Feasibility of 4D CT simulation with synchronized intravenous contrast injection in hepatocellular carcinoma.

BACKGROUND: Delivering Stereotactic Body Radiotherapy (SBRT) for Hepatocellular Carcinoma (HCC) is challenging mainly for two reasons: first, motion of the liver occurs in six degrees of freedom and, second, delineation of the tumor is difficult owing to a similar density of HCC to that of the adjoining healthy liver tissue in a non-contrast CT scan. To overcome both these challenges simultaneously, we performed a feasibility study to synchronize intravenous contrast to obtain an arterial and a delayed phase 4D CT. MATERIALS AND METHODS: We included seven HCC patients of planned for SBRT. 4D CT simulation was performed with synchronized intravenous contrast based on the formula TSCAN DELAY = T peak - (L0/Detector Coverage × Cine Duration in Seconds). This was followed by a delayed 4D CT scan. RESULTS: We found that, with our protocol, it is feasible to obtain a 4DCT with an arterial and a delayed phase making it comparable to a diagnostic multi-phase CT. The peak HU of the 4D scan and diagnostic CT were similar (mean peak HU 134.2 vs 143.1, p value = 0.58 N.S). Whereas in comparison with a non-contrast CT a significant rise in the peak HU was seen (mean peak 134.2 vs 61.4 p value = .00003). CONCLUSION: A synchronized contrast 4D CT simulation for HCC is safe and feasible. It results in good contrast enhancement comparable to a diagnostic 3D contrast CT scan.

Denoising of iodine-131 images using a median filter.

OBJECTIVE: An iodine-131 (I) image visually appears to be contaminated with impulse noise. The two-dimensional median filter removes noise without sacrificing the edge information. Its performance depends on the shape and size of the mask. In this study, we have compared the performance of a plus-shape and a square-shape median filter for I whole-body images and found the filter with optimum parameter that improves I image quality acceptable to nuclear medicine physicians. MATERIALS AND METHODS: A total of 150 whole-body I images were exported in DICOM format. These images were converted into PNG format and processed with a plus-shape and a square-shape median filter, with each shape mask having sizes of 3, 5, 7, and 9 pixels. The quality of the processed images was assessed by visual assessment by two nuclear medicine physicians and also quantitatively by evaluating metrics: mutual information, mean square error, peak signal-to-noise ratio, and difference entropy. Nuclear medicine physicians assigned a score to each image on the scale 1 (lowest) to 5 (highest) for image quality on the basis of the noise removal, smoothness, and edge information available in the image. Student's t-test was carried out to find the significant difference in the image quality (α=0.05) between the processed images with square-shape and cross-shape mask with the same pixel size. All experiments including statistical analysis were conducted using R installed on a personal computer. RESULTS: Both median filters improved the image quality of I images. The plus-shape median filter was found to show better performance in comparison with the square-shape median filter (P<0.001). The plus-shape median filter with a mask size of 7 pixels was found to be optimum for the processing of whole-body I images. CONCLUSION: The plus-shape median filter with a mask size of 7 pixels can be used to process whole-body I scintigraphic images without loss of clinical information.

Calculating Gamma Camera Uniformity Parameters: Beyond the Vendor-specific Protocol.

OBJECTIVES: The aim of this study was to develop and verify a personal computer-based software tool for calculating uniformity indices of gamma camera. MATERIALS AND METHODS: The program was developed in MATLAB R2013b under Microsoft Windows operating system. Noise-less digital phantoms with known uniformity parameters were used to verify the accuracy of the program. Two hundred and forty-four Co-57 flood source images were acquired on Symbia T6 and Discovery nuclear medicine/computed tomography 670. The uniformity indices of these images were determined with their respective vendor's software and also by the tool developed. Bland-Altman plots were used for measuring the agreements between the developed program and the vendor's program for the calculation of uniformity indices. RESULTS: The tool for calculating uniformity indices was found to be accurate. Uniformity indices measured with the tool revealed a very good correlation with vendor's software based on Bland-Altman analysis, as almost all measurements were within the ±2 standard deviation range. CONCLUSION: The software tool for calculation of uniformity indices is accurate, and the uniformity indices calculated by it are in agreement with uniformity indices calculated by the vendor's software.

Development of a Simple Image Processing Application that Makes Abdominopelvic Tumor Visible on Positron Emission Tomography/Computed Tomography Image.

INTRODUCTION: In this study, we have developed a simple image processing application in MATLAB that uses suprathreshold stochastic resonance (SSR) and helps the user to visualize abdominopelvic tumor on the exported prediuretic positron emission tomography/computed tomography (PET/CT) images. METHODS: A brainstorming session was conducted for requirement analysis for the program. It was decided that program should load the screen captured PET/CT images and then produces output images in a window with a slider control that should enable the user to view the best image that visualizes the tumor, if present. The program was implemented on personal computer using Microsoft Windows and MATLAB R2013b. RESULTS: The program has option for the user to select the input image. For the selected image, it displays output images generated using SSR in a separate window having a slider control. The slider control enables the user to view images and select one which seems to provide the best visualization of the area(s) of interest. CONCLUSION: The developed application enables the user to select, process, and view output images in the process of utilizing SSR to detect the presence of abdominopelvic tumor on prediuretic PET/CT image.

Development and Validation of the Suprathreshold Stochastic Resonance-Based Image Processing Method for the Detection of Abdomino-pelvic Tumor on PET/CT Scans.

PURPOSE: The detection of abdomino-pelvic tumors embedded in or nearby radioactive urine containing 18F-FDG activity is a challenging task on PET/CT scan. In this study, we propose and validate the suprathreshold stochastic resonance-based image processing method for the detection of these tumors. METHODS: The method consists of the addition of noise to the input image, and then thresholding it that creates one frame of intermediate image. One hundred such frames were generated and averaged to get the final image. The method was implemented using MATLAB R2013b on a personal computer. Noisy image was generated using random Poisson variates corresponding to each pixel of the input image. In order to verify the method, 30 sets of pre-diuretic and its corresponding post-diuretic PET/CT scan images (25 tumor images and 5 control images with no tumor) were included. For each sets of pre-diuretic image (input image), 26 images (at threshold values equal to mean counts multiplied by a constant factor ranging from 1.0 to 2.6 with increment step of 0.1) were created and visually inspected, and the image that most closely matched with the gold standard (corresponding post-diuretic image) was selected as the final output image. These images were further evaluated by two nuclear medicine physicians. RESULTS: In 22 out of 25 images, tumor was successfully detected. In five control images, no false positives were reported. Thus, the empirical probability of detection of abdomino-pelvic tumors evaluates to 0.88. CONCLUSION: The proposed method was able to detect abdomino-pelvic tumors on pre-diuretic PET/CT scan with a high probability of success and no false positives.