Seungyeon Choi

Purification, characterization, and primary structure of a chitinase from Pseudomonas sp. YHS-A2

Abstract A chitinase gene (chiA) from Pseudomonas sp. YHS-A2 was cloned into Escherichia coli using pUC19. The nucleotide sequence determination revealed a single open reading frame of chiA comprised of 1902 nucleotide base pairs and 633 deduced amino acids with a molecular weight of 67,452 Da. Amino acid sequence alignment showed that ChiA contains two putative chitin-binding domains and a single catalytic domain. Two proline-threonine repeat regions, which are linkers between catalytic and substrate-binding domains in some cellulases and xylanases, were also found. From E. coli, ChiA was purified 12.8-fold relative to the periplasmic fraction. The Michaelis constant and maximum initial velocity for p-nitrophenyl-N,N′-diacetylchitobiose were 1.06 mM and 44.4 μmol/h per mg protein, respectively. The purified ChiA binds not only to colloidal chitin but also to other substrates (avicel, chitosan, and xylan), but the binding affinity of avicel, chitosan, and xylan is around 10 times lower than that of colloidal chitin. The reaction of ChiA with colloidal chitin and chitooligosaccharides (trimer-hexamer) produced an end product of N,N′-diacetylchitobiose, indicating that ChiA is a chitobiosidase.

Feasibility study of shutter scan acquisition for region of interest (ROI) digital tomosynthesis

Abstract Dose reduction techniques have been studied in medical imaging. We propose shutter scan acquisition for region of interest (ROI) imaging to reduce the patient exposure dose received from a digital tomosynthesis system. A prototype chest digital tomosynthesis (CDT) system (LISTEM, Wonju, Korea) and the LUNGMAN phantom (Kyoto Kagaku, Japan) with lung nodules 8, 10, and 12 mm in size were used for this study. A total of 41 projections with shutter scan acquisition consisted of 21 truncated projections and 20 non‐truncated projections. For comparison, 41 projections using conventional full view scan acquisition were also acquired. Truncated projections obtained by shutter scan acquisition were corrected by proposed image processing procedure to remove the truncation artifacts. The image quality was evaluated using the contrast to noise ratio (CNR), coefficient of variation (COV), and figure of merit (FOM). We measured the dose area product (DAP) value to verify the dose reduction using shutter scan acquisition. The ROI of the reconstructed image from shutter scan acquisition showed enhanced contrast. The results showed that CNR values of 8 and 12 mm lung nodules increased by 6.38% and 21.21%, respectively, and the CNR value of 10 mm lung nodule decreased by 3.63%. COV values of the lung nodules were lower in a shutter scan image than in a full view scan image. FOM values of 8, 10, and 12 mm lung nodules increased by 3.06, 2.25, and 2.33 times, respectively. This study compared the proposed shutter scan and conventional full view scan acquisition. In conclusion, using a shutter scan acquisition method resulted in enhanced contrast images within the ROI and higher FOM values. The patient exposure dose of the proposed shutter scan acquisition method can be reduced by limiting the field of view (FOV) to focus on the ROI.

Optimization of shutter scan parameters in digital tomosynthesis system

In medical imaging field, various dose reduction techniques have been studied. We proposed shutter scan acquisition for region of interest (ROI) imaging to reduce the patient exposure dose in digital tomosynthesis system. Projections obtained by shutter scan acquisition is a combination of truncated projections and non-truncated projections. In this study, we call the number of truncated projections divided by the number of non-truncated projections as shutter weighting factor. The shutter scan acquisition parameters were optimized using 5 different acquisition sets with the shutter weighting factor (0.16, 0.35, 1.03, 3.05 and 7.1). A prototype CDT system (LISTEM, Korea) and the LUNGMAN phantom (Kyoto Kagaku, Japan) with an 8 mm lung nodule were used. A total of 81 projections with shutter scan acquisition were obtained in 5 sets according to shutter weighting factor. The image quality was investigated using the contrast noise ratio (CNR). We also calculated figure of merit (FOM) to determine optimal acquisition parameters for the shutter scan acquisition. The ROI of the reconstructed image with shutter scan acquisition showed enhanced contrast. The highest CNR and FOM value, shutter weighting factor 7.1, is the acquisition set consisting of 71 truncated projections and 10 non-truncated projections. In this study, we investigated the effects of composition ratio of the truncated and non-truncated projections on reconstructed images through the shutter scan acquisition. In addition, the optimal acquisition conditions for the shutter scan acquisition were determined by deriving the FOM values. In conclusion, we can suggest optimal shutter scan acquisition parameters on the lesion within the ROI to be diagnosed.

Feasibility study of contrast enhanced digital mammography based on photon-counting detector by projection-based weighting technique: a simulation study

Contrast enhanced digital mammography (CEDM) using dual energy technique has been studied due to its ability of emphasizing breast cancer. However, when using CEDM the patient dose and the toxicity of iodine should be considered. A photon counting detector (PCD), which has the ability of energy discrimination, has been regarded as an alternative technique to resolve the problem of excessive patient dose. The purpose of this study was to confirm the feasibility of CEDM based on the PCD by using a projection-based energy weighting technique. We used Geant4 Application for Tomographic Emission (GATE) version 6.0. We simulated two different types of PCD which were constructed with silicon (Si) and cadmium zinc telluride (CZT). Each inner cylinder filled with four iodine with different low concentrations and thicknesses in cylindrical shape of breast phantom. For comparison, we acquired a convention integrating mode image and five bin images based on PCD system by projection-based weighting technique. The results demonstrated that CEDM based on the PCD significantly improved contrast to noise ratio (CNR) compared to conventional integrating mode. As a result of applying the dual energy technique to the projection-based weighing image, the CNR of low concentration iodine was improved. In conclusion, the CEDM based on PCD with projection-based weighting technique has improved a detection capability of low concentration iodine than integrating mode.

A feasibility study of automatic lung nodule detection in chest digital tomosynthesis with machine learning based on support vector machine

The chest digital tomosynthesis(CDT) is recently developed medical device that has several advantage for diagnosing lung disease. For example, CDT provides depth information with relatively low radiation dose compared to computed tomography (CT). However, a major problem with CDT is the image artifacts associated with data incompleteness resulting from limited angle data acquisition in CDT geometry. For this reason, the sensitivity of lung disease was not clear compared to CT. In this study, to improve sensitivity of lung disease detection in CDT, we developed computer aided diagnosis (CAD) systems based on machine learning. For design CAD systems, we used 100 cases of lung nodules cropped images and 100 cases of normal lesion cropped images acquired by lung man phantoms and proto type CDT. We used machine learning techniques based on support vector machine and Gabor filter. The Gabor filter was used for extracting characteristics of lung nodules and we compared performance of feature extraction of Gabor filter with various scale and orientation parameters. We used 3, 4, 5 scales and 4, 6, 8 orientations. After extracting features, support vector machine (SVM) was used for classifying feature of lesions. The linear, polynomial and Gaussian kernels of SVM were compared to decide the best SVM conditions for CDT reconstruction images. The results of CAD system with machine learning showed the capability of automatically lung lesion detection. Furthermore detection performance was the best when Gabor filter with 5 scale and 8 orientation and SVM with Gaussian kernel were used. In conclusion, our suggested CAD system showed improving sensitivity of lung lesion detection in CDT and decide Gabor filter and SVM conditions to achieve higher detection performance of our developed CAD system for CDT.

Development of a prototype chest digital tomosynthesis R/F system

Digital tomosynthesis has an advantage of low radiation dose compared to conventional computed tomography (CT) by utilizing small number of projections (~80) acquired over a limited angular range. It can produce 3D volumetric data although they may have some artifacts due to incomplete sampling. Based upon these attractive merits, we developed a prototype digital tomosynthesis R/F system especially for the purpose of applications in chest imaging. Prototype chest digital tomosynthesis (CDT) R/F system contains an X-ray tube with high power R/F pulse generator, flat-panel detector, R/F table, electromechanical radiographic subsystems including precise motor controller, and a reconstruction server. For image reconstruction, users could select the reconstruction option between analytic and iterative methods. Reconstructed images of Catphan700 and LUNGMAN phantoms clearly and rapidly described the internal structures of the phantoms using graphics processing unit (GPU) programming. Contrast-to-noise ratio (CNR) values of the CTP682 module was higher in images using the simultaneous algebraic reconstruction technique (SART) than those using filtered backprojection (FBP) for all materials by factors of 2.60, 3.78, 5.50, 2.30, 3.70, and 2.52 for air, lung foam, low density polyethylene (LDPE), Delrin (acetal homopolymer resin), bone 50% (hydroxyapatite), and Teflon, respectively. Total elapsed times for producing 3D volume were 2.92 sec and 86.29 sec on average for FBP and SART (20 iterations), respectively. The times required for reconstruction were clinically feasible. Moreover, the total radiation dose from the system (5.68 mGy) could demonstrate a significant lowered radiation dose compared to conventional chest CT scan. Consequently, our prototype tomosynthesis R/F system represents an important advance in digital tomosynthesis applications.

Evaluation of effective detective quantum efficiency considering breast thickness and glandularity in prototype digital breast tomosynthesis system

Digital breast tomosynthesis (DBT) system is a novel imaging modality which is strongly depended on the performance of a detector. Recently, effective detective quantum efficiency (eDQE) has been introduced to solve the disadvantages of conventional DQE evaluations which do not consider clinical operating conditions. For eDQE evaluation, the variety of patient breast, especially the glandularity and thickness needs to be studied to consider different races of patient. For these reasons, eDQE in a prototype DBT system considering different breast thickness and glandularity was evaluated. In this study, we used the prototype DBT system with CsI(Tl) scintillator/CMOS flat panel digital detector developed by Korea Electrotechnology Research Institute (KERI). A scatter fraction, a transmission factor, an effective modulation transfer function (eMTF) and an effective normalized noise power spectrum (eNNPS) were measured in different thickness and glandularity of breast equivalent phantom. As results, scatter fraction increased and transmission fraction decreased by a factor of 2.09 and 6.25, respectively, as increasing glandularity and thickness. We also found that the breast phantom with small thickness presented high eMTF and low eNNPS. As results, eDQE from 4 cm thick breast phantom with 30% and 70% glandularity showed small changes from 0.20 to 0.19 at 0.1 mm-1, whereas eDQE from 50% glandularity of 3 cm and 5 cm presented relatively significant increase from 0.16 to 0.20 at 0.1 mm-1 spatial frequency. These indicated that eDQE was strongly affected by phantom thickness, but the effect of glandularity seemed to be trivial. According to our study, the whole system evaluation considering the races of patients from standard to abnormal cases is needed to be studied in future works.

Performance evaluation of algebraic reconstruction technique (ART) for prototype chest digital tomosynthesis (CDT) system

Chest digital tomosynthesis (CDT) is a new 3D imaging technique that can be expected to improve the detection of subtle lung disease over conventional chest radiography. Algorithm development for CDT system is challenging in that a limited number of low-dose projections are acquired over a limited angular range. To confirm the feasibility of algebraic reconstruction technique (ART) method under variations in key imaging parameters, quality metrics were conducted using LUNGMAN phantom included grand-glass opacity (GGO) tumor. Reconstructed images were acquired from the total 41 projection images over a total angular range of ±20°. We evaluated contrast-to-noise ratio (CNR) and artifacts spread function (ASF) to investigate the effect of reconstruction parameters such as number of iterations, relaxation parameter and initial guess on image quality. We found that proper value of ART relaxation parameter could improve image quality from the same projection. In this study, proper value of relaxation parameters for zero-image (ZI) and back-projection (BP) initial guesses were 0.4 and 0.6, respectively. Also, the maximum CNR values and the minimum full width at half maximum (FWHM) of ASF were acquired in the reconstructed images after 20 iterations and 3 iterations, respectively. According to the results, BP initial guess for ART method could provide better image quality than ZI initial guess. In conclusion, ART method with proper reconstruction parameters could improve image quality due to the limited angular range in CDT system.

GPU-accelerated compressed-sensing (CS) image reconstruction in chest digital tomosynthesis (CDT) using CUDA programming

A compressed-sensing (CS) technique has been rapidly applied in medical imaging field for retrieving volumetric data from highly under-sampled projections. Among many variant forms, CS technique based on a total-variation (TV) regularization strategy shows fairly reasonable results in cone-beam geometry. In this study, we implemented the TV-based CS image reconstruction strategy in our prototype chest digital tomosynthesis (CDT) R/F system. Due to the iterative nature of time consuming processes in solving a cost function, we took advantage of parallel computing using graphics processing units (GPU) by the compute unified device architecture (CUDA) programming to accelerate our algorithm. In order to compare the algorithmic performance of our proposed CS algorithm, conventional filtered back-projection (FBP) and simultaneous algebraic reconstruction technique (SART) reconstruction schemes were also studied. The results indicated that the CS produced better contrast-to-noise ratios (CNRs) in the physical phantom images (Teflon region-of-interest) by factors of 3.91 and 1.93 than FBP and SART images, respectively. The resulted human chest phantom images including lung nodules with different diameters also showed better visual appearance in the CS images. Our proposed GPU-accelerated CS reconstruction scheme could produce volumetric data up to 80 times than CPU programming. Total elapsed time for producing 50 coronal planes with 1024×1024 image matrix using 41 projection views were 216.74 seconds for proposed CS algorithms on our GPU programming, which could match the clinically feasible time (~ 3 min). Consequently, our results demonstrated that the proposed CS method showed a potential of additional dose reduction in digital tomosynthesis with reasonable image quality in a fast time.

Anatomical decomposition in dual energy chest digital tomosynthesis

Lung cancer is the leading cause of cancer death worldwide and the early diagnosis of lung cancer has recently become more important. For early screening lung cancer, computed tomography (CT) has been used as a gold standard for early diagnosis of lung cancer [1]. The major advantage of CT is that it is not susceptible to the problem of misdiagnosis caused by anatomical overlapping while CT has extremely high radiation dose and cost compared to chest radiography. Chest digital tomosynthesis (CDT) is a recently introduced new modality for lung cancer screening with relatively low radiation dose compared to CT [2] and also showing high sensitivity and specificity to prevent anatomical overlapping occurred in chest radiography. Dual energy material decomposition method has been proposed for better detection of pulmonary nodules as means of reducing the anatomical noise [3]. In this study, possibility of material decomposition in CDT was tested by simulation study and actual experiment using prototype CDT. Furthermore organ absorbed dose and effective dose were compared with single energy CDT. The Gate v6 (Geant4 application for tomographic emission), and TASMIP (Tungsten anode spectral model using the interpolating polynomial) code were used for simulation study and simulated cylinder shape phantom consisted of 4 inner beads which were filled with spine, rib, muscle and lung equivalent materials. The patient dose was estimated by PCXMC 1.5 Monte Carlo simulation tool [4]. The tomosynthesis scan was performed with a linear movement and 21 projection images were obtained over 30 degree of angular range with 1.5° degree of angular interval. The proto type CDT system has same geometry with simulation study and composed of E7869X (Toshiba, Japan) x-ray tube and FDX3543RPW (Toshiba, Japan) detector. The result images showed that reconstructed with dual energy clearly visualize lung filed by removing unnecessary bony structure. Furthermore, dual energy CDT could enhance spine bone hidden by heart effectively. The effective dose in dual energy CDT was slightly higher than single energy CDT, while only 10% of average thoracic CT [5]. Dual energy tomosynthesis is a new technique; therefore, there is little guidance for its integration into the clinical practice and this study can be used to improve diagnosis efficiency of lung field screening using CDT