Journal of Thoracic Imaging最新文献

Purpose: To assess the performance of a newly introduced deep learning-based reconstruction algorithm, namely the artificial intelligence iterative reconstruction (AIIR), in reducing the dose of pediatric chest CT by using the image data of below 3-year-old patients with congenital heart disease (CHD).

Materials and methods: The lung image available from routine-dose cardiac CT angiography (CTA) on below 3 years patients with CHD was employed as a reference for evaluating the paired low-dose chest CT. A total of 191 subjects were prospectively enrolled, where the dose for chest CT was reduced to ~0.1 mSv while the cardiac CTA protocol was kept unchanged. The low-dose chest CT images, obtained with the AIIR and the hybrid iterative reconstruction (HIR), were compared in image quality, ie, overall image quality and lung structure depiction, and in diagnostic performance, ie, severity assessment of pneumonia and airway stenosis.

Results: Compared with the reference, lung image quality was not found significantly different on low-dose AIIR images (all P>0.05) but obviously inferior with the HIR (all P<0.05). Compared with the HIR, low-dose AIIR images also achieved a closer pneumonia severity index (AIIR 4.32±3.82 vs. Ref 4.37±3.84, P>0.05; HIR 5.12±4.06 vs. Ref 4.37±3.84, P<0.05) and airway stenosis grading (consistently graded: AIIR 88.5% vs. HIR 56.5% ) to the reference.

Conclusions: AIIR has the potential for large dose reduction in chest CT of patients below 3 years of age while preserving image quality and achieving diagnostic results nearly equivalent to routine dose scans.

Purpose: To investigate the left ventricular (LV) trabecular complexity and evaluate its relationship with LV cardiac function and especially myocardial strain in patients with hypertrophic cardiomyopathy (HCM).

Materials and methods: A total of 100 patients were retrospectively recruited in the study, including 50 obstructive hypertrophic cardiomyopathy (HOCM) and 50 nonobstructive HCM (NOHCM). Fifty age-matched and sex-matched healthy participants were also enrolled. The global and regional LV fractal dimensions (FDs), the global radial, circumferential, and longitudinal strain (GRS, GCS, and GLS) for LV were measured. FDs and myocardial strain parameters among 3 groups with post hoc paired comparisons. Correlations analysis and receiver operating characteristic analysis were performed.

Results: Mean global FD, max basal FD, and max apical FD were higher in patients with HCM compared with the healthy individuals (1.310 ± 0.046 vs 1.229 ± 0.027, 1.388 ± 0.089 vs 1.313 ± 0.039, 1.393 ± 0.108 vs 1.270 ± 0.041, all P < 0.001). Patients with HOCM showed significantly higher max apical FD than patients with NOHCM (1.432 ± 0.100 vs 1.355 ± 0.102, P < 0.001). The increased global FD was associated with reduced myocardial deformation across all 3 measures of global strain (GCS: r = 0.529, P < 0.001; GLS: r = 0.54, P < 0.001; GRS: r = -0.253, P = 0.002). Max apical FD yielded an area under the curve of 0.73 (95% CI: 0.63-0.83) for discriminating HOCM from NOHCM.

Conclusions: LV trabecular complexity is compensatively increased in patients with HCM and the max apical FD was more pronounced in patients with HOCM. The increased LV global trabecular complexity might be correlated with LV systolic dysfunction.

Purpose: To assess the accuracy of transaortic valve replacement (TAVR) planning CT examinations with a broad detector and a single dose of contrast media to diagnose CAD in a large patient cohort.

Materials and methods: In this retrospective study, consecutive patients who underwent a dedicated TAVR planning CT examination with a single contrast media dose and a 320-detector row between November 2017 and March 2021 were screened for inclusion. Inclusion criteria were a complete and correctly performed CT exam as well as an invasive coronary angiography (ICA). The scan consisted of 3 series: (1) ECG-triggered calcium score series over the heart. (2) ECG triggered i.v. CM scanning over the heart covering the entire cardiac cycle (0% to 100%). (3) non-ECG triggered scanning over the thoracic-abdominal area including subclavian and femoral arteries. For 2 and 3, a single i.v. CM bolus was used (300 mg iodine per kg total body weight of iodixanol, minimum 47 mL, maximum 75 mL at 100 kVp; 90 mL at 120 kVp). CT-derived CAD was defined as either free of obstructive CAD (<50%) or showing obstructive disease (>50%), further subclassified in moderate stenosis (50%-70%), or severe stenosis (>70%) for each vessel. ICA data were used as standard of reference.

Results: We studied 599 patients (78.6±7.5 y, 358 men). In ICA, 428 of 2396 coronary vessels (17.8%) demonstrated stenosis of 50% or more. In a per-patient analysis, CTA had a sensitivity of 97.6% and specificity of 84.3% for the detection of patients with at least one vessel with stenosis of 50% or more as well as a NPV and PPV of 97.8% and 82.2%, respectively. In a per-vessel analysis, CTA had 80.8% sensitivity and 88.1% specificity for the detection of stenosis of 50% or more, as well as an NPV and PPV of 95.5% and 59.6%, respectively.

Conclusions: Single-dose TAVR planning CT imaging with a wide detector has high sensitivity and NPV to exclude at least moderate CAD in TAVR candidates.

Purpose: Computed tomography (CT) is crucial in oncologic imaging for precise diagnosis and staging. Beam-hardening artifacts from contrast media in the superior vena cava can degrade image quality and obscure adjacent structures, complicating lymph node assessment. This study examines the use of virtual monoenergetic reconstruction with photon-counting detector CT (photon-counting CT) to mitigate these artifacts.

Materials and methods: The retrospective study included 50 patients who underwent thoracoabdominal scans. Virtual monoenergetic reconstructions at nine keV levels (60 to 140 keV) were analyzed for Hounsfield Unit (HU) stability, image noise, and artifact index in various regions of interest (ROIs): mediastinal adipose tissue (ROI 1 to 3) and vascular stations (ROI 4 to 6) were compared with reference tissue (ROI 7 to 8). The diagnostic image quality of the keV levels was assessed using a 5-point Likert Scale.

Results: Lower keV values (60 to 80) exhibited higher image noise and lower HU stability in mediastinal adipose tissue compared with higher energies, with optimal noise reduction observed at 130 keV (ROI 1 to 3). HU stability in vascular structures (ROI 4 to 6) significantly improved above 80 keV, with the best performance at 140 keV. Artifact levels decreased progressively from 60 to 140 keV. Visually, keV levels of 110 keV (96% Likert ≥4) and 120 keV (60% Likert 4) were rated most diagnostically valuable, consistent with technical findings.

Conclusion: Virtual monoenergetic reconstructions with photon-counting CT effectively reduce beam-hardening artifacts near the superior vena cava, enhancing the visualization of lymph nodes and adjacent structures. This technology advances oncologic imaging by improving diagnostic accuracy in areas previously affected by artifact-related image degradation.

The term "aspiration" describes lung injury that results from unintentional passage of contents other than air into the lungs and bronchial tree, commonly from the gastrointestinal and upper respiratory tracts. Only a small proportion of aspiration-related events are symptomatic, especially in predisposed individuals such as patients with diminished consciousness, impaired swallowing, oesophageal motility disorders, and reflux disease. Aspiration-related syndromes can be classified based on the onset of presentation, composition of the aspirated substance, and anatomic site of injury. When considering the injury site, the aspirated material can either obstruct the airways, thereby presenting with obstructive features (eg, atelectasis on radiographs); it can alternatively affect the lung parenchyma. Lung injury due to aspiration of noxious agents such as acid or lipids is termed chemical aspiration pneumonitis. The aspirated contents can alternatively lead to lung parenchymal infection when the contents are infected, which is termed aspiration pneumonia. We have reviewed the imaging manifestations of various entities related to aspiration and have classified the abnormalities based on the site of injury and the nature of the culprit agent. Differences between "aspiration pneumonitis" and "aspiration pneumonia" are also explored. This is followed by an illustration of a few specific situations related to aspiration in pediatric and adult patients.

Purpose: This study aims to determine whether longitudinal changes in CT radiomic features (RFs) and systemic inflammatory indices outperform single-time-point assessment in predicting survival in advanced non-small cell lung cancer (NSCLC) treated with immune checkpoint inhibitors (ICIs).

Materials and methods: We retrospectively acquired pretreatment (T0) and first disease assessment (T1) RFs and systemic inflammatory indices from a single-center cohort of stage IV NSCLC patients and computed their delta (Δ) variation as [(T1-T0)/T0]. RFs from the primary tumor were selected for building baseline-radiomic (RAD) and Δ-RAD scores using the linear combination of standardized predictors detected by LASSO Cox regression models. Cox models were generated using clinical features alone or combined with baseline and Δ blood parameters and integrated with baseline-RAD and Δ-RAD. All models were 3-fold cross-validated. A prognostic index (PI) of each model was tested to stratify overall survival (OS) through Kaplan-Meier analysis.

Results: We included 90 ICI-treated NSCLC patients (median age 70 y [IQR=42 to 85], 63 males). Δ-RAD outperformed baseline-RAD for predicting OS [c-index: 0.632 (95%CI: 0.628 to 0.636) vs. 0.605 (95%CI: 0.601 to 0.608) in the test splits]. Integrating longitudinal changes of systemic inflammatory indices and Δ-RAD with clinical data led to the best model performance [Integrated-Δ model, c-index: 0.750 (95% CI: 0.749 to 0.751) in training and 0.718 (95% CI: 0.715 to 0.721) in testing splits]. PI enabled significant OS stratification within all the models ( P -value <0.01), reaching the greatest discriminative ability in Δ models (high-risk group HR up to 7.37, 95% CI: 3.9 to 13.94, P <0.01).

Conclusion: Δ-RAD improved OS prediction compared with single-time-point radiomic in advanced ICI-treated NSCLC. Integrating Δ-RAD with a longitudinal assessment of clinical and laboratory data further improved the prognostic performance.

Purpose: Effective identification of malignant part-solid lung nodules is crucial to eliminate risks due to therapeutic intervention or lack thereof. We aimed to develop delta radiomics and volumetric signatures, characterize changes in nodule properties over three presurgical time points, and assess the accuracy of nodule invasiveness identification when combined with immediate presurgical time point radiomics signature and clinical biomarkers.

Materials and methods: Cohort included 156 part-solid lung nodules with immediate presurgical CT scans and a subset of 122 nodules with scans at 3 presurgical time points. Region of interest segmentation was performed using ITK-SNAP, and feature extraction using CaPTk. Image parameter heterogeneity was mitigated at each time point using nested ComBat harmonization. For 122 nodules, delta radiomics features (ΔR AB = (R B -R A )/R A ) and delta volumes (ΔV AB = (V B -V A )/V A ) were computed between the time points. Principal Component Analysis was performed to construct immediate presurgical radiomics (Rs 1 ) and delta radiomics signatures (ΔRs 31 + ΔRs 21 + ΔRs 32 ). Identification of nodule pathology was performed using logistic regression on delta radiomics and immediate presurgical time point signatures, delta volumes (ΔV 31 + ΔV 21 + ΔV 32 ), and clinical variable (smoking status, BMI) models (train test split (2:1)).

Results: In delta radiomics analysis (n= 122 nodules), the best-performing model combined immediate pre-surgical time point and delta radiomics signatures, delta volumes, and clinical factors (classification accuracy [AUC]): (77.5% [0.73]) (train); (71.6% [0.69]) (test).

Conclusions: Delta radiomics and volumes can detect changes in nodule properties over time, which are predictive of nodule invasiveness. These tools could improve conventional radiologic assessment, allow for earlier intervention for aggressive nodules, and decrease unnecessary intervention-related morbidity.

Acute lung injury (ALI) is acute pulmonary inflammation with underlying pathology of disruption of the pulmonary vasculature endothelial and alveolar epithelial barriers. ALI is not an uncommon diagnosis and has a myriad of causes including pulmonary infection, (including sepsis), drugs, connective tissue disease, and polytrauma. Patients present clinically with hypoxemia with imaging supportive of bilateral pulmonary findings without pulmonary edema. The imaging findings in ALI mirror pathologic changes, with a transition from an early ("exudative") phase to a later fibroblast-rich ("organizing" or "proliferative") phase to, in some cases, a fibrotic phase. The diagnosis of ALI is separate from, but can clinically overlap in presentation with, acute respiratory distress syndrome and is characterized by diffuse alveolar damage and organizing pneumonia patterns on pathology. Clinical management is most often supportive and can include corticosteroids, mechanical ventilation, and careful fluid management, with the goal of preserving and recovering lung function.

Purpose: The study aimed to investigate the potential utility of left atrial (LA) strain by using cardiac magnetic resonance feature-tracking (CMR-FT) to predict left ventricular reverse remodeling (LVRR) following ST-segment elevation myocardial infarction (STEMI).

Materials and methods: Patients with a first STEMI treated by primary percutaneous coronary intervention were consecutively enrolled in the prospective study and underwent CMR scans at 5 days and 4 months. LA global longitudinal strain (reservoir strain [εs], conduit strain [εe], booster strain [εa]) and corresponding strain rate were assessed by CMR-FT using cine images. LVRR was defined as a reduction in the LV end-systolic volume index of >10% from baseline to follow-up. Logistic regression analyses were performed to determine the predictors of LVRR.

Results: Of 90 patients analyzed, patients with LVRR (n=35, 39%) showed higher values of LA strain and strain rate and less extensive infarct size (IS) compared with patients without LVRR (n=55, 61%) at initial and second CMR. The LVRR group demonstrated significant improvements in LV and LA cardiac function over time, especially the obvious increase in LA strain and strain rate. In multivariate logistic regression analyses, εs and εe, together with IS, were independent predictors of LVRR. The combination of εs and IS could optimally predict the LVRR with the highest area under the curve of 0.743.

Conclusions: Post-STEMI patients with LVRR presented better recovery from cardiac function and LA deformation compared with patients without LVRR. Assessment of εs and εe by using CMR-FT after STEMI enabled prediction of LVRR.