Lung-RADS Versus Pan-Canadian Early Detection of Lung Cancer Study Screening for Patients at High Risk of Lung Cancer

Evidence of variable quality from 6 diagnostic test accuracy studies indicates that the Pan-Canadian Early Detection of Lung Cancer (PanCan) model may perform better at determining which lung nodules identified by low-dose CT are cancerous compared to the Lung Imaging Reporting and Data System. However, evidence from 3 other studies, also of variable quality, suggests that the risk calculators have similar diagnostic test accuracy. No studies were identified that compared the clinical utility of PanCan versus the Lung Imaging Reporting and Data System. Results from 2 economic evaluations were inconsistent about the cost-effectiveness of the 2 lung cancer risk models. However, each study applied the models to different types of lung nodules. One evidence-based guideline recommended that PanCan be used in the UK for initial risk assessment and for the management of lung nodules.

Artificial intelligence in functional imaging of the lung

Artificial intelligence (AI) is transforming the way we perform advanced imaging. From high-resolution image reconstruction to predicting functional response from clinically acquired data, AI is promising to revolutionize clinical evaluation of lung performance, pushing the boundary in pulmonary functional imaging for patients suffering from respiratory conditions. In this review, we overview the current developments and expound on some of the encouraging new frontiers. We focus on the recent advances in machine learning and deep learning that enable reconstructing images, quantitating, and predicting functional responses of the lung. Finally, we shed light on the potential opportunities and challenges ahead in adopting AI for functional lung imaging in clinical settings.

Does Surgical Technique Influence the Burden of Lung Metastases in Patients with Pathologic Long Bone Fractures?

Background: The aims of this study are to (1) determine whether fixation of metastatic long bone fractures with an intramedullary nail (IMN) influences the incidence of lung metastasis in comparison to arthroplasty or ORIF (Arthro/ORIF); and (2) assess this relationship in primary tumor types; and (3) to assess survival implications of lung metastasis after surgery.Methods: Retrospective cohort study investigating 184 patients (107 IMN, and 77 Arthro/ORIF) surgically treated for metastatic long bone fractures. Patients were required to have a single surgically treated impending or established pathologic fracture of a long bone, pre-operative lung imaging (lung radiograph or computed tomography) and post-operative lung imaging within 6 months of surgery. Primary cancer types included were breast (n=70), lung (n = 43), prostate (n = 34), renal cell (n = 37). Statistical analyses were conducted using two-tailed Fisher’s exact tests, and Kaplan-Meier survival analyses.Results: Patients treated with IMN and ORIF/arthroplasty developed new or progressive lung metastases following surgery at an incidence of 34% and 26% respectively. Surgical method did not significant influence lung metastasis (p = 0.33). Furthermore, an analysis of primary cancer subgroups did not yield any differences between IMN vs Arthro/ORIF. Median survival for the entire cohort was 11 months and 1-year overall survival was 42.7% (95% CI: 35.4-49.8). Regardless of fixation method, the presence of new or progressive lung metastatic disease at follow up imaging study was found to have a negative impact on patient survival (p <0.001).Conclusions: In this study, progression of metastatic lung disease was not affected by long bone stabilization strategy. IM manipulation of metastatic long bone fractures therefore may not result in a clinically relevant increase in metastatic lung burden. The results of this study also suggest that lung metastasis within 6 months of surgery for metastatic long bone lesions is negatively associated with patient survival. Level of Evidence: III, therapeutic study

Lung-RADS usado no rastreamento do câncer de pulmão: a doença granulomatosa faz diferença?

Objetivo: o objetivo é analisar os resultados do rastreamento do câncer de pulmão por tomografia computadorizada de baixa dose (LDCT) por meio do Sistema de Relatórios e Dados de Triagem de TC de Pulmão (Lung-RADS) em um centro de câncer brasileiro. Materiais e métodos: revisamos retrospectivamente os prontuários de pacientes submetidos ao programa de rastreamento de câncer de pulmão de LDCT basal no A.C. Camargo Cancer Center. Os critérios de inclusão e exclusão foram iguais aos do National Lung Cancer Screening Trial (NLST). Os critérios para achados de imagem foram aqueles classificados de acordo com as categorias de avaliação do Lung Imaging Reporting and Data System (Lung-RADS). Resultados: Dos 287 indivíduos avaliados neste estudo, 72,1% apresentaram TC de triagem negativa (categorias 1 ou 2 do Lung-RADS), o restante teve TC de triagem positiva, considerando 5,6% na categoria 4A de Lung-RADS, 2,1% na categoria 4B e 1,0% na categoria 4X. Os principais achados foram avaliados em 218 (75,9%) indivíduos, com nódulos sólidos (64,8%), parcialmente sólidos (2,7%) e não sólidos (8,3%). A maioria dos pacientes (59,1%) apresentaram nódulos sólidos menores que 6 mm. Os resultados histológicos confirmaram câncer de pulmão em 2 casos (prevalência de 0,7% de todos os pacientes triados). Conclusões: A prevalência de câncer de pulmão em nossa amostra foi compatível com a literatura. No entanto, tivemos uma prevalência maior das categorias 3 e 4A do Lung-RADS do que o esperado. Isso pode estar associado à maior incidência de doenças granulomatosas, principalmente tuberculose, na população brasileira.

Pneumonia Caused by Lichtheimia Ramosa During the COVID-19 Pandemic in Hubei Province, China：A Case Report and Literature Review

BackgroundMucor infection cannot be ignored in patients with pulmonary shadowing with cavitation .This paper reports a case of mucormycosis during the COVID-19 pandemic in Hubei Province, China. Case PresentationA anesthesiology doctor was initially diagnosed as COVID-19 due to changes in lung imaging. Later Lichtheimia ramose was found by Metagenomic next generation sequencing (mNGS) in the Bronchoalveolar lavage fluid (BALF).After adjusting amphotericin B for anti-infective treatment, the patient's infection lesions were shranked and the symptoms were significantly relieved. ConclusionThe diagnosis of invasive fungal infections is very difficult, mNGS can make an accurate pathogenic diagnosis of invasive fungal diseases for the clinic and provide a basis for clinical treatment.