Measurement Variability of Same-Day CT Quantification of Interstitial Lung Disease: A Multicenter Prospective Study.

Purpose To investigate quantitative CT (QCT) measurement variability in interstitial lung disease (ILD) on the basis of two same-day CT scans. Materials and Methods Participants with ILD were enrolled in this multicenter prospective study between March and October 2022. Participants underwent two same-day CT scans at an interval of a few minutes. Deep learning-based texture analysis software was used to segment ILD features. Fibrosis extent was defined as the sum of reticular opacity and honeycombing cysts. Measurement variability between scans was assessed with Bland-Altman analyses for absolute and relative differences with 95% limits of agreement (LOA). The contribution of fibrosis extent to variability was analyzed using a multivariable linear mixed-effects model while adjusting for lung volume. Eight readers assessed ILD fibrosis stability with and without QCT information for 30 randomly selected samples. Results Sixty-five participants were enrolled in this study (mean age, 68.7 years ± 10 [SD]; 47 [72%] men, 18 [28%] women). Between two same-day CT scans, the 95% LOA for the mean absolute and relative differences of quantitative fibrosis extent were -0.9% to 1.0% and -14.8% to 16.1%, respectively. However, these variabilities increased to 95% LOA of -11.3% to 3.9% and -123.1% to 18.4% between CT scans with different reconstruction parameters. Multivariable analysis showed that absolute differences were not associated with the baseline extent of fibrosis (P = .09), but the relative differences were negatively associated (ß = -0.252, P < .001). The QCT results increased readers' specificity in interpreting ILD fibrosis stability (91.7% vs 94.6%, P = .02). Conclusion The absolute QCT measurement variability of fibrosis extent in ILD was 1% in same-day CT scans. Keywords: CT, CT-Quantitative, Thorax, Lung, Lung Diseases, Interstitial, Pulmonary Fibrosis, Diagnosis, Computer Assisted, Diagnostic Imaging Supplemental material is available for this article. © RSNA, 2024.

Coronary Artery Calcification on Low-Dose Lung Cancer Screening CT in South Korea: Visual and Artificial Intelligence-Based Assessment and Association With Cardiovascular Events.

Background: Coronary artery calcification (CAC) on lung cancer screening low-dose chest CT (LDCT) is a cardiovascular risk marker. South Korea was the first Asian country to initiate a national LDCT lung cancer screening program, although CAC-related outcomes are poorly explored. Objective: To evaluate CAC prevalence and severity using visual analysis and artificial intelligence (AI) methods and to characterize CAC's association with major adverse cardiovascular events (MACEs) in patients undergoing LDCT in Korea's national lung cancer screening program. Methods: This retrospective study included 1002 patients (mean age, 62.4±5.4 years; 994 men, 8 women) who underwent LDCT at two Korean medical centers between April 2017 and May 2023 as part of Korea's national lung cancer screening program. Two radiologists independently assessed CAC presence and severity using visual analysis, consulting a third radiologist to resolve differences. Two AI software applications were also used to assess CAC presence and severity. MACE occurrences were identified by EMR review. Results: Interreader agreement for CAC presence and severity, expressed as kappa, were 0.793 and 0.671, respectively. CAC prevalence was 53.4% by consensus visual assessment, 56.6% by AI software I, and 60.1% by AI software II. CAC severity was mild, moderate, and severe by consensus visual analysis in 28.0%, 10.3% and 15.1%; by AI software I in 39.9%, 14.0%, and 6.2%; and by AI software II in 34.9%, 14.3%, and 7.3%. MACE occurred in 36 of 625 (5.6%) patients with follow-up after LDCT (median, 1108 days). MACE incidence in patients with no, mild, moderate, and severe CAC, for consensus visual analysis was 1.1%, 5.0%, 2.9%, and 8.6% (p<.001); for AI software I was 1.3%, 3.0%, 7.9%, and 11.3% (p<.001); and for AI software II was 1.2%, 5.0%, 7.7%, and 9.6% (p<.001) Conclusion: For Korea's national lung cancer screening program, MACE occurrence increased significantly with increasing CAC severity, whether assessed by visual analysis or AI software. The study is limited by the large sex imbalance for Korea's national lung cancer screening program. Clinical Impact: The findings provide reference data for healthcare practitioners engaged in developing and overseeing national lung cancer screening programs, highlighting the importance of routine CAC evaluation.

Human-airway surface mesh smoothing based on graph convolutional neural networks.

BACKGROUND AND OBJECTIVE: A detailed representation of the airway geometry in the respiratory system is critical for predicting precise airflow and pressure behaviors in computed tomography (CT)-image-based computational fluid dynamics (CFD). The CT-image-based geometry often contains artifacts, noise, and discontinuities due to the so-called stair step effect. Hence, an advanced surface smoothing is necessary. The existing smoothing methods based on the Laplacian operator drastically shrink airway geometries, resulting in the loss of information related to smaller branches. This study aims to introduce an unsupervised airway-mesh-smoothing learning (AMSL) method that preserves the original geometry of the three-dimensional (3D) airway for accurate CT-image-based CFD simulations. METHOD: The AMSL method jointly trains two graph convolutional neural networks (GCNNs) defined on airway meshes to filter vertex positions and face normal vectors. In addition, it regularizes a combination of loss functions such as reproducibility, smoothness and consistency of vertex positions, and normal vectors. The AMSL adopts the concept of a deep mesh prior model, and it determines the self-similarity for mesh restoration without using a large dataset for training. Images of the airways of 20 subjects were smoothed by the AMSL method, and among them, the data of two subjects were used for the CFD simulations to assess the effect of airway smoothing on flow properties. RESULTS: In 18 of 20 benchmark problems, the proposed smoothing method delivered better results compared with the conventional or state-of-the-art deep learning methods. Unlike the traditional smoothing, the AMSL successfully constructed 20 smoothed airways with airway diameters that were consistent with the original CT images. Besides, CFD simulations with the airways obtained by the AMSL method showed much smaller pressure drop and wall shear stress than the results obtained by the traditional method. CONCLUSIONS: The airway model constructed by the AMSL method reproduces branch diameters accurately without any shrinkage, especially in the case of smaller airways. The accurate estimation of airway geometry using a smoothing method is critical for estimating flow properties in CFD simulations.

Structural and functional features of asthma participants with fixed airway obstruction using CT imaging and 1D computational fluid dynamics: A feasibility study.

Asthma with fixed airway obstruction (FAO) is associated with significant morbidity and rapid decline in lung function, making its treatment challenging. Quantitative computed tomography (QCT) along with data postprocessing is a useful tool to obtain detailed information on airway structure, parenchymal function, and computational flow features. In this study, we aim to identify the structural and functional differences between asthma with and without FAO. The FAO group was defined by a ratio of forced expiratory volume in 1 s (FEV1 ) to forced vital capacity (FVC), FEV1 /FVC <0.7. Accordingly, we obtained two sets of QCT images at inspiration and expiration of asthma subjects without (N = 24) and with FAO (N = 12). Structural and functional QCT-derived airway variables were extracted, including normalized hydraulic diameter, normalized airway wall thickness, functional small airway disease, and emphysema percentage. A one-dimensional (1D) computational fluid dynamics (CFD) model considering airway deformation was used to compare the pressure distribution between the two groups. The computational pressures showed strong correlations with the pulmonary function test (PFT)-based metrics. In conclusion, asthma participants with FAO had worse lung functions and higher-pressure drops than those without FAO.

Interstitial Lung Abnormality in Asian Population.

Interstitial lung abnormalities (ILAs) are radiologic abnormalities found incidentally on chest computed tomography (CT) that can be show a wide range of diseases, from subclinical lung fibrosis to early pulmonary fibrosis including definitive usual interstitial pneumonia. To clear up confusion about ILA, the Fleischner society published a position paper on the definition, clinical symptoms, increased mortality, radiologic progression, and management of ILAs based on several Western cohorts and articles. Recently, studies on long-term outcome, risk factors, and quantification of ILA to address the confusion have been published in Asia. The incidence of ILA was 7% to 10% for Westerners, while the prevalence of ILA was about 4% for Asians. ILA is closely related to various respiratory symptoms or increased rate of treatment-related complication in lung cancer. There is little difference between Westerners and Asians regarding the clinical importance of ILA. Although the role of quantitative CT as a screening tool for ILA requires further validation and standardized imaging protocols, using a threshold of 5% in at least one zone demonstrated 67.6% sensitivity, 93.3% specificity, and 90.5% accuracy, and a 1.8% area threshold showed 100% sensitivity and 99% specificity in South Korea. Based on the position paper released by the Fleischner society, I would like to report how much ILA occurs in the Asian population, what the prognosis is, and review what management strategies should be pursued in the future.

External validation of deep learning-based automated detection algorithm for chest radiograph: practical issues in outpatient clinic.

BACKGROUND: There have been no reports on diagnostic performance of deep learning-based automated detection (DLAD) for thoracic diseases in real-world outpatient clinic. PURPOSE: To validate DLAD for use at an outpatient clinic and analyze the interpretation time for chest radiographs. MATERIAL AND METHODS: This is a retrospective single-center study. From 18 January 2021 to 18 February 2021, 205 chest radiographs with DLAD and paired chest CT from 205 individuals (107 men and 98 women; mean ± SD age: 63 ± 8 years) from an outpatient clinic were analyzed for external validation and observer performance. Two radiologists independently reviewed the chest radiographs by referring to the paired chest CT and made reference standards. Two pulmonologists and two thoracic radiologists participated in observer performance tests, and the total amount of time taken during the test was measured. RESULTS: The performance of DLAD (area under the receiver operating characteristic curve [AUC] = 0.920) was significantly higher than that of pulmonologists (AUC = 0.756) and radiologists (AUC = 0.782) without assistance of DLAD. With help of DLAD, the AUCs were significantly higher for both groups (pulmonologists AUC = 0.853; radiologists AUC = 0.854). A greater than 50% decrease in mean interpretation time was observed in the pulmonologist group with assistance of DLAD compared to mean reading time without aid of DLAD (from 67 s per case to 30 s per case). No significant difference was observed in the radiologist group (from 61 s per case to 61 s per case). CONCLUSION: DLAD demonstrated good performance in interpreting chest radiographs of patients at an outpatient clinic, and was especially helpful for pulmonologists in improving performance.

Quantitative CT Analysis Based on Smoking Habits and Chronic Obstructive Pulmonary Disease in Patients with Normal Chest CT.

Purpose: To assess normal CT scans with quantitative CT (QCT) analysis based on smoking habits and chronic obstructive pulmonary disease (COPD). Materials and Methods: From January 2013 to December 2014, 90 male patients with normal chest CT and quantification analysis results were enrolled in our study [non-COPD never-smokers (n = 38) and smokers (n = 45), COPD smokers (n = 7)]. In addition, an age-matched cohort study was performed for seven smokers with COPD. The square root of the wall area of a hypothetical bronchus of internal perimeter 10 mm (Pi10), skewness, kurtosis, mean lung attenuation (MLA), and percentage of low attenuation area (%LAA) were evaluated. Results: Among patients without COPD, the Pi10 of smokers (4.176 ± 0.282) was about 0.1 mm thicker than that of never-smokers (4.070 ± 0.191, p = 0.047), and skewness and kurtosis of smokers (2.628 ± 0.484 and 6.448 ± 3.427) were lower than never-smokers (2.884 ± 0.624, p = 0.038 and 8.594 ± 4.944, p = 0.02). The Pi10 of COPD smokers (4.429 ± 0.435, n = 7) was about 0.4 mm thicker than never-smokers without COPD (3.996 ± 0.115, n = 14, p = 0.005). There were no significant differences in MLA and %LAA between groups (p > 0.05). Conclusion: Even on normal CT scans, QCT showed that the airway walls of smokers are thicker than never-smokers regardless of COPD and it preceded lung parenchymal changes.

Interstitial Lung Abnormalities at CT in the Korean National Lung Cancer Screening Program: Prevalence and Deep Learning-based Texture Analysis.

Background Interstitial lung abnormalities (ILAs) are associated with worse clinical outcomes, but ILA with lung cancer screening CT has not been quantitatively assessed. Purpose To determine the prevalence of ILA at CT examinations from the Korean National Lung Cancer Screening Program and define an optimal lung area threshold for ILA detection with CT with use of deep learning-based texture analysis. Materials and Methods This retrospective study included participants who underwent chest CT between April 2017 and December 2020 at two medical centers participating in the Korean National Lung Cancer Screening Program. CT findings were classified by three radiologists into three groups: no ILA, equivocal ILA, and ILA (fibrotic and nonfibrotic). Progression was evaluated between baseline and last follow-up CT scan. The extent of ILA was assessed visually and quantitatively with use of deep learning-based texture analysis. The Youden index was used to determine an optimal cutoff value for detecting ILA with use of texture analysis. Demographics and ILA subcategories were compared between participants with progressive and nonprogressive ILA. Results A total of 3118 participants were included in this study, and ILAs were observed with the CT scans of 120 individuals (4%). The median extent of ILA calculated by the quantitative system was 5.8% for the ILA group, 0.7% for the equivocal ILA group, and 0.1% for the no ILA group (P < .001). A 1.8% area threshold in a lung zone for quantitative detection of ILA showed 100% sensitivity and 99% specificity. Progression was observed in 48% of visually assessed fibrotic ILAs (15 of 31), and quantitative extent of ILA increased by 3.1% in subjects with progression. Conclusion ILAs were detected in 4% of the Korean lung cancer screening population. Deep learning-based texture analysis showed high sensitivity and specificity for detecting ILA with use of a 1.8% lung area cutoff value. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Egashira and Nishino in this issue.

An unsupervised image registration method employing chest computed tomography images and deep neural networks.

BACKGROUND: Deformable image registration is crucial for multiple radiation therapy applications. Fast registration of computed tomography (CT) lung images is challenging because of the large and nonlinear deformation between inspiration and expiration. With advancements in deep learning techniques, learning-based registration methods are considered efficient alternatives to traditional methods in terms of accuracy and computational cost. METHOD: In this study, an unsupervised lung registration network (LRN) with cycle-consistent training is proposed to align two acquired CT-derived lung datasets during breath-holds at inspiratory and expiratory levels without utilizing any ground-truth registration results. Generally, the LRN model uses three loss functions: image similarity, regularization, and Jacobian determinant. Here, LRN was trained on the CT datasets of 705 subjects and tested using 10 pairs of public CT DIR-Lab datasets. Furthermore, to evaluate the effectiveness of the registration technique, target registration errors (TREs) of the LRN model were compared with those of the conventional algorithm (sum of squared tissue volume difference; SSTVD) and a state-of-the-art unsupervised registration method (VoxelMorph). RESULTS: The results showed that the LRN with an average TRE of 1.78 ± 1.56 mm outperformed VoxelMorph with an average TRE of 2.43 ± 2.43 mm, which is comparable to that of SSTVD with an average TRE of 1.66 ± 1.49 mm. In addition, estimating the displacement vector field without any folding voxel consumed less than 2 s, demonstrating the superiority of the learning-based method with respect to fiducial marker tracking and the overall soft tissue alignment with a nearly real-time speed. CONCLUSIONS: Therefore, this proposed method shows significant potential for use in time-sensitive pulmonary studies, such as lung motion tracking and image-guided surgery.

[Lung Imaging Reporting and Data System (Lung-RADS) in Radiology: Strengths, Weaknesses and Improvement]. / 영상의학에서 폐영상 íŒë ê³¼ 자료체계: ê°•ì , ë‹¨ì , ê·¸ë¦¬ê³ ê°œì„ .

In 2019, the American College of Radiology announced Lung CT Screening Reporting & Data System (Lung-RADS) 1.1 to reduce lung cancer false positivity compared to that of Lung-RADS 1.0 for effective national lung cancer screening, and in December 2022, announced the new Lung-RADS 1.1, Lung-RADS® 2022 improvement. The Lung-RADS® 2022 measures the nodule size to the first decimal place compared to that of the Lung-RADS 1.0, to category 2 until the juxtapleural nodule size is < 10 mm, increases the size criterion of the ground glass nodule to 30 mm in category 2, and changes categories 4B and 4X to extremely suspicious. The category was divided according to the airway nodules location and shape or wall thickness of atypical pulmonary cysts. Herein, to help radiologists understand the Lung-RADS® 2022, this review will describe its advantages, disadvantages, and future improvements.

Prevalence and Long-term Outcomes of CT Interstitial Lung Abnormalities in a Health Screening Cohort.

Background The association between interstitial lung abnormalities (ILAs) and long-term outcomes has not been reported in Asian health screening populations. Purpose To investigate ILA prevalence in an Asian health screening cohort and determine rates and risks for ILA progression, lung cancer development, and mortality within the 10-year follow-up. Materials and Methods This observational, retrospective multicenter study included patients aged 50 years or older who underwent chest CT at three health screening centers over a 4-year period (2007-2010). ILA status was classified as none, equivocal ILA, and ILA (nonfibrotic or fibrotic). Progression was evaluated from baseline to the last follow-up CT examination, when available. The log-rank test was performed to compare mortality rates over time between ILA statuses. Multivariable Cox proportional hazards models were used to assess factors associated with hazards of ILA progression, lung cancer development, and mortality. Results Of the 2765 included patients (mean age, 59 years ± 7 [SD]; 2068 men), 94 (3%) had a finding of ILA (35 nonfibrotic and 59 fibrotic ILA) and 119 (4%) had equivocal ILA. The median time for CT follow-up and the entire observation was 8 and 12 years, respectively. ILA progression was observed in 80% (48 of 60) of patients with ILA over 8 years. Those with fibrotic and nonfibrotic ILA had a higher mortality rate than those without ILA (P < .001 and P = .01, respectively) over 12 years. Fibrotic ILA was independently associated with ILA progression (hazard ratio [HR], 10.3; 95% CI: 6.4, 16.4; P < .001), lung cancer development (HR, 4.4; 95% CI: 2.1, 9.1; P < .001), disease-specific mortality (HR, 6.7; 95% CI: 3.7, 12.2; P < .001), and all-cause mortality (HR, 2.5; 95% CI: 1.6, 3.8; P < .001) compared with no ILA. Conclusion The prevalence of interstitial lung abnormalities (ILAs) in an Asian health screening cohort was approximately 3%, and fibrotic ILA was an independent risk factor for ILA progression, lung cancer development, and mortality. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Hatabu and Hata in this issue.

Practical study on reconstruction of the regional anatomy course system based on clinical practice ability / 中华医学教育探索杂志

Regional anatomy teaching not only requires students to deal with the basic knowledge of human body including the level, location and adjacent relationship, but also to understand the clinical application of anatomical structure. Based on the four aspects of field anatomy, simulated surgery, clinical application lectures and CBL teaching, this study formulated a suitable assessment method to reconstruct the teaching system of regional anatomy relying on the improvement of the laboratory environment and the teacher team, aiming at cultivating students' clinical practice ability as the core and building a new regional anatomy course to meet the teaching needs of the new era.

The research status and development trends of brain-computer interfaces in medicine / 生物医学工程学杂志

Brain-computer interfaces (BCIs) have become one of the cutting-edge technologies in the world, and have been mainly applicated in medicine. In this article, we sorted out the development history and important scenarios of BCIs in medical application, analyzed the research progress, technology development, clinical transformation and product market through qualitative and quantitative analysis, and looked forward to the future trends. The results showed that the research hotspots included the processing and interpretation of electroencephalogram (EEG) signals, the development and application of machine learning algorithms, and the detection and treatment of neurological diseases. The technological key points included hardware development such as new electrodes, software development such as algorithms for EEG signal processing, and various medical applications such as rehabilitation and training in stroke patients. Currently, several invasive and non-invasive BCIs are in research. The R&D level of BCIs in China and the United State is leading the world, and have approved a number of non-invasive BCIs. In the future, BCIs will be applied to a wider range of medical fields. Related products will develop shift from a single mode to a combined mode. EEG signal acquisition devices will be miniaturized and wireless. The information flow and interaction between brain and machine will give birth to brain-machine fusion intelligence. Last but not least, the safety and ethical issues of BCIs will be taken seriously, and the relevant regulations and standards will be further improved.

[Use of Coronary CT Angiography as a Screening Tool for Coronary Artery Disease in Asymptomatic Healthy Individuals or Patients]. / 무증상 ì •ìƒì¸ 또는 환자의 관상동맥 질환 ì„ ë³„ 검사로서 관상동맥 ì „ì‚°í™”ë‹¨ì¸µì´¬ì˜ í˜ˆê´€ì¡°ì˜ìˆ ì˜ ìœ ìš©ì„±.

Early detection of potential asymptomatic coronary artery disease is very important, as patients with sudden cardiac death often do not show symptoms such as chest pain or motor dyspnea. Coronary CT angiography (CCTA) has long been unjustified as a screening tool for asymptomatic patients because of the risks posed by radiation exposure. However, there are still various opinions regarding the usefulness of CCTA for screening for coronary artery disease (CAD) in asymptomatic healthy individuals or patients. This review investigated the usefulness of coronary artery calcium score and CCTA as screening tests for CAD in asymptomatic healthy individuals or patients through various literature reviews. With the development of CT technology, recent studies have been conducted in asymptomatic CAD patients with a reduced radiation dose of less than 1 mSv. A total of 2.6% of asymptomatic subjects on CCTA found significant CAD over 70%, and it was concluded that screening CCTA for CAD showed prognostic power in predicting the future occurrence of CAD in asymptomatic people. However, after the completion of the current NIH SCOT-HEART 2 study, it may be possible to determine whether CCTA is appropriate as a screening tool for CAD in asymptomatic healthy individuals.

CT-based lung motion differences in patients with usual interstitial pneumonia and nonspecific interstitial pneumonia.

We applied quantitative CT image matching to assess the degree of motion in the idiopathic ILD such as usual interstitial pneumonia (UIP) and nonspecific interstitial pneumonia (NSIP). Twenty-one normal subjects and 42 idiopathic ILD (31 UIP and 11 NSIP) patients were retrospectively included. Inspiratory and expiratory CT images, reviewed by two experienced radiologists, were used to compute displacement vectors at local lung regions matched by image registration. Normalized three-dimensional and two-dimensional (dorsal-basal) displacements were computed at a sub-acinar scale. Displacements, volume changes, and tissue fractions in the whole lung and the lobes were compared between normal, UIP, and NSIP subjects. The dorsal-basal displacement in lower lobes was smaller in UIP patients than in NSIP or normal subjects (p = 0.03, p = 0.04). UIP and NSIP were not differentiated by volume changes in the whole lung or upper and lower lobes (p = 0.53, p = 0.12, p = 0.97), whereas the lower lobe air volume change was smaller in both UIP and NSIP than normal subjects (p = 0.02, p = 0.001). Regional expiratory tissue fractions and displacements showed positive correlations in normal and UIP subjects but not in NSIP subjects. In summary, lung motionography quantified by image registration-based lower lobe dorsal-basal displacement may be used to assess the degree of motion, reflecting limited motion due to fibrosis in the ILD such as UIP and NSIP.

Integrated Bioinformatics and Validation of lncRNA-Mediated ceRNA Network in Myocardial Ischemia/Reperfusion Injury.

Background: Myocardial ischemia/reperfusion (MI/R) injury is a common pathology in ischemia heart disease. Long noncoding RNAs (lncRNAs) are significant regulators related to many ischemia/reperfusion conditions. This study is aimed at exploring the molecule mechanism of lncRNA-mediated competing endogenous RNA (ceRNA) network in MI/R. Methods: The dataset profiles of MI/R and normal tissues (GSE130217 and GSE124176) were obtained from the GEO database. Integrated bioinformatics were performed to screen out differentially expressed genes (DEGs). Thereafter, an lncRNA-mediated ceRNA network was constructed by the starBase database. The GO annotations and KEGG pathway analysis were conducted to study action mechanism and related pathways of DEGs in MI/R. A model of hypoxia/reoxygenation- (H/R-) treated HL-1 cell was performed to verify the expression of lncRNAs through qRT-PCR. Results: 2406 differentially expressed- (DE-) mRNAs, 70 DE-lncRNAs, and 156 DE-miRNAs were acquired. These DEGs were conducted to construct an lncRNA-mediated ceRNA network, and a subnetwork including lncRNA Xist/miRNA-133c/mRNA (Slc30a9) was screen out. The functional enrichment analyses revealed that the lncRNAs involved in the ceRNA network might functions in oxidative stress and calcium signaling pathway. The lncRNA Xist expression is reduced under H/R conditions, followed by the increased level of miRNA-133c, thus downregulating the expression of Slc30a9. Conclusion: In sum, the identified ceRNA network which included the lncRNA Xist/miR-133c/Slc30a9 axis might contribute a better understanding to the pathogenesis and development of MI/R injury and offer a novel targeted therapy way.

What Findings on Chest CTs Can Delay Diagnosis of Pleuropulmonary Paragonimiasis?

PURPOSE: The purpose of this study was to investigate which findings were delayed in diagnosis with respect to chest CT findings of paragonimiasis. METHODS: This retrospective, informed questionnaire study was conducted to evaluate chest CT scans of 103 patients (58 men and 45 women; mean age 46.1 ± 14.6 years). The patients were diagnosed with paragonimiasis from 2003 to 2008 in four tertiary hospitals. Statistical analysis was performed using the chi-square test to identify differences between an initially correct diagnosis and an incorrect one of paragonimiasis on chest CT scans, for which we evaluated such variables as the location of lesion, type of parenchymal lesions, and worm migration track. RESULTS: Nodular opacities on chest CT scans were the most common findings (53/94, 56.4%). The sign of worm migration tracks was only present in 18.1% of cases (17/94). Although statistically insignificant, the form of consolidation (18/25, 72%) and mass (6/8, 75%) on CT was common in correct diagnostics, and the form of the worm migration track (12/17, 70.6%) was high in correct diagnostics. CONCLUSION: A delayed diagnosis of paragonimiasis may often be made in patients with non-nodular, parenchymal lesions who are negative for worm migration track on chest CT scans.

Congenital atlanto-occipital fusion and its effect on the myodural bridge: a case report utilizing the P45 plastination technique / Fusión atlanto-occipital congénita y su efecto sobre el puente miodural: reporte de un caso utilizando la técnica de plastinación P45

SUMMARY: The atlanto-occipital joint is composed of the superior fossa of the lateral masses of the atlas (C1) and the occipital condyles. Congenital Atlanto-occipital fusion (AOF) involves the osseous union of the base of the occiput (C0) and the atlas (C1). AOF or atlas occipitalization/assimilation represents a craniovertebral junction malformation (CVJM) which can be accompanied by other cranial or spinal malformations. AOF may be asymptomatic or patients may experience symptoms from neural compression as well as limited neck movement. The myodural bridge (MDB) complex is a dense fibrous structure that connects the suboccipital muscular and its related facia to the cervical spinal dura mater, passing through both the posterior atlanto-occipital and atlanto-axial interspaces. It is not known if atlas occipitilization can induce structural changes in the MDB complex and its associated suboccipital musculature. The suboccipital region of a cadaveric head and neck specimen from an 87-year-old Chinese male having a congenital AOF malformation with resultant changes to the MDB complex was observed. After being treated with the P45 plastination method, multiple slices obtained from the cadaveric head and neck specimen were examined with special attention paid to the suboccipital region and the CVJM. Congenital atlanto-occipital fusion malformations are defined as partial or complete fusion of the base of the occiput (C0) with the atlas (C1). In the present case of CVJM, unilateral fusion of the left occipital condyle with the left lateral mass of C1 was observed, as well as posterior central fusion of the posterior margin of the foramen magnum with the posterior arch of C1. Also noted was a unilateral variation of the course of the vertebral artery due to the narrowed posterior atlanto-occipital interspace. Surprisingly, complete agenesis of the rectus capitis posterior minor (RCPmi) and the obliques capitis superior (OCS) muscles was also observed in the plastinated slices. Interestingly, the MDB, which normally originates in part from the RCPmi muscle, was observed to originate from a superior bifurcation within an aspect of the nuchal ligament. Therefore, the observed changes involving the MDB complex appear to be an effective compensation to the suboccipital malformations.

RESUMEN: La articulación atlanto-occipital está compuesta por las caras articulares superiores de las masas laterales del atlas (C1) y los cóndilos occipitales. La fusión atlanto-occipital congénita (FAO) implica la unión ósea de la base del occipucio (C0) y el atlas (C1). La FAO u occipitalización/asimilación del atlas representa una malformación de la unión craneovertebral (MUCV) que puede presentar otras malformaciones craneales o espinales. La FAO puede ser asintomática o los pacientes pueden experimentar síntomas de compresión neural así como movimiento limitado del cuello. El complejo del puente miodural (PMD) es una estructura fibrosa densa que conecta el músculo suboccipital y su fascia relacionada con la duramadre espinal cervical, pasando a través de los espacios intermedios atlanto-occipital posterior y atlanto-axial. No se sabe si la occipitilización del atlas puede inducir cambios estructurales en el complejo PMD y en la musculatura suboccipital. Se observó en la región suboccipital de un espécimen cadavérico, cabeza y cuello de un varón chino de 87 años con una malformación congénita de FAO con los cambios resultantes en el complejo PMD. Se examinaron múltiples cortes obtenidos de la muestra de cabeza y cuello después de ser tratados con el método de plastinación P45, con especial atención a la región suboccipital y la MUCV. Las malformaciones congénitas por fusión atlanto-occipital se definen como la fusión parcial o completa de la base del occipucio (C0) con el atlas (C1). En el presente caso de MUCV se observó la fusión unilateral del cóndilo occipital izquierdo con la masa lateral izquierda de C1, así como fusión posterior central del margen posterior del foramen magnum con el arco posterior de C1. También se observó una variación unilateral del curso de la arteria vertebral por el estrechamiento del espacio interatlanto-occipital posterior. Se observó además agenesia completa de los músculos Rectus capitis posterior minor (RCPmi) y oblicuos capitis superior (OCS) en los cortes plastinados. Curiosamente, se observó que el MDB, que normalmente se origina en parte del músculo RCPmi, se origina en una bifurcación superior dentro de un aspecto del ligamento nucal. Por lo tanto, los cambios observados en el complejo PMD parecen ser una compensación de las malformaciones suboccipitales.

Structural and functional alterations of subjects with cement dust exposure: A longitudinal quantitative computed tomography-based study.

Cement dust exposure (CDE) can be a risk factor for pulmonary disease, causing changes in segmental airways and parenchymal lungs. This study investigates longitudinal alterations in quantitative computed tomography (CT)-based metrics due to CDE. We obtained CT-based airway structural and lung functional metrics from CDE subjects with baseline CT and follow-up CT scans performed three years later. From the CT, we extracted wall thickness (WT) and bifurcation angle (θ) at total lung capacity (TLC) and functional residual capacity (FRC), respectively. We also computed air volume (Vair), tissue volume (Vtissue), global lung shape, percentage of emphysema (Emph%), and more. Clinical measures were used to associate with CT-based metrics. Three years after their baseline, the pulmonary function tests of CDE subjects were similar or improved, but there were significant alterations in the CT-based structural and functional metrics. The follow-up CT scans showed changes in θ at most of the central airways; increased WT at the subgroup bronchi; smaller Vair at TLC at all except the right upper and lower lobes; smaller Vtissue at all lobes in TLC and FRC except for the upper lobes in FRC; smaller global lung shape; and greater Emph% at the right upper and lower lobes. CT-based structural and functional variables are more sensitive to the early identification of CDE subjects, while most clinical lung function changes were not noticeable. We speculate that the significant long-term changes in CT are uniquely observed in CDE subjects, different from smoking-induced structural changes.

Quantitative Assessment of Airway Changes in Fibrotic Interstitial Lung Abnormality Patients by Chest CT According to Cumulative Cigarette Smoking.

Purpose: The aim of this study was to evaluate the role of Pi10 in patients with fibrotic interstitial lung abnormality (fibrotic ILA) in a chest CT, according to cumulative cigarette smoking. Methods: We retrospectively assessed 54 fibrotic ILA patients and 18 healthy non-smokers (control) who underwent non-enhanced CT and pulmonary function tests. We quantitatively analyzed airway changes (the inner luminal area, airway inner parameter, airway wall thickness, Pi10, skewness, and kurtosis) in the chest CT of fibrotic ILA patients, and the fibrotic ILA patients were categorized into groups based on pack-years: light, moderate, heavy. Airway change data and pulmonary function tests among the three groups of fibrotic ILA patients were compared with those of the control group by one-way ANOVA. Results: Mean skewness (2.58 ± 0.36) and kurtosis (7.64 ± 2.36) in the control group were significantly different from those of the fibrotic ILA patients (1.89 ± 0.37 and 3.62 ± 1.70, respectively, p < 0.001). In fibrotic ILA group, only heavy smokers had significantly increased Pi10 (mean increase 0.04, p = 0.013), increased airway wall thickness of the segmental bronchi (mean increase 0.06 mm, p = 0.005), and decreased lung diffusing capacity for carbon monoxide (p = 0.023). Conclusion: Pi10, as a biomaker of quantitative CT in fibrotic ILA patients, can reveal that smoking affects airway remodeling.