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Strowd R, Ellingson B, Raymond C, Yao J, Wen PY, Ahluwalia M, Piotrowski A, Desai A, Clarke JL, Lieberman FS, Desideri S, Nabors LB, Ye X, Grossman S. Activity of a first-in-class oral HIF2-alpha inhibitor, PT2385, in patients with first recurrence of glioblastoma. J Neurooncol 2023; 165:101-112. [PMID: 37864646 PMCID: PMC10863646 DOI: 10.1007/s11060-023-04456-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Accepted: 09/19/2023] [Indexed: 10/23/2023]
Abstract
INTRODUCTION Hypoxia inducible factor 2-alpha (HIF2α) mediates cellular responses to hypoxia and is over-expressed in glioblastoma (GBM). PT2385 is an oral HIF2α inhibitor with in vivo activity against GBM. METHODS A two-stage single-arm open-label phase II study of adults with GBM at first recurrence following chemoradiation with measurable disease was conducted through the Adult Brain Tumor Consortium. PT2385 was administered at the phase II dose (800 mg b.i.d.). The primary outcome was objective radiographic response (ORR = complete response + partial response, CR + PR); secondary outcomes were safety, overall survival (OS), and progression free survival (PFS). Exploratory objectives included pharmacokinetics (day 15 Cmin), pharmacodynamics (erythropoietin, vascular endothelial growth factor), and pH-weighted amine- chemical exchange saturation transfer (CEST) MRI to quantify tumor acidity at baseline and explore associations with drug response. Stage 1 enrolled 24 patients with early stoppage for ≤ 1 ORR. RESULTS Of the 24 enrolled patients, median age was 62.1 (38.7-76.7) years, median KPS 80, MGMT promoter was methylated in 46% of tumors. PT2385 was well tolerated. Grade ≥ 3 drug-related adverse events were hypoxia (n = 2), hyponatremia (2), lymphopenia (1), anemia (1), and hyperglycemia (1). No objective radiographic responses were observed; median PFS was 1.8 months (95% CI 1.6-2.5) and OS was 7.7 months (95% CI 4.9-12.6). Drug exposure varied widely and did not differ by corticosteroid use (p = 0.12), antiepileptics (p = 0.09), or sex (p = 0.37). Patients with high systemic exposure had significantly longer PFS (6.7 vs 1.8 months, p = 0.009). Baseline acidity by pH-weighted CEST MRI correlated significantly with treatment duration (R2 = 0.49, p = 0.017). Non-enhancing infiltrative disease with high acidity gave rise to recurrence. CONCLUSIONS PT2385 monotherapy had limited activity in first recurrent GBM. Drug exposure was variable. Signals of activity were observed in GBM patients with high systemic exposure and acidic lesions on CEST imaging. A second-generation HIF2α inhibitor is being studied.
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Affiliation(s)
- Roy Strowd
- Wake Forest University School of Medicine, 1 Medical Center Boulevard, Winston Salem, NC, 27104, USA.
| | | | | | - Jingwen Yao
- University of California Los Angeles, Los Angeles, CA, USA
| | | | | | | | - Arati Desai
- University of Pennsylvania, Philadelphia, PA, USA
| | | | | | | | - L Burt Nabors
- University of Alabama at Birmingham, Birmingham, AL, USA
| | - Xiaobu Ye
- Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins, Baltimore, MD, USA
| | - Stuart Grossman
- Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins, Baltimore, MD, USA
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Cho NS, Hagiwara A, Yao J, Nathanson DA, Prins RM, Wang C, Raymond C, Desousa BR, Divakaruni A, Morrow DH, Nghiemphu PL, Lai A, Liau LM, Everson RG, Salamon N, Pope WB, Cloughesy TF, Ellingson BM. Amine-weighted chemical exchange saturation transfer magnetic resonance imaging in brain tumors. NMR IN BIOMEDICINE 2023; 36:e4785. [PMID: 35704275 DOI: 10.1002/nbm.4785] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/01/2021] [Revised: 05/31/2022] [Accepted: 06/10/2022] [Indexed: 05/23/2023]
Abstract
Amine-weighted chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI) is particularly valuable as an amine- and pH-sensitive imaging technique in brain tumors, targeting the intrinsically high concentration of amino acids with exchangeable amine protons and reduced extracellular pH in brain tumors. Amine-weighted CEST MRI contrast is dependent on the glioma genotype, likely related to differences in degree of malignancy and metabolic behavior. Amine-weighted CEST MRI may provide complementary value to anatomic imaging in conventional and exploratory therapies in brain tumors, including chemoradiation, antiangiogenic therapies, and immunotherapies. Continual improvement and clinical testing of amine-weighted CEST MRI has the potential to greatly impact patients with brain tumors by understanding vulnerabilities in the tumor microenvironment that may be therapeutically exploited.
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Affiliation(s)
- Nicholas S Cho
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, California, USA
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
- Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California, Los Angeles, Los Angeles, California, USA
- Medical Scientist Training Program, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
| | - Akifumi Hagiwara
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, California, USA
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
| | - Jingwen Yao
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, California, USA
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
- Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California, Los Angeles, Los Angeles, California, USA
| | - David A Nathanson
- Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
| | - Robert M Prins
- Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
| | - Chencai Wang
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, California, USA
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
| | - Catalina Raymond
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, California, USA
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
| | - Brandon R Desousa
- Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
| | - Ajit Divakaruni
- Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
| | - Danielle H Morrow
- Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
| | - Phioanh L Nghiemphu
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
- UCLA Brain Tumor Program, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
| | - Albert Lai
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
- UCLA Brain Tumor Program, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
| | - Linda M Liau
- Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
| | - Richard G Everson
- Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
| | - Noriko Salamon
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
| | - Whitney B Pope
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
| | - Timothy F Cloughesy
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
- UCLA Brain Tumor Program, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
| | - Benjamin M Ellingson
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, California, USA
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
- Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California, Los Angeles, Los Angeles, California, USA
- Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
- UCLA Brain Tumor Program, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
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3
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Larionova TD, Bastola S, Aksinina TE, Anufrieva KS, Wang J, Shender VO, Andreev DE, Kovalenko TF, Arapidi GP, Shnaider PV, Kazakova AN, Latyshev YA, Tatarskiy VV, Shtil AA, Moreau P, Giraud F, Li C, Wang Y, Rubtsova MP, Dontsova OA, Condro M, Ellingson BM, Shakhparonov MI, Kornblum HI, Nakano I, Pavlyukov MS. Alternative RNA splicing modulates ribosomal composition and determines the spatial phenotype of glioblastoma cells. Nat Cell Biol 2022; 24:1541-1557. [PMID: 36192632 PMCID: PMC10026424 DOI: 10.1038/s41556-022-00994-w] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2021] [Accepted: 08/15/2022] [Indexed: 02/08/2023]
Abstract
Glioblastoma (GBM) is characterized by exceptionally high intratumoral heterogeneity. However, the molecular mechanisms underlying the origin of different GBM cell populations remain unclear. Here, we found that the compositions of ribosomes of GBM cells in the tumour core and edge differ due to alternative RNA splicing. The acidic pH in the core switches before messenger RNA splicing of the ribosomal gene RPL22L1 towards the RPL22L1b isoform. This allows cells to survive acidosis, increases stemness and correlates with worse patient outcome. Mechanistically, RPL22L1b promotes RNA splicing by interacting with lncMALAT1 in the nucleus and inducing its degradation. Contrarily, in the tumour edge region, RPL22L1a interacts with ribosomes in the cytoplasm and upregulates the translation of multiple messenger RNAs including TP53. We found that the RPL22L1 isoform switch is regulated by SRSF4 and identified a compound that inhibits this process and decreases tumour growth. These findings demonstrate how distinct GBM cell populations arise during tumour growth. Targeting this mechanism may decrease GBM heterogeneity and facilitate therapy.
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Affiliation(s)
- Tatyana D Larionova
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russian Federation
| | - Soniya Bastola
- Department of Bioengineering, University of California Los Angeles, Los Angeles, CA, USA
| | - Tatiana E Aksinina
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russian Federation
| | - Ksenia S Anufrieva
- Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Federal Research and Clinical Center of Physical-Chemical Medicine, Federal Medical Biological Agency, Moscow, Russian Federation
- Federal Research and Clinical Center of Physical-Chemical Medicine, Federal Medical and Biological Agency, Moscow, Russian Federation
| | - Jia Wang
- Department of Neurosurgery, Centre of Brain Science, First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Victoria O Shender
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russian Federation
- Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Federal Research and Clinical Center of Physical-Chemical Medicine, Federal Medical Biological Agency, Moscow, Russian Federation
- Federal Research and Clinical Center of Physical-Chemical Medicine, Federal Medical and Biological Agency, Moscow, Russian Federation
| | - Dmitriy E Andreev
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russian Federation
- Belozersky Institute of Physico-Chemical Biology, Lomonosov Moscow State University, Moscow, Russian Federation
| | - Tatiana F Kovalenko
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russian Federation
| | - Georgij P Arapidi
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russian Federation
- Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Federal Research and Clinical Center of Physical-Chemical Medicine, Federal Medical Biological Agency, Moscow, Russian Federation
- Federal Research and Clinical Center of Physical-Chemical Medicine, Federal Medical and Biological Agency, Moscow, Russian Federation
| | - Polina V Shnaider
- Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Federal Research and Clinical Center of Physical-Chemical Medicine, Federal Medical Biological Agency, Moscow, Russian Federation
- Federal Research and Clinical Center of Physical-Chemical Medicine, Federal Medical and Biological Agency, Moscow, Russian Federation
| | - Anastasia N Kazakova
- Federal Research and Clinical Center of Physical-Chemical Medicine, Federal Medical and Biological Agency, Moscow, Russian Federation
| | - Yaroslav A Latyshev
- N.N. Burdenko National Medical Research Center of Neurosurgery, Ministry of Health of the Russian Federation, Moscow, Russian Federation
| | - Victor V Tatarskiy
- Institute of Gene Biology, Russian Academy of Sciences, Moscow, Russian Federation
| | - Alexander A Shtil
- Blokhin National Medical Research Center of Oncology, Moscow, Russian Federation
| | - Pascale Moreau
- Institute of Chemistry of Clermont-Ferrand, CNRS, Université Clermont Auvergne, Clermont-Ferrand, France
| | - Francis Giraud
- Institute of Chemistry of Clermont-Ferrand, CNRS, Université Clermont Auvergne, Clermont-Ferrand, France
| | - Chaoxi Li
- Department of Neurosurgery, School of Medicine and O'Neal Comprehensive Cancer Center, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Yichan Wang
- Department of Neurosurgery, Centre of Brain Science, First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Maria P Rubtsova
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russian Federation
- Belozersky Institute of Physico-Chemical Biology, Lomonosov Moscow State University, Moscow, Russian Federation
| | - Olga A Dontsova
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russian Federation
- Belozersky Institute of Physico-Chemical Biology, Lomonosov Moscow State University, Moscow, Russian Federation
- Center of Life Sciences, Skolkovo Institute of Science and Technology, Moscow, Russian Federation
| | - Michael Condro
- Department of Bioengineering, University of California Los Angeles, Los Angeles, CA, USA
| | - Benjamin M Ellingson
- Brain Tumor Imaging Laboratory, Center for Computer Vision and Imaging Biomarkers, University of California Los Angeles, Los Angeles, CA, USA
- Department of Radiological Sciences, University of California Los Angeles, Los Angeles, CA, USA
- Department of Psychiatry, University of California Los Angeles, Los Angeles, CA, USA
- Department of Neurosurgery, University of California Los Angeles, Los Angeles, CA, USA
| | | | - Harley I Kornblum
- Intellectual and Developmental Disabilities Research Center, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Ichiro Nakano
- Department of Neurosurgery, Medical Institute of Hokuto, Hokkaido, Japan.
| | - Marat S Pavlyukov
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russian Federation.
- Centre for Genomic Regulation, Barcelona Institute of Science and Technology, Barcelona, Spain.
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B 0 Correction for 3T Amide Proton Transfer (APT) MRI Using a Simplified Two-Pool Lorentzian Model of Symmetric Water and Asymmetric Solutes. Tomography 2022; 8:1974-1986. [PMID: 36006063 PMCID: PMC9412582 DOI: 10.3390/tomography8040165] [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: 05/04/2022] [Revised: 07/17/2022] [Accepted: 07/27/2022] [Indexed: 11/16/2022] Open
Abstract
Amide proton transfer (APT)-weighted MRI is a promising molecular imaging technique that has been employed in clinic for detection and grading of brain tumors. MTRasym, the quantification method of APT, is easily influenced by B0 inhomogeneity and causes artifacts. Current model-free interpolation methods have enabled moderate B0 correction for middle offsets, but have performed poorly at limbic offsets. To address this shortcoming, we proposed a practical B0 correction approach that is suitable under time-limited sparse acquisition scenarios and for B1 ≥ 1 μT under 3T. In this study, this approach employed a simplified Lorentzian model containing only two pools of symmetric water and asymmetric solutes, to describe the Z-spectral shape with wide and ‘invisible’ CEST peaks. The B0 correction was then performed on the basis of the fitted two-pool Lorentzian lines, instead of using conventional model-free interpolation. The approach was firstly evaluated on densely sampled Z-spectra data by using the spline interpolation of all acquired 16 offsets as the gold standard. When only six offsets were available for B0 correction, our method outperformed conventional methods. In particular, the errors at limbic offsets were significantly reduced (n = 8, p < 0.01). Secondly, our method was assessed on the six-offset APT data of nine brain tumor patients. Our MTRasym (3.5 ppm), using the two-pool model, displayed a similar contrast to the vendor-provided B0-orrected MTRasym (3.5 ppm). While the vendor failed in correcting B0 at 4.3 and 2.7 ppm for a large portion of voxels, our method enabled well differentiation of B0 artifacts from tumors. In conclusion, the proposed approach could alleviate analysis errors caused by B0 inhomogeneity, which is useful for facilitating the comprehensive metabolic analysis of brain tumors.
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Yao J, Hagiwara A, Oughourlian TC, Wang C, Raymond C, Pope WB, Salamon N, Lai A, Ji M, Nghiemphu PL, Liau LM, Cloughesy TF, Ellingson BM. Diagnostic and Prognostic Value of pH- and Oxygen-Sensitive Magnetic Resonance Imaging in Glioma: A Retrospective Study. Cancers (Basel) 2022; 14:2520. [PMID: 35626127 PMCID: PMC9139712 DOI: 10.3390/cancers14102520] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Revised: 05/11/2022] [Accepted: 05/17/2022] [Indexed: 01/19/2023] Open
Abstract
Characterization of hypoxia and tissue acidosis could advance the understanding of glioma biology and improve patient management. In this study, we evaluated the ability of a pH- and oxygen-sensitive magnetic resonance imaging (MRI) technique to differentiate glioma genotypes, including isocitrate dehydrogenase (IDH) mutation, 1p/19q co-deletion, and epidermal growth factor receptor (EGFR) amplification, and investigated its prognostic value. A total of 159 adult glioma patients were scanned with pH- and oxygen-sensitive MRI at 3T. We quantified the pH-sensitive measure of magnetization transfer ratio asymmetry (MTRasym) and oxygen-sensitive measure of R2’ within the tumor region-of-interest. IDH mutant gliomas showed significantly lower MTRasym × R2’ (p < 0.001), which differentiated IDH mutation status with sensitivity and specificity of 90.0% and 71.9%. Within IDH mutants, 1p/19q codeletion was associated with lower tumor acidity (p < 0.0001, sensitivity 76.9%, specificity 91.3%), while IDH wild-type, EGFR-amplified gliomas were more hypoxic (R2’ p = 0.024, sensitivity 66.7%, specificity 76.9%). Both R2’ and MTRasym × R2’ were significantly associated with patient overall survival (R2’: p = 0.045; MTRasym × R2’: p = 0.002) and progression-free survival (R2’: p = 0.010; MTRasym × R2’: p < 0.0001), independent of patient age, treatment status, and IDH status. The pH- and oxygen-sensitive MRI is a clinically feasible and potentially valuable imaging technique for distinguishing glioma subtypes and providing additional prognostic value to clinical practice.
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Affiliation(s)
- Jingwen Yao
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, CA 90024, USA; (J.Y.); (A.H.); (T.C.O.); (C.W.); (C.R.)
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, CA 90024, USA; (W.B.P.); (N.S.)
| | - Akifumi Hagiwara
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, CA 90024, USA; (J.Y.); (A.H.); (T.C.O.); (C.W.); (C.R.)
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, CA 90024, USA; (W.B.P.); (N.S.)
| | - Talia C. Oughourlian
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, CA 90024, USA; (J.Y.); (A.H.); (T.C.O.); (C.W.); (C.R.)
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, CA 90024, USA; (W.B.P.); (N.S.)
- Neuroscience Interdepartmental Program, David Geffen School of Medicine, University of California, Los Angeles, CA 90024, USA
| | - Chencai Wang
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, CA 90024, USA; (J.Y.); (A.H.); (T.C.O.); (C.W.); (C.R.)
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, CA 90024, USA; (W.B.P.); (N.S.)
| | - Catalina Raymond
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, CA 90024, USA; (J.Y.); (A.H.); (T.C.O.); (C.W.); (C.R.)
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, CA 90024, USA; (W.B.P.); (N.S.)
| | - Whitney B. Pope
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, CA 90024, USA; (W.B.P.); (N.S.)
| | - Noriko Salamon
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, CA 90024, USA; (W.B.P.); (N.S.)
| | - Albert Lai
- UCLA Neuro-Oncology Program, University of California, Los Angeles, CA 90024, USA; (A.L.); (M.J.); (P.L.N.); (T.F.C.)
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA 90024, USA
| | - Matthew Ji
- UCLA Neuro-Oncology Program, University of California, Los Angeles, CA 90024, USA; (A.L.); (M.J.); (P.L.N.); (T.F.C.)
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA 90024, USA
| | - Phioanh L. Nghiemphu
- UCLA Neuro-Oncology Program, University of California, Los Angeles, CA 90024, USA; (A.L.); (M.J.); (P.L.N.); (T.F.C.)
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA 90024, USA
| | - Linda M. Liau
- Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, CA 90024, USA;
| | - Timothy F. Cloughesy
- UCLA Neuro-Oncology Program, University of California, Los Angeles, CA 90024, USA; (A.L.); (M.J.); (P.L.N.); (T.F.C.)
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA 90024, USA
| | - Benjamin M. Ellingson
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, CA 90024, USA; (J.Y.); (A.H.); (T.C.O.); (C.W.); (C.R.)
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, CA 90024, USA; (W.B.P.); (N.S.)
- UCLA Neuro-Oncology Program, University of California, Los Angeles, CA 90024, USA; (A.L.); (M.J.); (P.L.N.); (T.F.C.)
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6
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Hagiwara A, Yao J, Raymond C, Cho NS, Everson R, Patel K, Morrow DH, Desousa BR, Mareninov S, Chun S, Nathanson DA, Yong WH, Andrei G, Divakaruni AS, Salamon N, Pope WB, Nghiemphu PL, Liau LM, Cloughesy TF, Ellingson BM. "Aerobic glycolytic imaging" of human gliomas using combined pH-, oxygen-, and perfusion-weighted magnetic resonance imaging. Neuroimage Clin 2022; 32:102882. [PMID: 34911188 PMCID: PMC8609049 DOI: 10.1016/j.nicl.2021.102882] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Revised: 11/10/2021] [Accepted: 11/11/2021] [Indexed: 01/24/2023]
Abstract
Aerobic glycolytic imaging combines pH-, oxygen-, and perfusion-weighted MRI. Aerobic glycolytic imaging depicts abnormal glucose metabolism of gliomas. IDH wild-type gliomas show higher aerobic glycolytic index compared with mutants. Aerobic glycolytic index in IDH wild-type glioma is correlated with glucose uptake. Aerobic glycolytic index in IDH mutant glioma is correlated to lactate transporters.
Purpose To quantify abnormal metabolism of diffuse gliomas using “aerobic glycolytic imaging” and investigate its biological correlation. Methods All subjects underwent a pH-weighted amine chemical exchange saturation transfer spin-and-gradient-echo echoplanar imaging (CEST-SAGE-EPI) and dynamic susceptibility contrast perfusion MRI. Relative oxygen extraction fraction (rOEF) was estimated as the ratio of reversible transverse relaxation rate R2′ to normalized relative cerebral blood volume. An aerobic glycolytic index (AGI) was derived by the ratio of pH-weighted image contrast (MTRasym at 3.0 ppm) to rOEF. AGI was compared between different tumor types (N = 51, 30 IDH mutant and 21 IDH wild type). Metabolic MR parameters were correlated with 18F-FDG uptake (N = 8, IDH wild-type glioblastoma), expression of key glycolytic proteins using immunohistochemistry (N = 38 samples, 21 from IDH mutant and 17 from IDH wild type), and bioenergetics analysis on purified tumor cells (N = 7, IDH wild-type high grade). Results AGI was significantly lower in IDH mutant than wild-type gliomas (0.48 ± 0.48 vs. 0.70 ± 0.48; P = 0.03). AGI was strongly correlated with 18F-FDG uptake both in non-enhancing tumor (Spearman, ρ = 0.81; P = 0.01) and enhancing tumor (ρ = 0.81; P = 0.01). AGI was significantly correlated with glucose transporter 3 (ρ = 0.71; P = 0.004) and hexokinase 2 (ρ = 0.73; P = 0.003) in IDH wild-type glioma, and monocarboxylate transporter 1 (ρ = 0.59; P = 0.009) in IDH mutant glioma. Additionally, a significant correlation was found between AGI derived from bioenergetics analysis and that estimated from MRI (ρ = 0.79; P = 0.04). Conclusion AGI derived from molecular MRI was correlated with glucose uptake (18F-FDG and glucose transporter 3/hexokinase 2) and cellular AGI in IDH wild-type gliomas, whereas AGI in IDH mutant gliomas appeared associated with monocarboxylate transporter density.
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Affiliation(s)
- Akifumi Hagiwara
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, CA, USA; Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA; Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan
| | - Jingwen Yao
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, CA, USA; Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA; Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California Los Angeles, Los Angeles, CA, USA
| | - Catalina Raymond
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, CA, USA; Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Nicholas S Cho
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, CA, USA; Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA; Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California Los Angeles, Los Angeles, CA, USA; Medical Scientist Training Program, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Richard Everson
- Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Kunal Patel
- Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Danielle H Morrow
- Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Brandon R Desousa
- Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Sergey Mareninov
- Department of Pathology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Saewon Chun
- UCLA Neuro-Oncology Program, University of California, Los Angeles, Los Angeles, CA, USA
| | - David A Nathanson
- Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - William H Yong
- Department of Pathology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Gafita Andrei
- Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Ajit S Divakaruni
- Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Noriko Salamon
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Whitney B Pope
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Phioanh L Nghiemphu
- UCLA Neuro-Oncology Program, University of California, Los Angeles, Los Angeles, CA, USA; Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Linda M Liau
- Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Timothy F Cloughesy
- UCLA Neuro-Oncology Program, University of California, Los Angeles, Los Angeles, CA, USA; Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Benjamin M Ellingson
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, CA, USA; Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA; Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California Los Angeles, Los Angeles, CA, USA; UCLA Neuro-Oncology Program, University of California, Los Angeles, Los Angeles, CA, USA; Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA.
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7
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Hagiwara A, Tatekawa H, Yao J, Raymond C, Everson R, Patel K, Mareninov S, Yong WH, Salamon N, Pope WB, Nghiemphu PL, Liau LM, Cloughesy TF, Ellingson BM. Visualization of tumor heterogeneity and prediction of isocitrate dehydrogenase mutation status for human gliomas using multiparametric physiologic and metabolic MRI. Sci Rep 2022; 12:1078. [PMID: 35058510 PMCID: PMC8776874 DOI: 10.1038/s41598-022-05077-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Accepted: 12/10/2021] [Indexed: 01/19/2023] Open
Abstract
This study aimed to differentiate isocitrate dehydrogenase (IDH) mutation status with the voxel-wise clustering method of multiparametric magnetic resonance imaging (MRI) and to discover biological underpinnings of the clusters. A total of 69 patients with treatment-naïve diffuse glioma were scanned with pH-sensitive amine chemical exchange saturation transfer MRI, diffusion-weighted imaging, fluid-attenuated inversion recovery, and contrast-enhanced T1-weighted imaging at 3 T. An unsupervised two-level clustering approach was used for feature extraction from acquired images. The logarithmic ratio of the labels in each class within tumor regions was applied to a support vector machine to differentiate IDH status. The highest performance to predict IDH mutation status was found for 10-class clustering, with a mean area under the curve, accuracy, sensitivity, and specificity of 0.94, 0.91, 0.90, and 0.91, respectively. Targeted biopsies revealed that the tissues with labels 7-10 showed high expression levels of hypoxia-inducible factor 1-alpha, glucose transporter 3, and hexokinase 2, which are typical of IDH wild-type glioma, whereas those with labels 1 showed low expression of these proteins. In conclusion, A machine learning model successfully predicted the IDH mutation status of gliomas, and the resulting clusters properly reflected the metabolic status of the tumors.
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Affiliation(s)
- Akifumi Hagiwara
- grid.19006.3e0000 0000 9632 6718UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, 924 Westwood Blvd., Suite 615, Los Angeles, CA 90024 USA ,grid.19006.3e0000 0000 9632 6718Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA USA ,grid.258269.20000 0004 1762 2738Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan
| | - Hiroyuki Tatekawa
- grid.19006.3e0000 0000 9632 6718UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, 924 Westwood Blvd., Suite 615, Los Angeles, CA 90024 USA ,grid.19006.3e0000 0000 9632 6718Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA USA ,grid.261445.00000 0001 1009 6411Department of Diagnostic and Interventional Radiology, Osaka City University Graduate School of Medicine, Osaka, Japan
| | - Jingwen Yao
- grid.19006.3e0000 0000 9632 6718UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, 924 Westwood Blvd., Suite 615, Los Angeles, CA 90024 USA ,grid.19006.3e0000 0000 9632 6718Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA USA ,grid.19006.3e0000 0000 9632 6718Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California Los Angeles, Los Angeles, CA USA
| | - Catalina Raymond
- grid.19006.3e0000 0000 9632 6718UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, 924 Westwood Blvd., Suite 615, Los Angeles, CA 90024 USA ,grid.19006.3e0000 0000 9632 6718Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA USA
| | - Richard Everson
- grid.19006.3e0000 0000 9632 6718Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA USA
| | - Kunal Patel
- grid.19006.3e0000 0000 9632 6718Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA USA
| | - Sergey Mareninov
- grid.19006.3e0000 0000 9632 6718Department of Pathology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA USA
| | - William H. Yong
- grid.19006.3e0000 0000 9632 6718Department of Pathology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA USA
| | - Noriko Salamon
- grid.19006.3e0000 0000 9632 6718Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA USA
| | - Whitney B. Pope
- grid.19006.3e0000 0000 9632 6718Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA USA
| | - Phioanh L. Nghiemphu
- grid.19006.3e0000 0000 9632 6718UCLA Neuro-Oncology Program, University of California, Los Angeles, Los Angeles, CA USA ,grid.19006.3e0000 0000 9632 6718Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA USA
| | - Linda M. Liau
- grid.19006.3e0000 0000 9632 6718Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA USA
| | - Timothy F. Cloughesy
- grid.19006.3e0000 0000 9632 6718UCLA Neuro-Oncology Program, University of California, Los Angeles, Los Angeles, CA USA ,grid.19006.3e0000 0000 9632 6718Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA USA
| | - Benjamin M. Ellingson
- grid.19006.3e0000 0000 9632 6718UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, 924 Westwood Blvd., Suite 615, Los Angeles, CA 90024 USA ,grid.19006.3e0000 0000 9632 6718Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA USA ,grid.19006.3e0000 0000 9632 6718Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California Los Angeles, Los Angeles, CA USA ,grid.19006.3e0000 0000 9632 6718UCLA Neuro-Oncology Program, University of California, Los Angeles, Los Angeles, CA USA ,grid.19006.3e0000 0000 9632 6718Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA USA
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8
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Ellingson BM, Wen PY, Cloughesy TF. Therapeutic Response Assessment of High-Grade Gliomas During Early-Phase Drug Development in the Era of Molecular and Immunotherapies. Cancer J 2021; 27:395-403. [PMID: 34570454 PMCID: PMC8480435 DOI: 10.1097/ppo.0000000000000543] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
ABSTRACT Several new therapeutic strategies have emerged over the past decades to address unmet clinical needs in high-grade gliomas, including targeted molecular agents and various forms of immunotherapy. Each of these strategies requires addressing fundamental questions, depending on the stage of drug development, including ensuring drug penetration into the brain, engagement of the drug with the desired target, biologic effects downstream from the target including metabolic and/or physiologic changes, and identifying evidence of clinical activity that could be expanded upon to increase the likelihood of a meaningful survival benefit. The current review article highlights these strategies and outlines how imaging technology can be used for therapeutic response evaluation in both targeted and immunotherapies in early phases of drug development in high-grade gliomas.
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Affiliation(s)
- Benjamin M. Ellingson
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA
| | - Patrick Y. Wen
- Center for Neuro-Oncology, Dana-Farber Cancer Institute, Harvard University, Boston, MA
| | - Timothy F. Cloughesy
- UCLA Neuro Oncology Program, Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA
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9
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Akbari H, Kazerooni AF, Ware JB, Mamourian E, Anderson H, Guiry S, Sako C, Raymond C, Yao J, Brem S, O'Rourke DM, Desai AS, Bagley SJ, Ellingson BM, Davatzikos C, Nabavizadeh A. Quantification of tumor microenvironment acidity in glioblastoma using principal component analysis of dynamic susceptibility contrast enhanced MR imaging. Sci Rep 2021; 11:15011. [PMID: 34294864 PMCID: PMC8298590 DOI: 10.1038/s41598-021-94560-3] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2021] [Accepted: 06/28/2021] [Indexed: 11/22/2022] Open
Abstract
Glioblastoma (GBM) has high metabolic demands, which can lead to acidification of the tumor microenvironment. We hypothesize that a machine learning model built on temporal principal component analysis (PCA) of dynamic susceptibility contrast-enhanced (DSC) perfusion MRI can be used to estimate tumor acidity in GBM, as estimated by pH-sensitive amine chemical exchange saturation transfer echo-planar imaging (CEST-EPI). We analyzed 78 MRI scans in 32 treatment naïve and post-treatment GBM patients. All patients were imaged with DSC-MRI, and pH-weighting that was quantified from CEST-EPI estimation of the magnetization transfer ratio asymmetry (MTRasym) at 3 ppm. Enhancing tumor (ET), non-enhancing core (NC), and peritumoral T2 hyperintensity (namely, edema, ED) were used to extract principal components (PCs) and to build support vector machines regression (SVR) models to predict MTRasym values using PCs. Our predicted map correlated with MTRasym values with Spearman's r equal to 0.66, 0.47, 0.67, 0.71, in NC, ET, ED, and overall, respectively (p < 0.006). The results of this study demonstrates that PCA analysis of DSC imaging data can provide information about tumor pH in GBM patients, with the strongest association within the peritumoral regions.
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Affiliation(s)
- Hamed Akbari
- Department of Radiology, Perelman School of Medicine, Hospital of University of Pennsylvania, University of Pennsylvania, Philadelphia, PA, USA
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Anahita Fathi Kazerooni
- Department of Radiology, Perelman School of Medicine, Hospital of University of Pennsylvania, University of Pennsylvania, Philadelphia, PA, USA
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Jeffrey B Ware
- Department of Radiology, Perelman School of Medicine, Hospital of University of Pennsylvania, University of Pennsylvania, Philadelphia, PA, USA
| | - Elizabeth Mamourian
- Department of Radiology, Perelman School of Medicine, Hospital of University of Pennsylvania, University of Pennsylvania, Philadelphia, PA, USA
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Hannah Anderson
- Department of Radiology, Perelman School of Medicine, Hospital of University of Pennsylvania, University of Pennsylvania, Philadelphia, PA, USA
| | - Samantha Guiry
- Department of Radiology, Perelman School of Medicine, Hospital of University of Pennsylvania, University of Pennsylvania, Philadelphia, PA, USA
| | - Chiharu Sako
- Department of Radiology, Perelman School of Medicine, Hospital of University of Pennsylvania, University of Pennsylvania, Philadelphia, PA, USA
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Catalina Raymond
- UCLA Brain Tumor Imaging Laboratory, Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Jingwen Yao
- UCLA Brain Tumor Imaging Laboratory, Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Steven Brem
- Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Donald M O'Rourke
- Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Arati S Desai
- Division of Hematology-Oncology, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Stephen J Bagley
- Division of Hematology-Oncology, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Benjamin M Ellingson
- UCLA Brain Tumor Imaging Laboratory, Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Christos Davatzikos
- Department of Radiology, Perelman School of Medicine, Hospital of University of Pennsylvania, University of Pennsylvania, Philadelphia, PA, USA
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Ali Nabavizadeh
- Department of Radiology, Perelman School of Medicine, Hospital of University of Pennsylvania, University of Pennsylvania, Philadelphia, PA, USA.
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10
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Yao J, Wang C, Raymond C, Bergstrom B, Chen X, Das K, Dinh H, Kim ZS, Le AN, Lim MWJ, Pham JAN, Prusan JD, Rao SS, Nathanson DA, Ellingson BM. A physical phantom for amine chemical exchange saturation transfer (CEST) MRI. MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE 2021; 34:569-580. [PMID: 33484366 DOI: 10.1007/s10334-020-00902-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/24/2020] [Revised: 11/13/2020] [Accepted: 12/09/2020] [Indexed: 11/26/2022]
Abstract
OBJECTIVE To develop a robust amine chemical exchange saturation transfer (CEST) physical phantom, validate the temporal stability, and create a supporting software for automatic image processing and quality assurance. MATERIALS AND METHODS The phantom was designed as an assembled laser-cut acrylic rack and 18 vials of phantom solutions, prepared with different pHs, glycine concentrations, and gadolinium concentrations. We evaluated glycine concentrations using ultraviolet absorbance for 70 days and measured the pH, relaxation rates, and CEST contrast for 94 days after preparation. We used Spearman's correlation to determine if glycine degraded over time. Linear regression and Bland-Altman analysis were performed between baseline and follow-up measurements of pH and MRI properties. RESULTS No degradation of glycine was observed (p > 0.05). The pH and MRI measurements stayed stable for 3 months and showed high consistency across time points (R2 = 1.00 for pH, R1, R2, and CEST contrast), which was further validated by the Bland-Altman plots. Examples of automatically generated reports are provided. DISCUSSION We designed a physical phantom for amine CEST-MRI, which is easy to assemble and transfer, holds 18 different solutions, and has excellent short-term chemical and MRI stability. We believe this robust phantom will facilitate the development of novel sequences and cross-scanners validations.
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Affiliation(s)
- Jingwen Yao
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, CA, USA
- Departments of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, 924 Westwood Blvd., Suite 615, Los Angeles, CA, 90024, USA
- Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California, Los Angeles, Los Angeles, CA, USA
| | - Chencai Wang
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, CA, USA
- Departments of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, 924 Westwood Blvd., Suite 615, Los Angeles, CA, 90024, USA
| | - Catalina Raymond
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, CA, USA
- Departments of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, 924 Westwood Blvd., Suite 615, Los Angeles, CA, 90024, USA
| | - Blake Bergstrom
- Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California, Los Angeles, Los Angeles, CA, USA
| | - Xing Chen
- Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California, Los Angeles, Los Angeles, CA, USA
| | - Kaveri Das
- Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Bioengineering Innovation and Design, Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Huy Dinh
- Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California, Los Angeles, Los Angeles, CA, USA
| | - Zoe S Kim
- Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California, Los Angeles, Los Angeles, CA, USA
| | - Angela N Le
- Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California, Los Angeles, Los Angeles, CA, USA
| | - Matthew W J Lim
- Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California, Los Angeles, Los Angeles, CA, USA
| | - Jane A N Pham
- Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California, Los Angeles, Los Angeles, CA, USA
| | - Joseph D Prusan
- Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California, Los Angeles, Los Angeles, CA, USA
| | - Sriram S Rao
- Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California, Los Angeles, Los Angeles, CA, USA
| | - David A Nathanson
- Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Benjamin M Ellingson
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, CA, USA.
- Departments of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, 924 Westwood Blvd., Suite 615, Los Angeles, CA, 90024, USA.
- Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California, Los Angeles, Los Angeles, CA, USA.
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11
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Yao J, Chakhoyan A, Nathanson DA, Yong WH, Salamon N, Raymond C, Mareninov S, Lai A, Nghiemphu PL, Prins RM, Pope WB, Everson RG, Liau LM, Cloughesy TF, Ellingson BM. Metabolic characterization of human IDH mutant and wild type gliomas using simultaneous pH- and oxygen-sensitive molecular MRI. Neuro Oncol 2020; 21:1184-1196. [PMID: 31066901 DOI: 10.1093/neuonc/noz078] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Isocitrate dehydrogenase 1 (IDH1) mutant gliomas are thought to have distinct metabolic characteristics, including a blunted response to hypoxia and lower glycolytic flux. We hypothesized that non-invasive quantification of abnormal metabolic behavior in human IDH1 mutant gliomas could be performed using a new pH- and oxygen-sensitive molecular MRI technique. METHODS Simultaneous pH- and oxygen-sensitive MRI was obtained at 3T using amine CEST-SAGE-EPI. The pH-dependent measure of the magnetization transfer ratio asymmetry (MTRasym) at 3 ppm and oxygen-sensitive measure of R2' were quantified in 90 patients with gliomas. Additionally, stereotactic, image-guided biopsies were performed in 20 patients for a total of 52 samples. The association between imaging measurements and hypoxia-inducible factor 1 alpha (HIF1α) expression was identified using Pearson correlation analysis. RESULTS IDH1 mutant gliomas exhibited significantly lower MTRasym at 3 ppm, R2', and MTRasymxR2' (P = 0.007, P = 0.003, and P = 0.001, respectively). MTRasymxR2' could identify IDH1 mutant gliomas with a high sensitivity (81.0%) and specificity (81.3%). HIF1α was positively correlated with MTRasym at 3 ppm, R2' and MTRasymxR2' in IDH1 wild type (r = 0.610, P = 0.003; r = 0.667, P = 0.008; r = 0.635, P = 0.006), but only MTRasymxR2' in IDH1 mutant gliomas (r = 0.727, P = 0.039). CONCLUSIONS IDH1 mutant gliomas have distinct metabolic and microenvironment characteristics compared with wild type gliomas. An imaging biomarker combining tumor acidity and hypoxia (MTRasymxR2') can differentiate IDH1 mutation status and is correlated with tumor acidity and hypoxia.
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Affiliation(s)
- Jingwen Yao
- UCLA Brain Tumor Imaging Laboratory, Center for Computer Vision and Imaging Biomarkers, University of California Los Angeles, Los Angeles, California.,Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California.,Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California Los Angeles, Los Angeles, California
| | - Ararat Chakhoyan
- UCLA Brain Tumor Imaging Laboratory, Center for Computer Vision and Imaging Biomarkers, University of California Los Angeles, Los Angeles, California.,Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California
| | - David A Nathanson
- Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California
| | - William H Yong
- Department of Pathology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California
| | - Noriko Salamon
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California
| | - Catalina Raymond
- UCLA Brain Tumor Imaging Laboratory, Center for Computer Vision and Imaging Biomarkers, University of California Los Angeles, Los Angeles, California.,Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California
| | - Sergey Mareninov
- Department of Pathology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California
| | - Albert Lai
- UCLA Neuro-Oncology Program, University of California Los Angeles, Los Angeles, California.,Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California
| | - Phioanh L Nghiemphu
- UCLA Neuro-Oncology Program, University of California Los Angeles, Los Angeles, California.,Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California
| | - Robert M Prins
- Department of Neurosurgery, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California
| | - Whitney B Pope
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California
| | - Richard G Everson
- Department of Neurosurgery, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California
| | - Linda M Liau
- Department of Neurosurgery, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California
| | - Timothy F Cloughesy
- UCLA Neuro-Oncology Program, University of California Los Angeles, Los Angeles, California.,Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California
| | - Benjamin M Ellingson
- UCLA Brain Tumor Imaging Laboratory, Center for Computer Vision and Imaging Biomarkers, University of California Los Angeles, Los Angeles, California.,Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California.,Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California Los Angeles, Los Angeles, California.,UCLA Neuro-Oncology Program, University of California Los Angeles, Los Angeles, California
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12
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Yao J, Wang C, Ellingson BM. Influence of phosphate concentration on amine, amide, and hydroxyl CEST contrast. Magn Reson Med 2020; 85:1062-1078. [PMID: 32936483 DOI: 10.1002/mrm.28481] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2020] [Revised: 07/24/2020] [Accepted: 07/27/2020] [Indexed: 12/11/2022]
Abstract
PURPOSE To evaluate the influence of phosphate on amine, amide, and hydroxyl CEST contrast using Bloch-McConnell simulations applied to physical phantom data. METHODS Phantom solutions of 4 representative metabolites with exchangeable protons-glycine (α-amine protons), Cr (η-amine protons), egg white protein (amide protons), and glucose (hydroxyl protons)-were prepared at different pH levels (5.6 to 8.9) and phosphate concentrations (5 to 80 mM). CEST images of the phantom were collected with CEST-EPI sequence at 3 tesla. The CEST data were then fitted to full Bloch-McConnell equation simulations to estimate the exchange rate constants. With the fitted parameters, simulations were performed to evaluate the intracellular and extracellular contributions of CEST signals in normal brain tissue and brain tumors, as well as in dynamic glucose-enhanced experiments. RESULTS The exchange rates of α-amine and hydroxyl protons were found to be highly dependent on both pH and phosphate concentrations, whereas the exchange rates of η-amine and amide protons were pH-dependent, albeit not catalyzed by phosphate. With phosphate being predominantly intracellular, CEST contrast of α-amine exhibited a higher sensitivity to changes in the extracellular microenvironment. Simulations of dynamic glucose-enhanced signals demonstrated that the contrast between normal and tumor tissue was mostly due to the extracellular CEST effect. CONCLUSION The proton exchange rates in some metabolites can be greatly catalyzed by the presence of phosphate at physiological concentrations, which substantially alters the CEST contrast. Catalytic agents should be considered as confounding factors in future CEST-MRI research. This new dimension may also benefit the development of novel phosphate-sensitive imaging methods.
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Affiliation(s)
- Jingwen Yao
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, California, USA.,Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA.,Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California, Los Angeles, Los Angeles, California, USA
| | - Chencai Wang
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, California, USA.,Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
| | - Benjamin M Ellingson
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, California, USA.,Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA.,Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California, Los Angeles, Los Angeles, California, USA.,Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
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Human IDH mutant 1p/19q co-deleted gliomas have low tumor acidity as evidenced by molecular MRI and PET: a retrospective study. Sci Rep 2020; 10:11922. [PMID: 32681084 PMCID: PMC7367867 DOI: 10.1038/s41598-020-68733-5] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2020] [Accepted: 06/01/2020] [Indexed: 01/19/2023] Open
Abstract
Co-deletion of 1p/19q is a hallmark of oligodendroglioma and predicts better survival. However, little is understood about its metabolic characteristics. In this study, we aimed to explore the extracellular acidity of WHO grade II and III gliomas associated with 1p/19q co-deletion. We included 76 glioma patients who received amine chemical exchange saturation transfer (CEST) imaging at 3 T. Magnetic transfer ratio asymmetry (MTRasym) at 3.0 ppm was used as the pH-sensitive CEST biomarker, with higher MTRasym indicating lower pH. To control for the confounder factors, T2 relaxometry and l-6-18F-fluoro-3,4-dihydroxyphenylalnine (18F-FDOPA) PET data were collected in a subset of patients. We found a significantly lower MTRasym in 1p/19q co-deleted gliomas (co-deleted, 1.17% ± 0.32%; non-co-deleted, 1.72% ± 0.41%, P = 1.13 × 10−7), while FDOPA (P = 0.92) and T2 (P = 0.61) were not significantly affected. Receiver operating characteristic analysis confirmed that MTRasym could discriminate co-deletion status with an area under the curve of 0.85. In analysis of covariance, 1p/19q co-deletion status was the only significant contributor to the variability in MTRasym when controlling for age and FDOPA (P = 2.91 × 10−3) or T2 (P = 8.03 × 10−6). In conclusion, 1p/19q co-deleted gliomas were less acidic, which may be related to better prognosis. Amine CEST-MRI may serve as a non-invasive biomarker for identifying 1p/19q co-deletion status.
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Wang YL, Yao J, Chakhoyan A, Raymond C, Salamon N, Liau LM, Nghiemphu PL, Lai A, Pope WB, Nguyen N, Ji M, Cloughesy TF, Ellingson BM. Association between Tumor Acidity and Hypervascularity in Human Gliomas Using pH-Weighted Amine Chemical Exchange Saturation Transfer Echo-Planar Imaging and Dynamic Susceptibility Contrast Perfusion MRI at 3T. AJNR Am J Neuroradiol 2019; 40:979-986. [PMID: 31097430 DOI: 10.3174/ajnr.a6063] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2018] [Accepted: 04/10/2019] [Indexed: 01/15/2023]
Abstract
BACKGROUND AND PURPOSE Acidification of the tumor microenvironment from abnormal metabolism along with angiogenesis to meet metabolic demands are both hallmarks of malignant brain tumors; however, the interdependency of tumor acidity and vascularity has not been explored. Therefore, our aim was to investigate the association between pH-sensitive amine chemical exchange saturation transfer echoplanar imaging (CEST-EPI) and relative cerebral blood volume (CBV) measurements obtained from dynamic susceptibility contrast (DSC) perfusion MRI in patients with gliomas. MATERIALS AND METHODS In this retrospective study, 90 patients with histologically confirmed gliomas were scanned between 2015 and 2018 (median age, 50.3 years; male/female ratio = 59:31). pH-weighting was obtained using chemical exchange saturation transfer echo-planar imaging estimation of the magnetization transfer ratio asymmetry at 3 ppm, and CBV was estimated using DSC-MR imaging. The voxelwise correlation and patient-wise median value correlation between the magnetization transfer ratio asymmetry at 3 ppm and CBV within T2-hyperintense lesions and contrast-enhancing lesions were evaluated using the Pearson correlation analysis. RESULTS General colocalization of elevated perfusion and high acidity was observed in tumors, with local intratumor heterogeneity. For patient-wise analysis, median CBV and magnetization transfer ratio asymmetry at 3 ppm within T2-hyperintense lesions were significantly correlated (R = 0.3180, P = .002), but not in areas of contrast enhancement (P = .52). The positive correlation in T2-hyperintense lesions remained within high-grade gliomas (R = 0.4128, P = .001) and in isocitrate dehydrogenase wild-type gliomas (R = 0.4300, P = .002), but not in World Health Organization II or in isocitrate dehydrogenase mutant tumors. Both magnetization transfer ratio asymmetry at 3 ppm and the voxelwise correlation between magnetization transfer ratio asymmetry and CBV were higher in high-grade gliomas compared with low-grade gliomas in T2-hyperintense tumors (magnetization transfer ratio asymmetry, P = .02; Pearson correlation, P = .01). The same trend held when comparing isocitrate dehydrogenase wild-type gliomas and isocitrate dehydrogenase mutant gliomas (magnetization transfer ratio asymmetry, P = .04; Pearson correlation, P = .01). CONCLUSIONS A positive linear correlation between CBV and acidity in areas of T2-hyperintense, nonenhancing tumor, but not enhancing tumor, was observed across patients. Local heterogeneity was observed within individual tumors.
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Affiliation(s)
- Y-L Wang
- From the UCLA Brain Tumor Imaging Laboratory (Y.-L.W., J.Y., A.C., C.R., B.M.E.).,Department of Radiology (Y.-L.W.), People's Liberation Army General Hospital, Beijing, China
| | - J Yao
- From the UCLA Brain Tumor Imaging Laboratory (Y.-L.W., J.Y., A.C., C.R., B.M.E.).,Center for Computer Vision and Imaging Biomarkers, Department of Radiological Sciences (J.Y., A.C., C.R., N.S., W.B.P., B.M.E.).,Department of Bioengineering (J.Y., B.M.E.), Henry Samueli School of Engineering and Applied Science, University of California, Los Angeles, Los Angeles, California
| | - A Chakhoyan
- From the UCLA Brain Tumor Imaging Laboratory (Y.-L.W., J.Y., A.C., C.R., B.M.E.).,Center for Computer Vision and Imaging Biomarkers, Department of Radiological Sciences (J.Y., A.C., C.R., N.S., W.B.P., B.M.E.)
| | - C Raymond
- From the UCLA Brain Tumor Imaging Laboratory (Y.-L.W., J.Y., A.C., C.R., B.M.E.).,Center for Computer Vision and Imaging Biomarkers, Department of Radiological Sciences (J.Y., A.C., C.R., N.S., W.B.P., B.M.E.)
| | - N Salamon
- Center for Computer Vision and Imaging Biomarkers, Department of Radiological Sciences (J.Y., A.C., C.R., N.S., W.B.P., B.M.E.)
| | - L M Liau
- UCLA Brain Research Institute (L.M.L., A.L., B.M.E.).,Department of Neurosurgery (L.M.L.), David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California
| | - P L Nghiemphu
- Department of Neurology (P.L.N., A.L., N.N., M.J., T.F.C.)
| | - A Lai
- Department of Neurology (P.L.N., A.L., N.N., M.J., T.F.C.).,UCLA Brain Research Institute (L.M.L., A.L., B.M.E.)
| | - W B Pope
- Center for Computer Vision and Imaging Biomarkers, Department of Radiological Sciences (J.Y., A.C., C.R., N.S., W.B.P., B.M.E.)
| | - N Nguyen
- Department of Neurology (P.L.N., A.L., N.N., M.J., T.F.C.)
| | - M Ji
- Department of Neurology (P.L.N., A.L., N.N., M.J., T.F.C.)
| | - T F Cloughesy
- Department of Neurology (P.L.N., A.L., N.N., M.J., T.F.C.)
| | - B M Ellingson
- From the UCLA Brain Tumor Imaging Laboratory (Y.-L.W., J.Y., A.C., C.R., B.M.E.) .,Center for Computer Vision and Imaging Biomarkers, Department of Radiological Sciences (J.Y., A.C., C.R., N.S., W.B.P., B.M.E.).,Physics and Biology in Medicine (B.M.E.).,Department of Psychiatry and Biobehavioral Sciences (B.M.E.).,UCLA Brain Research Institute (L.M.L., A.L., B.M.E.).,Department of Bioengineering (J.Y., B.M.E.), Henry Samueli School of Engineering and Applied Science, University of California, Los Angeles, Los Angeles, California
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pH-weighted amine chemical exchange saturation transfer echoplanar imaging (CEST-EPI) as a potential early biomarker for bevacizumab failure in recurrent glioblastoma. J Neurooncol 2019; 142:587-595. [PMID: 30806888 DOI: 10.1007/s11060-019-03132-z] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2019] [Accepted: 02/21/2019] [Indexed: 11/27/2022]
Abstract
PURPOSE The objective of the current study was to explore the efficacy of using pH-weighted amine CEST-EPI as a potential non-invasive imaging biomarker for treatment response and/or failure in recurrent GBM patients treated with bevacizumab. METHOD A total of 11 patients with recurrent GBM treated with bevacizumab were included in this prospective study. CEST-EPI, perfusion MRI, and standardized anatomic MRI were obtained in patients before and after bevacizumab administration. CEST-EPI measures of magnetization transfer ratio asymmetry (MTRasym) at 3 ppm were used for pH-weighted imaging contrast. Multiple measures were examined for their association with progression-free survival (PFS). RESULT Tumor acidity, measured with MTRasym at 3 ppm, was significantly reduced in both contrast enhancing and non-enhancing tumor after bevacizumab (p = 0.0002 and p < 0.00001, respectively). The reduction in tumor acidity in both contrast enhancing and non-enhancing tumor was linearly correlated with PFS (p = 0.044 and p = 0.00026, respectively). In 9 of the 11 patients, areas of residual acidity were localized to areas of tumor recurrence, typically around 2 months prior to radiographic progression. Univariate (p = 0.006) and multivariate Cox regression controlling for age (p = 0.009) both indicated that change in tumor acidity (ΔMTRasym at 3 ppm) was a significant predictor of PFS. CONCLUSIONS This pilot study suggests pH-weighted amine CEST MRI may have value as a non-invasive, early imaging biomarker for bevacizumab treatment response and failure. Early decreases MTRasym at 3.0 ppm in recurrent GBM after bevacizumab may be associated with better PFS. Residual or emerging regions of acidity may colocalize to the site of tumor recurrence.
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Ellingson BM, Yao J, Raymond C, Chakhoyan A, Khatibi K, Salamon N, Villablanca JP, Wanner I, Real CR, Laiwalla A, McArthur DL, Monti MM, Hovda DA, Vespa PM. pH-weighted molecular MRI in human traumatic brain injury (TBI) using amine proton chemical exchange saturation transfer echoplanar imaging (CEST EPI). Neuroimage Clin 2019; 22:101736. [PMID: 30826686 PMCID: PMC6396390 DOI: 10.1016/j.nicl.2019.101736] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2018] [Revised: 01/09/2019] [Accepted: 02/24/2019] [Indexed: 12/28/2022]
Abstract
Cerebral acidosis is a consequence of secondary injury mechanisms following traumatic brain injury (TBI), including excitotoxicity and ischemia, with potentially significant clinical implications. However, there remains an unmet clinical need for technology for non-invasive, high resolution pH imaging of human TBI for studying metabolic changes following injury. The current study examined 17 patients with TBI and 20 healthy controls using amine chemical exchange saturation transfer echoplanar imaging (CEST EPI), a novel pH-weighted molecular MR imaging technique, on a clinical 3T MR scanner. Results showed significantly elevated pH-weighted image contrast (MTRasym at 3 ppm) in areas of T2 hyperintensity or edema (P < 0.0001), and a strong negative correlation with Glasgow Coma Scale (GCS) at the time of the MRI exam (R2 = 0.4777, P = 0.0021), Glasgow Outcome Scale - Extended (GOSE) at 6 months from injury (R2 = 0.5334, P = 0.0107), and a non-linear correlation with the time from injury to MRI exam (R2 = 0.6317, P = 0.0004). This evidence suggests clinical feasibility and potential value of pH-weighted amine CEST EPI as a high-resolution imaging tool for identifying tissue most at risk for long-term damage due to cerebral acidosis.
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Affiliation(s)
- Benjamin M Ellingson
- UCLA Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA; Dept. of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA.
| | - Jingwen Yao
- UCLA Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA; Dept. of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California Los Angeles, Los Angeles, CA, USA
| | - Catalina Raymond
- UCLA Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA; Dept. of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Ararat Chakhoyan
- UCLA Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA; Dept. of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Kasra Khatibi
- Dept. of Neurosurgery, UCLA Brain Injury Research Center, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Noriko Salamon
- Dept. of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - J Pablo Villablanca
- Dept. of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Ina Wanner
- Dept. of Neurosurgery, UCLA Brain Injury Research Center, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Courtney R Real
- Dept. of Neurosurgery, UCLA Brain Injury Research Center, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Azim Laiwalla
- Dept. of Neurosurgery, UCLA Brain Injury Research Center, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - David L McArthur
- Dept. of Neurosurgery, UCLA Brain Injury Research Center, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Martin M Monti
- Dept. of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA; Dept. of Neurosurgery, UCLA Brain Injury Research Center, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - David A Hovda
- Dept. of Neurosurgery, UCLA Brain Injury Research Center, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Paul M Vespa
- Dept. of Neurosurgery, UCLA Brain Injury Research Center, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
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