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Advances in Cardiopulmonary Imaging
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Advances in Cardiopulmonary Imaging

A special issue of Diagnostics (ISSN 2075-4418). This special issue belongs to the section "Medical Imaging and Theranostics".

Deadline for manuscript submissions: closed (31 May 2022) | Viewed by 39672

Special Issue Editor

Dr. Chiara Martini

E-Mail Website
Guest Editor
1. Department of Medicine and Surgery, University of Parma, Maggiore Hospital, Via Gramsci 14, 43126 Parma, Italy
2. Department of Diagnostic, Parma University Hospital, Via Gramsci 14, 43126 Parma, Italy
Interests: cardiac imaging; pulmonary imaging; cardiac computed tomography; cardiac magnetic resonance; post-processing; artificial intelligence
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue showcases recent advances in concomitant cardiac and pulmonary imaging. In particular, selected original research articles are included that highlight the use of advanced to better characterize morphological and functional characterization in multimodality diagnostic techniques. The technological advancement of imaging and post-processing equipment These techniques will likely become essential tools to assist radiologist interpretations as they are eventually incorporated into the workflow. Potential applications that are of research interest include implementing automated anatomy; segmentation and measurement for diagnosis; 3D printing , in order to predict optimal treatment selection and assess treatment response.

Dr. Chiara Martini
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Diagnostics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • cardia
  • pulmonary
  • imaging
  • X-ray
  • computed tomography
  • magnetic resonance
  • echocardiography
  • lung ultrasound
  • ultrasound
  • multimodality imaging
  • pulmonary heart disease

Published Papers (17 papers)

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Research

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10 pages, 1742 KiB  
Article
Diagnostic Efficacy of CT Examination on Early Detection of Lung Cancer during Pandemic of COVID-19
by Yanjie Zhao, Ruibin Wang, Feng Shi, Jiangping Wu, Fusheng Jiang and Qingkun Song
Diagnostics 2022, 12(10), 2317; https://doi.org/10.3390/diagnostics12102317 - 26 Sep 2022
Cited by 1 | Viewed by 1190
Abstract
Background: Since the outbreak of COVID-19 in 2020, routine CT examination was recommended to hospitalized patients at some hospitals and discovered lung cancer patients at an early stage. This study aimed to investigate the detection efficacy of routine CT examination on early diagnosis [...] Read more.
Background: Since the outbreak of COVID-19 in 2020, routine CT examination was recommended to hospitalized patients at some hospitals and discovered lung cancer patients at an early stage. This study aimed to investigate the detection efficacy of routine CT examination on early diagnosis of lung cancer, especially on pathological characteristics. Methods: The epidemic of COVID-19 outbreak in January 2020 in China, and routine CT examination was recommended to hospitalized patients in June 2020 and ended in July 2021. Based on the time points, we compared the diagnosis efficacy between three periods: pre-period, peri-period, and the period of routine CT examination. Results: During the period of routine CT examination, more early stages of lung cancer were detected and the tumor size was reduced to 2.14 cm from 3.21 cm at pre-period (p = 0.03). The proportion of lung adenocarcinoma and early stage adenocarcinoma was increased by 12% and 30% in the period of routine CT examination, with referral to the pre-period of CT examination (p < 0.05). A total of 61% of diagnosed patients had the wild type of TP53 gene during the period of routine CT examination, compared to 45% of patients at the pre-period of CT examination (p = 0.001). The median Ki-67 index was 15% among patients diagnosed at the period of routine CT examination and increased to 35% at the pre-period of CT examination (p < 0.001). The period of routine CT examination was associated with a 78% higher probability of detecting an early stage of adenocarcinoma (OR = 1.78, 95%CI 1.03, 3.08) but no significant association was observed for squamous cell carcinoma. From the pre-period to the period of routine CT examination, the proportion of female patients and non-smoking patients increased by 57% and 44%, respectively (p < 0.001). Conclusion: Routine CT examination could detect more lung cancer at an early stage, especially for adenocarcinoma, and detect patients with less aggressive features. Further studies were warranted to confirm the findings. Full article
(This article belongs to the Special Issue Advances in Cardiopulmonary Imaging)
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15 pages, 7468 KiB  
Article
Different Lung Parenchyma Quantification Using Dissimilar Segmentation Software: A Multi-Center Study for COVID-19 Patients
by Camilla Risoli, Marco Nicolò, Davide Colombi, Marco Moia, Fausto Rapacioli, Pietro Anselmi, Emanuele Michieletti, Roberta Ambrosini, Marco Di Terlizzi, Luigi Grazioli, Cristian Colmo, Angelo Di Naro, Matteo Pio Natale, Alessandro Tombolesi, Altin Adraman, Domenico Tuttolomondo, Cosimo Costantino, Elisa Vetti and Chiara Martini
Diagnostics 2022, 12(6), 1501; https://doi.org/10.3390/diagnostics12061501 - 20 Jun 2022
Cited by 10 | Viewed by 2582
Abstract
Background: Chest Computed Tomography (CT) imaging has played a central role in the diagnosis of interstitial pneumonia in patients affected by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and can be used to obtain the extent of lung involvement in COVID-19 pneumonia patients [...] Read more.
Background: Chest Computed Tomography (CT) imaging has played a central role in the diagnosis of interstitial pneumonia in patients affected by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and can be used to obtain the extent of lung involvement in COVID-19 pneumonia patients either qualitatively, via visual inspection, or quantitatively, via AI-based software. This study aims to compare the qualitative/quantitative pathological lung extension data on COVID-19 patients. Secondly, the quantitative data obtained were compared to verify their concordance since they were derived from three different lung segmentation software. Methods: This double-center study includes a total of 120 COVID-19 patients (60 from each center) with positive reverse-transcription polymerase chain reaction (RT-PCR) who underwent a chest CT scan from November 2020 to February 2021. CT scans were analyzed retrospectively and independently in each center. Specifically, CT images were examined manually by two different and experienced radiologists for each center, providing the qualitative extent score of lung involvement, whereas the quantitative analysis was performed by one trained radiographer for each center using three different software: 3DSlicer, CT Lung Density Analysis, and CT Pulmo 3D. Results: The agreement between radiologists for visual estimation of pneumonia at CT can be defined as good (ICC 0.79, 95% CI 0.73–0.84). The statistical tests show that 3DSlicer overestimates the measures assessed; however, ICC index returns a value of 0.92 (CI 0.90–0.94), indicating excellent reliability within the three software employed. ICC was also performed between each single software and the median of the visual score provided by the radiologists. This statistical analysis underlines that the best agreement is between 3D Slicer “LungCTAnalyzer” and the median of the visual score (0.75 with a CI 0.67–82 and with a median value of 22% of disease extension for the software and 25% for the visual values). Conclusions: This study provides for the first time a direct comparison between the actual gold standard, which is represented by the qualitative information described by radiologists, and novel quantitative AI-based techniques, here represented by three different commonly used lung segmentation software, underlying the importance of these specific values that in the future could be implemented as consistent prognostic and clinical course parameters. Full article
(This article belongs to the Special Issue Advances in Cardiopulmonary Imaging)
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11 pages, 1076 KiB  
Article
Jointly Optimized Deep Neural Networks to Synthesize Monoenergetic Images from Single-Energy CT Angiography for Improving Classification of Pulmonary Embolism
by Matthias A. Fink, Constantin Seibold, Hans-Ulrich Kauczor, Rainer Stiefelhagen and Jens Kleesiek
Diagnostics 2022, 12(5), 1224; https://doi.org/10.3390/diagnostics12051224 - 13 May 2022
Cited by 5 | Viewed by 1893
Abstract
Detector-based spectral CT offers the possibility of obtaining spectral information from which discrete acquisitions at different energy levels can be derived, yielding so-called virtual monoenergetic images (VMI). In this study, we aimed to develop a jointly optimized deep-learning framework based on dual-energy CT [...] Read more.
Detector-based spectral CT offers the possibility of obtaining spectral information from which discrete acquisitions at different energy levels can be derived, yielding so-called virtual monoenergetic images (VMI). In this study, we aimed to develop a jointly optimized deep-learning framework based on dual-energy CT pulmonary angiography (DE-CTPA) data to generate synthetic monoenergetic images (SMI) for improving automatic pulmonary embolism (PE) detection in single-energy CTPA scans. For this purpose, we used two datasets: our institutional DE-CTPA dataset D1, comprising polyenergetic arterial series and the corresponding VMI at low-energy levels (40 keV) with 7892 image pairs, and a 10% subset of the 2020 RSNA Pulmonary Embolism CT Dataset D2, which consisted of 161,253 polyenergetic images with dichotomous slice-wise annotations (PE/no PE). We trained a fully convolutional encoder-decoder on D1 to generate SMI from single-energy CTPA scans of D2, which were then fed into a ResNet50 network for training of the downstream PE classification task. The quantitative results on the reconstruction ability of our framework revealed high-quality visual SMI predictions with reconstruction results of 0.984 ± 0.002 (structural similarity) and 41.706 ± 0.547 dB (peak signal-to-noise ratio). PE classification resulted in an AUC of 0.84 for our model, which achieved improved performance compared to other naïve approaches with AUCs up to 0.81. Our study stresses the role of using joint optimization strategies for deep-learning algorithms to improve automatic PE detection. The proposed pipeline may prove to be beneficial for computer-aided detection systems and could help rescue CTPA studies with suboptimal opacification of the pulmonary arteries from single-energy CT scanners. Full article
(This article belongs to the Special Issue Advances in Cardiopulmonary Imaging)
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15 pages, 2524 KiB  
Article
Automated Detection, Segmentation, and Classification of Pericardial Effusions on Chest CT Using a Deep Convolutional Neural Network
by Adrian Jonathan Wilder-Smith, Shan Yang, Thomas Weikert, Jens Bremerich, Philip Haaf, Martin Segeroth, Lars C. Ebert, Alexander Sauter and Raphael Sexauer
Diagnostics 2022, 12(5), 1045; https://doi.org/10.3390/diagnostics12051045 - 21 Apr 2022
Cited by 3 | Viewed by 2332
Abstract
Pericardial effusions (PEFs) are often missed on Computed Tomography (CT), which particularly affects the outcome of patients presenting with hemodynamic compromise. An automatic PEF detection, segmentation, and classification tool would expedite and improve CT based PEF diagnosis; 258 CTs with (206 with simple [...] Read more.
Pericardial effusions (PEFs) are often missed on Computed Tomography (CT), which particularly affects the outcome of patients presenting with hemodynamic compromise. An automatic PEF detection, segmentation, and classification tool would expedite and improve CT based PEF diagnosis; 258 CTs with (206 with simple PEF, 52 with hemopericardium) and without PEF (each 134 with contrast, 124 non-enhanced) were identified using the radiology report (01/2016–01/2021). PEF were manually 3D-segmented. A deep convolutional neural network (nnU-Net) was trained on 316 cases and separately tested on the remaining 200 and 22 external post-mortem CTs. Inter-reader variability was tested on 40 CTs. PEF classification utilized the median Hounsfield unit from each prediction. The sensitivity and specificity for PEF detection was 97% (95% CI 91.48–99.38%) and 100.00% (95% CI 96.38–100.00%) and 89.74% and 83.61% for diagnosing hemopericardium (AUC 0.944, 95% CI 0.904–0.984). Model performance (Dice coefficient: 0.75 ± 0.01) was non-inferior to inter-reader (0.69 ± 0.02) and was unaffected by contrast administration nor alternative chest pathology (p > 0.05). External dataset testing yielded similar results. Our model reliably detects, segments, and classifies PEF on CT in a complex dataset, potentially serving as an alert tool whilst enhancing report quality. The model and corresponding datasets are publicly available. Full article
(This article belongs to the Special Issue Advances in Cardiopulmonary Imaging)
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14 pages, 1411 KiB  
Article
Computed Tomography Texture Analysis of Carotid Plaque as Predictor of Unfavorable Outcome after Carotid Artery Stenting: A Preliminary Study
by Davide Colombi, Flavio Cesare Bodini, Beatrice Rossi, Margherita Bossalini, Camilla Risoli, Nicola Morelli, Marcello Petrini, Nicola Sverzellati and Emanuele Michieletti
Diagnostics 2021, 11(12), 2214; https://doi.org/10.3390/diagnostics11122214 - 27 Nov 2021
Cited by 4 | Viewed by 1880
Abstract
Novel biomarkers are advocated to manage carotid plaques. Therefore, we aimed to test the association between textural features of carotid plaque at computed tomography angiography (CTA) and unfavorable outcome after carotid artery stenting (CAS). Between January 2010 and January 2021, were selected 172 [...] Read more.
Novel biomarkers are advocated to manage carotid plaques. Therefore, we aimed to test the association between textural features of carotid plaque at computed tomography angiography (CTA) and unfavorable outcome after carotid artery stenting (CAS). Between January 2010 and January 2021, were selected 172 patients (median age, 77 years; 112/172, 65% men) who underwent CAS with CTA of the supra-aortic vessels performed within prior 6 months. Standard descriptors of the density histogram were derived by open-source software automated analysis obtained by CTA plaque segmentation. Multiple logistic regression analysis, receiver operating characteristic (ROC) curve analysis and the area under the ROC (AUC) were used to identify potential prognostic variables and to assess the model performance for predicting unfavorable outcome (periprocedural death or myocardial infarction and any ipsilateral acute neurological event). Unfavorable outcome occurred in 17/172 (10%) patients (median age, 79 years; 12/17, 70% men). Kurtosis was an independent predictor of unfavorable outcome (odds ratio, 0.79; confidence interval, 0.65–0.97; p = 0.029). The predictive model for unfavorable outcome including CTA textural features outperformed the model without textural features (AUC 0.789 vs. 0.695, p = 0.004). In patients with stenotic carotid plaque, kurtosis derived by CTA density histogram analysis is an independent predictor of unfavorable outcome after CAS. Full article
(This article belongs to the Special Issue Advances in Cardiopulmonary Imaging)
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10 pages, 2022 KiB  
Article
Atrial Fibrillation and Peri-Atrial Inflammation Measured through Adipose Tissue Attenuation on Cardiac Computed Tomography
by Nicola Gaibazzi, Chiara Martini, Giorgio Benatti, Alessandro Anselmo Palumbo, Giovanna Cacciola and Domenico Tuttolomondo
Diagnostics 2021, 11(11), 2087; https://doi.org/10.3390/diagnostics11112087 - 11 Nov 2021
Cited by 10 | Viewed by 1699
Abstract
Background: Inflammation plays a key role in atrial fibrillation (AF). Epicardial adipose tissue around the atrial wall can influence atrial morpho-functional properties. The aim of this study was to assess whether an increased quantity and/or density of adipose tissue located around the left [...] Read more.
Background: Inflammation plays a key role in atrial fibrillation (AF). Epicardial adipose tissue around the atrial wall can influence atrial morpho-functional properties. The aim of this study was to assess whether an increased quantity and/or density of adipose tissue located around the left atrium (Fat-LA) are related to AF, independently from atrial size. Methods: eighty patients who underwent AF ablation and 80 patients without history of AF were selected. The Fat-LA mass was quantified as tissue within −190 to −30 Hounsfield Units (HU) on cardiac computed tomography angiograms (CCTA), and the mean adipose tissue attenuation was assessed. Results: Adipose tissue mass was higher in patients with AF (5.42 ± 2.94 mL) versus non-AF (4.16 ± 2.55 mL, p = 0.007), but relative fat quantity did not differ after adjusting for atrial size. Mean fat density was significantly higher in AF (−69.15 HU) versus non-AF (−76.82 HU, p < 0.0001) participants. In the logistic regression models, only the addition of mean Fat-LA attenuation led to a significant improvement of the model’s chi-square (from 22.89 of the clinical model to 31.69 of the clinical and adipose tissue attenuation model, p < 0.01) and discrimination (AUC from 0.775 to 0.829). Conclusions: Fat-LA volume is significantly greater only in absolute terms in patients with AF, but this difference does not hold after adjusting for the larger LA of AF subjects. On the contrary, a higher Fat-LA density was associated with AF, independently from LA size, providing incremental value over other variables that are associated with AF. Full article
(This article belongs to the Special Issue Advances in Cardiopulmonary Imaging)
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11 pages, 2873 KiB  
Article
CT-Based Radiomics Helps to Predict Residual Lung Lesions in COVID-19 Patients at Three Months after Discharge
by Jia Huang, Feihong Wu, Leqing Chen, Jie Yu, Wengang Sun, Zhuang Nie, Huan Liu, Fan Yang and Chuansheng Zheng
Diagnostics 2021, 11(10), 1814; https://doi.org/10.3390/diagnostics11101814 - 30 Sep 2021
Cited by 6 | Viewed by 1727
Abstract
Background: In this study, our focus was on pulmonary sequelae of coronavirus disease 2019 (COVID-19). We aimed to develop and validate CT-based radiomic models for predicting the presence of residual lung lesions in COVID-19 survivors at three months after discharge. Methods: We retrospectively [...] Read more.
Background: In this study, our focus was on pulmonary sequelae of coronavirus disease 2019 (COVID-19). We aimed to develop and validate CT-based radiomic models for predicting the presence of residual lung lesions in COVID-19 survivors at three months after discharge. Methods: We retrospectively enrolled 162 COVID-19 confirmed patients in our hospital (84 patients with residual lung lesions and 78 patients without residual lung lesions, at three months after discharge). The patients were all randomly allocated to a training set (n = 114) or a test set (n = 48). Radiomic features were extracted from chest CT images in different regions (entire lung or lesion) and at different time points (at hospital admission or at discharge) to build different models, sequentially, or in combination, as follows: (1) Lesion_A model (based on the lesion region at admission CT); (2) Lesion_D model (based on the lesion region at discharge CT); (3) Δlesion model (based on the lesion region at admission CT and discharge CT); (4) Lung_A model (based on the lung region at admission CT); (5) Lung_D model (based on the lung region at discharge CT); (6) Δlung model (based on the lung region at admission CT and discharge CT). The area under the receiver operating characteristic curve (AUC), sensitivity, and specificity were used to evaluate the predictive performances of the radiomic models. Results: Among the six models, the Lesion_D and the Δlesion models achieved better predictive efficacy, with AUCs of 0.907 and 0.927, sensitivity of 0.898 and 0.763, and specificity of 0.855 and 0.964 in the training set, and AUCs of 0.875 and 0.837, sensitivity of 0.920 and 0.680, and specificity of 0.826 and 0.913 in the test set, respectively. Conclusions: The CT-based radiomic models showed good predictive effects on the presence of residual lung lesions in COVID-19 survivors at three months after discharge, which may help doctors to plan follow-up work and to reduce the psychological burden of COVID-19 survivors. Full article
(This article belongs to the Special Issue Advances in Cardiopulmonary Imaging)
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12 pages, 2719 KiB  
Article
The Histopathological Correlate of Peri-Vascular Adipose Tissue Attenuation on Computed Tomography in Surgical Ascending Aorta Aneurysms: Is This a Measure of Tissue Inflammation?
by Nicola Gaibazzi, Domenico Tuttolomondo, Francesco Nicolini, Alessandro Tafuni, Daniele Sartorio, Chiara Martini, Francesco Maestri, Alan Gallingani, Massimo De Filippo and Domenico Corradi
Diagnostics 2021, 11(10), 1799; https://doi.org/10.3390/diagnostics11101799 - 29 Sep 2021
Cited by 8 | Viewed by 1852
Abstract
On computed tomography (CT) imaging, a peri-vascular adipose tissue attenuation (pVAT) measure has been proposed as a non-invasive correlate of inflammation in the coronary artery vessels, and a single research group provided histopathological demonstration of this radiological/pathological correspondence. Our group has shown that [...] Read more.
On computed tomography (CT) imaging, a peri-vascular adipose tissue attenuation (pVAT) measure has been proposed as a non-invasive correlate of inflammation in the coronary artery vessels, and a single research group provided histopathological demonstration of this radiological/pathological correspondence. Our group has shown that patients with surgical-grade ascending aorta (AA) aneurysm display higher pVAT compared with patients with smaller aneurysms or normal AA. Based on histopathological studies on coronary arteries, we speculated that this correlation may be related to a non-otherwise specified aortic inflammatory process. However, since adipose tissue around the AA is often scant, and there are no histopathological studies confirming such hypothesized association between higher pVAT and inflammation around the AA, we cannot exclude that this pVAT change is secondary to different mechanisms, unrelated to the actual presence of peri-vascular inflammation. We performed a retrospective clinical/radiological/pathological study in 78 patients who underwent AA surgery with the aim to correlate pre-operatory pVAT on CT with histopathological findings from the surgical specimens. Histopathological review and immunohistochemistry were performed on the surgical aortic samples. The AA adventitial/periadventitial adipose tissue had higher pVAT by an increasing collagen fiber deposition, which progressively makes the fat hypotrophic and, in the late stages of this process, it replaces the normal soft tissue composition in this location. In the ascending aorta, pVAT on CT imaging is probably not a proxy for the presence of current vascular inflammation, although it may track changes involving the progressive substitution of perivascular adipose cells by higher-pVAT tissues, mainly fibrotic replacement. Full article
(This article belongs to the Special Issue Advances in Cardiopulmonary Imaging)
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11 pages, 6902 KiB  
Article
Total Lung and Lobar Quantitative Assessment Based on Paired Inspiratory–Expiratory Chest CT in Healthy Adults: Correlation with Pulmonary Ventilatory Function
by Feihong Wu, Leqing Chen, Jia Huang, Wenliang Fan, Jinrong Yang, Xiaohui Zhang, Yang Jin, Fan Yang and Chuansheng Zheng
Diagnostics 2021, 11(10), 1791; https://doi.org/10.3390/diagnostics11101791 - 28 Sep 2021
Cited by 3 | Viewed by 2280
Abstract
Objective: To provide the quantitative volumetric data of the total lung and lobes in inspiration and expiration from healthy adults, and to explore the value of paired inspiratory–expiratory chest CT scan in pulmonary ventilatory function and further explore the influence of each lobe [...] Read more.
Objective: To provide the quantitative volumetric data of the total lung and lobes in inspiration and expiration from healthy adults, and to explore the value of paired inspiratory–expiratory chest CT scan in pulmonary ventilatory function and further explore the influence of each lobe on ventilation. Methods: A total of 65 adults (29 males and 36 females) with normal clinical pulmonary function test (PFT) and paired inspiratory–expiratory chest CT scan were retrospectively enrolled. The inspiratory and expiratory volumetric indexes of the total lung (TL) and 5 lobes (left upper lobe [LUL], left lower lobe [LLL], right upper lobe [RUL], right middle lobe [RML], and right lower lobe [RLL]) were obtained by Philips IntelliSpace Portal image postprocessing workstation, including inspiratory lung volume (LVin), expiratory lung volume (LVex), volume change (∆LV), and well-aerated lung volume (WAL, lung tissue with CT threshold between −950 and −750 HU in inspiratory scan). Spearman correlation analysis was used to explore the correlation between CT quantitative indexes of the total lung and ventilatory function indexes (including total lung capacity [TLC], residual volume [RV], and force vital capacity [FVC]). Multiple stepwise regression analysis was used to explore the influence of each lobe on ventilation. Results: At end-inspiratory phase, the LVin-TL was 4664.6 (4282.7, 5916.2) mL, the WALTL was 4173 (3639.6, 5250.9) mL; both showed excellent correlation with TLC (LVin-TL: r = 0.890, p < 0.001; WALTL: r = 0.879, p < 0.001). From multiple linear regression analysis with lobar CT indexes as variables, the LVin and WAL of these two lobes, LLL and RUL, showed a significant relationship with TLC. At end-expiratory phase, the LVex-TL was 2325.2 (1969.7, 2722.5) mL with good correlation with RV (r = 0.811, p < 0.001), of which the LVex of RUL and RML had a significant relationship with RV. For the volumetric change within breathing, the ∆LVTL was 2485.6 (2169.8, 3078.1) mL with good correlation with FVC (r = 0.719, p < 0.001), moreover, WALTL showed a better correlation with FVC (r = 0.817, p < 0.001) than that of ∆LVTL. Likewise, there was also a strong association between ∆LV, WAL of these two lobes (LLL and RUL), and FVC. Conclusions: The quantitative indexes derived from paired inspiratory–expiratory chest CT could reflect the clinical pulmonary ventilatory function, LLL, and RUL give greater impact on ventilation. Thus, the pulmonary functional evaluation needs to be more precise and not limited to the total lung level. Full article
(This article belongs to the Special Issue Advances in Cardiopulmonary Imaging)
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Review

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13 pages, 4909 KiB  
Review
Pulmonary Fibrosis Related to Amiodarone—Is It a Standard Pathophysiological Pattern? A Case-Based Literature Review
by Corina Eugenia Budin, Iuliu Gabriel Cocuz, Adrian Horațiu Sabău, Raluca Niculescu, Ingrid Renata Ianosi, Vladimir Ioan and Ovidiu Simion Cotoi
Diagnostics 2022, 12(12), 3217; https://doi.org/10.3390/diagnostics12123217 - 19 Dec 2022
Cited by 8 | Viewed by 3685
Abstract
Amiodarone hydrochloride is an antiarrhythmic drug, with proven efficacy in prevention and treatment of numerous arrhythmias, atrial fibrillation especially, or ventricular arrhythmias, with a long half-life (55–60 days). The increased risk of developing amiodarone-induced pulmonary fibrosis is directly related to the dose and [...] Read more.
Amiodarone hydrochloride is an antiarrhythmic drug, with proven efficacy in prevention and treatment of numerous arrhythmias, atrial fibrillation especially, or ventricular arrhythmias, with a long half-life (55–60 days). The increased risk of developing amiodarone-induced pulmonary fibrosis is directly related to the dose and the duration of the intake. Amiodarone-induced pulmonary toxicity is conditioned by dose, patient’s age, and pre-existent pulmonary pathologies. The pattern for drug-induced lung injury may vary in many forms, but the amiodarone can cause polymorphous injuries such as diffuse alveolar damage, chronical interstitial pneumonia, organizing pneumonia, pulmonary hemorrhage, lung nodules or pleural disease. The pathological mechanism of pulmonary injury induced by amiodarone consists of the accumulation of phospholipid complexes in histocytes and type II pneumocytes. Differential diagnosis of pulmonary fibrosis induced by amiodarone is made mainly with idiopathic pulmonary fibrosis, left ventricular failure or infectious disease. Before starting treatment with amiodarone, patients should be informed of potential adverse effects and any new respiratory symptoms should promptly be reported to their family physician or attending physician. The assessment carried out at the initiation of amiodarone treatment should include at least chest X-ray and respiratory function tests and extrapulmonary evaluation. Full article
(This article belongs to the Special Issue Advances in Cardiopulmonary Imaging)
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18 pages, 1391 KiB  
Review
Cardiovascular Magnetic Resonance Imaging in the Early Detection of Cardiotoxicity Induced by Cancer Therapies
by Xiaoting Wei, Ling Lin, Guizhi Zhang and Xuhui Zhou
Diagnostics 2022, 12(8), 1846; https://doi.org/10.3390/diagnostics12081846 - 30 Jul 2022
Cited by 4 | Viewed by 2391
Abstract
The significant progress in cancer treatment, including chemotherapy, immunotherapy, radiotherapy, and combination therapies, has led to higher long-term survival rates in cancer patients, while the cardiotoxicity caused by cancer treatment has become increasingly prominent. Cardiovascular magnetic resonance (CMR) is a non-invasive comprehensive imaging [...] Read more.
The significant progress in cancer treatment, including chemotherapy, immunotherapy, radiotherapy, and combination therapies, has led to higher long-term survival rates in cancer patients, while the cardiotoxicity caused by cancer treatment has become increasingly prominent. Cardiovascular magnetic resonance (CMR) is a non-invasive comprehensive imaging modality that provides not only anatomical information, but also tissue characteristics and cardiometabolic and energetic assessment, leading to its increased use in the early identification of cardiotoxicity, and is of major importance in improving the survival rate of cancer patients. This review focused on CMR techniques, including myocardial strain analysis, T1 mapping, T2 mapping, and extracellular volume fraction (ECV) calculation in the detection of early myocardial injury induced by cancer therapies. We summarized the existing studies and ongoing clinical trials using CMR for the assessment of subclinical ventricular dysfunction and myocardial changes at the tissue level. The main focus was to explore the potential of clinical and preclinical CMR techniques for continuous non-invasive monitoring of myocardial toxicity associated with cancer therapy. Full article
(This article belongs to the Special Issue Advances in Cardiopulmonary Imaging)
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14 pages, 2686 KiB  
Review
Use of POCUS in Chest Pain and Dyspnea in Emergency Department: What Role Could It Have?
by Andrea Piccioni, Laura Franza, Federico Rosa, Federica Manca, Giulia Pignataro, Lucia Salvatore, Benedetta Simeoni, Marcello Candelli, Marcello Covino and Francesco Franceschi
Diagnostics 2022, 12(7), 1620; https://doi.org/10.3390/diagnostics12071620 - 03 Jul 2022
Cited by 3 | Viewed by 2608
Abstract
Chest pain and dyspnea are common symptoms in patients presenting to the emergency room (ER); oftentimes it is not possible to clearly identify the underlying cause, which may cause the patient to have to return to the ER. In other cases, while it [...] Read more.
Chest pain and dyspnea are common symptoms in patients presenting to the emergency room (ER); oftentimes it is not possible to clearly identify the underlying cause, which may cause the patient to have to return to the ER. In other cases, while it is possible to identify the underlying cause, it is necessary to perform a large number of tests before being able to make a diagnosis. Over the last twenty years, emergency medicine physicians have had the possibility of using ultrasound to help them make and rule out diagnoses. Specific ultrasound tests have been designed to evaluate patients presenting with specific symptoms to ensure a fast, yet complete, evaluation. In this paper, we examine the role of ultrasound in helping physicians understand the etiology behind chest pain and dyspnea. We analyze the different diseases and disorders which may cause chest pain and dyspnea as symptoms and discuss the corresponding ultrasound findings. Full article
(This article belongs to the Special Issue Advances in Cardiopulmonary Imaging)
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14 pages, 1428 KiB  
Review
Planning the Follow-Up of Patients with Stable Chronic Coronary Artery Disease
by Guillermo Romero-Farina and Santiago Aguadé-Bruix
Diagnostics 2021, 11(10), 1762; https://doi.org/10.3390/diagnostics11101762 - 25 Sep 2021
Cited by 2 | Viewed by 2917
Abstract
Cardiovascular disease remains the leading cause of death among Europeans, Americans, and around the world. In addition, the prevalence of coronary artery disease (CAD) is increasing, with the highest number of hospital visits, hospital readmissions for patients with decompensated heart failure, and a [...] Read more.
Cardiovascular disease remains the leading cause of death among Europeans, Americans, and around the world. In addition, the prevalence of coronary artery disease (CAD) is increasing, with the highest number of hospital visits, hospital readmissions for patients with decompensated heart failure, and a high economic cost. It is, therefore, a priority to try to plan the follow-up of patients with stable chronic CAD (scCAD) in relation to the published data, experience, and new technology that we have today. Planning the follow-up of patients with scCAD goes beyond the information provided by clinical management guidelines. It requires understanding the importance of a cross-sectional and longitudinal analysis in the clinical history of scCAD, because it has an impact on the cost of healthcare in relation to mortality, economic factors, and the burden of medical consultations. Using the data provided in this work facilitates and standardizes the clinical follow-up of patients with scCAD, and following the marked line makes the work for the clinical physician much easier, by including most clinical possibilities and actions to consider. The follow-up intervals vary according to the clinical situation of each patient and can be highly variable. In addition, the ability to properly study patients with imaging techniques, to stratify at different levels of risk, helps plan the intervals during follow-up. Given the complexity of coronary artery disease and the diversity of clinical cases, more studies are required in the future focused on improving the planning of follow-up for patients with scCAD. The perspective and future direction are related to the valuable utility of integrated imaging techniques in clinical follow-up. Full article
(This article belongs to the Special Issue Advances in Cardiopulmonary Imaging)
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12 pages, 6755 KiB  
Review
Lung Transplantation: CT Assessment of Chronic Lung Allograft Dysfunction (CLAD)
by Anne-Laure Brun, Marie-Laure Chabi, Clément Picard, François Mellot and Philippe A. Grenier
Diagnostics 2021, 11(5), 817; https://doi.org/10.3390/diagnostics11050817 - 30 Apr 2021
Cited by 10 | Viewed by 2884
Abstract
Chronic lung allograft rejection remains one of the major causes of morbi-mortality after lung transplantation. The term Chronic Lung Allograft Dysfunction (CLAD) has been proposed to describe the different processes that lead to a significant and persistent deterioration in lung function without identifiable [...] Read more.
Chronic lung allograft rejection remains one of the major causes of morbi-mortality after lung transplantation. The term Chronic Lung Allograft Dysfunction (CLAD) has been proposed to describe the different processes that lead to a significant and persistent deterioration in lung function without identifiable causes. The two main phenotypes of CLAD are Bronchiolitis Obliterans Syndrome (BOS) and Restrictive Allograft Syndrome (RAS), each of them characterized by particular functional and imaging features. These entities can be associated (mixed phenotype) or switched from one to the other. If CLAD remains a clinical diagnosis based on spirometry, computed tomography (CT) scan plays an important role in the diagnosis and follow-up of CLAD patients, to exclude identifiable causes of functional decline when CLAD is first suspected, to detect early abnormalities that can precede the diagnosis of CLAD (particularly RAS), to differentiate between the obstructive and restrictive phenotypes, and to detect exacerbations and evolution from one phenotype to the other. Recognition of early signs of rejection is crucial for better understanding of physiopathologic pathways and optimal management of patients. Full article
(This article belongs to the Special Issue Advances in Cardiopulmonary Imaging)
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3 pages, 1095 KiB  
Interesting Images
Pericarditis and Takotsubo Syndrome—Diagnosis of Cardiac Complications of Post-Acute COVID-19 Syndrome in a 77-Year-Old Woman
by Malgorzata Zalewska-Adamiec, Hanna Bachorzewska-Gajewska and Slawomir Dobrzycki
Diagnostics 2022, 12(10), 2304; https://doi.org/10.3390/diagnostics12102304 - 24 Sep 2022
Cited by 1 | Viewed by 1430
Abstract
The SARS-CoV-2 virus infection most often takes the form of acute COVID-19 respiratory disease, but in some patients, it turns into acute COVID-19 syndrome after a few weeks. Cardiac complications occur in the form of acute and post-acute diseases and the most common [...] Read more.
The SARS-CoV-2 virus infection most often takes the form of acute COVID-19 respiratory disease, but in some patients, it turns into acute COVID-19 syndrome after a few weeks. Cardiac complications occur in the form of acute and post-acute diseases and the most common are myocarditis, pericarditis, arrhythmias, and acute coronary syndromes or Takotsubo syndrome. Cardiovascular complications are often the cause of hospitalization and death in COVID-19 patients. We present the case of a 77-year-old woman who was admitted to the clinic with suspected myocardial infarction. Coronary arteriography revealed atherosclerotic wall lesions, and echocardiography showed a good contractility of the left ventricle and fluid in the pericardial sac. Pericarditis was diagnosed. In the following days, acute kidney damage was observed, and one hemodialysis session was performed. On the sixth day of hospitalization, a sudden cardiac arrest occurred, and the patient was resuscitated. The echocardiogaphy showed abnormal contractility of the left ventricular with the ejection fraction of 15%—Takotsubo image. After a few hours, a cardiac arrest occurred again, and the patient died. Full article
(This article belongs to the Special Issue Advances in Cardiopulmonary Imaging)
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5 pages, 1178 KiB  
Interesting Images
Bronchoalveolar Lavage as a Diagnostic Tool in an Atypical Pulmonary Langerhans Cell Histiocytosis
by Ovidiu Fira-Mladinescu, Noemi Suppini, Gheorghe-Emilian Olteanu, Corneluta Fira-Mladinescu and Daniel Traila
Diagnostics 2022, 12(6), 1394; https://doi.org/10.3390/diagnostics12061394 - 04 Jun 2022
Cited by 1 | Viewed by 1760
Abstract
Pulmonary Langerhans cell histiocytosis (PLCH) is an uncommon diffuse cystic lung disease that occurs almost exclusively in young adult smokers. High-resolution computed tomography of the chest allows a confident diagnosis of PLCH in typical presentation, when nodules, cavitating nodules, and cysts coexist and [...] Read more.
Pulmonary Langerhans cell histiocytosis (PLCH) is an uncommon diffuse cystic lung disease that occurs almost exclusively in young adult smokers. High-resolution computed tomography of the chest allows a confident diagnosis of PLCH in typical presentation, when nodules, cavitating nodules, and cysts coexist and show a predominance for the upper and middle lung. Atypical presentations require histology for diagnosis. Histologic diagnosis rests on the demonstration of increased numbers of Langerhans cells and/or specific histological changes. PLCH is one of the few diseases in which bronchoalveolar lavage (BAL) has a high diagnostic value and can in some circumstances replace lung biopsy. We present a case of PLCH in an elderly non-smoker. Chest imaging revealed the presence of advanced interstitial lung disease with a fibrocystic pattern. BAL cellular analyses disclosed a macrophage pattern with CD1a phenotype that strongly supports the PLCH diagnosis, even in the setting of atypical clinical presentation and a lack of smoking exposure. PLCH is extremely rare in non-smokers and could represent a distinct phenotype. Full article
(This article belongs to the Special Issue Advances in Cardiopulmonary Imaging)
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8 pages, 897 KiB  
Systematic Review
Perivascular Adipose Tissue Attenuation on Computed Tomography beyond the Coronary Arteries. A Systematic Review
by Domenico Tuttolomondo, Chiara Martini, Francesco Nicolini, Francesco Formica, Alessandro Pini, Francesco Secchi, Riccardo Volpi, Massimo De Filippo and Nicola Gaibazzi
Diagnostics 2021, 11(8), 1495; https://doi.org/10.3390/diagnostics11081495 - 19 Aug 2021
Cited by 6 | Viewed by 2163
Abstract
(1) Background: Perivascular adipose tissue attenuation, measured with computed tomography imaging, is a marker of mean local vascular inflammation since it reflects the morphological changes of the fat tissue in direct contact with the vessel. This method is thoroughly validated in coronary arteries, [...] Read more.
(1) Background: Perivascular adipose tissue attenuation, measured with computed tomography imaging, is a marker of mean local vascular inflammation since it reflects the morphological changes of the fat tissue in direct contact with the vessel. This method is thoroughly validated in coronary arteries, but few studies have been performed in other vascular beds. The aim of the present study is to provide insight into the potential application of perivascular adipose tissue attenuation through computed tomography imaging in extra-coronary arteries. (2) Methods: A comprehensive search of the scientific literature published in the last 30 years (1990–2020) has been performed on Medline. (3) Results: A Medline databases search for titles, abstracts, and keywords returned 3251 records. After the exclusion of repetitions and the application of inclusion and exclusion criteria and abstract screening, 37 studies were selected for full-text evaluation. Three papers were finally included in the systematic review. Perivascular adipose tissue attenuation assessment was studied in the internal carotid artery, ascending thoracic aorta, and abdominal aorta. (4) Conclusions: Perivascular adipose tissue attenuation seems to be an applicable parameter in all investigated vascular beds, generally with good inter-observer reproducibility. Full article
(This article belongs to the Special Issue Advances in Cardiopulmonary Imaging)
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