Early Post-discharge Pain Trajectories After Thoracoscopic Sublobar Resection for Stage IA Non-small Cell Lung Cancer.

Background: Thoracoscopic sublobar resection is emerging as a main treatment option for early-stage non-small cell lung cancer (NSCLC). This study aimed to determine whether distinct early post-discharge pain trajectories could be identified in patients with stage IA NSCLC undergoing thoracoscopic sublobar resection.

Methods: The data were collected from a longitudinal prospective observational cohort (CN-PRO-Lung 3).

Ternary-Classification Habitat Model for Invasiveness and Grade of Lung Adenocarcinoma Presenting as a Subsolid Nodule on Low-Dose Chest CT: A Multicenter Study.

Habitat imaging provides a novel approach to capture spatial heterogeneity within lesions. To develop a ternary-classification habitat model to characterize lung adenocarcinoma presenting as a subsolid nodule (SSN) on CT and to test the model's diagnostic performance compared with 2D and radiomic models. This retrospective study included 747 patients (median age, 56 years; 241 male, 506 female) with 834 resected lung adenocarcinomas that presented as SSNs on low-dose CT between July 2018 and May 2023.

Quantitative Measures of Pure Ground-Glass Nodules from an Artificial Intelligence Software for Predicting Invasiveness of Pulmonary Adenocarcinoma on Low-Dose CT: A Multicenter Study.

: Deep learning-based artificial intelligence (AI) tools have been gradually used to detect and segment pulmonary nodules in clinical practice. This study aimed to assess the diagnostic performance of quantitative measures derived from a commercially available AI software for predicting the invasiveness of pulmonary adenocarcinomas that manifested as pure ground-glass nodules (pGGNs) on low-dose CT (LDCT) in lung cancer screening. : A total of 388 pGGNs were consecutively enrolled and divided into a training cohort (198 from center 1 between February 2019 and April 2022), testing cohort (99 from center 1 between April 2022 and March 2023), and external validation cohort (91 from centers 2 and 3 between January 2021 and August 2023).

Neoadjuvant chemotherapy or chemoradiotherapy plus sintilimab versus neoadjuvant chemoradiotherapy for locally advanced oesophageal squamous cell carcinoma: a study protocol of a multicentre, randomised, controlled, phase III trial (SCIENCE study).

Introduction: Oesophageal squamous cell carcinoma (ESCC) is a globally challenging digestive tract malignancy with poor prognosis and limited treatment options. Early-stage ESCC is often asymptomatic, leading to a late-stage diagnosis in many cases. Neoadjuvant therapy combined with surgery is the standard treatment approach for locally advanced ESCC.

A preoperative pathological staging prediction model for esophageal cancer based on CT radiomics.

Background: Accurate and comprehensive preoperative staging is one of the most important prognostic factors for the management of esophageal cancer (EC). We aimed to develop and validate predictive models using radiomics from preoperative contrast-enhanced Computed Tomography (CT) images to assess pathological staging in EC patients.

Methods: This study retrospectively included 161 patients who underwent esophagectomy at Sichuan Cancer Hospital from July 2018 to February 2023.

Predicting High-risk Lung Adenocarcinoma in Solid and Part-solid Nodules on Low-dose CT: A Multicenter Study.

Rationale And Objectives: High-grade patterns, visceral pleural invasion, lymphovascular invasion, spread through air spaces, and lymph node metastasis are high-risk factors and associated with poor prognosis in lung adenocarcinomas (LUADs). This study aimed to construct and validate a radiomic model and a radiographic model derived from low-dose CT (LDCT) for predicting high-risk LUADs in solid and part-solid nodules.

Materials And Methods: This study retrospectively enrolled 658 pathologically confirmed LUADs from July 2018 to December 2022 from four centers, which were divided into training set (n=411), internal validation set (n=139), and external validation set (n=108).

Comparing the Efficacy of Empirical Anti-Infective Therapy and Follow-Up Observation for Newly Diagnosed Pulmonary Ground-Glass Nodules With Suspected Inflammatory Etiology: A Multicenter Prospective Observational Study Protocol.

Background And Aims: The optimal management strategy for newly diagnosed pulmonary ground-glass nodules (GGNs) with suspected inflammatory etiology remains controversial in clinical practice. Empirical anti-inflammatory therapy is commonly used, but its efficacy compared with that of follow-up observation lacks high-quality evidence. Therefore, this study aims to compare the effectiveness of empirical anti-infective therapy and follow-up observation for pulmonary GGNs in real-world settings.

Early Postoperative Patient-Reported Outcomes of Sarcopenia Versus Nonsarcopenia in Patients Undergoing Video-Assisted Thoracoscopic Surgery for Lung Cancer.

Background: To compare early postoperative patient-reported outcomes between sarcopenic and nonsarcopenic patients undergoing video-assisted thoracoscopic surgery (VATS) for lung cancer.

Methods: The data used in this study were acquired from a longitudinal prospective study (CN-PRO-Lung 1) between November 2017 and January 2020. Skeletal muscle index was measured at L3 vertebral level on preoperative computed tomography to identify sarcopenia based on an established threshold.

Predicting the Invasiveness of Pulmonary Adenocarcinomas in Pure Ground-Glass Nodules Using the Nodule Diameter: A Systematic Review, Meta-Analysis, and Validation in an Independent Cohort.

The nodule diameter was commonly used to predict the invasiveness of pulmonary adenocarcinomas in pure ground-glass nodules (pGGNs). However, the diagnostic performance and optimal cut-off values were inconsistent. We conducted a meta-analysis to evaluate the diagnostic performance of the nodule diameter for predicting the invasiveness of pulmonary adenocarcinomas in pGGNs and validated the cut-off value of the diameter in an independent cohort.

Collaborative multidisciplinary management and expertise of cT2-3 locally advanced operable esophageal squamous cell carcinoma: a report of two cases.

Background: The accurate clinical staging of esophageal squamous cell carcinoma (ESCC) is pivotal for guiding treatment strategies. However, the current precision in staging for clinical T (cT)2 and cT3 stages remains unsatisfactory. This article discusses the role of multidisciplinary teams (MDTs) in the clinical staging and formulation of neoadjuvant treatment strategies for locally advanced operable ESCC.

The solid component within part-solid nodules: 3-dimensional quantification, correlation with the malignant grade of nonmucinous pulmonary adenocarcinomas, and comparisons with 2-dimentional measures and semantic features in low-dose computed tomography.

Background: There is no consensus on 3-dimensional (3D) quantification method for solid component within part-solid nodules (PSNs). This study aimed to find the optimal attenuation threshold for the 3D solid component proportion in low-dose computed tomography (LDCT), namely the consolidation/tumor ratio of volume (CTRV), basing on its correlation with the malignant grade of nonmucinous pulmonary adenocarcinomas (PAs) according to the 5th edition of World Health Organization classification. Then we tested the ability of CTRV to predict high-risk nonmucinous PAs in PSNs, and compare its performance with 2-dimensional (2D) measures and semantic features.

An ordinal radiomic model to predict the differentiation grade of invasive non-mucinous pulmonary adenocarcinoma based on low-dose computed tomography in lung cancer screening.

Objectives: To construct a radiomic model of low-dose CT (LDCT) to predict the differentiation grade of invasive non-mucinous pulmonary adenocarcinoma (IPA) and compare its diagnostic performance with quantitative-semantic model and radiologists.

Methods: A total of 682 pulmonary nodules were divided into the primary cohort (181 grade 1; 254 grade 2; 64 grade 3) and validation cohort (69 grade 1; 99 grade 2; 15 grade 3) according to scanners. The radiomic and quantitative-semantic models were built using ordinal logistic regression.

Radiomic and quantitative-semantic models of low-dose computed tomography for predicting the poorly differentiated invasive non-mucinous pulmonary adenocarcinoma.

Purpose: Poorly differentiated invasive non-mucinous pulmonary adenocarcinoma (IPA), based on the novel grading system, was related to poor prognosis, with a high risk of lymph node metastasis and local recurrence. This study aimed to build the radiomic and quantitative-semantic models of low-dose computed tomography (LDCT) to preoperatively predict the poorly differentiated IPA in nodules with solid component, and compare their diagnostic performance with radiologists.

Materials And Methods: A total of 396 nodules from 388 eligible patients, who underwent LDCT scan within 2 weeks before surgery and were pathologically diagnosed with IPA, were retrospectively enrolled between July 2018 and December 2021.

Quantitative parameters of enhanced dual-energy computed tomography for differentiating lung cancers from benign lesions in solid pulmonary nodules.

Objectives: This study aimed to investigate the ability of quantitative parameters of dual-energy computed tomography (DECT) and nodule size for differentiation between lung cancers and benign lesions in solid pulmonary nodules.

Materials And Methods: A total of 151 pathologically confirmed solid pulmonary nodules including 78 lung cancers and 73 benign lesions from 147 patients were consecutively and retrospectively enrolled who underwent dual-phase contrast-enhanced DECT. The following features were analyzed: diameter, volume, Lung CT Screening Reporting and Data System (Lung-RADS) categorization, and DECT-derived quantitative parameters including effective atomic number (Zeff), iodine concentration (IC), and normalized iodine concentration (NIC) in arterial and venous phases.

Development and validation of qualitative and quantitative models to predict invasiveness of lung adenocarcinomas manifesting as pure ground-glass nodules based on low-dose computed tomography during lung cancer screening.

Background: Due to different management strategy and prognosis of different subtypes of lung adenocarcinomas appearing as pure ground-glass nodules (pGGNs), it is important to differentiate invasive adenocarcinoma (IA) from adenocarcinoma in situ/minimally invasive adenocarcinoma (AIS/MIA) during lung cancer screening. The aim of this study was to develop and validate the qualitative and quantitative models to predict the invasiveness of lung adenocarcinoma appearing as pGGNs based on low-dose computed tomography (LDCT) and compare their diagnostic performance with that of intraoperative frozen section (FS).

Methods: A total of 223 consecutive pathologically confirmed pGGNs from March 2018 to December 2020 were divided into a primary cohort (96 IAs and 64 AIS/MIAs) and validation cohort (39 IAs and 24 AIS/MIAs) according to scans (Brilliance iCT and Somatom Definition Flash) performed at Sichuan Cancer Hospital and Institute.

Prediction of invasive adenocarcinomas manifesting as pure ground-glass nodules based on radiomic signature of low-dose CT in lung cancer screening.

Objective: To develop a radiomic model based on low-dose CT (LDCT) to distinguish invasive adenocarcinomas (IAs) from adenocarcinoma /minimally invasive adenocarcinomas (AIS/MIAs) manifesting as pure ground-glass nodules (pGGNs) and compare its performance with conventional quantitative and semantic features of LDCT, radiomic model of standard-dose CT, and intraoperative frozen section (FS).

Methods: A total of 147 consecutive pathologically confirmed pGGNs were divided into primary cohort (43 IAs and 60 AIS/MIAs) and validation cohort (19 IAs and 25 AIS/MIAs). Logistic regression models were built using conventional quantitative and semantic features, selected radiomic features of LDCT and standard-dose CT, and intraoperative FS diagnosis, respectively.

Radiomic features of axillary lymph nodes based on pharmacokinetic modeling DCE-MRI allow preoperative diagnosis of their metastatic status in breast cancer.

Objective: To study the feasibility of use of radiomic features extracted from axillary lymph nodes for diagnosis of their metastatic status in patients with breast cancer.

Materials And Methods: A total of 176 axillary lymph nodes of patients with breast cancer, consisting of 87 metastatic axillary lymph nodes (ALNM) and 89 negative axillary lymph nodes proven by surgery, were retrospectively reviewed from the database of our cancer center. For each selected axillary lymph node, 106 radiomic features based on preoperative pharmacokinetic modeling dynamic contrast enhanced magnetic resonance imaging (PK-DCE-MRI) and 5 conventional image features were obtained.

Comparison of Radiomic Models Based on Low-Dose and Standard-Dose CT for Prediction of Adenocarcinomas and Benign Lesions in Solid Pulmonary Nodules.

Objectives: This study aimed to develop radiomic models based on low-dose CT (LDCT) and standard-dose CT to distinguish adenocarcinomas from benign lesions in patients with solid solitary pulmonary nodules and compare the performance among these radiomic models and Lung CT Screening Reporting and Data System (Lung-RADS). The reproducibility of radiomic features between LDCT and standard-dose CT were also evaluated.

Methods: A total of 141 consecutive pathologically confirmed solid solitary pulmonary nodules were enrolled including 50 adenocarcinomas and 48 benign nodules in primary cohort and 22 adenocarcinomas and 21 benign nodules in validation cohort.

Chemotherapy-induced grey matter abnormalities in cancer survivors: a voxel-wise neuroimaging meta-analysis.

Background: Findings regarding chemotherapy-induced grey matter abnormalities are heterogeneous, and no meta-analysis has quantitatively assessed brain structural alterations in cancer survivors treated with chemotherapy.

Purpose: To investigate the grey matter abnormalities in non-CNS (central nervous system) cancer survivors treated with chemotherapy using Anisotropic Effect Size Signed Differential Mapping (AES-SDM) software.

Method: We identified studies published up to Sep 2018 that compared grey matter in non-CNS cancer survivors treated with chemotherapy (CT+, 10 data sets including 433 individuals) and cancer survivors not treated with chemotherapy (CT-, 7 data sets including 210 individuals) or healthy controls (HC, 3 data sets including 407 individuals) using whole-brain VBM.

Accuracy of Pulmonary Nodule Volumetry Using Noise-Optimized Virtual Monoenergetic Image and Nonlinear Blending Image Algorithms in Dual-Energy Computed Tomography: A Phantom Study.

Objective: The aim of the study was to assess accuracy of pulmonary nodule volumetry using noise-optimized virtual monoenergetic image (VMI+) and nonlinear blending image (NBI) algorithms in dual-energy computed tomography (DECT).

Methods: An anthropomorphic chest phantom with 10 simulated nodules (5 solid nodules and 5 ground-glass opacities) was scanned using DECT80/Sn140kV, DECT100/Sn140kV, and single-energy CT (SECT120kV/200mAs), respectively. The dual-energy images were reconstructed using VMI+ (70 keV) and NBI algorithms.

Merged image reconstruction for anomalous systemic arterial supply to a normal lung.

We present a rare case of anomalous systemic arterial supply to normal basal segments of the left lower lobe. Plain computed tomography (CT) showed an occupancy lesion in the left lower lobe. Contrast CT and merged three-dimensional (3D) image reconstruction showed that the anomalous systemic artery originated from the descending aorta and substituted the basilar segmental pulmonary artery and the arterial supply to the basilar segment of left lower lobe.

Accuracy of Pulmonary Nodule Volumetry at Different Exposure Parameters in Low-Dose Computed Tomography: A Phantom Study.

Objective: To explore the exposure parameters with minimized radiation dose for accurate pulmonary nodule volumetry using low-dose computed tomography (LDCT).

Methods: An anthropomorphic chest phantom with 11 pulmonary nodules (6 solid nodules and 5 ground-glass opacities) was scanned using 256-slice multidetector computed tomography scanner at various tube voltage and current (combinations of 80, 100 and 120 kV with 10 to 30 mAs). Raw data sets were reconstructed using the hybrid iterative reconstruction method and nodule volume was calculated by a semiautomatic software.

Screening baseline characteristics of early lung cancer on low-dose computed tomography with computer-aided detection in a Chinese population.

Objectives: This study investigated appropriate baseline characteristics for screening a Chinese population at high risk of early lung cancer, assisted by low-dose computed tomography (LDCT) with computer-aided detection (CAD). Included is a discussion of the viability of using LDCT in the screening guideline and optimizing the guideline.

Methods: In 2014, 1016 individuals from Sichuan Province were enrolled who satisfied the criteria for high risk according to the 2013 National Comprehensive Cancer Network (NCCN) Guidelines for Non-Small Cell Lung Cancer.