental prognostic value and reclassification ability of three models (model 1, baseline risk factors; model 2, model 1 + SSS; and model 3, model 2 + SSS progression) for major adverse cardiovascular events (MACEs) were compared.

Results: In total, 516 patients (aged 56.40 ± 9.56 y, 67.4% men) were enrolled. During a mean follow-up of 65.29 months, 114 MACE occurred. The MACE group exhibited higher CACS and SSS than the non-MACE group at baseline and follow-up CCTA ( P < 0.001), and demonstrated higher coronary atherosclerosis progression than the non-MACE group (ΔSSS: 2.63 ± 2.50 vs 1.06 ± 1.78, P < 0.001; ΔCACS: 115.15 ± 186.66 vs 89.91 ± 173.08, P = 0.019). SSS progression provided additional prognostic information (C-index = 0.757 vs 0.715, P < 0.001; integrated discrimination index = 0.066, P < 0.001) and improved the reclassification ability of risk (categorical-net reclassification index = 0.149, P = 0.015) compared with model 2.

Conclusions: Coronary atherosclerosis progression through CCTA significantly increased the prognostic value and risk stratification for MACE compared with baseline risk factor evaluation and CCTA only.

Purpose: To investigate the imaging performance and parametric analysis of magnetic resonance imaging (MRI) immediately after microwave ablation (MWA) of lung malignancies.

Materials and methods: We retrospectively analyzed the MRI performance immediately after MWA of 34 cases of lung malignancies. The ablation zone parameters of lung malignancies were measured, including the long diameter (L), short diameter (S), and safety margin of the ablation zone on plain computed tomography (CT), T1-weighted imaging (T1WI), and T2-weighted imaging (T2WI) after MWA. The study calculated the tumor volume (V 0 ), the ablation zone volume (V 1 ), and the ratio of V 0 to V 1 (V%). Statistical differences between the parameters were analyzed.

Results: The ablation area of the lesion exhibited central low signal and peripheral high signal on T2WI, central high signal and peripheral equal or high signal on T1WI, and circumferential enhancement in the periphery. The safety margin measured on T2WI was greater than that measured on plain CT and T1WI. On plain CT, the L, S, and V 1 were smaller in the effective treatment group than in the ineffective treatment group ( P <0.05). On T1WI, the V% and safety margin were greater in the effective treatment group than in the ineffective treatment group ( P =0.009 and P =0.016, respectively).

Conclusions: MRI may be a new, valuable method to assess immediate efficacy after MWA for lung malignancies using the ablation zone parameters V% on T1WI and safety margin on T2WI.

We present a non-smoker woman in her 40s with PLCH who presented with atypical imaging findings of multiple pulmonary noncavitary nodules without air cysts with repeated waxing and waning.

Purpose: Delays to biopsy and surgery after lung nodule detection can impact survival from lung cancer. The aim of this study was to identify factors associated with delay in a lung cancer screening (LCS) program.

Materials and methods: We evaluated patients in an LCS program from May 2015 through October 2021 with a malignant lung nodule classified as lung CT screening reporting and data system (Lung-RADS) 4B/4X. A cutoff of more than 30 days between screening computed tomography (CT) and first tissue sampling and a cutoff of more than 60 days between screening CT and surgery were considered delayed. We evaluated the relationship between delays to first tissue sampling and surgery and patient sex, age, race, smoking status, median income by zip code, language, Lung-RADS category, and site of surgery (academic vs community hospital).

Results: A total of 185 lung cancers met the inclusion criteria, of which 150 underwent surgical resection. The median time from LCS CT to first tissue sampling was 42 days, and the median time from CT to surgery was 52 days. 127 (69%) patients experienced a first tissue sampling delay and 60 (40%) had a surgical delay. In multivariable analysis, active smoking status was associated with delay to first tissue sampling (odds ratio: 3.0, CI: 1.4-6.6, P = 0.005). Only performing enhanced diagnostic CT of the chest before surgery was associated with delayed lung cancer surgery (odds ratio: 30, CI: 3.6-252, P = 0.02). There was no statistically significant difference in delays with patients' sex, age, race, language, or Lung-RADS category.

Conclusion: Delays to first tissue sampling and surgery in a LCS program were associated with current smoking and performing diagnostic CT before surgery.

Purpose: To explore and compare the diagnostic values of mono-exponential, bi-exponential, and stretched-exponential diffusion-weighted imaging (DWI) parameters of primary lesions and lymph nodes (LNs) to predict mediastinal LN metastasis in patients with non-small cell lung cancer.

Patients and methods: Sixty-one patients with non-small cell lung cancer underwent preoperative magnetic resonance imaging, including multiple b -value DWI. The DWI parameters, including apparent diffusion coefficient (ADC) from a mono-exponential model, true diffusion (D) coefficient, pseudo-diffusion (D*) coefficient, and perfusion fraction (f) from a bi-exponential model, distributed diffusion coefficient (DDC) and intravoxel diffusion heterogeneity index (α) from a stretched-exponential model of primary tumors and LNs and the size characteristics of LNs, were measured and compared. Multivariate logistic regression analysis was used to establish models for predicting mediastinal LN metastasis. Receiver operating characteristic analysis was applied to evaluate diagnostic performances.

Results: The DWI parameters of primary tumors showed no statistical significance between LN metastasis-positive and LN metastasis-negative groups. Nonmetastatic LNs had significantly higher ADC, D, DDC, and α values compared with metastatic LNs (all P < 0.05). The short-dimension, long-dimension, and short-long dimension ratio of metastatic LNs was significantly larger than those of nonmetastatic ones (all P < 0.05). The D value showed the best diagnostic performance among all DWI-derived single parameters, and the short dimension of LNs performed the same among all the size variables. Furthermore, the combination of DWI parameters (ADC and D) and the short dimension of LNs can significantly improve diagnostic efficiency.

Conclusions: The ADC, D, DDC, and α from the mono-exponential, bi-exponential, and stretched-exponential models were demonstrated efficient in differentiating benign from metastatic LNs, and the combination of ADC, D, and short dimension of LNs may have a better diagnostic performance than DWI or size-derived parameters either in combination or individually.

Purpose: Inflammatory changes in epicardial (EAT) and pericardial adipose tissue (PAT) are associated with increased overall cardiovascular risk. Using routine, preinterventional cardiac CT data, we examined the predictive value of quantity and quality of EAT and PAT for outcome after transcatheter aortic valve replacement (TAVR).

Materials and methods: Cardiac CT data of 1197 patients who underwent TAVR at the in-house heart center between 2011 and 2020 were retrospectively analyzed. The amount and density of EAT and PAT were quantified from single-slice CT images at the level of the aortic valve. Using established risk scores and known independent risk factors, a clinical benchmark model (BMI, Chronic kidney disease stage, EuroSCORE 2, STS Prom, year of intervention) for outcome prediction (2-year mortality) after TAVR was established. Subsequently, we tested whether the additional inclusion of area and density values of EAT and PAT in the clinical benchmark model improved prediction. For this purpose, the cohort was divided into a training (n=798) and a test cohort (n=399).

Results: Within the 2-year follow-up, 264 patients died. In the training cohort, particularly the addition of EAT density to the clinical benchmark model showed a significant association with outcome (hazard ratio 1.04, 95% CI: 1.01-1.07; P =0.013). In the test cohort, the outcome prediction of the clinical benchmark model was also significantly improved with the inclusion of EAT density (c-statistic: 0.589 vs. 0.628; P =0.026).

Conclusions: EAT density as a surrogate marker of EAT inflammation was associated with 2-year mortality after TAVR and may improve outcome prediction independent of established risk parameters.