High-Resolution CT for Small-Animal Imaging Research

Preclinical imaging has a critical role in phenotyping, in drug discovery, and in providing a basic understanding of mechanisms of disease. Translating imaging methods from humans to small animals is not an easy task. The purpose of this work is to review high-resolution computed tomography (CT) also known as micro-CT for small-animal imaging. We present the principles, the technologies, the image quality parameters, and the types of applications. We show that micro-CT can be used to provide not only morphological but also functional information such as cardiac function or vascular permeability. Another way in which micro-CT can be used in the study of both function and anatomy is by combining it with other imaging modalities, such as positron emission tomography or single-photon emission tomography. Compared to other modalities, micro-CT imaging is usually regarded as being able to provide higher throughput at lower cost and higher resolution. The limitations are usually associated with the relatively poor contrast mechanisms and the radiation damage, although the use of novel nanoparticle-based contrast agents and careful design of studies can address these limitations.

Correction for Eddy Current-Induced Echo-Shifting Effect in Partial-Fourier Diffusion Tensor Imaging.

In most diffusion tensor imaging (DTI) studies, images are acquired with either a partial-Fourier or a parallel partial-Fourier echo-planar imaging (EPI) sequence, in order to shorten the echo time and increase the signal-to-noise ratio (SNR). However, eddy currents induced by the diffusion-sensitizing gradients can often lead to a shift of the echo in k-space, resulting in three distinct types of artifacts in partial-Fourier DTI. Here, we present an improved DTI acquisition and reconstruction scheme, capable of generating high-quality and high-SNR DTI data without eddy current-induced artifacts. This new scheme consists of three components, respectively, addressing the three distinct types of artifacts. First, a k-space energy-anchored DTI sequence is designed to recover eddy current-induced signal loss (i.e., Type 1 artifact). Second, a multischeme partial-Fourier reconstruction is used to eliminate artificial signal elevation (i.e., Type 2 artifact) associated with the conventional partial-Fourier reconstruction. Third, a signal intensity correction is applied to remove artificial signal modulations due to eddy current-induced erroneous T2(∗) -weighting (i.e., Type 3 artifact). These systematic improvements will greatly increase the consistency and accuracy of DTI measurements, expanding the utility of DTI in translational applications where quantitative robustness is much needed.

Development and Optimization of Four-dimensional Magnetic Resonance Imaging (4D-MRI) for Radiation Therapy

A tenet of modern radiotherapy (RT) is to identify the treatment target accurately, following which the high-dose treatment volume may be expanded into the surrounding tissues in order to create the clinical and planning target volumes. Respiratory motion can induce errors in target volume delineation and dose delivery in radiation therapy for thoracic and abdominal cancers. Historically, radiotherapy treatment planning in the thoracic and abdominal regions has used 2D or 3D images acquired under uncoached free-breathing conditions, irrespective of whether the target tumor is moving or not. Once the gross target volume has been delineated, standard margins are commonly added in order to account for motion. However, the generic margins do not usually take the target motion trajectory into consideration. That may lead to under- or over-estimate motion with subsequent risk of missing the target during treatment or irradiating excessive normal tissue. That introduces systematic errors into treatment planning and delivery. In clinical practice, four-dimensional (4D) imaging has been popular in For RT motion management. It provides temporal information about tumor and organ at risk motion, and it permits patient-specific treatment planning. The most common contemporary imaging technique for identifying tumor motion is 4D computed tomography (4D-CT). However, CT has poor soft tissue contrast and it induce ionizing radiation hazard. In the last decade, 4D magnetic resonance imaging (4D-MRI) has become an emerging tool to image respiratory motion, especially in the abdomen, because of the superior soft-tissue contrast. Recently, several 4D-MRI techniques have been proposed, including prospective and retrospective approaches. Nevertheless, 4D-MRI techniques are faced with several challenges: 1) suboptimal and inconsistent tumor contrast with large inter-patient variation; 2) relatively low temporal-spatial resolution; 3) it lacks a reliable respiratory surrogate. In this research work, novel 4D-MRI techniques applying MRI weightings that was not used in existing 4D-MRI techniques, including T2/T1-weighted, T2-weighted and Diffusion-weighted MRI were investigated. A result-driven phase retrospective sorting method was proposed, and it was applied to image space as well as k-space of MR imaging. Novel image-based respiratory surrogates were developed, improved and evaluated.

Radiotherapy Assessment Using Diffusion Weighted MRI

Purpose: There are two goals of this study. The first goal of this study is to investigate the feasibility of using classic textural feature extraction in radiotherapy response assessment among a unique cohort of early stage breast cancer patients who received the single-dose preoperative radiotherapy. The second goal of this study is to investigate the clinical feasibility of using classic texture features as potential biomarkers which are supplementary to regional apparent diffusion coefficient in gynecological cancer radiotherapy response assessment.

Methods and Materials: For the breast cancer study, 15 patients with early stage breast cancer were enrolled in this retrospective study. Each patient received a single-fraction radiation treatment, and DWI and DCE-MRI scans were conducted before and after the radiotherapy. DWI scans were acquired using a spin-echo EPI sequence with diffusion weighting factors of b = 0 and b = 500 mm2/s, and the apparent diffusion coefficient (ADC) maps were calculated. DCE-MRI scans were acquired using a T1-weighted 3D SPGR sequence with a temporal resolution of about 1 minute. The contrast agent (CA) was intravenously injected with a 0.1 mmol/kg bodyweight dose at 2 ml/s. Two parameters, volume transfer constant (Ktrans) and kep were analyzed using the two-compartment Tofts pharmacokinetic model. For pharmacokinetic parametric maps and ADC maps, 33 textural features were generated from the clinical target volume (CTV) in a 3D fashion using the classic gray level co-occurrence matrix (GLCOM) and gray level run length matrix (GLRLM). Wilcoxon signed-rank test was used to determine the significance of each texture feature’s change after the radiotherapy. The significance was set to 0.05 with Bonferroni correction.

For the gynecological cancer study, 12 female patients with gynecologic cancer treated with fractionated external beam radiotherapy (EBRT) combined with high dose rate (HDR) intracavitary brachytherapy were studied. Each patient first received EBRT treatment followed by five fractions of HDR treatment. Before EBRT and before each fraction of brachytherapy, Diffusion Weighted MRI (DWI-MRI) and CT scans were acquired. DWI scans were acquired in sagittal plane utilizing a spin-echo echo-planar imaging sequence with weighting factors of b = 500 s/mm2 and b = 1000 s/mm2, one set of images of b = 0 s/mm2 were also acquired. ADC maps were calculated using linear least-square fitting method. Distributed diffusion coefficient (DDC) maps and stretching parameter α were calculated. For ADC and DDC maps, 33 classic texture features were generated utilizing the classic gray level run length matrix (GLRLM) and gray level co-occurrence matrix (GLCOM) from high-risk clinical target volume (HR-CTV). Wilcoxon signed-rank statistics test was applied to determine the significance of each feature’s numerical value change after radiotherapy. Significance level was set to 0.05 with multi-comparison correction if applicable.

Results: For the breast cancer study, regarding ADC maps calculated from DWI-MRI, 24 out of 33 CTV features changed significantly after the radiotherapy. For DCE-MRI pharmacokinetic parameters, all 33 CTV features of Ktrans and 33 features of kep changed significantly.

For the gynecological cancer study, regarding ADC maps, 28 out of 33 HR-CTV texture features showed significant changes after the EBRT treatment. 28 out of 33 HR-CTV texture features indicated significant changes after HDR treatments. The texture features that indicated significant changes after HDR treatments are the same as those after EBRT treatment. 28 out of 33 HR-CTV texture features showed significant changes after whole radiotherapy treatment process. The texture features that indicated significant changes for the whole treatment process are the same as those after HDR treatments.

Conclusion: Initial results indicate that certain classic texture features are sensitive to radiation-induced changes. Classic texture features with significant numerical changes can be used in monitoring radiotherapy effect. This might suggest that certain texture features might be used as biomarkers which are supplementary to ADC and DDC for assessment of radiotherapy response in breast cancer and gynecological cancer.