Journal of X-Ray Science and Technology - Volume 27, issue 6

Authors: Wang, Yi | Liu, Shanshan | Lou, Shiliang | Zhang, Weiqian | Cai, Huaiyu | Chen, Xiaodong

Article Type: Research Article

Abstract: BACKGROUND: Optical coherence tomography (OCT) is a non-invasive diagnosing tool used in clinics. Due to its high resolution (<10um), it is appropriate for the early detection of tiny infections. It has been widely used in diagnosis and treatment of diseases, evaluation of therapeutic efficacy, and monitoring of various physiological and pathological processes. OBJECTIVE: To systemically review literature to summarize the clinic application of OCT in recent years. METHODS: For clinic applications that OCT has been applied, we selected studies that describe the most relevant works. The discussion included: 1) which tissue could be used in the …OCT detection, 2) which character of different tissue could be used as diagnosing criteria, 3) which diseases and pathological process have been diagnosed or monitored using OCT imaging, and 4) the recent development of clinic OCT diagnosing. RESULTS: The literature showed that the OCT had been listed as a routine test choice for ophthalmic diseases, while the first commercial product for cardiovascular OCT detection had gotten clearance. Meanwhile, as the development of commercial benchtop OCT equipment and tiny fiber probe, the commercial application of OCT in dermatology, dentistry, gastroenterology and urology also had great potential in the near future. CONCLUSIONS: The analysis and discussions showed that OCT, as an optical diagnosing method, has been used successfully in many clinical fields, and has the potential to be a standard inspection method in several clinic fields, such as dermatology, dentistry and cardiovascular. Show more

Keywords: Optical coherence tomography (OCT), clinical application of OCT

DOI: 10.3233/XST-190559

Citation: Journal of X-Ray Science and Technology, vol. 27, no. 6, pp. 995-1006, 2019

Authors: Caldwell, Matthew | Griffin, Lewis D.

Article Type: Research Article

Abstract: BACKGROUND: X-ray imaging is a crucial and ubiquitous tool for detecting threats to transport security, but interpretation of the images presents a logistical bottleneck. Recent advances in Deep Learning image classification offer hope of improving throughput through automation. However, Deep Learning methods require large quantities of labelled training data. While photographic data is cheap and plentiful, comparable training sets are seldom available for the X-ray domain. OBJECTIVE: To determine whether and to what extent it is feasible to exploit the availability of photo data to supplement the training of X-ray threat detectors. METHODS: A new dataset …was collected, consisting of 1901 matched pairs of photo & X-ray images of 501 common objects. Of these, 258 pairs were of 69 objects considered threats in the context of aviation. This data was used to test a variety of transfer learning approaches. A simple model of threat cue availability was developed to understand the limits of this transferability. RESULTS: Appearance features learned from photos provide a useful basis for training classifiers. Some transfer from the photo to the X-ray domain is possible as ∼40% of danger cues are shared between the modalities, but the effectiveness of this transfer is limited since ∼60% of cues are not. CONCLUSIONS: Transfer learning is beneficial when X-ray data is very scarce—of the order of tens of training images in our experiments—but provides no significant benefit when hundreds or thousands of X-ray images are available. Show more

Keywords: Automated threat detection, deep learning, transfer learning, security imaging

DOI: 10.3233/XST-190545

Citation: Journal of X-Ray Science and Technology, vol. 27, no. 6, pp. 1007-1020, 2019

Authors: Sun, Zong-Qiong | Hu, Shu-Dong | Li, Jie | Wang, Teng | Duan, Shao-Feng | Wang, Jun

Article Type: Research Article

Abstract: PURPOSE: To test the feasibility of differentiate gastric cancer from gastric stromal tumor using a radiomics study based on contrast-enhanced CT images. MATERIALS AND METHODS: The contrast-enhanced CT image data of 60 patients with gastric cancer and 40 patients with gastric stromal tumor confirmed by postoperative pathology were retrospectively analyzed. First, CT images were read by two senior radiologists to acquire subjective CT signs model, including perigastric fatty infiltration, perigastric enlarged lymph nodes, the enhancement and growth modes of gastric tumors. Second, the manual segmentation of gastric tumors from the CT images was performed by the two radiologists …to extract radiomics features via ITK-SNAP software, and to construct radiomics signature model. Finally, a diagnostic model integrated with subjective CT signs and radiomics signatures was constructed. The diagnostic efficacy of three models in differentiating gastric cancer from gastric stromal tumor was compared by using receiver operating characteristic curves (ROC). RESULTS: There are statistically significant differences between the gastric cancer and gastric stromal tumor in the perigastric enlarged lymph nodes, growth mode and radiomics signature (p  < 0.05). The area under ROC curve (AUC), sensitivity and accuracy of subjective CT signs model were the lowest among the three models. While the combined model yields the highest AUC value (0.903), specificity (93.33%) and accuracy (86.00%) among the three models (p  = 0.03). CONCLUSION: The diagnostic model integrating subjective CT signs and radiomics signature can improve the diagnostic accuracy of gastric tumors. Show more

Keywords: Gastric cancer, gastrointestinal stromal tumor, computed tomography, X-ray, radiomics, diagnosis

DOI: 10.3233/XST-190574

Citation: Journal of X-Ray Science and Technology, vol. 27, no. 6, pp. 1021-1031, 2019

Authors: Yang, Fan | Jia, Xianyuan | Lei, Pinggui | He, Yan | Xiang, Yining | Jiao, Jun | Zhou, Shi | Qian, Wei | Duan, Qinghong

Article Type: Research Article

Abstract: OBJECTIVE: To develop and test a novel method for automatic quantification of hepatic steatosis in histologic images based on the deep learning scheme designed to predict the fat ratio directly, which aims to improve accuracy in diagnosis of non-alcoholic fatty liver disease (NAFLD) with objective assessment of the severity of hepatic steatosis instead of subjective visual estimation. MATERIALS AND METHODS: Thirty-six 8-week old New Zealand white rabbits of both sexes were fed with high-cholesterol, high-fat diet and sacrificed under deep anesthesia at various time points to obtain the pathological specimen. All rabbits were performed by multislice computed tomography …for surveillance to measure density changes of liver parenchyma. A deep learning scheme using a convolutional neural network was developed to directly predict the liver fat ratio based on the pathological images. The average error value, standard deviation, and accuracy (error <5%) were evaluated and compared between the deep learning scheme and manual segmentation results. The Pearson’s correlation coefficient was also calculated in this study. RESULTS: The deep learning scheme performs successfully on rabbit liver histologic data, showing a high degree of accuracy and stability. The average error value, standard deviation, and accuracy (error <5%) were 3.21%, 4.02%, and 79.10% for the cropped images, 2.22%, 1.92%, and 88.34% for the original images, respectively. The strong positive correlation was also observed for cropped images (R = 0.9227) and original images (R = 0.9255) in comparison to labeled fat ratio. CONCLUSIONS: This new deep learning scheme may aid in the quantification of steatosis in the liver and facilitate its treatment by providing an earlier clinical diagnosis. Show more

Keywords: Quantitative assessment, hepatic steatosis, NAFLD, convolutional neural network, deep learning

DOI: 10.3233/XST-190570

Citation: Journal of X-Ray Science and Technology, vol. 27, no. 6, pp. 1033-1045, 2019

Authors: Najafzadeh, Milad | Hoseini-Ghafarokhi, Mojtaba | Bolagh, Rezgar Shahi Mayn | Haghparast, Mohammad | Zarifi, Shiva | Nickfarjam, Abolfazl | Farhood, Bagher | Chow, James C.L.

Article Type: Research Article

Abstract: OBJECTIVE: This study aims to benchmark a Monte Carlo (MC) model of the 18 MV photon beam produced by the Siemens Oncor® linac using the BEAMnrc and DOSXYZnrc codes. METHODS: By matching the percentage depth doses and beam profiles calculated by MC simulations with measurements, the initial electron beam parameters including electron energy, full width at half maximum (spatial FWHM), and mean angular spread were derived for the 10×10 cm2 and 20×20 cm2 field sizes. The MC model of the 18 MV photon beam was then validated against the measurements for different field sizes (5×5, 30×30 and …40×40 cm2 ) by gamma index analysis. RESULTS: The optimum values for electron energy, spatial FWHM and mean angular spread were 14.2 MeV, 0.08 cm and 0.8 degree, respectively. The MC simulations yielded the comparable measurement results of these optimum parameters. The gamma passing rates (with acceptance criteria of 1% /1 mm) for percentage depth doses were found to be 100% for all field sizes. For cross-line profiles, the gamma passing rates were 100%, 97%, 95%, 96% and 95% for 5×5, 10×10, 20×20, 30×30 and 40×40 cm2 field sizes, respectively. CONCLUSIONS: By validation of the MC model of Siemens Oncor® linac using various field sizes, it was found that both dose profiles of small and large field sizes were very sensitive to the changes in spatial FWHM and mean angular spread of the primary electron beam from the bending magnet. Hence, it is recommended that both small and large field sizes of the 18 MV photon beams should be considered in the Monte Carlo linac modeling. Show more

Keywords: Radiotherapy, Monte Carlo simulation, benchmarking, Siemens Oncor, gamma analysis

DOI: 10.3233/XST-190568

Citation: Journal of X-Ray Science and Technology, vol. 27, no. 6, pp. 1047-1070, 2019

Authors: Wu, Vincent W.C. | Ng, Amanda P.L. | Cheung, Emily K.W.

Article Type: Research Article

Abstract: The recent advancements in radiotherapy technologies have made delivery of the highly conformal dose to the target volume possible. With the increasing popularity of delivering high dose per fraction in modern radiotherapy schemes such as in stereotactic body radiotherapy and stereotactic body ablative therapy, high degree of treatment precision is essential. In order to achieve this, we have to overcome the potential difficulties caused by patient instability due to immobilization problems; patient anxiety and random motion due to prolonged treatment time; tumor deformation and baseline shift during a treatment course. This is even challenging for patients receiving radiotherapy in the …chest and abdominal regions because it is affected by the patient’s respiration which inevitably leads to tumor motion. Therefore, monitoring of intrafractional motion has become increasingly important in modern radiotherapy. Major intrafractional motion management strategies including integration of respiratory motion in treatment planning; breath-hold technique; forced shallow breathing with abdominal compression; respiratory gating and dynamic real-time tumor tracking have been developed. Successful intrafractional motion management is able to reduce the planning target margin and ensures planned dose delivery to the target and organs at risk. Meanwhile, the emergency of MRI-linear accelerator has facilitated radiation-free real-time monitoring of soft tissue during treatment and could be the future modality in motion management. This review article summarizes the various approaches that deal with intrafractional target, organs or patient motion with discussion of their advantages and limitations. In addition, the potential future advancements including MRI-based tumor tracking are also discussed. Show more

Keywords: Intrafractional motion, respiratory gating, breath-hold, tumor tracking, real-time motion management

DOI: 10.3233/XST-180472

Citation: Journal of X-Ray Science and Technology, vol. 27, no. 6, pp. 1071-1086, 2019

Authors: Khan, Sajid Ullah | Ullah, Imran | Ahmed, Imran | Imran, Ali | Ullah, Najeeb

Article Type: Research Article

Abstract: Brain and its structure are extremely complex with deep levels of details. Applying image processing methods of brain image can be very useful in many practical domains. Magnetic Resonance Imaging (MRI) is widely used imaging technique and has particular advantage by possessing the capability of providing highly detailed images of brain soft tissues than any other imaging techniques. The real challenge at hand for researchers is to perform precise segmentation while overcoming the effects of noise and other imaging artifacts like intensity in homogeneity introduced in medical images during image acquisition process. In this research work, a directional weighted optimized …Fuzzy C-Means (dws FCM) method has been proposed for segmentation of brain MR images. This method works by incorporating the spatial information of the pixels of the images and assigning the directional weights to the neighborhood. In order to validate the proposed segmentation framework, a comprehensive set of experiments have been performed on publically available standard simulated as well as real datasets. The experimental results showed 95% of accuracy and the performance of the proposed segmentation framework is much better and the framework suppress the sufficient amount of noise especially rician noise and reproduce good segmentation by overcoming the effect of intensity in homogeneity. Show more

Keywords: Rician noise, directional weighted spatial fuzzy C-mean, image segmentation, MRI, optimal extraction

DOI: 10.3233/XST-190547

Citation: Journal of X-Ray Science and Technology, vol. 27, no. 6, pp. 1087-1099, 2019

Authors: Yao, Gongjie | Zou, Yongning | Wang, Jue | Yu, Haosong | Chen, Taoyan

Article Type: Research Article

Abstract:  The aim of this study is to present a fully automated registration algorithm that allows for alignment and errors analysis of the 3D surface model obtained from industrial computed tomography (CT) images with the computer-aided design (CAD) model. First, two pre-processing steps are executed by the algorithm namely, CAD model subdivision and representing models. Next, two improved registration procedures are applied including covariance descriptors-based coarse registration with a novel and automatic calibration, followed by a fine registration technique that utilizes an improved iterative closest points (ICP) algorithm, which is what we proposed with a novel estimation method for registration error. …Finally, using a novel strategy that we proposed for error display, the quantitative data analysis results can simultaneously estimate both positive and negative deviation of the surface registration errors more precisely and fully expressed. Comparing to the original ICP algorithm, the quantitative data of experimental results demonstrate that the average registration errors of carburetors and valves are reduced by 0.80 millimeter at least. Therefore, this study demonstrates that the proposed new algorithm is not only capable of fully automating the registration of 3D surface model to a CAD model but also beneficial for quantitatively determining the surface manufacturing error more precisely. Show more

Keywords: Registration, advanced covariance descriptors-based, improved ICP, CT surface model, deviation measurement

DOI: 10.3233/XST-190561

Citation: Journal of X-Ray Science and Technology, vol. 27, no. 6, pp. 1101-1119, 2019

Authors: Tao, Wei | Sun, Chuanyang | Yang, Dongrong | Zang, Yachen | Zhu, Jin | Zhang, Yuanyuan | Wang, Gang | Xue, Boxin

Article Type: Research Article

Abstract: Purpose: To evaluate safety, efficacy and clinical outcomes after photovaporization of the prostate with the 180W-XPS Greenlight laser in patients with low urinary tracts symptom secondary to benign prostatic hyperplasia (BPH). Materials and Methods: All 102 patients with lower urinary tract symptoms who underwent 180W XPS laser vaporization of the prostate from April 2017 to April 2018 were enrolled. The preoperative parameters, postoperative functional, uroflowmetry outcomes and complications were collected. Results: All patients were successfully treated with 180W XPS laser vaporization. Mean preoperative prostate volume was 81±28.7 ml and mean laser time was 28.2±12.5 minutes. No major …complications intraoperatively or postoperatively were observed and no blood transfusions were required. Comparing to preoperative characteristics, International Prostate Symptom Score (IPSS), maximum flow rate (Qmax) and post-void residual (PVR) parameters were improved significantly and sustained during the follow-up period. At 3, 6 and 12-month follow-ups, mean urinary peak flow increased from 6.2±2.1 ml per second to 19.8±4.6, 19.4±4.7 and 19.6±4.9 ml per second, respectively. Mean International Prostate Symptom Scores decreased over time, from 28.9±4.5 to 8.2±1.6, 6.2±1.22 and 5.88±1.15 at 3, 6, 12 months, respectively. Conclusions: 180W XPS Greenlight laser vaporization is a safe and effective treatment option for patients with lower urinary tract symptoms secondary to BPH. Show more

Keywords: Benign prostatic hyperplasia (BPH), 180W XPS Greenlight laser, mini-invasive treatment of BPH

DOI: 10.3233/XST-190550

Citation: Journal of X-Ray Science and Technology, vol. 27, no. 6, pp. 1121-1129, 2019

Authors: Li, Yan | Dai, Yongliang | Guo, Youmin | Wang, Jiansheng | Duan, Xiaoyi

Article Type: Research Article

Abstract: OBJECTIVE: Since cancer treatment and outcome differ among the patients diagnosed with breast cancer at different stages, this study aims to elucidate the factors associated with PET/CT staging, treatment effect, and maximal standardized uptake value (SUVmax ) in breast cancer patients. METHODS: Twenty-eight patients who underwent two PET/CT examinations with the complete pathological and immunohistochemical data were retrospectively reviewed. Pearson and Spearman correlation analyses were performed to investigate the relationships of patient PET/CT staging (first round PET/CT), treatment effect (comparison between the results of two rounds of PET/CT), and tumor SUVmax , with respect to patient age, tumor …location, tumor long diameter, short diameter, time of first round PET/CT examination, histological type and grade, axillary lymph node metastasis rate, interval between the two PET/CT examinations, treatment method, and the expression of the estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2), P53, and Ki67. RESULTS: PET/CT staging (first round PET/CT) relates to HER2 and Ki67 expression with the correlation coefficients of 0.432 and 0.552, and P -values of 0.022 and 0.002, respectively. The treatment effect (comparison between the results of two rounds of PET/CT) associates with tumor site and P53 expression in which the correlation coefficients are – 0.412 and 0.845, and P -values are 0.029 and 0.000, respectively. The measured SUVmax correlates well with the tumor long diameter, short diameter, and treatment effect in which the correlation coefficients are 0.943, 0.886, and 0.878, and P -values are 0.005, 0.019, and 0.02, respectively. CONCLUSIONS: Study results indicate that PET/CT staging and treatment effect associate well with SUVmax and immunohistochemical results of tumor, while SUVmax of tumor associates well with tumor size. Show more

Keywords: PET/CT, FDG, breast cancer

DOI: 10.3233/XST-190544

Citation: Journal of X-Ray Science and Technology, vol. 27, no. 6, pp. 1131-1144, 2019