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.

Generating High-Resolution Synthetic CT from Lung MRI with Ultrashort Echo Times: Initial Evaluation in Cystic Fibrosis.

Background Lung MRI with ultrashort echo times (UTEs) enables high-resolution and radiation-free morphologic imaging; however, its image quality is still lower than that of CT. Purpose To assess the image quality and clinical applicability of synthetic CT images generated from UTE MRI by a generative adversarial network (GAN). Materials and Methods This retrospective study included patients with cystic fibrosis (CF) who underwent both UTE MRI and CT on the same day at one of six institutions between January 2018 and December 2022. The two-dimensional GAN algorithm was trained using paired MRI and CT sections and tested, along with an external data set. Image quality was assessed quantitatively by measuring apparent contrast-to-noise ratio, apparent signal-to-noise ratio, and overall noise and qualitatively by using visual scores for features including artifacts. Two readers evaluated CF-related structural abnormalities and used them to determine clinical Bhalla scores. Results The training, test, and external data sets comprised 82 patients with CF (mean age, 21 years ± 11 [SD]; 42 male), 28 patients (mean age, 18 years ± 11; 16 male), and 46 patients (mean age, 20 years ± 11; 24 male), respectively. In the test data set, the contrast-to-noise ratio of synthetic CT images (median, 303 [IQR, 221-382]) was higher than that of UTE MRI scans (median, 9.3 [IQR, 6.6-35]; P < .001). The median signal-to-noise ratio was similar between synthetic and real CT (88 [IQR, 84-92] vs 88 [IQR, 86-91]; P = .96). Synthetic CT had a lower noise level than real CT (median score, 26 [IQR, 22-30] vs 42 [IQR, 32-50]; P < .001) and the lowest level of artifacts (median score, 0 [IQR, 0-0]; P < .001). The concordance between Bhalla scores for synthetic and real CT images was almost perfect (intraclass correlation coefficient, ≥0.92). Conclusion Synthetic CT images showed almost perfect concordance with real CT images for the depiction of CF-related pulmonary alterations and had better image quality than UTE MRI. Clinical trial registration no. NCT03357562 © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Schiebler and Glide-Hurst in this issue.

Development and external validation of a prediction model for the transition from mild to moderate or severe form of COVID-19.

OBJECTIVES: COVID-19 pandemic seems to be under control. However, despite the vaccines, 5 to 10% of the patients with mild disease develop moderate to critical forms with potential lethal evolution. In addition to assess lung infection spread, chest CT helps to detect complications. Developing a prediction model to identify at-risk patients of worsening from mild COVID-19 combining simple clinical and biological parameters with qualitative or quantitative data using CT would be relevant to organizing optimal patient management. METHODS: Four French hospitals were used for model training and internal validation. External validation was conducted in two independent hospitals. We used easy-to-obtain clinical (age, gender, smoking, symptoms' onset, cardiovascular comorbidities, diabetes, chronic respiratory diseases, immunosuppression) and biological parameters (lymphocytes, CRP) with qualitative or quantitative data (including radiomics) from the initial CT in mild COVID-19 patients. RESULTS: Qualitative CT scan with clinical and biological parameters can predict which patients with an initial mild presentation would develop a moderate to critical form of COVID-19, with a c-index of 0.70 (95% CI 0.63; 0.77). CT scan quantification improved the performance of the prediction up to 0.73 (95% CI 0.67; 0.79) and radiomics up to 0.77 (95% CI 0.71; 0.83). Results were similar in both validation cohorts, considering CT scans with or without injection. CONCLUSION: Adding CT scan quantification or radiomics to simple clinical and biological parameters can better predict which patients with an initial mild COVID-19 would worsen than qualitative analyses alone. This tool could help to the fair use of healthcare resources and to screen patients for potential new drugs to prevent a pejorative evolution of COVID-19. CLINICAL TRIAL REGISTRATION: NCT04481620. CLINICAL RELEVANCE STATEMENT: CT scan quantification or radiomics analysis is superior to qualitative analysis, when used with simple clinical and biological parameters, to determine which patients with an initial mild presentation of COVID-19 would worsen to a moderate to critical form. KEY POINTS: • Qualitative CT scan analyses with simple clinical and biological parameters can predict which patients with an initial mild COVID-19 and respiratory symptoms would worsen with a c-index of 0.70. • Adding CT scan quantification improves the performance of the clinical prediction model to an AUC of 0.73. • Radiomics analyses slightly improve the performance of the model to a c-index of 0.77.

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.

Pleural Plaques and the Role of Exposure to Mineral Particles in the Asbestos Post-exposure Survey.

BACKGROUND: Previous studies have inconsistently reported associations between refractory ceramic fibers (RCFs) or mineral wool fibers (MWFs) and the presence of pleural plaques. All these studies were based on chest radiographs, known to be associated with a poor sensitivity for the diagnosis of pleural plaques. RESEARCH QUESTION: Does the risk of pleural plaques increase with cumulative exposure to RCFs, MWFs, and silica? If the risk does increase, do these dose-response relationships depend on the co-exposure to asbestos or, conversely, are the dose-response relationships for asbestos modified by co-exposure to RCFs, MWFs, and silica? STUDY DESIGN AND METHODS: Volunteer workers were invited to participate in a CT scan screening program for asbestos-related diseases in France. Asbestos exposure was assessed by industrial hygienists, and exposure to RCFs, MWFs, and silica was determined by using job-exposure matrices. A cumulative exposure index (CEI) was then calculated for each subject and separately for each of the four mineral particle exposures. All available CT scans were submitted to randomized double reading by a panel of radiologists. RESULTS: In this cohort of 5,457 subjects, significant dose-response relationships were determined after adjustment for asbestos exposure between CEI to RCF or MWF and the risk of PPs (ORs of 1.29 [95% CI, 1.00-1.67] and 1.84 [95% CI, 1.49-2.27] for the highest CEI quartile, respectively). Significant interactions were found between asbestos on one hand and MWF or RCF on the other. INTERPRETATION: This study suggests the existence of a significant association between exposure to RCFs and MWFs and the presence of pleural plaques in a large population previously exposed to asbestos and screened by using CT scans.

A comparative study of two automated solutions for cross-sectional skeletal muscle measurement from abdominal computed tomography images.

BACKGROUND: Measurement of cross-sectional muscle area (CSMA) at the mid third lumbar vertebra (L3) level from computed tomography (CT) images is becoming one of the reference methods for sarcopenia diagnosis. However, manual skeletal muscle segmentation is tedious and is thus restricted to research. Automated solutions are required for use in clinical practice. PURPOSE: The aim of this study was to compare the reliability of two automated solutions for the measurement of CSMA. METHODS: We conducted a retrospective analysis of CT images in our hospital database. We included consecutive individuals hospitalized at the Grenoble University Hospital in France between January and May 2018 with abdominal CT images and sagittal reconstruction. We used two types of software to automatically segment skeletal muscle: ABACS, a module of the SliceOmatic software solution "ABACS-SliceOmatic," and a deep learning-based solution called "AutoMATiCA." Manual segmentation was performed by a medical expert to generate reference data using "SliceOmatic." The Dice similarity coefficient (DSC) was used to measure overlap between the results of the manual and the automated segmentations. The DSC value for each method was compared with the Mann-Whitney U test. RESULTS: A total of 676 hospitalized individuals was retrospectively included (365 males [53.8%] and 312 females [46.2%]). The median DSC for SliceOmatic vs AutoMATiCA (0.969 [5th percentile: 0.909]) was greater than the median DSC for SliceOmatic vs. ABACS-SliceOmatic (0.949 [5th percentile: 0.836]) (p < 0.001). CONCLUSIONS: AutoMATiCA, which used artificial intelligence, was more reliable than ABACS-SliceOmatic for skeletal muscle segmentation at the L3 level in a cohort of hospitalized individuals. The next step is to develop and validate a neural network that can identify L3 slices, which is currently a fastidious process.

A Retrospective Comparison of the Efficacy of Embolization with Imipenem/Cilastatin and Microspheres in the Management of Chronic Shoulder Pain.

PURPOSE: To compare the efficacy of embolization with imipenem/cilastatin and microspheres in chronic shoulder pain. METHODS: This retrospective study included 29 patients who underwent embolization for chronic shoulder pain between June 2017 and March 2022 with calibrated MSs from 100 to 250 µm or IMP/CS. The main objective was the clinical success evaluated by the Minimum Clinically Important Difference (MCID) at 3 months after the procedure, validated if the patient responded yes to 2 questions: (1) Is the pain less severe than before the procedure? (2) Are you satisfied with the procedure? The decrease in visual analogue pain scale scores and the safety of the procedure were evaluated. RESULTS: Embolization was achieved in all patients. In the MS group, 4/15 patients (26.7%) experienced clinical success at 3 months according to MCID versus 10/14 patients (71.4%) in the IMP/CS group (p = 0.02). The mean VAS decreases were respectively - 28.6% ± 34.6 in the MS group and - 36.8% ± 27.8 in the IMP/CS group at 1 month (p = 0.50), - 29.9% ± 29.0 and - 39.6% ± 23.0 at 3 months (p = 0.33) and - 30.6% ± 32.8 and - 46.6% ± 28.4 at 6 months after the procedure (p = 0.26). Eleven patients (73.3%) in the MS group and 3 patients (21.4%) in the IMP/CS group had complications (p = 0.01). Among them, 2/15 patients (13.3%) had transient skin ischaemia in the MS group. CONCLUSION: Embolization with IMP/CS may be more effective and safer than MSs in the management of chronic shoulder pain.

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).

Simple Aspiration versus Drainage for Complete Pneumothorax: A Randomized Noninferiority Trial.

Rationale: Management of first episodes of primary spontaneous pneumothorax remains the subject of debate. Objectives: To determine whether first-line simple aspiration is noninferior to first-line chest tube drainage for lung expansion in patients with complete primary spontaneous pneumothorax. Methods: We conducted a prospective, open-label, randomized noninferiority trial. Adults aged 18-50 years with complete primary spontaneous pneumothorax (total separation of the lung from the chest wall), recruited at 31 French hospitals from 2009 to 2015, received simple aspiration (n = 200) or chest tube drainage (n = 202) as first-line treatment. The primary outcome was pulmonary expansion 24 hours after the procedure. Secondary outcomes were tolerance of treatment, occurrence of adverse events, and recurrence of pneumothorax within 1 year. Substantial discordance in the numerical inputs used for trial planning and the actual trial rates of the primary outcome resulted in a reevaluation of the trial analysis plan. Measurement and Main Results: Treatment failure occurred in 29% in the aspiration group and 18% in the chest tube drainage group (difference in failure rate, 0.113; 95% confidence interval [CI], 0.026-0.200). The aspiration group experienced less pain overall (mean difference, -1.4; 95% CI, -1.89, -0.91), less pain limiting breathing (frequency difference, -0.18; 95% CI, -0.27, -0.09), and less kinking of the device (frequency difference, -0.05; 95% CI, -0.09, -0.01). Recurrence of pneumothorax was 20% in this group versus 27% in the drainage group (frequency difference, -0.07; 95% CI, -0.16, +0.02). Conclusions: First-line management of complete primary spontaneous pneumothorax with simple aspiration had a higher failure rate than chest tube drainage but was better tolerated with fewer adverse events. Clinical trial registered with www.clinicaltrials.gov (NCT01008228).

French practical guidelines for the diagnosis and management of idiopathic pulmonary fibrosis - 2021 update. Full-length version.

BACKGROUND: Since the latest 2017 French guidelines, knowledge about idiopathic pulmonary fibrosis has evolved considerably. METHODS: Practical guidelines were drafted on the initiative of the Coordinating Reference Center for Rare Pulmonary Diseases, led by the French Language Pulmonology Society (SPLF), by a coordinating group, a writing group, and a review group, with the involvement of the entire OrphaLung network, pulmonologists practicing in various settings, radiologists, pathologists, a general practitioner, a health manager, and a patient association. The method followed the "Clinical Practice Guidelines" process of the French National Authority for Health (HAS), including an online vote using a Likert scale. RESULTS: After a literature review, 54 guidelines were formulated, improved, and then validated by the working groups. These guidelines addressed multiple aspects of the disease: epidemiology, diagnostic procedures, quality criteria and interpretation of chest CT scans, lung biopsy indication and procedures, etiological workup, methods and indications for family screening and genetic testing, assessment of the functional impairment and prognosis, indication and use of antifibrotic agents, lung transplantation, management of symptoms, comorbidities and complications, treatment of chronic respiratory failure, diagnosis and management of acute exacerbations of fibrosis. CONCLUSION: These evidence-based guidelines are intended to guide the diagnosis and practical management of idiopathic pulmonary fibrosis.

Feasibility of Neovessel Embolization in a Large Animal Model of Tendinopathy: Safety and Efficacy of Various Embolization Agents.

Targeting neovessels in chronic tendinopathies has emerged as a new therapeutic approach and several embolization agents have been reported. The aim of this study was to investigate the feasibility of embolization with different agents in a porcine model of patellar tendinopathy and evaluate their safety and efficacy. Eight 3-month-old male piglets underwent percutaneous injection of collagenase type I to induce patellar tendinopathies (n = 16 tendons). They were divided into four groups (2 piglets, 4 tendons/group): the control group, 50-100 µm microspheres group, 100-300 µm microspheres group, and the Imipenem/Cilastatin (IMP/CS) group. Angiography and embolization were performed for each patellar tendon on day 7 (D7). The neovessels were evaluated visually with an angiography on day 14. The pathological analysis assessed the efficacy (Bonar score, number of neovessels/mm2) and safety (off-target persistent cutaneous ischemic modifications and presence of off-target embolization agents). The technical success was 92%, with a failed embolization for one tendon due to an arterial dissection. Neoangiogenesis was significantly less important in the embolized groups compared to the control group angiographies (p = 0.04) but not with respect to histology (Bonar score p = 0.15, neovessels p = 0.07). Off-target cutaneous embolization was more frequently depicted in the histology of the 50-100 µm microspheres group (p = 0.02). Embolization of this animal model with induced patellar tendinopathy was technically feasible with different agents and allowed assessing the safety and efficacy of neovessel destruction. Particles smaller than 100 µm seemed to be associated with more complications.

Pleural plaques and risk of lung cancer in workers formerly occupationally exposed to asbestos: extension of follow-up.

BACKGROUND: Occupational asbestos exposure is associated with pleural plaques (PP), a benign disease often seen as a marker of past exposure to asbestos and lung cancer. The association between these two diseases has not been formally proved, the aim of this study was to evaluate this association in the asbestos-related disease cohort (ARDCO) cohort. METHODS: ARDCO is a French multicentric cohort including workers formerly occupationally exposed to asbestos from 2003 to 2005. CT scan was performed to diagnose PP with double reading and lung cancer (incidence and mortality) was followed through health insurance data and death certificates. Cox models were used to estimate the association between PP and lung cancer adjusting for occupational asbestos exposure (represented by cumulative exposure index, time since first exposure and time since last exposure) and smoking status. RESULTS: A total of 176 cases (of 5050 subjects) and 88 deaths (of 4938 subjects) of lung cancer were recorded. Smoking status was identified as an effect modifier. Lung cancer incidence and mortality were significantly associated with PP only in non-smokers, respectively, HR=3.13 (95% CI 1.04 to 9.35) and HR=16.83 (95% CI 1.87 to 151.24) after adjustment for age, occupational asbestos exposure and smoking status. CONCLUSIONS: ARDCO study was the first to study this association considering equal asbestos exposure, and more specifically, our study is the first to test smoking as an effect modifier, so comparison with scientific literature is difficult. Our results seem to consolidate the hypothesis that PP may be an independent risk factor for lung cancer but they must be interpreted with caution.

Management of Symptomatic Vascularized Retained Products of Conception by Proximal Uterine Artery Embolization with Gelatin Sponge Torpedoes.

PURPOSE: To evaluate the effectiveness and safety of temporary proximal uterine artery embolization (UAE) for the treatment of highly vascularized retained products of conception (RPOCs). MATERIALS AND METHODS: This retrospective analysis included women who underwent treatment for vaginal bleeding after abortion, miscarriage, or delivery, with highly vascularized RPOCs detected by Doppler ultrasound (US) (ie, presence of an enhanced myometrial vascularity, a low resistance index of <0.5, and a peak systolic velocity of ≥0.7 m/s). A unilateral or bilateral embolization with torpedoes of gelatin foam was performed. From November 2017 to January 2021, 24 women with a median age of 30 years (interquartile range, 26.0-34.5 years) with symptomatic highly vascularized RPOCs were included. Clinical success was defined as bleeding arrest between the UAE and 1-month follow-up. Technical success was defined as the complete obstruction of at least 1 uterine artery supplying vascular abnormalities. The safety of the procedure according to the classification of the Society of Interventional Radiology and evolution of lesions on US were also reported. RESULTS: Technical success was achieved in all 24 (100%) patients, with bilateral arterial embolization in 19 (79%) patients and unilateral embolization in 5 (21%) patients. Clinical success was achieved in all 24 (100%) patients. Five patients still had uterine retention at the 1-month follow-up, including 2 patients with highly vascularized RPOCs. Two patients benefited from hysteroscopy, and 3 had noninvasive management. Four minor adverse events were reported (1 patient had infectious endometritis and 3 patients had a postembolization syndrome). CONCLUSIONS: Proximal UAE with torpedoes of gelatin foam is safe and effective for the management of symptomatic highly vascularized RPOCs.

Response to PEEP in COVID-19 ARDS patients with and without extracorporeal membrane oxygenation. A multicenter case-control computed tomography study.

BACKGROUND: PEEP selection in severe COVID-19 patients under extracorporeal membrane oxygenation (ECMO) is challenging as no study has assessed the alveolar recruitability in this setting. The aim of the study was to compare lung recruitability and the impact of PEEP on lung aeration in moderate and severe ARDS patients with or without ECMO, using computed tomography (CT). METHODS: We conducted a two-center prospective observational case-control study in adult COVID-19-related patients who had an indication for CT within 72 h of ARDS onset in non-ECMO patients or within 72  h after ECMO onset. Ninety-nine patients were included, of whom 24 had severe ARDS under ECMO, 59 severe ARDS without ECMO and 16 moderate ARDS. RESULTS: Non-inflated lung at PEEP 5 cmH2O was significantly greater in ECMO than in non-ECMO patients. Recruitment induced by increasing PEEP from 5 to 15 cmH2O was not significantly different between ECMO and non-ECMO patients, while PEEP-induced hyperinflation was significantly lower in the ECMO group and virtually nonexistent. The median [IQR] fraction of recruitable lung mass between PEEP 5 and 15 cmH2O was 6 [4-10]%. Total superimposed pressure at PEEP 5 cmH2O was significantly higher in ECMO patients and amounted to 12 [11-13] cmH2O. The hyperinflation-to-recruitment ratio (i.e., a trade-off index of the adverse effects and benefits of PEEP) was significantly lower in ECMO patients and was lower than one in 23 (96%) ECMO patients, 41 (69%) severe non-ECMO patients and 8 (50%) moderate ARDS patients. Compliance of the aerated lung at PEEP 5 cmH2O corrected for PEEP-induced recruitment (CBABY LUNG) was significantly lower in ECMO patients than in non-ECMO patients and was linearly related to the logarithm of the hyperinflation-to-recruitment ratio. CONCLUSIONS: Lung recruitability of COVID-19 pneumonia is not significantly different between ECMO and non-ECMO patients, with substantial interindividual variations. The balance between hyperinflation and recruitment induced by PEEP increase from 5 to 15 cmH2O appears favorable in virtually all ECMO patients, while this PEEP level is required to counteract compressive forces leading to lung collapse. CBABY LUNG is significantly lower in ECMO patients, independently of lung recruitability.

ODIASP: Clinically Contextualized Image Analysis Using the PREDIMED Clinical Data Warehouse, Towards a Better Diagnosis of Sarcopenia.

Big Data and Deep Learning approaches offer new opportunities for medical data analysis. With these technologies, PREDIMED, the clinical data warehouse of Grenoble Alps University Hospital, sets up first clinical studies on retrospective data. In particular, ODIASP study, aims to develop and evaluate deep learning-based tools for automatic sarcopenia diagnosis, while using data collected via PREDIMED, in particular, medical images. Here we describe a methodology of data preparation for a clinical study via PREDIMED.

Computed Tomography Registration-Derived Regional Ventilation Indices Compared to Global Lung Function Parameters in Patients With COPD.

CT registration-derived indices provide data on regional lung functional changes in COPD. However, because unlike spirometry which involves dynamic maximal breathing maneuvers, CT-based functional parameters are assessed between two static breath-holds, it is not clear how regional and global lung function parameters relate to each other. We assessed the relationship between CT-density change (dHU), specific volume change (dsV), and regional lung tissue deformation (J) with global spirometric and plethysmographic parameters, gas exchange, exercise capacity, dyspnoea, and disease stage in a prospective cohort study in 102 COPD patients. There were positive correlations of dHU, dsV, and J with spirometric variables, DLCO and gas exchange, 6-min walking distance, and negative correlations with plethysmographic lung volumes and indices of trapping and lung distension as well as GOLD stage. Stepwise regression identified FEV1/FVC (standardized ß = 0.429, p < 0.0001), RV/TLC (ß = -0.37, p < 0.0001), and BMI (ß = 0.27, p=<0.001) as the strongest predictors of CT intensity-based metrics dHU, with similar findings for dsV, while FEV1/FVC (ß = 0.32, p=<0.001) and RV/TLC (ß = -0.48, p=<0.0001) were identified as those for J. These data suggest that regional lung function is related to two major pathophysiological processes involved in global lung function deterioration in COPD: chronic airflow obstruction and gas trapping, with an additional contribution of nutritional status, which in turn determines respiratory muscle strength. Our data confirm previous findings in the literature, suggesting the potential of CT image-based regional lung function metrics as the biomarkers of disease severity and provide mechanistic insight into the interpretation of regional lung function indices in patients with COPD.

Deep Learning for the Automatic Quantification of Pleural Plaques in Asbestos-Exposed Subjects.

OBJECTIVE: This study aimed to develop and validate an automated artificial intelligence (AI)-driven quantification of pleural plaques in a population of retired workers previously occupationally exposed to asbestos. METHODS: CT scans of former workers previously occupationally exposed to asbestos who participated in the multicenter APEXS (Asbestos PostExposure Survey) study were collected retrospectively between 2010 and 2017 during the second and the third rounds of the survey. A hundred and forty-one participants with pleural plaques identified by expert radiologists at the 2nd and the 3rd CT screenings were included. Maximum Intensity Projection (MIP) with 5 mm thickness was used to reduce the number of CT slices for manual delineation. A Deep Learning AI algorithm using 2D-convolutional neural networks was trained with 8280 images from 138 CT scans of 69 participants for the semantic labeling of Pleural Plaques (PP). In all, 2160 CT images from 36 CT scans of 18 participants were used for AI testing versus ground-truth labels (GT). The clinical validity of the method was evaluated longitudinally in 54 participants with pleural plaques. RESULTS: The concordance correlation coefficient (CCC) between AI-driven and GT was almost perfect (>0.98) for the volume extent of both PP and calcified PP. The 2D pixel similarity overlap of AI versus GT was good (DICE = 0.63) for PP, whether they were calcified or not, and very good (DICE = 0.82) for calcified PP. A longitudinal comparison of the volumetric extent of PP showed a significant increase in PP volumes (p < 0.001) between the 2nd and the 3rd CT screenings with an average delay of 5 years. CONCLUSIONS: AI allows a fully automated volumetric quantification of pleural plaques showing volumetric progression of PP over a five-year period. The reproducible PP volume evaluation may enable further investigations for the comprehension of the unclear relationships between pleural plaques and both respiratory function and occurrence of thoracic malignancy.

Adjusting D-dimer to Lung Disease Extent to Exclude Pulmonary Embolism in COVID-19 Patients (Co-LEAD).

OBJECTIVE: D-dimer measurement is a safe tool to exclude pulmonary embolism (PE), but its specificity decreases in coronavirus disease 2019 (COVID-19) patients. Our aim was to derive a new algorithm with a specific D-dimer threshold for COVID-19 patients. METHODS: We conducted a French multicenter, retrospective cohort study among 774 COVID-19 patients with suspected PE. D-dimer threshold adjusted to extent of lung damage found on computed tomography (CT) was derived in a patient set (n = 337), and its safety assessed in an independent validation set (n = 337). RESULTS: According to receiver operating characteristic curves, in the derivation set, D-dimer safely excluded PE, with one false negative, when using a 900 ng/mL threshold when lung damage extent was <50% and 1,700 ng/mL when lung damage extent was ≥50%. In the derivation set, the algorithm sensitivity was 98.2% (95% confidence interval [CI]: 94.7-100.0) and its specificity 28.4% (95% CI: 24.1-32.3). The negative likelihood ratio (NLR) was 0.06 (95% CI: 0.01-0.44) and the area under the curve (AUC) was 0.63 (95% CI: 0.60-0.67). In the validation set, sensitivity and specificity were 96.7% (95% CI: 88.7-99.6) and 39.2% (95% CI: 32.2-46.1), respectively. The NLR was 0.08 (95% CI; 0.02-0.33), and the AUC did not differ from that of the derivation set (0.68, 95% CI: 0.64-0.72, p = 0.097). Using the Co-LEAD algorithm, 76 among 250 (30.4%) COVID-19 patients with suspected PE could have been managed without CT pulmonary angiography (CTPA) and 88 patients would have required two CTs. CONCLUSION: The Co-LEAD algorithm could safely exclude PE, and could reduce the use of CTPA in COVID-19 patients. Further prospective studies need to validate this strategy.

Survival of clinical stage III NSCLC according to therapeutic strategy: Relevance of the tumor board decision in the era of immunotherapy.

INTRODUCTION: Stage III NSCLC comprises a heterogeneous population. Different treatment strategies are available, including surgery, radiotherapy, and chemotherapy. The PACIFIC trial results represented a significant change and improvement in the therapeutic strategy for these patients. We aimed to compare the different treatment strategies employed in Stage III NSCLC patients within our institution. METHODS: All Stage III NSCLC patients discussed during the weekly thoracic oncology multidisciplinary team meetings at the University hospital Grenoble Alpes (France) between January 2010 and January 2017 were included. Patients' overall survival (OS) according to treatment strategies along with their respective changes were compared. RESULTS: Overall, 476 patients were identified. Among patients initially scheduled to receive neoadjuvant chemotherapy followed by surgery (n = 60), only 37 (62%) actually underwent surgery. Median OS of the cohort was 21.3 months [IQR 25%-75%: 9.6-48.3]. Patients who received neoadjuvant chemotherapy followed by surgery displayed better survival than those treated by CT-RT: 53.2 months [IQR 25%-75%: 16.1-87.3] versus 23.9 [IQR 25%-75%, 13.3-48.1]. Survival was slightly superior for patients treated by upfront CT-RT than for those planned for neoadjuvant chemotherapy followed by surgery who eventually converted to CT-RT (concurrent or sequential): 23.9 months [IQR 25%-75%: 13.3-48.1] versus 20.4 [IQR 25%-75%:10.8-36], respectively. CONCLUSION: While patients who underwent neoadjuvant chemotherapy followed by surgery displayed a better survival than those treated using CT-RT, switch from surgery to CT-RT actually shortened survival. These results stress the relevance of the tumor board in deciding which is the best therapeutic strategy for Stage III disease patients.