Rena Widita

Automated Calculation of Water-equivalent Diameter (DW) Based on AAPM Task Group 220

The purpose of this study is to accurately and effectively automate the calculation of the water‐equivalent diameter (DW) from 3D CT images for estimating the size‐specific dose. DW is the metric that characterizes the patient size and attenuation. In this study, DW was calculated for standard CTDI phantoms and patient images. Two types of phantom were used, one representing the head with a diameter of 16 cm and the other representing the body with a diameter of 32 cm. Images of 63 patients were also taken, 32 who had undergone a CT head examination and 31 who had undergone a CT thorax examination. There are three main parts to our algorithm for automated DW calculation. The first part is to read 3D images and convert the CT data into Hounsfield units (HU). The second part is to find the contour of the phantoms or patients automatically. And the third part is to automate the calculation of DW based on the automated contouring for every slice (DW,all). The results of this study show that the automated calculation of DW and the manual calculation are in good agreement for phantoms and patients. The differences between the automated calculation of DW and the manual calculation are less than 0.5%. The results of this study also show that the estimating of DW,all using DW,n=1 (central slice along longitudinal axis) produces percentage differences of −0.92%±3.37% and 6.75%±1.92%, and estimating DW,all using DW,n=9 produces percentage differences of 0.23%±0.16% and 0.87%±0.36%, for thorax and head examinations, respectively. From this study, the percentage differences between normalized size‐specific dose estimate for every slice (nSSDEall) and nSSDEn=1 are 0.74%±2.82% and −4.35%±1.18% for thorax and head examinations, respectively; between nSSDEall and nSSDEn=9 are 0.00%±0.46% and −0.60%±0.24% for thorax and head examinations, respectively. PACS number(s): 87.57.Q‐, 87.57.uq‐The purpose of this study is to accurately and effectively automate the calculation of the water-equivalent diameter (DW) from 3D CT images for estimating the size-specific dose. DW is the metric that characterizes the patient size and attenuation. In this study, DW was calculated for standard CTDI phantoms and patient images. Two types of phantom were used, one representing the head with a diameter of 16 cm and the other representing the body with a diameter of 32 cm. Images of 63 patients were also taken, 32 who had undergone a CT head examination and 31 who had undergone a CT thorax examination. There are three main parts to our algorithm for automated DW calculation. The first part is to read 3D images and convert the CT data into Hounsfield units (HU). The second part is to find the contour of the phantoms or patients automatically. And the third part is to automate the calculation of DW based on the automated contouring for every slice (DW,all). The results of this study show that the automated calculation of DW and the manual calculation are in good agreement for phantoms and patients. The differences between the automated calculation of DW and the manual calculation are less than 0.5%. The results of this study also show that the estimating of DW,all using DW,n=1 (central slice along longitudinal axis) produces percentage differences of -0.92%±3.37% and 6.75%±1.92%, and estimating DW,all using DW,n=9 produces percentage differences of 0.23%±0.16% and 0.87%±0.36%, for thorax and head examinations, respectively. From this study, the percentage differences between normalized size-specific dose estimate for every slice (nSSDEall) and nSSDEn=1 are 0.74%±2.82% and -4.35%±1.18% for thorax and head examinations, respectively; between nSSDEall and nSSDEn=9 are 0.00%±0.46% and -0.60%±0.24% for thorax and head examinations, respectively. PACS number(s): 87.57.Q-, 87.57.uq.

A fully automated calculation of size-specific dose estimates (SSDE) in thoracic and head CT examinations

The purpose of this study is to automatically calculate and then investigate the size- specific dose estimate (SSDE) in thoracic and head CT examinations undertaken using standard imaging protocols. The effective diameter (Deff ), the water equivalent diameter (Dw ), and the SSDE were calculated automatically from patient images. We investigated sixteen adult patients who underwent a CT head examination and thirty adult patients who underwent a CT thorax examination. Our results showed that the Dw value in the thoracic region was 4.5% lower than the value of Deff , while the Dw value in the head region was 8.6% higher than the value of Deff . The relationships between diameter (Deff and Dw ) and CTDIvol were distinctive. In the head region, decreasing the patient diameter resulted in a constant CTDIvol due to the tube current modulation (TCM) being off, while in the thoracic region decreasing the patient diameter resulted in a decrease in value of CTDIvol due to TCM being on. In the head region, decreasing the patient diameter resulted in an increase in the value of SSDE, while in the thoracic region decreasing the patient diameter resulted in a decrease in the value of SSDE.

Profile of CT scan output dose in axial and helical modes using convolution

The profile of the CT scan output dose is crucial for establishing the patient dose profile. The purpose of this study is to investigate the profile of the CT scan output dose in both axial and helical modes using convolution. A single scan output dose profile (SSDP) in the center of a head phantom was measured using a solid-state detector. The multiple scan output dose profile (MSDP) in the axial mode was calculated using convolution between SSDP and delta function, whereas for the helical mode MSDP was calculated using convolution between SSDP and the rectangular function. MSDPs were calculated for a number of scans (5, 10, 15, 20 and 25). The multiple scan average dose (MSAD) for differing numbers of scans was compared to the value of CT dose index (CTDI). Finally, the edge values of MSDP for every scan number were compared to the corresponding MSAD values. MSDPs were successfully generated by using convolution between a SSDP and the appropriate function. We found that CTDI only accurately estimates MSAD when the number of scans was more than 10. We also found that the edge values of the profiles were 42% to 93% lower than that the corresponding MSADs.

A SIMPLE METHOD FOR CALIBRATING PIXEL VALUES OF THE CT LOCALIZER RADIOGRAPH FOR CALCULATING WATER-EQUIVALENT DIAMETER AND SIZE-SPECIFIC DOSE ESTIMATE

The purpose of this study is to establish the relationship between the pixel value (I) of the CT localizer radiograph and water-equivalent thickness (tw) in a straightforward procedure. We used a body CTDI phantom, which was scanned in the AP and LAT projections. After transformation from the pixel values of the images to tw, water-equivalent diameter (Dw) and size-specific dose estimate were calculated on an anthropomorphic phantom and 30 patients retrospectively. We found a linear correlation between I and tw, with R2 ≥ 0.980. The Dw values based on the CT localizer radiograph were comparable to those calculated using axial images. The Dw difference for the anthropomorphic phantom between AP projection and axial images was 5.4 ± 4.2%, and between LAT projection and axial images was 6.7 ± 5.3%. The Dw differences for the patients between CT localizer radiograph and axial images was 2.3 ± 3.2%.

New noise reduction method for reducing CT scan dose: Combining Wiener filtering and edge detection algorithm

New noise reduction method for reducing dose of CT scans has been proposed. The new method is expected to address the major problems in the noise reduction algorithm, i.e. the decreasing in the spatial resolution of the image. The proposed method was developed by combining adaptive Wiener filtering and edge detection algorithms. The first step, the image was filtered with a Wiener filter. Separately, edge detection operation performed on the original image using the Prewitt method. The next step, a new image was generated based on the edge detection operation. At the edge area, the image was taken from the original image, while at the non-edge area, the image was taken from the image that had been filtered with a Wiener filter. The new method was tested on a CT image of the spatial resolution phantom, which was scanned by different current-time multiplication, namely 80, 130 and 200 mAs, while other exposure factors were kept in constant conditions. The spatial resolution phantom consists of six sets of bar pattern made of plexi-glass and separated at some distance by water. The new image quality assessed from the amount of noise and the magnitude of spatial resolution. Noise was calculated by determining the standard deviation of the homogeneous regions, while the spatial resolution was assessed by observation of the area sets of the bar pattern. In addition, to evaluate the performance of this new method has also been tested on patient CT images. From the measurements, the new method can reduce the noise to an average 64.85%, with a spatial resolution does not decrease significantly. Visually, the third set bar on the image phantom (the distance between the bar 1.0 mm) can still be distinguished, as well as on the original image. Meanwhile, if the image is only processed using Wiener filter, the second set bar (the distance between the bar 1.3 mm) are distinguishable. Testing this new method to patient image, its results in relatively the same. Thus, using this new method, it provides the potential for dose reduction more than 60%.New noise reduction method for reducing dose of CT scans has been proposed. The new method is expected to address the major problems in the noise reduction algorithm, i.e. the decreasing in the spatial resolution of the image. The proposed method was developed by combining adaptive Wiener filtering and edge detection algorithms. The first step, the image was filtered with a Wiener filter. Separately, edge detection operation performed on the original image using the Prewitt method. The next step, a new image was generated based on the edge detection operation. At the edge area, the image was taken from the original image, while at the non-edge area, the image was taken from the image that had been filtered with a Wiener filter. The new method was tested on a CT image of the spatial resolution phantom, which was scanned by different current-time multiplication, namely 80, 130 and 200 mAs, while other exposure factors were kept in constant conditions. The spatial resolution phantom consists of six sets of b...

Nanosecond pulsed electric fields (nsPEFs) low cost generator design using power MOSFET and Cockcroft-Walton multiplier circuit as high voltage DC source

Purpose: Non-ionizing radiation therapy for cancer using pulsed electric field with high intensity field has become an interesting field new research topic. A new method using nanosecond pulsed electric fields (nsPEFs) offers a novel means to treat cancer. Not like the conventional electroporation, nsPEFs able to create nanopores in all membranes of the cell, including membrane in cell organelles, like mitochondria and nucleus. NsPEFs will promote cell death in several cell types, including cancer cell by apoptosis mechanism. NsPEFs will use pulse with intensity of electric field higher than conventional electroporation, between 20–100 kV/cm and with shorter duration of pulse than conventional electroporation. NsPEFs requires a generator to produce high voltage pulse and to achieve high intensity electric field with proper pulse width. However, manufacturing cost for creating generator that generates a high voltage with short duration for nsPEFs purposes is highly expensive. Hence, the aim of this research is to obtain the low cost generator design that is able to produce a high voltage pulse with nanosecond width and will be used for nsPEFs purposes. Method: Cockcroft-Walton multiplier circuit will boost the input of 220 volt AC into high voltage DC around 1500 volt and it will be combined by a series of power MOSFET as a fast switch to obtain a high voltage with nanosecond pulse width. The motivation using Cockcroft-Walton multiplier is to acquire a low-cost high voltage DC generator; it will use capacitors and diodes arranged like a step. Power MOSFET connected in series is used as voltage divider to share the high voltage in order not to damage them. Results: This design is expected to acquire a low-cost generator that can achieve the high voltage pulse in amount of −1.5 kV with falltime 3 ns and risetime 15 ns into a 50Ω load that will be used for nsPEFs purposes. Further detailed on the circuit design will be explained at presentation.

Reconstruction 3-dimensional image from 2-dimensional image of status optical coherence tomography (OCT) for analysis of changes in retinal thickness

Optical Coherence Tomography is often used in medical image acquisition to diagnose that change due easy to use and low price. Unfortunately, this type of examination produces a two-dimensional retinal image of the point of acquisition. Therefore, this study developed a method that combines and reconstruct 2-dimensional retinal images into three-dimensional images to display volumetric macular accurately. The system is built with three main stages: data acquisition, data extraction and 3-dimensional reconstruction. At data acquisition step, Optical Coherence Tomography produced six *.jpg images of each patient were further extracted with MATLAB 2010a software into six one-dimensional arrays. The six arrays are combined into a 3-dimensional matrix using a kriging interpolation method with SURFER9 resulting 3-dimensional graphics of macula. Finally, system provides three-dimensional color graphs based on the data distribution normal macula. The reconstruction system which has been designed produces three-dimensional images with size of 481 × 481 × h (retinal thickness) pixels.

New AIRS: The medical imaging software for segmentation and registration of elastic organs in SPECT/CT

We have been successfully improved our software, Automated Image Registration and Segmentation (AIRS), to fuse the CT and SPECT images of elastic organs. Segmentation and registration of elastic organs presents many challenges. Many artifacts can arise in SPECT/CT scans. Also, different organs and tissues have very similar gray levels, which consign thresholding to limited utility. We have been developed a new software to solve different registration and segmentation problems that arises in tomographic data sets. It will be demonstrated that the information obtained by SPECT/CT is more accurate in evaluating patients/objects than that obtained from either SPECT or CT alone. We used multi-modality registration which is amenable for images produced by different modalities and having unclear boundaries between tissues. The segmentation components used in this software is region growing algorithms which have proven to be an effective approach for image segmentation. Our method is designed to perform with clin...

Boron Neutron Capture Therapy (BNCT) Dose Calculation using Geometrical Factors Spherical Interface for Glioblastoma Multiforme

Boron Neutron Capture Therapy (BNCT) is a cancer therapy by utilizing thermal neutron to produce alpha particles and lithium nuclei. The superiority of BNCT is that the radiation effects could be limited only for the tumor cells. BNCT radiation dose depends on the distribution of boron in the tumor. Absorbed dose to the cells from the reaction 10B (n, α) 7Li was calculated near interface medium containing boron and boron‐free region. The method considers the contribution of the alpha particle and recoiled lithium particle to the absorbed dose and the variation of Linear Energy Transfer (LET) charged particles energy. Geometrical factor data of boron distribution for the spherical surface is used to calculate the energy absorbed in the tumor cells, brain and scalp for case Glioblastoma Multiforme. The result shows that the optimal dose in tumor is obtained for boron concentrations of 22.1 mg 10B/g blood.

AIRS: The Medical Imaging Software for Segmentation and Registration in SPECT/CT

We have been successfully developed a new software, Automated Image Registration and Segmentation (AIRS), to fuse the CT and SPECT images. It is designed to solve different registration and segmentation problems that arises in tomographic data sets. AIRS is addressed to obtain anatomic information to be applied to NanoSpect system which is imaging for nano‐tissues or small animals. It will be demonstrated that the information obtained by SPECT/CT is more accurate in evaluating patients/objects than that obtained from either SPECT or CT alone. The registration methods developed here are for both two‐dimensional and three‐dimensional registration. We used normalized mutual information (NMI) which is amenable for images produced by different modalities and having unclear boundaries between tissues. The segmentation components used in this software is region growing algorithms which have proven to be an effective approach for image segmentation. The implementations of region growing developed here are connect...