Lingyan Kong

Clinical management of breast cancer lung metastasis is challenging because of the complexity of dynamic lesion assessment. Traditional methods based on RECIST1.1 rely on size measurement, and existing studies require image registration and are limited to lesion-level assessment. In this study, we proposed a patient-level spatiotemporal assessment framework without registration to comprehensively analyze multiple lesions evolvement based on longitudinal CT images. Our method considers metastatic lesions that vary in size and often overlap with complex structures such as blood vessels and bones, and avoids potential registration errors. Our method outperforms state-of-the-art methods on both the Peking Union Medical College Hospital breast cancer lung metastasis dataset and the publicly available dataset. The model also showed excellent performance in a multicenter validation across four medical centers. We established a patient-level metastatic breast cancer assessment framework, providing a practical solution for longitudinal treatment monitoring.

Objectives: To assess the performance of the “dark blood” (DB) technique, deep-learning reconstruction (DLR), and their combination on aortic images for large-vessel vasculitis (LVV) patients. Materials and methods: Fifty patients diagnosed with LVV scheduled for aortic computed tomography angiography (CTA) were prospectively recruited in a single center. Arterial and delayed-phase images of the aorta were reconstructed using the hybrid iterative reconstruction (HIR) and DLR algorithms. HIR or DLR DB image sets were generated using corresponding arterial and delayed-phase image sets based on a “contrast-enhancement-boost” technique. Quantitative parameters of aortic wall image quality were evaluated. Results: Compared to the arterial phase image sets, decreased image noise and increased signal-noise-ratio (SNR) and CNR_outer (all p < 0.05) were obtained for the DB image sets. Compared with delayed-phase image sets, dark-blood image sets combined with the DLR algorithm revealed equivalent noise (p > 0.99) and increased SNR (p < 0.001), CNR_outer (p = 0.006), and CNR_inner (p < 0.001). For overall image quality, the scores of DB image sets were significantly higher than those of delayed-phase image sets (all p < 0.001). Image sets obtained using the DLR algorithm received significantly better qualitative scores (all p < 0.05) in all three phases. The image quality improvement caused by the DLR algorithm was most prominent for the DB phase image sets. Conclusion: DB CTA improves image quality and provides better visualization of the aorta for the LVV aorta vessel wall. The DB technique reconstructed by the DLR algorithm achieved the best overall performance compared with the other image sequences. Critical relevance statement: Deep-learning-based “dark blood” images improve vessel wall image wall quality and boundary visualization. Key Points: Dark blood CTA improves image quality and provides better aortic wall visualization. Deep-learning CTA presented higher quality and subjective scores compared to HIR. Combination of dark blood and deep-learning reconstruction obtained the best overall performance. Graphical

Breast periductal stromal tumor (PDST) is a rare biphasic tumor, with both benign ductal epithelium and non-phyllodes sarcomatous stroma. Its imaging features were rarely reported due to the rarity. In this study, we describe the case of a 48-year-old female who presented with a palpable mass in the right breast. Presurgery imaging evaluations of full-field digital mammography (FFDM), digital breast tomosynthesis (DBT), and ultrasonography (US) were performed. The imaging features include the following: 1. multiple solid lobulated lesions comprising nearly the entire right breast; 2. hypoechoic heterogeneous masses with internal separations and abundant blood flow; 3. FFDM and DBT showed multiple irregular high-density masses with lobulated margin, partially integrated. The patient underwent extended mastectomy of the right breast. The surgical pathology confirmed a PDST. After excision of the mass, she was followed up in the outpatient clinic for 25 months without local recurrence or distant metastasis.

Objective:To evaluate cyclic changes of fractional anisotropy (FA) and apparent diffusion coefficient (ADC) values of normal uterus in different age groups during the menstrual cycle, and the correlation with serum female hormone levels.Methods:29 normal volunteers accepted diffusion tensor imaging of the uterus on menstrual phase (MP), follicular phase (FP), ovulatory phase (OP) and luteal phase. FA and ADC values of different uterine layers on midsagittal images were measured. Differences between two age groups during the menstrual cycle were evaluated using liner mixed models and one-way analysis of variance. Pearson correlation analysis compared variation of FA and ADC values with serum female hormone levels measured in MP.Results:During menstrual cycle, endometrial FA values declined, whereas ADC values increased with significant differences (p < 0.05). Serum oestradiol (E) levels correlated moderately with variations of FA values between MP-FP (p = 0.045; r = 0.389) and MP-OP (p = 0.008; r = 0.511)....

Objective:To evaluate the clinical value of dual-source CT (DSCT) coronary angiography in the diagnosis of coronary artery fistula (CAF) in adults.Methods:A large cohort of 17,548 patients, who underwent DSCT coronary angiography in our hospital between January 2008 and October 2013, were retrospectively reviewed for CAF. The origin, course and drainage site of CAF and coexisting abnormalities were analysed. The conventional angiography results, treatments and follow-up DSCT images were also evaluated.Results:A total of 33 CAFs from 17,548 patients were detected. The incidence of CAF was 0.19% by DSCT. CAF originating from the left coronary artery (LCA) was found in 14 (42.4%) patients, from right coronary artery (RCA) in 4 (12.1%) cases and from both LCA and RCA in 15 (45.5%) patients. The pulmonary artery was the most common site of drainage (28/33, 84.8%). 8 of the 33 (24.2%) cases were associated with aneurysms. Six cases were associated with coronary artery atherosclerosis. Four patients underwent co...