Structured reporting for fibrosing lung disease: a model shared by radiologist and pulmonologist

The Unveiled Triad: Clinical, Radiological and Pathological Insights into Hypersensitivity Pneumonitis

Hypersensitivity pneumonitis (HP) is a diffuse parenchymal lung disease (DLPD) characterized by complex interstitial lung damage with polymorphic and protean inflammatory aspects affecting lung tissue targets including small airways, the interstitium, alveolar compartments and vascular structures. HP shares clinical and often radiological features with other lung diseases in acute or chronic forms. In its natural temporal evolution, if specific therapy is not initiated promptly, HP leads to progressive fibrotic damage with reduced lung volumes and impaired gas exchange. The prevalence of HP varies considerably worldwide, influenced by factors like imprecise disease classification, diagnostic method limitations for obtaining a confident diagnosis, diagnostic limitations in the correct processing of high-resolution computed tomography (HRCT) radiological parameters, unreliable medical history, diverse geographical conditions, heterogeneous agricultural and industrial practices and occasionally ineffective individual protections regarding occupational exposures and host risk factors. The aim of this review is to present an accurate and detailed 360-degree analysis of HP considering HRCT patterns and the role of the broncho-alveolar lavage (BAL), without neglecting biopsy and anatomopathological aspects and future technological developments that could make the diagnosis of this disease less challenging.

Establishing quantitative radiographic criteria for the diagnosis of pleuroparenchymal fibroelastosis

PURPOSE

Pleuroparenchymal Fibroelastosis (PPFE) is a type of pulmonary fibrosis most commonly occurring at the apices. Patients with PPFE have an increased risk of adverse effects from lung biopsy and in the post-surgical setting. Here, we investigated simple and reproducible measurements on chest CT to evaluate their predictive value in diagnosing PPFE.

METHODS

We analyzed a cohort of patients with histologically-proven PPFE and compared them to a cohort of patients diagnosed with "biapical scarring" (BAS) on chest CT. We measured plueuroparenchymal thickness using several independent parameters on chest CT. We also assessed other radiologic and clinical characteristics to identify if any were predictive of PPFF.

RESULTS

Our analysis demonstrated the average greatest apical thickness with a cut off of 4.5 mm yielded a sensitivity of 94.4% and a specificity of 88.9%, and an area under the curve of 97.2%. Single greatest apical thickness with a cut off of 7.5 mm had a sensitivity of 100% and a specificity of 88.9%, with the area under the curve of 97.8%. Average greatest upper lobe thickness with a cut off of 8.0 mm had a sensitivity of 88.9% and a specificity of 100%, with an area under the curve of 98.2%. Single greatest upper lobe thickness with a cut off of 8.5 yielded both a sensitivity and specificity of 94.4% and an area under the curve of 94.3%.

CONCLUSION

Measurements described above are highly sensitive and specific for the diagnosis of PPFE and warrant investigation with a larger cohort of patients.

Tips and Tricks in Thoracic Radiology for Beginners: A Findings-Based Approach

This review has the purpose of illustrating schematically and comprehensively the key concepts for the beginner who approaches chest radiology for the first time. The approach to thoracic imaging may be challenging for the beginner due to the wide spectrum of diseases, their overlap, and the complexity of radiological findings. The first step consists of the proper assessment of the basic imaging findings. This review is divided into three main districts (mediastinum, pleura, focal and diffuse diseases of the lung parenchyma): the main findings will be discussed in a clinical scenario. Radiological tips and tricks, and relative clinical background, will be provided to orient the beginner toward the differential diagnoses of the main thoracic diseases.

Primary Lymphoproliferative Lung Diseases: Imaging and Multidisciplinary Approach

Lymphoproliferative lung diseases are a heterogeneous group of disorders characterized by primary or secondary involvement of the lung. Primary pulmonary lymphomas are the most common type, representing 0.5–1% of all primary malignancies of the lung. The radiological presentation is often heterogeneous and non-specific: consolidations, masses, and nodules are the most common findings, followed by ground-glass opacities and interstitial involvement, more common in secondary lung lymphomas. These findings usually show a prevalent perilymphatic spread along bronchovascular bundles, without a prevalence in the upper or lower lung lobes. An ancillary sign, such as a “halo sign”, “reverse halo sign”, air bronchogram, or CT angiogram sign, may be present and can help rule out a differential diagnosis. Since a wide spectrum of pulmonary parenchymal diseases may mimic lymphoma, a correct clinical evaluation and a multidisciplinary approach are mandatory. In this sense, despite High-Resolution Computer Tomography (HRCT) representing the gold standard, a tissue sample is needed for a certain and definitive diagnosis. Cryobiopsy is a relatively new technique that permits the obtaining of a larger amount of tissue without significant artifacts, and is less invasive and more precise than surgical biopsy.

Structured report improves radiology residents' performance in reporting chest high-resolution computed tomography: a study in patients with connective tissue disease

PURPOSE To evaluate the performance of radiology residents (RRs) when using a dedicated structured report (SR) template for chest HRCT in patients with suspected connective tissue disease-interstitial lung disease (CTD-ILD), compared to the traditional narrative report (NR). METHODS We retrospectively evaluated 50 HRCT exams in patients with suspected CTD-ILD. A chest-devoted radiologist reported all the HRCT exams as the reference standard, pointing out pulmonary fibrosis findings (i.e., honeycombing, traction bronchiectasis, reticulation, and volume loss), presence and pattern of ILD, and possible other diagnoses. We divided four RRs into two groups according to their expertise level. In each group, RRs reported all HRCT examinations alternatively with NR or SR, noting each report's reporting time. The Cohen's Kappa, Wilcoxon, and McNemar tests were used for statistical analysis. RESULTS Regarding the pulmonary fibrosis findings, we found higher agreement between RRs and the reference standard reader when using SR than NR, regardless of their expertise level, except for volume loss.RRs' accuracy for "other diagnosis" was higher when using SR than NR, moving from 0.48 to 0.66 in the novel group (p = 0.035) and from 0.44 to 0.80 in the expertise group (p < 0.001). No differences in accuracy were found between ILD presence and ILD pattern. The reporting time was significantly lower (p = 0.001) when using SR than NR. CONCLUSION SR is of value in increasing the reporting of critical chest HRCT findings in the complex CTD-ILD scenario and should be used early and systematically during the residency.

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.

Portal vein thrombosis in patients with chronic liver diseases: From conventional to quantitative imaging

Portal vein thrombosis is a pathological condition characterized by the lumen occlusion of the portal vein and its intrahepatic branches, commonly associated to chronic liver diseases. Portal vein thrombosis is often asymptomatic and discovered as an incidental finding in the follow-up of chronic hepatopathy. Imaging plays a pivotal role in the detection and characterization of portal vein thrombosis in patients with hepatocellular carcinoma. Ultrasound and Color-Doppler ultrasound are usually the first-line imaging modalities for its detection, but they have limits related to operator-experience, patient size, meteorism and the restrained field-of view. Unenhanced cross-sectional imaging doesn't provide specific signs of portal vein thrombosis except under certain specific circumstances. Conventional contrast-enhanced imaging can depict portal vein thrombosis as an endoluminal filling defect best detected in venous phase and can differentiate between non-neoplastic and neoplastic thrombus based on the contrast enhanced uptake, but not always rule-out the malignant nature. Functional and quantitative imaging techniques and software seem to be more accurate. The purpose of this work is to provide the reader with an accurate overview focused on the main imaging features of portal vein thrombosis.

The role of the combination of echo-HRCT score as a tool to evaluate the presence of pulmonary hypertension in idiopathic pulmonary fibrosis

Pulmonary hypertension (PH) is defined as an elevated mean pulmonary artery pressure at rest (mPAP ≥ 25 mmHg), evaluated by right heart catheterization (RHC). The aim of the present study was to evaluate HRCT findings in relation to transthoracic echocardiographic data to better characterize PH in IPF patients and to identify a non-invasive composite index with high predictive value for PH in these patients. 37 IPF patients were enrolled in this retrospective study. All patients underwent a complete assessment for PH, including transthoracic Doppler echocardiography, HRCT scan and right heart catheterization. Right heart catheterization was done in 19 patients (51.3%) as pre-lung transplant assessment and in 18 patients (48.6%) to confirm PH, suspected on the basis of echocardiography. Twenty out of 37 patients (54%) were confirmed to have PH by RHC. Multivariate regression showed that the combination of sPAP, PA area measured by HRCT and the ratio of the diameter of the segmental artery to that of the adjacent bronchus in the apicoposterior segment of the left upper lobe was strongly correlated with mPAP (R² = 0.53; p = 0.0009). The ROC analysis showed that 931.6 was the ULN for PA area, with 86% sensitivity and 61% specificity (0.839 AUC); 20.34 was the ULN for the ratio of PA area to ascending aorta diameter, with 100% sensitivity and 50% specificity (0.804 AUC). The composite index proposed in the present study could help early detection of IPF patients suspected of PH requiring confirmation by RHC (if deemed clinically necessary).

Screen-detected solid nodules: from detection of nodule to structured reporting

Lung cancer screening (LCS) is gaining some interest worldwide after positive results from International trials. Unlike other screening practices, LCS is performed by an extremely sensitive test, namely low-dose computed tomography (LDCT) that can detect the smallest nodules in lung parenchyma. Up-to-date detection approaches, such as computer aided detection systems, have been increasingly employed for lung nodule automatic identification and are largely used in most LCS programs as a complementary tool to visual reading. Solid nodules of any size are represented in the vast majority of subjects undergoing LDCT. However, less than 1% of solid nodules will be diagnosed lung cancer. This fact calls for specific characterization of nodules to avoid false positives, overinvestigation, and reduce the risks associated with nodule work up. Recent research has been exploring the potential of artificial intelligence, including deep learning techniques, to enhance the accuracy of both detection and characterisation of lung nodule. Computer aided detection and diagnosis algorithms based on artificial intelligence approaches have demonstrated the ability to accurately detect and characterize parenchymal nodules, reducing the number of false positives, and to outperform some of the currently used risk models for prediction of lung cancer risk, potentially reducing the proportion of surveillance CT scans. These forthcoming approaches will eventually integrate a new reasoning for development of future guidelines, which are expected to evolve into precision and personalized stratification of lung cancer risk stratification by continuous fashion, as opposed to the current format with a limited number of risk classes within fixed thresholds of nodule size. This review aims to detail the standard of reference for optimal management of solid nodules by low-dose computed and its projection into the fine selection of candidates for work up.

COVID-19 pneumonia: computer-aided quantification of healthy lung parenchyma, emphysema, ground glass and consolidation on chest computed tomography (CT)

OBJECTIVE

To calculate by means of a computer-aided tool the volumes of healthy residual lung parenchyma, of emphysema, of ground glass opacity (GGO) and of consolidation on chest computed tomography (CT) in patients with suspected viral pneumonia by COVID-19.

MATERIALS AND METHODS

This study included 116 patients that for suspected COVID-19 infection were subjected to the reverse transcription real-time fluorescence polymerase chain reaction (RT-PCR) test. A computer-aided tool was used to calculate on chest CT images healthy residual lung parenchyma, emphysema, GGO and consolidation volumes for both right and left lung. Expert radiologists, in consensus, assessed the CT images using a structured report and attributed a radiological severity score at the disease pulmonary involvement using a scale of five levels. Nonparametric test was performed to assess differences statistically significant among groups.

RESULTS

GGO was the most represented feature in suspected CT by COVID-19 infection; it is present in 102/109 (93.6%) patients with a volume percentage value of 19.50% and a median value of 0.64 L, while the emphysema and consolidation volumes were low (0.01 L and 0.03 L, respectively). Among quantified volume, only GGO volume had a difference statistically significant between the group of patients with suspected versus non-suspected CT for COVID-19 (p < < 0.01). There were differences statistically significant among the groups based on radiological severity score in terms of healthy residual parenchyma volume, of GGO volume and of consolidations volume (p < < 0.001).

CONCLUSION

We demonstrated that, using a computer-aided tool, the COVID-19 pneumonia was mirrored with a percentage median value of GGO of 19.50% and that only GGO volume had a difference significant between the patients with suspected or non-suspected CT for COVID-19 infection.

Clinical and laboratory data, radiological structured report findings and quantitative evaluation of lung involvement on baseline chest CT in COVID-19 patients to predict prognosis

OBJECTIVE

To evaluate by means of regression models the relationships between baseline clinical and laboratory data and lung involvement on baseline chest CT and to quantify the thoracic disease using an artificial intelligence tool and a visual scoring system to predict prognosis in patients with COVID-19 pneumonia.

MATERIALS AND METHODS

This study included 103 (41 women and 62 men; 68.8 years of mean age-range, 29-93 years) with suspicious COVID-19 viral infection evaluated by reverse transcription real-time fluorescence polymerase chain reaction (RT-PCR) test. All patients underwent CT examinations at the time of admission in addition to clinical and laboratory findings recording. All chest CT examinations were reviewed using a structured report. Moreover, using an artificial intelligence tool we performed an automatic segmentation on CT images based on Hounsfield unit to calculate residual healthy lung parenchyma, ground-glass opacities (GGO), consolidations and emphysema volumes for both right and left lungs. Two expert radiologists, in consensus, attributed at the CT pulmonary disease involvement a severity score using a scale of 5 levels; the score was attributed for GGO and consolidation for each lung, and then, an overall radiological severity visual score was obtained summing the single score. Univariate and multivariate regression analysis was performed.

RESULTS

Symptoms and comorbidities did not show differences statistically significant in terms of patient outcome. Instead, SpO2 was significantly lower in patients hospitalized in critical conditions or died while age, HS CRP, leukocyte count, neutrophils, LDH, d-dimer, troponin, creatinine and azotemia, ALT, AST and bilirubin values were significantly higher. GGO and consolidations were the main CT patterns (a variable combination of GGO and consolidations was found in 87.8% of patients). CT COVID-19 disease was prevalently bilateral (77.6%) with peripheral distribution (74.5%) and multiple lobes localizations (52.0%). Consolidation, emphysema and residual healthy lung parenchyma volumes showed statistically significant differences in the three groups of patients based on outcome (patients discharged at home, patients hospitalized in stable conditions and patient hospitalized in critical conditions or died) while GGO volume did not affect the patient's outcome. Moreover, the overall radiological severity visual score (cutoff ≥ 8) was a predictor of patient outcome. The highest value of R-squared (R2 = 0.93) was obtained by the model that combines clinical/laboratory findings at CT volumes. The highest accuracy was obtained by clinical/laboratory and CT findings model with a sensitivity, specificity and accuracy, respectively, of 88%, 78% and 81% to predict discharged/stable patients versus critical/died patients.

CONCLUSION

In conclusion, both CT visual score and computerized software-based quantification of the consolidation, emphysema and residual healthy lung parenchyma on chest CT images were independent predictors of outcome in patients with COVID-19 pneumonia.

Cardiac magnetic resonance in arrhythmogenic cardiomyopathies

Over the past few years, the approach to the 'arrhythmic patient' has profoundly changed. An early clinical presentation of arrhythmia is often accompanied by non-specific symptoms and followed by inconclusive electrocardiographic findings. In this scenario, cardiac magnetic resonance (CMR) has been established as a clinical tool of fundamental importance for a correct prognostic stratification of the arrhythmic patient. This technique provides a high-spatial-resolution tomographic evaluation of the heart, which allows studying accurately the ventricular volumes, identifying even segmental kinetic anomalies and properly detecting diffuse or focal tissue alterations through an excellent tissue characterization, while depicting different patterns of fibrosis distribution, myocardial edema or fatty substitution. Through these capabilities, CMR has a pivotal role for the adequate management of the arrhythmic patient, allowing the identification of those phenotypic manifestations characteristic of structural heart diseases. Therefore, CMR provides valuable information to reclassify the patient within the wide spectrum of potentially arrhythmogenic heart diseases, the definition of which remains the major determinants for both an adequate treatment and a poor prognosis. The purpose of this review study was to focus on the role of CMR in the evaluation of the main cardiac clinical entities associated with arrhythmogenic phenomena and to present a brief debate on the main pathophysiological mechanisms involved in the arrhythmogenesis process.

Chest CT Computerized Aided Quantification of PNEUMONIA Lesions in COVID-19 Infection: A Comparison among Three Commercial Software

PURPOSE

To compare different commercial software in the quantification of Pneumonia Lesions in COVID-19 infection and to stratify the patients based on the disease severity using on chest computed tomography (CT) images.

MATERIALS AND METHODS

We retrospectively examined 162 patients with confirmed COVID-19 infection by reverse transcriptase-polymerase chain reaction (RT-PCR) test. All cases were evaluated separately by radiologists (visually) and by using three computer software programs: (1) Thoracic VCAR software, GE Healthcare, United States; (2) Myrian, Intrasense, France; (3) InferRead, InferVision Europe, Wiesbaden, Germany. The degree of lesions was visually scored by the radiologist using a score on 5 levels (none, mild, moderate, severe, and critic). The parameters obtained using the computer tools included healthy residual lung parenchyma, ground-glass opacity area, and consolidation volume. Intraclass coefficient (ICC), Spearman correlation analysis, and non-parametric tests were performed.

RESULTS

Thoracic VCAR software was not able to perform volumes segmentation in 26/162 (16.0%) cases, Myrian software in 12/162 (7.4%) patients while InferRead software in 61/162 (37.7%) patients. A great variability (ICC ranged for 0.17 to 0.51) was detected among the quantitative measurements of the residual healthy lung parenchyma volume, GGO, and consolidations volumes calculated by different computer tools. The overall radiological severity score was moderately correlated with the residual healthy lung parenchyma volume obtained by ThoracicVCAR or Myrian software, with the GGO area obtained by the ThoracicVCAR tool and with consolidation volume obtained by Myrian software. Quantified volumes by InferRead software had a low correlation with the overall radiological severity score.

CONCLUSIONS

Computer-aided pneumonia quantification could be an easy and feasible way to stratify COVID-19 cases according to severity; however, a great variability among quantitative measurements provided by computer tools should be considered.

Structured report for chest high-resolution computed tomography in patients with connective tissue disease: Impact on the report quality as perceived by referring clinicians

RATIONALE AND OBJECTIVES

To evaluate the impact on perceived report quality of referring rheumatologists for a chest high-resolution computed tomography (HRCT) structured report (SR) template for patients with connective tissue disease (CTD), compared to the traditional narrative report (NR).

MATERIALS AND METHODS

We retrospectively considered 123 HRCTs in patients with CTD. Three radiologists, blinded to the original NRs they wrote during clinical routine, re-reported each HRCT using an SR dedicated template. We then divided all NR-SR couples into three groups (41 HRCT each). Each group was evaluated by one of three rheumatologists (R1, R2, R3), who expressed their perceived report quality for the respective pools of NRs and SRs in terms of completeness, clarity (both on a 10-points scale), and clinical relevance (on a 5-points scale). The Wilcoxon test and the McNemar test were used for statistical analysis.

RESULTS

For each rheumatologist, SR received higher ratings compared to NR for completeness (median ratings: R1, 10 vs. 7; R2, 10 vs. 8; R3, 10 vs. 6, all p < 0.0001), clarity (median ratings: R1, 10 vs. 7; R2, 10 vs. 8; R3, 10 vs. 7, all p < 0.0001), and clinical relevance (median ratings: R1, 5 vs. 4; R2, 5 vs. 4; R3, 5 vs. 1, all p < 0.0001). After rating dichotomization, the use of SR led to a significant increase (p < 0.01) in completeness, clarity, and clinical relevance as compared to NR, except for clarity as perceived by R2 (p = 1).

CONCLUSION

Referring rheumatologists' perceived report quality for structured reporting of HRCT in patients with CTD was superior to narrative reporting.

Well-aerated Lung on Admitting Chest CT to Predict Adverse Outcome in COVID-19 Pneumonia

Background CT of patients with severe acute respiratory syndrome coronavirus 2 disease depicts the extent of lung involvement in coronavirus disease 2019 (COVID-19) pneumonia. Purpose To determine the value of quantification of the well-aerated lung (WAL) obtained at admission chest CT to determine prognosis in patients with COVID-19 pneumonia. Materials and Methods Imaging of patients admitted at the emergency department between February 17 and March 10, 2020 who underwent chest CT were retrospectively analyzed. Patients with negative results of reverse-transcription polymerase chain reaction for severe acute respiratory syndrome coronavirus 2 at nasal-pharyngeal swabbing, negative chest CT findings, and incomplete clinical data were excluded. CT images were analyzed for quantification of WAL visually (%V-WAL), with open-source software (%S-WAL), and with absolute volume (VOL-WAL). Clinical parameters included patient characteristics, comorbidities, symptom type and duration, oxygen saturation, and laboratory values. Logistic regression was used to evaluate the relationship between clinical parameters and CT metrics versus patient outcome (intensive care unit [ICU] admission or death vs no ICU admission or death). The area under the receiver operating characteristic curve (AUC) was calculated to determine model performance. Results The study included 236 patients (59 of 123 [25%] were female; median age, 68 years). A %V-WAL less than 73% (odds ratio [OR], 5.4; 95% confidence interval [CI]: 2.7, 10.8; P < .001), %S-WAL less than 71% (OR, 3.8; 95% CI: 1.9, 7.5; P < .001), and VOL-WAL less than 2.9 L (OR, 2.6; 95% CI: 1.2, 5.8; P < .01) were predictors of ICU admission or death. In comparison with clinical models containing only clinical parameters (AUC = 0.83), all three quantitative models showed better diagnostic performance (AUC = 0.86 for all models). The models containing %V-WAL less than 73% and VOL-WAL less than 2.9 L were superior in terms of performance as compared with the models containing only clinical parameters (P = .04 for both models). Conclusion In patients with confirmed coronavirus disease 2019 pneumonia, visual or software quantification of the extent of CT lung abnormality were predictors of intensive care unit admission or death. ©  RSNA, 2020 Online supplemental material is available for this article.

Quantification of Lung Fibrosis in IPF-Like Mouse Model and Pharmacological Response to Treatment by Micro-Computed Tomography

Idiopathic pulmonary fibrosis (IPF) is a chronic progressive degenerative lung disease leading to respiratory failure and death. Although anti-fibrotic drugs are now available for treating IPF, their clinical efficacy is limited and lung transplantation remains the only modality to prolong survival of IPF patients. Despite its limitations, the bleomycin (BLM) animal model remains the best characterized experimental tool for studying disease pathogenesis and assessing efficacy of novel potential drugs. In the present study, the effects of oropharyngeal (OA) and intratracheal (IT) administration of BLM were compared in C57BL/6 mice. The development of lung fibrosis was followed in vivo for 28 days after BLM administration by micro-computed tomography and ex vivo by histological analyses (bronchoalveolar lavage, histology in the left lung to stage fibrosis severity and hydroxyproline determination in the right lung). In a separate study, the antifibrotic effect of Nintedanib was investigated after oral administration (60 mg/kg for two weeks) in the OA BLM model. Lung fibrosis severity and duration after BLM OA and IT administration was comparable. However, a more homogeneous distribution of fibrotic lesions among lung lobes was apparent after OA administration. Quantification of fibrosis by micro-CT based on % of poorly aerated tissue revealed that this readout correlated significantly with the standard histological methods in the OA model. These findings were further confirmed in a second study in the OA model, evaluating Nintedanib anti-fibrotic effects. Indeed, compared to the BLM group, Nintedanib inhibited significantly the increase in % of poorly aerated areas (26%) and reduced ex vivo histological lesions and hydroxyproline levels by 49 and 41%, respectively. This study indicated that micro-computed tomography is a valuable in vivo technology for lung fibrosis quantification, which will be very helpful in the future to better evaluate new anti-fibrotic drug candidates.

Multidisciplinary Approach in the Early Detection of Undiagnosed Connective Tissue Diseases in Patients With Interstitial Lung Disease: A Retrospective Cohort Study

Interstitial lung disease (ILD) encompasses a wide range of parenchymal lung pathologies with different clinical, histological, radiological, and serological features. Follow-up, treatment, and prognosis are strongly influenced by the underlying pathogenesis. Considering that an ILD may complicate the course of any connective tissue disease (CTD) and that CTD's signs are not always easily identifiable, it could be useful to screen every ILD patient for a possible CTD. The recent definition of interstitial pneumonia with autoimmune features is a further confirmation of the close relationship between CTD and ILD. In this context, the multidisciplinary approach is assuming a growing and accepted role in the correct diagnosis and follow-up, to as early as possible define the best therapeutic strategy. However, despite clinical advantages, until now, the pathways of the multidisciplinary approach in ILD patients are largely heterogeneous across different centers and the best strategy to apply is still to be established and validated. Aims of this article are to describe the organization of our multidisciplinary group for ILD, which is mainly focused on the early identification and management of CTD in patients with ILD and to show our results in a 1 year period of observation. We found that 15% of patients referred for ILD had an underlying CTD, 33% had interstitial pneumonia with autoimmune feature, and 52% had ILD without detectable CTD. Furthermore, we demonstrated that the adoption of a standardized strategy consisting of a screening questionnaire, specific laboratory tests, and nailfold videocapillaroscopy in all incident ILD proved useful in making the right diagnosis.

Primary pulmonary lymphoma: imaging findings in 30 cases

PURPOSE

To present our experience of cases of primary pulmonary lymphoma (PPL) found between January 2002 and July 2018, focusing on the radiological features and the differential diagnosis in order to contribute to the difficult role of the radiologist in the disease identification and to help the clinicians to reach the diagnosis.

MATERIALS AND METHODS

CT scans of 30 patients (14 men and 16 women, aged 58-86, mean age 72 years) with PPL were retrospectively reviewed. All patients had a histopathological confirmation of the disease: MALT lymphoma (23 patients, 76.6%); diffuse large B-cell lymphoma-DLBCL (seven patients, 23.4%). All the staging CT scans were evaluated by three experienced radiologists dedicated to thoracic disease in order to radiologically define the predominant pattern of presentation.

RESULTS

The following parenchymal patterns were observed: 11 patients with single/multiple nodules, five with masses/mass-like consolidations, 14 with consolidations with air bronchogram, 16 with ground-glass opacity, ten with angiogram sign, 22 with perilymphatic and/or peribronchovascular spread, 15 with associated lymphadenopathies, and 13 with pleural/chest wall involvement. The main characteristics of PPLs were the presence of consolidations and ground-glass opacities, with perilymphatic and/or bronchovascular spread.

CONCLUSION

All the characteristics of the work should alert the radiologist to consider lymphoma among the possible differential diagnoses, always correlating the results of the CT examination with appropriate clinical laboratory evaluations.

Contextual Radiology Reporting: A New Approach to Neuroradiology Structured Templates

Structured reporting has many advantages over conventional narrative reporting and has been advocated for standard usage by radiologic societies and literature. Traditional structured reports though are often not tailored to the appropriate clinical situation, are generic, and can be overly constraining. Contextual reporting is an alternative method of structured reporting that is specifically related to the disease or examination indication. Herein, we create a library of 50 contextual structured reports for neuroradiologists and emphasize their clinical value over noncontextual structured reporting. These templates are located in the On-line Appendix, and a downloadable PowerScribe 360 file may be accessed at https://drive.google.com/open?id=1AlPUmfAXPzjkMFcHf7vGKF4Q-vIdpflT.