Dataset Information

Differentiation between glioma and radiation necrosis using molecular magnetic resonance imaging of endogenous proteins and peptides.

ABSTRACT: It remains difficult to distinguish tumor recurrence from radiation necrosis after brain tumor therapy. Here we show that these lesions can be distinguished using the amide proton transfer (APT) magnetic resonance imaging (MRI) signals of endogenous cellular proteins and peptides as an imaging biomarker. When comparing two models of orthotopic glioma (SF188/V+ glioma and 9L gliosarcoma) with a model of radiation necrosis in rats, we could clearly differentiate viable glioma (hyperintense) from radiation necrosis (hypointense to isointense) by APT MRI. When we irradiated rats with U87MG gliomas, the APT signals in the irradiated tumors had decreased substantially by 3 d and 6 d after radiation. The amide protons that can be detected by APT provide a unique and noninvasive MRI biomarker for distinguishing viable malignancy from radiation necrosis and predicting tumor response to therapy.

SUBMITTER: Zhou J

PROVIDER: S-EPMC3058561 | biostudies-literature | 2011 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Differentiation between glioma and radiation necrosis using molecular magnetic resonance imaging of endogenous proteins and peptides.

Zhou Jinyuan J Tryggestad Erik E Wen Zhibo Z Lal Bachchu B Zhou Tingting T Grossman Rachel R Wang Silun S Yan Kun K Fu De-Xue DX Ford Eric E Tyler Betty B Blakeley Jaishri J Laterra John J van Zijl Peter C M PC

Nature medicine 20101219 1

It remains difficult to distinguish tumor recurrence from radiation necrosis after brain tumor therapy. Here we show that these lesions can be distinguished using the amide proton transfer (APT) magnetic resonance imaging (MRI) signals of endogenous cellular proteins and peptides as an imaging biomarker. When comparing two models of orthotopic glioma (SF188/V+ glioma and 9L gliosarcoma) with a model of radiation necrosis in rats, we could clearly differentiate viable glioma (hyperintense) from r ...[more]

PMID: 21170048

Similar Datasets

Project description:BackgroundThe radiological differential diagnosis between tumor recurrence and radiation-induced necrosis (ie, pseudoprogression) is of paramount importance in the management of glioma patients.ObjectiveThis research aims to develop a deep learning methodology for automated differentiation of tumor recurrence from radiation necrosis based on routine magnetic resonance imaging (MRI) scans.MethodsIn this retrospective study, 146 patients who underwent radiation therapy after glioma resection and presented with suspected recurrent lesions at the follow-up MRI examination were selected for analysis. Routine MRI scans were acquired from each patient, including T1, T2, and gadolinium-contrast-enhanced T1 sequences. Of those cases, 96 (65.8%) were confirmed as glioma recurrence on postsurgical pathological examination, while 50 (34.2%) were diagnosed as necrosis. A light-weighted deep neural network (DNN) (ie, efficient radionecrosis neural network [ERN-Net]) was proposed to learn radiological features of gliomas and necrosis from MRI scans. Sensitivity, specificity, accuracy, and area under the curve (AUC) were used to evaluate performance of the model in both image-wise and subject-wise classifications. Preoperative diagnostic performance of the model was also compared to that of the state-of-the-art DNN models and five experienced neurosurgeons.ResultsDNN models based on multimodal MRI outperformed single-modal models. ERN-Net achieved the highest AUC in both image-wise (0.915) and subject-wise (0.958) classification tasks. The evaluated DNN models achieved an average sensitivity of 0.947 (SD 0.033), specificity of 0.817 (SD 0.075), and accuracy of 0.903 (SD 0.026), which were significantly better than the tested neurosurgeons (P=.02 in sensitivity and P<.001 in specificity and accuracy).ConclusionsDeep learning offers a useful computational tool for the differential diagnosis between recurrent gliomas and necrosis. The proposed ERN-Net model, a simple and effective DNN model, achieved excellent performance on routine MRI scans and showed a high clinical applicability.

Project description:Radiotherapy remains the cornerstone of curative treatment for inoperable locally advanced lung cancer, given concomitantly with platinum-based chemotherapy. With poor overall survival, research efforts continue to explore whether integration of advanced radiation techniques will assist safe treatment intensification with the potential for improving outcomes. One advance is the integration of magnetic resonance imaging (MRI) in the treatment pathway, providing anatomical and functional information with excellent soft tissue contrast without exposure of the patient to radiation. MRI may complement or improve the diagnostic staging accuracy of F-18 fluorodeoxyglucose position emission tomography and computerized tomography imaging, particularly in assessing local tumour invasion and is also effective for identification of nodal and distant metastatic disease. Incorporating anatomical MRI sequences into lung radiotherapy treatment planning is a novel application and may improve target volume and organs at risk delineation reproducibility. Furthermore, functional MRI may facilitate dose painting for heterogeneous target volumes and prediction of normal tissue toxicity to guide adaptive strategies. MRI sequences are rapidly developing and although the issue of intra-thoracic motion has historically hindered the quality of MRI due to the effect of motion, progress is being made in this field. Four-dimensional MRI has the potential to complement or supersede 4D CT and 4D F-18-FDG PET, by providing superior spatial resolution. A number of MR-guided radiotherapy delivery units are now available, combining a radiotherapy delivery machine (linear accelerator or cobalt-60 unit) with MRI at varying magnetic field strengths. This novel hybrid technology is evolving with many technical challenges to overcome. It is anticipated that the clinical benefits of MR-guided radiotherapy will be derived from the ability to adapt treatment on the fly for each fraction and in real-time, using 'beam-on' imaging. The lung tumour site group of the Atlantic MR-Linac consortium is working to generate a challenging MR-guided adaptive workflow for multi-institution treatment intensification trials in this patient group.

Project description:OBJECTIVES:The aim of this study was to determine if hyperpolarized [1,4-13C2]malate imaging could measure cardiomyocyte necrosis after myocardial infarction (MI). BACKGROUND:MI is defined by an acute burst of cellular necrosis and the subsequent cascade of structural and functional adaptations. Quantifying necrosis in the clinic after MI remains challenging. Magnetic resonance-based detection of the conversion of hyperpolarized [1,4-13C2]fumarate to [1,4-13C2]malate, enabled by disrupted cell membrane integrity, has measured cellular necrosis in vivo in other tissue types. Our aim was to determine whether hyperpolarized [1,4-13C2]malate imaging could measure necrosis after MI. METHODS:Isolated perfused hearts were given hyperpolarized [1,4-13C2]fumarate at baseline, immediately after 20 min of ischemia, and after 45 min of reperfusion. Magnetic resonance spectroscopy measured conversion into [1,4-13C2]malate. Left ventricular function and energetics were monitored throughout the protocol, buffer samples were collected and hearts were preserved for further analyses. For in vivo studies, magnetic resonance spectroscopy and a novel spatial-spectral magnetic resonance imaging sequence were implemented to assess cardiomyocyte necrosis in rats, 1 day and 1 week after cryo-induced MI. RESULTS:In isolated hearts, [1,4-13C2]malate production became apparent after 45 min of reperfusion, and increased 2.7-fold compared with baseline. Expression of dicarboxylic acid transporter genes were negligible in healthy and reperfused hearts, and lactate dehydrogenase release and infarct size were significantly increased in reperfused hearts. Nonlinear regression revealed that [1,4-13C2]malate production was induced when adenosine triphosphate was depleted by >50%, below 5.3 mmol/l (R2 = 0.904). In vivo, the quantity of [1,4-13C2]malate visible increased 82-fold over controls 1 day after infarction, maintaining a 31-fold increase 7 days post-infarct. [1,4-13C2]Malate could be resolved using hyperpolarized magnetic resonance imaging in the infarct region one day after MI; [1,4-13C2]malate was not visible in control hearts. CONCLUSIONS:Malate production in the infarcted heart appears to provide a specific probe of necrosis acutely after MI, and for at least 1 week afterward. This technique could offer an alternative noninvasive method to measure cellular necrosis in heart disease, and warrants further investigation in patients.

Dataset Information

Differentiation between glioma and radiation necrosis using molecular magnetic resonance imaging of endogenous proteins and peptides.

Publications

Differentiation between glioma and radiation necrosis using molecular magnetic resonance imaging of endogenous proteins and peptides.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets