Diagnosis of Tuberculosis in a Case of Chronic Urticaria following Omalizumab Therapy.

In Italy, tuberculosis (TB) incidence in the last decade has remained constant at under 10 cases/100,000 inhabitants. In the Philippines, TB annual incidence is greater than 500 cases/100,000 inhabitants. Omalizumab is a humanized anti-IgE monoclonal antibody approved for the treatment of chronic spontaneous urticaria. We report the case of a 32-year-old Filipino woman who suffered from chronic urticaria, treated with topic steroids since June 2022 and systemic steroids for 2 weeks. In November 2022, she started omalizumab therapy at a monthly dose of 300 mg; she was not screened for TB infection. In the same month, a left laterocervical lymphadenopathy arose, which worsened in February 2023 (diameter: 3 cm). The patient recovered in April 2023 in INMI "Lazzaro Spallanzani" in Rome for suspected TB. Chest CT showed a "tree in bud" pattern at the upper-right pulmonary lobe. The patient tested positive for lymph node biopsy molecular tuberculosis. The patient started standard antituberculosis therapy. She discontinued omalizumab. To our knowledge, this is the second diagnosed TB case during omalizumab treatment, which suggests that attention should be paid to the known risk of TB during biotechnological treatments. Even if current guidelines do not recommend screening for TB before starting anti-IgE therapy, further data should be sought to assess the relationship between omalizumab treatment and active TB. Our experience suggests that screening for TB should be carried out in patients from highly tuberculosis-endemic countries before starting omalizumab therapy.

Imaging Severity COVID-19 Assessment in Vaccinated and Unvaccinated Patients: Comparison of the Different Variants in a High Volume Italian Reference Center.

Purpose: To analyze the vaccine effect by comparing five groups: unvaccinated patients with Alpha variant, unvaccinated patients with Delta variant, vaccinated patients with Delta variant, unvaccinated patients with Omicron variant, and vaccinated patients with Omicron variant, assessing the "gravity" of COVID-19 pulmonary involvement, based on CT findings in critically ill patients admitted to Intensive Care Unit (ICU). Methods: Patients were selected by ICU database considering the period from December 2021 to 23 March 2022, according to the following inclusion criteria: patients with proven Omicron variant COVID-19 infection with known COVID-19 vaccination with at least two doses and with chest Computed Tomography (CT) study during ICU hospitalization. Wee also evaluated the ICU database considering the period from March 2020 to December 2021, to select unvaccinated consecutive patients with Alpha variant, subjected to CT study, consecutive unvaccinated and vaccinated patients with Delta variant, subjected to CT study, and, consecutive unvaccinated patients with Omicron variant, subjected to CT study. CT images were evaluated qualitatively using a severity score scale of 5 levels (none involvement, mild: ≤25% of involvement, moderate: 26−50% of involvement, severe: 51−75% of involvement, and critical involvement: 76−100%) and quantitatively, using the Philips IntelliSpace Portal clinical application CT COPD computer tool. For each patient the lung volumetry was performed identifying the percentage value of aerated residual lung volume. Non-parametric tests for continuous and categorical variables were performed to assess statistically significant differences among groups. Results: The patient study group was composed of 13 vaccinated patients affected by the Omicron variant (Omicron V). As control groups we identified: 20 unvaccinated patients with Alpha variant (Alpha NV); 20 unvaccinated patients with Delta variant (Delta NV); 18 vaccinated patients with Delta variant (Delta V); and 20 unvaccinated patients affected by the Omicron variant (Omicron NV). No differences between the groups under examination were found (p value > 0.05 at Chi square test) in terms of risk factors (age, cardiovascular diseases, diabetes, immunosuppression, chronic kidney, cardiac, pulmonary, neurologic, and liver disease, etc.). A different median value of aerated residual lung volume was observed in the Delta variant groups: median value of aerated residual lung volume was 46.70% in unvaccinated patients compared to 67.10% in vaccinated patients. In addition, in patients with Delta variant every other extracted volume by automatic tool showed a statistically significant difference between vaccinated and unvaccinated group. Statistically significant differences were observed for each extracted volume by automatic tool between unvaccinated patients affected by Alpha variant and vaccinated patients affected by Delta variant of COVID-19. Good statistically significant correlations among volumes extracted by automatic tool for each lung lobe and overall radiological severity score were obtained (ICC range 0.71−0.86). GGO was the main sign of COVID-19 lesions on CT images found in 87 of the 91 (95.6%) patients. No statistically significant differences were observed in CT findings (ground glass opacities (GGO), consolidation or crazy paving sign) among patient groups. Conclusion: In our study, we showed that in critically ill patients no difference were observed in terms of severity of disease or exitus, between unvaccinated and vaccinated patients. The only statistically significant differences were observed, with regard to the severity of COVID-19 pulmonary parenchymal involvement, between unvaccinated patients affected by Alpha variant and vaccinated patients affected by Delta variant, and between unvaccinated patients with Delta variant and vaccinated patients with Delta variant.

Incidence of Pneumothorax and Pneumomediastinum in 497 COVID-19 Patients with Moderate-Severe ARDS over a Year of the Pandemic: An Observational Study in an Italian Third Level COVID-19 Hospital.

(1) Background: COVID-19 is a novel cause of acute respiratory distress syndrome (ARDS). Indeed, with the increase of ARDS cases due to the COVID-19 pandemic, there has also been an increase in the incidence of cases with pneumothorax (PNX) and pneumomediastinum (PNM). However, the incidence and the predictors of PNX/PMN in these patients are currently unclear and even conflicting. (2) Methods: The present observational study analyzed the incidence of barotrauma (PNX/PNM) in COVID-19 patients with moderate-severe ARDS hospitalized in a year of the pandemic, also focusing on the three waves occurring during the year, and treated with positive-pressure ventilation (PPV). We collected demographic and clinical data. (3) Results: During this period, 40 patients developed PNX/PNM. The overall incidence of barotrauma in all COVID-19 patients hospitalized in a year was 1.6%, and in those with moderate-severe ARDS in PPV was 7.2% and 3.8 events per 1000 positive-pressure ventilator days. The incidence of barotrauma in moderate-severe ARDS COVID-19 patients during the three waves was 7.8%, 7.4%, and 8.7%, respectively. Treatment with noninvasive respiratory support alone was associated with an incidence of barotrauma of 9.1% and 2.6 events per 1000 noninvasive ventilator days, of which 95% were admitted to the ICU after the event, due to a worsening of respiratory parameters. The incidence of barotrauma of ICU COVID-19 patients in invasive ventilation over a year was 5.8% and 2.7 events per 1000 invasive ventilator days. There was no significant difference in demographics and clinical features between the barotrauma and non-barotrauma group. The mortality was higher in the barotrauma group (17 patients died, 47.2%) than in the non-barotrauma group (170 patients died, 37%), although this difference was not statistically significant (p = 0.429). (4) Conclusions: The incidence of PNX/PNM in moderate-severe ARDS COVID-19 patients did not differ significantly between the three waves over a year, and does not appear to be very different from that in ARDS patients in the pre-COVID era. The barotrauma does not appear to significantly increase mortality in COVID-19 patients with moderate-severe ARDS if protective ventilation strategies are applied. Attention should be paid to the risk of barotrauma in COVID-19 patients in noninvasive ventilation because the event increases the probability of admission to the intensive care unit (ICU) and intubation.

Quantitative Analysis of Residual COVID-19 Lung CT Features: Consistency among Two Commercial Software.

OBJECTIVE: To investigate two commercial software and their efficacy in the assessment of chest CT sequelae in patients affected by COVID-19 pneumonia, comparing the consistency of tools. MATERIALS AND METHODS: Included in the study group were 120 COVID-19 patients (56 women and 104 men; 61 years of median age; range: 21-93 years) who underwent chest CT examinations at discharge between 5 March 2020 and 15 March 2021 and again at a follow-up time (3 months; range 30-237 days). A qualitative assessment by expert radiologists in the infectious disease field (experience of at least 5 years) was performed, and a quantitative evaluation using thoracic VCAR software (GE Healthcare, Chicago, Illinois, United States) and a pneumonia module of ANKE ASG-340 CT workstation (HTS Med & Anke, Naples, Italy) was performed. The qualitative evaluation included the presence of ground glass opacities (GGOs) consolidation, interlobular septal thickening, fibrotic-like changes (reticular pattern and/or honeycombing), bronchiectasis, air bronchogram, bronchial wall thickening, pulmonary nodules surrounded by GGOs, pleural and pericardial effusion, lymphadenopathy, and emphysema. A quantitative evaluation included the measurements of GGOs, consolidations, emphysema, residual healthy parenchyma, and total lung volumes for the right and left lung. A chi-square test and non-parametric test were utilized to verify the differences between groups. Correlation coefficients were used to analyze the correlation and variability among quantitative measurements by different computer tools. A receiver operating characteristic (ROC) analysis was performed. RESULTS: The correlation coefficients showed great variability among the quantitative measurements by different tools when calculated on baseline CT scans and considering all patients. Instead, a good correlation (≥0.6) was obtained for the quantitative GGO, as well as the consolidation volumes obtained by two tools when calculated on baseline CT scans, considering the control group. An excellent correlation (≥0.75) was obtained for the quantitative residual healthy lung parenchyma volume, GGO, consolidation volumes obtained by two tools when calculated on follow-up CT scans, and for residual healthy lung parenchyma and GGO quantification when the percentage change of these volumes were calculated between a baseline and follow-up scan. The highest value of accuracy to identify patients with RT-PCR positive compared to the control group was obtained by a GGO total volume quantification by thoracic VCAR (accuracy = 0.75). CONCLUSIONS: Computer aided quantification could be an easy and feasible way to assess chest CT sequelae due to COVID-19 pneumonia; however, a great variability among measurements provided by different tools should be considered.

Management of Spontaneous Bleeding in COVID-19 Inpatients: Is Embolization Always Needed?

BACKGROUND: critically ill patients with SARS-CoV-2 infection present a hypercoagulable condition. Anticoagulant therapy is currently recommended to reduce thrombotic risk, leading to potentially severe complications like spontaneous bleeding (SB). Percutaneous transcatheter arterial embolization (PTAE) can be life-saving in critical patients, in addition to medical therapy. We report a major COVID-19 Italian Research Hospital experience during the pandemic, with particular focus on indications and technique of embolization. METHODS: We retrospectively included all subjects with SB and with a microbiologically confirmed SARS-CoV-2 infection, over one year of pandemic, selecting two different groups: (a) patients treated with PTAE and medical therapy; (b) patients treated only with medical therapy. Computed tomography (CT) scan findings, clinical conditions, and biological findings were collected. RESULTS: 21/1075 patients presented soft tissue SB with an incidence of 1.95%. 10/21 patients were treated with PTAE and medical therapy with a 30-days survival of 70%. Arterial blush, contrast late enhancement, and dimensions at CT scan were found discriminating for the embolization (p < 0.05). CONCLUSIONS: PTAE is an important tool in severely ill, bleeding COVID-19 patients. The decision for PTAE of COVID-19 patients must be carefully weighted with particular attention paid to the clinical and biological condition, hematoma location and volume.

An explainable AI system for automated COVID-19 assessment and lesion categorization from CT-scans.

COVID-19 infection caused by SARS-CoV-2 pathogen has been a catastrophic pandemic outbreak all over the world, with exponential increasing of confirmed cases and, unfortunately, deaths. In this work we propose an AI-powered pipeline, based on the deep-learning paradigm, for automated COVID-19 detection and lesion categorization from CT scans. We first propose a new segmentation module aimed at automatically identifying lung parenchyma and lobes. Next, we combine the segmentation network with classification networks for COVID-19 identification and lesion categorization. We compare the model's classification results with those obtained by three expert radiologists on a dataset of 166 CT scans. Results showed a sensitivity of 90.3% and a specificity of 93.5% for COVID-19 detection, at least on par with those yielded by the expert radiologists, and an average lesion categorization accuracy of about 84%. Moreover, a significant role is played by prior lung and lobe segmentation, that allowed us to enhance classification performance by over 6 percent points. The interpretation of the trained AI models reveals that the most significant areas for supporting the decision on COVID-19 identification are consistent with the lesions clinically associated to the virus, i.e., crazy paving, consolidation and ground glass. This means that the artificial models are able to discriminate a positive patient from a negative one (both controls and patients with interstitial pneumonia tested negative to COVID) by evaluating the presence of those lesions into CT scans. Finally, the AI models are integrated into a user-friendly GUI to support AI explainability for radiologists, which is publicly available at http://perceivelab.com/covid-ai. The whole AI system is unique since, to the best of our knowledge, it is the first AI-based software, publicly available, that attempts to explain to radiologists what information is used by AI methods for making decisions and that proactively involves them in the decision loop to further improve the COVID-19 understanding.

Risk and predictive factors of prolonged viral RNA shedding in upper respiratory specimens in a large cohort of COVID-19 patients admitted to an Italian reference hospital.

BACKGROUND: Limited data are available about the predictors and outcomes associated with prolonged SARS-CoV-2 RNA shedding (VS). METHODS: A retrospective study including COVID-19 patients admitted to an Italian hospital between March 1 and July 1, 2020. Predictors of viral clearance (VC) and prolonged VS from the upper respiratory tract were assessed by Poisson regression and logistic regression analyses. The causal relation between VS and clinical outcomes was evaluated through an inverse probability weighted Cox model. RESULTS: The study included 536 subjects. The median duration of VS from symptoms onset was 18 days. The estimated 30-day probability of VC was 70.2%. Patients with comorbidities, lymphopenia at hospital admission, or moderate/severe respiratory disease had a lower chance of VC. The development of moderate/severe respiratory failure, delayed hospital admission after symptoms onset, baseline comorbidities, or D-dimer >1000ng/mL at admission independently predicted prolonged VS. The achievement of VC doubled the chance of clinical recovery and reduced the probability of death/mechanical ventilation. CONCLUSIONS: Respiratory disease severity, comorbidities, delayed hospital admission and inflammatory markers negatively predicted VC, which resulted to be associated with better clinical outcomes. These findings highlight the importance of prompt hospitalization of symptomatic patients, especially where signs of severity or comorbidities are present.

Development of a clinical decision support system for severity risk prediction and triage of COVID-19 patients at hospital admission: an international multicentre study.

BACKGROUND: The outbreak of coronavirus disease 2019 (COVID-19) has globally strained medical resources and caused significant mortality. OBJECTIVE: To develop and validate a machine-learning model based on clinical features for severity risk assessment and triage for COVID-19 patients at hospital admission. METHOD: 725 patients were used to train and validate the model. This included a retrospective cohort from Wuhan, China of 299 hospitalised COVID-19 patients from 23 December 2019 to 13 February 2020, and five cohorts with 426 patients from eight centres in China, Italy and Belgium from 20 February 2020 to 21 March 2020. The main outcome was the onset of severe or critical illness during hospitalisation. Model performances were quantified using the area under the receiver operating characteristic curve (AUC) and metrics derived from the confusion matrix. RESULTS: In the retrospective cohort, the median age was 50 years and 137 (45.8%) were male. In the five test cohorts, the median age was 62 years and 236 (55.4%) were male. The model was prospectively validated on five cohorts yielding AUCs ranging from 0.84 to 0.93, with accuracies ranging from 74.4% to 87.5%, sensitivities ranging from 75.0% to 96.9%, and specificities ranging from 55.0% to 88.0%, most of which performed better than the pneumonia severity index. The cut-off values of the low-, medium- and high-risk probabilities were 0.21 and 0.80. The online calculators can be found at www.covid19risk.ai. CONCLUSION: The machine-learning model, nomogram and online calculator might be useful to access the onset of severe and critical illness among COVID-19 patients and triage at hospital admission.

Patient Access to an Online Portal for Outpatient Radiological Images and Reports: Two Years' Experience.

To assess the incidence of outpatient examinations delivered through a web portal in the Latium Region in 2 years and compare socio-demographic characteristics of these users compared to the total of examinations performed. All radiological exams (including MRI, X-ray and CT) performed from March 2017 to February 2019 were retrospectively analysed. For each exam, anonymized data of users who attended the exam were extracted and their characteristics were compared according to digital access to the reports. Overall, 9068 exams were performed in 6720 patients (55.8% males, median age 58 years, interquartile range (IQR) 46-70) of which 90.2% residents in Rome province, mainly attending a single radiological examination (77.3%). Among all exams, 446 (4.9%) were accessed, of which 190 (4.4%) in the first and 5.4% in the second year (p < 0.041). MRI was the type of exams mostly accessed (175, 7.0%). Being resident in the provinces of the Latium Region other than Rome was associated with a higher access rate (OR = 1.84, p = 0.001). Considering the overall costs sustained to implement a web portal which allows users a personal access to their own reports, if all users would have accessed/downloaded their exams, an overall users' and hospital savings up to €255,808.28 could have been determined. The use of a web portal could represent a consistent economical advantage for the user, the hospital and the environment. Even if increasing over time, the use of web portal is still limited and strategies to increase the use of such systems should be implemented.

2019-novel Coronavirus severe adult respiratory distress syndrome in two cases in Italy: An uncommon radiological presentation.

INTRODUCTION: Several recent case reports have described common early chest imaging findings of lung pathology caused by 2019 novel Coronavirus (SARS-COV2) which appear to be similar to those seen previously in SARS-CoV and MERS-CoV infected patients. OBJECTIVE: We present some remarkable imaging findings of the first two patients identified in Italy with COVID-19 infection travelling from Wuhan, China. The follow-up with chest X-Rays and CT scans was also included, showing a progressive adult respiratory distress syndrome (ARDS). RESULTS: Moderate to severe progression of the lung infiltrates, with increasing percentage of high-density infiltrates sustained by a bilateral and multi-segmental extension of lung opacities, were seen. During the follow-up, apart from pleural effusions, a tubular and enlarged appearance of pulmonary vessels with a sudden caliber reduction was seen, mainly found in the dichotomic tracts, where the center of a new insurgent pulmonary lesion was seen. It could be an early alert radiological sign to predict initial lung deterioration. Another uncommon element was the presence of mediastinal lymphadenopathy with short-axis oval nodes. CONCLUSIONS: Although only two patients have been studied, these findings are consistent with the radiological pattern described in literature. Finally, the pulmonary vessels enlargement in areas where new lung infiltrates develop in the follow-up CT scan, could describe an early predictor radiological sign of lung impairment.

Pulmonary measles disease: old and new imaging tools.

BACKGROUND: Measles virus can cause lower respiratory tract infection, so that chest radiography is necessary to investigate lung involvement in patients with respiratory distress. PURPOSE: To assess measles pneumonia imaging during the measles outbreak occurred in 2016-2017 in Italy. MATERIAL AND METHODS: We retrospectively observed adult patients with a serological diagnosis of measles, who underwent chest-X rays for suspected pneumonia. If a normal radiography resulted, the patient underwent unenhanced CT. A CT post processing software package was used for an additional quantitative lung and airway involvement analysis . RESULTS: Among 290 patients affected by measles, 150 underwent chest-X ray. Traditional imaging allowed the pneumonia diagnosis in 114 patients (76%). The most frequent abnormality at chest X-rays was bronchial wall thickening, observed in 88.5% of the cases; radiological findings are faint in the 25% of the cases (29/114 patients). In nine subjects with a normal chest X-ray, unenhanced CT with a quantitative analysis was performed, and depicted features consistent with constrictive bronchiolitis. CONCLUSION: Measles may produce bronchiolitis and pneumonia. In the cases in which involvement of pulmonary parenchyma is not sufficient to result in radiological abnormalities, CT used with a dedicated postprocessing software package, provides an accurate lungs and airways analysis, also determining the percentage of lung involvement.

CT texture analysis in colorectal liver metastases: A better way than size and volume measurements to assess response to chemotherapy?

BACKGROUND: Response Evaluation Criteria In Solid Tumors (RECIST) are known to have limitations in assessing the response of colorectal liver metastases (CRLMs) to chemotherapy. OBJECTIVE: The objective of this article is to compare CT texture analysis to RECIST-based size measurements and tumor volumetry for response assessment of CRLMs to chemotherapy. METHODS: Twenty-one patients with CRLMs underwent CT pre- and post-chemotherapy. Texture parameters mean intensity (M), entropy (E) and uniformity (U) were assessed for the largest metastatic lesion using different filter values (0.0 = no/0.5 = fine/1.5 = medium/2.5 = coarse filtration). Total volume (cm(3)) of all metastatic lesions and the largest size of one to two lesions (according to RECIST 1.1) were determined. Potential predictive parameters to differentiate good responders (n = 9; histological TRG 1-2) from poor responders (n = 12; TRG 3-5) were identified by univariable logistic regression analysis and subsequently tested in multivariable logistic regression analysis. Diagnostic odds ratios were recorded. RESULTS: The best predictive texture parameters were Δuniformity and Δentropy (without filtration). Odds ratios for Δuniformity and Δentropy in the multivariable analyses were 0.95 and 1.34, respectively. Pre- and post-treatment texture parameters, as well as the various size and volume measures, were not significant predictors. Odds ratios for Δsize and Δvolume in the univariable logistic regression were 1.08 and 1.05, respectively. CONCLUSIONS: Relative differences in CT texture occurring after treatment hold promise to assess the pathologic response to chemotherapy in patients with CRLMs and may be better predictors of response than changes in lesion size or volume.

Extraosseus Ewing sarcoma: An uncommon periclavicular location.

A rapidly enlarging right sternoclavicular mass in a young male was labeled as a nonspecific mass. MRI played a crucial role in characterizing the lesion, helping to define the possible mesenchymal origin and the relative involvement of the surrounding structures. We also discuss the differential diagnosis of an extraosseus Ewing sarcoma (ES), with its imaging findings.