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Schneider KL, Hao X, Keuenhof KS, Berglund LL, Fischbach A, Ahmadpour D, Chawla S, Gómez P, Höög JL, Widlund PO, Nyström T. Elimination of virus-like particles reduces protein aggregation and extends replicative lifespan in Saccharomyces cerevisiae. Proc Natl Acad Sci U S A 2024; 121:e2313538121. [PMID: 38527193 PMCID: PMC10998562 DOI: 10.1073/pnas.2313538121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Accepted: 02/04/2024] [Indexed: 03/27/2024] Open
Abstract
A major consequence of aging and stress, in yeast to humans, is an increased accumulation of protein aggregates at distinct sites within the cells. Using genetic screens, immunoelectron microscopy, and three-dimensional modeling in our efforts to elucidate the importance of aggregate annexation, we found that most aggregates in yeast accumulate near the surface of mitochondria. Further, we show that virus-like particles (VLPs), which are part of the retrotransposition cycle of Ty elements, are markedly enriched in these sites of protein aggregation. RNA interference-mediated silencing of Ty expression perturbed aggregate sequestration to mitochondria, reduced overall protein aggregation, mitigated toxicity of a Huntington's disease model, and expanded the replicative lifespan of yeast in a partially Hsp104-dependent manner. The results are in line with recent data demonstrating that VLPs might act as aging factors in mammals, including humans, and extend these findings by linking VLPs to a toxic accumulation of protein aggregates and raising the possibility that they might negatively influence neurological disease progression.
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Affiliation(s)
- K. L. Schneider
- Department of Microbiology and Immunology, Institute for Biomedicine, Sahlgrenska Academy, Centre for Ageing and Health—AgeCap, University of Gothenburg, Gothenburg40530, Sweden
| | - X. Hao
- Department of Microbiology and Immunology, Institute for Biomedicine, Sahlgrenska Academy, Centre for Ageing and Health—AgeCap, University of Gothenburg, Gothenburg40530, Sweden
| | - K. S. Keuenhof
- Department for Chemistry and Molecular Biology, University of Gothenburg, Gothenburg41390, Sweden
| | - L. L. Berglund
- Department for Chemistry and Molecular Biology, University of Gothenburg, Gothenburg41390, Sweden
| | - A. Fischbach
- Department of Microbiology and Immunology, Institute for Biomedicine, Sahlgrenska Academy, Centre for Ageing and Health—AgeCap, University of Gothenburg, Gothenburg40530, Sweden
| | - D. Ahmadpour
- Department of Microbiology and Immunology, Institute for Biomedicine, Sahlgrenska Academy, Centre for Ageing and Health—AgeCap, University of Gothenburg, Gothenburg40530, Sweden
| | - S. Chawla
- Department of Microbiology and Immunology, Institute for Biomedicine, Sahlgrenska Academy, Centre for Ageing and Health—AgeCap, University of Gothenburg, Gothenburg40530, Sweden
| | - P. Gómez
- Department of Microbiology and Immunology, Institute for Biomedicine, Sahlgrenska Academy, Centre for Ageing and Health—AgeCap, University of Gothenburg, Gothenburg40530, Sweden
| | - J. L. Höög
- Department for Chemistry and Molecular Biology, University of Gothenburg, Gothenburg41390, Sweden
| | - P. O. Widlund
- Department of Microbiology and Immunology, Institute for Biomedicine, Sahlgrenska Academy, Centre for Ageing and Health—AgeCap, University of Gothenburg, Gothenburg40530, Sweden
| | - T. Nyström
- Department of Microbiology and Immunology, Institute for Biomedicine, Sahlgrenska Academy, Centre for Ageing and Health—AgeCap, University of Gothenburg, Gothenburg40530, Sweden
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Giuraniuc CV, Parkin C, Almeida MC, Fricker M, Shadmani P, Nye S, Wehmeier S, Chawla S, Bedekovic T, Lehtovirta-Morley L, Richards DM, Gow NA, Brand AC. Dynamic calcium-mediated stress response and recovery signatures in the fungal pathogen, Candida albicans. mBio 2023; 14:e0115723. [PMID: 37750683 PMCID: PMC10653887 DOI: 10.1128/mbio.01157-23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Accepted: 08/07/2023] [Indexed: 09/27/2023] Open
Abstract
IMPORTANCE Intracellular calcium signaling plays an important role in the resistance and adaptation to stresses encountered by fungal pathogens within the host. This study reports the optimization of the GCaMP fluorescent calcium reporter for live-cell imaging of dynamic calcium responses in single cells of the pathogen, Candida albicans, for the first time. Exposure to membrane, osmotic or oxidative stress generated both specific changes in single cell intracellular calcium spiking and longer calcium transients across the population. Repeated treatments showed that calcium dynamics become unaffected by some stresses but not others, consistent with known cell adaptation mechanisms. By expressing GCaMP in mutant strains and tracking the viability of individual cells over time, the relative contributions of key signaling pathways to calcium flux, stress adaptation, and cell death were demonstrated. This reporter, therefore, permits the study of calcium dynamics, homeostasis, and signaling in C. albicans at a previously unattainable level of detail.
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Affiliation(s)
- C. V. Giuraniuc
- School of Medicine, Medical Sciences & Nutrition, University of Aberdeen, Aberdeen, United Kingdom
| | - C. Parkin
- MRC Centre for Medical Mycology at the University of Exeter, Exeter, United Kingdom
| | - M. C. Almeida
- School of Medicine, Medical Sciences & Nutrition, University of Aberdeen, Aberdeen, United Kingdom
| | - M. Fricker
- School of Plant Sciences, University of Oxford, Oxford, United Kingdom
| | - P. Shadmani
- Living Systems Institute, University of Exeter, Exeter, United Kingdom
| | - S. Nye
- Living Systems Institute, University of Exeter, Exeter, United Kingdom
| | - S. Wehmeier
- School of Medicine, Medical Sciences & Nutrition, University of Aberdeen, Aberdeen, United Kingdom
| | - S. Chawla
- School of Medicine, Medical Sciences & Nutrition, University of Aberdeen, Aberdeen, United Kingdom
| | - T. Bedekovic
- School of Medicine, Medical Sciences & Nutrition, University of Aberdeen, Aberdeen, United Kingdom
- MRC Centre for Medical Mycology at the University of Exeter, Exeter, United Kingdom
| | - L. Lehtovirta-Morley
- School of Medicine, Medical Sciences & Nutrition, University of Aberdeen, Aberdeen, United Kingdom
| | - D. M. Richards
- Living Systems Institute, University of Exeter, Exeter, United Kingdom
- Department of Physics and Astronomy, University of Exeter, Exeter, United Kingdom
| | - N. A. Gow
- School of Medicine, Medical Sciences & Nutrition, University of Aberdeen, Aberdeen, United Kingdom
- MRC Centre for Medical Mycology at the University of Exeter, Exeter, United Kingdom
| | - A. C. Brand
- School of Medicine, Medical Sciences & Nutrition, University of Aberdeen, Aberdeen, United Kingdom
- MRC Centre for Medical Mycology at the University of Exeter, Exeter, United Kingdom
- Living Systems Institute, University of Exeter, Exeter, United Kingdom
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de Godoy LL, Lim KC, Rajan A, Verma G, Hanaoka M, O’Rourke DM, Lee JYK, Desai A, Chawla S, Mohan S. Non-Invasive Assessment of Isocitrate Dehydrogenase-Mutant Gliomas Using Optimized Proton Magnetic Resonance Spectroscopy on a Routine Clinical 3-Tesla MRI. Cancers (Basel) 2023; 15:4453. [PMID: 37760422 PMCID: PMC10526791 DOI: 10.3390/cancers15184453] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2023] [Revised: 08/22/2023] [Accepted: 08/31/2023] [Indexed: 09/29/2023] Open
Abstract
PURPOSE The isocitrate dehydrogenase (IDH) mutation has become one of the most important prognostic biomarkers in glioma management, indicating better treatment response and prognosis. IDH mutations confer neomorphic activity leading to the conversion of alpha-ketoglutarate (α-KG) to 2-hydroxyglutarate (2HG). The purpose of this study was to investigate the clinical potential of proton MR spectroscopy (1H-MRS) in identifying IDH-mutant gliomas by detecting characteristic resonances of 2HG and its complex interplay with other clinically relevant metabolites. MATERIALS AND METHODS Thirty-two patients with suspected infiltrative glioma underwent a single-voxel (SVS, n = 17) and/or single-slice-multivoxel (1H-MRSI, n = 15) proton MR spectroscopy (1H-MRS) sequence with an optimized echo-time (97 ms) on 3T-MRI. Spectroscopy data were analyzed using the linear combination (LC) model. Cramér-Rao lower bound (CRLB) values of <40% were considered acceptable for detecting 2HG and <20% for other metabolites. Immunohistochemical analyses for determining IDH mutational status were subsequently performed from resected tumor specimens and findings were compared with the results from spectral data. Mann-Whitney and chi-squared tests were performed to ascertain differences in metabolite levels between IDH-mutant and IDH-wild-type gliomas. Receiver operating characteristic (ROC) curve analyses were also performed. RESULTS Data from eight cases were excluded due to poor spectral quality or non-tumor-related etiology, and final data analyses were performed from 24 cases. Of these cases, 9/12 (75%) were correctly identified as IDH-mutant or IDH-wildtype gliomas through SVS and 10/12 (83%) through 1H-MRSI with an overall concordance rate of 79% (19/24). The sensitivity, specificity, positive predictive value, and negative predictive value were 80%, 77%, 86%, and 70%, respectively. The metabolite 2HG was found to be significant in predicting IDH-mutant gliomas through the chi-squared test (p < 0.01). The IDH-mutant gliomas also had a significantly higher NAA/Cr ratio (1.20 ± 0.09 vs. 0.75 ± 0.12 p = 0.016) and lower Glx/Cr ratio (0.86 ± 0.078 vs. 1.88 ± 0.66; p = 0.029) than those with IDH wild-type gliomas. The areas under the ROC curves for NAA/Cr and Glx/Cr were 0.808 and 0.786, respectively. CONCLUSIONS Noninvasive optimized 1H-MRS may be useful in predicting IDH mutational status and 2HG may serve as a valuable diagnostic and prognostic biomarker in patients with gliomas.
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Affiliation(s)
- Laiz Laura de Godoy
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19104, USA; (L.L.d.G.); (A.R.); (M.H.); (S.M.)
| | - Kheng Choon Lim
- Department of Neuroradiology, Singapore General Hospital, Singapore 169609, Singapore;
| | - Archith Rajan
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19104, USA; (L.L.d.G.); (A.R.); (M.H.); (S.M.)
| | - Gaurav Verma
- Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA;
| | - Mauro Hanaoka
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19104, USA; (L.L.d.G.); (A.R.); (M.H.); (S.M.)
| | - Donald M. O’Rourke
- Department of Neurosurgery, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19104, USA; (D.M.O.); (J.Y.K.L.)
- Abramson Cancer Center, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19104, USA;
- Glioblastoma Translational Center of Excellence, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19014, USA
| | - John Y. K. Lee
- Department of Neurosurgery, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19104, USA; (D.M.O.); (J.Y.K.L.)
- Abramson Cancer Center, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19104, USA;
- Glioblastoma Translational Center of Excellence, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19014, USA
| | - Arati Desai
- Abramson Cancer Center, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19104, USA;
- Glioblastoma Translational Center of Excellence, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19014, USA
| | - Sanjeev Chawla
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19104, USA; (L.L.d.G.); (A.R.); (M.H.); (S.M.)
| | - Suyash Mohan
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19104, USA; (L.L.d.G.); (A.R.); (M.H.); (S.M.)
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de Godoy LL, Chawla S, Brem S, Mohan S. Taming Glioblastoma in "Real Time": Integrating Multimodal Advanced Neuroimaging/AI Tools Towards Creating a Robust and Therapy Agnostic Model for Response Assessment in Neuro-Oncology. Clin Cancer Res 2023; 29:2588-2592. [PMID: 37227179 DOI: 10.1158/1078-0432.ccr-23-0009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2023] [Revised: 03/20/2023] [Accepted: 05/04/2023] [Indexed: 05/10/2023]
Abstract
The highly aggressive nature of glioblastoma carries a dismal prognosis despite aggressive multimodal therapy. Alternative treatment regimens, such as immunotherapies, are known to intensify the inflammatory response in the treatment field. Follow-up imaging in these scenarios often mimics disease progression on conventional MRI, making accurate evaluation extremely challenging. To this end, revised criteria for assessment of treatment response in high-grade gliomas were successfully proposed by the RANO Working Group to distinguish pseudoprogression from true progression, with intrinsic constraints related to the postcontrast T1-weighted MRI sequence. To address these existing limitations, our group proposes a more objective and quantifiable "treatment agnostic" model, integrating into the RANO criteria advanced multimodal neuroimaging techniques, such as diffusion tensor imaging (DTI), dynamic susceptibility contrast-perfusion weighted imaging (DSC-PWI), dynamic contrast enhanced (DCE)-MRI, MR spectroscopy, and amino acid-based positron emission tomography (PET) imaging tracers, along with artificial intelligence (AI) tools (radiomics, radiogenomics, and radiopathomics) and molecular information to address this complex issue of treatment-related changes versus tumor progression in "real-time", particularly in the early posttreatment window. Our perspective delineates the potential of incorporating multimodal neuroimaging techniques to improve consistency and automation for the assessment of early treatment response in neuro-oncology.
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Affiliation(s)
- Laiz Laura de Godoy
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania
| | - Sanjeev Chawla
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania
| | - Steven Brem
- Department of Neurosurgery, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania
- Abramson Cancer Center, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania
- Glioblastoma Translational Center of Excellence, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania
| | - Suyash Mohan
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania
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5
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de Godoy LL, Chawla S, Brem S, Wang S, O'Rourke DM, Nasrallah MP, Desai A, Loevner LA, Liau LM, Mohan S. Assessment of treatment response to dendritic cell vaccine in patients with glioblastoma using a multiparametric MRI-based prediction model. J Neurooncol 2023; 163:173-183. [PMID: 37129737 DOI: 10.1007/s11060-023-04324-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Accepted: 04/24/2023] [Indexed: 05/03/2023]
Abstract
PURPOSE Autologous tumor lysate-loaded dendritic cell vaccine (DCVax-L) is a promising treatment modality for glioblastomas. The purpose of this study was to investigate the potential utility of multiparametric MRI-based prediction model in evaluating treatment response in glioblastoma patients treated with DCVax-L. METHODS Seventeen glioblastoma patients treated with standard-of-care therapy + DCVax-L were included. When tumor progression (TP) was suspected and repeat surgery was being contemplated, we sought to ascertain the number of cases correctly classified as TP + mixed response or pseudoprogression (PsP) from multiparametric MRI-based prediction model using histopathology/mRANO criteria as ground truth. Multiparametric MRI model consisted of predictive probabilities (PP) of tumor progression computed from diffusion and perfusion MRI-derived parameters. A comparison of overall survival (OS) was performed between patients treated with standard-of-care therapy + DCVax-L and standard-of-care therapy alone (external controls). Additionally, Kaplan-Meier analyses were performed to compare OS between two groups of patients using PsP, Ki-67, and MGMT promoter methylation status as stratification variables. RESULTS Multiparametric MRI model correctly predicted TP + mixed response in 72.7% of cases (8/11) and PsP in 83.3% (5/6) with an overall concordance rate of 76.5% with final diagnosis as determined by histopathology/mRANO criteria. There was a significant concordant correlation coefficient between PP values and histopathology/mRANO criteria (r = 0.54; p = 0.026). DCVax-L-treated patients had significantly prolonged OS than those treated with standard-of-care therapy (22.38 ± 12.8 vs. 13.8 ± 9.5 months, p = 0.040). Additionally, glioblastomas with PsP, MGMT promoter methylation status, and Ki-67 values below median had longer OS than their counterparts. CONCLUSION Multiparametric MRI-based prediction model can assess treatment response to DCVax-L in patients with glioblastoma.
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Affiliation(s)
- Laiz Laura de Godoy
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Sanjeev Chawla
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA.
| | - Steven Brem
- Department of Neurosurgery, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
- Abramson Cancer Center, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
- Glioblastoma Translational Center of Excellence, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Sumei Wang
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Donald M O'Rourke
- Department of Neurosurgery, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
- Abramson Cancer Center, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
- Glioblastoma Translational Center of Excellence, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - MacLean P Nasrallah
- Glioblastoma Translational Center of Excellence, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
- Clinical Pathology and Laboratory Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Arati Desai
- Abramson Cancer Center, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
- Glioblastoma Translational Center of Excellence, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Laurie A Loevner
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Linda M Liau
- Department of Neurosurgery, University of California Los Angeles David Geffen School of Medicine & Jonsson Comprehensive Cancer Center, Los Angeles, CA, USA
| | - Suyash Mohan
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
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de Godoy LL, Mohan S, Wang S, Nasrallah MP, Sakai Y, O'Rourke DM, Bagley S, Desai A, Loevner LA, Poptani H, Chawla S. Validation of multiparametric MRI based prediction model in identification of pseudoprogression in glioblastomas. J Transl Med 2023; 21:287. [PMID: 37118754 PMCID: PMC10142504 DOI: 10.1186/s12967-023-03941-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2022] [Accepted: 01/30/2023] [Indexed: 04/30/2023] Open
Abstract
BACKGROUND Accurate differentiation of pseudoprogression (PsP) from tumor progression (TP) in glioblastomas (GBMs) is essential for appropriate clinical management and prognostication of these patients. In the present study, we sought to validate the findings of our previously developed multiparametric MRI model in a new cohort of GBM patients treated with standard therapy in identifying PsP cases. METHODS Fifty-six GBM patients demonstrating enhancing lesions within 6 months after completion of concurrent chemo-radiotherapy (CCRT) underwent anatomical imaging, diffusion and perfusion MRI on a 3 T magnet. Subsequently, patients were classified as TP + mixed tumor (n = 37) and PsP (n = 19). When tumor specimens were available from repeat surgery, histopathologic findings were used to identify TP + mixed tumor (> 25% malignant features; n = 34) or PsP (< 25% malignant features; n = 16). In case of non-availability of tumor specimens, ≥ 2 consecutive conventional MRIs using mRANO criteria were used to determine TP + mixed tumor (n = 3) or PsP (n = 3). The multiparametric MRI-based prediction model consisted of predictive probabilities (PP) of tumor progression computed from diffusion and perfusion MRI derived parameters from contrast enhancing regions. In the next step, PP values were used to characterize each lesion as PsP or TP+ mixed tumor. The lesions were considered as PsP if the PP value was < 50% and TP+ mixed tumor if the PP value was ≥ 50%. Pearson test was used to determine the concordance correlation coefficient between PP values and histopathology/mRANO criteria. The area under ROC curve (AUC) was used as a quantitative measure for assessing the discriminatory accuracy of the prediction model in identifying PsP and TP+ mixed tumor. RESULTS Multiparametric MRI model correctly predicted PsP in 95% (18/19) and TP+ mixed tumor in 57% of cases (21/37) with an overall concordance rate of 70% (39/56) with final diagnosis as determined by histopathology/mRANO criteria. There was a significant concordant correlation coefficient between PP values and histopathology/mRANO criteria (r = 0.56; p < 0.001). The ROC analyses revealed an accuracy of 75.7% in distinguishing PsP from TP+ mixed tumor. Leave-one-out cross-validation test revealed that 73.2% of cases were correctly classified as PsP and TP + mixed tumor. CONCLUSIONS Our multiparametric MRI based prediction model may be helpful in identifying PsP in GBM patients.
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Affiliation(s)
- Laiz Laura de Godoy
- Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Suyash Mohan
- Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Sumei Wang
- Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - MacLean P Nasrallah
- Clinical Pathology and Laboratory Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Yu Sakai
- Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Donald M O'Rourke
- Neurosurgery, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Stephen Bagley
- Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Arati Desai
- Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Laurie A Loevner
- Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Harish Poptani
- Molecular and Clinical Cancer Medicine, University of Liverpool, Liverpool, UK
| | - Sanjeev Chawla
- Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA.
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Tadepalli M, Chhaparwal A, Chawla S, Srivastava S, Dao T, Chhaparwal A, Naren S, Sathyamurthy S, Mukkavilli S, Putha P, Reddy B, Vo L, Warrier P. PP01.59 Performance of a Deep Learning Algorithm for the Early Detection of Malignant Lung Nodules. J Thorac Oncol 2023. [DOI: 10.1016/j.jtho.2022.09.085] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/30/2023]
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Hosseini SA, Hosseini E, Hajianfar G, Shiri I, Servaes S, Rosa-Neto P, Godoy L, Nasrallah MP, O’Rourke DM, Mohan S, Chawla S. MRI-Based Radiomics Combined with Deep Learning for Distinguishing IDH-Mutant WHO Grade 4 Astrocytomas from IDH-Wild-Type Glioblastomas. Cancers (Basel) 2023; 15:cancers15030951. [PMID: 36765908 PMCID: PMC9913426 DOI: 10.3390/cancers15030951] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2023] [Revised: 01/30/2023] [Accepted: 01/30/2023] [Indexed: 02/05/2023] Open
Abstract
This study aimed to investigate the potential of quantitative radiomic data extracted from conventional MR images in discriminating IDH-mutant grade 4 astrocytomas from IDH-wild-type glioblastomas (GBMs). A cohort of 57 treatment-naïve patients with IDH-mutant grade 4 astrocytomas (n = 23) and IDH-wild-type GBMs (n = 34) underwent anatomical imaging on a 3T MR system with standard parameters. Post-contrast T1-weighted and T2-FLAIR images were co-registered. A semi-automatic segmentation approach was used to generate regions of interest (ROIs) from different tissue components of neoplasms. A total of 1050 radiomic features were extracted from each image. The data were split randomly into training and testing sets. A deep learning-based data augmentation method (CTGAN) was implemented to synthesize 200 datasets from the training sets. A total of 18 classifiers were used to distinguish two genotypes of grade 4 astrocytomas. From generated data using 80% training set, the best discriminatory power was obtained from core tumor regions overlaid on post-contrast T1 using the K-best feature selection algorithm and a Gaussian naïve Bayes classifier (AUC = 0.93, accuracy = 0.92, sensitivity = 1, specificity = 0.86, PR_AUC = 0.92). Similarly, high diagnostic performances were obtained from original and generated data using 50% and 30% training sets. Our findings suggest that conventional MR imaging-based radiomic features combined with machine/deep learning methods may be valuable in discriminating IDH-mutant grade 4 astrocytomas from IDH-wild-type GBMs.
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Affiliation(s)
- Seyyed Ali Hosseini
- Translational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, Douglas Hospital, McGill University, Montréal, QC H4H 1R3, Canada
- Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montréal, QC H3A 2B4, Canada
- Correspondence: (S.A.H.); (S.C.); Tel.: +1-438-929-6575 (S.A.H.); +1-215-615-1662 (S.C.)
| | - Elahe Hosseini
- Department of Electrical and Computer Engineering, Kharazmi University, Tehran 15719-14911, Iran
| | - Ghasem Hajianfar
- Rajaie Cardiovascular Medical and Research Center, Iran University of Medical Science, Tehran 19956-14331, Iran
| | - Isaac Shiri
- Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, CH-1211 Geneva, Switzerland
| | - Stijn Servaes
- Translational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, Douglas Hospital, McGill University, Montréal, QC H4H 1R3, Canada
- Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montréal, QC H3A 2B4, Canada
| | - Pedro Rosa-Neto
- Translational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, Douglas Hospital, McGill University, Montréal, QC H4H 1R3, Canada
- Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montréal, QC H3A 2B4, Canada
| | - Laiz Godoy
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19104, USA
| | - MacLean P. Nasrallah
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Donald M. O’Rourke
- Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Suyash Mohan
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Sanjeev Chawla
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19104, USA
- Correspondence: (S.A.H.); (S.C.); Tel.: +1-438-929-6575 (S.A.H.); +1-215-615-1662 (S.C.)
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Shin SS, Chawla S, Jang DH, Mazandi VM, Weeks MK, Kilbaugh TJ. Imaging of White Matter Injury Correlates with Plasma and Tissue Biomarkers in Pediatric Porcine Model of Traumatic Brain Injury. J Neurotrauma 2023; 40:74-85. [PMID: 35876453 PMCID: PMC9917326 DOI: 10.1089/neu.2022.0178] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2023] Open
Abstract
Traumatic brain injury (TBI) causes significant white matter injury, which has been characterized by various rodent and human clinical studies. The exact time course of imaging changes in a pediatric brain after TBI and its relation to biomarkers of injury and cellular function, however, is unknown. To study the changes in major white matter structures using a valid model of TBI that is comparable to a human pediatric brain in terms of size and anatomical features, we utilized a four-week-old pediatric porcine model of injury with controlled cortical impact (CCI). Using diffusion tensor imaging differential tractography, we show progressive anisotropy changes at major white matter tracts such as the corona radiata and inferior fronto-occipital fasciculus between day 1 and day 30 after injury. Moreover, correlational tractography shows a large part of bilateral corona radiata having positive correlation with the markers of cellular respiration. In contrast, bilateral corona radiata has a negative correlation with the plasma biomarkers of injury such as neurofilament light or glial fibrillary acidic protein. These are expected correlational findings given that higher integrity of white matter would be expected to correlate with lower injury biomarkers. We then studied the magnetic resonance spectroscopy findings and report decrease in a N-acetylaspartate/creatinine (NAA/Cr) ratio at the pericontusional cortex, subcortical white matter, corona radiata, thalamus, genu, and splenium of corpus callosum at 30 days indicating injury. There was also an increase in choline/creatinine ratio in these regions indicating rapid membrane turnover. Given the need for a pediatric TBI model that is comparable to human pediatric TBI, these data support the use of a pediatric pig model with CCI in future investigations of therapeutic agents. This model will allow future TBI researchers to rapidly translate our pre-clinical study findings into clinical trials for pediatric TBI.
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Affiliation(s)
- Samuel S. Shin
- Division of Neurocritical Care, Department of Neurology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Sanjeev Chawla
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - David H. Jang
- Department of Emergency Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Vanessa M. Mazandi
- Department of Anesthesiology and Critical Care Medicine, The Children's Hospital of Philadelphia, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - M. Katie Weeks
- Department of Anesthesiology and Critical Care Medicine, The Children's Hospital of Philadelphia, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Todd J. Kilbaugh
- Department of Anesthesiology and Critical Care Medicine, The Children's Hospital of Philadelphia, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA
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10
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Romeo V, Stanzione A, Ugga L, Cuocolo R, Cocozza S, Quarantelli M, Chawla S, Farina D, Golay X, Parker G, Shukla-Dave A, Thoeny H, Vidiri A, Brunetti A, Surlan-Popovic K, Bisdas S. Clinical indications and acquisition protocol for the use of dynamic contrast-enhanced MRI in head and neck cancer squamous cell carcinoma: recommendations from an expert panel. Insights Imaging 2022; 13:198. [PMID: 36528678 PMCID: PMC9759606 DOI: 10.1186/s13244-022-01317-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Accepted: 10/19/2022] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND The clinical role of perfusion-weighted MRI (PWI) in head and neck squamous cell carcinoma (HNSCC) remains to be defined. The aim of this study was to provide evidence-based recommendations for the use of PWI sequence in HNSCC with regard to clinical indications and acquisition parameters. METHODS Public databases were searched, and selected papers evaluated applying the Oxford criteria 2011. A questionnaire was prepared including statements on clinical indications of PWI as well as its acquisition technique and submitted to selected panelists who worked in anonymity using a modified Delphi approach. Each panelist was asked to rate each statement using a 7-point Likert scale (1 = strongly disagree, 7 = strongly agree). Statements with scores equal or inferior to 5 assigned by at least two panelists were revised and re-submitted for the subsequent Delphi round to reach a final consensus. RESULTS Two Delphi rounds were conducted. The final questionnaire consisted of 6 statements on clinical indications of PWI and 9 statements on the acquisition technique of PWI. Four of 19 (21%) statements obtained scores equal or inferior to 5 by two panelists, all dealing with clinical indications. The Delphi process was considered concluded as reasons entered by panelists for lower scores were mainly related to the lack of robust evidence, so that no further modifications were suggested. CONCLUSIONS Evidence-based recommendations on the use of PWI have been provided by an independent panel of experts worldwide, encouraging a standardized use of PWI across university and research centers to produce more robust evidence.
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Affiliation(s)
- Valeria Romeo
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Naples, Italy
| | - Arnaldo Stanzione
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Naples, Italy
| | - Lorenzo Ugga
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Naples, Italy
| | - Renato Cuocolo
- Department of Clinical Medicine and Surgery, University of Naples "Federico II", Naples, Italy.,Interdepartmental Research Center on Management and Innovation in Healthcare - CIRMIS, University of Naples Federico II, Naples, Italy
| | - Sirio Cocozza
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Naples, Italy
| | - Mario Quarantelli
- Biostructure and Bioimaging Institute, National Research Council, Naples, Italy
| | - Sanjeev Chawla
- Department of Radiology, Perelman School of Medicine, the University of Pennsylvania, Philadelphia, PA, USA
| | - Davide Farina
- Department of Medical and Surgical Specialties, Radiological Sciences, and Public Health, University of Brescia, Brescia, Italy
| | - Xavier Golay
- Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, University College London, London, UK.,Lysholm Department of Neuroradiology, The National Hospital for Neurology and Neurosurgery, University College Hospitals NHS Trust, London, UK
| | - Geoff Parker
- Department of Computer Science, Centre for Medical Image Computing, Queen Square Institute of Neurology, University College London, London, UK
| | - Amita Shukla-Dave
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA.,Departments of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Harriet Thoeny
- Department of Radiology, Cantonal Hospital Fribourg, University of Fribourg, Fribourg, Switzerland
| | - Antonello Vidiri
- Department of Radiology and Diagnostic Imaging, IRCCS Regina Elena National Cancer Institute, Rome, Italy
| | - Arturo Brunetti
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Naples, Italy
| | | | - Sotirios Bisdas
- Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, University College London, London, UK. .,Lysholm Department of Neuroradiology, The National Hospital for Neurology and Neurosurgery, University College Hospitals NHS Trust, London, UK.
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11
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de Godoy LL, Chen YJ, Chawla S, Viaene AN, Wang S, Loevner LA, Alonso-Basanta M, Poptani H, Mohan S. Prognostication of overall survival in patients with brain metastases using diffusion tensor imaging and dynamic susceptibility contrast-enhanced MRI. Br J Radiol 2022; 95:20220516. [PMID: 36354164 PMCID: PMC9733614 DOI: 10.1259/bjr.20220516] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Revised: 08/23/2022] [Accepted: 09/30/2022] [Indexed: 11/11/2022] Open
Abstract
OBJECTIVES To investigate the prognostic utility of DTI and DSC-PWI perfusion-derived parameters in brain metastases patients. METHODS Retrospective analyses of DTI-derived parameters (MD, FA, CL, CP, and CS) and DSC-perfusion PWI-derived rCBVmax from 101 patients diagnosed with brain metastases prior to treatment were performed. Using semi-automated segmentation, DTI metrics and rCBVmax were quantified from enhancing areas of the dominant metastatic lesion. For each metric, patients were classified as short- and long-term survivors based on analysis of the best coefficient for each parameter and percentile to separate the groups. Kaplan-Meier analysis was used to compare mOS between these groups. Multivariate survival analysis was subsequently conducted. A correlative histopathologic analysis was performed in a subcohort (n = 10) with DTI metrics and rCBVmax on opposite ends of the spectrum. RESULTS Significant differences in mOS were observed for MDmin (p < 0.05), FA (p < 0.01), CL (p < 0.05), and CP (p < 0.01) and trend toward significance for rCBVmax (p = 0.07) between the two risk groups, in the univariate analysis. On multivariate analysis, the best predictive survival model was comprised of MDmin (p = 0.05), rCBVmax (p < 0.05), RPA (p < 0.0001), and number of lesions (p = 0.07). On histopathology, metastatic tumors showed significant differences in the amount of stroma depending on the combination of DTI metrics and rCBVmax values. Patients with high stromal content demonstrated poorer mOS. CONCLUSION Pretreatment DTI-derived parameters, notably MDmin and rCBVmax, are promising imaging markers for prognostication of OS in patients with brain metastases. Stromal cellularity may be a contributing factor to these differences. ADVANCES IN KNOWLEDGE The correlation of DTI-derived metrics and perfusion MRI with patient outcomes has not been investigated in patients with treatment naïve brain metastasis. DTI and DSC-PWI can aid in therapeutic decision-making by providing additional clinical guidance.
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Affiliation(s)
- Laiz Laura de Godoy
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, United States
| | - Yin Jie Chen
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, United States
| | - Sanjeev Chawla
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, United States
| | - Angela N Viaene
- Division of Anatomic Pathology, Children’s Hospital of Philadelphia, Philadelphia, United States
| | - Sumei Wang
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, United States
| | - Laurie A Loevner
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, United States
| | - Michelle Alonso-Basanta
- Department of Radiation Oncology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, United States
| | - Harish Poptani
- Department of Molecular and Clinical Cancer Medicine, University of Liverpool, Liverpool, United Kingdom
| | - Suyash Mohan
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, United States
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12
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Chawla S, Verma G, Reddy Nanga RP, Mohan S, Poptani H. Emerging metabolic imaging and spectroscopic methods to study neurodegenerative diseases. Veins and Lymphatics 2022. [DOI: 10.4081/vl.2022.10946] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Abstract
Proton magnetic resonance spectroscopy (1H-MRS) allows non-invasive assessment of the metabolic landscape of biological tissue. Despite demonstrating promising findings in clinical practice, single-voxel or single-slice two-dimensional 1H-MRS methods present a few challenges mainly related to limited spatial coverage and low spatial and spectral resolutions. In the recent past, the advent of more sophisticated metabolic imaging and spectroscopic sequences, such as three-dimensional echoplanar spectroscopic imaging (3D-EPSI), two-dimensional correlation spectroscopy (2D-COSY), and chemical exchange saturation technique (CEST) has revolutionized the field of metabolomics. For the metabolic characterization of diffused neurodegenerative diseases, whole brain coverage is essential for a comprehensive overview of the topography and understanding of the underlying pathophysiological processes. The 3D-EPSI sequence allows the acquisition of whole brain (volumetric) metabolite maps with high spatial resolution.1 These metabolite maps can be co-registered to anatomical images for facilitating the mapping of metabolite alterations from different brain regions in a single session, thus providing the true spatial extent of a global disease. The potential of 3D‐EPSI in characterizing several neurological and neurodegenerative disorders has been reported. On conventional one-dimensional 1H-MRS, spectral peaks due to methyl, methylene, and methine protons from N-acetyl aspartate, glutamate, glutamine, gamma-aminobutyric acid, and taurine extensively overlap in the spectral region of 2-4 ppm, often confounding the reliable detection and quantification of these metabolites. In contrast, 2D-COSY offers unambiguous identification of potentially overlapping resonances by dispersing the multiplet structure of scalar (J)-coupled spin systems into a second spectral dimension,2 especially at higher field strength3,4 and by exploiting the unlikely possibility that two metabolites would share identical chemical shifts in two-dimensions. Due to technical limitations and long acquisition time, 2D-COSY sequence has not been widely used to study neurodegenerative diseases. However, future modifications would benefit from implementing faster acquisition schemes and improved spectral fitting methods for data analysis. We believe that these new approaches could make the clinical applications of the 2D-COSY sequence faster, easier, and more versatile. CEST is a relatively novel metabolic imaging modality that allows the detection of specific exogenous and endogenous metabolites/molecules present at millimolar concentrations. Exchangeable solute protons present in chemical functional groups such as amide (-CONH), amine (-NH2) or hydroxyl (-OH) resonate at a frequency different from bulk water protons. These labile protons are selectively saturated using radiofrequency irradiation, which is subsequently transferred to the bulk water pool, leading to a decrease in the water signal intensity proportional to the concentration of solute molecules, number of labile protons and proton exchange rate.5 CEST offers more than two orders of magnitude higher sensitivity compared to 1H-MRS in detecting metabolites such as glutamate, creatine, myoinositol and mobile peptides.5 While amide proton transfer (APT) imaging has been investigated in various neurological disorders, other CEST imaging techniques such as glutamate-CEST, creatine-CEST have been performed only in pre-clinical or pilot clinical studies related to neurodegenerative diseases. We believe that these newer developments in metabolic imaging techniques will have a significant impact in reshaping our understanding of biochemical profiles of various neurodegenerative diseases. However, standardization and harmonization of acquisition parameters are required for fast-tracking the implementation of these metabolic techniques into routine clinical workflow.
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13
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Chawla S, Loevner L, Mohan S, Lin A, Sehgal CM, Poptani H. Dynamic contrast-enhanced MRI and Doppler sonography in patients with squamous cell carcinoma of head and neck treated with induction chemotherapy. J Clin Ultrasound 2022; 50:1353-1359. [PMID: 36205388 DOI: 10.1002/jcu.23361] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Revised: 09/05/2022] [Accepted: 09/15/2022] [Indexed: 06/16/2023]
Abstract
In view of the inherent limitations associated with performing dynamic contrast enhanced-magnetic resonance imaging (DCE-MRI) in clinical settings, current study was designed to provide a proof of principle that Doppler sonography and DCE-MRI derived perfusion parameters yield similar hemodynamic information from metastatic lymph nodes in squamous cell carcinomas of head and neck (HNSCCs). Strong positive correlations between volume fraction of plasma space in tissues (Vp ) and blood volume (r = 0.72, p = 0.02) and between Vp and %area perfused (r = 0.65, p = 0.04) were observed. Additionally, a moderate positive correlation trending towards significance was obtained between volume transfer constant (Ktrans ) and %area perfused (r = 0.49, p = 0.09).
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Affiliation(s)
- Sanjeev Chawla
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Laurie Loevner
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Suyash Mohan
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Alexander Lin
- Department of Radiation Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Chandra M Sehgal
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Harish Poptani
- Department of Molecular and Clinical Cancer Medicine, University of Liverpool, Liverpool, UK
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14
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Jain V, de Godoy LL, Mohan S, Chawla S, Learned K, Jain G, Wehrli FW, Alonso-Basanta M. Cerebral hemodynamic and metabolic dysregulation in the postradiation brain. J Neuroimaging 2022; 32:1027-1043. [PMID: 36156829 DOI: 10.1111/jon.13053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Revised: 09/08/2022] [Accepted: 09/09/2022] [Indexed: 11/28/2022] Open
Abstract
Technological advances in the delivery of radiation and other novel cancer therapies have significantly improved the 5-year survival rates over the last few decades. Although recent developments have helped to better manage the acute effects of radiation, the late effects such as impairment in cognition continue to remain of concern. Accruing data in the literature have implicated derangements in hemodynamic parameters and metabolic activity of the irradiated normal brain as predictive of cognitive impairment. Multiparametric imaging modalities have allowed us to precisely quantify functional and metabolic information, enhancing the anatomic and morphologic data provided by conventional MRI sequences, thereby contributing as noninvasive imaging-based biomarkers of radiation-induced brain injury. In this review, we have elaborated on the mechanisms of radiation-induced brain injury and discussed several novel imaging modalities, including MR spectroscopy, MR perfusion imaging, functional MR, SPECT, and PET that provide pathophysiological and functional insights into the postradiation brain, and its correlation with radiation dose as well as clinical neurocognitive outcomes. Additionally, we explored some innovative imaging modalities, such as quantitative blood oxygenation level-dependent imaging, susceptibility-based oxygenation measurement, and T2-based oxygenation measurement, that hold promise in delineating the potential mechanisms underlying deleterious neurocognitive changes seen in the postradiation setting. We aim that this comprehensive review of a range of imaging modalities will help elucidate the hemodynamic and metabolic injury mechanisms underlying cognitive impairment in the irradiated normal brain in order to optimize treatment regimens and improve the quality of life for these patients.
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Affiliation(s)
- Varsha Jain
- Department of Radiation Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.,Department of Radiation Oncology, Jefferson University Hospital, 111 South 11th Street, Philadelphia, PA, 19107, USA
| | - Laiz Laura de Godoy
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Suyash Mohan
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Sanjeev Chawla
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Kim Learned
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Gaurav Jain
- Department of Neurological Surgery, Jefferson University Hospital, Philadelphia, Pennsylvania, USA
| | - Felix W Wehrli
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Michelle Alonso-Basanta
- Department of Radiation Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
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15
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Kutuk T, Walker J, Ballo M, Cameron R, Bustamante Alvarez J, Chawla S, Luk E, Behl D, Dal Pra A, Morganstein N, Refaat T, Sheybani A, Squillante C, Zhang J, Kotecha R. EP07.01-019 Multiinstitutional Patterns of Use and Compliance with Tumor Treating Fields for Patients with Unresectable Malignant Pleural Mesothelioma. J Thorac Oncol 2022. [DOI: 10.1016/j.jtho.2022.07.551] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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16
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Chawla S, Bukhari S, Afridi OM, Wang S, Yadav SK, Akbari H, Verma G, Nath K, Haris M, Bagley S, Davatzikos C, Loevner LA, Mohan S. Metabolic and physiologic magnetic resonance imaging in distinguishing true progression from pseudoprogression in patients with glioblastoma. NMR Biomed 2022; 35:e4719. [PMID: 35233862 PMCID: PMC9203929 DOI: 10.1002/nbm.4719] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/30/2020] [Revised: 02/22/2022] [Accepted: 02/25/2022] [Indexed: 05/15/2023]
Abstract
Pseudoprogression (PsP) refers to treatment-related clinico-radiologic changes mimicking true progression (TP) that occurs in patients with glioblastoma (GBM), predominantly within the first 6 months after the completion of surgery and concurrent chemoradiation therapy (CCRT) with temozolomide. Accurate differentiation of TP from PsP is essential for making informed decisions on appropriate therapeutic intervention as well as for prognostication of these patients. Conventional neuroimaging findings are often equivocal in distinguishing between TP and PsP and present a considerable diagnostic dilemma to oncologists and radiologists. These challenges have emphasized the need for developing alternative imaging techniques that may aid in the accurate diagnosis of TP and PsP. In this review, we encapsulate the current state of knowledge in the clinical applications of commonly used metabolic and physiologic magnetic resonance (MR) imaging techniques such as diffusion and perfusion imaging and proton spectroscopy in distinguishing TP from PsP. We also showcase the potential of promising imaging techniques, such as amide proton transfer and amino acid-based positron emission tomography, in providing useful information about the treatment response. Additionally, we highlight the role of "radiomics", which is an emerging field of radiology that has the potential to change the way in which advanced MR techniques are utilized in assessing treatment response in GBM patients. Finally, we present our institutional experiences and discuss future perspectives on the role of multiparametric MR imaging in identifying PsP in GBM patients treated with "standard-of-care" CCRT as well as novel/targeted therapies.
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Affiliation(s)
- Sanjeev Chawla
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Sultan Bukhari
- Rowan School of Osteopathic Medicine at Rowan University, Voorhees, New Jersey, USA
| | - Omar M. Afridi
- Rowan School of Osteopathic Medicine at Rowan University, Voorhees, New Jersey, USA
| | - Sumei Wang
- Department of Cardiology, Lenox Hill Hospital, Northwell Health, New York, New York, USA
| | - Santosh K. Yadav
- Laboratory of Functional and Molecular Imaging, Sidra Medicine, Doha, Qatar
| | - Hamed Akbari
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Gaurav Verma
- Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, USA
| | - Kavindra Nath
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Mohammad Haris
- Laboratory of Functional and Molecular Imaging, Sidra Medicine, Doha, Qatar
| | - Stephen Bagley
- Department of Hematology-Oncology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Christos Davatzikos
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Laurie A. Loevner
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Suyash Mohan
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA
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Kouli O, Murray V, Bhatia S, Cambridge WA, Kawka M, Shafi S, Knight SR, Kamarajah SK, McLean KA, Glasbey JC, Khaw RA, Ahmed W, Akhbari M, Baker D, Borakati A, Mills E, Thavayogan R, Yasin I, Raubenheimer K, Ridley W, Sarrami M, Zhang G, Egoroff N, Pockney P, Richards T, Bhangu A, Creagh-Brown B, Edwards M, Harrison EM, Lee M, Nepogodiev D, Pinkney T, Pearse R, Smart N, Vohra R, Sohrabi C, Jamieson A, Nguyen M, Rahman A, English C, Tincknell L, Kakodkar P, Kwek I, Punjabi N, Burns J, Varghese S, Erotocritou M, McGuckin S, Vayalapra S, Dominguez E, Moneim J, Salehi M, Tan HL, Yoong A, Zhu L, Seale B, Nowinka Z, Patel N, Chrisp B, Harris J, Maleyko I, Muneeb F, Gough M, James CE, Skan O, Chowdhury A, Rebuffa N, Khan H, Down B, Fatimah Hussain Q, Adams M, Bailey A, Cullen G, Fu YXJ, McClement B, Taylor A, Aitken S, Bachelet B, Brousse de Gersigny J, Chang C, Khehra B, Lahoud N, Lee Solano M, Louca M, Rozenbroek P, Rozitis E, Agbinya N, Anderson E, Arwi G, Barry I, Batchelor C, Chong T, Choo LY, Clark L, Daniels M, Goh J, Handa A, Hanna J, Huynh L, Jeon A, Kanbour A, Lee A, Lee J, Lee T, Leigh J, Ly D, McGregor F, Moss J, Nejatian M, O'Loughlin E, Ramos I, Sanchez B, Shrivathsa A, Sincari A, Sobhi S, Swart R, Trimboli J, Wignall P, Bourke E, Chong A, Clayton S, Dawson A, Hardy E, Iqbal R, Le L, Mao S, Marinelli I, Metcalfe H, Panicker D, R HH, Ridgway S, Tan HH, Thong S, Van M, Woon S, Woon-Shoo-Tong XS, Yu S, Ali K, Chee J, Chiu C, Chow YW, Duller A, Nagappan P, Ng S, Selvanathan M, Sheridan C, Temple M, Do JE, Dudi-Venkata NN, Humphries E, Li L, Mansour LT, Massy-Westropp C, Fang B, Farbood K, Hong H, Huang Y, Joan M, Koh C, Liu YHA, Mahajan T, Muller E, Park R, Tanudisastro M, Wu JJG, Chopra P, Giang S, Radcliffe S, Thach P, Wallace D, Wilkes A, Chinta SH, Li J, Phan J, Rahman F, Segaran A, Shannon J, Zhang M, Adams N, Bonte A, Choudhry A, Colterjohn N, Croyle JA, Donohue J, Feighery A, Keane A, McNamara D, Munir K, Roche D, Sabnani R, Seligman D, Sharma S, Stickney Z, Suchy H, Tan R, Yordi S, Ahmed I, Aranha M, El Sabawy D, Garwood P, Harnett M, Holohan R, Howard R, Kayyal Y, Krakoski N, Lupo M, McGilberry W, Nepon H, Scoleri Y, Urbina C, Ahmad Fuad MF, Ahmed O, Jaswantlal D, Kelly E, Khan MHT, Naidu D, Neo WX, O'Neill R, Sugrue M, Abbas JD, Abdul-Fattah S, Azlan A, Barry K, Idris NS, Kaka N, Mc Dermott D, Mohammad Nasir MN, Mozo M, Rehal A, Shaikh Yousef M, Wong RH, Curran E, Gardner M, Hogan A, Julka R, Lasser G, Ní Chorráin N, Ting J, Browne R, George S, Janjua Z, Leung Shing V, Megally M, Murphy S, Ravenscroft L, Vedadi A, Vyas V, Bryan A, Sheikh A, Ubhi J, Vannelli K, Vawda A, Adeusi L, Doherty C, Fitzgerald C, Gallagher H, Gill P, Hamza H, Hogan M, Kelly S, Larry J, Lynch P, Mazeni NA, O'Connell R, O'Loghlin R, Singh K, Abbas Syed R, Ali A, Alkandari B, Arnold A, Arora E, Azam R, Breathnach C, Cheema J, Compton M, Curran S, Elliott JA, Jayasamraj O, Mohammed N, Noone A, Pal A, Pandey S, Quinn P, Sheridan R, Siew L, Tan EP, Tio SW, Toh VTR, Walsh M, Yap C, Yassa J, Young T, Agarwal N, Almoosawy SA, Bowen K, Bruce D, Connachan R, Cook A, Daniell A, Elliott M, Fung HKF, Irving A, Laurie S, Lee YJ, Lim ZX, Maddineni S, McClenaghan RE, Muthuganesan V, Ravichandran P, Roberts N, Shaji S, Solt S, Toshney E, Arnold C, Baker O, Belais F, Bojanic C, Byrne M, Chau CYC, De Soysa S, Eldridge M, Fairey M, Fearnhead N, Guéroult A, Ho JSY, Joshi K, Kadiyala N, Khalid S, Khan F, Kumar K, Lewis E, Magee J, Manetta-Jones D, Mann S, McKeown L, Mitrofan C, Mohamed T, Monnickendam A, Ng AYKC, Ortu A, Patel M, Pope T, Pressling S, Purohit K, Saji S, Shah Foridi J, Shah R, Siddiqui SS, Surman K, Utukuri M, Varghese A, Williams CYK, Yang JJ, Billson E, Cheah E, Holmes P, Hussain S, Murdock D, Nicholls A, Patel P, Ramana G, Saleki M, Spence H, Thomas D, Yu C, Abousamra M, Brown C, Conti I, Donnelly A, Durand M, French N, Goan R, O'Kane E, Rubinchik P, Gardiner H, Kempf B, Lai YL, Matthews H, Minford E, Rafferty C, Reid C, Sheridan N, Al Bahri T, Bhoombla N, Rao BM, Titu L, Chatha S, Field C, Gandhi T, Gulati R, Jha R, Jones Sam MT, Karim S, Patel R, Saunders M, Sharma K, Abid S, Heath E, Kurup D, Patel A, Ali M, Cresswell B, Felstead D, Jennings K, Kaluarachchi T, Lazzereschi L, Mayson H, Miah JE, Reinders B, Rosser A, Thomas C, Williams H, Al-Hamid Z, Alsadoun L, Chlubek M, Fernando P, Gaunt E, Gercek Y, Maniar R, Ma R, Matson M, Moore S, Morris A, Nagappan PG, Ratnayake M, Rockall L, Shallcross O, Sinha A, Tan KE, Virdee S, Wenlock R, Donnelly HA, Ghazal R, Hughes I, Liu X, McFadden M, Misbert E, Mogey P, O'Hara A, Peace C, Rainey C, Raja P, Salem M, Salmon J, Tan CH, Alves D, Bahl S, Baker C, Coulthurst J, Koysombat K, Linn T, Rai P, Sharma A, Shergill A, Ahmed M, Ahmed S, Belk LH, Choudhry H, Cummings D, Dixon Y, Dobinson C, Edwards J, Flint J, Franco Da Silva C, Gallie R, Gardener M, Glover T, Greasley M, Hatab A, Howells R, Hussey T, Khan A, Mann A, Morrison H, Ng A, Osmond R, Padmakumar N, Pervaiz F, Prince R, Qureshi A, Sawhney R, Sigurdson B, Stephenson L, Vora K, Zacken A, Cope P, Di Traglia R, Ferarrio I, Hackett N, Healicon R, Horseman L, Lam LI, Meerdink M, Menham D, Murphy R, Nimmo I, Ramaesh A, Rees J, Soame R, Dilaver N, Adebambo D, Brown E, Burt J, Foster K, Kaliyappan L, Knight P, Politis A, Richardson E, Townsend J, Abdi M, Ball M, Easby S, Gill N, Ho E, Iqbal H, Matthews M, Nubi S, Nwokocha JO, Okafor I, Perry G, Sinartio B, Vanukuru N, Walkley D, Welch T, Yates J, Yeshitila N, Bryans K, Campbell B, Gray C, Keys R, Macartney M, Chamberlain G, Khatri A, Kucheria A, Lee STP, Reese G, Roy choudhury J, Tan WYR, Teh JJ, Ting A, Kazi S, Kontovounisios C, Vutipongsatorn K, Amarnath T, Balasubramanian N, Bassett E, Gurung P, Lim J, Panjikkaran A, Sanalla A, Alkoot M, Bacigalupo V, Eardley N, Horton M, Hurry A, Isti C, Maskell P, Nursiah K, Punn G, Salih H, Epanomeritakis E, Foulkes A, Henderson R, Johnston E, McCullough H, McLarnon M, Morrison E, Cheung A, Cho SH, Eriksson F, Hedges J, Low Z, May C, Musto L, Nagi S, Nur S, Salau E, Shabbir S, Thomas MC, Uthayanan L, Vig S, Zaheer M, Zeng G, Ashcroft-Quinn S, Brown R, Hayes J, McConville R, French R, Gilliam A, Sheetal S, Shehzad MU, Bani W, Christie I, Franklyn J, Khan M, Russell J, Smolarek S, Varadarassou R, Ahmed SK, Narayanaswamy S, Sealy J, Shah M, Dodhia V, Manukyan A, O'Hare R, Orbell J, Chung I, Forenc K, Gupta A, Agarwal A, Al Dabbagh A, Bennewith R, Bottomley J, Chu TSM, Chu YYA, Doherty W, Evans B, Hainsworth P, Hosfield T, Li CH, McCullagh I, Mehta A, Thaker A, Thompson B, Virdi A, Walker H, Wilkins E, Dixon C, Hassan MR, Lotca N, Tong KS, Batchelor-Parry H, Chaudhari S, Harris T, Hooper J, Johnson C, Mulvihill C, Nayler J, Olutobi O, Piramanayagam B, Stones K, Sussman M, Weaver C, Alam F, Al Rawi M, Andrew F, Arrayeh A, Azizan N, Hassan A, Iqbal Z, John I, Jones M, Kalake O, Keast M, Nicholas J, Patil A, Powell K, Roberts P, Sabri A, Segue AK, Shah A, Shaik Mohamed SA, Shehadeh A, Shenoy S, Tong A, Upcott M, Vijayasingam D, Anarfi S, Dauncey J, Devindaran A, Havalda P, Komninos G, Mwendwa E, Norman C, Richards J, Urquhart A, Allan J, Cahya E, Hunt H, McWhirter C, Norton R, Roxburgh C, Tan JY, Ali Butt S, Hansdot S, Haq I, Mootien A, Sanchez I, Vainas T, Deliyannis E, Tan M, Vipond M, Chittoor Satish NN, Dattani A, De Carvalho L, Gaston-Grubb M, Karunanithy L, Lowe B, Pace C, Raju K, Roope J, Taylor C, Youssef H, Munro T, Thorn C, Wong KHF, Yunus A, Chawla S, Datta A, Dinesh AA, Field D, Georgi T, Gwozdz A, Hamstead E, Howard N, Isleyen N, Jackson N, Kingdon J, Sagoo KS, Schizas A, Yin L, Aung E, Aung YY, Franklin S, Han SM, Kim WC, Martin Segura A, Rossi M, Ross T, Tirimanna R, Wang B, Zakieh O, Ben-Arzi H, Flach A, Jackson E, Magers S, Olu abara C, Rogers E, Sugden K, Tan H, Veliah S, Walton U, Asif A, Bharwada Y, Bowley D, Broekhuizen A, Cooper L, Evans N, Girdlestone H, Ling C, Mann H, Mehmood N, Mulvenna CL, Rainer N, Trout I, Gujjuri R, Jeyaraman D, Leong E, Singh D, Smith E, Anderton J, Barabas M, Goyal S, Howard D, Joshi A, Mitchell D, Weatherby T, Badminton R, Bird R, Burtle D, Choi NY, Devalia K, Farr E, Fischer F, Fish J, Gunn F, Jacobs D, Johnston P, Kalakoutas A, Lau E, Loo YNAF, Louden H, Makariou N, Mohammadi K, Nayab Y, Ruhomaun S, Ryliskyte R, Saeed M, Shinde P, Sudul M, Theodoropoulou K, Valadao-Spoorenberg J, Vlachou F, Arshad SR, Janmohamed AM, Noor M, Oyerinde O, Saha A, Syed Y, Watkinson W, Ahmadi H, Akintunde A, Alsaady A, Bradley J, Brothwood D, Burton M, Higgs M, Hoyle C, Katsura C, Lathan R, Louani A, Mandalia R, Prihartadi AS, Qaddoura B, Sandland-Taylor L, Thadani S, Thompson A, Walshaw J, Teo S, Ali S, Bawa JH, Fox S, Gargan K, Haider SA, Hanna N, Hatoum A, Khan Z, Krzak AM, Li T, Pitt J, Tan GJS, Ullah Z, Wilson E, Cleaver J, Colman J, Copeland L, Coulson A, Davis P, Faisal H, Hassan F, Hughes JT, Jabr Y, Mahmoud Ali F, Nahaboo Solim ZN, Sangheli A, Shaya S, Thompson R, Cornwall H, De Andres Crespo M, Fay E, Findlay J, Groves E, Jones O, Killen A, Millo J, Thomas S, Ward J, Wilkins M, Zaki F, Zilber E, Bhavra K, Bilolikar A, Charalambous M, Elawad A, Eleni A, Fawdon R, Gibbins A, Livingstone D, Mala D, Oke SE, Padmakumar D, Patsalides MA, Payne D, Ralphs C, Roney A, Sardar N, Stefanova K, Surti F, Timms R, Tosney G, Bannister J, Clement NS, Cullimore V, Kamal F, Lendor J, McKay J, Mcswiggan J, Minhas N, Seneviratne K, Simeen S, Valverde J, Watson N, Bloom I, Dinh TH, Hirniak J, Joseph R, Kansagra M, Lai CKN, Melamed N, Patel J, Randev J, Sedighi T, Shurovi B, Sodhi J, Vadgama N, Abdulla S, Adabavazeh B, Champion A, Chennupati R, Chu K, Devi S, Haji A, Schulz J, Testa F, Davies P, Gurung B, Howell S, Modi P, Pervaiz A, Zahid M, Abdolrazaghi S, Abi Aoun R, Anjum Z, Bawa G, Bhardwaj R, Brown S, Enver M, Gill D, Gopikrishna D, Gurung D, Kanwal A, Kaushal P, Khanna A, Lovell E, McEvoy C, Mirza M, Nabeel S, Naseem S, Pandya K, Perkins R, Pulakal R, Ray M, Reay C, Reilly S, Round A, Seehra J, Shakeel NM, Singh B, Vijay Sukhnani M, Brown L, Desai B, Elzanati H, Godhaniya J, Kavanagh E, Kent J, Kishor A, Liu A, Norwood M, Shaari N, Wood C, Wood M, Brown A, Chellapuri A, Ferriman A, Ghosh I, Kulkarni N, Noton T, Pinto A, Rajesh S, Varghese B, Wenban C, Aly R, Barciela C, Brookes T, Corrin E, Goldsworthy M, Mohamed Azhar MS, Moore J, Nakhuda S, Ng D, Pillay S, Port S, Abdullah M, Akinyemi J, Islam S, Kale A, Lewis A, Manjunath T, McCabe H, Misra S, Stubley T, Tam JP, Waraich N, Chaora T, Ford C, Osinkolu I, Pong G, Rai J, Risquet R, Ainsworth J, Ayandokun P, Barham E, Barrett G, Barry J, Bisson E, Bridges I, Burke D, Cann J, Cloney M, Coates S, Cripps P, Davies C, Francis N, Green S, Handley G, Hathaway D, Hurt L, Jenkins S, Johnston C, Khadka A, McGee U, Morris D, Murray R, Norbury C, Pierrepont Z, Richards C, Ross O, Ruddy A, Salmon C, Shield M, Soanes K, Spencer N, Taverner S, Williams C, Wills-Wood W, Woodward S, Chow J, Fan J, Guest O, Hunter I, Moon WY, Arthur-Quarm S, Edwards P, Hamlyn V, McEneaney L, N D G, Pranoy S, Ting M, Abada S, Alawattegama LH, Ashok A, Carey C, Gogna A, Haglund C, Hurley P, Leelo N, Liu B, Mannan F, Paramjothy K, Ramlogan K, Raymond-Hayling O, Shanmugarajah A, Solichan D, Wilkinson B, Ahmad NA, Allan D, Amin A, Bakina C, Burns F, Cameron F, Campbell A, Cavanagh S, Chan SMZ, Chapman S, Chong V, Edelsten E, Ekpete O, El Sheikh M, Ghose R, Hassane A, Henderson C, Hilton-Christie S, Husain M, Hussain H, Javid Z, Johnson-Ogbuneke J, Johnston A, Khalil M, Leung TCC, Makin I, Muralidharan V, Naeem M, Patil P, Ravichandran S, Saraeva D, Shankey-Smith W, Sharma N, Swan R, Waudby-West R, Wilkinson A, Wright K, Balasubramanian A, Bhatti S, Chalkley M, Chou WK, Dixon M, Evans L, Fisher K, Gandhi P, Ho S, Lau YB, Lowe S, Meechan C, Murali N, Musonda C, Njoku P, Ochieng L, Pervez MU, Seebah K, Shaikh I, Sikder MA, Vanker R, Alom J, Bajaj V, Coleman O, Finch G, Goss J, Jenkins C, Kontothanassis A, Liew MS, Ng K, Outram M, Shakeel MM, Tawn J, Zuhairy S, Chapple K, Cinnamond A, Coleman S, George HA, Goulder L, Hare N, Hawksley J, Kret A, Luesley A, Mecia L, Porter H, Puddy E, Richardson G, Sohail B, Srikaran V, Tadross D, Tobin J, Tokidis E, Young L, Ashdown T, Bratsos S, Koomson A, Kufuor A, Lim MQ, Shah S, Thorne EPC, Warusavitarne J, Xu S, Abigail S, Ahmed A, Ahmed J, Akmal A, Al-Khafaji M, Amini B, Arshad M, Bogie E, Brazkiewicz M, Carroll M, Chandegra A, Cirelli C, Deng A, Fairclough S, Fung YJ, Gornell C, Green RL, Green SV, Gulamhussein AHM, Isaac AG, Jan R, Jegatheeswaran L, Knee M, Kotecha J, Kotecha S, Maxwell-Armstrong C, McIntyre C, Mendis N, Naing TKP, Oberman J, Ong ZX, Ramalingam A, Saeed Adam A, Tan LL, Towell S, Yadav J, Anandampillai R, Chung S, Hounat A, Ibrahim B, Jeyakumar G, Khalil A, Khan UA, Nair G, Owusu-Ayim M, Wilson M, Kanani A, Kilkelly B, Ogunmwonyi I, Ong L, Samra B, Schomerus L, Shea J, Turner O, Yang Y, Amin M, Blott N, Clark A, Feather A, Forrest M, Hague S, Hamilton K, Higginbotham G, Hope E, Karimian S, Loveday K, Malik H, McKenna O, Noor A, Onsiong C, Patel B, Radcliffe N, Shah P, Tye L, Verma K, Walford R, Yusufi U, Zachariah M, Casey A, Doré C, Fludder V, Fortescue L, Kalapu SS, Karel E, Khera G, Smith C, Appleton B, Ashaye A, Boggon E, Evans A, Faris Mahmood H, Hinchcliffe Z, Marei O, Silva I, Spooner C, Thomas G, Timlin M, Wellington J, Yao SL, Abdelrazek M, Abdelrazik Y, Bee F, Joseph A, Mounce A, Parry G, Vignarajah N, Biddles D, Creissen A, Kolhe S, K T, Lea A, Ledda V, O'Loughlin P, Scanlon J, Shetty N, Weller C, Abdalla M, Adeoye A, Bhatti M, Chadda KR, Chu J, Elhakim H, Foster-Davies H, Rabie M, Tailor B, Webb S, Abdelrahim ASA, Choo SY, Jiwa A, Mangam S, Murray S, Shandramohan A, Aghanenu O, Budd W, Hayre J, Khanom S, Liew ZY, McKinney R, Moody N, Muhammad-Kamal H, Odogwu J, Patel D, Roy C, Sattar Z, Shahrokhi N, Sinha I, Thomson E, Wonga L, Bain J, Khan J, Ricardo D, Bevis R, Cherry C, Darkwa S, Drew W, Griffiths E, Konda N, Madani D, Mak JKC, Meda B, Odunukwe U, Preest G, Raheel F, Rajaseharan A, Ramgopal A, Risbrooke C, Selvaratnam K, Sethunath G, Tabassum R, Taylor J, Thakker A, Wijesingha N, Wybrew R, Yasin T, Ahmed Osman A, Alfadhel S, Carberry E, Chen JY, Drake I, Glen P, Jayasuriya N, Kawar L, Myatt R, Sinan LOH, Siu SSY, Tjen V, Adeboyejo O, Bacon H, Barnes R, Birnie C, D'Cunha Kamath A, Hughes E, Middleton S, Owen R, Schofield E, Short C, Smith R, Wang H, Willett M, Zimmerman M, Balfour J, Chadwick T, Coombe-Jones M, Do Le HP, Faulkner G, Hobson K, Shehata Z, Beattie M, Chmielewski G, Chong C, Donnelly B, Drusch B, Ellis J, Farrelly C, Feyi-Waboso J, Hibell I, Hoade L, Ho C, Jones H, Kodiatt B, Lidder P, Ni Cheallaigh L, Norman R, Patabendi I, Penfold H, Playfair M, Pomeroy S, Ralph C, Rottenburg H, Sebastian J, Sheehan M, Stanley V, Welchman J, Ajdarpasic D, Antypas A, Azouaghe O, Basi S, Bettoli G, Bhattarai S, Bommireddy L, Bourne K, Budding J, Cookey-Bresi R, Cummins T, Davies G, Fabelurin C, Gwilliam R, Hanley J, Hird A, Kruczynska A, Langhorne B, Lund J, Lutchman I, McGuinness R, Neary M, Pampapathi S, Pang E, Podbicanin S, Rai N, Redhouse White G, Sujith J, Thomas P, Walker I, Winterton R, Anderson P, Barrington M, Bhadra K, Clark G, Fowler G, Gibson C, Hudson S, Kaminskaite V, Lawday S, Longshaw A, MacKrill E, McLachlan F, Murdeshwar A, Nieuwoudt R, Parker P, Randall R, Rawlins E, Reeves SA, Rye D, Sirkis T, Sykes B, Ventress N, Wosinska N, Akram B, Burton L, Coombs A, Long R, Magowan D, Ong C, Sethi M, Williams G, Chan C, Chan LH, Fernando D, Gaba F, Khor Z, Les JW, Mak R, Moin S, Ng Kee Kwong KC, Paterson-Brown S, Tew YY, Bardon A, Burrell K, Coldwell C, Costa I, Dexter E, Hardy A, Khojani M, Mazurek J, Raymond T, Reddy V, Reynolds J, Soma A, Agiotakis S, Alsusa H, Desai N, Peristerakis I, Adcock A, Ayub H, Bennett T, Bibi F, Brenac S, Chapman T, Clarke G, Clark F, Galvin C, Gwyn-Jones A, Henry-Blake C, Kerner S, Kiandee M, Lovett A, Pilecka A, Ravindran R, Siddique H, Sikand T, Treadwell K, Akmal K, Apata A, Barton O, Broad G, Darling H, Dhuga Y, Emms L, Habib S, Jain R, Jeater J, Kan CYP, Kathiravelupillai A, Khatkar H, Kirmani S, Kulasabanathan K, Lacey H, Lal K, Manafa C, Mansoor M, McDonald S, Mittal A, Mustoe S, Nottrodt L, Oliver P, Papapetrou I, Pattinson F, Raja M, Reyhani H, Shahmiri A, Small O, Soni U, Aguirrezabala Armbruster B, Bunni J, Hakim MA, Hawkins-Hooker L, Howell KA, Hullait R, Jaskowska A, Ottewell L, Thomas-Jones I, Vasudev A, Clements B, Fenton J, Gill M, Haider S, Lim AJM, Maguire H, McMullan J, Nicoletti J, Samuel S, Unais MA, White N, Yao PC, Yow L, Boyle C, Brady R, Cheekoty P, Cheong J, Chew SJHL, Chow R, Ganewatta Kankanamge D, Mamer L, Mohammed B, Ng Chieng Hin J, Renji Chungath R, Royston A, Sharrad E, Sinclair R, Tingle S, Treherne K, Wyatt F, Maniarasu VS, Moug S, Appanna T, Bucknall T, Hussain F, Owen A, Parry M, Parry R, Sagua N, Spofforth K, Yuen ECT, Bosley N, Hardie W, Moore T, Regas C, Abdel-Khaleq S, Ali N, Bashiti H, Buxton-Hopley R, Constantinides M, D'Afflitto M, Deshpande A, Duque Golding J, Frisira E, Germani Batacchi M, Gomaa A, Hay D, Hutchison R, Iakovou A, Iakovou D, Ismail E, Jefferson S, Jones L, Khouli Y, Knowles C, Mason J, McCaughan R, Moffatt J, Morawala A, Nadir H, Neyroud F, Nikookam Y, Parmar A, Pinto L, Ramamoorthy R, Richards E, Thomson S, Trainer C, Valetopoulou A, Vassiliou A, Wantman A, Wilde S, Dickinson M, Rockall T, Senn D, Wcislo K, Zalmay P, Adelekan K, Allen K, Bajaj M, Gatumbu P, Hang S, Hashmi Y, Kaur T, Kawesha A, Kisiel A, Woodmass M, Adelowo T, Ahari D, Alhwaishel K, Atherton R, Clayton B, Cockroft A, Curtis Lopez C, Hilton M, Ismail N, Kouadria M, Lee L, MacConnachie A, Monks F, Mungroo S, Nikoletopoulou C, Pearce L, Sara X, Shahid A, Suresh G, Wilcha R, Atiyah A, Davies E, Dermanis A, Gibbons H, Hyde A, Lawson A, Lee C, Leung-Tack M, Li Saw Hee J, Mostafa O, Nair D, Pattani N, Plumbley-Jones J, Pufal K, Ramesh P, Sanghera J, Saram S, Scadding S, See S, Stringer H, Torrance A, Vardon H, Wyn-Griffiths F, Brew A, Kaur G, Soni D, Tickle A, Akbar Z, Appleyard T, Figg K, Jayawardena P, Johnson A, Kamran Siddiqui Z, Lacy-Colson J, Oatham R, Rowlands B, Sludden E, Turnbull C, Allin D, Ansar Z, Azeez Z, Dale VH, Garg J, Horner A, Jones S, Knight S, McGregor C, McKenna J, McLelland T, Packham-Smith A, Rowsell K, Spector-Hill I, Adeniken E, Baker J, Bartlett M, Chikomba L, Connell B, Deekonda P, Dhar M, Elmansouri A, Gamage K, Goodhew R, Hanna P, Knight J, Luca A, Maasoumi N, Mahamoud F, Manji S, Marwaha PK, Mason F, Oluboyede A, Pigott L, Razaq AM, Richardson M, Saddaoui I, Wijeyendram P, Yau S, Atkins W, Liang K, Miles N, Praveen B, Ashai S, Braganza J, Common J, Cundy A, Davies R, Guthrie J, Handa I, Iqbal M, Ismail R, Jones C, Jones I, Lee KS, Levene A, Okocha M, Olivier J, Smith A, Subramaniam E, Tandle S, Wang A, Watson A, Wilson C, Chan XHF, Khoo E, Montgomery C, Norris M, Pugalenthi PP, Common T, Cook E, Mistry H, Shinmar HS, Agarwal G, Bandyopadhyay S, Brazier B, Carroll L, Goede A, Harbourne A, Lakhani A, Lami M, Larwood J, Martin J, Merchant J, Pattenden S, Pradhan A, Raafat N, Rothwell E, Shammoon Y, Sudarshan R, Vickers E, Wingfield L, Ashworth I, Azizi S, Bhate R, Chowdhury T, Christou A, Davies L, Dwaraknath M, Farah Y, Garner J, Gureviciute E, Hart E, Jain A, Javid S, Kankam HK, Kaur Toor P, Kaz R, Kermali M, Khan I, Mattson A, McManus A, Murphy M, Nair K, Ngemoh D, Norton E, Olabiran A, Parry L, Payne T, Pillai K, Price S, Punjabi K, Raghunathan A, Ramwell A, Raza M, Ritehnia J, Simpson G, Smith W, Sodeinde S, Studd L, Subramaniam M, Thomas J, Towey S, Tsang E, Tuteja D, Vasani J, Vio M, Badran A, Adams J, Anthony Wilkinson J, Asvandi S, Austin T, Bald A, Bix E, Carrick M, Chander B, Chowdhury S, Cooper Drake B, Crosbie S, D Portela S, Francis D, Gallagher C, Gillespie R, Gravett H, Gupta P, Ilyas C, James G, Johny J, Jones A, Kinder F, MacLeod C, Macrow C, Maqsood-Shah A, Mather J, McCann L, McMahon R, Mitham E, Mohamed M, Munton E, Nightingale K, O'Neill K, Onyemuchara I, Senior R, Shanahan A, Sherlock J, Spyridoulias A, Stavrou C, Stokes D, Tamang R, Taylor E, Trafford C, Uden C, Waddington C, Yassin D, Zaman M, Bangi S, Cheng T, Chew D, Hussain N, Imani-Masouleh S, Mahasivam G, McKnight G, Ng HL, Ota HC, Pasha T, Ravindran W, Shah K, Vishnu K S, Zaman S, Carr W, Cope S, Eagles EJ, Howarth-Maddison M, Li CY, Reed J, Ridge A, Stubbs T, Teasdaled D, Umar R, Worthington J, Dhebri A, Kalenderov R, Alattas A, Arain Z, Bhudia R, Chia D, Daniel S, Dar T, Garland H, Girish M, Hampson A, Kyriacou H, Lehovsky K, Mullins W, Omorphos N, Vasdev N, Venkatesh A, Waldock W, Bhandari A, Brown G, Choa G, Eichenauer CE, Ezennia K, Kidwai Z, Lloyd-Thomas A, Macaskill Stewart A, Massardi C, Sinclair E, Skajaa N, Smith M, Tan I, Afsheen N, Anuar A, Azam Z, Bhatia P, Davies-kelly N, Dickinson S, Elkawafi M, Ganapathy M, Gupta S, Khoury EG, Licudi D, Mehta V, Neequaye S, Nita G, Tay VL, Zhao S, Botsa E, Cuthbert H, Elliott J, Furlepa M, Lehmann J, Mangtani A, Narayan A, Nazarian S, Parmar C, Shah D, Shaw C, Zhao Z, Beck C, Caldwell S, Clements JM, French B, Kenny R, Kirk S, Lindsay J, McClung A, McLaughlin N, Watson S, Whiteside E, Alyacoubi S, Arumugam V, Beg R, Dawas K, Garg S, Lloyd ER, Mahfouz Y, Manobharath N, Moonesinghe R, Morka N, Patel K, Prashar J, Yip S, Adeeko ES, Ajekigbe F, Bhat A, Evans C, Farrugia A, Gurung C, Long T, Malik B, Manirajan S, Newport D, Rayer J, Ridha A, Ross E, Saran T, Sinker A, Waruingi D, Allen R, Al Sadek Y, Alves do Canto Brum H, Asharaf H, Ashman M, Balakumar V, Barrington J, Baskaran R, Berry A, Bhachoo H, Bilal A, Boaden L, Chia WL, Covell G, Crook D, Dadnam F, Davis L, De Berker H, Doyle C, Fox C, Gruffydd-Davies M, Hafouda Y, Hill A, Hubbard E, Hunter A, Inpadhas V, Jamshaid M, Jandu G, Jeyanthi M, Jones T, Kantor C, Kwak SY, Malik N, Matt R, McNulty P, Miles C, Mohomed A, Myat P, Niharika J, Nixon A, O'Reilly D, Parmar K, Pengelly S, Price L, Ramsden M, Turnor R, Wales E, Waring H, Wu M, Yang T, Ye TTS, Zander A, Zeicu C, Bellam S, Francombe J, Kawamoto N, Rahman MR, Sathyanarayana A, Tang HT, Cheung J, Hollingshead J, Page V, Sugarman J, Wong E, Chiong J, Fung E, Kan SY, Kiang J, Kok J, Krahelski O, Liew MY, Lyell B, Sharif Z, Speake D, Alim L, Amakye NY, Chandrasekaran J, Chandratreya N, Drake J, Owoso T, Thu YM, Abou El Ela Bourquin B, Alberts J, Chapman D, Rehnnuma N, Ainsworth K, Carpenter H, Emmanuel T, Fisher T, Gabrel M, Guan Z, Hollows S, Hotouras A, Ip Fung Chun N, Jaffer S, Kallikas G, Kennedy N, Lewinsohn B, Liu FY, Mohammed S, Rutherfurd A, Situ T, Stammer A, Taylor F, Thin N, Urgesi E, Zhang N, Ahmad MA, Bishop A, Bowes A, Dixit A, Glasson R, Hatta S, Hatt K, Larcombe S, Preece J, Riordan E, Fegredo D, Haq MZ, Li C, McCann G, Stewart D, Baraza W, Bhullar D, Burt G, Coyle J, Deans J, Devine A, Hird R, Ikotun O, Manchip G, Ross C, Storey L, Tan WWL, Tse C, Warner C, Whitehead M, Wu F, Court EL, Crisp E, Huttman M, Mayes F, Robertson H, Rosen H, Sandberg C, Smith H, Al Bakry M, Ashwell W, Bajaj S, Bandyopadhyay D, Browlee O, Burway S, Chand CP, Elsayeh K, Elsharkawi A, Evans E, Ferrin S, Fort-Schaale A, Iacob M, I K, Impelliziere Licastro G, Mankoo AS, Olaniyan T, Otun J, Pereira R, Reddy R, Saeed D, Simmonds O, Singhal G, Tron K, Wickstone C, Williams R, Bradshaw E, De Kock Jewell V, Houlden C, Knight C, Metezai H, Mirza-Davies A, Seymour Z, Spink D, Wischhusen S. Evaluation of prognostic risk models for postoperative pulmonary complications in adult patients undergoing major abdominal surgery: a systematic review and international external validation cohort study. Lancet Digit Health 2022; 4:e520-e531. [PMID: 35750401 DOI: 10.1016/s2589-7500(22)00069-3] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2021] [Revised: 01/07/2022] [Accepted: 04/06/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND Stratifying risk of postoperative pulmonary complications after major abdominal surgery allows clinicians to modify risk through targeted interventions and enhanced monitoring. In this study, we aimed to identify and validate prognostic models against a new consensus definition of postoperative pulmonary complications. METHODS We did a systematic review and international external validation cohort study. The systematic review was done in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. We searched MEDLINE and Embase on March 1, 2020, for articles published in English that reported on risk prediction models for postoperative pulmonary complications following abdominal surgery. External validation of existing models was done within a prospective international cohort study of adult patients (≥18 years) undergoing major abdominal surgery. Data were collected between Jan 1, 2019, and April 30, 2019, in the UK, Ireland, and Australia. Discriminative ability and prognostic accuracy summary statistics were compared between models for the 30-day postoperative pulmonary complication rate as defined by the Standardised Endpoints in Perioperative Medicine Core Outcome Measures in Perioperative and Anaesthetic Care (StEP-COMPAC). Model performance was compared using the area under the receiver operating characteristic curve (AUROCC). FINDINGS In total, we identified 2903 records from our literature search; of which, 2514 (86·6%) unique records were screened, 121 (4·8%) of 2514 full texts were assessed for eligibility, and 29 unique prognostic models were identified. Nine (31·0%) of 29 models had score development reported only, 19 (65·5%) had undergone internal validation, and only four (13·8%) had been externally validated. Data to validate six eligible models were collected in the international external validation cohort study. Data from 11 591 patients were available, with an overall postoperative pulmonary complication rate of 7·8% (n=903). None of the six models showed good discrimination (defined as AUROCC ≥0·70) for identifying postoperative pulmonary complications, with the Assess Respiratory Risk in Surgical Patients in Catalonia score showing the best discrimination (AUROCC 0·700 [95% CI 0·683-0·717]). INTERPRETATION In the pre-COVID-19 pandemic data, variability in the risk of pulmonary complications (StEP-COMPAC definition) following major abdominal surgery was poorly described by existing prognostication tools. To improve surgical safety during the COVID-19 pandemic recovery and beyond, novel risk stratification tools are required. FUNDING British Journal of Surgery Society.
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Nisar S, Bhat AA, Masoodi T, Hashem S, Akhtar S, Ali TA, Amjad S, Chawla S, Bagga P, Frenneaux MP, Reddy R, Fakhro K, Haris M. Genetics of glutamate and its receptors in autism spectrum disorder. Mol Psychiatry 2022; 27:2380-2392. [PMID: 35296811 PMCID: PMC9135628 DOI: 10.1038/s41380-022-01506-w] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/18/2021] [Revised: 02/11/2022] [Accepted: 02/22/2022] [Indexed: 12/11/2022]
Abstract
Autism spectrum disorder (ASD) is a neurodevelopmental impairment characterized by deficits in social interaction skills, impaired communication, and repetitive and restricted behaviors that are thought to be due to altered neurotransmission processes. The amino acid glutamate is an essential excitatory neurotransmitter in the human brain that regulates cognitive functions such as learning and memory, which are usually impaired in ASD. Over the last several years, increasing evidence from genetics, neuroimaging, protein expression, and animal model studies supporting the notion of altered glutamate metabolism has heightened the interest in evaluating glutamatergic dysfunction in ASD. Numerous pharmacological, behavioral, and imaging studies have demonstrated the imbalance in excitatory and inhibitory neurotransmitters, thus revealing the involvement of the glutamatergic system in ASD pathology. Here, we review the effects of genetic alterations on glutamate and its receptors in ASD and the role of non-invasive imaging modalities in detecting these changes. We also highlight the potential therapeutic targets associated with impaired glutamatergic pathways.
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Affiliation(s)
- Sabah Nisar
- Laboratory of Molecular and Metabolic Imaging, Sidra Medicine, P.O. Box 26999, Doha, Qatar
| | - Ajaz A Bhat
- Laboratory of Molecular and Metabolic Imaging, Sidra Medicine, P.O. Box 26999, Doha, Qatar
| | - Tariq Masoodi
- Laboratory of Molecular and Metabolic Imaging, Sidra Medicine, P.O. Box 26999, Doha, Qatar
| | - Sheema Hashem
- Laboratory of Molecular and Metabolic Imaging, Sidra Medicine, P.O. Box 26999, Doha, Qatar
| | - Sabah Akhtar
- Laboratory of Molecular and Metabolic Imaging, Sidra Medicine, P.O. Box 26999, Doha, Qatar
| | - Tayyiba Akbar Ali
- Laboratory of Molecular and Metabolic Imaging, Sidra Medicine, P.O. Box 26999, Doha, Qatar
| | - Sara Amjad
- Shibli National College, Azamgarh, Uttar Pradesh, 276001, India
| | - Sanjeev Chawla
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Puneet Bagga
- Department of Diagnostic Imaging, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Michael P Frenneaux
- Academic Health System, Hamad Medical Corporation, P.O. Box 3050, Doha, Qatar
| | - Ravinder Reddy
- Center for Advanced Metabolic Imaging in Precision Medicine, Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Khalid Fakhro
- Department of Human Genetics, Sidra Medicine, P.O. Box 26999, Doha, Qatar
- Department of Genetic Medicine, Weill Cornell Medical College, P.O. Box 24144, Doha, Qatar
| | - Mohammad Haris
- Laboratory of Molecular and Metabolic Imaging, Sidra Medicine, P.O. Box 26999, Doha, Qatar.
- Center for Advanced Metabolic Imaging in Precision Medicine, Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, 19104, USA.
- Laboratory of Animal Research, Qatar University, P.O. Box 2713, Doha, Qatar.
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Kumar M, Nanga RPR, Chawla S. Editorial: Structural, Metabolic, and Physiologic MR Imaging to Study Glioblastomas. Front Neurol 2022; 13:887027. [PMID: 35432174 PMCID: PMC9005642 DOI: 10.3389/fneur.2022.887027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Accepted: 03/08/2022] [Indexed: 11/25/2022] Open
Affiliation(s)
- Manoj Kumar
- Department of Neuroimaging and Intervention Radiology, National Institute of Mental Health and Neurosciences, Bangalore, India
- *Correspondence: Manoj Kumar
| | - Ravi Prakash Reddy Nanga
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, United States
| | - Sanjeev Chawla
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, United States
- Sanjeev Chawla
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20
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Kumar M, Nanga RPR, Verma G, Wilson N, Brisset JC, Nath K, Chawla S. Emerging MR Imaging and Spectroscopic Methods to Study Brain Tumor Metabolism. Front Neurol 2022; 13:789355. [PMID: 35370872 PMCID: PMC8967433 DOI: 10.3389/fneur.2022.789355] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2021] [Accepted: 01/31/2022] [Indexed: 11/13/2022] Open
Abstract
Proton magnetic resonance spectroscopy (1H-MRS) provides a non-invasive biochemical profile of brain tumors. The conventional 1H-MRS methods present a few challenges mainly related to limited spatial coverage and low spatial and spectral resolutions. In the recent past, the advent and development of more sophisticated metabolic imaging and spectroscopic sequences have revolutionized the field of neuro-oncologic metabolomics. In this review article, we will briefly describe the scientific premises of three-dimensional echoplanar spectroscopic imaging (3D-EPSI), two-dimensional correlation spectroscopy (2D-COSY), and chemical exchange saturation technique (CEST) MRI techniques. Several published studies have shown how these emerging techniques can significantly impact the management of patients with glioma by determining histologic grades, molecular profiles, planning treatment strategies, and assessing the therapeutic responses. The purpose of this review article is to summarize the potential clinical applications of these techniques in studying brain tumor metabolism.
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Affiliation(s)
- Manoj Kumar
- Department of Neuroimaging and Interventional Radiology, National Institute of Mental Health and Neurosciences, Bengaluru, India
| | - Ravi Prakash Reddy Nanga
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, United States
| | - Gaurav Verma
- Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Neil Wilson
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, United States
| | | | - Kavindra Nath
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, United States
| | - Sanjeev Chawla
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, United States
- *Correspondence: Sanjeev Chawla
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21
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Lee SC, Hariharan H, Arias-Mendoza F, Mizsei G, Nath K, Chawla S, Elliott M, Reddy R, Glickson J. Coherence pathway analysis of J-coupled lipids and lactate and effective suppression of lipids upon the selective multiple quantum coherence lactate editing sequence. Biomed Phys Eng Express 2022; 8. [PMID: 35193126 DOI: 10.1088/2057-1976/ac57ad] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2021] [Accepted: 02/21/2022] [Indexed: 11/11/2022]
Abstract
Objective:The selective multiple quantum coherence (Sel-MQC) sequence is a magnetic resonance spectroscopy (MRS) technique used to detect lactate and suppress co-resonant lipid signalsin vivo. The coherence pathways of J-coupled lipids upon the sequence, however, have not been studied, hindering a logical design of the sequence to fully attenuate lipid signals. The objective of this study is to elucidate the coherence pathways of J-coupled lipids upon the Sel-MQC sequence and find a strategy to effectively suppress lipid signals from these pathways while keeping the lactate signal.Approach:The product operator formalism was used to express the evolutions of the J-coupled spins of lipids and lactate. The transformations of the product operators by the spectrally selective pulses of the sequence were calculated by using the off-resonance rotation matrices. The coherence pathways and the conversion rates of the individual pathways were derived from them. Experiments were performed on phantoms and two human subjects at 3T.Main results:The coherence pathways contributing to the various lipid resonance signals by the Sel-MQC sequence depending on the gradient ratios and RF pulse lengths were identified. Theoretical calculations of the signals from the determined coherence pathways and signal attenuations by gradients matched the experimental data very well. Lipid signals from fatty tissues of the subjects were successfully suppressed to the noise level by using the gradient ratio -0.8:-1:2 or 1:0.8:2. The new gradient ratios kept the lactate signal the same as with the previously used gradient ratio 0:-1:2.Significance:The study has elucidated the coherence pathways of J-coupled lipids upon the Sel-MQC sequence and demonstrated how lipid signals can be effectively suppressed while keeping lactate signals by using information from the coherence pathway analysis. The findings enable applying the Sel-MQC sequence to lactate detection in an environment of high concentrations of lipids.
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Affiliation(s)
- Seung-Cheol Lee
- University of Pennsylvania, 423 Guardian Dr., Philadelphia, Pennsylvania, 19104-6243, UNITED STATES
| | - Hari Hariharan
- University of Pennsylvania, 422 Curie Boulevard, Philadelphia, Pennsylvania, 19104, UNITED STATES
| | - Fernando Arias-Mendoza
- University of Pennsylvania, 423 Guardian Dr., Philadelphia, Pennsylvania, 19104, UNITED STATES
| | - Gabor Mizsei
- University of Pennsylvania, 423 Guardian Dr., Philadelphia, Pennsylvania, 19104, UNITED STATES
| | - Kavindra Nath
- University of Pennsylvania, 423 Guardian Dr., Philadelphia, Pennsylvania, 19014, UNITED STATES
| | - Sanjeev Chawla
- University of Pennsylvania, 3400 Spruce Street, Philadelphia, Pennsylvania, 19104, UNITED STATES
| | - Mark Elliott
- University of Pennsylvania, 422 Curie Boulevard, Philadelphia, Pennsylvania, 19104, UNITED STATES
| | - Ravinder Reddy
- University of Pennsylvania, 422 Curie Boulevard, Philadelphia, Pennsylvania, 19104, UNITED STATES
| | - Jerry Glickson
- University of Pennsylvania, 423 Guardian Dr., Philadelphia, Pennsylvania, 19104, UNITED STATES
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22
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Chawla S, Asadollahi S, Gupta PK, Nath K, Brem S, Mohan S. Advanced magnetic resonance imaging and spectroscopy in a case of neurocysticercosis from North America. Neuroradiol J 2022; 35:119-125. [PMID: 34167362 PMCID: PMC8826293 DOI: 10.1177/19714009211026889] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023] Open
Abstract
Neurocysticercosis (NCC) is a parasitic infection caused by Cysticercus cellulosae, the metacestode of pork tapeworm (Taenia solium). NCC is one of the most common public health problems worldwide. We present a patient harboring a bilobed ring-enhancing lesion with a presumed diagnosis of brain metastasis, who returned to the USA after traveling to an endemic region. The diagnosis of NCC was established based on a characteristic resonance of succinate on proton magnetic resonance spectroscopy. Also, higher mean diffusivity and lower fractional anisotropy along with relative cerebral blood volume were observed from the lesion compared to contralateral normal brain regions. Multiparametric analysis may improve the differential diagnosis of ring-enhancing intracranial lesions such as NCC.
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Affiliation(s)
- Sanjeev Chawla
- Department of Radiology, Perelman School of
Medicine at the University of Pennsylvania, USA,Sanjeev Chawla, Department of Radiology, Division
of Neuroradiology, 219 Dulles Building, 3400 Spruce Street, Perelman School of Medicine at
the University of Pennsylvania, Philadelphia, PA 19104, USA.
| | - Shadi Asadollahi
- Department of Radiology, Perelman School of
Medicine at the University of Pennsylvania, USA
| | - Pradeep Kumar Gupta
- Department of Radiology, Perelman School of
Medicine at the University of Pennsylvania, USA
| | - Kavindra Nath
- Department of Radiology, Perelman School of
Medicine at the University of Pennsylvania, USA
| | - Steven Brem
- Department of Neurosurgery, Perelman School
of Medicine at the University of Pennsylvania, USA
| | - Suyash Mohan
- Department of Radiology, Perelman School of
Medicine at the University of Pennsylvania, USA
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23
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Fathi Kazerooni A, Bagley SJ, Akbari H, Saxena S, Bagheri S, Guo J, Chawla S, Nabavizadeh A, Mohan S, Bakas S, Davatzikos C, Nasrallah MP. Applications of Radiomics and Radiogenomics in High-Grade Gliomas in the Era of Precision Medicine. Cancers (Basel) 2021; 13:cancers13235921. [PMID: 34885031 PMCID: PMC8656630 DOI: 10.3390/cancers13235921] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Revised: 11/19/2021] [Accepted: 11/22/2021] [Indexed: 12/22/2022] Open
Abstract
Simple Summary Radiomics and radiogenomics offer new insight into high-grade glioma biology, as well as into glioma behavior in response to standard therapies. In this article, we provide neuro-oncology, neuropathology, and computational perspectives on the role of radiomics in providing more accurate diagnoses, prognostication, and surveillance of patients with high-grade glioma, and on the potential application of radiomics in clinical practice, with the overarching goal of advancing precision medicine for optimal patient care. Abstract Machine learning (ML) integrated with medical imaging has introduced new perspectives in precision diagnostics of high-grade gliomas, through radiomics and radiogenomics. This has raised hopes for characterizing noninvasive and in vivo biomarkers for prediction of patient survival, tumor recurrence, and genomics and therefore encouraging treatments tailored to individualized needs. Characterization of tumor infiltration based on pre-operative multi-parametric magnetic resonance imaging (MP-MRI) scans may allow prediction of the loci of future tumor recurrence and thereby aid in planning the course of treatment for the patients, such as optimizing the extent of resection and the dose and target area of radiation. Imaging signatures of tumor genomics can help in identifying the patients who benefit from certain targeted therapies. Specifying molecular properties of gliomas and prediction of their changes over time and with treatment would allow optimization of treatment. In this article, we provide neuro-oncology, neuropathology, and computational perspectives on the promise of radiomics and radiogenomics for allowing personalized treatments of patients with gliomas and discuss the challenges and limitations of these methods in multi-institutional clinical trials and suggestions to mitigate the issues and the future directions.
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Affiliation(s)
- Anahita Fathi Kazerooni
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA 19104, USA; (A.F.K.); (H.A.); (S.S.); (J.G.); (A.N.); (S.M.); (S.B.); (C.D.)
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; (S.B.); (S.C.)
| | - Stephen J. Bagley
- Abramson Cancer Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA;
- Glioblastoma Translational Center of Excellence, Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Hamed Akbari
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA 19104, USA; (A.F.K.); (H.A.); (S.S.); (J.G.); (A.N.); (S.M.); (S.B.); (C.D.)
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; (S.B.); (S.C.)
| | - Sanjay Saxena
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA 19104, USA; (A.F.K.); (H.A.); (S.S.); (J.G.); (A.N.); (S.M.); (S.B.); (C.D.)
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; (S.B.); (S.C.)
| | - Sina Bagheri
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; (S.B.); (S.C.)
| | - Jun Guo
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA 19104, USA; (A.F.K.); (H.A.); (S.S.); (J.G.); (A.N.); (S.M.); (S.B.); (C.D.)
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; (S.B.); (S.C.)
| | - Sanjeev Chawla
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; (S.B.); (S.C.)
| | - Ali Nabavizadeh
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA 19104, USA; (A.F.K.); (H.A.); (S.S.); (J.G.); (A.N.); (S.M.); (S.B.); (C.D.)
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; (S.B.); (S.C.)
| | - Suyash Mohan
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA 19104, USA; (A.F.K.); (H.A.); (S.S.); (J.G.); (A.N.); (S.M.); (S.B.); (C.D.)
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; (S.B.); (S.C.)
| | - Spyridon Bakas
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA 19104, USA; (A.F.K.); (H.A.); (S.S.); (J.G.); (A.N.); (S.M.); (S.B.); (C.D.)
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; (S.B.); (S.C.)
- Department of Pathology & Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Christos Davatzikos
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA 19104, USA; (A.F.K.); (H.A.); (S.S.); (J.G.); (A.N.); (S.M.); (S.B.); (C.D.)
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; (S.B.); (S.C.)
| | - MacLean P. Nasrallah
- Glioblastoma Translational Center of Excellence, Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Pathology & Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Correspondence:
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Lak H, Sammour Y, Chahine J, Chawla S, Kadri A, Popovic Z, Tarakji K, Svensson LG, Reed G, Puri R, Krishnaswamy A, Kapadia S. Impact of new-onset left bundle branch block on clinical and echocardiographic outcomes after TAVR with SAPIEN-3 valve. Eur Heart J 2021. [DOI: 10.1093/eurheartj/ehab724.2179] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Abstract
Background
New left bundle branch block (LBBB) is a common finding after transcatheter aortic valve replacement (TAVR) that can result in worse outcomes after TAVR. We aim to investigate the impact of new-onset LBBB after TAVR using the SAPIEN-3 (S3) valve.
Methods
Consecutive patients who underwent transfemoral-TAVR with S3 valve between April 2015 and December 2018 were included. Exclusion criteria included pre-existing LBBB, right bundle branch block, left anterior hemiblock, left posterior hemiblock, wide QRS ≥120 msec, prior permanent pacemaker (PPM), and non-transfemoral access.
Results
Among 612 patients, 11.4% developed new-onset LBBB upon discharge. Implantation depth was the only predictor of new-onset LBBB (OR 1.294; 95% CI 1.121–1.493; p<0.001). The median (IQR) length of stay was longer with new-onset LBBB [3 (2–5) days vs. 2 (1–3) days; p<0.001]. New-onset LBBB was associated with higher thirty-day PPM requirement (18.6% vs. 5.4%; p<0.001) including those implanted after discharge (4.3% vs. 0.9%; p=0.02). There was no difference in 3-year all-cause mortality between both groups (30.9% vs. 30.6%; log-rank p=0.829). Further, new-onset LBBB was associated with lower left ventricular ejection fraction (LVEF) at both 30 days (55.9±11.4% vs. 59.3±9%; p=0.026) and 1 year (55±12% vs. 60.1±8.9%; p=0.002) despite no differences at baseline. These changes were still present when we stratified patients according to baseline LVEF (≥50% or <50%). We also noted higher mean LV end-diastolic volume index (51.4±18.6 vs. 46.4±15.1 ml/m2; p=0.036), and LV end-systolic volume index (23.2±14.1 vs. 18.9±9.7 ml/m2; p=0.009) with new-onset LBBB at 1 year. Lastly, there were significantly higher rates of heart failure readmissions at 1 year with new-onset LBBB (10.7% vs. 4.4%; log-rank p=0.033).
Conclusion
Among our cohort of S3 recipients, new-onset LBBB was associated with higher PPM requirement, worse LVEF, higher LV volumes and increased risk of heart failure hospitalizations. However, it did not affect mortality in the short-to-intermediate post-TAVR period.
Funding Acknowledgement
Type of funding sources: None. Figure 1. All-cause Survival
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Affiliation(s)
- H Lak
- Cleveland Clinic Foundation, Cleveland, United States of America
| | - Y Sammour
- Cleveland Clinic Foundation, Cleveland, United States of America
| | - J Chahine
- Cleveland Clinic Foundation, Cleveland, United States of America
| | - S Chawla
- Cleveland Clinic Foundation, Cleveland, United States of America
| | - A Kadri
- Cleveland Clinic Foundation, Cleveland, United States of America
| | - Z Popovic
- Cleveland Clinic Foundation, Cleveland, United States of America
| | - K Tarakji
- Cleveland Clinic Foundation, Cleveland, United States of America
| | - L G Svensson
- Cleveland Clinic Foundation, Cleveland, United States of America
| | - G Reed
- Cleveland Clinic Foundation, Cleveland, United States of America
| | - R Puri
- Cleveland Clinic Foundation, Cleveland, United States of America
| | - A Krishnaswamy
- Cleveland Clinic Foundation, Cleveland, United States of America
| | - S Kapadia
- Cleveland Clinic Foundation, Cleveland, United States of America
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Lak H, Sammour Y, Chawla S, Svensson LG, Yun J, Harb S, Reed GW, Puri R, Jaber W, Krishnaswamy A, Kapadia S. Impact of doppler velocity index after transcatheter aortic valve replacement using Sapien-3 valve – a single centre experience. Eur Heart J 2021. [DOI: 10.1093/eurheartj/ehab724.2178] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Abstract
Background
Little is known about the hemodynamic performance of Edwards Sapien-3 (S3) valve after Transcatheter Aortic Valve Replacement (TAVR). Doppler velocity index (DVI) is a better indicator of prosthetic valve function as it is independent of valve size and flow, unlike mean gradient and peak velocity which are flow-dependent.
Methods
In this study, we compare outcomes based on differences in DVI among a consecutive series of patients who underwent S3 TAVR between April 2015 and December 2018. Our institutional review board approved the study and informed consents were obtained from the subjects.
Results
Among 921 patients who had follow-up echocardiograms within 30 days after TAVR, 60.8% had DVI ≤0.5, while 39.2% had DVI >0.5. The median 30-day DVI was 0.47 with a standard deviation of 0.11 and mean 0.49 and interquartile range 0.41–0.55. The baseline clinical and procedural characteristics were similar between both groups with the exception of less post-dilation (36.8% vs. 47.4%; p=0.001) and greater implantation depth (2.59±1.99 vs. 2.31±1.9mm; p=0.031) with DVI ≤0.5. The rates of aortic valve calcification, pre dilation, pre-TAVR aortic regurgitation (AR) were similar. At baseline, there were no differences between both groups in mean or peak gradients or aortic velocity time integral (VTI). At 1 year, mean gradients were higher with DVI ≤0.5 (12.7±5.6 vs. 11.1±4.6 mmHg; p=0.001). DVI ≤0.5 was associated with higher peak gradients (24.2±10.2 vs. 21.4±8.7 mmHg; p=0.002), and aortic VTI (51.4±13.5 vs. 46.8±12.2 cm; p<0.001) at 1 year, especially with the 26mm and 29mm prostheses. Compared with DVI>0.5 group, patients in DVI<0.5 group had lower baseline left ventricular ejection fraction (LVEF) (54.5±12.2% vs. 58.9±11.2%; p<0.001), higher left ventricular end-diastolic volume index (LVEDVi) (54.3±20.9 vs. 49.4±17.4 ml/m2; p=0.001), higher LV end-systolic volume index (LVESVi) (25.2±16.5 vs. 21.3±12.7 ml/m2; p=0.001), and similar LV mass index (110.7±31.9 vs. 106.9±32.7 g/m2; p=0.134). 1-year mortality rates among patients who had DVI ≤0.5 compared to DVI >0.5 were lower (6.6% vs. 10.6%; log-rank p=0.033), however no difference was noted at both 2 years (17.3% vs. 20.1%; log-rank p=0.151), and 3 years after TAVR (30.7% vs. 31.2%; log-rank p=0.333).
Conclusions
DVI<0.5 was associated with higher peak gradients and lower baseline LVEF. DVI <0.5 group patients had lower 1-year mortality but similar mortality at 2 and 3-years of follow up.
Funding Acknowledgement
Type of funding sources: None. Figure 1. All-cause SurvivalFigure 2. Hemodynamic Data
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Affiliation(s)
- H Lak
- Cleveland Clinic Foundation, Cleveland, United States of America
| | - Y Sammour
- Cleveland Clinic Foundation, Cleveland, United States of America
| | - S Chawla
- Cleveland Clinic Foundation, Cleveland, United States of America
| | - L G Svensson
- Cleveland Clinic Foundation, Cleveland, United States of America
| | - J Yun
- Cleveland Clinic Foundation, Cleveland, United States of America
| | - S Harb
- Cleveland Clinic Foundation, Cleveland, United States of America
| | - G W Reed
- Cleveland Clinic Foundation, Cleveland, United States of America
| | - R Puri
- Cleveland Clinic Foundation, Cleveland, United States of America
| | - W Jaber
- Cleveland Clinic Foundation, Cleveland, United States of America
| | - A Krishnaswamy
- Cleveland Clinic Foundation, Cleveland, United States of America
| | - S Kapadia
- Cleveland Clinic Foundation, Cleveland, United States of America
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Lak H, Sammour Y, Chawla S, Gajulapalli RD, Kumar A, Parikh P, Svensson LG, Harb S, Tarakji K, Wazni O, Reed GW, Puri R, Krishnaswamy A, Kapadia S. Impact of pacing-related differences on clinical and echocardiographic outcomes after TAVR with SAPIEN-3 valve. Eur Heart J 2021. [DOI: 10.1093/eurheartj/ehab724.2180] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Abstract
Background
Data regarding the impact of pacing on outcomes after transcatheter aortic valve replacement (TAVR) is evolving especially with regards to pre-existing PPM. We examined the impact of new and prior PPM on clinical and hemodynamic outcomes after SAPIEN-3 (S3) TAVR.
Methods
Consecutive patients who underwent transfemoral-TAVR using S3 valve between April 2015 and December 2018 at our Clinic were included.
Results
Among 1028 patients, 10.2% required new PPM within 30 days, while 14% had pre-existing PPM. The presence of either prior or new PPM had no impact on 3-year mortality (log-rank p=0.6), or 1-year major adverse cardiac and cerebrovascular event (MACCE) (log-rank p=0.65). New PPM was associated with lower left ventricular ejection fraction (LVEF) at both 30 days (54.4±11.3% vs. 58.4±10.1%; p=0.001), and 1 year (54.2±12% vs. 59.1±9.9%; p=0.009) compared to no PPM. Similarly, prior PPM was associated with worse LVEF at 30 days (53.6±12.3%; p<0.001) and 1 year (55.5±12.1%; p=0.006) compared to no PPM. Interestingly, new PPM was associated with lower 1-year mean gradient (11.4±3.8 vs. 12.6±5.6 mmHg; p=0.04), and peak gradient (21.3±6.5 vs. 24.1±10.4 mmHg; p=0.01) despite no baseline differences. Prior PPM was also associated with lower 1-year mean gradient (10.3±4.4 mmHg; p=0.001), and peak gradient (19.4±8 mmHg; p<0.001), and higher doppler velocity index (0.51±0.12 vs. 0.47±0.13; p=0.039). Moreover, 1-year LV end-systolic volume (LVESVi) was higher with new (23.2±16.1 vs. 20±10.8 ml/m2; p=0.038), and prior PPM (24.5±19.7; p=0.038) compared to no PPM. Prior PPM was associated with higher moderate-to-severe tricuspid regurgitation (35.3% vs. 17.7%; p<0.001). There were no differences with regards to the rest of the studied echocardiographic outcomes at 1 year.
Conclusion
In this S3 cohort, new and prior PPM did not affect 3-year mortality or 1-year MACCE, however they were associated with worse LVEF, higher LVESVi and lower mean and peak gradients on follow-up compared to no PPM.
Funding Acknowledgement
Type of funding sources: None. Figure 1. All-cause Survival
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Affiliation(s)
- H Lak
- Cleveland Clinic Foundation, Cleveland, United States of America
| | - Y Sammour
- Cleveland Clinic Foundation, Cleveland, United States of America
| | - S Chawla
- Cleveland Clinic Foundation, Cleveland, United States of America
| | - R D Gajulapalli
- Cleveland Clinic Foundation, Cleveland, United States of America
| | - A Kumar
- Cleveland Clinic Foundation, Cleveland, United States of America
| | - P Parikh
- Cleveland Clinic Foundation, Cleveland, United States of America
| | - L G Svensson
- Cleveland Clinic Foundation, Cleveland, United States of America
| | - S Harb
- Cleveland Clinic Foundation, Cleveland, United States of America
| | - K Tarakji
- Cleveland Clinic Foundation, Cleveland, United States of America
| | - O Wazni
- Cleveland Clinic Foundation, Cleveland, United States of America
| | - G W Reed
- Cleveland Clinic Foundation, Cleveland, United States of America
| | - R Puri
- Cleveland Clinic Foundation, Cleveland, United States of America
| | - A Krishnaswamy
- Cleveland Clinic Foundation, Cleveland, United States of America
| | - S Kapadia
- Cleveland Clinic Foundation, Cleveland, United States of America
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Lak H, Chawla S, Verma B, Vural A, Gad M, Shekhar S, Nair R, Yun J, Burns D, Puri R, Reed G, Harb S, Krishnaswamy A, Kapadia S. Outcomes of transfemoral-transcatheter aortic valve replacement with Sapien-3 valve in liver cirrhosis patients. Eur Heart J 2021. [DOI: 10.1093/eurheartj/ehab724.2177] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Abstract
Background
Little is known about the outcomes of liver cirrhosis patients with severe aortic stenosis (AS) who undergo transcatheter aortic valve replacement (TAVR).
Methods
We undertook a retrospective analysis of consecutive patients with severe symptomatic AS who underwent transfemoral-TAVR with Sapien-3 valve at our Clinic between April 2015 and December 2018, yielding 32 patients with liver cirrhosis on imaging including ultrasound and/or computed tomography. Their baseline characteristics, procedural and long-term outcomes after TAVR with the non-cirrhotic group were compared, along with their management strategies as per the hepatology team.
Results
Among 1028 patients, 32 were assigned to the cirrhosis, and 996 were assigned to the non-cirrhosis (control) group. Compared with the control group cirrhotic patients were slightly younger in age (74.5 vs 81.2 years), had a slightly higher BMI (31.3 vs 29.3), and had a higher incidence of prior history of myocardial infarction (38% vs 33%). Baseline variables including the history of smoking, hypertension, diabetes, and atrial fibrillation were comparable in both groups. Among cirrhotic patients (n=32), the most common etiologies were non-alcoholic steatohepatitis (NASH) (37.5%), Alcoholism (18.75%), and Hepatitis C (12.5%). The mean MELD-NA score was 11.8 and 67% of patients were Child PUGH Class A and 33% were Child PUGH Class B and all patients had a Child PUGH score of ≥5. 53% of patients (n=17) in the cirrhosis group were evaluated by Hepatology and 12.5% (n=4) were evaluated for a liver transplant but only 1 patient had a liver transplant post-TAVR. Compared with the control group cirrhotic patients had similar 1-year mortality (12% vs 12%, p=1), had a lower rate of 30-day new pacemaker post tavr (6% vs 9% p=0.85), had a higher rate of 1-year readmission for heart failure (12% vs 5% p=0.12) and similar 1-year major adverse cardiac and cerebrovascular event (MACCE) rate (15% vs 14% p=0.98)
Conclusion
Patients with severe AS undergoing TAVR with concomitant liver cirrhosis demonstrate comparable outcomes compared with their non- cirrhotic counterparts. NASH followed by alcoholic cirrhosis was found to be most common etiology.
Funding Acknowledgement
Type of funding sources: None. Figure 1Figure 2
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Affiliation(s)
- H Lak
- Cleveland Clinic Foundation, Cleveland, United States of America
| | - S Chawla
- Cleveland Clinic Foundation, Cleveland, United States of America
| | - B Verma
- Cleveland Clinic Foundation, Cleveland, United States of America
| | - A Vural
- Cleveland Clinic Foundation, Cleveland, United States of America
| | - M Gad
- Cleveland Clinic Foundation, Cleveland, United States of America
| | - S Shekhar
- Cleveland Clinic Foundation, Cleveland, United States of America
| | - R Nair
- Cleveland Clinic Foundation, Cleveland, United States of America
| | - J Yun
- Cleveland Clinic Foundation, Cleveland, United States of America
| | - D Burns
- Cleveland Clinic Foundation, Cleveland, United States of America
| | - R Puri
- Cleveland Clinic Foundation, Cleveland, United States of America
| | - G Reed
- Cleveland Clinic Foundation, Cleveland, United States of America
| | - S Harb
- Cleveland Clinic Foundation, Cleveland, United States of America
| | - A Krishnaswamy
- Cleveland Clinic Foundation, Cleveland, United States of America
| | - S Kapadia
- Cleveland Clinic Foundation, Cleveland, United States of America
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Mohan S, Wang S, Chawla S, Abdullah K, Desai A, Maloney E, Brem S. Multiparametric MRI assessment of response to convection-enhanced intratumoral delivery of MDNA55, an interleukin-4 receptor targeted immunotherapy, for recurrent glioblastoma. Surg Neurol Int 2021; 12:337. [PMID: 34345478 PMCID: PMC8326072 DOI: 10.25259/sni_353_2021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2021] [Accepted: 06/09/2021] [Indexed: 11/04/2022] Open
Abstract
Background Glioblastoma (GBM) is the most common malignant brain tumor and carries a dismal prognosis. Attempts to develop biologically targeted therapies are challenging as the blood-brain barrier can limit drugs from reaching their target when administered through conventional (intravenous or oral) routes. Furthermore, systemic toxicity of drugs often limits their therapeutic potential. To circumvent these problems, convection-enhanced delivery (CED) provides direct, targeted, intralesional therapy with a secondary objective to alter the tumor microenvironment from an immunologically "cold" (nonresponsive) to an "inflamed" (immunoresponsive) tumor. Case Description We report a patient with right occipital recurrent GBM harboring poor prognostic genotypes who was treated with MRI-guided CED of a fusion protein MDNA55 (a targeted toxin directed toward the interleukin-4 receptor). The patient underwent serial anatomical, diffusion, and perfusion MRI scans before initiation of targeted therapy and at 1, 3-month posttherapy. Increased mean diffusivity along with decreased fractional anisotropy and maximum relative cerebral blood volume was noted at follow-up periods relative to baseline. Conclusion Our findings suggest that diffusion and perfusion MRI techniques may be useful in evaluating early response to CED of MDNA55 in recurrent GBM patients.
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Affiliation(s)
- Suyash Mohan
- Department of Radiology, Division of Neuroradiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, United States
| | - Sumei Wang
- Department of Radiology, Division of Neuroradiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, United States
| | - Sanjeev Chawla
- Department of Radiology, Division of Neuroradiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, United States
| | - Kalil Abdullah
- Department of Neurosurgery, University of Texas-Southwestern Medical Center, Dallas, Texas, United States
| | - Arati Desai
- Department of Medicine Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, United States
| | - Eileen Maloney
- Department of Neurosurgery, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, United States
| | - Steven Brem
- Department of Neurosurgery, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, United States
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Jain R, Mallya MV, Amoncar S, Palyekar S, Adsul HP, Kumar R, Chawla S. Seroprevalence of SARS-CoV-2 among potential convalescent plasma donors and analysis of their deferral pattern: Experience from tertiary care hospital in western India. Transfus Clin Biol 2021; 29:60-64. [PMID: 34302953 PMCID: PMC8295051 DOI: 10.1016/j.tracli.2021.07.004] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2021] [Revised: 07/08/2021] [Accepted: 07/13/2021] [Indexed: 12/30/2022]
Abstract
Background and objectives Seroprevalence estimation of COVID-19 is quite necessary for controlling the transmission of SARS-CoV-2 infection. Seroprevalence rate in recovered COVID-19 patients help us to identify individual with anti-SARS-CoV-2 antibodies and its protective nature. The objective of present study was to evaluate seroprevalence of SARS-CoV-2 among potential convalescent plasma donors and analysis of their deferral reasons. Materials and methods A total 400 potential convalescent plasma donors were enrolled over five-month period for this prospective study. Inclusion criteria were lab confirmed COVID-19 recovered patients and 14 days of symptoms free period. All prospective plasmapheresis donors were tested for IgG SARS-CoV-2 antibody through chemiluminescent microparticle immunoassay, CBC, serum protein, blood grouping along with other required test for normal blood donation as per Drugs & Cosmetics Act. After pre donation testing and medical examination if donor was found to be ineligible for plasmapheresis was deferred. Seroprevalence rate was calculated by positive IgG antibody test results among the potential plasma donors. Results Seroprevalence rate was 87% for IgG SARS-CoV-2 antibodies in prospective convalescent plasma donors (recovered COVID-19 patients). There was no significant difference in seroprevalence rate between different sub-groups with respect to gender, age, blood groups, Rh factor, mode of treatment, day of Ab testing and repeat plasma donation. Most common reason for their deferral was absent IgG SARS-CoV-2 antibodies (13%) followed by absenteeism of eligible screen donors (6.7%), low Hb (1.7%) and poor veins for plasmapheresis (1.7%). Till five-month study period none of the plasmapheresis develop symptoms of reinfection with COVID-19. Conclusion In all, 13% recovered patients did not develop IgG antibodies after SARS-CoV-2 infection. SARS-CoV-2 IgG antibodies persist for quite some time and are protective against reinfection. More long-term serology studies are needed to understand better antibody response kinetics and duration of persistence of IgG antibodies.
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Affiliation(s)
- R Jain
- Department(s) and institution(s) - Department of Blood Bank, Goa Medical College, Goa 403202, India.
| | - M V Mallya
- Department(s) and institution(s) - Department of Blood Bank, Goa Medical College, Goa 403202, India
| | - S Amoncar
- Department(s) and institution(s) - Department of Blood Bank, Goa Medical College, Goa 403202, India
| | - S Palyekar
- Department(s) and institution(s) - Department of Blood Bank, Goa Medical College, Goa 403202, India
| | - H P Adsul
- Department(s) and institution(s) - Department of Blood Bank, Goa Medical College, Goa 403202, India
| | - R Kumar
- Department(s) and institution(s) - Department of Transfusion medicine, Main Blood Bank, Ansari Nagar, AIIMS, New Delhi 110029, India
| | - S Chawla
- Department(s) and institution(s) - Department of Community Medicine, Pt. JLNGMCH, Chamba, Himachal Pradesh, India
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30
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Sydnor VJ, Larsen B, Kohler C, Crow AJD, Rush SL, Calkins ME, Gur RC, Gur RE, Ruparel K, Kable JW, Young JF, Chawla S, Elliott MA, Shinohara RT, Nanga RPR, Reddy R, Wolf DH, Satterthwaite TD, Roalf DR. Diminished reward responsiveness is associated with lower reward network GluCEST: an ultra-high field glutamate imaging study. Mol Psychiatry 2021; 26:2137-2147. [PMID: 33479514 PMCID: PMC8292427 DOI: 10.1038/s41380-020-00986-y] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Revised: 11/22/2020] [Accepted: 12/03/2020] [Indexed: 12/12/2022]
Abstract
Low reward responsiveness (RR) is associated with poor psychological well-being, psychiatric disorder risk, and psychotropic treatment resistance. Functional MRI studies have reported decreased activity within the brain's reward network in individuals with RR deficits, however the neurochemistry underlying network hypofunction in those with low RR remains unclear. This study employed ultra-high field glutamate chemical exchange saturation transfer (GluCEST) imaging to investigate the hypothesis that glutamatergic deficits within the reward network contribute to low RR. GluCEST images were acquired at 7.0 T from 45 participants (ages 15-29, 30 females) including 15 healthy individuals, 11 with depression, and 19 with psychosis spectrum symptoms. The GluCEST contrast, a measure sensitive to local glutamate concentration, was quantified in a meta-analytically defined reward network comprised of cortical, subcortical, and brainstem regions. Associations between brain GluCEST contrast and Behavioral Activation System Scale RR scores were assessed using multiple linear regressions. Analyses revealed that reward network GluCEST contrast was positively and selectively associated with RR, but not other clinical features. Follow-up investigations identified that this association was driven by the subcortical reward network and network areas that encode the salience of valenced stimuli. We observed no association between RR and the GluCEST contrast within non-reward cortex. This study thus provides new evidence that reward network glutamate levels contribute to individual differences in RR. Decreased reward network excitatory neurotransmission or metabolism may be mechanisms driving reward network hypofunction and RR deficits. These findings provide a framework for understanding the efficacy of glutamate-modulating psychotropics such as ketamine for treating anhedonia.
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Affiliation(s)
- Valerie J. Sydnor
- Penn Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Bart Larsen
- Penn Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Christian Kohler
- Penn Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA;,Penn-CHOP Lifespan Brain Institute, University of Pennsylvania, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | - Andrew J. D. Crow
- Penn Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Sage L. Rush
- Penn Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Monica E. Calkins
- Penn Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA;,Penn-CHOP Lifespan Brain Institute, University of Pennsylvania, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | - Ruben C. Gur
- Penn Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA;,Penn-CHOP Lifespan Brain Institute, University of Pennsylvania, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | - Raquel E. Gur
- Penn Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA;,Penn-CHOP Lifespan Brain Institute, University of Pennsylvania, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | - Kosha Ruparel
- Penn Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA;,Penn-CHOP Lifespan Brain Institute, University of Pennsylvania, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | - Joseph W. Kable
- Department of Psychology, University of Pennsylvania, Philadelphia, PA, USA;,MindCORE, University of Pennsylvania, Philadelphia, PA, USA
| | - Jami F. Young
- Penn Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA;,Penn-CHOP Lifespan Brain Institute, University of Pennsylvania, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | - Sanjeev Chawla
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Mark A. Elliott
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Russell T. Shinohara
- Penn Statistics in Imaging and Visualization Endeavor, Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA;,Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | | | - Ravinder Reddy
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Daniel H. Wolf
- Penn Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA;,Penn-CHOP Lifespan Brain Institute, University of Pennsylvania, Children’s Hospital of Philadelphia, Philadelphia, PA, USA;,Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Theodore D. Satterthwaite
- Penn Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA;,Penn-CHOP Lifespan Brain Institute, University of Pennsylvania, Children’s Hospital of Philadelphia, Philadelphia, PA, USA;,Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - David R. Roalf
- Penn Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA;,Penn-CHOP Lifespan Brain Institute, University of Pennsylvania, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
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Lehoczky G, Mumme M, Pelttari K, Trofin R, Chawla S, Haug M, Egloff C, Jakob M, Martin I, Barbero A. New single-stage, arthroscopic cartilage regeneration therapy with nasal chondrocytes. Cytotherapy 2021. [DOI: 10.1016/s1465324921005016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
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Karlsson M, Yang Z, Chawla S, Delso N, Pukenas B, Elmér E, Hugerth M, Margulies SS, Ehinger J, Hansson MJ, Wang KKW, Kilbaugh TJ. Evaluation of Diffusion Tensor Imaging and Fluid Based Biomarkers in a Large Animal Trial of Cyclosporine in Focal Traumatic Brain Injury. J Neurotrauma 2021; 38:1870-1878. [PMID: 33191835 DOI: 10.1089/neu.2020.7317] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
All phase III trials evaluating medical treatments for traumatic brain injury (TBI), performed to date, have failed. To facilitate future success there is a need for novel outcome metrics that can bridge pre-clinical studies to clinical proof of concept trials. Our objective was to assess diffusion tensor imaging (DTI) and biofluid-based biomarkers as efficacy outcome metrics in a large animal study evaluating the efficacy of cyclosporine in TBI. This work builds on our previously published study that demonstrated a reduced volume of injury by 35% with cyclosporine treatment based on magnetic resonance imaging (MRI) results. A focal contusion injury was induced in piglets using a controlled cortical impact (CCI) device. Cyclosporine in a novel Cremophor/Kolliphor EL-free lipid emulsion, NeuroSTAT, was administered by continuous intravenous infusion for 5 days. The animals underwent DTI on day 5. Glial fibrillary acidic protein (GFAP), as a measure of astroglia injury, and neurofilament light (NF-L), as a measure of axonal injury, were measured in blood on days 1, 2, and 5, and in cerebrospinal fluid (CSF) on day 5 post-injury. Normalized fractional anisotropy (FA) was significantly (p = 0.027) higher in in the treatment group, indicating preserved tissue integrity with treatment. For the biomarkers, we observed a statistical trend of a decreased level of NF-L in CSF (p = 0.051), in the treatment group relative to placebo, indicating less axonal injury. Our findings suggest that DTI, and possibly CSF NF-L, may be feasible as translational end-points assessing neuroprotective drugs in TBI.
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Affiliation(s)
- Michael Karlsson
- Department of Neurosurgery, Rigshospitalet, Copenhagen, Denmark.,Mitochondrial Medicine, Department of Clinical Sciences, Lund University, Lund, Sweden.,Department of Anesthesiology and Critical Care, Children's Hospital of Philadelphia, Perelman School of Medicine at University of Pennsylvania, Philadelphia, USA
| | - Zhihui Yang
- Program for Neurotrauma, Neuroproteomics, and Biomarkers Research, Department of Emergency Medicine, University of Florida, Gainesville, Florida, USA
| | - Sanjeev Chawla
- Department of Radiology, Perelman School of Medicine at University of Pennsylvania, Philadelphia, USA
| | - Nile Delso
- Department of Anesthesiology and Critical Care, Children's Hospital of Philadelphia, Perelman School of Medicine at University of Pennsylvania, Philadelphia, USA
| | - Bryan Pukenas
- Department of Radiology, Perelman School of Medicine at University of Pennsylvania, Philadelphia, USA
| | - Eskil Elmér
- Mitochondrial Medicine, Department of Clinical Sciences, Lund University, Lund, Sweden.,Abliva AB, Lund, Sweden
| | | | - Susan S Margulies
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia, USA
| | - Johannes Ehinger
- Mitochondrial Medicine, Department of Clinical Sciences, Lund University, Lund, Sweden
| | - Magnus J Hansson
- Mitochondrial Medicine, Department of Clinical Sciences, Lund University, Lund, Sweden.,Abliva AB, Lund, Sweden
| | - Kevin K W Wang
- Program for Neurotrauma, Neuroproteomics, and Biomarkers Research, Department of Emergency Medicine, University of Florida, Gainesville, Florida, USA
| | - Todd J Kilbaugh
- Department of Anesthesiology and Critical Care, Children's Hospital of Philadelphia, Perelman School of Medicine at University of Pennsylvania, Philadelphia, USA
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Yoon SY, Hunter JE, Chawla S, Clarke DL, Molony C, O'Donnell PA, Bagel JH, Kumar M, Poptani H, Vite CH, Wolfe JH. Global CNS correction in a large brain model of human alpha-mannosidosis by intravascular gene therapy. Brain 2020; 143:2058-2072. [PMID: 32671406 DOI: 10.1093/brain/awaa161] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2019] [Revised: 03/06/2020] [Accepted: 04/02/2020] [Indexed: 12/15/2022] Open
Abstract
Intravascular injection of certain adeno-associated virus vector serotypes can cross the blood-brain barrier to deliver a gene into the CNS. However, gene distribution has been much more limited within the brains of large animals compared to rodents, rendering this approach suboptimal for treatment of the global brain lesions present in most human neurogenetic diseases. The most commonly used serotype in animal and human studies is 9, which also has the property of being transported via axonal pathways to distal neurons. A small number of other serotypes share this property, three of which were tested intravenously in mice compared to 9. Serotype hu.11 transduced fewer cells in the brain than 9, rh8 was similar to 9, but hu.32 mediated substantially greater transduction than the others throughout the mouse brain. To evaluate the potential for therapeutic application of the hu.32 serotype in a gyrencephalic brain of larger mammals, a hu.32 vector expressing the green fluorescent protein reporter gene was evaluated in the cat. Transduction was widely distributed in the cat brain, including in the cerebral cortex, an important target since mental retardation is an important component of many of the human neurogenetic diseases. The therapeutic potential of a hu.32 serotype vector was evaluated in the cat homologue of the human lysosomal storage disease alpha-mannosidosis, which has globally distributed lysosomal storage lesions in the brain. Treated alpha-mannosidosis cats had reduced severity of neurological signs and extended life spans compared to untreated cats. The extent of therapy was dose dependent and intra-arterial injection was more effective than intravenous delivery. Pre-mortem, non-invasive magnetic resonance spectroscopy and diffusion tensor imaging detected differences between the low and high doses, and showed normalization of grey and white matter imaging parameters at the higher dose. The imaging analysis was corroborated by post-mortem histological analysis, which showed reversal of histopathology throughout the brain with the high dose, intra-arterial treatment. The hu.32 serotype would appear to provide a significant advantage for effective treatment of the gyrencephalic brain by systemic adeno-associated virus delivery in human neurological diseases with widespread brain lesions.
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Affiliation(s)
- Sea Young Yoon
- Research Institute of Children's Hospital of Philadelphia, Philadelphia, USA
| | - Jacqueline E Hunter
- Research Institute of Children's Hospital of Philadelphia, Philadelphia, USA
| | - Sanjeev Chawla
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
| | - Dana L Clarke
- W.F. Goodman Center for Comparative Medical Genetics, School of Veterinary Medicine, University of Pennsylvania, Philadelphia, USA
| | - Caitlyn Molony
- W.F. Goodman Center for Comparative Medical Genetics, School of Veterinary Medicine, University of Pennsylvania, Philadelphia, USA
| | - Patricia A O'Donnell
- W.F. Goodman Center for Comparative Medical Genetics, School of Veterinary Medicine, University of Pennsylvania, Philadelphia, USA
| | - Jessica H Bagel
- W.F. Goodman Center for Comparative Medical Genetics, School of Veterinary Medicine, University of Pennsylvania, Philadelphia, USA
| | - Manoj Kumar
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
| | - Harish Poptani
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
| | - Charles H Vite
- W.F. Goodman Center for Comparative Medical Genetics, School of Veterinary Medicine, University of Pennsylvania, Philadelphia, USA
| | - John H Wolfe
- Research Institute of Children's Hospital of Philadelphia, Philadelphia, USA.,W.F. Goodman Center for Comparative Medical Genetics, School of Veterinary Medicine, University of Pennsylvania, Philadelphia, USA.,Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
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Karpf L, Chawla S, Desiderio L, Mohan S. NCOG-26. IMPACT OF GENDER ON TUMOR TREATING FIELDS COMPLIANCE IN PATIENTS WITH GLIOBLASTOMA. Neuro Oncol 2020. [DOI: 10.1093/neuonc/noaa215.564] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Abstract
BACKGROUND
Tumor treating fields (TTFields) has emerged as a novel antimitotic modality to treat glioblastoma (GBM). Recently, a positive association was reported between TTFields dose at the tumor bed and survival outcomes in GBM patients. Dose density depends upon power density and compliance rate (cumulative amount of time TTFields therapy is delivered to the patient). Increased compliance with TTFields has been proposed as an independent prognostic factor for improved clinical benefits. There is evidence that females tend to respond better than males to standard therapy. However, the impact of gender and age on TTFields compliance is not fully understood in GBM patients.
OBJECTIVE
To investigate potential interactions amongst age, gender and TTFields compliance in GBM patients.
METHODS
A cohort of 16 patients (males =9; females=7; mean-age=60.8±7.6years) with newly diagnosed and recurrent GBM receiving TTFields were analyzed retrospectively. Device usage time was collected from internal log files in each case. The mean duration of TTFields therapy in patients was 4 months. Chi-square and independent sample T-tests were performed to evaluate differences in compliance rates based on patient age and gender and to examine gender-age relationships. Additionally, Pearson correlation analyses were performed to determine associations between gender and compliance rates. The probability (p) value of 0.05 was considered significant.
RESULTS
A trend (p=0.067) towards greater TTFields compliance was observed in females (80.1±0.11%) versus males (63.0±0.22%). Additionally, there was a strong positive correlation (R=0.73; p=0.058) between age and compliance rates for female patients. There were 6 patients ≥ 65 years and 10 patients < 65 years. However, we did not find significant differences in compliance rate and gender variables between patients ≥ 65 years and < 65 years of age.
CONCLUSIONS
Our results demonstrate gender influences TTFields compliance amongst GBM patients. However, future studies with larger cohorts are warranted to validate these findings.
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Affiliation(s)
- Lauren Karpf
- University of Pennsylvania, Philadelphia, PA, USA
| | - Sanjeev Chawla
- Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | | | - Suyash Mohan
- Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
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Chawla S, Wang S, Nazem A, Burke M, MacLean N, Bagley S, Brem S, Mohan S. NIMG-39. UTILITY OF PHYSIOLOGIC MR METRICS IN DISTINGUISHING TRUE-PROGRESSION FROM PSEUDOPROGRESSION IN GLIOBLASTOMAS STRATIFIED BY MGMT PROMOTER METHYLATION. Neuro Oncol 2020. [DOI: 10.1093/neuonc/noaa215.652] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Abstract
BACKGROUND
Methylation of O6-methyl-guanine-methyl transferase MGMT gene promoter is associated with favorable prognosis in glioblastoma (GBM) patients treated with surgery and chemoradiation therapy (CRT).
OBJECTIVE
To investigate potential of diffusion and perfusion MR imaging in distinguishing TP from PsP in GBM patients stratified by MGMT status.
METHODS
A cohort of 92 patients demonstrating new/increasing enhancing lesions within six months of completion of CRT underwent 3T MR imaging. Median values of mean diffusivity (MD), fractional anisotropy (FA), anisotropy coefficients [linear(CL), planar (CP), and spherical (CS)] and maximum relative cerebral blood volume (rCBVmax) were computed from enhancing lesions. Patients were classified as TP (n=65) and PsP (n=27) based on histopathology or follow-up MRI scans. Mann-Whitney, independent-sample T-tests and receiver operating characteristic (ROC) curve analyses were performed to distinguish TP from PsP. Of 92 patients, MGMT status was available from 60 patients [MGMT-methylated (n=23) and MGMT-unmethylated (n=37)]. Statistical analyses were also performed in distinguishing TP (n=15) and PsP (n=8) from MGMT-methylated and MGMT-unmethylated subgroups (TP=28; PsP=9). A p-value of 0.05 was considered significant.
RESULTS
Significantly higher rCBVmax and FA and a trend towards higher CP were observed in TP compared to PsP. Among these parameters, rCBVmax had the best sensitivity=62%, specificity=68% and accuracy=67% in distinguishing TP from PsP. ROC analysis revealed sensitivity=54%, specificity=78% and accuracy=68% after combination of these parameters. In MGMT methylated patients, only rCBVmax was significantly higher in TP than in PsP with sensitivity=79%, specificity=67% and accuracy=74% at a threshold rCBVmax value of 2.23. In MGMT unmethylated group, a trend towards higher rCBVmax was observed in TP than in PsP with sensitivity=67%, specificity=77%, accuracy=69%, threshold value=2.89.
CONCLUSION
Physiologic imaging parameters demonstrate variable diagnostic values for detecting PsP in GBM patients stratified by MGMT status. The best parameter in distinguishing TP from PsP was rCBVmax in patients demonstrating MGMT promoter methylation.
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Affiliation(s)
- Sanjeev Chawla
- Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Sumei Wang
- Lenox Hill Hospital, Northwell Health, New York, NY, USA
| | - Amir Nazem
- Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Morgan Burke
- Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Nasrallah MacLean
- Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Stephen Bagley
- Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Steven Brem
- Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Suyash Mohan
- Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
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Chawla S, Kim SG, Loevner LA, Wang S, Mohan S, Lin A, Poptani H. Prediction of distant metastases in patients with squamous cell carcinoma of head and neck using DWI and DCE-MRI. Head Neck 2020; 42:3295-3306. [PMID: 32737951 DOI: 10.1002/hed.26386] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2019] [Revised: 05/30/2020] [Accepted: 06/26/2020] [Indexed: 12/20/2022] Open
Abstract
BACKGROUND The primary purpose was to evaluate the prognostic potential of diffusion imaging (DWI) and dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) in predicting distant metastases in squamous cell carcinoma of head and neck (HNSCC) patients. The secondary aim was to examine differences in DWI and DCE-MRI-derived parameters on the basis of human papilloma virus (HPV) status, differentiation grade, and nodal stage of HNSCC. METHODS Fifty-six patients underwent pretreatment DWI and DCE-MRI. Patients were divided into groups who subsequently did (n = 12) or did not develop distant metastases (n = 44). Median values of apparent diffusion coefficient (ADC), volume transfer constant (Ktrans ), and mean intracellular water-lifetime (τi ) and volume were computed from metastatic lymph nodes and were compared between two groups. Prognostic utility of HPV status, differentiation grading, and nodal staging was also evaluated both in isolation or in combination with MRI parameters in distinguishing patients with and without distant metastases. Additionally, MRI parameters were compared between two groups based on dichotomous HPV status, differentiation grade, and nodal stage. RESULTS Lower but not significantly different Ktrans (0.51 ± 0.15 minute-1 vs 0.60 ± 0.05 minute-1 ) and not significantly different τi (0.13 ± 0.03 second vs 0.19 ± 0.02 second) were observed in patients who developed distant metastases than those who did not. Additionally, no significant differences in ADC or volume were found. τi, was the best parameter in discriminating two groups with moderate sensitivity (67%) and specificity (61.4%). Multivariate logistic regression analyses did not improve the overall prognostic performance for combination of all variables. A trend toward higher τi was observed in HPV-positive patients than those with HPV-negative patients. Also, a trend toward higher Ktrans was observed in poorly differentiated HNSCCs than those with moderately differentiated HNSCCs. CONCLUSION Pretreatment DCE-MRI may be useful in predicting distant metastases in HNSCC.
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Affiliation(s)
- Sanjeev Chawla
- Department of Radiology, Perelman School of Medicine, the University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Sungheon G Kim
- Department of Radiology, Perelman School of Medicine, the University of Pennsylvania, Philadelphia, Pennsylvania, USA.,Department of Radiology, New York University Langone Medical Center, New York, New York, USA
| | - Laurie A Loevner
- Department of Radiology, Perelman School of Medicine, the University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Sumei Wang
- Department of Radiology, Perelman School of Medicine, the University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Suyash Mohan
- Department of Radiology, Perelman School of Medicine, the University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Alexander Lin
- Department of Radiation Oncology, Perelman School of Medicine, the University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Harish Poptani
- Department of Radiology, Perelman School of Medicine, the University of Pennsylvania, Philadelphia, Pennsylvania, USA.,Department of Cellular and Molecular Physiology, University of Liverpool, Liverpool, UK
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Chawla S, Ge Y, Wuerfel J, Asadollahi S, Mohan S, Paul F, Sinnecker T, Kister I. Longitudinal ultra-high field MRI of brain lesions in neuromyelitis optica spectrum disorders. Mult Scler Relat Disord 2020; 42:102066. [PMID: 32272444 DOI: 10.1016/j.msard.2020.102066] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2019] [Revised: 02/19/2020] [Accepted: 03/20/2020] [Indexed: 11/16/2022]
Abstract
BACKGROUND In neuromyelitis optica spectrum disorder (NMOSD), clinical disability in NMOSD patients is relapse-related and progressive phase is rare. This observation raises the question whether there is any radiographic disease activity. The aim of present study was to determine the longitudinal changes in cerebral lesion number, lesion size, lesion-to-venule relationship, and morphological patterns of lesions in NMOSD using multiparametric 7T MR imaging. We also aimed to assess brain volume changes in NMOSD. METHODS A cohort of 22 patients with NMOSD underwent high-resolution 3D-susceptibility weighted imaging (SWI) and 2D-gradient-echo (GRE-T2*) weighted imaging on 7T MRI of brain at baseline and after ~2.8 years of follow-up. Morphologic imaging characteristics, and signal intensity patterns of lesions were recorded at both time points. Lesions were classified as "iron-laden" if they demonstrated hypointense signal on GRE-T2* images and/or SWI as well as hyperintense signal on quantitative susceptibility mapping (QSM). Lesions were considered "non-iron-laden" if they were hyperintense on GRE-T2*/SWI and isointense or hyperintense on QSM. Additionally, fractional brain parenchymal volume (fBPV) was computed at both time points. RESULTS A total of 169 lesions were observed at baseline. At follow-up, 6 new lesions were found in 5 patients. In one patient, a single lesion could not be detected on the follow-up scan. No appreciable change in lesion size and vessel-lesion relationship was observed at follow up. All lesions demonstrated hyperintense signal intensity on GRE-T2* weighted images and isointense signal on QSM at both time points. Therefore, these lesions were considered as non-associated with iron pathology. Additionally, no significant change in brain volume was observed: fBPV 0.78 ± 0.06 at baseline vs. 0.77 ± 0.05 at follow up, p>0.05. CONCLUSION Cerebral lesions in NMOSD patients remain 'inert' and do not show any substantial variations in morphological characteristics during a 2-3-year follow-up period.
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Affiliation(s)
- Sanjeev Chawla
- Center for Advanced Imaging Innovation and Research (CAI2R), Bernard and Irene Schwartz Center for Biomedical Imaging, United States; Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, United States.
| | - Yulin Ge
- Center for Advanced Imaging Innovation and Research (CAI2R), Bernard and Irene Schwartz Center for Biomedical Imaging, United States
| | - Jens Wuerfel
- MIAC AG and Department of Biomedical Engineering, University of Basel, Switzerland; NeuroCure Clinical Research Center and Experimental and Clinical Research Center, Max Delbrueck Center for Molecular Medicine, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Shadi Asadollahi
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, United States
| | - Suyash Mohan
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, United States
| | - Friedemann Paul
- NeuroCure Clinical Research Center and Experimental and Clinical Research Center, Max Delbrueck Center for Molecular Medicine, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Tim Sinnecker
- NeuroCure Clinical Research Center and Experimental and Clinical Research Center, Max Delbrueck Center for Molecular Medicine, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Ilya Kister
- Department of Neurology, New York University School of Medicine, Prague, New York, NY 10016, United States
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38
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Gonçalves FG, Chawla S, Mohan S. Emerging MRI Techniques to Redefine Treatment Response in Patients With Glioblastoma. J Magn Reson Imaging 2020; 52:978-997. [PMID: 32190946 DOI: 10.1002/jmri.27105] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2019] [Revised: 01/28/2020] [Accepted: 01/30/2020] [Indexed: 12/14/2022] Open
Abstract
Glioblastoma is the most common and most malignant primary brain tumor. Despite aggressive multimodal treatment, its prognosis remains poor. Even with continuous developments in MRI, which has provided us with newer insights into the diagnosis and understanding of tumor biology, response assessment in the posttherapy setting remains challenging. We believe that the integration of additional information from advanced neuroimaging techniques can further improve the diagnostic accuracy of conventional MRI. In this article, we review the utility of advanced neuroimaging techniques such as diffusion-weighted imaging, diffusion tensor imaging, perfusion-weighted imaging, proton magnetic resonance spectroscopy, and chemical exchange saturation transfer in characterizing and evaluating treatment response in patients with glioblastoma. We will also discuss the existing challenges and limitations of using these techniques in clinical settings and possible solutions to avoiding pitfalls in study design, data acquisition, and analysis for future studies. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY STAGE: 3 J. Magn. Reson. Imaging 2020;52:978-997.
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Affiliation(s)
| | - Sanjeev Chawla
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Suyash Mohan
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA
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39
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Kamesh Iyer S, Moon BF, Josselyn N, Ruparel K, Roalf D, Song JW, Guiry S, Ware JB, Kurtz RM, Chawla S, Nabavizadeh SA, Witschey WR. Data-Driven Quantitative Susceptibility Mapping Using Loss Adaptive Dipole Inversion (LADI). J Magn Reson Imaging 2020; 52:823-835. [PMID: 32128914 DOI: 10.1002/jmri.27103] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2019] [Revised: 01/31/2020] [Accepted: 02/01/2020] [Indexed: 02/04/2023] Open
Abstract
BACKGROUND Quantitative susceptibility mapping (QSM) uses prior information to reconstruct maps, but prior information may not show pathology and introduce inconsistencies with susceptibility maps, degrade image quality and inadvertently smoothing image features. PURPOSE To develop a local field data-driven QSM reconstruction that does not depend on spatial edge prior information. STUDY TYPE Retrospective. SUBJECTS, ANIMAL MODELS A dataset from 2016 ISMRM QSM Challenge, 11 patients with glioblastoma, a patient with microbleeds and porcine heart. SEQUENCE/FIELD STRENGTH 3D gradient echo sequence on 3T and 7T scanners. ASSESSMENT Accuracy was compared to Calculation of Susceptibility through Multiple Orientation Sampling (COSMOS), and several published techniques using region of interest (ROI) measurements, root-mean-squared error (RMSE), structural similarity index metric (SSIM), and high-frequency error norm (HFEN). Numerical ranking and semiquantitative image grading was performed by three expert observers to assess overall image quality (IQ) and image sharpness (IS). STATISTICAL TESTS Bland-Altman, Friedman test, and Conover multiple comparisons. RESULTS Loss adaptive dipole inversion (LADI) (β = 0.82, R2 = 0.96), morphology-enabled dipole inversion (MEDI) (β = 0.91, R2 = 0.97), and fast nonlinear susceptibility inversion (FANSI) (β = 0.81, R2 = 0.98) had excellent correlation with COSMOS and no bias was detected (bias = 0.006 ± 0.014, P < 0.05). In glioblastoma patients, LADI showed consistently better performance (IQGrade = 2.6 ± 0.4, ISGrade = 2.6 ± 0.3, IQRank = 3.5 ± 0.4, ISRank = 3.9 ± 0.2) compared with MEDI (IQGrade = 2.1 ± 0.3, ISGrade = 2 ± 0.5, IQRank = 2.4 ± 0.5, ISRank = 2.8 ± 0.2) and FANSI (IQGrade = 2.2 ± 0.5, ISGrade = 2 ± 0.4, IQRank = 2.8 ± 0.3, ISRank = 2.1 ± 0.2). Dark artifact visible near the infarcted region in MEDI (InfMEDI = -0.27 ± 0.06 ppm) was better mitigated by FANSI (InfFANSI-TGV = -0.17 ± 0.05 ppm) and LADI (InfLADI = -0.18 ± 0.05 ppm). CONCLUSION For neuroimaging applications, LADI preserved image sharpness and fine features in glioblastoma and microbleed patients. LADI performed better at mitigating artifacts in cardiac QSM. EVIDENCE LEVEL 4 TECHNICAL EFFICACY STAGE: 1 J. Magn. Reson. Imaging 2020;52:823-835.
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Affiliation(s)
- Srikant Kamesh Iyer
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Brianna F Moon
- Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Nicholas Josselyn
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Kosha Ruparel
- Department of Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - David Roalf
- Department of Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Jae W Song
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Samantha Guiry
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Jeffrey B Ware
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Robert M Kurtz
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Sanjeev Chawla
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - S Ali Nabavizadeh
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Walter R Witschey
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
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Zakaria R, Chen YJ, Hughes DM, Wang S, Chawla S, Poptani H, Berghoff AS, Preusser M, Jenkinson MD, Mohan S. Does the application of diffusion weighted imaging improve the prediction of survival in patients with resected brain metastases? A retrospective multicenter study. Cancer Imaging 2020; 20:16. [PMID: 32028999 PMCID: PMC7006156 DOI: 10.1186/s40644-020-0295-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2019] [Accepted: 01/22/2020] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Brain metastases are common in clinical practice. Many clinical scales exist for predicting survival and hence deciding on best treatment but none are individualised and none use quantitative imaging parameters. A multicenter study was carried out to evaluate the prognostic utility of a simple diffusion weighted MRI parameter, tumor apparent diffusion coefficient (ADC). METHODS A retrospective analysis of imaging and clinical data was performed on a cohort of 223 adult patients over a ten-year period 2002-2012 pooled from three institutions. All patients underwent surgical resection with histologically confirmed brain metastases and received adjuvant whole brain radiotherapy and/or chemotherapy. Survival was modelled using standard clinical variables and statistically compared with and without the addition of tumor ADC. RESULTS The median overall survival was 9.6 months (95% CI 7.5-11.7) for this cohort. Greater age (p = 0.002), worse performance status (p < 0.0001) and uncontrolled extracranial disease (p < 0.0001) were all significantly associated with shorter survival in univariate analysis. Adjuvant whole brain radiotherapy (p = 0.007) and higher tumor ADC (p < 0.001) were associated with prolonged survival. Combining values of tumor ADC with conventional clinical scoring systems such as the Graded Prognostic Assessment (GPA) score significantly improved the modelling of survival (e.g. concordance increased from 0.5956 to 0.6277 with Akaike's Information Criterion reduced from 1335 to 1324). CONCLUSIONS Combining advanced MRI readings such as tumor ADC with clinical scoring systems is a potentially simple method for improving and individualising the estimation of survival in patients having surgery for brain metastases.
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Affiliation(s)
- Rasheed Zakaria
- Department of Neurosurgery, The Walton Centre NHS Foundation Trust, Liverpool, UK. .,Institute of Integrative Biology, University of Liverpool, Liverpool, UK.
| | - Yin Jie Chen
- Division of Neuroradiology, Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, USA
| | | | - Sumei Wang
- Division of Neuroradiology, Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, USA
| | - Sanjeev Chawla
- Division of Neuroradiology, Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, USA
| | - Harish Poptani
- Institute of Translational Medicine, University of Liverpool, Liverpool, UK
| | - Anna S Berghoff
- Department of Medicine I, Division of Oncology, Medical University of Vienna, Vienna, Austria
| | - Matthias Preusser
- Department of Medicine I, Division of Oncology, Medical University of Vienna, Vienna, Austria
| | - Michael D Jenkinson
- Department of Neurosurgery, The Walton Centre NHS Foundation Trust, Liverpool, UK.,Institute of Translational Medicine, University of Liverpool, Liverpool, UK
| | - Suyash Mohan
- Division of Neuroradiology, Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, USA
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Chawla S, Chameettachal S, Ghosh S. Corrigendum to “Probing the role of scaffold dimensionality and media composition on matrix production and phenotype of fibroblasts” [Mater. Sci. Eng. C Mater. Biol. Appl. 49 (2015) 588–596]. Materials Science and Engineering: C 2019; 105:110147. [DOI: 10.1016/j.msec.2019.110147] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
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Ocean A, Noel M, Wang-Gillam A, Chawla S, Chung V, Pant S, Korn R, De Priore G, Picozzi V. Phase II monotherapy efficacy of cancer metabolism targeting SM-88 in heavily pre-treated PDAC patients. Ann Oncol 2019. [DOI: 10.1093/annonc/mdz247.046] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
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Lee A, Ehsanullah J, Chawla S, Shenoy D, Fertleman M. 17IMPROVING PERIOPERATIVE CARE IN PATIENTS OVER 60 YEARS WITH A FRACTURED NECK OF FEMUR. Age Ageing 2019. [DOI: 10.1093/ageing/afz055.17] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Affiliation(s)
- A Lee
- Orthogeriatric Department, St Mary’s Hospital, London
| | - J Ehsanullah
- Orthogeriatric Department, St Mary’s Hospital, London
| | - S Chawla
- Orthogeriatric Department, St Mary’s Hospital, London
| | - D Shenoy
- Orthogeriatric Department, St Mary’s Hospital, London
| | - M Fertleman
- Orthogeriatric Department, St Mary’s Hospital, London
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Noel M, Wang-Gillam A, Ocean A, Chawla S, Chung V, DelPriore G, Picozzi V. SM-88 therapy in high-risk poor prognosis pancreatic cancer (PDAC). Ann Oncol 2019. [DOI: 10.1093/annonc/mdz155.058] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
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Chawla S, Lee SC, Mohan S, Wang S, Nasrallah M, Vossough A, Krejza J, Melhem ER, Nabavizadeh SA. Lack of choline elevation on proton magnetic resonance spectroscopy in grade I-III gliomas. Neuroradiol J 2019; 32:250-258. [PMID: 31050313 DOI: 10.1177/1971400919846509] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023] Open
Abstract
Elevated levels of choline are generally emphasized as marker of increased cellularity and cell membrane turnover in gliomas. In this study, we investigated the incidence rate of lack of choline/creatine and choline/water elevation in a population of grade I-III gliomas. A cohort of 41 patients with histopathologically confirmed gliomas underwent multi-voxel proton magnetic resonance spectroscopy on a 3 T magnetic resonance system prior to treatment. Peak areas for choline and myoinositol were measured from all voxels that exhibited hyperintensity on fluid-attenuated inversion recovery images and were normalized to creatine and unsuppressed water from each voxel. The average metabolite/creatine and metabolite/water ratios from these voxels were then computed. Similarly, average metabolite ratios were computed from normal brain parenchyma. Gliomas were considered for lack of choline elevation when choline/creatine and choline/water ratios from neoplastic regions were less than those from normal brain parenchyma regions. Six of 41 (14.6%) grade I-III gliomas showed lack of elevation for choline/creatine and choline/water ratios compared to normal brain parenchyma. Four of these six gliomas also demonstrated elevated levels of myoinositol/creatine ratio. All other gliomas (n = 35) had elevated choline levels from neoplastic regions relative to normal parenchyma. The sensitivity of choline/creatine or choline/water in determining a grade I-III glioma was 85.4%. These findings suggest that a lack of choline/creatine or choline/water elevation may be seen in some gliomas and low choline levels should not prevent us from considering the possibility of a grade I-III glioma.
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Affiliation(s)
- Sanjeev Chawla
- 1 Departments of Radiology, Perelman School of Medicine at the University of Pennsylvania, USA
| | - Seung-Cheol Lee
- 1 Departments of Radiology, Perelman School of Medicine at the University of Pennsylvania, USA
| | - Suyash Mohan
- 1 Departments of Radiology, Perelman School of Medicine at the University of Pennsylvania, USA
| | - Sumei Wang
- 1 Departments of Radiology, Perelman School of Medicine at the University of Pennsylvania, USA
| | - MacLean Nasrallah
- 2 Department of Pathology and Laboratory Medicine, Perelman School of Medicine at the University of Pennsylvania, USA
| | - Arastoo Vossough
- 1 Departments of Radiology, Perelman School of Medicine at the University of Pennsylvania, USA.,3 Department of Radiology, Children's Hospital of Philadelphia, USA
| | - Jaroslaw Krejza
- 1 Departments of Radiology, Perelman School of Medicine at the University of Pennsylvania, USA.,4 Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, USA
| | - Elias R Melhem
- 1 Departments of Radiology, Perelman School of Medicine at the University of Pennsylvania, USA.,4 Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, USA
| | - S Ali Nabavizadeh
- 1 Departments of Radiology, Perelman School of Medicine at the University of Pennsylvania, USA
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Affiliation(s)
- S Chawla
- Chelsea and Westminster Hospital, Fulham Road, London, SW10 9NH, U.K
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47
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Schwartzberg L, Bhat G, Mezei K, Lang I, Moon YW, Senviratne L, Chawla S, Cobb P, Yang Z. Abstract P1-13-05: Efficacy and safety of eflapegrastim confirmed in reducing severe neutropenia in breast cancer patients treated with myelosuppressive chemotherapy in the second Phase 3 randomized controlled multinational trial compared to pegfilgrastim (RECOVER trial). Cancer Res 2019. [DOI: 10.1158/1538-7445.sabcs18-p1-13-05] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Abstract
Background:
Eflapegrastim is a novel investigational biologic comprised of recombinant human G-CSF covalently linked to the human immunoglobulin G4FC fragment using proprietary LAPSCOVERY™ technology with potentially unique distribution to areas rich in FcRn receptors. RECOVER is the second Phase 3 study to investigate the non-inferiority (NI) of eflapegrastim to pegfilgrastim in patients receiving chemotherapy for breast cancer. The first Phase 3 study, ADVANCE, has demonstrated the non-inferiority of eflapegrastim comparing to pegfilgrastim in the duration of severe neutropenia (DSN) in breast cancer patients receiving docetaxel and cyclophosphamide (TC) and was previously published at ASCO 2018 meeting.
TrialDesign:
Patients with Stage I to Stage IIIA breast cancer from centers in the USA, Canada, Poland, Hungary, South Korea and India were treated on Day 1 of each of four 21-day cycles with adjuvant or neo-adjuvant TC. On Day 2 of each cycle, patients received a single subcutaneous dose of either eflapegrastim 13.2 mg/0.6 mL (equivalent to 3.6 mg G-CSF) or pegfilgrastim (6 mg) in a 1:1 ratio. Patients had CBCs drawn on Day 1 prior to chemotherapy and Days 4-15 daily or until recovery of neutropenia in Cycle 1. CBC was also collected on Days 1, 4, 7, 10 and 15 in Cycles 2-4. The primary endpoint was to demonstrate the non-inferiority of eflapegrastim comparing to pegfilgrastim as measured by the mean DSN in Cycle 1 with NI margin of <0.62 day.
Results:
In a total of 237 intent-to-treat patients (randomized to 118 eflapegrastim; 119 pegfilgrastim), median age was 59 years (range 29 to 88 years); mean (SD) DSN was 0.31 (0.688) days for eflapegrastim and 0.39 (0.949) days for pegfilgrastim, demonstrating the non-inferiority (95% CI of ΔDSN: [-0.292, 0.129]; p<0.0001). Non-inferiority of eflapegrastim for DSN was maintained across all 4 cycles. There were no statistically significant differences in secondary endpoints: time to ANC recovery, depth of ANC nadir and incidence of FN at Cycle 1. The common Grade 3/4 adverse events observed in≥5%of patients were similar across both arms and were mainly hematologic including neutropenia, lymphopenia, anemia and leukopenia. Grade 3/4 bone pain and febrile neutropenia rates were similar across both arms and were less than 5%.
Conclusions:
Eflapegrastim, a novel long acting G-CSF demonstrated non-inferiority to pegfilgrastim in the reduction of DSN in breast cancer patients treated with TC and has validated the results from the first Phase 3 ADVANCE study. Eflapegrastim was safe and well-tolerated with a similar safety profile to pegfilgrastim.
Citation Format: Schwartzberg L, Bhat G, Mezei K, Lang I, Moon YW, Senviratne L, Chawla S, Cobb P, Yang Z. Efficacy and safety of eflapegrastim confirmed in reducing severe neutropenia in breast cancer patients treated with myelosuppressive chemotherapy in the second Phase 3 randomized controlled multinational trial compared to pegfilgrastim (RECOVER trial) [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P1-13-05.
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Affiliation(s)
- L Schwartzberg
- West Cancer Center, Germantown, TN; Spectrum Pharmaceuticals, Irvine, CA; Szabolcs-Szatmar-Bereg Megyei Korhazak es Egyetemi Oktato Korhaz, Onkologiai Osztaly, Nyiregyhaza, Hungary; Orszagos Onkologiai Intezet, "B" Belgyogyaszati Onkologiai Osztaly, Budapest, Hungary; Cha Bundang Medical Center, Seongnam, Republic of Korea; Los Angeles Hematology and Oncology Medical Group, Los Angeles, CA; St Vincent Frontier Cancer Center, Billings, MT
| | - G Bhat
- West Cancer Center, Germantown, TN; Spectrum Pharmaceuticals, Irvine, CA; Szabolcs-Szatmar-Bereg Megyei Korhazak es Egyetemi Oktato Korhaz, Onkologiai Osztaly, Nyiregyhaza, Hungary; Orszagos Onkologiai Intezet, "B" Belgyogyaszati Onkologiai Osztaly, Budapest, Hungary; Cha Bundang Medical Center, Seongnam, Republic of Korea; Los Angeles Hematology and Oncology Medical Group, Los Angeles, CA; St Vincent Frontier Cancer Center, Billings, MT
| | - K Mezei
- West Cancer Center, Germantown, TN; Spectrum Pharmaceuticals, Irvine, CA; Szabolcs-Szatmar-Bereg Megyei Korhazak es Egyetemi Oktato Korhaz, Onkologiai Osztaly, Nyiregyhaza, Hungary; Orszagos Onkologiai Intezet, "B" Belgyogyaszati Onkologiai Osztaly, Budapest, Hungary; Cha Bundang Medical Center, Seongnam, Republic of Korea; Los Angeles Hematology and Oncology Medical Group, Los Angeles, CA; St Vincent Frontier Cancer Center, Billings, MT
| | - I Lang
- West Cancer Center, Germantown, TN; Spectrum Pharmaceuticals, Irvine, CA; Szabolcs-Szatmar-Bereg Megyei Korhazak es Egyetemi Oktato Korhaz, Onkologiai Osztaly, Nyiregyhaza, Hungary; Orszagos Onkologiai Intezet, "B" Belgyogyaszati Onkologiai Osztaly, Budapest, Hungary; Cha Bundang Medical Center, Seongnam, Republic of Korea; Los Angeles Hematology and Oncology Medical Group, Los Angeles, CA; St Vincent Frontier Cancer Center, Billings, MT
| | - YW Moon
- West Cancer Center, Germantown, TN; Spectrum Pharmaceuticals, Irvine, CA; Szabolcs-Szatmar-Bereg Megyei Korhazak es Egyetemi Oktato Korhaz, Onkologiai Osztaly, Nyiregyhaza, Hungary; Orszagos Onkologiai Intezet, "B" Belgyogyaszati Onkologiai Osztaly, Budapest, Hungary; Cha Bundang Medical Center, Seongnam, Republic of Korea; Los Angeles Hematology and Oncology Medical Group, Los Angeles, CA; St Vincent Frontier Cancer Center, Billings, MT
| | - L Senviratne
- West Cancer Center, Germantown, TN; Spectrum Pharmaceuticals, Irvine, CA; Szabolcs-Szatmar-Bereg Megyei Korhazak es Egyetemi Oktato Korhaz, Onkologiai Osztaly, Nyiregyhaza, Hungary; Orszagos Onkologiai Intezet, "B" Belgyogyaszati Onkologiai Osztaly, Budapest, Hungary; Cha Bundang Medical Center, Seongnam, Republic of Korea; Los Angeles Hematology and Oncology Medical Group, Los Angeles, CA; St Vincent Frontier Cancer Center, Billings, MT
| | - S Chawla
- West Cancer Center, Germantown, TN; Spectrum Pharmaceuticals, Irvine, CA; Szabolcs-Szatmar-Bereg Megyei Korhazak es Egyetemi Oktato Korhaz, Onkologiai Osztaly, Nyiregyhaza, Hungary; Orszagos Onkologiai Intezet, "B" Belgyogyaszati Onkologiai Osztaly, Budapest, Hungary; Cha Bundang Medical Center, Seongnam, Republic of Korea; Los Angeles Hematology and Oncology Medical Group, Los Angeles, CA; St Vincent Frontier Cancer Center, Billings, MT
| | - P Cobb
- West Cancer Center, Germantown, TN; Spectrum Pharmaceuticals, Irvine, CA; Szabolcs-Szatmar-Bereg Megyei Korhazak es Egyetemi Oktato Korhaz, Onkologiai Osztaly, Nyiregyhaza, Hungary; Orszagos Onkologiai Intezet, "B" Belgyogyaszati Onkologiai Osztaly, Budapest, Hungary; Cha Bundang Medical Center, Seongnam, Republic of Korea; Los Angeles Hematology and Oncology Medical Group, Los Angeles, CA; St Vincent Frontier Cancer Center, Billings, MT
| | - Z Yang
- West Cancer Center, Germantown, TN; Spectrum Pharmaceuticals, Irvine, CA; Szabolcs-Szatmar-Bereg Megyei Korhazak es Egyetemi Oktato Korhaz, Onkologiai Osztaly, Nyiregyhaza, Hungary; Orszagos Onkologiai Intezet, "B" Belgyogyaszati Onkologiai Osztaly, Budapest, Hungary; Cha Bundang Medical Center, Seongnam, Republic of Korea; Los Angeles Hematology and Oncology Medical Group, Los Angeles, CA; St Vincent Frontier Cancer Center, Billings, MT
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Verma G, Chawla S, Mohan S, Wang S, Nasrallah M, Sheriff S, Desai A, Brem S, O'Rourke DM, Wolf RL, Maudsley AA, Poptani H. Three-dimensional echo planar spectroscopic imaging for differentiation of true progression from pseudoprogression in patients with glioblastoma. NMR Biomed 2019; 32:e4042. [PMID: 30556932 PMCID: PMC6519064 DOI: 10.1002/nbm.4042] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/24/2018] [Revised: 10/30/2018] [Accepted: 10/31/2018] [Indexed: 05/20/2023]
Abstract
Accurate differentiation of true progression (TP) from pseudoprogression (PsP) in patients with glioblastomas (GBMs) is essential for planning adequate treatment and for estimating clinical outcome measures and future prognosis. The purpose of this study was to investigate the utility of three-dimensional echo planar spectroscopic imaging (3D-EPSI) in distinguishing TP from PsP in GBM patients. For this institutional review board approved and HIPAA compliant retrospective study, 27 patients with GBM demonstrating enhancing lesions within six months of completion of concurrent chemo-radiation therapy were included. Of these, 18 were subsequently classified as TP and 9 as PsP based on histological features or follow-up MRI studies. Parametric maps of choline/creatine (Cho/Cr) and choline/N-acetylaspartate (Cho/NAA) were computed and co-registered with post-contrast T1 -weighted and FLAIR images. All lesions were segmented into contrast enhancing (CER), immediate peritumoral (IPR), and distal peritumoral (DPR) regions. For each region, Cho/Cr and Cho/NAA ratios were normalized to corresponding metabolite ratios from contralateral normal parenchyma and compared between TP and PsP groups. Logistic regression analyses were performed to obtain the best model to distinguish TP from PsP. Significantly higher Cho/NAA was observed from CER (2.69 ± 1.00 versus 1.56 ± 0.51, p = 0.003), IPR (2.31 ± 0.92 versus 1.53 ± 0.56, p = 0.030), and DPR (1.80 ± 0.68 versus 1.19 ± 0.28, p = 0.035) regions in TP patients compared with those with PsP. Additionally, significantly elevated Cho/Cr (1.74 ± 0.44 versus 1.34 ± 0.26, p = 0.023) from CER was observed in TP compared with PsP. When these parameters were incorporated in multivariate regression analyses, a discriminatory model with a sensitivity of 94% and a specificity of 87% was observed in distinguishing TP from PsP. These results indicate the utility of 3D-EPSI in differentiating TP from PsP with high sensitivity and specificity.
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Affiliation(s)
- Gaurav Verma
- Department of RadiologyPerelman School of Medicine at the University of PennsylvaniaPhiladelphiaPAUSA
| | - Sanjeev Chawla
- Department of RadiologyPerelman School of Medicine at the University of PennsylvaniaPhiladelphiaPAUSA
| | - Suyash Mohan
- Department of RadiologyPerelman School of Medicine at the University of PennsylvaniaPhiladelphiaPAUSA
| | - Sumei Wang
- Department of RadiologyPerelman School of Medicine at the University of PennsylvaniaPhiladelphiaPAUSA
| | - MacLean Nasrallah
- Department of Pathology and Lab MedicinePerelman School of Medicine at the University of PennsylvaniaPhiladelphiaPAUSA
| | | | - Arati Desai
- Department of Hematology‐OncologyPerelman School of Medicine at the University of PennsylvaniaPhiladelphiaPAUSA
| | - Steven Brem
- Department of NeurosurgeryPerelman School of Medicine at the University of PennsylvaniaPhiladelphiaPAUSA
| | - Donald M. O'Rourke
- Department of NeurosurgeryPerelman School of Medicine at the University of PennsylvaniaPhiladelphiaPAUSA
| | - Ronald L. Wolf
- Department of RadiologyPerelman School of Medicine at the University of PennsylvaniaPhiladelphiaPAUSA
| | | | - Harish Poptani
- Department of RadiologyPerelman School of Medicine at the University of PennsylvaniaPhiladelphiaPAUSA
- Department of Cellular and Molecular PhysiologyUniversity of LiverpoolLiverpoolUK
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Mohan S, Wang S, Coban G, Kural F, Chawla S, O'Rourke DM, Poptani H. Detection of occult neoplastic infiltration in the corpus callosum and prediction of overall survival in patients with glioblastoma using diffusion tensor imaging. Eur J Radiol 2019; 112:106-111. [PMID: 30777198 DOI: 10.1016/j.ejrad.2019.01.015] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2018] [Revised: 11/29/2018] [Accepted: 01/14/2019] [Indexed: 01/22/2023]
Abstract
OBJECTIVE Corpus callosum (CC) involvement is a poor prognostic factor in patients with glioblastoma (GBM). The purpose of this study was to determine whether diffusion tensor imaging (DTI) can quantify occult tumor infiltration in the CC and predict the overall survival in GBM patients. METHODS Forty-eight patients with pathologically proven GBM and 17 normal subjects were included in this retrospective study. Patients were divided into four groups based on CC invasion and overall survival: long survivors without CC invasion; short survivors without CC invasion; long survivors with CC invasion; short survivors with CC invasion. All patients underwent DTI at 3T MRI scanner. Fractional anisotropy (FA) and mean diffusivity (MD) values were measured from genu, mid-body, and splenium of the CC. The mean values of these parameters were compared between different groups and Kaplan Meier curves were used for prediction of overall survival. RESULTS Patients with short survival and CC invasion had the lowest FA values (0.64 ± 0.05) from the CC compared with other groups (p < 0.05). Receiver operator characteristic curve (ROC) analysis indicated that a FA cutoff value of 0.70 was the best predictor for overall survival with an area under the curve (AUC) of 0.77, sensitivity 1, specificity 0.59. Kaplan-Meier survival curves demonstrated that the mean survival time was significantly longer for patients with high FA (>0.70) compared with those with low FA (<0.70) (p < 0.001). CONCLUSIONS FA values from the CC can quantify occult tumor infiltration and serve as a sensitive prognostic marker for prediction of overall survival in GBM patients.
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Affiliation(s)
- Suyash Mohan
- Department of Radiology, Division of Neuroradiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA.
| | - Sumei Wang
- Department of Radiology, Division of Neuroradiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Gokcen Coban
- Department of Radiology, Hacettepe University Medical School, Ankara, Turkey
| | - Feride Kural
- Department of Radiology, Baskent University School of Medicine, Ankara, Turkey
| | - Sanjeev Chawla
- Department of Radiology, Division of Neuroradiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Donald M O'Rourke
- Department of Neurosurgery, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Harish Poptani
- Department of Radiology, Division of Neuroradiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA; Department of Cellular and Molecular Physiology, University of Liverpool, Liverpool, UK
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Wang S, O'Rourke DM, Chawla S, Verma G, Nasrallah MP, Morrissette JJD, Plesa G, June CH, Brem S, Maloney E, Desai A, Wolf RL, Poptani H, Mohan S. Multiparametric magnetic resonance imaging in the assessment of anti-EGFRvIII chimeric antigen receptor T cell therapy in patients with recurrent glioblastoma. Br J Cancer 2018; 120:54-56. [PMID: 30478409 PMCID: PMC6325110 DOI: 10.1038/s41416-018-0342-0] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2018] [Revised: 10/29/2018] [Accepted: 10/30/2018] [Indexed: 11/09/2022] Open
Abstract
EGFRvIII targeted chimeric antigen receptor T (CAR-T) cell therapy has recently been reported for treating glioblastomas (GBMs); however, physiology-based MRI parameters have not been evaluated in this setting. Ten patients underwent multiparametric MRI at baseline, 1, 2 and 3 months after CAR-T therapy. Logistic regression model derived progression probabilities (PP) using imaging parameters were used to assess treatment response. Four lesions from "early surgery" group demonstrated high PP at baseline suggestive of progression, which was confirmed histologically. Out of eight lesions from remaining six patients, three lesions with low PP at baseline remained stable. Two lesions with high PP at baseline were associated with large decreases in PP reflecting treatment response, whereas other two lesions with high PP at baseline continued to demonstrate progression. One patient didn't have baseline data but demonstrated progression on follow-up. Our findings indicate that multiparametric MRI may be helpful in monitoring CAR-T related early therapeutic changes in GBM patients.
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Affiliation(s)
- Sumei Wang
- Department of Radiology, Division of Neuroradiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Donald M O'Rourke
- Department of Neurosurgery, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Sanjeev Chawla
- Department of Radiology, Division of Neuroradiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Gaurav Verma
- Department of Radiology, Division of Neuroradiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - MacLean P Nasrallah
- Department of Pathology and Laboratory Medicine, Division of Neuropathology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Jennifer J D Morrissette
- Department of Pathology and Laboratory Medicine, Division of Precision and Computational Diagnostics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Gabriela Plesa
- Center for Cellular Immunotherapies, University of Pennsylvania, Philadelphia, PA, USA
| | - Carl H June
- Center for Cellular Immunotherapies, University of Pennsylvania, Philadelphia, PA, USA
| | - Steven Brem
- Department of Neurosurgery, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Eileen Maloney
- Department of Neurosurgery, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Arati Desai
- Department of Medicine, Division of Hematology-Oncology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Ronald L Wolf
- Department of Radiology, Division of Neuroradiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Harish Poptani
- Department of Radiology, Division of Neuroradiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA.,Department of Cellular and Molecular Physiology, University of Liverpool, Liverpool, UK
| | - Suyash Mohan
- Department of Radiology, Division of Neuroradiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA.
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