The crazy-paving pattern: a radiological-pathological correlation. Insights Imaging. 2011;2:117-132. [PMID: 22347941 PMCID: PMC3259383 DOI: 10.1007/s13244-010-0060-5]

Secondary organising pneumonia associated to COVID-19 infection in patients with central nervous system inflammatory demyelinating diseases treated with anti-CD20 therapies

BACKGROUND

Organizing pneumonia (OP), an interstitial lung disease, has been observed in patients with inflammatory demyelinating diseases (IDDs) treated with anti-CD20, particularly after COVID-19, but data are limited.

AIM

To provide a detailed characterization of COVID-19-associated OP in IDD patients treated with anti-CD20.

METHODS

Bi-centric retrospective cohort study including patients with multiple sclerosis (MS), aquaporin-4-positive neuromyelitis optica spectrum disorder (AQP4 + NMOSD), and myelin oligodendrocyte glycoprotein antibody disease (MOGAD) who received anti-CD20 and were diagnosed with COVID-19-associated OP between March 2020 and October 2023.

RESULTS

Nineteen patients were included (mean age 46.8 years; 52.6% female; 63% rituximab, 37% ocrelizumab). Sixteen had MS, two MOGAD, and one AQP4 + NMOSD. Intermittent fever was the predominant symptom. Hospitalization occurred in all but one patient, without fatalities. Chest CT consistently showed OP patterns. Thirteen patients had positive severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) PCR in bronchoalveolar lavage. Treatments included corticosteroids, antivirals, monoclonal antibodies, and convalescent plasma. Fourteen patients postponed infusions; nine resumed post-recovery (median 11.9 months), two switched due to hypogammaglobulinemia, and three stopped. After a mean follow-up of 1.5 years, lung abnormalities and clinical manifestations resolved in 18 patients; however, 13 experienced long-COVID.

CONCLUSIONS

In anti-CD20-treated patients with recurrent fever and distinctive CT features, COVID-19-associated OP should be considered.

The radiologist's role in detecting systemic anticancer therapy-related interstitial lung disease: an educational review

Systemic anticancer therapies (SACTs) are the leading cause of drug-induced interstitial lung disease (ILD). As more novel SACTs become approved, the incidence of this potentially life-threatening adverse event (AE) may increase. Early detection of SACT-related ILD allows for prompt implementation of drug-specific management recommendations, improving the likelihood of AE resolution and, in some instances, widening the patient's eligibility for future cancer treatment options. ILD requires a diagnosis of exclusion through collaboration with the patient's multidisciplinary team to rule out other possible etiologies of new or worsening respiratory signs and symptoms. At Grade 1, ILD is asymptomatic, and thus the radiologist is key to detecting the AE prior to the disease severity worsening. Planned computed tomography scans should be reviewed for the presence of ILD in addition to being assessed for tumor response to treatment, and when ILD is suspected, a high-resolution computed tomography (HRCT) scan should be requested immediately. An HRCT scan, with < 2-mm slice thickness, is the most appropriate method for detecting ILD. Multiple patterns of ILD exist, which can impact patient prognosis. The four main patterns include acute interstitial pneumonia / acute respiratory distress syndrome, organizing pneumonia, hypersensitivity pneumonitis, and non-specific interstitial pneumonia; their distinct radiological features, along with rarer patterns, are discussed here. Furthermore, HRCT is essential for following the course of ILD and might help to determine the intensity of AE management and the appropriateness of re-challenging with SACT, where indicated by drug-specific prescribing information. ILD events should be monitored closely until complete resolution. CRITICAL RELEVANCE STATEMENT: The incidence of potentially treatment-limiting and life-threatening systemic anticancer therapy-related interstitial lung disease (SACT-related ILD) events is likely increasing as more novel regimens become approved. This review provides best-practice recommendations for the early detection of SACT-related ILD by radiologists. KEY POINTS: Radiologists are crucial in detecting asymptomatic (Grade 1) ILD before severity/prognosis worsens. High-resolution computed tomography is the most appropriate method for detecting ILD. Drug-induced ILD is a diagnosis of exclusion, involving a multidisciplinary team. Familiarity with common HRCT patterns, described here, is key for prompt detection. Physicians should highlight systemic anticancer therapies (SACTs) with a known risk for interstitial lung diseases (ILD) on scan requisitions.

Validation of Diagnostic Accuracy and Disease Severity Correlation of Chest Computed Tomography Severity Scores in Patients with COVID-19 Pneumonia

The aim of our study was to establish and compare the diagnostic accuracy and clinical applicability of published chest CT severity scoring systems used for COVID-19 pneumonia assessment and to propose the most efficient CT scoring system with the highest diagnostic performance and the most accurate prediction of disease severity. This retrospective study included 218 patients with PCR-confirmed SARS-CoV-2 infection and chest CT. Two radiologists blindly evaluated CT scans and calculated nine different CT severity scores (CT SSs). The diagnostic validity of CT SSs was tested by ROC analysis. Interobserver agreement was excellent (intraclass correlation coefficient: 0.982-0.995). The predominance of either consolidations or a combination of consolidations and ground-glass opacities (GGOs) was a predictor of more severe disease (both p < 0.005), while GGO prevalence alone was not. Correlation between all CT SSs was high, ranging from 0.848 to 0.971. CT SS 30 had the highest diagnostic accuracy (AUC = 0.805) in discriminating mild from severe COVID-19 disease compared to all the other proposed scoring systems (AUC range 0.755-0.788). In conclusion, CT SS 30 achieved the highest diagnostic accuracy in predicting the severity of COVID-19 disease while maintaining simplicity, reproducibility, and applicability in complex clinical settings.

Stepwise progression of invasive mucinous adenocarcinoma based on radiological and biological characteristics

INTRODUCTION

Invasive mucinous lung adenocarcinoma (IMA) has unique radiological findings and pathological characteristics. IMA is classified into solitary and pneumonic types; however, it is unclear whether these are biologically identical.

METHODS

A single-center retrospective analysis was performed for 70 IMA patients (solitary type [n = 38] and pneumonic type [n = 32]) who underwent pulmonary resection between January 2010 and December 2018. We compared clinical and biological characteristics between the two types.

RESULTS

The frequencies of genetic alternations such as EGFR, KRAS, BRAF, GNAS, ERBB2, TP53, NRG1, and MET were not different. Immunohistochemically, expression of MUC1 was significantly more common in the pneumonic type (5.0% versus 20.0%, p = 0.01) and diffuse MUC6 positive in the solitary type (39.0% versus 13.0%, p = 0.02). We further classified solitary types into those with or without ground-glass opacity (GGO) and pneumonic types into those with or without crazy-paving appearance (CPA), and evaluated their surgical outcomes. Five-year overall survival and relapse free survival rates were 95.8%/86.6%, 64.3%/70.7%, 74.6%/68.9%, and 50.0%/28.6% in patients with solitary type with GGO, solitary type without GGO, pneumonic type without CPA, and pneumonic type with CPA, respectively.

CONCLUSIONS

There were no differences in genetic alternations; however, mucin expression pattern was different. Surgical outcomes were different according to the presence of GGO in the solitary type and the presence of CPA in the pneumonic type. These findings suggested a stepwise progression from solitary to pneumonic IMA.

Automated diagnosis of COVID-19 using radiological modalities and Artificial Intelligence functionalities: A retrospective study based on chest HRCT database

Background and Objective

The spread of coronavirus has been challenging for the healthcare system's proper management and diagnosis during the rapid spread and control of the infection. Real-time reverse transcription-polymerase chain reaction (RT-PCR), though considered the standard testing measure, has low sensitivity and is time-consuming, which restricts the fast screening of individuals. Therefore, computer tomography (CT) is used to complement the traditional approaches and provide fast and effective screening over other diagnostic methods. This work aims to appraise the importance of chest CT findings of COVID-19 and post-COVID in the diagnosis and prognosis of infected patients and to explore the ways and means to integrate CT findings for the development of advanced Artificial Intelligence (AI) tool-based predictive diagnostic techniques.

Methods

The retrospective study includes a 188 patient database with COVID-19 infection confirmed by RT-PCR testing, including post-COVID patients. Patients underwent chest high-resolution computer tomography (HRCT), where the images were evaluated for common COVID-19 findings and involvement of the lung and its lobes based on the coverage region. The radiological modalities analyzed in this study may help the researchers in generating a predictive model based on AI tools for further classification with a high degree of reliability.

Results

Mild to moderate ground glass opacities (GGO) with or without consolidation, crazy paving patterns, and halo signs were common COVID-19 related findings. A CT score is assigned to every patient based on the severity of lung lobe involvement.

Conclusion

Typical multifocal, bilateral, and peripheral distributions of GGO are the main characteristics related to COVID-19 pneumonia. Chest HRCT can be considered a standard method for timely and efficient assessment of disease progression and management severity. With its fusion with AI tools, chest HRCT can be used as a one-stop platform for radiological investigation and automated diagnosis system.

Regional ventilation in spontaneously breathing COVID-19 patients during postural maneuvers assessed by electrical impedance tomography

BACKGROUND

Gravity-dependent positioning therapy is an established concept in the treatment of severe acute respiratory distress syndrome and improves oxygenation in spontaneously breathing patients with hypoxemic acute respiratory failure. In patients with coronavirus disease 2019, this therapy seems to be less effective. Electrical impedance tomography as a point-of-care functional imaging modality for visualizing regional ventilation can possibly help identify patients who might benefit from positioning therapy and guide those maneuvers in real-time. Therefore, in this prospective observational study, we aimed to discover typical patterns in response to positioning maneuvers.

METHODS

Distribution of ventilation in 10 healthy volunteers and in 12 patients with hypoxemic respiratory failure due to coronavirus disease 2019 was measured in supine, left, and right lateral positions using electrical impedance tomography.

RESULTS

In this study, patients with coronavirus disease 2019 showed a variety of ventilation patterns, which were not predictable, whereas all but one healthy volunteer showed a typical and expected gravity-dependent distribution of ventilation with the body positions.

CONCLUSION

Distribution of ventilation and response to lateral positioning is variable and thus unpredictable in spontaneously breathing patients with coronavirus disease 2019. Electrical impedance tomography might add useful information on the immediate reaction to postural maneuvers and should be elucidated further in clinical studies. Therefore, we suggest a customized individualized positioning therapy guided by electrical impedance tomography.

The diagnosis of leptospirosis complicated by pulmonary tuberculosis complemented by metagenomic next-generation sequencing: A case report

Leptospirosis is a zoonotic infection caused by the pathogenic Leptospira. Leptospirosis is transmitted mainly through contact with contaminated rivers, lakes, or animals carrying Leptospira. Human leptospirosis has a wide range of non-specific clinical manifestations ranging from fever, hypotension, and myalgia to multi-organ dysfunction, which severely hampers the timely clinical diagnosis and treatment of leptospirosis. Therefore, there is an urgent clinical need for an efficient strategy/method that can be used for the accurate diagnosis of leptospirosis, especially in critically ill patients. Here, we report a case of a 75-year-old male patient with clinical presentation of fever, cough, and diarrhea. Initial laboratory tests and a computed tomography (CT) scan of the chest suggested only tuberculosis. The patient was finally diagnosed with pulmonary tuberculosis (PTB) combined with leptospirosis by sputum Xpert MTB RIF, epidemiological investigations, and delayed serological testing. Furthermore, through metagenomic next-generation sequencing (mNGS) of clinical samples of cerebrospinal fluid (CSF), urine, plasma and sputum, the causative pathogens were identified as Mycobacterium tuberculosis complex and Leptospira spp. With specific treatment for both leptospirosis and tuberculosis, and associated supportive care (e.g., hemodialysis), the patient showed a good prognosis. This case report suggests that mNGS can generate a useful complement to conventional pathogenic diagnostic methods through more detailed etiological screening (i.e., at the level of species or species complex).

Multicenter Study on COVID-19 Lung Computed Tomography Segmentation with varying Glass Ground Opacities using Unseen Deep Learning Artificial Intelligence Paradigms: COVLIAS 1.0 Validation

Variations in COVID-19 lesions such as glass ground opacities (GGO), consolidations, and crazy paving can compromise the ability of solo-deep learning (SDL) or hybrid-deep learning (HDL) artificial intelligence (AI) models in predicting automated COVID-19 lung segmentation in Computed Tomography (CT) from unseen data leading to poor clinical manifestations. As the first study of its kind, “COVLIAS 1.0-Unseen” proves two hypotheses, (i) contrast adjustment is vital for AI, and (ii) HDL is superior to SDL. In a multicenter study, 10,000 CT slices were collected from 72 Italian (ITA) patients with low-GGO, and 80 Croatian (CRO) patients with high-GGO. Hounsfield Units (HU) were automatically adjusted to train the AI models and predict from test data, leading to four combinations—two Unseen sets: (i) train-CRO:test-ITA, (ii) train-ITA:test-CRO, and two Seen sets: (iii) train-CRO:test-CRO, (iv) train-ITA:test-ITA. COVILAS used three SDL models: PSPNet, SegNet, UNet and six HDL models: VGG-PSPNet, VGG-SegNet, VGG-UNet, ResNet-PSPNet, ResNet-SegNet, and ResNet-UNet. Two trained, blinded senior radiologists conducted ground truth annotations. Five types of performance metrics were used to validate COVLIAS 1.0-Unseen which was further benchmarked against MedSeg, an open-source web-based system. After HU adjustment for DS and JI, HDL (Unseen AI) > SDL (Unseen AI) by 4% and 5%, respectively. For CC, HDL (Unseen AI) > SDL (Unseen AI) by 6%. The COVLIAS-MedSeg difference was < 5%, meeting regulatory guidelines.Unseen AI was successfully demonstrated using automated HU adjustment. HDL was found to be superior to SDL.

Eight pruning deep learning models for low storage and high-speed COVID-19 computed tomography lung segmentation and heatmap-based lesion localization: A multicenter study using COVLIAS 2.0

BACKGROUND

COVLIAS 1.0: an automated lung segmentation was designed for COVID-19 diagnosis. It has issues related to storage space and speed. This study shows that COVLIAS 2.0 uses pruned AI (PAI) networks for improving both storage and speed, wiliest high performance on lung segmentation and lesion localization.

METHOD

ology: The proposed study uses multicenter ∼9,000 CT slices from two different nations, namely, CroMed from Croatia (80 patients, experimental data), and NovMed from Italy (72 patients, validation data). We hypothesize that by using pruning and evolutionary optimization algorithms, the size of the AI models can be reduced significantly, ensuring optimal performance. Eight different pruning techniques (i) differential evolution (DE), (ii) genetic algorithm (GA), (iii) particle swarm optimization algorithm (PSO), and (iv) whale optimization algorithm (WO) in two deep learning frameworks (i) Fully connected network (FCN) and (ii) SegNet were designed. COVLIAS 2.0 was validated using "Unseen NovMed" and benchmarked against MedSeg. Statistical tests for stability and reliability were also conducted.

RESULTS

Pruning algorithms (i) FCN-DE, (ii) FCN-GA, (iii) FCN-PSO, and (iv) FCN-WO showed improvement in storage by 92.4%, 95.3%, 98.7%, and 99.8% respectively when compared against solo FCN, and (v) SegNet-DE, (vi) SegNet-GA, (vii) SegNet-PSO, and (viii) SegNet-WO showed improvement by 97.1%, 97.9%, 98.8%, and 99.2% respectively when compared against solo SegNet. AUC > 0.94 (p < 0.0001) on CroMed and > 0.86 (p < 0.0001) on NovMed data set for all eight EA model. PAI <0.25 s per image. DenseNet-121-based Grad-CAM heatmaps showed validation on glass ground opacity lesions.

CONCLUSIONS

Eight PAI networks that were successfully validated are five times faster, storage efficient, and could be used in clinical settings.

Radiological Finding of Crazy-Paving Pattern in COVID-19 Pneumonia

The recent global pandemic of coronavirus disease 2019 (COVID-19) has brought many radiographic findings in other respiratory disease processes. One of these radiological findings is crazy paving. This paper discusses crazy paving in a 75-year-old female with dyspnea, nonproductive cough, pleuritic chest pain, and a polymerase chain reaction (PCR) positive test for COVID-19 infection. Chest CT showed ground-glass opacities and interlobular septal thickening consistent with a crazy-paving appearance. As part of the common CT findings of patients with active COVID-19 infection, crazy paving should prompt the interpreting radiologist to consider COVID-19 pneumonia as part of the differential.

COVLIAS 2.0-cXAI: Cloud-Based Explainable Deep Learning System for COVID-19 Lesion Localization in Computed Tomography Scans

Background: The previous COVID-19 lung diagnosis system lacks both scientific validation and the role of explainable artificial intelligence (AI) for understanding lesion localization. This study presents a cloud-based explainable AI, the “COVLIAS 2.0-cXAI” system using four kinds of class activation maps (CAM) models. Methodology: Our cohort consisted of ~6000 CT slices from two sources (Croatia, 80 COVID-19 patients and Italy, 15 control patients). COVLIAS 2.0-cXAI design consisted of three stages: (i) automated lung segmentation using hybrid deep learning ResNet-UNet model by automatic adjustment of Hounsfield units, hyperparameter optimization, and parallel and distributed training, (ii) classification using three kinds of DenseNet (DN) models (DN-121, DN-169, DN-201), and (iii) validation using four kinds of CAM visualization techniques: gradient-weighted class activation mapping (Grad-CAM), Grad-CAM++, score-weighted CAM (Score-CAM), and FasterScore-CAM. The COVLIAS 2.0-cXAI was validated by three trained senior radiologists for its stability and reliability. The Friedman test was also performed on the scores of the three radiologists. Results: The ResNet-UNet segmentation model resulted in dice similarity of 0.96, Jaccard index of 0.93, a correlation coefficient of 0.99, with a figure-of-merit of 95.99%, while the classifier accuracies for the three DN nets (DN-121, DN-169, and DN-201) were 98%, 98%, and 99% with a loss of ~0.003, ~0.0025, and ~0.002 using 50 epochs, respectively. The mean AUC for all three DN models was 0.99 (p < 0.0001). The COVLIAS 2.0-cXAI showed 80% scans for mean alignment index (MAI) between heatmaps and gold standard, a score of four out of five, establishing the system for clinical settings. Conclusions: The COVLIAS 2.0-cXAI successfully showed a cloud-based explainable AI system for lesion localization in lung CT scans.

Unusual Diffuse Ground-Glass Opacities in the Lungs on 18F-FDG PET/CT: A Case of Melanoma With Pulmonary Metastasis

ABSTRACT

A 61-year-old man was diagnosed with a malignant melanoma and underwent a resection; he presented with progressive dyspnea after treatment with interferon for 2 months. 18F-FDG PET/CT scan revealed diffuse ground-glass opacities (GGOs) in both lungs with mildly elevated 18F-FDG uptake, similar to that observed with interstitial inflammation. However, a lung biopsy confirmed that the diffuse GGOs were pulmonary metastases of melanoma and were positive for the BRAF mutation. The diffuse GGOs and the progressive dyspnea disappeared after BRAF-targeted therapy. This represents an unusual case of lung metastases from melanoma, mistakenly interpreted as lung inflammation induced by immunotherapy.

Crazy vaping and crazy-paving, a case of E-Cigarette/Vaping-Associated Lung Injury (EVALI) with chest CT showing crazy-paving pattern

E-cigarettes are devices that generate an aerosol by heating a fluid containing multiple chemicals, such as nicotine, additives, and flavorings. They were developed to aid in smoking cessation and were promoted as socially acceptable, healthier, cheaper than conventional cigarettes. Multiple lung disorders related to e-cigarette use are reported, and they range from mild cases of pneumonitis to life-threatening lung disorders that may require intubation and mechanical ventilation. Most of the complications are due to the generation of various unknown and potentially harmful chemicals within the aerosol generated in the e-cigarette. These disorders are known collectively as e-cigarette/Vaping-associated lung injury (EVALI). E-cigarettes are marketed as safer alternatives to traditional cigarettes, with the highest rates of use are noted in young smokers. Given the significant prevalence of e-cigarettes use and their pulmonary complications, EVALI should be considered a potential etiology in the broad differential diagnosis of patients with pulmonary disease and a history of vaping. Herein, we present a case of cryptogenic organizing pneumonia with a chest C.T. showing a crazy-paving pattern in a patient with a history of vaping.

Risk Factors of In-Hospital Mortality in Non-Specialized Tertiary Center Repurposed for Medical Care to COVID-19 Patients in Russia

The purpose of our study is to investigate the risk factors of in-hospital mortality among patients who were admitted in an emergency setting to a non-specialized tertiary center during the first peak of coronavirus disease in Moscow in 2020. The Federal Center of Brain and Neurotechnologies of the Federal Medical and Biological Agency of Russia was repurposed for medical care for COVID-19 patients from 6th of April to 16th of June 2020 and admitted the patients who were transported by an ambulance with severe disease. In our study, we analyzed the data of 635 hospitalized patients aged 59.1 ± 15.1 years. The data included epidemiologic and demographic characteristics, laboratory, echocardiographic and radiographic findings, comorbidities, and complications of the COVID-19, developed during the hospital stay. Results of our study support previous reports that risk factors of mortality among hospitalized patients are older age, male gender (OR 1.91, 95% CI 1.03–3.52), previous myocardial infarction (OR 3.15, 95% CI 1.47–6.73), previous acute cerebrovascular event (stroke, OR = 3.78, 95% CI 1.44–9.92), known oncological disease (OR = 3.39, 95% CI 1.39–8.26), and alcohol abuse (OR 6.98, 95% CI 1.62–30.13). According to the data collected, high body mass index and smoking did not influence the clinical outcome. Arterial hypertension was found to be protective against in-hospital mortality in patients with coronavirus pneumonia in the older age group. The neutrophil-to-lymphocyte ratio showed a significant increase in those patients who died during the hospitalization, and the borderline was found to be 2.5. CT pattern of “crazy paving” was more prevalent in those patients who died since their first CT scan, and it was a 4-fold increase in the risk of death in case of aortic and coronal calcinosis (4.22, 95% CI 2.13–8.40). Results largely support data from other studies and emphasize that some factors play a major role in patients’ stratification and medical care provided to them.

SARS-CoV-2 diagnosis using medical imaging techniques and artificial intelligence: A review

OBJECTIVE

SARS-CoV-2 is a worldwide health emergency with unrecognized clinical features. This paper aims to review the most recent medical imaging techniques used for the diagnosis of SARS-CoV-2 and their potential contributions to attenuate the pandemic. Recent researches, including artificial intelligence tools, will be described.

METHODS

We review the main clinical features of SARS-CoV-2 revealed by different medical imaging techniques. First, we present the clinical findings of each technique. Then, we describe several artificial intelligence approaches introduced for the SARS-CoV-2 diagnosis.

RESULTS

CT is the most accurate diagnostic modality of SARS-CoV-2. Additionally, ground-glass opacities and consolidation are the most common signs of SARS-CoV-2 in CT images. However, other findings such as reticular pattern, and crazy paving could be observed. We also found that pleural effusion and pneumothorax features are less common in SARS-CoV-2. According to the literature, the B lines artifacts and pleural line irregularities are the common signs of SARS-CoV-2 in ultrasound images. We have also stated the different studies, focusing on artificial intelligence tools, to evaluate the SARS-CoV-2 severity. We found that most of the reported works based on deep learning focused on the detection of SARS-CoV-2 from medical images while the challenge for the radiologists is how to differentiate between SARS-CoV-2 and other viral infections with the same clinical features.

CONCLUSION

The identification of SARS-CoV-2 manifestations on medical images is a key step in radiological workflow for the diagnosis of the virus and could be useful for researchers working on computer-aided diagnosis of pulmonary infections.

The Crazy-Paving Pattern in Chest CT Imaging of COVID-19 Patients: An Alarming Sign for Hospitalization

Background: The outbreak of coronavirus disease 2019 (COVID-19) has become a major threat to all humans. Objectives: To assess the association between the patients’ clinical and laboratory records, computed tomography (CT) findings, and epidemiological features of COVID-19 with the severity of the disease. Patients and Methods: In this retrospective case-control study conducted on the medical records of confirmed COVID-19 pneumonia patients on admission, we investigated the CT manifestations and clinical and laboratory risk factors for progression to severe COVID-19 pneumonia. The medical records and radiological CT features of confirmed COVID-19 patients were reviewed in one public hospital and one respiratory clinic in Qom, Iran, from August 1 to September 30, 2020. Results: Of 236 confirmed COVID-19 cases, 62 were infected with moderate to severe COVID-19 and required hospital admission, and 174 were followed-up on an outpatient basis. A significant difference was found in the mean age of the outpatient and hospitalized groups. The incidence of bilateral lung involvement, consolidations, linear opacities, crazy-paving pattern, air bronchogram, and number of lobes involved were significantly higher in the hospitalized group compared to the outpatient group. However, the crazy-paving pattern was only significantly associated with an oxygen saturation (SpO2) level < 90% and, coughing. Our findings indicated that the crazy-paving pattern was significantly associated with the inflammatory phase. The presence of this pattern on admission, SpO2 < 90%, older age, and diabetes were independent risk factors for progression to severe COVID-19. Conclusion: The crazy-paving pattern can predict the severity of COVID-19, which is of great importance in the management and follow-up of COVID-19 pneumonia patients. Clinical factors, such as aging, male gender, and diabetes, may be risk factors for the crazy-paving pattern. Severe cough is the most important clinical sign related to this pattern, along with an SpO2 < 90%, which is an important sign of COVID-19 severity.

Evaluation of initial chest computed tomography (CT) findings of COVID-19 pneumonia in 117 deceased patients: a retrospective study

Background/aim

There is no study in the literature in which only chest computed tomography (CT) findings of deceased cases obtained at admission were examined, and the relationship between these findings and mortality was evaluated.

Materials and methods

In this retrospective study, a total of 117 deceased patients with COVID-19 infection confirmed by positive polymerase chain reaction and undergone chest CT were enrolled. We evaluated initial chest CT findings and their relationship, location, prevalence, and the frequency with mortality.

Results

The mean age of patients was 73 ±18 years; 71 of all patients were male and 46 were female. The predominant feature was pure ground-glass opacity (GGO) lesion (82.0%), and 59.8% of cases had pure consolidation. There was no cavitation or architectural distorsion. Pericardial effusion was found in 9.4% the patients, and pleural effusions were found in 15.3% of them. Mediastinal lymphadenopathy was only 11.9% in total.

Conclusion

In deceased patients, on admission CTs, pure consolidation, pleural and pericardial effusion, mediastinal LAP were more common than ordinary cases. It was these findings that should also raise the concern when they were seen on chest CT; therefore, these radiologic features have the potential to represent prognostic imaging markers in patients with COVID-19 pneumonia.

Chest CT Imaging Characteristics of COVID-19 Pneumonia in Surviving and Non-surviving Hospitalized Patients: A Retrospective Study in a Referral Center in Tehran, Iran

Background: Coronavirus disease 2019 (COVID-19) has several chest computed tomography (CT) characteristics, which are important for the early management of this disease, because viral detection via RT-PCR can be time-consuming, resulting in a delayed pneumonia diagnosis. The Radiological Society of North America (RSNA) proposed a reporting language for CT findings related to COVID-19 and defined four CT categories: typical, indeterminate, atypical, and negative. Objectives: To retrospectively evaluate the chest CT characteristics of patients with COVID-19 pneumonia. Patients and Methods: A total of 115 hospitalized laboratory-verified COVID-19 cases, underdoing chest CT scan, were included in this study from April 30 to May 15, 2020. Of 115 cases, 53 were discharged from the hospital, and 62 expired. The initial clinical features and chest CT scans were assessed for the type, pattern, distribution, and frequency of lesions. Moreover, the findings were compared between ward-hospitalized, intensive care unit (ICU)-admitted, and non-surviving (expired) patients. Results: Of four CT categories, typical CT findings for COVID-19 were more frequent in the expired group (77.4%), compared to the ward-admitted (44.8%) and ICU-admitted (70.8%) groups (P = 0.017). However, no significant difference was observed in the prevalence of intermediate or atypical CT findings between the groups. Negative CT scans for the diagnosis of COVID-19 were significantly fewer in the expired group (0%) as compared to the ward-admitted (10.3%) and ICU-admitted (8.3%) groups (P = 0.0180). Also, the mean number of involved lung lobes and segments was significantly higher in the expired group compared to the other two groups (P = 0.032 and 0.010, respectively). The right upper lobe involvement, right middle lobe involvement, bilateral involvement, central lesion, air bronchogram, and pleural effusion were among CT scan findings with a significantly higher prevalence in non-surviving cases (P < 0.0001, 0.047, 0.01, 0.036, 0.038, and 0.047, respectively). Conclusion: The increased number of involved lung lobes and segments, bilateral and central distribution patterns, air bronchogram, and severe pleural effusion in the initial chest CT scan can be related to the increased severity and poor prognosis of COVID-19.

Comparing Lung CT in COVID-19 Pneumonia and Acute Heart Failure: An Imaging Conundrum

Background Chest computed tomography (CT) provides an effective modality to evaluate patients with suspected coronavirus disease 2019 (COVID-19). However, overlapping imaging findings with cardiogenic pulmonary edema is not uncommon. Reports comparing the chest CT features of these diseases have not been elaborated. Thus, we aimed to show the difference between the low-dose lung CT findings of COVID-19 pneumonia and comparing them to those with acute heart failure (HF). Methods This retrospective analysis enrolled hospitalized patients with COVID-19 (n=10) and acute heart failure (n=9) that exclusively underwent low-dose chest CT scans within 24 hours of admission. Clinical and lung CT characteristics were collected and analyzed. Results The appearance of ground-glass-opacities (GGOs) has been recorded in all individuals in the HF and COVID-19 groups. There was no significant statistical difference between the two groups for rounded morphology, consolidation, crazy paving pattern, lesion distribution, and parenchymal band (P> 0.05). However, diffuse lesions were more frequent in HF cases (55.6% vs. 0%) than in COVID-19 pneumonia, which had a predominantly multifocal pattern. Notably, CT images in HF patients were more likely to have signs of interstitial tissue thickening, such as the interlobular septums, fissures, and peribronchovascular interstitium (55.6% vs 0%, 88.9% vs 20% and 44.4% vs 0%, respectively), as well as cardiomegaly (77.8% vs 0%), increased artery to bronchus ratio (55.6% vs 0%), and pleural effusions (77.8% vs 0%). Conclusions Major overlaps of lung CT imaging features existed between COVID-19 pneumonia and acute HF cases. However, signs of fluid redistribution are clues that favor HF over COVID-19 pneumonia.

Quantitative assessment of lung involvement on chest CT at admission: Impact on hypoxia and outcome in COVID-19 patients

BACKGROUND

The aim of this study was to quantify COVID-19 pneumonia features using CT performed at time of admission to emergency department in order to predict patients' hypoxia during the hospitalization and outcome.

METHODS

Consecutive chest CT performed in the emergency department between March 1st and April 7th 2020 for COVID-19 pneumonia were analyzed. The three features of pneumonia (GGO, semi-consolidation and consolidation) and the percentage of well-aerated lung were quantified using a HU threshold based software. ROC curves identified the optimal cut-off values of CT parameters to predict hypoxia worsening and hospital discharge. Multiple Cox proportional hazards regression was used to analyze the capability of CT quantitative features, demographic and clinical variables to predict the time to hospital discharge.

RESULTS

Seventy-seven patients (median age 56-years-old, 51 men) with COVID-19 pneumonia at CT were enrolled. The quantitative features of COVID-19 pneumonia were not associated to age, sex and time-from-symptoms onset, whereas higher number of comorbidities was correlated to lower well-aerated parenchyma ratio (rho = -0.234, p = 0.04) and increased semi-consolidation ratio (rho = -0.303, p = 0.008). Well-aerated lung (≤57%), semi-consolidation (≥17%) and consolidation (≥9%) predicted worst hypoxemia during hospitalization, with moderate areas under curves (AUC 0.76, 0.75, 0.77, respectively). Multiple Cox regression identified younger age (p < 0.01), female sex (p < 0.001), longer time-from-symptoms onset (p = 0.049), semi-consolidation ≤17% (p < 0.01) and consolidation ≤13% (p = 0.03) as independent predictors of shorter time to hospital discharge.

CONCLUSION

Quantification of pneumonia features on admitting chest CT predicted hypoxia worsening during hospitalization and time to hospital discharge in COVID-19 patients.

Mild dyspnea presenting as 'crazy-paving' on chest computed tomography

Pulmonary alveolar proteinoisis (PAP) is a rare disease characterized by accumulation of proteinaceous material in the alveolar spaces. Here, we report a case of mild dyspnea with incidental ‘crazy-paving’ pattern on chest computed tomography (CT). Further evaluation and bronchoscopy found to have PAP.

Crazy-paving patterns as rare radiological manifestations of pulmonary cryptococcosis: a case report

Background

Crazy-paving patterns are rarely reported as radiological manifestations of pulmonary cryptococcosis.

Case presentation

Herein, we presented a very rare case of a crazy-paving pattern as a radiological manifestation of pulmonary cryptococcosis in a patient with primary ciliary dyskinesia. The diagnosis of pulmonary cryptococcosis and primary ciliary dyskinesia was ultimately confirmed by bronchoscopic biopsy, fungus culture, whole exome sequencing of blood, etc. The patient received flucytosine (PO, 5 g per day) and amphotericin B (IV, 70 mg per day) during hospitalization and sequential therapy with voriconazole (PO, 200 mg twice a day) after discharge. He recovered during follow-up.

Conclusions

We concluded that pulmonary cryptococcosis should be considered a possible cause of crazy-paving patterns in chest CT scans.

When pneumonia is not COVID-19

During the COVID-19 epidemic, the prevalence of the disease means that practically any lung opacity on an X-ray could represent pneumonia due to infection with SARS-CoV-2. Nevertheless, atypical radiologic findings add weight to negative microbiological or serological tests. Likewise, outside the epidemic wave and with the return of other respiratory diseases, radiologists can play an important role in decision making about diagnoses, treatment, or preventive measures (isolation), provided they know the key findings for entities that can simulate COVID-19 pneumonia. Unifocal opacities or opacities located in upper lung fields and predominant airway involvement, in addition to other key radiologic and clinical findings detailed in this paper, make it necessary to widen the spectrum of possible diagnoses.

When pneumonia is not COVID-19

During the COVID-19 epidemic, the prevalence of the disease means that practically any lung opacity on an X-ray could represent pneumonia due to infection with SARS-CoV-2. Nevertheless, atypical radiologic findings add weight to negative microbiological or serological tests. Likewise, outside the epidemic wave and with the return of other respiratory diseases, radiologists can play an important role in decision making about diagnoses, treatment, or preventive measures (isolation), provided they know the key findings for entities that can simulate COVID-19 pneumonia. Unifocal opacities or opacities located in upper lung fields and predominant airway involvement, in addition to other key radiologic and clinical findings detailed in this paper, make it necessary to widen the spectrum of possible diagnoses.

Dandelion and focal crazy paving signs: the lung CT based predictors for evaluation of the severity of coronavirus disease

PURPOSE

To describe the radiological features of coronavirus disease 19 (COVID-19) and to explore the significant signs that indicate severity of disease.

MATERIALS AND METHODS

We collected data retrospectively of 180 cases of COVID-19, from 15 January 2020 to 31 March 2020, from both the Wuhan Zhongnan and Beijing Ditan Hospitals, including 103 cases of mild and 77 cases of severe pneumonia. All patients had their first chest computed tomography scan within five days of symptom onset. The dandelion sign was defined by a focal ground glass opacity (GGO) with a central thickening of the airway wall, and the focal crazy paving sign was defined by a focal GGO with thickening of the interlobular septa.

RESULTS

Consolidation presented in only 4.9% (5/103) of the mild pneumonia cases, which was significantly lower than that in severe pneumonia cases (70.1% 54/77), p < .001). Multifocal distribution and pure GGOs were observed more frequently in severe cases of pneumonia (p < .05). The dandelion sign was present in 86.4% (89/103) of the mild pneumonia cases, significantly more frequent than those with severe pneumonia (13.0% [10/77], p < .001). The focal crazy paving sign presented in 65.0% (67/103) of the mild pneumonia cases and was significantly more frequent than in severe cases (23.4% [18/77], p < .001). The hospital stay duration of the mild pneumonia group (13.6 ± 7.2 days) was significantly shorter than the severe pneumonia group (26.6 ± 11.7 days, p < .001).

CONCLUSIONS

Consolidation, pure GGO and multifocal distribution on a CT scan were associated with severe COVID-19. The dandelion and focal crazy paving signs indicate mild COVID-19.

A 16-Year-Old Boy With Cough and Fever in the Era of COVID-19

A 16-year-old white boy with a history of chronic lung disease of prematurity, cough-variant asthma, and incidental lung nodules presented to the emergency center in spring 2020 with acute onset dry cough, shortness of breath, and fever. An initial history, gathered from his mother because of the patient's respiratory distress, revealed no recent travel. However, his mother is a health care worker at a hospital, and sick contacts included ongoing contact with a friend with cold-like symptoms. He had a variety of animals at home, including a dog, cats, fish, rodents, and reptiles. He had a history of vaping tobacco products >6 months ago. Fever and respiratory symptoms were associated with fatigue, chest tightness, abdominal pain, and myalgias. On examination, he was ill appearing and had tachycardia, tachypnea, borderline hypoxia with an oxygen saturation of 91% on room air, diminished breath sounds at the lung bases, and unremarkable abdominal examination results. A chest radiograph was consistent with the lung examination, revealing bilateral lower lobe hazy infiltrates. He showed initial improvement for 48 hours with antibiotics, intravenous fluid resuscitation, oxygen via nasal cannula, albuterol, and prednisone. Subsequently, he worsened with persistent high fever, increasing respiratory distress with pulmonary findings, and severe persistent epigastric pain, which added a layer of diagnostic complexity. As this patient's clinical course evolved and further history became available, pulmonary medicine and infectious diseases services were consulted to guide diagnostic evaluation and treatment of this patient early in the era of coronavirus disease 2019.

Morphological patterns and distributions in portable chest radiographs of COVID-19-positive cases admitted to a tertiary care hospital: An early experience from Scandinavia

INTRODUCTION

Chest radiographic (CXR) features, particularly portable CXR findings, of COVID-19 have not yet been systematically described, either as a baseline tool or as a follow-up method, despite the continuing global pandemic. There is a marked paucity of articles detailing the CXR findings vis-à-vis a multitude of articles dedicated to the CT features of COVID-19. The purpose of this article is to describe the morphological and distributional patterns of the lung opacities in CXR and to classify the spectrum of essential features on portable AP chest radiographs of PCR-positive COVID-19 patients admitted in a tertiary care hospital in Scandinavia. To our knowledge, this is the first article to describe the morphological and topographical features of CXRs in COVID-19-positive cases.

METHODS

A retrospective analysis of twenty (20) RT-PCR-positive COVID-19 patients admitted to the hospital between 12.03.2020 to 10.04.2020 was done in this study. Morphology and distribution of the opacities were reviewed by two senior consultants and analysed for patterns.

RESULTS

Most patients had ground-glass opacities (80-85%) and interspersed interstitial opacities (70-75%), often with a characteristic appearance. The opacities were mostly bilateral (80%) and distributed in the lower zones (and to some extent mid zones) and in the middle and peripheral regions, with a tendency to merge towards the hilar areas. There were high interobserver agreements among various parameters and no significant statistical difference between observer 1 and 2.

CONCLUSION

Chest radiographics show characteristic patterns and distributions, which can be used as an adjunct in the diagnosis and follow-up of COVID-19 patients in specific clinical contexts.

Radiation-induced lung toxicity - cellular and molecular mechanisms of pathogenesis, management, and literature review

Lung, breast, and esophageal cancer represent three common malignancies with high incidence and mortality worldwide. The management of these tumors critically relies on radiotherapy as a major part of multi-modality care, and treatment-related toxicities, such as radiation-induced pneumonitis and/or lung fibrosis, are important dose limiting factors with direct impact on patient outcomes and quality of life. In this review, we summarize the current understanding of radiation-induced pneumonitis and pulmonary fibrosis, present predictive factors as well as recent diagnostic and therapeutic advances. Novel candidates for molecularly targeted approaches to prevent and/or treat radiation-induced pneumonitis and pulmonary fibrosis are discussed.

Can CT performed in the early disease phase predict outcome of patients with COVID 19 pneumonia? Analysis of a cohort of 64 patients from Germany

PURPOSE

The aim of this study was to investigate if CT performed in the early disease phase can predict the course of COVID-19 pneumonia in a German cohort.

METHOD

All patients with RT-PCR proven COVID-19 pneumonia and chest CT performed within 10 days of symptom onset between March 1st and April 15th 2020 were retrospectively identified from two tertiary care hospitals. 12 CT features, their distribution in the lung and the global extent of opacifications were evaluated. For analysis of prognosis two compound outcomes were defined: positive outcome was defined as either discharge or regular ward care; negative outcome was defined as need for mechanical ventilation, treatment on intensive care unit, extracorporeal membrane oxygenation or death. Follow-up was performed until June 19th. For statistical analysis uni- und multivariable logistic regression models were calculated.

RESULTS

64 patients were included in the study. By univariable analysis the following parameters predicted a negative outcome: consolidation (p = 0.034), crazy paving (p = 0.004), geographic shape of opacification (p = 0.022), dilatation of bronchi (p = 0.002), air bronchogram (p = 0.013), vessel enlargement (p = 0.014), pleural effusion (p = 0.05), bilateral disease (p = 0.004), involvement of the upper lobes (p = 0.004, p = 0.015) or the right middle lobe (p < 0.001) and severe extent of opacifications (p = 0.002). Multivariable analysis revealed crazy paving and severe extent of parenchymal involvement to be independently predictive for a poor outcome.

CONCLUSIONS

Easy to assess CT features in the early phase of disease independently predicted an adverse outcome of patients with COVID-19 pneumonia.

Alveolar proteinosis due to toxic inhalation at workplace

We report a clinical case of a 39-year old male, without any known previous medical condition but with occupational exposure to paints and dust cement, who presented an autoimmune pulmonary alveolar proteinosis (PAP) triggered by exposure to toxic inhalation at his workplace. PAP is a rare lung disease characterized by intra-alveolar abnormal accumulation of surfactant. The presence of a crazy-paving pattern in high-resolution computed tomography scan brings the suspicion of PAP although histopathology results of bronchoalveolar lavage are always required for its final diagnosis. The autoimmune form of PAP due to toxic inhalation, such as the one here described, is rare and it is usually difficult to establish a causal relationship.

Typical and atypical COVID-19 computed tomography findings

In December 2019 a novel coronavirus, named severe acute respiratory syndrome coronavirus 2 was identified and the disease associated was named coronavirus disease 2019 (COVID-19). Fever, cough, myalgia, fatigue associated to dyspnea represent most common clinical symptoms of the disease. The reference standard for diagnosis of severe acute respiratory syndrome coronavirus 2 infection is real time reverse-transcription polymerase chain reaction test applied on respiratory tract specimens. Despite of lower specificity, chest computed tomography (CT), as reported in manifold scientific studies, showed high sensitivity, therefore it may help in the early detection, management and follow-up of COVID-19 pneumonia. Patients affected by COVID-19 pneumonia usually showed on chest CT some typical features, such as: Bilateral ground glass opacities characterized by multilobe involvement with posterior and peripheral distribution; parenchymal consolidations with or without air bronchogram; interlobular septal thickening; crazy paving pattern, represented by interlobular and intralobular septal thickening surrounded by ground-glass opacities; subsegmental pulmonary vessels enlargement (> 3 mm). Halo sign, reversed halo sign, cavitation and pleural or pericardial effusion represent some of atypical findings of COVID-19 pneumonia. On the other hand lymphadenopathy's and bronchiectasis' frequency is unclear, indeed conflicting data emerged in literature. Radiologists play a key role in recognition of high suspicious findings of COVID-19 on chest CT, both typical and atypical ones. Thus, the aim of this review is to illustrate typical and atypical CT findings of COVID-19.

Pulmonary Alveolar Proteinosis in Hereditary and Autoimmune Forms With 2 Cases

Pulmonary alveolar proteinosis (PAP) is a respiratory pathology characterized by the accumulation and increase of surfactant-derived material in the lungs. In clinical practice, PAP may present as the primary form, which includes autoimmune and hereditary PAP, or as the secondary form. Diffuse alveolar radiopacities on chest x-ray and the crazy-paving pattern on high-resolution computed tomography are important, although not specific findings for PAP. Bronchoalveolar lavage biopsy is a diagnostic method, and whole-lung lavage remains the criterion standard for the treatment of PAP. Evidence is required regarding treatment with exogenous anti-granulocyte/macrophage colony-stimulating factor.Here, we present a 13-year-old male patient with hereditary PAP and a 15-year-old female patient with autoimmune PAP who presented with complaints of easy fatigability and weakness to emphasize the importance of keeping in mind PAP as a differential diagnosis in patients with respiratory failure findings.

Cryptogenic Organizing Pneumonia: Evolution of Morphological Patterns Assessed by HRCT

To evaluate the radiological findings in patients with cryptogenic organizing pneumonia (COP) before steroid treatment and their behavior after therapy, we retrospectively evaluated a total of 22 patients with a diagnosis of COP made by bronchoalveolar lavage (BAL), biopsy or clinical/radiological features, and the patients were followed between 2014 and 2018 at the hospital; the demographic data, symptoms, radiologic findings, diagnostic methods and treatment plans of patients were collected from patients’ hospital records. At least two CT scans of 22 patients (16 female and six men) were evaluated, the first one before starting steroid therapy and the others after therapy. At baseline CT scans, the most common radiological finding was the presence of consolidations (18/22 patients, 81.8%); ground-glass opacities were also very common (15/25, 68.1%). The other findings were as follows: nodules and masses (5/22, 22.7%), atoll sign (4/22, 18.1%), perilobular pattern (3/22, 13.6%) and parenchymal bands (3/22, 13.6%). Two patients had a significant relapse after reducing/interrupting therapy, while three had a complete resolution and are not currently under therapy (maintenance of clinical remission with no oral corticosteroid (OCS)). In High-resolution computed tomography (HRCT) scans after therapy, consolidations were still observable in seven patients (five in new areas of the lung-migratory infiltrates), while most of them disappeared, leaving a residual area of ground glass opacity in two patients. One patient had a residual of the perilobular pattern, with the disappearing of the other findings (consolidations and ground-glass opacities). Two patients developed a fibrosing pattern despite the therapy (9.5%). Cryptogenic organizing pneumonia tends to respond to oral corticosteroid treatment, but some patients may have a null or partial response. We highlight the behavior of this disease after proper therapy.

Association between chest CT features and clinical course of Coronavirus Disease 2019

Purpose

This retrospective study aims to illustrate the radiographic characteristics of Coronavirus Disease 2019 and the correlation with the clinical course.

Methods

195 hospitalized patients confirmed as Coronavirus Disease 2019 at First Hospital of Changsha, Hunan Province from December 31, 2019 to February 20, 2020 were enrolled. Chest computed tomography scan, clinical data and laboratory tests results were collected accordingly. Variable characteristics were recorded, radiographic evolution and outcome were analyzed along with the time course. Representative laboratory tests results were analyzed based on the image findings.

Results

Majority of the patients showed bilateral (73.8%), multiple lobes involvements (75.9%), peripheral distribution (83.1%), ground-glass opacification (41.0%), increased vascular margins (63.1%), long axis parallelism (55.9%), patchy ground-glass opacities beneath the pleura (51.3%) and consolidation (45.6%). According to the repeated radiology analysis, patients of improving/stable group tended to have younger age compared with worsening group (45.3 ± 15.0 VS. 59.3 ± 13.5, P = 0.001). Based on the laboratory test results, patients with positive image findings shared elder age, 46.0 (35.0–60.0)VS.31.0 (12.0–37.0) P < 0.001, and higher chance developing fever(P < 0.05); higher level of lymphocytes, C-reactive protein, erythrocyte sedimentation rate and lactate dehydrogenase; lower level of white blood cells, neutrophil and albumin(P < 0.001).

Conclusions

There are several specific image changes along with the disease progression may be helpful in early recognition and differential diagnosis of Coronavirus Disease 2019. Comprehensive assessments of both imaging feature and laboratory test results may offer an intact knowledge of Coronavirus Disease 2019.

Challenges and countermeasures of thoracic oncology in the epidemic of COVID-19

Since December, 2019, a 2019 novel coronavirus disease (COVID-19) infected by the severe acute respiratory syndrome corona virus 2 (SARS-CoV-2) emerged in Wuhan, Hubei province, and the epidemic situation has continued to spread globally. The epidemic spread of COVID-19 has brought great challenges to the clinical practice of thoracic oncology. Outpatient clinics need to strengthen the differential diagnosis of initial symptoms, pulmonary ground-glass opacity (GGO), consolidation, interstitial and/or interlobular septal thickening, and crazy paving appearance. In the routine of oncology, the differential diagnosis of adverse events from COVID-19 is also significant, including radiation pneumonitis, checkpoint inhibitor pneumonitis (CIP), neutropenic fever, and so on. During the epidemic, indications of transbronchial biopsy (TBB) and CT-guided percutaneous thoracic biopsy are strictly controlled. For patients who are planning to undergo biopsy operation, screening to exclude the possibility of COVID-19 should be carried out. For confirmed or suspected patients, three-level protection should be performed during the operation. Disinfection and isolation measures should be strictly carried out during the operation. At last, more attention to the protection of cancer patients and give priority to the treatment of infected cancer patients.

Analysis of bronchoalveolar lavage samples collected from 30 patients with drug-induced pneumonitis

BACKGROUND

Drug-induced pneumonitis is a disease encountered by pulmonologists in the clinical setting. The diagnosis generally considers the patient's clinical course and the results of peripheral blood tests, radiological examinations, and often bronchoscopic examinations. However, few studies have reported the association between radiological patterns such as ground-glass opacity (GGO) or consolidation, and bronchoalveolar lavage fluid (BALF) cell fractions. This study aimed to clarify this association.

METHODS

Patients with a Naranjo's score of probable or definite were enrolled, and all 30 patients were categorized under probable. Data such as patient background, blood examination results, radiological findings, and BALF cell fractions were retrospectively collected. The association between BALF cell fractions and other factors such as chest computed tomography (CT) findings was evaluated.

RESULTS

The most common radiological finding in patients with lymphocyte-dominant BALF was GGO, with only one patient exhibiting consolidation. However, patients with eosinophil-dominant BALF were more likely to have consolidation; only three cases showed crazy paving and one showed GGO. In addition, patients with a GGO-dominant pattern on CT had an increased lymphocyte fraction of 41.0%; those with a consolidation-dominant pattern showed a relatively high eosinophil fraction of 5.2%; and those with a crazy paving pattern showed elevated eosinophil and neutrophil fractions of 19.1% and 9.9%, respectively.

CONCLUSIONS

In this study, a remarkable difference in radiological findings was observed among different BALF patterns.

Two cases of lymphangitic carcinomatosis as the primary symptom of colorectal carcinoma that achieved complete remission using combination anti-EGFR antibody therapy

Clinicians often encounter cases of pulmonary lymphangitic carcinomatosis when treating patients with cancer. When such a condition develops before the diagnosis of cancer, its diagnosis is often challenging. Herein, we report about two patients with colorectal carcinoma diagnosed after the identification of lymphangitic carcinomatosis, which achieved complete remission with combination anti-epidermal growth factor receptor (anti-EGFR) antibody therapy. In case 1, a 74-year-old woman presented with cough and dyspnea that had persisted for 1 month. She had unresectable advanced carcinoma of the sigmoid colon with lymphangitic carcinomatosis. Her respiratory status gradually deteriorated due to the disease. Thus, FOLFIRI plus cetuximab therapy was initiated. Her dyspnea rapidly resolved with the treatment, and complete remission of lymphangitic carcinomatosis was achieved. In case 2, a 46-year-old man presented with fever and dyspnea that had persisted for 1 month. He had unresectable advanced carcinoma of the transverse colon with lymphangitic carcinomatosis. FOLFOXIRI therapy was then initiated. However, his respiratory status did not improve. Therefore, his treatment was immediately switched to FOLFIRI plus panitumumab. His dyspnea rapidly resolved with the treatment, and complete remission of lymphangitic carcinomatosis was achieved. In oncologic emergencies, such as lymphangitic carcinomatosis, requiring an early response to treatment, the administration of anti-EGFR antibodies may be a highly effective treatment option.

Niemann-Pick disease type B: HRCT assessment of pulmonary involvement

OBJECTIVE

To analyze HRCT findings in patients with Niemann-Pick disease (NPD) type B, in order to determine the frequency of HRCT patterns and their distribution in the lung parenchyma, as well as the most common clinical characteristics.

METHODS

We studied 13 patients (3 males and 10 females) aged 5 to 56 years. HRCT images were independently evaluated by two observers, and disagreements were resolved by consensus. The inclusion criteria were presence of abnormal HRCT findings and diagnosis of NPD type B confirmed by histopathological examination of a bone marrow, lung, or liver biopsy specimen.

RESULTS

The most common clinical findings were hepatosplenomegaly and mild to moderate dyspnea. The most common HRCT patterns were smooth interlobular septal thickening and ground-glass opacities, which were both present in all patients. Intralobular lines were present in 12 patients (92.3%). A crazy-paving pattern was observed in 5 patients (38.4%), and areas of air trapping were identified in only 1 case (7.6%). Pulmonary involvement was bilateral in all cases, with the most affected area being the lower lung zone.

CONCLUSIONS

Smooth interlobular septal thickening, with or without associated ground-glass opacities, in patients with hepatosplenomegaly is the most common finding in NPD type B.

The effectiveness of N-acetylcysteine for an adult case of pulmonary alveolar proteinosis: A case report

Introduction

Pulmonary alveolar proteinosis is a rare disease that is characterized by accumulation of surfactant and phospholipids in the pulmonary alveoli. The current mainstay of treatment is whole lung lavage. There have been rare reports that have revealed the effectiveness of N-acetylcysteine on a secondary PAP.

Case presentation

A 45-year old man complained of shortness of breath and a productive cough with white sputum. He inhaled stone powder as an occupational hazard. CT scan of his chest radiograph showed ground glass changes superimposed on a reticular pattern as the so-called ‘crazy paving’ pattern. Lung biopsy revealed alveolar proteinaceous material with positive PAS stain. He eventually was diagnosed as PAP. He refused a whole lung lavage therapy, so the patient was rendered N-acetylcysteine as an antioxidant, enhanced immunotherapy and anti-infective treatment. His clinical symptoms and radiological manifestation improved gradually. No substantial adverse reactions were reported.

Conclusions

Persistent oral N-acetylcysteine may be an alternative treatment option for secondary PAP.

Pulmonary alveolar proteinosis - a crazy presentation of dyspnea

This case report demonstrates 44-year old man, presenting with recurring clinical pneumonias during a period of over 1 year. The patient was clinically affected with, i.a., weight loss, finger clubbing and severely reduced diffusion capacity. Repetitive chest x-rays showed bilateral and consolidating infiltrates, and a high-resolution computed tomography of the thorax (HRCT) exposed ground glass opacities superimposed on a reticular pattern as the so-called ‘crazy paving’ pattern. A bronchoscopic alveolar lavage revealed alveolar proteinaceous material compatible with the diagnosis pulmonary alveolar proteinosis (PAP). PAP is a rare syndrome where surfactant is accumulated in the alveoli, causing respiratory disease in typically young to middle-aged patients with male predominance. Both symptoms and prognosis are variable, and range from spontaneous remission to terminal respiratory failure. The standard treatment is whole lung lavage, where surfactant is mechanically rinsed from the lungs. The lack of specific clinical symptoms makes it easy to overlook the diagnosis, as supported by this case report. It serves as a reminder, that the findings of a crazy paving pattern on HRCT in young adults should alert of this rare disease, and advises on the further examinations required to make the diagnosis.

Gastric adenocarcinoma revealed by atypical pulmonary lymphangitic carcinomatosis

Pulmonary lymphangitic carcinomatosis (PLC) is a well-known form of tumour metastasis to the pulmonary lymphatic system or to the adjacent interstitial tissue resulting in thickening of the bronchovascular bundle and septa. Another type of tumour metastasis to the lung involves the pulmonary vascular system and is known as pulmonary tumour thrombotic microangiopathy (PTTM). In this article, we will describe the unusual case of a young Chinese woman with gastric adenocarcinoma revealed by atypical radiographic lesions consistent with both PLC and PTTM. We will discuss the existing evidence and hypotheses about the pathophysiology of both conditions.

Crazy paving pattern as a rare radiological manifestation of peripheral T-cell lymphoma (PTCL) with lung involvement: A case report

We report on a 70-year old woman with dyspnea, systemic lymphadenopathy and abnormal chest computed tomography (CT) findings. A complete laboratory testing as well as mediastinal tissue sampling via Endobronchial Ultrasound (EBUS)-guided Transbronchial Needle Biopsy (TBNB) did not reveal a definite diagnosis. After experiencing acute respiratory failure which led to intensive care unit, the patient underwent a cervical lymph node biopsy which revealed peripheral T-cell lymphoma not otherwise specified (PTCL-NOS). A CT-guided trans-thoracic lung biopsy was performed that showed involvement of the lung parenchyma in the context of PTCL-NOS. Lung involvement is a rare extra-nodal manifestation of PTCL. The imaging patterns of this lymphoma have not been well described. We conclude that the finding of crazy paving pattern is a rare manifestation of this disease. In patients with pre-existing lymphoma, lung involvement should be included in the differential due to high pre-test probability.

Rapid onset of amiodarone induced pulmonary toxicity after lung lobe resection - A case report and review of recent literature

Amiodarone-induced pulmonary toxicity (APT) is a severe side effect that can lead to lung fibrosis or fatal respiratory failure. Usually APT occurs during long term therapy after administration of prolonged loading doses or high cumulative doses. We present the case of a 58 year old woman who underwent thoracic surgery with lobe resection. She developed atrial fibrillation with hemodynamic-instability on the first post-operative day. We initiated amiodarone therapy and four days later she developed respiratory failure. The pulmonary function further deteriorated showing signs of an acute respiratory distress syndrome (ARDS). We therefore started mechanical ventilation, but still the gas exchange did not improve. A computer tomography-(CT)-scan presented bilateral interstitial and alveolar infiltrations. The patient also presented with leukocytosis, elevated C-reactive protein (CRP) levels however without elevated procalcitonin (PCT) concentrations. In the tracheal secretion we only harvested foam cells, but got no evidence for pathogens causing pneumonia. We immediately started glucocorticoid therapy with prednisolone 50 mg/d for five days. Almost instantaneously the gas exchange ameliorated. We were able to wean the patient from the respirator within five days. Pulmonary infiltrations were nearly vanished in a CT-scan few days later and completely disappeared in follow up examinations. This case demonstrates a per-acute onset of APT caused by a low loading dose in association with thoracic surgery. The initiation of glucocorticoid therapy in parallel to amiodarone withdrawal led to full recovery of the patient. One should consider APT when signs of pulmonary failure occur during brief periods of amiodarone therapy especially after thoracic surgery.

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Amiodarone-induced pulmonary toxicity (APT) can develop after low dose and short term amiodarone therapy.

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The early generation of APT is supported by thoracic surgery.

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APT can cause severe adult respiratory distress syndrome, leading to respiratory failure.

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Glucocorticoid therapy ameliorates APT symptoms and can restore respiratory failure in early state.