Pulmonary Hypertension in Chronic Lung Diseases: What Role Do Radiologists Play?

Pulmonary hypertension (PH) is a pathophysiological disorder, defined by a mean pulmonary arterial pressure (mPAP) > 20 mmHg at rest, as assessed by right heart catheterization (RHC). PH is not a specific disease, as it may be observed in multiple clinical conditions and may complicate a variety of thoracic diseases. Conditions associated with the risk of developing PH are categorized into five different groups, according to similar clinical presentations, pathological findings, hemodynamic characteristics, and treatment strategy. Most chronic lung diseases that may be complicated by PH belong to group 3 (interstitial lung diseases, chronic obstructive pulmonary disease, combined pulmonary fibrosis, and emphysema) and are associated with the lowest overall survival among all groups. However, some of the chronic pulmonary diseases may develop PH with unclear/multifactorial mechanisms and are included in group 5 PH (sarcoidosis, pulmonary Langerhans' cell histiocytosis, and neurofibromatosis type 1). This paper focuses on PH associated with chronic lung diseases, in which radiological imaging-particularly computed tomography (CT)-plays a crucial role in diagnosis and classification. Radiologists should become familiar with the hemodynamical, physiological, and radiological aspects of PH and chronic lung diseases in patients at risk of developing PH, whose prognosis and treatment depend on the underlying disease.

Extension of Lung Damage at Chest Computed Tomography in Severely Ill COVID-19 Patients Treated with Interleukin-6 Receptor Blockers Correlates with Inflammatory Cytokines Production and Prognosis.

Elevated inflammatory markers are associated with severe coronavirus disease 2019 (COVID-19), and some patients benefit from Interleukin (IL)-6 pathway inhibitors. Different chest computed tomography (CT) scoring systems have shown a prognostic value in COVID-19, but not specifically in anti-IL-6-treated patients at high risk of respiratory failure. We aimed to explore the relationship between baseline CT findings and inflammatory conditions and to evaluate the prognostic value of chest CT scores and laboratory findings in COVID-19 patients specifically treated with anti-IL-6. Baseline CT lung involvement was assessed in 51 hospitalized COVID-19 patients naive to glucocorticoids and other immunosuppressants using four CT scoring systems. CT data were correlated with systemic inflammation and 30-day prognosis after anti-IL-6 treatment. All the considered CT scores showed a negative correlation with pulmonary function and a positive one with C-reactive protein (CRP), IL-6, IL-8, and Tumor Necrosis Factor α (TNF-α) serum levels. All the performed scores were prognostic factors, but the disease extension assessed by the six-lung-zone CT score (S24) was the only independently associated with intensive care unit (ICU) admission (p = 0.04). In conclusion, CT involvement correlates with laboratory inflammation markers and is an independent prognostic factor in COVID-19 patients representing a further tool to implement prognostic stratification in hospitalized patients.

Quantitative computed tomography predicts outcomes in idiopathic pulmonary fibrosis.

BACKGROUND AND OBJECTIVE: Prediction of disease course in patients with progressive pulmonary fibrosis remains challenging. The purpose of this study was to assess the prognostic value of lung fibrosis extent quantified at computed tomography (CT) using data-driven texture analysis (DTA) in a large cohort of well-characterized patients with idiopathic pulmonary fibrosis (IPF) enrolled in a national registry. METHODS: This retrospective analysis included participants in the Australian IPF Registry with available CT between 2007 and 2016. CT scans were analysed using the DTA method to quantify the extent of lung fibrosis. Demographics, longitudinal pulmonary function and quantitative CT metrics were compared using descriptive statistics. Linear mixed models, and Cox analyses adjusted for age, gender, BMI, smoking history and treatment with anti-fibrotics were performed to assess the relationships between baseline DTA, pulmonary function metrics and outcomes. RESULTS: CT scans of 393 participants were analysed, 221 of which had available pulmonary function testing obtained within 90 days of CT. Linear mixed-effect modelling showed that baseline DTA score was significantly associated with annual rate of decline in forced vital capacity and diffusing capacity of carbon monoxide. In multivariable Cox proportional hazard models, greater extent of lung fibrosis was associated with poorer transplant-free survival (hazard ratio [HR] 1.20, p < 0.0001) and progression-free survival (HR 1.14, p < 0.0001). CONCLUSION: In a multi-centre observational registry of patients with IPF, the extent of fibrotic abnormality on baseline CT quantified using DTA is associated with outcomes independent of pulmonary function.

Deep Learning-based Outcome Prediction in Progressive Fibrotic Lung Disease Using High-Resolution Computed Tomography.

Rationale: Reliable outcome prediction in patients with fibrotic lung disease using baseline high-resolution computed tomography (HRCT) data remains challenging. Objectives: To evaluate the prognostic accuracy of a deep learning algorithm (SOFIA [Systematic Objective Fibrotic Imaging Analysis Algorithm]), trained and validated in the identification of usual interstitial pneumonia (UIP)-like features on HRCT (UIP probability), in a large cohort of well-characterized patients with progressive fibrotic lung disease drawn from a national registry. Methods: SOFIA and radiologist UIP probabilities were converted to Prospective Investigation of Pulmonary Embolism Diagnosis (PIOPED)-based UIP probability categories (UIP not included in the differential, 0-4%; low probability of UIP, 5-29%; intermediate probability of UIP, 30-69%; high probability of UIP, 70-94%; and pathognomonic for UIP, 95-100%), and their prognostic utility was assessed using Cox proportional hazards modeling. Measurements and Main Results: In multivariable analysis adjusting for age, sex, guideline-based radiologic diagnosis, anddisease severity (using total interstitial lung disease [ILD] extent on HRCT, percent predicted FVC, DlCO, or the composite physiologic index), only SOFIA UIP probability PIOPED categories predicted survival. SOFIA-PIOPED UIP probability categories remained prognostically significant in patients considered indeterminate (n = 83) by expert radiologist consensus (hazard ratio, 1.73; P < 0.0001; 95% confidence interval, 1.40-2.14). In patients undergoing surgical lung biopsy (n = 86), after adjusting for guideline-based histologic pattern and total ILD extent on HRCT, only SOFIA-PIOPED probabilities were predictive of mortality (hazard ratio, 1.75; P < 0.0001; 95% confidence interval, 1.37-2.25). Conclusions: Deep learning-based UIP probability on HRCT provides enhanced outcome prediction in patients with progressive fibrotic lung disease when compared with expert radiologist evaluation or guideline-based histologic pattern. In principle, this tool may be useful in multidisciplinary characterization of fibrotic lung disease. The utility of this technology as a decision support system when ILD expertise is unavailable requires further investigation.

The evolution of computer-based analysis of high-resolution CT of the chest in patients with IPF.

In patients with idiopathic pulmonary fibrosis (IPF), there is an urgent need of biomarkers which can predict disease behaviour or response to treatment. Most published studies report results based on continuous data which can be difficult to apply to individual patients in clinical practice. Having antifibrotic therapies makes it even more important that we can accurately diagnose and prognosticate in IPF patients. Advances in computer technology over the past decade have provided computer-based methods for objectively quantifying fibrotic lung disease on high-resolution CT of the chest with greater strength than visual CT analysis scores. These computer-based methods and, more recently, the arrival of deep learning-based image analysis might provide a response to these unsolved problems. The purpose of this commentary is to provide insights into the problems associated with visual interpretation of HRCT, describe of the current technologies used to provide quantification of disease on HRCT and prognostication in IPF patients, discuss challenges to the implementation of this technology and future directions.

Role of delayed phase contrast-enhanced CT in the intra-thoracic staging of non-small cell lung cancer (NSCLC): What does it add?

PURPOSE: The aim of the study was to investigate differences in non-small cell lung cancer (NSCLC) intra-thoracic staging by using contrast-enhanced computed tomography (ce-CT) at the arterial phase (AP), at the arterial plus delayed phases (AP + DEP), and at the delayed phase (DEP), and to evaluate their potential impact on disease staging. MATERIALS AND METHODS: Two chest radiologists with different level of expertise and a general radiologist independently reviewed the chest CT exams of 150 patients with NSCLC; CT scans were performed 40 s (AP) and 60 s (DEP) after contrast material injection. Image assessment included three reading sessions: session A (AP), session B (AP + DEP) and session C (DEP). CT descriptors for the primary tumour (T), regional nodal involvement (N), and intra-thoracic metastases (M) were evaluated in each reading session. Readers had to assign a confidence level (CL) for the assessment of each descriptor and define the TNM stage. Friedman and Cochran Q test was used to compare the assessments of the 3 reading sessions; inter-reader agreement was determined (Intraclass Correlation Coefficient - ICC). RESULTS: The CL was significantly higher in sessions B and C than in session A for all descriptors, with the exception of pulmonary arterial invasion. Primary tumour inner necrosis and regional nodal involvement were detected in a significantly higher number of cases in sessions B and C as compared to session A (p ≤ 0.001). DEP significantly changed N stage determination (p < 0.001), particularly N3, and excluded chest wall invasion (p = 0.05) and venous invasion (p = 0.001). The agreement was good among the 3 readers (ICC = 0.761) and excellent between the 2 chest radiologists (ICC ≥ 0.940), regardless of the contrast phase. CONCLUSIONS: The 60-second DEP ce-CT for staging NSCLC significantly increased the readers' CL, changed the N stage determination, and helped excluding chest wall invasion and venous invasion.

Structured Reporting of Lung Cancer Staging: A Consensus Proposal.

BACKGROUND: Structured reporting (SR) in radiology is becoming necessary and has recently been recognized by major scientific societies. This study aimed to build CT-based structured reports for lung cancer during the staging phase, in order to improve communication between radiologists, members of the multidisciplinary team and patients. MATERIALS AND METHODS: A panel of expert radiologists, members of the Italian Society of Medical and Interventional Radiology, was established. A modified Delphi exercise was used to build the structural report and to assess the level of agreement for all the report sections. The Cronbach's alpha (Cα) correlation coefficient was used to assess internal consistency for each section and to perform a quality analysis according to the average inter-item correlation. RESULTS: The final SR version was built by including 16 items in the "Patient Clinical Data" section, 4 items in the "Clinical Evaluation" section, 8 items in the "Exam Technique" section, 22 items in the "Report" section, and 5 items in the "Conclusion" section. Overall, 55 items were included in the final version of the SR. The overall mean of the scores of the experts and the sum of scores for the structured report were 4.5 (range 1-5) and 631 (mean value 67.54, STD 7.53), respectively, in the first round. The items of the structured report with higher accordance in the first round were primary lesion features, lymph nodes, metastasis and conclusions. The overall mean of the scores of the experts and the sum of scores for staging in the structured report were 4.7 (range 4-5) and 807 (mean value 70.11, STD 4.81), respectively, in the second round. The Cronbach's alpha (Cα) correlation coefficient was 0.89 in the first round and 0.92 in the second round for staging in the structured report. CONCLUSIONS: The wide implementation of SR is critical for providing referring physicians and patients with the best quality of service, and for providing researchers with the best quality of data in the context of the big data exploitation of the available clinical data. Implementation is complex, requiring mature technology to successfully address pending user-friendliness, organizational and interoperability challenges.

Novelties in Imaging of Thoracic Sarcoidosis.

Sarcoidosis is a systemic granulomatous disease affecting various organs, and the lungs are the most commonly involved. According to guidelines, diagnosis relies on a consistent clinical picture, histological demonstration of non-caseating granulomas, and exclusion of other diseases with similar histological or clinical picture. Nevertheless, chest imaging plays an important role in both diagnostic assessment, allowing to avoid biopsy in some situations, and prognostic evaluation. Despite the demonstrated lower sensitivity of chest X-ray (CXR) in the evaluation of chest findings compared to high-resolution computed tomography (HRCT), CXR still retains a pivotal role in both diagnostic and prognostic assessment in sarcoidosis. Moreover, despite the huge progress made in the field of radiation dose reduction, chest magnetic resonance (MR), and quantitative imaging, very little research has focused on their application in sarcoidosis. In this review, we aim to describe the latest novelties in diagnostic and prognostic assessment of thoracic sarcoidosis and to identify the fields of research that require investigation.

A Case of Primary Localized Small Bowel Amyloidosis Studied by 18F-Choline and Contrast-Enhanced 18F-FDG PET/CT.

Amyloidosis is a rare hereditary or acquired protein deposition disorder with different etiologies, characterized by pathological protein deposition essentially in nearly any organs or tissues. There are 2 major forms: primary and secondary amyloidosis. Moreover, it is possible to have systemic or localized disease. The localized form of amyloidosis affecting the small intestine is rare, and it is characterized by the formation of precursor proteins at the site of the lesion. We report a case of localized small bowel amyloidosis studied by F-choline and F-FDG-iodinated PET/CT performed for staging an aggressive prostatic cancer.

Uniportal VATS Coil-Assisted Resections for GGOs.

BACKGROUNDS: Although uniportal video-assisted thoracic surgery (VATS) theoretically allows the direct palpation of any zone of the lung through a small incision, sometimes it can be difficult to localize pure ground-glass opacities anyway. The aim of this study is to evaluate the usefulness and safety of preoperative computed tomography (CT)-guided microcoil localization of GGO nodules in patients undergoing uniportal VATS lung resection. METHODS: The clinical data and CT images of 30 consecutive patients (30 pulmonary nodules) who underwent preoperative CT-guided coil localization and subsequent uniportal VATS resection, from January 2017 to October 2018, were reviewed. RESULTS: All the CT-localization procedures have been performed with success (30/30) and the mean procedure time was 35±15 minutes. The mean size of the nodules was 15,53±6,72 mm, and the mean distance of the nodules from the pleural surface was 19,08±12,08 mm. Eleven nodules (36,7%) were pure ground-glass opacities and 19 (63,3%) were mixed ground-glass with a solid component of 50% or more. In 5 cases, the localization procedure was complicated by asymptomatic pneumothoraxes and in 1 case the pneumothorax required chest tube insertion. In any case a conversion to thoracotomy was avoided because all nodules were identified and resected through uniportal VATS. CONCLUSIONS: Preoperative CT-guided coil localization seems to be a feasible, safe, and accurate procedure. It makes uniportal VATS an easy approach even for resecting small, deep, and impalpable nodules.

Variable radiological lung nodule evaluation leads to divergent management recommendations.

Radiological evaluation of incidentally detected lung nodules on computed tomography (CT) influences management. We assessed international radiological variation in 1) pulmonary nodule characterisation; 2) hypothetical guideline-derived management; and 3) radiologists' management recommendations.107 radiologists from 25 countries evaluated 69 CT-detected nodules, recording: 1) first-choice composition (solid, part-solid or ground-glass, with percentage confidence); 2) morphological features; 3) dimensions; 4) recommended management; and 5) decision-influencing factors. We modelled hypothetical management decisions on the 2005 and updated 2017 Fleischner Society, and both liberal and parsimonious interpretations of the British Thoracic Society 2015 guidelines.Overall agreement for first-choice nodule composition was good (Fleiss' κ=0.65), but poorest for part-solid nodules (weighted κ 0.62, interquartile range 0.50-0.71). Morphological variables, including spiculation (κ=0.35), showed poor-to-moderate agreement (κ=0.23-0.53). Variation in diameter was greatest at key thresholds (5 mm and 6 mm). Agreement for radiologists' recommendations was poor (κ=0.30); 21% disagreed with the majority. Although agreement within the four guideline-modelled management strategies was good (κ=0.63-0.73), 5-10% of radiologists would disagree with majority decisions if they applied guidelines strictly.Agreement was lowest for part-solid nodules, while significant measurement variation exists at important size thresholds. These variations resulted in generally good agreement for guideline-modelled management, but poor agreement for radiologists' actual recommendations.

Deep learning for classifying fibrotic lung disease on high-resolution computed tomography: a case-cohort study.

BACKGROUND: Based on international diagnostic guidelines, high-resolution CT plays a central part in the diagnosis of fibrotic lung disease. In the correct clinical context, when high-resolution CT appearances are those of usual interstitial pneumonia, a diagnosis of idiopathic pulmonary fibrosis can be made without surgical lung biopsy. We investigated the use of a deep learning algorithm for provision of automated classification of fibrotic lung disease on high-resolution CT according to criteria specified in two international diagnostic guideline statements: the 2011 American Thoracic Society (ATS)/European Respiratory Society (ERS)/Japanese Respiratory Society (JRS)/Latin American Thoracic Association (ALAT) guidelines for diagnosis and management of idiopathic pulmonary fibrosis and the Fleischner Society diagnostic criteria for idiopathic pulmonary fibrosis. METHODS: In this case-cohort study, for algorithm development and testing, a database of 1157 anonymised high-resolution CT scans showing evidence of diffuse fibrotic lung disease was generated from two institutions. We separated the scans into three non-overlapping cohorts (training set, n=929; validation set, n=89; and test set A, n=139) and classified them using 2011 ATS/ERS/JRS/ALAT idiopathic pulmonary fibrosis diagnostic guidelines. For each scan, the lungs were segmented and resampled to create a maximum of 500 unique four slice combinations, which we converted into image montages. The final training dataset consisted of 420 096 unique montages for algorithm training. We evaluated algorithm performance, reported as accuracy, prognostic accuracy, and weighted κ coefficient (κw) of interobserver agreement, on test set A and a cohort of 150 high-resolution CT scans (test set B) with fibrotic lung disease compared with the majority vote of 91 specialist thoracic radiologists drawn from multiple international thoracic imaging societies. We then reclassified high-resolution CT scans according to Fleischner Society diagnostic criteria for idiopathic pulmonary fibrosis. We retrained the algorithm using these criteria and evaluated its performance on 75 fibrotic lung disease specific high-resolution CT scans compared with four specialist thoracic radiologists using weighted κ coefficient of interobserver agreement. FINDINGS: The accuracy of the algorithm on test set A was 76·4%, with 92·7% of diagnoses within one category. The algorithm took 2·31 s to evaluate 150 four slice montages (each montage representing a single case from test set B). The median accuracy of the thoracic radiologists on test set B was 70·7% (IQR 65·3-74·7), and the accuracy of the algorithm was 73·3% (93·3% were within one category), outperforming 60 (66%) of 91 thoracic radiologists. Median interobserver agreement between each of the thoracic radiologists and the radiologist's majority opinion was good (κw=0·67 [IQR 0·58-0·72]). Interobserver agreement between the algorithm and the radiologist's majority opinion was good (κw=0·69), outperforming 56 (62%) of 91 thoracic radiologists. The algorithm provided equally prognostic discrimination between usual interstitial pneumonia and non-usual interstitial pneumonia diagnoses (hazard ratio 2·88, 95% CI 1·79-4·61, p<0·0001) compared with the majority opinion of the thoracic radiologists (2·74, 1·67-4·48, p<0·0001). For Fleischner Society high-resolution CT criteria for usual interstitial pneumonia, median interobserver agreement between the radiologists was moderate (κw=0·56 [IQR 0·55-0·58]), but was good between the algorithm and the radiologists (κw=0·64 [0·55-0·72]). INTERPRETATION: High-resolution CT evaluation by a deep learning algorithm might provide low-cost, reproducible, near-instantaneous classification of fibrotic lung disease with human-level accuracy. These methods could be of benefit to centres at which thoracic imaging expertise is scarce, as well as for stratification of patients in clinical trials. FUNDING: None.

The added value of chemical shift MRI in the preoperative diagnosis of thymolipoma.

Thymolipoma is a rare tumor of the thymus. Classic radiologic findings of thymolipoma include fatty masses of the anterior mediastinum in conjunction with the thymus. Differential diagnosis with other more aggressive entities like liposarcoma and teratoma can be challenging. We report a case where chemical shift magnetic resonance imaging helped in the differential diagnosis.

Pulmonary fibrolysis in a patient with idiopathic pulmonary fibrosis: improvement of clinical and radiological pattern after treatment with pirfenidone.

Idiopathic Pulmonary Fibrosis (IPF) is a chronic, progressive, fibrosing interstitial pneumonia associated with the histologic and/or radiologic pattern of usual interstitial pneumonia (UIP). Nowadays, the high-resolution computed tomography pattern of "definite UIP" is enough to define a diagnosis of UIP without histological proof. This is pivotal especially in elderly patients with comorbidities. Early recognition of IPF is relevant for its prognostic implication. Some pharmacological strategies have been proposing novel molecules that tend to slow lung function decline, even though without healing fibrosis. We report a case of ex-heavy smoker male with IPF showing clinical and radiological improvement after 11 months of treatment with Pirfenidone. The definite diagnosis was challenging and it was reached by a multidisciplinary approach.

Multifunctional Assessment of Non-Small Cell Lung Cancer: Perfusion-Metabolic Correlation.

PURPOSE: The aim of this study was to investigate the relationship between whole-tumor CT perfusion and FDG PET/CT parameters in non-small cell lung cancer (NSCLC). METHODS: Twenty-five patients with NSCLC were prospectively included. CT perfusion parameters calculated were blood flow (BF), blood volume (BV), mean transit time, and peak enhancement intensity. SUVmax, SUVpeak, SUVmean, metabolic tumor volume (MTV), and total lesion glycolysis (TLG) were evaluated for PET/CT. Tumor diameter and volume were measured, and lesions were divided according to maximum axial diameter in more than 3 cm and 3 cm or less. The correlations between CT perfusion and PET/CT parameters were assessed in all tumors, as well as according to tumor diameter and volume. RESULTS: Lesion diameter and volume showed a negative correlation with BF and BV (r = -0.78, -0.78, -0.57, -0.48, respectively) and a positive correlation with mean transit time (r = 0.55, 0.65, respectively). The negative correlation between BF and lesion diameter and volume was confirmed in the subgroup of lesions of more than 3 cm (r = -0.68, -0.68, respectively). A positive correlation between SUVmax, SUVpeak, SUVmean, and lesion volume was observed (r = 0.50, 0.50, 0.46, respectively) and confirmed in lesions 3 cm or less (r = 0.81, 0.79, 0.78, respectively). Metabolic tumor volume and TLG showed a positive correlation with lesion diameter and volume in the overall population (r = 0.93, 0.87, 0.88, 0.90, respectively) and in lesions of more than 3 cm (r = 0.89, 0.84, 0.84, 0.79, respectively). Blood flow and BV showed a negative correlation with MTV and TLG (r = -0.77, -0.74, and -0.58, -0.48, respectively) in the overall population and with MTV in lesions of more than 3 cm (r = -0.69, -0.62, respectively). CONCLUSIONS: Perfusion and metabolic parameters seem to depend on tumor size. The bigger the tumor, the lower the BF and the BV and, conversely, the higher the SUVpeak, MTV, and TLG. This information would be useful in the clinical setting when diagnosing or treating NSCLC, especially with novel therapies and/or for radiation treatment modulation.

Radiological and nuclear medicine imaging of sarcoidosis.

Sarcoidosis is a multisystem chronic inflammatory disease of unknown etiology characterized by widespread growth of non-caseating granulomas. The diagnosis of sarcoidosis is based on clinical and imaging presentation, histologic confirmation and the absence of alternative diseases. Radiology and Nuclear Medicine play an essential role in the diagnostic work-up of patients with sarcoidosis to assess disease extent and activity. In addition, imaging modalities have shown their potential in managing these patients in terms of treatment response and prognostic assessment. Sarcoidosis has a predilection for chest involvement, showing typical and atypical manifestations in the lungs, airways and hilar/mediastinal lymph nodes. Chest radiography (X-ray) still plays an important role in suggesting diagnosis for cases with typical presentation of sarcoidosis, while computed tomography (CT) has higher accuracy in detecting early stage disease and in narrowing differential diagnosis, particularly in atypical manifestations. For extrathoracic involvement, both CT and MR (magnetic resonance) have comparable performance even though MR is the modality of choice for assessing neurosarcoidosis and cardiac sarcoidosis. In the last decades positron emission tomography/CT (PET/CT) has demonstrated an increasing and relevant value in assessing disease extent and activity, treatment planning and therapy response, with a crucial role in the management of cardiac sarcoidosis. In this article, an overview of the possible imaging manifestations of thoracic and extrathoracic sarcoidosis and current concepts on staging, response assessment and prognosis is provided. Finally, the potential applications of non-FDG radiotracers is briefly discussed.