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High-risk habitat radiomics model based on ultrasound images for predicting lateral neck lymph node metastasis in differentiated thyroid cancer.
BMC Med Imaging
January 2025
Cancer Center, Department of Ultrasound Medicine, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, No. 158 Shang tang Road, Hangzhou, Zhejiang, 310011, China.
Background: This study aims to evaluate the predictive usefulness of a habitat radiomics model based on ultrasound images for anticipating lateral neck lymph node metastasis (LLNM) in differentiated thyroid cancer (DTC), and for pinpointing high-risk habitat regions and significant radiomics traits.
Methods: A group of 214 patients diagnosed with differentiated thyroid carcinoma (DTC) between August 2021 and August 2023 were included, consisting of 107 patients with confirmed postoperative lateral lymph node metastasis (LLNM) and 107 patients without metastasis or lateral cervical lymph node involvement. An additional cohort of 43 patients was recruited to serve as an independent external testing group for this study.
Integrated intraoperative predictive model for malignancy risk assessment of thyroid nodules with atypia of undetermined significance cytology.
Sci 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 PDFTOM500: A Multi-Organ Annotated Orbital MRI Dataset for Thyroid Eye Disease.
Sci Data
January 2025
Department of Ophthalmology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
This study presents TOM500, a comprehensive multi-organ annotated orbital magnetic resonance imaging (MRI) dataset. It includes clinical data, T2-weighted MRI scans, and corresponding segmentations from 500 patients with thyroid eye disease (TED) during their initial visit. TED is a common autoimmune disorder with distinct orbital MRI features.
View Article and Find Full Text PDFDeep Learning Technology for Classification of Thyroid Nodules Using Multi-View Ultrasound Images: Potential Benefits and Challenges in Clinical Application.
Endocrinol Metab (Seoul)
January 2025
Division of Endocrinology and Metabolism, Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul, Korea.
Background: This study aimed to evaluate the applicability of deep learning technology to thyroid ultrasound images for classification of thyroid nodules.
Methods: This retrospective analysis included ultrasound images of patients with thyroid nodules investigated by fine-needle aspiration at the thyroid clinic of a single center from April 2010 to September 2012. Thyroid nodules with cytopathologic results of Bethesda category V (suspicious for malignancy) or VI (malignant) were defined as thyroid cancer.
Validation of a tele-robotic ultrasound system for abdomen and thyroid gland explorations: a comparison with standard ultrasound.
Ultrasound J
January 2025
Department of Radiology, Hospital Universitari Vall d'Hebron, Passeig de la Vall d'Hebron, 119-129, 08035, Barcelona, Spain.
Background: Tele-robotic ultrasound (US) is a novel technique that might help overcome the current shortage of radiologists and poor access to radiologists and/or sonographers in remote or rural areas. Despite the promising results of this technology in the past two decades, there is still insufficient data about its advantages and limits, as well as the implementation in routine clinical practice and the learning curve for the user. The purpose of this prospective cohort-based study is to evaluate the performance of a 5G-based tele-robotic US system for abdominal and thyroid gland assessment in a cohort of healthy volunteers and outpatients, as well as assessing the learning curve and patient satisfaction.
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