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Zhang Y, Wang F, Huang Y. PDZK1 is correlated with DCE-MRI perfusion parameters in high-grade glioma. Clinics (Sao Paulo) 2024; 79:100367. [PMID: 38692010 PMCID: PMC11070665 DOI: 10.1016/j.clinsp.2024.100367] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/01/2023] [Revised: 03/11/2024] [Accepted: 04/11/2024] [Indexed: 05/03/2024] Open
Abstract
OBJECTIVE This study investigated the relationship between PDZK1 expression and Dynamic Contrast-Enhanced MRI (DCE-MRI) perfusion parameters in High-Grade Glioma (HGG). METHODS Preoperative DCE-MRI scanning was performed on 80 patients with HGG to obtain DCE perfusion transfer coefficient (Ktrans), vascular plasma volume fraction (vp), extracellular volume fraction (ve), and reverse transfer constant (kep). PDZK1 in HGG patients was detected, and its correlation with DCE-MRI perfusion parameters was assessed by the Pearson method. An analysis of Cox regression was performed to determine the risk factors affecting survival, while Kaplan-Meier and log-rank tests to evaluate PDZK1's prognostic significance, and ROC curve analysis to assess its diagnostic value. RESULTS PDZK1 was upregulated in HGG patients and predicted poor overall survival and progression-free survival. Moreover, PDZK1 expression distinguished grade III from grade IV HGG. PDZK1 expression was positively correlated with Ktrans 90, and ve_90, and negatively correlated with kep_max, and kep_90. CONCLUSION PDZK1 is upregulated in HGG, predicts poor survival, and differentiates tumor grading in HGG patients. PDZK1 expression is correlated with DCE-MRI perfusion parameters.
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Affiliation(s)
- Yi Zhang
- Department of Radiology, The First People's Hospital of Shuangliu District, (West China Airport Hospital of Sichuan University), Chengdu City, Sichuan Province, China.
| | - Feng Wang
- Department of Radiology, The First People's Hospital of Shuangliu District, (West China Airport Hospital of Sichuan University), Chengdu City, Sichuan Province, China
| | - YongLi Huang
- Department of Radiology, The First People's Hospital of Shuangliu District, (West China Airport Hospital of Sichuan University), Chengdu City, Sichuan Province, China
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2
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Frosina G. Recapitulating the Key Advances in the Diagnosis and Prognosis of High-Grade Gliomas: Second Half of 2021 Update. Int J Mol Sci 2023; 24:ijms24076375. [PMID: 37047356 PMCID: PMC10094646 DOI: 10.3390/ijms24076375] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2023] [Revised: 03/02/2023] [Accepted: 03/24/2023] [Indexed: 03/31/2023] Open
Abstract
High-grade gliomas (World Health Organization grades III and IV) are the most frequent and fatal brain tumors, with median overall survivals of 24–72 and 14–16 months, respectively. We reviewed the progress in the diagnosis and prognosis of high-grade gliomas published in the second half of 2021. A literature search was performed in PubMed using the general terms “radio* and gliom*” and a time limit from 1 July 2021 to 31 December 2021. Important advances were provided in both imaging and non-imaging diagnoses of these hard-to-treat cancers. Our prognostic capacity also increased during the second half of 2021. This review article demonstrates slow, but steady improvements, both scientifically and technically, which express an increased chance that patients with high-grade gliomas may be correctly diagnosed without invasive procedures. The prognosis of those patients strictly depends on the final results of that complex diagnostic process, with widely varying survival rates.
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Huang YS, Chen JLY, Chen HM, Yeh LH, Shih JY, Yen RF, Chang YC. Assessing tumor angiogenesis using dynamic contrast-enhanced integrated magnetic resonance-positron emission tomography in patients with non-small-cell lung cancer. BMC Cancer 2021; 21:348. [PMID: 33794813 PMCID: PMC8017855 DOI: 10.1186/s12885-021-08064-4] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2020] [Accepted: 03/18/2021] [Indexed: 12/18/2022] Open
Abstract
Background Angiogenesis assessment is important for personalized therapeutic intervention in patients with non-small-cell lung cancer (NSCLC). This study investigated whether radiologic parameters obtained by dynamic contrast-enhanced (DCE)-integrated magnetic resonance-positron emission tomography (MR-PET) could be used to quantitatively assess tumor angiogenesis in NSCLC. Methods This prospective cohort study included 75 patients with NSCLC who underwent DCE-integrated MR-PET at diagnosis. The following parameters were analyzed: metabolic tumor volume (MTV), maximum standardized uptake value (SUVmax), reverse reflux rate constant (kep), volume transfer constant (Ktrans), blood plasma volume fraction (vp), extracellular extravascular volume fraction (ve), apparent diffusion coefficient (ADC), and initial area under the time-to-signal intensity curve at 60 s post enhancement (iAUC60). Serum biomarkers of tumor angiogenesis, including vascular endothelial growth factor-A (VEGF-A), angiogenin, and angiopoietin-1, were measured by enzyme-linked immunosorbent assays simultaneously. Results Serum VEGF-A (p = 0.002), angiogenin (p = 0.023), and Ang-1 (p < 0.001) concentrations were significantly elevated in NSCLC patients compared with healthy individuals. MR-PET parameters, including MTV, Ktrans, and kep, showed strong linear correlations (p < 0.001) with serum angiogenesis-related biomarkers. Serum VEGF-A concentrations (p = 0.004), MTV values (p < 0.001), and kep values (p = 0.029) were significantly higher in patients with advanced-stage disease (stage III or IV) than in those with early-stage disease (stage I or II). Patients with initial higher values of angiogenesis-related MR-PET parameters, including MTV > 30 cm3 (p = 0.046), Ktrans > 200 10− 3/min (p = 0.069), and kep > 900 10− 3/min (p = 0.048), may have benefited from angiogenesis inhibitor therapy, which thus led to significantly longer overall survival. Conclusions The present findings suggest that DCE-integrated MR-PET provides a reliable, non-invasive, quantitative assessment of tumor angiogenesis; can guide the use of angiogenesis inhibitors toward longer survival; and will play an important role in the personalized treatment of NSCLC.
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Affiliation(s)
- Yu-Sen Huang
- Department of Radiology, National Taiwan University College of Medicine, No. 7, Chung-Shan S. Rd., Taipei, 100, Taiwan.,Department of Medical Imaging, National Taiwan University Hospital, Taipei, Taiwan
| | - Jenny Ling-Yu Chen
- Department of Radiology, National Taiwan University College of Medicine, No. 7, Chung-Shan S. Rd., Taipei, 100, Taiwan.,Department of Oncology, National Taiwan University Hospital, Taipei, Taiwan.,National Taiwan University Cancer Center, National Taiwan University College of Medicine, Taipei, Taiwan
| | - Hsin-Ming Chen
- Department of Medical Imaging, National Taiwan University Hospital, Taipei, Taiwan
| | - Li-Hao Yeh
- Department of Medical Imaging, National Taiwan University Hospital, Taipei, Taiwan
| | - Jin-Yuan Shih
- Department of Internal Medicine National Taiwan University Hospital, Taipei, Taiwan
| | - Ruoh-Fang Yen
- Department of Nuclear Medicine, National Taiwan University Hospital, Taipei, Taiwan
| | - Yeun-Chung Chang
- Department of Radiology, National Taiwan University College of Medicine, No. 7, Chung-Shan S. Rd., Taipei, 100, Taiwan. .,Department of Medical Imaging, National Taiwan University Hospital, Taipei, Taiwan.
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Park YW, Ahn SS, Moon JH, Kim EH, Kang SG, Chang JH, Kim SH, Lee SK. Dynamic contrast-enhanced MRI may be helpful to predict response and prognosis after bevacizumab treatment in patients with recurrent high-grade glioma: comparison with diffusion tensor and dynamic susceptibility contrast imaging. Neuroradiology 2021; 63:1811-1822. [PMID: 33755766 DOI: 10.1007/s00234-021-02693-z] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2021] [Accepted: 03/15/2021] [Indexed: 12/20/2022]
Abstract
PURPOSE We aimed to evaluate the utility of diffusion tensor imaging (DTI), dynamic contrast-enhanced (DCE), and dynamic susceptibility contrast (DSC) imaging for stratifying bevacizumab treatment outcomes in patients with recurrent high-grade glioma. METHODS Fifty-three patients with recurrent high-grade glioma who underwent baseline magnetic resonance imaging including DTI, DCE, and DSC before bevacizumab treatment were included. The mean apparent diffusion coefficient, fractional anisotropy, normalized cerebral blood volume, normalized cerebral blood flow, volume transfer constant, rate transfer coefficient (Kep), extravascular extracellular volume fraction, and plasma volume fraction were assessed. Predictors of response status, progression-free survival (PFS), and overall survival (OS) were determined using logistic regression and Cox proportional hazard modeling. RESULTS Responders (n = 16) showed significantly longer PFS and OS (P < 0.001) compared with nonresponders (n = 37). Multivariable analysis revealed that lower mean Kep (odds ratio = 0.01, P = 0.008) was the only independent predictor of favorable response after adjustment for age, isocitrate dehydrogenase (IDH) mutation status, and O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation status. Multivariable Cox proportional hazard modeling showed that a higher mean Kep was the only variable associated with shorter PFS (hazard ratio [HR] = 7.90, P = 0.006) and OS (HR = 9.71, P = 0.020) after adjustment for age, IDH mutation status, and MGMT promoter methylation status. CONCLUSION Baseline mean Kep may be a useful biomarker for predicting response and stratifying patient outcomes following bevacizumab treatment in patients with recurrent high-grade glioma.
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Affiliation(s)
- Yae Won Park
- Department of Radiology and Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 120-752, Korea
| | - Sung Soo Ahn
- Department of Radiology and Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 120-752, Korea.
| | - Ju Hyung Moon
- Department of Neurosurgery, Yonsei University College of Medicine, Seoul, Korea
| | - Eui Hyun Kim
- Department of Neurosurgery, Yonsei University College of Medicine, Seoul, Korea
| | - Seok-Gu Kang
- Department of Neurosurgery, Yonsei University College of Medicine, Seoul, Korea
| | - Jong Hee Chang
- Department of Neurosurgery, Yonsei University College of Medicine, Seoul, Korea
| | - Se Hoon Kim
- Department of Pathology, Yonsei University College of Medicine, Seoul, Korea
| | - Seung-Koo Lee
- Department of Radiology and Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 120-752, Korea
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Enhanced Rim on MDCT of Colorectal Liver Metastases: Assessment of Ability to Predict Progression-Free Survival and Response to Bevacizumab-Based Chemotherapy. AJR Am J Roentgenol 2020; 215:1377-1383. [PMID: 32991216 DOI: 10.2214/ajr.19.22280] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
OBJECTIVE. The purpose of this article is to evaluate the enhanced rim on the portal venous phase (PVP) on MDCT as a predictor of 1-year progression-free survival (PFS) and response to bevacizumab-based chemotherapy in patients with colorectal liver metastases (CRLM). MATERIALS AND METHODS. We retrospectively identified 111 patients with primary unresectable CRLM treated with bevacizumab-based chemotherapy at two institutions between 2012 and 2018. Pretreatment contrast-enhanced MDCT images were reviewed and data on clinical characteristics were collected from the electronic medical records. Univariable and multivariable analyses were conducted to assess several imaging features and clinical characteristics as potential predictors of 1-year PFS and objective response rate (ORR). RESULTS. After 1 year of follow-up, liver metastatic tumor progression was detected in 52 patients (46.8%) after bevacizumab-based chemotherapy. A log-rank test showed that enhanced rim on PVP (chi-square test, 5.862; p = 0.015) and the occurrence of liver resection surgery (chi-square test, 7.836; p = 0.005) were significant predictors of 1-year PFS. Multivariable analysis showed that enhanced rim on PVP images was an independent predictor of 1-year PFS (hazard ratio, 0.510; 95% CI, 0.282-0.926; p = 0.027) and ORR (odds ratio, 4.694; p < 0.001). CONCLUSION. The presence of an enhanced rim on PVP MDCT is an independent predictor of survival and response to bevacizumab-based chemotherapy among patients with CRLM.
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Han Y, Chai F, Wei J, Yue Y, Cheng J, Gu D, Zhang Y, Tong T, Sheng W, Hong N, Ye Y, Wang Y, Tian J. Identification of Predominant Histopathological Growth Patterns of Colorectal Liver Metastasis by Multi-Habitat and Multi-Sequence Based Radiomics Analysis. Front Oncol 2020; 10:1363. [PMID: 32923388 PMCID: PMC7456817 DOI: 10.3389/fonc.2020.01363] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2019] [Accepted: 06/29/2020] [Indexed: 12/21/2022] Open
Abstract
Purpose: Developing an MRI-based radiomics model to effectively and accurately predict the predominant histopathologic growth patterns (HGPs) of colorectal liver metastases (CRLMs). Materials and Methods: In this study, 182 resected and histopathological proven CRLMs of chemotherapy-naive patients from two institutions, including 123 replacement CRLMs and 59 desmoplastic CRLMs, were retrospectively analyzed. Radiomics analysis was performed on two regions of interest (ROI), the tumor zone and the tumor-liver interface (TLI) zone. Decision tree (DT) algorithm was used for radiomics modeling on each MR sequence, and fused radiomics model was constructed by combining the radiomics signature of each sequence. The clinical and combination models were developed through multivariate logistic regression method. The performance of the developed models was assessed by receiver operating characteristic (ROC) curves with indicators of area under curve (AUC), accuracy, sensitivity, and specificity. A nomogram was constructed to evaluate the discrimination, calibration, and usefulness. Results: The fused radiomicstumor and radiomicsTLI models showed better performance than any single sequence and clinical model. In addition, the radiomicsTLI model exhibited better performance than radiomicstumor model (AUC of 0.912 vs. 0.879) in internal validation cohort. The combination model showed good discrimination, and the AUC of nomogram was 0.971, 0.909, and 0.905 in the training, internal validation, and external validation cohorts, respectively. Conclusion: MRI-based radiomics method has high potential in predicting the predominant HGPs of CRLM. Preoperative non-invasive identification of predominant HGPs could further explore the ability of HGPs as a potential biomarker for clinical treatment strategy, reflecting different biological pathways.
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Affiliation(s)
- Yuqi Han
- School of Life Science and Technology, Xidian University, Xi'an, China.,Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China.,Beijing Key Laboratory of Molecular Imaging, Beijing, China
| | - Fan Chai
- Department of Radiology, Peking University People's Hospital, Beijing, China
| | - Jingwei Wei
- Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China.,Beijing Key Laboratory of Molecular Imaging, Beijing, China
| | - Yali Yue
- Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Jin Cheng
- Department of Radiology, Peking University People's Hospital, Beijing, China
| | - Dongsheng Gu
- Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China.,Beijing Key Laboratory of Molecular Imaging, Beijing, China
| | - Yinli Zhang
- Department of Pathology, Peking University People's Hospital, Beijing, China
| | - Tong Tong
- Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Weiqi Sheng
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.,Department of Pathology, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Nan Hong
- Department of Radiology, Peking University People's Hospital, Beijing, China
| | - Yingjiang Ye
- Department of Gastrointestinal Surgery, Peking University People' Hospital, Beijing, China
| | - Yi Wang
- Department of Radiology, Peking University People's Hospital, Beijing, China
| | - Jie Tian
- Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China.,Beijing Key Laboratory of Molecular Imaging, Beijing, China.,Beijing Advanced Innovation Centre for Big Data-Based Precision Medicine, School of Medicine, Beihang University, Beijing, China.,Engineering Research Centre of Molecular and Neuro Imaging of Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, China
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7
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Shamsdin SA, Mehrafshan A, Rakei SM, Mehrabani D. Evaluation of VEGF, FGF and PDGF and Serum Levels of Inflammatory Cytokines in Patients with Glioma and Meningioma in Southern Iran. Asian Pac J Cancer Prev 2019; 20:2883-2890. [PMID: 31653130 PMCID: PMC6982662 DOI: 10.31557/apjcp.2019.20.10.2883] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2018] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND Meningioma and glioma are common central nervous system tumors. Hypoxic tumor cells secrete angiogenic cytokines, such as vascular endothelial growth factor (VEGF), platelet-derived growth factor (PDGF) and basic fibroblast growth factor (bFGF) that stimulate neovascular formation and inflammatory cytokine, such as TNF-α and IL-1β. We measured these serum levels in patients with glial cell tumors and meningioma. MATERIALS AND METHODS This was a case-control study in 2014-2015 on patients diagnosed with meningioma/glioma. All demographic and clinical data were registered. The tumor volume and intraoperative bleeding were recorded. Serum levels of VEGF, PDGF, FGF, TNF-α and IL-1β were measured by ELISA methods. RESULTS Ninety-six patients were enrolled in this study, 32 in each group. Patients VEGF level with cranial tumor, glioma/meningioma had increased. VEGF level was highest among grade IV tumors, larger tumors, and in glioblastoma multiform. There was an upsurge in VEGF serum level as glioma grade increased. The highest VEGF levels were seen in parasagittal meningioma. In contrast to VEGF, PDGF was slightly elevated in glial cell tumors, which was significantly elevated in meningioma. Higher PDGF correlated with increased intraoperative bleeding, especially in meningioma cases. Oligodendroglial tumors expressed higher PDGF levels in contrast to other glial tumors. FGF level was not statistically significant. TNF-α and IL-1β expressions were significantly higher in the meningioma and glioma group in comparison to control group. CONCLUSION We found increased VEGF and PDGF serum levels in CNS patient's tumor. A different role for PDGF was found in the pathogenesis of neovascularization of meningioma, as well as oligodendroglioma. No significant result was found for FGF. TNF-α and IL-1β can serve as key prognostic biomarker in high-grade glioma and meningioma patients.
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Affiliation(s)
- Seyedeh Azra Shamsdin
- Gastroenterohepatology Research Center, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Ali Mehrafshan
- Department of Neurosurgery, Qom University of Medical Sciences, Qom, Iran
| | | | - Davood Mehrabani
- Gastroenterohepatology Research Center, Shiraz University of Medical Sciences, Shiraz, Iran
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8
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Zormpas-Petridis K, Jerome NP, Blackledge MD, Carceller F, Poon E, Clarke M, McErlean CM, Barone G, Koers A, Vaidya SJ, Marshall LV, Pearson ADJ, Moreno L, Anderson J, Sebire N, McHugh K, Koh DM, Yuan Y, Chesler L, Robinson SP, Jamin Y. MRI Imaging of the Hemodynamic Vasculature of Neuroblastoma Predicts Response to Antiangiogenic Treatment. Cancer Res 2019; 79:2978-2991. [PMID: 30877107 PMCID: PMC6558276 DOI: 10.1158/0008-5472.can-18-3412] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2018] [Revised: 01/25/2019] [Accepted: 03/12/2019] [Indexed: 12/14/2022]
Abstract
Childhood neuroblastoma is a hypervascular tumor of neural origin, for which antiangiogenic drugs are currently being evaluated; however, predictive biomarkers of treatment response, crucial for successful delivery of precision therapeutics, are lacking. We describe an MRI-pathologic cross-correlative approach using intrinsic susceptibility (IS) and susceptibility contrast (SC) MRI to noninvasively map the vascular phenotype in neuroblastoma Th-MYCN transgenic mice treated with the vascular endothelial growth factor receptor inhibitor cediranib. We showed that the transverse MRI relaxation rate R 2* (second-1) and fractional blood volume (fBV, %) were sensitive imaging biomarkers of hemorrhage and vascular density, respectively, and were also predictive biomarkers of response to cediranib. Comparison with MRI and pathology from patients with MYCN-amplified neuroblastoma confirmed the high degree to which the Th-MYCN model vascular phenotype recapitulated that of the clinical phenotype, thereby supporting further evaluation of IS- and SC-MRI in the clinic. This study reinforces the potential role of functional MRI in delivering precision medicine to children with neuroblastoma. SIGNIFICANCE: This study shows that functional MRI predicts response to vascular-targeted therapy in a genetically engineered murine model of neuroblastoma.
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Affiliation(s)
- Konstantinos Zormpas-Petridis
- Division of Radiotherapy and Imaging, The Institute of Cancer Research, London and The Royal Marsden NHS Trust, Sutton, Surrey, United Kingdom
| | - Neil P Jerome
- Division of Radiotherapy and Imaging, The Institute of Cancer Research, London and The Royal Marsden NHS Trust, Sutton, Surrey, United Kingdom
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
- Clinic of Radiology and Nuclear Medicine, St. Olavs Hospital, Trondheim, Norway
| | - Matthew D Blackledge
- Division of Radiotherapy and Imaging, The Institute of Cancer Research, London and The Royal Marsden NHS Trust, Sutton, Surrey, United Kingdom
| | - Fernando Carceller
- Division of Clinical Studies, The Institute of Cancer Research, London and The Royal Marsden NHS Trust, Sutton, Surrey, United Kingdom
| | - Evon Poon
- Division of Clinical Studies, The Institute of Cancer Research, London and The Royal Marsden NHS Trust, Sutton, Surrey, United Kingdom
| | - Matthew Clarke
- Division of Molecular Pathology, The Institute of Cancer Research, London and The Royal Marsden NHS Trust, Sutton, Surrey, United Kingdom
| | - Ciara M McErlean
- Division of Radiotherapy and Imaging, The Institute of Cancer Research, London and The Royal Marsden NHS Trust, Sutton, Surrey, United Kingdom
| | - Giuseppe Barone
- Department of Pediatric Oncology, Great Ormond Street Hospital for Children, London, United Kingdom
| | - Alexander Koers
- Division of Clinical Studies, The Institute of Cancer Research, London and The Royal Marsden NHS Trust, Sutton, Surrey, United Kingdom
| | - Sucheta J Vaidya
- Division of Clinical Studies, The Institute of Cancer Research, London and The Royal Marsden NHS Trust, Sutton, Surrey, United Kingdom
| | - Lynley V Marshall
- Division of Clinical Studies, The Institute of Cancer Research, London and The Royal Marsden NHS Trust, Sutton, Surrey, United Kingdom
| | - Andrew D J Pearson
- Division of Clinical Studies, The Institute of Cancer Research, London and The Royal Marsden NHS Trust, Sutton, Surrey, United Kingdom
| | - Lucas Moreno
- Clinical Research Unit, Pediatric Oncology, Hematology and Stem Cell Transplant Department, Hospital Infantil Universitario Ninõ Jesús, Madrid, Spain
| | - John Anderson
- Department of Pediatric Oncology, Great Ormond Street Hospital for Children, London, United Kingdom
- UCL Great Ormond Street Institute of Child Health, London, United Kingdom
| | - Neil Sebire
- UCL Great Ormond Street Institute of Child Health, London, United Kingdom
- Department of Histopathology, Great Ormond Street Hospital for Children, London, United Kingdom
| | - Kieran McHugh
- Department of Radiology, Great Ormond Street Hospital for Children, London, United Kingdom
| | - Dow-Mu Koh
- Division of Radiotherapy and Imaging, The Institute of Cancer Research, London and The Royal Marsden NHS Trust, Sutton, Surrey, United Kingdom
| | - Yinyin Yuan
- Division of Molecular Pathology, The Institute of Cancer Research, London and The Royal Marsden NHS Trust, Sutton, Surrey, United Kingdom
| | - Louis Chesler
- Division of Clinical Studies, The Institute of Cancer Research, London and The Royal Marsden NHS Trust, Sutton, Surrey, United Kingdom
| | - Simon P Robinson
- Division of Radiotherapy and Imaging, The Institute of Cancer Research, London and The Royal Marsden NHS Trust, Sutton, Surrey, United Kingdom
| | - Yann Jamin
- Division of Radiotherapy and Imaging, The Institute of Cancer Research, London and The Royal Marsden NHS Trust, Sutton, Surrey, United Kingdom.
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9
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Scarpelli M, Simoncic U, Perlman S, Liu G, Jeraj R. Dynamic 18F-FLT PET imaging of spatiotemporal changes in tumor cell proliferation and vasculature reveals the mechanistic actions of anti-angiogenic therapy. Phys Med Biol 2018; 63:155008. [PMID: 29978839 DOI: 10.1088/1361-6560/aad1be] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Anti-angiogenic therapies target tumor vasculature and tumor cells, thus a concurrent assessment of these targets would lead to a greater understanding of therapeutic resistance and facilitate development of improved therapeutic strategies. We utilize dynamic 3'-deoxy-3'-18F-fluorothymidine positron emission tomography (18F-FLT PET) scanning to concurrently assess changes in tumor cell proliferation and vasculature during anti-angiogenic therapy, providing insight into how these therapies may be used effectively with combination chemotherapy. Thirty-three patients with advanced solid malignancies underwent treatment with vascular endothelial growth factor receptor inhibitor (VEGFR-TKI) axitinib on an intermittent schedule (two-weeks-on/one-week-off). Patients had up to three dynamic 18F-FLT PET/CT scans: at baseline, after two weeks of continuous VEGFR-TKI treatment, and following a one week treatment break. 18F-FLT kinetics were analyzed using a two-tissue compartment kinetic model. Kinetic parameters V b and K 1 were extracted to quantify changes in tumor vasculature and the 18F-FLT flux constant K i was calculated to quantify changes in tumor cell proliferation. Two weeks of continuous axitinib exposure led to decreases in V b (median -21%, P = 0.07), K 1 (median -39%, P < 0.01), and K i (median -37%, P < 0.01), corresponding to diminished tumor vasculature and cell proliferation that may antagonize treatment with concurrent chemotherapy. Axitinib treatment breaks led to significant increases in V b (median +42%, P < 0.01), K 1 (median +46%, P < 0.01), and K i (median +39%, P < 0.01) that is suggestive of an optimal time to schedule synergistic chemotherapy. Significant negative correlations (rho ⩽ -0.70, P < 0.01) were found between changes in tumor vasculature during axitinib exposure weeks and changes in tumor vasculature during treatment breaks. Imaging with dynamic 18F-FLT PET revealed new insights relating to the interplay of vascular and proliferative pharmacodynamics of axitinib therapy, facilitating a greater understanding of the mechanistic actions of VEGFR-TKIs. Increases in tumor vasculature and cell proliferation during VEGFR-TKI treatment breaks, suggests this period is an optimal time to schedule synergistic chemotherapy and warrants further investigation.
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Affiliation(s)
- Matthew Scarpelli
- Department of Medical Physics, University of Wisconsin, 1111 Highland Ave, Madison, WI 53792, United States of America
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10
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Hauge A, Wegner CS, Gaustad JV, Simonsen TG, Andersen LMK, Rofstad EK. Diffusion-Weighted MRI Is Insensitive to Changes in the Tumor Microenvironment Induced by Antiangiogenic Therapy. Transl Oncol 2018; 11:1128-1136. [PMID: 30036782 PMCID: PMC6072800 DOI: 10.1016/j.tranon.2018.07.005] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2018] [Revised: 07/03/2018] [Accepted: 07/06/2018] [Indexed: 12/29/2022] Open
Abstract
Antiangiogenic treatment (AAT) used in combination with radiation therapy or chemotherapy is a promising strategy for the treatment of several cancer diseases. The vascularity and oxygenation of tumors may be changed significantly by AAT, and consequently, a noninvasive method for monitoring AAT-induced changes in these microenvironmental parameters is needed. The purpose of this study was to evaluate the potential usefulness of diffusion-weighted magnetic resonance imaging (DW-MRI). DW-MRI was conducted with a Bruker Biospec 7.05-T scanner using four diffusion weightings and diffusion sensitization gradients in three orthogonal directions. Maps of the apparent diffusion coefficient (ADC) were calculated by using a monoexponential diffusion model. Two cervical carcinoma xenograft models (BK-12, HL-16) were treated with bevacizumab, and two pancreatic carcinoma xenograft models (BxPC-3, Panc-1) were treated with sunitinib. Pimonidazole and CD31 were used as markers of hypoxia and blood vessels, respectively, and fraction of hypoxic tissue (HFPim) and microvascular density (MVD) were quantified by analyzing immunohistochemical preparations. MVD decreased significantly after AAT in BK-12, HL-16, and BxPC-3 tumors, and this decrease was sufficiently large to cause a significant increase in HFPim in BK-12 and BxPC-3 tumors. The ADC maps of treated tumors and untreated control tumors were not significantly different in any of these three tumor models, suggesting that the AAT-induced microenvironmental changes were not detectable by DW-MRI. DW-MRI is insensitive to changes in tumor vascularity and oxygenation induced by bevacizumab or sunitinib treatment.
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Affiliation(s)
- Anette Hauge
- Group of Radiation Biology and Tumor Physiology, Department of Radiation Biology, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway
| | - Catherine S Wegner
- Group of Radiation Biology and Tumor Physiology, Department of Radiation Biology, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway
| | - Jon-Vidar Gaustad
- Group of Radiation Biology and Tumor Physiology, Department of Radiation Biology, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway
| | - Trude G Simonsen
- Group of Radiation Biology and Tumor Physiology, Department of Radiation Biology, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway
| | - Lise Mari K Andersen
- Group of Radiation Biology and Tumor Physiology, Department of Radiation Biology, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway
| | - Einar K Rofstad
- Group of Radiation Biology and Tumor Physiology, Department of Radiation Biology, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway.
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11
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Kong Z, Yan C, Zhu R, Wang J, Wang Y, Wang Y, Wang R, Feng F, Ma W. Imaging biomarkers guided anti-angiogenic therapy for malignant gliomas. NEUROIMAGE-CLINICAL 2018; 20:51-60. [PMID: 30069427 PMCID: PMC6067083 DOI: 10.1016/j.nicl.2018.07.001] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/13/2018] [Revised: 07/02/2018] [Accepted: 07/03/2018] [Indexed: 12/24/2022]
Abstract
Antiangiogenic therapy is a universal approach to the treatment of malignant gliomas but fails to prolong the overall survival of newly diagnosed or recurrent glioblastoma patients. Imaging biomarkers are quantitative imaging parameters capable of objectively describing biological processes, pathological changes and treatment responses in some situations and have been utilized for outcome predictions of malignant gliomas in anti-angiogenic therapy. Advanced magnetic resonance imaging techniques (including perfusion-weighted imaging and diffusion-weighted imaging), positron emission computed tomography and magnetic resonance spectroscopy are imaging techniques that can be used to acquire imaging biomarkers, including the relative cerebral blood volume (rCBV), Ktrans, and the apparent diffusion coefficient (ADC). Imaging indicators for a better prognosis when treating malignant gliomas with antiangiogenic therapy include the following: a lower pre- or post-treatment rCBV, less change in rCBV during treatment, a lower pre-treatment Ktrans, a higher vascular normalization index during treatment, less change in arterio-venous overlap during treatment, lower pre-treatment ADC values for the lower peak, smaller ADC volume changes during treatment, and metabolic changes in glucose and phenylalanine. The investigation and utilization of these imaging markers may confront challenges, but may also promote further development of anti-angiogenic therapy. Despite considerable evidence, future prospective studies are critically needed to consolidate the current data and identify novel biomarkers. Anti-angiogenic therapy only benefits specific populations of glioma patients. Advanced imaging techniques can produce quantitative imaging biomarkers. Physiological and metabolic parameter can predict outcome for anti-angiogenic therapy. Larger prospective studies are needed to provide further evidence.
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Key Words
- 18F-FDOPA, 3,4-dihydroxy-6-[18F]-fluoro-l-phenylalanine
- 18F-FLT, [18F]-fluoro-3-deoxy-3-L-fluorothymidine
- ADC, apparent diffusion coefficient
- AVOL, arterio-venous overlap
- Anti-angiogenic
- BBB, blood brain barrier
- Biomarkers
- CBF, cerebral blood flow
- CBV, cerebral blood volume
- CNS, central nervous system
- CT, computed tomography
- D-2HG, D-2-hydroxypentanedioic acid
- DCE-MRI, dynamic contrast-enhanced magnetic resonance imaging
- DSC-MRI, dynamic susceptibility contrast magnetic resonance imaging
- DWI, diffusion-weighted imaging
- FDG, fluorodeoxyglucose
- FLAIR, fluid-attenuated inversion recovery
- FSE pcASL, fast spin echo pseudocontinuous artery spin labeling
- GBM, glioblastoma
- Glioma
- Imaging
- Ktrans, volume transfer constant between blood plasma and extravascular extracellular space
- MRI, magnetic resonance imaging
- MRS, magnetic resonance spectroscopy
- OS, overall survival
- PET, positron emission computed tomography
- PFS, progression-free survival
- PWI, perfusion-weighted imaging
- RANO, Response Assessment in Neuro-Oncology
- ROI, region of interest
- RSI, restriction spectrum imaging
- SUV, standardized uptake value
- TMZ, temozolomide
- Therapy
- VAI, vessel architectural imaging
- VEGF-A, vascular endothelial growth factor A
- VNI, vascular normalization index.
- fDMs, functional diffusion maps
- nGBM, newly diagnosed glioblastoma
- rCBF, relative cerebral blood flow
- rCBV, relative cerebral blood volume
- rGBM, recurrent glioblastoma
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Affiliation(s)
- Ziren Kong
- Department of Neurosurgery, Chinese Academy of Medical Sciences, Peking Union Medical College Hospital, Beijing, China
| | - Chengrui Yan
- Department of Neurosurgery, Chinese Academy of Medical Sciences, Peking Union Medical College Hospital, Beijing, China; Department of Neurosurgery, Peking University International Hospital, Peking University, Beijing, China
| | - Ruizhe Zhu
- Department of Neurosurgery, Chinese Academy of Medical Sciences, Peking Union Medical College Hospital, Beijing, China
| | - Jiaru Wang
- Department of Neurosurgery, Chinese Academy of Medical Sciences, Peking Union Medical College Hospital, Beijing, China
| | - Yaning Wang
- Department of Neurosurgery, Chinese Academy of Medical Sciences, Peking Union Medical College Hospital, Beijing, China
| | - Yu Wang
- Department of Neurosurgery, Chinese Academy of Medical Sciences, Peking Union Medical College Hospital, Beijing, China.
| | - Renzhi Wang
- Department of Neurosurgery, Chinese Academy of Medical Sciences, Peking Union Medical College Hospital, Beijing, China.
| | - Feng Feng
- Department of Radiology, Chinese Academy of Medical Sciences, Peking Union Medical College Hospital, Beijing, China..
| | - Wenbin Ma
- Department of Neurosurgery, Chinese Academy of Medical Sciences, Peking Union Medical College Hospital, Beijing, China.
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12
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Wegner CS, Hauge A, Simonsen TG, Gaustad JV, Andersen LMK, Rofstad EK. DCE-MRI of Sunitinib-Induced Changes in Tumor Microvasculature and Hypoxia: A Study of Pancreatic Ductal Adenocarcinoma Xenografts. Neoplasia 2018; 20:734-744. [PMID: 29886124 PMCID: PMC6041378 DOI: 10.1016/j.neo.2018.05.006] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2018] [Revised: 05/16/2018] [Accepted: 05/21/2018] [Indexed: 12/14/2022]
Abstract
The purpose of this study was dual: to investigate (a) whether sunitinib may induce changes in tumor microvasculature and hypoxia in pancreatic ductal adenocarcinoma (PDAC) and (b) whether any changes can be detected by DCE-MRI. Sunitinib-treated and untreated control tumors of two PDAC xenograft models (BxPC-3 and Panc-1) were subjected to DCE-MRI before the imaged tumors were prepared for quantitative analysis of immunohistochemical preparations. Pimonidazole was used as a hypoxia marker, and fraction of hypoxic tissue (HFPim), density of CD31-positive microvessels (MVDCD31), and density of αSMA-positive microvessels (MVDαSMA) were measured. Parametric images of Ktrans and ve were derived from the DCE-MRI data by using the Tofts pharmacokinetic model. BxPC-3 tumors showed increased HFPim, decreased MVDCD31, unchanged MVDαSMA, and increased vessel maturation index (VMI = MVDαSMA/MVDCD31) after sunitinib treatment. The increase in VMI was seen because sunitinib induced selective pruning rather than maturation of αSMA-negative microvessels. Even though the microvessels in sunitinib-treated tumors were less abnormal than those in untreated tumors, this microvessel normalization did not improve the function of the microvascular network or normalize the tumor microenvironment. In Panc-1 tumors, HFPim, MVDCD31, MVDαSMA, and VMI were unchanged after sunitinib treatment. Median Ktrans increased with increasing MVDCD31 and decreased with increasing HFPim, and the correlations were similar for treated and untreated BXPC-3 and Panc-1 tumors. These observations suggest that sunitinib may induce significant changes in the microenvironment of PDACs, and furthermore, that Ktrans may be an adequate measure of tumor vascular density and hypoxia in untreated as well as sunitinib-treated PDACs.
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Key Words
- αsma, α smooth muscle actin
- angpt/tie, angiopoietin/tyrosine kinase with immunoglobulin-like and epidermal growth factor-like domains
- dce-mri, dynamic contrast-enhanced magnetic resonance imaging
- fov, field of view
- he, hematoxylin and eosin
- hf, hypoxic fraction
- il-8/nf-κb, interleukin-8/nuclear factor-κb
- ktrans, volume transfer constant
- mvd, microvessel density
- pdac, pancreatic ductal adenocarcinoma
- roi, region of interest
- te, echo time
- tr, repetition time
- ve, fractional distribution volume
- vegf/vegf-r, vascular endothelial growth factor/vegf-receptor
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Affiliation(s)
- Catherine S Wegner
- Group of Radiation Biology and Tumor Physiology, Department of Radiation Biology, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway
| | - Anette Hauge
- Group of Radiation Biology and Tumor Physiology, Department of Radiation Biology, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway
| | - Trude G Simonsen
- Group of Radiation Biology and Tumor Physiology, Department of Radiation Biology, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway
| | - Jon-Vidar Gaustad
- Group of Radiation Biology and Tumor Physiology, Department of Radiation Biology, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway
| | - Lise Mari K Andersen
- Group of Radiation Biology and Tumor Physiology, Department of Radiation Biology, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway
| | - Einar K Rofstad
- Group of Radiation Biology and Tumor Physiology, Department of Radiation Biology, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway.
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13
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Jiang T, Qiao M, Zhao C, Li X, Gao G, Su C, Ren S, Zhou C. Pretreatment neutrophil-to-lymphocyte ratio is associated with outcome of advanced-stage cancer patients treated with immunotherapy: a meta-analysis. Cancer Immunol Immunother 2018; 67:713-727. [PMID: 29423649 PMCID: PMC11028313 DOI: 10.1007/s00262-018-2126-z] [Citation(s) in RCA: 61] [Impact Index Per Article: 10.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2017] [Accepted: 02/06/2018] [Indexed: 12/18/2022]
Abstract
BACKGROUND To investigate the association between pretreatment blood neutrophil-to-lymphocyte ratio (NLR) and clinical outcomes for advanced-stage cancer patients treated with immunotherapy. METHODS We conducted a comprehensive literature search to assess the relationship between pretreatment blood NLR and overall survival (OS) or progression-free survival (PFS) in advanced-stage cancer patients treated with immunotherapy. Published data including hazard ratios (HRs) and related 95% confidence interval (CI) were extracted. Pooled estimates of treatment outcomes were calculated using RevMan 5.3.5. RESULTS Twenty-seven studies with 4647 patients were included in the current study. The pooled results suggested that high pretreatment blood NLR was correlated with significant shorter OS (HR = 1.98, 95% CI 1.66-2.36, P < 0.001) and PFS (HR = 1.78, 95% CI 1.48-2.15, P < 0.001). Subgroup analysis stratified by study targets revealed that anti-VEGF/VEGFR therapy (HR = 2.04, 95% CI 1.61-2.60, P < 0.001) and immune checkpoints blockade (HR = 2.16, 95% CI 1.86-2.51, P < 0.001) were significantly associated with inferior OS while other targets (HR = 1.63, 95% CI 0.89-2.99, P = 0.120) were not associated with OS. There was no correlation between distinct NLR cutoff values and OS ([Formula: see text] = 0.218, P = 0.329) or PFS benefit ([Formula: see text] = - 0.386, P = 0.140). Of note, HRs of PFS showed significant correlation with HRs of OS ([Formula: see text] = 0.656, P = 0.015). CONCLUSION Elevated pretreatment blood NLR was a promising prognostic and predictive biomarker for advanced-stage cancer patients treated with immunotherapy.
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Affiliation(s)
- Tao Jiang
- Department of Medical Oncology, Shanghai Pulmonary Hospital, Thoracic Cancer Institute, Tongji University School of Medicine, No. 507, Zheng Min Road, Shanghai, 200433, People's Republic of China
| | - Meng Qiao
- Department of Medical Oncology, Shanghai Pulmonary Hospital, Thoracic Cancer Institute, Tongji University School of Medicine, No. 507, Zheng Min Road, Shanghai, 200433, People's Republic of China
| | - Chao Zhao
- Department of Lung Cancer and Immunology, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, 200433, People's Republic of China
| | - Xuefei Li
- Department of Lung Cancer and Immunology, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, 200433, People's Republic of China
| | - Guanghui Gao
- Department of Medical Oncology, Shanghai Pulmonary Hospital, Thoracic Cancer Institute, Tongji University School of Medicine, No. 507, Zheng Min Road, Shanghai, 200433, People's Republic of China
| | - Chunxia Su
- Department of Medical Oncology, Shanghai Pulmonary Hospital, Thoracic Cancer Institute, Tongji University School of Medicine, No. 507, Zheng Min Road, Shanghai, 200433, People's Republic of China
| | - Shengxiang Ren
- Department of Medical Oncology, Shanghai Pulmonary Hospital, Thoracic Cancer Institute, Tongji University School of Medicine, No. 507, Zheng Min Road, Shanghai, 200433, People's Republic of China
| | - Caicun Zhou
- Department of Medical Oncology, Shanghai Pulmonary Hospital, Thoracic Cancer Institute, Tongji University School of Medicine, No. 507, Zheng Min Road, Shanghai, 200433, People's Republic of China.
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14
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Little RA, Barjat H, Hare JI, Jenner M, Watson Y, Cheung S, Holliday K, Zhang W, O'Connor JPB, Barry ST, Puri S, Parker GJM, Waterton JC. Evaluation of dynamic contrast-enhanced MRI biomarkers for stratified cancer medicine: How do permeability and perfusion vary between human tumours? Magn Reson Imaging 2018; 46:98-105. [PMID: 29154898 DOI: 10.1016/j.mri.2017.11.008] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2017] [Revised: 11/08/2017] [Accepted: 11/13/2017] [Indexed: 12/18/2022]
Abstract
BACKGROUND Solid tumours exhibit enhanced vessel permeability and fenestrated endothelium to varying degree, but it is unknown how this varies in patients between and within tumour types. Dynamic contrast-enhanced (DCE) MRI provides a measure of perfusion and permeability, the transfer constant Ktrans, which could be employed for such comparisons in patients. AIM To test the hypothesis that different tumour types exhibit systematically different Ktrans. MATERIALS AND METHODS DCE-MRI data were retrieved from 342 solid tumours in 230 patients. These data were from 18 previous studies, each of which had had a different analysis protocol. All data were reanalysed using a standardised workflow using an extended Tofts model. A model of the posterior density of median Ktrans was built assuming a log-normal distribution and fitting a simple Bayesian hierarchical model. RESULTS 12 histological tumour types were included. In glioma, median Ktrans was 0.016min-1 and for non-glioma tumours, median Ktrans ranged from 0.10 (cervical) to 0.21min-1 (prostate metastatic to bone). The geometric mean (95% CI) across all the non-glioma tumours was 0.15 (0.05, 0.45)min-1. There was insufficient separation between the posterior densities to be able to predict the Ktrans value of a tumour given the tumour type, except that the median Ktrans for gliomas was below 0.05min-1 with 80% probability, and median Ktrans measurements for the remaining tumour types were between 0.05 and 0.4min-1 with 80% probability. CONCLUSION With the exception of glioma, our hypothesis that different tumour types exhibit different Ktrans was not supported. Studies in which tumour permeability is believed to affect outcome should not simply seek tumour types thought to exhibit high permeability. Instead, Ktrans is an idiopathic parameter, and, where permeability is important, Ktrans should be measured in each tumour to personalise that treatment.
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Affiliation(s)
- Ross A Little
- Centre for Imaging Sciences, Division of Informatics Imaging & Data Sciences, School of Health Sciences, Faculty of Biology Medicine & Health, University of Manchester, Manchester Academic Health Sciences Centre, Manchester M13 9PL, UK.
| | - Hervé Barjat
- Formerly AstraZeneca, Alderley Park, Macclesfield, Cheshire SK10 4TG, UK.
| | - Jennifer I Hare
- IMED Oncology, AstraZeneca, Li Ka Shing Centre, Cambridge CB2 0RE, UK.
| | - Mary Jenner
- Formerly AstraZeneca, Alderley Park, Macclesfield, Cheshire SK10 4TG, UK
| | - Yvonne Watson
- Centre for Imaging Sciences, Division of Informatics Imaging & Data Sciences, School of Health Sciences, Faculty of Biology Medicine & Health, University of Manchester, Manchester Academic Health Sciences Centre, Manchester M13 9PL, UK.
| | - Susan Cheung
- Centre for Imaging Sciences, Division of Informatics Imaging & Data Sciences, School of Health Sciences, Faculty of Biology Medicine & Health, University of Manchester, Manchester Academic Health Sciences Centre, Manchester M13 9PL, UK.
| | - Katherine Holliday
- Centre for Imaging Sciences, Division of Informatics Imaging & Data Sciences, School of Health Sciences, Faculty of Biology Medicine & Health, University of Manchester, Manchester Academic Health Sciences Centre, Manchester M13 9PL, UK.
| | - Weijuan Zhang
- Centre for Imaging Sciences, Division of Informatics Imaging & Data Sciences, School of Health Sciences, Faculty of Biology Medicine & Health, University of Manchester, Manchester Academic Health Sciences Centre, Manchester M13 9PL, UK.
| | - James P B O'Connor
- Division of Cancer Sciences, Faculty of Biology Medicine & Health, University of Manchester, Manchester Academic Health Sciences Centre, Oxford Road, Manchester M13 9PL, UK. James.O'
| | - Simon T Barry
- IMED Oncology, AstraZeneca, Li Ka Shing Centre, Cambridge CB2 0RE, UK.
| | - Sanyogitta Puri
- AstraZeneca, Alderley Park, Macclesfield, Cheshire SK10 4TG, UK.
| | - Geoffrey J M Parker
- Centre for Imaging Sciences, Division of Informatics Imaging & Data Sciences, School of Health Sciences, Faculty of Biology Medicine & Health, University of Manchester, Manchester Academic Health Sciences Centre, Manchester M13 9PL, UK; Bioxydyn Ltd., Rutherford House, Manchester M15 6SZ, UK.
| | - John C Waterton
- Centre for Imaging Sciences, Division of Informatics Imaging & Data Sciences, School of Health Sciences, Faculty of Biology Medicine & Health, University of Manchester, Manchester Academic Health Sciences Centre, Manchester M13 9PL, UK; Formerly AstraZeneca, Alderley Park, Macclesfield, Cheshire SK10 4TG, UK; Bioxydyn Ltd., Rutherford House, Manchester M15 6SZ, UK.
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15
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Backhaus P, Noto B, Avramovic N, Grubert LS, Huss S, Bögemann M, Stegger L, Weckesser M, Schäfers M, Rahbar K. Targeting PSMA by radioligands in non-prostate disease—current status and future perspectives. Eur J Nucl Med Mol Imaging 2018; 45:860-877. [DOI: 10.1007/s00259-017-3922-y] [Citation(s) in RCA: 93] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2017] [Accepted: 12/25/2017] [Indexed: 12/11/2022]
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16
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Kim J, Kim E, Euceda LR, Meyer DE, Langseth K, Bathen TF, Moestue SA, Huuse EM. Multiparametric characterization of response to anti-angiogenic therapy using USPIO contrast-enhanced MRI in combination with dynamic contrast-enhanced MRI. J Magn Reson Imaging 2017; 47:1589-1600. [DOI: 10.1002/jmri.25898] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2017] [Accepted: 11/03/2017] [Indexed: 12/28/2022] Open
Affiliation(s)
- Jana Kim
- Department of Circulation and Medical Imaging; NTNU - Norwegian University of Science and Technology; Trondheim Norway
- Department of Radiology and Nuclear Medicine; St. Olavs Hospital, Trondheim University Hospital; Trondheim Norway
| | - Eugene Kim
- Department of Circulation and Medical Imaging; NTNU - Norwegian University of Science and Technology; Trondheim Norway
- Department of Radiology and Nuclear Medicine; St. Olavs Hospital, Trondheim University Hospital; Trondheim Norway
| | - Leslie R. Euceda
- Department of Circulation and Medical Imaging; NTNU - Norwegian University of Science and Technology; Trondheim Norway
| | - Dan E. Meyer
- Biosciences Technology Organization, GE Global Research Center; Niskayuna NY United States
| | | | - Tone F. Bathen
- Department of Circulation and Medical Imaging; NTNU - Norwegian University of Science and Technology; Trondheim Norway
| | - Siver A. Moestue
- Department of Circulation and Medical Imaging; NTNU - Norwegian University of Science and Technology; Trondheim Norway
- Department of Laboratory Medicine, Women's and Children's Health; NTNU - Norwegian University of Science and Technology; Trondheim Norway
| | - Else Marie Huuse
- Department of Circulation and Medical Imaging; NTNU - Norwegian University of Science and Technology; Trondheim Norway
- Department of Radiology and Nuclear Medicine; St. Olavs Hospital, Trondheim University Hospital; Trondheim Norway
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17
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Arai H, Miyakawa K, Denda T, Mizukami T, Horie Y, Izawa N, Hirakawa M, Ogura T, Tsuda T, Sunakawa Y, Nakajima TE. Early morphological change for predicting outcome in metastatic colorectal cancer after regorafenib. Oncotarget 2017; 8:110530-110539. [PMID: 29299166 PMCID: PMC5746401 DOI: 10.18632/oncotarget.22807] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2017] [Accepted: 11/13/2017] [Indexed: 12/28/2022] Open
Abstract
Background and Objective It is unclear whether early morphological change (EMC) is a predictive marker for regorafenib in metastatic colorectal cancer (mCRC). Therefore, the present study investigated whether EMC can predict the outcome of mCRC patients receiving regorafenib. Results This study evaluated 68 patients. Among 52 patients with lung metastasis, 16 (31%) had cavity formation (CF). The median progression-free survival (PFS) and overall survival (OS) in patients with/without CF were 4.2/2.4 months (p<0.01) and 9.2/6.5 months (p=0.09), respectively. Among 45 patients with liver metastasis, 14 (31%) had active morphological response (MR). The median PFS and OS in patients with/without active MR were 5.3/2.4 months (p<0.01) and 13.6/6.9 months (p=0.02), respectively. Overall, 25 patients (37%) had EMC. The median PFS and OS in patients with/without EMC were 5.3/2.1 months (p<0.01) and 13.3/6.1 months (p<0.01), respectively. Materials and Methods This retrospective study included mCRC patients with lung and/or liver metastases receiving regorafenib. CF in lung metastasis and MR in liver metastasis were evaluated at the first post-treatment computed tomography scan. EMC was determined as CF and/or active MR. We compared PFS and OS between patients with and those without EMC. Conclusions EMC could be a useful predictive marker for regorafenib in mCRC.
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Affiliation(s)
- Hiroyuki Arai
- Department of Clinical Oncology, St. Marianna University School of Medicine, Kawasaki, Japan
| | - Kunihisa Miyakawa
- Department of Radiology, St. Marianna University School of Medicine, Kawasaki, Japan
| | - Tadamichi Denda
- Division of Gastroenterology, Chiba Cancer Center, Chiba, Japan
| | - Takuro Mizukami
- Department of Clinical Oncology, St. Marianna University School of Medicine, Kawasaki, Japan
| | - Yoshiki Horie
- Department of Clinical Oncology, St. Marianna University School of Medicine, Kawasaki, Japan
| | - Naoki Izawa
- Department of Clinical Oncology, St. Marianna University School of Medicine, Kawasaki, Japan
| | - Mami Hirakawa
- Department of Clinical Oncology, St. Marianna University School of Medicine, Kawasaki, Japan
| | - Takashi Ogura
- Department of Clinical Oncology, St. Marianna University School of Medicine, Kawasaki, Japan
| | - Takashi Tsuda
- Department of Clinical Oncology, St. Marianna University School of Medicine, Kawasaki, Japan
| | - Yu Sunakawa
- Department of Clinical Oncology, St. Marianna University School of Medicine, Kawasaki, Japan
| | - Takako Eguchi Nakajima
- Department of Clinical Oncology, St. Marianna University School of Medicine, Kawasaki, Japan
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18
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Robinson SP, Boult JKR, Vasudev NS, Reynolds AR. Monitoring the Vascular Response and Resistance to Sunitinib in Renal Cell Carcinoma In Vivo with Susceptibility Contrast MRI. Cancer Res 2017; 77:4127-4134. [PMID: 28566330 PMCID: PMC6175052 DOI: 10.1158/0008-5472.can-17-0248] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2017] [Revised: 04/03/2017] [Accepted: 05/22/2017] [Indexed: 12/25/2022]
Abstract
Antiangiogenic therapy is efficacious in metastatic renal cell carcinoma (mRCC). However, the ability of antiangiogenic drugs to delay tumor progression and extend survival is limited, due to either innate or acquired drug resistance. Furthermore, there are currently no validated biomarkers that predict which mRCC patients will benefit from antiangiogenic therapy. Here, we exploit susceptibility contrast MRI (SC-MRI) using intravascular ultrasmall superparamagnetic iron oxide particles to quantify and evaluate tumor fractional blood volume (fBV) as a noninvasive imaging biomarker of response to the antiangiogenic drug sunitinib. We also interrogate the vascular phenotype of RCC xenografts exhibiting acquired resistance to sunitinib. SC-MRI of 786-0 xenografts prior to and 2 weeks after daily treatment with 40 mg/kg sunitinib revealed a 71% (P < 0.01) reduction in fBV in the absence of any change in tumor volume. This response was associated with significantly lower microvessel density (P < 0.01) and lower uptake of the perfusion marker Hoechst 33342 (P < 0.05). The average pretreatment tumor fBV was negatively correlated (R2 = 0.92, P < 0.0001) with sunitinib-induced changes in tumor fBV across the cohort. SC-MRI also revealed suppressed fBV in tumors that acquired resistance to sunitinib. In conclusion, SC-MRI enabled monitoring of the antiangiogenic response of 786-0 RCC xenografts to sunitinib, which revealed that pretreatment tumor fBV was found to be a predictive biomarker of subsequent reduction in tumor blood volume in response to sunitinib, and acquired resistance to sunitinib was not associated with a parallel increase in tumor blood volume. Cancer Res; 77(15); 4127-34. ©2017 AACR.
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Affiliation(s)
- Simon P Robinson
- Cancer Research UK Cancer Imaging Centre, Division of Radiotherapy & Imaging, The Institute of Cancer Research, London, United Kingdom.
| | - Jessica K R Boult
- Cancer Research UK Cancer Imaging Centre, Division of Radiotherapy & Imaging, The Institute of Cancer Research, London, United Kingdom
| | - Naveen S Vasudev
- Tumour Biology Team, The Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, London, United Kingdom
| | - Andrew R Reynolds
- Tumour Biology Team, The Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, London, United Kingdom
- Early Clinical Development, Innovative Medicines and Early Development, AstraZeneca, Cambridge, United Kingdom
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19
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O'Connor JPB, Aboagye EO, Adams JE, Aerts HJWL, Barrington SF, Beer AJ, Boellaard R, Bohndiek SE, Brady M, Brown G, Buckley DL, Chenevert TL, Clarke LP, Collette S, Cook GJ, deSouza NM, Dickson JC, Dive C, Evelhoch JL, Faivre-Finn C, Gallagher FA, Gilbert FJ, Gillies RJ, Goh V, Griffiths JR, Groves AM, Halligan S, Harris AL, Hawkes DJ, Hoekstra OS, Huang EP, Hutton BF, Jackson EF, Jayson GC, Jones A, Koh DM, Lacombe D, Lambin P, Lassau N, Leach MO, Lee TY, Leen EL, Lewis JS, Liu Y, Lythgoe MF, Manoharan P, Maxwell RJ, Miles KA, Morgan B, Morris S, Ng T, Padhani AR, Parker GJM, Partridge M, Pathak AP, Peet AC, Punwani S, Reynolds AR, Robinson SP, Shankar LK, Sharma RA, Soloviev D, Stroobants S, Sullivan DC, Taylor SA, Tofts PS, Tozer GM, van Herk M, Walker-Samuel S, Wason J, Williams KJ, Workman P, Yankeelov TE, Brindle KM, McShane LM, Jackson A, Waterton JC. Imaging biomarker roadmap for cancer studies. Nat Rev Clin Oncol 2017; 14:169-186. [PMID: 27725679 PMCID: PMC5378302 DOI: 10.1038/nrclinonc.2016.162] [Citation(s) in RCA: 674] [Impact Index Per Article: 96.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Imaging biomarkers (IBs) are integral to the routine management of patients with cancer. IBs used daily in oncology include clinical TNM stage, objective response and left ventricular ejection fraction. Other CT, MRI, PET and ultrasonography biomarkers are used extensively in cancer research and drug development. New IBs need to be established either as useful tools for testing research hypotheses in clinical trials and research studies, or as clinical decision-making tools for use in healthcare, by crossing 'translational gaps' through validation and qualification. Important differences exist between IBs and biospecimen-derived biomarkers and, therefore, the development of IBs requires a tailored 'roadmap'. Recognizing this need, Cancer Research UK (CRUK) and the European Organisation for Research and Treatment of Cancer (EORTC) assembled experts to review, debate and summarize the challenges of IB validation and qualification. This consensus group has produced 14 key recommendations for accelerating the clinical translation of IBs, which highlight the role of parallel (rather than sequential) tracks of technical (assay) validation, biological/clinical validation and assessment of cost-effectiveness; the need for IB standardization and accreditation systems; the need to continually revisit IB precision; an alternative framework for biological/clinical validation of IBs; and the essential requirements for multicentre studies to qualify IBs for clinical use.
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Affiliation(s)
- James P B O'Connor
- CRUK and EPSRC Cancer Imaging Centre in Cambridge and Manchester, University of Manchester, Manchester, UK
| | - Eric O Aboagye
- Department of Surgery and Cancer, Imperial College, London, UK
| | - Judith E Adams
- Department of Clinical Radiology, Central Manchester University Hospitals NHS Foundation Trust, Manchester, UK
| | - Hugo J W L Aerts
- Department of Radiation Oncology, Harvard Medical School, Boston, MA
| | - Sally F Barrington
- CRUK and EPSRC Comprehensive Imaging Centre at KCL and UCL, Kings College London, London, UK
| | - Ambros J Beer
- Department of Nuclear Medicine, University Hospital Ulm, Ulm, Germany
| | - Ronald Boellaard
- Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, Groningen, The Netherlands
| | - Sarah E Bohndiek
- CRUK and EPSRC Cancer Imaging Centre in Cambridge and Manchester, University of Cambridge, Cambridge, UK
| | - Michael Brady
- CRUK and EPSRC Cancer Imaging Centre, University of Oxford, Oxford, UK
| | - Gina Brown
- Radiology Department, Royal Marsden Hospital, London, UK
| | - David L Buckley
- Division of Biomedical Imaging, University of Leeds, Leeds, UK
| | | | | | | | - Gary J Cook
- CRUK and EPSRC Comprehensive Imaging Centre at KCL and UCL, Kings College London, London, UK
| | - Nandita M deSouza
- CRUK Cancer Imaging Centre, The Institute of Cancer Research, London, UK
| | - John C Dickson
- CRUK and EPSRC Cancer Imaging Centre at KCL and UCL, University College London, London, UK
| | - Caroline Dive
- Clinical and Experimental Pharmacology, CRUK Manchester Institute, Manchester, UK
| | | | - Corinne Faivre-Finn
- Radiotherapy Related Research Group, University of Manchester, Manchester, UK
| | - Ferdia A Gallagher
- CRUK and EPSRC Cancer Imaging Centre in Cambridge and Manchester, University of Cambridge, Cambridge, UK
| | - Fiona J Gilbert
- CRUK and EPSRC Cancer Imaging Centre in Cambridge and Manchester, University of Cambridge, Cambridge, UK
| | | | - Vicky Goh
- CRUK and EPSRC Comprehensive Imaging Centre at KCL and UCL, Kings College London, London, UK
| | - John R Griffiths
- CRUK and EPSRC Cancer Imaging Centre in Cambridge and Manchester, University of Cambridge, Cambridge, UK
| | - Ashley M Groves
- CRUK and EPSRC Cancer Imaging Centre at KCL and UCL, University College London, London, UK
| | - Steve Halligan
- CRUK and EPSRC Cancer Imaging Centre at KCL and UCL, University College London, London, UK
| | - Adrian L Harris
- CRUK and EPSRC Cancer Imaging Centre, University of Oxford, Oxford, UK
| | - David J Hawkes
- CRUK and EPSRC Cancer Imaging Centre at KCL and UCL, University College London, London, UK
| | - Otto S Hoekstra
- Department of Radiology and Nuclear Medicine, VU University Medical Centre, Amsterdam, The Netherlands
| | - Erich P Huang
- Biometric Research Program, National Cancer Institute, Bethesda, MD
| | - Brian F Hutton
- CRUK and EPSRC Cancer Imaging Centre at KCL and UCL, University College London, London, UK
| | - Edward F Jackson
- Department of Medical Physics, University of Wisconsin, Madison, WI
| | - Gordon C Jayson
- Institute of Cancer Sciences, University of Manchester, Manchester, UK
| | - Andrew Jones
- Medical Physics, The Christie Hospital NHS Foundation Trust, Manchester, UK
| | - Dow-Mu Koh
- CRUK Cancer Imaging Centre, The Institute of Cancer Research, London, UK
| | | | - Philippe Lambin
- Department of Radiation Oncology, University of Maastricht, Maastricht, Netherlands
| | - Nathalie Lassau
- Department of Imaging, Gustave Roussy Cancer Campus, Villejuif, France
| | - Martin O Leach
- CRUK Cancer Imaging Centre, The Institute of Cancer Research, London, UK
| | - Ting-Yim Lee
- Imaging Research Labs, Robarts Research Institute, London, Ontario, Canada
| | - Edward L Leen
- Department of Surgery and Cancer, Imperial College, London, UK
| | - Jason S Lewis
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Yan Liu
- EORTC Headquarters, EORTC, Brussels, Belgium
| | - Mark F Lythgoe
- Centre for Advanced Biomedical Imaging, University College London, London, UK
| | - Prakash Manoharan
- CRUK and EPSRC Cancer Imaging Centre in Cambridge and Manchester, University of Manchester, Manchester, UK
| | - Ross J Maxwell
- Northern Institute for Cancer Research, Newcastle University, Newcastle, UK
| | - Kenneth A Miles
- CRUK and EPSRC Cancer Imaging Centre at KCL and UCL, University College London, London, UK
| | - Bruno Morgan
- Cancer Studies and Molecular Medicine, University of Leicester, Leicester, UK
| | - Steve Morris
- Institute of Epidemiology and Health, University College London, London, UK
| | - Tony Ng
- CRUK and EPSRC Comprehensive Imaging Centre at KCL and UCL, Kings College London, London, UK
| | - Anwar R Padhani
- Paul Strickland Scanner Centre, Mount Vernon Hospital, London, UK
| | - Geoff J M Parker
- CRUK and EPSRC Cancer Imaging Centre in Cambridge and Manchester, University of Manchester, Manchester, UK
| | - Mike Partridge
- CRUK and EPSRC Cancer Imaging Centre, University of Oxford, Oxford, UK
| | - Arvind P Pathak
- Department of Radiology, The Johns Hopkins University School of Medicine, Baltimore, MD
| | - Andrew C Peet
- Institute of Cancer and Genomics, University of Birmingham, Birmingham, UK
| | - Shonit Punwani
- CRUK and EPSRC Cancer Imaging Centre at KCL and UCL, University College London, London, UK
| | - Andrew R Reynolds
- Breakthrough Breast Cancer Research Centre, The Institute of Cancer Research, London, UK
| | - Simon P Robinson
- CRUK Cancer Imaging Centre, The Institute of Cancer Research, London, UK
| | | | - Ricky A Sharma
- CRUK and EPSRC Cancer Imaging Centre at KCL and UCL, University College London, London, UK
| | - Dmitry Soloviev
- CRUK and EPSRC Cancer Imaging Centre in Cambridge and Manchester, University of Cambridge, Cambridge, UK
| | - Sigrid Stroobants
- Molecular Imaging Center Antwerp, University of Antwerp, Antwerp, Belgium
| | - Daniel C Sullivan
- Department of Radiology, Duke University School of Medicine, Durham, NC
| | - Stuart A Taylor
- CRUK and EPSRC Cancer Imaging Centre at KCL and UCL, University College London, London, UK
| | - Paul S Tofts
- Brighton and Sussex Medical School, University of Sussex, Brighton, UK
| | - Gillian M Tozer
- Department of Oncology and Metabolism, University of Sheffield, Sheffield, UK
| | - Marcel van Herk
- Radiotherapy Related Research Group, University of Manchester, Manchester, UK
| | - Simon Walker-Samuel
- Centre for Advanced Biomedical Imaging, University College London, London, UK
| | | | - Kaye J Williams
- CRUK and EPSRC Cancer Imaging Centre in Cambridge and Manchester, University of Manchester, Manchester, UK
| | - Paul Workman
- CRUK Cancer Therapeutics Unit, The Institute of Cancer Research, London, UK
| | - Thomas E Yankeelov
- Institute of Computational Engineering and Sciences, The University of Texas, Austin, TX
| | - Kevin M Brindle
- CRUK and EPSRC Cancer Imaging Centre in Cambridge and Manchester, University of Cambridge, Cambridge, UK
| | - Lisa M McShane
- Biometric Research Program, National Cancer Institute, Bethesda, MD
| | - Alan Jackson
- CRUK and EPSRC Cancer Imaging Centre in Cambridge and Manchester, University of Manchester, Manchester, UK
| | - John C Waterton
- CRUK and EPSRC Cancer Imaging Centre in Cambridge and Manchester, University of Manchester, Manchester, UK
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Laviña B. Brain Vascular Imaging Techniques. Int J Mol Sci 2016; 18:ijms18010070. [PMID: 28042833 PMCID: PMC5297705 DOI: 10.3390/ijms18010070] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2016] [Revised: 12/13/2016] [Accepted: 12/26/2016] [Indexed: 12/13/2022] Open
Abstract
Recent major improvements in a number of imaging techniques now allow for the study of the brain in ways that could not be considered previously. Researchers today have well-developed tools to specifically examine the dynamic nature of the blood vessels in the brain during development and adulthood; as well as to observe the vascular responses in disease situations in vivo. This review offers a concise summary and brief historical reference of different imaging techniques and how these tools can be applied to study the brain vasculature and the blood-brain barrier integrity in both healthy and disease states. Moreover, it offers an overview on available transgenic animal models to study vascular biology and a description of useful online brain atlases.
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Affiliation(s)
- Bàrbara Laviña
- Department of Immunology, Genetics and Pathology, Rudbeck Laboratory, Uppsala University, 75185 Uppsala, Sweden.
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21
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Lapeyre-Prost A, Terme M, Pernot S, Pointet AL, Voron T, Tartour E, Taieb J. Immunomodulatory Activity of VEGF in Cancer. INTERNATIONAL REVIEW OF CELL AND MOLECULAR BIOLOGY 2016; 330:295-342. [PMID: 28215534 DOI: 10.1016/bs.ircmb.2016.09.007] [Citation(s) in RCA: 133] [Impact Index Per Article: 16.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
The ability of tumor cells to escape tumor immunosurveillance contributes to cancer development. Factors produced in the tumor microenvironment create "tolerizing" conditions and thereby help the tumor to evade antitumoral immune responses. VEGF-A, already known for its major role in tumor vessel growth (neoangiogenesis), was recently identified as a key factor in tumor-induced immunosuppression. In particular, VEGF-A fosters the proliferation of immunosuppressive cells, limits T-cell recruitment into tumors, and promotes T-cell exhaustion. Antiangiogenic therapies have shown significant efficacy in patients with a variety of solid tumors, preventing tumor progression by limiting tumor-induced angiogenesis. VEGF-targeting therapies have also been shown to modulate the tumor-induced immunosuppressive microenvironment, enhancing Th1-type T-cell responses and increasing tumor infiltration by T cells. The immunomodulatory properties of VEGF-targeting therapies open up new perspectives for cancer treatment, especially through strategies combining antiangiogenic drugs with immunotherapy. Preclinical models and early clinical studies of these combined approaches have given promising results.
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Affiliation(s)
- A Lapeyre-Prost
- INSERM U970, PARCC (Paris Cardiovascular Research Center), Université Paris-Descartes, Paris, France
| | - M Terme
- INSERM U970, PARCC (Paris Cardiovascular Research Center), Université Paris-Descartes, Paris, France.
| | - S Pernot
- INSERM U970, PARCC (Paris Cardiovascular Research Center), Université Paris-Descartes, Paris, France; Service d'hépatogastroentérologie et d'oncologie digestive, Hôpital Européen Georges Pompidou, Paris, France
| | - A-L Pointet
- INSERM U970, PARCC (Paris Cardiovascular Research Center), Université Paris-Descartes, Paris, France; Service d'hépatogastroentérologie et d'oncologie digestive, Hôpital Européen Georges Pompidou, Paris, France
| | - T Voron
- INSERM U970, PARCC (Paris Cardiovascular Research Center), Université Paris-Descartes, Paris, France; Service de chirurgie digestive, Hôpital Européen Georges Pompidou, Paris, France
| | - E Tartour
- INSERM U970, PARCC (Paris Cardiovascular Research Center), Université Paris-Descartes, Paris, France; Service d'immunologie biologique. Hôpital Européen Georges Pompidou, Paris, France
| | - J Taieb
- INSERM U970, PARCC (Paris Cardiovascular Research Center), Université Paris-Descartes, Paris, France; Service d'hépatogastroentérologie et d'oncologie digestive, Hôpital Européen Georges Pompidou, Paris, France.
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22
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Ulyte A, Katsaros VK, Liouta E, Stranjalis G, Boskos C, Papanikolaou N, Usinskiene J, Bisdas S. Prognostic value of preoperative dynamic contrast-enhanced MRI perfusion parameters for high-grade glioma patients. Neuroradiology 2016; 58:1197-1208. [PMID: 27796446 PMCID: PMC5153415 DOI: 10.1007/s00234-016-1741-7] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2016] [Accepted: 08/16/2016] [Indexed: 12/22/2022]
Abstract
Introduction The prognostic value of the dynamic contrast-enhanced (DCE) MRI perfusion and its histogram analysis-derived metrics is not well established for high-grade glioma (HGG) patients. The aim of this prospective study was to investigate DCE perfusion transfer coefficient (Ktrans), vascular plasma volume fraction (vp), extracellular volume fraction (ve), reverse transfer constant (kep), and initial area under gadolinium concentration time curve (IAUGC) as predictors of progression-free (PFS) and overall survival (OS) in HGG patients. Methods Sixty-nine patients with suspected anaplastic astrocytoma or glioblastoma underwent preoperative DCE-MRI scans. DCE perfusion whole tumor region histogram parameters, clinical details, and PFS and OS data were obtained. Univariate, multivariate, and Kaplan–Meier survival analyses were conducted. Receiver operating characteristic (ROC) curve analysis was employed to identify perfusion parameters with the best differentiation performance. Results On univariate analysis, ve and skewness of vp had significant negative impacts, while kep had significant positive impact on OS (P < 0.05). ve was also a negative predictor of PFS (P < 0.05). Patients with lower ve and IAUGC had longer median PFS and OS on Kaplan–Meier analysis (P < 0.05). Ktrans and ve could also differentiate grade III from IV gliomas (area under the curve 0.819 and 0.791, respectively). Conclusions High ve is a consistent predictor of worse PFS and OS in HGG glioma patients. vp skewness and kep are also predictive for OS. Ktrans and ve demonstrated the best diagnostic performance for differentiating grade III from IV gliomas.
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Affiliation(s)
- Agne Ulyte
- Faculty of Medicine, Vilnius University, Vilnius, Lithuania
| | - Vasileios K Katsaros
- Department of Advanced Imaging Modalities - CT and MRI, General Anticancer and Oncological Hospital "St. Savvas", Athens, Greece.,Department of Neurosurgery, Evangelismos Hospital, University of Athens, Athens, Greece
| | - Evangelia Liouta
- Department of Neurosurgery, Evangelismos Hospital, University of Athens, Athens, Greece
| | - Georgios Stranjalis
- Department of Neurosurgery, Evangelismos Hospital, University of Athens, Athens, Greece
| | - Christos Boskos
- Department of Neurosurgery, Evangelismos Hospital, University of Athens, Athens, Greece.,Department of Radiation Oncology, General Anticancer and Oncological Hospital "St. Savvas", Athens, Greece
| | - Nickolas Papanikolaou
- Department of Radiology, Centre for the Unknown, Champalimaud Foundation, Lisbon, Portugal
| | - Jurgita Usinskiene
- National Cancer Institute, Vilnius, Lithuania.,Affidea Lietuva, Vilnius, Lithuania
| | - Sotirios Bisdas
- Department of Neuroradiology, The National Hospital for Neurology and Neurosurgery, University College London Hospitals, Box 65, Queen Square 8-11, London, WC1N 3BG, UK.
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23
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Lassau N, Coiffier B, Kind M, Vilgrain V, Lacroix J, Cuinet M, Taieb S, Aziza R, Sarran A, Labbe-Devilliers C, Gallix B, Lucidarme O, Ptak Y, Rocher L, Caquot LM, Chagnon S, Marion D, Luciani A, Feutray S, Uzan-Augui J, Benatsou B, Bonastre J, Koscielny S. Selection of an early biomarker for vascular normalization using dynamic contrast-enhanced ultrasonography to predict outcomes of metastatic patients treated with bevacizumab. Ann Oncol 2016; 27:1922-8. [PMID: 27502701 DOI: 10.1093/annonc/mdw280] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2016] [Accepted: 07/06/2016] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND Dynamic contrast-enhanced ultrasonography (DCE-US) has been used for evaluation of tumor response to antiangiogenic treatments. The objective of this study was to assess the link between DCE-US data obtained during the first week of treatment and subsequent tumor progression. PATIENTS AND METHODS Patients treated with antiangiogenic therapies were included in a multicentric prospective study from 2007 to 2010. DCE-US examinations were available at baseline and at day 7. For each examination, a 3 min perfusion curve was recorded just after injection of a contrast agent. Each perfusion curve was modeled with seven parameters. We analyzed the correlation between criteria measured up to day 7 on freedom from progression (FFP). The impact was assessed globally, according to tumor localization and to type of treatment. RESULTS The median follow-up was 20 months. The mean transit time (MTT) evaluated at day 7 was the only criterion significantly associated with FFP (P = 0.002). The cut-off point maximizing the difference between FFP curves was 12 s. Patients with at least a 12 s MTT had a better FFP. The results according to tumor type were significantly heterogeneous: the impact of MTT on FFP was more marked for breast cancer (P = 0.004) and for colon cancer (P = 0.025) than for other tumor types. Similarly, the differences in FFP according to MTT at day 7 were marked (P = 0.004) in patients receiving bevacizumab. CONCLUSION The MTT evaluated with DCE-US at day 7 is significantly correlated to FFP of patients treated with bevacizumab. This criterion might be linked to vascular normalization. AFSSAPS NO 2007-A00399-44.
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Affiliation(s)
- N Lassau
- Gustave Roussy, Université Paris-Saclay, Imaging Department, Villejuif, and IR4M, Centre National de la Recherche Scientifique, Université Paris-Sud, Université Paris-Saclay, Villejuif
| | - B Coiffier
- Gustave Roussy, Université Paris-Saclay, Imaging Department, Villejuif, and IR4M, Centre National de la Recherche Scientifique, Université Paris-Sud, Université Paris-Saclay, Villejuif
| | - M Kind
- Imaging Department, Institut Bergonié, Bordeaux
| | - V Vilgrain
- Radiology Department, Assistance Publique-Hôpitaux de Paris, Hôpital Beaujon, Clichy
| | - J Lacroix
- Radiology Department, Centre François Baclesse, Caen
| | - M Cuinet
- Radiology Department, Centre Léon Bérard, Lyon
| | - S Taieb
- Radiology Department, Centre Oscar Lambret, Lille
| | - R Aziza
- Radiodiagnostics Department, Centre Claudius Regaud, Toulouse
| | - A Sarran
- Imaging Department, Institut Paoli Calmettes, Marseille
| | | | - B Gallix
- Department of Abdominal and Digestive Imaging, Hôpital Saint-Eloi, Montpellier and Department of Radiology, McGill University Health Center, Montreal, Canada
| | - O Lucidarme
- Radiology Department, CHU La Pitié-Salpêtrière, Paris
| | - Y Ptak
- Radiodiagnostics Department, Centre Jean Perrin, Clermont-Ferrand
| | - L Rocher
- Radiology Department, CHU Bicêtre, Le Kremlin-Bicêtre
| | - L M Caquot
- Radiodiagnostics and Imaging Department, Institut Jean Godinot, Reims
| | - S Chagnon
- Radiology Department, Hôpital Ambroise Paré, Boulogne-Billancourt
| | - D Marion
- Radiology Department, CHU Hôtel-Dieu, Lyon
| | - A Luciani
- Radiology Department, CHU Henri Mondor, Créteil
| | - S Feutray
- Radiology Department, Centre Georges-François Leclerc, Dijon
| | | | - B Benatsou
- Gustave Roussy, Université Paris-Saclay, Imaging Department, Villejuif, and IR4M, Centre National de la Recherche Scientifique, Université Paris-Sud, Université Paris-Saclay, Villejuif
| | - J Bonastre
- Service biostatistique et épidémiologie, Gustave Roussy and CESP Centre for Research in Epidemiology and Population Health, INSERM U1018, Paris-Sud Univ., Villejuif, France
| | - S Koscielny
- Service biostatistique et épidémiologie, Gustave Roussy and CESP Centre for Research in Epidemiology and Population Health, INSERM U1018, Paris-Sud Univ., Villejuif, France
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24
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Mehta S, Hughes NP, Li S, Jubb A, Adams R, Lord S, Koumakis L, van Stiphout R, Padhani A, Makris A, Buffa FM, Harris AL. Radiogenomics Monitoring in Breast Cancer Identifies Metabolism and Immune Checkpoints as Early Actionable Mechanisms of Resistance to Anti-angiogenic Treatment. EBioMedicine 2016; 10:109-16. [PMID: 27474395 PMCID: PMC5006694 DOI: 10.1016/j.ebiom.2016.07.017] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2016] [Revised: 07/07/2016] [Accepted: 07/14/2016] [Indexed: 02/07/2023] Open
Abstract
Anti-VEGF antibody bevacizumab has prolonged progression-free survival in several cancer types, however acquired resistance is common. Adaption has been observed pre-clinically, but no human study has shown timing and genes involved, enabling formulation of new clinical paradigms. In a window-of-opportunity study in 35 ductal breast cancer patients for 2weeks prior to neoadjuvant chemotherapy, we monitored bevacizumab response by Dynamic Contrast-Enhanced Magnetic Resonance [DCE-MRI], transcriptomic and pathology. Initial treatment response showed significant overall decrease in DCE-MRI median K(trans), angiogenic factors such ESM1 and FLT1, and proliferation. However, it also revealed great heterogeneity, spanning from downregulation of blood vessel density and central necrosis to continued growth with new vasculature. Crucially, significantly upregulated pathways leading to resistance included glycolysis and pH adaptation, PI3K-Akt and immune checkpoint signaling, for which inhibitors exist, making a strong case to investigate such combinations. These findings support that anti-angiogenesis trials should incorporate initial enrichment of patients with high K(trans), and a range of targeted therapeutic options to meet potential early resistance pathways. Multi-arm adaptive trials are ongoing using molecular markers for targeted agents, but our results suggest this needs to be further modified by much earlier adaptation when using drugs affecting the tumor microenvironment.
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Affiliation(s)
- Shaveta Mehta
- Department of Oncology, University of Oxford, Oxford, UK
| | - Nick P Hughes
- Department of Engineering, University of Oxford, Oxford, UK
| | - Sonia Li
- Paul Strickland Scanner Centre, Northwood, Middlesex, UK
| | - Adrian Jubb
- Department of Oncology, University of Oxford, Oxford, UK
| | - Rosie Adams
- Department of Oncology, University of Oxford, Oxford, UK
| | - Simon Lord
- Department of Oncology, University of Oxford, Oxford, UK
| | | | | | - Anwar Padhani
- Mount Vernon Cancer Centre, Northwood, Middlesex, UK
| | - Andreas Makris
- Paul Strickland Scanner Centre, Northwood, Middlesex, UK
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25
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Abstract
Angiogenesis, the formation of new blood vessels from pre-existing vessels, has been validated as a target in several tumour types through randomised trials, incorporating vascular endothelial growth factor (VEGF) pathway inhibitors into the therapeutic armoury. Although some tumours such as renal cell carcinoma, ovarian and cervical cancers, and pancreatic neuroendocrine tumours are sensitive to these drugs, others such as prostate cancer, pancreatic adenocarcinoma, and melanoma are resistant. Even when drugs have yielded significant results, improvements in progression-free survival, and, in some cases, overall survival, are modest. Thus, a crucial issue in development of these drugs is the search for predictive biomarkers-tests that predict which patients will, and will not, benefit before initiation of therapy. Development of biomarkers is important because of the need to balance efficacy, toxicity, and cost. Novel combinations of these drugs with other antiangiogenics or other classes of drugs are being developed, and the appreciation that these drugs have immunomodulatory and other modes of action will lead to combination regimens that capitalise on these newly understood mechanisms.
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Affiliation(s)
- Gordon C Jayson
- Institute of Cancer Sciences and Christie Hospital, University of Manchester, Manchester, UK.
| | - Robert Kerbel
- Biological Sciences Platform, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Lee M Ellis
- Department of Surgical Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, USA; Department of Molecular and Cellular Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Adrian L Harris
- Department of Medical Oncology, Churchill Hospital, University of Oxford, Oxford, UK
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26
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Turco S, Wijkstra H, Mischi M. Mathematical Models of Contrast Transport Kinetics for Cancer Diagnostic Imaging: A Review. IEEE Rev Biomed Eng 2016; 9:121-47. [PMID: 27337725 DOI: 10.1109/rbme.2016.2583541] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
Angiogenesis plays a fundamental role in cancer growth and the formation of metastasis. Novel cancer therapies aimed at inhibiting angiogenic processes and/or disrupting angiogenic tumor vasculature are currently being developed and clinically tested. The need for earlier and improved cancer diagnosis, and for early evaluation and monitoring of therapeutic response to angiogenic treatment, have led to the development of several imaging methods for in vivo noninvasive assessment of angiogenesis. The combination of dynamic contrast-enhanced imaging with mathematical modeling of the contrast agent kinetics enables quantitative assessment of the structural and functional changes in the microvasculature that are associated with tumor angiogenesis. In this paper, we review quantitative imaging of angiogenesis with dynamic contrast-enhanced magnetic resonance imaging, computed tomography, and ultrasound.
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27
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Chen BB, Hsu CY, Yu CW, Liang PC, Hsu C, Hsu CH, Cheng AL, Shih TTF. Dynamic Contrast-enhanced MR Imaging of Advanced Hepatocellular Carcinoma: Comparison with the Liver Parenchyma and Correlation with the Survival of Patients Receiving Systemic Therapy. Radiology 2016; 281:454-464. [PMID: 27171020 DOI: 10.1148/radiol.2016152659] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Purpose To retrospectively compare the perfusion parameters of advanced hepatocellular carcinoma (HCC) measured with dynamic contrast material-enhanced (DCE) magnetic resonance (MR) imaging with surrounding liver parenchyma to determine the relationship between these parameters and uncensored overall survival (OS). Materials and Methods This retrospective study had institutional review board approval, and informed consent was waived. DCE MR imaging was performed in 92 patients with advanced HCC before systemic treatment was administered (19 patients received a placebo). Three semiquantitative (peak, slope, and area under the gadolinium concentration-time curve [AUC]) and six quantitative (arterial fraction, arterial flow, portal flow, total blood flow, distribution volume, and mean transit time) parameters were calculated by placing regions of interest in the largest area of the tumor and background liver parenchyma. The DCE MR imaging parameters between the tumor and normal liver were compared with paired Wilcoxon test. By using the Cox proportional hazards model for univariate and multivariate analyses, the association of DCE MR imaging parameters and OS was investigated. Results HCC demonstrated significantly higher peak, slope, AUC, arterial fraction, and arterial flow but lower portal flow, distribution volume, and mean transit time than did the background liver (all P < .05). Patients with high peak in the tumor had longer OS (P = .005) than did those with low peak. Cox multivariate analysis identified peak as an independent predictor of OS (P = .032) after adjusting for age, sex, treatment, tumor size, and portal vein thrombosis. Conclusion DCE MR imaging parameters can be used to differentiate advanced HCC from the background liver, and peak, a semiquantitative parameter, is associated with outcome in patients with advanced HCC before systemic therapy. © RSNA, 2016 An earlier incorrect version of this article appeared online. This article was corrected on July 22, 2016.
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Affiliation(s)
- Bang-Bin Chen
- From the Department of Medical Imaging and Radiology (B.B.C., C.Y.H., C.W.Y., P.C.L.) and Department of Oncology (C.H., C.H.H., A.L.C.), National Taiwan University College of Medicine and Hospital, Taipei, Taiwan; Department of Radiology (C.Y.H.), Taipei Hospital, Ministry of Health and Welfare, New Taipei, Taiwan; and Department of Medical Imaging, Taipei City Hospital, No 7 Chung-Shan South Rd, Taipei 10016, Taiwan (T.T.F.S.)
| | - Chao-Yu Hsu
- From the Department of Medical Imaging and Radiology (B.B.C., C.Y.H., C.W.Y., P.C.L.) and Department of Oncology (C.H., C.H.H., A.L.C.), National Taiwan University College of Medicine and Hospital, Taipei, Taiwan; Department of Radiology (C.Y.H.), Taipei Hospital, Ministry of Health and Welfare, New Taipei, Taiwan; and Department of Medical Imaging, Taipei City Hospital, No 7 Chung-Shan South Rd, Taipei 10016, Taiwan (T.T.F.S.)
| | - Chih-Wei Yu
- From the Department of Medical Imaging and Radiology (B.B.C., C.Y.H., C.W.Y., P.C.L.) and Department of Oncology (C.H., C.H.H., A.L.C.), National Taiwan University College of Medicine and Hospital, Taipei, Taiwan; Department of Radiology (C.Y.H.), Taipei Hospital, Ministry of Health and Welfare, New Taipei, Taiwan; and Department of Medical Imaging, Taipei City Hospital, No 7 Chung-Shan South Rd, Taipei 10016, Taiwan (T.T.F.S.)
| | - Po-Chin Liang
- From the Department of Medical Imaging and Radiology (B.B.C., C.Y.H., C.W.Y., P.C.L.) and Department of Oncology (C.H., C.H.H., A.L.C.), National Taiwan University College of Medicine and Hospital, Taipei, Taiwan; Department of Radiology (C.Y.H.), Taipei Hospital, Ministry of Health and Welfare, New Taipei, Taiwan; and Department of Medical Imaging, Taipei City Hospital, No 7 Chung-Shan South Rd, Taipei 10016, Taiwan (T.T.F.S.)
| | - Chiun Hsu
- From the Department of Medical Imaging and Radiology (B.B.C., C.Y.H., C.W.Y., P.C.L.) and Department of Oncology (C.H., C.H.H., A.L.C.), National Taiwan University College of Medicine and Hospital, Taipei, Taiwan; Department of Radiology (C.Y.H.), Taipei Hospital, Ministry of Health and Welfare, New Taipei, Taiwan; and Department of Medical Imaging, Taipei City Hospital, No 7 Chung-Shan South Rd, Taipei 10016, Taiwan (T.T.F.S.)
| | - Chih-Hung Hsu
- From the Department of Medical Imaging and Radiology (B.B.C., C.Y.H., C.W.Y., P.C.L.) and Department of Oncology (C.H., C.H.H., A.L.C.), National Taiwan University College of Medicine and Hospital, Taipei, Taiwan; Department of Radiology (C.Y.H.), Taipei Hospital, Ministry of Health and Welfare, New Taipei, Taiwan; and Department of Medical Imaging, Taipei City Hospital, No 7 Chung-Shan South Rd, Taipei 10016, Taiwan (T.T.F.S.)
| | - Ann-Lii Cheng
- From the Department of Medical Imaging and Radiology (B.B.C., C.Y.H., C.W.Y., P.C.L.) and Department of Oncology (C.H., C.H.H., A.L.C.), National Taiwan University College of Medicine and Hospital, Taipei, Taiwan; Department of Radiology (C.Y.H.), Taipei Hospital, Ministry of Health and Welfare, New Taipei, Taiwan; and Department of Medical Imaging, Taipei City Hospital, No 7 Chung-Shan South Rd, Taipei 10016, Taiwan (T.T.F.S.)
| | - Tiffany Ting-Fang Shih
- From the Department of Medical Imaging and Radiology (B.B.C., C.Y.H., C.W.Y., P.C.L.) and Department of Oncology (C.H., C.H.H., A.L.C.), National Taiwan University College of Medicine and Hospital, Taipei, Taiwan; Department of Radiology (C.Y.H.), Taipei Hospital, Ministry of Health and Welfare, New Taipei, Taiwan; and Department of Medical Imaging, Taipei City Hospital, No 7 Chung-Shan South Rd, Taipei 10016, Taiwan (T.T.F.S.)
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Salem A, O'Connor JPB. Assessment of Tumor Angiogenesis: Dynamic Contrast-enhanced MR Imaging and Beyond. Magn Reson Imaging Clin N Am 2016; 24:45-56. [PMID: 26613875 DOI: 10.1016/j.mric.2015.08.010] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Dynamic contrast-enhanced (DCE) MR imaging is used increasingly often to evaluate tumor angiogenesis and the efficacy of antiangiogenic drugs. In clinical practice DCE-MR imaging applications are largely centered on lesion detection, characterization, and localization. In research, DCE-MR imaging helps inform decision making in early-phase clinical trials by showing efficacy and by selecting dose and schedule. However, the role of these techniques in patient selection is uncertain. Future research is required to optimize existing DCE-MR imaging methods and to fully validate these biomarkers for wider use in patient care and in drug development.
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Affiliation(s)
- Ahmed Salem
- Cancer Research UK and EPSRC Cancer Imaging Centre, University of Manchester, Oxford Road, Manchester M13 9PT, UK
| | - James P B O'Connor
- Cancer Research UK and EPSRC Cancer Imaging Centre, University of Manchester, Oxford Road, Manchester M13 9PT, UK. james.o'
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29
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Lim Y, Han SW, Yoon JH, Lee JM, Lee JM, Paeng JC, Won JK, Kang GH, Jeong SY, Park KJ, Lee KH, Kim JH, Kim TY. Clinical Implication of Anti-Angiogenic Effect of Regorafenib in Metastatic Colorectal Cancer. PLoS One 2015; 10:e0145004. [PMID: 26671465 PMCID: PMC4684400 DOI: 10.1371/journal.pone.0145004] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2015] [Accepted: 11/24/2015] [Indexed: 12/19/2022] Open
Abstract
Background Regorafenib induces distinct radiological changes that represent its anti-angiogenic effect. However, clinical implication of the changes is unclear. Methods Tumor attenuation as measured by Hounsfield units (HU) in contrast-enhanced computed tomography (CT) and cavitary changes of lung metastases were analyzed in association with treatment outcome of metastatic colorectal cancer patients (N = 80) treated with regorafenib in a prospective study. Results 141 lesions in 72 patients were analyzed with HU. After 2 cycles of regorafenib, 87.5% of patients showed decrease of HU (Median change -23.9%, range -61.5%–20.7%). Lesional attenuation change was modestly associated with metabolic changes of 18-fluoro-deoxyglucose positron emission tomography-CT (Pearson’s r = 0.37, p = 0.002). Among 53 patients with lung metastases, 17 (32.1%) developed cavitary changes. There were no differences in disease control rate, progression-free survival, or overall survival according to the radiological changes. At the time of progressive disease (PD) according to RECIST 1.1, HU was lower than baseline in 86.0% (43/50) and cavitary change of lung metastasis persisted without refilling in 84.6% (11/13). Conclusion Regorafenib showed prominent anti-angiogenic effect in colorectal cancer, but the changes were not associated with treatment outcome. However, the anti-angiogenic effects persisted at the time of PD, which suggests that we may need to develop new treatment strategies.
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Affiliation(s)
- Yoojoo Lim
- Department of Internal Medicine, Seoul National University Hospital, Seoul, Korea
| | - Sae-Won Han
- Department of Internal Medicine, Seoul National University Hospital, Seoul, Korea
- Cancer Research Institute, Seoul National University College of Medicine, Seoul, Korea
| | - Jeong Hee Yoon
- Department of Radiology, Seoul National University Hospital, Seoul, Korea
| | - Jeong Min Lee
- Department of Radiology, Seoul National University Hospital, Seoul, Korea
| | - Jung Min Lee
- Department of Nuclear Medicine, Seoul National University Hospital, Seoul, Korea
| | - Jin Chul Paeng
- Department of Nuclear Medicine, Seoul National University Hospital, Seoul, Korea
| | - Jae-Kyung Won
- Department of Pathology, Seoul National University Hospital, Seoul, Korea
| | - Gyeong Hoon Kang
- Department of Pathology, Seoul National University Hospital, Seoul, Korea
| | - Seung-Yong Jeong
- Department of Surgery, Seoul National University Hospital, Seoul, Korea
| | - Kyu Joo Park
- Department of Surgery, Seoul National University Hospital, Seoul, Korea
| | - Kyung-Hun Lee
- Department of Internal Medicine, Seoul National University Hospital, Seoul, Korea
| | - Jee Hyun Kim
- Department of Internal Medicine, Seoul National University Bundang Hospital, Seongnam-si, Geyonggi-do, Korea
| | - Tae-You Kim
- Department of Internal Medicine, Seoul National University Hospital, Seoul, Korea
- Cancer Research Institute, Seoul National University College of Medicine, Seoul, Korea
- Department of Molecular Medicine & Biopharmaceutical Sciences, Graduate School of Convergence Science and Technology, Seoul National University, Seoul, Korea
- * E-mail:
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30
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Winfield JM, Payne GS, deSouza NM. Functional MRI and CT biomarkers in oncology. Eur J Nucl Med Mol Imaging 2015; 42:562-78. [PMID: 25578953 DOI: 10.1007/s00259-014-2979-0] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2014] [Accepted: 12/15/2014] [Indexed: 02/07/2023]
Abstract
Imaging biomarkers derived from MRI or CT describe functional properties of tumours and normal tissues. They are finding increasing numbers of applications in diagnosis, monitoring of response to treatment and assessment of progression or recurrence. Imaging biomarkers also provide scope for assessment of heterogeneity within and between lesions. A wide variety of functional parameters have been investigated for use as biomarkers in oncology. Some imaging techniques are used routinely in clinical applications while others are currently restricted to clinical trials or preclinical studies. Apparent diffusion coefficient, magnetization transfer ratio and native T1 relaxation time provide information about structure and organization of tissues. Vascular properties may be described using parameters derived from dynamic contrast-enhanced MRI, dynamic contrast-enhanced CT, transverse relaxation rate (R2*), vessel size index and relative blood volume, while magnetic resonance spectroscopy may be used to probe the metabolic profile of tumours. This review describes the mechanisms of contrast underpinning each technique and the technical requirements for robust and reproducible imaging. The current status of each biomarker is described in terms of its validation, qualification and clinical applications, followed by a discussion of the current limitations and future perspectives.
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Affiliation(s)
- J M Winfield
- CRUK Imaging Centre at the Institute of Cancer Research, Institute of Cancer Research and Royal Marsden NHS Foundation Trust, Sutton, UK,
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31
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García-Figueiras R, Padhani AR, Beer AJ, Baleato-González S, Vilanova JC, Luna A, Oleaga L, Gómez-Caamaño A, Koh DM. Imaging of Tumor Angiogenesis for Radiologists--Part 2: Clinical Utility. Curr Probl Diagn Radiol 2015; 44:425-36. [PMID: 25863438 DOI: 10.1067/j.cpradiol.2015.02.009] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2014] [Revised: 02/24/2015] [Accepted: 02/28/2015] [Indexed: 12/26/2022]
Abstract
Angiogenesis is a key cancer hallmark involved in tumor growth and metastasis development. Angiogenesis and tumor microenvironment significantly influence the response of tumors to therapies. Imaging techniques have changed our understanding of the process of angiogenesis, the resulting vascular performance, and the tumor microenvironment. This article reviews the status and potential clinical value of the imaging modalities used to assess the status of tumor vasculature in vivo, before, during, and after treatment.
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Affiliation(s)
- Roberto García-Figueiras
- Department of Radiology, Hospital Clínico Universitario de Santiago de Compostela, Santiago de Compostela, Spain.
| | - Anwar R Padhani
- Paul Strickland Scanner Centre, Mount Vernon Cancer Centre, Northwood, Middlesex, England, UK
| | - Ambros J Beer
- Klinik für Nuklearmedizin, Universitätsklinikum Ulm; Ulm, Germany
| | - Sandra Baleato-González
- Department of Radiology, Hospital Clínico Universitario de Santiago de Compostela, Santiago de Compostela, Spain
| | - Joan C Vilanova
- Department of Radiology, Clínica Girona, IDI, University of Girona, Girona, Spain
| | - Antonio Luna
- Advanced Medical Imaging, Clinica Las Nieves, SERCOSA (Servicio Radiologia Computerizada), Grupo Health Time, Jaén, Spain; Department of Radiology, Case Western Reserve University, Cleveland, OH
| | - Laura Oleaga
- Department of Radiology, Hospital Clínic Barcelona, Barcelona, Spain
| | - Antonio Gómez-Caamaño
- Department of Radiotherapy, Hospital Clínico Universitario de Santiago de Compostela, Santiago de Compostela, Spain
| | - Dow-Mu Koh
- Functional Imaging, Royal Marsden Hospital, Sutton, Surrey, England, UK
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32
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Lassau N, Bonastre J, Kind M, Vilgrain V, Lacroix J, Cuinet M, Taieb S, Aziza R, Sarran A, Labbe-Devilliers C, Gallix B, Lucidarme O, Ptak Y, Rocher L, Caquot LM, Chagnon S, Marion D, Luciani A, Feutray S, Uzan-Augui J, Coiffier B, Benastou B, Koscielny S. Validation of dynamic contrast-enhanced ultrasound in predicting outcomes of antiangiogenic therapy for solid tumors: the French multicenter support for innovative and expensive techniques study. Invest Radiol 2014; 49:794-800. [PMID: 24991866 PMCID: PMC4222794 DOI: 10.1097/rli.0000000000000085] [Citation(s) in RCA: 97] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
OBJECTIVES Dynamic contrast-enhanced ultrasound (DCE-US) has been used in single-center studies to evaluate tumor response to antiangiogenic treatments: the change of area under the perfusion curve (AUC), a criterion linked to blood volume, was consistently correlated with the Response Evaluation Criteria in Solid Tumors response. The main objective here was to do a multicentric validation of the use of DCE-US to evaluate tumor response in different solid tumor types treated by several antiangiogenic agents. A secondary objective was to evaluate the costs of the procedure. MATERIALS AND METHODS This prospective study included patients from 2007 to 2010 in 19 centers (8 teaching hospitals and 11 comprehensive cancer centers). All patients treated with antiangiogenic therapy were eligible. Dynamic contrast-enhanced ultrasound examinations were performed at baseline as well as on days 7, 15, 30, and 60. For each examination, a perfusion curve was recorded during 3 minutes after injection of a contrast agent. Change from baseline at each time point was estimated for each of 7 fitted criteria. The main end point was freedom from progression (FFP). Criterion/time-point combinations with the strongest correlation with FFP were analyzed further to estimate an optimal cutoff point. RESULTS A total of 1968 DCE-US examinations in 539 patients were analyzed. The median follow-up was 1.65 years. Variations from baseline were significant at day 30 for several criteria, with AUC having the most significant association with FFP (P = 0.00002). Patients with a greater than 40% decrease in AUC at day 30 had better FFP (P = 0.005) and overall survival (P = 0.05). The mean cost of each DCE-US was 180&OV0556;, which corresponds to $250 using the current exchange rate. CONCLUSIONS Dynamic contrast-enhanced ultrasound is a new functional imaging technique that provides a validated criterion, namely, the change of AUC from baseline to day 30, which is predictive of tumor progression in a large multicenter cohort. Because of its low cost, it should be considered in the routine evaluation of solid tumors treated with antiangiogenic therapy.
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Affiliation(s)
- Nathalie Lassau
- From the *Integrated Research Cancer Institute, Research Department, Villejuif; †Service Biostatistique et Épidémiologie, Gustave Roussy, Villejuif; ‡Imaging Department, Institut Bergonié, Bordeaux; §Department of Radiology, Assistance Publique-Hôpitaux de Paris, Hôpital Beaujon, Clichy, and Université Paris Diderot, Sorbonne Paris Cité; ∥Department of Radiology, Centre François Baclesse, Caen; ¶Department of Radiology, Centre Léon Bérard, Lyon; #Imaging Department, Centre Oscar Lambret, Lille; **Radiodiagnostics Department, Centre Claudius Regaud, Toulouse; ††Imaging Department, Institut Paoli Calmettes, Marseille; ‡‡Radiodiagnostics Department, Centre R Gauducheau, Institut de Cancérologie de l’Ouest Nantes; §§Department of Abdominal and Digestive Imaging, Hôpital Saint-Éloi, Montpellier; ∥∥Radiology Department, Centre Hospitalier Universitaire La Pitié-Salpêtrière, Paris; ¶¶Radiodiagnostics Department, Centre Jean Perrin, Clermont-Ferrand; ##Radiology Department, Centre Hospitalier Universitaire Bicêtre, Le Kremlin-Bicêtre; ***Radiodiagnostics and Imaging Department, Institut Jean Godinot, Reims; †††Ultrasonography Department, Hôpital Ambroise Paré, Boulogne-Billancourt; ‡‡‡Radiology Department, Centre Hospitalier Universitaire Hôtel-Dieu, Lyon; §§§Radiology Department, Centre Hospitalier Universitaire Henri Mondor, Créteil; ∥∥∥Imaging Department, Centre Georges-François Leclerc, Dijon Cedex; and ¶¶¶Radiology Department, Hôpital Cochin, Paris, France
| | - Julia Bonastre
- From the *Integrated Research Cancer Institute, Research Department, Villejuif; †Service Biostatistique et Épidémiologie, Gustave Roussy, Villejuif; ‡Imaging Department, Institut Bergonié, Bordeaux; §Department of Radiology, Assistance Publique-Hôpitaux de Paris, Hôpital Beaujon, Clichy, and Université Paris Diderot, Sorbonne Paris Cité; ∥Department of Radiology, Centre François Baclesse, Caen; ¶Department of Radiology, Centre Léon Bérard, Lyon; #Imaging Department, Centre Oscar Lambret, Lille; **Radiodiagnostics Department, Centre Claudius Regaud, Toulouse; ††Imaging Department, Institut Paoli Calmettes, Marseille; ‡‡Radiodiagnostics Department, Centre R Gauducheau, Institut de Cancérologie de l’Ouest Nantes; §§Department of Abdominal and Digestive Imaging, Hôpital Saint-Éloi, Montpellier; ∥∥Radiology Department, Centre Hospitalier Universitaire La Pitié-Salpêtrière, Paris; ¶¶Radiodiagnostics Department, Centre Jean Perrin, Clermont-Ferrand; ##Radiology Department, Centre Hospitalier Universitaire Bicêtre, Le Kremlin-Bicêtre; ***Radiodiagnostics and Imaging Department, Institut Jean Godinot, Reims; †††Ultrasonography Department, Hôpital Ambroise Paré, Boulogne-Billancourt; ‡‡‡Radiology Department, Centre Hospitalier Universitaire Hôtel-Dieu, Lyon; §§§Radiology Department, Centre Hospitalier Universitaire Henri Mondor, Créteil; ∥∥∥Imaging Department, Centre Georges-François Leclerc, Dijon Cedex; and ¶¶¶Radiology Department, Hôpital Cochin, Paris, France
| | - Michèle Kind
- From the *Integrated Research Cancer Institute, Research Department, Villejuif; †Service Biostatistique et Épidémiologie, Gustave Roussy, Villejuif; ‡Imaging Department, Institut Bergonié, Bordeaux; §Department of Radiology, Assistance Publique-Hôpitaux de Paris, Hôpital Beaujon, Clichy, and Université Paris Diderot, Sorbonne Paris Cité; ∥Department of Radiology, Centre François Baclesse, Caen; ¶Department of Radiology, Centre Léon Bérard, Lyon; #Imaging Department, Centre Oscar Lambret, Lille; **Radiodiagnostics Department, Centre Claudius Regaud, Toulouse; ††Imaging Department, Institut Paoli Calmettes, Marseille; ‡‡Radiodiagnostics Department, Centre R Gauducheau, Institut de Cancérologie de l’Ouest Nantes; §§Department of Abdominal and Digestive Imaging, Hôpital Saint-Éloi, Montpellier; ∥∥Radiology Department, Centre Hospitalier Universitaire La Pitié-Salpêtrière, Paris; ¶¶Radiodiagnostics Department, Centre Jean Perrin, Clermont-Ferrand; ##Radiology Department, Centre Hospitalier Universitaire Bicêtre, Le Kremlin-Bicêtre; ***Radiodiagnostics and Imaging Department, Institut Jean Godinot, Reims; †††Ultrasonography Department, Hôpital Ambroise Paré, Boulogne-Billancourt; ‡‡‡Radiology Department, Centre Hospitalier Universitaire Hôtel-Dieu, Lyon; §§§Radiology Department, Centre Hospitalier Universitaire Henri Mondor, Créteil; ∥∥∥Imaging Department, Centre Georges-François Leclerc, Dijon Cedex; and ¶¶¶Radiology Department, Hôpital Cochin, Paris, France
| | - Valérie Vilgrain
- From the *Integrated Research Cancer Institute, Research Department, Villejuif; †Service Biostatistique et Épidémiologie, Gustave Roussy, Villejuif; ‡Imaging Department, Institut Bergonié, Bordeaux; §Department of Radiology, Assistance Publique-Hôpitaux de Paris, Hôpital Beaujon, Clichy, and Université Paris Diderot, Sorbonne Paris Cité; ∥Department of Radiology, Centre François Baclesse, Caen; ¶Department of Radiology, Centre Léon Bérard, Lyon; #Imaging Department, Centre Oscar Lambret, Lille; **Radiodiagnostics Department, Centre Claudius Regaud, Toulouse; ††Imaging Department, Institut Paoli Calmettes, Marseille; ‡‡Radiodiagnostics Department, Centre R Gauducheau, Institut de Cancérologie de l’Ouest Nantes; §§Department of Abdominal and Digestive Imaging, Hôpital Saint-Éloi, Montpellier; ∥∥Radiology Department, Centre Hospitalier Universitaire La Pitié-Salpêtrière, Paris; ¶¶Radiodiagnostics Department, Centre Jean Perrin, Clermont-Ferrand; ##Radiology Department, Centre Hospitalier Universitaire Bicêtre, Le Kremlin-Bicêtre; ***Radiodiagnostics and Imaging Department, Institut Jean Godinot, Reims; †††Ultrasonography Department, Hôpital Ambroise Paré, Boulogne-Billancourt; ‡‡‡Radiology Department, Centre Hospitalier Universitaire Hôtel-Dieu, Lyon; §§§Radiology Department, Centre Hospitalier Universitaire Henri Mondor, Créteil; ∥∥∥Imaging Department, Centre Georges-François Leclerc, Dijon Cedex; and ¶¶¶Radiology Department, Hôpital Cochin, Paris, France
| | - Joëlle Lacroix
- From the *Integrated Research Cancer Institute, Research Department, Villejuif; †Service Biostatistique et Épidémiologie, Gustave Roussy, Villejuif; ‡Imaging Department, Institut Bergonié, Bordeaux; §Department of Radiology, Assistance Publique-Hôpitaux de Paris, Hôpital Beaujon, Clichy, and Université Paris Diderot, Sorbonne Paris Cité; ∥Department of Radiology, Centre François Baclesse, Caen; ¶Department of Radiology, Centre Léon Bérard, Lyon; #Imaging Department, Centre Oscar Lambret, Lille; **Radiodiagnostics Department, Centre Claudius Regaud, Toulouse; ††Imaging Department, Institut Paoli Calmettes, Marseille; ‡‡Radiodiagnostics Department, Centre R Gauducheau, Institut de Cancérologie de l’Ouest Nantes; §§Department of Abdominal and Digestive Imaging, Hôpital Saint-Éloi, Montpellier; ∥∥Radiology Department, Centre Hospitalier Universitaire La Pitié-Salpêtrière, Paris; ¶¶Radiodiagnostics Department, Centre Jean Perrin, Clermont-Ferrand; ##Radiology Department, Centre Hospitalier Universitaire Bicêtre, Le Kremlin-Bicêtre; ***Radiodiagnostics and Imaging Department, Institut Jean Godinot, Reims; †††Ultrasonography Department, Hôpital Ambroise Paré, Boulogne-Billancourt; ‡‡‡Radiology Department, Centre Hospitalier Universitaire Hôtel-Dieu, Lyon; §§§Radiology Department, Centre Hospitalier Universitaire Henri Mondor, Créteil; ∥∥∥Imaging Department, Centre Georges-François Leclerc, Dijon Cedex; and ¶¶¶Radiology Department, Hôpital Cochin, Paris, France
| | - Marie Cuinet
- From the *Integrated Research Cancer Institute, Research Department, Villejuif; †Service Biostatistique et Épidémiologie, Gustave Roussy, Villejuif; ‡Imaging Department, Institut Bergonié, Bordeaux; §Department of Radiology, Assistance Publique-Hôpitaux de Paris, Hôpital Beaujon, Clichy, and Université Paris Diderot, Sorbonne Paris Cité; ∥Department of Radiology, Centre François Baclesse, Caen; ¶Department of Radiology, Centre Léon Bérard, Lyon; #Imaging Department, Centre Oscar Lambret, Lille; **Radiodiagnostics Department, Centre Claudius Regaud, Toulouse; ††Imaging Department, Institut Paoli Calmettes, Marseille; ‡‡Radiodiagnostics Department, Centre R Gauducheau, Institut de Cancérologie de l’Ouest Nantes; §§Department of Abdominal and Digestive Imaging, Hôpital Saint-Éloi, Montpellier; ∥∥Radiology Department, Centre Hospitalier Universitaire La Pitié-Salpêtrière, Paris; ¶¶Radiodiagnostics Department, Centre Jean Perrin, Clermont-Ferrand; ##Radiology Department, Centre Hospitalier Universitaire Bicêtre, Le Kremlin-Bicêtre; ***Radiodiagnostics and Imaging Department, Institut Jean Godinot, Reims; †††Ultrasonography Department, Hôpital Ambroise Paré, Boulogne-Billancourt; ‡‡‡Radiology Department, Centre Hospitalier Universitaire Hôtel-Dieu, Lyon; §§§Radiology Department, Centre Hospitalier Universitaire Henri Mondor, Créteil; ∥∥∥Imaging Department, Centre Georges-François Leclerc, Dijon Cedex; and ¶¶¶Radiology Department, Hôpital Cochin, Paris, France
| | - Sophie Taieb
- From the *Integrated Research Cancer Institute, Research Department, Villejuif; †Service Biostatistique et Épidémiologie, Gustave Roussy, Villejuif; ‡Imaging Department, Institut Bergonié, Bordeaux; §Department of Radiology, Assistance Publique-Hôpitaux de Paris, Hôpital Beaujon, Clichy, and Université Paris Diderot, Sorbonne Paris Cité; ∥Department of Radiology, Centre François Baclesse, Caen; ¶Department of Radiology, Centre Léon Bérard, Lyon; #Imaging Department, Centre Oscar Lambret, Lille; **Radiodiagnostics Department, Centre Claudius Regaud, Toulouse; ††Imaging Department, Institut Paoli Calmettes, Marseille; ‡‡Radiodiagnostics Department, Centre R Gauducheau, Institut de Cancérologie de l’Ouest Nantes; §§Department of Abdominal and Digestive Imaging, Hôpital Saint-Éloi, Montpellier; ∥∥Radiology Department, Centre Hospitalier Universitaire La Pitié-Salpêtrière, Paris; ¶¶Radiodiagnostics Department, Centre Jean Perrin, Clermont-Ferrand; ##Radiology Department, Centre Hospitalier Universitaire Bicêtre, Le Kremlin-Bicêtre; ***Radiodiagnostics and Imaging Department, Institut Jean Godinot, Reims; †††Ultrasonography Department, Hôpital Ambroise Paré, Boulogne-Billancourt; ‡‡‡Radiology Department, Centre Hospitalier Universitaire Hôtel-Dieu, Lyon; §§§Radiology Department, Centre Hospitalier Universitaire Henri Mondor, Créteil; ∥∥∥Imaging Department, Centre Georges-François Leclerc, Dijon Cedex; and ¶¶¶Radiology Department, Hôpital Cochin, Paris, France
| | - Richard Aziza
- From the *Integrated Research Cancer Institute, Research Department, Villejuif; †Service Biostatistique et Épidémiologie, Gustave Roussy, Villejuif; ‡Imaging Department, Institut Bergonié, Bordeaux; §Department of Radiology, Assistance Publique-Hôpitaux de Paris, Hôpital Beaujon, Clichy, and Université Paris Diderot, Sorbonne Paris Cité; ∥Department of Radiology, Centre François Baclesse, Caen; ¶Department of Radiology, Centre Léon Bérard, Lyon; #Imaging Department, Centre Oscar Lambret, Lille; **Radiodiagnostics Department, Centre Claudius Regaud, Toulouse; ††Imaging Department, Institut Paoli Calmettes, Marseille; ‡‡Radiodiagnostics Department, Centre R Gauducheau, Institut de Cancérologie de l’Ouest Nantes; §§Department of Abdominal and Digestive Imaging, Hôpital Saint-Éloi, Montpellier; ∥∥Radiology Department, Centre Hospitalier Universitaire La Pitié-Salpêtrière, Paris; ¶¶Radiodiagnostics Department, Centre Jean Perrin, Clermont-Ferrand; ##Radiology Department, Centre Hospitalier Universitaire Bicêtre, Le Kremlin-Bicêtre; ***Radiodiagnostics and Imaging Department, Institut Jean Godinot, Reims; †††Ultrasonography Department, Hôpital Ambroise Paré, Boulogne-Billancourt; ‡‡‡Radiology Department, Centre Hospitalier Universitaire Hôtel-Dieu, Lyon; §§§Radiology Department, Centre Hospitalier Universitaire Henri Mondor, Créteil; ∥∥∥Imaging Department, Centre Georges-François Leclerc, Dijon Cedex; and ¶¶¶Radiology Department, Hôpital Cochin, Paris, France
| | - Antony Sarran
- From the *Integrated Research Cancer Institute, Research Department, Villejuif; †Service Biostatistique et Épidémiologie, Gustave Roussy, Villejuif; ‡Imaging Department, Institut Bergonié, Bordeaux; §Department of Radiology, Assistance Publique-Hôpitaux de Paris, Hôpital Beaujon, Clichy, and Université Paris Diderot, Sorbonne Paris Cité; ∥Department of Radiology, Centre François Baclesse, Caen; ¶Department of Radiology, Centre Léon Bérard, Lyon; #Imaging Department, Centre Oscar Lambret, Lille; **Radiodiagnostics Department, Centre Claudius Regaud, Toulouse; ††Imaging Department, Institut Paoli Calmettes, Marseille; ‡‡Radiodiagnostics Department, Centre R Gauducheau, Institut de Cancérologie de l’Ouest Nantes; §§Department of Abdominal and Digestive Imaging, Hôpital Saint-Éloi, Montpellier; ∥∥Radiology Department, Centre Hospitalier Universitaire La Pitié-Salpêtrière, Paris; ¶¶Radiodiagnostics Department, Centre Jean Perrin, Clermont-Ferrand; ##Radiology Department, Centre Hospitalier Universitaire Bicêtre, Le Kremlin-Bicêtre; ***Radiodiagnostics and Imaging Department, Institut Jean Godinot, Reims; †††Ultrasonography Department, Hôpital Ambroise Paré, Boulogne-Billancourt; ‡‡‡Radiology Department, Centre Hospitalier Universitaire Hôtel-Dieu, Lyon; §§§Radiology Department, Centre Hospitalier Universitaire Henri Mondor, Créteil; ∥∥∥Imaging Department, Centre Georges-François Leclerc, Dijon Cedex; and ¶¶¶Radiology Department, Hôpital Cochin, Paris, France
| | - Catherine Labbe-Devilliers
- From the *Integrated Research Cancer Institute, Research Department, Villejuif; †Service Biostatistique et Épidémiologie, Gustave Roussy, Villejuif; ‡Imaging Department, Institut Bergonié, Bordeaux; §Department of Radiology, Assistance Publique-Hôpitaux de Paris, Hôpital Beaujon, Clichy, and Université Paris Diderot, Sorbonne Paris Cité; ∥Department of Radiology, Centre François Baclesse, Caen; ¶Department of Radiology, Centre Léon Bérard, Lyon; #Imaging Department, Centre Oscar Lambret, Lille; **Radiodiagnostics Department, Centre Claudius Regaud, Toulouse; ††Imaging Department, Institut Paoli Calmettes, Marseille; ‡‡Radiodiagnostics Department, Centre R Gauducheau, Institut de Cancérologie de l’Ouest Nantes; §§Department of Abdominal and Digestive Imaging, Hôpital Saint-Éloi, Montpellier; ∥∥Radiology Department, Centre Hospitalier Universitaire La Pitié-Salpêtrière, Paris; ¶¶Radiodiagnostics Department, Centre Jean Perrin, Clermont-Ferrand; ##Radiology Department, Centre Hospitalier Universitaire Bicêtre, Le Kremlin-Bicêtre; ***Radiodiagnostics and Imaging Department, Institut Jean Godinot, Reims; †††Ultrasonography Department, Hôpital Ambroise Paré, Boulogne-Billancourt; ‡‡‡Radiology Department, Centre Hospitalier Universitaire Hôtel-Dieu, Lyon; §§§Radiology Department, Centre Hospitalier Universitaire Henri Mondor, Créteil; ∥∥∥Imaging Department, Centre Georges-François Leclerc, Dijon Cedex; and ¶¶¶Radiology Department, Hôpital Cochin, Paris, France
| | - Benoit Gallix
- From the *Integrated Research Cancer Institute, Research Department, Villejuif; †Service Biostatistique et Épidémiologie, Gustave Roussy, Villejuif; ‡Imaging Department, Institut Bergonié, Bordeaux; §Department of Radiology, Assistance Publique-Hôpitaux de Paris, Hôpital Beaujon, Clichy, and Université Paris Diderot, Sorbonne Paris Cité; ∥Department of Radiology, Centre François Baclesse, Caen; ¶Department of Radiology, Centre Léon Bérard, Lyon; #Imaging Department, Centre Oscar Lambret, Lille; **Radiodiagnostics Department, Centre Claudius Regaud, Toulouse; ††Imaging Department, Institut Paoli Calmettes, Marseille; ‡‡Radiodiagnostics Department, Centre R Gauducheau, Institut de Cancérologie de l’Ouest Nantes; §§Department of Abdominal and Digestive Imaging, Hôpital Saint-Éloi, Montpellier; ∥∥Radiology Department, Centre Hospitalier Universitaire La Pitié-Salpêtrière, Paris; ¶¶Radiodiagnostics Department, Centre Jean Perrin, Clermont-Ferrand; ##Radiology Department, Centre Hospitalier Universitaire Bicêtre, Le Kremlin-Bicêtre; ***Radiodiagnostics and Imaging Department, Institut Jean Godinot, Reims; †††Ultrasonography Department, Hôpital Ambroise Paré, Boulogne-Billancourt; ‡‡‡Radiology Department, Centre Hospitalier Universitaire Hôtel-Dieu, Lyon; §§§Radiology Department, Centre Hospitalier Universitaire Henri Mondor, Créteil; ∥∥∥Imaging Department, Centre Georges-François Leclerc, Dijon Cedex; and ¶¶¶Radiology Department, Hôpital Cochin, Paris, France
| | - Olivier Lucidarme
- From the *Integrated Research Cancer Institute, Research Department, Villejuif; †Service Biostatistique et Épidémiologie, Gustave Roussy, Villejuif; ‡Imaging Department, Institut Bergonié, Bordeaux; §Department of Radiology, Assistance Publique-Hôpitaux de Paris, Hôpital Beaujon, Clichy, and Université Paris Diderot, Sorbonne Paris Cité; ∥Department of Radiology, Centre François Baclesse, Caen; ¶Department of Radiology, Centre Léon Bérard, Lyon; #Imaging Department, Centre Oscar Lambret, Lille; **Radiodiagnostics Department, Centre Claudius Regaud, Toulouse; ††Imaging Department, Institut Paoli Calmettes, Marseille; ‡‡Radiodiagnostics Department, Centre R Gauducheau, Institut de Cancérologie de l’Ouest Nantes; §§Department of Abdominal and Digestive Imaging, Hôpital Saint-Éloi, Montpellier; ∥∥Radiology Department, Centre Hospitalier Universitaire La Pitié-Salpêtrière, Paris; ¶¶Radiodiagnostics Department, Centre Jean Perrin, Clermont-Ferrand; ##Radiology Department, Centre Hospitalier Universitaire Bicêtre, Le Kremlin-Bicêtre; ***Radiodiagnostics and Imaging Department, Institut Jean Godinot, Reims; †††Ultrasonography Department, Hôpital Ambroise Paré, Boulogne-Billancourt; ‡‡‡Radiology Department, Centre Hospitalier Universitaire Hôtel-Dieu, Lyon; §§§Radiology Department, Centre Hospitalier Universitaire Henri Mondor, Créteil; ∥∥∥Imaging Department, Centre Georges-François Leclerc, Dijon Cedex; and ¶¶¶Radiology Department, Hôpital Cochin, Paris, France
| | - Yvette Ptak
- From the *Integrated Research Cancer Institute, Research Department, Villejuif; †Service Biostatistique et Épidémiologie, Gustave Roussy, Villejuif; ‡Imaging Department, Institut Bergonié, Bordeaux; §Department of Radiology, Assistance Publique-Hôpitaux de Paris, Hôpital Beaujon, Clichy, and Université Paris Diderot, Sorbonne Paris Cité; ∥Department of Radiology, Centre François Baclesse, Caen; ¶Department of Radiology, Centre Léon Bérard, Lyon; #Imaging Department, Centre Oscar Lambret, Lille; **Radiodiagnostics Department, Centre Claudius Regaud, Toulouse; ††Imaging Department, Institut Paoli Calmettes, Marseille; ‡‡Radiodiagnostics Department, Centre R Gauducheau, Institut de Cancérologie de l’Ouest Nantes; §§Department of Abdominal and Digestive Imaging, Hôpital Saint-Éloi, Montpellier; ∥∥Radiology Department, Centre Hospitalier Universitaire La Pitié-Salpêtrière, Paris; ¶¶Radiodiagnostics Department, Centre Jean Perrin, Clermont-Ferrand; ##Radiology Department, Centre Hospitalier Universitaire Bicêtre, Le Kremlin-Bicêtre; ***Radiodiagnostics and Imaging Department, Institut Jean Godinot, Reims; †††Ultrasonography Department, Hôpital Ambroise Paré, Boulogne-Billancourt; ‡‡‡Radiology Department, Centre Hospitalier Universitaire Hôtel-Dieu, Lyon; §§§Radiology Department, Centre Hospitalier Universitaire Henri Mondor, Créteil; ∥∥∥Imaging Department, Centre Georges-François Leclerc, Dijon Cedex; and ¶¶¶Radiology Department, Hôpital Cochin, Paris, France
| | - Laurence Rocher
- From the *Integrated Research Cancer Institute, Research Department, Villejuif; †Service Biostatistique et Épidémiologie, Gustave Roussy, Villejuif; ‡Imaging Department, Institut Bergonié, Bordeaux; §Department of Radiology, Assistance Publique-Hôpitaux de Paris, Hôpital Beaujon, Clichy, and Université Paris Diderot, Sorbonne Paris Cité; ∥Department of Radiology, Centre François Baclesse, Caen; ¶Department of Radiology, Centre Léon Bérard, Lyon; #Imaging Department, Centre Oscar Lambret, Lille; **Radiodiagnostics Department, Centre Claudius Regaud, Toulouse; ††Imaging Department, Institut Paoli Calmettes, Marseille; ‡‡Radiodiagnostics Department, Centre R Gauducheau, Institut de Cancérologie de l’Ouest Nantes; §§Department of Abdominal and Digestive Imaging, Hôpital Saint-Éloi, Montpellier; ∥∥Radiology Department, Centre Hospitalier Universitaire La Pitié-Salpêtrière, Paris; ¶¶Radiodiagnostics Department, Centre Jean Perrin, Clermont-Ferrand; ##Radiology Department, Centre Hospitalier Universitaire Bicêtre, Le Kremlin-Bicêtre; ***Radiodiagnostics and Imaging Department, Institut Jean Godinot, Reims; †††Ultrasonography Department, Hôpital Ambroise Paré, Boulogne-Billancourt; ‡‡‡Radiology Department, Centre Hospitalier Universitaire Hôtel-Dieu, Lyon; §§§Radiology Department, Centre Hospitalier Universitaire Henri Mondor, Créteil; ∥∥∥Imaging Department, Centre Georges-François Leclerc, Dijon Cedex; and ¶¶¶Radiology Department, Hôpital Cochin, Paris, France
| | - Louis-Michel Caquot
- From the *Integrated Research Cancer Institute, Research Department, Villejuif; †Service Biostatistique et Épidémiologie, Gustave Roussy, Villejuif; ‡Imaging Department, Institut Bergonié, Bordeaux; §Department of Radiology, Assistance Publique-Hôpitaux de Paris, Hôpital Beaujon, Clichy, and Université Paris Diderot, Sorbonne Paris Cité; ∥Department of Radiology, Centre François Baclesse, Caen; ¶Department of Radiology, Centre Léon Bérard, Lyon; #Imaging Department, Centre Oscar Lambret, Lille; **Radiodiagnostics Department, Centre Claudius Regaud, Toulouse; ††Imaging Department, Institut Paoli Calmettes, Marseille; ‡‡Radiodiagnostics Department, Centre R Gauducheau, Institut de Cancérologie de l’Ouest Nantes; §§Department of Abdominal and Digestive Imaging, Hôpital Saint-Éloi, Montpellier; ∥∥Radiology Department, Centre Hospitalier Universitaire La Pitié-Salpêtrière, Paris; ¶¶Radiodiagnostics Department, Centre Jean Perrin, Clermont-Ferrand; ##Radiology Department, Centre Hospitalier Universitaire Bicêtre, Le Kremlin-Bicêtre; ***Radiodiagnostics and Imaging Department, Institut Jean Godinot, Reims; †††Ultrasonography Department, Hôpital Ambroise Paré, Boulogne-Billancourt; ‡‡‡Radiology Department, Centre Hospitalier Universitaire Hôtel-Dieu, Lyon; §§§Radiology Department, Centre Hospitalier Universitaire Henri Mondor, Créteil; ∥∥∥Imaging Department, Centre Georges-François Leclerc, Dijon Cedex; and ¶¶¶Radiology Department, Hôpital Cochin, Paris, France
| | - Sophie Chagnon
- From the *Integrated Research Cancer Institute, Research Department, Villejuif; †Service Biostatistique et Épidémiologie, Gustave Roussy, Villejuif; ‡Imaging Department, Institut Bergonié, Bordeaux; §Department of Radiology, Assistance Publique-Hôpitaux de Paris, Hôpital Beaujon, Clichy, and Université Paris Diderot, Sorbonne Paris Cité; ∥Department of Radiology, Centre François Baclesse, Caen; ¶Department of Radiology, Centre Léon Bérard, Lyon; #Imaging Department, Centre Oscar Lambret, Lille; **Radiodiagnostics Department, Centre Claudius Regaud, Toulouse; ††Imaging Department, Institut Paoli Calmettes, Marseille; ‡‡Radiodiagnostics Department, Centre R Gauducheau, Institut de Cancérologie de l’Ouest Nantes; §§Department of Abdominal and Digestive Imaging, Hôpital Saint-Éloi, Montpellier; ∥∥Radiology Department, Centre Hospitalier Universitaire La Pitié-Salpêtrière, Paris; ¶¶Radiodiagnostics Department, Centre Jean Perrin, Clermont-Ferrand; ##Radiology Department, Centre Hospitalier Universitaire Bicêtre, Le Kremlin-Bicêtre; ***Radiodiagnostics and Imaging Department, Institut Jean Godinot, Reims; †††Ultrasonography Department, Hôpital Ambroise Paré, Boulogne-Billancourt; ‡‡‡Radiology Department, Centre Hospitalier Universitaire Hôtel-Dieu, Lyon; §§§Radiology Department, Centre Hospitalier Universitaire Henri Mondor, Créteil; ∥∥∥Imaging Department, Centre Georges-François Leclerc, Dijon Cedex; and ¶¶¶Radiology Department, Hôpital Cochin, Paris, France
| | - Denis Marion
- From the *Integrated Research Cancer Institute, Research Department, Villejuif; †Service Biostatistique et Épidémiologie, Gustave Roussy, Villejuif; ‡Imaging Department, Institut Bergonié, Bordeaux; §Department of Radiology, Assistance Publique-Hôpitaux de Paris, Hôpital Beaujon, Clichy, and Université Paris Diderot, Sorbonne Paris Cité; ∥Department of Radiology, Centre François Baclesse, Caen; ¶Department of Radiology, Centre Léon Bérard, Lyon; #Imaging Department, Centre Oscar Lambret, Lille; **Radiodiagnostics Department, Centre Claudius Regaud, Toulouse; ††Imaging Department, Institut Paoli Calmettes, Marseille; ‡‡Radiodiagnostics Department, Centre R Gauducheau, Institut de Cancérologie de l’Ouest Nantes; §§Department of Abdominal and Digestive Imaging, Hôpital Saint-Éloi, Montpellier; ∥∥Radiology Department, Centre Hospitalier Universitaire La Pitié-Salpêtrière, Paris; ¶¶Radiodiagnostics Department, Centre Jean Perrin, Clermont-Ferrand; ##Radiology Department, Centre Hospitalier Universitaire Bicêtre, Le Kremlin-Bicêtre; ***Radiodiagnostics and Imaging Department, Institut Jean Godinot, Reims; †††Ultrasonography Department, Hôpital Ambroise Paré, Boulogne-Billancourt; ‡‡‡Radiology Department, Centre Hospitalier Universitaire Hôtel-Dieu, Lyon; §§§Radiology Department, Centre Hospitalier Universitaire Henri Mondor, Créteil; ∥∥∥Imaging Department, Centre Georges-François Leclerc, Dijon Cedex; and ¶¶¶Radiology Department, Hôpital Cochin, Paris, France
| | - Alain Luciani
- From the *Integrated Research Cancer Institute, Research Department, Villejuif; †Service Biostatistique et Épidémiologie, Gustave Roussy, Villejuif; ‡Imaging Department, Institut Bergonié, Bordeaux; §Department of Radiology, Assistance Publique-Hôpitaux de Paris, Hôpital Beaujon, Clichy, and Université Paris Diderot, Sorbonne Paris Cité; ∥Department of Radiology, Centre François Baclesse, Caen; ¶Department of Radiology, Centre Léon Bérard, Lyon; #Imaging Department, Centre Oscar Lambret, Lille; **Radiodiagnostics Department, Centre Claudius Regaud, Toulouse; ††Imaging Department, Institut Paoli Calmettes, Marseille; ‡‡Radiodiagnostics Department, Centre R Gauducheau, Institut de Cancérologie de l’Ouest Nantes; §§Department of Abdominal and Digestive Imaging, Hôpital Saint-Éloi, Montpellier; ∥∥Radiology Department, Centre Hospitalier Universitaire La Pitié-Salpêtrière, Paris; ¶¶Radiodiagnostics Department, Centre Jean Perrin, Clermont-Ferrand; ##Radiology Department, Centre Hospitalier Universitaire Bicêtre, Le Kremlin-Bicêtre; ***Radiodiagnostics and Imaging Department, Institut Jean Godinot, Reims; †††Ultrasonography Department, Hôpital Ambroise Paré, Boulogne-Billancourt; ‡‡‡Radiology Department, Centre Hospitalier Universitaire Hôtel-Dieu, Lyon; §§§Radiology Department, Centre Hospitalier Universitaire Henri Mondor, Créteil; ∥∥∥Imaging Department, Centre Georges-François Leclerc, Dijon Cedex; and ¶¶¶Radiology Department, Hôpital Cochin, Paris, France
| | - Sylvaine Feutray
- From the *Integrated Research Cancer Institute, Research Department, Villejuif; †Service Biostatistique et Épidémiologie, Gustave Roussy, Villejuif; ‡Imaging Department, Institut Bergonié, Bordeaux; §Department of Radiology, Assistance Publique-Hôpitaux de Paris, Hôpital Beaujon, Clichy, and Université Paris Diderot, Sorbonne Paris Cité; ∥Department of Radiology, Centre François Baclesse, Caen; ¶Department of Radiology, Centre Léon Bérard, Lyon; #Imaging Department, Centre Oscar Lambret, Lille; **Radiodiagnostics Department, Centre Claudius Regaud, Toulouse; ††Imaging Department, Institut Paoli Calmettes, Marseille; ‡‡Radiodiagnostics Department, Centre R Gauducheau, Institut de Cancérologie de l’Ouest Nantes; §§Department of Abdominal and Digestive Imaging, Hôpital Saint-Éloi, Montpellier; ∥∥Radiology Department, Centre Hospitalier Universitaire La Pitié-Salpêtrière, Paris; ¶¶Radiodiagnostics Department, Centre Jean Perrin, Clermont-Ferrand; ##Radiology Department, Centre Hospitalier Universitaire Bicêtre, Le Kremlin-Bicêtre; ***Radiodiagnostics and Imaging Department, Institut Jean Godinot, Reims; †††Ultrasonography Department, Hôpital Ambroise Paré, Boulogne-Billancourt; ‡‡‡Radiology Department, Centre Hospitalier Universitaire Hôtel-Dieu, Lyon; §§§Radiology Department, Centre Hospitalier Universitaire Henri Mondor, Créteil; ∥∥∥Imaging Department, Centre Georges-François Leclerc, Dijon Cedex; and ¶¶¶Radiology Department, Hôpital Cochin, Paris, France
| | - Joëlle Uzan-Augui
- From the *Integrated Research Cancer Institute, Research Department, Villejuif; †Service Biostatistique et Épidémiologie, Gustave Roussy, Villejuif; ‡Imaging Department, Institut Bergonié, Bordeaux; §Department of Radiology, Assistance Publique-Hôpitaux de Paris, Hôpital Beaujon, Clichy, and Université Paris Diderot, Sorbonne Paris Cité; ∥Department of Radiology, Centre François Baclesse, Caen; ¶Department of Radiology, Centre Léon Bérard, Lyon; #Imaging Department, Centre Oscar Lambret, Lille; **Radiodiagnostics Department, Centre Claudius Regaud, Toulouse; ††Imaging Department, Institut Paoli Calmettes, Marseille; ‡‡Radiodiagnostics Department, Centre R Gauducheau, Institut de Cancérologie de l’Ouest Nantes; §§Department of Abdominal and Digestive Imaging, Hôpital Saint-Éloi, Montpellier; ∥∥Radiology Department, Centre Hospitalier Universitaire La Pitié-Salpêtrière, Paris; ¶¶Radiodiagnostics Department, Centre Jean Perrin, Clermont-Ferrand; ##Radiology Department, Centre Hospitalier Universitaire Bicêtre, Le Kremlin-Bicêtre; ***Radiodiagnostics and Imaging Department, Institut Jean Godinot, Reims; †††Ultrasonography Department, Hôpital Ambroise Paré, Boulogne-Billancourt; ‡‡‡Radiology Department, Centre Hospitalier Universitaire Hôtel-Dieu, Lyon; §§§Radiology Department, Centre Hospitalier Universitaire Henri Mondor, Créteil; ∥∥∥Imaging Department, Centre Georges-François Leclerc, Dijon Cedex; and ¶¶¶Radiology Department, Hôpital Cochin, Paris, France
| | - Benedicte Coiffier
- From the *Integrated Research Cancer Institute, Research Department, Villejuif; †Service Biostatistique et Épidémiologie, Gustave Roussy, Villejuif; ‡Imaging Department, Institut Bergonié, Bordeaux; §Department of Radiology, Assistance Publique-Hôpitaux de Paris, Hôpital Beaujon, Clichy, and Université Paris Diderot, Sorbonne Paris Cité; ∥Department of Radiology, Centre François Baclesse, Caen; ¶Department of Radiology, Centre Léon Bérard, Lyon; #Imaging Department, Centre Oscar Lambret, Lille; **Radiodiagnostics Department, Centre Claudius Regaud, Toulouse; ††Imaging Department, Institut Paoli Calmettes, Marseille; ‡‡Radiodiagnostics Department, Centre R Gauducheau, Institut de Cancérologie de l’Ouest Nantes; §§Department of Abdominal and Digestive Imaging, Hôpital Saint-Éloi, Montpellier; ∥∥Radiology Department, Centre Hospitalier Universitaire La Pitié-Salpêtrière, Paris; ¶¶Radiodiagnostics Department, Centre Jean Perrin, Clermont-Ferrand; ##Radiology Department, Centre Hospitalier Universitaire Bicêtre, Le Kremlin-Bicêtre; ***Radiodiagnostics and Imaging Department, Institut Jean Godinot, Reims; †††Ultrasonography Department, Hôpital Ambroise Paré, Boulogne-Billancourt; ‡‡‡Radiology Department, Centre Hospitalier Universitaire Hôtel-Dieu, Lyon; §§§Radiology Department, Centre Hospitalier Universitaire Henri Mondor, Créteil; ∥∥∥Imaging Department, Centre Georges-François Leclerc, Dijon Cedex; and ¶¶¶Radiology Department, Hôpital Cochin, Paris, France
| | - Baya Benastou
- From the *Integrated Research Cancer Institute, Research Department, Villejuif; †Service Biostatistique et Épidémiologie, Gustave Roussy, Villejuif; ‡Imaging Department, Institut Bergonié, Bordeaux; §Department of Radiology, Assistance Publique-Hôpitaux de Paris, Hôpital Beaujon, Clichy, and Université Paris Diderot, Sorbonne Paris Cité; ∥Department of Radiology, Centre François Baclesse, Caen; ¶Department of Radiology, Centre Léon Bérard, Lyon; #Imaging Department, Centre Oscar Lambret, Lille; **Radiodiagnostics Department, Centre Claudius Regaud, Toulouse; ††Imaging Department, Institut Paoli Calmettes, Marseille; ‡‡Radiodiagnostics Department, Centre R Gauducheau, Institut de Cancérologie de l’Ouest Nantes; §§Department of Abdominal and Digestive Imaging, Hôpital Saint-Éloi, Montpellier; ∥∥Radiology Department, Centre Hospitalier Universitaire La Pitié-Salpêtrière, Paris; ¶¶Radiodiagnostics Department, Centre Jean Perrin, Clermont-Ferrand; ##Radiology Department, Centre Hospitalier Universitaire Bicêtre, Le Kremlin-Bicêtre; ***Radiodiagnostics and Imaging Department, Institut Jean Godinot, Reims; †††Ultrasonography Department, Hôpital Ambroise Paré, Boulogne-Billancourt; ‡‡‡Radiology Department, Centre Hospitalier Universitaire Hôtel-Dieu, Lyon; §§§Radiology Department, Centre Hospitalier Universitaire Henri Mondor, Créteil; ∥∥∥Imaging Department, Centre Georges-François Leclerc, Dijon Cedex; and ¶¶¶Radiology Department, Hôpital Cochin, Paris, France
| | - Serge Koscielny
- From the *Integrated Research Cancer Institute, Research Department, Villejuif; †Service Biostatistique et Épidémiologie, Gustave Roussy, Villejuif; ‡Imaging Department, Institut Bergonié, Bordeaux; §Department of Radiology, Assistance Publique-Hôpitaux de Paris, Hôpital Beaujon, Clichy, and Université Paris Diderot, Sorbonne Paris Cité; ∥Department of Radiology, Centre François Baclesse, Caen; ¶Department of Radiology, Centre Léon Bérard, Lyon; #Imaging Department, Centre Oscar Lambret, Lille; **Radiodiagnostics Department, Centre Claudius Regaud, Toulouse; ††Imaging Department, Institut Paoli Calmettes, Marseille; ‡‡Radiodiagnostics Department, Centre R Gauducheau, Institut de Cancérologie de l’Ouest Nantes; §§Department of Abdominal and Digestive Imaging, Hôpital Saint-Éloi, Montpellier; ∥∥Radiology Department, Centre Hospitalier Universitaire La Pitié-Salpêtrière, Paris; ¶¶Radiodiagnostics Department, Centre Jean Perrin, Clermont-Ferrand; ##Radiology Department, Centre Hospitalier Universitaire Bicêtre, Le Kremlin-Bicêtre; ***Radiodiagnostics and Imaging Department, Institut Jean Godinot, Reims; †††Ultrasonography Department, Hôpital Ambroise Paré, Boulogne-Billancourt; ‡‡‡Radiology Department, Centre Hospitalier Universitaire Hôtel-Dieu, Lyon; §§§Radiology Department, Centre Hospitalier Universitaire Henri Mondor, Créteil; ∥∥∥Imaging Department, Centre Georges-François Leclerc, Dijon Cedex; and ¶¶¶Radiology Department, Hôpital Cochin, Paris, France
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Kickingereder P, Wiestler B, Graf M, Heiland S, Schlemmer HP, Wick W, Wick A, Bendszus M, Radbruch A. Evaluation of dynamic contrast-enhanced MRI derived microvascular permeability in recurrent glioblastoma treated with bevacizumab. J Neurooncol 2014; 121:373-80. [PMID: 25359396 DOI: 10.1007/s11060-014-1644-6] [Citation(s) in RCA: 38] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2014] [Accepted: 10/18/2014] [Indexed: 01/18/2023]
Abstract
Bevacizumab, an antibody to vascular endothelial growth factor, is commonly used in the setting of recurrent glioblastoma (rGB). The aim of the present study was to evaluate whether dynamic-contrast-enhanced MRI (DCE-MRI) derived microvascular permeability is related to bevacizumab treatment outcome in rGB. Twenty-two patients with rGB underwent DCE-MRI at a median of 2.6 weeks prior initializing bevacizumab therapy. Follow-up MRI-scans (DCE-MRI available for 19/22 patients) were obtained after a median of 9.9 weeks. The volume transfer constant (K(trans))--an estimate related to microvascular permeability--at baseline and voxel-wise-reduction (VWR) in K(trans) at first follow-up were measured from the entire contrast-enhancing tumor (CET) and correlated with progression-free and overall survival (PFS, OS) using uni- and multivariate cox-regression (significance-level p < 0.05). Baseline K(trans) ranged from 0.050 to 0.205 min(-1) (median, 0.109 min(-1)). The VWR in K(trans) ranged from 19.9 to 97.2 % (median, 89.4 %). Patients with lower baseline K(trans) and higher VWR in K(trans) showed significantly longer PFS and OS. Given the strong correlation of VWR in K(trans) and CET-volume changes (Spearman's ρ = -0.73, p < 0.01) both variables were included in a multivariate model. Thereby, neither VWR in K(trans) nor CET-volume changes retained independent significance for PFS or OS. Pre-treatment K(trans) stratifies PFS and OS in patients with bevacizumab-treated rGB. Although early pharmacodynamics changes in K(trans) were not assessed, the VWR in K(trans) at first follow-up had no additional benefit over assessment of CET-volume changes. Further prospective trials are needed to confirm these findings and to elucidate the potential role of pre-treatment K(trans) as a predictive and/or prognostic biomarker.
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Affiliation(s)
- Philipp Kickingereder
- Department of Neuroradiology, University of Heidelberg Medical Center, Heidelberg, Germany,
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Larsson C, Kleppestø M, Grothe I, Vardal J, Bjørnerud A. T1in high-grade glioma and the influence of different measurement strategies on parameter estimations in DCE-MRI. J Magn Reson Imaging 2014; 42:97-104. [DOI: 10.1002/jmri.24772] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2014] [Accepted: 09/16/2014] [Indexed: 11/07/2022] Open
Affiliation(s)
| | - Magne Kleppestø
- The Intervention Centre; Oslo University Hospital; Oslo Norway
- Faculty of Medicine; University of Oslo; Oslo Norway
| | - Inge Grothe
- Department of Psychology; University of Oslo; Oslo Norway
| | - Jonas Vardal
- The Intervention Centre; Oslo University Hospital; Oslo Norway
- Faculty of Medicine; University of Oslo; Oslo Norway
| | - Atle Bjørnerud
- The Intervention Centre; Oslo University Hospital; Oslo Norway
- Department of Physics; University of Oslo; Oslo Norway
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Colliez F, Neveu MA, Magat J, Cao Pham TT, Gallez B, Jordan BF. Qualification of a Noninvasive Magnetic Resonance Imaging Biomarker to Assess Tumor Oxygenation. Clin Cancer Res 2014; 20:5403-11. [DOI: 10.1158/1078-0432.ccr-13-3434] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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Anti-angiogenic therapy for cancer: current progress, unresolved questions and future directions. Angiogenesis 2014; 17:471-94. [PMID: 24482243 PMCID: PMC4061466 DOI: 10.1007/s10456-014-9420-y] [Citation(s) in RCA: 507] [Impact Index Per Article: 50.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2013] [Accepted: 01/15/2014] [Indexed: 12/17/2022]
Abstract
Tumours require a vascular supply to grow and can achieve this via the expression of pro-angiogenic growth factors, including members of the vascular endothelial growth factor (VEGF) family of ligands. Since one or more of the VEGF ligand family is overexpressed in most solid cancers, there was great optimism that inhibition of the VEGF pathway would represent an effective anti-angiogenic therapy for most tumour types. Encouragingly, VEGF pathway targeted drugs such as bevacizumab, sunitinib and aflibercept have shown activity in certain settings. However, inhibition of VEGF signalling is not effective in all cancers, prompting the need to further understand how the vasculature can be effectively targeted in tumours. Here we present a succinct review of the progress with VEGF-targeted therapy and the unresolved questions that exist in the field: including its use in different disease stages (metastatic, adjuvant, neoadjuvant), interactions with chemotherapy, duration and scheduling of therapy, potential predictive biomarkers and proposed mechanisms of resistance, including paradoxical effects such as enhanced tumour aggressiveness. In terms of future directions, we discuss the need to delineate further the complexities of tumour vascularisation if we are to develop more effective and personalised anti-angiogenic therapies.
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León L, García-Figueiras R, García-Figueras R, Suárez C, Arjonilla A, Puente J, Vargas B, Méndez Vidal MJ, Sebastiá C. Recommendations for the clinical and radiological evaluation of response to treatment in metastatic renal cell cancer. Target Oncol 2013; 9:9-24. [PMID: 24338498 DOI: 10.1007/s11523-013-0304-7] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2013] [Accepted: 11/28/2013] [Indexed: 12/21/2022]
Abstract
The evaluation of response to treatment is a critical step for determining the effectiveness of oncology drugs. Targeted therapies such as tyrosine kinase inhibitors and mammalian target of rapamycin inhibitors are active drugs in patients with metastatic renal cell carcinoma (mRCC). However, treatment with this type of drugs may not result in significant reductions in tumor size, so standard evaluation criteria based on tumor size, such as Response Evaluation Criteria in Solid Tumors (RECIST), may be inappropriate for evaluating response to treatment in patients with mRCC. In fact, targeted therapies apparently yield low response rates that do not reflect increased disease control they may cause and, consequently, the benefit in terms of time to progression. To improve the clinical and radiological evaluation of response to treatment in patients with mRCC treated with targeted drugs, a group of 32 experts in this field have reviewed different aspects related to this issue and have put together a series of recommendations with the intention of providing guidance to clinicians on this matter.
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Affiliation(s)
- Luís León
- Medical Oncology Department, Complejo Hospitalario Universitario de Santiago, A Coruña, Spain,
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Jensen RL, Mumert ML, Gillespie DL, Kinney AY, Schabel MC, Salzman KL. Preoperative dynamic contrast-enhanced MRI correlates with molecular markers of hypoxia and vascularity in specific areas of intratumoral microenvironment and is predictive of patient outcome. Neuro Oncol 2013; 16:280-91. [PMID: 24305704 DOI: 10.1093/neuonc/not148] [Citation(s) in RCA: 78] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022] Open
Abstract
BACKGROUND Measures of tumor vascularity and hypoxia have been correlated with glioma grade and outcome. Dynamic contrast-enhanced (DCE) MRI can noninvasively map tumor blood flow, vascularity, and permeability. In this prospective observational cohort pilot study, preoperative imaging was correlated with molecular markers of hypoxia, vascularity, proliferation, and progression-free and overall patient survival. METHODS Pharmacokinetic modeling methods were used to generate maps of tumor blood flow, extraction fraction, permeability-surface area product, transfer constant, washout rate, interstitial volume, blood volume, capillary transit time, and capillary heterogeneity from preoperative DCE-MRI data in human glioma patients. Tissue was obtained from areas of peritumoral edema, active tumor, hypoxic penumbra, and necrotic core and evaluated for vascularity, proliferation, and expression of hypoxia-regulated molecules. DCE-MRI parameter values were correlated with hypoxia-regulated protein expression at tissue sample sites. RESULTS Patient survival correlated with DCE parameters in 2 cases: capillary heterogeneity in active tumor and interstitial volume in areas of peritumoral edema. Statistically significant correlations were observed between several DCE parameters and tissue markers. In addition, MIB-1 index was predictive of overall survival (P = .044) and correlated with vascular endothelial growth factor expression in hypoxic penumbra (r = 0.7933, P = .0071) and peritumoral edema (r = 0.4546). Increased microvessel density correlated with worse patient outcome (P = .026). CONCLUSIONS Our findings suggest that DCE-MRI may facilitate noninvasive preoperative predictions of areas of tumor with increased hypoxia and proliferation. Both imaging and hypoxia biomarkers are predictive of patient outcome. This has the potential to allow unprecedented prognostic decisions and to guide therapies to specific tumor areas.
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Affiliation(s)
- Randy L Jensen
- Corresponding author: Randy L. Jensen, MD, PhD, Huntsman Cancer Institute and Departments of Neurosurgery, Radiation Oncology, Oncological Sciences, Clinical Neuroscience Center, University of Utah, 175 North Medical Drive, Salt Lake City, Utah 84132.
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Shaik-Dasthagirisaheb YB, Varvara G, Murmura G, Saggini A, Potalivo G, Caraffa A, Antinolfi P, Tete' S, Tripodi D, Conti F, Cianchetti E, Toniato E, Rosati M, Conti P, Speranza L, Pantalone A, Saggini R, Theoharides TC, Pandolfi F. Vascular endothelial growth factor (VEGF), mast cells and inflammation. Int J Immunopathol Pharmacol 2013; 26:327-35. [PMID: 23755748 DOI: 10.1177/039463201302600206] [Citation(s) in RCA: 84] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023] Open
Abstract
Vascular endothelial growth factor (VEGF) is one of the most important inducers of angiogenesis, therefore blocking angiogenesis has led to great promise in the treatment of various cancers and inflammatory diseases. VEGF, expressed in response to soluble mediators such as cytokines and growth factors, is important in the physiological development of blood vessels as well as development of vessels in tumors. In cancer patients VEGF levels are increased, and the expression of VEGF is associated with poor prognosis in diseases. VEGF is a mediator of angiogenesis and inflammation which are closely integrated processes in a number of physiological and pathological conditions including obesity, psoriasis, autoimmune diseases and tumor. Mast cells can be activated by anti-IgE to release potent mediators of inflammation and can also respond to bacterial or viral antigens, cytokines, growth factors and hormones, leading to differential release of distinct mediators without degranulation. Substance P strongly induces VEGF in mast cells, and IL-33 contributes to the stimulation and release of VEGF in human mast cells in a dose-dependent manner and acts synergistically in combination with Substance P. Here we report a strong link between VEGF and mast cells and we depict their role in inflammation and immunity.
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Changes in tumour vessel density upon treatment with anti-angiogenic agents: relationship with response and resistance to therapy. Br J Cancer 2013; 109:1230-42. [PMID: 23922108 PMCID: PMC3778288 DOI: 10.1038/bjc.2013.429] [Citation(s) in RCA: 38] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2013] [Revised: 06/30/2013] [Accepted: 07/04/2013] [Indexed: 12/20/2022] Open
Abstract
Background: We examine how changes in a surrogate marker of tumour vessel density correlate with response and resistance to anti-angiogenic therapy. Methods: In metastatic renal cancer patients treated with anti-angiogenic tyrosine kinase inhibitors, arterial phase contrast-enhanced computed tomography was used to simultaneously measure changes in: (a) tumour size, and (b) tumour enhancement (a surrogate marker of tumour vessel density) within individual lesions. Results: No correlation between baseline tumour enhancement and lesion shrinkage was observed, but a reduction in tumour enhancement on treatment was strongly correlated with reduction in lesion size (r=0.654, P<0.0001). However, close examination of individual metastases revealed different types of response: (1) good vascular response with significant tumour shrinkage, (2) good vascular response with stabilisation of disease, (3) poor vascular response with stabilisation of disease and (4) poor vascular response with progression. Moreover, contrasting responses between different lesions within the same patient were observed. We also assessed rebound vascularisation in tumours that acquired resistance to treatment. The amplitude of rebound vascularisation was greater in lesions that had a better initial response to therapy (P=0.008). Interpretation: Changes in a surrogate marker of tumour vessel density correlate with response and resistance to anti-angiogenic therapy. The data provide insight into the mechanisms that underlie response and resistance to this class of agent.
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