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Özdemir İ, Etyemez S, Barker PB. High-field downfield MR spectroscopic imaging in the human brain. Magn Reson Med 2024; 92:890-899. [PMID: 38469953 PMCID: PMC11209804 DOI: 10.1002/mrm.30075] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Revised: 02/07/2024] [Accepted: 02/19/2024] [Indexed: 03/13/2024]
Abstract
PURPOSE To investigate the feasibility of downfield MR spectroscopic imaging (DF-MRSI) in the human brain at 7T. METHODS A 7T DF-MRSI pulse sequence was implemented based on the previously described methodology at 3T, with 3D phase-encoding,1 3 ‾ 3 1 ‾ $$ 1\overline{3}3\overline{1} $$ spectral-spatial excitation, and frequency selective refocusing. Data were pre-processed followed by analysis using the "LCModel" software package, and metabolite maps created from the LCModel results. Total scan time, including brain MRI and a water-reference MRSI, was 24 min. The sequence was tested in 10 normal volunteers. Estimated metabolite levels and uncertainty values (Cramer Rao lower bounds, CRLBs) for nine downfield peaks were compared between seven different brain regions, anterior cingulate cortex (ACC), centrum semiovale (CSO), corpus callosum (CC), cerebellar vermis (CV), dorsolateral prefrontal cortex (DLPFC), posterior cingulate cortex (PCC), and thalamus (Thal). RESULTS DF peaks were relatively uniformly distributed throughout the brain, with only a small number of peaks showing any significant regional variations. Most DF peaks had average CRLB<25% in most brain regions. Average SNR values were higher for the brain regions ACC and DLPFC (˜7 ± 0.95, mean ± SD) while in a range of 3.4-6.0 for other brain regions. Average linewidth (FWHM) values were greater than 35 Hz in the ACC, CV, and Thal, and 22 Hz in CC, CSO, DLPFC, and PCC. CONCLUSION High-field DF-MRSI is able to spatially map exchangeable protons in the human brain at high resolution and with near whole-brain coverage in acceptable scan times, and in the future may be used to study metabolism of brain tumors or other neuropathological disorders.
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Affiliation(s)
- İpek Özdemir
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Semra Etyemez
- Department of Obstetrics & Gynecology, Weill Cornell Medicine, New York, NY
- Department of Psychiatry, Weill Cornell Medicine, New York, NY
| | - Peter B. Barker
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F.M. Kennedy Krieger Institute, Baltimore, MD, United States
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Liu C, Li Z, Chen Z, Zhao B, Zheng Z, Song X. Highly-accelerated CEST MRI using frequency-offset-dependent k-space sampling and deep-learning reconstruction. Magn Reson Med 2024; 92:688-701. [PMID: 38623899 DOI: 10.1002/mrm.30089] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Revised: 01/31/2024] [Accepted: 03/02/2024] [Indexed: 04/17/2024]
Abstract
PURPOSE To develop a highly accelerated CEST Z-spectral acquisition method using a specifically-designed k-space sampling pattern and corresponding deep-learning-based reconstruction. METHODS For k-space down-sampling, a customized pattern was proposed for CEST, with the randomized probability following a frequency-offset-dependent (FOD) function in the direction of saturation offset. For reconstruction, the convolution network (CNN) was enhanced with a Partially Separable (PS) function to optimize the spatial domain and frequency domain separately. Retrospective experiments on a self-acquired human brain dataset (13 healthy adults and 15 brain tumor patients) were conducted using k-space resampling. The prospective performance was also assessed on six healthy subjects. RESULTS In retrospective experiments, the combination of FOD sampling and PS network (FOD + PSN) showed the best quantitative metrics for reconstruction, outperforming three other combinations of conventional sampling with varying density and a regular CNN (nMSE and SSIM, p < 0.001 for healthy subjects). Across all acceleration factors from 4 to 14, the FOD + PSN approach consistently outperformed the comparative methods in four contrast maps including MTRasym, MTRrex, as well as the Lorentzian Difference maps of amide and nuclear Overhauser effect (NOE). In the subspace replacement experiment, the error distribution demonstrated the denoising benefits achieved in the spatial subspace. Finally, our prospective results obtained from healthy adults and brain tumor patients (14×) exhibited the initial feasibility of our method, albeit with less accurate reconstruction than retrospective ones. CONCLUSION The combination of FOD sampling and PSN reconstruction enabled highly accelerated CEST MRI acquisition, which may facilitate CEST metabolic MRI for brain tumor patients.
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Affiliation(s)
- Chuyu Liu
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, Tsinghua University, Beijing, China
| | - Zhongsen Li
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, Tsinghua University, Beijing, China
| | - Zhensen Chen
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
| | - Benqi Zhao
- Department of Radiology, Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua University, Beijing, China
| | - Zhuozhao Zheng
- Department of Radiology, Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua University, Beijing, China
| | - Xiaolei Song
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, Tsinghua University, Beijing, China
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Sun PZ. Quasi-steady-state (QUASS) reconstruction enhances T 1 normalization in apparent exchange-dependent relaxation (AREX) analysis: A reevaluation of T 1 correction in quantitative CEST MRI of rodent brain tumor models. Magn Reson Med 2024; 92:236-245. [PMID: 38380727 PMCID: PMC11055669 DOI: 10.1002/mrm.30056] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Revised: 01/26/2024] [Accepted: 02/04/2024] [Indexed: 02/22/2024]
Abstract
PURPOSE The apparent exchange-dependent relaxation (AREX) analysis has been proposed as an effective means to correct T1 contribution in CEST quantification. However, it has been recognized that AREX T1 correction is not straightforward if CEST scans are not performed under the equilibrium condition. Our study aimed to test if quasi-steady-state (QUASS) reconstruction could boost the accuracy of the AREX metric under common non-equilibrium scan conditions. THEORY AND METHODS Numerical simulation and in vivo scans were performed to assess the AREX metric accuracy. The CEST signal was simulated under different relaxation delays, RF saturation amplitudes, and durations. The AREX was evaluated as a function of the bulk water T1 and labile proton concentration using the multiple linear regression model. AREX MRI was also assessed in brain tumor rodent models, with both apparent CEST scans and QUASS reconstruction. RESULTS Simulation showed that the AREX calculation from apparent CEST scans, under non-equilibrium conditions, had significant dependence on labile proton fraction ratio, RF saturation time, and T1. In comparison, QUASS-boosted AREX depended on the labile proton fraction ratio without significant dependence on T1 and RF saturation time. Whereas the apparent (2.7 ± 0.8%) and QUASS MTR asymmetry (2.8 ± 0.8%) contrast between normal and tumor regions of interest (ROIs) were significant, the difference was small. In comparison, AREX contrast between normal and tumor ROIs calculated from the apparent CEST scan and QUASS reconstruction was 3.8 ± 1.1%/s and 4.4 ± 1.2%/s, respectively, statistically different from each other. CONCLUSIONS AREX analysis benefits from the QUASS-reconstructed equilibrium CEST effect for improved T1 correction and quantitative CEST analysis.
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Affiliation(s)
- Phillip Zhe Sun
- Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA
- Winship Cancer Institute, Emory University, Atlanta, GA
- Primate Imaging Center, Emory National Primate Research Center, Emory University, Atlanta, GA
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Obdeijn IV, Wiegers EC, Alic L, Plasschaert SLA, Kranendonk MEG, Hoogduin HM, Klomp DWJ, Wijnen JP, Lequin MH. Amide proton transfer weighted imaging in pediatric neuro-oncology: initial experience. NMR IN BIOMEDICINE 2024; 37:e5122. [PMID: 38369653 DOI: 10.1002/nbm.5122] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Revised: 12/22/2023] [Accepted: 01/22/2024] [Indexed: 02/20/2024]
Abstract
Amide proton transfer weighted (APTw) imaging enables in vivo assessment of tissue-bound mobile proteins and peptides through the detection of chemical exchange saturation transfer. Promising applications of APTw imaging have been shown in adult brain tumors. As pediatric brain tumors differ from their adult counterparts, we investigate the radiological appearance of pediatric brain tumors on APTw imaging. APTw imaging was conducted at 3 T. APTw maps were calculated using magnetization transfer ratio asymmetry at 3.5 ppm. First, the repeatability of APTw imaging was assessed in a phantom and in five healthy volunteers by calculating the within-subject coefficient of variation (wCV). APTw images of pediatric brain tumor patients were analyzed retrospectively. APTw levels were compared between solid tumor tissue and normal-appearing white matter (NAWM) and between pediatric high-grade glioma (pHGG) and pediatric low-grade glioma (pLGG) using t-tests. APTw maps were repeatable in supratentorial and infratentorial brain regions (wCV ranged from 11% to 39%), except those from the pontine region (wCV between 39% and 50%). APTw images of 23 children with brain tumor were analyzed (mean age 12 years ± 5, 12 male). Significantly higher APTw values are present in tumor compared with NAWM for both pHGG and pLGG (p < 0.05). APTw values were higher in pLGG subtype pilocytic astrocytoma compared with other pLGG subtypes (p < 0.05). Non-invasive characterization of pediatric brain tumor biology with APTw imaging could aid the radiologist in clinical decision-making.
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Affiliation(s)
- Iris V Obdeijn
- Center for Image Sciences, High Field MR Research Group, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Evita C Wiegers
- Center for Image Sciences, High Field MR Research Group, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Lejla Alic
- Magnetic Detection and Imaging Group, Technical Medical Center, University of Twente, Enschede, The Netherlands
| | - Sabine L A Plasschaert
- Department of Pediatric Neuro-Oncology, Princess Máxima Center for Pediatric Oncology, Utrecht, The Netherlands
| | - Mariëtte E G Kranendonk
- Department of Diagnostic Laboratory, Princess Máxima Center for Pediatric Oncology, Utrecht, The Netherlands
| | - Hans M Hoogduin
- Center for Image Sciences, High Field MR Research Group, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Dennis W J Klomp
- Center for Image Sciences, High Field MR Research Group, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Jannie P Wijnen
- Center for Image Sciences, High Field MR Research Group, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Maarten H Lequin
- Department of Pediatric Neuro-Oncology, Princess Máxima Center for Pediatric Oncology, Utrecht, The Netherlands
- Department of Radiology and Nuclear Medicine, University of Medical Center Utrecht, Utrecht, The Netherlands
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Shaghaghi M, Cai K. Analytical solution of the Bloch-McConnell equations for steady-state CEST Z-spectra. Magn Reson Imaging 2024; 109:74-82. [PMID: 38430977 DOI: 10.1016/j.mri.2024.02.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2024] [Revised: 02/22/2024] [Accepted: 02/23/2024] [Indexed: 03/05/2024]
Abstract
PURPOSE To derive an analytic expression for the steady-state Chemical Exchange Saturation Transfer (CEST) Z-spectra of a two-pool proton-exchanging system, facilitating simulations and expedited fitting of steady-state Z-spectra. METHOD The analytical expression is derived by directly solving the set of Bloch-McConnell differential equations in matrix form for a two-pool exchanging system, determining water magnetization under steady-state saturation across the entire Z-spectrum. The analytic solution is compared and validated against the numerical solution of Bloch-McConnell equations under prolonged saturation. The study also explores the line shape of a CEST peak, interpolating under-sampled Z-spectra, and Z-spectral fitting in the presence of noise. RESULTS The derived analytic solution accurately reproduces spectra obtained through numerical solutions. Direct fitting of simulated CEST spectra with the analytical solution yields the physical parameters of the exchanging system. The study shows that the analytical solution enables the reproduction of fully sampled spectra from sparsely sampled Z-spectra. Additionally, it confirms the approximation of the CEST spectrum of a single exchanging proton species with a Lorentzian function. Monte Carlo simulations reveal that the accuracy and precision of Z-spectral fittings for physical parameters are significantly influenced by data noise. The study also derives and discusses the analytical solution for three-pool Z-spectra. CONCLUSION The derived analytic solution for steady state Z-spectra can be utilized for simulations and Z-spectrum fitting, significantly reducing fitting times compared to numerical methods employed for fitting CEST Z-spectra.
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Affiliation(s)
- Mehran Shaghaghi
- Department of Radiology, University of Illinois at Chicago, Chicago, IL 60612, USA
| | - Kejia Cai
- Department of Radiology, University of Illinois at Chicago, Chicago, IL 60612, USA; Department of Biomedical Engineering, University of Illinois at Chicago, Chicago, IL 60607, USA.
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Almalki YE, Basha MAA, Metwally MI, Zeed NA, Nada MG, Alduraibi SK, Morsy AA, Balata R, Al Attar AZ, Amer MM, Farag MAEAM, Aly SA, Basha AMA, Hamed EM. Validating Brain Tumor Reporting and Data System (BT-RADS) as a Diagnostic Tool for Glioma Follow-Up after Surgery. Biomedicines 2024; 12:887. [PMID: 38672241 PMCID: PMC11048183 DOI: 10.3390/biomedicines12040887] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2024] [Revised: 04/03/2024] [Accepted: 04/09/2024] [Indexed: 04/28/2024] Open
Abstract
Gliomas are a type of brain tumor that requires accurate monitoring for progression following surgery. The Brain Tumor Reporting and Data System (BT-RADS) has emerged as a potential tool for improving diagnostic accuracy and reducing the need for repeated operations. This prospective multicenter study aimed to evaluate the diagnostic accuracy and reliability of BT-RADS in predicting tumor progression (TP) in postoperative glioma patients and evaluate its acceptance in clinical practice. The study enrolled patients with a history of partial or complete resection of high-grade glioma. All patients underwent two consecutive follow-up brain MRI examinations. Five neuroradiologists independently evaluated the MRI examinations using the BT-RADS. The diagnostic accuracy of the BT-RADS for predicting TP was calculated using histopathology after reoperation and clinical and imaging follow-up as reference standards. Reliability based on inter-reader agreement (IRA) was assessed using kappa statistics. Reader acceptance was evaluated using a short survey. The final analysis included 73 patients (male, 67.1%; female, 32.9%; mean age, 43.2 ± 12.9 years; age range, 31-67 years); 47.9% showed TP, and 52.1% showed no TP. According to readers, TP was observed in 25-41.7% of BT-3a, 61.5-88.9% of BT-3b, 75-90.9% of BT-3c, and 91.7-100% of BT-RADS-4. Considering >BT-RADS-3a as a cutoff value for TP, the sensitivity, specificity, and accuracy of the BT-RADS were 68.6-85.7%, 84.2-92.1%, and 78.1-86.3%, respectively, according to the reader. The overall IRA was good (κ = 0.75) for the final BT-RADS classification and very good for detecting new lesions (κ = 0.89). The readers completely agreed with the statement "the application of the BT-RADS should be encouraged" (score = 25). The BT-RADS has good diagnostic accuracy and reliability for predicting TP in postoperative glioma patients. However, BT-RADS 3 needs further improvements to increase its diagnostic accuracy.
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Affiliation(s)
- Yassir Edrees Almalki
- Division of Radiology, Department of Internal Medicine, Medical College, Najran University, Najran 61441, Saudi Arabia;
| | - Mohammad Abd Alkhalik Basha
- Department of Diagnostic Radiology, Faculty of Human Medicine, Zagazig University, Zagazig 44519, Egypt; (M.I.M.); (N.A.Z.); (M.G.N.); (E.M.H.)
| | - Maha Ibrahim Metwally
- Department of Diagnostic Radiology, Faculty of Human Medicine, Zagazig University, Zagazig 44519, Egypt; (M.I.M.); (N.A.Z.); (M.G.N.); (E.M.H.)
| | - Nesma Adel Zeed
- Department of Diagnostic Radiology, Faculty of Human Medicine, Zagazig University, Zagazig 44519, Egypt; (M.I.M.); (N.A.Z.); (M.G.N.); (E.M.H.)
| | - Mohamad Gamal Nada
- Department of Diagnostic Radiology, Faculty of Human Medicine, Zagazig University, Zagazig 44519, Egypt; (M.I.M.); (N.A.Z.); (M.G.N.); (E.M.H.)
| | | | - Ahmed A. Morsy
- Department of Neurosurgery, Faculty of Human Medicine, Zagazig University, Zagazig 44519, Egypt;
| | - Rawda Balata
- Department of Clinical Oncology and Nuclear Medicine, Faculty of Human Medicine, Zagazig University, Zagazig 44519, Egypt; (R.B.); (A.Z.A.A.)
| | - Ahmed Z. Al Attar
- Department of Clinical Oncology and Nuclear Medicine, Faculty of Human Medicine, Zagazig University, Zagazig 44519, Egypt; (R.B.); (A.Z.A.A.)
| | - Mona M. Amer
- Department of Neurology, Faculty of Human Medicine, Zagazig University, Zagazig 44519, Egypt;
| | | | - Sameh Abdelaziz Aly
- Department of Diagnostic Radiology, Faculty of Human Medicine, Benha University, Benha 13511, Egypt;
| | | | - Enas Mahmoud Hamed
- Department of Diagnostic Radiology, Faculty of Human Medicine, Zagazig University, Zagazig 44519, Egypt; (M.I.M.); (N.A.Z.); (M.G.N.); (E.M.H.)
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Li K, Zhu Q, Yang J, Zheng Y, Du S, Song M, Peng Q, Yang R, Liu Y, Qi L. Imaging and Liquid Biopsy for Distinguishing True Progression From Pseudoprogression in Gliomas, Current Advances and Challenges. Acad Radiol 2024:S1076-6332(24)00162-4. [PMID: 38614827 DOI: 10.1016/j.acra.2024.03.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2023] [Revised: 01/14/2024] [Accepted: 03/18/2024] [Indexed: 04/15/2024]
Abstract
RATIONALE AND OBJECTIVES Gliomas are aggressive brain tumors with a poor prognosis. Assessing treatment response is challenging because magnetic resonance imaging (MRI) may not distinguish true progression (TP) from pseudoprogression (PsP). This review aims to discuss imaging techniques and liquid biopsies used to distinguish TP from PsP. MATERIALS AND METHODS This review synthesizes existing literature to examine advances in imaging techniques, such as magnetic resonance diffusion imaging (MRDI), perfusion-weighted imaging (PWI) MRI, and liquid biopsies, for identifying TP or PsP through tumor markers and tissue characteristics. RESULTS Advanced imaging techniques, including MRDI and PWI MRI, have proven effective in delineating tumor tissue properties, offering valuable insights into glioma behavior. Similarly, liquid biopsy has emerged as a potent tool for identifying tumor-derived markers in biofluids, offering a non-invasive glimpse into tumor evolution. Despite their promise, these methodologies grapple with significant challenges. Their sensitivity remains inconsistent, complicating the accurate differentiation between TP and PSP. Furthermore, the absence of standardized protocols across platforms impedes the reliability of comparisons, while inherent biological variability adds complexity to data interpretation. CONCLUSION Their potential applications have been highlighted, but gaps remain before routine clinical use. Further research is needed to develop and validate these promising methods for distinguishing TP from PsP in gliomas.
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Affiliation(s)
- Kaishu Li
- Department of Neurosurgery, Affiliated Qingyuan Hospital,Guangzhou Medical University,Qingyuan People's Hospital, Qingyuan 511518, China; Department of Neurosurgery & Medical Research Center, Shunde Hospital, Southern Medical University (The First People's Hospital of Shunde Foshan), 1# Jiazi Road, Foshan, Guangdong 528300, China.; Department of Neurosurgery, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China
| | - Qihui Zhu
- Department of Neurosurgery, Affiliated Qingyuan Hospital,Guangzhou Medical University,Qingyuan People's Hospital, Qingyuan 511518, China
| | - Junyi Yang
- Department of Neurosurgery, Affiliated Qingyuan Hospital,Guangzhou Medical University,Qingyuan People's Hospital, Qingyuan 511518, China
| | - Yin Zheng
- Department of Neurosurgery, Affiliated Qingyuan Hospital,Guangzhou Medical University,Qingyuan People's Hospital, Qingyuan 511518, China
| | - Siyuan Du
- Institute of Digestive Disease of Guangzhou Medical University, Affiliated Qingyuan Hospital,Guangzhou Medical University,Qingyuan People's Hospital, Qingyuan 511518, China
| | - Meihui Song
- Institute of Digestive Disease of Guangzhou Medical University, Affiliated Qingyuan Hospital,Guangzhou Medical University,Qingyuan People's Hospital, Qingyuan 511518, China
| | - Qian Peng
- Institute of Digestive Disease of Guangzhou Medical University, Affiliated Qingyuan Hospital,Guangzhou Medical University,Qingyuan People's Hospital, Qingyuan 511518, China
| | - Runwei Yang
- Department of Neurosurgery & Medical Research Center, Shunde Hospital, Southern Medical University (The First People's Hospital of Shunde Foshan), 1# Jiazi Road, Foshan, Guangdong 528300, China
| | - Yawei Liu
- Department of Neurosurgery & Medical Research Center, Shunde Hospital, Southern Medical University (The First People's Hospital of Shunde Foshan), 1# Jiazi Road, Foshan, Guangdong 528300, China
| | - Ling Qi
- Institute of Digestive Disease of Guangzhou Medical University, Affiliated Qingyuan Hospital,Guangzhou Medical University,Qingyuan People's Hospital, Qingyuan 511518, China.
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Li Y, Zhang Y, Tian L, Li J, Li H, Wang X, Wang C. 3D amide proton transfer-weighted imaging may be useful for diagnosing early-stage breast cancer: a prospective monocentric study. Eur Radiol Exp 2024; 8:41. [PMID: 38584248 PMCID: PMC10999404 DOI: 10.1186/s41747-024-00439-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Accepted: 01/17/2024] [Indexed: 04/09/2024] Open
Abstract
BACKGROUND We investigated the value of three-dimensional amide proton transfer-weighted imaging (3D-APTWI) in the diagnosis of early-stage breast cancer (BC) and its correlation with the immunohistochemical characteristics of malignant lesions. METHODS Seventy-eight women underwent APTWI and dynamic contrast-enhanced (DCE)-MRI. Pathological results were categorized as either benign (n = 43) or malignant (n = 37) lesions. The parameters of APTWI and DCE-MRI were compared between the benign and malignant groups. The diagnostic value of 3D-APTWI was evaluated using the area under the receiver operating characteristic curve (ROC-AUC) to establish a diagnostic threshold. Pearson's correlation was used to analyze the correlation between the magnetization transfer asymmetry (MTRasym) and immunohistochemical characteristics. RESULTS The MTRasym and time-to-peak of malignancies were significantly lower than those of benign lesions (all p < 0.010). The volume transfer constant, rate constant, and wash-in and wash-out rates of malignancies were all significantly greater than those of benign lesions (all p < 0.010). ROC-AUCs of 3D-APTWI, DCE-MRI, and 3D-APTWI+DCE to differential diagnosis between early-stage BC and benign lesions were 0.816, 0.745, and 0.858, respectively. Only the difference between AUCAPT+DCE and AUCDCE was significant (p < 0.010). When a threshold of MTRasym for malignancy for 2.42%, the sensitivity and specificity of 3D-APTWI for BC diagnosis were 86.5% and 67.6%, respectively; MTRasym was modestly positively correlated with pathological grade (r = 0.476, p = 0.003) and Ki-67 (r = 0.419, p = 0.020). CONCLUSIONS 3D-APTWI may be used as a supplementary method for patients with contraindications of DCE-MRI. MTRasym can imply the proliferation activities of early-stage BC. RELEVANCE STATEMENT 3D-APTWI can be an alternative diagnostic method for patients with early-stage BC who are not suitable for contrast injection. KEY POINTS • 3D-APTWI reflects the changes in the microenvironment of early-stage breast cancer. • Combined 3D-APTWI is superior to DCE-MRI alone for early-stage breast cancer diagnosis. • 3D-APTWI improves the diagnostic accuracy of early-stage breast cancer.
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Affiliation(s)
- Yeqin Li
- Department of Radiology, Shandong Province Hospital of Traditional Chinese Medicine, Jinan, 250014, China
| | - Yan Zhang
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medcial University, Jinan, 250021, China
| | - Liwen Tian
- Department of Radiology, Shandong Public Health Clinical Center, Jinan, 250100, China
| | - Ju Li
- Department of Radiology, Shandong Public Health Clinical Center, Jinan, 250100, China
- Binzhou Medical University, Yantai, 264003, China
| | - Huihua Li
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medcial University, Jinan, 250021, China
| | - Ximing Wang
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medcial University, Jinan, 250021, China
| | - Cuiyan Wang
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medcial University, Jinan, 250021, China.
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Tseng CL, Zeng KL, Mellon EA, Soltys SG, Ruschin M, Lau AZ, Lutsik NS, Chan RW, Detsky J, Stewart J, Maralani PJ, Sahgal A. Evolving concepts in margin strategies and adaptive radiotherapy for glioblastoma: A new future is on the horizon. Neuro Oncol 2024; 26:S3-S16. [PMID: 38437669 PMCID: PMC10911794 DOI: 10.1093/neuonc/noad258] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/06/2024] Open
Abstract
Chemoradiotherapy is the standard treatment after maximal safe resection for glioblastoma (GBM). Despite advances in molecular profiling, surgical techniques, and neuro-imaging, there have been no major breakthroughs in radiotherapy (RT) volumes in decades. Although the majority of recurrences occur within the original gross tumor volume (GTV), treatment of a clinical target volume (CTV) ranging from 1.5 to 3.0 cm beyond the GTV remains the standard of care. Over the past 15 years, the incorporation of standard and functional MRI sequences into the treatment workflow has become a routine practice with increasing adoption of MR simulators, and new integrated MR-Linac technologies allowing for daily pre-, intra- and post-treatment MR imaging. There is now unprecedented ability to understand the tumor dynamics and biology of GBM during RT, and safe CTV margin reduction is being investigated with the goal of improving the therapeutic ratio. The purpose of this review is to discuss margin strategies and the potential for adaptive RT for GBM, with a focus on the challenges and opportunities associated with both online and offline adaptive workflows. Lastly, opportunities to biologically guide adaptive RT using non-invasive imaging biomarkers and the potential to define appropriate volumes for dose modification will be discussed.
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Affiliation(s)
- Chia-Lin Tseng
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario, Canada
| | - K Liang Zeng
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario, Canada
- Department of Radiation Oncology, Simcoe Muskoka Regional Cancer Program, Royal Victoria Regional Health Centre, University of Toronto, Toronto, Ontario, Canada
| | - Eric A Mellon
- Department of Radiation Oncology, Sylvester Comprehensive Cancer Center, Miller School of Medicine, University of Miami, Miami, Florida, USA
| | - Scott G Soltys
- Department of Radiation Oncology, Stanford University, Stanford, California, USA
| | - Mark Ruschin
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario, Canada
| | - Angus Z Lau
- Physical Sciences, Sunnybrook Research Institute, Toronto, Ontario, Canada
- Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
| | - Natalia S Lutsik
- Department of Radiation Oncology, Sylvester Comprehensive Cancer Center, Miller School of Medicine, University of Miami, Miami, Florida, USA
| | - Rachel W Chan
- Physical Sciences, Sunnybrook Research Institute, Toronto, Ontario, Canada
| | - Jay Detsky
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario, Canada
| | - James Stewart
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario, Canada
| | - Pejman J Maralani
- Department of Medical Imaging, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario, Canada
| | - Arjun Sahgal
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario, Canada
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Abstract
Magnetic resonance imaging-guided radiation therapy (MRIgRT) has improved soft tissue contrast over computed tomography (CT) based image-guided RT. Superior visualization of the target and surrounding radiosensitive structures has the potential to improve oncological outcomes partly due to safer dose-escalation and adaptive planning. In this review, we highlight the workflow of adaptive MRIgRT planning, which includes simulation imaging, daily MRI, identifying isocenter shifts, contouring, plan optimization, quality control, and delivery. Increased utilization of MRIgRT will depend on addressing technical limitations of this technology, while addressing treatment efficacy, cost-effectiveness, and workflow training.
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Affiliation(s)
- Cecil M Benitez
- Department of Radiation Oncology, UCLA Medical Center, Los Angeles, CA
| | - Michael D Chuong
- Department of Radiation Oncology, Miami Cancer Institute, Baptist Health South Florida; Miami, FL
| | - Luise A Künzel
- National Center for Tumor Diseases (NCT), Dresden; German Cancer Research Center (DKFZ), Heidelberg; Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden; Helmholtz-Zentrum Dresden - Rossendorf (HZDR), Dresden, Germany; Department of Radiotherapy and Radiation Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.; OncoRay-National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden Rossendorf, Dresden, Germany
| | - Daniela Thorwarth
- Department of Radiation Oncology, Section for Biomedical Physics, University of Tübingen, Tübingen, Germany..
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11
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Inoue A, Watanabe H, Kusakabe K, Nishikawa M, Shiraishi Y, Taniwaki M, Takimoto Y, Harada M, Furumochi T, Shigekawa S, Kitazawa R, Kido T, Ohnishi T, Kunieda T. Role of amide proton transfer imaging in maximizing tumor resection in malignant glioma: a possibility to take the place of 11C-methionine positron emission tomography. Neurosurg Rev 2023; 46:294. [PMID: 37925381 DOI: 10.1007/s10143-023-02202-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2023] [Revised: 07/22/2023] [Accepted: 10/29/2023] [Indexed: 11/06/2023]
Abstract
BACKGROUND Amide proton transfer (APT) imaging has been proposed as a technique to assess tumor metabolism. However, the relationship between APT imaging and other quantitative modalities including positron emission tomography (PET) has not been investigated in detail. This study aimed to evaluate the clinical usefulness of APT imaging in determining the metabolic status of malignant glioma and to compare findings with those from 11C-methionine (Met)-PET. METHODS This research analyzed APT imaging data from 20 consecutive patients with malignant glioma treated between January 2022 and July 2023. Patients underwent tumor resection and correlations between tumor activity and intensity of APT signal were investigated. We also compared 11C-Met-PET and APT imaging for the same regions of the perifocal tumor invasion area. RESULTS Clear, diagnostic APT images were obtained from all 20 cases. Mean APT intensity (APTmean) was significantly higher in the glioblastoma (GBM), IDH wild type group (27.2 ± 12.8%) than in other gliomas (6.0 ± 4.7%; p < 0.001). The cut-off APTmean to optimally distinguish between GBM and other malignant gliomas was 12.8%, offering 100% sensitivity and 83.3% specificity. These values for APTmean broadly matched the tumor-to-contralateral normal brain tissue ratio from 11C-Met-PET analysis (r = 0.66). The APT signal was also observed in the gadolinium non-contrast region on T1-weighted imaging, appearing to reflect the surrounding tumor-infiltrated area. CONCLUSIONS APT imaging can be used to evaluate the area of tumor invasion, similar to 11C-Met-PET. APT imaging revealed low invasiveness in patients and was useful in preoperative planning for tumor resection, facilitating maximum tumor resection including the tumor invasive area.
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Affiliation(s)
- Akihiro Inoue
- Department of Neurosurgery, Ehime University School of Medicine, 454 Shitsukawa, Toon, Ehime, 791-0295, Japan.
| | - Hideaki Watanabe
- Department of Neurosurgery, Ehime University School of Medicine, 454 Shitsukawa, Toon, Ehime, 791-0295, Japan
| | - Kosuke Kusakabe
- Department of Neurosurgery, Ehime University School of Medicine, 454 Shitsukawa, Toon, Ehime, 791-0295, Japan
| | - Masahiro Nishikawa
- Department of Neurosurgery, Ehime University School of Medicine, 454 Shitsukawa, Toon, Ehime, 791-0295, Japan
| | - Yasuhiro Shiraishi
- Division of Neurology, Ehime University Hospital, 454 Shitsukawa, Toon, Ehime, 791-0295, Japan
| | - Mashio Taniwaki
- Division of Diagnostic Pathology, Ehime University Hospital, 454 Shitsukawa, Toon, Ehime, 791-0295, Japan
| | - Yoshihiro Takimoto
- Division of Neurology, Ehime University Hospital, 454 Shitsukawa, Toon, Ehime, 791-0295, Japan
| | - Mizusa Harada
- Division of Neurology, Ehime University Hospital, 454 Shitsukawa, Toon, Ehime, 791-0295, Japan
| | - Taichi Furumochi
- Division of Neurology, Ehime University Hospital, 454 Shitsukawa, Toon, Ehime, 791-0295, Japan
| | - Seiji Shigekawa
- Department of Neurosurgery, Ehime University School of Medicine, 454 Shitsukawa, Toon, Ehime, 791-0295, Japan
| | - Riko Kitazawa
- Division of Neurology, Ehime University Hospital, 454 Shitsukawa, Toon, Ehime, 791-0295, Japan
| | - Teruhito Kido
- Department of Radiology, Ehime University School of Medicine, 454 Shitsukawa, Toon, Ehime, 791-0295, Japan
| | - Takanori Ohnishi
- Department of Neurosurgery, Washoukai Sadamoto Hospital, 1-6-1 Takehara, Matsuyama, Ehime, 790-0052, Japan
| | - Takeharu Kunieda
- Department of Neurosurgery, Ehime University School of Medicine, 454 Shitsukawa, Toon, Ehime, 791-0295, Japan
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12
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Song G, Chen Y, Luo X, Gong T, Yang H, Zhou J, Li C, Chen M. Amide proton transfer-weighted MRI features of acute ischemic stroke subtypes. NMR IN BIOMEDICINE 2023; 36:e4983. [PMID: 37259224 DOI: 10.1002/nbm.4983] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/08/2022] [Revised: 02/14/2023] [Accepted: 05/13/2023] [Indexed: 06/02/2023]
Abstract
Stroke is a highly heterogeneous disorder with distinct subtypes, and the stroke subtype influences the outcome. Amide proton transfer-weighted (APTW) MRI has been demonstrated to be promising in stroke patients, but the image characteristics of stroke subtypes have not been sufficiently investigated. The purpose of this study was to investigate the APTW MRI features of different subtypes of acute ischemic stroke (AIS). Ninety-two AIS patients presenting within 96 h of symptom onset were enrolled and examined with a 3.0-T MRI system. Patients were grouped into four subtypes: lacunar circulation infarcts (LACI, n = 33); total anterior circulation infarcts (TACI, n = 9); partial anterior circulation infarcts (PACI, n = 28); and posterior circulation infarcts (POCI, n = 22). APTW values in the lesion (APTWlesion ) and the contralateral normal-appearing region (APTWcontral ) were measured. The change in APTW values between the acute ischemic lesion and the contralateral normal-appearing region (APTWles-con ) was calculated. A two-sample t-test, one-way ANOVA, and the Chi-square method were used. There were significant differences between APTWlesion and APTWcontral in the three categories of nonlacunar strokes (TACI, PACI, and POCI, all p < 0.01), but not for lacunar strokes (LACI, p = 0.080). TACI patients had the lowest APTWlesion and APTWles-con in all groups (p < 0.05). In the POCI group, patients with supratentorial infarcts showed significant differences between APTWlesion and APTWcontral (p = 0.001), while the differences were not significant for infratentorial infarcts (p = 0.135). Our results suggest that the APT effect was heterogeneous in different stroke subtypes, and that APTW MRI gave an excellent performence in depicting nonlacunar AIS in supratentorial locations.
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Affiliation(s)
- Guodong Song
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
| | - Yuhui Chen
- Department of Neurology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China
| | - Xiaojie Luo
- Department of Radiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China
| | - Tao Gong
- Department of Neurology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China
| | - Huan Yang
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
| | - Jinyuan Zhou
- Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Maryland, USA
| | - Chunmei Li
- Department of Radiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China
| | - Min Chen
- Department of Radiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China
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13
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Huang Q, Wu J, Le N, Shen Y, Guo P, Schreck KC, Kamson D, Blair L, Heo HY, Li X, Li W, Sair HL, Blakeley JO, Laterra J, Holdhoff M, Grossman SA, Mukherjee D, Bettegowda C, van Zijl P, Zhou J, Jiang S. CEST2022: Amide proton transfer-weighted MRI improves the diagnostic performance of multiparametric non-contrast-enhanced MRI techniques in patients with post-treatment high-grade gliomas. Magn Reson Imaging 2023; 102:222-228. [PMID: 37321378 PMCID: PMC10528251 DOI: 10.1016/j.mri.2023.06.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Accepted: 06/12/2023] [Indexed: 06/17/2023]
Abstract
New or enlarged lesions in malignant gliomas after surgery and chemoradiation can be associated with tumor recurrence or treatment effect. Due to similar radiographic characteristics, conventional-and even some advanced MRI techniques-are limited in distinguishing these two pathologies. Amide proton transfer-weighted (APTw) MRI, a protein-based molecular imaging technique that does not require the administration of any exogenous contrast agent, was recently introduced into the clinical setting. In this study, we evaluated and compared the diagnostic performances of APTw MRI with several non-contrast-enhanced MRI sequences, such as diffusion-weighted imaging, susceptibility-weighted imaging, and pseudo-continuous arterial spin labeling. Thirty-nine scans from 28 glioma patients were obtained on a 3 T MRI scanner. A histogram analysis approach was employed to extract parameters from each tumor area. Statistically significant parameters (P < 0.05) were selected to train multivariate logistic regression models to evaluate the performance of MRI sequences. Multiple histogram parameters, particularly from APTw and pseudo-continuous arterial spin labeling images, demonstrated significant differences between treatment effect and recurrent tumor. The regression model trained on the combination of all significant histogram parameters achieved the best result (area under the curve = 0.89). We found that APTw images added value to other advanced MR images for the differentiation of treatment effect and tumor recurrence.
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Affiliation(s)
- Qianqi Huang
- Department of Radiology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA; Department of Biomedical Engineering, Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Jingpu Wu
- Department of Radiology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA; Department of Applied Mathematics and Statistics, Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Nhat Le
- Department of Radiology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA; Department of Computer Science, Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Yiqing Shen
- Department of Radiology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA; Department of Computer Science, Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Pengfei Guo
- Department of Radiology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA; Department of Computer Science, Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Karisa C Schreck
- Department of Neurology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA; Department of Oncology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - David Kamson
- Department of Oncology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Lindsay Blair
- Department of Neurology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Hye-Young Heo
- Department of Radiology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Xu Li
- Department of Radiology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Wenbo Li
- Department of Radiology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Haris L Sair
- Department of Radiology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA; Malone Center for Engineering in Healthcare, The Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Jaishri O Blakeley
- Department of Neurology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA; Department of Oncology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - John Laterra
- Department of Neurology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA; Department of Oncology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Matthias Holdhoff
- Department of Oncology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Stuart A Grossman
- Department of Oncology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Debraj Mukherjee
- Department of Neurosurgery, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Chetan Bettegowda
- Department of Neurosurgery, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Peter van Zijl
- Department of Radiology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Jinyuan Zhou
- Department of Radiology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Shanshan Jiang
- Department of Radiology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA.
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14
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Özdemir İ, Kamson DO, Etyemez S, Blair L, Lin DDM, Barker PB. Downfield Proton MRSI at 3 Tesla: A Pilot Study in Human Brain Tumors. Cancers (Basel) 2023; 15:4311. [PMID: 37686587 PMCID: PMC10486526 DOI: 10.3390/cancers15174311] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Revised: 08/23/2023] [Accepted: 08/25/2023] [Indexed: 09/10/2023] Open
Abstract
PURPOSE To investigate the use of 3D downfield proton magnetic resonance spectroscopic imaging (DF-MRSI) for evaluation of tumor recurrence in patients with glioblastoma (GBM). METHODS Seven patients (4F, age range 44-65 and mean ± standard deviation 59.3 ± 7.5 years) with previously treated GBM were scanned using a recently developed 3D DF-MRSI sequence at 3T. Short TE 3D DF-MRSI and water reference 3D-MRSI scans were collected with a nominal spatial resolution of 0.7 cm3. DF volume data in eight slices covered 12 cm of brain in the cranio-caudal axis. Data were analyzed using the 'LCModel' program and a basis set containing nine peaks ranging in frequency between 6.83 to 8.49 ppm. The DF8.18 (assigned to amides) and DF7.90 peaks were selected for the creation of metabolic images and statistical analysis. Longitudinal MR images and clinical history were used to classify brain lesions as either recurrent tumor or treatment effect, which may include necrosis. DF-MRSI data were compared between lesion groups (recurrent tumor, treatment effect) and normal-appearing brain. RESULTS Of the seven brain tumor patients, two were classified as having recurrent tumor and the rest were classified as treatment effect. Amide metabolite levels from recurrent tumor regions were significantly (p < 0.05) higher compared to both normal-appearing brain and treatment effect regions. Amide levels in lesion voxels classified as treatment effect were significantly lower than normal brain. CONCLUSIONS 3D DF-MRSI in human brain tumors at 3T is feasible and was well tolerated by all patients enrolled in this preliminary study. Amide levels measured by 3D DF-MRSI were significantly different between treatment effect and tumor regrowth.
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Affiliation(s)
- İpek Özdemir
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - David O. Kamson
- Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Semra Etyemez
- Department of Obstetrics & Gynecology, Weill Cornell Medicine, New York, NY 10065, USA
- Department of Psychiatry, Weill Cornell Medicine, New York, NY 10065, USA
| | - Lindsay Blair
- Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Doris D. M. Lin
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Peter B. Barker
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- F.M. Kirby Center for Functional Brain MRI, The Kennedy Krieger Institute, Baltimore, MD 21205, USA
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15
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von Knebel Doeberitz N, Kroh F, König L, Boyd PS, Graß S, Bauspieß C, Scherer M, Unterberg A, Bendszus M, Wick W, Bachert P, Debus J, Ladd ME, Schlemmer HP, Goerke S, Korzowski A, Paech D. Post-Surgical Depositions of Blood Products Are No Major Confounder for the Diagnostic and Prognostic Performance of CEST MRI in Patients with Glioma. Biomedicines 2023; 11:2348. [PMID: 37760790 PMCID: PMC10525358 DOI: 10.3390/biomedicines11092348] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Revised: 08/11/2023] [Accepted: 08/16/2023] [Indexed: 09/29/2023] Open
Abstract
Amide proton transfer (APT) and semi-solid magnetization transfer (ssMT) imaging can predict clinical outcomes in patients with glioma. However, the treatment of brain tumors is accompanied by the deposition of blood products within the tumor area in most cases. For this reason, the objective was to assess whether the diagnostic interpretation of the APT and ssMT is affected by methemoglobin (mHb) and hemosiderin (Hs) depositions at the first follow-up MRI 4 to 6 weeks after the completion of radiotherapy. A total of 34 participants underwent APT and ssMT imaging by applying reconstruction methods described by Zhou et al. (APTwasym), Goerke et al. (MTRRexAPT and MTRRexMT) and Mehrabian et al. (MTconst). Contrast-enhancing tumor (CE), whole tumor (WT), mHb and Hs were segmented on contrast-enhanced T1wCE, T2w-FLAIR, T1w and T2*w images. ROC-analysis, Kaplan-Meier analysis and the log rank test were used to test for the association of mean contrast values with therapy response and overall survival (OS) before (WT and CE) and after correcting tumor volumes for mHb and Hs (CEC and WTC). CEC showed higher associations of the MTRRexMT with therapy response (CE: AUC = 0.677, p = 0.081; CEC: AUC = 0.705, p = 0.044) and of the APTwasym with OS (CE: HR = 2.634, p = 0.040; CEC: HR = 2.240, p = 0.095). In contrast, WTC showed a lower association of the APTwasym with survival (WT: HR = 2.304, p = 0.0849; WTC: HR = 2.990, p = 0.020). Overall, a sophisticated correction for blood products did not substantially influence the clinical performance of APT and ssMT imaging in patients with glioma early after radiotherapy.
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Affiliation(s)
| | - Florian Kroh
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
- Department of Physics and Astronomy, University of Heidelberg, 69120 Heidelberg, Germany
| | - Laila König
- Department of Radiation Oncology, Heidelberg University Hospital, 69120 Heidelberg, Germany
| | - Philip S. Boyd
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Svenja Graß
- Division of Radiology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Cora Bauspieß
- Division of Radiology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Moritz Scherer
- Department of Neurosurgery, University Hospital Heidelberg, 69120 Heidelberg, Germany
| | - Andreas Unterberg
- Department of Neurosurgery, University Hospital Heidelberg, 69120 Heidelberg, Germany
- Faculty of Medicine, University of Heidelberg, 69120 Heidelberg, Germany
| | - Martin Bendszus
- Faculty of Medicine, University of Heidelberg, 69120 Heidelberg, Germany
- Department of Neuroradiology, University Hospital Heidelberg, 69120 Heidelberg, Germany
| | - Wolfgang Wick
- Faculty of Medicine, University of Heidelberg, 69120 Heidelberg, Germany
- Department of Neurology, University Hospital Heidelberg, 69120 Heidelberg, Germany
| | - Peter Bachert
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
- Department of Physics and Astronomy, University of Heidelberg, 69120 Heidelberg, Germany
| | - Jürgen Debus
- Department of Radiation Oncology, Heidelberg University Hospital, 69120 Heidelberg, Germany
- Faculty of Medicine, University of Heidelberg, 69120 Heidelberg, Germany
- Clinical Cooperation Unit Radiation Oncology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Mark E. Ladd
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
- Department of Physics and Astronomy, University of Heidelberg, 69120 Heidelberg, Germany
- Faculty of Medicine, University of Heidelberg, 69120 Heidelberg, Germany
| | - Heinz-Peter Schlemmer
- Division of Radiology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
- Faculty of Medicine, University of Heidelberg, 69120 Heidelberg, Germany
| | - Steffen Goerke
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Andreas Korzowski
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Daniel Paech
- Division of Radiology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
- Department of Neuroradiology, University Hospital Bonn, 53127 Bonn, Germany
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16
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Qian Z, Liu R, Wu Z, Hsu YC, Fu C, Sun Y, Wu D, Zhang Y. Saturation-prolongated and inhomogeneity-mitigated chemical exchange saturation transfer imaging with parallel transmission. NMR IN BIOMEDICINE 2023; 36:e4689. [PMID: 34994025 DOI: 10.1002/nbm.4689] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/25/2021] [Revised: 12/20/2021] [Accepted: 01/04/2022] [Indexed: 05/23/2023]
Abstract
Chemical exchange saturation transfer (CEST) imaging benefits from a longer saturation duration and a higher saturation duty cycle. Dielectric shading effects occur when the radiofrequency (RF) wavelength approaches the object size. Here, we proposed a simultaneous parallel transmission-based CEST (pTx-CEST) sequence to prolongate the saturation duration at a 100% duty cycle and improve the RF saturation homogeneity in CEST imaging. The simultaneous pTx-CEST sequence was implemented by switching the CEST saturation module from the non-pTx to pTx mode, using the pTx functionality with both transmit channels being driven simultaneously (instead of time-interleaved). The optimization of amplitude ratio and phase difference settings between RF channels for best B1 homogeneity was performed in phantoms of two different sizes mimicking the human brain and abdomen. The optimal amplitude and phase settings generating the best B1 homogeneity in the phantoms were used in pTx-CEST scans of the human study. The comparison of the maximum achievable saturation duration between the non-pTx-CEST and pTx-CEST sequences was performed in a protein phantom, healthy volunteers, and a metastatic brain tumor patient. The optimal amplitude ratio and phase difference setting between transmit channels manifested circular and elliptical polarization in the head-sized and abdomen-sized phantoms. In the brain, the maximum saturation durations achieved at a 100% duty cycle using the simultaneous pTx-CEST sequence were prolonged to 2240, 3220, and 4200 ms compared with 980 ms using the non-pTx-CEST sequence at repetition times of 3, 4, and 5 s, respectively. The longer saturation duration helped improve the image contrast between the tumor and the normal tissue in the patient. The optimized elliptical polarization mode saturation pulses yielded improved uniformity of CEST signals acquired from the human abdomen. The proposed simultaneous pTx-CEST sequence enabled essentially arbitrarily long saturation duration at a 100% duty cycle and helped reduce the dielectric shading effects with the optimized RF setting.
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Affiliation(s)
- Zihua Qian
- Department of Radiology, The Children's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Ruibin Liu
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China
| | - Zhe Wu
- Techna Institute, University Health Network, Toronto, Ontario, Canada
| | - Yi-Cheng Hsu
- MR Collaboration, Siemens Healthcare Ltd., Shanghai, China
| | - Caixia Fu
- MR Application Development, Siemens Shenzhen Magnetic Resonance Ltd., Shenzhen, China
| | - Yi Sun
- MR Collaboration, Siemens Healthcare Ltd., Shanghai, China
| | - Dan Wu
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China
- Cancer Center, Zhejiang University, Hangzhou, Zhejiang, China
| | - Yi Zhang
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China
- Cancer Center, Zhejiang University, Hangzhou, Zhejiang, China
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17
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Knebel Doeberitz NV, Kroh F, Breitling J, König L, Maksimovic S, Graß S, Adeberg S, Scherer M, Unterberg A, Bendszus M, Wick W, Bachert P, Debus J, Ladd ME, Schlemmer HP, Korzowski A, Goerke S, Paech D. CEST Imaging of the APT and ssMT predict the overall survival of patients with glioma at the first follow-up after completion of radiotherapy at 3T. Radiother Oncol 2023; 184:109694. [PMID: 37150450 DOI: 10.1016/j.radonc.2023.109694] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Revised: 04/27/2023] [Accepted: 04/28/2023] [Indexed: 05/09/2023]
Abstract
BACKGROUND AND PURPOSE Outcome prediction of patients with glioma early after the completion of radiotherapy represents a major clinical challenge. Previously, the prognostic value of chemical exchange saturation transfer (CEST) imaging has been demonstrated in patients with newly diagnosed glioma. The objective of this study was to assess the potential of amide proton transfer (APT)-, relayed nuclear Overhauser effect (rNOE)- and semi-solid magnetization transfer (ssMT)-imaging according to Zhou et al. (APTwasym), Goerke et al. (MTRRexAPT, MTRRexNOE and MTRRexMT) and Mehrabian et al. (PeakAreaAPT, PeakAreaNOE and MTconst) for the prognostication of the overall survival (OS) of patients with glioma at the first follow-up after the completion of radiotherapy. MATERIALS AND METHODS 49 of 72 participants with diffuse glioma, who underwent CEST MRI at 3T between July 2018 and December 2021 4 to 6 weeks after the completion of radiotherapy, were analyzed. Contrast-enhancing tumor (CE) and whole tumor (WT) volumes were segmented on T2w-FLAIR and contrast-enhanced T1w images. Kaplan-Meier analysis and logrank-test were used for statistical analyses. RESULTS APTw imaging demonstrated the strongest association with OS (HR=4.66, p<0.001). The MTconst (HR=2.54, p=0.044) was associated with the OS of participants with residual contrast-enhancing glioma tissue, whilst the MTRRexAPT (HR=2.44, p=0.056) showed a trend in this sub-cohort. The MTRRexNOE, MTRRexMT and PeakAreaNOE were not associated with survival. CONCLUSION Imaging of the APT and ssMT at the first follow-up 4 to 6 weeks after the completion of radiotherapy at 3T were associated with the overall survival of patients with glioma.
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Affiliation(s)
| | - Florian Kroh
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany; Department of Physics and Astronomy, University of Heidelberg, Heidelberg, Germany
| | - Johannes Breitling
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Laila König
- Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany
| | - Srdjan Maksimovic
- Division of Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Svenja Graß
- Division of Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Sebastian Adeberg
- Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany; Faculty of Medicine, University of Heidelberg, Heidelberg, Germany
| | - Moritz Scherer
- Department of Neurosurgery, University Hospital Heidelberg, Heidelberg, Germany
| | - Andreas Unterberg
- Department of Neurosurgery, University Hospital Heidelberg, Heidelberg, Germany; Faculty of Medicine, University of Heidelberg, Heidelberg, Germany
| | - Martin Bendszus
- Department of Neuroradiology, University Hospital Heidelberg, Heidelberg, Germany; Faculty of Medicine, University of Heidelberg, Heidelberg, Germany
| | - Wolfgang Wick
- Department of Neurology, University Hospital Heidelberg, Heidelberg, Germany; Faculty of Medicine, University of Heidelberg, Heidelberg, Germany
| | - Peter Bachert
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany; Department of Physics and Astronomy, University of Heidelberg, Heidelberg, Germany
| | - Jürgen Debus
- Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany; Clinical Cooperation Unit Radiation Oncology, German Cancer Research Center (DKFZ), Heidelberg, Germany; Faculty of Medicine, University of Heidelberg, Heidelberg, Germany
| | - Mark E Ladd
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany; Department of Physics and Astronomy, University of Heidelberg, Heidelberg, Germany; Faculty of Medicine, University of Heidelberg, Heidelberg, Germany
| | - Heinz-Peter Schlemmer
- Division of Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany; Faculty of Medicine, University of Heidelberg, Heidelberg, Germany
| | - Andreas Korzowski
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Steffen Goerke
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Daniel Paech
- Division of Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany; Department of Neuroradiology, University Hospital Bonn, Bonn, Germany.
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Yong X, Lu S, Hsu YC, Fu C, Sun Y, Zhang Y. Numerical fitting of Extrapolated semisolid Magnetization transfer Reference signals: Improved detection of ischemic stroke. Magn Reson Med 2023; 90:722-736. [PMID: 37052377 DOI: 10.1002/mrm.29660] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Revised: 03/09/2023] [Accepted: 03/18/2023] [Indexed: 04/14/2023]
Abstract
PURPOSE To propose a novel Numerical fitting method of the Extrapolated semisolid Magnetization transfer Reference (NEMR) signal for quantifying the CEST effect. THEORY AND METHODS Modified two-pool Bloch-McConnell equations were used to numerically fit the magnetization transfer (MT) and direct water saturation (DS) signals at far off-resonance frequencies, which was subsequently extrapolated into the frequency range of amide proton transfer (APT) and nuclear Overhauser enhancement (NOE) pools. Then the subtraction of the fitted two-pool z-spectrum and the experimentally acquired z-spectrum yielded APT# and NOE# signals mostly free of MT and DS contamination. Several strategies were used to accelerate the NEMR fitting. Furthermore, the proposed NEMR method was compared with the conventional extrapolated semisolid magnetization transfer reference (EMR) and magnetization transfer ratio asymmetry (MTRasym ) methods in simulations and stroke patients. RESULTS The combination of RF downsampling, MT lineshape look-up table, and conversion of MATLAB code to C code accelerated the NEMR fitting by over 2700-fold. Monte-Carlo simulations showed that NEMR had higher accuracy than EMR and eliminated the requirement of the steady-state condition. In ischemic stroke patients, the NEMR maps at 1 μT removed hypointense artifacts seen on EMR and MTRasym images, and better depicted stroke lesions than EMR. For NEMR, NOE# yielded significantly (p < 0.05) stronger signal contrast between stroke and normal tissues than APT# at 1 μT. CONCLUSION The proposed NEMR method is suitable for arbitrary saturation settings and can remove MT and DS contamination from the CEST signal for improved detection of ischemic stroke.
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Affiliation(s)
- Xingwang Yong
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China
| | - Shanshan Lu
- The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Yi-Cheng Hsu
- MR Collaboration, Siemens Healthcare Ltd., Shanghai, China
| | - Caixia Fu
- Siemens Shenzhen Magnetic Resonance Ltd., Shenzhen, Guangdong, China
| | - Yi Sun
- MR Collaboration, Siemens Healthcare Ltd., Shanghai, China
| | - Yi Zhang
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China
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Metwally MI, Hafez FFM, Ibrahim SA, Morsy AA, Zeed NA. The value of adding DWI and FLAIR signal changes in the resection cavity on the diagnostic performance of BT-RADS category 3 for tumor progression prediction in post-treated glioma patients: a prospective pilot study. THE EGYPTIAN JOURNAL OF RADIOLOGY AND NUCLEAR MEDICINE 2023. [DOI: 10.1186/s43055-023-00993-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/08/2023] Open
Abstract
Abstract
Background
BT-RADS is a structured reporting system of post-treatment glioma. BT-RADS category 3 carries a probability of recurrent malignancy versus treatment-related changes. The aim of this study is to evaluate the additive value of DWI and resection cavity FLAIR signal changes to BT-RADS category 3 in the prediction of tumor progression. We prospectively evaluated follow-up contrast-enhanced MR imaging where 27 post-treated glioma patients were assigned BT-RADS category 3. In all images, FLAIR signal, enhancement component, mass effect, and ADCmean were assessed. We used imaging follow-up from the second stage of the study as the gold standard for comparing the diagnostic performance of BT-RADS category 3 for predicting tumor recurrence before and after the addition of DWI and resection cavity FLAIR signal changes. ROC curves analyses were assessed and compared using the Delong test.
Results
48.1% of patients had tumor recurrence and 51.9% of patients had treatment-related changes. There was significant difference between ADCmean in recurrent and non-recurrent groups measuring 0.9 and 1.15 × 10−3mm2/s, respectively (p value < 0.001). BT-RADS, BT-RADS added DWI, and BT-RADS added DWI and resection cavity FLAIR signal had a specificity of 64.3, 71.4, and 71.4%, sensitivity of 76.9, 84.6, and 92.3%, and accuracy of 70.5, 77.8, and 81.5%, with improved AUC from 0.706 (95% CI of 0.50–0.86) to 0.78 (95% CI of 0.58–0.92) to 0.819 (95% CI of 0.64–0.94), respectively.
Conclusions
Adding DWI and resection cavity FLAIR signal alteration improves the diagnostic performance of BT-RADS category 3.
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Zu T, Sun Y, Wu D, Zhang Y. Joint K-space and Image-space Parallel Imaging (KIPI) for accelerated chemical exchange saturation transfer acquisition. Magn Reson Med 2023; 89:922-936. [PMID: 36336741 DOI: 10.1002/mrm.29480] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Revised: 08/25/2022] [Accepted: 09/16/2022] [Indexed: 11/09/2022]
Abstract
PURPOSE To develop an auto-calibrated technique by joint K-space and Image-space Parallel Imaging (KIPI) for accelerated CEST acquisition. THEORY AND METHODS The KIPI method selects a calibration frame with a low acceleration factor (AF) and auto-calibration signals (ACS) acquired, from which the coil sensitivity profiles and artifact correction maps are calculated after restoring the k-space by GRAPPA. Then the other frames with high AF and without ACS can be reconstructed by SENSE and artifact suppression. The signal leakage due to the T2 -decay filtering in k-space compromises the SENSE reconstruction, which can be corrected by the artifact suppression algorithm of KIPI. The 2D and 3D imaging experiments were done on the phantom, healthy volunteer, and brain tumor patient with a 3T scanner. RESULTS The proposed KIPI method was evaluated by retrospectively undersampled data with variable AFs and compared against existing parallel imaging methods (SENSE/auto, GRAPPA, and ESPIRiT). KIPI enabled CEST frames with random AFs to achieve similar image quality, eliminated the strong aliasing artifacts, and generated significantly smaller errors than the other methods (p < 0.01). The KIPI method permitted an AF up to 12-fold in both phase-encoding and slice-encoding directions for 3D CEST source images, achieving an overall 8.2-fold speedup in scan time. CONCLUSION KIPI is a novel auto-calibrated parallel imaging method that enables variable AFs for different CEST frames, achieves a significant reduction in scan time, and does not compromise the accuracy of CEST maps.
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Affiliation(s)
- Tao Zu
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China
| | - Yi Sun
- MR Collaboration, Siemens Healthcare Ltd., Shanghai, China
| | - Dan Wu
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China
| | - Yi Zhang
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China
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21
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Three-Dimensional Gradient-Echo-Based Amide Proton Transfer-Weighted Imaging of Brain Tumors: Comparison With Two-Dimensional Spin-Echo-Based Amide Proton Transfer-Weighted Imaging. J Comput Assist Tomogr 2023; 47:00004728-990000000-00139. [PMID: 36790914 DOI: 10.1097/rct.0000000000001432] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/16/2023]
Abstract
OBJECTIVE Although amide proton transfer-weighted (APTw) imaging is reported by 2-dimensional (2D) spin-echo-based sequencing, 3-dimensional (3D) APTw imaging can be obtained by gradient-echo-based sequencing. The purpose of this study was to compare the efficacy of APTw imaging between 2D and 3D imaging in patients with various brain tumors. METHODS A total of 49 patients who had undergone 53 examinations [5 low-grade gliomas (LGG), 16 high-grade gliomas (HGG), 6 malignant lymphomas, 4 metastases, and 22 meningiomas] underwent APTw imaging using 2D and 3D sequences. The magnetization transfer ratio asymmetry (MTRasym) was assessed by means of region of interest measurements. Pearson correlation was performed to determine the relationship between MTRasym for the 2 methods, and Student's t test to compare MTRasym for LGG and HGG. The diagnostic accuracy to differentiate HGG from LGG of the 2 methods was compared by means of the McNemar test. RESULTS Three-dimensional APTw imaging showed a significant correlation with 2D APTw imaging (r = 0.79, P < 0.0001). The limits of agreement between the 2 methods were -0.021 ± 1.42%. The MTRasym of HGG (2D: 1.97 ± 0.96, 3D: 2.11 ± 0.95) was significantly higher than those of LGG (2D: 0.46 ± 0.89%, P < 0.01; 3D: 0.15 ± 1.09%, P < 0.001). The diagnostic performance of the 2 methods to differentiate HGG from LGG was not significantly different (P = 1). CONCLUSIONS The potential capability of 3D APTw imaging is equal to or greater than that of 2D APTw imaging and is considered at least as valuable in patients with brain tumors.
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Nabavizadeh A, Barkovich MJ, Mian A, Ngo V, Kazerooni AF, Villanueva-Meyer JE. Current state of pediatric neuro-oncology imaging, challenges and future directions. Neoplasia 2023; 37:100886. [PMID: 36774835 PMCID: PMC9945752 DOI: 10.1016/j.neo.2023.100886] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Revised: 01/20/2023] [Accepted: 02/05/2023] [Indexed: 02/12/2023]
Abstract
Imaging plays a central role in neuro-oncology including primary diagnosis, treatment planning, and surveillance of tumors. The emergence of quantitative imaging and radiomics provided an uprecedented opportunity to compile mineable databases that can be utilized in a variety of applications. In this review, we aim to summarize the current state of conventional and advanced imaging techniques, standardization efforts, fast protocols, contrast and sedation in pediatric neuro-oncologic imaging, radiomics-radiogenomics, multi-omics and molecular imaging approaches. We will also address the existing challenges and discuss future directions.
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Affiliation(s)
- Ali Nabavizadeh
- Department of Radiology, Hospital of University of Pennsylvania, Perelman School of Medicine of the University of Pennsylvania, Philadelphia, Pennsylvania, USA; Center for Data-Driven Discovery in Biomedicine (D3b), Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.
| | - Matthew J Barkovich
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California, USA
| | - Ali Mian
- Division of Neuroradiology, Mallinckrodt Institute of Radiology, Washington University in St. Louis, Missouri, USA
| | - Van Ngo
- Saint Louis University School of Medicine, St. Louis, Missouri, USA
| | - Anahita Fathi Kazerooni
- Center for Data-Driven Discovery in Biomedicine (D3b), Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - Javier E Villanueva-Meyer
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California, USA
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23
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Molecular MRI-Based Monitoring of Cancer Immunotherapy Treatment Response. Int J Mol Sci 2023; 24:ijms24043151. [PMID: 36834563 PMCID: PMC9959624 DOI: 10.3390/ijms24043151] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2023] [Revised: 01/29/2023] [Accepted: 02/02/2023] [Indexed: 02/09/2023] Open
Abstract
Immunotherapy constitutes a paradigm shift in cancer treatment. Its FDA approval for several indications has yielded improved prognosis for cases where traditional therapy has shown limited efficiency. However, many patients still fail to benefit from this treatment modality, and the exact mechanisms responsible for tumor response are unknown. Noninvasive treatment monitoring is crucial for longitudinal tumor characterization and the early detection of non-responders. While various medical imaging techniques can provide a morphological picture of the lesion and its surrounding tissue, a molecular-oriented imaging approach holds the key to unraveling biological effects that occur much earlier in the immunotherapy timeline. Magnetic resonance imaging (MRI) is a highly versatile imaging modality, where the image contrast can be tailored to emphasize a particular biophysical property of interest using advanced engineering of the imaging pipeline. In this review, recent advances in molecular-MRI based cancer immunotherapy monitoring are described. Next, the presentation of the underlying physics, computational, and biological features are complemented by a critical analysis of the results obtained in preclinical and clinical studies. Finally, emerging artificial intelligence (AI)-based strategies to further distill, quantify, and interpret the image-based molecular MRI information are discussed in terms of perspectives for the future.
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Cohen O, Yu VY, Tringale KR, Young RJ, Perlman O, Farrar CT, Otazo R. CEST MR fingerprinting (CEST-MRF) for brain tumor quantification using EPI readout and deep learning reconstruction. Magn Reson Med 2023; 89:233-249. [PMID: 36128888 PMCID: PMC9617776 DOI: 10.1002/mrm.29448] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Revised: 08/09/2022] [Accepted: 08/19/2022] [Indexed: 01/21/2023]
Abstract
PURPOSE To develop a clinical CEST MR fingerprinting (CEST-MRF) method for brain tumor quantification using EPI acquisition and deep learning reconstruction. METHODS A CEST-MRF pulse sequence originally designed for animal imaging was modified to conform to hardware limits on clinical scanners while keeping scan time under 2 min. Quantitative MRF reconstruction was performed using a deep reconstruction network (DRONE) to yield the water relaxation and chemical exchange parameters. The feasibility of the six parameter DRONE reconstruction was tested in simulations using a digital brain phantom. A healthy subject was scanned with the CEST-MRF sequence, conventional MRF and CEST sequences for comparison. Reproducibility was assessed via test-retest experiments and the concordance correlation coefficient calculated for white matter and gray matter. The clinical utility of CEST-MRF was demonstrated on four patients with brain metastases in comparison to standard clinical imaging sequences. Tumors were segmented into edema, solid core, and necrotic core regions and the CEST-MRF values compared to the contra-lateral side. RESULTS DRONE reconstruction of the digital phantom yielded a normalized RMS error of ≤7% for all parameters. The CEST-MRF parameters were in good agreement with those from conventional MRF and CEST sequences and previous studies. The mean concordance correlation coefficient for all six parameters was 0.98 ± 0.01 in white matter and 0.98 ± 0.02 in gray matter. The CEST-MRF values in nearly all tumor regions were significantly different (P = 0.05) from each other and the contra-lateral side. CONCLUSION Combination of EPI readout and deep learning reconstruction enabled fast, accurate and reproducible CEST-MRF in brain tumors.
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Affiliation(s)
- Ouri Cohen
- Department of Medical PhysicsMemorial Sloan Kettering Cancer Center
New YorkNew YorkUSA
| | - Victoria Y. Yu
- Department of Medical PhysicsMemorial Sloan Kettering Cancer Center
New YorkNew YorkUSA
| | - Kathryn R. Tringale
- Department of Radiation OncologyMemorial Sloan Kettering Cancer CenterNew YorkNew YorkUSA
| | - Robert J. Young
- Department of RadiologyMemorial Sloan Kettering Cancer CenterNew YorkNew YorkUSA
| | - Or Perlman
- Athinoula A. Martinos Center for Biomedical Imaging, Department of RadiologyMassachusetts General Hospital and Harvard Medical SchoolCharlestownMassachusettsUSA
- Department of Biomedical EngineeringTel Aviv UniversityTel AvivIsrael
- Sagol School of NeuroscienceTel Aviv UniversityTel AvivIsrael
| | - Christian T. Farrar
- Athinoula A. Martinos Center for Biomedical Imaging, Department of RadiologyMassachusetts General Hospital and Harvard Medical SchoolCharlestownMassachusettsUSA
| | - Ricardo Otazo
- Department of Medical PhysicsMemorial Sloan Kettering Cancer Center
New YorkNew YorkUSA
- Department of RadiologyMemorial Sloan Kettering Cancer CenterNew YorkNew YorkUSA
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Hou H, Diao Y, Yu J, Xu M, Wang L, Li Z, Song T, Liu Y, Yuan Z. Differentiation of true progression from treatment response in high-grade glioma treated with chemoradiation: a comparison study of 3D-APTW and 3D-PcASL imaging and DWI. NMR IN BIOMEDICINE 2023; 36:e4821. [PMID: 36031734 DOI: 10.1002/nbm.4821] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/26/2022] [Revised: 08/19/2022] [Accepted: 08/20/2022] [Indexed: 06/15/2023]
Abstract
PURPOSE To assess and compare the diagnostic performance of 3D amide proton-transfer-weighted (3D-APTW) imaging, 3D pseudocontinuous arterial spin-labeling (3D-PcASL) imaging, and diffusion-weighted imaging in distinguishing true progression (TP) from treatment response (TR) in posttreatment malignant glioma patients. MATERIALS AND METHODS Forty-eight patients with suspected tumor recurrence were prospectively enrolled. Histological or longitudinal routine MRI follow-up over six months was assessed to confirm lesion type. The apparent diffusion coefficient (ADC), relative APTWmax (rAPTW), and relative CBFmax values (rCBF) were measured in lesions with enhancing regions on post-gadolinium T1 -weighted MRI. MRI parameters between the TP and TR groups were compared using Student's t tests. In addition, a receiver operating characteristic (ROC) curve was constructed, and the area under the ROC curve (AUC) was calculated to assess the differentiation diagnostic performance of each parameter. RESULTS The TP group showed a significantly higher rAPTW and rCBF than the TR group; the AUCs of rAPTW and rCBF to distinguish between TP and TR were 0.911 (with sensitivity of 90.3% and specificity of 82.4%) and 0.852 (with sensitivity of 80.6% and specificity of 82.4%), respectively. By adding the rAPTW values to rCBF values, the diagnostic ability was improved from 0.852 to 0.951. ADC showed no significant differences between the TP and TR groups, with an AUC lower than 0.70. CONCLUSION Both 3D-PcASL and 3D-APTW imaging could distinguish TP from TR, and 3D-APTW had a better diagnostic performance. Combining the rAPTW values and rCBF values achieved a better diagnostic performance.
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Affiliation(s)
- Huimin Hou
- Department of Radiology, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
- Department of Radiology, Weihai Municipal Hospital, Cheeloo College of Medicine, Shandong University, Weihai, China
| | - Yanzhao Diao
- Department of Radiology, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Jinchao Yu
- Department of Radiology, Weihai Municipal Hospital, Cheeloo College of Medicine, Shandong University, Weihai, China
| | - Min Xu
- Department of Radiology, Weihai Municipal Hospital, Cheeloo College of Medicine, Shandong University, Weihai, China
| | - Liming Wang
- Department of Radiology, Weihai Municipal Hospital, Cheeloo College of Medicine, Shandong University, Weihai, China
| | - Zhenzhi Li
- Department of Radiology, Weihai Municipal Hospital, Cheeloo College of Medicine, Shandong University, Weihai, China
| | - Tao Song
- Department of Neurosurgery, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China
- Department of Neurosurgery, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Yu Liu
- Department of Pathology, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Zhenguo Yuan
- Department of Radiology, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
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Jiang S, Guo P, Heo HY, Zhang Y, Wu J, Jin Y, Laterra J, Eberhart CG, Lim M, Blakeley JO. Radiomics analysis of amide proton transfer-weighted and structural MR images for treatment response assessment in malignant gliomas. NMR IN BIOMEDICINE 2023; 36:e4824. [PMID: 36057449 PMCID: PMC10502874 DOI: 10.1002/nbm.4824] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Revised: 08/25/2022] [Accepted: 08/28/2022] [Indexed: 06/15/2023]
Abstract
The purpose of this study was to evaluate the value of amide proton transfer-weighted (APTw) MRI radiomic features for the differentiation of tumor recurrence from treatment effect in malignant gliomas. Eighty-six patients who had suspected tumor recurrence after completion of chemoradiation or radiotherapy, and who had APTw-MRI data acquired at 3 T, were retrospectively analyzed. Using a fluid-attenuated inversion recovery (FLAIR) image-based mask, radiomics analysis was applied to the processed APTw and structural MR images. A chi-square automatic interaction detector decision tree was used for classification analysis. Models with and without APTw features were built using the same strategy. Tenfold cross-validation was applied to obtain the overall classification performance of each model. Sixty patients were confirmed as having tumor recurrence, and the remainder were confirmed as having treatment effect, at median time points of 190 and 171 days after therapy, respectively. There were 525 radiomic features extracted from each of the processed APTw and structural MR images. Based on these, the APTw-based model yielded the highest accuracy (86.0%) for the differentiation of tumor recurrence from treatment effect, compared with 74.4%, 76.7%, 83.7%, and 76.7% for T1 w, T2 w, FLAIR, and Gd-T1 w, respectively. Model classification accuracy was 82.6% when using the combined structural MR images (T1 w, T2 w, FLAIR, Gd-T1 w), and increased to 89.5% when using these structural plus APTw images. The corresponding sensitivity and specificity were 85.0% and 76.9% for the combination of structural MR images, and 85.0% and 100% after adding APTw image features. Adding APTw-based radiomic features increased MRI accuracy in the assessment of the treatment response in post-treatment malignant gliomas.
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Affiliation(s)
- Shanshan Jiang
- Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Maryland, USA
| | - Pengfei Guo
- Department of Computer Science, Johns Hopkins University, Baltimore, Maryland, USA
| | - Hye-Young Heo
- Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Maryland, USA
| | - Yi Zhang
- Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Maryland, USA
| | - Jingpu Wu
- Department of Applied Mathematics and Statistics, Johns Hopkins University, Baltimore, Maryland, USA
| | - Yuecen Jin
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, USA
| | - John Laterra
- Department of Neurology, Johns Hopkins University, Baltimore, Maryland, USA
- Hugo W. Moser Research Institute at Kennedy Krieger, Baltimore, Maryland, USA
| | | | - Michael Lim
- Department of Neurosurgery, Johns Hopkins University, Baltimore, Maryland, USA
- Department of Neurosurgery, Stanford University, Palo Alto, California, USA
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Hesse F, Wright AJ, Somai V, Bulat F, Kreis F, Brindle KM. Imaging Glioblastoma Response to Radiotherapy Using 2H Magnetic Resonance Spectroscopy Measurements of Fumarate Metabolism. Cancer Res 2022; 82:3622-3633. [PMID: 35972377 PMCID: PMC9530651 DOI: 10.1158/0008-5472.can-22-0101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2022] [Revised: 03/25/2022] [Accepted: 08/08/2022] [Indexed: 11/16/2022]
Abstract
Early detection of tumor cell death in glioblastoma following treatment with chemoradiation has the potential to distinguish between true disease progression and pseudoprogression. Tumor cell death can be detected noninvasively in vivo by imaging the production of [2,3-2H2]malate from [2,3-2H2]fumarate using 2H magnetic resonance (MR) spectroscopic imaging. We show here that 2H MR spectroscopy and spectroscopic imaging measurements of [2,3-2H2]fumarate metabolism can detect tumor cell death in orthotopically implanted glioblastoma models within 48 hours following the completion of chemoradiation. Following the injection of [2,3-2H2]fumarate into tumor-bearing mice, production of [2,3-2H2]malate was measured in a human cell line-derived model and in radiosensitive and radioresistant patient-derived models of glioblastoma that were treated with temozolomide followed by targeted fractionated irradiation. The increase in the [2,3-2H2]malate/[2,3-2H2]fumarate signal ratio posttreatment, which correlated with histologic assessment of cell death, was a more sensitive indicator of treatment response than diffusion-weighted and contrast agent-enhanced 1H MRI measurements, which have been used clinically to detect responses of glioblastoma to chemoradiation. Overall, early detection of glioblastoma cell death using 2H MRI of malate production from fumarate could help improve the clinical evaluation of response to chemoradiation. SIGNIFICANCE 2H magnetic resonance imaging of labeled fumarate metabolism can detect early evidence of tumor cell death following chemoradiation, meeting a clinical need to reliably detect treatment response in glioblastoma.
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Affiliation(s)
- Friederike Hesse
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom
| | - Alan J. Wright
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom
| | - Vencel Somai
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom
- Department of Radiology, School of Clinical Medicine, Cambridge Biomedical Campus, University of Cambridge, Cambridge, United Kingdom
| | - Flaviu Bulat
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom
- Department of Chemistry, University of Cambridge, Cambridge, United Kingdom
| | - Felix Kreis
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom
| | - Kevin M. Brindle
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom
- Department of Biochemistry, University of Cambridge, Cambridge, United Kingdom
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McCarthy L, Verma G, Hangel G, Neal A, Moffat BA, Stockmann JP, Andronesi OC, Balchandani P, Hadjipanayis CG. Application of 7T MRS to High-Grade Gliomas. AJNR Am J Neuroradiol 2022; 43:1378-1395. [PMID: 35618424 PMCID: PMC9575545 DOI: 10.3174/ajnr.a7502] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2021] [Accepted: 02/11/2022] [Indexed: 01/26/2023]
Abstract
MRS, including single-voxel spectroscopy and MR spectroscopic imaging, captures metabolites in high-grade gliomas. Emerging evidence indicates that 7T MRS may be more sensitive to aberrant metabolic activity than lower-field strength MRS. However, the literature on the use of 7T MRS to visualize high-grade gliomas has not been summarized. We aimed to identify metabolic information provided by 7T MRS, optimal spectroscopic sequences, and areas for improvement in and new applications for 7T MRS. Literature was found on PubMed using "high-grade glioma," "malignant glioma," "glioblastoma," "anaplastic astrocytoma," "7T," "MR spectroscopy," and "MR spectroscopic imaging." 7T MRS offers higher SNR, modestly improved spatial resolution, and better resolution of overlapping resonances. 7T MRS also yields reduced Cramér-Rao lower bound values. These features help to quantify D-2-hydroxyglutarate in isocitrate dehydrogenase 1 and 2 gliomas and to isolate variable glutamate, increased glutamine, and increased glycine with higher sensitivity and specificity. 7T MRS may better characterize tumor infiltration and treatment effect in high-grade gliomas, though further study is necessary. 7T MRS will benefit from increased sample size; reductions in field inhomogeneity, specific absorption rate, and acquisition time; and advanced editing techniques. These findings suggest that 7T MRS may advance understanding of high-grade glioma metabolism, with reduced Cramér-Rao lower bound values and better measurement of smaller metabolite signals. Nevertheless, 7T is not widely used clinically, and technical improvements are necessary. 7T MRS isolates metabolites that may be valuable therapeutic targets in high-grade gliomas, potentially resulting in wider ranging neuro-oncologic applications.
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Affiliation(s)
- L McCarthy
- From the Department of Neurosurgery (L.M., C.G.H.), Icahn School of Medicine at Mount Sinai, Mount Sinai Health System, New York, New York
| | - G Verma
- BioMedical Engineering and Imaging Institute (G.V., P.B.), Icahn School of Medicine at Mount Sinai, New York, New York
| | - G Hangel
- Department of Neurosurgery (G.H.)
- High-field MR Center (G.H.), Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - A Neal
- Department of Medicine (A.N.), Royal Melbourne Hospital, University of Melbourne, Melbourne, Australia
- Department of Neurology (A.N.), Royal Melbourne Hospital, Melbourne, Australia
| | - B A Moffat
- The Melbourne Brain Centre Imaging Unit (B.A.M.), Department of Radiology, The University of Melbourne, Melbourne, Australia
| | - J P Stockmann
- A. A. Martinos Center for Biomedical Imaging (J.P.S., O.C.A.), Massachusetts General Hospital, Charlestown, Massachusetts
- Harvard Medical School (J.P.S., O.C.A.), Boston, Massachusetts
| | - O C Andronesi
- A. A. Martinos Center for Biomedical Imaging (J.P.S., O.C.A.), Massachusetts General Hospital, Charlestown, Massachusetts
- Harvard Medical School (J.P.S., O.C.A.), Boston, Massachusetts
| | - P Balchandani
- BioMedical Engineering and Imaging Institute (G.V., P.B.), Icahn School of Medicine at Mount Sinai, New York, New York
| | - C G Hadjipanayis
- From the Department of Neurosurgery (L.M., C.G.H.), Icahn School of Medicine at Mount Sinai, Mount Sinai Health System, New York, New York
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Qin D, Yang G, Jing H, Tan Y, Zhao B, Zhang H. Tumor Progression and Treatment-Related Changes: Radiological Diagnosis Challenges for the Evaluation of Post Treated Glioma. Cancers (Basel) 2022; 14:cancers14153771. [PMID: 35954435 PMCID: PMC9367286 DOI: 10.3390/cancers14153771] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2022] [Revised: 07/25/2022] [Accepted: 07/27/2022] [Indexed: 12/30/2022] Open
Abstract
Simple Summary Glioma is the most common primary malignant tumor of the adult central nervous system. Despite aggressive multimodal treatment, its prognosis remains poor. During follow-up, it remains challenging to distinguish treatment-related changes from tumor progression in treated patients with gliomas due to both share clinical symptoms and morphological imaging characteristics (with new and/or increasing enhancing mass lesions). The early effective identification of tumor progression and treatment-related changes is of great significance for the prognosis and treatment of gliomas. We believe that advanced neuroimaging techniques can provide additional information for distinguishing both at an early stage. In this article, we focus on the research of magnetic resonance imaging technology and artificial intelligence in tumor progression and treatment-related changes. Finally, it provides new ideas and insights for clinical diagnosis. Abstract As the most common neuro-epithelial tumors of the central nervous system in adults, gliomas are highly malignant and easy to recurrence, with a dismal prognosis. Imaging studies are indispensable for tracking tumor progression (TP) or treatment-related changes (TRCs). During follow-up, distinguishing TRCs from TP in treated patients with gliomas remains challenging as both share similar clinical symptoms and morphological imaging characteristics (with new and/or increasing enhancing mass lesions) and fulfill criteria for progression. Thus, the early identification of TP and TRCs is of great significance for determining the prognosis and treatment. Histopathological biopsy is currently the gold standard for TP and TRC diagnosis. However, the invasive nature of this technique limits its clinical application. Advanced imaging methods (e.g., diffusion magnetic resonance imaging (MRI), perfusion MRI, magnetic resonance spectroscopy (MRS), positron emission tomography (PET), amide proton transfer (APT) and artificial intelligence (AI)) provide a non-invasive and feasible technical means for identifying of TP and TRCs at an early stage, which have recently become research hotspots. This paper reviews the current research on using the abovementioned advanced imaging methods to identify TP and TRCs of gliomas. First, the review focuses on the pathological changes of the two entities to establish a theoretical basis for imaging identification. Then, it elaborates on the application of different imaging techniques and AI in identifying the two entities. Finally, the current challenges and future prospects of these techniques and methods are discussed.
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Affiliation(s)
- Danlei Qin
- College of Medical Imaging, Shanxi Medical University, Taiyuan 030001, China;
- Shanxi Province Key Laboratory of Oral Diseases Prevention and New Materials, Shanxi Medical University School, Hospital of Stomatology, Taiyuan 030001, China
| | - Guoqiang Yang
- Department of Radiology, First Clinical Medical College, Shanxi Medical University, Taiyuan 030001, China; (G.Y.); (Y.T.)
| | - Hui Jing
- Department of MRI, The Six Hospital, Shanxi Medical University, Taiyuan 030008, China;
| | - Yan Tan
- Department of Radiology, First Clinical Medical College, Shanxi Medical University, Taiyuan 030001, China; (G.Y.); (Y.T.)
| | - Bin Zhao
- College of Medical Imaging, Shanxi Medical University, Taiyuan 030001, China;
- Shanxi Province Key Laboratory of Oral Diseases Prevention and New Materials, Shanxi Medical University School, Hospital of Stomatology, Taiyuan 030001, China
- Correspondence: (B.Z.); (H.Z.)
| | - Hui Zhang
- College of Medical Imaging, Shanxi Medical University, Taiyuan 030001, China;
- Department of Radiology, First Clinical Medical College, Shanxi Medical University, Taiyuan 030001, China; (G.Y.); (Y.T.)
- Intelligent Imaging Big Data and Functional Nano-imaging Engineering Research Center of Shanxi Province, Taiyuan 030001, China
- Correspondence: (B.Z.); (H.Z.)
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30
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Taylor C, Ekert JO, Sefcikova V, Fersht N, Samandouras G. Discriminators of pseudoprogression and true progression in high-grade gliomas: A systematic review and meta-analysis. Sci Rep 2022; 12:13258. [PMID: 35918373 PMCID: PMC9345984 DOI: 10.1038/s41598-022-16726-x] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Accepted: 07/14/2022] [Indexed: 11/09/2022] Open
Abstract
High-grade gliomas remain the most common primary brain tumour with limited treatments options and early recurrence rates following adjuvant treatments. However, differentiating true tumour progression (TTP) from treatment-related effects or pseudoprogression (PsP), may critically influence subsequent management options. Structural MRI is routinely employed to evaluate treatment responses, but misdiagnosis of TTP or PsP may lead to continuation of ineffective or premature cessation of effective treatments, respectively. A systematic review and meta-analysis were conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-analyses method. Embase, MEDLINE, Web of Science and Google Scholar were searched for methods applied to differentiate PsP and TTP, and studies were selected using pre-specified eligibility criteria. The sensitivity and specificity of included studies were summarised. Three of the identified methods were compared in a separate subgroup meta-analysis. Thirty studies assessing seven distinct neuroimaging methods in 1372 patients were included in the systematic review. The highest performing methods in the subgroup analysis were DWI (AUC = 0.93 [0.91-0.95]) and DSC-MRI (AUC = 0.93 [0.90-0.95]), compared to DCE-MRI (AUC = 0.90 [0.87-0.93]). 18F-fluoroethyltyrosine PET (18F-FET PET) and amide proton transfer-weighted MRI (APTw-MRI) also showed high diagnostic accuracy, but results were based on few low-powered studies. Both DWI and DSC-MRI performed with high sensitivity and specificity for differentiating PsP from TTP. Considering the technical parameters and feasibility of each identified method, the authors suggested that, at present, DSC-MRI technique holds the most clinical potential.
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Affiliation(s)
- Chris Taylor
- UCL Queen Square Institute of Neurology, University College London, Gower St., Bloomsbury, Queen Square, London, WC1E 6BT, UK.
| | - Justyna O Ekert
- Wellcome Centre for Human Neuroimaging, University College London, 12 Queen Square, London, UK
| | - Viktoria Sefcikova
- UCL Queen Square Institute of Neurology, University College London, Gower St., Bloomsbury, Queen Square, London, WC1E 6BT, UK
| | - Naomi Fersht
- Department of Oncology, University College London Hospitals NHS Foundation Trust, London, UK
| | - George Samandouras
- Wellcome Centre for Human Neuroimaging, University College London, 12 Queen Square, London, UK
- Victor Horsley Department of Neurosurgery, The National Hospital for Neurology and Neurosurgery, Queen Square, London, UK
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Chen K, Jiang XW, Deng LJ, She HL. Differentiation between glioma recurrence and treatment effects using amide proton transfer imaging: A mini-Bayesian bivariate meta-analysis. Front Oncol 2022; 12:852076. [PMID: 35978813 PMCID: PMC9376615 DOI: 10.3389/fonc.2022.852076] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Accepted: 06/29/2022] [Indexed: 11/24/2022] Open
Abstract
Background Amide proton transfer (APT) imaging as an emerging MRI approach has been used for distinguishing tumor recurrence (TR) and treatment effects (TEs) in glioma patients, but the initial results from recent studies are different. Aim The aim of this study is to systematically review and quantify the diagnostic performance of APT in assessing treatment response in patients with post-treatment gliomas. Methods A systematic search in PubMed, EMBASE, and the Web of Science was performed to retrieve related original studies. For the single and added value of APT imaging in distinguishing TR from TEs, we calculated pooled sensitivity and specificity by using Bayesian bivariate meta-analyses. Results Six studies were included, five of which reported on single APT imaging parameters and four of which reported on multiparametric MRI combined with APT imaging parameters. For single APT imaging parameters, the pooled sensitivity and specificity were 0.85 (95% CI: 0.75–0.92) and 0.88 (95% CI: 0.74–0.97). For multiparametric MRI including APT, the pooled sensitivity and specificity were 0.92 (95% CI: 0.85–0.97) and 0.83 (95% CI: 0.55–0.97), respectively. In addition, in the three studies reported on both single and added value of APT imaging parameters, the combined imaging parameters further improved diagnostic performance, yielding pooled sensitivity and specificity of 0.91 (95% CI: 0.80–0.97) and 0.92 (95% CI: 0.79–0.98), respectively, but the pooled sensitivity was 0.81 (95% CI: 0.65-0.93) and specificity was 0.82 (95% CI: 0.61–0.94) for single APT imaging parameters. Conclusion APT imaging showed high diagnostic performance in assessing treatment response in patients with post-treatment gliomas, and the addition of APT imaging to other advanced MRI techniques can improve the diagnostic accuracy for distinguishing TR from TE.
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Affiliation(s)
- Kai Chen
- Department of Medical Imaging, Shenzhen Samii Medical Center, Shenzhen, China
| | - Xi-Wen Jiang
- Department of Medical Imaging, Affiliated Hospital of Xiangnan University (Clinical College), Chenzhou, China
| | - Li-jing Deng
- Department of Neonatology, Shenzhen Third People’s Hospital, Second Hospital Affiliated to Southern University of Science and Technology, Shenzhen, China
| | - Hua-Long She
- Department of Medical Imaging, Affiliated Hospital of Xiangnan University (Clinical College), Chenzhou, China
- *Correspondence: Hua-Long She,
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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 IN BIOMEDICINE 2022; 35:e4719. [PMID: 35233862 PMCID: PMC9203929 DOI: 10.1002/nbm.4719] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [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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33
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Li AY, Iv M. Conventional and Advanced Imaging Techniques in Post-treatment Glioma Imaging. FRONTIERS IN RADIOLOGY 2022; 2:883293. [PMID: 37492665 PMCID: PMC10365131 DOI: 10.3389/fradi.2022.883293] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/24/2022] [Accepted: 06/06/2022] [Indexed: 07/27/2023]
Abstract
Despite decades of advancement in the diagnosis and therapy of gliomas, the most malignant primary brain tumors, the overall survival rate is still dismal, and their post-treatment imaging appearance remains very challenging to interpret. Since the limitations of conventional magnetic resonance imaging (MRI) in the distinction between recurrence and treatment effect have been recognized, a variety of advanced MR and functional imaging techniques including diffusion-weighted imaging (DWI), diffusion tensor imaging (DTI), perfusion-weighted imaging (PWI), MR spectroscopy (MRS), as well as a variety of radiotracers for single photon emission computed tomography (SPECT) and positron emission tomography (PET) have been investigated for this indication along with voxel-based and more quantitative analytical methods in recent years. Machine learning and radiomics approaches in recent years have shown promise in distinguishing between recurrence and treatment effect as well as improving prognostication in a malignancy with a very short life expectancy. This review provides a comprehensive overview of the conventional and advanced imaging techniques with the potential to differentiate recurrence from treatment effect and includes updates in the state-of-the-art in advanced imaging with a brief overview of emerging experimental techniques. A series of representative cases are provided to illustrate the synthesis of conventional and advanced imaging with the clinical context which informs the radiologic evaluation of gliomas in the post-treatment setting.
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Affiliation(s)
- Anna Y. Li
- Department of Radiology, Stanford University School of Medicine, Stanford, CA, United States
| | - Michael Iv
- Division of Neuroimaging and Neurointervention, Department of Radiology, Stanford University School of Medicine, Stanford, CA, United States
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Zhou J, Zaiss M, Knutsson L, Sun PZ, Ahn SS, Aime S, Bachert P, Blakeley JO, Cai K, Chappell MA, Chen M, Gochberg DF, Goerke S, Heo HY, Jiang S, Jin T, Kim SG, Laterra J, Paech D, Pagel MD, Park JE, Reddy R, Sakata A, Sartoretti-Schefer S, Sherry AD, Smith SA, Stanisz GJ, Sundgren PC, Togao O, Vandsburger M, Wen Z, Wu Y, Zhang Y, Zhu W, Zu Z, van Zijl PCM. Review and consensus recommendations on clinical APT-weighted imaging approaches at 3T: Application to brain tumors. Magn Reson Med 2022; 88:546-574. [PMID: 35452155 PMCID: PMC9321891 DOI: 10.1002/mrm.29241] [Citation(s) in RCA: 73] [Impact Index Per Article: 36.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2021] [Revised: 02/26/2022] [Accepted: 03/02/2022] [Indexed: 12/16/2022]
Abstract
Amide proton transfer-weighted (APTw) MR imaging shows promise as a biomarker of brain tumor status. Currently used APTw MRI pulse sequences and protocols vary substantially among different institutes, and there are no agreed-on standards in the imaging community. Therefore, the results acquired from different research centers are difficult to compare, which hampers uniform clinical application and interpretation. This paper reviews current clinical APTw imaging approaches and provides a rationale for optimized APTw brain tumor imaging at 3 T, including specific recommendations for pulse sequences, acquisition protocols, and data processing methods. We expect that these consensus recommendations will become the first broadly accepted guidelines for APTw imaging of brain tumors on 3 T MRI systems from different vendors. This will allow more medical centers to use the same or comparable APTw MRI techniques for the detection, characterization, and monitoring of brain tumors, enabling multi-center trials in larger patient cohorts and, ultimately, routine clinical use.
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Affiliation(s)
- Jinyuan Zhou
- Division of MR Research, Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Moritz Zaiss
- Magnetic Resonance Center, Max Planck Institute for Biological Cybernetics, Tübingen, Germany.,Institute of Neuroradiology, University Hospital Erlangen, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Linda Knutsson
- Division of MR Research, Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,Department of Medical Radiation Physics, Lund University, Lund, Sweden.,F.M. Kirby Research Center for Functional Brain Imaging, Hugo W. Moser Research Institute at Kennedy Krieger, Baltimore, Maryland, USA
| | - Phillip Zhe Sun
- Yerkes Imaging Center, Yerkes National Primate Research Center, Emory University, Atlanta, Georgia, USA
| | - Sung Soo Ahn
- Department of Radiology and Research Institute of Radiological Science, Yonsei University College of Medicine, Seoul, South Korea
| | - Silvio Aime
- Molecular Imaging Center, Department of Molecular Biotechnology and Health Sciences, University of Torino, Torino, Italy
| | - Peter Bachert
- Department of Medical Physics in Radiology, German Cancer Research Center, Heidelberg, Germany.,Faculty of Physics and Astronomy, University of Heidelberg, Heidelberg, Germany
| | - Jaishri O Blakeley
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Kejia Cai
- Department of Radiology, University of Illinois at Chicago, Chicago, Illinois, USA
| | - Michael A Chappell
- Mental Health and Clinical Neurosciences and Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, Nottingham, UK.,Nottingham Biomedical Research Centre, Queen's Medical Centre, University of Nottingham, Nottingham, UK
| | - Min Chen
- Department of Radiology, Beijing Hospital, National Center of Gerontology, Beijing, China
| | - Daniel F Gochberg
- Vanderbilt University Institute of Imaging Science (VUIIS), Vanderbilt University Medical Center, Nashville, Tennessee, USA.,Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, Tennessee, USA.,Department of Physics, Vanderbilt University, Nashville, Tennessee, USA
| | - Steffen Goerke
- Department of Medical Physics in Radiology, German Cancer Research Center, Heidelberg, Germany
| | - Hye-Young Heo
- Division of MR Research, Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Shanshan Jiang
- Division of MR Research, Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Tao Jin
- Department of Radiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Seong-Gi Kim
- Center for Neuroscience Imaging Research, Institute for Basic Science and Department of Biomedical Engineering, Sungkyunkwan University, Suwon, South Korea
| | - John Laterra
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,Hugo W. Moser Research Institute at Kennedy Krieger, Baltimore, Maryland, USA
| | - Daniel Paech
- Department of Radiology, German Cancer Research Center, Heidelberg, Germany.,Clinic for Neuroradiology, University Hospital Bonn, Bonn, Germany
| | - Mark D Pagel
- Department of Cancer Systems Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Ji Eun Park
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, South Korea
| | - Ravinder Reddy
- Center for Advance Metabolic Imaging in Precision Medicine, Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Akihiko Sakata
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | | | - A Dean Sherry
- Advanced Imaging Research Center and Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Texas, USA.,Department of Chemistry and Biochemistry, University of Texas at Dallas, Richardson, Texas, USA
| | - Seth A Smith
- Vanderbilt University Institute of Imaging Science (VUIIS), Vanderbilt University Medical Center, Nashville, Tennessee, USA.,Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, Tennessee, USA.,Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA
| | - Greg J Stanisz
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
| | - Pia C Sundgren
- Department of Diagnostic Radiology/Clinical Sciences Lund, Lund University, Lund, Sweden.,Lund University Bioimaging Center, Lund University, Lund, Sweden.,Department of Medical Imaging and Physiology, Skåne University Hospital, Lund University, Lund, Sweden
| | - Osamu Togao
- Department of Molecular Imaging and Diagnosis, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | | | - Zhibo Wen
- Department of Radiology, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, China
| | - Yin Wu
- Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, China
| | - Yi Zhang
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China
| | - Wenzhen Zhu
- Department of Radiology, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Zhongliang Zu
- Vanderbilt University Institute of Imaging Science (VUIIS), Vanderbilt University Medical Center, Nashville, Tennessee, USA.,Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Peter C M van Zijl
- Division of MR Research, Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,F.M. Kirby Research Center for Functional Brain Imaging, Hugo W. Moser Research Institute at Kennedy Krieger, Baltimore, Maryland, USA
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35
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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] [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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Booth TC, Wiegers EC, Warnert EAH, Schmainda KM, Riemer F, Nechifor RE, Keil VC, Hangel G, Figueiredo P, Álvarez-Torres MDM, Henriksen OM. High-Grade Glioma Treatment Response Monitoring Biomarkers: A Position Statement on the Evidence Supporting the Use of Advanced MRI Techniques in the Clinic, and the Latest Bench-to-Bedside Developments. Part 2: Spectroscopy, Chemical Exchange Saturation, Multiparametric Imaging, and Radiomics. Front Oncol 2022; 11:811425. [PMID: 35340697 PMCID: PMC8948428 DOI: 10.3389/fonc.2021.811425] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Accepted: 12/28/2021] [Indexed: 01/16/2023] Open
Abstract
Objective To summarize evidence for use of advanced MRI techniques as monitoring biomarkers in the clinic, and to highlight the latest bench-to-bedside developments. Methods The current evidence regarding the potential for monitoring biomarkers was reviewed and individual modalities of metabolism and/or chemical composition imaging discussed. Perfusion, permeability, and microstructure imaging were similarly analyzed in Part 1 of this two-part review article and are valuable reading as background to this article. We appraise the clinic readiness of all the individual modalities and consider methodologies involving machine learning (radiomics) and the combination of MRI approaches (multiparametric imaging). Results The biochemical composition of high-grade gliomas is markedly different from healthy brain tissue. Magnetic resonance spectroscopy allows the simultaneous acquisition of an array of metabolic alterations, with choline-based ratios appearing to be consistently discriminatory in treatment response assessment, although challenges remain despite this being a mature technique. Promising directions relate to ultra-high field strengths, 2-hydroxyglutarate analysis, and the use of non-proton nuclei. Labile protons on endogenous proteins can be selectively targeted with chemical exchange saturation transfer to give high resolution images. The body of evidence for clinical application of amide proton transfer imaging has been building for a decade, but more evidence is required to confirm chemical exchange saturation transfer use as a monitoring biomarker. Multiparametric methodologies, including the incorporation of nuclear medicine techniques, combine probes measuring different tumor properties. Although potentially synergistic, the limitations of each individual modality also can be compounded, particularly in the absence of standardization. Machine learning requires large datasets with high-quality annotation; there is currently low-level evidence for monitoring biomarker clinical application. Conclusion Advanced MRI techniques show huge promise in treatment response assessment. The clinical readiness analysis highlights that most monitoring biomarkers require standardized international consensus guidelines, with more facilitation regarding technique implementation and reporting in the clinic.
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Affiliation(s)
- Thomas C. Booth
- School of Biomedical Engineering and Imaging Sciences, King’s College London, St. Thomas’ Hospital, London, United Kingdom
- Department of Neuroradiology, King’s College Hospital NHS Foundation Trust, London, United Kingdom
| | - Evita C. Wiegers
- Department of Radiology, University Medical Center Utrecht, Utrecht, Netherlands
| | | | - Kathleen M. Schmainda
- Department of Biophysics, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Frank Riemer
- Mohn Medical Imaging and Visualization Centre (MMIV), Department of Radiology, Haukeland University Hospital, Bergen, Norway
| | - Ruben E. Nechifor
- Department of Clinical Psychology and Psychotherapy International Institute for the Advanced Studies of Psychotherapy and Applied Mental Health, Babes-Bolyai University, Cluj-Napoca, Romania
| | - Vera C. Keil
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, location VUmc, Amsterdam, Netherlands
| | - Gilbert Hangel
- Department of Neurosurgery & High-Field MR Centre, Department of Biomedical Imaging and Image-Guided Therapy, Medical University Vienna, Vienna, Austria
| | - Patrícia Figueiredo
- Department of Bioengineering and Institute for Systems and Robotics - Lisboa, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
| | | | - Otto M. Henriksen
- Department of Clinical Physiology, Nuclear medicine and PET, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark
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Liu Z, Zou L, Yang Q, Qian L, Li T, Luo H, Che C, Lei Y, Chen P, Qiu C, Liu X, Wu Y, Luo D. Baseline Amide Proton Transfer Imaging at 3T Fails to Predict Early Response to Induction Chemotherapy in Nasopharyngeal Carcinoma. Front Oncol 2022; 12:822756. [PMID: 35211414 PMCID: PMC8861375 DOI: 10.3389/fonc.2022.822756] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2021] [Accepted: 01/14/2022] [Indexed: 12/24/2022] Open
Abstract
Background Early identification of nasopharyngeal carcinoma (NPC) patients with high risk of failure to induction chemotherapy (IC) would facilitate prompt individualized treatment decisions and thus reduce toxicity and improve overall survival rate. This study aims to investigate the value of amide proton transfer (APT) imaging in predicting short-term response of NPC to IC and its potential correlation with well-established prognosis-related clinical characteristics. Methods and Materials A total of 80 pathologically confirmed NPC patients receiving pre-treatment APT imaging at 3T were retrospectively enrolled. Using asymmetry analysis, APT maps were calculated with mean (APTmean), 90th percentile (APT90) of APT signals in manually segmented NPC measured. APT values were compared among groups with different histopathological subtypes, clinical stages (namely, T, M, N, and overall stages), EBV-related indices (EBV-DNA), or responses to induction chemotherapy, using Mann–Whitney U test or Kruskal–Wallis H test. Results NPC showed significantly higher APTmean than normal nasopharyngeal tissues (1.81 ± 0.62% vs.1.32 ± 0.56%, P <0.001). APT signals showed no significant difference between undifferentiated and differentiated NPC subtypes groups, different EBV-DNA groups, or among T, N, M stages and overall clinical stages of II, III, IVA and IVB (all P >0.05). Similarly, baseline APT-related parameters did not differ significantly among different treatment response groups after IC, no matter if evaluated with RECIST criteria or sum volumetric regression ratio (SVRR) (all P >0.05). Conclusion NPC showed significantly stronger APT effect than normal nasopharyngeal tissue, facilitating NPC lesion detection and early identification. However, stationary baseline APT values exhibited no significant correlation with histologic subtypes, clinical stages and EBV-related indices, and showed limited value to predict short-term treatment response to IC.
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Affiliation(s)
- Zhou Liu
- Department of Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China.,Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Liyan Zou
- Department of Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China
| | - Qian Yang
- Department of Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China
| | - Long Qian
- MR Research, GE Healthcare, Beijing, China
| | - Tianran Li
- Department of Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China
| | - Honghong Luo
- Department of Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China
| | - Canwen Che
- Department of Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China
| | - Yuanyuan Lei
- Department of Pathology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China
| | - Peng Chen
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China
| | - Chunyan Qiu
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China
| | - Xin Liu
- Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Yin Wu
- Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Dehong Luo
- Department of Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China.,Department of Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
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Molecular Imaging of Brain Tumors and Drug Delivery Using CEST MRI: Promises and Challenges. Pharmaceutics 2022; 14:pharmaceutics14020451. [PMID: 35214183 PMCID: PMC8880023 DOI: 10.3390/pharmaceutics14020451] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2022] [Revised: 02/16/2022] [Accepted: 02/17/2022] [Indexed: 12/10/2022] Open
Abstract
Chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI) detects molecules in their natural forms in a sensitive and non-invasive manner. This makes it a robust approach to assess brain tumors and related molecular alterations using endogenous molecules, such as proteins/peptides, and drugs approved for clinical use. In this review, we will discuss the promises of CEST MRI in the identification of tumors, tumor grading, detecting molecular alterations related to isocitrate dehydrogenase (IDH) and O-6-methylguanine-DNA methyltransferase (MGMT), assessment of treatment effects, and using multiple contrasts of CEST to develop theranostic approaches for cancer treatments. Promising applications include (i) using the CEST contrast of amide protons of proteins/peptides to detect brain tumors, such as glioblastoma multiforme (GBM) and low-grade gliomas; (ii) using multiple CEST contrasts for tumor stratification, and (iii) evaluation of the efficacy of drug delivery without the need of metallic or radioactive labels. These promising applications have raised enthusiasm, however, the use of CEST MRI is not trivial. CEST contrast depends on the pulse sequences, saturation parameters, methods used to analyze the CEST spectrum (i.e., Z-spectrum), and, importantly, how to interpret changes in CEST contrast and related molecular alterations in the brain. Emerging pulse sequence designs and data analysis approaches, including those assisted with deep learning, have enhanced the capability of CEST MRI in detecting molecules in brain tumors. CEST has become a specific marker for tumor grading and has the potential for prognosis and theranostics in brain tumors. With increasing understanding of the technical aspects and associated molecular alterations detected by CEST MRI, this young field is expected to have wide clinical applications in the near future.
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Lingl JP, Wunderlich A, Goerke S, Paech D, Ladd ME, Liebig P, Pala A, Kim SY, Braun M, Schmitz BL, Beer M, Rosskopf J. The Value of APTw CEST MRI in Routine Clinical Assessment of Human Brain Tumor Patients at 3T. Diagnostics (Basel) 2022; 12:diagnostics12020490. [PMID: 35204583 PMCID: PMC8871436 DOI: 10.3390/diagnostics12020490] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2022] [Revised: 02/08/2022] [Accepted: 02/10/2022] [Indexed: 12/10/2022] Open
Abstract
Background. With fast-growing evidence in literature for clinical applications of chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI), this prospective study aimed at applying amide proton transfer-weighted (APTw) CEST imaging in a clinical setting to assess its diagnostic potential in differentiation of intracranial tumors at 3 tesla (T). Methods. Using the asymmetry magnetization transfer ratio (MTRasym) analysis, CEST signals were quantitatively investigated in the tumor areas and in a similar sized region of the normal-appearing white matter (NAWM) on the contralateral hemisphere of 27 patients with intracranial tumors. Area under curve (AUC) analyses were used and results were compared to perfusion-weighted imaging (PWI). Results. Using APTw CEST, contrast-enhancing tumor areas showed significantly higher APTw CEST metrics than contralateral NAWM (AUC = 0.82; p < 0.01). In subgroup analyses of each tumor entity vs. NAWM, statistically significant effects were yielded for glioblastomas (AUC = 0.96; p < 0.01) and for meningiomas (AUC = 1.0; p < 0.01) but not for lymphomas as well as metastases (p > 0.05). PWI showed results comparable to APTw CEST in glioblastoma (p < 0.01). Conclusions. This prospective study confirmed the high diagnostic potential of APTw CEST imaging in a routine clinical setting to differentiate brain tumors.
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Affiliation(s)
- Julia P. Lingl
- Department of Radiology, Ulm University, Albert-Einstein-Allee 23, 89081 Ulm, Germany; (J.P.L.); (A.W.); (S.Y.K.); (M.B.); (B.L.S.); (M.B.)
| | - Arthur Wunderlich
- Department of Radiology, Ulm University, Albert-Einstein-Allee 23, 89081 Ulm, Germany; (J.P.L.); (A.W.); (S.Y.K.); (M.B.); (B.L.S.); (M.B.)
| | - Steffen Goerke
- German Cancer Research Center (DKFZ), Department of Medical Physics in Radiology, Im Neuenheimer Feld 280, 69120 Heidelberg, Germany; (S.G.); (M.E.L.)
| | - Daniel Paech
- German Cancer Research Center (DKFZ), Division of Radiology, Im Neuenheimer Feld 280, 69120 Heidelberg, Germany;
- Department of Neuroradiology, Venusberg-Campus 1, Bonn University, 53127 Bonn, Germany
| | - Mark E. Ladd
- German Cancer Research Center (DKFZ), Department of Medical Physics in Radiology, Im Neuenheimer Feld 280, 69120 Heidelberg, Germany; (S.G.); (M.E.L.)
- Faculty of Medicine, University of Heidelberg, Im Neuenheimer Feld 672, 69120 Heidelberg, Germany
- Faculty of Physics and Astronomy, University of Heidelberg, Im Neuenheimer Feld 226, 69120 Heidelberg, Germany
| | - Patrick Liebig
- Siemens Healthcare GmbH, Henkestraße 127, 91052 Erlangen, Germany;
| | - Andrej Pala
- Department of Neurosurgery, Bezirkskrankenhaus Guenzburg, Lindenallee 2, 89312 Guenzburg, Germany;
| | - Soung Yung Kim
- Department of Radiology, Ulm University, Albert-Einstein-Allee 23, 89081 Ulm, Germany; (J.P.L.); (A.W.); (S.Y.K.); (M.B.); (B.L.S.); (M.B.)
- Section of Neuroradiology, Bezirkskrankenhaus Guenzburg, Lindenallee 2, 89312 Guenzburg, Germany
| | - Michael Braun
- Department of Radiology, Ulm University, Albert-Einstein-Allee 23, 89081 Ulm, Germany; (J.P.L.); (A.W.); (S.Y.K.); (M.B.); (B.L.S.); (M.B.)
- Section of Neuroradiology, Bezirkskrankenhaus Guenzburg, Lindenallee 2, 89312 Guenzburg, Germany
| | - Bernd L. Schmitz
- Department of Radiology, Ulm University, Albert-Einstein-Allee 23, 89081 Ulm, Germany; (J.P.L.); (A.W.); (S.Y.K.); (M.B.); (B.L.S.); (M.B.)
- Section of Neuroradiology, Bezirkskrankenhaus Guenzburg, Lindenallee 2, 89312 Guenzburg, Germany
| | - Meinrad Beer
- Department of Radiology, Ulm University, Albert-Einstein-Allee 23, 89081 Ulm, Germany; (J.P.L.); (A.W.); (S.Y.K.); (M.B.); (B.L.S.); (M.B.)
| | - Johannes Rosskopf
- Department of Radiology, Ulm University, Albert-Einstein-Allee 23, 89081 Ulm, Germany; (J.P.L.); (A.W.); (S.Y.K.); (M.B.); (B.L.S.); (M.B.)
- Section of Neuroradiology, Bezirkskrankenhaus Guenzburg, Lindenallee 2, 89312 Guenzburg, Germany
- Correspondence:
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Ye X, Schreck KC, Ozer BH, Grossman SA. High-grade glioma therapy: adding flexibility in trial design to improve patient outcomes. Expert Rev Anticancer Ther 2022; 22:275-287. [PMID: 35130447 DOI: 10.1080/14737140.2022.2038138] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
INTRODUCTION Outcomes for patients with high grade gliomas have changed little over the past thirty years. This realization prompted renewed efforts to increase flexibility in the design and conduct of clinical brain tumor trials. AREAS COVERED This manuscript reviews the development of clinical trial methods, challenges and considerations of flexible clinical trial designs, approaches to improve identification and testing of active agents for high grade gliomas, and evaluation of their delivery to the central nervous system. EXPERT OPINION Flexibility can be introduced in clinical trials in several ways. Flexible designs tout smaller sample sizes, adaptive modifications, fewer control arms, and inclusion of multiple arms in one study. Unfortunately, modifications in study designs cannot address two challenges that are largely responsible for the lack of progress in treating high grade gliomas: 1) the identification of active pharmaceutical agents and 2) the delivery of these agents to brain tumor tissue in therapeutic concentrations. To improve the outcomes of patients with high grade gliomas efforts must be focused on the pre-clinical screening of drugs for activity, the ability of these agents to achieve therapeutic concentrations in non-enhancing tumors, and a willingness to introduce novel compounds in minimally pre-treated patient populations.
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Affiliation(s)
- Xiaobu Ye
- The Johns Hopkins University School of Medicine and Sidney Kimmel Comprehensive Cancer Center, Baltimore MD, USA
| | - Karisa C Schreck
- The Johns Hopkins University School of Medicine and Sidney Kimmel Comprehensive Cancer Center, Baltimore MD, USA
| | - Byram H Ozer
- The Johns Hopkins University School of Medicine and Sidney Kimmel Comprehensive Cancer Center, Baltimore MD, USA
| | - Stuart A Grossman
- The Johns Hopkins University School of Medicine and Sidney Kimmel Comprehensive Cancer Center, Baltimore MD, USA
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Mancini L, Casagranda S, Gautier G, Peter P, Lopez B, Thorne L, McEvoy A, Miserocchi A, Samandouras G, Kitchen N, Brandner S, De Vita E, Torrealdea F, Rega M, Schmitt B, Liebig P, Sanverdi E, Golay X, Bisdas S. CEST MRI provides amide/amine surrogate biomarkers for treatment-naïve glioma sub-typing. Eur J Nucl Med Mol Imaging 2022; 49:2377-2391. [PMID: 35029738 PMCID: PMC9165287 DOI: 10.1007/s00259-022-05676-1] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2021] [Accepted: 12/31/2021] [Indexed: 11/24/2022]
Abstract
PURPOSE Accurate glioma classification affects patient management and is challenging on non- or low-enhancing gliomas. This study investigated the clinical value of different chemical exchange saturation transfer (CEST) metrics for glioma classification and assessed the diagnostic effect of the presence of abundant fluid in glioma subpopulations. METHODS Forty-five treatment-naïve glioma patients with known isocitrate dehydrogenase (IDH) mutation and 1p/19q codeletion status received CEST MRI (B1rms = 2μT, Tsat = 3.5 s) at 3 T. Magnetization transfer ratio asymmetry and CEST metrics (amides: offset range 3-4 ppm, amines: 1.5-2.5 ppm, amide/amine ratio) were calculated with two models: 'asymmetry-based' (AB) and 'fluid-suppressed' (FS). The presence of T2/FLAIR mismatch was noted. RESULTS IDH-wild type had higher amide/amine ratio than IDH-mutant_1p/19qcodel (p < 0.022). Amide/amine ratio and amine levels differentiated IDH-wild type from IDH-mutant (p < 0.0045) and from IDH-mutant_1p/19qret (p < 0.021). IDH-mutant_1p/19qret had higher amides and amines than IDH-mutant_1p/19qcodel (p < 0.035). IDH-mutant_1p/19qret with AB/FS mismatch had higher amines than IDH-mutant_1p/19qret without AB/FS mismatch ( < 0.016). In IDH-mutant_1p/19qret, the presence of AB/FS mismatch was closely related to the presence of T2/FLAIR mismatch (p = 0.014). CONCLUSIONS CEST-derived biomarkers for amides, amines, and their ratio can help with histomolecular staging in gliomas without intense contrast enhancement. T2/FLAIR mismatch is reflected in the presence of AB/FS CEST mismatch. The AB/FS CEST mismatch identifies glioma subgroups that may have prognostic and clinical relevance.
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Affiliation(s)
- Laura Mancini
- Box65, Lysholm Department of Neuroradiology, The National Hospital for Neurology & Neurosurgery, University College London Hospitals NHS Foundation Trust, 8-11 Queen Square, London, WC1N 3BG, UK.
- Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, London, UK.
| | | | | | | | | | - Lewis Thorne
- Department of Neurosurgery, The National Hospital for Neurology & Neurosurgery, University College London Hospitals NHS Foundation Trust, London, UK
| | - Andrew McEvoy
- Department of Neurosurgery, The National Hospital for Neurology & Neurosurgery, University College London Hospitals NHS Foundation Trust, London, UK
| | - Anna Miserocchi
- Department of Neurosurgery, The National Hospital for Neurology & Neurosurgery, University College London Hospitals NHS Foundation Trust, London, UK
| | - George Samandouras
- Department of Neurosurgery, The National Hospital for Neurology & Neurosurgery, University College London Hospitals NHS Foundation Trust, London, UK
| | - Neil Kitchen
- Department of Neurosurgery, The National Hospital for Neurology & Neurosurgery, University College London Hospitals NHS Foundation Trust, London, UK
| | - Sebastian Brandner
- Division of Neuropathology, UCL Queen Square Institute of Neurology, London, UK
- The National Hospital for Neurology and Neurosurgery, University College London Hospitals NHS Foundation Trust, London, UK
| | - Enrico De Vita
- Box65, Lysholm Department of Neuroradiology, The National Hospital for Neurology & Neurosurgery, University College London Hospitals NHS Foundation Trust, 8-11 Queen Square, London, WC1N 3BG, UK
- Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, London, UK
| | - Francisco Torrealdea
- University College Hospital, University College of London Hospitals NHS Foundation Trust, London, UK
| | - Marilena Rega
- University College Hospital, University College of London Hospitals NHS Foundation Trust, London, UK
| | | | | | - Eser Sanverdi
- Box65, Lysholm Department of Neuroradiology, The National Hospital for Neurology & Neurosurgery, University College London Hospitals NHS Foundation Trust, 8-11 Queen Square, London, WC1N 3BG, UK
- Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, London, UK
| | - Xavier Golay
- Box65, Lysholm Department of Neuroradiology, The National Hospital for Neurology & Neurosurgery, University College London Hospitals NHS Foundation Trust, 8-11 Queen Square, London, WC1N 3BG, UK
- Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, London, UK
| | - Sotirios Bisdas
- Box65, Lysholm Department of Neuroradiology, The National Hospital for Neurology & Neurosurgery, University College London Hospitals NHS Foundation Trust, 8-11 Queen Square, London, WC1N 3BG, UK
- Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, London, UK
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Guo P, Unberath M, Heo HY, Eberhart CG, Lim M, Blakeley JO, Jiang S. Learning-based analysis of amide proton transfer-weighted MRI to identify true progression in glioma patients. NEUROIMAGE: CLINICAL 2022; 35:103121. [PMID: 35905666 PMCID: PMC9421489 DOI: 10.1016/j.nicl.2022.103121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Revised: 07/13/2022] [Accepted: 07/14/2022] [Indexed: 11/29/2022] Open
Affiliation(s)
- Pengfei Guo
- Department of Radiology, Johns Hopkins University, Baltimore, MD, USA; Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
| | - Mathias Unberath
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
| | - Hye-Young Heo
- Department of Radiology, Johns Hopkins University, Baltimore, MD, USA
| | | | - Michael Lim
- Department of Neurosurgery, Johns Hopkins University, Baltimore, MD, USA
| | | | - Shanshan Jiang
- Department of Radiology, Johns Hopkins University, Baltimore, MD, USA.
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Li Y, Ma Y, Wu Z, Xie R, Zeng F, Cai H, Lui S, Song B, Chen L, Wu M. Advanced Imaging Techniques for Differentiating Pseudoprogression and Tumor Recurrence After Immunotherapy for Glioblastoma. Front Immunol 2021; 12:790674. [PMID: 34899760 PMCID: PMC8656432 DOI: 10.3389/fimmu.2021.790674] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2021] [Accepted: 11/08/2021] [Indexed: 02/05/2023] Open
Abstract
Glioblastoma (GBM) is the most common malignant tumor of the central nervous system with poor prognosis. Although the field of immunotherapy in glioma is developing rapidly, glioblastoma is still prone to recurrence under strong immune intervention. The major challenges in the process of immunotherapy are evaluating the curative effect, accurately distinguishing between treatment-related reactions and tumor recurrence, and providing guidance for clinical decision-making. Since the conventional magnetic resonance imaging (MRI) is usually difficult to distinguish between pseudoprogression and the true tumor progression, many studies have used various advanced imaging techniques to evaluate treatment-related responses. Meanwhile, criteria for efficacy evaluation of immunotherapy are constantly updated and improved. A standard imaging scheme to evaluate immunotherapeutic response will benefit patients finally. This review mainly summarizes the application status and future trend of several advanced imaging techniques in evaluating the efficacy of GBM immunotherapy.
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Affiliation(s)
- Yan Li
- Huaxi MR Research Center (HMRRC), Department of Radiology, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China
| | - Yiqi Ma
- Huaxi MR Research Center (HMRRC), Department of Radiology, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China
| | - Zijun Wu
- Huaxi MR Research Center (HMRRC), Department of Radiology, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China
| | - Ruoxi Xie
- Huaxi MR Research Center (HMRRC), Department of Radiology, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China
| | - Fanxin Zeng
- Department of Clinic Medical Center, Dazhou Central Hospital, Dazhou, China
| | - Huawei Cai
- Laboratory of Clinical Nuclear Medicine, Department of Nuclear Medicine, West China Hospital, Sichuan University, Chengdu, China
| | - Su Lui
- Huaxi MR Research Center (HMRRC), Department of Radiology, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China
| | - Bin Song
- Huaxi MR Research Center (HMRRC), Department of Radiology, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China
| | - Lei Chen
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, China.,Department of Clinical Research Management, West China Hospital, Sichuan University, Chengdu, China
| | - Min Wu
- Huaxi MR Research Center (HMRRC), Department of Radiology, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China.,Department of Clinic Medical Center, Dazhou Central Hospital, Dazhou, China
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Gonçalves FG, Viaene AN, Vossough A. Advanced Magnetic Resonance Imaging in Pediatric Glioblastomas. Front Neurol 2021; 12:733323. [PMID: 34858308 PMCID: PMC8631300 DOI: 10.3389/fneur.2021.733323] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Accepted: 10/12/2021] [Indexed: 12/26/2022] Open
Abstract
The shortly upcoming 5th edition of the World Health Organization Classification of Tumors of the Central Nervous System is bringing extensive changes in the terminology of diffuse high-grade gliomas (DHGGs). Previously "glioblastoma," as a descriptive entity, could have been applied to classify some tumors from the family of pediatric or adult DHGGs. However, now the term "glioblastoma" has been divested and is no longer applied to tumors in the family of pediatric types of DHGGs. As an entity, glioblastoma remains, however, in the family of adult types of diffuse gliomas under the insignia of "glioblastoma, IDH-wildtype." Of note, glioblastomas still can be detected in children when glioblastoma, IDH-wildtype is found in this population, despite being much more common in adults. Despite the separation from the family of pediatric types of DHGGs, what was previously labeled as "pediatric glioblastomas" still remains with novel labels and as new entities. As a result of advances in molecular biology, most of the previously called "pediatric glioblastomas" are now classified in one of the four family members of pediatric types of DHGGs. In this review, the term glioblastoma is still apocryphally employed mainly due to its historical relevance and the paucity of recent literature dealing with the recently described new entities. Therefore, "glioblastoma" is used here as an umbrella term in the attempt to encompass multiple entities such as astrocytoma, IDH-mutant (grade 4); glioblastoma, IDH-wildtype; diffuse hemispheric glioma, H3 G34-mutant; diffuse pediatric-type high-grade glioma, H3-wildtype and IDH-wildtype; and high grade infant-type hemispheric glioma. Glioblastomas are highly aggressive neoplasms. They may arise anywhere in the developing central nervous system, including the spinal cord. Signs and symptoms are non-specific, typically of short duration, and usually derived from increased intracranial pressure or seizure. Localized symptoms may also occur. The standard of care of "pediatric glioblastomas" is not well-established, typically composed of surgery with maximal safe tumor resection. Subsequent chemoradiation is recommended if the patient is older than 3 years. If younger than 3 years, surgery is followed by chemotherapy. In general, "pediatric glioblastomas" also have a poor prognosis despite surgery and adjuvant therapy. Magnetic resonance imaging (MRI) is the imaging modality of choice for the evaluation of glioblastomas. In addition to the typical conventional MRI features, i.e., highly heterogeneous invasive masses with indistinct borders, mass effect on surrounding structures, and a variable degree of enhancement, the lesions may show restricted diffusion in the solid components, hemorrhage, and increased perfusion, reflecting increased vascularity and angiogenesis. In addition, magnetic resonance spectroscopy has proven helpful in pre- and postsurgical evaluation. Lastly, we will refer to new MRI techniques, which have already been applied in evaluating adult glioblastomas, with promising results, yet not widely utilized in children.
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Affiliation(s)
- Fabrício Guimarães Gonçalves
- Division of Neuroradiology, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, United States
| | - Angela N Viaene
- Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, United States.,Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Arastoo Vossough
- Division of Neuroradiology, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, United States.,Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
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Du X, He Q, Zhang B, Li N, Zeng X, Li W. Diagnostic accuracy of diffusion-weighted imaging in differentiating glioma recurrence from posttreatment-related changes: a meta-analysis. Expert Rev Anticancer Ther 2021; 22:123-130. [PMID: 34727815 DOI: 10.1080/14737140.2022.2000396] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
BACKGROUND Magnetic resonance imaging (MRI) is the most commonly used imaging method to evaluate glioma recurrence. However, conventional MRI has difficulty distinguishing glioma accurately. This study aimed to explore the value of diffusion weighted imaging (DWI) in evaluating glioma recurrence and post-treatment-related changes. RESEARCH DESIGN AND METHODS PubMed, Cochrane Library, Embase, Web of Science, China National Knowledge Infrastructure (CNKI), Wanfang Database and China Science and Technology Journal Database were extensively searched in accordance with inclusion criteria and exclusion criteria to obtain appropriate included studies. The quality of the included studies was evaluated using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool. Combined sensitivity and specificity and the area under the summary receiver operating characteristic curve (SROC) with the 95% confidence interval (CI) were calculated. RESULTS Seventeen high-quality studies were included. The combined sensitivity was 0.82 (95% CI: 0.76-0.87), the specificity was 0.83 (95% CI: 0.76-0.89), the positive likelihood ratio was 4.9 (95% CI: 3.2-7.5), the negative likelihood ratio was 0.21 (95% CI: 0.15-0.30), the diagnostic odds ratio was 23 (95%: CI 11-48), and the area under the SROC was 0.90 (95% CI: 0.87-0.92). CONCLUSIONS This meta-analysis suggests that DWI has high sensitivity, specificity and accuracy in differentiating glioma recurrence.
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Affiliation(s)
- Xiaoli Du
- Department of Radiology, Chengdu First People's Hospital, Chengdu, China
| | - Qian He
- Department of Radiology, Chengdu First People's Hospital, Chengdu, China
| | - Boli Zhang
- Department of Radiology, Chengdu First People's Hospital, Chengdu, China
| | - Na Li
- Department of Radiology, Chengdu First People's Hospital, Chengdu, China
| | - Xuewen Zeng
- Department of Radiology, Chengdu First People's Hospital, Chengdu, China
| | - Wenbo Li
- Department of Radiology, Chengdu First People's Hospital, Chengdu, China
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Zhang H, Zhou J, Peng Y. Amide Proton Transfer-Weighted MR Imaging of Pediatric Central Nervous System Diseases. Magn Reson Imaging Clin N Am 2021; 29:631-641. [PMID: 34717850 DOI: 10.1016/j.mric.2021.06.012] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
Amide proton transfer-weighted (APTw) imaging is a molecular MR imaging technique that can detect the concentration of the amide protons in mobile cellular proteins and peptides or a pH change in vivo. Previous studies have indicated that APTw MR imaging can be used to detect malignant brain tumors, stroke, and other neurologic diseases, although the clinical application in pediatric patients remains limited. The authors briefly introduce the basic principles of APTw imaging. Then, they review early clinical applications of this approach to pediatric central nervous system diseases, including pediatric brain development, hypoxic-ischemic encephalopathy, intracranial infection, and brain tumors.
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Affiliation(s)
- Hong Zhang
- Department of Radiology, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, 56 Nan Li Shi Road, Xi Cheng District, Beijing, 100045, China
| | - Jinyuan Zhou
- Division of MR Research, Department of Radiology, Johns Hopkins University School of Medicine, 600 N. Wolfe Street, Park 336, Baltimore, MD 21287, USA
| | - Yun Peng
- Department of Radiology, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, 56 Nan Li Shi Road, Xi Cheng District, Beijing, 100045, China.
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Abstract
PURPOSE OF REVIEW This review aims to cover current MRI techniques for assessing treatment response in brain tumors, with a focus on radio-induced lesions. RECENT FINDINGS Pseudoprogression and radionecrosis are common radiological entities after brain tumor irradiation and are difficult to distinguish from real progression, with major consequences on daily patient care. To date, shortcomings of conventional MRI have been largely recognized but morphological sequences are still used in official response assessment criteria. Several complementary advanced techniques have been proposed but none of them have been validated, hampering their clinical use. Among advanced MRI, brain perfusion measures increase diagnostic accuracy, especially when added with spectroscopy and susceptibility-weighted imaging. However, lack of reproducibility, because of several hard-to-control variables, is still a major limitation for their standardization in routine protocols. Amide Proton Transfer is an emerging molecular imaging technique that promises to offer new metrics by indirectly quantifying intracellular mobile proteins and peptide concentration. Preliminary studies suggest that this noncontrast sequence may add key biomarkers in tumor evaluation, especially in posttherapeutic settings. SUMMARY Benefits and pitfalls of conventional and advanced imaging on posttreatment assessment are discussed and the potential added value of APT in this clinicoradiological evolving scenario is introduced.
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Affiliation(s)
- Lucia Nichelli
- Department of Neuroradiology, Sorbonne Université, Assistance Publique-Hôpitaux de Paris, Groupe Hospitalier Pitié-Salpêtrière-Charles Foix
- Sorbonne Université, INSERM, CNRS, Assistance Publique-Hôpitaux de Paris, Institut du Cerveau et de la Moelle épinière, boulevard de l’Hôpital, Paris
| | - Stefano Casagranda
- Department of Research & Innovation, Olea Medical, avenue des Sorbiers, La Ciotat, France
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Guo P, Wang P, Yasarla R, Zhou J, Patel VM, Jiang S. Anatomic and Molecular MR Image Synthesis Using Confidence Guided CNNs. IEEE TRANSACTIONS ON MEDICAL IMAGING 2021; 40:2832-2844. [PMID: 33351754 PMCID: PMC8543492 DOI: 10.1109/tmi.2020.3046460] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Data-driven automatic approaches have demonstrated their great potential in resolving various clinical diagnostic dilemmas in neuro-oncology, especially with the help of standard anatomic and advanced molecular MR images. However, data quantity and quality remain a key determinant, and a significant limit of the potential applications. In our previous work, we explored the synthesis of anatomic and molecular MR image networks (SAMR) in patients with post-treatment malignant gliomas. In this work, we extend this through a confidence-guided SAMR (CG-SAMR) that synthesizes data from lesion contour information to multi-modal MR images, including T1-weighted ( [Formula: see text]), gadolinium enhanced [Formula: see text] (Gd- [Formula: see text]), T2-weighted ( [Formula: see text]), and fluid-attenuated inversion recovery ( FLAIR ), as well as the molecular amide proton transfer-weighted ( [Formula: see text]) sequence. We introduce a module that guides the synthesis based on a confidence measure of the intermediate results. Furthermore, we extend the proposed architecture to allow training using unpaired data. Extensive experiments on real clinical data demonstrate that the proposed model can perform better than current the state-of-the-art synthesis methods. Our code is available at https://github.com/guopengf/CG-SAMR.
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Hampton DG, Goldman-Yassen AE, Sun PZ, Hu R. Metabolic Magnetic Resonance Imaging in Neuroimaging: Magnetic Resonance Spectroscopy, Sodium Magnetic Resonance Imaging and Chemical Exchange Saturation Transfer. Semin Ultrasound CT MR 2021; 42:452-462. [PMID: 34537114 DOI: 10.1053/j.sult.2021.07.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Magnetic resonance (MR) is a powerful and versatile technique that offers much more beyond conventional anatomic imaging and has the potential of probing in vivo metabolism. Although MR spectroscopy (MRS) predates clinical MR imaging (MRI), its clinical application has been limited by technical and practical challenges. Other MR techniques actively being developed for in vivo metabolic imaging include sodium concentration imaging and chemical exchange saturation transfer. This article will review some of the practical aspects of MRS in neuroimaging, introduce sodium MRI and chemical exchange saturation transfer MRI, and highlight some of their emerging clinical applications.
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Affiliation(s)
- Daniel G Hampton
- Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA.
| | - Adam E Goldman-Yassen
- Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA
| | - Phillip Zhe Sun
- Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA; Yerkes Imaging Center, Yerkes National Primate Research Center, Emory University, Atlanta, GA
| | - Ranliang Hu
- Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA
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Wen Q, Wang K, Hsu YC, Xu Y, Sun Y, Wu D, Zhang Y. Chemical exchange saturation transfer imaging for epilepsy secondary to tuberous sclerosis complex at 3 T: Optimization and analysis. NMR IN BIOMEDICINE 2021; 34:e4563. [PMID: 34046976 DOI: 10.1002/nbm.4563] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/14/2020] [Revised: 03/16/2021] [Accepted: 05/01/2021] [Indexed: 06/12/2023]
Abstract
The homeostasis of various metabolites is impaired in epilepsy secondary to the tuberous sclerosis complex (TSC). Chemical exchange saturation transfer (CEST) imaging is an emerging molecular MRI technique that can detect various metabolites and proteins in vivo. However, the role of CEST imaging for TSC-associated epilepsy has not been assessed. Here, we aim to investigate the feasibility of applying CEST imaging to TSC-associated epilepsy, optimize the CEST acquisition parameters, and provide an analysis method for exploring the dominant molecular contributors to the CEST signal measured. Nine TSC epilepsy patients were scanned on a 3-T MRI system. The CEST saturation frequencies were swept from -6 to 6 ppm with 12 different combinations of saturation power (4, 3, 2 and 1 μT) and duration (1000, 700 and 400 ms). Furthermore, a two-stage simulation method based on the seven-pool Bloch-McConnell model was proposed to assess the contribution of each exchangeable pool to the CEST signal in normal-appearing white matter and cortical tubers, which avoided the complexity and uncertainty of full Bloch-McConnell fitting. The results showed that under the optimal saturation duration of 1000 ms, the greatest contrast between tubers and normal tissues occurred around 3, 2.5, 1.75 and 3.5 ppm for B1 of 4, 3, 2 and 1 μT, respectively. At the optimal frequency offsets, the CEST values of tubers were significantly higher than those in the normal brain tissues (P < 0.01). Furthermore, the two-stage analysis suggested that the amine pool played a dominant role in yielding the contrast between cortical tubers and normal tissues. These results indicate that CEST MRI may serve as a potentially useful tool for identifying tubers in TSC, and the two-stage analysis method may provide a route for investigating the molecular contributions to the CEST contrast in biological tissues.
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Affiliation(s)
- Qingqing Wen
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China
| | - Kang Wang
- Department of Neurology, First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
| | - Yi-Cheng Hsu
- MR Collaboration, Siemens Healthcare Ltd., Shanghai, China
| | - Yan Xu
- Department of Neurosurgery, Zhejiang Provincial People's Hospital, Hangzhou, Zhejiang, China
| | - Yi Sun
- MR Collaboration, Siemens Healthcare Ltd., Shanghai, China
| | - Dan Wu
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China
- Department of Neurology, First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
| | - Yi Zhang
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China
- Department of Neurology, First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
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