Po-Chou Chen

The Impact of Flip Angle and TR on the Enhancement Ratio of Dynamic Gadobutrol-enhanced MR Imaging: In Vivo VX2 Tumor Model and Computer Simulation

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is widely used to diagnose cancer and monitor therapy. The maximum enhancement ratio (ERmax) obtained from the curve of signal intensity over time could be a biomarker to distinguish cancer from normal tissue or benign tumors. We evaluated the impact of flip angle (FA) and repetition time (TR) on the ERmax values of dynamic gadobutrol-enhanced MR imaging, obtaining T1-weighted (T1W) MR imaging of VX2 tumors using 2-dimensional fast spoiled gradient echo (2D FSPGR) with various FAs (30°, 60° and 90°) at 1.5 tesla before and after injection of 0.1 mmol/kg gadobutrol. In vivo study indicated significant differences between ERmax values and area under the ER-time curve (AUC100) of VX2 tumors and muscle tissue, with the highest ERmax and AUC100 at FA 90°. Computer simulation also demonstrated the ER as a strictly increasing monotonic function in the closed interval [0°, 90°] for a given TR when using T1W FSPGR, and the highest ER value always occurred at FA 90°. The FA for the highest ER differed from that for the highest signal-to-noise or contrast-to-noise ratio. For long TR, the ER value increases gradually. However, for short TR, the ER value increases rapidly and plateaus so that the ER value changes little beyond a certain FA value. Therefore, we suggest use of a higher FA, near 90°, to obtain a higher ERmax for long TR in 2D SPGR or FSPGR and a smaller FA, much less than 90°, to reach an appropriate ERmax for short TR in 3D SPGR or FSPGR. This information could be helpful in setting the optimal parameters for DCE-MRI.

Effect of gadobutrol on VX2 magnetic resonance diffusion-weighted imaging

The aim of this study was to evaluate the effect of contrast agent gadobutrol on the magnetic resonance diffusion-weighted imaging (MR DWI). Gadobutrol has higher relaxivity than Gd-DTPA and it also has higher formulation 1.0 M than Gd-DTPA 0.5 M. VX2 tumor implanted on the left thigh of each New Zealand rabbit was used as the animal model. The MR scanning was performed using a 1.5 T clinical whole-body MR scanner with an 8-channel knee coil. The results showed that there were significant differences in the signal-to-noise ratio (SNR) and apparent diffusion coefficient (ADC) values between tumor and muscle both before and after gadobutrol injection (0.1 mmol/kg). However, there were no significant differences in the SNR and ADC values of tumor or muscle before and after gadobutol administration. There were also no significant difference in the contrast-to-noise ratio (CNR) values of tumor and muscle before and after gadobutrol injection.

Monitoring of VX2 tumor growth in rabbit liver using T2-weighted and dynamic contrast-enhanced magnetic resonance imaging at 1.5T

This study aimed to investigate the VX2 tumor growth in rabbit liver using T2-weighted imaging (T2WI) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Five New Zealand white (NZW) rabbits were implanted with VX2 cell suspension in liver. Afterwards, MRI was performed 7, 14, 21 and 28 days after tumor implantation. A 1.5T clinical MRI scanner was used to perform scans. After 3-plane localizer, T1 weighted imaging (T1WI), T2WI, and DCE-MRI using a three-dimensional gradient echo pulse sequence was performed. After 4 pre-contrast images were acquired, each rabbit was injected i.v. with 0.1 mmol/kg Dotarem. The total scan time after Dotarem administration was 30 minutes. All acquired images were analyzed using ImageJ software. Several regions of interest were selected from the rims of tumor, liver, and muscle. The enhancement ratio (ER) was calculated by dividing the MR signal after Dotarem injection to the MR signal before Dotarem injection. The maximum ER (ER_max) value of tumor for each rabbit was observed right after the Dotarem injection. The T2W MR signal intensities (T2W_SI) and the ER_max values obtained 7, 14, 21 and 28 days after tumor implantation were analyzed with a linear regression algorithm. Both T2W_SI and ER_max of tumors increased with time. The changes for T2W_SI and ER_max of tumors between 7 and 28 days after tumor implantation were 32.66% and 18.14%, respectively. T2W_SI is more sensitive than ER_max for monitoring the growth of VX2 tumor in a rabbit liver model.

Monitoring Fractional Anisotropy in Developing Rabbit Brain Using MR Diffusion Tensor Imaging at 3T

The aim of this study was to investigate the factional anisotropy (FA) in various regions of developing rabbit brain using magnetic resonance diffusion tensor imaging (MR DTI) at 3 T. A whole-body clinical MR imaging (MRI) scanner with a 15-channel high resolution knee coil was used. An echo-planar-imaging (EPI)-DTI pulse sequence was performed. Five 5 week-old New Zealand white (NZW) rabbits underwent MRI once per week for 24 weeks. After scanning, FA maps were obtained. ROIs (regions of interests) in the frontal lobe, parietal & temporal lobe, and occipital lobe were measured. FA changes with time were evaluated with a linear regression analysis. The results show that the FA values in all lobes of the brain increased linearly with age. The ranking of FA values was FA(frontal lobe) < FA(parietal & temporal lobe) > FA(occipital lobe). There was significant difference (p < 0.05) among these lobes. FA values are associated with the nerve development and brain functions. The FA change rate could be a biomarker to monitor the brain development. Understanding the FA values of various lobes during development could provide helpful information to diagnosis the abnormal syndrome earlier and have a better treatment and prognosis. This study established a brain MR-DTI protocol for rabbits to investigate the brain anatomy during development using clinical MRI. This technique can be further applied to the pre-clinical diagnosis, treatment, prognosis and follow-up of brain lesions.

QUANTIFYING ACTIVE CONTOUR MODEL (ACM) SEGMENTED REGION USING EDGE-LINKING AND REGION-FILLING ALGORITHM (ERA)

Active contour model (ACM) algorithm is an effective and accurate method to segment out the regions of interest (ROIs) and has been widely used in many clinical imaging systems. In addition to segmenting out the lesion contour, how to accurately quantify the area/volume of the lesion is also important and challenging. Some quantification methods performed manually are time-consuming. To increase the accuracy and efficiency in quantifying the ACM segmented regions, a simple, straightforward, accurate and efficient automatic region quantification method with edge-linking and region-filling algorithm (ERA) for the ACM segmented regions was developed. Three types of computer simulated images, namely closed contour simulated images (CCSIs), discrete contour simulated images (DCSIs) and intact region simulated images (IRSIs) were created to evaluate the accuracy of the region-filling process, edge-linking process and ERA after ACM image segmentation process, respectively. Furthermore, the results of ERA were compared with those of the direct subtraction method (DSM). The ERA was also applied to quantify the area/volume of an irregularly-shaped lymphoma in a MR brain image. The results showed that the average percentage errors on the region-filling process, edge-linking process and ERA (0%, 0.03% and 7.52%, respectively) were significantly lower than those of DSM (15.85%, 15.08% and 20.36%, respectively) in quantifying the ROIs. The application of ERA to quantify the area/volume of an irregularly-shaped lymphoma in a MR brain image was successfully demonstrated. In conclusions, ERA outperforms the DSM in quantifying the area/volume of ACM segmented regions and might increase the efficiency and accuracy in clinical diagnosis and treatment.

OPTIMAL CONCENTRATIONS OF GADOVIST IN T1-WEIGHTED MAGNETIC RESONANCE IMAGING: PHANTOM STUDY AND COMPUTER SIMULATION

Contrast-Enhanced Magnetic Resonance Imaging (CE-MRI) has been widely used in the diagnosis of lesions. Many contrast agents with various chemical and pharmacokinetic properties have been developed for clinical use. The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) after the contrast agent administration depend on many factors, e.g. category and injected dosage of contrast agents, field strength of magnetic resonance (MR) scanner, slew rate of gradient, type of radiofrequency coil, reconstruction algorithm, pulse sequences, and so on. Gadovist is a newly developed contrast agent with high formulation of 1.0 M. It has been used in MR angiography and perfusion studies. The aim of this study is to investigate the optimal concentrations of Gadovist in MR T1-weighted (T1W) images from phantom study and computer simulation. A phantom made of 21 test tubes with various concentrations of Gadovist (0–160 mM) was investigated. All the studies were performed on a 1.5-T clinical whole-body scanner. Four T1W pulse sequences, including two-dimensional spoiled gradient echo (2DSPGR), three-dimensional fast spoiled gradient echo (3DFSPGR), conventional spin echo (CSE), and inversion recovery (IR) were employed to produce T1W images. The CNR values were calculated from regions of interest (ROIs) of all test tubes and the optimal concentration for each pulse sequence was determined. The T1 and T2 values of the phantom were also measured to obtain the relaxivities (r1 and r2). Afterward, the optimal concentration for each pulse sequence could be obtained from computer simulation by using the r1 and r2 values. The results showed that the measured optimal concentrations for 2DSPGR, 3DFSPGR, CSE and IR are 10, 20, 2.5, and 2.5 mM, respectively. The r1 and r2 values of the Gadovist phantom are 4.1 and 5.7 mM-1s-1, respectively. The optimal concentrations obtained from computer simulation are 13.5, 22.8, 2.0, and 2.7 mM for 2DSPGR, 3DFSPGR, CSE, and IR, respectively. The optimal concentrations obtained from computer simulation and phantom study are in good agreement.

Host Specific Codon Usage Pattern of H1N1 Influenza A Viruses

Codon usage preference and the highly expressed genes have strong correlations occur in many organisms. Codon usage preference of viruses may evolve much similar with its infected host to increase the fitness. In this study we investigated differences in codon usage preferences among influenza A H1N1 viruses which infected avian, swine and human, and may cause major pandemic around world. The relative synonymous codon usage (RSCU) indices of HA gene in H1N1 viruses were calculated and we further incorporate the principal component analysis (PCA) to characterizing different host infected viruses. Host-specific codon usage pattern of H1N1 viruses were reported in this study. In 2009 influenza A H1N1 virus was a major epidemic challenge of disease control department. We propose to use the codon based method to gain a better understanding of the features of virus genome and evolutionary processes.

Evaluating the effects of chronic MDMA abuses on cerebral metabolism using proton magnetic resonance spectroscopy ( 1 H-MRS)

MDMA is a widely abused amphetamine derivative that alters serotonin (5-HT) release via the reverse serotonin re-uptake transporter (SERT) mechanism. This phenomenon leads to neurotoxicity in the synaptic clefts, especially in the striatum. As the major function of the striatum is planning and modulating movement pathways and cognitive processes, the objective of this study is to investigate the neuronal viability of chronic MDMA-influenced rats, as well as the effect of re-challenged MDMA.

Volume quantification for the ACM segmented regions

Active contour model (ACM) algorithm has been proven to be an efficient and accurate method to segment out the regions of interest even in the images with high noise or low contrast. Some quantification methods are time consuming because they are performed manually. A new volume quantification method was proposed for quantifying the ACM segmented regions. The purpose of this study is to develop a simple, straight forward, accurate and efficient automatic volume quantification method with edge linking and region filling processes (AVQM) for the ACM segmented regions. Three computer simulated images were created to evaluate the accuracy of the proposed method. These simulated images were used for the accuracy evaluations. Furthermore, the results of AVQM were compared with those of the direct counting method (DCM). It is found that the average percentage error of AVQM (9.24%) is significantly lower than those of DCM (42.88%) in quantifying the regions of interest. In conclusion, AVQM is more accurate and more reliable than DCM in quantifying the volume of ACM segmented regions.

The Quantitative Assessment of Gd-DTPA in Contrast Enhanced Magnetic Resonance Angiography

Recently, the use of MRI contrast agents has been proven to be substantially improved sensitivity and specificity in many clinical applications. CE-MRA has higher blood signal based on the T1 and T2-shortening property of contrast agents, so that even the small vessels can be visualized. The use of contrast agents can improve lesion detection and characterization. The routinely used dose of contrast agents in the routine MRI examinations only relies on the weight of the subject. The purpose of this study is to obtain the clinically optimal dose for 3D-TOF (time-of-flight) pulse sequences for CE-MRA examinations. In the phantom study, ten test tubes were filled with saline mixed with different dose of Gd-DTPA. It is found that the optimal dose of Gd-DTPA for saline phantom by using 3D-TOF pulse sequences is 20 mM. Also, there has no differences of optimal doses between Omniscan and Magnivist contrast agents Gd-DTPA. The results show that consistent high quality CE-MRA images might be obtained by using 0.25M Gd-DTPA (half of the routine dose) with 3~4 cc/sec injection rate for all clinical cases. The benefits of this study might be to minimize dose and potential toxicity. Additionally, the decrease of the cost of contrast agents might be achieved. It is expected to provide the recommended dose of Gd-DTPA for contrast enhanced MRA in clinical routine diagnosis