Rationale: There is a growing need to accurately estimate the prognosis of idiopathic pulmonary fibrosis (IPF) in clinical practice, given the development of effective drugs for treating IPF. Objectives: To develop artificial intelligence-based image analysis software to detect parenchymal and airway abnormalities on computed tomographic (CT) imaging of the chest and to explore their prognostic importance in patients with IPF. Methods: A novel artificial intelligence-based quantitative CT image analysis software (AIQCT) was developed by applying 304 high-resolution CT (HRCT) scans from patients with diffuse lung diseases as the training set. AIQCT automatically categorized and quantified 10 types of parenchymal patterns as well as airways, expressing the volumes as percentages of the total lung volume. To validate the software, the area percentages of each lesion quantified by AIQCT were compared with those of the visual scores using 30 plain high-resolution CT images with lung diseases. In addition, three-dimensional analysis for similarity with ground truth was performed using HRCT images from 10 patients with IPF. AIQCT was then applied to 120 patients with IPF who underwent HRCT scanning of the chest at our institute. Associations between the measured volumes and survival were analyzed. Results: The correlations between AIQCT and the visual scores were moderate to strong (correlation coefficient 0.44–0.95) depending on the parenchymal pattern. The Dice indices for similarity between AIQCT data and ground truth were 0.67, 0.76, and 0.64 for reticulation, honeycombing, and bronchi, respectively. During a median follow-up period of 2,184 days, 66 patients died, and 1 underwent lung transplantation. In multivariable Cox regression analysis, bronchial volumes (adjusted hazard ratio [HR], 1.33; 95% confidence interval [CI], 1.16–1.53) and normal lung volumes (adjusted HR, 0.97; 95% CI, 0.94–0.99) were independently associated with survival after adjusting for the gender-age-lung physiology stage of IPF. Conclusions: Our newly developed artificial intelligence-based image analysis software successfully quantified parenchymal lesions and airway volumes. Bronchial and normal lung volumes on HRCT imaging of the chest may provide additional prognostic information on the gender-age-lung physiology stage of IPF.

The aim of this study was to evaluate the diagnostic utility of a novel test kit that could theoretically detect all serogroups of Legionella pneumophila for diagnosing Legionella pneumonia, in comparison with existing kits. This study was conducted in 16 hospitals in Japan from April 2016 to December 2018. Three urinary antigen test kits were used: the novel kit (LAC-116), BinaxNOW Legionella (Binax), and Q-line Kyokutou Legionella (Q-line). In addition, sputum culture and nucleic acid detection tests and serum antibody tests were performed where possible. The diagnostic accuracy and correlations of the novel kit with the two existing kits were analyzed. In total, 56 patients were diagnosed with Legionella pneumonia. The sensitivities of LAC-116, Binax, and Q-line were 79%, 84%, and 71%, respectively. The overall match rate between LAC-116 and Binax was 96.8% and between LAC-116 and Q-line was 96.4%. One patient had L. pneumophila serogroup 2, and only LAC-116 showed a positive result, whereas Binax and Q-line did not. The novel Legionella urinary antigen test kit was useful for diagnosing Legionella pneumonia. In addition, it could detect Legionella pneumonia caused by non-L. pneumophila serogroup 1.

Background: In interstitial pneumonia (IP)-associated lung cancer, immune checkpoint inhibitor pneumonitis (ICIP) is common with immune checkpoint inhibitor (ICI) treatment. The purpose of the present study was to clarify the safety and efficacy of ICI treatment for patients with lung cancer with IP.Methods: This multicentre retrospective observational study was conducted from June 2016 to December 2020 in patients with primary lung cancer with IP who received ICI treatment.Results: A total of 200 patients (median age 70 years; male/female, 176/24) were enrolled from 27 institutions. ICIP occurred in 61 patients (30.5%), pneumonitis grades 3–5 in 32 patients (15.5%) and death in nine patients (4.5%). The common computed tomography pattern of ICIP was organising pneumonia in 29 patients (47.5%). Subsequently, diffuse alveolar damage (DAD) pattern was observed in 19 patients (31.1%) who had a significantly worse prognosis than those with a non-DAD pattern (median progression-free survival (PFS) 115 daysversus226 days, p=0.042; median overall survival (OS) 334 daysversus1316 days, p<0.001). Immune-related adverse events (irAEs) occurred in approximately 50% of patients. Patients with irAEs (n=100) had a better prognosis than those without irAEs (n=100) (median PFS 200 daysversus77 days, p<0.001; median OS 597 daysversus390 days p=0.0074). The objective response rate and disease control rate were 41.3% and 68.5%, respectively.Conclusions: Although ICI treatment was effective for patients with lung cancer with IP, ICIP developed in approximately 30% of patients. Patients with irAEs had a significantly better PFS and OS than those without irAEs.

Propionibacterium acnes is implicated in the pathogenesis of sarcoidosis. We investigated the usefulness of immunohistochemistry (IHC) with a commercially available P. acnes-specific monoclonal antibody (PAB antibody) for differentiating sarcoidosis from other granulomatous diseases. Formalin-fixed paraffin-embedded tissue samples from 94 sarcoidosis patients and 30 control patients with other granulomatous diseases were examined by the original manual IHC method. We also compared the detection frequency of P. acnes in sarcoid granulomas between manual and automated IHC methods. P. acnes was detected in sarcoid granulomas of samples obtained by transbronchial lung biopsy (64%), video-associated thoracic surgery (67%), endobronchial-ultrasound-guided transbronchial-needle aspiration (32%), lymph node biopsy (80%), and skin biopsy (80%) from sarcoidosis patients, but not in any non-sarcoid granulomas of the samples obtained from control patients. P. acnes outside granulomas, however, was frequently detected in both groups. The detection status of P. acnes in granulomas did not correlate with the clinical characteristics of sarcoidosis patients. The automated Leica system exhibited the best detection sensitivity (72%) and almost an identical localization for P. acnes in sarcoid granulomas compared with the manual method. IHC with a PAB antibody is useful for differentiating sarcoidosis from other granulomatous diseases by detecting P. acnes in granulomas. An automated method by the Leica system can be used in pathology laboratories for differential diagnosis of granulomas by IHC with the PAB antibody.