Korean Journal of Radiology最新文献

Objective: This study investigated the feasibility and prognostic relevance of threshold-based quantification of myocardial delayed enhancement (MDE) on CT in patients with nonischemic dilated cardiomyopathy (NIDCM).

Materials and methods: Forty-three patients with NIDCM (59.3 ± 17.1 years; 21 male) were included in the study and underwent cardiac CT and MRI. MDE was quantified manually and with a threshold-based quantification method using cutoffs of 2, 3, and 4 standard deviations (SDs) on three sets of CT images (100 kVp, 120 kVp, and 70 keV). Interobserver agreement in MDE quantification was assessed using the intraclass correlation coefficient (ICC). Agreement between CT and MRI was evaluated using the Bland-Altman method and the concordance correlation coefficient (CCC). Patients were followed up for the subsequent occurrence of the primary composite outcome, including cardiac death, heart transplantation, heart failure hospitalization, or appropriate use of an implantable cardioverter-defibrillator. The Kaplan-Meier method was used to estimate event-free survival according to MDE levels.

Results: Late gadolinium enhancement (LGE) was observed in 29 patients (67%, 29/43), and the mean LGE found with the 5-SD threshold was 4.1% ± 3.6%. The 4-SD threshold on 70-keV CT showed excellent interobserver agreement (ICC = 0.810) and the highest concordance with MRI (CCC = 0.803). This method also yielded the smallest bias with the narrowest range of 95% limits of agreement compared to MRI (bias, -0.119%; 95% limits of agreement, -4.216% to 3.978%). During a median follow-up of 1625 days (interquartile range, 712-1430 days), 10 patients (23%, 10/43) experienced the primary composite outcome. Event-free survival significantly differed between risk subgroups divided by the optimal MDE cutoff of 4.3% (log-rank P = 0.005).

Conclusion: The 4-SD threshold on 70-keV monochromatic CT yielded results comparable to those of MRI for quantifying MDE as a marker of myocardial fibrosis, which showed prognostic value in patients with NIDCM.

Objective: To evaluate the safety and clinical outcomes of the Passeo-18 Lux drug-coated balloon (DCB) in endovascular revascularization procedures under real-world conditions in a Korean population with atherosclerotic disease of the infrainguinal arteries, including below-the-knee (BTK) arteries.

Materials and methods: Eight institutions in the Republic of Korea participated in this prospective, multicenter, single-arm, post-market surveillance study. Two hundred patients with Rutherford class 2-5 peripheral arterial disease and infrainguinal lesions suitable for endovascular treatment were competitively enrolled. Data were collected at baseline, the time of intervention, discharge, and 1-, 6-, 12-, and 24-month follow-up visits. The primary safety endpoint was freedom from major adverse events (MAE) within 6 months (except when limiting the time frame for procedure- or device-related mortality to within 30 days), and the primary effectiveness endpoint was freedom from clinically driven target lesion revascularization (CD-TLR) within 12 months after the procedure.

Results: A total of 197 patients with 332 target lesions were analyzed. Two-thirds of the patients had diabetes mellitus, and 41.6% had chronic limb-threatening ischemia. The median target lesion length was 100 mm (interquartile range: 56-133 mm). Of the target lesions, 35.2% were occlusions, and 14.8% were located in the BTK arteries. Rate of freedom from MAE was 97.9% at 6 months, and the rate of freedom from CD-TLR was 95.0% and 92.2% at 12 and 24 months, respectively. Subgroup analysis of 43 patients and 49 target lesions involving the BTK arteries showed rate of freedom from MAE of 92.8% at 6 months and rates of freedom from CD-TLR of 88.8% and 84.4% at 12 and 24 months, respectively.

Conclusion: The results of the present study, including the BTK subgroup analysis, showed outcomes comparable to those of other DCB studies, confirming the safety and effectiveness of Passeo-18 Lux DCB in the Korean population.

Objective: To prospectively investigate the influence of the menstrual cycle on the background parenchymal signal (BPS) and apparent diffusion coefficient (ADC) of the breast on diffusion-weighted MRI (DW-MRI) in healthy premenopausal women.

Materials and methods: Seven healthy premenopausal women (median age, 37 years; range, 33-49 years) with regular menstrual cycles participated in this study. DW-MRI was performed during each of the four phases of the menstrual cycle (four examinations in total). Three radiologists independently assessed the BPS visual grade on images with b-values of 800 sec/mm² (b800), 1200 sec/mm² (b1200), and a synthetic 1500 sec/mm² (sb1500). Additionally, one radiologist conducted a quantitative analysis to measure the BPS volume (%) and ADC values of the BPS (ADC_BPS) and fibroglandular tissue (ADC_FGT). Changes in the visual grade, BPS volume (%), ADC_BPS, and ADC_FGT during the menstrual cycle were descriptively analyzed.

Results: The visual grade of BPS in seven women varied from mild to marked on b800 and from minimal to moderate on b1200 and sb1500. As the b-value increased, the visual grade of BPS decreased. On b800 and sb1500, two of the seven volunteers showed the highest visual grade in the early follicular phase (EFP). On b1200, three of the seven volunteers showed the highest visual grades in EFP. The BPS volume (%) on b800 and b1200 showed the highest value in three of the six volunteers with dense breasts in EFP. Three of the seven volunteers showed the lowest ADC_BPS in the EFP. Four of the seven volunteers showed the highest ADC_BPS in the early luteal phase (ELP) and the lowest ADC_FGT in the late follicular phase (LFP).

Conclusion: Most volunteers did not exhibit specific BPS patterns during their menstrual cycles. However, the highest BPS and lowest ADC_BPS were more frequently observed in EFP than in the other menstrual cycle phases, whereas the highest ADC_BPS was more common in ELP. The lowest ADC_FGT was more frequent in LFP.

Hepatocellular carcinoma (HCC) is a biologically heterogeneous tumor characterized by varying degrees of aggressiveness. The current treatment strategy for HCC is predominantly determined by the overall tumor burden, and does not address the diverse prognoses of patients with HCC owing to its heterogeneity. Therefore, the prognostication of HCC using imaging data is crucial for optimizing patient management. Although some radiologic features have been demonstrated to be indicative of the biologic behavior of HCC, traditional radiologic methods for HCC prognostication are based on visually-assessed prognostic findings, and are limited by subjectivity and inter-observer variability. Consequently, artificial intelligence has emerged as a promising method for image-based prognostication of HCC. Unlike traditional radiologic image analysis, artificial intelligence based on radiomics or deep learning utilizes numerous image-derived quantitative features, potentially offering an objective, detailed, and comprehensive analysis of the tumor phenotypes. Artificial intelligence, particularly radiomics has displayed potential in a variety of applications, including the prediction of microvascular invasion, recurrence risk after locoregional treatment, and response to systemic therapy. This review highlights the potential value of artificial intelligence in the prognostication of HCC as well as its limitations and future prospects.