1
|
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.
Collapse
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
| |
Collapse
|
2
|
Cronin AE, Liebig P, Detombe SA, Duggal N, Bartha R. Reproducibility of 3D pH-weighted chemical exchange saturation transfer contrast in the healthy cervical spinal cord. NMR IN BIOMEDICINE 2024; 37:e5103. [PMID: 38243648 DOI: 10.1002/nbm.5103] [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: 08/07/2023] [Revised: 12/01/2023] [Accepted: 12/20/2023] [Indexed: 01/21/2024]
Abstract
Spinal cord ischemia and hypoxia can be caused by compression, injury, and vascular alterations. Measuring ischemia and hypoxia directly in the spinal cord noninvasively remains challenging. Ischemia and hypoxia alter tissue pH, providing a physiologic parameter that may be more directly related to tissue viability. Chemical exchange saturation transfer (CEST) is an MRI contrast mechanism that can be made sensitive to pH. More specifically, amine/amide concentration independent detection (AACID) is a recently developed endogenous CEST contrast that has demonstrated sensitivity to intracellular pH at 9.4 T. The goal of this study was to evaluate the reproducibility of AACID CEST measurements at different levels of the healthy cervical spinal cord at 3.0 T incorporating B1 correction. Using a 3.0 T MRI scanner, two 3D CEST scans (saturation pulse train followed by a 3D snapshot gradient-echo readout) were performed on 12 healthy subjects approximately 10 days apart, with the CEST volume centered at the C4 level for all subjects. Scan-rescan reproducibility was evaluated by examining between and within-subject coefficients of variation (CVs) and absolute AACID value differences. The C4 level of the spinal cord demonstrated the lowest within-subject CVs (4.1%-4.3%), between-subject CVs (5.6%-6.3%), and absolute AACID percent difference (5.8-6.1%). The B1 correction scheme significantly improved reproducibility (adjusted p-value = 0.002) compared with the noncorrected data, suggesting that implementing B1 corrections in the spinal cord is beneficial. It was concluded that pH-weighted AACID measurements, incorporating B1-inhomogeneity correction, were reproducible within subjects along the healthy cervical spinal cord and that optimal image quality was achieved at the center of the 3D CEST volume.
Collapse
Affiliation(s)
- Alicia E Cronin
- Department of Medical Biophysics, Schulich School of Medicine & Dentistry, Western University, London, Ontario, Canada
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, Schulich School of Medicine & Dentistry, Western University, London, Ontario, Canada
| | | | - Sarah A Detombe
- Department of Clinical Neurological Sciences, London Health Sciences Centre, London, Ontario, Canada
| | - Neil Duggal
- Department of Medical Biophysics, Schulich School of Medicine & Dentistry, Western University, London, Ontario, Canada
- Department of Clinical Neurological Sciences, London Health Sciences Centre, London, Ontario, Canada
| | - Robert Bartha
- Department of Medical Biophysics, Schulich School of Medicine & Dentistry, Western University, London, Ontario, Canada
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, Schulich School of Medicine & Dentistry, Western University, London, Ontario, Canada
| |
Collapse
|
3
|
Ohno Y, Yui M, Yamamoto K, Takenaka D, Koyama H, Nagata H, Ueda T, Ikeda H, Ozawa Y, Toyama H, Yoshikawa T. Chemical Exchange Saturation Transfer MRI: Capability for Predicting Therapeutic Effect of Chemoradiotherapy on Non-Small Cell Lung Cancer Patients. J Magn Reson Imaging 2023; 58:174-186. [PMID: 36971493 DOI: 10.1002/jmri.28691] [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: 01/26/2023] [Revised: 03/02/2023] [Accepted: 03/03/2023] [Indexed: 03/29/2023] Open
Abstract
BACKGROUND Amide proton transfer (APT) weighted chemical exchange saturation transfer CEST (APTw/CEST) magnetic resonance imaging (MRI) has been suggested as having the potential for assessing the therapeutic effect of brain tumors or rectal cancer. Moreover, diffusion-weighted imaging (DWI) and positron emission tomography fused with computed tomography by means of 2-[fluorine-18]-fluoro-2-deoxy-D-glucose (FDG-PET/CT) have been suggested as useful in same setting. PURPOSE To compare the capability of APTw/CEST imaging, DWI, and FDG-PET/CT for predicting therapeutic effect of chemoradiotherapy (CRT) on stage III non-small cell lung cancer (NSCLC) patients. STUDY TYPE Prospective. POPULATION Eighty-four consecutive patients with Stage III NSCLC, 45 men (age range, 62-75 years; mean age, 71 years) and 39 women (age range, 57-75 years; mean age, 70 years). All patients were then divided into two groups (Response Evaluation Criteria in Solid Tumors [RECIST] responders, consisting of the complete response and partial response groups, and RECIST non-responders, consisting of the stable disease and progressive disease groups). FIELD STRENGTH/SEQUENCE 3 T, echo planar imaging or fast advanced spin-echo (FASE) sequences for DWI and 2D half Fourier FASE sequences with magnetization transfer pulses for CEST imaging. ASSESSMENT Magnetization transfer ratio asymmetry (MTRasym ) at 3.5 ppm, apparent diffusion coefficient (ADC), and maximum standard uptake value (SUVmax, ) on PET/CT were assessed by means of region of interest (ROI) measurements at primary tumor. STATISTICAL TESTS Kaplan-Meier method followed by log-rank test and Cox proportional hazards regression analysis with multivariate analysis. A P value <0.05 was considered statistically significant. RESULTS Progression-free survival (PFS) and overall survival (OS) had significant difference between two groups. MTRasym at 3.5 ppm (hazard ratio [HR] = 0.70) and SUVmax (HR = 1.41) were identified as significant predictors for PFS. Tumor staging (HR = 0.57) was also significant predictors for OS. DATA CONCLUSION APTw/CEST imaging showed potential performance as DWI and FDG-PET/CT for predicting the therapeutic effect of CRT on stage III NSCLC patients. LEVEL OF EVIDENCE 2 TECHNICAL EFFICACY: Stage 1.
Collapse
Affiliation(s)
- Yoshiharu Ohno
- Department of Radiology, Fujita Health University School of Medicine, Toyoake, Japan
- Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Medicine, Toyoake, Japan
- Division of Functional and Diagnostic Imaging Research, Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Japan
| | - Masao Yui
- Canon Medical Systems Corporation, Otawara, Japan
| | | | - Daisuke Takenaka
- Department of Radiology, Fujita Health University School of Medicine, Toyoake, Japan
- Department of Diagnostic Radiology, Hyogo Cancer Center, Akashi, Japan
| | - Hisanobu Koyama
- Department of Radiology, Osaka Police Hospital, Osaka, Japan
- Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Japan
| | - Hiroyuki Nagata
- Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Medicine, Toyoake, Japan
| | - Takahiro Ueda
- Department of Radiology, Fujita Health University School of Medicine, Toyoake, Japan
| | - Hirotaka Ikeda
- Department of Radiology, Fujita Health University School of Medicine, Toyoake, Japan
| | - Yoshiyuki Ozawa
- Department of Radiology, Fujita Health University School of Medicine, Toyoake, Japan
- Department of Radiology, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan
| | - Hiroshi Toyama
- Department of Radiology, Fujita Health University School of Medicine, Toyoake, Japan
| | - Takeshi Yoshikawa
- Department of Radiology, Fujita Health University School of Medicine, Toyoake, Japan
- Division of Functional and Diagnostic Imaging Research, Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Japan
- Department of Diagnostic Radiology, Hyogo Cancer Center, Akashi, Japan
| |
Collapse
|
4
|
Jabehdar Maralani P, Chan RW, Lam WW, Oakden W, Oglesby R, Lau A, Mehrabian H, Heyn C, Chan AK, Soliman H, Sahgal A, Stanisz GJ. Chemical Exchange Saturation Transfer MRI: What Neuro-Oncology Clinicians Need To Know. Technol Cancer Res Treat 2023; 22:15330338231208613. [PMID: 37872686 PMCID: PMC10594966 DOI: 10.1177/15330338231208613] [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: 07/11/2023] [Revised: 09/19/2023] [Accepted: 09/28/2023] [Indexed: 10/25/2023] Open
Abstract
Chemical exchange saturation transfer (CEST) is a relatively novel magnetic resonance imaging (MRI) technique with an image contrast designed for in vivo measurement of certain endogenous molecules with protons that are exchangeable with water protons, such as amide proton transfer commonly used for neuro-oncology applications. Recent technological advances have made it feasible to implement CEST on clinical grade scanners within practical acquisition times, creating new opportunities to integrate CEST in clinical workflow. In addition, the majority of CEST applications used in neuro-oncology are performed without the use gadolinium-based contrast agents which are another appealing feature of this technique. This review is written for clinicians involved in neuro-oncologic care (nonphysicists) as the target audience explaining what they need to know as CEST makes its way into practice. The purpose of this article is to (1) review the basic physics and technical principles of CEST MRI, and (2) review the practical applications of CEST in neuro-oncology.
Collapse
Affiliation(s)
- Pejman Jabehdar Maralani
- Department of Medical Imaging, University of Toronto, Toronto, ON, Canada
- Physical Sciences, Sunnybrook Research Institute, Toronto, ON, Canada
| | - Rachel W. Chan
- Physical Sciences, Sunnybrook Research Institute, Toronto, ON, Canada
| | - Wilfred W. Lam
- Physical Sciences, Sunnybrook Research Institute, Toronto, ON, Canada
| | - Wendy Oakden
- Physical Sciences, Sunnybrook Research Institute, Toronto, ON, Canada
| | - Ryan Oglesby
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Angus Lau
- Physical Sciences, Sunnybrook Research Institute, Toronto, ON, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Hatef Mehrabian
- Physical Sciences, Sunnybrook Research Institute, Toronto, ON, Canada
| | - Chris Heyn
- Department of Medical Imaging, University of Toronto, Toronto, ON, Canada
| | - Aimee K.M. Chan
- Physical Sciences, Sunnybrook Research Institute, Toronto, ON, Canada
| | - Hany Soliman
- Department of Radiation Oncology, University of Toronto, Toronto, ON, Canada
| | - Arjun Sahgal
- Department of Radiation Oncology, University of Toronto, Toronto, ON, Canada
| | - Greg J. Stanisz
- Physical Sciences, Sunnybrook Research Institute, Toronto, ON, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
| |
Collapse
|
5
|
Tseng CL, Chen H, Stewart J, Lau AZ, Chan RW, Lawrence LSP, Myrehaug S, Soliman H, Detsky J, Lim-Fat MJ, Lipsman N, Das S, Heyn C, Maralani PJ, Binda S, Perry J, Keller B, Stanisz GJ, Ruschin M, Sahgal A. High grade glioma radiation therapy on a high field 1.5 Tesla MR-Linac - workflow and initial experience with daily adapt-to-position (ATP) MR guidance: A first report. Front Oncol 2022; 12:1060098. [PMID: 36518316 PMCID: PMC9742425 DOI: 10.3389/fonc.2022.1060098] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2022] [Accepted: 11/10/2022] [Indexed: 07/30/2023] Open
Abstract
PURPOSE This study reports the workflow and initial clinical experience of high grade glioma (HGG) radiotherapy on the 1.5 T MR-Linac (MRL), with a focus on the temporal variations of the tumor and feasibility of multi-parametric image (mpMRI) acquisition during routine treatment workflow. MATERIALS AND METHODS Ten HGG patients treated with radiation within the first year of the MRL's clinical operation, between October 2019 and August 2020, were identified from a prospective database. Workflow timings were recorded and online adaptive plans were generated using the Adapt-To-Position (ATP) workflow. Temporal variation within the FLAIR hyperintense region (FHR) was assessed by the relative FHR volumes (n = 281 contours) and migration distances (maximum linear displacement of the volume). Research mpMRIs were acquired on the MRL during radiation and changes in selected functional parameters were investigated within the FHR. RESULTS All patients completed radiotherapy to a median dose of 60 Gy (range, 54-60 Gy) in 30 fractions (range, 30-33), receiving a total of 287 fractions on the MRL. The mean in-room time per fraction with or without post-beam research imaging was 42.9 minutes (range, 25.0-69.0 minutes) and 37.3 minutes (range, 24.0-51.0 minutes), respectively. Three patients (30%) required re-planning between fractions 9 to 12 due to progression of tumor and/or edema identified on daily MRL imaging. At the 10, 20, and 30-day post-first fraction time points 3, 3, and 4 patients, respectively, had a FHR volume that changed by at least 20% relative to the first fraction. Research mpMRIs were successfully acquired on the MRL. The median apparent diffusion coefficient (ADC) within the FHR and the volumes of FLAIR were significantly correlated when data from all patients and time points were pooled (R=0.68, p<.001). CONCLUSION We report the first clinical series of HGG patients treated with radiotherapy on the MRL. The ATP workflow and treatment times were clinically acceptable, and daily online MRL imaging triggered adaptive re-planning for selected patients. Acquisition of mpMRIs was feasible on the MRL during routine treatment workflow. Prospective clinical outcomes data is anticipated from the ongoing UNITED phase 2 trial to further refine the role of MR-guided adaptive radiotherapy.
Collapse
Affiliation(s)
- Chia-Lin Tseng
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
| | - Hanbo Chen
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
| | - James Stewart
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
| | - Angus Z. Lau
- Physical Sciences Platform, Sunnybrook Research Institute, Toronto, ON, Canada
- Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Rachel W. Chan
- Physical Sciences Platform, Sunnybrook Research Institute, Toronto, ON, Canada
| | | | - Sten Myrehaug
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
| | - Hany Soliman
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
| | - Jay Detsky
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
| | - Mary Jane Lim-Fat
- Department of Medicine, Division of Neurology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
| | - Nir Lipsman
- Division of Neurosurgery, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
| | - Sunit Das
- Division of Neurosurgery, St. Michael’s Hospital, University of Toronto, Toronto, ON, Canada
| | - Chinthaka Heyn
- Department of Medical Imaging, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
| | - Pejman J. Maralani
- Department of Medical Imaging, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
| | - Shawn Binda
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
| | - James Perry
- Department of Medicine, Division of Neurology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
| | - Brian Keller
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
| | - Greg J. Stanisz
- Physical Sciences Platform, Sunnybrook Research Institute, Toronto, ON, Canada
- Medical Biophysics, University of Toronto, Toronto, ON, Canada
- Department of Neurosurgery and Paediatric Neurosurgery, Medical University, Lublin, Poland
| | - Mark Ruschin
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
| | - Arjun Sahgal
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
| |
Collapse
|
6
|
Jalalifar SA, Soliman H, Sahgal A, Sadeghi-Naini A. Predicting the outcome of radiotherapy in brain metastasis by integrating the clinical and MRI-based deep learning features. Med Phys 2022; 49:7167-7178. [PMID: 35727568 PMCID: PMC10083982 DOI: 10.1002/mp.15814] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2021] [Revised: 05/28/2022] [Accepted: 05/30/2022] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND A considerable proportion of metastatic brain tumors progress locally despite stereotactic radiation treatment, and it can take months before such local progression is evident on follow-up imaging. Prediction of radiotherapy outcome in terms of tumor local failure is crucial for these patients and can facilitate treatment adjustments or allow for early salvage therapies. PURPOSE In this work, a novel deep learning architecture is introduced to predict the outcome of local control/failure in brain metastasis treated with stereotactic radiation therapy using treatment-planning magnetic resonance imaging (MRI) and standard clinical attributes. METHODS At the core of the proposed architecture is an InceptionResentV2 network to extract distinct features from each MRI slice for local outcome prediction. A recurrent or transformer network is integrated into the architecture to incorporate spatial dependencies between MRI slices into the predictive modeling. A visualization method based on prediction difference analysis is coupled with the deep learning model to illustrate how different regions of each lesion on MRI contribute to the model's prediction. The model was trained and optimized using the data acquired from 99 patients (116 lesions) and evaluated on an independent test set of 25 patients (40 lesions). RESULTS The results demonstrate the promising potential of the MRI deep learning features for outcome prediction, outperforming standard clinical variables. The prediction model with only clinical variables demonstrated an area under the receiver operating characteristic curve (AUC) of 0.68. The MRI deep learning models resulted in AUCs in the range of 0.72 to 0.83 depending on the mechanism to integrate information from MRI slices of each lesion. The best prediction performance (AUC = 0.86) was associated with the model that combined the MRI deep learning features with clinical variables and incorporated the inter-slice dependencies using a long short-term memory recurrent network. The visualization results highlighted the importance of tumor/lesion margins in local outcome prediction for brain metastasis. CONCLUSIONS The promising results of this study show the possibility of early prediction of radiotherapy outcome for brain metastasis via deep learning of MRI and clinical attributes at pre-treatment and encourage future studies on larger groups of patients treated with other radiotherapy modalities.
Collapse
Affiliation(s)
- Seyed Ali Jalalifar
- Department of Electrical Engineering and Computer Science, Lassonde School of Engineering, York University, Toronto, Ontario, Canada
| | - Hany Soliman
- Department of Radiation Oncology, Odette Cancer Centre, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada.,Department of Radiation Oncology, University of Toronto, Toronto, Ontario, Canada.,Physical Sciences Platform, Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
| | - Arjun Sahgal
- Department of Radiation Oncology, Odette Cancer Centre, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada.,Department of Radiation Oncology, University of Toronto, Toronto, Ontario, Canada.,Physical Sciences Platform, Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
| | - Ali Sadeghi-Naini
- Department of Electrical Engineering and Computer Science, Lassonde School of Engineering, York University, Toronto, Ontario, Canada.,Department of Radiation Oncology, Odette Cancer Centre, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada.,Physical Sciences Platform, Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada.,Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
| |
Collapse
|
7
|
Mehrabian H, Chan RW, Sahgal A, Chen H, Theriault A, Lam WW, Myrehaug S, Tseng CL, Husain Z, Detsky J, Soliman H, Stanisz GJ. Chemical Exchange Saturation Transfer MRI for Differentiating Radiation Necrosis From Tumor Progression in Brain Metastasis-Application in a Clinical Setting. J Magn Reson Imaging 2022; 57:1713-1725. [PMID: 36219521 DOI: 10.1002/jmri.28440] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2022] [Revised: 09/07/2022] [Accepted: 09/08/2022] [Indexed: 02/03/2023] Open
Abstract
BACKGROUND High radiation doses of stereotactic radiosurgery (SRS) for brain metastases (BM) can increase the likelihood of radiation necrosis (RN). Advanced MRI sequences can improve the differentiation between RN and tumor progression (TP). PURPOSE To use saturation transfer MRI methods including chemical exchange saturation transfer (CEST) and magnetization transfer (MT) to distinguish RN from TP. STUDY TYPE Prospective cohort study. SUBJECTS Seventy patients (median age 60; 73% females) with BM (75 lesions) post-SRS. FIELD STRENGTH/SEQUENCE 3-T, CEST imaging using low/high-power (saturation B1 = 0.52 and 2.0 μT), quantitative MT imaging using B1 = 1.5, 3.0, and 5.0 μT, WAter Saturation Shift Referencing (WASSR), WAter Shift And B1 (WASABI), T1 , and T2 mapping. All used gradient echoes except T2 mapping (gradient and spin echo). ASSESSMENT Voxel-wise metrics included: magnetization transfer ratio (MTR); apparent exchange-dependent relaxation (AREX); MTR asymmetry; normalized MT exchange rate and pool size product; direct water saturation peak width; and the observed T1 and T2 . Regions of interests (ROIs) were manually contoured on the post-Gd T1 w. The mean (of median ROI values) was compared between groups. Clinical outcomes were determined by clinical and radiologic follow-up or histopathology. STATISTICAL TESTS t-Test, univariable and multivariable logistic regression, receiver operating characteristic, and area under the curve (AUC) with sensitivity/specificity values with the optimal cut point using the Youden index, Akaike information criterion (AIC), Cohen's d. P < 0.05 with Bonferroni correction was considered significant. RESULTS Seven metrics showed significant differences between RN and TP. The high-power MTR showed the highest AUC of 0.88, followed by low-power MTR (AUC = 0.87). The combination of low-power CEST scans improved the separation compared to individual parameters (with an AIC of 70.3 for low-power MTR/AREX). Cohen's d effect size showed that the MTR provided the largest effect sizes among all metrics. DATA CONCLUSION Significant differences between RN and TP were observed based on saturation transfer MRI. EVIDENCE LEVEL 3 Technical Efficacy: Stage 2.
Collapse
Affiliation(s)
- Hatef Mehrabian
- Physical Sciences Platform, Sunnybrook Research Institute, Toronto, Ontario, Canada
| | - Rachel W Chan
- Physical Sciences Platform, Sunnybrook Research Institute, Toronto, Ontario, Canada
| | - Arjun Sahgal
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario, Canada
| | - Hanbo Chen
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario, Canada
| | - Aimee Theriault
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario, Canada
| | - Wilfred W Lam
- Physical Sciences Platform, Sunnybrook Research Institute, Toronto, Ontario, Canada
| | - Sten Myrehaug
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario, Canada
| | - Chia-Lin Tseng
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario, Canada
| | - Zain Husain
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario, Canada
| | - Jay Detsky
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario, Canada
| | - Hany Soliman
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario, Canada
| | - Greg J Stanisz
- Physical Sciences Platform, Sunnybrook Research Institute, Toronto, Ontario, Canada.,Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada.,Department of Neurosurgery and Pediatric Neurosurgery, Medical University of Lublin, Lublin, Poland
| |
Collapse
|
8
|
Perlman O, Ito H, Herz K, Shono N, Nakashima H, Zaiss M, Chiocca EA, Cohen O, Rosen MS, Farrar CT. Quantitative imaging of apoptosis following oncolytic virotherapy by magnetic resonance fingerprinting aided by deep learning. Nat Biomed Eng 2022; 6:648-657. [PMID: 34764440 PMCID: PMC9091056 DOI: 10.1038/s41551-021-00809-7] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2020] [Accepted: 07/07/2021] [Indexed: 12/17/2022]
Abstract
Non-invasive imaging methods for detecting intratumoural viral spread and host responses to oncolytic virotherapy are either slow, lack specificity or require the use of radioactive or metal-based contrast agents. Here we show that in mice with glioblastoma multiforme, the early apoptotic responses to oncolytic virotherapy (characterized by decreased cytosolic pH and reduced protein synthesis) can be rapidly detected via chemical-exchange-saturation-transfer magnetic resonance fingerprinting (CEST-MRF) aided by deep learning. By leveraging a deep neural network trained with simulated magnetic resonance fingerprints, CEST-MRF can generate quantitative maps of intratumoural pH and of protein and lipid concentrations by selectively labelling the exchangeable amide protons of endogenous proteins and the exchangeable macromolecule protons of lipids, without requiring exogenous contrast agents. We also show that in a healthy volunteer, CEST-MRF yielded molecular parameters that are in good agreement with values from the literature. Deep-learning-aided CEST-MRF may also be amenable to the characterization of host responses to other cancer therapies and to the detection of cardiac and neurological pathologies.
Collapse
Affiliation(s)
- Or Perlman
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA.
| | - Hirotaka Ito
- Department of Neurosurgery, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Kai Herz
- Magnetic Resonance Center, Max Planck Institute for Biological Cybernetics, Tübingen, Germany
- Department of Biomedical Magnetic Resonance, University of Tübingen, Tübingen, Germany
| | - Naoyuki Shono
- Department of Neurosurgery, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Hiroshi Nakashima
- Department of Neurosurgery, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Moritz Zaiss
- Magnetic Resonance Center, Max Planck Institute for Biological Cybernetics, Tübingen, Germany
- Department of Neuroradiology, Friedrich-Alexander Universität Erlangen-Nürnberg (FAU), University Hospital Erlangen, Erlangen, Germany
| | - E Antonio Chiocca
- Department of Neurosurgery, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Ouri Cohen
- Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Matthew S Rosen
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
- Department of Physics, Harvard University, Cambridge, MA, USA
| | - Christian T Farrar
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA.
| |
Collapse
|
9
|
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: 7] [Impact Index Per Article: 3.5] [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.
Collapse
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:
| |
Collapse
|
10
|
Cuccia F, Alongi F, Belka C, Boldrini L, Hörner-Rieber J, McNair H, Rigo M, Schoenmakers M, Niyazi M, Slagter J, Votta C, Corradini S. Patient positioning and immobilization procedures for hybrid MR-Linac systems. Radiat Oncol 2021; 16:183. [PMID: 34544481 PMCID: PMC8454038 DOI: 10.1186/s13014-021-01910-6] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2021] [Accepted: 09/09/2021] [Indexed: 02/08/2023] Open
Abstract
Hybrid magnetic resonance (MR)-guided linear accelerators represent a new horizon in the field of radiation oncology. By harnessing the favorable combination of on-board MR-imaging with the possibility to daily recalculate the treatment plan based on real-time anatomy, the accuracy in target and organs-at-risk identification is expected to be improved, with the aim to provide the best tailored treatment. To date, two main MR-linac hybrid machines are available, Elekta Unity and Viewray MRIdian. Of note, compared to conventional linacs, these devices raise practical issues due to the positioning phase for the need to include the coil in the immobilization procedure and in order to perform the best reproducible positioning, also in light of the potentially longer treatment time. Given the relative novelty of this technology, there are few literature data regarding the procedures and the workflows for patient positioning and immobilization for MR-guided daily adaptive radiotherapy. In the present narrative review, we resume the currently available literature and provide an overview of the positioning and setup procedures for all the anatomical districts for hybrid MR-linac systems.
Collapse
Affiliation(s)
- Francesco Cuccia
- Advanced Radiation Oncology Department, IRCCS Sacro Cuore Don Calabria Hospital, Negrar Di Valpolicella, VR, Italy.
| | - Filippo Alongi
- Advanced Radiation Oncology Department, IRCCS Sacro Cuore Don Calabria Hospital, Negrar Di Valpolicella, VR, Italy
- University of Brescia, Brescia, Italy
| | - Claus Belka
- Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany
| | - Luca Boldrini
- Radiology, Radiation Oncology and Hematology Department, Fondazione Policlinico Universitario "Agostino Gemelli" IRCCS, Roma, Italy
| | - Juliane Hörner-Rieber
- Department of Radiation Oncology, University Hospital of Heidelberg, National Center for Radiation Oncology (NCRO), Heidelberg Institute for Radiation Oncology (HIRO), Heidelberg, Germany
| | - Helen McNair
- The Royal Marsden NHS Foundation Trust, and Institute of Cancer Research Sutton, Surrey, UK
| | - Michele Rigo
- Advanced Radiation Oncology Department, IRCCS Sacro Cuore Don Calabria Hospital, Negrar Di Valpolicella, VR, Italy
| | - Maartje Schoenmakers
- Department of Radiation Oncology, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX, Utrecht, The Netherlands
| | - Maximilian Niyazi
- Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany
| | - Judith Slagter
- Department of Radiation Oncology - Cancer Center Amsterdam, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Claudio Votta
- Radiology, Radiation Oncology and Hematology Department, Fondazione Policlinico Universitario "Agostino Gemelli" IRCCS, Roma, Italy
| | - Stefanie Corradini
- Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany
| |
Collapse
|
11
|
Chan RW, Lawrence LSP, Oglesby RT, Chen H, Stewart J, Theriault A, Campbell M, Ruschin M, Myrehaug S, Atenafu EG, Keller B, Chugh B, MacKenzie S, Tseng CL, Detsky J, Maralani PJ, Czarnota GJ, Stanisz GJ, Sahgal A, Lau AZ. Chemical exchange saturation transfer MRI in central nervous system tumours on a 1.5 T MR-Linac. Radiother Oncol 2021; 162:140-149. [PMID: 34280403 DOI: 10.1016/j.radonc.2021.07.010] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2021] [Revised: 07/06/2021] [Accepted: 07/08/2021] [Indexed: 11/30/2022]
Abstract
PURPOSE To describe the implementation and initial results of using Chemical Exchange Saturation Transfer (CEST) for monitoring patients with central nervous system (CNS) tumours treated using a 1.5 tesla MR-guided radiotherapy system. METHODS CNS patients were treated with up to 30 fractions (total dose up to 60 Gy) using a 1.5 T Elekta Unity MR-Linac. CEST scans were obtained in 54 subjects at one or more time points during treatment. CEST metrics, including the amide magnetization transfer ratio (MTRAmide), nuclear Overhauser effect (NOE) MTR (MTRNOE) and asymmetry, were quantified in phantoms and CNS patients. The signal was investigated between tumour and white matter, across time, and across disease categories including high- and low-grade tumours. RESULTS The gross tumour volume (GTV) exhibited lower MTRAmide and MTRNOE and higher asymmetry compared to contralateral normal appearing white matter. Signal changes in the GTV during fractionated radiotherapy were observed. There were differences between high- and low-grade tumours, with higher CEST asymmetry associated with higher grade disease. CONCLUSION CEST MRI using a 1.5 T MR-Linac was demonstrated to be feasible for in vivo imaging of CNS tumours. CEST images showed tumour/white-matter contrast, temporal CEST signal changes, and associations with tumour grade. These results show promise for the eventual goal of using metabolic imaging to inform the design of adaptive radiotherapy protocols.
Collapse
Affiliation(s)
- Rachel W Chan
- Physical Sciences Platform, Sunnybrook Research Institute, Toronto, Canada.
| | - Liam S P Lawrence
- Department of Medical Biophysics, University of Toronto, Toronto, Canada
| | - Ryan T Oglesby
- Physical Sciences Platform, Sunnybrook Research Institute, Toronto, Canada; Department of Medical Biophysics, University of Toronto, Toronto, Canada
| | - Hanbo Chen
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada
| | - James Stewart
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada
| | - Aimee Theriault
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada
| | - Mikki Campbell
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada
| | - Mark Ruschin
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada
| | - Sten Myrehaug
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada
| | - Eshetu G Atenafu
- Department of Biostatistics, University Health Network, University of Toronto, Toronto, Canada
| | - Brian Keller
- Department of Biostatistics, University Health Network, University of Toronto, Toronto, Canada
| | - Brige Chugh
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada; Department of Physics, Ryerson University, Toronto, Canada
| | - Scott MacKenzie
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada
| | - Chia-Lin Tseng
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada
| | - Jay Detsky
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada
| | - Pejman J Maralani
- Department of Medical Imaging, University of Toronto, Sunnybrook Health Sciences Centre, Toronto, Canada
| | - Greg J Czarnota
- Physical Sciences Platform, Sunnybrook Research Institute, Toronto, Canada; Department of Medical Biophysics, University of Toronto, Toronto, Canada; Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada
| | - Greg J Stanisz
- Physical Sciences Platform, Sunnybrook Research Institute, Toronto, Canada; Department of Medical Biophysics, University of Toronto, Toronto, Canada; Department of Neurosurgery and Pediatric Neurosurgery, Medical University of Lublin, Lublin, Poland
| | - Arjun Sahgal
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada
| | - Angus Z Lau
- Physical Sciences Platform, Sunnybrook Research Institute, Toronto, Canada; Department of Medical Biophysics, University of Toronto, Toronto, Canada
| |
Collapse
|
12
|
Mouraviev A, Detsky J, Sahgal A, Ruschin M, Lee YK, Karam I, Heyn C, Stanisz GJ, Martel AL. Use of radiomics for the prediction of local control of brain metastases after stereotactic radiosurgery. Neuro Oncol 2021; 22:797-805. [PMID: 31956919 DOI: 10.1093/neuonc/noaa007] [Citation(s) in RCA: 52] [Impact Index Per Article: 17.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
BACKGROUND Local response prediction for brain metastases (BM) after stereotactic radiosurgery (SRS) is challenging, particularly for smaller BM, as existing criteria are based solely on unidimensional measurements. This investigation sought to determine whether radiomic features provide additional value to routinely available clinical and dosimetric variables to predict local recurrence following SRS. METHODS Analyzed were 408 BM in 87 patients treated with SRS. A total of 440 radiomic features were extracted from the tumor core and the peritumoral regions, using the baseline pretreatment volumetric post-contrast T1 (T1c) and volumetric T2 fluid-attenuated inversion recovery (FLAIR) MRI sequences. Local tumor progression was determined based on Response Assessment in Neuro-Oncology‒BM criteria, with a maximum axial diameter growth of >20% on the follow-up T1c indicating local failure. The top radiomic features were determined based on resampled random forest (RF) feature importance. An RF classifier was trained using each set of features and evaluated using the area under the receiver operating characteristic curve (AUC). RESULTS The addition of any one of the top 10 radiomic features to the set of clinical features resulted in a statistically significant (P < 0.001) increase in the AUC. An optimized combination of radiomic and clinical features resulted in a 19% higher resampled AUC (mean = 0.793; 95% CI = 0.792-0.795) than clinical features alone (0.669, 0.668-0.671). CONCLUSIONS The increase in AUC of the RF classifier, after incorporating radiomic features, suggests that quantitative characterization of tumor appearance on pretreatment T1c and FLAIR adds value to known clinical and dosimetric variables for predicting local failure.
Collapse
Affiliation(s)
- Andrei Mouraviev
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
| | - Jay Detsky
- Odette Cancer Center, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
| | - Arjun Sahgal
- Odette Cancer Center, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
| | - Mark Ruschin
- Odette Cancer Center, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
| | - Young K Lee
- Odette Cancer Center, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
| | - Irene Karam
- Odette Cancer Center, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
| | - Chris Heyn
- Odette Cancer Center, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
| | - Greg J Stanisz
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada.,Physical Sciences, Sunnybrook Research Institute, Toronto, Ontario, Canada
| | - Anne L Martel
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada.,Physical Sciences, Sunnybrook Research Institute, Toronto, Ontario, Canada
| |
Collapse
|
13
|
Overcast WB, Davis KM, Ho CY, Hutchins GD, Green MA, Graner BD, Veronesi MC. Advanced imaging techniques for neuro-oncologic tumor diagnosis, with an emphasis on PET-MRI imaging of malignant brain tumors. Curr Oncol Rep 2021; 23:34. [PMID: 33599882 PMCID: PMC7892735 DOI: 10.1007/s11912-021-01020-2] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/11/2021] [Indexed: 12/15/2022]
Abstract
PURPOSE OF REVIEW This review will explore the latest in advanced imaging techniques, with a focus on the complementary nature of multiparametric, multimodality imaging using magnetic resonance imaging (MRI) and positron emission tomography (PET). RECENT FINDINGS Advanced MRI techniques including perfusion-weighted imaging (PWI), MR spectroscopy (MRS), diffusion-weighted imaging (DWI), and MR chemical exchange saturation transfer (CEST) offer significant advantages over conventional MR imaging when evaluating tumor extent, predicting grade, and assessing treatment response. PET performed in addition to advanced MRI provides complementary information regarding tumor metabolic properties, particularly when performed simultaneously. 18F-fluoroethyltyrosine (FET) PET improves the specificity of tumor diagnosis and evaluation of post-treatment changes. Incorporation of radiogenomics and machine learning methods further improve advanced imaging. The complementary nature of combining advanced imaging techniques across modalities for brain tumor imaging and incorporating technologies such as radiogenomics has the potential to reshape the landscape in neuro-oncology.
Collapse
Affiliation(s)
- Wynton B. Overcast
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, 550 N University Blvd. Room 0663, Indianapolis, IN 46202 USA
| | - Korbin M. Davis
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, 550 N University Blvd. Room 0663, Indianapolis, IN 46202 USA
| | - Chang Y. Ho
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Goodman Hall, 355 West 16th Street, Suite 4100, Indianapolis, IN 46202 USA
| | - Gary D. Hutchins
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Research 2 Building (R2), Room E124, 920 W. Walnut Street, Indianapolis, IN 46202-5181 USA
| | - Mark A. Green
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Research 2 Building (R2), Room E124, 920 W. Walnut Street, Indianapolis, IN 46202-5181 USA
| | - Brian D. Graner
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Goodman Hall, 355 West 16th Street, Suite 4100, Indianapolis, IN 46202 USA
| | - Michael C. Veronesi
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Research 2 Building (R2), Room E174, 920 W. Walnut Street, Indianapolis, IN 46202-5181 USA
| |
Collapse
|
14
|
Masmudi-Martín M, Zhu L, Sanchez-Navarro M, Priego N, Casanova-Acebes M, Ruiz-Rodado V, Giralt E, Valiente M. Brain metastasis models: What should we aim to achieve better treatments? Adv Drug Deliv Rev 2021; 169:79-99. [PMID: 33321154 DOI: 10.1016/j.addr.2020.12.002] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2020] [Revised: 11/16/2020] [Accepted: 12/04/2020] [Indexed: 02/07/2023]
Abstract
Brain metastasis is emerging as a unique entity in oncology based on its particular biology and, consequently, the pharmacological approaches that should be considered. We discuss the current state of modelling this specific progression of cancer and how these experimental models have been used to test multiple pharmacologic strategies over the years. In spite of pre-clinical evidences demonstrating brain metastasis vulnerabilities, many clinical trials have excluded patients with brain metastasis. Fortunately, this trend is getting to an end given the increasing importance of secondary brain tumors in the clinic and a better knowledge of the underlying biology. We discuss emerging trends and unsolved issues that will shape how we will study experimental brain metastasis in the years to come.
Collapse
|
15
|
Imaging of Response to Radiosurgery and Immunotherapy in Brain Metastases: Quo Vadis? Curr Treat Options Neurol 2021. [DOI: 10.1007/s11940-021-00664-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
Abstract
Abstract
Purpose of Review
This review presents an overview of how advanced imaging techniques may help to overcome shortcomings of anatomical MRI for response assessment in patients with brain metastases who are undergoing stereotactic radiosurgery, immunotherapy, or combinations thereof.
Recent Findings
Study results suggest that parameters derived from amino acid PET, diffusion- and perfusion-weighted MRI, MR spectroscopy, and newer MRI methods are particularly helpful for the evaluation of the response to radiosurgery or checkpoint inhibitor immunotherapy and provide valuable information for the differentiation of radiotherapy-induced changes such as radiation necrosis from brain metastases. The evaluation of these imaging modalities is also of great interest in the light of emerging high-throughput analysis methods such as radiomics, which allow the acquisition of additional data at a low cost.
Summary
Preliminary results are promising and should be further evaluated. Shortcomings are different levels of PET and MRI standardization, the number of patients enrolled in studies, and the monocentric and retrospective character of most studies.
Collapse
|
16
|
Longo DL, Irrera P, Consolino L, Sun PZ, McMahon MT. Renal pH Imaging Using Chemical Exchange Saturation Transfer (CEST) MRI: Basic Concept. Methods Mol Biol 2021; 2216:241-256. [PMID: 33476004 DOI: 10.1007/978-1-0716-0978-1_14] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/19/2023]
Abstract
Magnetic Resonance Imaging (MRI) has been actively explored in the last several decades for assessing renal function by providing several physiological information, including glomerular filtration rate, renal plasma flow, tissue oxygenation and water diffusion. Within MRI, the developing field of chemical exchange saturation transfer (CEST) has potential to provide further functional information for diagnosing kidney diseases. Both endogenous produced molecules as well as exogenously administered CEST agents have been exploited for providing functional information related to kidney diseases in preclinical studies. In particular, CEST MRI has been exploited for assessing the acid-base homeostasis in the kidney and for monitoring pH changes in several disease models. This review summarizes several CEST MRI procedures for assessing kidney functionality and pH, for monitoring renal pH changes in different kidney injury models and for evaluating renal allograft rejection.This chapter is based upon work from the COST Action PARENCHIMA, a community-driven network funded by the European Cooperation in Science and Technology (COST) program of the European Union, which aims to improve the reproducibility and standardization of renal MRI biomarkers. This introduction chapter is complemented by two separate chapters describing the experimental procedure and data analysis.
Collapse
Affiliation(s)
- Dario Livio Longo
- Institute of Biostructures and Bioimaging (IBB), Italian National Research Council (CNR), Torino, Italy.
| | - Pietro Irrera
- University of Campania "Luigi Vanvitelli", Napoli, Italy
| | - Lorena Consolino
- Department of Molecular Biotechnology and Health Sciences, University of Torino, Torino, Italy
| | - Phillip Zhe Sun
- Yerkes Imaging Center, Yerkes National Primate Research Center, Emory University, Atlanta, GA, USA
- Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - Michael T McMahon
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
- Division of MR Research, The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| |
Collapse
|
17
|
Aasen SN, Espedal H, Keunen O, Adamsen TCH, Bjerkvig R, Thorsen F. Current landscape and future perspectives in preclinical MR and PET imaging of brain metastasis. Neurooncol Adv 2021; 3:vdab151. [PMID: 34988446 PMCID: PMC8704384 DOI: 10.1093/noajnl/vdab151] [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] [Indexed: 11/13/2022] Open
Abstract
Brain metastasis (BM) is a major cause of cancer patient morbidity. Clinical magnetic resonance imaging (MRI) and positron emission tomography (PET) represent important resources to assess tumor progression and treatment responses. In preclinical research, anatomical MRI and to some extent functional MRI have frequently been used to assess tumor progression. In contrast, PET has only to a limited extent been used in animal BM research. A considerable culprit is that results from most preclinical studies have shown little impact on the implementation of new treatment strategies in the clinic. This emphasizes the need for the development of robust, high-quality preclinical imaging strategies with potential for clinical translation. This review focuses on advanced preclinical MRI and PET imaging methods for BM, describing their applications in the context of what has been done in the clinic. The strengths and shortcomings of each technology are presented, and recommendations for future directions in the development of the individual imaging modalities are suggested. Finally, we highlight recent developments in quantitative MRI and PET, the use of radiomics and multimodal imaging, and the need for a standardization of imaging technologies and protocols between preclinical centers.
Collapse
Affiliation(s)
- Synnøve Nymark Aasen
- Department of Biomedicine, University of Bergen, Bergen, Norway
- Department of Health and Functioning, Western Norway University of Applied Sciences, Bergen, Norway
| | - Heidi Espedal
- The Molecular Imaging Center, Department of Biomedicine, University of Bergen, Bergen, Norway
- Mohn Medical Imaging and Visualization Centre, Department of Clinical Medicine, University of Bergen, Bergen, Norway
| | - Olivier Keunen
- Translational Radiomics, Department of Oncology, Luxembourg Institute of Health, Luxembourg, Luxembourg
| | - Tom Christian Holm Adamsen
- Centre for Nuclear Medicine, Department of Radiology, Haukeland University Hospital, Bergen, Norway
- 180 °N – Bergen Tracer Development Centre, Department of Radiology, Haukeland University Hospital, Bergen, Norway
- Department of Chemistry, University of Bergen, Bergen, Norway
| | - Rolf Bjerkvig
- Department of Biomedicine, University of Bergen, Bergen, Norway
- NorLux Neuro-Oncology Laboratory, Department of Oncology, Luxembourg Institute of Health, Luxembourg, Luxembourg
| | - Frits Thorsen
- Department of Biomedicine, University of Bergen, Bergen, Norway
- The Molecular Imaging Center, Department of Biomedicine, University of Bergen, Bergen, Norway
- Department of Neurosurgery, Qilu Hospital of Shandong University and Brain Science Research Institute, Shandong University, Key Laboratory of Brain Functional Remodeling, Shandong, Jinan, P.R. China
| |
Collapse
|
18
|
Shah AD, Shridhar Konar A, Paudyal R, Oh JH, LoCastro E, Nuñez DA, Swinburne N, Vachha B, Ulaner GA, Young RJ, Holodny AI, Beal K, Shukla-Dave A, Hatzoglou V. Diffusion and Perfusion MRI Predicts Response Preceding and Shortly After Radiosurgery to Brain Metastases: A Pilot Study. J Neuroimaging 2020; 31:317-323. [PMID: 33370467 DOI: 10.1111/jon.12828] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2020] [Revised: 11/20/2020] [Accepted: 12/06/2020] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND AND PURPOSE To determine the ability of diffusion-weighted imaging (DWI) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to predict long-term response of brain metastases prior to and within 72 hours of stereotactic radiosurgery (SRS). METHODS In this prospective pilot study, multiple b-value DWI and T1-weighted DCE-MRI were performed in patients with brain metastases before and within 72 hours following SRS. Diffusion-weighted images were analyzed using the monoexponential and intravoxel incoherent motion (IVIM) models. DCE-MRI data were analyzed using the extended Tofts pharmacokinetic model. The parameters obtained with these methods were correlated with brain metastasis outcomes according to modified Response Assessment in Neuro-Oncology Brain Metastases criteria. RESULTS We included 25 lesions from 16 patients; 16 patients underwent pre-SRS MRI and 12 of 16 patients underwent both pre- and early (within 72 hours) post-SRS MRI. The perfusion fraction (f) derived from IVIM early post-SRS was higher in lesions demonstrating progressive disease than in lesions demonstrating stable disease, partial response, or complete response (q = .041). Pre-SRS extracellular extravascular volume fraction, ve , and volume transfer coefficient, Ktrans , derived from DCE-MRI were higher in nonresponders versus responders (q = .041). CONCLUSIONS Quantitative DWI and DCE-MRI are feasible imaging methods in the pre- and early (within 72 hours) post-SRS evaluation of brain metastases. DWI- and DCE-MRI-derived parameters demonstrated physiologic changes (tumor cellularity and vascularity) and offer potentially useful biomarkers that can predict treatment response. This allows for initiation of alternate therapies within an effective time window that may help prevent disease progression.
Collapse
Affiliation(s)
- Akash Deelip Shah
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY
| | | | - Ramesh Paudyal
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Jung Hun Oh
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Eve LoCastro
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY
| | - David Aramburu Nuñez
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Nathaniel Swinburne
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Behroze Vachha
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Gary A Ulaner
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Robert J Young
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Andrei I Holodny
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Kathryn Beal
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Amita Shukla-Dave
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY.,Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Vaios Hatzoglou
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY
| |
Collapse
|
19
|
Glioma consensus contouring recommendations from a MR-Linac International Consortium Research Group and evaluation of a CT-MRI and MRI-only workflow. J Neurooncol 2020; 149:305-314. [PMID: 32860571 PMCID: PMC7541359 DOI: 10.1007/s11060-020-03605-6] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2020] [Accepted: 08/23/2020] [Indexed: 02/07/2023]
Abstract
Introduction This study proposes contouring recommendations for radiation treatment planning target volumes and organs-at-risk (OARs) for both low grade and high grade gliomas. Methods Ten cases consisting of 5 glioblastomas and 5 grade II or III gliomas, including their respective gross tumor volume (GTV), clinical target volume (CTV), and OARs were each contoured by 6 experienced neuro-radiation oncologists from 5 international institutions. Each case was first contoured using only MRI sequences (MRI-only), and then re-contoured with the addition of a fused planning CT (CT-MRI). The level of agreement among all contours was assessed using simultaneous truth and performance level estimation (STAPLE) with the kappa statistic and Dice similarity coefficient. Results A high level of agreement was observed between the GTV and CTV contours in the MRI-only workflow with a mean kappa of 0.88 and 0.89, respectively, with no statistically significant differences compared to the CT-MRI workflow (p = 0.88 and p = 0.82 for GTV and CTV, respectively). Agreement in cochlea contours improved from a mean kappa of 0.39 to 0.41, to 0.69 to 0.71 with the addition of CT information (p < 0.0001 for both cochleae). Substantial to near perfect level of agreement was observed in all other contoured OARs with a mean kappa range of 0.60 to 0.90 in both MRI-only and CT-MRI workflows. Conclusions Consensus contouring recommendations for low grade and high grade gliomas were established using the results from the consensus STAPLE contours, which will serve as a basis for further study and clinical trials by the MR-Linac Consortium. Electronic supplementary material The online version of this article (10.1007/s11060-020-03605-6) contains supplementary material, which is available to authorized users.
Collapse
|
20
|
Park JE, Kim HS, Park SY, Jung SC, Kim JH, Heo HY. Identification of Early Response to Anti-Angiogenic Therapy in Recurrent Glioblastoma: Amide Proton Transfer–weighted and Perfusion-weighted MRI compared with Diffusion-weighted MRI. Radiology 2020; 295:397-406. [DOI: 10.1148/radiol.2020191376] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Affiliation(s)
- Ji Eun Park
- From the Department of Radiology and Research Institute of Radiology (J.E.P., H.S.K., S.C.J.), Department of Clinical Epidemiology and Biostatistics (S.Y.P.), and Department of Neurosurgery (J.H.K.), University of Ulsan College of Medicine, Asan Medical Center, 43 Olympic-ro 88, Songpa-Gu, Seoul 05505, Korea; and Department of Radiology, Johns Hopkins University, Baltimore, Md (H.Y.H.)
| | - Ho Sung Kim
- From the Department of Radiology and Research Institute of Radiology (J.E.P., H.S.K., S.C.J.), Department of Clinical Epidemiology and Biostatistics (S.Y.P.), and Department of Neurosurgery (J.H.K.), University of Ulsan College of Medicine, Asan Medical Center, 43 Olympic-ro 88, Songpa-Gu, Seoul 05505, Korea; and Department of Radiology, Johns Hopkins University, Baltimore, Md (H.Y.H.)
| | - Seo Young Park
- From the Department of Radiology and Research Institute of Radiology (J.E.P., H.S.K., S.C.J.), Department of Clinical Epidemiology and Biostatistics (S.Y.P.), and Department of Neurosurgery (J.H.K.), University of Ulsan College of Medicine, Asan Medical Center, 43 Olympic-ro 88, Songpa-Gu, Seoul 05505, Korea; and Department of Radiology, Johns Hopkins University, Baltimore, Md (H.Y.H.)
| | - Seung Chai Jung
- From the Department of Radiology and Research Institute of Radiology (J.E.P., H.S.K., S.C.J.), Department of Clinical Epidemiology and Biostatistics (S.Y.P.), and Department of Neurosurgery (J.H.K.), University of Ulsan College of Medicine, Asan Medical Center, 43 Olympic-ro 88, Songpa-Gu, Seoul 05505, Korea; and Department of Radiology, Johns Hopkins University, Baltimore, Md (H.Y.H.)
| | - Jeong Hoon Kim
- From the Department of Radiology and Research Institute of Radiology (J.E.P., H.S.K., S.C.J.), Department of Clinical Epidemiology and Biostatistics (S.Y.P.), and Department of Neurosurgery (J.H.K.), University of Ulsan College of Medicine, Asan Medical Center, 43 Olympic-ro 88, Songpa-Gu, Seoul 05505, Korea; and Department of Radiology, Johns Hopkins University, Baltimore, Md (H.Y.H.)
| | - Hye-Young Heo
- From the Department of Radiology and Research Institute of Radiology (J.E.P., H.S.K., S.C.J.), Department of Clinical Epidemiology and Biostatistics (S.Y.P.), and Department of Neurosurgery (J.H.K.), University of Ulsan College of Medicine, Asan Medical Center, 43 Olympic-ro 88, Songpa-Gu, Seoul 05505, Korea; and Department of Radiology, Johns Hopkins University, Baltimore, Md (H.Y.H.)
| |
Collapse
|
21
|
Tong E, McCullagh KL, Iv M. Advanced Imaging of Brain Metastases: From Augmenting Visualization and Improving Diagnosis to Evaluating Treatment Response. Front Neurol 2020; 11:270. [PMID: 32351445 PMCID: PMC7174761 DOI: 10.3389/fneur.2020.00270] [Citation(s) in RCA: 39] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2019] [Accepted: 03/24/2020] [Indexed: 12/11/2022] Open
Abstract
Early detection of brain metastases and differentiation from other neuropathologies is crucial. Although biopsy is often required for definitive diagnosis, imaging can provide useful information. After treatment commences, imaging is also performed to assess the efficacy of treatment. Contrast-enhanced magnetic resonance imaging (MRI) is the traditional imaging method for the evaluation of brain metastases, as it provides information about lesion size, morphology, and macroscopic properties. Newer MRI sequences have been developed to increase the conspicuity of detecting enhancing metastases. Other advanced MRI techniques, that have the capability to probe beyond the anatomic structure, are available to characterize micro-structures, cellularity, physiology, perfusion, and metabolism. Artificial intelligence provides powerful computational tools for detection, segmentation, classification, prediction, and prognosis. We highlight and review a few advanced MRI techniques for the assessment of brain metastases-specifically for (1) diagnosis, including differentiating between malignancy types and (2) evaluation of treatment response, including the differentiation between radiation necrosis and disease progression.
Collapse
Affiliation(s)
- Elizabeth Tong
- Stanford University Medical Center, Stanford, CA, United States
| | | | - Michael Iv
- Stanford University Medical Center, Stanford, CA, United States
| |
Collapse
|
22
|
Abstract
Brain metastases are a very common manifestation of cancer that have historically been approached as a single disease entity given the uniform association with poor clinical outcomes. Fortunately, our understanding of the biology and molecular underpinnings of brain metastases has greatly improved, resulting in more sophisticated prognostic models and multiple patient-related and disease-specific treatment paradigms. In addition, the therapeutic armamentarium has expanded from whole-brain radiotherapy and surgery to include stereotactic radiosurgery, targeted therapies and immunotherapies, which are often used sequentially or in combination. Advances in neuroimaging have provided additional opportunities to accurately screen for intracranial disease at initial cancer diagnosis, target intracranial lesions with precision during treatment and help differentiate the effects of treatment from disease progression by incorporating functional imaging. Given the numerous available treatment options for patients with brain metastases, a multidisciplinary approach is strongly recommended to personalize the treatment of each patient in an effort to improve the therapeutic ratio. Given the ongoing controversies regarding the optimal sequencing of the available and expanding treatment options for patients with brain metastases, enrolment in clinical trials is essential to advance our understanding of this complex and common disease. In this Review, we describe the key features of diagnosis, risk stratification and modern paradigms in the treatment and management of patients with brain metastases and provide speculation on future research directions.
Collapse
|
23
|
Schwarz D, Bendszus M, Breckwoldt MO. Clinical Value of Susceptibility Weighted Imaging of Brain Metastases. Front Neurol 2020; 11:55. [PMID: 32117017 PMCID: PMC7010951 DOI: 10.3389/fneur.2020.00055] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2019] [Accepted: 01/15/2020] [Indexed: 12/25/2022] Open
Abstract
MRI is used for screening, initial diagnosis and follow-up of brain metastases. Multiparametric MRI protocols encompass an array of image sequences to depict key aspects of metastases morphology and biology. Given the recent safety concerns of Gd-administration and the retention of linear Gd-agents in the brain, non-contrast sequences are currently evaluated regarding their diagnostic value for brain imaging studies. Susceptibility weighted imaging has been established as a valuable clinical and research tool that is heavily used in clinical practice and utilized in diverse pathologies ranging from neuroinflammation, neurovascular disease to neurooncology. We review the value of SWI in the field of brain metastases with an emphasis on its role in early diagnosis, determination of the primary tumor entity, treatment monitoring and discuss therapy-associated changes that can affect SWI. We also review recent insights on the role of “isolated SWI signals” and the controversy on the specificity of SWI for the early detection of brain metastases.
Collapse
Affiliation(s)
- Daniel Schwarz
- Neuroradiology Department, University Hospital Heidelberg, Heidelberg, Germany
| | - Martin Bendszus
- Neuroradiology Department, University Hospital Heidelberg, Heidelberg, Germany
| | - Michael O Breckwoldt
- Neuroradiology Department, University Hospital Heidelberg, Heidelberg, Germany.,Clinical Cooperation Unit Neuroimmunology and Brain Tumor Immunology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| |
Collapse
|
24
|
Okuchi S, Hammam A, Golay X, Kim M, Thust S. Endogenous Chemical Exchange Saturation Transfer MRI for the Diagnosis and Therapy Response Assessment of Brain Tumors: A Systematic Review. Radiol Imaging Cancer 2020; 2:e190036. [PMID: 33778693 PMCID: PMC7983695 DOI: 10.1148/rycan.2020190036] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2019] [Revised: 09/13/2019] [Accepted: 10/21/2019] [Indexed: 01/09/2023]
Abstract
Purpose To generate a narrative synthesis of published data on the use of endogenous chemical exchange saturation transfer (CEST) MRI in brain tumors. Materials and Methods A systematic database search (PubMed, Ovid Embase, Cochrane Library) was used to collate eligible studies. Two researchers independently screened publications according to predefined exclusion and inclusion criteria, followed by comprehensive data extraction. All included studies were subjected to a bias risk assessment using the Quality Assessment of Diagnostic Accuracy Studies tool. Results The electronic database search identified 430 studies, of which 36 fulfilled the inclusion criteria. The final selection of included studies was categorized into five groups as follows: grading gliomas, 19 studies (area under the receiver operating characteristic curve [AUC], 0.500-1.000); predicting molecular subtypes of gliomas, five studies (AUC, 0.610-0.920); distinction of different brain tumor types, seven studies (AUC, 0.707-0.905); therapy response assessment, three studies (AUC not given); and differentiating recurrence from treatment-related changes, five studies (AUC, 0.880-0.980). A high bias risk was observed in a substantial proportion of studies. Conclusion Endogenous CEST MRI offers valuable, potentially unique information in brain tumors, but its diagnostic accuracy remains incompletely known. Further research is required to assess the method's role in support of molecular genetic diagnosis, to investigate its use in the posttreatment phase, and to compare techniques with a view to standardization.Keywords: Brain/Brain Stem, MR-Imaging, Neuro-OncologySupplemental material is available for this article.© RSNA, 2020.
Collapse
Affiliation(s)
- Sachi Okuchi
- From the Department of Brain Repair and Rehabilitation, University College London, Institute of Neurology, London, England (S.O., A.H., X.G., M.K., S.T.); Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, 54 Shogoin-Kawaharacho, Sakyo-ku, Kyoto 606-8507, Japan (S.O.); and Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, London, England (S.T.)
| | - Ahmed Hammam
- From the Department of Brain Repair and Rehabilitation, University College London, Institute of Neurology, London, England (S.O., A.H., X.G., M.K., S.T.); Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, 54 Shogoin-Kawaharacho, Sakyo-ku, Kyoto 606-8507, Japan (S.O.); and Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, London, England (S.T.)
| | - Xavier Golay
- From the Department of Brain Repair and Rehabilitation, University College London, Institute of Neurology, London, England (S.O., A.H., X.G., M.K., S.T.); Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, 54 Shogoin-Kawaharacho, Sakyo-ku, Kyoto 606-8507, Japan (S.O.); and Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, London, England (S.T.)
| | - Mina Kim
- From the Department of Brain Repair and Rehabilitation, University College London, Institute of Neurology, London, England (S.O., A.H., X.G., M.K., S.T.); Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, 54 Shogoin-Kawaharacho, Sakyo-ku, Kyoto 606-8507, Japan (S.O.); and Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, London, England (S.T.)
| | - Stefanie Thust
- From the Department of Brain Repair and Rehabilitation, University College London, Institute of Neurology, London, England (S.O., A.H., X.G., M.K., S.T.); Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, 54 Shogoin-Kawaharacho, Sakyo-ku, Kyoto 606-8507, Japan (S.O.); and Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, London, England (S.T.)
| |
Collapse
|
25
|
Breitling J, Deshmane A, Goerke S, Korzowski A, Herz K, Ladd ME, Scheffler K, Bachert P, Zaiss M. Adaptive denoising for chemical exchange saturation transfer MR imaging. NMR IN BIOMEDICINE 2019; 32:e4133. [PMID: 31361064 DOI: 10.1002/nbm.4133] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/20/2019] [Revised: 06/03/2019] [Accepted: 06/04/2019] [Indexed: 06/10/2023]
Abstract
High image signal-to-noise ratio (SNR) is required to reliably detect the inherently small chemical exchange saturation transfer (CEST) effects in vivo. In this study, it was demonstrated that identifying spectral redundancies of CEST data by principal component analysis (PCA) in combination with an appropriate data-driven extraction of relevant information can be used for an effective and robust denoising of CEST spectra. The relationship between the number of relevant principal components and SNR was studied on fitted in vivo Z-spectra with artificially introduced noise. Three different data-driven criteria to automatically determine the optimal number of necessary components were investigated. In addition, these criteria facilitate straightforward assessment of data quality that could provide guidance for CEST MR protocols in terms of SNR. Insights were applied to achieve a robust denoising of highly sampled low power Z-spectra of the human brain at 3 and 7 T. The median criterion provided the best estimation for the optimal number of components consistently for all three investigated artificial noise levels. Application of the denoising technique to in vivo data revealed a considerable increase in image quality for the amide and rNOE contrast with a considerable SNR gain. At 7 T the denoising capability was quantified to be comparable or even superior to an averaging of six measurements. The proposed denoising algorithm enables an efficient and robust denoising of CEST data by combining PCA with appropriate data-driven truncation criteria. With this generally applicable technique at hand, small CEST effects can be reliably detected without the need for repeated measurements.
Collapse
Affiliation(s)
- Johannes Breitling
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Max-Planck-Institute for Nuclear Physics, Heidelberg, Germany
- Faculty of Physics and Astronomy, University of Heidelberg, Heidelberg, Germany
| | - Anagha Deshmane
- Department of High-field Magnetic Resonance, Max-Planck-Institute for Biological Cybernetics, Tuebingen, Germany
| | - Steffen Goerke
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Andreas Korzowski
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Kai Herz
- Department of High-field Magnetic Resonance, Max-Planck-Institute for Biological Cybernetics, Tuebingen, Germany
- IMPRS for Cognitive and Systems Neuroscience, University of Tuebingen, Tuebingen, Germany
| | - Mark E Ladd
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Faculty of Physics and Astronomy, University of Heidelberg, Heidelberg, Germany
- Faculty of Medicine, University of Heidelberg, Heidelberg, Germany
| | - Klaus Scheffler
- Department of High-field Magnetic Resonance, Max-Planck-Institute for Biological Cybernetics, Tuebingen, Germany
- Department of Biomedical Magnetic Resonance, University of Tuebingen, Germany
| | - Peter Bachert
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Faculty of Physics and Astronomy, University of Heidelberg, Heidelberg, Germany
| | - Moritz Zaiss
- Department of High-field Magnetic Resonance, Max-Planck-Institute for Biological Cybernetics, Tuebingen, Germany
| |
Collapse
|
26
|
Lin Y, Luo X, Yu L, Zhang Y, Zhou J, Jiang Y, Zhang C, Zhang J, Li C, Chen M. Amide proton transfer-weighted MRI for predicting histological grade of hepatocellular carcinoma: comparison with diffusion-weighted imaging. Quant Imaging Med Surg 2019; 9:1641-1651. [PMID: 31728308 DOI: 10.21037/qims.2019.08.07] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
Background Hepatocellular carcinoma (HCC) is the most common primary malignant tumor of the liver, preoperative grading of HCC is of great clinical significance. Amide proton transfer-weighted (APTw) imaging, as a novel contrast mechanism in the field of molecular imaging, provided new diagnostic ideas for the grading of HCC. Methods Between May 2017 and April 2018, 32 consecutive patients with pathologically confirmed HCC were enrolled, including 19 high-grade HCCs and 13 low-grade HCCs. DWI and APTw scanning was performed on a 3T MRI scanner. Two observers drew regions of interest independently by referring to the axial T2-weighted imaging, and APTw and apparent diffusion coefficient (ADC) values were obtained. Inter- and intra-observer agreements were assessed with the intraclass correlation coefficients (ICCs). The independent sample t test was used to compare the APTw and ADC values between the high- and low-grade HCC tumor parenchyma. The receiver operating characteristic curve was used to analyze the diagnostic efficacy of high- from low-grade HCC tumors. Spearman correlation analysis was used to assess the relationship between APTw and ADC values and HCC histological grades. Results There were significant differences between the APTw or ADC values for the high- and low-grade HCCs (P=0.034 and 0.010). Both APTw and DWI had good diagnostic performance in differentiating the high- from the low-grade HCCs, with areas under the curves of 0.814 and 0.745, respectively. Moderate correlations existed between APTw values and histological grades (r=0.534; P=0.002), as well as ADC values and histological grades (r=-0.417; P=0.018). Conclusions The APTw imaging is a useful imaging biomarker that complements DWI for the more accurate and comprehensive HCC characterization.
Collapse
Affiliation(s)
- Yue Lin
- Department of Radiology, Beijing Hospital, National Center of Gerontology, Beijing 100730, China.,Graduate School of Peking Union Medical College, Beijing 100730, China
| | - Xiaojie Luo
- Department of Radiology, Beijing Hospital, National Center of Gerontology, Beijing 100730, China
| | - Lu Yu
- Department of Radiology, Beijing Hospital, National Center of Gerontology, Beijing 100730, China.,Graduate School of Peking Union Medical College, Beijing 100730, China
| | - Yi Zhang
- Center for Brain Imaging Science and Technology, Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou 310058, China
| | - Jinyuan Zhou
- Department of Radiology, Johns Hopkins University, Baltimore, MD, USA
| | - Yuwei Jiang
- Department of Radiology, Beijing Hospital, National Center of Gerontology, Beijing 100730, China
| | - Chen Zhang
- Department of Radiology, Beijing Hospital, National Center of Gerontology, Beijing 100730, China
| | - Jintao Zhang
- Department of Radiology, Beijing Hospital, National Center of Gerontology, Beijing 100730, China
| | - Chunmei Li
- Department of Radiology, Beijing Hospital, National Center of Gerontology, Beijing 100730, China
| | - Min Chen
- Department of Radiology, Beijing Hospital, National Center of Gerontology, Beijing 100730, China.,Graduate School of Peking Union Medical College, Beijing 100730, China
| |
Collapse
|
27
|
Knowles BR, Friedrich F, Fischer C, Paech D, Ladd ME. Beyond T2 and 3T: New MRI techniques for clinicians. Clin Transl Radiat Oncol 2019; 18:87-97. [PMID: 31341982 PMCID: PMC6630188 DOI: 10.1016/j.ctro.2019.04.009] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2019] [Revised: 04/11/2019] [Accepted: 04/11/2019] [Indexed: 12/12/2022] Open
Abstract
Technological advances in Magnetic Resonance Imaging (MRI) in terms of field strength and hybrid MR systems have led to improvements in tumor imaging in terms of anatomy and functionality. This review paper discusses the applications of such advances in the field of radiation oncology with regards to treatment planning, therapy guidance and monitoring tumor response and predicting outcome.
Collapse
Affiliation(s)
- Benjamin R. Knowles
- Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Florian Friedrich
- Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Department of Physics and Astronomy, University of Heidelberg, Heidelberg, Germany
| | - Carola Fischer
- Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Department of Physics and Astronomy, University of Heidelberg, Heidelberg, Germany
| | - Daniel Paech
- Department of Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Mark E. Ladd
- Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Department of Physics and Astronomy, University of Heidelberg, Heidelberg, Germany
| |
Collapse
|
28
|
Krikken E, van der Kemp WJ, Khlebnikov V, van Dalen T, Los M, van Laarhoven HW, Luijten PR, van den Bosch MA, Klomp DW, Wijnen JP. Contradiction between amide-CEST signal and pH in breast cancer explained with metabolic MRI. NMR IN BIOMEDICINE 2019; 32:e4110. [PMID: 31136039 PMCID: PMC6772111 DOI: 10.1002/nbm.4110] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/01/2019] [Revised: 04/08/2019] [Accepted: 04/09/2019] [Indexed: 06/09/2023]
Abstract
PURPOSE Metabolic MRI is a noninvasive technique that can give new insights into understanding cancer metabolism and finding biomarkers to evaluate or monitor treatment plans. Using this technique, a previous study has shown an increase in pH during neoadjuvant chemotherapy (NAC) treatment, while recent observation in a different study showed a reduced amide proton transfer (APT) signal during NAC treatment (negative relation). These findings are counterintuitive, given the known intrinsic positive relation of APT signal to pH. METHODS In this study we combined APT MRI and 31 P-MRSI measurements to unravel the relation between the APT signal and pH in breast cancer. Twenty-two breast cancer patients were scanned with a 7 T MRI before and after the first cycle of NAC treatment. pH was determined by the chemical shift of inorganic phosphate (Pi). RESULTS While APT signals have a positive relation to pH and amide content, we observed a direct negative linear correlation between APT signals and pH in breast tumors in vivo. CONCLUSIONS As differentiation of cancer stages was confirmed by observation of a linear correlation between cell proliferation marker PE/Pi (phosphoethanolamine over inorganic phosphate) and pH in the tumor, our data demonstrates that the concentration of mobile proteins likely supersedes the contribution of the exchange rate to the APT signal.
Collapse
Affiliation(s)
- Erwin Krikken
- Department of RadiologyUniversity Medical Center UtrechtUtrechtThe Netherlands
| | | | - Vitaliy Khlebnikov
- Department of RadiologyUniversity Medical Center UtrechtUtrechtThe Netherlands
| | | | - Maartje Los
- Department of Medical OncologySt. Antonius ZiekenhuisNieuwegein/UtrechtThe Netherlands
| | - Hanneke W.M. van Laarhoven
- Department of Medical Oncology, Academic Medical Centre AmsterdamCancer Center AmsterdamAmsterdamThe Netherlands
| | - Peter R. Luijten
- Department of RadiologyUniversity Medical Center UtrechtUtrechtThe Netherlands
| | | | - Dennis W.J. Klomp
- Department of RadiologyUniversity Medical Center UtrechtUtrechtThe Netherlands
| | - Jannie P. Wijnen
- Department of RadiologyUniversity Medical Center UtrechtUtrechtThe Netherlands
| |
Collapse
|
29
|
Zhang Y, Heo HY, Jiang S, Zhou J, Bottomley PA. Fast 3D chemical exchange saturation transfer imaging with variably-accelerated sensitivity encoding (vSENSE). Magn Reson Med 2019; 82:2046-2061. [PMID: 31264278 DOI: 10.1002/mrm.27881] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2019] [Revised: 05/31/2019] [Accepted: 06/02/2019] [Indexed: 12/20/2022]
Abstract
PURPOSE To extend the variably-accelerated sensitivity encoding (vSENSE) method from 2D to 3D for fast chemical exchange saturation transfer (CEST) imaging, and prospectively implement it for clinical MRI. METHODS The CEST scans were acquired from 7 normal volunteers and 15 brain tumor patients using a 3T clinical scanner. The 2D and 3D "artifact suppression" (AS) vSENSE algorithms were applied to generate sensitivity maps from a first scan acquired with conventional SENSE-accelerated 2D and 3D CEST data. The AS sensitivity maps were then applied to reconstruct the other CEST frames at higher acceleration factors. Both retrospective and prospective acceleration in phase-encoding and slice-encoding dimensions were implemented. RESULTS Applying the 2D AS vSENSE algorithm to a 2-fold undersampled 3.5-ppm CEST frame halved the scan time of conventional SENSE, while generating essentially identical reconstruction errors (p ≈ 1.0). The 3D AS vSENSE algorithm permitted prospective acceleration by up to 8-fold, in total, from phase-encoding and slice-encoding directions for individual source CEST images, and an overall speed-up in scan time of 5-fold. The resulting vSENSE-accelerated amide proton transfer-weighted images agreed with conventional 2-fold-accelerated SENSE CEST results in brain tumor patients and healthy volunteers. Importantly, the vSENSE method eliminated unfolding artifacts in the slice-encoding direction that compromised conventional SENSE CEST scans. CONCLUSION The vSENSE method can be extended to 3D CEST imaging to provide higher acceleration factors than conventional SENSE without compromising accuracy.
Collapse
Affiliation(s)
- 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.,Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Maryland
| | - Hye-Young Heo
- Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Maryland
| | - Shanshan Jiang
- Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Maryland
| | - Jinyuan Zhou
- Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Maryland
| | - Paul A Bottomley
- Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Maryland
| |
Collapse
|
30
|
Chan RW, Myrehaug S, Stanisz GJ, Sahgal A, Lau AZ. Quantification of pulsed saturation transfer at 1.5T and 3T. Magn Reson Med 2019; 82:1684-1699. [DOI: 10.1002/mrm.27856] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2019] [Revised: 05/12/2019] [Accepted: 05/21/2019] [Indexed: 12/22/2022]
Affiliation(s)
- Rachel W. Chan
- Department of Physical Sciences Sunnybrook Research Institute Toronto Canada
| | - Sten Myrehaug
- Department of Radiation Oncology Sunnybrook Health Sciences Centre Toronto Canada
- Department of Radiation Oncology University of Toronto Toronto Canada
| | - Greg J. Stanisz
- Department of Physical Sciences Sunnybrook Research Institute Toronto Canada
- Department of Medical Biophysics University of Toronto Toronto Canada
- Department of Neurosurgery and Pediatric Neurosurgery Medical University Lublin Poland
| | - Arjun Sahgal
- Department of Physical Sciences Sunnybrook Research Institute Toronto Canada
- Department of Radiation Oncology Sunnybrook Health Sciences Centre Toronto Canada
- Department of Radiation Oncology University of Toronto Toronto Canada
| | - Angus Z. Lau
- Department of Physical Sciences Sunnybrook Research Institute Toronto Canada
- Department of Medical Biophysics University of Toronto Toronto Canada
| |
Collapse
|
31
|
Mehrabian H, Detsky J, Soliman H, Sahgal A, Stanisz GJ. Advanced Magnetic Resonance Imaging Techniques in Management of Brain Metastases. Front Oncol 2019; 9:440. [PMID: 31214496 PMCID: PMC6558019 DOI: 10.3389/fonc.2019.00440] [Citation(s) in RCA: 38] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2018] [Accepted: 05/08/2019] [Indexed: 01/18/2023] Open
Abstract
Brain metastases are the most common intracranial tumors and occur in 20–40% of all cancer patients. Lung cancer, breast cancer, and melanoma are the most frequent primary cancers to develop brain metastases. Treatment options include surgical resection, whole brain radiotherapy, stereotactic radiosurgery, and systemic treatment such as targeted or immune therapy. Anatomical magnetic resonance imaging (MRI) of the tumor (in particular post-Gadolinium T1-weighted and T2-weighted FLAIR) provide information about lesion morphology and structure, and are routinely used in clinical practice for both detection and treatment response evaluation for brain metastases. Advanced MRI biomarkers that characterize the cellular, biophysical, micro-structural and metabolic features of tumors have the potential to improve the management of brain metastases from early detection and diagnosis, to evaluating treatment response. Magnetic resonance spectroscopy (MRS), chemical exchange saturation transfer (CEST), quantitative magnetization transfer (qMT), diffusion-based tissue microstructure imaging, trans-membrane water exchange mapping, and magnetic susceptibility weighted imaging (SWI) are advanced MRI techniques that will be reviewed in this article as they pertain to brain metastases.
Collapse
Affiliation(s)
- Hatef Mehrabian
- Physical Sciences, Sunnybrook Research Institute, Toronto, ON, Canada.,Radiology and Biomedical Imaging, University of California, San Francisco (UCSF), San Francisco, CA, United States
| | - Jay Detsky
- Radiation Oncology, Sunnybrook Health Sciences Centre, Toronto, ON, Canada.,Radiation Oncology, University of Toronto, Toronto, ON, Canada
| | - Hany Soliman
- Radiation Oncology, Sunnybrook Health Sciences Centre, Toronto, ON, Canada.,Radiation Oncology, University of Toronto, Toronto, ON, Canada
| | - Arjun Sahgal
- Physical Sciences, Sunnybrook Research Institute, Toronto, ON, Canada.,Radiation Oncology, Sunnybrook Health Sciences Centre, Toronto, ON, Canada.,Radiation Oncology, University of Toronto, Toronto, ON, Canada
| | - Greg J Stanisz
- Physical Sciences, Sunnybrook Research Institute, Toronto, ON, Canada.,Department of Neurosurgery and Pediatric Neurosurgery, Medical University, Lublin, Poland
| |
Collapse
|
32
|
Goerke S, Soehngen Y, Deshmane A, Zaiss M, Breitling J, Boyd PS, Herz K, Zimmermann F, Klika KD, Schlemmer H, Paech D, Ladd ME, Bachert P. Relaxation‐compensated APT and rNOE CEST‐MRI of human brain tumors at 3 T. Magn Reson Med 2019; 82:622-632. [DOI: 10.1002/mrm.27751] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2019] [Revised: 02/27/2019] [Accepted: 03/02/2019] [Indexed: 12/12/2022]
Affiliation(s)
- Steffen Goerke
- Division of Medical Physics in Radiology German Cancer Research Center Heidelberg Germany
| | - Yannick Soehngen
- Division of Medical Physics in Radiology German Cancer Research Center Heidelberg Germany
- Faculty of Physics and Astronomy University of Heidelberg Heidelberg Germany
| | - Anagha Deshmane
- Department of High‐Field Magnetic Resonance Max‐Planck‐Institute for Biological Cybernetics Tübingen Germany
| | - Moritz Zaiss
- Department of High‐Field Magnetic Resonance Max‐Planck‐Institute for Biological Cybernetics Tübingen Germany
| | - Johannes Breitling
- Division of Medical Physics in Radiology German Cancer Research Center Heidelberg Germany
- Faculty of Physics and Astronomy University of Heidelberg Heidelberg Germany
- Max‐Planck‐Institute for Nuclear Physics Heidelberg Germany
| | - Philip S. Boyd
- Division of Medical Physics in Radiology German Cancer Research Center Heidelberg Germany
- Faculty of Physics and Astronomy University of Heidelberg Heidelberg Germany
| | - Kai Herz
- Department of High‐Field Magnetic Resonance Max‐Planck‐Institute for Biological Cybernetics Tübingen Germany
| | - Ferdinand Zimmermann
- Division of Medical Physics in Radiology German Cancer Research Center Heidelberg Germany
- Faculty of Physics and Astronomy University of Heidelberg Heidelberg Germany
| | - Karel D. Klika
- Molecular Structure Analysis German Cancer Research Center Heidelberg Germany
| | - Heinz‐Peter Schlemmer
- Department of Radiology German Cancer Research Center Heidelberg Germany
- Faculty of Medicine University of Heidelberg Heidelberg Germany
| | - Daniel Paech
- Department of Radiology German Cancer Research Center Heidelberg Germany
| | - Mark E. Ladd
- Division of Medical Physics in Radiology German Cancer Research Center Heidelberg Germany
- Faculty of Physics and Astronomy University of Heidelberg Heidelberg Germany
- Faculty of Medicine University of Heidelberg Heidelberg Germany
| | - Peter Bachert
- Division of Medical Physics in Radiology German Cancer Research Center Heidelberg Germany
- Faculty of Physics and Astronomy University of Heidelberg Heidelberg Germany
| |
Collapse
|
33
|
Meissner J, Korzowski A, Regnery S, Goerke S, Breitling J, Floca RO, Debus J, Schlemmer H, Ladd ME, Bachert P, Adeberg S, Paech D. Early response assessment of glioma patients to definitive chemoradiotherapy using chemical exchange saturation transfer imaging at 7 T. J Magn Reson Imaging 2019; 50:1268-1277. [DOI: 10.1002/jmri.26702] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2018] [Revised: 02/15/2019] [Accepted: 02/15/2019] [Indexed: 12/17/2022] Open
Affiliation(s)
- Jan‐Eric Meissner
- Division of Medical Physics in RadiologyGerman Cancer Research Center (DKFZ) Heidelberg Germany
| | - Andreas Korzowski
- Division of Medical Physics in RadiologyGerman Cancer Research Center (DKFZ) Heidelberg Germany
| | - Sebastian Regnery
- Department of Radiation OncologyUniversity Hospital Heidelberg Heidelberg Germany
| | - Steffen Goerke
- Division of Medical Physics in RadiologyGerman Cancer Research Center (DKFZ) Heidelberg Germany
| | - Johannes Breitling
- Division of Medical Physics in RadiologyGerman Cancer Research Center (DKFZ) Heidelberg Germany
- Faculty of Physics and AstronomyUniversity of Heidelberg Heidelberg Germany
- MPI for Nuclear PhysicsMax‐Planck‐Society Heidelberg Germany
| | - Ralf Omar Floca
- Division of Medical Image ComputingGerman Cancer Research Center (DKFZ) Heidelberg Germany
- Heidelberg Institute of Radiation Oncology (HIRO)National Center for Radiation Research in Oncology (NCRO) Heidelberg Germany
| | - Jürgen Debus
- Department of Radiation OncologyUniversity Hospital Heidelberg Heidelberg Germany
| | | | - Mark Edward Ladd
- Division of Medical Physics in RadiologyGerman Cancer Research Center (DKFZ) Heidelberg Germany
- Faculty of Physics and AstronomyUniversity of Heidelberg Heidelberg Germany
- Faculty of MedicineUniversity of Heidelberg Heidelberg Germany
| | - Peter Bachert
- Division of Medical Physics in RadiologyGerman Cancer Research Center (DKFZ) Heidelberg Germany
- Faculty of Physics and AstronomyUniversity of Heidelberg Heidelberg Germany
| | - Sebastian Adeberg
- Department of Radiation OncologyUniversity Hospital Heidelberg Heidelberg Germany
- Heidelberg Institute of Radiation Oncology (HIRO)National Center for Radiation Research in Oncology (NCRO) Heidelberg Germany
| | - Daniel Paech
- Division of RadiologyGerman Cancer Research Center (DKFZ) Heidelberg Germany
| |
Collapse
|
34
|
Paech D, Dreher C, Regnery S, Meissner JE, Goerke S, Windschuh J, Oberhollenzer J, Schultheiss M, Deike-Hofmann K, Bickelhaupt S, Radbruch A, Zaiss M, Unterberg A, Wick W, Bendszus M, Bachert P, Ladd ME, Schlemmer HP. Relaxation-compensated amide proton transfer (APT) MRI signal intensity is associated with survival and progression in high-grade glioma patients. Eur Radiol 2019; 29:4957-4967. [PMID: 30809720 DOI: 10.1007/s00330-019-06066-2] [Citation(s) in RCA: 47] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2018] [Revised: 12/28/2018] [Accepted: 02/04/2019] [Indexed: 12/30/2022]
Abstract
OBJECTIVES The purpose of this study was to investigate the association of relaxation-compensated chemical exchange saturation transfer (CEST) MRI with overall survival (OS) and progression-free survival (PFS) in newly diagnosed high-grade glioma (HGG) patients. METHODS Twenty-six patients with newly diagnosed high-grade glioma (WHO grades III-IV) were included in this prospective IRB-approved study. CEST MRI was performed on a 7.0-T whole-body scanner. Association of patient OS/PFS with relaxation-compensated CEST MRI (amide proton transfer (APT), relayed nuclear Overhauser effect (rNOE)/NOE, downfield-rNOE-suppressed APT (dns-APT)) and diffusion-weighted imaging (apparent diffusion coefficient) were assessed using the univariate Cox proportional hazards regression model. Hazard ratios (HRs) and corresponding 95% confidence intervals were calculated. Furthermore, OS/PFS association with clinical parameters (age, gender, O6-methylguanine-DNA methyltransferase (MGMT) promotor methylation status, and therapy: biopsy + radio-chemotherapy vs. debulking surgery + radio-chemotherapy) were tested accordingly. RESULTS Relaxation-compensated APT MRI was significantly correlated with patient OS (HR = 3.15, p = 0.02) and PFS (HR = 1.83, p = 0.009). The strongest association with PFS was found for the dns-APT metric (HR = 2.61, p = 0.002). These results still stand for the relaxation-compensated APT contrasts in a homogenous subcohort of n = 22 glioblastoma patients with isocitrate dehydrogenase (IDH) wild-type status. Among the tested clinical parameters, patient age (HR = 1.1, p = 0.001) and therapy (HR = 3.68, p = 0.026) were significant for OS; age additionally for PFS (HR = 1.04, p = 0.048). CONCLUSION Relaxation-compensated APT MRI signal intensity is associated with overall survival and progression-free survival in newly diagnosed, previously untreated glioma patients and may, therefore, help to customize treatment and response monitoring in the future. KEY POINTS • Amide proton transfer (APT) MRI signal intensity is associated with overall survival and progression in glioma patients. • Relaxation compensation enhances the information value of APT MRI in tumors. • Chemical exchange saturation transfer (CEST) MRI may serve as a non-invasive biomarker to predict prognosis and customize treatment.
Collapse
Affiliation(s)
- Daniel Paech
- Division of Radiology, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120, Heidelberg, Germany.
| | - Constantin Dreher
- Division of Radiology, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120, Heidelberg, Germany
| | - Sebastian Regnery
- Division of Radiology, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120, Heidelberg, Germany.,Department of Radiation Oncology, University Hospital Heidelberg, Im Neuenheimer Feld 400, 69120, Heidelberg, Germany
| | - Jan-Eric Meissner
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120, Heidelberg, Germany
| | - Steffen Goerke
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120, Heidelberg, Germany
| | - Johannes Windschuh
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120, Heidelberg, Germany
| | - Johanna Oberhollenzer
- Division of Radiology, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120, Heidelberg, Germany
| | - Miriam Schultheiss
- Division of Radiology, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120, Heidelberg, Germany
| | - Katerina Deike-Hofmann
- Division of Radiology, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120, Heidelberg, Germany
| | - Sebastian Bickelhaupt
- Division of Radiology, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120, Heidelberg, Germany
| | - Alexander Radbruch
- Division of Radiology, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120, Heidelberg, Germany.,Department of Radiology, University Hospital Essen, Essen, Germany
| | - Moritz Zaiss
- Magnetic Resonance Center, Max-Planck-Institute for Biological Cybernetics, Tuebingen, Germany
| | - Andreas Unterberg
- Department of Neurosurgery, University Hospital Heidelberg, Im Neuenheimer Feld 400, 69120, Heidelberg, Germany
| | - Wolfgang Wick
- Department of Neurology, University Hospital Heidelberg, Im Neuenheimer Feld 400, 69120, Heidelberg, Germany
| | - Martin Bendszus
- Department of Neuroradiology, University Hospital Heidelberg, Im Neuenheimer Feld 400, 69120, Heidelberg, Germany
| | - Peter Bachert
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120, Heidelberg, Germany
| | - Mark E Ladd
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120, Heidelberg, Germany.,Faculty 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), Im Neuenheimer Feld 280, 69120, Heidelberg, Germany
| |
Collapse
|
35
|
Zhou J, Heo HY, Knutsson L, van Zijl PCM, Jiang S. APT-weighted MRI: Techniques, current neuro applications, and challenging issues. J Magn Reson Imaging 2019; 50:347-364. [PMID: 30663162 DOI: 10.1002/jmri.26645] [Citation(s) in RCA: 199] [Impact Index Per Article: 39.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2018] [Revised: 12/26/2018] [Accepted: 12/27/2018] [Indexed: 02/06/2023] Open
Abstract
Amide proton transfer-weighted (APTw) imaging is a molecular MRI technique that generates image contrast based predominantly on the amide protons in mobile cellular proteins and peptides that are endogenous in tissue. This technique, the most studied type of chemical exchange saturation transfer imaging, has been used successfully for imaging of protein content and pH, the latter being possible due to the strong dependence of the amide proton exchange rate on pH. In this article we briefly review the basic principles and recent technical advances of APTw imaging, which is showing promise clinically, especially for characterizing brain tumors and distinguishing recurrent tumor from treatment effects. Early applications of this approach to stroke, Alzheimer's disease, Parkinson's disease, multiple sclerosis, and traumatic brain injury are also illustrated. Finally, we outline the technical challenges for clinical APT-based imaging and discuss several controversies regarding the origin of APTw imaging signals in vivo. Level of Evidence: 3 Technical Efficacy Stage: 3 J. Magn. Reson. Imaging 2019;50:347-364.
Collapse
Affiliation(s)
- Jinyuan Zhou
- Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Maryland, USA.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Hye-Young Heo
- Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Maryland, USA.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Linda Knutsson
- Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Maryland, USA.,Department of Medical Radiation Physics, Lund University, Lund, Sweden
| | - Peter C M van Zijl
- Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Maryland, USA.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Shanshan Jiang
- Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Maryland, USA.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| |
Collapse
|
36
|
Deshmane A, Zaiss M, Lindig T, Herz K, Schuppert M, Gandhi C, Bender B, Ernemann U, Scheffler K. 3D gradient echo snapshot CEST MRI with low power saturation for human studies at 3T. Magn Reson Med 2018; 81:2412-2423. [PMID: 30431179 PMCID: PMC6718050 DOI: 10.1002/mrm.27569] [Citation(s) in RCA: 51] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2018] [Revised: 09/21/2018] [Accepted: 09/25/2018] [Indexed: 01/11/2023]
Abstract
Purpose For clinical implementation, a chemical exchange saturation transfer (CEST) imaging sequence must be fast, with high signal‐to‐noise ratio (SNR), 3D coverage, and produce robust contrast. However, spectrally selective CEST contrast requires dense sampling of the Z‐spectrum, which increases scan duration. This article proposes a compromise: using a 3D snapshot gradient echo (GRE) readout with optimized CEST presaturation, sampling, and postprocessing, highly resolved Z‐spectroscopy at 3T is made possible with 3D coverage at almost no extra time cost. Methods A 3D snapshot CEST sequence was optimized for low‐power CEST MRI at 3T. Pulsed saturation was optimized for saturation power and saturation duration. Spectral sampling and postprocessing (B0 correction, denoising) was optimized for spectrally selective Lorentzian CEST effect extraction. Reproducibility was demonstrated in 3 healthy volunteers and feasibility was shown in 1 tumor patient. Results Low‐power saturation was achieved by a train of 80 pulses of duration tp = 20 ms (total saturation time tsat = 3.2 seconds at 50% duty cycle) with B1 = 0.6 μT at 54 irradiation frequency offsets. With the 3D snapshot CEST sequence, a 180 × 220 × 54 mm field of view was acquired in 7 seconds per offset. Spectrally selective CEST effects at +3.5 and –3.5 ppm were quantified using multi‐Lorentzian fitting. Reproducibility was high with an intersubject coefficient of variation below 10% in CEST contrasts. Amide and nuclear overhauser effect CEST effects showed similar correlations in tumor and necrosis as show in previous ultra‐high field work. Conclusion A sophisticated CEST tool ready for clinical application was developed and tested for feasibility.
Collapse
Affiliation(s)
- Anagha Deshmane
- High‐field Magnetic Resonance Center, Max Planck Institute for Biological CyberneticsTübingenGermany
| | - Moritz Zaiss
- High‐field Magnetic Resonance Center, Max Planck Institute for Biological CyberneticsTübingenGermany
| | - Tobias Lindig
- Department of Diagnostic and Interventional NeuroradiologyUniversity Clinics TübingenTübingenGermany
| | - Kai Herz
- High‐field Magnetic Resonance Center, Max Planck Institute for Biological CyberneticsTübingenGermany
| | - Mark Schuppert
- High‐field Magnetic Resonance Center, Max Planck Institute for Biological CyberneticsTübingenGermany
| | - Chirayu Gandhi
- High‐field Magnetic Resonance Center, Max Planck Institute for Biological CyberneticsTübingenGermany
| | - Benjamin Bender
- Department of Diagnostic and Interventional NeuroradiologyUniversity Clinics TübingenTübingenGermany
| | - Ulrike Ernemann
- Department of Diagnostic and Interventional NeuroradiologyUniversity Clinics TübingenTübingenGermany
| | - Klaus Scheffler
- High‐field Magnetic Resonance Center, Max Planck Institute for Biological CyberneticsTübingenGermany
- Department of Biomedical Magnetic ResonanceEberhard‐Karls University TübingenTübingenGermany
| |
Collapse
|
37
|
Differentiation of Normal and Radioresistant Prostate Cancer Xenografts Using Magnetization Transfer-Prepared MRI. Sci Rep 2018; 8:10447. [PMID: 29992999 PMCID: PMC6041323 DOI: 10.1038/s41598-018-28731-0] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2018] [Accepted: 06/27/2018] [Indexed: 01/31/2023] Open
Abstract
The ability of MRI to differentiate between normal and radioresistant cancer was investigated in prostate tumour xenografts in mice. Specifically, the process of magnetization exchange between water and other molecules was studied. It was found that magnetization transfer from semisolid macromolecules (MT) and chemical exchange saturation transfer (CEST) combined were significantly different between groups (p < 0.01). Further, the T2 relaxation of the semisolid macromolecular pool (T2,B), a parameter specific to MT, was found to be significantly different (p < 0.01). Also significantly different were the rNOE contributions associated with methine groups at -0.9 ppm with a saturation B1 of 0.5 µT (p < 0.01) and with other aliphatic groups at -3.3 ppm with 0.5 and 2 µT (both p < 0.05). Independently, using a live-cell metabolic assay, normal cells were found to have a greater metabolic rate than radioresistant ones. Thus, MRI provides a novel, in vivo method to quantify the metabolic rate of tumours and predict their radiosensitivity.
Collapse
|
38
|
Regnery S, Adeberg S, Dreher C, Oberhollenzer J, Meissner JE, Goerke S, Windschuh J, Deike-Hofmann K, Bickelhaupt S, Zaiss M, Radbruch A, Bendszus M, Wick W, Unterberg A, Rieken S, Debus J, Bachert P, Ladd M, Schlemmer HP, Paech D. Chemical exchange saturation transfer MRI serves as predictor of early progression in glioblastoma patients. Oncotarget 2018; 9:28772-28783. [PMID: 29983895 PMCID: PMC6033360 DOI: 10.18632/oncotarget.25594] [Citation(s) in RCA: 43] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2018] [Accepted: 05/24/2018] [Indexed: 12/03/2022] Open
Abstract
PURPOSE To prospectively investigate chemical exchange saturation transfer (CEST) MRI in glioblastoma patients as predictor of early tumor progression after first-line treatment. EXPERIMENTAL DESIGN Twenty previously untreated glioblastoma patients underwent CEST MRI employing a 7T whole-body scanner. Nuclear Overhauser effect (NOE) as well as amide proton transfer (APT) CEST signals were isolated using Lorentzian difference (LD) analysis and relaxation compensated by the apparent exchange-dependent relaxation rate (AREX) evaluation. Additionally, NOE-weighted asymmetric magnetic transfer ratio (MTRasym) and downfield-NOE-suppressed APT (dns-APT) were calculated. Patient response to consecutive treatment was determined according to the RANO criteria. Mean signal intensities of each contrast in the whole tumor area were compared between early-progressive and stable disease. RESULTS Pre-treatment tumor signal intensity differed significantly regarding responsiveness to first-line therapy in NOE-LD (p = 0.0001), NOE-weighted MTRasym (p = 0.0186) and dns-APT (p = 0.0328) contrasts. Hence, significant prediction of early progression was possible employing NOE-LD (AUC = 0.98, p = 0.0005), NOE-weighted MTRasym (AUC = 0.83, p = 0.0166) and dns-APT (AUC = 0.80, p = 0.0318). The NOE-LD provided the highest sensitivity (91%) and specificity (100%). CONCLUSIONS CEST derived contrasts, particularly NOE-weighted imaging and dns-APT, yielded significant predictors of early progression after fist-line therapy in glioblastoma. Therefore, CEST MRI might be considered as non-invasive tool for customization of treatment in the future.
Collapse
Affiliation(s)
- Sebastian Regnery
- Department of Radiation Oncology, University Hospital Heidelberg, Heidelberg, Germany
- German Cancer Research Center (DKFZ), Division of Radiology, Heidelberg, Germany
| | - Sebastian Adeberg
- German Cancer Research Center (DKFZ), HIRO (Heidelberg Institute for Radiation Oncology), Heidelberg, Germany
| | - Constantin Dreher
- German Cancer Research Center (DKFZ), Division of Radiology, Heidelberg, Germany
| | | | - Jan-Eric Meissner
- German Cancer Research Center (DKFZ), Division of Medical Physics in Radiology, Heidelberg, Germany
| | - Steffen Goerke
- German Cancer Research Center (DKFZ), Division of Medical Physics in Radiology, Heidelberg, Germany
| | - Johannes Windschuh
- German Cancer Research Center (DKFZ), Division of Medical Physics in Radiology, Heidelberg, Germany
| | | | | | | | - Alexander Radbruch
- German Cancer Research Center (DKFZ), Division of Radiology, Heidelberg, Germany
| | - Martin Bendszus
- Department of Neuroradiology, University Hospital Heidelberg, Heidelberg, Germany
| | - Wolfgang Wick
- Department of Neurology, University Hospital Heidelberg, Heidelberg, Germany
| | - Andreas Unterberg
- Department of Neurosurgery, University Hospital Heidelberg, Heidelberg, Germany
| | - Stefan Rieken
- Department of Radiation Oncology, University Hospital Heidelberg, Heidelberg, Germany
| | - Jürgen Debus
- Department of Radiation Oncology, University Hospital Heidelberg, Heidelberg, Germany
| | - Peter Bachert
- German Cancer Research Center (DKFZ), Division of Medical Physics in Radiology, Heidelberg, Germany
| | - Mark Ladd
- German Cancer Research Center (DKFZ), Division of Medical Physics in Radiology, Heidelberg, Germany
- Faculty of Physics and Astronomy, University of Heidelberg, Heidelberg, Germany
- Faculty of Medicine, University of Heidelberg, Heidelberg, Germany
| | | | - Daniel Paech
- German Cancer Research Center (DKFZ), Division of Radiology, Heidelberg, Germany
| |
Collapse
|
39
|
Mehrabian H, Myrehaug S, Soliman H, Sahgal A, Stanisz GJ. Evaluation of Glioblastoma Response to Therapy With Chemical Exchange Saturation Transfer. Int J Radiat Oncol Biol Phys 2018; 101:713-723. [PMID: 29893279 DOI: 10.1016/j.ijrobp.2018.03.057] [Citation(s) in RCA: 36] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2017] [Revised: 03/02/2018] [Accepted: 03/27/2018] [Indexed: 11/25/2022]
Abstract
PURPOSE To monitor cellular and metabolic characteristics of glioblastoma (GBM) over the course of standard 6-week chemoradiation treatment with chemical exchange saturation transfer (CEST)-MRI; and to identify the earliest time point CEST could determine subsequent therapeutic response. METHODS AND MATERIALS Nineteen patients with newly diagnosed GBM were recruited, and CEST-MRI was acquired immediately before (Day0), 2 weeks (Day14) and 4 weeks (Day28) into treatment, and 1 month after the end of treatment (Day70). Several CEST metrics, including magnetization transfer ratio and area under the curve of CEST peaks corresponding to nuclear Overhauser effect (NOE) and amide protons (MTRNOE, MTRAmide, CESTNOE, and CESTAmide respectively), magnetization transfer (MT), and direct water effect were investigated. Lack of early progression was determined as no increase in tumor size or worsening of clinical symptoms according to routine post-chemoradiation serial structural MRI. RESULTS Changes in MTRNOE (nonprogressors = 1.35 ± 0.18, progressors = 0.97 ± 0.22, P = .006) and MTRAmide (nonprogressors = 1.25 ± 0.17, progressors = 0.99 ± 0.10, P = .017) between baseline (Day0) and Day14 resulted in the best separation of nonprogressors from progressors. Moreover, the baseline (Day0) MTRNOE (nonprogressors = 6.5% ± 1.6%, progressors = 9.1% ± 2.1%, P = .015), MTRAmide (nonprogressors = 6.7% ± 1.7%, progressors = 8.9% ± 1.9%, P = .028), MT (nonprogressors = 3.8% ± 0.9%, progressors = 5.4% ± 1.4%, P = .019), and CESTNOE (nonprogressors = 4.1%ċHz ± 1.7%ċHz, progressors = 6.1%ċHz ± 1.9%ċHz, P = .044) were able to identify progressors even before the start of the treatment. CONCLUSIONS Chemical exchange saturation transfer (CEST) provides imaging-based biomarkers of GBM response as early as 2 weeks into the treatment. Certain CEST metrics can characterize tumor aggressiveness and identify early progressors even before beginning the treatment. Such an early biomarker of response may allow for adjusting the GBM treatment plan for adaptive radiation therapy in early progressors and more confidently continuing standard adjuvant treatment for nonprogressors.
Collapse
Affiliation(s)
- Hatef Mehrabian
- Medical Biophysics, University of Toronto, Toronto, Ontario, Canada; Physical Sciences, Sunnybrook Research Institute, Toronto, Ontario, Canada.
| | - Sten Myrehaug
- Radiation Oncology, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada; Department of Radiation Oncology, University of Toronto, Toronto, Ontario, Canada
| | - Hany Soliman
- Radiation Oncology, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada; Department of Radiation Oncology, University of Toronto, Toronto, Ontario, Canada
| | - Arjun Sahgal
- Physical Sciences, Sunnybrook Research Institute, Toronto, Ontario, Canada; Radiation Oncology, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada; Department of Radiation Oncology, University of Toronto, Toronto, Ontario, Canada
| | - Greg J Stanisz
- Medical Biophysics, University of Toronto, Toronto, Ontario, Canada; Physical Sciences, Sunnybrook Research Institute, Toronto, Ontario, Canada; Department of Neurosurgery and Pediatric Neurosurgery, Medical University, Lublin, Poland
| |
Collapse
|
40
|
Mehrabian H, Lam WW, Myrehaug S, Sahgal A, Stanisz GJ. Glioblastoma (GBM) effects on quantitative MRI of contralateral normal appearing white matter. J Neurooncol 2018; 139:97-106. [PMID: 29594656 DOI: 10.1007/s11060-018-2846-0] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2017] [Accepted: 03/22/2018] [Indexed: 12/19/2022]
Abstract
PURPOSE The objective was to investigate (with quantitative MRI) whether the normal appearing white matter (NAWM) of glioblastoma (GBM) patients on the contralateral side (cNAWM) was different from NAWM of healthy controls. METHODS Thirteen patients with newly diagnosed GBM and nine healthy age-matched controls were MRI-scanned with quantitative magnetization transfer (qMT), chemical exchange saturation transfer (CEST), and transverse relaxation time (T2)-mapping. MRI scans were performed after surgery and before chemo-radiation treatment. Comprehensive qMT, CEST, T2 data were acquired. A two-pool MT model was fit to qMT data in transient state, to calculate MT model parameters [Formula: see text]. CEST signal was isolated by removing the contributions from the MT and direct water saturation, and CEST signal was calculated for Amide (CESTAmide), Amine (CESTAmine) and nuclear overhauser effect, NOE (CESTNOE). RESULTS There was no difference between GBM patients and normal controls in the qMT properties of the macromolecular pool [Formula: see text]. However, their free water pool spectrum was different (1/RaT2a,patient = 28.1 ± 3.9, 1/RaT2a,control = 25.0 ± 1.1, p = 0.03). This difference could be attributed to the difference in their T2 time ([Formula: see text] = 83 ± 4, [Formula: see text] = 88 ± 1, p = 0.004). CEST signals were statistically significantly different with the CESTAmide having the largest difference between the two cohorts (CESTAmide,patient = 2.8 ± 0.4, CESTAmide,control = 3.4 ± 0.5, p = 0.009). CONCLUSIONS CEST in cNAWM of GBM patients was lower than healthy controls which could be caused by modified brain metabolism due to tumor cell infiltration. There was no difference in MT properties of the patients and controls, however, the differences in free water pool properties were mainly due to reduced T2 in cNAWM of the patients (resulting from structural changes and increased cellularity).
Collapse
Affiliation(s)
- Hatef Mehrabian
- Medical Biophysics, University of Toronto, Toronto, ON, Canada. .,Radiology and Biomedical Imaging, University of California, San Francisco (UCSF), 1700 - 4th St., Suite BH 201, San Francisco, CA, 94158, USA.
| | - Wilfred W Lam
- Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Sten Myrehaug
- Radiation Oncology, Sunnybrook Health Sciences Centre, Toronto, ON, Canada.,Department of Radiation Oncology, University of Toronto, Toronto, ON, Canada
| | - Arjun Sahgal
- Physical Sciences, Sunnybrook Research Institute, Toronto, ON, Canada.,Radiation Oncology, Sunnybrook Health Sciences Centre, Toronto, ON, Canada.,Department of Radiation Oncology, University of Toronto, Toronto, ON, Canada
| | - Greg J Stanisz
- Medical Biophysics, University of Toronto, Toronto, ON, Canada.,Physical Sciences, Sunnybrook Research Institute, Toronto, ON, Canada.,Department of Neurosurgery and Pediatric Neurosurgery, Medical University, Lublin, Poland
| |
Collapse
|
41
|
Faruqi S, Tseng CL, Whyne C, Alghamdi M, Wilson J, Myrehaug S, Soliman H, Lee Y, Maralani P, Yang V, Fisher C, Sahgal A. Vertebral Compression Fracture After Spine Stereotactic Body Radiation Therapy: A Review of the Pathophysiology and Risk Factors. Neurosurgery 2017; 83:314-322. [DOI: 10.1093/neuros/nyx493] [Citation(s) in RCA: 73] [Impact Index Per Article: 10.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2017] [Accepted: 09/07/2017] [Indexed: 01/23/2023] Open
Abstract
Abstract
BACKGROUND
Vertebral compression fracture (VCF) is a challenging and not infrequent complication observed following spine stereotactic body radiation therapy (SBRT).
OBJECTIVE
To summarize the data from the multiple studies that have been published, addressing the risk and predictive factors for VCF post-SBRT.
METHODS
A systematic literature review was conducted. Studies were selected if they specifically addressed risk factors for post-SBRT VCF in their analyses.
RESULTS
A total of 11 studies were identified, reporting both the risk of VCF post-SBRT and an analysis of risk factors based on univariate and multivariate analysis. A total of 2911 spinal segments were treated with a crude VCF rate of 13.9%. The most frequently identified risk factors on multivariate analysis were: lytic disease (hazard ratio [HR] range, 2.76-12.2), baseline VCF prior to SBRT (HR range, 1.69-9.25), higher dose per fraction SBRT (HR range, 5.03-6.82), spinal deformity (HR range, 2.99-11.1), older age (HR range, 2.15-5.67), and more than 40% to 50% of vertebral body involved by tumor (HR range, 3.9-4.46). In the 9 studies that specifically reported on the use of post-SBRT surgical procedures, 37% of VCF had undergone an intervention (range, 11%-60%).
CONCLUSION
VCF is an important adverse effect following SBRT. Risk factors have been identified to guide the selection of high-risk patients. Evidence-based algorithms with respect to patient selection and intervention are needed.
Collapse
Affiliation(s)
- Salman Faruqi
- Department of Radiation Oncology, Sunnybrook Odette Cancer Centre, University of Toronto, Toronto, Ontario, Canada
| | - Chia-Lin Tseng
- Department of Radiation Oncology, Sunnybrook Odette Cancer Centre, University of Toronto, Toronto, Ontario, Canada
| | - Cari Whyne
- Orthopaedic Biomechanics Laboratory, Sunnybrook Research Institute, Department of Surgery, University of Toronto, Toronto, Ontario, Canada
| | - Majed Alghamdi
- Department of Radiation Oncology, Sunnybrook Odette Cancer Centre, University of Toronto, Toronto, Ontario, Canada
| | - Jefferson Wilson
- Department of Neurosurgery, St. Michael's Hospital, University of Toronto, Toronto, Ontario, Canada
| | - Sten Myrehaug
- Department of Radiation Oncology, Sunnybrook Odette Cancer Centre, University of Toronto, Toronto, Ontario, Canada
| | - Hany Soliman
- Department of Radiation Oncology, Sunnybrook Odette Cancer Centre, University of Toronto, Toronto, Ontario, Canada
| | - Young Lee
- Department of Radiation Oncology, Sunnybrook Odette Cancer Centre, University of Toronto, Toronto, Ontario, Canada
| | - Pejman Maralani
- Department of Radiology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario, Canada
| | - Victor Yang
- Department of Neurosurgery, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario, Canada
| | - Charles Fisher
- Department of Neurosurgery, Vancouver General Hospital, University of British Columbia, Vancouver, British Columbia, Canada
| | - Arjun Sahgal
- Department of Radiation Oncology, Sunnybrook Odette Cancer Centre, University of Toronto, Toronto, Ontario, Canada
| |
Collapse
|
42
|
Cao Y, Tseng CL, Balter JM, Teng F, Parmar HA, Sahgal A. MR-guided radiation therapy: transformative technology and its role in the central nervous system. Neuro Oncol 2017; 19:ii16-ii29. [PMID: 28380637 DOI: 10.1093/neuonc/nox006] [Citation(s) in RCA: 46] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023] Open
Abstract
This review article describes advancement of magnetic resonance imaging technologies in radiation therapy planning, guidance, and adaptation of brain tumors. The potential for MR-guided radiation therapy to improve outcomes and the challenges in its adoption are discussed.
Collapse
Affiliation(s)
- Yue Cao
- Departments of Radiation Oncology, University of Michigan, Ann Arbor, Michigan, USA
- Radiology, University of Michigan, Ann Arbor, Michigan, USA
- Biomedical Engineering, University of Michigan, Ann Arbor, Michigan, USA
| | - Chia-Lin Tseng
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario, Canada
| | - James M Balter
- Departments of Radiation Oncology, University of Michigan, Ann Arbor, Michigan, USA
| | - Feifei Teng
- Departments of Radiation Oncology, University of Michigan, Ann Arbor, Michigan, USA
- Department of Radiation Oncology, Shandong Cancer Hospital, Shandong University, Jinan, China
| | | | - Arjun Sahgal
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario, Canada
| |
Collapse
|