Value of multiplanar reconstruction in multi-slice computed tomography for the detection of foreign body in the pulmonary artery: a case report.

Multi-slice computed tomography (MSCT) is the primary method for the detection and visualization of foreign bodies in the pulmonary artery because it provides high sensitivity and accuracy. It is very difficult to diagnose a patient with a non-iatrogenic pulmonary artery foreign body who does not have a history of a penetrating trauma. This case report describes a 36-year-old male that presented with coughing and haemoptysis. Based on conventional coronal and cross-sectional CT, the foreign body was misdiagnosed as pulmonary tuberculosis and pulmonary artery thrombosis. During treatment of the bronchial artery embolization and anti-tuberculosis therapy, the patient continued to experience haemoptysis. After further analysis of the pulmonary artery CT angiography images and curved multiplane reconstruction, an approximately 6-cm long toothpick was identified in the pulmonary artery with an unclear entry route. After surgery to remove the toothpick, symptoms of coughing and haemoptysis were resolved. This current case demonstrated that multiplane reconstruction in MSCT can improve the detection and visualization of pulmonary artery foreign bodies, which can aid in the diagnosis of pulmonary artery diseases of unknown cause.

An MRI-Based Radiomic Model for Individualized Prediction of Hepatocellular Carcinoma in Patients With Hepatitis B Virus-Related Cirrhosis.

Objective: To develop and validate a radiomic nomogram for individualized prediction of hepatocellular carcinoma (HCC) in HBV cirrhosis patients based on baseline magnetic resonance imaging examinations and clinical data. Methods: 364 patients with HBV cirrhosis from five hospitals were assigned to the training, internal validation, external validation-1 or external validation-2 cohort. All patients underwent baseline magnetic resonance image (MRI) scans and clinical follow-up within three-year time. Clinical risk factors and MRI-based features were extracted and analyzed. The radiomic signatures were built using the radiomics-score (Rad-score) that calculated for each patient as a linear weighted combination of selected MRI-based features. Prognostic performances of the clinical and radiomic nomograms were evaluated with Cox modeling in the training and validation cohorts. Results: Eighteen features were selected for inclusion in the Rad-score prognostic model. The radiomic signature from multi-sequence MRI yielded a concordance index (C-index) of 0.710, 0.681, 0.632 and 0.658 in the training, internal validation, external validation-1, external validation-2 cohorts, respectively. Sex and Child-Turcotte-Pugh (CTP) class were the most prognostic clinical risk factors in univariate Cox proportional hazards analyses. The radiomic combined nomogram that integrated the radiomic signature with the clinical factors yielded a C-index of 0.746, 0.710, and 0.641 in the training, internal validation, and external validation-1 cohorts, respectively, which was an improvement over either the clinical nomogram or radiomic signature alone. Conclusion: We developed an MRI-based radiomic combined nomogram with good discrimination ability for the individualized prediction of HCC in HBV cirrhosis patients within three-year time.