Lung Window Research Articles

Precise characterization of a solitary pulmonary nodule using tumor shadow disappearance rate-corrected F-18 FDG PET and enhanced CT.

We aimed to characterize solitary pulmonary nodule (SPN) using imaging parameters for F-18 fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) or enhanced CT corrected by tumor shadow disappearance rate (TDR) to reflect the tissue density.We enrolled 51 patients with an SPN who underwent PET/CT and chest CT with enhancement. The FDG uptake of SPN was evaluated using maximum standardized uptake value (SUVmax) on PET/CT. The mean Hounsfield unit (HU) for each SPN was evaluated over the region of interest on nonenhanced and enhanced CT images. The change in mean HU (HUpeak-pre) was quantified by subtracting the mean HU of the preenhanced CT from that of the post-enhanced CT. TDR was defined as the ratio of the tumor area, which disappears at a mediastinal window, to the tumor area of the lung window. We investigated which parameters (SUVmax or HUpeak-pre) could contribute to the characterization of SPN classified by TDR value and whether diagnostic performance could be improved using TDR-corrected imaging parameters.For SPN with higher tissue density (TDR <42%, n = 22), high value of SUVmax (≥3.1) was a significant factor to predict malignancy (P = .006). High value of HUpeak-pre (≥38) was a significant factor to characterize SPN (P = .002) with lower tissue density (TDR ≥42%, n = 29). The combined approach using TDR-corrected parameters had better predictive performance to characterize SPN than SUVmax only (P = .031).Applying imaging parameters such as SUVmax or HUpeak-pre in consideration of tissue density calculated with TDR could contribute to accurate characterization of SPN.

Vulnerabilities of radiomic features to respiratory motion on four-dimensional computed tomography-based average intensity projection images: A phantom study.

PurposeTo evaluate the influence of respiratory motion on the robustness of radiomic features on four‐dimensional computed tomography (4DCT)‐based average intensity projection (AIP) images by employing an anthropomorphic chest phantom.MethodsThree spherical objects (φ30 mm), namely, acrylic (100 Hounsfield unit [HU], homogeneous), rubber (−140 HU, homogeneous), and cork (−630 HU, heterogeneous), were moved with motion amplitudes of 0, 1, 2.5, 4, 6, 8, and 10 mm in the phantom, and 4DCT scans were repeated at four different locations. Thereafter, the AIP images were generated considering the average of the 10 respiratory phases of the 4DCT images. Further, the targets were manually delineated on the AIP images in the lung window setting. A total of 851 radiomic features, including 107 unfiltered features and 744 wavelet filter‐based features, were extracted from the region of interest for each material. The feature robustness among the different target motion amplitude (ε) was evaluated by normalizing the feature variability of the target motion relative to the variability of data from 573 patients with early‐stage non‐small cell lung cancer. The features with absolute ε values ≤0.5 were considered highly robust to target motions.ResultsThe percentage of robust unfiltered and wavelet filter‐based features with a motion amplitude of 1 mm was greater than 83.2% and 93.4%, respectively; however, the percentage decreased by more than 24.3% and 17.6%, respectively, for motion amplitudes greater than 2.5 mm. The movement of cork had a small effect on the feature robustness compared to that of acrylic and rubber, regardless of the target motion amplitudes.ConclusionsOur phantom study demonstrated that target motion amplitudes ≤1 mm led to the robustness of radiomic features on the 4DCT‐based AIP images of thoracic regions. The frequency components and directions of the wavelet filters may be essential factors in 4DCT‐based radiomic analysis.

Therapeutic effect of cycloserine combined with anti-tuberculosis drugs in the treatment of multidrug-resistant tuberculosis

&#x0D; &#x0D; &#x0D; &#x0D; Purpose: The present study analyzes the comprehensive therapeutic effect of cycloserine, in combination with anti-tuberculosis drugs using chest X-ray and chest CT (computed tomography) scan techniques.&#x0D; Methods: A total of 90 patients, diagnosed with multidrug resistant tuberculosis (MDR TB) were subjected to chest x-ray and CT scan before and after treatment in the two groups. Different views such as sagittal, coronal, lung window and multiplanar imaging of mediastinal window were taken. Some parameters such as case detection rate (CDR) in chest X-ray and CT scan and comprehensive curative effect were observed in two groups. Further, the changes in chest CT signs in addition to absorption of focus, cavity closure and changes in CT extra pulmonary signs were also observed.&#x0D; Results: The clinical profile of the patients and the course of disease were statistically insignificant (p &gt; 0.05). Total effectiveness rate and case detection rate (CDR) values exhibited a significant difference between the groups (p &lt; 0.05). Lung consolidation, nodules and cavities significantly improved in both groups before and after the treatment (p &lt; 0.05). Both groups showed significant improvements in extrapulmonary signs in CT scan (p &lt; 0.05) after the treatment.&#x0D; Conclusion: Based on the study outcomes, the CT scan method has good potentials for diagnosing and treating MDR TB at the early stages. Further, it can clarify the signs and outcomes of the disease at early stages, thus providing the medical fraternity a great opportunity to cure the disease.&#x0D; &#x0D; &#x0D; &#x0D;

Utility of Maximum Intensity Projections in Volumetric High Resolution Computed Tomography Lung in the Evaluation of Diffuse Lung Diseases- A Retrospective Analysis

Introduction: Though volumetric High Resolution Computed Tomography (HRCT) has increased the sensitivity of diagnosing diffuse lung diseases, there are some drawbacks related with lesion detection. Post processing techniques like Maximum Intensity Projection (MIP) can help in increasing the sensitivity of HRCT further. Aim: To study various possible utilities of MIP in HRCT lung. Materials and Methods: A retrospective cross-sectional study was done in a tertiary care hospital, including all Computed Tomography (CT) scans performed in July 2020 to August 2020, with multiple lung findings and diffuse involvement of lungs. Two radiologists reviewed the base mean axial images of 1 mm and MIP images in sliding scale from 2 to 10 mm in lung window. They recorded the findings in every scan based on widely accepted basic pattern of interpretation of HRCT thorax. The slice/slab thickness that best depicted each finding was noted. Inter reader agreement was calculated for each finding. Results: Fifty nine CT cases, which included scans of 34 males and 25 female patients with a mean age of 37.4±12.5 years were reviewed. There was near perfect to substantial agreement between the two radiologists on various findings (kappa &gt; 0.75). MIP images of 6-10 mm slab thickness were best suited to detect smaller nodules, assess vessel size in areas of mosaic attenuation and detect dense lesions in images with poor breath hold. The MIP images of 2-5 mm thickness were useful in detecting the location in relation to secondary pulmonary lobule, reticular densities and crazy-paving densities. Conclusion: The MIP being an easy to use and readily available post processing technique, when used with volumetric HRCT dataset of thorax enhanced the value of HRCT in detecting various lesions.

346. Head to Toe Imaging of Complications and Sequelae of COVID- 19 and COVID-19 Vaccination

BackgroundCOVID 19 is associated with a hypercoagulable state with cytokine storm syndrome and thrombocytopenia leading to complications across various systems. COVID-19 infection, its treatment, resultant immunosuppression, and pre-existing comorbidities have made patients vulnerable to secondary infectionsMethodsWe systematically reviewed COVID-19 cases between Jan to May 2021 for pulmonary and extrapulmonary complications. Patients with recent COVID-19 vaccination and neurological symptoms were also included.Figure 1. “Black turbinate” sign of mucormycosis Contrast enhanced coronal T1 FS images of paranasal sinuses shows necrotic non-enhancing right superior and middle turbinates (*) with extension into the right orbital fat.FIGURE 2 - A composite image of Coronal CT of upper abdomen in arterial phase and lung bases in lung window showing wedge showing right renal infarcts (line arrow) due to inferior polar artery thrombosis and ground glass opacities (solid arrow) in lung bases. Results Neurological complications: Neurological complications include ischemic and haemorrhagic strokes. Other complications are encephalopathy, encephalitis, Guillain-Barré syndrome, acute hemorrhagic necrotizing encephalopathy. Demyelination and radiculopathies are seen as post vaccination complications. Mucormycosis: Unprecedented high rate of invasive fungal sinusitis in association with COVID -19 is reported from the Indian subcontinent. This has a propensity for intra orbital and intracranial extension. COVID -19 associated coagulopathy: COVID -19 is a pro-inflammatory hypercoagulable state. Pulmonary thromboembolism, deep venous thrombosis and catheter related thrombosis are well documented. Cardiac complications: Cardiac manifestations include Myocardial Injury with non-obstructed coronary arteries (MINOCA), myocarditis, myocardial ischemia, cardiomyopathy. Pulmonary complications and sequelae of COVID -19: Progression of lung injury to ARDS during the initial phase and fibrosis of parenchyma in the recovery phase. Spontaneous pneumomediastinum, pneumatoceles and pneumothorax and secondary infections are identified in our study. COVID- 19 associated gastrointestinal complications: Patients evaluated for renal colic, pancreatitis, cholecystitis showed, ground glass opacities or subpleural bands in typical Covid-19 distribution. COVID-19 may lead of acute kidney and bowel injury due to arterial thrombosis. COVID - 19 associated myonecrosis: Ischemia of the small caliber vessels may result in myonecrosis.FIGURE 3 - Coronal STIR image shows thickened and hyperintense trunks and divisions of the right brachial plexus suggestive of plexopathy in a COVID -19 patient with H/O recent COVID-19 vaccination. Figure 4. Axial CT chest section in lung window showing pneumothorax (white arrow) and pneumatocele ( grey arrow) with peripheral ground glass opacities and consolidations in both lungs. ConclusionAwareness of these unusual manifestations will facilitate an early diagnosis, improve management and help reduce morbidity and mortalityDisclosures All Authors: No reported disclosures

326. Radiologic Findings of COVID-19 Associated Mucormycosis (CAM) from India

BackgroundThe unique feature of the second wave of the COVID -19 pandemic in India has been the alarming surge of acute invasive fungal infection among COVID -19 patients. The increased incidence of rhino-orbito-cerebral mucormycosis is a matter of concern, as this fulminant infection has high morbidity and mortality. Hence, it is imperative to understand it’s imaging features, for early diagnosis, staging and treatment.MethodsWe systematically reviewed 32 COVID-19 cases with imaging diagnosis of acute invasive fungal rhino-sinusitis or rhino-orbital-cerebral disease between March to May 2021. These patients underwent contrast MRI of the paranasal sinus, orbit and brain. Contrast enhanced CT chest and paranasal sinuses were done as needed.ResultsThe age group ranged between 30 to 71 yrs with male preponderance. The most common predisposing factors were intravenous steroid therapy and supplemental oxygen. All cases were confirmed by fungal culture and most common was Mucor. The rhino-orbito-cerebral mucormycosis was staged as belowStageNo. of cases1 (Limited to nasal cavity)22 (Involving Paranasal sinuses) 143 (Involvement of orbit)84 (Involvement of CNS)8In our study we found that the most common site in the nasal cavity was the middle turbinate /meatus and the earliest sign was non-enhancing / “black” turbinate. Premaxillary and retroantral fat necrosis was the earliest sign of soft tissue invasion. Spread via the sphenopalatine foramen and pterygopalatine fossa was more common than bony erosions. Orbital cellulitis and optic neuritis were the most common among stage 3 cases. Of patients with CNS involvement, the most common were cavernous sinus thrombosis and trigeminal neuritis. Two patients with pulmonary mucormycosis showed large necrotic cavitary lesions, giving the characteristic “bird’s nest” appearance.Figure 1. Black turbinate Contrast enhanced coronal T1 FS images of paranasal sinuses shows necrotic non-enhancing right superior and middle turbinates (*)Figure 2: Axial contrast enhanced T1 FS image showing necrotic non enhancing premaxillary (arrowhead) and retroantral fat (straight arrow) walled off by thin enhancing rim. Figure 3: Contrast enhanced axial T1 FS images of paranasal sinuses shows necrotic non-enhancing left middle meatus spreading along sphenopalatine foramen in to pterygopalatine fossa (arrow head) ConclusionThe mortality rate was 20% in our study. In our short term follow up, 30 % of recovered patients had relapse on imaging due to incomplete clearance and partial antifungal treatment. High clinical suspicion and low imaging threshold are vital for early Mucormycosis detection in COVID-19 patients. Familiarity with early imaging signs is critical to prevent associated morbidity /mortality.Figure 4: Contrast enhanced coronal T1 FS and diffusion weighted images shows necrotic non-enhancing left middle meatus with left orbital cellulitis (*) and optic neuritis (white arrow) Figure 5. Bird’s nest Axial CT chest image in lung window shows necrotic right upper lobe cavity with internal septations and debris on a background of surrounding COVID-19 changes.Disclosures All Authors: No reported disclosures

Comparison of lung image quality between CT Ark and Brilliance 64 CT during COVID-19

AimThis study is to compare the lung image quality between shelter hospital CT (CT Ark) and ordinary CT scans (Brilliance 64) scans.MethodsThe patients who received scans with CT Ark or Brilliance 64 CT were enrolled. Their lung images were divided into two groups according to the scanner. The objective evaluation methods of signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were used. The subjective evaluation methods including the evaluation of the fine structure under the lung window and the evaluation of the general structure under the mediastinum window were compared. Kappa method was used to assess the reliability of the subjective evaluation. The subjective evaluation results were analyzed using the Wilcoxon rank sum test. SNR and CNR were tested using independent sample t tests.ResultsThere was no statistical difference in somatotype of enrolled subjects. The Kappa value between the two observers was between 0.68 and 0.81, indicating good consistency. For subjective evaluation results, the rank sum test P value of fine structure evaluation and general structure evaluation by the two observers was ≥ 0.05. For objective evaluation results, SNR and CNR between the two CT scanners were significantly different (P<0.05). Notably, the absolute values ​​of SNR and CNR of the CT Ark were larger than Brilliance 64 CT scanner.ConclusionCT Ark is fully capable of scanning the lungs of the COVID-19 patients during the epidemic in the shelter hospital.

Chest Computed Tomography Images in Neonatal Bronchial Pneumonia under the Adaptive Statistical Iterative Reconstruction Algorithm.

This study was to explore the application value of chest computed tomography (CT) images processed by artificial intelligence (AI) algorithms in the diagnosis of neonatal bronchial pneumonia (NBP). The AI adaptive statistical iterative reconstruction (ASiR) algorithm was adopted to reconstruct the chest CT image to compare and analyze the effect of the reconstruction of CT image under the ASiR algorithm under different preweight and postweight values based on the objective measurement and subjective evaluation. 85 neonates with pneumonia treated in hospital from September 1, 2015, to July 1, 2020, were selected as the research objects to analyze their CT imaging characteristics. Subsequently, the peripheral blood of healthy neonates during the same period was collected, and the levels of C-reactive protein (CRP) and erythrocyte sedimentation rate (ESR) were detected. The efficiency of CT examination, CRP, ESR, and combined examination in the diagnosis of NBP was analyzed. The results showed that the subjective quality score, lung window subjective score, and mediastinal window subjective score were the highest after CT image reconstruction when the preweight value of the ASiR algorithm was 50%. After treatment, 79 NBP cases (92.9%) showed ground-glass features in CT images. Compared with the healthy neonates, the levels of CRP and ESR in the peripheral blood of neonates with bronchial pneumonia were much lower (P < 0.05). The accuracy rates of CT examination, CRP examination, ESR examination, CRP + ESR examination, and CRP + ESR + CT examination for the diagnosis of NBP were 80.7%, 75.3%, 75.1%, 80.3%, and 98.6%, respectively. CT technology based on AI algorithm showed high clinical application value in the feature analysis of NBP.

Prognostic Radiological Tools for Clinical Stage IA Pure Solid Lung Cancer.

In this study, we analyzed prognostic radiological tools and surgical outcomes for radiologically pure solid adenocarcinomas (AD) and squamous cell carcinoma (SQ) in clinical stage IA. We retrospectively investigated 130 patients who underwent surgical resections. We assessed the predictive risk factors for recurrence and pathological lymph node metastasis (LNM). There was no statistical difference in recurrence free survival (RFS) or cancer-specific survival (CSS) between AD and SQ groups (p = 0.642 and p = 0.403, respectively). In the whole cohort, tumor size on lung window and mediastinal settings, and tumor disappearance ratio using high-resolution computed tomography (HRCT) were not prognostic parameters (p = 0.127, 0.066, and 0.082, respectively). The maximal standardized uptake value (SUVmax) using positron emission tomography-CT was associated with recurrence (p = 0.016). According to the receiver operating characteristic curve, the cut-off value of SUVmax for recurrence was 4.6 (p = 0.016). The quantitative continuous variables using any radiological tools were not associated with LNM. However, tumor diameter on mediastinal setting ≥8 mm with SUVmax ≥2.4 could be a risk factor for LNM. Pure solid AD and SQ were equivalent for the RFS and CSS. SUVmax was useful to predict recurrence. The tumor diameter on a mediastinal setting and SUVmax were useful in predicting pathological LNM.

Subsolid Lung Adenocarcinomas: Radiological, Clinical and Pathological Features and Outcomes

Lung adenocarcinomas manifesting as subsolid nodules usually have a favorable prognosis. This study aimed to have a comprehensive investigation of the radiological and clinicopathologic features and oncological outcomes of subsolid nodules. Between March 2010 and December 2015, 865 patients with surgically resected clinical IA subsolid lung adenocarcinoma were retrospectively reviewed. Patients were classified into the pure ground-glass nodules (GGN) (pGGN [n=358], without solid component on lung and mediastinal windows), heterogeneous GGN (hGGN [n=65], only with solid components on lung window), and real part-solid nodule (rPSN [n=442], with solid component on both lung and mediastinal windows) groups. The clinicopathological features and survival time of the three groups were compared between groups. There was a significant increase in median tumor size (P < 0.001), solid component size measured at lung window (LW-SCS) (P < 0.001), and the proportion of invasive adenocarcinoma subtypes (P < 0.001) from pGGNs to hGGNs to rPSNs. After adjustment for LW-SCS, adenocarcinomas with predominant lepidic patterns were still more common in hGGNs than in rPSNs (P=0.009). Patients with rPSNs had a significantly worse recurrence-free survival (RFS) than those with pGGNs and hGGNs (5-year: 91.9% versus 100% versus 100%, P < 0.001). Multivariate Cox analyses revealed that gender (both P < 0.05) and clinical T category (based on lung window [LW-cT] [P=0.002] or mediastinal window [MW-cT] [P < 0.001]) were independent prognostic factors of RFS in the rPSN group. HGGNs represented as an intermediate subtype between pGGNs and rPSNs. Both pGGNs and hGGNs had excellent outcomes, while rPSNs exhibited a worse prognosis than them. Clinical T category and gender had prognostic implications for rPSNs.

Realistic Lung Nodule Synthesis With Multi-Target Co-Guided Adversarial Mechanism.

The important cues for a realistic lung nodule synthesis include the diversity in shape and background, controllability of semantic feature levels, and overall CT image quality. To incorporate these cues as the multiple learning targets, we introduce the Multi-Target Co-Guided Adversarial Mechanism, which utilizes the foreground and background mask to guide nodule shape and lung tissues, takes advantage of the CT lung and mediastinal window as the guidance of spiculation and texture control, respectively. Further, we propose a Multi-Target Co-Guided Synthesizing Network with a joint loss function to realize the co-guidance of image generation and semantic feature learning. The proposed network contains a Mask-Guided Generative Adversarial Sub-Network (MGGAN) and a Window-Guided Semantic Learning Sub-Network (WGSLN). The MGGAN generates the initial synthesis using the mask combined with the foreground and background masks, guiding the generation of nodule shape and background tissues. Meanwhile, the WGSLN controls the semantic features and refines the synthesis quality by transforming the initial synthesis into the CT lung and mediastinal window, and performing the spiculation and texture learning simultaneously. We validated our method using the quantitative analysis of authenticity under the Fréchet Inception Score, and the results show its state-of-the-art performance. We also evaluated our method as a data augmentation method to predict malignancy level on the LIDC-IDRI database, and the results show that the accuracy of VGG-16 is improved by 5.6%. The experimental results confirm the effectiveness of the proposed method.

Can Alveolar-Arterial Difference and Lung Ultrasound Help the Clinical Decision Making in Patients with COVID-19?

Background: COVID-19 is an emerging infectious disease, that is heavily challenging health systems worldwide. Admission Arterial Blood Gas (ABG) and Lung Ultrasound (LUS) can be of great help in clinical decision making, especially during the current pandemic and the consequent overcrowding of the Emergency Department (ED). The aim of the study was to demonstrate the capability of alveolar-to-arterial oxygen difference (AaDO2) in predicting the need for subsequent oxygen support and survival in patients with COVID-19 infection, especially in the presence of baseline normal PaO2/FiO2 ratio (P/F) values. Methods: A cohort of 223 swab-confirmed COVID-19 patients underwent clinical evaluation, blood tests, ABG and LUS in the ED. LUS score was derived from 12 ultrasound lung windows. AaDO2 was derived as AaDO2 = ((FiO2) (Atmospheric pressure − H2O pressure) − (PaCO2/R)) − PaO2. Endpoints were subsequent oxygen support need and survival. Results: A close relationship between AaDO2 and P/F and between AaDO2 and LUS score was observed (R2 = 0.88 and R2 = 0.67, respectively; p < 0.001 for both). In the subgroup of patients with P/F between 300 and 400, 94.7% (n = 107) had high AaDO2 values, and 51.4% (n = 55) received oxygen support, with 2 ICU admissions and 10 deaths. According to ROC analysis, AaDO2 > 39.4 had 83.6% sensitivity and 90.5% specificity (AUC 0.936; p < 0.001) in predicting subsequent oxygen support, whereas a LUS score > 6 showed 89.7% sensitivity and 75.0% specificity (AUC 0.896; p < 0.001). Kaplan–Meier curves showed different mortality in the AaDO2 subgroups (p = 0.0025). Conclusions: LUS and AaDO2 are easy and effective tools, which allow bedside risk stratification in patients with COVID-19, especially when P/F values, signs, and symptoms are not indicative of severe lung dysfunction.

Frequency of Incidental Ageing-Related Lung Findings in an Elderly Population: A Saudi Teleradiology CT Study

Objectives: To assess the frequency of ageing-related lung changes seen on computed tomography (CT) chest examinations performed on teleradiology cohort of elderly patients.&#x0D; Materials and Methods: An experienced radiologist retrospectively assessed at a 3-month worth of teleradiology data of CT chest, abdomen and pelvis performed for detection or staging of malignancy is in asymptomatic patients 60 years old and older, residing in Saudi Arabia. Patients with known smoking history or obscuring abnormalities were excluded. Lung windows were analyzed to detect bronchial wall thickening, mosaic attenuation, linear scars, reticulations and pneumatocoeles. Bronchial thickening and mosaic attenuation were stratified by severity, while the scars and pneumatocoeles were stratified by number.&#x0D; Results: A total of 26 cases were collected out of 137 patients, with a mean age of 67 years old (61% males). Bronchial wall thickening was detected and 56%, with 35% being of moderate degree. Mosaic attenuation was detected in 26%, with 70% being of mild degree. Linear scarring was seen and 61%, in the absence of reticulations. Pneumatocoeles were detected in 26%, with 22% being more than 2 in numbers.&#x0D; Conclusion: In a select teleradiology cohort of asymptomatic CT chest imaging in elderly patients, bronchial wall thickening, mosaic attenuation, linear scarring pneumatocoeles are frequently encountered. Such findings should not lead to clinical or imaging misinterpretations.

Solid Components in the Mediastinal Window of Computed Tomography Define a Distinct Subtype of Subsolid Nodules in Clinical Stage I Lung Cancers

BackgroundWe aimed to validate the clinicopathologic characteristics and prognostic value of the presence of solid components in the mediastinal window of computed tomography scan in clinical stage I pulmonary subsolid nodules (SSNs). MethodsWe retrospectively evaluated patients with pulmonary SSNs resected between 2011 and 2016. We classified SSNs into heterogeneous ground-glass nodules (HGGNs) (solid component detected only in lung window) and part-solid nodules (PSNs) (solid component detected both in lung/mediastinal windows). ResultsA total of 487 patients (216 PSNs) were included. PSNs were associated with higher frequencies of micropapillary or solid pathologic patterns (18.1% vs. 3.3%; P < .001), epidermal growth factor receptor gene mutation (39.4% vs. 32.8%), and other types of gene mutations (2.3% vs. 1.1%; P = .043). Logistic regression analysis revealed that male sex (odds ratio [OR], 2.58; 95% confidence interval [CI], 1.20-5.57; P = .016) and higher consolidation tumor ratio (CTR) (OR, 110.04; 95% CI, 8.56-1414.39; P < .001) remained independent for invasive adenocarcinomas with poor differentiation. Receiver operating characteristic analyses revealed that solid component size in the mediastinal window (area under the curve [AUC], 0.731; 95% CI, 0.653-0.808; P < .0001) showed a better predictive ability to poor differentiation compared with solid component size in the lung window and CTR. The 5-year recurrence-free survival (RFS) rate of PSNs was worse than that of HGGNs (94.6% vs. 99.1%; P = .019). Multivariate Cox regression revealed that positive lymph node status (hazard ratio, 22.99; 95% CI, 4.52-116.86; P < .001) indicated worse RFS for PSNs. ConclusionSSNs with solid components in mediastinal window demonstrated clinicopathologic and prognostic features different from those without in clinical stage I lung cancer. Solid components in mediastinal window was a strong predictor of poor differentiation.

Computed Tomography of the Chest: Basic Principles

Tomography is a process by which an image layer of the body is produced, while the images of the structures above and below that layer are made invisible by blurring. computed tomography (CT), the most widely used cross-sectional imaging methods used in medicine, forms cross-sectional images by avoiding super-imposition of structures that occurs in conventional chest imaging, with a &gt;10-fold increase in attenuation sensitivity, within a second without need for breath holding. Like X-ray, an imaging contrast is generated as a consequence of differences in attenuation between the adjacent tissues. The higher the attenuation of the X-ray beam, the brighter the tissue on CT images, and vice versa. The only drawback is the potentially harmful radiation that is measured according to the amount of radiation received by the whole body. Simply, the amount of radiation from a chest CT is equivalent to 400 X-rays. Standard CT usually takes the image of the whole lung and compresses thick slices of about 7-10 mm into images and contrast can be given to highlight structures. High resolution (HRCT) has excellent spatial resolution and very useful for assessing the architecture of the lung. It does not involve IV contrast, acquires thin, non-contiguous slices, at 10-15 mm intervals with thin slices of lung tissues at regular intervals. This reduces the radiation dose by up to 90% compared to standard CT. The axial images are most commonly viewed using lung, mediastinal and bone window. The pulmonary window is specially used for the interpretation of lung parenchyma, airways and interstitial tissues but the mediastinal window is for the interpretation of mediastinal structures. CT interpretation needs a structured and logical approach.&#x0D; DS (Child) H J 2019; 35(1) : 63-69

A comparative study to evaluate CT-based semantic and radiomic features in preoperative diagnosis of invasive pulmonary adenocarcinomas manifesting\xa0as subsolid nodules

This study aims to predict the histological invasiveness of pulmonary adenocarcinoma spectrum manifesting with subsolid nodules ≦ 3 cm using the preoperative CT-based radiomic approach. A total of 186 patients with 203 SSNs confirmed with surgically pathologic proof were retrospectively reviewed from February 2016 to March 2020 for training cohort modeling. The validation cohort included 50 subjects with 57 SSNs confirmed with surgically pathologic proof from April 2020 to August 2020. CT-based radiomic features were extracted using an open-source software with 3D nodular volume segmentation manually. The association between CT-based conventional features/selected radiomic features and histological invasiveness of pulmonary adenocarcinoma status were analyzed. Diagnostic models were built using conventional CT features, selected radiomic CT features and experienced radiologists. In addition, we compared diagnostic performance between radiomic CT feature, conventional CT features and experienced radiologists. In the training cohort of 203 SSNs, there were 106 invasive lesions and 97 pre-invasive lesions. Logistic analysis identified that a selected radiomic feature named GLCM_Entropy_log10 was the predictor for histological invasiveness of pulmonary adenocarcinoma spectrum (OR: 38.081, 95% CI 2.735–530.309, p = 0.007). The sensitivity and specificity for predicting histological invasiveness of pulmonary adenocarcinoma spectrum using the cutoff value of CT-based radiomic parameter (GLCM_Entropy_log10) were 84.8% and 79.2% respectively (area under curve, 0.878). The diagnostic model of CT-based radiomic feature was compared to those of conventional CT feature (morphologic and quantitative) and three experienced radiologists. The diagnostic performance of radiomic feature was similar to those of the quantitative CT feature (nodular size and solid component, both lung and mediastinal window) in prediction invasive pulmonary adenocarcinoma (IPA). The AUC value of CT radiomic feature was higher than those of conventional CT morphologic feature and three experienced radiologists. The c-statistic of the training cohort model was 0.878 (95% CI 0.831–0.925) and 0.923 (0.854–0.991) in the validation cohort. Calibration was good in both cohorts. The diagnostic performance of CT-based radiomic feature is not inferior to solid component (lung and mediastinal window) and nodular size for predicting invasiveness. CT-based radiomic feature and nomogram could help to differentiate IPA lesions from preinvasive lesions in the both independent training and validation cohorts. The nomogram may help clinicians with decision making in the management of subsolid nodules.

Intravital Imaging of Pulmonary Immune Response in Inflammation and Infection.

Intravital microscopy (IVM) is a unique imaging method providing insights in cellular functions and interactions in real-time, without the need for tissue extraction from the body. IVM of the lungs has specific challenges such as restricted organ accessibility, respiratory movements, and limited penetration depth. Various surgical approaches and microscopic setups have been adapted in order to overcome these challenges. Among others, these include the development of suction stabilized lung windows and the use of more advanced optical techniques. Consequently, lung IVM has uncovered mechanisms of leukocyte recruitment and function in several models of pulmonary inflammation and infection. This review focuses on bacterial pneumonia, aspiration pneumonia, sepsis-induced acute lung Injury, and cystic fibrosis, as examples of lung inflammation and infection. In addition, critical details of intravital imaging techniques of the lungs are discussed.

Image quality of ultralow-dose chest CT using deep learning techniques: potential superiority of vendor-agnostic post-processing over vendor-specific techniques.

To compare the image quality between the vendor-agnostic and vendor-specific algorithms on ultralow-dose chest CT. Vendor-agnostic deep learning post-processing model (DLM), vendor-specific deep learning image reconstruction (DLIR, high level), and adaptive statistical iterative reconstruction (ASiR, 70%) algorithms were employed. One hundred consecutive ultralow-dose noncontrast CT scans (CTDIvol; mean, 0.33 ± 0.056 mGy) were reconstructed with five algorithms: DLM-stnd (standard kernel), DLM-shrp (sharp kernel), DLIR, ASiR-stnd, and ASiR-shrp. Three thoracic radiologists blinded to the reconstruction algorithms reviewed five sets of 100 images and assessed subjective noise, spatial resolution, distortion artifact, and overall image quality. They selected the most preferred algorithm among five image sets for each case. Image noise and signal-to-noise ratio were measured. Edge-rise-distance was measured at a pulmonary vessel, i.e., the distance between two points where attenuation was 10% and 90% of maximal intravascular intensity. The skewness of attenuation was calculated in homogeneous areas. DLM-stnd, followed by DLIR, showed the best subjective noise on both lung and mediastinal windows, while DLIR yielded the least measured noise (ps < .0001). Compared to DLM-stnd, DLIR showed inferior subjective spatial resolution on lung window and higher edge-rise-distance (ps < .0001). Additionally, DLIR showed the most frequent distortion artifacts and deviated skewness (ps < .0001). DLM-stnd scored the best overall image quality, followed by DLM-shrp and DLIR (mean score 3.89 ± 0.19, 3.68 ± 0.24, and 3.53 ± 0.33; ps < .001). Two among three readers preferred DLM-stnd on both windows. Although DLIR provided the best quantitative noise profile, DLM-stnd showed the best overall image quality with fewer artifacts and was preferred by two among three readers. • A vendor-agnostic deep learning post-processing algorithm applied to ultralow-dose chest CT exhibited the best image quality compared to vendor-specific deep learning algorithm and ASiR techniques. • Two out of three readers preferred a vendor-agnostic deep learning post-processing algorithm in comparison to vendor-specific deep learning algorithm and ASiR techniques. • A vendor-specific deep learning reconstruction algorithm yielded the least image noise, but showed significantly more frequent specific distortion artifacts and increased skewness of attenuation compared to a vendor-agnostic algorithm.

Retrospective analysis of chest HRCT findings in coronavirus disease pandemic (COVID-19)- An early experience.

Context:Corona virus disease (COVID-19) has spread in a rampant manner all over the World causing severe acute respiratory illness. Prompt recognition of disease is invaluable to ensure timely treatment, and rapid patient isolation is crucial for containment of this communicable disease.Aims:To evaluate the performance of high resolution CT (HRCT) in the diagnosis of COVID-19. To establish the role of HRCT in prognosis of affected patients and to assess severity of disease based on HRCT findings.Settings and Design:This retrospective study included 216 patients admitted to our institute with a diagnosis of COVID-19 infection confirmed by nucleic acid RT-PCR testing.Subjects and Methods:Patients underwent non contrast HRCT chest examination and images were reconstructed in thin 1.25 mm lung window. Images were evaluated for presence of lung lesions & CT severity score was assigned to each patient based on number of lung lobes involved.Results:Ground-glass opacities (GGOs) with or without consolidation, interlobular septal thickening, the “reversed halo” sign (Atoll sign) and GGO's with rounded nodular pattern are common CT features of COVID-19Conclusions:Typical peripheral subpleural distributions of GGO's with bilateral asymmetrical lung involvement are characteristic features of COVID19 pneumonia. Chest HRCT can be a very useful and standard imaging method to assess the severity and progression of the disease and thereby optimizing the management of patients. With increasing case load all over the world HRCT can be used as a one stop radiological investigation for the diagnosis and prognosis of corona virus disease.

The value of pulmonary nodule diameter and consolidation/tumor rate in the prediction of lymph node metastasis in early-stage (cT1N0M0) lung adenocarcinoma

BackgroundWe aimed to determine whether the use of pulmonary nodule diameter and CTR predicts lymph nodes (LNs) metastasis for early-stage (cT1N0M0) lung adenocarcinoma.MethodsWe retrospectively analyzed 433 consecutive patients who underwent therapeutic surgical resection in our hospital. Information about age, sex, history of malignancy, smoking index, high-resolution computed tomography (HRCT) imaging information, pathologic findings, and status of LNs metastasis were collected.ResultsA total of 433 patients were included 277 women and 156 men, with a median age of 58.09±9.41 years. On univariate and multivariate analysis, visceral pleural invasion (VPI) (P=0.005), the diameter of nodule measured by postoperative pathology (DP) (P=0.011), the largest axial diameter of the lesion on the mediastinal window (DM) (P<0.001), the ratio of the maximum diameter of consolidation relative to the maximum tumor diameter from the lung window (CTR) (P=0.01), and total dissected LNs number (P=0.005) categories were independent facto for LNs metastasis. The receiver operating characteristic (ROC) curve showed that DM ≥11.81 cm, or CTR ≥79.50%, or VPI indicated LNs metastasis. LNs metastasis patients could be better predicted by a total dissected LNs number with a cutoff point of 13.5 for lung cancer.ConclusionsVPI, DP, DM, CTR, and total dissected LNs number categories were independent factors for LNs metastasis. If DM ≥11.81 cm, or CTR ≥79.50%, or VPI systemic lymphadenectomy was recommended. We suggested 14 LNs as the cut point for the evaluation LNs examination.