Quantification of Resection Margin following Sublobar Resection in Lung Cancer Patients through Pre- and Post-Operative CT Image Comparison: Utilizing a CT-Based 3D Reconstruction Algorithm.

Sublobar resection has emerged as a standard treatment option for early-stage peripheral non-small cell lung cancer. Achieving an adequate resection margin is crucial to prevent local tumor recurrence. However, gross measurement of the resection margin may lack accuracy due to the elasticity of lung tissue and interobserver variability. Therefore, this study aimed to develop an objective measurement method, the CT-based 3D reconstruction algorithm, to quantify the resection margin following sublobar resection in lung cancer patients through pre- and post-operative CT image comparison. An automated subvascular matching technique was first developed to ensure accuracy and reproducibility in the matching process. Following the extraction of matched feature points, another key technique involves calculating the displacement field within the image. This is particularly important for mapping discontinuous deformation fields around the surgical resection area. A transformation based on thin-plate spline is used for medical image registration. Upon completing the final step of image registration, the distance at the resection margin was measured. After developing the CT-based 3D reconstruction algorithm, we included 12 cases for resection margin distance measurement, comprising 4 right middle lobectomies, 6 segmentectomies, and 2 wedge resections. The outcomes obtained with our method revealed that the target registration error for all cases was less than 2.5 mm. Our method demonstrated the feasibility of measuring the resection margin following sublobar resection in lung cancer patients through pre- and post-operative CT image comparison. Further validation with a multicenter, large cohort, and analysis of clinical outcome correlation is necessary in future studies.

Deep Learning Analysis for Predicting Tumor Spread through Air Space in Early-Stage Lung Adenocarcinoma Pathology Images.

The presence of spread through air spaces (STASs) in early-stage lung adenocarcinoma is a significant prognostic factor associated with disease recurrence and poor outcomes. Although current STAS detection methods rely on pathological examinations, the advent of artificial intelligence (AI) offers opportunities for automated histopathological image analysis. This study developed a deep learning (DL) model for STAS prediction and investigated the correlation between the prediction results and patient outcomes. To develop the DL-based STAS prediction model, 1053 digital pathology whole-slide images (WSIs) from the competition dataset were enrolled in the training set, and 227 WSIs from the National Taiwan University Hospital were enrolled for external validation. A YOLOv5-based framework comprising preprocessing, candidate detection, false-positive reduction, and patient-based prediction was proposed for STAS prediction. The model achieved an area under the curve (AUC) of 0.83 in predicting STAS presence, with 72% accuracy, 81% sensitivity, and 63% specificity. Additionally, the DL model demonstrated a prognostic value in disease-free survival compared to that of pathological evaluation. These findings suggest that DL-based STAS prediction could serve as an adjunctive screening tool and facilitate clinical decision-making in patients with early-stage lung adenocarcinoma.

Clinicopathological Features and Significance of Epidermal Growth Factor Receptor Mutation in Surgically Resected Early-Stage Lung Adenocarcinoma.

The clinicopathological presentation of early-stage lung adenocarcinoma patients with epidermal growth factor receptor (EGFR) mutations has been seldom studied. Our study enrolled patients with stage I and II lung adenocarcinoma between January 2014 and December 2017 at the National Taiwan University Hospital. Clinicopathological features and prognosis were retrospectively reviewed and analyzed depending on EGFR mutation status. EGFR mutations were detected in 622 (60%) out of 1034 patients. Compared to the group without EGFR mutations, the group with EGFR mutations had more patients above 65 years of age (p < 0.001), more non-lepidic histological subtypes (p < 0.001), higher CEA levels (p = 0.044), higher grade of pleural (p = 0.02) and lymphovascular (p = 0.001) invasion, higher histological grade (p < 0.001), and a more advanced pathological stage (p = 0.022). In multivariate analysis, there was no significant difference in PFS or OS between the EGFR mutant and wild-type groups. In subtype analysis, the tumors with an L858R mutation had a more lepidic predominant histological type (p = 0.019) and less lymphovascular invasion (p = 0.011). No significant differences in PFS or OS were detected between the exon 19 deletion and L858R mutation groups. In early-stage lung adenocarcinoma, EGFR mutation may be considered as a treatment response predictor for tyrosine kinase inhibitors, instead of a predictor of clinical prognosis.

Video-assisted thoracoscopic surgery for primary pulmonary cryptococcosis.

BACKGROUND: The surgical outcome for primary pulmonary cryptococcosis remains unclear. In this study, we investigated the clinical characteristics, treatment, and outcomes of video-assisted thoracoscopic surgery (VATS) for primary pulmonary cryptococcosis. METHODS: We retrospectively reviewed the medical records of 49 patients with confirmed pulmonary cryptococcosis who underwent VATS for pulmonary nodules at the National Taiwan University Hospital between May 2013 and March 2019. Serum cryptococcal antigen (CryAg)-positive and CryAg-negative patients were compared. RESULTS: The diagnosis of pulmonary cryptococcosis was confirmed using histopathology or tissue swab culture. The mean age of the patients was 56.0 ± 12.2 years, and 27 patients (55.1%) were male. Most patients were asymptomatic (67.3%) and admitted following the detection of pulmonary lesions on a computed tomography scan of the chest. A greater proportion of patients in the CryAg-positive group (62.5%) underwent lobectomy compared with those in the CryAg-negative group (7.3%, P < 0.001). Three patients (6.1%) had neurological symptoms (headache or dizziness) and all were serum CryAg-positive. One patient with Cryptococcus gattii developed fluctuating serum CryAg titers after a 12-month antifungal treatment. No relapse occurred in the remaining 48 patients, irrespective of postoperative antifungal treatment. CONCLUSION: In patients with primary pulmonary cryptococcosis, serum CryAg detection rate is low, and VATS was an effective and safe diagnostic and therapeutic tool.