Displaying publications 261 - 280 of 288 in total

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  1. Raghavendra U, Gudigar A, Maithri M, Gertych A, Meiburger KM, Yeong CH, et al.
    Comput Biol Med, 2018 04 01;95:55-62.
    PMID: 29455080 DOI: 10.1016/j.compbiomed.2018.02.002
    Ultrasound imaging is one of the most common visualizing tools used by radiologists to identify the location of thyroid nodules. However, visual assessment of nodules is difficult and often affected by inter- and intra-observer variabilities. Thus, a computer-aided diagnosis (CAD) system can be helpful to cross-verify the severity of nodules. This paper proposes a new CAD system to characterize thyroid nodules using optimized multi-level elongated quinary patterns. In this study, higher order spectral (HOS) entropy features extracted from these patterns appropriately distinguished benign and malignant nodules under particle swarm optimization (PSO) and support vector machine (SVM) frameworks. Our CAD algorithm achieved a maximum accuracy of 97.71% and 97.01% in private and public datasets respectively. The evaluation of this CAD system on both private and public datasets confirmed its effectiveness as a secondary tool in assisting radiological findings.
  2. Tan SK, Yeong CH, Raja Aman RRA, Ng KH, Abdul Aziz YF, Chee KH, et al.
    Br J Radiol, 2018 Jul;91(1088):20170874.
    PMID: 29493261 DOI: 10.1259/bjr.20170874
    OBJECTIVE: This study aimed (1) to perform a systematic review on scanning parameters and contrast medium (CM) reduction methods used in prospectively electrocardiography (ECG-triggered low tube voltage coronary CT angiography (CCTA), (2) to compare the achievable dose reduction and image quality and (3) to propose appropriate scanning techniques and CM administration methods.

    METHODS: A systematic search was performed in PubMed, the Cochrane library, CINAHL, Web of Science, ScienceDirect and Scopus, where 20 studies were selected for analysis of scanning parameters and CM reduction methods.

    RESULTS: The mean effective dose (HE) ranged from 0.31 to 2.75 mSv at 80 kVp, 0.69 to 6.29 mSv at 100 kVp and 1.53 to 10.7 mSv at 120 kVp. Radiation dose reductions of 38 to 83% at 80 kVp and 3 to 80% at 100 kVp could be achieved with preserved image quality. Similar vessel contrast enhancement to 120 kVp could be obtained by applying iodine delivery rate (IDR) of 1.35 to 1.45 g s-1 with total iodine dose (TID) of between 10.9 and 16.2 g at 80 kVp and IDR of 1.08 to 1.70 g s-1 with TID of between 18.9 and 20.9 g at 100 kVp.

    CONCLUSION: This systematic review found that radiation doses could be reduced to a rate of 38 to 83% at 80 kVp, and 3 to 80% at 100 kVp without compromising the image quality. Advances in knowledge: The suggested appropriate scanning parameters and CM reduction methods can be used to help users in achieving diagnostic image quality with reduced radiation dose.

  3. Abdul Hadi MFR, Abdullah AN, Hashikin NAA, Ying CK, Yeong CH, Yoon TL, et al.
    Med Phys, 2022 Dec;49(12):7742-7753.
    PMID: 36098271 DOI: 10.1002/mp.15980
    PURPOSE: Monte Carlo (MC) simulation is an important technique that can help design advanced and challenging experimental setups. GATE (Geant4 application for tomographic emission) is a useful simulation toolkit for applications in nuclear medicine. Transarterial radioembolization is a treatment for liver cancer, where microspheres embedded with yttrium-90 (90 Y) are administered intra-arterially to the tumor. Personalized dosimetry for this treatment may provide higher dosimetry accuracy compared to the conventional partition model (PM) calculation. However, incorporation of three-dimensional tomographic input data into MC simulation is an intricate process. In this article, 3D Slicer, free and open-source software, was utilized for the incorporation of patient tomographic images into GATE to demonstrate the feasibility of personalized dosimetry in hepatic radioembolization with 90 Y.

    METHODS: In this article, the steps involved in importing, segmenting, and registering tomographic images using 3D Slicer were thoroughly described, before importing them into GATE for MC simulation. The absorbed doses estimated using GATE were then compared with that of PM. SlicerRT, a 3D Slicer extension, was then used to visualize the isodose from the MC simulation.

    RESULTS: A workflow diagram consisting of all the steps taken in the utilization of 3D Slicer for personalized dosimetry in 90 Y radioembolization has been presented in this article. In comparison to the MC simulation, the absorbed doses to the tumor and normal liver were overestimated by PM by 105.55% and 20.23%, respectively, whereas for lungs, the absorbed dose estimated by PM was underestimated by 25.32%. These values were supported by the isodose distribution obtained via SlicerRT, suggesting the presence of beta particles outside the volumes of interest. These findings demonstrate the importance of personalized dosimetry for a more accurate absorbed dose estimation compared to PM.

    CONCLUSION: The methodology provided in this study can assist users (especially students or researchers who are new to MC simulation) in navigating intricate steps required in the importation of tomographic data for MC simulation. These steps can also be utilized for other radiation therapy related applications, not necessarily limited to internal dosimetry.

  4. Jahmunah V, Sudarshan VK, Oh SL, Gururajan R, Gururajan R, Zhou X, et al.
    Int J Imaging Syst Technol, 2021 Jun;31(2):455-471.
    PMID: 33821093 DOI: 10.1002/ima.22552
    In 2020 the world is facing unprecedented challenges due to COVID-19. To address these challenges, many digital tools are being explored and developed to contain the spread of the disease. With the lack of availability of vaccines, there is an urgent need to avert resurgence of infections by putting some measures, such as contact tracing, in place. While digital tools, such as phone applications are advantageous, they also pose challenges and have limitations (eg, wireless coverage could be an issue in some cases). On the other hand, wearable devices, when coupled with the Internet of Things (IoT), are expected to influence lifestyle and healthcare directly, and they may be useful for health monitoring during the global pandemic and beyond. In this work, we conduct a literature review of contact tracing methods and applications. Based on the literature review, we found limitations in gathering health data, such as insufficient network coverage. To address these shortcomings, we propose a novel intelligent tool that will be useful for contact tracing and prediction of COVID-19 clusters. The solution comprises a phone application combined with a wearable device, infused with unique intelligent IoT features (complex data analysis and intelligent data visualization) embedded within the system to aid in COVID-19 analysis. Contact tracing applications must establish data collection and data interpretation. Intelligent data interpretation can assist epidemiological scientists in anticipating clusters, and can enable them to take necessary action in improving public health management. Our proposed tool could also be used to curb disease incidence in future global health crises.
  5. See MH, Yip KC, Teh MS, Teoh LY, Lai LL, Wong LK, et al.
    J Plast Reconstr Aesthet Surg, 2023 Aug;83:380-395.
    PMID: 37302244 DOI: 10.1016/j.bjps.2023.04.003
    BACKGROUND: Breast ptosis is characterized by the inferolateral descent of the glandular area and nipple-areola complex. A high degree of ptosis may negatively impact a woman's attractiveness and self-confidence. There are various classifications and measurement techniques for breast ptosis used as references in the medical and garment industry. A practical and comprehensive classification will provide accurate standardized definitions of the degrees of ptosis to facilitate the development of corrective surgeries and well-fitting undergarments for women in need.

    METHODS: A systematic review on the classification and assessment techniques to measure breast ptosis was carried out based on the Preferred Reporting Items for Systemic Reviews and Meta-Analyses (PRISMA) guidelines. The risk of bias was assessed using the modified Newcastle-Ottawa scale for observational studies, whereas the Revised Cochrane risk-of-bias tool for randomized trials (RoB2) was used to evaluate randomized studies.

    RESULTS: Of 2550 articles identified in the literature search, 16 observational and 2 randomized studies describing the classification and assessment techniques of breast ptosis were included in the review. A total of 2033 subjects were involved. Half of the total observational studies had a Newcastle-Ottawa scale score of 5 and above. In addition, all randomized trials recorded a low overall bias.

    CONCLUSION: A total of 7 classifications and 4 measurement techniques for breast ptosis were identified. However, most studies did not demonstrate a clear derivation of sample size beside lacking robust statistical analysis. Hence, further studies that apply the latest technology to combine the strength of previous assessment techniques are needed to develop better classification system that is applicable to all affected women.

  6. Cheng YW, Chong CC, Cheng CK, Wang CH, Ng KH, Witoon T, et al.
    J Environ Manage, 2024 Feb;351:119919.
    PMID: 38157572 DOI: 10.1016/j.jenvman.2023.119919
    To replace the obsolete ponding system, palm oil mill effluent (POME) steam reforming (SR) over net-acidic LaNiO3 and net-basic LaCoO3 were proposed as the POME primary treatments, with promising H2-rich syngas production. Herein, the long-term evaluation of POME SR was scrutinized with both catalysts under the optimal conditions (600 °C, 0.09 mL POME/min, 0.3 g catalyst, & 74-105 μm catalyst particle size) to examine the catalyst microstructure changes, transient process stability, and final effluent evaluation. Extensive characterization proved the (i) adsorption of POME vapour on catalysts before SR, (ii) deposition of carbon and minerals on spent SR catalysts, and (iii) dominance of coking deactivation over sintering deactivation at 600 °C. Despite its longer run, spent LaCoO3 (50.54 wt%) had similar carbon deposition with spent LaNiO3 (50.44 wt%), concurring with its excellent coke resistance. Spent LaCoO3 (6.12 wt%; large protruding crystals) suffered a harsher mineral deposition than spent LaNiO3 (3.71 wt%; thin film coating), confirming that lower reactivity increased residence time of reactants. Transient syngas evolution of both SR catalysts was relatively steady up to 4 h but perturbed by coking deactivation thereafter. La2O2CO3 acted as an intermediate species that hastened the coke removal via reverse Boudouard reaction upon its decarbonation. La2O2CO3 decarbonation occurred continuously in LaCoO3 system but intermittently in LaNiO3 system. LaNiO3 system only lasted for 13 h as its compact ash blocked the gas flow. LaCoO3 system lasted longer (17 h) with its porous ash, but it eventually failed because KCl crystallites blocked its active sites. Relatively, LaCoO3 system offered greater net H2 production (72.78%) and POME treatment volume (30.77%) than LaNiO3 system. SR could attain appreciable POME degradation (>97% COD, BOD5, TSS, & colour intensity). Withal, SR-treated POME should be polished to further reduce its incompliant COD and BOD5.
  7. Ismail UN, Azlan CA, Khairullah S, Azman RR, Omar NF, Md Shah MN, et al.
    J Magn Reson Imaging, 2024 Dec;60(6):2447-2456.
    PMID: 38556790 DOI: 10.1002/jmri.29366
    BACKGROUND: Growing evidence suggests that marrow adipocytes play an active role in the regulation of bone metabolism and hematopoiesis. However, research on the relationship between bone and fat in the context of hematological diseases, particularly β-thalassemia, remains limited.

    PURPOSE: To investigate the relationship between marrow fat and cortical bone thickness in β-thalassemia and to identify key determinants influencing these variables.

    STUDY TYPE: Prospective.

    SUBJECTS: Thirty-five subjects in four subject groups of increasing disease severity: 6 healthy control (25.0 ± 5.3 years, 2 male), 4 β-thalassemia minor, 13 intermedia, and 12 major (29.1 ± 6.4 years, 15 male).

    FIELD STRENGTH/SEQUENCE: 3.0 T, 3D fast low angle shot sequence and T1-weighted turbo spin echo.

    ASSESSMENT: Analyses on proton density fat fraction (PDFF) and R2* values in femur subregions (femoral head, greater trochanter, intertrochanteric, diaphysis, distal) and cortical thickness (CBI) of the subjects' left femur. Clinical data such as age, sex, body mass index (BMI), and disease severity were also included.

    STATISTICAL TESTS: One-way analysis of variance (ANOVA), mixed ANOVA, Pearson correlation and multiple regression. P-values <0.05 were considered significant.

    RESULTS: Bone marrow PDFF significantly varied between the femur subregions, F(2.89,89.63) = 44.185 and disease severity, F(1,3) = 12.357. A significant interaction between subject groups and femur subregions on bone marrow PDFF was observed, F(8.67,89.63) = 3.723. Notably, a moderate positive correlation was observed between PDFF and CBI (r = 0.33-0.45). Multiple regression models for both PDFF (R2 = 0.476, F(13,151) = 10.547) and CBI (R2 = 0.477, F(13,151) = 10.580) were significant. Significant predictors for PDFF were disease severity (βTMi = 0.36, βTMa = 0.17), CBI (β = 0.24), R2* (β = -0.32), and height (β = -0.29) while for CBI, the significant determinants were sex (β = -0.27), BMI (β = 0.55), disease severity (βTMi = 2.15), and PDFF (β = 0.25).

    DATA CONCLUSION: This study revealed a positive correlation between bone marrow fat fraction and cortical bone thickness in β-thalassemia with varying disease severity, potentially indicating a complex interplay between bone health and marrow composition.

    EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 3.

  8. Ng KH, Cheung KY, Hu YM, Inamura K, Kim HJ, Krisanachinda A, et al.
    Australas Phys Eng Sci Med, 2009 Dec;32(4):175-9.
    PMID: 20169835
    This document is the first of a series of policy statements being issued by the Asia-Oceania Federation of Organizations for Medical Physics (AFOMP). The document was developed by the AFOMP Professional Development Committee (PDC) and was endorsed for official release by AFOMP Council in 2006. The main purpose of the document was to give guidance to AFOMP member organizations on the role and responsibilities of clinical medical physicists. A definition of clinical medical physicist has also been provided. This document discusses the following topics: professional aspects of education and training; responsibilities of the clinical medical physicist; status and organization of the clinical medical physics service and the need for clinical medical physics service.
  9. Ho E, Abdullah B, Tang A, Nordin A, Nair A, Lim G, et al.
    Biomed Imaging Interv J, 2008 Oct;4(4):e44.
    PMID: 21611021 DOI: 10.2349/biij.4.4.e44
    To date, the College of Radiology (CoR) does not see any clear benefit in performing whole body screening computed tomography (CT) examinations in healthy asymptomatic individuals. There are radiation risk issues in CT and principles of screening should be adhered to. There may be a role for targeted cardiac screening CT that derives calcium score, especially for asymptomatic medium-risk individuals and CT colonography when used as part of a strategic programme for colorectal cancer screening in those 50 years and older. However, population based screening CT examinations may become appropriate when evidence emerges regarding a clear benefit for the patient outweighing the associated radiation risks.
  10. Azlan CA, Wong JHD, Tan LK, A D Huri MSN, Ung NM, Pallath V, et al.
    Phys Med, 2020 Dec;80:10-16.
    PMID: 33070007 DOI: 10.1016/j.ejmp.2020.10.002
    PURPOSE: We present the implementation of e-learning in the Master of Medical Physics programme at the University of Malaya during a partial lockdown from March to June 2020 due to the COVID-19 pandemic.

    METHODS: Teaching and Learning (T&L) activities were conducted virtually on e-learning platforms. The students' experience and feedback were evaluated after 15 weeks.

    RESULTS: We found that while students preferred face-to-face, physical teaching, they were able to adapt to the new norm of e-learning. More than 60% of the students agreed that pre-recorded lectures and viewing videos of practical sessions, plus answering short questions, were beneficial. Certain aspects, such as hands-on practical and clinical experience, could never be replaced. The e-learning and study-from-home environment accorded a lot of flexibility. However, students also found it challenging to focus because of distractions, lack of engagement and mental stress. Technical problems, such as poor Internet connectivity and limited data plans, also compounded the problem.

    CONCLUSION: We expect e-learning to prevail in future. Hybrid learning strategies, which includes face-to-face classes and e-learning, will become common, at least in the medical physics programme of the University of Malaya even after the pandemic.

  11. Ninomiya K, Arimura H, Chan WY, Tanaka K, Mizuno S, Muhammad Gowdh NF, et al.
    PLoS One, 2021;16(1):e0244354.
    PMID: 33428651 DOI: 10.1371/journal.pone.0244354
    OBJECTIVES: To propose a novel robust radiogenomics approach to the identification of epidermal growth factor receptor (EGFR) mutations among patients with non-small cell lung cancer (NSCLC) using Betti numbers (BNs).

    MATERIALS AND METHODS: Contrast enhanced computed tomography (CT) images of 194 multi-racial NSCLC patients (79 EGFR mutants and 115 wildtypes) were collected from three different countries using 5 manufacturers' scanners with a variety of scanning parameters. Ninety-nine cases obtained from the University of Malaya Medical Centre (UMMC) in Malaysia were used for training and validation procedures. Forty-one cases collected from the Kyushu University Hospital (KUH) in Japan and fifty-four cases obtained from The Cancer Imaging Archive (TCIA) in America were used for a test procedure. Radiomic features were obtained from BN maps, which represent topologically invariant heterogeneous characteristics of lung cancer on CT images, by applying histogram- and texture-based feature computations. A BN-based signature was determined using support vector machine (SVM) models with the best combination of features that maximized a robustness index (RI) which defined a higher total area under receiver operating characteristics curves (AUCs) and lower difference of AUCs between the training and the validation. The SVM model was built using the signature and optimized in a five-fold cross validation. The BN-based model was compared to conventional original image (OI)- and wavelet-decomposition (WD)-based models with respect to the RI between the validation and the test.

    RESULTS: The BN-based model showed a higher RI of 1.51 compared with the models based on the OI (RI: 1.33) and the WD (RI: 1.29).

    CONCLUSION: The proposed model showed higher robustness than the conventional models in the identification of EGFR mutations among NSCLC patients. The results suggested the robustness of the BN-based approach against variations in image scanner/scanning parameters.

  12. Kiew LV, Cheah HY, Voon SH, Gallon E, Movellan J, Ng KH, et al.
    Nanomedicine, 2017 05;13(4):1447-1458.
    PMID: 28214608 DOI: 10.1016/j.nano.2017.02.002
    In photodynamic therapy (PDT), the low absorptivity of photosensitizers in an aqueous environment reduces singlet oxygen generation efficiency and thereby decreases photosensitizing efficacy in biological conditions. To circumvent this problem, we designed a phthalocyanine-poly-L-glutamic acid conjugate (1-PG) made from a new phthalocyanine (Pc 1) monofunctionalized to allow adequate conjugation to PGA. The resulting 1-PG conjugate retained high absorptivity in the near-infrared (NIR) region at its λmax675nm in an aqueous environment. The 1-PG conjugate demonstrated good singlet oxygen generation efficiency, increased uptake by 4 T1 breast cancer cells via clathrin-mediated endocytosis, and enhanced photocytotoxic efficacy. The conjugate also displayed a high light-dark toxicity ratio, approximately 1.5-fold greater than zinc phthalocyanine at higher concentration (10 μM), an important feature for the reduction of dark toxicity and unwanted side effects. These results suggest that the 1-PG conjugate could be a useful alternative for deep tissue treatment with enhanced anti-cancer (PDT) efficacy.
  13. Zulkawi N, Ng KH, Zamberi NR, Yeap SK, Satharasinghe DA, Tan SW, et al.
    Drug Des Devel Ther, 2018;12:1373-1383.
    PMID: 29872261 DOI: 10.2147/DDDT.S157803
    Background: Fermented food has been widely consumed as health food to ameliorate or prevent several chronic diseases including diabetes. Xeniji™, a fermented food paste (FFP), has been previously reported with various bioactivities, which may be caused by the presence of several metabolites including polyphenolic acids, flavonoids, and vitamins. In this study, the anti-hyperglycemic and anti-inflammatory effects of FFP were assessed.

    Methods: In this study, type 2 diabetes model mice were induced by streptozotocin and high-fat diet (HFD) and used to evaluate the antihyperglycemic and anti-inflammatory effects of FFP. Mice were fed with HFD and challenged with 30 mg/kg body weight (BW) of streptozotocin for 1 month followed by 6 weeks of supplementation with 0.1 and 1.0 g/kg BW of FFP. Metformin was used as positive control treatment.

    Results: Xeniji™-supplemented hyperglycemic mice were recorded with lower glucose level after 6 weeks of duration. This effect was contributed by the improvement of insulin sensitivity in the hyperglycemic mice indicated by the oral glucose tolerance test, insulin tolerance test, and end point insulin level. In addition, gene expression study has shown that the antihyperglycemic effect of FFP is related to the improvement of lipid and glucose metabolism in the mice. Furthermore, both 0.1 and 1 g/kg BW of FFP was able to reduce hyperglycemia-related inflammation indicated by the reduction of proinflammatory cytokines, NF-kB and iNOS gene expression and nitric oxide level.

    Conclusion: FFP potentially demonstrated in vivo antihyperglycemic and anti-inflammatory effects on HFD and streptozotocin-induced diabetic mice.

  14. Jong WL, Ung NM, Wong JH, Ng KH, Wan Ishak WZ, Abdul Malik R, et al.
    Phys Med, 2016 Nov;32(11):1466-1474.
    PMID: 27842982 DOI: 10.1016/j.ejmp.2016.10.022
    The purpose of this study is to measure patient skin dose in tangential breast radiotherapy. Treatment planning dose calculation algorithm such as Pencil Beam Convolution (PBC) and in vivo dosimetry techniques such as radiochromic film can be used to accurately monitor radiation doses at tissue depths, but they are inaccurate for skin dose measurement. A MOSFET-based (MOSkin) detector was used to measure skin dose in this study. Tangential breast radiotherapies ("bolus" and "no bolus") were simulated on an anthropomorphic phantom and the skin doses were measured. Skin doses were also measured in 13 patients undergoing each of the techniques. In the patient study, the EBT2 measurements and PBC calculation tended to over-estimate the skin dose compared with the MOSkin detector (p<0.05) in the "no bolus radiotherapy". No significant differences were observed in the "bolus radiotherapy" (p>0.05). The results from patients were similar to that of the phantom study. This shows that the EBT2 measurement and PBC calculation, while able to predict accurate doses at tissue depths, are inaccurate in predicting doses at build-up regions. The clinical application of the MOSkin detectors showed that the average total skin doses received by patients were 1662±129cGy (medial) and 1893±199cGy (lateral) during "no bolus radiotherapy". The average total skin doses were 4030±72cGy (medial) and 4004±91cGy (lateral) for "bolus radiotherapy". In some cases, patient skin doses were shown to exceed the dose toxicity level for skin erythema. Hence, a suitable device for in vivo dosimetry is necessary to accurately determine skin dose.
  15. Rajendra Acharya U, Meiburger KM, Wei Koh JE, Vicnesh J, Ciaccio EJ, Shu Lih O, et al.
    Artif Intell Med, 2019 09;100:101724.
    PMID: 31607348 DOI: 10.1016/j.artmed.2019.101724
    Cardiovascular diseases are the primary cause of death globally. These are often associated with atherosclerosis. This inflammation process triggers important variations in the coronary arteries (CA) and can lead to coronary artery disease (CAD). The presence of CA calcification (CAC) has recently been shown to be a strong predictor of CAD. In this clinical setting, computed tomography angiography (CTA) has begun to play a crucial role as a non-intrusive imaging method to characterize and study CA plaques. Herein, we describe an automated algorithm to classify plaque as either normal, calcified, or non-calcified using 2646 CTA images acquired from 73 patients. The automated technique is based on various features that are extracted from the Gabor transform of the acquired CTA images. Specifically, seven features are extracted from the Gabor coefficients : energy, and Kapur, Max, Rényi, Shannon, Vajda, and Yager entropies. The features were then ordered based on the F-value and input to numerous classification methods to achieve the best classification accuracy with the least number of features. Moreover, two well-known feature reduction techniques were employed, and the features acquired were also ranked according to F-value and input to several classifiers. The best classification results were obtained using all computed features without the employment of feature reduction, using a probabilistic neural network. An accuracy, positive predictive value, sensitivity, and specificity of 89.09%, 91.70%, 91.83% and 83.70% was obtained, respectively. Based on these results, it is evident that the technique can be helpful in the automated classification of plaques present in CTA images, and may become an important tool to reduce procedural costs and patient radiation dose. This could also aid clinicians in plaque diagnostics.
  16. Acharya UR, Raghavendra U, Fujita H, Hagiwara Y, Koh JE, Jen Hong T, et al.
    Comput Biol Med, 2016 12 01;79:250-258.
    PMID: 27825038 DOI: 10.1016/j.compbiomed.2016.10.022
    Fatty liver disease (FLD) is reversible disease and can be treated, if it is identified at an early stage. However, if diagnosed at the later stage, it can progress to an advanced liver disease such as cirrhosis which may ultimately lead to death. Therefore, it is essential to detect it at an early stage before the disease progresses to an irreversible stage. Several non-invasive computer-aided techniques are proposed to assist in the early detection of FLD and cirrhosis using ultrasound images. In this work, we are proposing an algorithm to discriminate automatically the normal, FLD and cirrhosis ultrasound images using curvelet transform (CT) method. Higher order spectra (HOS) bispectrum, HOS phase, fuzzy, Kapoor, max, Renyi, Shannon, Vajda and Yager entropies are extracted from CT coefficients. These extracted features are subjected to locality sensitive discriminant analysis (LSDA) feature reduction method. Then these LSDA coefficients ranked based on F-value are fed to different classifiers to choose the best performing classifier using minimum number of features. Our proposed technique can characterize normal, FLD and cirrhosis using probabilistic neural network (PNN) classifier with an accuracy of 97.33%, specificity of 100.00% and sensitivity of 96.00% using only six features. In addition, these chosen features are used to develop a liver disease index (LDI) to differentiate the normal, FLD and cirrhosis classes using a single number. This can significantly help the radiologists to discriminate FLD and cirrhosis in their routine liver screening.
  17. Acharya UR, Ng WL, Rahmat K, Sudarshan VK, Koh JEW, Tan JH, et al.
    Comput Biol Med, 2017 12 01;91:13-20.
    PMID: 29031099 DOI: 10.1016/j.compbiomed.2017.10.001
    Shear wave elastography (SWE) examination using ultrasound elastography (USE) is a popular imaging procedure for obtaining elasticity information of breast lesions. Elasticity parameters obtained through SWE can be used as biomarkers that can distinguish malignant breast lesions from benign ones. Furthermore, the elasticity parameters extracted from SWE can speed up the diagnosis and possibly reduce human errors. In this paper, Shearlet transform and local binary pattern histograms (LBPH) are proposed as an original algorithm to differentiate malignant and benign breast lesions. First, Shearlet transform is applied on the SWE images to acquire low frequency, horizontal and vertical cone coefficients. Next, LBPH features are extracted from the Shearlet transform coefficients and subjected to dimensionality reduction using locality sensitivity discriminating analysis (LSDA). The reduced LSDA components are ranked and then fed to several classifiers for the automated classification of breast lesions. A probabilistic neural network classifier trained only with seven top ranked features performed best, and achieved 98.08% accuracy, 98.63% sensitivity, and 97.59% specificity in distinguishing malignant from benign breast lesions. The high sensitivity and specificity of our system indicates that it can be employed as a primary screening tool for faster diagnosis of breast malignancies, thereby possibly reducing the mortality rate due to breast cancer.
  18. Givehchi S, Safari MJ, Tan SK, Md Shah MNB, Sani FBM, Azman RR, et al.
    Phys Med, 2018 Jan;45:198-204.
    PMID: 29373248 DOI: 10.1016/j.ejmp.2017.09.137
    PURPOSE: Accurate determination of the bifurcation angle and correlation with plaque buildup may lead to the prediction of coronary artery disease (CAD). This work evaluates two techniques to measure bifurcation angles in 3D space using coronary computed tomography angiography (CCTA).

    MATERIALS AND METHODS: Nine phantoms were fabricated with different bifurcation angles ranging from 55.3° to 134.5°. General X-ray and CCTA were employed to acquire 2D and 3D images of the bifurcation phantoms, respectively. Multiplanar reformation (MPR) and volume rendering technique (VRT) were used to measure the bifurcation angle between the left anterior descending (LAD) and left circumflex arteries (LCx). The measured angles were compared with the true values to determine the accuracy of each measurement technique. Inter-observer variability was evaluated. The two techniques were further applied on 50 clinical CCTA cases to verify its clinical value.

    RESULTS: In the phantom setting, the mean absolute differences calculated between the true and measured angles by MPR and VRT were 2.4°±2.2° and 3.8°±2.9°, respectively. Strong correlation was found between the true and measured bifurcation angles. Furthermore, no significant differences were found between the bifurcation angles measured using either technique. In clinical settings, large difference of 12.0°±10.6° was found between the two techniques.

    CONCLUSION: In the phantom setting, both techniques demonstrated a significant correlation to the true bifurcation angle. Despite the lack of agreement of the two techniques in the clinical context, our findings in phantoms suggest that MPR should be preferred to VRT for the measurement of coronary bifurcation angle by CCTA.

  19. Anam C, Naufal A, Sutanto H, Arifin Z, Hidayanto E, Tan LK, et al.
    Biomed Phys Eng Express, 2023 May 30;9(4).
    PMID: 37216929 DOI: 10.1088/2057-1976/acd785
    Objective. To develop an algorithm to measure slice thickness running on three types of Catphan phantoms with the ability to adapt to any misalignment and rotation of the phantoms.Method. Images of Catphan 500, 504, and 604 phantoms were examined. In addition, images with various slice thicknesses ranging from 1.5 to 10.0 mm, distance to the iso-center and phantom rotations were also examined. The automatic slice thickness algorithm was carried out by processing only objects within a circle having a diameter of half the diameter of the phantom. A segmentation was performed within an inner circle with dynamic thresholds to produce binary images with wire and bead objects within it. Region properties were used to distinguish wire ramps and bead objects. At each identified wire ramp, the angle was detected using the Hough transform. Profile lines were then placed on each ramp based on the centroid coordinates and detected angles, and the full-width at half maximum (FWHM) was determined for the average profile. The slice thickness was obtained by multiplying the FWHM by the tangent of the ramp angle (23°).Results. Automatic measurements work well and have only a small difference (<0.5 mm) from manual measurements. For slice thickness variation, automatic measurement successfully performs segmentation and correctly locates the profile line on all wire ramps. The results show measured slice thicknesses that are close (<3 mm) to the nominal thickness at thin slices, but slightly deviated for thicker slices. There is a strong correlation (R2= 0.873) between automatic and manual measurements. Testing the algorithm at various distances from the iso-center and phantom rotation angle also produced accurate results.Conclusion. An automated algorithm for measuring slice thickness on three types of Catphan CT phantom images has been developed. The algorithm works well on various thicknesses, distances from the iso-center, and phantom rotations.
  20. Ninomiya K, Arimura H, Tanaka K, Chan WY, Kabata Y, Mizuno S, et al.
    Comput Methods Programs Biomed, 2023 Jun;236:107544.
    PMID: 37148668 DOI: 10.1016/j.cmpb.2023.107544
    OBJECTIVES: To elucidate a novel radiogenomics approach using three-dimensional (3D) topologically invariant Betti numbers (BNs) for topological characterization of epidermal growth factor receptor (EGFR) Del19 and L858R mutation subtypes.

    METHODS: In total, 154 patients (wild-type EGFR, 72 patients; Del19 mutation, 45 patients; and L858R mutation, 37 patients) were retrospectively enrolled and randomly divided into 92 training and 62 test cases. Two support vector machine (SVM) models to distinguish between wild-type and mutant EGFR (mutation [M] classification) as well as between the Del19 and L858R subtypes (subtype [S] classification) were trained using 3DBN features. These features were computed from 3DBN maps by using histogram and texture analyses. The 3DBN maps were generated using computed tomography (CT) images based on the Čech complex constructed on sets of points in the images. These points were defined by coordinates of voxels with CT values higher than several threshold values. The M classification model was built using image features and demographic parameters of sex and smoking status. The SVM models were evaluated by determining their classification accuracies. The feasibility of the 3DBN model was compared with those of conventional radiomic models based on pseudo-3D BN (p3DBN), two-dimensional BN (2DBN), and CT and wavelet-decomposition (WD) images. The validation of the model was repeated with 100 times random sampling.

    RESULTS: The mean test accuracies for M classification with 3DBN, p3DBN, 2DBN, CT, and WD images were 0.810, 0.733, 0.838, 0.782, and 0.799, respectively. The mean test accuracies for S classification with 3DBN, p3DBN, 2DBN, CT, and WD images were 0.773, 0.694, 0.657, 0.581, and 0.696, respectively.

    CONCLUSION: 3DBN features, which showed a radiogenomic association with the characteristics of the EGFR Del19/L858R mutation subtypes, yielded higher accuracy for subtype classifications in comparison with conventional features.

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