Jelena Mihailovic - Academia.edu (original) (raw)

Papers by Jelena Mihailovic

Research paper thumbnail of Imaging the Transmembrane and Transendothelial Sodium Gradients in Gliomas

ABSTRACTHigh sodium (Na+) in extracellular (Na+e) and blood (Na+b) compartments and low Na+in int... more ABSTRACTHigh sodium (Na+) in extracellular (Na+e) and blood (Na+b) compartments and low Na+in intracellular milieu (Na+i) produce strong transmembrane (ΔNa+mem) and weak transendothelial (ΔNa+end) gradients respectively, which reflect cell membrane potential (Vm) and blood-brain barrier (BBB) integrity. We developed a sodium (23Na) magnetic resonance spectroscopic imaging (MRSI) method using an intravenously-administered paramagnetic contrast agent to measure ΔNa+memand ΔNa+end.In vitro23Na-MRSI established that the23Na signal is strongly shifted by the agent compared to biological factors.In vivo23Na-MRSI showed Na+iremained unshifted and Na+bwas more shifted than Na+e, and these together created weakened ΔNa+memand enhanced ΔNa+endin rat gliomas. Specifically, RG2 and U87 tumors maintained weakened ΔNa+mem(i.e., depolarizedVm) implying an aggressive state for proliferation, and RG2 tumors displayed elevated ΔNa+endsuggesting altered BBB integrity.23Na-MRSI will allow explorations ...

Research paper thumbnail of Advanced magnetic resonance techniques in early differentiation of pseudo-progression vs. progression in patients with glioblastoma multiforme

Vojnosanitetski pregled, 2017

Background/Aim. The diagnosis of glioblastoma multiforme progression may be confounded by a pheno... more Background/Aim. The diagnosis of glioblastoma multiforme progression may be confounded by a phenomena termed pseudoprogression (PSP) and pseudoresponse (RCT) which has become more common with the adoption of radiation therapy with concurrent and adjuvant application of temozolomide (CRT). Distinguishing of these phenomena is based on the follow-up scans since no single imaging method or technique is yet capable of performing their discrimination. In this study, we evaluated the dynamic susceptibility contrast (DSC perfusion) imaging and magnetic resonance (MR) spectroscopy to predict the prognosis and time to progression in the patients with glioblastoma multiforme. Methods. Fourty patients with primary glioblastoma multiforme were included in the analysis. The patients were examined in 3rd week after surgery and 10th week after the beginning of CRT. The MR exams were performed using the 1.5 T MR scanner (Avanto; Siemens, Erlangen, Germany). The maps of perfusion parameters and time...

Research paper thumbnail of The application of local histograms of apparent difusion coefficient in differentiation of brain astrocytomas

Vojnosanitetski pregled, 2017

Background/Aim. Microstructural diversity of brain astrocytomas makes their diagnostics and diffe... more Background/Aim. Microstructural diversity of brain astrocytomas makes their diagnostics and differentiation by using the diffusion weighted imaging (DWI) difficult. In this study we used the histogram-based positioning of regions of interests on the apparent diffusion coefficient (ADC) maps in order to restrict the determination of diffusion parameters to regions of interest (ROI) corresponding to maximum cellularity. Success of ADC standard deviation (?ADC) and kurtosis (K) in differentiation of brain astrocytomas was evaluated. Methods. The thirtyone patients (16 women and 15 men, median age 37 years, age range 6?72 years) with suspected supratentorial astrocytomas were included in the retrospective study. The magnetic resonance imaging (MRI) examinations were performed using the 1.5 T MR system (Avanto; Siemens, Erlangen, Germany) and 8-channel phased array head coil. The DWI images were acquired in three orthogonal directions for the b-values 0, 500 and 1000 s mm-2. The histogra...

Research paper thumbnail of Evaluating U-net Brain Extraction for Multi-site and Longitudinal Preclinical Stroke Imaging

Rodent stroke models are important for evaluating treatments and understanding the pathophysiolog... more Rodent stroke models are important for evaluating treatments and understanding the pathophysiology and behavioral changes of brain ischemia, and magnetic resonance imaging (MRI) is a valuable tool for measuring outcome in preclinical studies. Brain extraction is an essential first step in most neuroimaging pipelines; however, it can be challenging in the presence of severe pathology and when dataset quality is highly variable. Convolutional neural networks (CNNs) can improve accuracy and reduce operator time, facilitating high throughput preclinical studies. As part of an ongoing preclinical stroke imaging study, we developed a deep-learning mouse brain extraction tool by using a U-net CNN. While previous studies have evaluated U-net architectures, we sought to evaluate their practical performance across data types. We ask how performance is affected with data across: six imaging centers, two time points after experimental stroke, and across four MRI contrasts. We trained, validated, and tested a typical U-net model on 240 multimodal MRI datasets including quantitative multi-echo T2 and apparent diffusivity coefficient (ADC) maps, and performed qualitative evaluation with a large preclinical stroke database (N=1,368). We describe the design and development of this system, and report our findings linking data characteristics to segmentation performance. We consistently found high accuracy and ability of the U-net architecture to generalize performance in a range of 95-97% accuracy, with only modest reductions in performance based on lower fidelity imaging hardware and brain pathology. This work can help inform the design of future preclinical rodent imaging studies and improve their scalability and reliability.

Research paper thumbnail of Imaging the Transmembrane and Transendothelial Sodium Gradients in Gliomas

ABSTRACTHigh sodium (Na+) in extracellular (Na+e) and blood (Na+b) compartments and low Na+in int... more ABSTRACTHigh sodium (Na+) in extracellular (Na+e) and blood (Na+b) compartments and low Na+in intracellular milieu (Na+i) produce strong transmembrane (ΔNa+mem) and weak transendothelial (ΔNa+end) gradients respectively, which reflect cell membrane potential (Vm) and blood-brain barrier (BBB) integrity. We developed a sodium (23Na) magnetic resonance spectroscopic imaging (MRSI) method using an intravenously-administered paramagnetic contrast agent to measure ΔNa+memand ΔNa+end.In vitro23Na-MRSI established that the23Na signal is strongly shifted by the agent compared to biological factors.In vivo23Na-MRSI showed Na+iremained unshifted and Na+bwas more shifted than Na+e, and these together created weakened ΔNa+memand enhanced ΔNa+endin rat gliomas. Specifically, RG2 and U87 tumors maintained weakened ΔNa+mem(i.e., depolarizedVm) implying an aggressive state for proliferation, and RG2 tumors displayed elevated ΔNa+endsuggesting altered BBB integrity.23Na-MRSI will allow explorations ...

Research paper thumbnail of Advanced magnetic resonance techniques in early differentiation of pseudo-progression vs. progression in patients with glioblastoma multiforme

Vojnosanitetski pregled, 2017

Background/Aim. The diagnosis of glioblastoma multiforme progression may be confounded by a pheno... more Background/Aim. The diagnosis of glioblastoma multiforme progression may be confounded by a phenomena termed pseudoprogression (PSP) and pseudoresponse (RCT) which has become more common with the adoption of radiation therapy with concurrent and adjuvant application of temozolomide (CRT). Distinguishing of these phenomena is based on the follow-up scans since no single imaging method or technique is yet capable of performing their discrimination. In this study, we evaluated the dynamic susceptibility contrast (DSC perfusion) imaging and magnetic resonance (MR) spectroscopy to predict the prognosis and time to progression in the patients with glioblastoma multiforme. Methods. Fourty patients with primary glioblastoma multiforme were included in the analysis. The patients were examined in 3rd week after surgery and 10th week after the beginning of CRT. The MR exams were performed using the 1.5 T MR scanner (Avanto; Siemens, Erlangen, Germany). The maps of perfusion parameters and time...

Research paper thumbnail of The application of local histograms of apparent difusion coefficient in differentiation of brain astrocytomas

Vojnosanitetski pregled, 2017

Background/Aim. Microstructural diversity of brain astrocytomas makes their diagnostics and diffe... more Background/Aim. Microstructural diversity of brain astrocytomas makes their diagnostics and differentiation by using the diffusion weighted imaging (DWI) difficult. In this study we used the histogram-based positioning of regions of interests on the apparent diffusion coefficient (ADC) maps in order to restrict the determination of diffusion parameters to regions of interest (ROI) corresponding to maximum cellularity. Success of ADC standard deviation (?ADC) and kurtosis (K) in differentiation of brain astrocytomas was evaluated. Methods. The thirtyone patients (16 women and 15 men, median age 37 years, age range 6?72 years) with suspected supratentorial astrocytomas were included in the retrospective study. The magnetic resonance imaging (MRI) examinations were performed using the 1.5 T MR system (Avanto; Siemens, Erlangen, Germany) and 8-channel phased array head coil. The DWI images were acquired in three orthogonal directions for the b-values 0, 500 and 1000 s mm-2. The histogra...

Research paper thumbnail of Evaluating U-net Brain Extraction for Multi-site and Longitudinal Preclinical Stroke Imaging

Rodent stroke models are important for evaluating treatments and understanding the pathophysiolog... more Rodent stroke models are important for evaluating treatments and understanding the pathophysiology and behavioral changes of brain ischemia, and magnetic resonance imaging (MRI) is a valuable tool for measuring outcome in preclinical studies. Brain extraction is an essential first step in most neuroimaging pipelines; however, it can be challenging in the presence of severe pathology and when dataset quality is highly variable. Convolutional neural networks (CNNs) can improve accuracy and reduce operator time, facilitating high throughput preclinical studies. As part of an ongoing preclinical stroke imaging study, we developed a deep-learning mouse brain extraction tool by using a U-net CNN. While previous studies have evaluated U-net architectures, we sought to evaluate their practical performance across data types. We ask how performance is affected with data across: six imaging centers, two time points after experimental stroke, and across four MRI contrasts. We trained, validated, and tested a typical U-net model on 240 multimodal MRI datasets including quantitative multi-echo T2 and apparent diffusivity coefficient (ADC) maps, and performed qualitative evaluation with a large preclinical stroke database (N=1,368). We describe the design and development of this system, and report our findings linking data characteristics to segmentation performance. We consistently found high accuracy and ability of the U-net architecture to generalize performance in a range of 95-97% accuracy, with only modest reductions in performance based on lower fidelity imaging hardware and brain pathology. This work can help inform the design of future preclinical rodent imaging studies and improve their scalability and reliability.