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Background Most of the data regarding prevalence and size distribution of solid lung nodules originates from lung cancer screening studies that target high-risk populations or from Asian general cohorts. In recent years, the identification of lung nodules in non-high-risk populations, scanned for clinical indications, has increased. However, little is known about the presence of solid lung nodules in the Northern European nonsmoking population. Purpose To study the prevalence and size distribution of solid lung nodules by age and sex in a nonsmoking population. Materials and Methods Participants included nonsmokers (never or former smokers) from the population-based Imaging in Lifelines study conducted in the Northern Netherlands. Participants (age ≥ 45 years) with completed lung function tests underwent chest low-dose CT scans. Seven trained readers registered the presence and size of solid lung nodules measuring 30 mm3 or greater using semiautomated software. The prevalence and size of lung nodules (≥30 mm3), clinically relevant lung nodules (≥100 mm3), and actionable nodules (≥300 mm3) are presented by 5-year categories and by sex. Results A total of 10 431 participants (median age, 60.4 years [IQR, 53.8-70.8 years]; 56.6% [n = 5908] female participants; 46.1% [n = 4812] never smokers and 53.9% [n = 5619] former smokers) were included. Of these, 42.0% (n = 4377) had at least one lung nodule (male participants, 47.5% [2149 of 4523]; female participants, 37.7% [2228 of 5908]). The prevalence of lung nodules increased from age 45-49.9 years (male participants, 39.4% [219 of 556]; female participants, 27.7% [236 of 851]) to age 80 years or older (male participants, 60.7% [246 of 405]; female participants, 50.9% [163 of 320]). Clinically relevant lung nodules were present in 11.1% (1155 of 10 431) of participants, with prevalence increasing with age (male participants, 8.5%-24.4%; female participants, 3.7%-15.6%), whereas actionable nodules were present in 1.1%-6.4% of male participants and 0.6%-4.9% of female participants. Conclusion Lung nodules were present in a substantial proportion of all age groups in the Northern European nonsmoking population, with slightly higher prevalence for male participants than female participants. © RSNA, 2024 Supplemental material is available for this article.
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Neoplasias Pulmonares , Tomografía Computarizada por Rayos X , Humanos , Masculino , Femenino , Persona de Mediana Edad , Anciano , Países Bajos/epidemiología , Tomografía Computarizada por Rayos X/métodos , Prevalencia , Neoplasias Pulmonares/diagnóstico por imagen , Neoplasias Pulmonares/epidemiología , Nódulo Pulmonar Solitario/diagnóstico por imagen , Nódulos Pulmonares Múltiples/diagnóstico por imagen , Nódulos Pulmonares Múltiples/epidemiología , Factores Sexuales , Pulmón/diagnóstico por imagen , No Fumadores/estadística & datos numéricos , Distribución por Edad , Factores de Edad , Distribución por SexoRESUMEN
Background CT-derived bronchial parameters have been linked to chronic obstructive pulmonary disease and asthma severity, but little is known about these parameters in healthy individuals. Purpose To investigate the distribution of bronchial parameters at low-dose CT in individuals with healthy lungs from a Dutch general population. Materials and Methods In this prospective study, low-dose chest CT performed between May 2017 and October 2022 were obtained from participants who had completed the second-round assessment of the prospective, longitudinal Imaging in Lifelines study. Participants were aged at least 45 years, and those with abnormal spirometry, self-reported respiratory disease, or signs of lung disease at CT were excluded. Airway lumens and walls were segmented automatically. The square root of the bronchial wall area of a hypothetical airway with an internal perimeter of 10 mm (Pi10), luminal area (LA), wall thickness (WT), and wall area percentage were calculated. Associations between sex, age, height, weight, smoking status, and bronchial parameters were assessed using univariable and multivariable analyses. Results The study sample was composed of 8869 participants with healthy lungs (mean age, 60.9 years ± 10.4 [SD]; 4841 [54.6%] female participants), including 3672 (41.4%) never-smokers and 1197 (13.5%) individuals who currently smoke. Bronchial parameters for male participants were higher than those for female participants (Pi10, slope [ß] range = 3.49-3.66 mm; LA, ß range = 25.40-29.76 mm2; WT, ß range = 0.98-1.03 mm; all P < .001). Increasing age correlated with higher Pi10, LA, and WT (r2 range = 0.06-0.09, 0.02-0.01, and 0.02-0.07, respectively; all P < .001). Never-smoking individuals had the lowest Pi10 followed by formerly smoking and currently smoking individuals (3.62 mm ± 0.13, 3.68 mm ± 0.14, and 3.70 mm ± 0.14, respectively; all P < .001). In multivariable regression models, age, sex, height, weight, and smoking history explained up to 46% of the variation in bronchial parameters. Conclusion In healthy individuals, bronchial parameters differed by sex, height, weight, and smoking history; male sex and increasing age were associated with wider lumens and thicker walls. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Emrich and Varga-Szemes in this issue.
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Tomografía Computarizada por Rayos X , Humanos , Masculino , Femenino , Persona de Mediana Edad , Tomografía Computarizada por Rayos X/métodos , Estudios Prospectivos , Pulmón/diagnóstico por imagen , Bronquios/diagnóstico por imagen , Dosis de Radiación , Anciano , Países BajosRESUMEN
BACKGROUND: This population-based study aimed to identify the risk factors for lung nodules in a Western European general population. METHODS: We quantified the presence or absence of lung nodules among 12 055 participants of the Dutch population-based ImaLife (Imaging in Lifelines) study (age ≥45â years) who underwent low-dose chest computed tomography. Outcomes included the presence of 1) at least one solid lung nodule (volume ≥30â mm3) and 2) a clinically relevant lung nodule (volume ≥100â mm3). Fully adjusted multivariable logistic regression models were applied overall and stratified by smoking status to identify independent risk factors for the presence of nodules. RESULTS: Among the 12 055 participants (44.1% male; median age 60â years; 39.9% never-smokers; 98.7% White), we found lung nodules in 41.8% (5045 out of 12 055) and clinically relevant nodules in 11.4% (1377 out of 12 055); the corresponding figures among never-smokers were 38.8% and 9.5%, respectively. Factors independently associated with increased odds of having any lung nodule included male sex, older age, low educational level, former smoking, asbestos exposure and COPD. Among never-smokers, a family history of lung cancer increased the odds of both lung nodules and clinically relevant nodules. Among former and current smokers, low educational level was positively associated with lung nodules, whereas being overweight was negatively associated. Among current smokers, asbestos exposure and low physical activity were associated with clinically relevant nodules. CONCLUSIONS: The study provides a large-scale evaluation of lung nodules and associated risk factors in a Western European general population: lung nodules and clinically relevant nodules were prevalent, and never-smokers with a family history of lung cancer were a non-negligible group.
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Neoplasias Pulmonares , Fumar , Tomografía Computarizada por Rayos X , Humanos , Masculino , Femenino , Persona de Mediana Edad , Anciano , Factores de Riesgo , Fumar/epidemiología , Neoplasias Pulmonares/epidemiología , Neoplasias Pulmonares/diagnóstico por imagen , Países Bajos/epidemiología , Modelos Logísticos , Nódulos Pulmonares Múltiples/diagnóstico por imagen , Nódulos Pulmonares Múltiples/epidemiología , Nódulo Pulmonar Solitario/diagnóstico por imagen , Nódulo Pulmonar Solitario/epidemiología , Análisis Multivariante , Enfermedad Pulmonar Obstructiva Crónica/epidemiología , Enfermedad Pulmonar Obstructiva Crónica/diagnóstico por imagen , Amianto/efectos adversos , Pulmón/diagnóstico por imagenRESUMEN
The aim of this phantom study was to assess the detectability and volumetric accuracy of pulmonary nodules on photon-counting detector CT (PCD-CT) at different low-dose levels compared to conventional energy-integrating detector CT (EID-CT). In-house fabricated artificial nodules of different shapes (spherical, lobulated, spiculated), sizes (2.5-10 mm and 5-1222 mm3), and densities (-330 HU and 100 HU) were randomly inserted into an anthropomorphic thorax phantom. The phantom was scanned with a low-dose chest protocol with PCD-CT and EID-CT, in which the dose with PCD-CT was lowered from 100% to 10% with respect to the EID-CT reference dose. Two blinded observers independently assessed the CT examinations of the nodules. A third observer measured the nodule volumes using commercial software. The influence of the scanner type, dose, observer, physical nodule volume, shape, and density on the detectability and volumetric accuracy was assessed by a multivariable regression analysis. In 120 CT examinations, 642 nodules were present. Observer 1 and 2 detected 367 (57%) and 289 nodules (45%), respectively. With PCD-CT and EID-CT, the nodule detectability was similar. The physical nodule volumes were underestimated by 20% (range 8-52%) with PCD-CT and 24% (range 9-52%) with EID-CT. With PCD-CT, no significant decrease in the detectability and volumetric accuracy was found at dose reductions down to 10% of the reference dose (p > 0.05). The detectability and volumetric accuracy were significantly influenced by the observer, nodule volume, and a spiculated nodule shape (p < 0.05), but not by dose, CT scanner type, and nodule density (p > 0.05). Low-dose PCD-CT demonstrates potential to detect and assess the volumes of pulmonary nodules, even with a radiation dose reduction of up to 90%.
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BACKGROUND: Deep learning is an important means to realize the automatic detection, segmentation, and classification of pulmonary nodules in computed tomography (CT) images. An entire CT scan cannot directly be used by deep learning models due to image size, image format, image dimensionality, and other factors. Between the acquisition of the CT scan and feeding the data into the deep learning model, there are several steps including data use permission, data access and download, data annotation, and data preprocessing. This paper aims to recommend a complete and detailed guide for researchers who want to engage in interdisciplinary lung nodule research of CT images and Artificial Intelligence (AI) engineering. METHODS: The data preparation pipeline used the following four popular large-scale datasets: LIDC-IDRI (Lung Image Database Consortium image collection), LUNA16 (Lung Nodule Analysis 2016), NLST (National Lung Screening Trial) and NELSON (The Dutch-Belgian Randomized Lung Cancer Screening Trial). The dataset preparation is presented in chronological order. FINDINGS: The different data preparation steps before deep learning were identified. These include both more generic steps and steps dedicated to lung nodule research. For each of these steps, the required process, necessity, and example code or tools for actual implementation are provided. DISCUSSION AND CONCLUSION: Depending on the specific research question, researchers should be aware of the various preparation steps required and carefully select datasets, data annotation methods, and image preprocessing methods. Moreover, it is vital to acknowledge that each auxiliary tool or code has its specific scope of use and limitations. This paper proposes a standardized data preparation process while clearly demonstrating the principles and sequence of different steps. A data preparation pipeline can be quickly realized by following these proposed steps and implementing the suggested example codes and tools.
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Predicted lung volumes based on the Global Lung Function Initiative (GLI) model are used in pulmonary disease detection and monitoring. It is unknown how well the predicted lung volume corresponds with computed tomography (CT) derived total lung volume (TLV). The aim of this study was to compare the GLI-2021 model predictions of total lung capacity (TLC) with CT-derived TLV. 151 female and 139 male healthy participants (age 45-65 years) were consecutively selected from a Dutch general population cohort, the Imaging in Lifelines (ImaLife) cohort. In ImaLife, all participants underwent low-dose, inspiratory chest CT. TLV was measured by an automated analysis, and compared to predicted TLC based on the GLI-2021 model. Bland-Altman analysis was performed for analysis of systematic bias and range between limits of agreement. To further mimic the GLI-cohort all analyses were repeated in a subset of never-smokers (51% of the cohort). Mean±SD of TLV was 4.7±0.9 L in women and 6.2±1.2 L in men. TLC overestimated TLV, with systematic bias of 1.0 L in women and 1.6 L in men. Range between limits of agreement was 3.2 L for women and 4.2 L for men, indicating high variability. Performing the analysis with never-smokers yielded similar results. In conclusion, in a healthy cohort, predicted TLC substantially overestimates CT-derived TLV, with low precision and accuracy. In a clinical context where an accurate or precise lung volume is required, measurement of lung volume should be considered.
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Enfermedades Pulmonares , Pulmón , Humanos , Femenino , Masculino , Persona de Mediana Edad , Anciano , Pulmón/diagnóstico por imagen , Mediciones del Volumen Pulmonar , Tomografía Computarizada por Rayos X/métodos , Capacidad Pulmonar TotalRESUMEN
OBJECTIVE: To evaluate detectability and semi-automatic diameter and volume measurements of pulmonary nodules in ultralow-dose CT (ULDCT) vs regular-dose CT (RDCT). METHODS: Fifty patients with chronic obstructive pulmonary disease (COPD) underwent RDCT on 64-multidetector CT (120 kV, filtered back projection), and ULDCT on third-generation dual source CT (100 kV with tin filter, advanced modeled iterative reconstruction). One radiologist evaluated the presence of nodules on both scans in random order, with discrepancies judged by two independent radiologists and consensus reading. Sensitivity of nodule detection on RDCT and ULDCT was compared to reader consensus. Systematic error in semi-automatically derived diameter and volume, and 95% limits of agreement (LoA) were evaluated. Nodule classification was compared by κ statistics. RESULTS: ULDCT resulted in 83.1% (95% CI: 81.0-85.2) dose reduction compared to RDCT (p < 0.001). 45 nodules were present, with diameter range 4.0-25.3 mm and volume range 16.0-4483.0 mm3. Detection sensitivity was non-significant (p = 0.503) between RDCT 88.8% (95% CI: 76.0-96.3) and ULDCT 95.5% (95% CI: 84.9-99.5). No systematic bias in diameter measurements (median difference: -0.2 mm) or volumetry (median difference: -6 mm3) was found for ULDCT compared to RDCT. The 95% LoA for diameter and volume measurements were ±3.0 mm and ±33.5%, respectively. κ value for nodule classification was 0.852 for diameter measurements and 0.930 for volumetry. CONCLUSION: ULDCT based on Sn100 kV enables comparable detectability of solid pulmonary nodules in COPD patients, at 83% reduced radiation dose compared to RDCT, without relevant difference in nodule measurement and size classification. ADVANCES IN KNOWLEDGE: Pulmonary nodule detectability and measurements in ULDCT are comparable to RDCT.
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Neoplasias Pulmonares , Nódulos Pulmonares Múltiples , Enfermedad Pulmonar Obstructiva Crónica , Humanos , Neoplasias Pulmonares/diagnóstico por imagen , Tomografía Computarizada Multidetector , Nódulos Pulmonares Múltiples/diagnóstico por imagen , Enfermedad Pulmonar Obstructiva Crónica/diagnóstico por imagen , Dosis de Radiación , Interpretación de Imagen Radiográfica Asistida por Computador/métodosRESUMEN
BACKGROUND: Chest computed tomography (CT) emphysema quantification is a vital diagnostic tool in patient evaluation for bronchoscopic lung volume reduction (BLVR). Smooth kernels for CT image reconstruction are generally recommended for quantitative analyses. This recommendation is not always followed, which may affect quantification of emphysema extent and eventually, treatment decisions. OBJECTIVE: The main goal is to demonstrate the influence of CT reconstruction kernels on emphysema quantification in patients with severe COPD, considered for BLVR. METHODS: Chest CT scans were acquired with one multi-detector CT system and reconstructed using three different kernels: smooth, medium smooth, and sharp. Other parameters were kept constant. Emphysema scores (ESs), meaning the percentage of voxels below -950 Hounsfield units, were calculated and compared to the smooth reference kernel using paired t tests. Bland-Altman plots were made to assess the biases and limits of agreement between kernels. RESULTS: Ninety-eight COPD patient CT scans were analyzed. The sharp kernel had a systematic bias of 6.2% and limits of agreement of 16.6% to -4.2% compared to the smooth kernel. The medium smooth kernel had a systematic bias of 5.7% and limits of agreement of 9.2% and 2.2% compared to the smooth kernel. The ES differed, for a single patient, up to 18% for different kernels. CONCLUSIONS: Chest CT kernel reconstruction can lead to a significant difference in emphysema severity quantification. This may cause invalid treatment selection in COPD patients evaluated for BLVR. Standardization of a smooth CT kernel setting and/or normalization to a standard kernel is strongly recommended.
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Enfisema , Enfermedad Pulmonar Obstructiva Crónica , Enfisema Pulmonar , Humanos , Neumonectomía , Enfisema Pulmonar/diagnóstico por imagen , Enfisema Pulmonar/cirugía , Enfermedad Pulmonar Obstructiva Crónica/complicaciones , Enfermedad Pulmonar Obstructiva Crónica/diagnóstico por imagen , Enfermedad Pulmonar Obstructiva Crónica/cirugía , Tomografía Computarizada Multidetector , Enfisema/cirugíaRESUMEN
AIMS: To evaluate the ability of Systematic COronary Risk Estimation 2 (SCORE2) and other pre-screening methods to identify individuals with high coronary artery calcium score (CACS) in the general population. METHODS AND RESULTS: Computed tomography-based CACS quantification was performed in 6530 individuals aged 45 years or older from the general population. Various pre-screening methods to guide referral for CACS were evaluated. Miss rates for high CACS (CACS ≥300 and ≥100) were evaluated for various pre-screening methods: moderate (≥5%) and high (≥10%) SCORE2 risk, any traditional coronary artery disease (CAD) risk factor, any Risk Or Benefit IN Screening for CArdiovascular Disease (ROBINSCA) risk factor, and moderately (>3â mg/24â h) increased urine albumin excretion (UAE). Out of 6530 participants, 643 (9.8%) had CACS ≥300 and 1236 (18.9%) had CACS ≥100. For CACS ≥300 and CACS ≥100, miss rate was 32 and 41% for pre-screening by moderate (≥5%) SCORE2 risk and 81 and 87% for high (≥10%) SCORE2 risk, respectively. For CACS ≥300 and CACS ≥100, miss rate was 8 and 11% for pre-screening by at least one CAD risk factor, 24 and 25% for at least one ROBINSCA risk factor, and 67 and 67% for moderately increased UAE, respectively. CONCLUSION: Many individuals with high CACS in the general population are left unidentified when only performing CACS in case of at least moderate (≥5%) SCORE2, which closely resembles current clinical practice. Less stringent pre-screening by presence of at least one CAD risk factor to guide CACS identifies more individuals with high CACS and could improve CAD prevention.
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Enfermedad de la Arteria Coronaria , Humanos , Enfermedad de la Arteria Coronaria/epidemiología , Calcio , Angiografía Coronaria/métodos , Medición de Riesgo , Factores de Riesgo , Valor Predictivo de las PruebasRESUMEN
PURPOSE: Aim was to assess CT characteristics of lung nodules in never and former smokers compared to current smokers in a population-based setting. METHOD: We included individuals aged 45-60 years taking part in the ImaLife (Imaging in Lifelines) study, with at least one solid lung nodule (≥30 mm3) on low-dose chest CT. Qualitative (location, shape, margin, nodule type, attached structures) and quantitative (count, diameter, volume) nodule characteristics were evaluated. Based on Fleischner criteria, 'high risk' nodules were defined. To examine the association between smoking status and nodule CT characteristics of participants, multi-level multinomial logistic regression corrected for clustering of nodules within participants was performed, where all odds ratios (aORs) were adjusted for age and sex. RESULTS: Overall, 1,639 individuals (median age: 55.0, IQR:50.5-58.5, 50.5% men) were included, with 42.1% never smokers, 35.3% former smokers and 22.6% current smokers. A total of 3,222 solid nodules were identified; 39.7% of individuals had multiple nodules. Nodule size, location, type and attachment were similar for never compared to current smokers. The odds of nodules with an irregular shape and irregular margin was lower in never smokers (aOR:0.64, 95 %CI:0.44-0.93; aOR:0.60, 95 %CI:0.41-0.88, respectively) and former smokers (aOR:0.61, 95 %CI:0.41-0.90; aOR:0.57, 95 %CI:0.38-0.85, respectively) compared to current smokers. The odds of a detected nodule being 'high risk' was similar for never versus current smokers (never smokers: aOR = 0.90; 95% CI:0.73-1.11). CONCLUSIONS: CT-based characteristics of solid lung nodules in never and former smokers differed only slightly from current smokers. Among individuals with solid nodules, 'high-risk' nodules were equally common in never smokers and current smokers.
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Neoplasias Pulmonares , Nódulo Pulmonar Solitario , Femenino , Humanos , Modelos Logísticos , Neoplasias Pulmonares/diagnóstico por imagen , Neoplasias Pulmonares/epidemiología , Masculino , Persona de Mediana Edad , Fumadores , Nódulo Pulmonar Solitario/diagnóstico por imagen , Nódulo Pulmonar Solitario/epidemiología , Tomografía Computarizada por Rayos X/métodosRESUMEN
INTRODUCTION: In emphysema patient being evaluated for bronchoscopic lung volume reduction (BLVR), accurate measurement of lung volumes is important. Total lung capacity (TLC) and residual volume (RV) are commonly measured by body plethysmography but can also be derived from chest computed tomography (CT). Spirometry-gated CT scanning potentially improves the agreement of CT and body plethysmography. The aim of this study was to compare lung volumes derived from spirometry-gated CT and "breath-hold-coached" CT to the reference standard: body plethysmography. METHODS: In this single-centre retrospective cohort study, emphysema patients being evaluated for BLVR underwent body plethysmography, inspiration (TLC) and expiration (RV) CT scan with spirometer guidance ("gated group") or with breath-hold-coaching ("non-gated group"). Quantitative analysis was used to calculate lung volumes from the CT. RESULTS: 200 patients were included in the study (mean±sd age 62±8â years, forced expiratory flow in 1â s 29.2±8.7%, TLC 7.50±1.46â L, RV 4.54±1.07â L). The mean±sd CT-derived TLC was 280±340â mL lower compared to body plethysmography in the gated group (n=100), and 590±430â mL lower for the non-gated group (n=100) (both p<0.001). The mean±sd CT-derived RV was 300±470â mL higher in the gated group and 700±720 mL higher in the non-gated group (both p<0.001). Pearson correlation factors were 0.947 for TLC gated, 0.917 for TLC non-gated, 0.823 for RV gated, 0.693 for RV non-gated, 0.539 for %RV/TLC gated and 0.204 for %RV/TLC non-gated. The differences between the gated and non-gated CT results for TLC and RV were significant for all measurements (p<0.001). CONCLUSION: In severe COPD patients with emphysema, CT-derived lung volumes are strongly correlated to body plethysmography lung volumes, and especially for RV, more accurate when using spirometry gating.
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Assessment of image noise is a relevant issue in computed tomography (CT). Noise is routinely measured by the standard deviation of density values (Hounsfield units, HU) within a circular region of interest (ROI). We explored the effect of a spherical volume of interest (VOI) on noise measurements. Forty-nine chronic obstructive pulmonary disease patients underwent CT with clinical protocol (regular dose [RD], volumetric CT dose index [CTDIvol] 3.04 mGy, 64-slice unit), and ultra-low dose (ULD) protocol (median CTDIvol 0.38 mGy, dual-source unit). Noise was measured in 27 1-cm2 ROIs and 27 0.75-cm3 VOIs inside the trachea. Median true noise was 21 HU (range 17-29) for RD-CT and 33 HU (26-39) for ULD-CT. The VOI approach resulted in a lower mean distance between limits of agreement compared to ROI: 5.9 versus 10.0 HU for RD-CT (-40%); 4.7 versus 9.9 HU for ULD-CT (-53%). Mean systematic bias barely changed: -1.6 versus -0.9HU for RD-CT; 0.0 to 0.4HU for ULD-CT. The average measurement time was 6.8 s (ROI) versus 9.7 (VOI), independent of dose level. For chest CT, measuring noise with a VOI-based instead of a ROI-based approach reduces variability by 40-53%, without a relevant effect on systematic bias and measurement time.
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Tomografía Computarizada por Rayos X , Humanos , Dosis de RadiaciónRESUMEN
We investigated whether presence and characteristics of lung nodules in the general population using low-dose computed tomography (LDCT) varied by season. Imaging in Lifelines (ImaLife) study participants who underwent chest LDCT-scanning between October 2018 and October 2019 were included in this sub-study. Hay fever season (summer) was defined as 1st April to 30th September and Influenza season (winter) as 1st October to 31st March. All lung nodules with volume of ≥ 30 mm3 (approximately 3 mm in diameter) were registered. In total, 2496 lung nodules were found in 1312 (38%) of the 3456 included participants (nodules per participant ranging from 1 to 21, median 1). In summer, 711 (54%) participants had 1 or more lung nodule(s) compared to 601 (46%) participants in winter (p = 0.002). Of the spherical, perifissural and left-upper-lobe nodules, relatively more were detected in winter, whereas of the polygonal-, irregular-shaped and centrally-calcified nodules, relatively more were detected in summer. Various seasonal diseases with inflammation as underlying pathophysiology may influence presence and characteristics of lung nodules. Further investigation into underlying pathophysiology using short-term LDCT follow-up could help optimize the management strategy for CT-detected lung nodules in clinical practice.
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Neoplasias Pulmonares/diagnóstico , Pulmón/diagnóstico por imagen , Tomografía Computarizada por Rayos X/métodos , Adulto , Anciano , Detección Precoz del Cáncer , Femenino , Humanos , Neoplasias Pulmonares/epidemiología , Masculino , Persona de Mediana Edad , Países Bajos/epidemiología , Prevalencia , Dosis de Radiación , Análisis de Regresión , Estaciones del AñoRESUMEN
OBJECTIVES: To investigate the association of pericoronary adipose tissue mean attenuation (PCATMA) with coronary artery disease (CAD) characteristics on coronary computed tomography angiography (CCTA). METHODS: We retrospectively investigated 165 symptomatic patients who underwent third-generation dual-source CCTA at 70kVp: 93 with and 72 without CAD (204 arteries with plaque, 291 without plaque). CCTA was evaluated for presence and characteristics of CAD per artery. PCATMA was measured proximally and across the most severe stenosis. Patient-level, proximal PCATMA was defined as the mean of the proximal PCATMA of the three main coronary arteries. Analyses were performed on patient and vessel level. RESULTS: Mean proximal PCATMA was -96.2 ± 7.1 HU and -95.6 ± 7.8HU for patients with and without CAD (p = 0.644). In arteries with plaque, proximal and lesion-specific PCATMA was similar (-96.1 ± 9.6 HU, -95.9 ± 11.2 HU, p = 0.608). Lesion-specific PCATMA of arteries with plaque (-94.7 HU) differed from proximal PCATMA of arteries without plaque (-97.2 HU, p = 0.015). Minimal stenosis showed higher lesion-specific PCATMA (-94.0 HU) than severe stenosis (-98.5 HU, p = 0.030). Lesion-specific PCATMA of non-calcified, mixed, and calcified plaque was -96.5 HU, -94.6 HU, and -89.9 HU (p = 0.004). Vessel-based total plaque, lipid-rich necrotic core, and calcified plaque burden showed a very weak to moderate correlation with proximal PCATMA. CONCLUSIONS: Lesion-specific PCATMA was higher in arteries with plaque than proximal PCATMA in arteries without plaque. Lesion-specific PCATMA was higher in non-calcified and mixed plaques compared to calcified plaques, and in minimal stenosis compared to severe; proximal PCATMA did not show these relationships. This suggests that lesion-specific PCATMA is related to plaque development and vulnerability. KEY POINTS: ⢠In symptomatic patients undergoing CCTA at 70 kVp, PCATMA was higher in coronary arteries with plaque than those without plaque. ⢠PCATMA was higher for non-calcified and mixed plaques compared to calcified plaques, and for minimal stenosis compared to severe stenosis. ⢠In contrast to PCATMA measurement of the proximal vessels, lesion-specific PCATMA showed clear relationships with plaque presence and stenosis degree.
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Enfermedad de la Arteria Coronaria , Estenosis Coronaria , Placa Aterosclerótica , Tejido Adiposo/diagnóstico por imagen , Angiografía por Tomografía Computarizada , Constricción Patológica , Angiografía Coronaria , Enfermedad de la Arteria Coronaria/diagnóstico por imagen , Estenosis Coronaria/diagnóstico por imagen , Vasos Coronarios/diagnóstico por imagen , Humanos , Placa Aterosclerótica/diagnóstico por imagen , Valor Predictivo de las Pruebas , Estudios RetrospectivosRESUMEN
BACKGROUND: To determine the effect of low-dose, high-pitch non-electrocardiographic (ECG)-triggered chest CT on coronary artery calcium (CAC) detection, quantification and risk stratification, compared to ECG-triggered cardiac CT. METHODS: We selected 1,000 participants from the ImaLife study, 50% with coronary calcification on cardiac CT. All participants underwent non-contrast cardiac CT followed by chest CT using third-generation dual-source technology. Reconstruction settings were equal for both acquisitions. CAC scores were determined by Agatston's method, and divided dichotomously (0, >0), and into risk categories (0, 1-99, 100-399, ≥400). We investigated the influence of heart rate and body mass index (BMI) on risk reclassification. RESULTS: Positive CAC scores on cardiac CT ranged from 1 to 6926 (median 39). Compared to cardiac CT, chest CT had sensitivity of 0.96 (95%CI 0.94-0.98) and specificity of 0.99 (95%CI 0.97-0.99) for CAC detection (κ = 0.95). In participants with coronary calcification on cardiac CT, CAC score on chest CT was lower than on cardiac CT (median 30 versus 40, pË0.001). Agreement in CAC-based risk strata was excellent (weighted κ = 0.95). Sixty-five cases (6.5%) were reclassified by one risk category in chest CT, with fifty-five (84.6%) shifting downward. Higher BMI resulted in higher reclassification rate (13% for BMI ≥30 versus 5.2% for BMI <30, p = 0.001), but there was no effect of heart rate. CONCLUSION: Low-dose, high-pitch chest CT, using third-generation dual-source technology shows almost perfect agreement with cardiac CT in CAC detection and risk stratification. However, low-dose chest CT mainly underestimates the CAC score as compared to cardiac CT, and results in inaccurate risk categorization in BMI ≥30.
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Angiografía por Tomografía Computarizada , Angiografía Coronaria , Enfermedad de la Arteria Coronaria/diagnóstico por imagen , Vasos Coronarios/diagnóstico por imagen , Radiografía Torácica , Calcificación Vascular/diagnóstico por imagen , Anciano , Técnicas de Imagen Sincronizada Cardíacas , Electrocardiografía , Femenino , Humanos , Masculino , Persona de Mediana Edad , Valor Predictivo de las Pruebas , Dosis de Radiación , Reproducibilidad de los Resultados , Índice de Severidad de la EnfermedadRESUMEN
PURPOSE: To investigate image quality and bronchial wall quantification in low- and ultralow-dose third-generation dual-source computed tomography (CT). METHODS: A lung specimen from a formerly healthy male was scanned using third-generation dual-source CT at standard-dose (51 mAs/120 kV, CTDIvol 3.41 mGy), low-dose (1/4th and 1/10th of standard dose), and ultralow-dose setting (1/20th). Low kV (70, 80, 90, and Sn100 kV) scanning was applied in each low/ultralow-dose setting, combined with adaptive mAs to keep a constant dose. Images were reconstructed at advanced modeled iterative reconstruction (ADMIRE) levels 1, 3, and 5 for each scan. Bronchial wall were semi-automatically measured from the lobar level to subsegmental level. Spearman correlation analysis was performed between bronchial wall quantification (wall thickness and wall area percentage) and protocol settings (dose, kV, and ADMIRE). ANOVA with a post hoc pairwise test was used to compare signal-to-noise ratio (SNR), noise and bronchial wall quantification values among standard- and low/ultralow-dose settings, and among ADMIRE levels. RESULTS: Bronchial wall quantification had no correlation with dose level, kV, or ADMIRE level (|correlation coefficients| < 0.3). SNR and noise showed no statistically significant differences at different kV in the same ADMIRE level (1, 3, or 5) and in the same dose group (P > 0.05). Generally, there were no significant differences in bronchial wall quantification among the standard- and low/ultralow-dose settings, and among different ADMIRE levels (P > 0.05). CONCLUSION: The combined use of low/ultralow-dose scanning and ADMIRE does not influence bronchial wall quantification compared to standard-dose CT. This specimen study suggests the potential that an ultralow-dose scan can be used for bronchial wall quantification.
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Interpretación de Imagen Radiográfica Asistida por Computador , Tomografía Computarizada por Rayos X , Estudios de Factibilidad , Humanos , Pulmón/diagnóstico por imagen , Masculino , Dosis de RadiaciónRESUMEN
OBJECTIVES: To determine normal pericoronary adipose tissue mean attenuation (PCATMA) values for left the anterior descending (LAD), left circumflex (LCX), and right coronary artery (RCA) in patients without plaques on coronary CT angiography (cCTA), taking into account tube voltage influence. METHODS: This retrospective study included 192 patients (76 (39.6%) men; median age 49 years (range, 19-79)) who underwent cCTA with third-generation dual-source CT for the suspicion of CAD between 2015 and 2017. We selected patients without plaque on cCTA. PCATMA was measured semi-automatically on cCTA images in the proximal segment of the three main coronary arteries with 10 mm length. Paired t-testing was used to compare PCATMA between combinations of two coronary arteries within each patient, and one-way ANOVA testing was used to compare PCATMA in different kV groups. RESULTS: The overall mean ± standard deviation (SD) PCATMA was - 90.3 ± 11.1 HU. PCATMA in men was higher than that in women: - 88.5 ± 10.5 HU versus - 91.5 ± 11.3 HU (p = 0.001). PCATMA of LAD, LCX, and RCA was - 92.4 ± 11.6 HU, - 88.4 ± 9.9 HU, and - 90.2 ± 11.4 HU, respectively. Pairwise comparison of the arteries showed significant difference in PCATMA: LAD and LCX (p < 0.001), LAD and RCA (p = 0.009), LCX and RCA (p = 0.033). PCATMA of the 70 kV, 80 kV, 90 kV, 100 kV, and 120 kV groups was - 95.6 ± 9.6 HU, - 90.2 ± 11.5 HU, - 87.3 ± 9.9 HU, - 82.7 ± 6.2 HU, and - 79.3 ± 6.8 HU, respectively (p < 0.001). CONCLUSIONS: In patients without plaque on cCTA, PCATMA varied by tube voltage, with minor differences in PCATMA between coronary arteries (LAD, LCX, RCA). PCATMA values need to be interpreted taking into account tube voltage setting. KEY POINTS: ⢠In patients without plaque on cCTA, PCATMA differs slightly by coronary artery (LAD, LCX, RCA). ⢠Tube voltage of cCTA affects PCATMA measurement, with mean PCATMA increasing linearly with increasing kV. ⢠For longitudinal cCTA analysis of PCATMA , the use of equal kV setting is strongly recommended.
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Tejido Adiposo/diagnóstico por imagen , Angiografía por Tomografía Computarizada , Angiografía Coronaria , Vasos Coronarios/diagnóstico por imagen , Placa Aterosclerótica/diagnóstico por imagen , Adulto , Anciano , Femenino , Humanos , Masculino , Persona de Mediana Edad , Valores de Referencia , Reproducibilidad de los Resultados , Estudios Retrospectivos , Adulto JovenRESUMEN
OBJECTIVE: The aim of this phantom study was to investigate the effect of scan parameters and noise suppression techniques on the minimum radiation dose for acceptable image quality for CT emphysema densitometry. METHODS: The COPDGene phantom was scanned on a third generation dual-source CT system with 16 scan setups (CTDIvol 0.035-10.680 mGy). Images were reconstructed at 1.0/0.7 mm slice thickness/increment, with three kernels (one soft, two hard), filtered backprojection and three grades of third-generation iterative reconstruction (IR). Additionally, deep learning-based noise suppression software was applied. Main outcomes: overlap in area of the normalized histograms of CT density for the emphysema insert and lung material, and the radiation dose required for a maximum of 4.3% overlap (defined as acceptable image quality). RESULTS: In total, 384 scan reconstructions were analyzed. Decreasing radiation dose resulted in an exponential increase of the overlap in normalized histograms of CT density. The overlap was 11-91% for the lowest dose setting (CTDIvol 0.035mGy). The soft kernel reconstruction showed less histogram overlap than hard filter kernels. IR and noise suppression also reduced overlap. Using intermediate grade IR plus noise suppression software allowed for 85% radiation dose reduction while maintaining acceptable image quality. CONCLUSION: CT density histogram overlap can quantify the degree of discernibility of emphysema and healthy lung tissue. Noise suppression software, IR, and soft reconstruction kernels substantially decrease the dose required for acceptable image quality. ADVANCES IN KNOWLEDGE: Noise suppression software, IR, and soft reconstruction kernels allow radiation dose reduction by 85% while still allowing differentiation between emphysema and normal lung tissue.
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Fantasmas de Imagen , Enfisema Pulmonar/diagnóstico por imagen , Dosis de Radiación , Tomografía Computarizada por Rayos X/métodos , Humanos , Interpretación de Imagen Radiográfica Asistida por Computador/métodosRESUMEN
Lung cancer, chronic obstructive pulmonary disease (COPD), and coronary artery disease (CAD) are expected to cause most deaths by 2050. State-of-the-art computed tomography (CT) allows early detection of lung cancer and simultaneous evaluation of imaging biomarkers for the early stages of COPD, based on pulmonary density and bronchial wall thickness, and of CAD, based on the coronary artery calcium score (CACS), at low radiation dose. To determine cut-off values for positive tests for elevated risk and presence of disease is one of the major tasks before considering implementation of CT screening in a general population. The ImaLife (Imaging in Lifelines) study, embedded in the Lifelines study, is designed to establish the reference values of the imaging biomarkers for the big three diseases in a well-defined general population aged 45 years and older. In total, 12,000 participants will undergo CACS and chest acquisitions with latest CT technology. The estimated percentage of individuals with lung nodules needing further workup is around 1-2%. Given the around 10% prevalence of COPD and CAD in the general population, the expected number of COPD and CAD is around 1000 each. So far, nearly 4000 participants have been included. The ImaLife study will allow differentiation between normal aging of the pulmonary and cardiovascular system and early stages of the big three diseases based on low-dose CT imaging. This information can be finally integrated into personalized precision health strategies in the general population.
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Enfermedad de la Arteria Coronaria/diagnóstico por imagen , Detección Precoz del Cáncer , Neoplasias Pulmonares/diagnóstico por imagen , Pulmón/diagnóstico por imagen , Enfermedad Pulmonar Obstructiva Crónica/diagnóstico por imagen , Tomografía Computarizada por Rayos X/métodos , Adulto , Anciano , Anciano de 80 o más Años , Femenino , Humanos , Masculino , Tamizaje Masivo , Persona de Mediana Edad , Vigilancia de la Población , Valor Predictivo de las PruebasRESUMEN
To investigate the relationship between dynamic changes of coronary artery geometry and coronary artery disease (CAD) using computed tomography (CT). Seventy-one patients underwent coronary CT angiography with retrospective electrocardiographic gating. End-systolic (ES) and end-diastolic (ED) phases were automatically determined by dedicated software. Centerlines were extracted for the right and left coronary artery. Differences between ES and ED curvature and tortuosity were determined. Associations of change in geometrical parameters with plaque types and degree of stenosis were investigated using linear mixed models. The differences in number of inflection points were analyzed using Wilcoxon signed-rank tests. Tests were done on artery and segment level. One hundred thirty-seven arteries (64.3%) and 456 (71.4%) segments were included. Curvature was significantly higher in ES than in ED phase for arteries (p = 0.002) and segments (p < 0.001). The difference was significant only at segment level for tortuosity (p = 0.005). Number of inflection points was significantly higher in ES phase on both artery and segment level (p < 0.001). No significant relationships were found between degree of stenosis and plaque types and dynamic change in geometrical parameters. Non-invasive imaging by cardiac CT can quantify change in geometrical parameters of the coronary arteries during the cardiac cycle. Dynamic change of vessel geometry through the cardiac cycle was not found to be related to the presence of CAD.