Relationship Between Lung Volumes and Heterogeneity in the Response to Elexacaftor/Tezacaftor/Ivacaftor in Patients With Cystic Fibrosis and Advanced Lung Disease.

BACKGROUND: The effects of elexacaftor/tezacaftor/ivacaftor (ETI) on respiratory outcomes for people with cystic fibrosis (CF) were demonstrated by several clinical trials, mainly based on simple spirometry. However, gains in lung function may vary greatly between patients, and predictors of FEV1 change after treatment are still missing. RESEARCH QUESTION: Which ventilatory parameters are involved in the heterogeneity of FEV1 change after 12-month ETI treatment in people with CF with advanced lung disease? STUDY DESIGN AND METHODS: This was a multicenter, observational, prospective cohort study at two major CF centers in Italy. We enrolled 47 adults with CF and advanced lung disease (FEV1 < 40% or actively listed for lung transplant) who started ETI treatment between December 2019 and December 2021. At treatment initiation and after 12 months, patients underwent body plethysmography. Values were compared at the two time points. To assess the relationship between baseline plethysmography measurements and treatment-induced changes in FEV1, we used the Spearman rank correlation coefficient (r) and median quantile regressions. RESULTS: After 12 months of ETI treatment, there was a significant increase in FEV1 % predicted from a median value of 36.0 (25th-75th percentile, 33-39) to 52 (25th-75th percentile, 43-61) (P < .001). Inspiratory capacity/total lung capacity (TLC) ratio also increased from 32.0 (25th-75th percentile, 28.6-36.9) to 36.3 (25th-75th percentile, 33.4-41.3) (P < .001). Specific airway resistance decreased from 263 (25th-75th percentile, 182-405) to 207 (25th-75th percentile, 120-258) (P < .001). Functional residual capacity/TLC ratio decreased from 68.2 (25th-75th percentile, 63.3-71.9) to 63.9 (25th-75th percentile, 58.8-67.1) (P < .001), and residual volume (RV)/TLC ratio decreased from 53.1 (25th-75th percentile, 48.3-59.4) to 45.6 (25th-75th percentile, 39.4-49.8) (P < .001). Changes in FEV1 % predicted negatively correlated with baseline functional residual capacity/TLC ratio (r = -0.38, P = .009) and RV/TLC ratio (r= -0.42, P = .004). After adjustment for age at treatment initiation and cystic fibrosis transmembrane conductance regulator genotype, we estimated that for each 10-unit increase in baseline RV/TLC ratio, the expected median change in FEV1 decreased by 2.3 (95% CI, -5.8 to -0.8). INTERPRETATION: ETI was associated with improvements in both static and dynamic volumes in people with CF and advanced lung disease. Heterogeneity in FEV1 % predicted change after 12 months of treatment may be predicted by the severity of hyperinflation at baseline.

Prediction of Ablation Volume in Percutaneous Lung Microwave Ablation: A Single Centre Retrospective Study.

BACKGROUND: Percutaneous Microwave Ablation (MWA) of lung malignancies is a procedure with many technical challenges, among them the risk of residual disease. Recently, dedicated software able to predict the volume of the ablated area was introduced. Cone-beam computed tomography (CBCT) is the imaging guidance of choice for pulmonary ablation in our institution. The volumetric prediction software (VPS) has been installed and used in combination with CBCT to check the correct position of the device. Our study aimed to compare the results of MWA of pulmonary tumours performed using CBCT with and without VPS. METHODS: We retrospectively reviewed 1-month follow-up enhanced contrast-enhanced computed tomography (CECT) scans of 10 patients who underwent ablation with the assistance of VPS (group 1) and of 10 patients who were treated without the assistance of VPS (group 2). All patients were treated for curative purposes, the maximum axial diameter of lesions ranged between 5 and 22 mm in group 1 and between 5 and 25 mm in group 2. We compared the presence of residual disease between the two groups. RESULTS: In group 1 residual disease was seen in only 1 patient (10%) in which VPS had ensured complete coverage of the tumour. In group 2 residual disease was found in 3 patients (30%). CONCLUSIONS: Using this software during MWA of lung malignancies could improve the efficacy of the treatment compared to the conventional only CBCT guidance.

CT after Lung Microwave Ablation: Normal Findings and Evolution Patterns of Treated Lesions.

Imaging-guided percutaneous ablative treatments, such as radiofrequency ablation (RFA), cryoablation and microwave ablation (MWA), have been developed for the treatment of unresectable primary and secondary lung tumors in patients with advanced-stage disease or comorbidities contraindicating surgery. Among these therapies, MWA has recently shown promising results in the treatment of pulmonary neoplasms. The potential advantages of MWA over RFA include faster ablation times, higher intra-tumoral temperatures, larger ablation zones and lower susceptibility to the heat sink effect, resulting in greater efficacy in proximity to vascular structures. Despite encouraging results supporting its efficacy, there is a relative paucity of data in the literature regarding the role of computer tomography (CT) to monitor MWA-treated lesions, and the CT appearance of their morphologic evolution and complications. For both interventional and non-interventional radiologists, it is crucial to be familiar with the CT features of such treated lesions in order to detect incomplete therapy or recurrent disease at early stage, as well as to recognize initial signs of complications. The aim of this pictorial essay is to describe the typical CT features during follow-up of lung lesions treated with percutaneous MWA and how to interpret and differentiate them from other radiological findings, such as recurrence and complications, that are commonly encountered in this setting.

Detection and Classification of Bronchiectasis Through Convolutional Neural Networks.

PURPOSE: Bronchiectasis is a chronic disease characterized by an irreversible dilatation of bronchi leading to chronic infection, airway inflammation, and progressive lung damage. Three specific patterns of bronchiectasis are distinguished in clinical practice: cylindrical, varicose, and cystic. The predominance and the extension of the type of bronchiectasis provide important clinical information. However, characterization is often challenging and is subject to high interobserver variability. The aim of this study is to provide an automatic tool for the detection and classification of bronchiectasis through convolutional neural networks. MATERIALS AND METHODS: Two distinct approaches were adopted: (i) direct network performing a multilabel classification of 32×32 regions of interest (ROIs) into 4 classes: healthy, cylindrical, cystic, and varicose and (ii) a 2-network serial approach, where the first network performed a binary classification between normal tissue and bronchiectasis and the second one classified the ROIs containing abnormal bronchi into one of the 3 bronchiectasis typologies. Performances of the networks were compared with other architectures presented in the literature. RESULTS: Computed tomography from healthy individuals (n=9, age=47±6, FEV1%pred=109±17, FVC%pred=116±17) and bronchiectasis patients (n=21, age=59±15, FEV1%pred=74±25, FVC%pred=91±22) were collected. A total of 19,059 manually selected ROIs were used for training and testing. The serial approach provided the best results with an accuracy and F1 score average of 0.84, respectively. Slightly lower performances were observed for the direct network (accuracy=0.81 and F1 score average=0.82). On the test set, cylindrical bronchiectasis was the subtype classified with highest accuracy, while most of the misclassifications were related to the varicose pattern, mainly to the cylindrical class. CONCLUSION: The developed networks accurately detect and classify bronchiectasis disease, allowing to collect quantitative information regarding the radiologic severity and the topographical distribution of bronchiectasis subtype.

Interobserver variability in the evaluation of primary graft dysfunction after lung transplantation: impact of radiological training and analysis of discordant cases.

PURPOSE: Radiologic criteria for the diagnosis of primary graft dysfunction (PGD) after lung transplantation are nonspecific and can lead to misinterpretation. The primary aim of our study was to assess the interobserver agreement in the evaluation of chest X-rays (CXRs) for PGD diagnosis and to establish whether a specific training could have an impact on concordance rates. Secondary aim was to analyze causes of interobserver discordances. MATERIAL AND METHODS: We retrospectively enrolled 164 patients who received bilateral lung transplantation at our institution, between February 2013 and December 2019. Three radiologists independently reviewed postoperative CXRs and classified them as suggestive or not for PGD. Two of the Raters performed a specific training before the beginning of the study. A senior thoracic radiologist subsequently analyzed all discordant cases among the Raters with the best agreement. Statistical analysis to calculate interobserver variability was percent agreement, Cohen's kappa and intraclass correlation coefficient. RESULTS: A total of 473 CXRs were evaluated. A very high concordance among the two trained Raters, 1 and 2, was found (K = 0.90, ICC = 0.90), while a poorer agreement was found in the other two pairings (Raters 1 and 3: K = 0.34, ICC = 0.40; Raters 2 and 3: K = 0.35, ICC = 0.40). The main cause of disagreement (52.4% of discordant cases) between Raters 1 and 2 was the overestimation of peribronchial thickening in the absence of unequivocal bilateral lung opacities or the incorrect assessment of unilateral alterations. CONCLUSION: To properly identify PGD, it is recommended for radiologists to receive an adequate specific training.

A rare case of paradoxical pulmonary embolism in spontaneous aortocaval fistula.

Aortocaval fistula (ACF) is a rare complication of abdominal aortic aneurysm (AAA), occurring in less than 1% of all AAAs. Paradoxical embolism can rarely be associated with ACF, pulmonary embolism may originate from dislodgment of thrombotic material from the AAA in the inferior vena cava (IVC) through the ACF. We report a case of a patient admitted to the emergency department with abdominal pain and shortness of breath who immediately underwent thoraco-abdominal CT. Imaging allowed a prompt pre-operative diagnosis of an ACF between an AAA and the IVC, also identifying CT signs of right heart overload and the presence of a paradoxical pulmonary embolism.

Chest X-ray findings in a large cohort of 1117 patients with SARS-CoV-2 infection: a multicenter study during COVID-19 outbreak in Italy.

To describe radiographic key patterns on Chest X-ray (CXR) in patients with SARS-CoV-2 infection, assessing the prevalence of radiographic signs of interstitial pneumonia. To evaluate pattern variation between a baseline and a follow-up CXR. 1117 patients tested positive for SARS-CoV-2 infection were retrospectively enrolled from four centers in Lombardy region. All patients underwent a CXR at presentation. Follow-up CXR was performed when clinically indicated. Two radiologists in each center reviewed images and classified them as suggestive or not for interstitial pneumonia, recording the presence of ground-glass opacity (GGO), reticular pattern or consolidation and their distribution. Pearson's χ2 test for categorical variables and McNemar test (χ2 for paired data) were performed. Patients mean age 63.3 years, 767 were males (65.5%). The main result is the large proportion of positive CXR in COVID-19 patients. Baseline CXR was positive in 940 patients (80.3%), with significant differences in age and sex distribution between patients with positive and negative CXR. 382 patients underwent a follow-up CXR. The most frequent pattern on baseline CXR was the GGO (66.1%), on follow-up was consolidation (53.4%). The most common distributions were peripheral and middle-lower lung zone. We described key-patterns and their distribution on CXR in a large cohort of COVID-19 patients: GGO was the most frequent finding on baseline CXR, while we found an increase in the proportion of lung consolidation on follow-up CXR. CXR proved to be a reliable tool in our cohort obtaining positive results in 80.3% of the baseline cases.

Early detection of deep vein thrombosis in patients with coronavirus disease 2019: who to screen and who not to with Doppler ultrasound?

PURPOSE: Aim of the study is to evaluate the incidence of DVT in COVID-19 patients and its correlation with the severity of the disease and with clinical and laboratory findings. METHODS: 234 symptomatic patients with COVID-19, diagnosed according to the World Health Organization guidelines, were included in the study. The severity of the disease was classified as moderate, severe and critical. Doppler ultrasound (DUS) was performed in all patients. DUS findings, clinical, laboratory's and therapeutic variables were investigated by contingency tables, Pearson chi square test and by Student t test and Fisher's exact test. ROC curve analysis was applied to study significant continuous variables. RESULTS: Overall incidence of DVT was 10.7% (25/234): 1.6% (1/60) among moderate cases, 13.8% (24/174) in severely and critically ill patients. Prolonged bedrest and intensive care unit admission were significantly associated with the presence of DVT (19.7%). Fraction of inspired oxygen, P/F ratio, respiratory rate, heparin administration, D-dimer, IL-6, ferritin and CRP showed correlation with DVT. CONCLUSION: DUS may be considered a useful and valid tool for early identification of DVT. In less severely affected patients, DUS as screening of DVT might be unnecessary. High rate of DVT found in severe patients and its correlation with respiratory parameters and some significant laboratory findings suggests that these can be used as a screening tool for patients who should be getting DUS.

Determination of disease severity in COVID-19 patients using deep learning in chest X-ray images.

PURPOSE: Chest X-ray plays a key role in diagnosis and management of COVID-19 patients and imaging features associated with clinical elements may assist with the development or validation of automated image analysis tools. We aimed to identify associations between clinical and radiographic features as well as to assess the feasibility of deep learning applied to chest X-rays in the setting of an acute COVID-19 outbreak. METHODS: A retrospective study of X-rays, clinical, and laboratory data was performed from 48 SARS-CoV-2 RT-PCR positive patients (age 60±17 years, 15 women) between February 22 and March 6, 2020 from a tertiary care hospital in Milan, Italy. Sixty-five chest X-rays were reviewed by two radiologists for alveolar and interstitial opacities and classified by severity on a scale from 0 to 3. Clinical factors (age, symptoms, comorbidities) were investigated for association with opacity severity and also with placement of central line or endotracheal tube. Deep learning models were then trained for two tasks: lung segmentation and opacity detection. Imaging characteristics were compared to clinical datapoints using the unpaired student's t-test or Mann-Whitney U test. Cohen's kappa analysis was used to evaluate the concordance of deep learning to conventional radiologist interpretation. RESULTS: Fifty-six percent of patients presented with alveolar opacities, 73% had interstitial opacities, and 23% had normal X-rays. The presence of alveolar or interstitial opacities was statistically correlated with age (P = 0.008) and comorbidities (P = 0.005). The extent of alveolar or interstitial opacities on baseline X-ray was significantly associated with the presence of endotracheal tube (P = 0.0008 and P = 0.049) or central line (P = 0.003 and P = 0.007). In comparison to human interpretation, the deep learning model achieved a kappa concordance of 0.51 for alveolar opacities and 0.71 for interstitial opacities. CONCLUSION: Chest X-ray analysis in an acute COVID-19 outbreak showed that the severity of opacities was associated with advanced age, comorbidities, as well as acuity of care. Artificial intelligence tools based upon deep learning of COVID-19 chest X-rays are feasible in the acute outbreak setting.

Preparation of a radiology department in an Italian hospital dedicated to COVID-19 patients.

Preparedness for the ongoing coronavirus disease 2019 (COVID-19) and its spread in Italy called for setting up of adequately equipped and dedicated health facilities to manage sick patients while protecting healthcare workers, uninfected patients, and the community. In our country, in a short time span, the demand for critical care beds exceeded supply. A new sequestered hospital completely dedicated to intensive care (IC) for isolated COVID-19 patients needed to be designed, constructed, and deployed. Along with this new initiative, the new concept of "Pandemic Radiology Unit" was implemented as a practical solution to the emerging crisis, born out of a critical and urgent acute need. The present article describes logistics, planning, and practical design issues for such a pandemic radiology and critical care unit (e.g., space, infection control, safety of healthcare workers, etc.) adopted in the IC Hospital Unit for the care and management of COVID-19 patients.

Treatment of epistaxis in hereditary hemorrhagic telangiectasia patients by argon plasma coagulation with local anesthesia.

BACKGROUND: Recurrent epistaxis is the most common manifestation of hereditary hemorrhagic telangiectasia (HHT). The aim of this study was to determine the role and efficacy of argon plasma coagulation (APC) in the management of epistaxis caused by HHT. METHODS: From 1997 to 2004, 43 patients with diagnosed HHT were treated for recurrent epistaxis with APC in our department. RESULTS: Thirty-six patients reported substantial reduction of bleeding after treatment. Of the 18 patients who previously needed blood transfusions, 13 reported substantial reduction of bleeding after treatment and no blood transfusions were necessary. CONCLUSION: APC allows a control of epistaxis in HHT patients and guarantees a long time free from blood transfusions. This treatment modality can be performed with local anesthesia, is not invasive, is well tolerated, is inexpensive, and can be used as a first step even in patients who need to undergo several blood transfusions for their epistaxis.

Pulmonary hypertension: role of computed tomography and magnetic resonance imaging.

Multidetector computed tomography (MDCT) and magnetic resonance imaging (MRI) have a leading role in the diagnosis and evaluation of pulmonary arterial hypertension. Technical aspects, advantages, limitations and potential contraindications will be considered. MDCT has many advantages: 1) fast examination, 2) good identification of central and peripheral vessels, 3) good characterization of parenchymal findings, and 4) good evaluation of the heart and mediastinal structures. Limitations are: 1) the use of iodinated contrast material, and 2) radiation exposure. MRI allows: 1) cardiac morphological and functional studies, and 2) identification of central pulmonary arteries. Limitations are: 1) long scanning time, 2) poor definition of peripheral arteries, and 3) impossibility of pulmonary evaluation. MDCT and MRI findings allow: 1) quick diagnosis of pulmonary arterial hypertension, 2) differential diagnosis between primary and secondary forms, 3) evaluation of cardiac manifestations, and 4) morphological and functional follow-up studies in surgically treated and untreated patients.