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Goldman J, Hagiwara A, Yao J, Raymond C, Ong C, Bakhti R, Kwon E, Farhat M, Torres C, Erickson LG, Curl BJ, Lee M, Pope WB, Salamon N, Nghiemphu PL, Ji M, Eldred BS, Liau LM, Lai A, Cloughesy TF, Chung C, Ellingson BM. Paradoxical Association Between Relative Cerebral Blood Volume Dynamics Following Chemoradiation and Increased Progression-Free Survival in Newly Diagnosed IDH Wild-Type MGMT Promoter Methylated Glioblastoma With Measurable Disease. Front Oncol 2022; 12:849993. [PMID: 35371980 PMCID: PMC8964348 DOI: 10.3389/fonc.2022.849993] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2022] [Accepted: 02/07/2022] [Indexed: 11/15/2022] Open
Abstract
Background and Purpose While relative cerebral blood volume (rCBV) may be diagnostic and prognostic for survival in glioblastoma (GBM), changes in rCBV during chemoradiation in the subset of newly diagnosed GBM with subtotal resection and the impact of MGMT promoter methylation status on survival have not been explored. This study aimed to investigate the association between rCBV response, MGMT methylation status, and progression-free (PFS) and overall survival (OS) in newly diagnosed GBM with measurable enhancing lesions. Methods 1,153 newly diagnosed IDH wild-type GBM patients were screened and 53 patients (4.6%) had measurable post-surgical tumor (>1mL). rCBV was measured before and after patients underwent chemoradiation. Patients with a decrease in rCBV >10% were considered rCBV Responders, while patients with an increase or a decrease in rCBV <10% were considered rCBV Non-Responders. The association between change in enhancing tumor volume, change in rCBV, MGMT promotor methylation status, and PFS or OS were explored. Results A decrease in tumor volume following chemoradiation trended towards longer OS (p=0.12; median OS=26.8 vs. 16.3 months). Paradoxically, rCBV Non-Responders had a significantly improved PFS compared to Responders (p=0.047; median PFS=9.6 vs. 7.2 months). MGMT methylated rCBV Non-Responders exhibited a significantly longer PFS compared to MGMT unmethylated rCBV Non-Responders (p<0.001; median PFS=0.5 vs. 7.1 months), and MGMT methylated rCBV Non-Responders trended towards longer PFS compared to methylated rCBV Responders (p=0.089; median PFS=20.5 vs. 13.8 months). Conclusions This preliminary report demonstrates that in newly diagnosed IDH wild-type GBM with measurable enhancing disease after surgery (5% of patients), an enigmatic non-response in rCBV was associated with longer PFS, particularly in MGMT methylated patients.
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Affiliation(s)
- Jodi Goldman
- UCLA Brain Tumor Imaging Laboratory, Center for Computer Vision and Imaging Biomarkers, Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States.,Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
| | - Akifumi Hagiwara
- UCLA Brain Tumor Imaging Laboratory, Center for Computer Vision and Imaging Biomarkers, Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States.,Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
| | - Jingwen Yao
- UCLA Brain Tumor Imaging Laboratory, Center for Computer Vision and Imaging Biomarkers, Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States.,Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
| | - Catalina Raymond
- UCLA Brain Tumor Imaging Laboratory, Center for Computer Vision and Imaging Biomarkers, Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States.,Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
| | - Christian Ong
- UCLA Brain Tumor Imaging Laboratory, Center for Computer Vision and Imaging Biomarkers, Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States.,Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
| | - Rojin Bakhti
- UCLA Brain Tumor Imaging Laboratory, Center for Computer Vision and Imaging Biomarkers, Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States.,Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
| | - Elizabeth Kwon
- UCLA Brain Tumor Imaging Laboratory, Center for Computer Vision and Imaging Biomarkers, Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States.,Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
| | - Maguy Farhat
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Carlo Torres
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Lily G Erickson
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Brandon J Curl
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Maggie Lee
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Whitney B Pope
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
| | - Noriko Salamon
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
| | - Phioanh L Nghiemphu
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
| | - Matthew Ji
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
| | - Blaine S Eldred
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
| | - Linda M Liau
- Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
| | - Albert Lai
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
| | - Timothy F Cloughesy
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
| | - Caroline Chung
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Benjamin M Ellingson
- UCLA Brain Tumor Imaging Laboratory, Center for Computer Vision and Imaging Biomarkers, Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States.,Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States.,Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
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2
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Differentiation between benign and malignant ovarian masses using multiparametric MRI. Diagn Interv Imaging 2020; 101:147-155. [DOI: 10.1016/j.diii.2020.01.006] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2019] [Revised: 01/05/2020] [Accepted: 01/06/2020] [Indexed: 12/16/2022]
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3
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Liu TT, Achrol AS, Mitchell LA, Rodriguez SA, Feroze A, Iv M, Kim C, Chaudhary N, Gevaert O, Stuart JM, Harsh GR, Chang SD, Rubin DL. Magnetic resonance perfusion image features uncover an angiogenic subgroup of glioblastoma patients with poor survival and better response to antiangiogenic treatment. Neuro Oncol 2018; 19:997-1007. [PMID: 28007759 DOI: 10.1093/neuonc/now270] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
Background In previous clinical trials, antiangiogenic therapies such as bevacizumab did not show efficacy in patients with newly diagnosed glioblastoma (GBM). This may be a result of the heterogeneity of GBM, which has a variety of imaging-based phenotypes and gene expression patterns. In this study, we sought to identify a phenotypic subtype of GBM patients who have distinct tumor-image features and molecular activities and who may benefit from antiangiogenic therapies. Methods Quantitative image features characterizing subregions of tumors and the whole tumor were extracted from preoperative and pretherapy perfusion magnetic resonance (MR) images of 117 GBM patients in 2 independent cohorts. Unsupervised consensus clustering was performed to identify robust clusters of GBM in each cohort. Cox survival and gene set enrichment analyses were conducted to characterize the clinical significance and molecular pathway activities of the clusters. The differential treatment efficacy of antiangiogenic therapy between the clusters was evaluated. Results A subgroup of patients with elevated perfusion features was identified and was significantly associated with poor patient survival after accounting for other clinical covariates (P values <.01; hazard ratios > 3) consistently found in both cohorts. Angiogenesis and hypoxia pathways were enriched in this subgroup of patients, suggesting the potential efficacy of antiangiogenic therapy. Patients of the angiogenic subgroups pooled from both cohorts, who had chemotherapy information available, had significantly longer survival when treated with antiangiogenic therapy (log-rank P=.022). Conclusions Our findings suggest that an angiogenic subtype of GBM patients may benefit from antiangiogenic therapy with improved overall survival.
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Affiliation(s)
- Tiffany T Liu
- Department of Neurosurgery, Stanford University, Stanford, California; Department of Radiology, Stanford University, Stanford, California; Stanford Center for Biomedical Informatics Research and Biomedical Informatics Training Program, Stanford, California; School of Medicine, Stanford University, Stanford, California; Department of Biomolecular Engineering, University of California, Santa Cruz, California
| | - Achal S Achrol
- Department of Neurosurgery, Stanford University, Stanford, California; Department of Radiology, Stanford University, Stanford, California; Stanford Center for Biomedical Informatics Research and Biomedical Informatics Training Program, Stanford, California; School of Medicine, Stanford University, Stanford, California; Department of Biomolecular Engineering, University of California, Santa Cruz, California
| | - Lex A Mitchell
- Department of Neurosurgery, Stanford University, Stanford, California; Department of Radiology, Stanford University, Stanford, California; Stanford Center for Biomedical Informatics Research and Biomedical Informatics Training Program, Stanford, California; School of Medicine, Stanford University, Stanford, California; Department of Biomolecular Engineering, University of California, Santa Cruz, California
| | - Scott A Rodriguez
- Department of Neurosurgery, Stanford University, Stanford, California; Department of Radiology, Stanford University, Stanford, California; Stanford Center for Biomedical Informatics Research and Biomedical Informatics Training Program, Stanford, California; School of Medicine, Stanford University, Stanford, California; Department of Biomolecular Engineering, University of California, Santa Cruz, California
| | - Abdullah Feroze
- Department of Neurosurgery, Stanford University, Stanford, California; Department of Radiology, Stanford University, Stanford, California; Stanford Center for Biomedical Informatics Research and Biomedical Informatics Training Program, Stanford, California; School of Medicine, Stanford University, Stanford, California; Department of Biomolecular Engineering, University of California, Santa Cruz, California
| | - Michael Iv
- Department of Neurosurgery, Stanford University, Stanford, California; Department of Radiology, Stanford University, Stanford, California; Stanford Center for Biomedical Informatics Research and Biomedical Informatics Training Program, Stanford, California; School of Medicine, Stanford University, Stanford, California; Department of Biomolecular Engineering, University of California, Santa Cruz, California
| | - Christine Kim
- Department of Neurosurgery, Stanford University, Stanford, California; Department of Radiology, Stanford University, Stanford, California; Stanford Center for Biomedical Informatics Research and Biomedical Informatics Training Program, Stanford, California; School of Medicine, Stanford University, Stanford, California; Department of Biomolecular Engineering, University of California, Santa Cruz, California
| | - Navjot Chaudhary
- Department of Neurosurgery, Stanford University, Stanford, California; Department of Radiology, Stanford University, Stanford, California; Stanford Center for Biomedical Informatics Research and Biomedical Informatics Training Program, Stanford, California; School of Medicine, Stanford University, Stanford, California; Department of Biomolecular Engineering, University of California, Santa Cruz, California
| | - Olivier Gevaert
- Department of Neurosurgery, Stanford University, Stanford, California; Department of Radiology, Stanford University, Stanford, California; Stanford Center for Biomedical Informatics Research and Biomedical Informatics Training Program, Stanford, California; School of Medicine, Stanford University, Stanford, California; Department of Biomolecular Engineering, University of California, Santa Cruz, California
| | - Josh M Stuart
- Department of Neurosurgery, Stanford University, Stanford, California; Department of Radiology, Stanford University, Stanford, California; Stanford Center for Biomedical Informatics Research and Biomedical Informatics Training Program, Stanford, California; School of Medicine, Stanford University, Stanford, California; Department of Biomolecular Engineering, University of California, Santa Cruz, California
| | - Griffith R Harsh
- Department of Neurosurgery, Stanford University, Stanford, California; Department of Radiology, Stanford University, Stanford, California; Stanford Center for Biomedical Informatics Research and Biomedical Informatics Training Program, Stanford, California; School of Medicine, Stanford University, Stanford, California; Department of Biomolecular Engineering, University of California, Santa Cruz, California
| | - Steven D Chang
- Department of Neurosurgery, Stanford University, Stanford, California; Department of Radiology, Stanford University, Stanford, California; Stanford Center for Biomedical Informatics Research and Biomedical Informatics Training Program, Stanford, California; School of Medicine, Stanford University, Stanford, California; Department of Biomolecular Engineering, University of California, Santa Cruz, California
| | - Daniel L Rubin
- Department of Neurosurgery, Stanford University, Stanford, California; Department of Radiology, Stanford University, Stanford, California; Stanford Center for Biomedical Informatics Research and Biomedical Informatics Training Program, Stanford, California; School of Medicine, Stanford University, Stanford, California; Department of Biomolecular Engineering, University of California, Santa Cruz, California
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Li Y, Hickson JA, Ambrosi DJ, Haasch DL, Foster-Duke KD, Eaton LJ, DiGiammarino EL, Panchal SC, Jiang F, Mudd SR, Zhang C, Akella SS, Gao W, Ralston SL, Naumovski L, Gu J, Morgan-Lappe SE. ABT-165, a Dual Variable Domain Immunoglobulin (DVD-Ig) Targeting DLL4 and VEGF, Demonstrates Superior Efficacy and Favorable Safety Profiles in Preclinical Models. Mol Cancer Ther 2018; 17:1039-1050. [PMID: 29592882 DOI: 10.1158/1535-7163.mct-17-0800] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2017] [Revised: 12/28/2017] [Accepted: 03/08/2018] [Indexed: 11/16/2022]
Abstract
Antiangiogenic therapy is a clinically validated modality in cancer treatment. To date, all approved antiangiogenic drugs primarily inhibit the VEGF pathway. Delta-like ligand 4 (DLL4) has been identified as a potential drug target in VEGF-independent angiogenesis and tumor-initiating cell (TIC) survival. A dual-specific biologic targeting both VEGF and DLL4 could be an attractive strategy to improve the effectiveness of anti-VEGF therapy. ABT-165 was uniquely engineered using a proprietary dual-variable domain immunoglobulin (DVD-Ig) technology based on its ability to bind and inhibit both DLL4 and VEGF. In vivo, ABT-165 induced significant tumor growth inhibition compared with either parental antibody treatment alone, due, in part, to the disruption of functional tumor vasculature. In combination with chemotherapy agents, ABT-165 also induced greater antitumor response and outperformed anti-VEGF treatment. ABT-165 displayed nonlinear pharmacokinetic profiles in cynomolgus monkeys, with an apparent terminal half-life > 5 days at a target saturation dose. In a GLP monkey toxicity study, ABT-165 was well-tolerated at doses up to 200 mg/kg with non-adverse treatment-related histopathology findings limited to the liver and thymus. In summary, ABT-165 represents a novel antiangiogenic strategy that potently inhibits both DLL4 and VEGF, demonstrating favorable in vivo efficacy, pharmacokinetic, and safety profiles in preclinical models. Given these preclinical attributes, ABT-165 has progressed to a phase I study. Mol Cancer Ther; 17(5); 1039-50. ©2018 AACR.
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Affiliation(s)
- Yingchun Li
- Oncology Discovery, AbbVie Inc., North Chicago, Illinois
| | | | | | | | | | | | | | | | - Fang Jiang
- Oncology Discovery, AbbVie Inc., North Chicago, Illinois
| | - Sarah R Mudd
- Translational Imaging, AbbVie Inc., North Chicago, Illinois
| | - Catherine Zhang
- Drug Metabolism and Pharmacokinetics - Bioanalysis, AbbVie Biotherapeutics, Redwood City, California
| | - Surekha S Akella
- Preclinical Safety, AbbVie Biotherapeutics, Redwood City, California
| | - Wenqing Gao
- Drug Metabolism and Pharmacokinetics, AbbVie Inc., North Chicago, Illinois
| | | | - Louie Naumovski
- Oncology Early Development, AbbVie Inc., Redwood City, California
| | - Jijie Gu
- AbbVie Bioresearch Center, Worcester, Massachusetts
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5
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Singh AK, Garg RK, Gupta RK, Malhotra HS, Agrawal GR, Husain N, Pandey CM, Sahoo P, Kumar N. Dynamic contrast-enhanced (DCE) MRI derived kinetic perfusion indices may help predicting seizure control in single calcified neurocysticercosis. Magn Reson Imaging 2018; 49:55-62. [PMID: 29366682 DOI: 10.1016/j.mri.2018.01.001] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2017] [Accepted: 01/19/2018] [Indexed: 11/16/2022]
Abstract
BACKGROUND The factors responsible for seizure recurrence in patients with Solitary calcified neurocysticercosis (NCC) are not well understood. Blood brain barrier (BBB) breach may be associated with seizure recurrence. Dynamic contrast enhanced (DCE) MRI derived indices kep, ktrans and ve are useful in quantifying BBB permeability. In this study, we assessed the possible role of DCE-MRI and matrix metalloproteinases (MMP)-9 levels in predicting seizure recurrence. METHODS In this prospective-observational study, patients with new-onset seizures and a solitary calcified NCC were included. DCE-MRI was done to quantify BBB integrity. DCE-MRI parameters were measured as kep, ktrans and ve. MMP-9 levels were estimated. Patients were followed for 1 year, when DCE-MRI and MMP-9 levels were repeated. Patients were classified into two groups on the basis of seizure recurrence, which was defined as the recurrence of an episode of seizure at least 1 week after the initiation of the anti-epileptic drugs. Logistic regression analysis was done. RESULTS At 1-year of follow up, 8 out of 32 patients had seizure recurrence. Baseline DCE-MRI derived kep (p = 0.015) and MMP-9 levels (p = 0.019) were significantly higher in the seizure "recurrence" group compared with the "no recurrence" group. On within-group analysis, a significant increase in kep (p = 0.012), ve (p = 0.012), and MMP-9 levels (p = 0.017) was observed in the seizure "recurrence" group while a decrease was seen in ve and MMP-9 levels in the "no recurrence" group. CONCLUSION Higher values of DCE-MRI indices and MMP-9 levels, with a corresponding trend in the follow-up, can be useful in predicting lesions with a higher propensity for seizure recurrence.
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Affiliation(s)
- Alok Kumar Singh
- Department of Neurology, King George Medical University Uttar Pradesh, Lucknow, India
| | - Ravindra Kumar Garg
- Department of Neurology, King George Medical University Uttar Pradesh, Lucknow, India.
| | - Rakesh Kumar Gupta
- Department of Radiology and Imaging, Department of Radiology and Imaging, Fortis Memorial Research Institute, Gurgaon, India
| | | | - Gaurav Raj Agrawal
- Department of Radiodiagnosis, Dr. Ram Manohar Lohia Institute of Medical Sciences, Lucknow, India
| | - Nuzhat Husain
- Department of Pathology, Dr. Ram Manohar Lohia Institute of Medical Sciences, Lucknow, India
| | - Chandra Mani Pandey
- Department of Biostatistics & Health Informatics, Sanjay Gandhi Post Graduate Institute of Medical Sciences, Lucknow, India
| | | | - Neeraj Kumar
- Department of Neurology, King George Medical University Uttar Pradesh, Lucknow, India
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Study of Intrapatient Variability and Reproducibility of Quantitative Tumor Perfusion Parameters Evaluated With Dynamic Contrast-Enhanced Ultrasonography. Invest Radiol 2017; 52:148-154. [DOI: 10.1097/rli.0000000000000324] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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MR Imaging Biomarkers to Monitor Early Response to Hypoxia-Activated Prodrug TH-302 in Pancreatic Cancer Xenografts. PLoS One 2016; 11:e0155289. [PMID: 27227903 PMCID: PMC4882075 DOI: 10.1371/journal.pone.0155289] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2014] [Accepted: 04/27/2016] [Indexed: 01/05/2023] Open
Abstract
TH-302 is a hypoxia-activated prodrug known to activate selectively under the hypoxic conditions commonly found in solid tumors. It is currently being evaluated in clinical trials, including two trials in Pancreatic Ductal Adenocarcinomas (PDAC). The current study was undertaken to evaluate imaging biomarkers for prediction and response monitoring of TH-302 efficacy in xenograft models of PDAC. Dynamic contrast-enhanced (DCE) and diffusion weighted (DW) magnetic resonance imaging (MRI) were used to monitor acute effects on tumor vasculature and cellularity, respectively. Three human PDAC xenografts with known differential responses to TH-302 were imaged prior to, and at 24 h and 48 hours following a single dose of TH-302 or vehicle to determine if imaging changes presaged changes in tumor volumes. DW-MRI was performed at five b-values to generate apparent diffusion coefficient of water (ADC) maps. For DCE-MRI, a standard clinically available contrast reagent, Gd-DTPA, was used to determine blood flow into the tumor region of interest. TH-302 induced a dramatic decrease in the DCE transfer constant (Ktrans) within 48 hours after treatment in the sensitive tumors, Hs766t and Mia PaCa-2, whereas TH-302 had no effect on the perfusion behavior of resistant SU.86.86 tumors. Tumor cellularity, estimated from ADC, was significantly increased 24 and 48 hours after treatment in Hs766t, but was not observed in the Mia PaCa-2 and SU.86.86 groups. Notably, growth inhibition of Hs766t was observed immediately (day 3) following initiation of treatment, but was not observed in MiaPaCa-2 tumors until 8 days after initiation of treatment. Based on these preclinical findings, DCE-MRI measures of vascular perfusion dynamics and ADC measures of cell density are suggested as potential TH-302 response biomarkers in clinical trials.
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Khalifa F, Soliman A, El-Baz A, Abou El-Ghar M, El-Diasty T, Gimel'farb G, Ouseph R, Dwyer AC. Models and methods for analyzing DCE-MRI: a review. Med Phys 2015; 41:124301. [PMID: 25471985 DOI: 10.1118/1.4898202] [Citation(s) in RCA: 199] [Impact Index Per Article: 22.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
PURPOSE To present a review of most commonly used techniques to analyze dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), discusses their strengths and weaknesses, and outlines recent clinical applications of findings from these approaches. METHODS DCE-MRI allows for noninvasive quantitative analysis of contrast agent (CA) transient in soft tissues. Thus, it is an important and well-established tool to reveal microvasculature and perfusion in various clinical applications. In the last three decades, a host of nonparametric and parametric models and methods have been developed in order to quantify the CA's perfusion into tissue and estimate perfusion-related parameters (indexes) from signal- or concentration-time curves. These indexes are widely used in various clinical applications for the detection, characterization, and therapy monitoring of different diseases. RESULTS Promising theoretical findings and experimental results for the reviewed models and techniques in a variety of clinical applications suggest that DCE-MRI is a clinically relevant imaging modality, which can be used for early diagnosis of different diseases, such as breast and prostate cancer, renal rejection, and liver tumors. CONCLUSIONS Both nonparametric and parametric approaches for DCE-MRI analysis possess the ability to quantify tissue perfusion.
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Affiliation(s)
- Fahmi Khalifa
- BioImaging Laboratory, Department of Bioengineering, University of Louisville, Louisville, Kentucky 40292 and Electronics and Communication Engineering Department, Mansoura University, Mansoura 35516, Egypt
| | - Ahmed Soliman
- BioImaging Laboratory, Department of Bioengineering, University of Louisville, Louisville, Kentucky 40292
| | - Ayman El-Baz
- BioImaging Laboratory, Department of Bioengineering, University of Louisville, Louisville, Kentucky 40292
| | - Mohamed Abou El-Ghar
- Radiology Department, Urology and Nephrology Center, Mansoura University, Mansoura 35516, Egypt
| | - Tarek El-Diasty
- Radiology Department, Urology and Nephrology Center, Mansoura University, Mansoura 35516, Egypt
| | - Georgy Gimel'farb
- Department of Computer Science, University of Auckland, Auckland 1142, New Zealand
| | - Rosemary Ouseph
- Kidney Transplantation-Kidney Disease Center, University of Louisville, Louisville, Kentucky 40202
| | - Amy C Dwyer
- Kidney Transplantation-Kidney Disease Center, University of Louisville, Louisville, Kentucky 40202
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Weis JA, Flint KM, Sanchez V, Yankeelov TE, Miga MI. Assessing the accuracy and reproducibility of modality independent elastography in a murine model of breast cancer. J Med Imaging (Bellingham) 2015; 2:036001. [PMID: 26158120 DOI: 10.1117/1.jmi.2.3.036001] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2015] [Accepted: 06/02/2015] [Indexed: 01/21/2023] Open
Abstract
Cancer progression has been linked to mechanics. Therefore, there has been recent interest in developing noninvasive imaging tools for cancer assessment that are sensitive to changes in tissue mechanical properties. We have developed one such method, modality independent elastography (MIE), that estimates the relative elastic properties of tissue by fitting anatomical image volumes acquired before and after the application of compression to biomechanical models. The aim of this study was to assess the accuracy and reproducibility of the method using phantoms and a murine breast cancer model. Magnetic resonance imaging data were acquired, and the MIE method was used to estimate relative volumetric stiffness. Accuracy was assessed using phantom data by comparing to gold-standard mechanical testing of elasticity ratios. Validation error was [Formula: see text]. Reproducibility analysis was performed on animal data, and within-subject coefficients of variation ranged from 2 to 13% at the bulk level and 32% at the voxel level. To our knowledge, this is the first study to assess the reproducibility of an elasticity imaging metric in a preclinical cancer model. Our results suggest that the MIE method can reproducibly generate accurate estimates of the relative mechanical stiffness and provide guidance on the degree of change needed in order to declare biological changes rather than experimental error in future therapeutic studies.
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Affiliation(s)
- Jared A Weis
- Vanderbilt University , Department of Biomedical Engineering, PMB 351631, 2301 Vanderbilt Place, Nashville, Tennessee 37235-1631, United States ; Vanderbilt University , Institute of Imaging Science, 1161 21st Avenue South, AA-1105 MCN, Nashville, Tennessee 37232-2310, United States ; Vanderbilt University , Radiology and Radiological Sciences, 1161 21st Avenue South, MCN CCC-1118, Nashville, Tennessee 37232-2675, United States
| | - Katelyn M Flint
- Vanderbilt University , Department of Biomedical Engineering, PMB 351631, 2301 Vanderbilt Place, Nashville, Tennessee 37235-1631, United States
| | - Violeta Sanchez
- Vanderbilt University , Vanderbilt-Ingram Cancer Center, 2220 Pierce Avenue, 691 PRB, Nashville, Tennessee 37232-6838, United States
| | - Thomas E Yankeelov
- Vanderbilt University , Department of Biomedical Engineering, PMB 351631, 2301 Vanderbilt Place, Nashville, Tennessee 37235-1631, United States ; Vanderbilt University , Institute of Imaging Science, 1161 21st Avenue South, AA-1105 MCN, Nashville, Tennessee 37232-2310, United States ; Vanderbilt University , Radiology and Radiological Sciences, 1161 21st Avenue South, MCN CCC-1118, Nashville, Tennessee 37232-2675, United States ; Vanderbilt University , Vanderbilt-Ingram Cancer Center, 2220 Pierce Avenue, 691 PRB, Nashville, Tennessee 37232-6838, United States ; Vanderbilt University , Physics and Astronomy, PMB 401807, 2301 Vanderbilt Place, Nashville, Tennessee 37240-1807, United States ; Vanderbilt University , Cancer Biology, 2220 Pierce Avenue, 771 PRB, Nashville, Tennessee 37232-6840, United States
| | - Michael I Miga
- Vanderbilt University , Department of Biomedical Engineering, PMB 351631, 2301 Vanderbilt Place, Nashville, Tennessee 37235-1631, United States ; Vanderbilt University , Institute of Imaging Science, 1161 21st Avenue South, AA-1105 MCN, Nashville, Tennessee 37232-2310, United States ; Vanderbilt University , Radiology and Radiological Sciences, 1161 21st Avenue South, MCN CCC-1118, Nashville, Tennessee 37232-2675, United States ; Vanderbilt University , Vanderbilt-Ingram Cancer Center, 2220 Pierce Avenue, 691 PRB, Nashville, Tennessee 37232-6838, United States ; Vanderbilt University , Neurosurgery, T-4224 MCN Nashville, Tennessee 37232-2380, United States
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Kim H, Samuel S, Totenhagen JW, Warren M, Sellers JC, Buchsbaum DJ. Dynamic contrast enhanced magnetic resonance imaging of an orthotopic pancreatic cancer mouse model. J Vis Exp 2015:52641. [PMID: 25938718 PMCID: PMC4541579 DOI: 10.3791/52641] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023] Open
Abstract
Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) has been limitedly used for orthotopic pancreatic tumor xenografts due to severe respiratory motion artifact in the abdominal area. Orthotopic tumor models offer advantages over subcutaneous ones, because those can reflect the primary tumor microenvironment affecting blood supply, neovascularization, and tumor cell invasion. We have recently established a protocol of DCE-MRI of orthotopic pancreatic tumor xenografts in mouse models by securing tumors with an orthogonally bent plastic board to prevent motion transfer from the chest region during imaging. The pressure by this board was localized on the abdominal area, and has not resulted in respiratory difficulty of the animals. This article demonstrates the detailed procedure of orthotopic pancreatic tumor modeling using small animals and DCE-MRI of the tumor xenografts. Quantification method of pharmacokinetic parameters in DCE-MRI is also introduced. The procedure described in this article will assist investigators to apply DCE-MRI for orthotopic gastrointestinal cancer mouse models.
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Affiliation(s)
- Hyunki Kim
- Radiology, University of Alabama at Birmingham;
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Kim E, Lee E, Plummer C, Gil S, Popel AS, Pathak AP. Vasculature-specific MRI reveals differential anti-angiogenic effects of a biomimetic peptide in an orthotopic breast cancer model. Angiogenesis 2015; 18:125-36. [PMID: 25408417 PMCID: PMC4366284 DOI: 10.1007/s10456-014-9450-5] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2014] [Accepted: 11/09/2014] [Indexed: 12/31/2022]
Abstract
Translational vasculature-specific MRI biomarkers were used to measure the effects of a novel anti-angiogenic biomimetic peptide in an orthotopic MDA-MB-231 human triple-negative breast cancer model at an early growth stage. In vivo diffusion-weighted and steady-state susceptibility contrast (SSC) MRI was performed pre-treatment and 2 weeks post-treatment in tumor volume-matched treatment and control groups (n = 5/group). Treatment response was measured by changes in tumor volume; baseline transverse relaxation time (T2); apparent diffusion coefficient (ADC); and SSC-MRI metrics of blood volume, vessel size, and vessel density. These vasculature-specific SSC-MRI biomarkers were compared to the more conventional, non-vascular biomarkers (tumor growth, ADC, and T2) in terms of their sensitivity to anti-angiogenic treatment response. After 2 weeks of peptide treatment, tumor growth inhibition was evident but not yet significant, and the changes in ADC or T2 were not significantly different between treated and control groups. In contrast, the vascular MRI biomarkers revealed a significant anti-angiogenic response to the peptide after 2 weeks—blood volume and vessel size decreased, and vessel density increased in treated tumors; the opposite was seen in control tumors. The MRI results were validated with histology—H&E staining showed no difference in tumor viability between groups, while peptide-treated tumors exhibited decreased vascularity. These results indicate that translational SSC-MRI biomarkers are able to detect the differential effects of anti-angiogenic therapy on the tumor vasculature before significant tumor growth inhibition or changes in tumor viability.
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Affiliation(s)
- Eugene Kim
- Department of Biomedical Engineering, The Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Esak Lee
- Department of Biomedical Engineering, The Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Charlesa Plummer
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Stacy Gil
- Department of Biomedical Engineering, The Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Aleksander S. Popel
- Department of Biomedical Engineering, The Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, 720 Rutland Ave, 217 Traylor Bldg., Baltimore, MD 21205, USA
| | - Arvind P. Pathak
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, 720 Rutland Ave, 217 Traylor Bldg., Baltimore, MD 21205, USA
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Aryal M, Park J, Vykhodtseva N, Zhang YZ, McDannold N. Enhancement in blood-tumor barrier permeability and delivery of liposomal doxorubicin using focused ultrasound and microbubbles: evaluation during tumor progression in a rat glioma model. Phys Med Biol 2015; 60:2511-27. [PMID: 25746014 DOI: 10.1088/0031-9155/60/6/2511] [Citation(s) in RCA: 75] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Effective drug delivery to brain tumors is often challenging because of the heterogeneous permeability of the 'blood tumor barrier' (BTB) along with other factors such as increased interstitial pressure and drug efflux pumps. Focused ultrasound (FUS) combined with microbubbles can enhance the permeability of the BTB in brain tumors, as well as the blood-brain barrier in the surrounding tissue. In this study, dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) was used to characterize the FUS-induced permeability changes of the BTB in a rat glioma model at different times after implantation. 9L gliosarcoma cells were implanted in both hemispheres in male rats. At day 9, 14, or 17 days after implantation, FUS-induced BTB disruption using 690 kHz ultrasound and definity microbubbles was performed in one tumor in each animal. Before FUS, liposomal doxorubicin was administered at a dose of 5.67 mg kg(-1). This chemotherapy agent was previously shown to improve survival in animal glioma models. The transfer coefficient Ktrans describing extravasation of the MRI contrast agent Gd-DTPA was measured via DCE-MRI before and after sonication. We found that tumor doxorubicin concentrations increased monotonically (823 ± 600, 1817 ± 732 and 2432 ± 448 ng g(-1)) in the control tumors at 9, 14 and 17 d. With FUS-induced BTB disruption, the doxorubicin concentrations were enhanced significantly (P < 0.05, P < 0.01, and P < 0.0001 at days 9, 14, and 17, respectively) and were greater than the control tumors by a factor of two or more (2222 ± 784, 3687 ± 796 and 5658 ± 821 ng g(-1)) regardless of the stage of tumor growth. The transfer coefficient Ktrans was significantly (P < 0.05) enhanced compared to control tumors only at day 9 but not at day 14 or 17. These results suggest that FUS-induced enhancements in tumor drug delivery are relatively consistent over time, at least in this tumor model. These results are encouraging for the use of large drug carriers, as they suggest that even large/late-stage tumors can benefit from FUS-induced drug enhancement. Corresponding enhancements in Ktrans were found to be variable in large/late-stage tumors and not significantly different than controls, perhaps reflecting the size mismatch between the liposomal drug (~100 nm) and Gd-DTPA (molecular weight: 938 Da; hydrodynamic diameter: ≃2 nm). It may be necessary to use a larger MRI contrast agent to effectively evaluate the sonication-induced enhanced permeabilization in large/late-stage tumors when a large drug carrier such as a liposome is used.
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Affiliation(s)
- Muna Aryal
- Department of Physics, Boston College, 221 Longwood Avenue, Boston, MA 02115, USA. Department of Radiology, Brigham & Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
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Abstract
In view of the trend towards personalized treatment strategies for (cancer) patients, there is an increasing need to noninvasively determine individual patient characteristics. Such information enables physicians to administer to patients accurate therapy with appropriate timing. For the noninvasive visualization of disease-related features, imaging biomarkers are expected to play a crucial role. Next to the chemical development of imaging probes, this requires preclinical studies in animal tumour models. These studies provide proof-of-concept of imaging biomarkers and help determine the pharmacokinetics and target specificity of relevant imaging probes, features that provide the fundamentals for translation to the clinic. In this review we describe biological processes derived from the “hallmarks of cancer” that may serve as imaging biomarkers for diagnostic, prognostic and treatment response monitoring that are currently being studied in the preclinical setting. A number of these biomarkers are also being used for the initial preclinical assessment of new intervention strategies. Uniquely, noninvasive imaging approaches allow longitudinal assessment of changes in biological processes, providing information on the safety, pharmacokinetic profiles and target specificity of new drugs, and on the antitumour effectiveness of therapeutic interventions. Preclinical biomarker imaging can help guide translation to optimize clinical biomarker imaging and personalize (combination) therapies.
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