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A special issue of Journal of Clinical Medicine (ISSN 2077-0383). This special issue belongs to the section "Respiratory Medicine".

Deadline for manuscript submissions: closed (25 August 2025) | Viewed by 4931

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Dr. Chiara Romei

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2nd Radiology Unit, Department of Radiology, Pisa University Hospital, 56124 Pisa, Italy
Interests: interstitial lung disease; lung cancer; chest-CT; chest X-ray
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Special Issue Information

Dear Colleagues,

In recent years, there has been growing interest in lung imaging and the development of new techniques.

In particular, technological innovations have been observed in currently available methods, such as faster sequences with higher resolution in MRI of the lung, to overcome the inherent difficulties they present.

In addition, radiomics and artificial intelligence techniques have been developed and implemented to recognize and characterize lung nodules for the quantification of the progression of lung involvement in interstitial disease using CT.

This Special Issue aims to review major advances in lung imaging, with a focus on possible clinical applications.

Dr. Chiara Romei
Guest Editor

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Keywords

lung disease
lung cancer
chest-CT
chest X-ray
imaging

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Published Papers (4 papers)

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Research

14 pages, 724 KB

Open AccessArticle

Interstitial Lung Disease: Does It Represent a Real Comorbidity in Spondyloarthritis Patients? Results from an Ultrasound Monocentric Pilot Study

by Andrea Delle Sedie, Linda Carli, Annamaria Varrecchia, Cosimo Cigolini, Marco Di Battista, Lorenzo Esti, Federico Fattorini, Emanuele Calabresi and Marta Mosca

J. Clin. Med. 2025, 14(16), 5632; https://doi.org/10.3390/jcm14165632 - 9 Aug 2025

Viewed by 347

Abstract

Background/Objectives: Interstitial lung disease (ILD) is a frequent complication of rheumatoid arthritis (RA), representing the most common extra-articular manifestation (with a prevalence of about 10–60%) and the second cause of mortality. Spondyloarthritides (SpAs) are chronic arthritides that share with RA both a similar disease burden and similar therapeutical approaches. The evaluation of ILD is challenging, given the low sensitivity of X-ray and pulmonary function tests, and the radiation exposure linked to repetitive HRCT. Lung ultrasound (LUS) has shown potential in the evaluation of ILD in autoimmune diseases. The purpose of this study is to assess the prevalence of ILD in a cohort of SpA patients (pts) using LUS in comparison with healthy subjects (HSs). The secondary aim is to evaluate potential correlations between ILD and clinical features within the SpA cohort using LUS. Methods: Consecutive SpA out-patients were examined by LUS, applying the definition for pleural line irregularity (PLI) recently provided by the OMERACT taskforce for LUS in systemic sclerosis. Seventy-one intercostal spaces were studied (14 in the anterior chest, 27 lateral and 30 posterior) in all the pts/HS using an Esaote MyLab25 Gold US machine with a linear 7.5–10 MHz probe. A total pleural score was calculated. Each patient answered to Italian-validated PROs on respiratory function (Leicester and Saint-George), global health (SF-36) and dyspnea (mMRC scale). Clinical data on disease duration, disease onset, disease activity (at the moment of the examination) and methotrexate (MTX) or biologics treatment were collected from the medical records. Results: Seventy-three SpA pts (46 psoriatic arthritis -PsA- and 27 ankylosing spondylitis -AS-) and 56 HS were studied. No significant differences were demonstrated between groups (SpA vs. HS and PsA vs. AS) for age, sex, BMI and smoking habits. The total PLI score was significantly higher in SpA pts than in HS (p < 0.001). A positive correlation was found between the total PLI score and the PLI score from anterior, posterior and lateral chest. The posterior region of the chest showed a higher PLI score than the anterior and lateral regions. No statistically significant differences were found between PsA and AS. MTX use was not a risk factor for PLI (no differences were found between SpA MTX+ and SpA MTX- patients). PROs (Leicester, Saint-George and SF-36) were not related to the PLI total score. A significant correlation was found only between the SF36 score and the presence of PLI in the anterior chest. PROs were instead correlated with each other, showing a good concordance for absence/presence of symptoms. Disease activity, disease duration and age at disease-onset were not related to PLI total score. Smoking habit was found to be predictive of a significantly higher PLI score both in SpA patients and HSs. Conclusions: LUS examination shows a higher amount of PLI in SpA patients with respect to HSs. Smoking habit was the only clinical feature correlated to PLI on LUS examination in our population. Full article

(This article belongs to the Special Issue New Insights into Lung Imaging)

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12 pages, 1300 KB

Open AccessArticle

Improving Image Quality of Chest Radiography with Artificial Intelligence-Supported Dual-Energy X-Ray Imaging System: An Observer Preference Study in Healthy Volunteers

by Sung-Hyun Yoon, Jihang Kim, Junghoon Kim, Jong-Hyuk Lee, Ilwoong Choi, Choul-Woo Shin and Chang-Min Park

J. Clin. Med. 2025, 14(6), 2091; https://doi.org/10.3390/jcm14062091 - 19 Mar 2025

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Abstract

Background/Objectives: To compare the image quality of chest radiography with a dual-energy X-ray imaging system using AI technology (DE-AI) to that of conventional chest radiography with a standard protocol. Methods: In this prospective study, 52 healthy volunteers underwent dual-energy chest radiography. Images were obtained using two exposures at 60 kVp and 120 kVp, separated by a 150 ms interval. Four images were generated for each participant: a conventional image, an enhanced standard image, a soft-tissue-selective image, and a bone-selective image. A machine learning model optimized the cancellation parameters for generating soft-tissue and bone-selective images. To enhance image quality, motion artifacts were minimized using Laplacian pyramid diffeomorphic registration, while a wavelet directional cycle-consistent adversarial network (WavCycleGAN) reduced image noise. Four radiologists independently evaluated the visibility of thirteen anatomical regions (eight soft-tissue regions and five bone regions) and the overall image with a five-point scale of preference. Pooled mean values were calculated for each anatomic region through meta-analysis using a random-effects model. Results: Radiologists preferred DE-AI images to conventional chest radiographs in various anatomic regions. The enhanced standard image showed superior quality in 9 of 13 anatomic regions. Preference for the soft-tissue-selective image was statistically significant for three of eight anatomic regions. Preference for the bone-selective image was statistically significant for four of five anatomic regions. Conclusions: Images produced by DE-AI provide better visualization of thoracic structures. Full article

(This article belongs to the Special Issue New Insights into Lung Imaging)

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14 pages, 23439 KB

Open AccessFeature PaperArticle

Prognostic Value of Chest CT Volumetric Analysis in Patients with Malignant Pleural Mesothelioma

by Elisa Baratella, Eleonora Ercolani, Antonio Segalotti, Marina Troian, Stefano Lovadina, Fabiola Giudici, Pierluca Minelli, Barbara Ruaro, Francesco Salton and Maria Assunta Cova

J. Clin. Med. 2025, 14(5), 1547; https://doi.org/10.3390/jcm14051547 - 25 Feb 2025

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Abstract

Background/Objectives: Malignant pleural mesothelioma (MPM) is a rare, aggressive cancer linked to asbestos exposure and with poor overall survival. In recent years, CT volumetric analysis has gained increasing interest as a more accurate method for assessing tumor burden. This study aims to evaluate the prognostic value of chest CT volumetric analysis in MPM, comparing tumor volume with tumor thickness measurements and survival outcomes. Methods: This is a retrospective, observational analysis of all patients undergoing diagnostic thoracoscopy between 2014 and 2021 at the University Hospital of Cattinara (Trieste, Italy). Inclusion criteria were as follows: age ≥ 18 years, histological diagnosis of MPM, and the availability of at least one contrast-enhanced chest CT scan at the time of diagnosis. For each patient, the tumor thickness was measured on the axial plane at three levels (upper, middle, and lower hemithorax). Tumor and effusion volumes were calculated with the RayStation^® software version 11.7.174 (HealthMyne^®, Madison, WI, USA). Results: A total of 81 patients were eligible for analysis. Maximum and mean tumor thickness were strongly associated with survival, with higher thicknesses correlating with an increased risk of death (adjusted hazard ratio per doubling (aHR) of 1.97 (95%CI: 1.40–2.77) and of 2.23 (95%CI: 1.56–3.20), p < 0.001)), respectively, while the effect of the tumor volume on survival was nevertheless significant but less impactful (aHR = 1.26 (1.10–1.45, p < 0.001)). The presence and volume of effusion did not correlate with survival (p = 0.48 and p = 0.64, respectively). Conclusions: This study supports the role of quantitative parameters for staging MPM, particularly given the frequent discrepancies between clinical and pathological staging when relying solely on qualitative measures. Full article

(This article belongs to the Special Issue New Insights into Lung Imaging)

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11 pages, 1548 KB

Open AccessArticle

Quantitative Chest CT Analysis: Three Different Approaches to Quantify the Burden of Viral Interstitial Pneumonia Using COVID-19 as a Paradigm

by Salvatore Claudio Fanni, Leonardo Colligiani, Federica Volpi, Lisa Novaria, Michele Tonerini, Chiara Airoldi, Dario Plataroti, Brian J. Bartholmai, Annalisa De Liperi, Emanuele Neri and Chiara Romei

J. Clin. Med. 2024, 13(23), 7308; https://doi.org/10.3390/jcm13237308 - 1 Dec 2024

Viewed by 927

Abstract

Objectives: To investigate the relationship between COVID-19 pneumonia outcomes and three chest CT analysis approaches. Methods: Patients with COVID-19 pneumonia who underwent chest CT were included and divided into survivors/non-survivors and intubated/not-intubated. Chest CTs were analyzed through a (1) Total Severity Score visually quantified by an emergency (TSS1) and a thoracic radiologist (TSS2); (2) density mask technique quantifying normal parenchyma (DM_Norm 1) and ground glass opacities (DM_GGO1) repeated after the manual delineation of consolidations (DM_Norm2, DM_GGO2, DM_Consolidation); (3) texture analysis quantifying normal parenchyma (TA_Norm) and interstitial lung disease (TA_ILD). Association with outcomes was assessed through Chi-square and the Mann–Whitney test. The TSS inter-reader variability was assessed through intraclass correlation coefficient (ICC) and Bland–Altman analysis. The relationship between quantitative variables and outcomes was investigated through multivariate logistic regression analysis. Variables correlation was investigated using Spearman analysis. Results: Overall, 192 patients (mean age, 66.8 ± 15.4 years) were included. TSS was significantly higher in intubated patients but only TSS1 in survivors. TSS presented an ICC of 0.83 (0.76; 0.88) and a bias (LOA) of 1.55 (−4.69, 7.78). DM_Consolidation showed the greatest median difference between survivors/not survivors (p = 0.002). The strongest independent predictor for mortality was DM_Consolidation (AUC 0.688), while the strongest independent predictor for the intensity of care was TSS2 (0.7498). DM_Norm 2 was the singular feature independently associated with both the outcomes. DM_GGO1 strongly correlated with TA_ILD (ρ = 0.977). Conclusions: The DM technique and TA achieved consistent measurements and a better correlation with patient outcomes. Full article

(This article belongs to the Special Issue New Insights into Lung Imaging)

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