1
|
Pan K, Concannon K, Li J, Zhang J, Heymach JV, Le X. Emerging therapeutics and evolving assessment criteria for intracranial metastases in patients with oncogene-driven non-small-cell lung cancer. Nat Rev Clin Oncol 2023; 20:716-732. [PMID: 37592034 PMCID: PMC10851171 DOI: 10.1038/s41571-023-00808-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/21/2023] [Indexed: 08/19/2023]
Abstract
The improved survival outcomes of patients with non-small-cell lung cancer (NSCLC), largely owing to the improved control of systemic disease provided by immune-checkpoint inhibitors and novel targeted therapies, have highlighted the challenges posed by central nervous system (CNS) metastases as a devastating yet common complication, with up to 50% of patients developing such lesions during the course of the disease. Early-generation tyrosine-kinase inhibitors (TKIs) often provide robust systemic disease control in patients with oncogene-driven NSCLCs, although these agents are usually unable to accumulate to therapeutically relevant concentrations in the CNS owing to an inability to cross the blood-brain barrier. However, the past few years have seen a paradigm shift with the emergence of several novel or later-generation TKIs with improved CNS penetrance. Such agents have promising levels of activity against brain metastases, as demonstrated by data from preclinical and clinical studies. In this Review, we describe current preclinical and clinical evidence of the intracranial activity of TKIs targeting various oncogenic drivers in patients with NSCLC, with a focus on newer agents with enhanced CNS penetration, leptomeningeal disease and the need for intrathecal treatment options. We also discuss evolving assessment criteria and regulatory considerations for future clinical investigations.
Collapse
Affiliation(s)
- Kelsey Pan
- Department of Cancer Medicine, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Kyle Concannon
- Department of Cancer Medicine, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Jing Li
- Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Jianjun Zhang
- Department of Thoracic/Head and Neck Medical Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - John V Heymach
- Department of Thoracic/Head and Neck Medical Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Xiuning Le
- Department of Thoracic/Head and Neck Medical Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, USA.
| |
Collapse
|
2
|
Eraky AM. Radiological Biomarkers for Brain Metastases Prognosis: Quantitative Magnetic Resonance Imaging (MRI) Modalities As Non-invasive Biomarkers for the Effect of Radiotherapy. Cureus 2023; 15:e38353. [PMID: 37266043 PMCID: PMC10229388 DOI: 10.7759/cureus.38353] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/28/2023] [Indexed: 06/03/2023] Open
Abstract
Radiotherapy effect is achieved by its ability to cause DNA damage and induce apoptosis. In contrast, radiation can induce tumor cells' proliferation, invasiveness, and epithelial-mesenchymal transition (EMT). Besides developing radioresistance, this paradoxical effect of radiotherapy is considered a challenging problem in the field of radiotherapy. This highlights the importance of developing new modalities to diagnose radioresistance early to avoid any unnecessary exposure to radiation and differentiate between metastases recurrence versus post-radiation changes. Quantitative magnetic resonance imaging (MRI) techniques including diffusion-weighted imaging (DWI), dynamic susceptibility contrast (DSC), arterial spin labeling (ASL), and dynamic contrast-enhanced (DCE) represent potential biomarkers to diagnose metastases recurrence and radioresistance. In this review, we will focus on recent studies discussing the possibility of using DWI, DSC, ASL, and DCE to diagnose radioresistance and recurrence in patients with brain metastases.
Collapse
Affiliation(s)
- Akram M Eraky
- Neurological Surgery, Medical College of Wisconsin, Milwaukee, USA
| |
Collapse
|
3
|
Starck L, Skeie BS, Bartsch H, Grüner R. Arterial input functions in dynamic susceptibility contrast MRI (DSC-MRI) in longitudinal evaluation of brain metastases. Acta Radiol 2023; 64:1166-1174. [PMID: 35786055 DOI: 10.1177/02841851221109702] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) could be helpful to separate true disease progression from pseudo-progression in brain metastases when assessing the need for retreatment. However, the selection of arterial input functions (AIFs) is not standardized for analysis, limiting its use for this application. PURPOSE To compare population-based AIFs, AIFs specific to each patient, and AIFs specific to every visit in the longitudinal follow-up of brain metastases. MATERIAL AND METHODS Longitudinal data were collected from eight patients before treatment (6 of 8 patients) and after treatment (6-17 visits). Imaging was performed using a 1.5-T MRI system. Lesions were segmented by subtracting precontrast images from postcontrast images. Cerebral blood volume (rCBV) and cerebral blood flow (rCBF) were computed, and Pearson's product moment correlation coefficients were calculated to evaluate similarity of DSC parameters dependent on various AIF choices across time. AIF shape characteristics were compared. Parameter differences between white matter (WM) and gray matter (GM) were obtained to determine which AIF choice maximizes tissue differentiation. RESULTS Although DSC parameters follow similar patterns in time, the various AIF selections cause large parameter variations with relative standard deviations of up to ±60%. AIFs sampled in one patient across sessions more similar in shape than AIFs sampled across patients. Estimates of rCBV based on scan-specific AIFs differentiated better between perfusion in WM and GM than patient-specific or population-based AIFs (P ≤ 0.02). CONCLUSION Results indicate that scan-specific AIFs are the best choice for DSC-MRI parameter estimations in the longitudinal follow-up of brain metastases.
Collapse
Affiliation(s)
- Lea Starck
- Department of Physics and Technology, 1658University of Bergen, Bergen, Norway
- Mohn Medical Imaging and Visualization Centre, Bergen, Norway
| | - Bente Sandvei Skeie
- Department of Neurosurgery, 60498Haukeland University Hospital, Bergen, Norway
| | - Hauke Bartsch
- Mohn Medical Imaging and Visualization Centre, Bergen, Norway
- Department of Radiology, 60498Haukeland University Hospital, Bergen, Norway
| | - Renate Grüner
- Department of Physics and Technology, 1658University of Bergen, Bergen, Norway
- Mohn Medical Imaging and Visualization Centre, Bergen, Norway
- Department of Radiology, 60498Haukeland University Hospital, Bergen, Norway
| |
Collapse
|
4
|
Diagnostic Value of 18 F-FACBC PET/MRI in Brain Metastases. Clin Nucl Med 2022; 47:1030-1039. [PMID: 36241129 PMCID: PMC9653108 DOI: 10.1097/rlu.0000000000004435] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
PURPOSE The study aims to evaluate whether combined 18 F-FACBC PET/MRI could provide additional diagnostic information compared with MRI alone in brain metastases. PATIENTS AND METHODS Eighteen patients with newly diagnosed or suspected recurrence of brain metastases received dynamic 18 F-FACBC PET/MRI. Lesion detection was evaluated on PET and MRI scans in 2 groups depending on prior stereotactic radiosurgery (SRS group) or not (no-SRS group). SUVs, time-activity curves, and volumetric analyses of the lesions were performed. RESULTS In the no-SRS group, 29/29 brain lesions were defined as "MRI positive." With PET, 19/29 lesions were detected and had high tumor-to-background ratios (TBRs) (D max MR , ≥7 mm; SUV max , 1.2-8.4; TBR, 3.9-25.9), whereas 10/29 lesions were undetected (D max MR , ≤8 mm; SUV max , 0.3-1.2; TBR, 1.0-2.7). In the SRS group, 4/6 lesions were defined as "MRI positive," whereas 2/6 lesions were defined as "MRI negative" indicative of radiation necrosis. All 6 lesions were detected with PET (D max MR , ≥15 mm; SUV max , 1.4-4.2; TBR, 3.6-12.6). PET volumes correlated and were comparable in size with contrast-enhanced MRI volumes but were only partially congruent (mean DSC, 0.66). All time-activity curves had an early peak, followed by a plateau or a decreasing slope. CONCLUSIONS 18 F-FACBC PET demonstrated uptake in brain metastases from cancer of different origins (lung, gastrointestinal tract, breast, thyroid, and malignant melanoma). However, 18 F-FACBC PET/MRI did not improve detection of brain metastases compared with MRI but might detect tumor tissue beyond contrast enhancement on MRI. 18 F-FACBC PET should be further evaluated in recurrent brain metastases.
Collapse
|
5
|
Devan SP, Jiang X, Kang H, Luo G, Xie J, Zu Z, Stokes AM, Gore JC, McKnight CD, Kirschner AN, Xu J. Towards differentiation of brain tumor from radiation necrosis using multi-parametric MRI: Preliminary results at 4.7 T using rodent models. Magn Reson Imaging 2022; 94:144-150. [PMID: 36209946 PMCID: PMC10167709 DOI: 10.1016/j.mri.2022.10.002] [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: 07/19/2022] [Revised: 09/15/2022] [Accepted: 10/01/2022] [Indexed: 02/13/2023]
Abstract
BACKGROUND It remains a clinical challenge to differentiate brain tumors from radiation-induced necrosis in the brain. Despite significant improvements, no single MRI method has been validated adequately in the clinical setting. METHODS Multi-parametric MRI (mpMRI) was performed to differentiate 9L gliosarcoma from radiation necrosis in animal models. Five types of MRI methods probed complementary information on different scales i.e., T2 (relaxation), CEST based APT (probing mobile proteins/peptides) and rNOE (mobile macromolecules), qMT (macromolecules), diffusion based ADC (cell density) and SSIFT iAUC (cell size), and perfusion based DSC (blood volume and flow). RESULTS For single MRI parameters, iAUC and ADC provide the best discrimination of radiation necrosis and brain tumor. For mpMRI, a combination of iAUC, ADC, and APT shows the best classification performance based on a two-step analysis with the Lasso and Ridge regressions. CONCLUSION A general mpMRI approach is introduced to choosing candidate multiple MRI methods, identifying the most effective parameters from all the mpMRI parameters, and finding the appropriate combination of chosen parameters to maximize the classification performance to differentiate tumors from radiation necrosis.
Collapse
Affiliation(s)
- Sean P Devan
- Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States; Chemical and Physical Biology Program, Vanderbilt University, Nashville, TN, United States
| | - Xiaoyu Jiang
- Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States; Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Hakmook Kang
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Guozhen Luo
- Department of Radiation Oncology, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Jingping Xie
- Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Zhongliang Zu
- Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States; Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Ashley M Stokes
- Barrow Neuroimaging Innovation Center, Barrow Neurological Institute, Phoenix, AZ, United States
| | - John C Gore
- Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States; Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States; Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, United States; Department of Physics and Astronomy, Vanderbilt University, Nashville, TN, United States
| | - Colin D McKnight
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Austin N Kirschner
- Department of Radiation Oncology, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Junzhong Xu
- Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States; Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States; Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, United States; Department of Physics and Astronomy, Vanderbilt University, Nashville, TN, United States.
| |
Collapse
|
6
|
Teunissen WHT, Govaerts CW, Kramer MCA, Labrecque JA, Smits M, Dirven L, van der Hoorn A. Diagnostic accuracy of MRI techniques for treatment response evaluation in patients with brain metastasis: A systematic review and meta-analysis. Radiother Oncol 2022; 177:121-133. [PMID: 36377093 DOI: 10.1016/j.radonc.2022.10.026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Revised: 10/11/2022] [Accepted: 10/21/2022] [Indexed: 11/12/2022]
Abstract
BACKGROUND Treatment response assessment in patients with brain metastasis uses contrast enhanced T1-weighted MRI. Advanced MRI techniques have been studied, but the diagnostic accuracy is not well known. Therefore, we performed a metaanalysis to assess the diagnostic accuracy of the currently available MRI techniques for treatment response. METHODS A systematic literature search was done. Study selection and data extraction were done by two authors independently. Meta-analysis was performed using a bivariate random effects model. An independent cohort was used for DSC perfusion external validation of diagnostic accuracy. RESULTS Anatomical MRI (16 studies, 726 lesions) showed a pooled sensitivity of 79% and a specificity of 76%. DCE perfusion (4 studies, 114 lesions) showed a pooled sensitivity of 74% and a specificity of 92%. DSC perfusion (12 studies, 418 lesions) showed a pooled sensitivity was 83% with a specificity of 78%. Diffusion weighted imaging (7 studies, 288 lesions) showed a pooled sensitivity of 67% and a specificity of 79%. MRS (4 studies, 54 lesions) showed a pooled sensitivity of 80% and a specificity of 78%. Combined techniques (6 studies, 375 lesions) showed a pooled sensitivity of 84% and a specificity of 88%. External validation of DSC showed a lower sensitivity and a higher specificity for the reported cut-off values included in this metaanalysis. CONCLUSION A combination of techniques shows the highest diagnostic accuracy differentiating tumor progression from treatment induced abnormalities. External validation of imaging results is important to better define the reliability of imaging results with the different techniques.
Collapse
Affiliation(s)
- Wouter H T Teunissen
- Erasmus MC, department of Radiology and Nuclear Medicine, Rotterdam, the Netherlands; Brain Tumor Centre, Erasmus MC Cancer Institute, Rotterdam, the Netherlands; Medical Delta, Delft, The Netherlands
| | - Chris W Govaerts
- University Medical Center Groningen, Medical imaging center, department of Radiology, Groningen, the Netherlands
| | - Miranda C A Kramer
- University Medical Center Groningen, department of Radiotherapy, Groningen, the Netherlands
| | - Jeremy A Labrecque
- Erasmus MC, Netherlands Institute for Health Science (NIHES), Rotterdam, the Netherlands
| | - Marion Smits
- Erasmus MC, department of Radiology and Nuclear Medicine, Rotterdam, the Netherlands; Brain Tumor Centre, Erasmus MC Cancer Institute, Rotterdam, the Netherlands; Medical Delta, Delft, The Netherlands
| | - Linda Dirven
- Leiden University Medical Center, department of Neurology, Leiden, the Netherlands; Haaglanden Medical Center, department of Neurology, The Hague, the Netherlands
| | - Anouk van der Hoorn
- University Medical Center Groningen, Medical imaging center, department of Radiology, Groningen, the Netherlands.
| |
Collapse
|
7
|
Devan SP, Jiang X, Luo G, Xie J, Quirk JD, Engelbach JA, Harmsen H, McKinley ET, Cui J, Zu Z, Attia A, Garbow JR, Gore JC, McKnight CD, Kirschner AN, Xu J. Selective Cell Size MRI Differentiates Brain Tumors from Radiation Necrosis. Cancer Res 2022; 82:3603-3613. [PMID: 35877201 PMCID: PMC9532360 DOI: 10.1158/0008-5472.can-21-2929] [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: 08/30/2021] [Revised: 02/05/2022] [Accepted: 07/21/2022] [Indexed: 11/16/2022]
Abstract
Brain metastasis is a common characteristic of late-stage lung cancers. High doses of targeted radiotherapy can control tumor growth in the brain but can also result in radiotherapy-induced necrosis. Current methods are limited for distinguishing whether new parenchymal lesions following radiotherapy are recurrent tumors or radiotherapy-induced necrosis, but the clinical management of these two classes of lesions differs significantly. Here, we developed, validated, and evaluated a new MRI technique termed selective size imaging using filters via diffusion times (SSIFT) to differentiate brain tumors from radiotherapy necrosis in the brain. This approach generates a signal filter that leverages diffusion time dependence to establish a cell size-weighted map. Computer simulations in silico, cultured cancer cells in vitro, and animals with brain tumors in vivo were used to comprehensively validate the specificity of SSIFT for detecting typical large cancer cells and the ability to differentiate brain tumors from radiotherapy necrosis. SSIFT was also implemented in patients with metastatic brain cancer and radiotherapy necrosis. SSIFT showed high correlation with mean cell sizes in the relevant range of less than 20 μm. The specificity of SSIFT for brain tumors and reduced contrast in other brain etiologies allowed SSIFT to differentiate brain tumors from peritumoral edema and radiotherapy necrosis. In conclusion, this new, cell size-based MRI method provides a unique contrast to differentiate brain tumors from other pathologies in the brain. SIGNIFICANCE This work introduces and provides preclinical validation of a new diffusion MRI method that exploits intrinsic differences in cell sizes to distinguish brain tumors and radiotherapy necrosis.
Collapse
Affiliation(s)
- Sean P Devan
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Chemical and Physical Biology Program, Vanderbilt University, Nashville, TN, 37232, USA
| | - Xiaoyu Jiang
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Guozhen Luo
- Department of Radiation Oncology, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Jingping Xie
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - James D Quirk
- Mallinckrodt Institute of Radiology, Washington University, St. Louis, MO 63110, USA
| | - John A Engelbach
- Mallinckrodt Institute of Radiology, Washington University, St. Louis, MO 63110, USA
| | - Hannah Harmsen
- Department of Pathology, Microbiology, and Immunology, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Eliot T McKinley
- Department of Cell and Developmental Biology, Vanderbilt University, Nashville, TN, 37232, USA
| | - Jing Cui
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Zhongliang Zu
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Albert Attia
- Department of Radiation Oncology, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Joel R Garbow
- Mallinckrodt Institute of Radiology, Washington University, St. Louis, MO 63110, USA
- Alvin J Siteman Cancer Center, Washington University, St. Louis, MO, 63110, USA
| | - John C. Gore
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37232, USA
- Department of Physics and Astronomy, Vanderbilt University, Nashville, TN 37232, USA
| | - Colin D McKnight
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Austin N Kirschner
- Department of Radiation Oncology, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Junzhong Xu
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37232, USA
- Department of Physics and Astronomy, Vanderbilt University, Nashville, TN 37232, USA
| |
Collapse
|
8
|
Otman H, Farce J, Meneret P, Palard-Novello X, Le Reste PJ, Lecouillard I, Vauleon E, Chanchou M, Carsin Nicol B, Bertaux M, Devillers A, Mariano-Goulart D, Cachin F, Girard A, Le Jeune F. Delayed [ 18 F]-FDG PET Imaging Increases Diagnostic Performance and Reproducibility to Differentiate Recurrence of Brain Metastases From Radionecrosis. Clin Nucl Med 2022; 47:800-806. [PMID: 35695724 DOI: 10.1097/rlu.0000000000004305] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
PURPOSE Differentiating brain metastasis recurrence from radiation necrosis can be challenging during MRI follow-up after stereotactic radiotherapy. [ 18 F]-FDG is the most available PET tracer, but standard images performed 30 to 60 minutes postinjection provide insufficient accuracy. We compared the diagnostic performance and interobserver agreement of [ 18 F]-FDG PET with delayed images (4-5 hours postinjection) with the ones provided by standard and dual-time-point imaging. METHODS Consecutive patients referred for brain [ 18 F]-FDG PET after inconclusive MRI were retrospectively included between 2015 and 2020 in 3 centers. Two independent nuclear medicine physicians interpreted standard (visually), delayed (visually), and dual-time-point (semiquantitatively) images, respectively. Adjudication was applied in case of discrepancy. The final diagnosis was confirmed histologically or after 6 months of MRI follow-up. Areas under the receiver operating characteristic curves were pairwise compared. RESULTS Forty-eight lesions from 46 patients were analyzed. Primary tumors were mostly located in the lungs (57%) and breast (23%). The median delay between radiotherapy and PET was 15.7 months. The final diagnosis was tumor recurrence in 24 of 48 lesions (50%), with histological confirmation in 19 of 48 lesions (40%). Delayed images provided a larger area under the receiver operating characteristic curve (0.88; 95% confidence interval [CI], 0.75-0.95) than both standard (0.69; 95% CI, 0.54-0.81; P = 0.0014) and dual-time-point imaging (0.77; 95% CI, 0.63-0.88; P = 0.045), respectively. Interobserver agreement was almost perfect with delayed images ( κ = 0.83), whereas it was moderate with both standard ( κ = 0.48) and dual-time-point images ( κ = 0.61). CONCLUSIONS [ 18 F]-FDG PET with delayed images is an accurate and reliable alternative to differentiate metastasis recurrence from radiation necrosis in case of inconclusive MRI after brain stereotactic radiotherapy.
Collapse
Affiliation(s)
- Hosameldin Otman
- From the Department of Nuclear Medicine, Jean Perrin Center, Clermont-Ferrand
| | - Julien Farce
- Department of Nuclear Medicine, Eugène Marquis Center
| | | | | | | | | | | | | | | | - Marc Bertaux
- Department of Nuclear Medicine, Foch hospital, Suresnes
| | | | - Denis Mariano-Goulart
- Department of Nuclear Medicine. Montpellier University Hospital. PYMEDEXP, University of Montpellier, INSERM, CNRS, Montpellier, France
| | | | | | | |
Collapse
|
9
|
A Mohamed S, Adlung A, Ruder AM, Hoesl MAU, Schad L, Groden C, Giordano FA, Neumaier-Probst E. MRI Detection of Changes in Tissue Sodium Concentration in Brain Metastases after Stereotactic Radiosurgery: A Feasibility Study. J Neuroimaging 2020; 31:297-305. [PMID: 33351997 DOI: 10.1111/jon.12823] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2020] [Revised: 11/28/2020] [Accepted: 11/30/2020] [Indexed: 12/31/2022] Open
Abstract
BACKGROUND AND PURPOSE To date, treatment response to stereotactic radiosurgery (SRS) in brain metastases (BM) can only be determined by MRI evaluation of contrast-enhancing lesions in a long-time follow-up. Sodium MRI has been a subject of immense interest in imaging research as the measure of tissue sodium concentration (TSC) can give valuable quantitative information on cell viability. We aimed to analyze the longitudinal changes of TSC in BM measured with 23 Na MRI before and after SRS for assessment of early local tumor effects. METHODS Seven patients with a total of 12 previously untreated BM underwent SRS with 22 Gy. In addition to a standard MRI protocol including dynamic susceptibility-weighted contrast-enhanced perfusion, a 23 Na MRI was performed at three time points: (I) 2 days before, (II) 5 days, and (III) 40 days after SRS. Nine BMs were evaluated. The absolute TSC in the BM, the respective peritumoral edemas, and the normal-appearing corresponding contralateral brain area were assessed and the relative TSC were correlated to the changes in BM longest axial diameters. RESULTS TSC was elevated in nine BM at baseline before SRS with a mean of 73.4 ± 12.3 mM. A further increase in TSC was observed 5 days after SRS in all the nine BM with a mean of 86.9 ± 13 mM. Eight of nine BM showed a mean 60.6 ± 13.3% decrease in the longest axial diameter 40 days after SRS; at this time point, the TSC also had decreased to a mean 65.1 ± 7.9 mM. In contrast, one of the nine BM had a 13.4% increase in the largest axial diameter at time point III. The TSC of this BM showed a further TSC increase of 80.1 mM 40 days after SRS. CONCLUSION Changes in TSC using 23 Na MRI shows the possible capability to detect radiobiological changes in BM after SRS.
Collapse
Affiliation(s)
- Sherif A Mohamed
- Department of Neuroradiology, University Medical Center Mannheim, Heidelberg University, Mannheim, Germany
| | - Anne Adlung
- Department of Computer Assisted Clinical Medicine, University Medical Center Mannheim, Heidelberg University, Mannheim, Germany
| | - Arne M Ruder
- Department of Radiation Oncology, University Medical Center Mannheim, Heidelberg University, Mannheim, Germany
| | - Michaela A U Hoesl
- Department of Computer Assisted Clinical Medicine, University Medical Center Mannheim, Heidelberg University, Mannheim, Germany
| | - Lothar Schad
- Department of Computer Assisted Clinical Medicine, University Medical Center Mannheim, Heidelberg University, Mannheim, Germany
| | - Christoph Groden
- Department of Neuroradiology, University Medical Center Mannheim, Heidelberg University, Mannheim, Germany
| | - Frank A Giordano
- Department of Radiation Oncology, University Hospital Bonn, University of Bonn, Bonn, Germany
| | - Eva Neumaier-Probst
- Department of Neuroradiology, University Medical Center Mannheim, Heidelberg University, Mannheim, Germany
| |
Collapse
|
10
|
Reed LK, Huang JH. Variability of relative cerebral blood volume measurements of recurrent glioma. ANNALS OF TRANSLATIONAL MEDICINE 2019; 7:S260. [PMID: 32015979 PMCID: PMC6976513 DOI: 10.21037/atm.2019.12.41] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/25/2019] [Accepted: 12/05/2019] [Indexed: 11/06/2022]
Affiliation(s)
- Laura K. Reed
- Department of Neurosurgery, Baylor Scott & White Health, Scott and White Medical Center, Temple, TX, USA
- Department of Surgery, Texas A&M University College of Medicine, Temple, TX, USA
| | - Jason H. Huang
- Department of Neurosurgery, Baylor Scott & White Health, Scott and White Medical Center, Temple, TX, USA
- Department of Surgery, Texas A&M University College of Medicine, Temple, TX, USA
| |
Collapse
|