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  1. To develop a model based on intra- and peritumoral radiomics features derived from B-mode ultrasound (BMUS), strain elastography (SE), and shear wave elastography (SWE) for cervical lymph node metastasis (LNM)...

    Authors: Xian-Ya Zhang, Di Zhang, Wang Zhou, Zhi-Yuan Wang, Chao-Xue Zhang, Jin Li, Liang Wang and Xin-Wu Cui
    Citation: Cancer Imaging 2025 25:13
  2. Castleman disease (CD) is a rare lymphoproliferative disorder. This study is to evaluate the correlation between 18F-flurodeoxyglucose (18F-FDG) positron emission tomography-computed tomography (PET/CT) and clini...

    Authors: Guolin Wang, Qianhe Xu, Yinuo Liu, Huatao Wang, Fei Yang, Zhenfeng Liu and Xinhui Su
    Citation: Cancer Imaging 2025 25:12
  3. Intratumor heterogeneity (ITH) is a key biological characteristic of gliomas. This study aimed to characterize ITH in adult-type diffuse gliomas and assess the feasibility of using habitat imaging based on dyn...

    Authors: Xingrui Wang, Zhenhui Xie, Xiaoqing Wang, Yang Song, Shiteng Suo, Yan Ren, Wentao Hu, Yi Zhu, Mengqiu Cao and Yan Zhou
    Citation: Cancer Imaging 2025 25:11
  4. The machine learning model, which has been widely applied in prognosis assessment, can comprehensively evaluate patient status for accurate prognosis classification. There still has been a debate about which p...

    Authors: Jin-Can Huang, Shao-Cheng Lyu, Bing Pan, Han-Xuan Wang, You-Wei Ma, Tao Jiang, Qiang He and Ren Lang
    Citation: Cancer Imaging 2025 25:10
  5. The present study aimed to develop a nomogram model for predicting overall survival (OS) in esophageal squamous cell carcinoma (ESCC) patients.

    Authors: Ting Yan, Zhenpeng Yan, Guohui Chen, Songrui Xu, Chenxuan Wu, Qichao Zhou, Guolan Wang, Ying Li, Mengjiu Jia, Xiaofei Zhuang, Jie Yang, Lili Liu, Lu Wang, Qinglu Wu, Bin Wang and Tianyi Yan
    Citation: Cancer Imaging 2025 25:9
  6. Previous studies utilizing dual-energy CT (DECT) for evaluating treatment efficacy in nasopharyngeal cancinoma (NPC) are limited. This study aimed to investigate whether the parameters from DECT can predict th...

    Authors: Huanhuan Ren, Junhao Huang, Yao Huang, Bangyuan Long, Mei Zhang, Jing Zhang, Huarong Li, Tingting Huang, Daihong Liu, Ying Wang and Jiuquan Zhang
    Citation: Cancer Imaging 2025 25:8
  7. True total-body and extended axial field-of-view (AFOV) PET/CT with 1m or more of body coverage are now commercially available and dramatically increase system sensitivity over conventional AFOV PET/CT. The Si...

    Authors: Johanna Ingbritsen, Jason Callahan, Hugh Morgan, Melissa Munro, Robert E. Ware and Rodney J. Hicks
    Citation: Cancer Imaging 2025 25:7
  8. Programmed cell death 1/programmed death ligand-1 (PD-L1)-based immune checkpoint blockade is an effective treatment approach for non-small-cell lung cancer (NSCLC). However, immunohistochemistry does not accu...

    Authors: Lingzhou Zhao, Jiali Gong, Sisi Liao, Wenhua Huang, Jinhua Zhao and Yan Xing
    Citation: Cancer Imaging 2025 25:6
  9. Radiomic analysis of quantitative features extracted from segmented medical images can be used for predictive modeling of prognosis in brain tumor patients. Manual segmentation of the tumor components is time-...

    Authors: Qi Wan, Clifford Lindsay, Chenxi Zhang, Jisoo Kim, Xin Chen, Jing Li, Raymond Y. Huang, David A. Reardon, Geoffrey S. Young and Lei Qin
    Citation: Cancer Imaging 2025 25:5
  10. To establish and validate a dual-modal radiomics nomogram from grayscale ultrasound and color doppler flow imaging (CDFI) of cervical lymph nodes (LNs), aiming to improve the diagnostic accuracy of metastatic ...

    Authors: Jiajia Tang, Yan Tian, Jiaojiao Ma, Xuehua Xi, Liangkai Wang, Zhe Sun, Xinyi Liu, Xuejiao Yu and Bo Zhang
    Citation: Cancer Imaging 2025 25:4
  11. Radiomics holds great potential for the noninvasive evaluation of EGFR-TKIs and ICIs responses, but data privacy and model robustness challenges limit its current efficacy and safety. This study aims to develo...

    Authors: Xingping Zhang, Xingting Qiu, Yue Zhang, Qingwen Lai, Yanchun Zhang and Guijuan Zhang
    Citation: Cancer Imaging 2025 25:3
  12. Current diagnostic imaging modalities have limited ability to differentiate between malignant and benign pancreaticobiliary disease, and lack accuracy in detecting lymph node metastases. 18F-Prostate-Specific Mem...

    Authors: Jisce R. Puik, Thomas T. Poels, Gerrit K. J. Hooijer, Matthijs C. F. Cysouw, Joanne Verheij, Johanna W. Wilmink, Elisa Giovannetti, Geert Kazemier, Arantza Farina Sarasqueta, Daniela E. Oprea-Lager and Rutger-Jan Swijnenburg
    Citation: Cancer Imaging 2025 25:2
  13. Prostate cancer (PCa) is the leading cause of cancer-related morbidity and mortality in men worldwide. An early and accurate diagnosis is crucial for effective treatment and prognosis. Traditional invasive pro...

    Authors: Xin Huang, Huarong Ye, Yugang Hu, Yumeng Lei, Yi Tian, Xingyue Huang, Jun Zhang, Yao Zhang, Bin Gui, Qianhui Liu, Ge Zhang and Qing Deng
    Citation: Cancer Imaging 2025 25:1
  14. To assess and compare the diagnostic efficiency of histogram analysis of monochromatic and iodine images derived from spectral CT in predicting Ki-67 expression in gastric gastrointestinal stromal tumors (gGIST).

    Authors: Xianwang Liu, Tao Han, Yuzhu Wang, Hong Liu, Juan Deng, Caiqiang Xue, Shenglin Li and Junlin Zhou
    Citation: Cancer Imaging 2024 24:173
  15. This study aims to evaluate the effectiveness of deep learning features derived from multi-sequence magnetic resonance imaging (MRI) in determining the O6-methylguanine-DNA methyltransferase (MGMT) promoter methy...

    Authors: Xuan Yu, Jing Zhou, Yaping Wu, Yan Bai, Nan Meng, Qingxia Wu, Shuting Jin, Huanhuan Liu, Panlong Li and Meiyun Wang
    Citation: Cancer Imaging 2024 24:172
  16. Staging of non-small cell lung cancer (NSCLC) is commonly based on [18F]FDG PET/CT, in particular to exclude distant metastases and guide local therapy approaches like resection and radiotherapy. Although it is h...

    Authors: Alexander Brose, Isabelle Miederer, Jochem König, Eleni Gkika, Jörg Sahlmann, Tanja Schimek-Jasch, Mathias Schreckenberger, Ursula Nestle, Jutta Kappes and Matthias Miederer
    Citation: Cancer Imaging 2024 24:171
  17. The complex interactions of the tumor micromilieu may be reflected by diffusion-weighted imaging (DWI) derived from the magnetic resonance imaging (MRI). The present study investigated the association between ...

    Authors: Alexey Surov, Jan Borggrefe, Anne-Kathrin Höhn and Hans-Jonas Meyer
    Citation: Cancer Imaging 2024 24:170
  18. Gastrointestinal stromal tumors (GISTs) are the most common mesenchymal tumors of the gastrointestinal tract. Recent advent of tyrosine kinase inhibitors (TKIs) has significantly improved the prognosis of GIST...

    Authors: Zhenhui Xie, Qingwei Zhang, Ranying Zhang, Yuxuan Zhao, Wang Zhang, Yang Song, Dexin Yu, Jiang Lin, Xiaobo Li, Shiteng Suo and Yan Zhou
    Citation: Cancer Imaging 2024 24:169
  19. Diffuse large B-cell lymphoma (DLBCL) is a highly heterogeneous hematological malignancy resulting in a range of outcomes, and the early prediction of these outcomes has important implications for patient mana...

    Authors: Zhuxu Sun, Tianshuo Yang, Chongyang Ding, Yuye Shi, Luyi Cheng, Qingshen Jia and Weijing Tao
    Citation: Cancer Imaging 2024 24:168
  20. To develop a multimodal predictive model, Radiomics Integrated TLSs System (RAITS), based on preoperative CT radiomic features for the identification of TLSs in stage I lung adenocarcinoma patients and to eval...

    Authors: Xiaojiang Zhao, Yuhang Wang, Mengli Xue, Yun Ding, Han Zhang, Kai Wang, Jie Ren, Xin Li, Meilin Xu, Jun Lv, Zixiao Wang and Daqiang Sun
    Citation: Cancer Imaging 2024 24:167
  21. Recent advancements in novel anti-human epidermal growth factor receptor 2 (HER2) antibody-drug conjugates (ADCs) have highlighted the emerging HER2-low breast cancer subtype with promising therapeutic efficac...

    Authors: Yuan Gao, Lei Yin, Linlin Ma, Caixia Wu, Xiaojuan Zhu, Hongjin Liu, Li Liang, Jinzhi Chen, Yulong Chen, Jingming Ye, Ling Xu and Meng Liu
    Citation: Cancer Imaging 2024 24:166
  22. To verify overall survival predictions made with residual convolutional neural network-determined morphological response (ResNet-MR) in patients with unresectable synchronous liver-only metastatic colorectal c...

    Authors: Sung-Hua Chiu, Hsiao-Chi Li, Wei-Chou Chang, Chao-Cheng Wu, Hsuan-Hwai Lin, Cheng-Hsiang Lo and Ping-Ying Chang
    Citation: Cancer Imaging 2024 24:165
  23. To assess the utility of multiparametric MRI and clinical indicators in distinguishing nuclear grade and survival of clear cell renal cell carcinoma (ccRCC) complicated with venous tumor thrombus (VTT).

    Authors: Jian Zhao, Honghao Xu, Yonggui Fu, Xiaohui Ding, Meifeng Wang, Cheng Peng, Huanhuan Kang, Huiping Guo, Xu Bai, Shaopeng Zhou, Kan Liu, Lin Li, Xu Zhang, Xin Ma, Xinjiang Wang and Haiyi Wang
    Citation: Cancer Imaging 2024 24:164
  24. It is difficult for radiologists, especially junior radiologists with limited experience to make differential diagnoses between mediastinal lymphomas and thymic epithelial tumors (TETs) due to the overlapping ...

    Authors: Han Xia, Jiahui Yu, Kehui Nie, Jun Yang, Li Zhu and Shengjian Zhang
    Citation: Cancer Imaging 2024 24:163
  25. Although many well-known factors affect the maximum standardized uptake value (SUVmax), it remains the most requested and used parameter, especially among clinicians, despite other parameters, such as the stan...

    Authors: Cristiano Pini, Margarita Kirienko, Fabrizia Gelardi, Paola Bossi, Daoud Rahal, Luca Toschi, Gaia Ninatti, Marcello Rodari, Giuseppe Marulli, Lidija Antunovic, Arturo Chiti, Emanuele Voulaz and Martina Sollini
    Citation: Cancer Imaging 2024 24:162
  26. Identifying DNA mismatch repair deficiency (MMRd) is important for prognosis risk stratification in patients with early-stage endometrial cancer (EC), but there is a notable absence of cost-effective and non-i...

    Authors: Xiaoran Li, Bixiao Cui, Shijun Wang, Min Gao, Qiuyun Xing, Huawei Liu and Jie Lu
    Citation: Cancer Imaging 2024 24:161
  27. Bone biopsy is the gold standard for diagnosing bone metastases. However, there is no clinical consensus regarding the optimal imaging test for determining the puncture site.

    Authors: Yujie Chang, Yifeng Gu, Shunyi Ruan, Shengyu Xu, Jing Sun, Zhiyuan Jiang, Guangyu Yao, Zhiyu Wang and Hui Zhao
    Citation: Cancer Imaging 2024 24:160
  28. Advances in cancer diagnosis and treatment have substantially improved patient outcomes and survival in recent years. However, up to 75% of cancer patients and survivors, including those with non-central nervo...

    Authors: Quanquan Gu, Liya Wang, Tricia Z. King, Hongbo Chen, Longjiang Zhang, Jianming Ni and Hui Mao
    Citation: Cancer Imaging 2024 24:158
  29. Two-deoxy-2-[fluorine-18]-fluoro-d-glucose (18F-FDG) positron emission tomography (PET) is useful for detecting malignant lesions; however, the clinical significance of cardiac 18F-FDG uptake in patients with can...

    Authors: Kosuke Hashimoto, Kyoichi Kaira, Hisao Imai, Ou Yamaguchi, Atsuto Mouri, Ayako Shiono, Yu Miura, Kunihiko Kobayashi, Hiroshi Kagamu and Ichiei Kuji
    Citation: Cancer Imaging 2024 24:157
  30. There is an unmet need for a more accurate molecular imaging radiotracer in the field of non-seminomatous germ cell tumors (NSGCT). The clinical problem is that no single imaging modality is able to differenti...

    Authors: Narjess Ayati, Emran Askari, Maryam Fotouhi, Masume Soltanabadi, Atena Aghaee, Hesamoddin Roustaei and Andrew M. Scott
    Citation: Cancer Imaging 2024 24:156
  31. The aim of this study was to establish an ensemble learning model based on clinicopathological parameter and ultrasound radomics for assessing the risk of lateral cervical lymph node with short diameter less t...

    Authors: Yan Wang, Shuangqingyue Zhang, Minghui Zhang, Gaosen Zhang, Zhiguang Chen, Xuemei Wang, Ziyi Yang, Zijun Yu, He Ma, Zhihong Wang and Liang Sang
    Citation: Cancer Imaging 2024 24:155
  32. The Response Evaluation in Solid Tumors (RECIST) 1.1 provides key guidance for performing imaging response assessment and defines image-based outcome metrics in oncology clinical trials, including progression ...

    Authors: Kathleen Ruchalski, Jordan M. Anaokar, Matthias R. Benz, Rohit Dewan, Michael L. Douek and Jonathan G. Goldin
    Citation: Cancer Imaging 2024 24:154
  33. To develop an artificial intelligence (AI)-based model using Radiomics, deep learning (DL) features extracted from 18F-fluorodeoxyglucose (18F-FDG) Positron emission tomography/Computed Tomography (PET/CT) images...

    Authors: Ping Yuan, Zhen-Hao Huang, Yun-Hai Yang, Fei-Chao Bao, Ke Sun, Fang-Fang Chao, Ting-Ting Liu, Jing-Jing Zhang, Jin-Ming Xu, Xiang-Nan Li, Feng Li, Tao Ma, Hao Li, Zi-Hao Li, Shan-Feng Zhang, Jian Hu…
    Citation: Cancer Imaging 2024 24:153
  34. The metabolic response of primary central nervous system lymphoma (PCNSL) patients has yet to be evaluated. This study aimed to assess the prognostic value of a novel scoring scale, the intracranial metabolic ...

    Authors: Yiwen Mo, Yongjiang Li, Yuqian Huang, Mingshi Chen, Chao Zhou, Xinling Li, Yuan Wei, Ruping Li, Wei Fan and Xu Zhang
    Citation: Cancer Imaging 2024 24:152
  35. This study aims to construct predicting models using radiomic and clinical features in predicting first-line vascular endothelial growth factor receptor-tyrosine kinase inhibitor (VEGFR-TKI) early resistance i...

    Authors: Yichen Wang, Xinxin Zhang, Sicong Wang, Hongzhe Shi, Xinming Zhao and Yan Chen
    Citation: Cancer Imaging 2024 24:151
  36. Postoperative progressive cerebral edema and hemorrhage (PPCEH) are major complications after meningioma resection, yet their preoperative predictive studies are limited. The aim is to develop and validate a m...

    Authors: Kangjian Hu, Guirong Tan, Xueqing Liao, Weiyin Vivian Liu, Wenjing Han, Lingjing Hu, Haihui Jiang, Lijuan Yang, Ming Guo, Yaohong Deng, Zhihua Meng and Xiang Liu
    Citation: Cancer Imaging 2024 24:149
  37. To explore the value of dual-energy computed tomography (DECT) in differentiating pathological subtypes and the expression of immunohistochemical markers Ki-67 and thyroid transcription factor 1 (TTF-1) in pat...

    Authors: Yuting Wu, Jingxu Li, Li Ding, Jianbin Huang, Mingwang Chen, Xiaomei Li, Xiang Qin, Lisheng Huang, Zhao Chen, Yikai Xu and Chenggong Yan
    Citation: Cancer Imaging 2024 24:146
  38. Directly-injected therapies (DIT) include a broad range of agents within a developing research field in cancer immunotherapy, with encouraging clinical trial results in various tumour subtypes. Currently, the ...

    Authors: George Gabriel Bitar, Melissa Persad, Alina Dragan, Adebayo Alade, Pablo Jiménez-Labaig, Edward Johnston, Samuel J Withey, Nicos Fotiadis, Kevin J. Harrington and Derfel ap Dafydd
    Citation: Cancer Imaging 2024 24:145
  39. This study aims to develop and validate a predictive model that integrates clinical features, MRI radiomics, and nutritional-inflammatory biomarkers to forecast progression-free survival (PFS) in cervical canc...

    Authors: Qi Yan, Menghan- Wu, Jing Zhang, Jiayang- Yang, Guannan- Lv, Baojun- Qu, Yanping- Zhang, Xia Yan and Jianbo- Song
    Citation: Cancer Imaging 2024 24:144
  40. Tumor vascular physiology is an important determinant of disease progression as well as the therapeutic outcome of cancer treatment. Angiogenesis or the lack of it provides crucial information about the tumor’...

    Authors: Binita Shrestha, Noah B Stern, Annie Zhou, Andrew Dunn and Tyrone Porter
    Citation: Cancer Imaging 2024 24:143
  41. To conduct a head-to-head comparison between deep learning (DL) and radiomics models across institutions for predicting microvascular invasion (MVI) in hepatocellular carcinoma (HCC) and to investigate the mod...

    Authors: Weibin Zhang, Qihui Guo, Yuli Zhu, Meng Wang, Tong Zhang, Guangwen Cheng, Qi Zhang and Hong Ding
    Citation: Cancer Imaging 2024 24:142
  42. To compare the performance between one-slice two-dimensional (2D) and whole-volume three-dimensional (3D) computed tomography (CT)-based radiomics models in the prediction of lymphovascular invasion (LVI) stat...

    Authors: Yang Li, Xiaolong Gu, Li Yang, Xiangming Wang, Qi Wang, Xiaosheng Xu, Andu Zhang, Meng Yue, Mingbo Wang, Mengdi Cong, Jialiang Ren, Wei Ren and Gaofeng Shi
    Citation: Cancer Imaging 2024 24:141
  43. To explore the application value of a multimodal deep learning radiomics (MDLR) model in predicting the risk status of postoperative progression in solid stage I non-small cell lung cancer (NSCLC).

    Authors: Qionglian Kuang, Bao Feng, Kuncai Xu, Yehang Chen, Xiaojuan Chen, Xiaobei Duan, Xiaoyan Lei, Xiangmeng Chen, Kunwei Li and Wansheng Long
    Citation: Cancer Imaging 2024 24:140
  44. Authors: Ayatullah G. Mostafa, Zachary Abramson, Mina Ghbrial, Som Biswas, Sherwin Chan, Himani Darji, Jessica Gartrell, Seth E. Karol, Yimei Li, Daniel A. Mulrooney, Tushar Patni, Tarek M Zaghloul and M. Beth McCarville
    Citation: Cancer Imaging 2024 24:138

    The original article was published in Cancer Imaging 2024 24:115

  45. Since it has been found that the maximum metabolic activity of a cancer lesion shifts toward the lesion edge during cancer progression, normalized distances from the hot spot of radiotracer uptake to tumor cen...

    Authors: Sun-pyo Hong, Sang Mi Lee, Ik Dong Yoo, Jong Eun Lee, Sun Wook Han, Sung Yong Kim and Jeong Won Lee
    Citation: Cancer Imaging 2024 24:136

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