Introduction: To develop and validate a T2-weighted magnetic resonance imaging (MRI)-based radiomic signature associated with disease-free survival (DFS) in locally advanced cervical cancer.
Materials And Methods: The study comprised a training dataset of 132 patients (93 Norwegian; 39 The Cancer Imaging Archive (TCIA) and an independent validation Canadian dataset of 199 patients with FIGO stage IB-IVA cervical cancer treated with chemoradiation. Radiomic features were extracted using PyRadiomics. A radiomic signature was developed based on a multivariable radiomic prognostic model for DFS built using the training dataset, with minimal redundancy maximum relevancy feature selection method. Univariate and multivariable Cox regression analyses were then conducted to examine the association of the derived radiomic signature with DFS.
Results: A radiomic signature was prognostic for DFS in the training cohort (Norwegian hazard ratio [HR] 5.54, p = 0.002; TCIA HR 3.59, p = 0.04). The radiomic signature remained independently associated with DFS (HR 3.70, p = 0.004) when adjusted for stage and tumor volume. The radiomic signature was also prognostic for DFS in the validation cohort, both on univariate analysis (HR 2.22, p = 0.003), and multivariable analysis adjusted for stage and tumor volume (HR 1.84, p = 0.04). The 4-year DFS rates of patients with radiomic signature score > 0 vs ≤ 0 were 48.2 % vs 87.9 %, and 56.4 % vs 80.8 % for training and validation cohorts respectively.
Conclusion: An MRI-based radiomic signature can be used as a prognostic biomarker for DFS in patients with locally advanced cervical cancer undergoing chemoradiation.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1016/j.radonc.2024.110463 | DOI Listing |
Abdom Radiol (NY)
January 2025
First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China.
Purpose: HER2 expression is crucial for the application of HER2-targeted antibody-drug conjugates. This study aims to construct a predictive model by integrating multiparametric magnetic resonance imaging (mpMRI) based multimodal radiomics and the Vesical Imaging-Reporting and Data System (VI-RADS) score for noninvasive identification of HER2 status in bladder urothelial carcinoma (BUC).
Methods: A total of 197 patients were retrospectively enrolled and randomly divided into a training cohort (n = 145) and a testing cohort (n = 52).
Acad Radiol
January 2025
Imaging Center, Harbin Medical University Cancer Hospital, Haping Road No.150, Nangang District, Harbin 150081, China (Q-X.C., L-Q.Z., X-Y.W., H-X.Z., J-J.L., M-C.X., H-Y.S., Z-X.K.). Electronic address:
Rationale And Objectives: To propose a novel MRI-based hyper-fused radiomic approach to predict pathologic complete response (pCR) to neoadjuvant therapy (NAT) in breast cancer (BC).
Materials And Methods: Pretreatment dynamic contrast-enhanced (DCE) MRI and ultra-multi-b-value (UMB) diffusion-weighted imaging (DWI) data were acquired in BC patients who received NAT followed by surgery at two centers. Hyper-fused radiomic features (RFs) and conventional RFs were extracted from DCE-MRI or UMB-DWI.
Med Phys
January 2025
Department of Scientific Research and Academic, Cancer Hospital of China Medical University, Liaoning Cancer Hospital and Institute, Shenyang, Liaoning, P. R. China.
Background: This study aims to explore the value of habitat-based magnetic resonance imaging (MRI) radiomics for predicting the origin of brain metastasis (BM).
Purpose: To investigate whether habitat-based radiomics can identify the metastatic tumor type of BM and whether an imaging-based model that integrates the volume of peritumoral edema (VPE) can enhance predictive performance.
Methods: A primary cohort was developed with 384 patients from two centers, which comprises 734 BM lesions.
J Comput Assist Tomogr
November 2024
From the Department of Radiology, Affiliated Hospital of Nanjing University of Chinese Medicine, Jiangsu Province Hospital of Chinese Medicine, Nanjing, Jiangsu Province, China.
Objectives: The aim of the study is to investigate the ability of preoperative CT (Computed Tomography)-based radiomics signature to predict microvascular invasion (MVI) of intrahepatic mass-forming cholangiocarcinoma (IMCC) and develop radiomics-based prediction models.
Materials And Methods: Preoperative clinical data, basic CT features, and radiomics features of 121 IMCC patients (44 with MVI and 77 without MVI) were retrospectively reviewed. The loading and display of CT images, delineation of the volume of interest, and feature extraction were performed using 3D Slicer.
Front Oncol
December 2024
Department of Radiology, Affiliated Hospital of Qingdao University, Qingdao, China.
Background: The expression level of Ki-67 in nasopharyngeal carcinoma (NPC) affects the prognosis and treatment options of patients. Our study developed and validated an MRI-based radiomics nomogram for preoperative evaluation of Ki-67 expression levels in nasopharyngeal carcinoma (NPC).
Methods: In all, 133 patients with pathologically-confirmed (post-operatively) NPC who underwent MRI examination in one of two medical centers.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!