Contrast-enhanced Chest CT Research Articles

Analysis of contrast-enhanced spectral chest CT optimal monochromatic imaging combined with ASIR and ASIR-V.

The aim of the study was to explore the application of spectral chest CT optimal monochromatic imaging combined with ASIR and ASIR-V to optimize the image quality in the arterial phase. 62 patients who had undergone contrast-enhanced chest CT examination using spectral CT were included. Twelve sets of arterial phase images were acquired using GSI mode. The CNR, BHA values and subjective scores were statistically analysed. Thus, optimal monochromatic images were obtained. Then, the images were acquired by reconstruction using ASIR and ASIR-V at 30%, 50% and 70% levels. Six sets of images were obtained and compared with QC and the monochromatic image under FBP mode. In FBP mode, the CNR of 80-keV images was 7.7±2.0, showing no significant difference with QC images (p > 0.05). The BHA value in the blood vessels was 45.2±23.1, which was lower than that in QC images (p < 0.05). The subjective image quality score of 80-keV images was 4.50±0.62. No significant difference was found in QC images (p > 0.05). The subjective score of the artefacts was 2.45±0.62, which was lower than that of QC images (p < 0.05). Thus, 80 keV was chosen as the optimal monochromatic energy to be reconstructed with ASIR and ASIR-V. The CNR of the 80keV+50% ASIR-V group was 13.9±4.3, which was higher than those of 140-kVp and 80-keV images in FBP (p < 0.05). The subjective score was 4.90±0.298, which was higher than that of other groups (p < 0.05). Compared with conventional chest CT images in the arterial phase, 80keV+50% ASIR-V images can effectively eliminate beam-hardening artefacts and improve image quality.

Biphasic split-bolus injection protocol for routine contrast-enhanced chest CT: comparison with conventional early-phase single bolus technique.

To present a routine contrast-enhanced chest CT protocol with a split-bolus injection technique achieving combined early- and delayed phase images with a single aquisition, and to compare this technique with a conventional early-phase single-bolus chest CT protocol we formerly used at our institution, in terms of attenuation of great thoracic vessels, pleura, included hepatic and portal venous enhancement, contrast-related artifacts, and image quality. A total of 202 patients, who underwent routine contrast-enhanced chest CT examination aquired with either conventional early-phase single-bolus technique (group A,n = 102) or biphasic split-bolus protocol (group B,n = 100), were retrospectively included. Attenuation measurements were made by two radiologists independently on mediastinal window settings using a circular ROI at the following sites: main pulmonary artery (PA) at its bifurcation level, thoracal aorta (TA) at the level of MPA bifurcation,portal vein (PV) at porta hepatis, left and right hepatic lobe, and if present, thickened pleura (>2 mm) at the level with the most intense enhancement. Respective normalized enhancement values were also calculated. Contrast-related artifacts were graded and qualitative evaluation of mediastinal lymph nodes was performed by both reviewers independently. Background noise was measured and contrast-to-noise ratios (CNRs) of the liver and TA were calculated. While enhancement of thoracic vessels and normalised MPA enhancement did not differ significantly between both groups (p > 0.05), enhancement and normalised enhancement of pleura, liver parenchyma and PV was significantly greater in group B (p < 0.001). Perivenous artifacts limiting evaluation were less frequent in group B than in A and mediastinal lymph nodes were judged to be evaluated worse in group A than in group B with an excellent agreement between both observers. No significant difference was detected in CNRTA (p = 0.633), whereas CNR liver was higher in group B (p < 0.001). Our split-bolus chest CT injection protocol enables simultaneous enhancement for both vascular structures and soft tissues, and thus, might raise diagnostic confidence without the need of multiple acquisitions. We think that this CT protocol might also be a promising alternative in lung cancer staging, where combined contrast-enhanced CT of the chest and abdomen is indicated. We therefore suggest to further evaluate its diagnostic utility in this setting, in particular in comparison with a late delayed chest-upper abdominal CT imaging protocol.

Impact of Contrast Enhancement and Virtual Monoenergetic Image Energy Levels on Emphysema Quantification: Experience With Photon-Counting Detector Computed Tomography.

The aim of this study was to evaluate the impact of contrast enhancement and different virtual monoenergetic image energies on automatized emphysema quantification with photon-counting detector computed tomography (PCD-CT). Sixty patients who underwent contrast-enhanced chest CT on a first-generation, clinical dual-source PCD-CT were retrospectively included. Scans were performed in the multienergy (QuantumPlus) mode at 120 kV with weight-adjusted intravenous contrast agent. Virtual noncontrast (VNC) images as well as virtual monoenergetic images (VMIs) from 40 to 80 keV obtained in 10-keV intervals were reconstructed. Computed tomography attenuation was measured in the aorta. Noise was measured in subcutaneous fat and defined as the standard deviation of attenuation. Contrast-to-noise with region of interest in the ascending aorta and signal-to-noise ratio in the subcutaneous fat were calculated. Subjective image quality (and emphysema assessment, lung parenchyma evaluation, and vessel evaluation) was rated by 2 blinded radiologists. Emphysema quantification (with a threshold of -950 HU) was performed by a commercially available software. Virtual noncontrast images served as reference standard for emphysema quantification. Noise and contrast-to-noise ratio showed a strong negative correlation (r = -0.98; P < 0.01) to VMI energies. The score of subjective assessment was highest at 70 keV for lung parenchyma and 50 keV for pulmonary vessel evaluation (P < 0.001). The best trade-off for the assessment of emphysema while maintaining reasonable contrast for pulmonary vessel evaluation was determined between 60 and 70 keV. Overall, contrast-enhanced imaging led to significant and systematic underestimation of emphysema as compared with VNC (P < 0.001). This underestimation decreased with increasing VMI-energy (r = 0.98; P = 0.003). Emphysema quantification showed significantly (P < 0.05) increased emphysema volumes with increasing VMI energies, except between 60-70 keV and 70-80 keV. The least difference in emphysema quantification between contrast-enhanced scans and VNC was found at 80 keV. Computed tomography emphysema quantification was significantly affected by intravenous contrast administration and VMI-energy level. Virtual monoenergetic image at 80 keV yielded most comparable results to VNC. The best trade-off in qualitative as well as in quantitative image quality evaluation was determined at 60/70 keV.

Deep Learning Reconstruction Shows Better Lung Nodule Detection for Ultra-Low-Dose Chest CT.

Background Ultra-low-dose (ULD) CT could facilitate the clinical implementation of large-scale lung cancer screening while minimizing the radiation dose. However, traditional image reconstruction methods are associated with image noise in low-dose acquisitions. Purpose To compare the image quality and lung nodule detectability of deep learning image reconstruction (DLIR) and adaptive statistical iterative reconstruction-V (ASIR-V) in ULD CT. Materials and Methods Patients who underwent noncontrast ULD CT (performed at 0.07 or 0.14 mSv, similar to a single chest radiograph) and contrast-enhanced chest CT (CECT) from April to June 2020 were included in this prospective study. ULD CT images were reconstructed with filtered back projection (FBP), ASIR-V, and DLIR. Three-dimensional segmentation of lung tissue was performed to evaluate image noise. Radiologists detected and measured nodules with use of a deep learning-based nodule assessment system and recognized malignancy-related imaging features. Bland-Altman analysis and repeated-measures analysis of variance were used to evaluate the differences between ULD CT images and CECT images. Results A total of 203 participants (mean age ± standard deviation, 61 years ± 12; 129 men) with 1066 nodules were included, with 100 scans at 0.07 mSv and 103 scans at 0.14 mSv. The mean lung tissue noise ± standard deviation was 46 HU ± 4 for CECT and 59 HU ± 4, 56 HU ± 4, 53 HU ± 4, 54 HU ± 4, and 51 HU ± 4 in FBP, ASIR-V level 40%, ASIR-V level 80% (ASIR-V-80%), medium-strength DLIR, and high-strength DLIR (DLIR-H), respectively, of ULD CT scans (P < .001). The nodule detection rates of FBP reconstruction, ASIR-V-80%, and DLIR-H were 62.5% (666 of 1066 nodules), 73.3% (781 of 1066 nodules), and 75.8% (808 of 1066 nodules), respectively (P < .001). Bland-Altman analysis showed the percentage difference in long diameter from that of CECT was 9.3% (95% CI of the mean: 8.0, 10.6), 9.2% (95% CI of the mean: 8.0, 10.4), and 6.2% (95% CI of the mean: 5.0, 7.4) in FBP reconstruction, ASIR-V-80%, and DLIR-H, respectively (P < .001). Conclusion Compared with adaptive statistical iterative reconstruction-V, deep learning image reconstruction reduced image noise, increased nodule detection rate, and improved measurement accuracy on ultra-low-dose chest CT images. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Lee in this issue.

Investigation of the added value of CT-based radiomics in predicting the development of brain metastases in patients with radically treated stage III NSCLC.

Introduction:Despite radical intent therapy for patients with stage III non-small-cell lung cancer (NSCLC), cumulative incidence of brain metastases (BM) reaches 30%. Current risk stratification methods fail to accurately identify these patients. As radiomics features have been shown to have predictive value, this study aims to develop a model combining clinical risk factors with radiomics features for BM development in patients with radically treated stage III NSCLC.Methods:Retrospective analysis of two prospective multicentre studies. Inclusion criteria: adequately staged [18F-fluorodeoxyglucose positron emission tomography-computed tomography (18-FDG-PET-CT), contrast-enhanced chest CT, contrast-enhanced brain magnetic resonance imaging/CT] and radically treated stage III NSCLC, exclusion criteria: second primary within 2 years of NSCLC diagnosis and prior prophylactic cranial irradiation. Primary endpoint was BM development any time during follow-up (FU). CT-based radiomics features (N = 530) were extracted from the primary lung tumour on 18-FDG-PET-CT images, and a list of clinical features (N = 8) was collected. Univariate feature selection based on the area under the curve (AUC) of the receiver operating characteristic was performed to identify relevant features. Generalized linear models were trained using the selected features, and multivariate predictive performance was assessed through the AUC.Results:In total, 219 patients were eligible for analysis. Median FU was 59.4 months for the training cohort and 67.3 months for the validation cohort; 21 (15%) and 17 (22%) patients developed BM in the training and validation cohort, respectively. Two relevant clinical features (age and adenocarcinoma histology) and four relevant radiomics features were identified as predictive. The clinical model yielded the highest AUC value of 0.71 (95% CI: 0.58–0.84), better than radiomics or a combination of clinical parameters and radiomics (both an AUC of 0.62, 95% CIs of 0.47–076 and 0.48–0.76, respectively).Conclusion:CT-based radiomics features of primary NSCLC in the current setup could not improve on a model based on clinical predictors (age and adenocarcinoma histology) of BM development in radically treated stage III NSCLC patients.

Chronic cavitary pulmonary aspergillosis in an infant

A 7-month-old girl was admitted to the Pediatric Intensive Care Unit at West China Second University Hospital (Chengdu, China) with a recurrent cough for over 3 months, aggravated with fever and dyspnoea for 4 days before presentation. Physical examination revealed rough respiratory sounds, with crackles in both lungs. Blood gas analysis showed low concentrations of partial pressure of oxygen (65·4 mm Hg; normal range, 80–100 mm Hg) and increased lactate (3·4 mmol/L; normal range, 1·0–1·7 mmol/L). Screenings for Mycobacterium tuberculosis, Mycoplasma pneumoniae, and other bacteria and viruses in sputum and bronchoalveolar lavage fluid were negative. Serum (1,3)-β-D-glucan and galactomannan testing showed negative results. A chest x-ray showed bilateral pulmonary inflammation and local consolidation (figure A). Contrast-enhanced chest CT showed a large thick-walled cavity in the right lower lobe (figure B). The patient was treated with intravenous cefoperazone (0·35 g every 8 h) and inhaled acetylcysteine (3 mL every 12 h) for 4 days. High-flow nasal cannula oxygen therapy was implemented first to provide respiratory support to the patient. On day 5, the patient developed haemoptysis (5 mL). Her respiratory status progressively deteriorated and endotracheal intubation was required. Although there was no direct experimental evidence of fungal infection, the diagnosis of chronic cavitary pulmonary aspergillosis was suspected, based on the CT findings and clinical symptoms. The patient was treated with antifungal oral voriconazole (0·07 g every 12 h) for 3 months and her clinical and radiographic condition improved. Finally, the diagnosis of chronic cavitary pulmonary aspergillosis was confirmed by positivity of aspergillus-specific IgG assay.

Image quality assessment of pediatric chest and abdomen CT by deep learning reconstruction

BackgroundEfforts to reduce the radiation dose have continued steadily, with new reconstruction techniques. Recently, image denoising algorithms using artificial neural networks, termed deep learning reconstruction (DLR), have been applied to CT image reconstruction to overcome the drawbacks of iterative reconstruction (IR). The purpose of our study was to compare the objective and subjective image quality of DLR and IR on pediatric abdomen and chest CT images.MethodsThis retrospective study included pediatric body CT images from February 2020 to October 2020, performed on 51 patients (34 boys and 17 girls; age 1–18 years). Non-contrast chest CT (n = 16), contrast-enhanced chest CT (n = 12), and contrast-enhanced abdomen CT (n = 23) images were included. Standard 50% adaptive statistical iterative reconstruction V (ASIR-V) images were compared to images with 100% ASIR-V and DLR at medium and high strengths. Attenuation, noise, contrast to noise ratio (CNR), and signal to noise (SNR) measurements were performed. Overall image quality, artifacts, and noise were subjectively assessed by two radiologists using a four-point scale (superior, average, suboptimal, and unacceptable). A phantom scan was performed including the dose range of the clinical images used in our study, and the noise power spectrum (NPS) was calculated. Quantitative and qualitative parameters were compared using repeated-measures analysis of variance (ANOVA) with Bonferroni correction and Wilcoxon signed-rank tests.ResultsDLR had better CNR and SNR than 50% ASIR-V in both pediatric chest and abdomen CT images. When compared with 50% ASIR-V, high strength DLR was associated with noise reduction in non-contrast chest CT (33.0%), contrast-enhanced chest CT (39.6%), and contrast-enhanced abdomen CT (38.7%) with increases in CNR at 149.1%, 105.8%, and 53.1% respectively. The subjective assessment of overall image quality and the noise was also better on DLR images (p < 0.001). However, there was no significant difference in artifacts between reconstruction methods. From NPS analysis, DLR methods showed a pattern of reducing the magnitude of noise while maintaining the texture.ConclusionCompared with 50% ASIR-V, DLR improved pediatric body CT images with significant noise reduction. However, artifacts were not improved by DLR, regardless of strength.

Venous Air Microembolism in Chest CT Angiography: Evidence of Normalization of Deviance Phenomenon.

Purpose This article provides evidence that detection of venous air microbubbles (VAMB) in chest computed tomography angiography (CTA) can be an indicator for “normalization of deviance” phenomenon in CT. Method and Materials Institutional review board-approved retrospective study, with waiver for informed consent. Contrast-enhanced chest CT performed during 6 months were reviewed for presence of VAMB in venous segments visible in chest CT (subclavian, brachiocephalic vein, superior vena cava) and cardiac chambers. VAMB volumes were quantified through a semiautomatic method (MIAlite plugin for OsiriX), using a region of interest (ROI) covering the bubble. With basal results, protocols for correct injection technique were reinforced, and VAMB were estimated again at 1 and 3 months. Six months later, questionnaires were sent to the CT technologists to inquire about their perception of VAMB. Descriptive measures with central distribution and dispersion were performed; statistical significance was considered at p < 0.05. Results A total of 602 chest CTA were analyzed, 332 were women (55.14%), with a median age of 58 (interquartile range [IQR] 44–72) years. Among those, 16.11% (100 cases) presented VAMB. Most were emergency department patients (51.6%), male (50.3%), with a median age of 54 (IQR 26) years. There was no difference on detection of VAMB regarding sex ( p = 0.19), age ( p = 0.46), or referral diagnosis ( p = 0.35). Mean air bubbles volume was 0.2 mL (range 0.01–3.4 mL). After intervention, the number of exams with VAMB dropped to 3.29 % (3/91) ( p < 0.001). On the 6-month query, 50% of the technicians still considered that VMAB is inevitable, and 60% thought that the occurrence is not associated to risk, and therefore, not actionable. Conclusion VAMB are a frequent finding in chest CTA, and being independent from patient-related variables, it is likely due to technical issues such as intravenous access manipulation during the exam. Reduction after reinforcement of proper performance, and certification of a low concern from CT technicians for any risk associated, provides evidence that there is normalization of deviance in this everyday procedure.

Machine Learning-Based CT Radiomics Analysis for Prognostic Prediction in Metastatic Non-Small Cell Lung Cancer Patients With EGFR-T790M Mutation Receiving Third-Generation EGFR-TKI Osimertinib Treatment.

Background and PurposeAs a third-generation EGFR tyrosine kinase inhibitor (TKI), osimertinib is approved for treating advanced non-small cell lung cancer (NSCLC) patients with EGFR-T790M mutation after progression on first- or second-generation EGFR-TKIs such as gefitinib, erlotinib and afatinib. We aim at exploring the feasibility and effectiveness of using radiomic features from chest CT scan to predict the prognosis of metastatic non-small cell lung cancer (NSCLC) patients with EGFR-T790M mutation receiving second-line osimertinib therapy.MethodsContrast-enhanced and unenhanced chest CT images before osimertinib treatment were collected from 201 and 273 metastatic NSCLC patients with EGFR-T790M mutation, respectively. Radiomic features were extracted from the volume of interest. LASSO regression was used to preliminarily evaluate the prognostic values of different radiomic features. We then performed machine learning-based analyses including random forest (RF), support vector machine (SVM), stepwise regression (SR) and LASSO regression with 5-fold cross-validation (CV) to establish the optimal radiomic model for predicting the progression-free survival (PFS) of osimertinib treatment. Finally, a combined clinical-radiomic model was developed and validated using the concordance index (C-index), decision-curve analysis (DCA) and calibration curve analysis.ResultsDisease progression occurred in 174/273 (63.7%) cases. CT morphological features had no ability in predicting patients’ prognosis in osimertinib treatment. Univariate COX regression followed by LASSO regression analyses identified 23 and 6 radiomic features from the contrast-enhanced and unenhanced CT with prognostic value, respectively. The 23 contrast-enhanced radiomic features were further used to construct radiomic models using different machine learning strategies. Radiomic model built by SR exhibited superior predictive accuracy than RF, SVR or LASSO model (mean C-index of the 5-fold CV: 0.660 vs. 0.560 vs. 0.598 vs. 0.590). Adding the SR radiomic model to the clinical model could remarkably strengthen the C-index of the latter from 0.672 to 0.755. DCA and calibration curve analyses also demonstrated good performance of the combined clinical-radiomic model.ConclusionsRadiomic features extracted from the contrast-enhanced chest CT could be used to evaluate metastatic NSCLC patients’ prognosis in osimertinib treatment. Prognostic models combing both radiomic features and clinical factors had a great performance in predicting patients’ outcomes.

Thrombosis of the pulmonary arteries branches as a complication of COVID-19 pneumonia (a case report)

The article presents a rare case of thrombosis of the pulmonary arteries branches, which developed in a patient two months after infection with the SARS-CoV-2 virus, that caused bilateral polysegmental pneumonia. The thrombosis was suspected because of a high plasma D-dimer level. Contrast-enhanced chest CT was performed to make a definitive diagnosis. The absence of blood clots in the veins of the lower extremities and pelvis allowed us to conclude that the patient did not have thromboembolism, but rather a pulmonary thrombosis in situ. Such possible causes of venousthromboembolic complications as tumors, systemic diseases of the connective tissue, and antiphospholipid syndrome were excluded based on negative tests for tumor and autoimmune diseases markers. The long-stay in the hospital was associated with the inability of the patient to maintain the normal level of blood oxygen saturation independently due to the large area of the lung damage associated with COVID-19 pneumonia and ischemia caused by thrombosis of the branches of the pulmonary arteries.

Cumulative lifetime attributed risks for patients subjected to contrast enhanced chest CT examinations

The main aim here is to estimate the cumulative lifetime attributed risks (LARs) for patients subjected to contrast-enhanced chest computer tomography (CECCT). Further, the impact of the contrast media on the organs doses (ODs), effective dose (E*), LARs and scan acquisition parameters were assessed. The ODs, and E* of the CECCT scan for 17 patients were obtained without-contrast (S1) and with-contrast (S2) using the commercial software CT-EXPO. The LARs were calculated using age- and- gender specific risk factors. The relationship between the CT dose metrics (CTDIvol and DLP), mAs and scan-length were established using the Pearson's correlation coefficient-test. The Wilcoxon pairs t-test was used to determine the statistical differences between all quantities in both chest CT series. No significant differences were found between the CT scan series S1 and S2 in all the determined quantities including: CTDIvol (p = 0.772), DLP (p = 0.092), mAs (p = 0.450) and E* (p = 0.111). The ODs were higher with contrast media, particularly stomach and bone marrow. The LARs of developing lung cancer were particularly high for the females in their 60's about 1 in 3000 (or 0.03%). The highest LARs of all organ cancers reported were higher in females comparing to males 0.03% comparing to 0.01%). Female patients are at higher risk of developing cancers than males while undergoing CECCT wherein contrast media can contribute to increasing organ doses.

P54-5 Metastatic spinal cord compression caused by recurrent carcinoma ex pleomorphic adenoma of the parotid gland

Metastatic spinal cord compression (MSCC) is one of the serious sequelae of malignancy. Due to its rapid progression of neurological dysfunction, it is considered an oncologic emergency that demands prompt diagnosis and management. Most cases of MSCC occur from breast, lung, and prostate primaries. MSCC secondary to carcinoma ex pleomorphic adenoma of the parotid gland is rare. We report a 32-year-old Filipino ex-smoker male complaining of two-week history of progressive paresis associated with urinary and bowel retention. He had a history of total unilateral neck dissection for CEPA of the parotid gland last year followed by systemic chemotherapy with CAP regimen (cyclophosphamide 500 mg/m2, doxorubicin 50 mg/m2, cisplatin 50 mg/m2) for four cycles. Due to COVID-19 pandemic, he lost to follow-up. On examination, physical examination revealed an 8 x 8 cm recurrent fungating mass at the right post-auricular area with extension to the buccal cavity. Motor strength was 0/5 for both lower extremities with associated hyporeflexia. Sensation to pain, temperature, and proprioception was noted to be absent at the level of the umbilicus and below. Contrast-enhanced chest and abdominopelvic CT scan revealed mixed lytic-sclerotic osseous foci at the thoracic and lumbar vertebral bodies, multiple intramuscular soft tissue foci, as well as bilateral lung and pleural-based nodules. Whole body bone scan showed multiple bone metastases. Radiation therapy to the spine was given at a total of 30 cGy in 10 fractions. Intravenous dexamethasone and bone resorption therapy were given. Palliative chemotherapy (paclitaxel 200 mg/m2, carboplatin AUC 6 mg·min/mL) was subsequently started. Although relatively rare, MSCC should be taken into consideration when a patient with history of CEPA presents with paraplegia. Prompt diagnosis and management are particularly important in preventing permanent neurological damage.

Usefulness of 18F-FDG PET/CT in treatment-naive patients with thymic squamous cell carcinoma.

Thymic squamous cell carcinoma (TSCC) is very rare. This study aims to investigate the clinical utility of fluorine-18-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) in treatment-naive patients with TSCC. The tumor metabolic parameters of 18F-FDG PET/CT, including maximum standard uptake value (SUVmax), metabolic tumor volume of primary lesion (MTV-P) and combination of primary lesion and metastases (MTV-C), and total lesion glycolysis of primary lesion (TLG-P) and combination of primary lesion and metastases (TLG-C) were collected. Age, sex, smoking, serum tumor markers, tumor size, Masaoka-Koga stage, TNM stage, contrast-enhanced CT scan, and tumor immunity were also reviewed. Moreover, progression-free survival (PFS) and overall survival (OS) of these patients were analyzed. Forty-two treatment-naive patients with TSCC were enrolled in this study. All primary tumors were FDG-avid with the average SUVmax of 10.0 ± 4.5 (range, 1.5-20.4). Higher SUVmax, MTV-C, and TLG-C were observed in advanced Masaoka-Koga stage than early stage, and higher SUVmax was found in advanced TNM stage than early stage. Next, 36 out of 42 patients performed chest contrast-enhanced CT scan, which showed SUVmax associated with the enhancement degree of CT. Moreover, 27 out of 42 lesions were assessed tumor immunity, and the detective rates of PD-L1, PD-1, CD4, CD8, and Foxp3 were 59.3%, 37.0%, 59.3%, 100%, and 77.8%, respectively. Higher SUVmax was observed in lesions with lower CD4-positive tumor-infiltrating lymphocytes. Furthermore, 12- and 24-month PFS and OS rates were 62.0% vs 32.8% and 84.5% vs 68.9%, respectively. Multivariate Cox regression analysis showed that only MTV-C was an independent predictor of PFS. 18F-FDG PET/CT is useful in evaluating tumor staging, assessing CT enhancement degree, and detecting tumor immunity of TSCC before treatment. 18F-FDG PET/CT could also be a promising tool to provide prognostic information for treatment-naive patients with TSCC.

Consolidated lung on contrast-enhanced chest CT: the use of spectral-detector computed tomography parameters in differentiating atelectasis and pneumonia

ObjectivesTo investigate the value of spectral-detector computed tomography (SDCT) parameters for the quantitative differentiation between atelectasis and pneumonia on contrast-enhanced chest CT. Material and methodsSixty-three patients, 22 clinically diagnosed with pneumonia and 41 with atelectasis, underwent contrast-enhanced SDCT scans during the venous phase. CT numbers (Hounsfield Units [HU]) were measured on conventional reconstructions (CON120kVp) and the iodine concentration (Ciodine, [mg/ml]), and effective atomic number (Zeff) on spectral reconstructions, using region-of-interest (ROI) analysis. Receiver operating characteristics (ROC) and contrast-to-noise ratios (CNRs) were calculated to assess each reconstruction's potential to differentiate between atelectasis and pneumonia. ResultsOn contrast-enhanced SDCT, the difference between atelectasis and pneumonia was significant on CON120kVp, Ciodine, and Zeff images (p < 0.001). On CON120kVp images, a threshold of 81 HU achieved a sensitivity of 93 % and a specificity of 95 % for identifying pneumonia, while Ciodine and Zeff images reached the same sensitivity but lower specificities of 85 % and 83 %. CON120kVp images showed significantly higher CNRs between normal lung and atelectasis or pneumonia with 30.63 and 27.69 compared to Ciodine images with 3.54 and 1.27 and Zeff images with 4.22 and 7.63 (p < 0.001). None of the parameters could differentiate atelectasis and pneumonia without contrast media. ConclusionsContrast-enhanced SDCT can differentiate atelectasis and pneumonia based on the spectral parameters Ciodine, and Zeff. However, they had no added value compared to CT number measurement on CON120kVp images. Furthermore, contrast media is still needed for a differentiation based on quantitative SDCT parameters.

Mediastinal Tuberculoma Mimicking Malignant Cardiac Tumor: A Case Report

Background: The clinical manifestations of cardiac masses are diverse and lack specificity. Here we report a cardiac mass detected by transthoracic echocardiography. Multimodality imaging and pathological findings after the operation confirmed the mass as mediastinal tuberculoma. Case presentation: A 45-year-old male patient was admitted to our hospital reporting chest tightness, weight loss, and dyspnea for 3 months after exercise. Transthoracic echocardiography showed that there were a large number of pericardial effusions and a soft tissue mass measuring 7.7 cm × 4.5 cm in the upper mediastinum, which oppressed the right pulmonary artery and accelerated the blood flow of the left pulmonary artery. Contrast-enhanced ultrasonography showed degenerative inhomogeneous high enhancement of and an unclear boundary in the mass. Contrast-enhanced chest CT revealed punctate and patchy calcification in and uneven enhancement of the mass and the lymph nodes around the aortic arch. The mass was diagnosed as a malignant mediastinal tumor. Pathological analysis of the mass revealed chronic granulomatous tuberculosis. The symptoms abated significantly after antituberculosis treatment. The patient remained asymptomatic during follow-up. Conclusion: This report presents a rare case of mediastinal tuberculoma mimicking a malignant cardiac tumor. Multimodality imaging should be incorporated for differentiation of cardiac masses.

Un suono che inganna: quando sospettare il doppio arco aortico

The article describes a case of a 10-month-old male infant presenting with respiratory distress, laryngotracheitis and double aortic arch (DAA). Tracheal compression by vascular structures in infants is uncommon and may be masked by nonspecific respiratory symptoms. DAA is the most common vascular ring. Doctors should think about a congenital vascular ring due to DAA in children with repeated episodes of laryngitis, hissing breath, cough and dyspnoea when other common aetiologies are excluded. A precise diagnosis can be made through the contrast-enhanced chest CT scan.

Accelerated Pulmonary Ossification as a Sequela of SARS-CoV-2 Pneumonia

HomeRadiology: Cardiothoracic ImagingVol. 3, No. 2 PreviousNext Images in Cardiothoracic ImagingFree AccessPulmonary ImagingAccelerated Pulmonary Ossification as a Sequela of SARS-CoV-2 PneumoniaBeatriz García Moreno , Guadalupe Buitrago Weiland, María Luisa Sánchez Alegre, Jhon Edilberto Vanegas RodríguezBeatriz García Moreno , Guadalupe Buitrago Weiland, María Luisa Sánchez Alegre, Jhon Edilberto Vanegas RodríguezAuthor AffiliationsFrom the Department of Radiology, Hospital General Universitario Gregorio Marañón, Doctor Esquerdo 46, 28007 Madrid, Spain.Address correspondence to B.G.M. (e-mail: [email protected]).Beatriz García Moreno Guadalupe Buitrago WeilandMaría Luisa Sánchez AlegreJhon Edilberto Vanegas RodríguezPublished Online:Apr 1 2021https://doi.org/10.1148/ryct.2021200598MoreSectionsPDF ToolsImage ViewerAdd to favoritesCiteTrack Citations ShareShare onFacebookTwitterLinked In This case illustrates extensive dendriform lung ossification manifesting after SARS-CoV-2 pneumonia. Organizing pneumonia is an established CT finding in subacute SARS-CoV-2 infection (1,2), usually manifesting as bilateral consolidations (80%–95% of the cases) in a predominantly peripheral or peribronchial distribution, sometimes sparing the subpleural regions (3). Histologic analysis reveals plugs of fibroblastic tissue filling bronchioles and airspaces (3,4), which usually disappear after steroid treatment. However, fibromyxoid tissue may progress to fibrosis, a condition recently described as “cicatricial organizing pneumonia (4–6).” Some of these cases may evolve with pathologic osseous metaplasia, seen on imaging as nodular and branching calcifications, described as dendriform pulmonary ossification (5). This finding is usually seen in patients with underlying lung fibrosis, most commonly in usual interstitial pneumonia, and it is considered as a marker of chronicity and severity of lung fibrosis (7).Differential diagnoses include dystrophic calcifications, metastatic calcifications, and pulmonary alveolar microlithiasis. Dystrophic calcifications occur in diseased lung, in the settings of granulomatous infections, sarcoidosis, occupational lung diseases, and metabolic diseases (eg, as amyloidosis). Metastatic calcifications occur in normal lung due to hypercalcemia secondary to end-stage kidney disease. The differential diagnosis also includes nodular ossification seen in patients with chronic venous lung congestion (8). Normal renal function, phosphate calcium homeostasis, and the absence of any relevant past medical history or concomitant diseases excluded other causes of lung calcification/ossification in this case (Figs 1, 2).Figure 1: Images in a 49-year-old man who presented to the emergency department with SARS-CoV2 infection. A and B, Non–contrast-enhanced chest CT scans obtained 1 month after the onset of symptoms show multifocal peribronchovascular and peripheral consolidation, relatively sparing the subpleural region, consistent with organizing pneumonia. Follow-up chest CT was performed 6 months after steroid treatment. C, Axial and, D, coronal CT images show multiple micronodular calcifications within faint ground-glass opacities.Figure 1:Download as PowerPointOpen in Image Viewer Figure 2: Bone window images in same patient. Comparison between A, initial and, B, follow-up CT on axial maximum intensity projection images shows interval development of micronodular and branching calcifications, confirmed on C, coronal and, D, magnified axial views. Follow-up lung function testing revealed decreased diffusion capacity.Figure 2:Download as PowerPointOpen in Image Viewer Disclosures of Conflicts of Interest: B.G.M. disclosed no relevant relationships. G.B.W. disclosed no relevant relationships. M.L.S.A. disclosed no relevant relationships. J.E.V.R. disclosed no relevant relationships.Keywords: CT, Lung, Thorax Authors declared no funding for this work.

Angioplasty for the treatment of left brachiocephalic vein aneurysm: a case report

BackgroundBrachiocephalic vein aneurysm is a rare vascular malformation, which is often reported in case reports. At present it has attracted much attention due to the serious complications, such as vein aneurysm rupture, pulmonary embolism, venous thrombosis, etc. We report a case of left brachiocephalic vein aneurysm with compression symptoms.Case presentationa 52-year-old male who was admitted to our hospital with irritating cough for more than 1 month. Chest contrast-enhanced CT showed a localized expansion of 5.2 cm in diameter of the left brachiocephalic vein in the anterior mediastinum. The patient received venous angioplasty with brachiocephalic vein aneurysm resection, and the postoperative recovery was well.ConclusionSurgical operation is an effecive treatment method for brachiocephalic vein aneurysm, but it is still necessary to choose the appropriate way according to the type, size, location, lesion scope and complications of the vein aneurysm.

Magnetic resonance imaging for congenital lung malformations

Congenital lung malformations are most often identified on prenatal US screening. Fetal MRI is often performed to further evaluate these lesions. Although some of these lesions might cause prenatal or early postnatal symptoms that require urgent management, the majority are asymptomatic at birth and might be subtle or invisible on chest radiographs. Postnatal imaging is frequently deferred until 3–6 months of age, when surgery or long-term conservative management is contemplated. High-quality imaging and interpretation is needed to assist with appropriate decision-making. Contrast-enhanced chest CT, typically with angiographic technique, has been the usual postnatal imaging choice. In this review, the author discusses and illustrates the indications and use of postnatal MR imaging for bronchopulmonary malformations as well as some differential diagnoses and the advantages and disadvantages of MR versus CT.

Deep learning reconstruction for contrast-enhanced CT of the upper abdomen: similar image quality with lower radiation dose in direct comparison with iterative reconstruction.

To evaluate the effect of a commercial deep learning algorithm on the image quality of chest CT, focusing on the upper abdomen. One hundred consecutive patients who simultaneously underwent contrast-enhanced chest and abdominal CT were collected. The radiation dose was optimized for each scan (mean CTDIvol: chest CT, 3.19 ± 1.53 mGy; abdominal CT, 7.10 ± 1.88 mGy). Three image sets were collected: chest CT reconstructed with an adaptive statistical iterative reconstruction (ASiR-CHT; 50% blending), chest CT with a deep learning algorithm (DLIR-CHT), and abdominal CT with ASiR (ASiR-ABD; 40% blending). Afterwards, the images covering the upper abdomen were extracted, and image noise, the signal-to-noise ratio (SNR), and the contrast-to-noise ratio (CNR) were measured. For subjective evaluation, three radiologists independently assessed noise, spatial resolution, presence of artifacts, and overall image quality. Additionally, readers selected the most preferable reconstruction technique among three image sets for each case. The average measured noise for DLIR-CHT, ASiR-CHT, and ASiR-ABD was 8.01 ± 2.81, 14.8 ± 2.56, and 12.3 ± 2.28, respectively (p < .001). Deep learning-based image reconstruction (DLIR) also showed the best SNR and CNR (p < .001). However, in the subjective analysis, ASiR-ABD showed less subjective noise than DLIR (2.94 ± 0.23 vs. 2.87 ± 0.26; p < .001), while DLIR showed better spatial resolution (2.60 ± 0.34 vs. 2.44 ± 0.31; p = .02). ASiR-ABD showed a better overall image quality (p = .001), but two of the three readers preferred DLIR more frequently. With < 50% of the radiation dose, DLIR chest CT showed comparable image quality in the upper abdomen to that of dedicated abdominal CT and was preferred by most readers. • With < 50% radiation dose, a deep learning algorithm applied to contrast-enhanced chest CT exhibited better image noise and signal-to-noise ratio than standard abdominal CT with the ASiR technique. • Pooled readers mostly preferred deep learning algorithm-reconstructed contrast-enhanced chest CT reconstructed using a standard ASiR-reconstructed abdominal CT. • Reconstruction algorithm-induced distortion artifacts were more frequently observed on deep learning algorithm-reconstructed images, but diagnostic difficulty was reported in only 0.3% of cases.