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The deep learning radiomics nomogram helps to evaluate the lymph node status in cervical adenocarcinoma/adenosquamous carcinoma.
Front Oncol
December 2024
Department of Radiology, Jinshan Hospital, Fudan University, Shanghai, China.
Objectives: The accurate assessment of lymph node metastasis (LNM) can facilitate clinical decision-making on radiotherapy or radical hysterectomy (RH) in cervical adenocarcinoma (AC)/adenosquamous carcinoma (ASC). This study aims to develop a deep learning radiomics nomogram (DLRN) to preoperatively evaluate LNM in cervical AC/ASC.
Materials And Methods: A total of 652 patients from a multicenter were enrolled and randomly allocated into primary, internal, and external validation cohorts.
CT-3D MERGE fusion imaging improves image quality compared with CT and 3D MERGE in patients with lumbar disc herniation.
Front Neurol
December 2024
Department of Radiology, Qujing Second People's Hospital, Qujing, China.
Background: CT-routine MRI fusion imaging has recently become available to evaluate spinal anatomy before surgery. Due to the 3-5 mm slice thickness and non-isotropic of routine MRI sequence, the CT-routine MRI fusion imaging is not good. The MRI multiple recalled gradient echo (MERGE) sequence is potentially useful in diagnosis of lumbar degeneration disease due to the better nerve roots visualization, 1 mm slice thickness and its isotropy.
View Article and Find Full Text PDFEnsemble learning-based radiomics model for discriminating brain metastasis from glioblastoma.
Eur J Radiol
December 2024
Department of Diagnostic Radiology, City of Hope National Medical Center, Duarte, CA, USA.
Objective: Differentiating between brain metastasis (BM) and glioblastoma (GBM) preoperatively is challenging due to their similar imaging features on conventional brain MRI. This study aimed to enhance diagnostic accuracy through a machine learning model based on MRI radiomics data.
Methods: This retrospective study included 235 patients with confirmed solitary BM and 273 patients with GBM.
Development and Validation of a Nomogram Based on Multiparametric MRI for Predicting Lymph Node Metastasis in Endometrial Cancer: A Retrospective Cohort Study.
Acad Radiol
December 2024
Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China (Y.T., Y.W., Y.Y., X.Q., Y.H., J.L.); Key Laboratory of Early Prevention and Treatment for Regional High Frequency Tumor (Guangxi Medical University), Ministry of Education, Nanning 530021, Guangxi Zhuang Autonomous Region, PR China (J.L.). Electronic address:
Rationale And Objectives: To develop a radiomics nomogram based on clinical and magnetic resonance features to predict lymph node metastasis (LNM) in endometrial cancer (EC).
Materials And Methods: We retrospectively collected 308 patients with endometrial cancer (EC) from two centers. These patients were divided into a training set (n=155), a test set (n=67), and an external validation set (n=86).
Intraoperative variations in intra-axial brain tumor size after craniotomy: a prospective study with histopathological and tumor tissue composition correlation, introducing concepts of tumor expansion and tumor surfacing.
Neurosurg Rev
December 2024
Department of Neurosurgery, Neurosurgery Clinic, Birgunj, Nepal.
Intraoperative assessment of tumor margins can be challenging; as neoplastic cells may extend beyond the margins seen on preoperative imaging. Real-time intraoperative ultrasonography (IOUS) has emerged as a valuable tool for delineating tumor boundaries during surgery. However, concerns remain regarding its ability to accurately distinguish between tumor margins, peritumoral edema, and normal brain tissue.
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