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Keywords = pulmonary lobe segmentation

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12 pages, 2010 KiB  
Article
Prevalence and Clinical Implications of Pulmonary Vein Stenosis in Bronchiectasis: A 3D Reconstruction CT Study
by Xin Li, Yang Gu, Jinbai Miao, Ying Ji, Mingming Shao and Bin Hu
Adv. Respir. Med. 2024, 92(6), 526-537; https://doi.org/10.3390/arm92060046 - 16 Dec 2024
Viewed by 1273
Abstract
Background: Recent studies on bronchiectasis have revealed significant structural abnormalities and pathophysiological changes. However, there is limited research focused on pulmonary venous variability and congenital variation. Through our surgical observations, we noted that coarctation of pulmonary veins and atrophied lung volume are relatively [...] Read more.
Background: Recent studies on bronchiectasis have revealed significant structural abnormalities and pathophysiological changes. However, there is limited research focused on pulmonary venous variability and congenital variation. Through our surgical observations, we noted that coarctation of pulmonary veins and atrophied lung volume are relatively common in bronchiectasis patients. Therefore, we conducted a retrospective study to explore pulmonary venous variation and secondary manifestations in bronchiectasis cases, utilizing 3D reconstruction software (Mimics Innovation Suite 21.0, Materialise Dental, Leuven, Belgium) to draw conclusions supported by statistical evidence. Method: This retrospective study included patients with bronchiectasis and healthy individuals who underwent CT examinations at Beijing Chao-Yang Hospital between January 2017 and July 2023. Chest CT data were reconstructed using Materialise Mimics. Pulmonary veins and lung lobes were segmented from surrounding tissue based on an appropriate threshold determined by local grey values and image gradients. Subsequently, venous cross-sectional areas and lung volumes were measured for statistical analysis. Result: CT data from 174 inpatients with bronchiectasis and 75 cases from the health examination center were included. Three-dimensional reconstruction data revealed a significant reduction in cross-sectional areas of pulmonary veins in the left lower lobe (p < 0.001), the right lower lobe (p = 0.030), and the right middle lobe (p = 0.009) of bronchiectasis patients. Subgroup analyses indicated that approximately 73.5% of localized cases of the left lower lobe exhibited pulmonary vein stenosis, while in the diffuse group, this proportion was only 52.6%. Furthermore, the cross-sectional area of pulmonary veins had a gradually decreasing trend, based on a small sample. Lung function tests showed significant reductions in FEV1, FVC, and FEV1% in bronchiectasis patients, attributed to the loss of lung volume in the left lower lobe, which accounted for 60.9% of the included sample. Conclusions: Our recent findings suggest that pulmonary venous stenosis is a common variation in bronchiectasis and is often observed concurrently with reduced lung volume, particularly affecting the left lower lobe. Moreover, localized cases are more likely to suffer from pulmonary venous stenosis, with an ambiguous downtrend as the disease progresses. In conclusion, increased attention to pulmonary venous variation in bronchiectasis is warranted, and exploring new therapies to intervene in the early stages or alleviate obstruction may be beneficial. Full article
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20 pages, 3823 KiB  
Article
Pulmonary Fissure Segmentation in CT Images Using Image Filtering and Machine Learning
by Mikhail Fufin, Vladimir Makarov, Vadim I. Alfimov, Vladislav V. Ananev and Anna Ananeva
Tomography 2024, 10(10), 1645-1664; https://doi.org/10.3390/tomography10100121 - 9 Oct 2024
Cited by 1 | Viewed by 1678
Abstract
Background: Both lung lobe segmentation and lung fissure segmentation are useful in the clinical diagnosis and evaluation of lung disease. It is often of clinical interest to quantify each lobe separately because many diseases are associated with specific lobes. Fissure segmentation is important [...] Read more.
Background: Both lung lobe segmentation and lung fissure segmentation are useful in the clinical diagnosis and evaluation of lung disease. It is often of clinical interest to quantify each lobe separately because many diseases are associated with specific lobes. Fissure segmentation is important for a significant proportion of lung lobe segmentation methods, as well as for assessing fissure completeness, since there is an increasing requirement for the quantification of fissure integrity. Methods: We propose a method for the fully automatic segmentation of pulmonary fissures on lung computed tomography (CT) based on U-Net and PAN models using a Derivative of Stick (DoS) filter for data preprocessing. Model ensembling is also used to improve prediction accuracy. Results: Our method achieved an F1 score of 0.916 for right-lung fissures and 0.933 for left-lung fissures, which are significantly higher than the standalone DoS results (0.724 and 0.666, respectively). We also performed lung lobe segmentation using fissure segmentation. The lobe segmentation algorithm shows results close to those of state-of-the-art methods, with an average Dice score of 0.989. Conclusions: The proposed method segments pulmonary fissures efficiently and have low memory requirements, which makes it suitable for further research in this field involving rapid experimentation. Full article
(This article belongs to the Topic AI in Medical Imaging and Image Processing)
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11 pages, 3583 KiB  
Article
Increased Scan Speed and Pitch on Ultra-Low-Dose Chest CT: Effect on Nodule Volumetry and Image Quality
by Heejoo Bae, Ji Won Lee, Yeon Joo Jeong, Min-Hee Hwang and Geewon Lee
Medicina 2024, 60(8), 1301; https://doi.org/10.3390/medicina60081301 - 12 Aug 2024
Viewed by 1574
Abstract
Background and Objectives: This study’s objective was to investigate the influence of increased scan speed and pitch on image quality and nodule volumetry in patients who underwent ultra-low-dose chest computed tomography (CT). Material and Methods: One hundred and two patients who [...] Read more.
Background and Objectives: This study’s objective was to investigate the influence of increased scan speed and pitch on image quality and nodule volumetry in patients who underwent ultra-low-dose chest computed tomography (CT). Material and Methods: One hundred and two patients who had lung nodules were included in this study. Standard-speed, standard-pitch (SSSP) ultra-low-dose CT and high-speed, high-pitch (HSHP) ultra-low-dose CT were obtained for all patients. Image noise was measured as the standard deviation of attenuation. One hundred and sixty-three nodules were identified and classified according to location, volume, and nodule type. Volume measurement of detected pulmonary nodules was compared according to nodule location, volume, and nodule type. Motion artifacts at the right middle lobe, the lingular segment, and both lower lobes near the lung bases were evaluated. Subjective image quality analysis was also performed. Results: The HSHP CT scan demonstrated decreased motion artifacts at the left upper lobe lingular segment and left lower lobe compared to the SSSP CT scan (p < 0.001). The image noise was higher and the radiation dose was lower in the HSHP scan (p < 0.001). According to the nodule type, the absolute relative volume difference was significantly higher in ground glass opacity nodules compared with those of part-solid and solid nodules (p < 0.001). Conclusion: Our study results suggest that HSHP ultra-low-dose chest CT scans provide decreased motion artifacts and lower radiation doses compared to SSSP ultra-low-dose chest CT. However, lung nodule volumetry should be performed with caution for ground glass opacity nodules. Full article
(This article belongs to the Section Pulmonology)
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17 pages, 1320 KiB  
Article
The Importance of Topographical Recognition of Pulmonary Arteries in Diagnostics and Treatment of CTEPH, Based on an Analysis of a Dissected Case Model—A Pilot Study
by Matiss Zicans, Dzintra Kazoka, Mara Pilmane and Andris Skride
Diagnostics 2024, 14(15), 1684; https://doi.org/10.3390/diagnostics14151684 - 3 Aug 2024
Cited by 1 | Viewed by 1796
Abstract
Background: Knowledge of the anatomy of pulmonary arteries is essential in many invasive procedures concerning pulmonary circulation. In the diagnosis and treatment of chronic thromboembolic pulmonary hypertension (CTEPH), two-dimensional (2D) pulmonary angiography is used. Recognizing the topographic course of the pulmonary arteries and [...] Read more.
Background: Knowledge of the anatomy of pulmonary arteries is essential in many invasive procedures concerning pulmonary circulation. In the diagnosis and treatment of chronic thromboembolic pulmonary hypertension (CTEPH), two-dimensional (2D) pulmonary angiography is used. Recognizing the topographic course of the pulmonary arteries and understanding the status in three dimensions (3D) is paramount. This study aimed to evaluate and describe the branching variant of pulmonary arteries in a single case, as well as morphological parameters of the segmental arteries, like length, diameter and branching angles. Methods: One pair of embalmed human cadaver lungs was dissected by a scalpel and surgical forceps and was measured up to the subsegmental arteries. Results: The diameters (ranging from 3.04 to 9.29 mm) and lengths (ranging from 9.09 to 53.91 mm) of the pulmonary segmental arteries varied. The proximal branching angles were wide and close to perpendicular, while distally, the angles between the segmental and subsegmental arteries were narrower (30–45°). Upon evaluating the branching, rare variations were identified and delineated, notably in the lower lobes of both lungs. Conclusions: Utilizing knowledge and data in clinical settings is instrumental for effectively diagnosing and treating CTEPH. Further research is required to explore the complications in invasive procedures related to various anatomical variations. Full article
(This article belongs to the Special Issue Advances in Human Anatomy)
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21 pages, 13456 KiB  
Article
Tracking Ovine Pulmonary Adenocarcinoma Development Using an Experimental Jaagsiekte Sheep Retrovirus Infection Model
by Chris Cousens, James Meehan, David Collie, Steven Wright, Ziyuan Chang, Helen Todd, Jo Moore, Lynn Grant, Carola R. Daniel, Peter Tennant, Adrian Ritchie, James Nixon, Chris Proudfoot, Stefano Guido, Helen Brown, Calum D. Gray, Tom J. MacGillivray, R. Eddie Clutton, Stephen N. Greenhalgh, Rachael Gregson, David J. Griffiths, James Spivey, Nicole Storer, Chad E. Eckert and Mark Grayadd Show full author list remove Hide full author list
Genes 2024, 15(8), 1019; https://doi.org/10.3390/genes15081019 - 2 Aug 2024
Cited by 4 | Viewed by 1930
Abstract
Ovine pulmonary adenocarcinoma (OPA) is an infectious, neoplastic lung disease of sheep that causes significant animal welfare and economic issues throughout the world. Understanding OPA pathogenesis is key to developing tools to control its impact. Central to this need is the availability of [...] Read more.
Ovine pulmonary adenocarcinoma (OPA) is an infectious, neoplastic lung disease of sheep that causes significant animal welfare and economic issues throughout the world. Understanding OPA pathogenesis is key to developing tools to control its impact. Central to this need is the availability of model systems that can monitor and track events after Jaagsiekte sheep retrovirus (JSRV) infection. Here, we report the development of an experimentally induced OPA model intended for this purpose. Using three different viral dose groups (low, intermediate and high), localised OPA tumour development was induced by bronchoscopic JSRV instillation into the segmental bronchus of the right cardiac lung lobe. Pre-clinical OPA diagnosis and tumour progression were monitored by monthly computed tomography (CT) imaging and trans-thoracic ultrasound scanning. Post mortem examination and immunohistochemistry confirmed OPA development in 89% of the JSRV-instilled animals. All three viral doses produced a range of OPA lesion types, including microscopic disease and gross tumours; however, larger lesions were more frequently identified in the low and intermediate viral groups. Overall, 31% of JSRV-infected sheep developed localised advanced lesions. Of the sheep that developed localised advanced lesions, tumour volume doubling times (calculated using thoracic CT 3D reconstructions) were 14.8 ± 2.1 days. The ability of ultrasound to track tumour development was compared against CT; the results indicated a strong significant association between paired CT and ultrasound measurements at each time point (R2 = 0.799, p < 0.0001). We believe that the range of OPA lesion types induced by this model replicates aspects of naturally occurring disease and will improve OPA research by providing novel insights into JSRV infectivity and OPA disease progression. Full article
(This article belongs to the Special Issue Application of Animal Modeling in Cancer)
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7 pages, 1304 KiB  
Case Report
Fatal Hemoptysis Secondary to Severe Pulmonary Veins Stenosis and Fibrosing Mediastinitis following Radiofrequency Ablation for Atrial Fibrillation: A Case Report and Review of the Literature
by Vladut Mirel Burduloi, Flavia Catalina Corciova, Gabriela Dumachita Sargu, Raluca Ozana Chistol, Alexandra Cristina Rusu and Cristinel Ionel Stan
Reports 2024, 7(1), 2; https://doi.org/10.3390/reports7010002 - 26 Dec 2023
Viewed by 2135
Abstract
Fatal hemoptysis secondary to severe pulmonary veins stenosis and fibrosing mediastinitis is an exceptional late complication of radiofrequency ablation for atrial fibrillation. We report the case of a 53-year-old male with a history of atrial fibrillation treated by radiofrequency ablation and admitted in [...] Read more.
Fatal hemoptysis secondary to severe pulmonary veins stenosis and fibrosing mediastinitis is an exceptional late complication of radiofrequency ablation for atrial fibrillation. We report the case of a 53-year-old male with a history of atrial fibrillation treated by radiofrequency ablation and admitted in our center 6 months after the procedure because of aggravating dyspnea and fatigability. Transthoracic echocardiography showed moderate dilation of right heart cavities, severe pulmonary hypertension and a turbulent flow in superior pulmonary veins. The cardiologist suspected pulmonary vein(s) stenosis and so cardiac computed tomography (CT) angiography was performed, with findings of severe stenosis of the right superior, right inferior and left inferior pulmonary veins, near-occlusion of the left superior pulmonary vein and the vein draining the apical segment of the right lower lobe. The CT scan also revealed soft tissue attenuation of the mediastinum posterior to the left atrium suggesting fibrosing mediastinitis together with parenchymal findings consistent with pulmonary veno-oclusive disease and an area of hemorrhagic infarction. Fatal hemoptysis occurred 3 days later, before treatment was attempted. In conclusion, severe pulmonary vein stenosis and fibrosing mediastinitis are rare but devastating complications of radiofrequency ablation. Prevention and early diagnosis are the key elements as these entities are potentially life-threatening. Full article
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13 pages, 600 KiB  
Article
Lightweight Techniques to Improve Generalization and Robustness of U-Net Based Networks for Pulmonary Lobe Segmentation
by Armin A. Dadras, Achref Jaziri, Eric Frodl, Thomas J. Vogl, Julia Dietz and Andreas M. Bucher
Bioengineering 2024, 11(1), 21; https://doi.org/10.3390/bioengineering11010021 - 25 Dec 2023
Cited by 4 | Viewed by 2079
Abstract
Lung lobe segmentation in chest CT is relevant to a wide range of clinical applications. However, existing segmentation pipelines often exhibit vulnerabilities and performance degradations when applied to external datasets. This is usually attributed to the size of the available dataset or model. [...] Read more.
Lung lobe segmentation in chest CT is relevant to a wide range of clinical applications. However, existing segmentation pipelines often exhibit vulnerabilities and performance degradations when applied to external datasets. This is usually attributed to the size of the available dataset or model. We show that it is possible to enhance generalizability without huge resources by carefully curating the dataset and combining machine learning with medical expertise. Multiple machine learning techniques (self-supervision (SSL), attention (A), and data augmentation (DA)) are used to train a fast and fully-automated lung lobe segmentation model based on 2D U-Net. Our study involved evaluating these techniques on a diverse dataset collected under the RACOON project, encompassing 100 CT chest scans from patients with bacterial, viral, or SARS-CoV2 infections. We compare our model to a baseline U-Net trained on the same dataset. Our approach significantly improved segmentation accuracy (Dice score of 92.8% vs. 82.3%, p < 0.001). Moreover, our model achieved state-of-the-art performance (Dice score of 92.8% vs. 90.8% for the literature’s state-of-the-art, p = 0.102) with reduced training examples (69 vs. 231 CT Scans). Among the techniques, data augmentation with expert knowledge displayed the most significant impact, enhancing the Dice score by +0.056. Notably, these enhancements are not limited to lobe segmentation but can be seamlessly integrated into various medical imaging segmentation tasks, demonstrating their versatility and potential for broader applications. Full article
(This article belongs to the Special Issue Computed Tomography Techniques and Applications)
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11 pages, 14185 KiB  
Communication
Influencing Factors on Intersegmental Identification Adequacy in Segmentectomy with Intraoperative Indocyanine Green (ICG) Intravenous Administration
by Harushi Ueno, Tomohiro Setogawa, Ayaka Makita, Yuko Ohara, Yoshito Imamura, Shoji Okado, Hiroki Watanabe, Yuta Kawasumi, Yuka Kadomatsu, Taketo Kato, Shota Nakamura, Tetsuya Mizuno and Toyofumi Fengshi Chen-Yoshikawa
Cancers 2023, 15(24), 5876; https://doi.org/10.3390/cancers15245876 - 17 Dec 2023
Cited by 2 | Viewed by 1437
Abstract
Accurate identification of the intersegmental plane is essential in segmentectomy, and Indocyanine Green (ICG) assists in visualizing lung segments. Various factors, including patient-related, intraoperative, and technical issues, can influence boundary delineation. This study aims to assess the rate of unsuccessful intersegmental identification and [...] Read more.
Accurate identification of the intersegmental plane is essential in segmentectomy, and Indocyanine Green (ICG) assists in visualizing lung segments. Various factors, including patient-related, intraoperative, and technical issues, can influence boundary delineation. This study aims to assess the rate of unsuccessful intersegmental identification and identify the contributing factors. We analyzed cases of lung segmentectomy from April 2020 to March 2023, where intraoperative ICG was intravenously administered during robot-assisted or video-assisted thoracoscopic surgery. Cases where fluorescence extended beyond expected boundaries within 30 s were classified as the “unclear boundary group”. This group was then compared to the “clear boundary group”. The study encompassed 111 cases, 104 (94%) of which were classified under the “clear boundary group” and 7 (6%) under the “unclear boundary group”. The “unclear boundary group” had a significantly lower DLCO (15.7 vs. 11.8, p = 0.03) and DLCO/VA (4.3 vs. 3.0, p = 0.01) compared to the “clear boundary group”. All cases in the “unclear boundary group” underwent lower lobe segmentectomy. ICG administration effectively outlines pulmonary segments. Challenges in segment demarcation may occur in cases with low DLCO and DLCO/VA values, particularly during lower lobe segmentectomy. Full article
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17 pages, 5158 KiB  
Article
nmPLS-Net: Segmenting Pulmonary Lobes Using nmODE
by Peizhi Dong, Hao Niu, Zhang Yi and Xiuyuan Xu
Mathematics 2023, 11(22), 4675; https://doi.org/10.3390/math11224675 - 17 Nov 2023
Cited by 4 | Viewed by 1428
Abstract
Pulmonary lobe segmentation is vital for clinical diagnosis and treatment. Deep neural network-based pulmonary lobe segmentation methods have seen rapid development. However, there are challenges that remain, e.g., pulmonary fissures are always not clear or incomplete, especially in the complex situation of the [...] Read more.
Pulmonary lobe segmentation is vital for clinical diagnosis and treatment. Deep neural network-based pulmonary lobe segmentation methods have seen rapid development. However, there are challenges that remain, e.g., pulmonary fissures are always not clear or incomplete, especially in the complex situation of the trilobed right pulmonary, which leads to relatively poor results. To address this issue, this study proposes a novel method, called nmPLS-Net, to segment pulmonary lobes effectively using nmODE. Benefiting from its nonlinear and memory capacity, we construct an encoding network based on nmODE to extract features of the entire lung and dependencies between features. Then, we build a decoding network based on edge segmentation, which segments pulmonary lobes and focuses on effectively detecting pulmonary fissures. The experimental results on two datasets demonstrate that the proposed method achieves accurate pulmonary lobe segmentation. Full article
(This article belongs to the Special Issue Machine-Learning-Based Process and Analysis of Medical Images)
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12 pages, 6692 KiB  
Article
Arteria Praebronchialis (AP) Found on MDCT: An Updated Incidence and Branching Patterns
by Bo Mi Gil, Kyongmin Sarah Beck, Kyung Soo Kim and Dae Hee Han
Diagnostics 2023, 13(17), 2744; https://doi.org/10.3390/diagnostics13172744 - 24 Aug 2023
Viewed by 1154
Abstract
Preoperative detection of the arteria praebronchialis (AP), a rare variant mediastinal branch of the left pulmonary artery, can be crucial to a successful left-lung surgery; if the AP is overlooked and ligated during surgery, the blood supply to the remaining lobe may be [...] Read more.
Preoperative detection of the arteria praebronchialis (AP), a rare variant mediastinal branch of the left pulmonary artery, can be crucial to a successful left-lung surgery; if the AP is overlooked and ligated during surgery, the blood supply to the remaining lobe may be compromised. The purpose of this study was to update the incidence and branching patterns of the AP. From 18 April 2012 to 31 December 2022, contrast-enhanced CT was screened by one radiologist for the presence of AP. Branching patterns of the AP were analyzed by three thoracic radiologists. The incidence of AP was updated to 0.068% (18/26,310) from the previously reported 0.03%; the incidence of AP for male and female patients was 0.110% and 0.017%, respectively. AP supplied only the LLL in 10 cases and both the lingular division of LUL and LLL in nine cases. Dual segmental supply by both the AP and the normal left descending pulmonary artery existed in 15 cases; exclusive segmental supply by either artery existed in four cases. The AP supplies either the LLL alone or both LLL and the lingular division of LUL, and its incidence is not negligible in the male population, necessitating routine surveillance prior to pulmonary resection. Full article
(This article belongs to the Special Issue The Role of Anatomy in Medical Diagnosis and Pathology Analysis)
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9 pages, 4820 KiB  
Article
Pleuroparenchymal Fibroelastosis-like Lesions in Clinical Practice: A Rare Entity? Review of a Radiological Database
by Francesco Gentili, Vito Di Martino, Marta Forestieri, Francesco Mazzei, Susanna Guerrini, Elena Bargagli, Antonietta Gerardina Sisinni, Luca Volterrani and Maria Antonietta Mazzei
Diagnostics 2023, 13(9), 1627; https://doi.org/10.3390/diagnostics13091627 - 4 May 2023
Cited by 2 | Viewed by 3000
Abstract
Background: Pleuroparenchymal Fibroelastosis (PPFE) is a rare disease that consists of elastofibrosis that involves the pleura and subpleural lung parenchyma; it is an unusual pulmonary disease with unique clinical, radiological and pathological characteristics. According to recent studies, PPFE may not be a definite [...] Read more.
Background: Pleuroparenchymal Fibroelastosis (PPFE) is a rare disease that consists of elastofibrosis that involves the pleura and subpleural lung parenchyma; it is an unusual pulmonary disease with unique clinical, radiological and pathological characteristics. According to recent studies, PPFE may not be a definite disease but a form of chronic lung injury. The aim of this retrospective study is to determine the incidence and to evaluate the distribution, severity and progression of this radiological entity on high-resolution CT (HRCT) exams of the chest, performed in routine clinical practice. In total, 1514 HRCT exams performed in the period January 2016–June 2018 were analyzed. For each exam, the presence of PPFE was evaluated and a quantitative score was assigned (from 0 to 7 points, based on the maximum depth of fibrotic involvement of the parenchyma). When available, two exams with a time interval of at least 6 months were compared for each patient in order to evaluate progression (defined as the increase in the disease score). Patients were divided into different groups according to exposure and their associated diseases. Statistical analysis was performed by using the Wilcoxon test and Kruskal–Wallis test. Results: PPFE was detected in 174 out of 1514 patients (11.6%), with a mean score of 6.1 ± 3.9 (range 1–14). In 106 out of 174 patients (60.9%), a previous CT scan was available and an evolution of PPFE was detected in 19 of these (11.5%). Among these 19 patients with worsening PPFE, 4 had isolated PPFE that was associated with chronic exposure or connective tissue disorders, and the other 15 had an associated lung disease and/or a chronic exposure. In this group, it was found that the ventral segments of the upper lobes, fissures and apical segments of the lower lobes had a greater statistically significant involvement in the progression of the disease compared to the non-progressive group. In 16 of 174 patients (9.2%, 7 of which belonged to the radiological progression group) a biopsy through video-assisted thoracoscopic surgery or apicoectomy confirmed PPFE. Conclusion: PPFE-like lesions are not uncommon on HRCT exams in routine clinical practice, and are frequently found in patients with different forms of chronic lung injury. Further studies are necessary to explain why the disease progresses in some cases, while in most, it remains stationary over time. Full article
(This article belongs to the Special Issue Updates in Cardiothoracic Imaging)
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12 pages, 3686 KiB  
Article
A Fissure-Aided Registration Approach for Automatic Pulmonary Lobe Segmentation Using Deep Learning
by Mengfan Xue, Lu Han, Yiran Song, Fan Rao and Dongliang Peng
Sensors 2022, 22(21), 8560; https://doi.org/10.3390/s22218560 - 7 Nov 2022
Cited by 6 | Viewed by 2672
Abstract
The segmentation of pulmonary lobes is important in clinical assessment, lesion location, and surgical planning. Automatic lobe segmentation is challenging, mainly due to the incomplete fissures or the morphological variation resulting from lung disease. In this work, we propose a learning-based approach that [...] Read more.
The segmentation of pulmonary lobes is important in clinical assessment, lesion location, and surgical planning. Automatic lobe segmentation is challenging, mainly due to the incomplete fissures or the morphological variation resulting from lung disease. In this work, we propose a learning-based approach that incorporates information from the local fissures, the whole lung, and priori pulmonary anatomy knowledge to separate the lobes robustly and accurately. The prior pulmonary atlas is registered to the test CT images with the aid of the detected fissures. The result of the lobe segmentation is obtained by mapping the deformation function on the lobes-annotated atlas. The proposed method is evaluated in a custom dataset with COPD. Twenty-four CT scans randomly selected from the custom dataset were segmented manually and are available to the public. The experiments showed that the average dice coefficients were 0.95, 0.90, 0.97, 0.97, and 0.97, respectively, for the right upper, right middle, right lower, left upper, and left lower lobes. Moreover, the comparison of the performance with a former learning-based segmentation approach suggests that the presented method could achieve comparable segmentation accuracy and behave more robustly in cases with morphological specificity. Full article
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13 pages, 528 KiB  
Article
Pulmonary Involvement in SARS-CoV-2 Infection Estimates Myocardial Injury Risk
by Eduard Dumea, Mihai Lazar, Ecaterina Constanta Barbu, Cristina Emilia Chitu and Daniela Adriana Ion
Medicina 2022, 58(10), 1436; https://doi.org/10.3390/medicina58101436 - 11 Oct 2022
Cited by 4 | Viewed by 2671
Abstract
Background and Objectives: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection represents a pathology with primary pulmonary involvement and multisystemic impact, including cardiovascular injuries. The present study aimed to assess the value of clinical, biochemical, and imaging factors in COVID-19 patients in [...] Read more.
Background and Objectives: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection represents a pathology with primary pulmonary involvement and multisystemic impact, including cardiovascular injuries. The present study aimed to assess the value of clinical, biochemical, and imaging factors in COVID-19 patients in determining the severity of myocardial involvement, and to create a model that can be used toevaluate myocardial injury risk based on clinical, biochemical and imaging factors. Materials and Methods: We performed an observational cohort study on 150 consecutive patients, evaluating their age, sex, hospitalization period, peripheral oxygen saturation (SpO2) in ambient air, systolic and diastolic blood pressure, heart rate, respiratory rate, biochemical markers of cardiac dysfunction (TnI, and NT-proBNP), inflammatory markers (C reactive protein (CRP), fibrinogen, serum ferritin, interleukin-6 (IL-6), tumor necrosis factor alpha (TNFα)), D-dimers, lactate dehydrogenase (LDH), myoglobin and radio-imaging parameters. All patients underwent computerized tomography chest scan in the first two days following admission. Results: We observed elevated heart and respiratory rates, higher systolic blood pressure, and a lower diastolic blood pressure in the patients with cardiac injury; significant differences between groups were registered in TnI, NT-proBNP, LDH, CRP, and D-dimers. For the radiological parameters, we found proportional correlations with the myocardial injury for the severity of lung disease, number of pulmonary segments with alveolar consolidation, number of pulmonary lobes with pneumonia, crazy paving pattern, type of lung involvement, the extent of fibroatelectatic lesions and the mediastinal adenopathies. Conclusions: Myocardial injury occurred in 12% of patients in the study group. Ground glass opacities, interstitial interlobular septal thickening (crazy paving pattern), fibroatelectasic lesions and alveolar consolidations on CT scan were correlated with myocardial injury. Routine lung sectional imaging along with non-specific biomarkers (LDH, D-dimers, and CRP) can be further valuable in the characterization of the disease burden, thus impacting patient care. Full article
(This article belongs to the Collection Interdisciplinary Medicine – The Key For Personalized Medicine)
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18 pages, 3824 KiB  
Article
Detection and Classification of Bronchiectasis Based on Improved Mask-RCNN
by Ning Yue, Jingwei Zhang, Jing Zhao, Qinyan Zhang, Xinshan Lin and Jijiang Yang
Bioengineering 2022, 9(8), 359; https://doi.org/10.3390/bioengineering9080359 - 1 Aug 2022
Cited by 2 | Viewed by 3198
Abstract
Bronchiectasis is defined as a permanent dilation of the bronchi that can cause pulmonary ventilation dysfunction. CT examination is an important means of diagnosing bronchiectasis. It can also be used in severity scoring. Current studies on bronchiectasis have focused on high-resolution CT (HRCT), [...] Read more.
Bronchiectasis is defined as a permanent dilation of the bronchi that can cause pulmonary ventilation dysfunction. CT examination is an important means of diagnosing bronchiectasis. It can also be used in severity scoring. Current studies on bronchiectasis have focused on high-resolution CT (HRCT), ignoring the more common low-dose CT (LDCT). Methodologically, existing studies have not adopted an authoritative standard to classify the severity of bronchiectasis. In effect, the accuracy of detection and classification needs to be improved for practical application. In this paper, the ACER image enhancement method, RDU-Net lung lobe segmentation method and HDC Mask R-CNN model were proposed to detect and classify bronchiectasis. Moreover, a Python-based system was developed: after inputing an LDCT image of a patient’s lung, it can automatically perform a series of processing, then call on the trained deep learning model for detection and classification, and automatically obtain the patient’s bronchiectasis final score according to the Reiff and BRICS scoring criteria. In this paper, the mapping relationship between original lung CT image data and bronchiectasis scoring system was established. The accuracy of the method proposed in this paper was 91.4%; the IOU, sensitivity and specificity were 88.8%, 88.6% and 85.4%, respectively; and the recognition speed of one picture was about 1 s. Compared to a human doctor, the system can process large amounts of data simultaneously, quickly and efficiently, with the same judgment accuracy as a human doctor. Doctors only need to judge the uncertain cases, which significantly reduces the burden of doctors and provides a useful reference for doctors to diagnose the disease. Full article
(This article belongs to the Special Issue Artificial Intelligence Based Computer-Aided Diagnosis)
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13 pages, 2454 KiB  
Article
Dual-Energy CT Pulmonary Angiography for the Assessment of Surgical Accessibility in Patients with Chronic Thromboembolic Pulmonary Hypertension
by Matthias Eberhard, Micheal McInnis, Marc de Perrot, Mona Lichtblau, Silvia Ulrich, Ilhan Inci, Isabelle Opitz and Thomas Frauenfelder
Diagnostics 2022, 12(2), 228; https://doi.org/10.3390/diagnostics12020228 - 18 Jan 2022
Cited by 8 | Viewed by 2908
Abstract
We assessed the value of dual-energy CT pulmonary angiography (CTPA) for classification of the level of disease in chronic thromboembolic pulmonary hypertension (CTEPH) patients compared to the surgical Jamieson classification and prediction of hemodynamic changes after pulmonary endarterectomy. Forty-three CTEPH patients (mean age, [...] Read more.
We assessed the value of dual-energy CT pulmonary angiography (CTPA) for classification of the level of disease in chronic thromboembolic pulmonary hypertension (CTEPH) patients compared to the surgical Jamieson classification and prediction of hemodynamic changes after pulmonary endarterectomy. Forty-three CTEPH patients (mean age, 57 ± 16 years; 18 females) undergoing CTPA prior to surgery were retrospectively included. “Proximal” and “distal disease” were defined as L1 and 2a (main and lobar pulmonary artery [PA]) and L2b-4 (lower lobe basal trunk to subsegmental PA), respectively. Three radiologists had a moderate interobserver agreement for the radiological classification of disease (k = 0.55). Sensitivity was 92–100% and specificity was 24–53% to predict proximal disease according to the Jamieson classification. A median of 9 segments/patient had CTPA perfusion defects (range, 2–18 segments). L1 disease had a greater decrease in the mean pulmonary artery pressure (p = 0.029) and pulmonary vascular resistance (p = 0.011) after surgery compared to patients with L2a to L3 disease. The extent of perfusion defects was not associated with the level of disease or hemodynamic changes after surgery (p > 0.05 for all). CTPA is highly sensitive for predicting the level of disease in CTEPH patients with a moderate interobserver agreement. The radiological level of disease is associated with hemodynamic improvement after surgery. Full article
(This article belongs to the Topic Medical Image Analysis)
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