Background: Radiofrequency ablation is routinely used to treat cardiac arrhythmias, but gaps remain in ablation lesion sets because there is no direct visualization of ablation-related changes. In this study, we acutely identify and target gaps using a real-time magnetic resonance imaging (RT-MRI) system, leading to a complete and transmural ablation in the atrium.
Methods And Results: A swine model was used for these studies (n=12). Ablation lesions with a gap were created in the atrium using fluoroscopy and an electroanatomic system in the first group (n=5). The animal was then moved to a 3-tesla MRI system where high-resolution late gadolinium enhancement MRI was used to identify the gap. Using an RT-MRI catheter navigation and visualization system, the gap area was ablated in the MR scanner. In a second group (n=7), ablation lesions with varying gaps in between were created under RT-MRI guidance, and gap lengths determined using late gadolinium enhancement MR images were correlated with gap length measured from gross pathology. Gaps up to 1.0 mm were identified using gross pathology, and gaps up to 1.4 mm were identified using late gadolinium enhancement MRI. Using an RT-MRI system with active catheter navigation gaps can be targeted acutely, leading to lesion sets with no gaps. The correlation coefficient (R(2)) between the gap length was identified using MRI, and the gross pathology was 0.95.
Conclusions: RT-MRI system can be used to identify and acutely target gaps in atrial ablation lesion sets. Acute targeting of gaps in ablation lesion sets can potentially lead to significant improvement in clinical outcomes.
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http://dx.doi.org/10.1161/CIRCEP.112.973164 | DOI Listing |
Clin Rheumatol
January 2025
Department of Pediatrics, Qilu Hospital of Shandong University, Jinan, 250012, China.
Objective: We aimed to develop a useful nomogram for early identification of Kawasaki disease (KD) children at a high risk of intravenous immunoglobulin (IVIG) resistance and coronary artery lesion (CAL) complications to improve KD management.
Methods: Clinical data from 400 patients treated at our hospital between January 1, 2016, and December 31, 2023, were collected. Lasso regression was utilized to screen risk factors for IVIG resistance and CAL involvement.
Ann Hematol
January 2025
Department of Radiology, Radiotherapy and Hematology, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy.
In a previous preliminary study, radiomic features from the largest and the hottest lesion in baseline F-FDG PET/CT (bPET/CT) of classical Hodgkin's Lymphoma (cHL) predicted early response-to-treatment and prognosis. Aim of this large retrospectively-validated study is to evaluate the predictive role of two-lesions radiomics in comparison with other clinical and conventional PET/CT models. cHL patients with bPET/CT between 2010 and 2020 were retrospectively included and randomized into training-validation sets.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Thyroid Surgery, Ningbo Medical Center Lihuili Hospital, Ningbo, China.
Management of thyroid nodules with atypia of undetermined significance/follicular lesion of undetermined significance (AUS/FLUS) cytology is challenging because of uncertain malignancy risk. Intraoperative frozen section pathology provides real-time diagnosis for AUS/FLUS nodules undergoing surgery, but its accuracy is limited. This study aimed to develop an integrated predictive model combining clinical, ultrasound and IOFS features to improve intraoperative malignancy risk assessment.
View Article and Find Full Text PDFInsights Imaging
January 2025
Medical Research Department, Qingdao Hospital, University of Health and Rehabilitation Sciences (Qingdao Municipal Hospital), Qingdao, P. R. China.
Objective: To develop an automatic segmentation model to delineate the adnexal masses and construct a machine learning model to differentiate between low malignant risk and intermediate-high malignant risk of adnexal masses based on ovarian-adnexal reporting and data system (O-RADS).
Methods: A total of 663 ultrasound images of adnexal mass were collected and divided into two sets according to experienced radiologists: a low malignant risk set (n = 446) and an intermediate-high malignant risk set (n = 217). Deep learning segmentation models were trained and selected to automatically segment adnexal masses.
Am J Cancer Res
December 2024
Department of Breast Surgery, Huangpu Branch, Shanghai Ninth People's Hospital, Shanghai Jiaotong University School of Medicine Shanghai 200011, China.
Breast cancer is one of the malignant tumors that seriously threaten women's health, and early diagnosis and detection of breast cancer are crucial for effective treatment. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is an important diagnostic tool that allows for the dynamic observation of blood flow characteristics of breast tumors, including small lesions within the affected tissue. Currently, it is widely used in clinical practice and has been shown promising prospects.
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