Displaying publications 81 - 98 of 98 in total

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  1. Leong SS, Wong JHD, Md Shah MN, Vijayananthan A, Jalalonmuhali M, Chow TK, et al.
    Nephrology (Carlton), 2021 Jan;26(1):38-45.
    PMID: 33058334 DOI: 10.1111/nep.13805
    AIM: Renal biopsy is the gold standard for the histological characterization of chronic kidney disease (CKD), of which renal fibrosis is a dominant component, affecting its stiffness. The aim of this study was to investigate the correlation between kidney stiffness obtained by shear wave elastography (SWE) and renal histological fibrosis.

    METHODS: Shear wave elastography assessments were performed in 75 CKD patients who underwent renal biopsy. The SWE-derived estimates of the tissue Young's modulus (YM), given as kilopascals (kPa), were measured. YM was correlated to patients' renal histological scores, broadly categorized into glomerular, tubulointerstitial and vascular scores.

    RESULTS: Young's modulus correlates significantly with tubulointerstitial score (ρ = 0.442, P 

  2. Hashikin NAA, Yeong CH, Guatelli S, Abdullah BJJ, Ng KH, Malaroda A, et al.
    Phys Med Biol, 2017 Aug 22;62(18):7342-7356.
    PMID: 28686171 DOI: 10.1088/1361-6560/aa7e5b
    We aimed to investigate the validity of the partition model (PM) in estimating the absorbed doses to liver tumour ([Formula: see text]), normal liver tissue ([Formula: see text]) and lungs ([Formula: see text]), when cross-fire irradiations between these compartments are being considered. MIRD-5 phantom incorporated with various treatment parameters, i.e. tumour involvement (TI), tumour-to-normal liver uptake ratio (T/N) and lung shunting (LS), were simulated using the Geant4 Monte Carlo (MC) toolkit. 108track histories were generated for each combination of the three parameters to obtain the absorbed dose per activity uptake in each compartment ([Formula: see text], [Formula: see text], and [Formula: see text]). The administered activities, A were estimated using PM, so as to achieve either limiting doses to normal liver, [Formula: see text] or lungs, [Formula: see text] (70 or 30 Gy, respectively). Using these administered activities, the activity uptake in each compartment ([Formula: see text], [Formula: see text], and [Formula: see text]) was estimated and multiplied with the absorbed dose per activity uptake attained using the MC simulations, to obtain the actual dose received by each compartment. PM overestimated [Formula: see text] by 11.7% in all cases, due to the escaped particles from the lungs. [Formula: see text] and [Formula: see text] by MC were largely affected by T/N, which were not considered by PM due to cross-fire exclusion at the tumour-normal liver boundary. These have resulted in the overestimation of [Formula: see text] by up to 8% and underestimation of [Formula: see text] by as high as  -78%, by PM. When [Formula: see text] was estimated via PM, the MC simulations showed significantly higher [Formula: see text] for cases with higher T/N, and LS  ⩽  10%. All [Formula: see text] and [Formula: see text] by MC were overestimated by PM, thus [Formula: see text] were never exceeded. PM leads to inaccurate dose estimations due to the exclusion of cross-fire irradiation, i.e. between the tumour and normal liver tissue. Caution should be taken for cases with higher TI and T/N, and lower LS, as they contribute to major underestimation of [Formula: see text]. For [Formula: see text], a different correction factor for dose calculation may be used for improved accuracy.
  3. Hizam NDA, Ung NM, Jong WL, Zin HM, Rahman ATA, Loh JPY, et al.
    Phys Med, 2019 Nov;67:34-39.
    PMID: 31655398 DOI: 10.1016/j.ejmp.2019.10.023
    PURPOSE: Intensity Modulated Radiotherapy (IMRT) has changed the practice of radiotherapy since its implementation in the 1990s. The purpose of this study is to review current practice of IMRT in Malaysia.

    METHODS: A survey on medical physics aspects of IMRT is conducted on radiotherapy departments across Malaysia to assess the usage, experience and QA in IMRT, which is done for the first time in this country. A set of questionnaires was designed and sent to the physicist in charge for their responses. The questionnaire consisted of four sections; (i) Experience and qualification of medical physicists, (ii) CT simulation techniques (iii) Treatment planning and treatment unit, (iv) IMRT process, delivery and QA procedure.

    RESULTS: A total of 26 responses were collected, representing 26 departments out of 33 radiotherapy departments in operation across Malaysia (79% response rate). Results showed that the medical physics aspects of IMRT practice in Malaysia are homogenous, with some variations in certain areas of practices. Thirteen centres (52%) performed measurement-based QA using 2D array detector and analysed using gamma index criteria of 3%, 3 mm with variation confidence range. In relation to the IMRT delivery, 44% of Malaysia's physicist takes more than 8 h to plan a head and neck case compared to the UK study possibly due to the lack of professional training.

    CONCLUSIONS: This survey provides a picture of medical physics aspects of IMRT in Malaysia where the results/data can be used by radiotherapy departments to benchmark their local policies and practice.

  4. 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.
  5. 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.

  6. 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.

  7. 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.
  8. 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.

  9. 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.

  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. 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.
  13. 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.
  14. 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.
  15. 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.

  16. 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.

  17. Wee NK, Git KA, Lee WJ, Raval G, Pattokhov A, Ho ELM, et al.
    Korean J Radiol, 2024 Jul;25(7):603-612.
    PMID: 38942454 DOI: 10.3348/kjr.2024.0419
    Artificial intelligence (AI) is rapidly gaining recognition in the radiology domain as a greater number of radiologists are becoming AI-literate. However, the adoption and implementation of AI solutions in clinical settings have been slow, with points of contention. A group of AI users comprising mainly clinical radiologists across various Asian countries, including India, Japan, Malaysia, Singapore, Taiwan, Thailand, and Uzbekistan, formed the working group. This study aimed to draft position statements regarding the application and clinical deployment of AI in radiology. The primary aim is to raise awareness among the general public, promote professional interest and discussion, clarify ethical considerations when implementing AI technology, and engage the radiology profession in the ever-changing clinical practice. These position statements highlight pertinent issues that need to be addressed between care providers and care recipients. More importantly, this will help legalize the use of non-human instruments in clinical deployment without compromising ethical considerations, decision-making precision, and clinical professional standards. We base our study on four main principles of medical care-respect for patient autonomy, beneficence, non-maleficence, and justice.
  18. Lee YH, Quek ST, Khong PL, Lee CS, Wu JS, Zhang L, et al.
    Br J Radiol, 2020 Sep;93(1113):20200082.
    PMID: 32584595 DOI: 10.1259/bjr.20200082
    OBJECTIVE: To understand the status of pre-procedural safety practices in radiological examinations at radiology residency training institutions in various Asian regions.

    METHODS: A questionnaire based on the Joint Commission International Accreditation Standards was electronically sent to 3 institutions each in 10 geographical regions across 9 Asian countries. Questions addressing 45 practices were divided into 3 categories. A five-tier scale with numerical scores was used to evaluate safety practices in each institution. Responses obtained from three institutions in the United States were used to validate the execution rate of each surveyed safety practice.

    RESULTS: The institutional response rate was 70.0% (7 Asian regions, 21 institutions). 44 practices (all those surveyed except for the application of wrist tags for identifying patients with fall risks) were validated using the US participants. Overall, the Asian participants reached a consensus on 89% of the safety practices. Comparatively, most Asian participants did not routinely perform three pre-procedural practices in the examination appropriateness topic.

    CONCLUSION: Based on the responses from 21 participating Asian institutions, most routinely perform standard practices during radiological examinations except when it comes to examination appropriateness. This study can provide direction for safety policymakers scrutinizing and improving regional standards of care.

    ADVANCES IN KNOWLEDGE: This is the first multicenter survey study to elucidate pre-procedural safety practices in radiological examinations in seven Asian regions.

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