Prognostic value of metabolic tumor volume on [F]FDG PET/CT in addition to the TNM classification system of locally advanced non-small cell lung cancer.

Purpose: Staging of non-small cell lung cancer (NSCLC) is commonly based on [F]FDG PET/CT, in particular to exclude distant metastases and guide local therapy approaches like resection and radiotherapy. Although it is hoped that PET/CT will increase the value of primary staging compared to conventional imaging, it is generally limited to the characterization of TNM. The first aim of this study was to evaluate the PET parameter metabolic tumor volume (MTV) above liver background uptake as a prognostic marker in lung cancer.

CT-assessed sarcopenia and immune-related adverse events in patients with lung cancer: A competing risk time-to-event analysis.

Background: Immune checkpoint inhibitors (ICIs) can induce immune-related adverse events (irAEs). This study investigates the relationship between CT-assessed sarcopenia and irAEs in patients with lung cancer who are receiving ICIs.

Methods: Patients were enrolled if they had lung cancer treated with ICIs at the University Medical Center Groningen (2015-2021) and had undergone low-dose CT scans that included the third lumbar vertebral level (L3).

Intraoperative Molecular Imaging With Pafolacianine: Histologic Characteristics of Identified Nodules.

Background: With increased early detection efforts, surgery for early-stage lung cancer is expected to rise. Pafolacianine is the first FDA approved targeted optical imaging agent indicated as an adjunct for intraoperative identification of malignant and nonmalignant pulmonary lesions in adult patients with known or suspected cancer in the lung.

Methods: This is a retrospective review of the malignant and nonmalignant lesions identified by pafolacianine with intraoperative molecular imaging (IMI) in the multi-center Phase 2 and Phase 3 ELUCIDATE clinical trials.

Predicting early stage lung cancer recurrence and survival from combined tumor motion amplitude and radiomics on free-breathing 4D-CT.

Background: Cancer control outcomes of lung cancer are hypothesized to be affected by several confounding factors, including tumor heterogeneity and patient history, which have been hypothesized to mitigate the dose delivery effectiveness when treated with radiation therapy. Providing an accurate predictive model to identify patients at risk would enable tailored follow-up strategies during treatment.

Purpose: Our goal is to demonstrate the added prognostic value of including tumor displacement amplitude in a predictive model that combines clinical features and computed tomography (CT) radiomics for 2-year recurrence and survival in non-small-cell lung cancer (NSCLC) patients treated with curative-intent stereotactic body radiation therapy.

Image fusion for intraoperative evaluation of microwave ablation in non-small cell lung cancer: a retrospective cohort study.

Background: Patients with early-stage non-small cell lung cancer (NSCLC) who are intolerant to surgery have a poor prognosis. Microwave ablation is an effective treatment method. However, the density of the lesion may occasionally be similar to that of the ablation zone, thus rendering it difficult to identify the relative position of the lesion and ablation zone during ablation.

Preoperative assessment of tertiary lymphoid structures in stage I lung adenocarcinoma using CT radiomics: a multicenter retrospective cohort study.

Objective: To develop a multimodal predictive model, Radiomics Integrated TLSs System (RAITS), based on preoperative CT radiomic features for the identification of TLSs in stage I lung adenocarcinoma patients and to evaluate its potential in prognosis stratification and guiding personalized treatment.

Methods: The most recent preoperative chest CT thin-slice scans and postoperative hematoxylin and eosin-stained pathology sections of patients diagnosed with stage I LUAD were retrospectively collected. Tumor segmentation was achieved using an automatic virtual adversarial training segmentation algorithm based on a three-dimensional U-shape convolutional neural network (3D U-Net).

Uncertainty-aware automatic TNM staging classification for [F] Fluorodeoxyglucose PET-CT reports for lung cancer utilising transformer-based language models and multi-task learning.

Background: [F] Fluorodeoxyglucose (FDG) PET-CT is a clinical imaging modality widely used in diagnosing and staging lung cancer. The clinical findings of PET-CT studies are contained within free text reports, which can currently only be categorised by experts manually reading them. Pre-trained transformer-based language models (PLMs) have shown success in extracting complex linguistic features from text.

Predicting High-Grade Patterns in Stage I Solid Lung Adenocarcinoma: A Study of 371 Patients Using Refined Radiomics and Deep Learning-Guided CatBoost Classifier.

Introduction: This study aimed to devise a diagnostic algorithm, termed the Refined Radiomics and Deep Learning Features-Guided CatBoost Classifier (RRDLC-Classifier), and evaluate its efficacy in predicting pathological high-grade patterns in patients diagnosed with clinical stage I solid lung adenocarcinoma (LADC).

Methods: In this retrospective study, a total of 371 patients diagnosed with clinical stage I solid LADC were randomly categorized into training and validation sets in a 7:3 ratio. Uni- and multivariate logistic regression analyses were performed to examine the imaging findings that can be used to predict pathological high-grade patterns meticulously.

Clinico-pathological characteristics and treatment outcome in non-small cell lung cancer in Greenland 2015-2020 - a comparison with the cohort from 2004 to 2010.

Background And Purpose: Lung cancer is the leading cause of cancer-related mortality in Greenland. Since 2004, medical treatment of lung cancer has been available in Greenland. However, both diagnostic work-up and treatment logistics are hampered by the lack of medical services in smaller settlements, the infrastructure, and extreme arctic weather conditions.

Rare Pulmonary MALT Lymphomas and Its Differential Diagnosis On Chest CT.

Pulmonary nodules caused by mucosa-associated lymphomas (MALT lymphomas) are uncommon, comprising for less than 0.5% of all primary lung tumors. While biopsy is the main method for diagnosing the disease, the significance of differential pulmonary diagnosis based on imaging is often overlooked.

Novel Strategies for Lung Cancer Interventional Diagnostics.

Lung cancer is a major global health issue, with 2.21 million cases and 1.80 million deaths reported in 2020.

Lung Cancer Associated with Cystic Airspaces: Current Insights into Diagnosis, Pathophysiology, and Treatment Strategies.

Lung cancer associated with cystic airspaces (LCCA) is a rare subtype of non-small-cell lung cancer (NSCLC), accounting for 1-4% of cases. LCCA is characterized by the presence of cystic airspaces within or at the periphery of the tumor on imaging. LCCA poses significant clinical challenges due to its high risk of misdiagnosis or missed diagnosis, often leading to a worse prognosis compared to other forms of lung cancer.

Usefulness of computed tomography findings for predicting soft tissue sarcoma grades.

Soft tissue sarcomas (STSs) constitute a heterogeneous group of tumors that originate from mesenchymal cells. Imaging plays an important role in the assessment of the oncological stage of STSs. Computed tomography findings facilitate the identification of the tumor location and margins in relation to the surrounding anatomic boundaries and thereby enable preoperative planning of tumor management.

Enhanced recovery using lung tumour thermal ablation in scleroderma associated interstitial lung disease.

Image-guided thermal ablation is an alternative treatment for non-small cell lung cancer and can be performed in patients for whom general anaesthesia is not desired or contraindicated. This minimally invasive treatment is a promising approach in patients with early-stage lung cancer who are considered inoperable due to comorbidities. This short report describes an improved thermal ablation technique that considers the complexity of treating lung carcinoma in scleroderma-associated interstitial lung disease.

Systematic Review of the Comparative Studies of Image-guided Thermal Ablation, Stereotactic Radiosurgery, and Sublobar Resection for Treatment of High-Risk Patients with Stage I Non-Small Cell Lung Cancer.

The Clinical Practice Standards Committee of the American Association for Thoracic Surgery assembled an expert panel and conducted a systematic review of the literature detailing studies directly comparing treatment options for high-risk patients with stage I non-small cell lung cancer (NSCLC). A systematic search was performed to identify publications comparing outcomes following image-guided thermal ablation (IGTA), stereotactic ablative radiotherapy (SABR), and sublobar resection-the main treatment options applicable to high-risk patients with stage I NSCLC. There were no publications detailing completed randomized controlled trials comparing these treatment options.

Lung adenocarcinoma: characteristic radiological presentations.

Radiology, mainly computed tomography, has a fundamental role in diagnosis, staging and follow-up of lung adenocarcinoma, the most common type of pulmonary cancer. Within its broad spectrum of presentation, the pathological, clinical and morphological characteristics of this neoplasm allow, in an appropriate clinical context, to suggest certain histological subtypes among which are mucinous adenocarcinoma, lepidic growth adenocarcinoma or associated with cystic lung lesions. The objective of this review is to describe the pathologic, clinical and radiological features of those characteristic forms of lung carcinoma that can be diagnosed radiologically with fair accuracy.

Remote Symptom Monitoring of Patients With Advanced Lung Cancer (The ProWide Study): A Randomized Controlled Trial.

Purpose: Remote symptom monitoring of patients with cancer has previously shown potential for improving clinical outcomes. This study aimed to evaluate the effects of remote symptom monitoring in patients with lung cancer after palliative induction treatment.

Methods: In a Danish multicenter randomized controlled trial, patients were randomly assigned 1:1 to remote symptom monitoring (intervention arm) added to standard of care versus standard of care (control arm).

Feasibility of computed tomography-derived surgical margin assessment in an ex vivo sublobar lung resection model.

Objectives: Computed tomography imaging of a sublobar resection specimen may inform intraoperative surgical margin assessment. However, consistency with final pathological margins has not been previously evaluated. In this study, we investigated the concordance between surgical margin measurements by computed tomography versus pathology measurements using an ex vivo sublobar lung resection model.

Association of baseline plasma D-dimer and platelets with progression-free survival in patients with stage IV non-small cell lung cancer treated with anti-PD-1 antibody.

Background: In past studies, peripheral blood D-dimer and platelets have shown predictive value in the treatment of non-small cell lung cancer (NSCLC). However, it remains unclear whether pretreatment D-dimer and platelets can serve as biomarkers for predicting efficacy and prognosis in stage IV NSCLC patients without driver gene mutations receiving programmed cell death protein 1 (PD-1) antibody. Therefore, this study aims to investigate the correlation between baseline D-dimer and platelet levels and the efficacy and prognosis in the study population, aiding in determining the significance of baseline D-dimer and platelet levels as biomarkers.

Construction and validation of deep learning model for cachexia in extensive-stage small cell lung cancer patients treated with immune checkpoint inhibitors: a multicenter study.

Background: Cachexia is observed in around 60% of patients with extensive-stage small cell lung cancer (ES-SCLC) and may play an important role in the development of resistance to immunotherapy. This study aims to evaluate the influence of cachexia on the effectiveness of immunotherapy, develop and assess a deep learning (DL)-based prediction model for cachexia, as well as its prognostic value.

Methods: The analysis encompassed ES-SCLC patients who received the combination of first-line immunotherapy and chemotherapy from Shandong Cancer Hospital and Institute, Qilu Hospital, and Jining First People's Hospital.

Predictive value of longitudinal systemic inflammatory markers for pathologic response to neoadjuvant PD-1 blockade in resectable non-small cell lung cancer.

Background: Identifying biomarkers to predict responses for neoadjuvant immunotherapy in resectable non-small cell lung cancer (NSCLC) is under intensive study. Considering the interplay between cancer, inflammation, and immunosuppression, we hypothesized that circulating and imaging inflammatory markers could serve as indicators of anti-tumor immune responses, and thus conducting an exploratory study to reveal the predictive value of combining longitudinal systemic inflammatory markers in stratifying pathologic response to neoadjuvant sintilimab.

Methods: We retrospectively reviewed 36 patients (29 male and seven female) with NSCLC (stage IA-IIIB) who underwent pre- and post-treatment peripheral blood tests and F-fluorodeoxyglucose positron emission tomography/computed tomography (F-FDG PET/CT) scans before and after two cycles of neoadjuvant sintilimab (registration number: ChiCTR-OIC-17013726).

Mutational differences between primary cancer tissue and circulating tumor cells in early-stage non-small cell lung cancer.

Background: Early-stage non-small cell lung cancer (NSCLC) has a high recurrence rate despite proper management, including curative surgery. Circulating tumor cells (CTCs) are believed to play a key role in the distant metastasis of lung cancer. Immunofluorescence imaging studies of CTCs have revealed that they are associated with the prognosis of NSCLC.

An efficient combined intelligent system for segmentation and classification of lung cancer computed tomography images.

Background And Objective: One of the illnesses with most significant mortality and morbidity rates worldwide is lung cancer. From CT images, automatic lung tumor segmentation is significantly essential. However, segmentation has several difficulties, such as different sizes, variable shapes, and complex surrounding tissues.