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Li X, Liang X, Li Z, Liang J, Qi Z, Zhong L, Geng Z, Liang W, Quan X, Liang C, Liu Z. A novel stratification scheme combined with internal arteries in CT imaging for guiding postoperative adjuvant transarterial chemoembolization in hepatocellular carcinoma: a retrospective cohort study. Int J Surg 2024; 110:2556-2567. [PMID: 38377071 DOI: 10.1097/js9.0000000000001191] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Accepted: 01/31/2024] [Indexed: 02/22/2024]
Abstract
BACKGROUND Although postoperative adjuvant transarterial chemoembolization (PA-TACE) improves survival outcomes in a subset of patients with resected hepatocellular carcinoma (HCC), the lack of reliable biomarkers for patient selection remains a significant challenge. The present study aimed to evaluate whether computed tomography imaging can provide more value for predicting benefits from PA-TACE and to establish a new scheme for guiding PA-TACE benefits. METHODS In this retrospective study, patients with HCC who had undergone preoperative contrast-enhanced computed tomography and curative hepatectomy were evaluated. Inverse probability of treatment weight was performed to balance the difference of baseline characteristics. Cox models were used to test the interaction among PA-TACE, imaging features, and pathological indicators. An HCC imaging and pathological classification (HIPC) scheme incorporating these imaging and pathological indicators was established. RESULTS This study included 1488 patients [median age, 52 years (IQR, 45-61 years); 1309 male]. Microvascular invasion (MVI) positive, and diameter >5 cm tumors achieved a higher recurrence-free survival (RFS), and overall survival (OS) benefit, respectively, from PA-TACE than MVI negative, and diameter ≤5 cm tumors. Patients with internal arteries (IA) positive benefited more than those with IA-negative in terms of RFS ( P =0.016) and OS ( P =0.018). PA-TACE achieved significant RFS and OS improvements in HIPC3 (IA present and diameter >5 cm, or two or three tumors) patients but not in HIPC1 (diameter ≤5 cm, MVI negative) and HIPC2 (other single tumor) patients. Our scheme may decrease the number of patients receiving PA-TACE by ~36.5% compared to the previous suggestion. CONCLUSIONS IA can provide more value for predicting the benefit of PA-TACE treatment. The proposed HIPC scheme can be used to stratify patients with and without survival benefits from PA-TACE.
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Affiliation(s)
- Xinming Li
- Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University
- Department of Radiology
| | - Xiangjing Liang
- Ultrasound Medical Center, Zhujiang Hospital Southern Medical University
| | - Zhipeng Li
- Department of Radiology, Sun Yat-sen University Cancer Center
| | - Jianye Liang
- Department of Radiology, Sun Yat-sen University Cancer Center
| | | | - Liming Zhong
- School of Biomedical Engineering, Southern Medical University
| | - Zhijun Geng
- Department of Radiology, Sun Yat-sen University Cancer Center
| | | | | | - Changhong Liang
- Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University
- Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangzhou, People's Republic of China
| | - Zaiyi Liu
- Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University
- Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangzhou, People's Republic of China
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Bai Y, Liu J, Wang Y, Zhou B, Liu X, Dong X, Zheng C. Impact of Sarcopenia on Prognosis in Primary Hepatocellular Carcinoma Patients Treated with Transcatheter Arterial Chemoembolization: A Single Center Retrospective Study. J Cancer 2024; 15:1837-1847. [PMID: 38434977 PMCID: PMC10905400 DOI: 10.7150/jca.92976] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2023] [Accepted: 01/26/2024] [Indexed: 03/05/2024] Open
Abstract
Objective: This study aimed to investigate the prognostic effect of sarcopenia on primary hepatocellular carcinoma (HCC) patients after transcatheter arterial chemoembolization (TACE). Methods: This retrospective study enrolled 265 patients diagnosed with HCC who underwent TACE between April 2014 and February 2021. The patients were divided into two groups: the sarcopenia group (n=133) and the non-sarcopenia group (n=132). The study analyzed the differences in overall survival (OS) and progression-free survival (PFS) using Kaplan-Meier curves. The independent risk factors for OS and PFS were determined using univariate and multivariate Cox regression analysis. Based on these factors, the study constructed a prognostic risk grading system. Results: At 3 and 6 months post-TACE, the prognoses of the sarcopenia group were worse than that of the non-sarcopenia group according to the mRECIST criteria. Kaplan-Meier curves showed that the cumulative OS and PFS rate in the non-sarcopenia group were significantly higher compared to the sarcopenia group (HR=3.319, 95%CI: 2.283-4.824, Log-rank P < 0.001; HR=0.631, 95%CI: 0.486-0.820, Log-rank P < 0.001). Sarcopenia, maximal tumor diameter, and AFP ≥ 200 ng/mL were independent risk factors for OS and PFS. The prognostic risk grading system based on sarcopenia, AFP ≥ 200 ng/mL, and maximal tumor diameter≥8.9 cm showed significant differences in prognosis between risk groups. Conclusion: Sarcopenia had excellent predictive value for OS and PFS in patients after TACE, and AFP ≥ 200 ng/mL and maximal tumor diameter were also independent risk factors for a poor prognosis. The prognostic risk grading system based on sarcopenia, AFP, and maximal tumor diameter had good guiding value for the prognosis of patients.
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Affiliation(s)
- Yaowei Bai
- Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
- Hubei Province Key Laboratory of Molecular Imaging, Wuhan 430022, China
| | - Jiacheng Liu
- Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
- Hubei Province Key Laboratory of Molecular Imaging, Wuhan 430022, China
| | - Ying Wang
- Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
- Department of Radiology, Tongren Hospital of Wuhan University (Wuhan Third Hospital), Wuhan University, Wuhan 430060, China
| | - Binqian Zhou
- Department of Ultrasound, The Central Hospital of Wuhan, Tong ji Medical College, Huazhong University of Science and Technology, Wuhan 430014, China
| | - Xiaoming Liu
- Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
- Hubei Province Key Laboratory of Molecular Imaging, Wuhan 430022, China
| | - Xiangjun Dong
- Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
- Hubei Province Key Laboratory of Molecular Imaging, Wuhan 430022, China
| | - Chuansheng Zheng
- Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
- Hubei Province Key Laboratory of Molecular Imaging, Wuhan 430022, China
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Malone CD, Fetzer DT, Monsky WL, Itani M, Mellnick VM, Velez PA, Middleton WD, Averkiou MA, Ramaswamy RS. Contrast-enhanced US for the Interventional Radiologist: Current and Emerging Applications. Radiographics 2021; 40:562-588. [PMID: 32125955 DOI: 10.1148/rg.2020190183] [Citation(s) in RCA: 38] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
US is a powerful and nearly ubiquitous tool in the practice of interventional radiology. Use of contrast-enhanced US (CEUS) has gained traction in diagnostic imaging given the recent approval by the U.S. Food and Drug Administration (FDA) of microbubble contrast agents for use in the liver, such as sulfur hexafluoride lipid-type A microspheres. Adoption of CEUS by interventional radiologists can enhance not only procedure guidance but also preprocedure patient evaluation and assessment of treatment response across a wide spectrum of oncologic, vascular, and nonvascular procedures. In addition, the unique physical properties of microbubble contrast agents make them amenable as therapeutic vehicles in themselves, which can lay a foundation for future therapeutic innovations in the field in drug delivery, thrombolysis, and vascular flow augmentation. The purpose of this article is to provide an introduction to and overview of CEUS aimed at the interventional radiologist, highlighting its role before, during, and after frequently practiced oncologic and vascular interventions such as biopsy, ablation, transarterial chemoembolization, detection and control of hemorrhage, evaluation of transjugular intrahepatic portosystemic shunts (TIPS), detection of aortic endograft endoleak, thrombus detection and evaluation, evaluation of vascular malformations, lymphangiography, and percutaneous drain placement. Basic physical principles of CEUS, injection and scanning protocols, and logistics for practice implementation are also discussed. Early adoption of CEUS by the interventional radiology community will ensure rapid innovation of the field and development of future novel procedures. Online supplemental material is available for this article. ©RSNA, 2020.
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Affiliation(s)
- Christopher D Malone
- From the Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S Kingshighway Blvd, CB 8131, St Louis, MO 63110 (C.D.M., M.I., V.M.M., P.A.V., W.D.M., R.S.R.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (D.T.F.); Department of Radiology, University of Washington Medical Center, Seattle, Wash (W.L.M.); and Department of Bioengineering, University of Washington, Seattle, Wash (M.A.A.)
| | - David T Fetzer
- From the Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S Kingshighway Blvd, CB 8131, St Louis, MO 63110 (C.D.M., M.I., V.M.M., P.A.V., W.D.M., R.S.R.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (D.T.F.); Department of Radiology, University of Washington Medical Center, Seattle, Wash (W.L.M.); and Department of Bioengineering, University of Washington, Seattle, Wash (M.A.A.)
| | - Wayne L Monsky
- From the Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S Kingshighway Blvd, CB 8131, St Louis, MO 63110 (C.D.M., M.I., V.M.M., P.A.V., W.D.M., R.S.R.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (D.T.F.); Department of Radiology, University of Washington Medical Center, Seattle, Wash (W.L.M.); and Department of Bioengineering, University of Washington, Seattle, Wash (M.A.A.)
| | - Malak Itani
- From the Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S Kingshighway Blvd, CB 8131, St Louis, MO 63110 (C.D.M., M.I., V.M.M., P.A.V., W.D.M., R.S.R.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (D.T.F.); Department of Radiology, University of Washington Medical Center, Seattle, Wash (W.L.M.); and Department of Bioengineering, University of Washington, Seattle, Wash (M.A.A.)
| | - Vincent M Mellnick
- From the Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S Kingshighway Blvd, CB 8131, St Louis, MO 63110 (C.D.M., M.I., V.M.M., P.A.V., W.D.M., R.S.R.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (D.T.F.); Department of Radiology, University of Washington Medical Center, Seattle, Wash (W.L.M.); and Department of Bioengineering, University of Washington, Seattle, Wash (M.A.A.)
| | - Philip A Velez
- From the Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S Kingshighway Blvd, CB 8131, St Louis, MO 63110 (C.D.M., M.I., V.M.M., P.A.V., W.D.M., R.S.R.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (D.T.F.); Department of Radiology, University of Washington Medical Center, Seattle, Wash (W.L.M.); and Department of Bioengineering, University of Washington, Seattle, Wash (M.A.A.)
| | - William D Middleton
- From the Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S Kingshighway Blvd, CB 8131, St Louis, MO 63110 (C.D.M., M.I., V.M.M., P.A.V., W.D.M., R.S.R.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (D.T.F.); Department of Radiology, University of Washington Medical Center, Seattle, Wash (W.L.M.); and Department of Bioengineering, University of Washington, Seattle, Wash (M.A.A.)
| | - Michalakis A Averkiou
- From the Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S Kingshighway Blvd, CB 8131, St Louis, MO 63110 (C.D.M., M.I., V.M.M., P.A.V., W.D.M., R.S.R.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (D.T.F.); Department of Radiology, University of Washington Medical Center, Seattle, Wash (W.L.M.); and Department of Bioengineering, University of Washington, Seattle, Wash (M.A.A.)
| | - Raja S Ramaswamy
- From the Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S Kingshighway Blvd, CB 8131, St Louis, MO 63110 (C.D.M., M.I., V.M.M., P.A.V., W.D.M., R.S.R.); Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (D.T.F.); Department of Radiology, University of Washington Medical Center, Seattle, Wash (W.L.M.); and Department of Bioengineering, University of Washington, Seattle, Wash (M.A.A.)
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Yoo J, Lee JM. Diagnostic Value of High Frame Rate Contrast-enhanced Ultrasonography and Post-processing Contrast Vector Imaging for Evaluation of Focal Liver Lesions: A Feasibility Study. ULTRASOUND IN MEDICINE & BIOLOGY 2020; 46:2254-2264. [PMID: 32546409 DOI: 10.1016/j.ultrasmedbio.2020.05.001] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/29/2020] [Revised: 03/25/2020] [Accepted: 05/04/2020] [Indexed: 06/11/2023]
Abstract
This study evaluated the feasibility of contrast vector imaging (CVI) to characterize focal liver lesions. From July to October 2019, we prospectively enrolled 30 patients with focal liver lesions (hepatocellular carcinoma [HCC] [n = 19], metastasis [n = 8], combined HCC-cholangiocarcinoma [CC] [n = 1], intra-hepatic CC [n = 1] and sclerosed hemangioma [n = 1]). Contrast-enhanced ultrasound (CEUS) was performed with high frame rate contrast harmonic imaging technique by one radiologist, and post-processing CVI was obtained and analyzed by two radiologists. On combined CVI with CEUS, the staining pattern was significantly predominant in HCCs (9/11, 81.8%), while peripheral rim was frequent in non-HCCs (5/8, 62.5%) (p = 0.020). HCCs exhibited feeding arteries (8/11, 45.5%) and high velocity variance (10/11, 90.9 %), whereas non-HCCs showed detour pattern (4/8, 50.0%) with either a high or low velocity variance (4/8, 50.0%, both), with no significant inter-group differences (p = 0.052 and 0.080, respectively). In conclusion, CVI was feasible and provided quantitative and multi-parametric information of different types of hepatic tumors.
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Affiliation(s)
- Jeongin Yoo
- Department of Radiology, Seoul National University Hospital, Seoul, Korea
| | - Jeong Min Lee
- Department of Radiology, Seoul National University Hospital, Seoul, Korea; Seoul National University College of Medicine and Institute of Radiation Medicine, Seoul, Korea.
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Peng J, Kang S, Ning Z, Deng H, Shen J, Xu Y, Zhang J, Zhao W, Li X, Gong W, Huang J, Liu L. Residual convolutional neural network for predicting response of transarterial chemoembolization in hepatocellular carcinoma from CT imaging. Eur Radiol 2019; 30:413-424. [PMID: 31332558 PMCID: PMC6890698 DOI: 10.1007/s00330-019-06318-1] [Citation(s) in RCA: 101] [Impact Index Per Article: 20.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2019] [Revised: 05/21/2019] [Accepted: 06/11/2019] [Indexed: 02/07/2023]
Abstract
Background We attempted to train and validate a model of deep learning for the preoperative prediction of the response of patients with intermediate-stage hepatocellular carcinoma (HCC) undergoing transarterial chemoembolization (TACE). Method All computed tomography (CT) images were acquired for 562 patients from the Nan Fang Hospital (NFH), 89 patients from Zhu Hai Hospital Affiliated with Jinan University (ZHHAJU), and 138 patients from the Sun Yat-sen University Cancer Center (SYUCC). We built a predictive model from the outputs using the transfer learning techniques of a residual convolutional neural network (ResNet50). The prediction accuracy for each patch was revaluated in two independent validation cohorts. Results In the training set (NFH), the deep learning model had an accuracy of 84.3% and areas under curves (AUCs) of 0.97, 0.96, 0.95, and 0.96 for complete response (CR), partial response (PR), stable disease (SD), and progressive disease (PD), respectively. In the other two validation sets (ZHHAJU and SYUCC), the deep learning model had accuracies of 85.1% and 82.8% for CR, PR, SD, and PD. The ResNet50 model also had high AUCs for predicting the objective response of TACE therapy in patches and patients of three cohorts. Decision curve analysis (DCA) showed that the ResNet50 model had a high net benefit in the two validation cohorts. Conclusion The deep learning model presented a good performance for predicting the response of TACE therapy and could help clinicians in better screening patients with HCC who can benefit from the interventional treatment. Key Points • Therapy response of TACE can be predicted by a deep learning model based on CT images. • The probability value from a trained or validation deep learning model showed significant correlation with different therapy responses. • Further improvement is necessary before clinical utilization. Electronic supplementary material The online version of this article (10.1007/s00330-019-06318-1) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Jie Peng
- Hepatology Unit and Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China
- Department of Oncology, The Second Affiliated Hospital of Guizhou Medical University, Kaili, China
| | - Shuai Kang
- Hepatology Unit and Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China
| | - Zhengyuan Ning
- School of Biomedical Engineering, Southern Medical University, Guangzhou, China
| | - Hangxia Deng
- Department of Minimal Invasive Interventional Therapy, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, Guangzhou, 510000, China
| | - Jingxian Shen
- Department of Radiology, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, Guangzhou, China
| | - Yikai Xu
- Department of Medical Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Jing Zhang
- Department of Medical Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Wei Zhao
- Department of Interventional Radiology, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Xinling Li
- Department of Interventional Radiology, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Wuxing Gong
- Department of Oncology, Zhuhai Hospital Affiliated with Jinan University, Jinan University, Zhuhai, China
| | - Jinhua Huang
- Department of Minimal Invasive Interventional Therapy, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, Guangzhou, 510000, China.
| | - Li Liu
- Hepatology Unit and Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
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Affiliation(s)
- Soung Won Jeong
- Department of Internal Medicine, Soonchunhyang University Seoul Hospital, Soonchunhyang University College of Medicine, Seoul, Korea
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Arlt F, Chalopin C, Müns A, Meixensberger J, Lindner D. Intraoperative 3D contrast-enhanced ultrasound (CEUS): a prospective study of 50 patients with brain tumours. Acta Neurochir (Wien) 2016; 158:685-694. [PMID: 26883549 DOI: 10.1007/s00701-016-2738-z] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2015] [Accepted: 02/03/2016] [Indexed: 12/17/2022]
Abstract
BACKGROUND Reliable intraoperative resection control during surgery of malignant brain tumours is associated with the longer overall survival of patients. B-mode ultrasound (BUS) is a familiar intraoperative imaging application in neurosurgical procedures and supplies excellent image quality. However, due to resection-induced artefacts, its ability to distinguish between tumour borders, oedema, surrounding tissue and tumour remnants is sometimes limited. In experienced hands, this "bright rim effect" could be reduced. However, it should be determined, if contrast-enhanced ultrasound can improve this situation by providing high-quality imaging during the resection. The aim of this clinical study was to examine contrast-enhanced and three-dimensional reconstructed ultrasound (3D CEUS) in brain tumour surgery regarding the uptake of contrast agent pre- and post-tumour resection, imaging quality and in comparison with postoperative magnetic resonance imaging in different tumour entities. METHODS Fifty patients, suffering from various brain tumours intra-axial and extra-axial, who had all undergone surgery with the support of neuronavigation in our neurosurgical department, were included in the study. Their median age was 56 years (range, 28-79). Ultrasound imaging was performed before the Dura was opened and for resection control at the end of tumour resection as defined by the neurosurgeon. A high-end ultrasound (US) device (Toshiba Aplio XG®) with linear and sector probes for B-mode and CEUS was used. Navigation and 3D reconstruction were performed with a LOCALITE SonoNavigator® and the images were transferred digitally (DVI) to the navigation system. The contrast agent consists of echoic micro-bubbles showing tumour vascularisation. The ultrasound images were compared with the corresponding postoperative MR data in order to determine the accuracy and imaging quality of the tumours and tumour remnants after resection. RESULTS Different types of tumours were investigated. High, dynamic contrast agent uptake was observed in 19 of 21 patients (90 %) suffering from glioblastoma, while in 2 patients uptake was low and insufficient. In 52.4 % of glioblastoma and grade III astrocytoma patients CEUS led to an improved delineation in comparison to BUS and showed a high-resolution imaging quality of the tumour margins and tumour boarders. Grade II and grade III astrocytoma (n = 6) as well as metastasis (n = 18) also showed high contrast agent uptake, which led in 50 % to an improved imaging quality. In 5 of these 17 patients, intraoperative CEUS for resection control showed tumour remnants, leading to further tumour resection. Patients treated with CEUS showed no increased neurological deficits after tumour resection. No pharmacological side-effects occurred. CONCLUSIONS Three-dimensional CEUS is a reliable intraoperative imaging modality and could improve imaging quality. Ninety percent of the high-grade gliomas (HGG, glioblastoma and astrocytoma grade III) showed high contrast uptake with an improved imaging quality in more than 50 %. Gross total resection and incomplete resection of glioblastoma were adequately highlighted by 3D CEUS intraoperatively. The application of US contrast agent could be a helpful imaging tool, especially for resection control in glioblastoma surgery.
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Affiliation(s)
- Felix Arlt
- Klinik und Poliklinik für Neurochirurgie, Universitätsklinik Leipzig, Liebigstrasse 20, 04103, Leipzig, Germany.
| | - Claire Chalopin
- ICCAS (Innovation Centre Computer Assisted Surgery), Semmelweisstr 14, 04103, Leipzig, Germany
| | - Andrea Müns
- Klinik und Poliklinik für Neurochirurgie, Universitätsklinik Leipzig, Liebigstrasse 20, 04103, Leipzig, Germany
| | - Jürgen Meixensberger
- Klinik und Poliklinik für Neurochirurgie, Universitätsklinik Leipzig, Liebigstrasse 20, 04103, Leipzig, Germany
- ICCAS (Innovation Centre Computer Assisted Surgery), Semmelweisstr 14, 04103, Leipzig, Germany
| | - Dirk Lindner
- Klinik und Poliklinik für Neurochirurgie, Universitätsklinik Leipzig, Liebigstrasse 20, 04103, Leipzig, Germany
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