Lanuti, Michael D.

The NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines) for Non-Small Cell Lung Cancer (NSCLC) provide recommendations for the treatment of patients with NSCLC, including diagnosis, primary disease management, surveillance, and subsequent treatment. The panel has updated the list of recommended targeted therapies based on recent FDA approvals and clinical data. This selection from the NCCN Guidelines for NSCLC focuses on treatment recommendations for advanced or metastatic NSCLC with actionable biomarkers.

The NCCN Guidelines for Non–Small Cell Lung Cancer (NSCLC) provide recommendations for the treatment of NSCLC. These NCCN Guidelines Insights discuss recent updates to the NCCN Guidelines, with a focus on systemic therapy options for the treatment of patients with nonmetastatic NSCLC and the corresponding molecular testing considerations.

Thymomas and thymic carcinomas are rare mediastinal tumors that originate in the thymus. Patients with thymoma may experience symptoms associated with autoimmune paraneoplastic diseases (such as myasthenia gravis), which typically do not occur in patients with thymic carcinoma. The NCCN Guidelines for Thymomas and Thymic Carcinomas provide guidance for the diagnosis, treatment, and surveillance of patients with thymoma and thymic carcinoma. Involvement of a multidisciplinary team with experience treating thymomas and thymic carcinomas is highly recommended.

Abstract Introduction: Endobronchial optical coherence tomography (EB-OCT) imaging has unique potential to diagnose and quantify early, microscopic disease changes and assess therapeutic responsivity in interstitial lung disease (ILD). However, training and time requirements for interpretation and quantitative evaluation of large volumetric EB-OCT datasets need to be optimized to facilitate clinical adoption. We develop and validate a computationally-efficient, rapid EB-OCT quantitative image analysis framework using artificial intelligence (AI) with deep learning architecture for 2D feature segmentation, 3D feature burden and spatial distribution mapping, and computer-aided diagnosis in early ILD subjects. Methods: Volumetric EB-OCT datasets, consisting of 2D cross-sectional images, were acquired from multiple locations in the bilateral lungs of ILD and healthy control subjects. EB-OCT features were manually segmented from cross-sectional images by an expert EB-OCT reader, including fibrosis, microscopic honeycombing, traction bronchiolectasis, normal parenchyma, and emphysema. EB-OCT images with corresponding feature segmentations were used to train and validate a multiclass convolutional neural network. The 2D AI-based segmentation model was subsequently evaluated against manual ‘ground truth’ segmentations for each feature in a de novo ‘test’ dataset of independent subjects using dice similarity score, precision, recall/sensitivity, specificity, and balanced accuracy. To generate 3D AI-based quantitative feature burden and spatial distribution maps, AI-based feature segmentation was performed on each EB-OCT 2D cross-sectional image within a volumetric imaging site. Three external pathologist readers independently interpreted 3D AI-based features maps for each EB-OCT imaging site acquired for a subject (without access to EB-OCT images) and provided a single diagnosis of usual interstitial pneumonia (UIP) or non-UIP ILD. Performance of computer-aided ILD diagnosis was compared against independently evaluated histopathology, clinical diagnosis, and prior EB-OCT image interpretation. Results: EB-OCT was acquired in 51 subjects: 30 in vivo early ILD, 5 in vivo non-ILD controls, and 16 ex vivo end-stage ILD. Overall pixel similarity between 2D manual and AI-based segmentation demonstrated high accuracy for each ILD feature (mean balanced accuracy 0.9). 3D quantitative AI-based feature maps demonstrated strong agreement (Spearman ρ0.87, p<0.001) between manual and AI-based segmentation. AI-based computer-aided diagnosis demonstrated 100% sensitivity/specificity for histologic UIP and clinical IPF for all pathologist readers, with improved diagnostic accuracy and significantly reduced training (45-minute training, 75% reduction) and interpretation time (<1 minute per subject for computer-aided diagnosis, 88% reduction) compared to EB-OCT image interpretation. Conclusion: The AI-based EB-OCT image analysis framework could expedite computer-aided diagnosis of early ILD and robust, quantitative assessment of microscopic disease burden, progression, and therapeutic responsivity.

The NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines) for Non–Small Cell Lung Cancer (NSCLC) provide recommendations for the treatment of patients with NSCLC, including diagnosis, primary disease management, surveillance for relapse, and subsequent treatment. The panel has updated the list of recommended targeted therapies based on recent FDA approvals and clinical data. This selection from the NCCN Guidelines for NSCLC focuses on treatment recommendations for advanced or metastatic NSCLC with actionable molecular biomarkers.

Mesothelioma is a rare cancer that originates from the mesothelial surfaces of the pleura and other sites, and is estimated to occur in approximately 3,500 people in the United States annually. Pleural mesothelioma is the most common type and represents approximately 85% of these cases. The NCCN Guidelines for Mesothelioma: Pleural provide recommendations for the diagnosis, evaluation, treatment, and follow-up for patients with pleural mesothelioma. These NCCN Guidelines Insights highlight significant updates to the NCCN Guidelines for Mesothelioma: Pleural, including revised guidance on disease classification and systemic therapy options.

Mesothelioma is a rare cancer originating in mesothelial surfaces of the peritoneum, pleura, and other sites. These NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines) focus on peritoneal mesothelioma (PeM). The NCCN Guidelines for PeM provide recommendations for workup, diagnosis, and treatment of primary as well as previously treated PeM. The diagnosis of PeM may be delayed because PeM mimics other diseases and conditions and because the disease is so rare. The pathology section was recently updated to include new information about markers used to identify mesothelioma, which is difficult to diagnose. The term “malignant” is no longer used to classify mesotheliomas, because all mesotheliomas are now defined as malignant.

The NCCN Guidelines for Non–Small Cell Lung Cancer (NSCLC) provide recommendations for management of disease in patients with NSCLC. These NCCN Guidelines Insights focus on neoadjuvant and adjuvant (also known as perioperative) systemic therapy options for eligible patients with resectable NSCLC.

NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines) for Non–Small Cell Lung Cancer (NSCLC) provide recommended management for patients with NSCLC, including diagnosis, primary treatment, surveillance for relapse, and subsequent treatment. Patients with metastatic lung cancer who are eligible for targeted therapies or immunotherapies are now surviving longer. This selection from the NCCN Guidelines for NSCLC focuses on targeted therapies for patients with metastatic NSCLC and actionable mutations.