Local salient location-aware anomaly mask synthesis for pulmonary disease anomaly detection and lesion localization in CT images.

Automated pulmonary anomaly detection using computed tomography (CT) examinations is important for the early warning of pulmonary diseases and can support clinical diagnosis and decision-making. Most training of existing pulmonary disease detection and lesion segmentation models requires expert annotations, which is time-consuming and labour-intensive, and struggles to generalize across atypical diseases. In contrast, unsupervised anomaly detection alleviates the demand for dataset annotation and is more generalizable than supervised methods in detecting rare pathologies.

Quantitative Evaluation of Chronic Obstructive Pulmonary Disease and Risk Prediction of Acute Exacerbation by High-Resolution Computed Tomography.

Objective: It is imperative to popularize the tertiary prevention of chronic obstructive pulmonary disease (COPD) and to improve the diagnosis and treatment.

Methods: COPD patients were divided into mild ( = 18), moderate ( = 20), severe ( = 24), and extremely severe ( = 22) groups for performing high-resolution computed tomography (HRCT) and pulmonary function test. Serum procalcitonin (PCT) and high-sensitivity C-reactive protein (hs-CRP) were detected, and the occurrence rate of acute exacerbation COPD (AECOPD) was recorded during a 12-months follow-up period.

Radiomic analysis for preoperative prediction of cervical lymph node metastasis in patients with papillary thyroid carcinoma.

Purpose: Cervical lymph node (LN) metastasis of papillary thyroid carcinoma (PTC) is critical for treatment and prognosis. We explored the feasibility of using radiomics to preoperatively predict cervical LN metastasis in PTC patients.

Method: Total 221 PTC patients (training cohort: n = 154; validation cohort: n = 67; divided randomly at the ratio of 7:3) were enrolled and divided into 2 groups based on LN pathologic diagnosis (N0: n = 118; N1a and N1b: n = 88 and 15, respectively).

Plasma cell-free DNA level and its integrity as biomarkers to distinguish non-small cell lung cancer from tuberculosis.

Aims: The aim of this study was to evaluate the potential clinical value of the plasma cell-free DNA (cfDNA) concentrations and strand integrity as an auxiliary tool for Non-small cell lung cancer (NSCLC) differential diagnosis from tuberculosis in patients with solitary pulmonary nodules detected by computed tomography (CT).

Methods: This research was divided into 3 groups: NSCLC (n=106), tuberculosis (n=105) and healthy controls (n=107). The quantization of plasma DNA fragments was performed by quantitative real-time PCR.