Detection and severity quantification of pulmonary embolism with 3D CT data using an automated deep learning-based artificial solution.

PURPOSE: The purpose of this study was to propose a deep learning-based approach to detect pulmonary embolism and quantify its severity using the Qanadli score and the right-to-left ventricle diameter (RV/LV) ratio on three-dimensional (3D) computed tomography pulmonary angiography (CTPA) examinations with limited annotations. MATERIALS AND METHODS: Using a database of 3D CTPA examinations of 1268 patients with image-level annotations, and two other public datasets of CTPA examinations from 91 (CAD-PE) and 35 (FUME-PE) patients with pixel-level annotations, a pipeline consisting of: (i), detecting blood clots; (ii), performing PE-positive versus negative classification; (iii), estimating the Qanadli score; and (iv), predicting RV/LV diameter ratio was followed. The method was evaluated on a test set including 378 patients. The performance of PE classification and severity quantification was quantitatively assessed using an area under the curve (AUC) analysis for PE classification and a coefficient of determination (R²) for the Qanadli score and the RV/LV diameter ratio. RESULTS: Quantitative evaluation led to an overall AUC of 0.870 (95% confidence interval [CI]: 0.850-0.900) for PE classification task on the training set and an AUC of 0.852 (95% CI: 0.810-0.890) on the test set. Regression analysis yielded R² value of 0.717 (95% CI: 0.668-0.760) and of 0.723 (95% CI: 0.668-0.766) for the Qanadli score and the RV/LV diameter ratio estimation, respectively on the test set. CONCLUSION: This study shows the feasibility of utilizing AI-based assistance tools in detecting blood clots and estimating PE severity scores with 3D CTPA examinations. This is achieved by leveraging blood clots and cardiac segmentations. Further studies are needed to assess the effectiveness of these tools in clinical practice.

Cardiac Magnetic Resonance Identifies Responders to Cardiac Resynchronization Therapy with an Assessment of Septal Scar and Left Ventricular Dyssynchrony.

Background: The response to cardiac resynchronization therapy (CRT) depends on septal viability and correction of abnormal septal motion. This study investigates if cardiac magnetic resonance (CMR) as a single modality can identify CRT responders with combined imaging of pathological septal motion (septal flash) and septal scar. Methods: In a prospective, multicenter, observational study of 136 CRT recipients, septal scar was assessed using late gadolinium enhancement (LGE) (n = 127) and septal flash visually from cine CMR sequences. The primary endpoint was CRT response, defined as ≥15% reduction in LV end-systolic volume with echocardiography after 6 months. The secondary endpoint was heart transplantation or death of any cause assessed after 39 ± 13 months. Results: Septal scar and septal flash were independent predictors of CRT response in multivariable analysis (both p < 0.001), while QRS duration and morphology were not. The combined approach of septal scar and septal flash predicted CRT response with an area under the curve of 0.86 (95% confidence interval (CI): 0.78-0.94) and was a strong predictor of long-term survival without heart transplantation (hazard ratio 0.27, 95% CI: 0.10-0.79). The accuracy of the approach was similar in the subgroup with intermediate (130-150 ms) QRS duration. The combined approach was superior to septal scar and septal flash alone (p < 0.01). Conclusions: The combined assessment of septal scar and septal flash using CMR as a single-image modality identifies CRT responders with high accuracy and predicts long-term survival.

ONCOS-102 plus pemetrexed and platinum chemotherapy in malignant pleural mesothelioma: a randomized phase 2 study investigating clinical outcomes and the tumor microenvironment.

BACKGROUND: ONCOS-102, an oncolytic adenovirus expressing granulocyte-macrophage colony-stimulating factor, can alter the tumor microenvironment to an immunostimulatory state. Combining ONCOS-102 with standard-of-care chemotherapy for malignant pleural mesothelioma (MPM) may improve treatment outcomes. METHODS: In this open-label, randomized study, patients with unresectable MPM received intratumoral ONCOS-102 (3×1011 virus particles on days 1, 4, 8, 36, 78, and 120) and pemetrexed plus cisplatin/carboplatin (from day 22), or pemetrexed plus cisplatin/carboplatin alone. The primary endpoint was safety. Overall survival (OS), progression-free survival, objective response rate, and tumor immunologic activation (baseline and day 36 biopsies) were also assessed. RESULTS: In total, 31 patients (safety lead-in: n=6, randomized: n=25) were enrolled. Anemia (15.0% and 27.3%) and neutropenia (40.0% and 45.5%) were the most frequent grade ≥3 adverse events (AEs) in the ONCOS-102 (n=20) and chemotherapy-alone (n=11) cohorts. No patients discontinued ONCOS-102 due to AEs. No statistically significant difference in efficacy endpoints was observed. There was a numerical improvement in OS (30-month OS rate 34.1% vs 0; median OS 20.3 vs 13.5 months) with ONCOS-102 versus chemotherapy alone in chemotherapy-naïve patients (n=17). By day 36, ONCOS-102 was associated with increased T-cell infiltration and immune-related gene expression that was not observed in the control cohort. Substantial immune activation in the tumor microenvironment was associated with survival at month 18 in the ONCOS-102 cohort. CONCLUSIONS: ONCOS-102 plus pemetrexed and cisplatin/carboplatin was well tolerated by patients with MPM. In injected tumors, ONCOS-102 promoted a proinflammatory environment, including T-cell infiltration, which showed association with survival at month 18.

[Diagnosis and management of interstitial lung disease induced by antibody-drug conjugates in breast cancer: A French expert opinion paper]. / Diagnostic et prise en charge de la pneumopathie interstitielle diffuse induite par les anticorps conjugués dans le cancer du sein : avis d'expert.

Interstitial lung disease (ILD) has been reported with many cancer drugs including some recent antibody-drug conjugates (ADCs). The mechanisms of ILD induced by many chemotherapy drugs, other drug classes and ADCs used in cancer, including breast cancer, are not clearly elucidated. In the absence of specific clinical or radiological signs, the diagnosis of drug-induced ILD is often a diagnosis of exclusion. When present, the most frequent symptoms are respiratory signs (cough, dyspnea, chest pain) and general signs (fatigue, fever). Any suspicion of ILD should be evaluated by imaging and, if in doubt, the CT scan should be evaluated by a pulmonologist and a radiologist. A network of multidisciplinary experts for proactive early management of ILD is important, including oncologist, radiologist, pulmonologist, infectious disease specialist and nurses. Patient education is essential to report new or exacerbated lung symptoms and prevent high-grade ILD. Study drug is discontinued temporarily or permanently according to ILD severity and type of ADC. For asymptomatic cases (Grade 1), the efficacy of corticosteroids is not clearly established; for higher grades, the benefit/risk balance of long-term corticosteroid therapy should be considered for the dose and treatment duration. Hospitalization and oxygen supplementation are required for severe cases (Grades 3-4). For patient follow-up, the expertise of a pulmonologist is necessary with repeated chest scans, spirometry and DLCO. Preventing ADC-induced ILDs and evolution to high grade rests on a network of multidisciplinary experts for assessment of individual risk factors, early management, close follow-up and patient education.

Detection and quantification of pulmonary embolism with artificial intelligence: The SFR 2022 artificial intelligence data challenge.

PURPOSE: In 2022, the French Society of Radiology together with the French Society of Thoracic Imaging and CentraleSupelec organized their 13th data challenge. The aim was to aid in the diagnosis of pulmonary embolism, by identifying the presence of pulmonary embolism and by estimating the ratio between right and left ventricular (RV/LV) diameters, and an arterial obstruction index (Qanadli's score) using artificial intelligence. MATERIALS AND METHODS: The data challenge was composed of three tasks: the detection of pulmonary embolism, the RV/LV diameter ratio, and Qanadli's score. Sixteen centers all over France participated in the inclusion of the cases. A health data hosting certified web platform was established to facilitate the inclusion process of the anonymized CT examinations in compliance with general data protection regulation. CT pulmonary angiography images were collected. Each center provided the CT examinations with their annotations. A randomization process was established to pool the scans from different centers. Each team was required to have at least a radiologist, a data scientist, and an engineer. Data were provided in three batches to the teams, two for training and one for evaluation. The evaluation of the results was determined to rank the participants on the three tasks. RESULTS: A total of 1268 CT examinations were collected from the 16 centers following the inclusion criteria. The dataset was split into three batches of 310, 580 and 378 C T examinations provided to the participants respectively on September 5, 2022, October 7, 2022 and October 9, 2022. Seventy percent of the data from each center were used for training, and 30% for the evaluation. Seven teams with a total of 48 participants including data scientists, researchers, radiologists and engineering students were registered for participation. The metrics chosen for evaluation included areas under receiver operating characteristic curves, specificity and sensitivity for the classification task, and the coefficient of determination r2 for the regression tasks. The winning team achieved an overall score of 0.784. CONCLUSION: This multicenter study suggests that the use of artificial intelligence for the diagnosis of pulmonary embolism is possible on real data. Moreover, providing quantitative measures is mandatory for the interpretability of the results, and is of great aid to the radiologists especially in emergency settings.

French recommendations for the diagnosis and management of lymphangioleiomyomatosis.

BACKGROUND: The present article is an English-language version of the French National Diagnostic and Care Protocol, a pragmatic tool to optimize and harmonize the diagnosis, care pathway, management and follow-up of lymphangioleiomyomatosis in France. METHODS: Practical recommendations were developed in accordance with the method for developing a National Diagnosis and Care Protocol for rare diseases of the Haute Autorité de Santé and following international guidelines and literature on lymphangioleiomyomatosis. It was developed by a multidisciplinary group, with the help of patient representatives and of RespiFIL, the rare disease network on respiratory diseases. RESULTS: Lymphangioleiomyomatosis is a rare lung disease characterised by a proliferation of smooth muscle cells that leads to the formation of multiple lung cysts. It occurs sporadically or as part of a genetic disease called tuberous sclerosis complex (TSC). The document addresses multiple aspects of the disease, to guide the clinicians regarding when to suspect a diagnosis of lymphangioleiomyomatosis, what to do in case of recurrent pneumothorax or angiomyolipomas, what investigations are needed to make the diagnosis of lymphangioleiomyomatosis, what the diagnostic criteria are for lymphangioleiomyomatosis, what the principles of management are, and how follow-up can be organised. Recommendations are made regarding the use of pharmaceutical specialties and treatment other than medications. CONCLUSION: These recommendations are intended to guide the diagnosis and practical management of pulmonary lymphangioleiomyomatosis.

A case report of Covid-19 in an autoimmune pulmonary alveolar proteinosis: An association in tune with the times!

Autoimmune pulmonary alveolar proteinosis (PAP) is a rare disease characterized by the alveoli accumulation of surfactants proteins and lipids, which diagnosis is confirmed by the presence of GM-CSF antibodies in serum. PAP can be evoked when its characteristic images on chest computed-tomography (CT) are present: bilateral and multifocal ground-glass opacities and crazy-paving appearance. Patients with PAP are at an increased risk of opportunistic infections caused by Nocardia, mycobacteria and fungal pathogens due to impaired processing of pulmonary surfactant. We here report a typical case of newly diagnosed autoimmune PAP, with initial indication to realize a whole-lung lavage. Despite this treatment the patient presented a marked clinical worsening, with increasing need for oxygen and finally the need for mechanical ventilation. The chest CT was controlled and found to be typical of PAP, while the search for opportunistic infections remained negative. Finally, SARS-CoV-2 PCR was performed on bronchoalveolar lavage fluid, and was positive, whereas it had previously been negative twice. Our case report highlights the difficulty of distinguishing SARS-CoV-2 infection in the context of PAP, as the chest CT features are similar. We believe that a SARS-CoV-2 RT-PCR should be systematically realized in case of respiratory deterioration in PAP patients.

Strategies to safely rule out pulmonary embolism in COVID-19 outpatients: a multicenter retrospective study.

OBJECTIVES: The objective was to define a safe strategy to exclude pulmonary embolism (PE) in COVID-19 outpatients, without performing CT pulmonary angiogram (CTPA). METHODS: COVID-19 outpatients from 15 university hospitals who underwent a CTPA were retrospectively evaluated. D-Dimers, variables of the revised Geneva and Wells scores, as well as laboratory findings and clinical characteristics related to COVID-19 pneumonia, were collected. CTPA reports were reviewed for the presence of PE and the extent of COVID-19 disease. PE rule-out strategies were based solely on D-Dimer tests using different thresholds, the revised Geneva and Wells scores, and a COVID-19 PE prediction model built on our dataset were compared. The area under the receiver operating characteristics curve (AUC), failure rate, and efficiency were calculated. RESULTS: In total, 1369 patients were included of whom 124 were PE positive (9.1%). Failure rate and efficiency of D-Dimer > 500 µg/l were 0.9% (95%CI, 0.2-4.8%) and 10.1% (8.5-11.9%), respectively, increasing to 1.0% (0.2-5.3%) and 16.4% (14.4-18.7%), respectively, for an age-adjusted D-Dimer level. D-dimer > 1000 µg/l led to an unacceptable failure rate to 8.1% (4.4-14.5%). The best performances of the revised Geneva and Wells scores were obtained using the age-adjusted D-Dimer level. They had the same failure rate of 1.0% (0.2-5.3%) for efficiency of 16.8% (14.7-19.1%), and 16.9% (14.8-19.2%) respectively. The developed COVID-19 PE prediction model had an AUC of 0.609 (0.594-0.623) with an efficiency of 20.5% (18.4-22.8%) when its failure was set to 0.8%. CONCLUSIONS: The strategy to safely exclude PE in COVID-19 outpatients should not differ from that used in non-COVID-19 patients. The added value of the COVID-19 PE prediction model is minor. KEY POINTS: • D-dimer level remains the most important predictor of pulmonary embolism in COVID-19 patients. • The AUCs of the revised Geneva and Wells scores using an age-adjusted D-dimer threshold were 0.587 (95%CI, 0.572 to 0.603) and 0.588 (95%CI, 0.572 to 0.603). • The AUC of COVID-19-specific strategy to rule out pulmonary embolism ranged from 0.513 (95%CI: 0.503 to 0.522) to 0.609 (95%CI: 0.594 to 0.623).

[CT assessment in patients candidates for kidney transplantation: Benefits and indications]. / Bilan tomodensitométrique thoracique et abdomino-pelvien chez les patients insuffisants rénaux candidats à une transplantation rénale : intérêts et indications.

INTRODUCTION: Screening for neoplasms and vascular calcifications is a key step before kidney transplantation. American, European and French recommendations diverge on the imaging assessment to be carried out in this context. METHOD: We carried out a retrospective single-center study including patients who underwent imaging for kidney transplantation between the 01/01/2011 and the 12/31/2018. The neoplastic pathologies and vascular calcifications discovered on this assessment were noted. RESULTS: We included 579 patients: 293 performed a thoracic CT scan, 579 an abdominopelvic CT scan. The imaging work-up revealed 5 malignant thoracic tumors, 14 malignant abdominal tumors and 140 significant calcifications of the external iliac axes. All malignant chest tumors were found in patients with estimated smoking greater than or equal to 30 PY. DISCUSSION: Like the American recommendations, our results are in favor of performing a chest computed tomography in patients with smoking greater than or equal to 30 PY. Contrary to American and European recommendations, our results are in favor of performing an abdominopelvic tomodensitometry in all patients. CONCLUSION: Screening for vascular calcifications and neoplasms in kidney transplant candidates should include routine abdominopelvic CT and chest CT for smoking greater than or equal to 30 PY.

Malnutrition and decreased food intake at diagnosis are associated with hospitalization and mortality of idiopathic pulmonary fibrosis patients.

INTRODUCTION AND AIMS: Malnutrition is frequent in patients with idiopathic pulmonary fibrosis (IPF). We examined the relationship between malnutrition at diagnosis and all-cause hospitalization, survival, and acute exacerbation in newly diagnosed IPF patients. METHODS: In this prospective cohort study, the nutritional status of 153 consecutive newly-diagnosed IPF outpatients was evaluated by measuring body mass index (BMI), fat-free mass index (FFMI) with bioelectrical impedance analysis, and food intake with the Self Evaluation of Food Intake (SEFI)®. Diagnosis was taken as the baseline date and malnutrition was defined as an FFMI below 17 (men) or 15 kg/m2 (women). To determine the factors associated with all-cause hospitalization and mortality, univariate Cox regression analyses were performed and variables with P < 0.2 were included in a stepwise multivariable analysis. RESULTS: A quarter (26%; 40/153) of the patients were suffering from malnutrition at baseline, which was more frequent (62%) in patients whose BMI was <25 kg/m2. Patients whose baseline FFMI was low were more likely to be hospitalized (Hazard Ratio (HR) = 1.98 [95% confidence interval, 1.15; 3.41], P = 0.0139) and/or die (HR = 1.79 [1.11; 2.89], P = 0.0165), but their acute exacerbation rate was similar to that of patients with normal FFMIs. Decreased food intake (SEFI®<7) at baseline was associated with all-cause hospitalization (P = 0.003) and mortality (P < 0.0001) during follow-up. Baseline higher gender-age-physiology (GAP) scores (HR = 1.24 [1.01; 1.52], P = 0.0434; HR = 1.71 [1.37; 2.14], P < 0.0001, respectively), lower BMI (HR = 0.89 [0.83; 0.96], P = 0.003; HR = 0.89 [0.82; 0.96], P = 0.003), and decreased food intake (SEFI® score) (HR = 0.81 [0.71; 0.93], P = 0.003; HR = 0.72 [0.64; 0.81], P < 0.0001), but not FFMI, were independently associated with all-cause hospitalization and mortality rates during follow-up. CONCLUSIONS: Malnutrition and decreased food intake at IPF diagnosis are associated with all-cause hospitalization and mortality. Future studies will determine whether dedicated interventions to improve food intake and nutritional status could improve outcomes for IPF patients.

Cardiac radioablation for ventricular tachycardia: Which approach for incorporating cardiorespiratory motions into the planning target volume?

PURPOSE: To evaluate different approaches for generating a cardiorespiratory ITV for cardiac radioablation. METHODS: Four patients with ventricular tachycardia were included in this study. For each patient, cardiac-gated and respiration-correlated 4D-CT scans were acquired. The cardiorespiratory ITV was defined using registrations of the cardiac and respiratory 4D-CT images. Five different approaches, which differed in the number of incorporated cardiac phases (1, 2, 10, or 1 with a fixed 3 mm margin (FM) expansion) and respiratory phases (2 or 10), were evaluated. For each approach, a VMAT treatment plan was simulated. Target coverage (TC) and spill were evaluated geometrically and dosimetrically for each approach. RESULTS: When employing one cardiac phase, the TC did not exceed 85%. Using the two extreme phases of the cardiac and respiratory cycles resulted in a geometric TC < 88% for two patients, with a dosimetric TC of 83% for one patient. An acceptable TC for all patients (geometric TC > 89%, dosimetric TC > 92%) was only achieved when combining 10 respiratory phases with either 2 or 10 cardiac phases or a single cardiac phase with FM. The use of a single cardiac phase with FM combined with 10 respiratory phases lead to a mean geometric and dosimetric spill of 43% and 35%, respectively. CONCLUSION: For cardiac radioablation, the use of two extreme cardiac phases combined with 10 respiratory phases is a robust approach to generate a cardiorespiratory ITV. The use of a single cardiac phase with or without fixed margin expansion is not recommended based on this study.

Validation of a Whole Heart Segmentation from Computed Tomography Imaging Using a Deep-Learning Approach.

The aim of this study is to develop an automated deep-learning-based whole heart segmentation of ECG-gated computed tomography data. After 21 exclusions, CT acquired before transcatheter aortic valve implantation in 71 patients were reviewed and randomly split in a training (n = 55 patients), validation (n = 8 patients), and a test set (n = 8 patients). A fully automatic deep-learning method combining two convolutional neural networks performed segmentation of 10 cardiovascular structures, which was compared with the manually segmented reference by the Dice index. Correlations and agreement between myocardial volumes and mass were assessed. The algorithm demonstrated high accuracy (Dice score = 0.920; interquartile range: 0.906-0.925) and a low computing time (13.4 s, range 11.9-14.9). Correlations and agreement of volumes and mass were satisfactory for most structures. Six of ten structures were well segmented. Deep-learning-based method allowed automated WHS from ECG-gated CT data with a high accuracy. Challenges remain to improve right-sided structures segmentation and achieve daily clinical application.

Usefulness of Body Composition CT Analysis in Patients with Idiopathic Pulmonary Fibrosis: A Pilot Study.

PURPOSE: To evaluate the feasibility of a chest CT-based body composition analysis in idiopathic pulmonary fibrosis (IPF), and to investigate the respective contribution of lung and muscle CT quantitative analyses to the prognosis of IPF. METHOD: A total of 71 IPF patients were recruited at diagnosis. All patients underwent a standard chest CT-scan and a bioelectrical impedance analysis considered as reference standard for estimating malnutrition through the use of the fat-free mass index (FFMI). The skeletal muscle index (SMI) was measured on chest-CT at the level of the first lumbar vertebra by two radiologists. Lung fibrosis extent was quantified by three radiologists in consensus. The extent of emphysema, the pulmonary artery to aorta (PA/AO) diameter ratio and lymph node enlargement were also reported. Mortality and hospitalization over a 14-month follow-up were recorded. RESULTS: A low FFMI defining malnutrition was identified in 26.8% of patients. SMI was significantly lower in these patients (p<0.001) and was correlated with FFMI (r=0.637, p<0.001). Interobserver agreement of SMI measurement was very good (ICC=0.91). For diagnosing malnutrition, SMI showed a 0.79 sensitivity, a 0.69 specificity, a 0.48 PPV and a 0.90 NPV. In univariate analysis, fibrosis extent was significantly associated with death, while SMI did not reach significance. In multivariate analysis, fibrosis extent and PA/AO ratio were independently associated with hospitalization. CONCLUSIONS: SMI measured on chest CT could be a reliable tool to exclude malnutrition in IPF. A quantitative analysis of both fibrosis and skeletal muscle may allow holistic management of IPF patients.

Post hoc Analysis of Clinical Outcomes in Placebo- and Pirfenidone-Treated Patients with IPF Stratified by BMI and Weight Loss.

BACKGROUND: Weight loss is frequently reported in patients with idiopathic pulmonary fibrosis (IPF) and may be associated with worse outcomes in these patients. OBJECTIVE: The aim of this study was to investigate the relationships between body mass index (BMI) and weight loss, and outcomes over 1 year in patients with IPF. METHODS: Data were included from placebo patients enrolled in ASCEND (NCT01366209) and CAPACITY (NCT00287716 and NCT00287729), and all patients in INSPIRE (NCT00075998) and RIFF Cohort A (NCT01872689). An additional analysis included data from pirfenidone-treated patients. Outcomes (annualized change in percent predicted forced vital capacity [%FVC], percent predicted carbon monoxide diffusing capacity, 6-min walk distance, St. George's Respiratory Questionnaire total score, hospitalization, mortality, and serious adverse events) were analyzed by baseline BMI (<25 kg/m2, 25 kg/m2-<30 kg/m2, or ≥30 kg/m2) and annualized percent change in body weight (no loss, >0-<5% loss, or ≥5% loss). RESULTS: Placebo-treated patients with a baseline BMI <25 kg/m2 or annualized weight loss may experience worse outcomes versus those with a baseline BMI ≥25 kg/m2 or no weight loss. The proportion of placebo-treated patients who experienced a relative decline of ≥10% in %FVC or death up to 1 year post-randomization was highest in patients with a baseline BMI <25 kg/m2. Pirfenidone-treated patients with an annualized weight loss ≥5% may also experience worse outcomes versus those with no weight loss. CONCLUSIONS: Patients with a baseline BMI <25 kg/m2 or annualized weight loss of >0-<5% or ≥5% may experience worse outcomes over 1 year versus those with a baseline BMI ≥25 kg/m2 or no weight loss.

Intrapleural use of urokinase and DNase in pleural infections managed with repeated thoracentesis: A comparative cohort study.

INTRODUCTION: Evacuation of infected fluid in pleural infections is essential. To date, the use of an intrapleural fibrinolytic agent such as urokinase and DNase has not yet been assessed in infections managed by repeated therapeutic thoracentesis (RTT). METHODS: We performed a retrospective comparative study of two successive cohorts of consecutive patients with pleural infections from 2001 to 2018. Between 2001 and 2010, patients had RTT with intrapleural urokinase (RTT-U). After 2011, patients received intrapleural urokinase and DNase with RTT (RTT-UD). Data were collected through a standardized questionnaire. RESULTS: One hundred and thirty-three patients were included: 93 were men and the mean age was 59 years (standard deviation 17.2). Eighty-one patients were treated with a combination of intrapleural urokinase and DNase, and 52 were treated with intrapleural urokinase only. In the RTT-UD, RTT failure occurred in 14 patients (17%) compared to 10 (19%) in the RTT-U group (P = 0.82). There was no difference between the two groups in intensive care unit admission, surgical referrals or in-hospital mortality. RTT-UD was associated with faster time to apyrexia (aOR = 0.51, 95%CI [0.37-0.72]), a reduced length of hospital stay (aOR = 0.61, 95%CI [0.52-0.73]) and a higher volume of total pleural fluid retrieved (aOR = 1.38, 95%CI [1.02-1.88]). Complications were rare with only one hemothorax in the RTT-UD group and no pneumothorax requiring drainage in either group. CONCLUSION: Compared to urokinase only, intrapleural use of urokinase and DNase in RTT was associated with quicker defervescence, shorter hospital stay and increased volumes of pleural fluid drained. Randomized controlled trials evaluating urokinase and DNase with RTT technique would be required to confirm these results.

Long-Term Imaging Follow-Up in DIPNECH: Multicenter Experience.

Diffuse pulmonary neuroendocrine cell hyperplasia (DIPNECH) is a rare pre-invasive disease whose pathophysiology remains unclear. We aimed to assess long-term evolution in imaging of DIPNECH, in order to propose follow-up recommendations. Patients with histologically confirmed DIPNECH from four centers, evaluated between 2001 and 2020, were enrolled if they had at least two available chest computed tomography (CT) exams performed at least 24 months apart. CT exams were analyzed for the presence and the evolution of DIPNECH-related CT findings. Twenty-seven patients, mostly of female gender (n = 25/27; 93%) were included. Longitudinal follow-up over a median 63-month duration (IQR: 31-80 months) demonstrated an increase in the size of lung nodules in 19 patients (19/27, 70%) and the occurrence of metastatic spread in three patients (3/27, 11%). The metastatic spread was limited to mediastinal lymph nodes in one patient, whereas the other two patients had both lymph node and distant metastases. The mean time interval between baseline CT scan and metastatic spread was 70 months (14, 74 and 123 months). Therefore, long-term annual imaging follow-up of DIPNECH might be appropriate to encompass the heterogeneous longitudinal behavior of this disease.

Influenza- and COVID-19-Associated Pulmonary Aspergillosis: Are the Pictures Different?

Invasive pulmonary aspergillosis (IPA) in intensive care unit patients is a major concern. Influenza-associated acute respiratory distress syndrome (ARDS) and severe COVID-19 patients are both at risk of developing invasive fungal diseases. We used the new international definitions of influenza-associated pulmonary aspergillosis (IAPA) and COVID-19-associated pulmonary aspergillosis (CAPA) to compare the demographic, clinical, biological, and radiological aspects of IAPA and CAPA in a monocentric retrospective study. A total of 120 patients were included, 71 with influenza and 49 with COVID-19-associated ARDS. Among them, 27 fulfilled the newly published criteria of IPA: 17/71 IAPA (23.9%) and 10/49 CAPA (20.4%). Kaplan-Meier curves showed significantly higher 90-day mortality for IPA patients overall (p = 0.032), whereas mortality did not differ between CAPA and IAPA patients. Radiological findings showed differences between IAPA and CAPA, with a higher proportion of features suggestive of IPA during IAPA. Lastly, a wide proportion of IPA patients had low plasma voriconazole concentrations with a higher delay to reach concentrations > 2 mg/L in CAPA vs. IAPA patients (p = 0.045). Severe COVID-19 and influenza patients appeared very similar in terms of prevalence of IPA and outcome. The dramatic consequences on the patients' prognosis emphasize the need for a better awareness in these particular populations.

Study of Thoracic CT in COVID-19: The STOIC Project.

Background There are conflicting data regarding the diagnostic performance of chest CT for COVID-19 pneumonia. Disease extent at CT has been reported to influence prognosis. Purpose To create a large publicly available data set and assess the diagnostic and prognostic value of CT in COVID-19 pneumonia. Materials and Methods This multicenter, observational, retrospective cohort study involved 20 French university hospitals. Eligible patients presented at the emergency departments of the hospitals involved between March 1 and April 30th, 2020, and underwent both thoracic CT and reverse transcription-polymerase chain reaction (RT-PCR) testing for suspected COVID-19 pneumonia. CT images were read blinded to initial reports, RT-PCR, demographic characteristics, clinical symptoms, and outcome. Readers classified CT scans as either positive or negative for COVID-19 based on criteria published by the French Society of Radiology. Multivariable logistic regression was used to develop a model predicting severe outcome (intubation or death) at 1-month follow-up in patients positive for both RT-PCR and CT, using clinical and radiologic features. Results Among 10 930 patients screened for eligibility, 10 735 (median age, 65 years; interquartile range, 51-77 years; 6147 men) were included and 6448 (60%) had a positive RT-PCR result. With RT-PCR as reference, the sensitivity and specificity of CT were 80.2% (95% CI: 79.3, 81.2) and 79.7% (95% CI: 78.5, 80.9), respectively, with strong agreement between junior and senior radiologists (Gwet AC1 coefficient, 0.79). Of all the variables analyzed, the extent of pneumonia at CT (odds ratio, 3.25; 95% CI: 2.71, 3.89) was the best predictor of severe outcome at 1 month. A score based solely on clinical variables predicted a severe outcome with an area under the curve of 0.64 (95% CI: 0.62, 0.66), improving to 0.69 (95% CI: 0.6, 0.71) when it also included the extent of pneumonia and coronary calcium score at CT. Conclusion Using predefined criteria, CT reading is not influenced by reader's experience and helps predict the outcome at 1 month. ClinicalTrials.gov identifier: NCT04355507 Published under a CC BY 4.0 license. Online supplemental material is available for this article. See also the editorial by Rubin in this issue.

Successful heart transplantation for COVID-19-associated post-infectious fulminant myocarditis.

Various clinical presentations of the 2019 coronavirus disease (COVID-19) have been described, including post-infectious acute and fulminant myocarditis. Here, we describe the case of a young patient admitted for COVID-19-associated post-infectious fulminant myocarditis. Despite optimal pharmacologic management, haemodynamic status worsened requiring support by veno-arterial extracorporeal membrane oxygenation. Emergent heart transplantation was required at Day 11 given the absence of cardiac function improvement. The diagnosis of post-infectious COVID-19-associated myocarditis was made from both pathologic examination of the explanted heart and positive SARS-CoV-2 serology.

Evaluation of COVID-19 chest computed tomography: A texture analysis based on three-dimensional entropy.

Radiologists, and doctors in general, need relevant information for the quantification and characterization of pulmonary structures damaged by severe diseases, such as the Coronavirus disease 2019 (COVID-19). Texture-based analysis in scope of other pulmonary diseases has been used to screen, monitor, and provide valuable information for several kinds of diagnoses. To differentiate COVID-19 patients from healthy subjects and patients with other pulmonary diseases is crucial. Our goal is to quantify lung modifications in two pulmonary pathologies: COVID-19 and idiopathic pulmonary fibrosis (IPF). For this purpose, we propose the use of a three-dimensional multiscale fuzzy entropy (MFE3D) algorithm. The three groups tested (COVID-19 patients, IPF, and healthy subjects) were found to be statistically different for 9 scale factors ( p < 0.01 ). A complexity index (CI) based on the sum of entropy values is used to classify healthy subjects and COVID-19 patients showing an accuracy of 89.6 % , a sensitivity of 96.1 % , and a specificity of 76.9 % . Moreover, 4 different machine-learning models were also used to classify the same COVID-19 dataset for comparison purposes.