Cancer Imaging : the Official Publication of the International Cancer Imaging Society
Overview
Cancer Imaging is the official publication of the International Cancer Imaging Society, providing a comprehensive platform for the dissemination of cutting-edge research and advancements in the field of cancer imaging. This journal covers a wide range of topics, including radiology, nuclear medicine, molecular imaging, and image-guided interventions, with a focus on improving cancer diagnosis, staging, treatment planning, and monitoring. With its multidisciplinary approach, Cancer Imaging serves as an essential resource for researchers, clinicians, and healthcare professionals involved in canc
Details
Details
Abbr.
Cancer Imaging
Publisher
Springer Nature
Start
2000
End
Continuing
Frequency
Two no. a year
p-ISSN
1740-5025
e-ISSN
1470-7330
Country
United Kingdom
Language
English
Metrics
Metrics
h-index / Ranks: 5723
64
SJR / Ranks: 2741
1227
CiteScore / Ranks: 1970
8.60
JIF / Ranks: 1632
4.9
Recent Articles
1.
Chen W, Lin G, Feng Y, Chen Y, Li Y, Li J, et al.
Cancer Imaging
. 2025 Mar;
25(1):35.
PMID: 40083024
Background: To explore the value of intratumoral and peritumoral radiomics in preoperative prediction of anaplastic lymphoma kinase (ALK) mutation status and survival in patients with lung adenocarcinoma. Methods: We retrospectively...
2.
Yin P, Chen W, Fan Q, Yu R, Liu X, Liu T, et al.
Cancer Imaging
. 2025 Mar;
25(1):34.
PMID: 40082955
Background: Accurate segmentation of pelvic and sacral tumors (PSTs) in multi-sequence magnetic resonance imaging (MRI) is essential for effective treatment and surgical planning. Purpose: To develop a deep learning (DL)...
3.
Hosseini S, Hajianfar G, Hall B, Servaes S, Rosa-Neto P, Ghafarian P, et al.
Cancer Imaging
. 2025 Mar;
25(1):33.
PMID: 40075547
Purpose: This study aimed to select robust features against lung motion in a phantom study and use them as input to feature selection algorithms and machine learning classifiers in a...
4.
Ai Q, Leung H, Mo F, Mao K, Wong L, Liang Y, et al.
Cancer Imaging
. 2025 Mar;
25(1):32.
PMID: 40075537
Purpose: To investigate change in diffusion weighted imaging (DWI) between pre-treatment (pre-) and after induction chemotherapy (post-IC) for long-term outcome prediction in advanced nasopharyngeal carcinoma (adNPC). Materials And Methods: Mean...
5.
Dai L, Yin J, Xin X, Yao C, Tang Y, Xia X, et al.
Cancer Imaging
. 2025 Mar;
25(1):31.
PMID: 40075494
Background: Programmed death ligand 1 (PD-L1) expression status, closely related to immunotherapy outcomes, is a reliable biomarker for screening patients who may benefit from immunotherapy. Here, we developed and validated...
6.
Poroes F, Karampa P, Sartoretti T, Najberg H, Froehlich J, Reischauer C, et al.
Cancer Imaging
. 2025 Mar;
25(1):29.
PMID: 40069885
Background: Despite the increasing interest in abbreviated protocols, we adopted an extended protocol for all prostate MRIs. In this study, we assessed the benefits of an extended prostate MRI protocol,...
7.
Holmstrand H, Lindskog M, Sundin A, Hansen T
Cancer Imaging
. 2025 Mar;
25(1):30.
PMID: 40069778
Background: Non-small cell lung cancer (NSCLC) is a common neoplasm with poor prognosis in advanced stages. The clinical work-up in patients with locally advanced NSCLC mostly includes F-fluorodeoxyglucose positron emission...
8.
Chen Z, Sang L, Cheng Y, Wang X, Lv M, Liu Y, et al.
Cancer Imaging
. 2025 Mar;
25(1):28.
PMID: 40065469
Background: In 2020, we introduced the Greater Omentum Imaging-Reporting and Data System (GOI-RADS), a novel classification system related to peritoneal lesions. However, its clinical application remained unvalidated. Objective: This study...
9.
Han X, Guan J, Guo L, Jiao Q, Wang K, Hou F, et al.
Cancer Imaging
. 2025 Mar;
25(1):27.
PMID: 40065444
Background: To construct and assess a deep learning (DL) signature that employs computed tomography imaging to predict the expression status of programmed cell death ligand 1 in patients with bladder...
10.
Yang C, Zhu F, Yang J, Wang M, Zhang S, Zhao Z
Cancer Imaging
. 2025 Mar;
25(1):26.
PMID: 40065426
Objectives: To evaluate the feasibility and value of dynamic contrast-enhanced MRI (DCE-MRI) quantitative analysis and MRI-based radiomics in predicting the efficacy of microwave ablation (MWA) in lung cancers (LCs). Methods:...