Radiology. Imaging cancer最新文献

{"title":"Quantitative Ablation Confirmation Methods in Percutaneous Thermal Ablation of Malignant Liver Tumors: Technical Insights, Clinical Evidence, and Future Outlook.","authors":"Iwan Paolucci, Jessica Albuquerque Marques Silva, Yuan-Mao Lin, Alexander Shieh, Anna Maria Ierardi, Gianpaolo Caraffiello, Carlo Gazzera, Kyle A Jones, Paolo Fonio, Reto Bale, Kristy K Brock, Marco Calandri, Bruno C Odisio","doi":"10.1148/rycan.240293","DOIUrl":"https://doi.org/10.1148/rycan.240293","url":null,"abstract":"<p><p>Percutaneous image-guided thermal ablation is an established local curative-intent treatment technique for the treatment of primary and secondary malignant liver tumors. Whereas margin assessment after surgical resection can be accomplished with microscopic examination of the resected specimen, margin assessment after percutaneous thermal ablation relies on cross-sectional imaging. The critical measure of technical success is the minimal ablative margin (MAM), defined as the minimum distance between the tumor and the edge of the ablation zone. Traditionally, the MAM has been assessed qualitatively using anatomic landmarks, which has suboptimal accuracy and reproducibility and is prone to operator bias. Consequently, specialized software-based methods have been developed to standardize and automate MAM quantification. In this review, the authors discuss the technical components of such methods, including image acquisition, segmentation, registration, and MAM computation, define the sources of measurement error, describe available software solutions in terms of image processing techniques and modes of integration, and outline the current clinical evidence, which strongly supports the use of such dedicated software. Finally, the authors discuss current logistical and financial barriers to widespread use of ablation confirmation methods as well as potential solutions. <b>Keywords:</b> Ablation Techniques, CT, Image Postprocessing, Liver <i>Supplemental material is available for this article.</i> © RSNA, 2025.</p>","PeriodicalId":20786,"journal":{"name":"Radiology. Imaging cancer","volume":"7 3","pages":"e240293"},"PeriodicalIF":5.6,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144041865","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Time to Consider Diffusion Time: Exploring the Potential of Time-Dependent Diffusion MRI in Breast Cancer Imaging.","authors":"Masako Kataoka, Mami Iima","doi":"10.1148/rycan.250129","DOIUrl":"https://doi.org/10.1148/rycan.250129","url":null,"abstract":"","PeriodicalId":20786,"journal":{"name":"Radiology. Imaging cancer","volume":"7 3","pages":"e250129"},"PeriodicalIF":5.6,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144044768","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of Metastasis-directed Therapy Guided by Different PET/CT Radiotracers on Distant and Local Disease Control in Oligorecurrent Hormone-sensitive Prostate Cancer: A Secondary Analysis of the PRECISE-MDT Study.","authors":"Francesco Lanfranchi, Liliana Belgioia, Domenico Albano, Luca Triggiani, Flavia Linguanti, Luca Urso, Rosario Mazzola, Alessio Rizzo, Elisa D'Angelo, Francesco Dondi, Eneida Mataj, Gloria Pedersoli, Elisabetta Maria Abenavoli, Luca Vaggelli, Beatrice Detti, Naima Ortolan, Antonio Malorgio, Alessia Guarneri, Federico Garrou, Matilde Fiorini, Serena Grimaldi, Pietro Ghedini, Giuseppe Carlo Iorio, Antonella Iudicello, Guido Rovera, Giuseppe Fornarini, Diego Bongiovanni, Michela Marcenaro, Filippo Maria Pazienza, Giorgia Timon, Matteo Salgarello, Manuela Racca, Mirco Bartolomei, Stefano Panareo, Umberto Ricardi, Francesco Bertagna, Filippo Alongi, Salvina Barra, Silvia Morbelli, Gianmario Sambuceti, Matteo Bauckneht","doi":"10.1148/rycan.240150","DOIUrl":"https://doi.org/10.1148/rycan.240150","url":null,"abstract":"<p><p>Prospective trials suggest that metastasis-directed therapy (MDT) is an effective treatment for patients with oligometastatic prostate cancer (PCa). Gallium 68 (⁶⁸Ga) prostate-specific membrane antigen (PSMA)-11 PET/CT-guided MDT seems to improve the oncologic outcome in these patients compared with fluorine 18 (¹⁸F)-fluorocholine and ¹⁸F-PSMA-1007 PET/CT-guided MDT, but the effects in terms of local or distant disease control remain unclear. Thus, the present subanalysis of the PRECISE-MDT study analyzed patients with hormone-sensitive PCa who underwent MDT guided by PET/CT for nodal or bone oligorecurrent disease and were restaged with the same imaging modality in case of biochemical recurrence after MDT. Among 340 lesions detected in 241 male patients (median age, 74 [IQR, 9] years), ¹⁸F-fluorocholine, ⁶⁸Ga-PSMA-11, and ¹⁸F-PSMA-1007 PET/CT-guided MDT was performed in 179, 81, and 80 lesions, respectively. At restaging imaging, the PET/CT imaging modality used to guide MDT was not significantly associated with local recurrence-free survival (LRFS), with median LRFS not reached for ⁶⁸Ga-PSMA-11 PET/CT, ¹⁸F-PSMA-11 PET/CT, and ¹⁸F-fluorocholine PET/CT (<i>P</i> = .73). However, the detection rate of a new metastasis was significantly higher if MDT was guided by ¹⁸F-fluorocholine PET/CT (119 of 179 lesions, 66.5%) compared with ⁶⁸Ga-PSMA-11 or ¹⁸F-PSMA-1007 PET/CT (23 of 81 lesions, 28%, and 27 of 80, 34%, respectively; <i>P</i> < .001 for both). Moreover, MDT guided by ⁶⁸Ga-PSMA-11 PET/CT led to an improved median metastasis-free survival (MFS) (not reached) compared with ¹⁸F-PSMA-1007 (median MFS, 24.9 months; <i>P</i> < .001) or ¹⁸F-fluorocholine PET/CT (median MFS, 18 months; <i>P</i> < .001). These findings suggest that using different PET/CT imaging modalities to guide MDT might impact the distant disease control in this clinical scenario. <b>Keywords:</b> Radiation Therapy, Oncology, Urinary, Prostate, PET/CT <i>Supplemental material is available for this article.</i> Published under a CC BY 4.0 license.</p>","PeriodicalId":20786,"journal":{"name":"Radiology. Imaging cancer","volume":"7 3","pages":"e240150"},"PeriodicalIF":5.6,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144079877","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Air Embolism after Percutaneous Lung Biopsy or Ablation: A Report of Six Cases.","authors":"Rebecca Choi, Haylie Kieu-Mi Phan, Varshana Gurusamy, Rahul A Sheth, Bruno C Odisio, Kelvin Hong, Alda L Tam","doi":"10.1148/rycan.240379","DOIUrl":"10.1148/rycan.240379","url":null,"abstract":"<p><p>Systemic air embolism is a rare but potentially life-threatening complication of percutaneous lung biopsy and ablation. This report describes six patients (four male, two female) with air embolism following CT-guided lung interventions at two institutions between January 2021 and March 2024. Air embolisms were identified in locations such as the pulmonary vein, left ventricle, and coronary arteries, with clinical presentations ranging from asymptomatic to life-threatening events. Prompt intervention, including oxygen therapy, patient repositioning, and intravenous administration of epinephrine in cases of cardiac arrest, resulted in favorable outcomes. This series highlights the importance of early detection of systemic air embolism and tailored management strategies based on its anatomic location to mitigate risk of serious adverse events. <b>Keywords:</b> Interventional-Body, Complications, Ablation Techniques (Radiofrequency, Thermal, Chemical), Biopsy/Needle Aspiration, Lung, Electrocardiogram © RSNA, 2025.</p>","PeriodicalId":20786,"journal":{"name":"Radiology. Imaging cancer","volume":"7 3","pages":"e240379"},"PeriodicalIF":5.6,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143780998","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluating Automated Tools for Lesion Detection on ¹⁸F Fluoroestradiol PET/CT Images and Assessment of Concordance with Standard-of-Care Imaging in Metastatic Breast Cancer.","authors":"Renee Miller, Mark Battle, Kristen Wangerin, Daniel T Huff, Amy J Weisman, Song Chen, Timothy G Perk, Gary A Ulaner","doi":"10.1148/rycan.240253","DOIUrl":"https://doi.org/10.1148/rycan.240253","url":null,"abstract":"<p><p>Purpose To evaluate two automated tools for detecting lesions on fluorine 18 (¹⁸F) fluoroestradiol (FES) PET/CT images and assess concordance of ¹⁸F-FES PET/CT with standard diagnostic CT and/or ¹⁸F fluorodeoxyglucose (FDG) PET/CT in patients with breast cancer. Materials and Methods This retrospective analysis of a prospective study included participants with breast cancer who underwent ¹⁸F-FES PET/CT examinations (<i>n</i> = 52), ¹⁸F-FDG PET/CT examinations (<i>n</i> = 13 of 52), and diagnostic CT examinations (<i>n</i> = 37 of 52). A convolutional neural network was trained for lesion detection using manually contoured lesions. Concordance in lesions labeled by a nuclear medicine physician between ¹⁸F-FES and ¹⁸F-FDG PET/CT and between ¹⁸F-FES PET/CT and diagnostic CT was assessed using an automated software medical device. Lesion detection performance was evaluated using sensitivity and false positives per participant. Wilcoxon tests were used for statistical comparisons. Results The study included 52 participants. The lesion detection algorithm achieved a median sensitivity of 62% with 0 false positives per participant. Compared with sensitivity in overall lesion detection, the sensitivity was higher for detection of high-uptake lesions (maximum standardized uptake value > 1.5, <i>P</i> = .002) and similar for detection of large lesions (volume > 0.5 cm³, <i>P</i> = .15). The artificial intelligence (AI) lesion detection tool was combined with a standardized uptake value threshold to demonstrate a fully automated method of labeling patients as having FES-avid metastases. Additionally, automated concordance analysis showed that 17 of 25 participants (68%) had over half of the detected lesions across two modalities present on ¹⁸F-FES PET/CT images. Conclusion An AI model was trained to detect lesions on ¹⁸F-FES PET/CT images and an automated concordance tool measured heterogeneity between ¹⁸F-FES PET/CT and standard-of-care imaging. <b>Keywords:</b> Molecular Imaging-Cancer, Neural Networks, PET/CT, Breast, Computer Applications-General (Informatics), Segmentation, ¹⁸F-FES PET, Metastatic Breast Cancer, Lesion Detection, Artificial Intelligence, Lesion Matching <i>Supplemental material is available for this article.</i> Clinical Trials Identifier: NCT04883814 Published under a CC BY 4.0 license.</p>","PeriodicalId":20786,"journal":{"name":"Radiology. Imaging cancer","volume":"7 3","pages":"e240253"},"PeriodicalIF":5.6,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143994915","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Automatic Segmentation and Molecular Subtype Classification of Breast Cancer Using an MRI-based Deep Learning Framework.","authors":"Xiaoxia Wang, Xiaofei Hu, Churan Wang, Hua Yang, Yan Hu, Xiaosong Lan, Yao Huang, Ying Cao, Lijun Yan, Fandong Zhang, Yizhou Yu, Jiuquan Zhang","doi":"10.1148/rycan.240184","DOIUrl":"https://doi.org/10.1148/rycan.240184","url":null,"abstract":"<p><p>Purpose To build a deep learning framework using contrast-enhanced MRI for lesion segmentation and automatic molecular subtype classification in breast cancer. Materials and Methods This retrospective multicenter study included patients with biopsy-proven invasive breast cancer between January 2015 and January 2021. An automatic breast lesion segmentation model was developed using three-dimensional (3D) ResU-Net as the backbone, and its accuracy was evaluated in an internal and two external testing datasets using the Dice score. An ensemble model for classification of breast cancer into four molecular subtypes (Ensemble ResNet) was then developed by combining both two-dimensional and 3D lesion features. The performance of Ensemble ResNet was evaluated in the three testing datasets using the area under the receiver operating characteristic curve (AUC). Results A total of 687 female patients (mean age ± SD, 48.70 years ± 8.97) were included, with 289, 61, 73, and 264 patients included in the training, internal testing, and two external testing datasets, respectively. The proposed segmentation model achieved high accuracy in internal testing dataset 1, external testing dataset 2, and external testing dataset 3 (Dice scores: 0.86, 0.82, 0.85) and luminal A, luminal B, human epidermal growth factor receptor 2 (HER2)-enriched, and triple-negative breast cancer (TNBC) subtypes (Dice scores: 0.8571, 0.8323, 0.8199, 0.8481). Ensemble ResNet demonstrated high performance for the prediction of luminal A subtypes (AUC range, 0.74-0.84), luminal B subtypes (AUC range, 0.68-0.72), HER2-enriched subtypes (AUC range, 0.73-0.82), and TNBC (AUC range, 0.80-0.81) in the three testing datasets. Conclusion The proposed novel deep learning framework based on MRI achieved high, robust performance in fully automatic classification of breast cancer molecular subtypes. <b>Keywords:</b> MR-Imaging, Breast, Oncology, Breast Cancer, Molecular Subtype, Deep Learning Framework <i>Supplemental material is available for this article.</i> © RSNA, 2025.</p>","PeriodicalId":20786,"journal":{"name":"Radiology. Imaging cancer","volume":"7 3","pages":"e240184"},"PeriodicalIF":5.6,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143996218","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prospective Evaluation of Contrast-enhanced Mammography for Early Prediction of Pathologic Response after Neoadjuvant Therapy.","authors":"Lígia Pires-Gonçalves, Ana Teresa Aguiar, Conceição Leal, António Guimarães-Santos, Miguel Abreu, Rui Henrique","doi":"10.1148/rycan.240117","DOIUrl":"https://doi.org/10.1148/rycan.240117","url":null,"abstract":"<p><p>Purpose To assess whether changes in contrast-enhanced mammography (CEM)-derived lesion measurements after the first cycle of neoadjuvant therapy (NAT) can predict pathologic complete response (pCR) in individuals with breast cancer. Materials and Methods This prospective single-center pilot study enrolled consecutive participants with breast cancer treated with NAT who underwent CEM at baseline (May 2018 to December 2018). CEM was performed before and after the first cycle of NAT. Two breast radiologists independently evaluated the percentage change in the longest dimension of the lesion (CLD) and Response Evaluation Criteria in Solid Tumors (RECIST) 1.1 criteria at CEM. Multivariable logistic regression was used to identify independent predictors of pCR, and predictive performance was assessed using area under the receiver operating characteristic curve (AUC). Results Thirty-six participants (mean age ± SD, 48 years ± 10.3) were included; 11 (30.5%) participants achieved pCR. A CLD of at least 20.93% independently predicted pCR (odds ratio, 9.52; 95% CI: 1.34, 67.23; <i>P</i> = .02), achieving a sensitivity of 73% (eight of 11) and a specificity of 88% (22 of 25). Response according to RECIST 1.1 criteria was not associated with pCR (odds ratio, 3.22; 95% CI: 0.46, 22.53; <i>P</i> = .24). In participants with hormone-receptor negative breast cancer, a CLD of at least 20.93% was associated with a higher likelihood of pCR (odds ratio, 40.00; 95% CI: 2.01, 794.27; <i>P</i> = .005) and had an AUC of 0.86 (95% CI: 0.65, >0.99; <i>P</i> = .005). Conclusion CLD at CEM after the first cycle of NAT may be an early predictor of pCR in individuals with breast cancer. <b>Keywords:</b> Breast, Tumor Response, Mammography, Oncology, Neoadjuvant Therapy, Radiographic Image Enhancement, Pathologic Complete Response, Breast Tumor <i>Supplemental material is available for this article.</i> © RSNA, 2025.</p>","PeriodicalId":20786,"journal":{"name":"Radiology. Imaging cancer","volume":"7 3","pages":"e240117"},"PeriodicalIF":5.6,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144128453","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Radiation-induced Osteosarcoma of the Calvarium.","authors":"Sunil Kumar, Smily Sharma, Abhishek Nayak, Deepti An, Bejoy Thomas","doi":"10.1148/rycan.240502","DOIUrl":"https://doi.org/10.1148/rycan.240502","url":null,"abstract":"","PeriodicalId":20786,"journal":{"name":"Radiology. Imaging cancer","volume":"7 3","pages":"e240502"},"PeriodicalIF":5.6,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144021533","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Benign and Malignant Breast Lesions: Differentiation Using Microstructural Metrics Derived from Time-Dependent Diffusion MRI.","authors":"Yun Su, Ya Qiu, Xingke Huang, Yuqin Peng, Zehong Yang, Miamiao Ding, Lanxin Hu, Yishi Wang, Chen Zhao, Wenshu Qian, Xiang Zhang, Jun Shen","doi":"10.1148/rycan.240287","DOIUrl":"https://doi.org/10.1148/rycan.240287","url":null,"abstract":"<p><p>Purpose To investigate the diagnostic performance of microstructural metrics from time-dependent diffusion MRI (T_d-dMRI) in distinguishing between benign and malignant breast lesions. Materials and Methods This prospective study (ClinicalTrials.gov identifier: NCT05373628) enrolled participants with breast lesions confirmed with US, mammography, or both from January 2022 to June 2023. Participants underwent oscillating and pulsed gradient encoded T_d-dMRI and conventional diffusion-weighted imaging (DWI). T_d-dMRI data were fitted using the imaging microstructural parameters using limited spectrally edited diffusion model. Lesions were classified as benign or malignant based on pathology. Diagnostic performances of T_d-dMRI metrics and apparent diffusion coefficients (ADCs) from DWI in distinguishing between benign and malignant tumors were assessed using receiver operating characteristic analysis and compared using the DeLong test. Results The study included 102 female participants (mean age: 48 years ± 12 [SD]) with 105 breast lesions (three participants had two lesions), including 31 benign and 74 malignant lesions. The cell diameter, cell density, and intracellular volume fraction from T_d-dMRI were higher and the ADC was lower in malignant lesions compared with benign lesions (<i>P</i> < .001 to <i>P</i> = .001). Among microstructural metrics from T_d-dMRI, the cell density had the highest area under the receiver operating characteristic curve, which was higher than that of the ADC (0.93 [95% CI: 0.88, 0.98] vs 0.79 [95% CI: 0.70, 0.88], <i>P</i> = .03). Conclusion A single microstructural metric derived from T_d-dMRI, cell density, had higher performance than conventional ADC in distinguishing benign and malignant breast lesions. <b>Keywords:</b> MR-Diffusion Weighted Imaging, Breast Clinical trial registration no. NCT05373628 <i>Supplemental material is available for this article.</i> © RSNA, 2025.</p>","PeriodicalId":20786,"journal":{"name":"Radiology. Imaging cancer","volume":"7 3","pages":"e240287"},"PeriodicalIF":5.6,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144014135","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Beyond Conventional CT: Role of Dual-Energy CT in Monitoring Response to Therapy in Abdominal Malignancies.","authors":"Ali Pourvaziri, Nayla Mroueh, Rory L Cochran, Shravya Srinivas Rao, Avinash Kambadakone","doi":"10.1148/rycan.240142","DOIUrl":"https://doi.org/10.1148/rycan.240142","url":null,"abstract":"<p><p>In the era of precision medicine, imaging plays a critical role in evaluating treatment response to various oncologic therapies. For decades, conventional morphologic assessments using cross-sectional imaging have been the standard for monitoring the effectiveness of systemic and locoregional therapies in patients with cancer. However, the development of new functional imaging tools has widened the scope of imaging from mere response assessment to patient selection and outcome prediction. Dual-energy CT (DECT), known for its superior material differentiation capabilities, shows promise in enhancing treatment response evaluation. DECT-based iodine quantification methods are increasingly being investigated as surrogates for assessing tumor vascularity and physiology, which is particularly important in patients undergoing emerging targeted therapies. The purpose of this review article is to discuss the current and emerging role of DECT in assessing treatment response in patients with malignant abdominal tumors. <b>Keywords:</b> CT-Dual Energy, Transcatheter Tumor Therapy, Tumor Response, Iodine Uptake, Therapeutic Response © RSNA, 2025.</p>","PeriodicalId":20786,"journal":{"name":"Radiology. Imaging cancer","volume":"7 3","pages":"e240142"},"PeriodicalIF":5.6,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144014137","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}