Hepatic hemangiomas are the most common benign liver tumors. Typically, small- to medium-sized hemangiomas are asymptomatic and discovered incidentally through the widespread use of imaging techniques. Giant hemangiomas (>5 cm) have a higher risk of complications. A variety of imaging methods are used for diagnosis. Cavernous hemangioma is the most frequent type, but radiologists must be aware of other varieties. Conservative management is often adequate, but some cases necessitate targeted interventions. Although surgery was traditionally the main treatment, the evolution of minimally invasive procedures now often recommends transarterial chemoembolization as the treatment of choice.

This study evaluates the effectiveness of superselective transcatheter arterial chemoembolization (TACE) using a bleomycin–lipiodol emulsion in treating giant hepatic hemangiomas. A retrospective review included 31 patients with a mean age of 53 ± 10.42 years who underwent TACE from December 2014 to October 2022, with follow-up imaging examinations to assess outcomes. Technical success was defined as successful embolization of all feeding arteries, and clinical success was defined as a reduction in hemangioma volume by 50% or more on follow-up imaging. This study observed a 100% technical success rate. Post-embolization syndrome was common, and two cases of asymptomatic hepatic artery dissection were noted. Clinical success was achieved in 80.6% of patients, with significant volume reduction observed in the majority. Conclusively, superselective transcatheter arterial chemoembolization with bleomycin–lipiodol emulsions is presented as a viable and effective treatment option for giant hepatic hemangiomas. With no procedure-related mortality and significant volume reduction in most cases, this method offers a promising alternative to surgical intervention. This study’s findings suggest a need for further exploration and validation in larger-scale prospective studies.

In this study, we assess image quality in computed tomography scans reconstructed via DLIR (Deep Learning Image Reconstruction) and compare it with iterative reconstruction ASIR-V (Adaptive Statistical Iterative Reconstruction) in CT (computed tomography) scans of the head. The CT scans of 109 patients were subjected to both objective and subjective evaluation of image quality. The objective evaluation was based on the SNR (signal-to-noise ratio) and CNR (contrast-to-noise ratio) of the brain’s gray and white matter. The regions of interest for our study were set in the BGA (basal ganglia area) and PCF (posterior cranial fossa). Simultaneously, a subjective assessment of image quality, based on brain structure visibility, was conducted by experienced radiologists. In the assessed scans, we obtained up to a 54% increase in SNR for gray matter and a 60% increase for white matter using DLIR in comparison to ASIR-V. Moreover, we achieved a CNR increment of 58% in the BGA structures and 50% in the PCF. In the subjective assessment of the obtained images, DLIR had a mean rating score of 2.8, compared to the mean score of 2.6 for ASIR-V images. In conclusion, DLIR shows improved image quality compared to the standard iterative reconstruction of CT images of the head.

Coronary computed tomography angiography (CTA) is a widely accepted, non-invasive diagnostic modality for the evaluation of patients with suspected coronary artery disease (CAD). However, a limitation of CTA is its inability to provide information on the hemodynamic significance of the coronary lesion. The recently developed stress dynamic CT perfusion technique has emerged as a potential solution to this diagnostic challenge. Dynamic CT myocardial perfusion provides information on the hemodynamic consequences of coronary stenosis and is used to detect myocardial ischemia. The combination of stress dynamic CT myocardial perfusion with CTA provides a comprehensive assessment that integrates anatomical and functional information. CT myocardial perfusion has been validated in several clinical studies and has shown comparable accuracy to Positron Emission Tomography (PET) and stress magnetic resonance imaging (MRI) in the diagnosis of hemodynamically significant coronary stenosis and superior performance to Single Photon Emission Computed Tomography (SPECT). More importantly, CTP-derived myocardial perfusion has been shown to have a strong correlation with FFR, and the use of CTP results in a reduction of negative catheterizations. In the context of suspected stable coronary artery disease, the CT protocol with dynamic perfusion imaging combined with CTA eliminates the need for additional testing, making it a convenient “one-stop-shop” method and an effective gatekeeper to an invasive approach.

Purpose: To assess the efficacy and safety of a low-dose, computed tomography (CT)-guided transthoracic biopsy of lung and pleural lesions.Material and methods: A total of 135 low-dose, CT-guided transthoracic lung and pleural lesions biopsies were performed. A cutting needle was utilized in 124 cases, and fine needle aspiration biopsy was performed in 14 cases. In all cases, 14- to 22-gauge biopsy needles were used.Results: Diagnostic material was obtained in 111 (82.2%) patients. In 97 (71.8%) cases neoplastic lesions were found, predominantly adenocarcinoma and non-small cell carcinoma. In 14 (12.6%) cases non atypical cells were reported. Biopsy failed to obtain material suitable for histopathological examination in 24 (17.7%) cases. Complications occurred in 31 patients, including pneumothorax in 28 patients and haematoma in 3 cases.Conclusions: Based on the obtained results, it can be stated that low-dose, CT-guided transthoracic biopsy of lung and pleural tissues is an accurate and safe procedure. Also, it is linked to a low risk of complications such as a small pneumothorax.

Background and purpose: This study focuses on an objective evaluation of a novel reconstruction algorithm—Deep Learning Image Reconstruction (DLIR)—ability to improve image quality and reduce radiation dose compared to the established standard of Adaptive Statistical Iterative Reconstruction-V (ASIR-V), in unenhanced head computed tomography (CT). Materials and methods: A retrospective analysis of 163 consecutive unenhanced head CTs was conducted. Image quality assessment was computed on the objective parameters of Signal-to-Noise Ratio (SNR) and Contrast-to-Noise Ratio (CNR), derived from 5 regions of interest (ROI). The evaluation of DLIR dose reduction abilities was based on the analysis of the PACS derived parameters of dose length product and computed tomography dose index volume (CTDIvol). Results: Following the application of rigorous criteria, the study comprised 35 patients. Significant image quality improvement was achieved with the implementation of DLIR, as evidenced by up to a 145% and 160% increase in SNR in supra- and infratentorial regions, respectively. CNR measurements further confirmed the superiority of DLIR over ASIR-V, with an increase of 171.5% in the supratentorial region and a 59.3% increase in the infratentorial region. Despite the signal improvement and noise reduction DLIR facilitated radiation dose reduction of up to 44% in CTDIvol. Conclusion: Implementation of DLIR in head CT scans enables significant image quality improvement and dose reduction abilities compared to standard ASIR-V. However, the dose reduction feature was proven insufficient to counteract the lack of gantry angulation in wide-detector scanners.