To conduct a volumetric and movement analysis of lung parenchyma in prone positioning using deep neural networks (DNNs).
We included patients with suspected interstitial lung abnormalities or disease ...who underwent full-inspiratory supine and prone chest CT at a single institution between June 2021 and March 2022. A thoracic radiologist visually assessed the fibrosis extent in the total lung (using units of 10%) on supine CT. After preprocessing the images into 192×192×192 resolution, a DNN automatically segmented the whole lung and pulmonary lobes in prone and supine CT images. Affine registration matched the patient's center and location, and the DNN deformably registered prone and supine CT images to calculate the x-, y-, z-axis, and 3D pixel movements.
In total, 108 CT pairs had successful registration. Prone positioning significantly increased the left lower (90.2±69.5 mL, P = 0.000) and right lower lobar volumes (52.5±74.2 mL, P = 0.000). During deformable registration, the average maximum whole-lung pixel movements between the two positions were 1.5, 1.9, 1.6, and 2.8 cm in each axis and 3D plane. Compared to patients with <30% fibrosis, those with ≥30% fibrosis had smaller volume changes (P<0.001) and smaller pixel movements in all axes between the positions (P = 0.000-0.007). Forced vital capacity (FVC) correlated with the left lower lobar volume increase (Spearman correlation coefficient, 0.238) and the maximum whole-lung pixel movements in all axes (coefficients, 0.311 to 0.357).
Prone positioning led to the preferential expansion of the lower lobes, correlated with FVC, and lung fibrosis limited lung expansion during prone positioning.
This study presents a preliminary report on the chest radiographic and computed tomography (CT) findings of the 2019 novel coronavirus disease (COVID-19) pneumonia in Korea.
As part of a ...multi-institutional collaboration coordinated by the Korean Society of Thoracic Radiology, we collected nine patients with COVID-19 infections who had undergone chest radiography and CT scans. We analyzed the radiographic and CT findings of COVID-19 pneumonia at baseline. Fisher's exact test was used to compare CT findings depending on the shape of pulmonary lesions.
Three of the nine patients (33.3%) had parenchymal abnormalities detected by chest radiography, and most of the abnormalities were peripheral consolidations. Chest CT images showed bilateral involvement in eight of the nine patients, and a unilobar reversed halo sign in the other patient. In total, 77 pulmonary lesions were found, including patchy lesions (39%), large confluent lesions (13%), and small nodular lesions (48%). The peripheral and posterior lung fields were involved in 78% and 67% of the lesions, respectively. The lesions were typically ill-defined and were composed of mixed ground-glass opacities and consolidation or pure ground-glass opacities. Patchy to confluent lesions were primarily distributed in the lower lobes (
= 0.040) and along the pleura (
< 0.001), whereas nodular lesions were primarily distributed along the bronchovascular bundles (
= 0.006).
COVID-19 pneumonia in Korea primarily manifested as pure to mixed ground-glass opacities with a patchy to confluent or nodular shape in the bilateral peripheral posterior lungs. A considerable proportion of patients with COVID-19 pneumonia had normal chest radiographs.
Objectives
To determine the incidence, risk factors, and prognostic indicators of symptomatic air embolism after percutaneous transthoracic lung biopsy (PTLB) by conducting a systematic review and ...pooled analysis.
Methods
We searched the EMBASE and OVID-MEDLINE databases to identify studies that dealt with air embolism after PTLB and had extractable outcomes. The incidence of air embolism was pooled using a random effects model, and the causes of heterogeneity were investigated. To analyze risk factors for symptomatic embolism and unfavorable outcomes, multivariate logistic regression analysis was performed.
Results
The pooled incidence of symptomatic air embolism after PTLB was 0.08% (95% confidence interval CI, 0.048–0.128%;
I
2
= 45%). In the subgroup analysis and meta-regression, guidance modality and study size were found to explain the heterogeneity. Of the patients with symptomatic air embolism, 32.7% had unfavorable outcomes. The presence of an underlying disease (odds ratio OR, 5.939; 95% CI, 1.029–34.279;
p
= 0.046), the use of a ≥ 19-gauge needle (OR, 10.046; 95% CI, 1.103–91.469;
p
= 0.041), and coronary or intracranial air embolism (OR, 19.871; 95% CI, 2.725–14.925;
p
= 0.003) were independent risk factors for symptomatic embolism. Unfavorable outcomes were independently associated with the use of aspiration biopsy rather than core biopsy (OR, 3.302; 95% CI, 1.149–9.492;
p
= 0.027) and location of the air embolism in the coronary arteries or intracranial spaces (OR = 5.173; 95% CI = 1.309–20.447;
p
= 0.019).
Conclusion
The pooled incidence of symptomatic air embolism after PTLB was 0.08%, and one-third of cases had sequelae or died. Identifying whether coronary or intracranial emboli exist is crucial in suspected cases of air embolism after PTLB.
Key Points
•
The pooled incidence of symptomatic air embolism after percutaneous transthoracic lung biopsy was 0.08%, and one-third of patients with symptomatic air embolism had sequelae or died.
•
The risk factors for symptomatic air embolism were the presence of an underlying disease, the use of a ≥ 19-gauge needle, and coronary or intracranial air embolism.
•
Sequelae and death in patients with symptomatic air embolism were associated with the use of aspiration biopsy and coronary or intracranial locations of the air embolism.
Objectives
A recent meta-analysis of individual patient data revealed that preoperative percutaneous transthoracic needle lung biopsy (PTNB) was associated with an increased risk of ipsilateral ...pleural recurrence in stage I lung cancer. This study aimed to examine whether particular PTNB techniques reduced the risk of pleural recurrence.
Methods
We retrospectively included 415 consecutive patients with stage I lung cancer who underwent preoperative PTNB and curative resection from 2009 through 2016. Detailed information was collected, including clinical, PTNB technique, radiologic, and pathologic characteristics of lung cancer. Cox regression analyses were performed to identify risk factors for pleural recurrence before and after propensity score matching.
Results
The overall follow-up period after PTNB was 62.1 ± 23.0 months, and ipsilateral pleural recurrence occurred in 40 patients. Before propensity score matching, age (
p
= 0.063), microscopic pleural invasion (
p
= 0.065), and pathologic tumor size (
p
= 0.016) tended to be associated with pleural recurrence in univariate analyses and subsequently were matched using a propensity score. After propensity score matching, multivariate analysis revealed that ipsilateral pleural recurrence was associated with a larger target size on computed tomography (hazard ratio HR = 1.498; 95% CI, 1.506–2.125;
p
= 0.023) and microscopic lymphatic invasion (HR = 3.526; 95% CI, 1.491–8.341;
p
= 0.004). However, no PTNB techniques such as needle gauge, biopsy, or pleural passage numbers were associated with a reduced risk of recurrence.
Conclusions
No particular PTNB techniques were associated with reduced pleural seeding after PTNB in stage I lung cancer. Regardless of the technique, PTNB needs to be cautiously applied when early lung cancer is suspected, followed by curative treatment.
Key Points
•
Age, microscopic pleural invasion, and pathologic tumor size tended to be associated with pleural recurrence in stage I lung cancer before propensity matching.
•
After propensity matching, pre-biopsy CT target size and microscopic lymphatic invasion were associated with pleural recurrence.
•
No particular PTNB techniques were associated with reduced pleural seeding in stage I lung cancer before and after propensity matching.
Objectives
To evaluate the clinico-radiological findings of acute fibrinous and organizing pneumonia (AFOP) in the literature according to whether a surgical or non-surgical biopsy was performed, as ...well as to identify prognostic predictors.
Methods
We searched the Embase and OVID-MEDLINE databases to identify studies that presented CT findings of AFOP and had extractable individual patient data. We compared the clinical and CT findings of the patients depending on whether a surgical or non-surgical biopsy was performed and identified survival predictors using a multivariate logistic regression analysis.
Results
Eighty-one patients (surgical biopsy,
n
= 52; non-surgical biopsy,
n
= 29) from 63 studies were included. The surgical biopsy group frequently experienced an acute fulminant presentation (
p
= .011) and dyspnea (
p
= .001) and less frequently had a fever (
p
= .006) than the non-surgical biopsy group. The surgical biopsy group had a worse prognosis than the non-surgical biopsy group in terms of mechanical ventilation and mortality (both,
p
= .023). For survival analysis, the patients with the predominant CT finding of patchy or mass-like air-space consolidation survived more frequently (
p
< .001) than those with other CT findings. For prognostic predictors, subacute indolent presentation (
p
= .001) and patchy or mass-like air-space consolidation on CT images (
p
= .002) were independently associated with good survival.
Conclusions
Approximately one-third of alleged AFOP cases in the literature were diagnosed via non-surgical biopsy, but those cases had different symptomatic presentations and prognosis from surgically proven AFOP. Subacute indolent presentation and patchy or mass-like air-space consolidation at the presentation on CT images indicated a good prognosis in patients with AFOP.
Key Points
• Acute fibrinous and organizing pneumonia (AFOP) cases diagnosed via non-surgical biopsy had different symptomatic presentations and prognosis from surgically proven AFOP.
• Subacute indolent presentation and patchy or mass-like air-space consolidation on CT images indicated a good prognosis in patients with acute fibrinous and organizing pneumonia.
The influence of body fat on arterial stiffness remains controversial. This study was performed to investigate the associations between four different types of body fat parameters and brachial-ankle ...pulse wave velocity (baPWV). A total of 3758 subjects (mean age, 53.4 ± 8.8 years; females, 36.3%) who underwent health check-up were retrospectively analyzed. Anthropometric parameters including body mass index (BMI), waist circumference (WC) and waist-hip ratio (WHR) were assessed, and visceral fat area (VFA) was calculated by bioelectrical impedance analysis. In simple linear correlation analyses, baPWV was associated with WC, WHR and VFA (P < 0.001 for each), but not with BMI (P = 0.175). In multivariable analyses, BMI and WC were not associated with baPWV (P > 0.05 for each). Even after controlling for potential confounders, higher baPWV was significantly associated not only with higher WHR for > 0.90 in men and > 0.85 in women: odds ratio (OR), 1.23; 95% confidence interval (CI), 1.06-1.42; P = 0.005; for the highest tertile compared to the lowest tertile: OR, 1.38; 95% CI, 1.15-1.66; P < 0.001, but also with higher VFA (for ≥ 100 cm
: OR, 1.39; 95% CI, 1.20-1.60; P < 0.001; for the highest tertile compared to the lowest tertile: OR, 1.77; 95% CI, 1.48-2.12; P < 0.001). Our study showed that baPWV was correlated with WHR and VFA, but not with BMI and WC. This implies that arterial stiffness may be more strongly associated with abdominal obesity than overall obesity.
Objectives
To develop a deep learning–based pulmonary vessel segmentation algorithm (DLVS) from noncontrast chest CT and to investigate its clinical implications in assessing vascular remodeling of ...chronic obstructive lung disease (COPD) patients.
Methods
For development, 104 pulmonary CT angiography scans (49,054 slices) using a dual-source CT were collected, and spatiotemporally matched virtual noncontrast and 50-keV images were generated. Vessel maps were extracted from the 50-keV images. The 3-dimensional U-Net-based DLVS was trained to segment pulmonary vessels (with a vessel map as the output) from virtual noncontrast images (as the input). For external validation, vendor-independent noncontrast CT images (
n
= 14) and the VESSEL 12 challenge open dataset (
n
= 3) were used. For each case, 200 points were selected including 20 intra-lesional points, and the probability value for each point was extracted. For clinical validation, we included 281 COPD patients with low-dose noncontrast CTs. The DLVS-calculated volume of vessels with a cross-sectional area < 5 mm
2
(PVV5) and the PVV5 divided by total vessel volume (%PVV5) were measured.
Results
DLVS correctly segmented 99.1% of the intravascular points (1,387/1,400) and 93.1% of the extravascular points (1,309/1,400). The areas-under-the receiver-operating characteristic curve (AUROCs) were 0.977 and 0.969 for the two external validation datasets. For the COPD patients, both PPV5 and %PPV5 successfully differentiated severe patients whose FEV1 < 50 (AUROCs; 0.715 and 0.804) and were significantly correlated with the emphysema index (
P
s < .05).
Conclusions
DLVS successfully segmented pulmonary vessels on noncontrast chest CT by utilizing spatiotemporally matched 50-keV images from a dual-source CT scanner and showed promising clinical applicability in COPD.
Key Points
• We developed a deep learning pulmonary vessel segmentation algorithm using virtual noncontrast images and 50-keV enhanced images produced by a dual-source CT scanner.
• Our algorithm successfully segmented vessels on diseased lungs.
• Our algorithm showed promising results in assessing the loss of small vessel density in COPD patients.
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