Routine Chest Chest Computed Tomography Research Articles

Considerations for multidisciplinary management of synchronous primary breast cancer and primary lung cancer - Analysis of thirty-one patients.

The simultaneous (synchronous) presence of primary breast cancer and primary lung cancer diagnosed in a single individual is not an uncommon phenomenon. However, reference data for treatment strategy is scarce and "chaotic". In the present study we discuss the management strategy for this group of patients. We retrospectively reviewed patients in the primary breast cancer database of the Breast Center and the primary lung cancer database of the Thoracic Surgery Department I of Peking University Cancer Hospital. Patients with synchronous primary breast cancer and primary lung cancer who underwent surgery between December 2010 and December 2023 were included in the study. The sequence of outpatient visits, recommendations of multidisciplinary teams, perioperative treatment, and surgical procedures were reviewed. Meanwhile, survival analysis based on propensity score matching with 1:1 ratio was performed between the 31 patients and those with lung cancer only during the same period. A total of 31 patients with synchronous primary breast cancer and primary lung cancer were identified; all of the patients were women. The average age was 61 years. A total of 24 of the patients had visited the breast center first, and routine chest computed tomography (CT) showed evidence of primary lung cancer. The other seven patients had visited the thoracic surgery clinic first, and routine positron emission tomography (PET)-CT revealed the coexistence of primary breast cancer. All the patients had multidisciplinary team consultations, after which 20 patients were recommended to have preoperative treatment for breast cancer, two patients were recommended to have preoperative treatment for lung cancer, and nine patients were recommended to undergo surgery directly. After surgery, 23 patients received postoperative adjuvant treatment for breast cancer, and no patients needed postoperative adjuvant treatment for lung cancer. Survival analysis showed that there was no significant difference between the 31 patients and those with lung cancer only. Routine chest CT is needed for breast cancer patients before surgery, and PET-CT is required for the accurate staging of lung cancer patients. A multidisciplinary expert team should manage synchronous primary breast cancer and primary lung cancer. Emphasis should be placed on patients who need preoperative treatment before surgery. Particularly, for patients who need preoperative chemotherapy, a regimen should be chosen that balances the treatment of lung cancer and breast cancer.

Paediatric cancer risks associated with chest computed tomography (CT) scans: comparison of routine chest and COVID-19 diagnosis CT protocols

The aim of this study is to compare the radiation dose and cancer incidence risk associated with two chest Computed Tomography (CT) protocols: routine chest CT (RC-CT) and COVID-19 Diagnosis CT protocol (CD-CT). The study included 254 pediatric patients divided into three age groups: G1 (<5), G2 (5–<10), and G3 (10–15). The effective diameter, volumetric CT dose index (CTDIvol), dose length product (DLP), size specific dose estimate (SSDE), organ doses, and cancer incidence risk were calculated for the two protocols. Organ doses (mSv) and effective dose (mSv) were estimated using the National Cancer Institute dosimetry system for CT (NCICT) software. Estimation of cancer incidence risks were conducted according to the Biological Effects of Ionizing Radiation (BEIR) VII report. The oldest group (G3) in two protocols exhibited the greatest values for CTDIvol, DLP, effective dose and SSDE. The results showed that CD-CT protocol resulted in statistically significant (p < 0.05) lower organ doses and cancer incidence risk. The cancer incidence risk for both protocols did not exceed the reference levels reported in literature surveys on pediatric CT chest radiation dose for all age groups. It can be concluded that the choice of CT protocol can significantly impact the radiation dose received by pediatric patients during CT imaging, highlighting the importance of carefully selecting the appropriate protocol to minimize radiation exposure.

Artificial Intelligence-Based Emphysema Quantification in Routine Chest Computed Tomography: Correlation With Spirometry and Visual Emphysema Grading.

The aim of the study is to assess the correlation between artificial intelligence (AI)-based low attenuation volume percentage (LAV%) with forced expiratory volume in the first second to forced vital capacity (FEV1/FVC) and visual emphysema grades in routine chest computed tomography (CT). Furthermore, optimal LAV% cutoff values for predicting a FEV1/FVC < 70% or moderate to more extensive visual emphysema grades were calculated. In a retrospective study of 298 consecutive patients who underwent routine chest CT and spirometry examinations, LAV% was quantified using an AI-based software with a threshold < -950 HU. The FEV1/FVC was derived from spirometry, with FEV1/FVC < 70% indicating airway obstruction. The mean time interval of CT from spirometry was 3.87 ± 4.78 days. Severity of emphysema was visually graded by an experienced chest radiologist using an established 5-grade ordinal scale (Fleischner Society classification system). Spearman correlation coefficient between LAV% and FEV1/FVC was calculated. Receiver operating characteristic determined the optimal LAV% cutoff values for predicting a FEV1/FVC < 70% or a visual emphysema grade of moderate or higher (Fleischner grade 3-5). Significant correlation between LAV% and FEV1/FVC was found (ϱ = -0.477, P < 0.001). Increasing LAV% corresponded to higher visual emphysema grades. For patients with absent visual emphysema, mean LAV% was 2.98 ± 3.30, for patients with trace emphysema 3.22 ± 2.75, for patients with mild emphysema 3.90 ± 3.33, for patients with moderate emphysema 6.41 ± 3.46, for patients with confluent emphysema 9.02 ± 5.45, and for patients with destructive emphysema 16.90 ± 8.19. Optimal LAV% cutoff value for predicting a FEV1/FVC < 70 was 6.1 (area under the curve = 0.764, sensitivity = 0.773, specificity = 0.665), while for predicting a visual emphysema grade of moderate or higher, it was 4.7 (area under the curve = 0.802, sensitivity = 0.766, specificity = 0.742). Furthermore, correlation between visual emphysema grading and FEV1/FVC was found. In patients with FEV1/FVC < 70% a high proportion of subjects had emphysema grade 3 (moderate) or higher, whereas in patients with FEV1/FVC ≥ 70%, a larger proportion had emphysema grade 3 (moderate) or lower. The sensitivity for visual emphysema grading predicting a FEV1/FVC < 70% was 56.3% with an optimal cutoff point at a visual grade of 4 (confluent), demonstrating a lower sensitivity compared with LAV% (77.3%). A significant correlation between AI-based LAV% and FEV1/FVC as well as visual CT emphysema grades can be found in routine chest CT suggesting that AI-based LAV% measurement might be integrated as an add-on functional parameter in the evaluation of chest CT in the future.

Feasibility of using chest computed tomography (CT) imaging at the first lumbar vertebra (L1) level to assess skeletal muscle mass: a retrospective study

Background Skeletal muscle mass is an essential parameter for diagnosing sarcopenia. The gold standard for assessing skeletal muscle mass is using computed tomography (CT) to measure skeletal muscle area at the third lumbar vertebra (L3) level. This study aims to investigate whether skeletal muscle mass could be evaluated at the first lumbar vertebra (L1) level using images obtained from routine chest CT scans. Methods Skeletal muscle index (SMI, cm2/m2) and skeletal muscle density (SMD, HU) are commonly used to measure relative muscle mass and the degree of fat infiltration. This study used CT images at the L1 level to measure the skeletal muscle area (SMA, cm2) in 815 subjects from the health examination center. Linear regression analysis was used to explore the association between L1 and L3 measurements. The receiver operating characteristic (ROC) analysis was used to assess the predictive performance of L1 SMI for sarcopenia. The sex-specific cut-off values for low skeletal muscle mass in patients under the age of 60 were determined using the following formula: “mean − 1.28 × standard deviation.” A multivariate linear regression model was established. Results A significantly higher SMI at the L1 level was found in males than in females (43.88 ± 6.33 cm2/m2 vs 33.68 ± 5.03 cm2/m2; P &lt; 0.001). There were strong correlations between measures at the L1 and L3 levels in both the total subject and sex-specific analyses. A negative association was found between age and L3 SMI in males (r = −0.231, P = 0.038). Both body mass index (BMI) and body surface area (BSA) were positively associated with L1 SMI in both males and females. A multivariate analysis was used to establish a prediction rule to predict SMI at the L3 level. The assessment of consistency and interchangeability between predicted and actual SMI at the L3 level yielded moderately good results. Considering the significant differences observed between male and female participants, the sex-specific cut-off values of the L1 SMI for defining low skeletal muscle mass were 36.52 cm2/m2 in males and 27.29 cm2/m2 in females. Conclusions Based on a population from central China, the correlated indicators obtained at the L1 level from routine chest CT scans may serve as effective surrogate markers for those at the L3 level in assessing overall skeletal muscle mass.

Coronary artery calcium assessment on routine non-gated chest CT as a gatekeeper for additional imaging in patients with stable chest pain

Abstract Aims In Coronary Artery Disease (CAD), currently applied risk assessment methods often overestimate patients’ risk of obstructive CAD. To enhance and patient-tailor risk estimation, assessment of Coronary Artery Calcium (CAC) can be applied. In ∼10% of patients presenting with stable chest pain a non-gated chest computed tomography (CT) has been previously performed, suitable for CAC assessment. This study is the first to investigate the clinical value of CAC assessment on non-gated chest CT for risk assessment of obstructive CAD. Purpose This study aims to point out the clinical utility of visual CAC assessment for enhancing risk assessment and avoid unnecessary additional imaging in patients presenting with stable chest pain. Methods For this study, all patients referred for coronary CT angiography (CCTA), in whom a prior non-gated chest CT was performed, were included. To assess the extent of patients’ CAC, an ordinal score was applied. CAD was assessed on CCTA and obstructive CAD was defined as stenosis of ≥70%. Patients were stratified in to groups according to CAC severity, pre-test probability and number of risk factors. Percentages of patients with obstructive CAD were compared between the groups. Results A total of 181 patients of 30-88 years old were included. The percentage of obstructive CAD was significantly different between de CAC groups (p&amp;lt;0.01). The absence of CAC ruled out obstructive CAD with 100% certainty, irrespective of sex, pre-test probability, type of complaint and number of risk factors. Additionally, a mild CAC score ruled out obstructive CAD in patients with low – intermediate PTP or non-anginal complaints, with 100% certainty. Conclusion CAC assessment on non-gated chest CT can safely rule out obstructive CAD in patients presenting with stable chest pain and can therefore function as a radiation-free and cost-free gatekeeper for additional imaging.CCTA results for CAC severityDecisiontree patients with chest pain

Added value of an artificial intelligence algorithm in reducing the number of missed incidental acute pulmonary embolism in routine portal venous phase chest CT.

The purpose of this study was to evaluate the incremental value of artificial intelligence (AI) compared to the diagnostic accuracy of radiologists alone in detecting incidental acute pulmonary embolism (PE) on routine portal venous contrast-enhanced chest computed tomography (CT). CTs of 3089 consecutive patients referred to the radiology department for a routine contrast-enhanced chest CT between 27-5-2020 and 31-12-2020, were retrospectively analysed by a CE-certified and FDA-approved AI algorithm. The diagnostic performance of the AI was compared to the initial report. To determine the reference standard, discordant findings were independently evaluated by two readers. In case of disagreement, another experienced cardiothoracic radiologist with knowledge of the initial report and the AI output adjudicated. The prevalence of acute incidental PE in the reference standard was 2.2% (67 of 3089 patients). In 25 cases, AI detected initially unreported PE. This included three cases concerning central/lobar PE. Sensitivity of the AI algorithm was significantly higher than the outcome of the initial report (respectively 95.5% vs. 62.7%, p < 0.001), whereas specificity was very high for both (respectively 99.6% vs 99.9%, p = 0.012). The AI algorithm only showed a slightly higher amount of false-positive findings (11 vs. 2), resulting in a significantly lower PPV (85.3% vs. 95.5%, p = 0.047). The AI algorithm showed high diagnostic accuracy in diagnosing incidental PE, detecting an additional 25 cases of initially unreported PE, accounting for 37.3% of all positive cases. Radiologist support from AI algorithms in daily practice can prevent missed incidental acute PE on routine chest CT, without a high burden of false-positive cases. • Incidental pulmonary embolism is often missed by radiologists in non-diagnostic scans with suboptimal contrast opacification within the pulmonary trunk. • An artificial intelligence algorithm showed higher sensitivity detecting incidental pulmonary embolism on routine portal venous chest CT compared to the initial report. • Implementation of artificial intelligence support in routine daily practice will reduce the number of missed incidental pulmonary embolism.

Opportunistic screening at chest computed tomography: literature review of cardiovascular significance of incidental findings.

Several incidental cardiovascular findings are present in a routine chest computed tomography (CT) scan, many of which do not make it to the final radiology report. However, these findings have important clinical implications, particularly providing prognosis and risk-stratification for future cardiovascular events. The purpose of this article is to review the literature on these incidental cardiovascular findings in a routine chest CT and inform the radiologist on their clinical relevance. A time unlimited review of PubMed and Web of Science was performed by using relevant keywords. Articles in English that involved adults were included. Coronary artery calcification (CAC) is the most common incidental cardiac finding detected in a routine chest CT and is a significant predictor of cardiovascular events. Noncoronary vascular calcifications in chest CT include aortic valve, mitral annulus, and thoracic aortic calcifications (TAC). Among these, aortic valve calcification (AVC) has the strongest association with coronary artery disease and cardiovascular events. Additional cardiac findings such as myocardial scar and left ventricular size and noncardiac findings such as thoracic fat, bone density, hepatic steatosis, and breast artery calcifications can also help in risk stratification and patient management. The radiologist interpreting a routine chest CT should be cognizant of the incidental cardiovascular findings, which helps in the diagnosis and risk-stratification of cardiovascular disease. This will guide appropriate referral and management.

Opportunistic Screening for Atrial Fibrillation on Routine Chest Computed Tomography.

Quantitative biomarkers from chest computed tomography (CT) can facilitate the incidental detection of important diseases. Atrial fibrillation (AFib) substantially increases the risk for comorbid conditions including stroke. This study investigated the relationship between AFib status and left atrial enlargement (LAE) on CT. A total of 500 consecutive patients who had undergone nongated chest CTs were included, and left atrium maximal axial cross-sectional area (LA-MACSA), left atrium anterior-posterior dimension (LA-AP), and vertebral body cross-sectional area (VB-Area) were measured. Height, weight, age, sex, and diagnosis of AFib were obtained from the medical record. Parametric statistical analyses and receiver operating characteristic curves were performed. Machine learning classifiers were run with clinical risk factors and LA measurements to predict patients with AFib. Eighty-five patients with a diagnosis of AFib were identified. Mean LA-MACSA and LA-AP were significantly larger in patients with AFib than in patients without AFib (28.63 vs. 20.53cm 2 , P <0.000001; 4.34 vs. 3.5cm, P <0.000001, respectively), both with area under the curves (AUCs) of 0.73. Multivariable logistic regression analysis including age, sex, and VB-Area with LA-MACSA improved the AUC for predicting AFib (AUC=0.77). An LA-MACSA threshold of 30cm 2 demonstrated high specificity for AFib diagnosis at 92% and sensitivity of 48%, and LA-AP threshold at 4.5cm demonstrated 90% specificity and 42% sensitivity. A Bayesian machine learning model using age, sex, height, body surface area, and LA-MACSA predicted AFib with an AUC of 0.743. LA-MACSA or LA-AP can be rapidly measured from routine chest CT, and when >30 cm 2 and >4.5cm, respectively, are specific indicators to predict patients at increased risk for AFib.

Association between lung opacities and visceral fat in COVID-19 patients.

To assess the relationship between the amount of the epigastric visceral fat area and the severity of pneumonia in the course of COVID-19 using chest computed tomography (CT) examinations. 177 patients (54 female), with COVID-19 infection were included. A routine chest CT was performed to assess the severity of pneumonia. The affected lung tissue as well as semi-quantitative scales such as the Chest CT Score and Total Opacity Score were calculated using SyngoVia VB30A CT Pneumonia Analysis software. The epigastric region area of visceral fat (L1) was also determined. The mean value of the visceral adipose tissue area was 196.23 ± 101.36 cm2. The area of adipose tissue significantly correlated with the percentage of the affected lung tissue (r = 0.1476; p = 0.050), the Chest CT Score (r = 0.2086; p = 0.005), and the Total Opacity Score (r = 0.1744; p = 0.200). The mean area of adipose tissue in the age group ≥ 65 years was 216.13 ± 105.19 cm2, while in the group < 65 years, it was 169.18 ± 89.69 cm2. This difference was statistically significant (p = 0.002). The study showed a relationship between the area of visceral adipose tissue and the degree of lung inflammation in COVID-19 disease in patients under 65 years of age.

Abstract 13954: Cardiovascular Imaging Markers and Atherosclerotic Cardiovascular Disease in Lung Cancer Survivors

Introduction: Lung cancer survivors have heightened risk of atherosclerotic cardiovascular disease (ASCVD) due to shared risk factors. Chest computed tomography (CT) is routinely performed for cancer staging and radiotherapy (RT) planning. However, the extent of coronary artery calcium (CAC) and thoracic aortic calcium (TAC) is not routinely evaluated for ASCVD risk assessment. Methods: We evaluated the extent of CAC and TAC from chest CTs obtained for routine care prior to RT in a cohort of lung cancer survivors from 2007 to 2021 at a single academic health system that serves a large multiracial community. The demographics, baseline cardiovascular risk factors and baseline ASCVD (the composite of myocardial infarction, cerebrovascular disease, or peripheral arterial disease) were compared between survivors with and without CAC or TAC. The primary end point was incident ASCVD. Results: The cohort studied 603 subjects, including 19% non-Hispanic Whites, 33% non-Hispanic Blacks and 32% Hispanics. Mean age was 65±11 years, with 45% women. CAC was present in 72% of subjects and TAC in 85%. Individuals with CAC had higher prevalence of hypertension (75% vs 57%, p&lt;0.001), diabetes (41% vs 20%, p&lt;0.001) and hyperlipidemia (49% vs 26%, p&lt;0.001). Survivors with CAC had a higher prevalence of baseline ASCVD (33% vs 18%, p=0.001). Survivors with TAC yielded similar findings. In individuals without prior ASCVD, 10-year ASCVD risk score was higher in survivors with CAC (20%±21% vs 12%±13%, p=0.009) or with TAC (19%±20% vs 8%±8%, p=0.007). In a median follow-up time of 15 months, the new development of ASCVD appeared higher in survivors with CAC (23% vs 14%, p=0.04, Figure A) and with TAC (22% vs 8%, p=0.01, Figure B). Conclusions: In a large cohort of multiracial lung cancer survivors, presence of CAC or TAC based on routine chest CT at baseline is associated with a higher burden of ASCVD risk and predicts a higher risk of the new development of ASCVD during follow- up.

Using Routine Chest Computed Tomography to Diagnose Pulmonary Embolism.

This study investigated the use of routine contrast-enhanced chest computed tomography (CT) to diagnose unsuspected pulmonary embolism (PE). All adult routine contrast-enhanced chest CTs performed at Montefiore in 2018 were included. Pulmonary artery enhancement was measured by placing regions of interest in the pulmonary vasculature. Adequate enhancement was defined as 200 Hounsfield units (HU) or greater. Presence or absence of PE was noted. Descriptive statistics and logistic regression analysis were performed. A total of 3164 CTs were evaluated (55.8% women; mean age, 63.2 years). Main pulmonary enhancement was highly correlated with peripheral enhancement. Of all cases, 28.7% (907 of 3164) reached the 200 HU threshold. Greater enhancement was associated with female sex, older age, outpatients, and contrast amount administered. Pulmonary embolism-positive cases comprised 1.8% (58 of 3164) of total cases. Furthermore, 39.7% (23 of 58) of PE-positive cases reached the 200 HU threshold. Over one quarter of routine contrast-enhanced chest CT scans met the 200 HU threshold indicative of adequate pulmonary artery enhancement, including nearly half of the 2% of examinations positive for PE.

Pulmonary vein stump thrombosis after lung resection for lung cancer: clinical features and outcome.

Pulmonary vein stump thrombosis (PVST) is uncommonly encountered postoperative in-situ thrombosis in the stump of pulmonary veins after lung resection. Data regarding the incidence and clinical behaviour of PVST are scarce. Thus, this study aims to investigate the incidence, clinical characteristics and outcome of PVST after lung resection in patients with lung cancer. Follow-up enhanced chest computed tomography (CT) scans acquired after the surgery were retrospectively reviewed to determine PVST presence for patients with lung cancer who underwent lung resection in two tertiary referral centres. Out of the 1885 patients with lung cancer who underwent lobectomy or more extensive lung resection, PVST was observed in 37 patients (2.0%) on their follow-up chest CT. Most stump thrombi were observed in the left superior pulmonary vein [35 (94.6%)] and in patients who underwent left upper lobectomy [34 (91.9%)]. At the last CT follow-up of each patient, 33 (89.2%) exhibited complete resolution, three partial resolution and one stabilization. Eleven (29.7%) patients received anticoagulant therapy after the diagnosis. The rate of complete PVST resolution did not differ significantly between the anticoagulation and nonanticoagulation groups. None of the PVST patients experienced systemic embolic events, regardless of anticoagulation. The PVST incidence diagnosed at routine chest CT follow-up following lung cancer surgery was 2%. PVST was characterized by a benign clinical course without progression and systemic embolization, regardless of anticoagulation. However, further studies are required to determine individualized therapeutic strategies, including anticoagulation.

A spectrum of Thymic mucosa-associated lymphoid tissue lymphoma and Thymic amyloidosis in the patient with Auto immune disease: a case series.

BackgroundThe thymus is associated with an immunodeficient status, autoimmune disease (AD), and the common thymic tumor, thymoma. We encountered two rare thymic tumors, thymic mucosa-associated lymphoid tissue (MALT) lymphoma and localized thymic amyloidosis, both in the presence of Sjögren’s syndrome (SjS). This suggests a possible link between rare thymic tumors and SjS. Therefore, we reviewed cases of thymic tumors to examine the spectrum of these tumors in patients with AD.MethodsThe clinical information of thymic amyloidosis and MALT lymphoma surgically treated at Kanagawa Cardiovascular and Respiratory Center, and Yokohama City University Hospital from January 2010 to December 2019 were reviewed. The correlation between resected thymic tumors at same period and ADs were also investigated.ResultsThere were 5 cases of thymic amyloidosis and MALT lymphoma. ALL cases had coexistent ADs (4 SjS, 1 SSc). The median age was 66 (38–76) year-old, and 4 of the patients were female. Three cases had already diagnosed as ADs before detection of tumors. Only SSc case was received preceding steroid medication. Two cases diagnosed as SjS at the same time of the operation. The median maximum tumor diameter was 70 mm. On chest computed tomography (CT), tumors contained solid part and some cystic part at various rated. Calcification was recognized with appearance of amyloid deposition. All patients were surgically treated with total thymectomy and they are alive without recurrence. At the same period, there were 163 resected thymic tumors, including amyloidosis, MALT lymphoma, thymoma, thymic cancer, neuroendocrine tumor and so on. Among them, nine patients (5.5%) had ADs. There was a correlation between ADs and thymic MALT lymphoma/amyloidosis (P<0.001).ConclusionsWe propose a process for tumorigenesis of thymic MALT lymphoma and amyloidosis. Underlying AD causes persistent and chronic inflammatory reactions. In this theory, ADs, especially SjS, might be important underlying conditions in formation of rare tumors. When the clinician encounters a patient with AD, routine chest CT is recommended and may provide thymic tumors. Conversely, in case of mediastinum tumor, screening test for AD is also recommended.

Evaluation of a comprehensive pre-procedural screening protocol for COVID-19 in times of a high SARS CoV-2 prevalence: a prospective cross-sectional study

Background To minimise the risk of COVID-19 transmission, an ambulant screening protocol for COVID-19 in patients before admission to the hospital was implemented, combining the SARS CoV-2 reverse-transcriptase polymerase chain reaction (RT-PCR) on a nasopharyngeal swab, a chest computed tomography (CT) and assessment of clinical symptoms. The aim of this study was to evaluatethe diagnostic yield and the proportionality of this pre-procedural screeningprotocol. Methods In this mono-centre, prospective, cross-sectional study, all patients admitted to the hospital between 22nd April 2020 until 14th May 2020 for semi-urgent surgery, haematological or oncological treatment, or electrophysiological investigationunderwent a COVID-19 screening 2 days before their procedure. At a 2-week follow-up, the presence of clinical symptoms was evaluated by telephone as a post-hoc evaluation of the screening approach.Combined positive RT-PCR assay and/or positive chest CT was used as gold standard. Post-procedural outcomes of all patients diagnosed positive for COVID-19 were assessed. Results In total,528 patients were included of which 20 (3.8%) were diagnosed as COVID-19 positive and 508 (96.2%) as COVID-19 negative. 11 (55.0%) of COVID-19 positive patients had only a positive RT-PCR assay, 3 (15.0%) had only a positive chest CT and 6 (30%) had both a positive RT-PCR assay and chest CT. 10 out of 20 (50.0%) COVID-19 positive patients reported no single clinical symptom at the screening. At 2 week follow-up, 50% of these patients were still asymptomatic. 37.5% of all COVID-19 negative patients were symptomatic at screening. In the COVID-19 negative group without symptoms at screening, 78 (29.3%) patients developed clinical symptoms at a 2-week follow-up. Conclusion This study suggests that routine chest CT and assessment of self-reported symptoms have limited value in the preprocedural COVID-19 screening due to low sensitivity and/or specificity.

The role of visceral adiposity in the severity of COVID-19: Highlights from a unicenter cross-sectional pilot study in Germany

Background and aimsOverall obesity has recently been established as an independent risk factor for critical illness in patients with coronavirus disease 2019 (COVID-19). The role of fat distribution and especially that of visceral fat, which is often associated with metabolic syndrome, remains unclear. Therefore, this study aims at investigating the association between fat distribution and COVID-19 severity. MethodsThirty patients with COVID-19 and a mean age of 65.6 ± 13.1 years from a level-one medical center in Berlin, Germany, were included in the present cross-sectional analysis. COVID-19 was confirmed by polymerase chain reaction (PCR) from nasal and throat swabs. A severe clinical course of COVID-19 was defined by hospitalization in the intensive care unit (ICU) and/or invasive mechanical ventilation. Fat was measured at the level of the first lumbar vertebra on routinely acquired low-dose chest computed tomography (CT). ResultsAn increase in visceral fat area (VFA) by ten square centimeters was associated with a 1.37-fold higher likelihood of ICU treatment and a 1.32-fold higher likelihood of mechanical ventilation (adjusted for age and sex). For upper abdominal circumference, each additional centimeter of circumference was associated with a 1.13-fold higher likelihood of ICU treatment and a 1.25-fold higher likelihood of mechanical ventilation. ConclusionsOur proof-of-concept study suggests that visceral adipose tissue and upper abdominal circumference specifically increase the likelihood of COVID-19 severity. CT-based quantification of visceral adipose tissue and upper abdominal circumference in routine chest CTs may therefore be a simple tool for risk assessment in COVID-19 patients.

The yield of chest computed tomography in patients with locally advanced pancreatic cancer

ObjectiveTo evaluate the incidence of pulmonary metastases on chest computed tomography (CT) in patients with locally advanced pancreatic cancer (LAPC).MethodsAll patients diagnosed with LAPC in a single tertiary center (Erasmus MC) between October 2011 and December 2017 were reviewed. The staging chest CT scan and follow‐up chest CT scans were evaluated. Pulmonary nodules were divided into three categories: apparent benign, too small to characterize, and apparent malignant.ResultsIn 124 consecutive patients diagnosed with LAPC, 119 (96%) patients underwent a staging chest CT scan at the initial presentation. In 88 (74%) patients no pulmonary nodules were found; in 16 (13%) patients an apparent benign pulmonary nodule was found, and in 15 (13%) patients a pulmonary nodule too small to characterize was found. Follow‐up chest CT scan(s) were performed in 111 (93%) patients. In one patient with either no pulmonary nodule or an apparent benign pulmonary nodule at initial staging, an apparent malignant pulmonary nodule was found on a follow‐up chest CT scan. However, a biopsy of the nodule was inconclusive. Of 15 patients in whom a pulmonary nodule too small to characterize was found at staging, 12 (80%) patients underwent a follow‐up CT scan; in 4 (33%) of these patients, an apparent malignant pulmonary nodule was found.ConclusionIn patients with LAPC in whom at diagnosis a chest CT scan revealed either no pulmonary nodules or apparent benign pulmonary nodules, routine follow‐up chest CT scans is not recommended. Patients with pulmonary nodules too small to characterize are at risk to develop apparent malignant pulmonary nodules during follow‐up.

Deep learning detection and quantification of pneumothorax in heterogeneous routine chest computed tomography

BackgroundAutomatically detecting and quantifying pneumothorax on chest computed tomography (CT) may impact clinical decision-making. Machine learning methods published so far struggle with the heterogeneity of technical parameters and the presence of additional pathologies, highlighting the importance of stable algorithms.MethodsA deep residual UNet was developed and evaluated for automated, volume-level pneumothorax grading (i.e., labelling a volume whether a pneumothorax was present or not), and pixel-level classification (i.e., segmentation and quantification of pneumothorax), on a retrospective series of routine chest CT data. Ground truth annotations were provided by radiologists. The fully automated pixel-level pneumothorax segmentation method was trained using 43 chest CT scans and evaluated on 9 chest CT scans with pixel-level annotation basis and 567 chest CT scans on a volume-level basis.ResultsThis method achieved a receiver operating characteristic area under the curve (AUC) of 0.98, an average precision of 0.97, and a Dice similarity coefficient (DSC) of 0.94. This segmentation performance resulted to be similar to the inter-rater segmentation accuracy of two radiologists, who achieved a DSC of 0.92. The comparison of manual and automated pneumothorax quantification yielded a Pearson correlation coefficient of 0.996. The volume-level pneumothorax grading accuracy was evaluated on 567 chest CT scans and yielded an AUC of 0.98 and an average precision of 0.95.ConclusionsWe proposed a deep learning method for the detection and quantification of pneumothorax in heterogeneous routine clinical data that may facilitate the automated triage of urgent examinations and enable treatment decision support.

Routine Chest Computed Tomography for Staging of Pancreatic Head Carcinoma.

The diagnostic value of routine chest computed tomography (CT) in addition to abdominal CT in workup for pancreatic head carcinoma is unclear. The aim of this study was to determine if routine chest CT revealed significant lesions that altered the management of patients with suspected pancreatic head carcinoma. All Dutch pancreatic cancer centers were surveyed on the use of chest CT in preoperative staging. In addition, a single-center retrospective cohort study was performed including all patients referred with suspected pancreatic head malignancy without chest CT between 2005 and 2016. The primary end point was the proportion of patients in which chest CT revealed clinically significant lesions, leading to a change in management. In 7 of 18 Dutch pancreatic cancer centers (39%), a preoperative chest CT is not routinely performed. In the study cohort, 170 of 848 patients (20%) were referred without chest CT and underwent one by local protocol. Chest CT revealed new suspicious lesions in 17 patients (10%), of whom 6 had metastatic disease (3.5%). Routine use of chest CT in diagnostic workup for pancreatic head carcinoma reveals clinically significant lesions in 10% of patients, being metastases in up to 4%.

Machine Learning for Automatic Paraspinous Muscle Area and Attenuation Measures on Low-Dose Chest CT Scans

To develop and evaluate an automated machine learning (ML) algorithm for segmenting the paraspinous muscles on chest computed tomography (CT) scans to evaluate for presence of sarcopenia. A convolutional neural network based on the U-Net architecture was trained to perform muscle segmentation on a dataset of 1875 single slice CT images and was tested on 209 CT images of participants in the National Lung Screening Trial. Low-dose, noncontrast CT examinations were obtained at 33 clinical sites, using scanners from four manufacturers. The study participants had a mean age of 71.6 years (range, 70-74 years). Ground truth was obtained by manually segmenting the left paraspinous muscle at the level of the T12 vertebra. Muscle cross-sectional area (CSA) and muscle attenuation (MA) were recorded. Comparison between the ML algorithm and ground truth measures of muscle CSA and MA were obtained using Dice similarity coefficients and Pearson correlations. Compared to ground truth segmentation, the ML algorithm achieved median (standard deviation) Dice scores of 0.94 (0.04) in the test set. Mean (SD) muscle CSA was 14.3 (3.6) cm2 for ground truth and 13.7 (3.5) cm2 for ML segmentation. Mean (SD) MA was 41.6 (7.6) Hounsfield units (HU) for ground truth and 43.5 (7.9) HU for ML segmentation. There was high correlation between ML algorithm and ground truth for muscle CSA (r2 = 0.86; p < 0.0001) and MA (r2 = 0.95; p < 0.0001). The ML algorithm for measurement of paraspinous muscles compared favorably to manual ground truth measurements in the NLST. The algorithm generalized well to a heterogeneous set of low-dose CT images and may be capable of automated quantification of muscle metrics to screen for sarcopenia on routine chest CT examinations.

Organ doses evaluation for chest computed tomography procedures with TL dosimeters: Comparison with Monte Carlo simulations.

PurposeTo evaluate organ doses in routine and low‐dose chest computed tomography (CT) protocols using an experimental methodology. To compare experimental results with results obtained by the National Cancer Institute dosimetry system for CT (NCICT) organ dose calculator. To address the differences on organ dose measurements using tube current modulation (TCM) and fixed tube current protocols.MethodsAn experimental approach to evaluate organ doses in pediatric and adult anthropomorphic phantoms using thermoluminescent dosimeters (TLDs) was employed in this study. Several analyses were performed in order to establish the best way to achieve the main results in this investigation. The protocols used in this study were selected after an analysis of patient data collected from the Institute of Radiology of the School of Medicine of the University of São Paulo (InRad). The image quality was evaluated by a radiologist from this institution. Six chest adult protocols and four chest pediatric protocols were evaluated. Lung doses were evaluated for the adult phantom and lung and thyroid doses were evaluated for the pediatric phantom. The irradiations were performed using both a GE and a Philips CT scanner. Finally, organ doses measured with dosimeters were compared with Monte Carlo simulations performed with NCICT.ResultsAfter analyzing the data collected from all CT examinations performed during a period of 3 yr, the authors identified that adult and pediatric chest CT are among the most applied protocol in patients in that clinical institution, demonstrating the relevance on evaluating organ doses due to these examinations. With regards to the scan parameters adopted, the authors identified that using 80 kV instead of 120 kV for a pediatric chest routine CT, with TCM in both situations, can lead up to a 28.7% decrease on the absorbed dose. Moreover, in comparison to the standard adult protocol, which is performed with fixed mAs, TCM, and ultra low‐dose protocols resulted in dose reductions of up to 35.0% and 90.0%, respectively. Finally, the percent differences found between experimental and Monte Carlo simulated organ doses were within a 20% interval.ConclusionsThe results obtained in this study measured the impact on the absorbed dose in routine chest CT by changing several scan parameters while the image quality could be potentially preserved.