Background Reliable predictive imaging markers of response to immune checkpoint inhibitors are needed. Purpose To develop and validate a pretreatment CT-based radiomics signature to predict response to immune checkpoint inhibitors in advanced solid tumors. Materials and Methods In this retrospective study, a radiomics signature was developed in patients with advanced solid tumors (including breast, cervix, gastrointestinal) treated with anti-programmed cell death-1 or programmed cell death ligand-1 monotherapy from August 2012 to May 2018 (cohort 1). This was tested in patients with bladder and lung cancer (cohorts 2 and 3). Radiomics variables were extracted from all metastases delineated at pretreatment CT and selected by using an elastic-net model. A regression model combined radiomics and clinical variables with response as the end point. Biologic validation of the radiomics score with RNA profiling of cytotoxic cells (cohort 4) was assessed with Mann-Whitney analysis. Results The radiomics signature was developed in 85 patients (cohort 1: mean age, 58 years ± 13 [standard deviation]; 43 men) and tested on 46 patients (cohort 2: mean age, 70 years ± 12; 37 men) and 47 patients (cohort 3: mean age, 64 years ± 11; 40 men). Biologic validation was performed in a further cohort of 20 patients (cohort 4: mean age, 60 years ± 13; 14 men). The radiomics signature was associated with clinical response to immune checkpoint inhibitors (area under the curve [AUC], 0.70; 95% CI: 0.64, 0.77; < .001). In cohorts 2 and 3, the AUC was 0.67 (95% CI: 0.58, 0.76) and 0.67 (95% CI: 0.56, 0.77; < .001), respectively. A radiomics-clinical signature (including baseline albumin level and lymphocyte count) improved on radiomics-only performance (AUC, 0.74 [95% CI: 0.63, 0.84; < .001]; Akaike information criterion, 107.00 and 109.90, respectively). Conclusion A pretreatment CT-based radiomics signature is associated with response to immune checkpoint inhibitors, likely reflecting the tumor immunophenotype. © RSNA, 2021 See also the editorial by Summers in this issue.
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http://dx.doi.org/10.1148/radiol.2021200928 | 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.
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