Browsing by Author "Kakanand Srungboonmee"

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    Computer-aided classification of alzheimer's disease based on support vector machine with combination of cerebral image features in MRI
    (Mahidol University. Mahidol University Library and Knowledge Center, 2016) Chonnikan Jongkreangkrai; Yudthaphon Vichianin; Chiraporn Tocharoenchai; Kakanand Srungboonmee
    Several studies have differentiated Alzheimer's disease (AD) using cerebral image features derived from magnetic resonance (MR) brain images, such as the volume and shape of hippocampus and cerebral cortical thicknesses. In this study, we were interested in combining cerebral image features, including hippocampus and amygdala volumes, and entorhinal cortex thickness to improve the performance of the AD differentiation. Thus, the aim of this study was to investigate the useful cerebral image features obtained from MRI for computer-aided classification of AD patients using a support vector machine (SVM). T1-weighted MR brain images of 100 AD patients and those of 100 normal subjects obtained from Alzheimer's Disease Neuroimaging Initiative were studied. FreeSurfer (software for analysis of brain imaging data) was used to measure hippocampus and amygdala volumes, and entorhinal cortex thicknesses in left and right brain hemispheres. Relative volumes of hippocampus and amygdala were then calculated using total intracranial volume (TIV) to correct the variation in individual head size. SVM was employed for classification of AD patients using five different combinations of cerebral image features (H: left and right hippocampus relative volumes, A: left and right amygdala relative volumes, E: left and right entorhinal cortex thicknesses, HA: left and right hippocampus and amygdala relative volumes, and ALL: all features). Receiver operating characteristic (ROC) analysis and area under the curve (AUC) were used to evaluate the method. AUC values of 5 cerebral feature combinations were 0.8575 (H), 0.8374 (A), 0.8422 (E), 0.8631 (HA), and 0.8906 (ALL), respectively. Although using all features (ALL) provided the highest AUC, there were no statistically significant differences among them except for the A feature. Our results showed that all combinations of cerebral image features derived from T1- weighted MR brain images may be feasible for computer-aided classification of AD patients by using SVM.
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    Development of a software tool for an internal dosimetry using MIRD method
    (Mahidol University. Mahidol University Library and Knowledge Center, 2016) Anucha Chaichana; Chiraporn Tocharoenchai; Yudthaphon Vichianin; Kakanand Srungboonmee
    The aim of this thesis was to develop software which provides sufficient tools for internal dosimetry using the MIRD (Medical Internal Radiation Dose) method in a single environment. The graphic user-interface development environment (GUIDE) in MATLAB software was used to develop a graphic user-interface-based software named CALRADDOSE. The absorbed-dose calculation in this software was performed using the MIRD method. The data for absorbed-dose calculation, including radiation decay data, organ masses, and absorbed fraction, were downloaded from the RADAR website. The CALRADDOSE software consisted of five modules such as the 'Welcome' module for creating a main directory and navigating to other modules, the 'Planar Image Processing' module for planar image analysis, the 'SPECT Image Processing' module for SPECT image analysis, the 'Residence Time Calculation' module for residence time calculation, and the 'Dose Calculation' module for absorbed-dose calculation. To evaluate the accuracy of the calculation processes in the CALRADDOSE software, fifteen Ga-67 studies were used as test datasets. Paired t- test was performed with a 95% confidence interval in order to compare residence times and absorbed doses obtained from this software and those obtained from the commercial software named OLINDA/EXM (Organ Level Internal Dose Assessment). The results showed that there was no statistically significant difference in the residence times and absorbed doses calculated by CALRADDOSE and OLINDA/EXM with p-value = 0.489 and 0.228, respectively. In conclusion, CALRADDOSE is a graphic user-interface-based software, which can perform all steps of internal dosimetry within a single environment leading to reduced calculation time and reduced possibility of error. CALRADDOSE also provides fast and accurate results which may be useful for educational, research, or clinical purposes.
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    Elucidating the structure-activity relationship of curcumin and its biological activities
    (2014-07-01) Chanin Nantasenamat; Saw Simeon; Abdul Hafeez; Veda Prachayasittikul; Apilak Worachartcheewan; Napat Songtawee; Kakanand Srungboonmee; Chartchalerm Isarankura-Na-Ayudhya; Supaluk Prachayasittikul; Virapong Prachayasittikul; Mahidol University
    © 2014 Nova Science Publishers, Inc. Curcumin is a major constituent of the turmeric plant Curcuma longa, a member of the Zingiberaceae family, which is cultivated in India, most parts of Southeast Asia, Asia and other parts of the world. Curcumin has been shown to afford a wide range of pharmacological activities encompassing antioxidative, anti-inflammatory, antibacterial, antifungal, antiviral, antiproliferative, proapoptotic and anti-atherosclerotic effects as well as medicinal benefits against neurodegenerative diseases, arthritis, allergy, inflammatory bowel disease, nephrotoxicity, AIDS, psoriasis, diabetes, multiple sclerosis, cardiovascular disease and lung fibrosis. Moreover, curcumin could suppress inflammatory cytokines as well as suppress various target proteins in cancer cell lines. Owing to its multi-faceted health benefits, curcumin has been used as health supplements as well as natural remedy while several clinical trials are under way to investigate its potential therapeutic usage. This chapter discusses the origins of curcumin's biological activities in light of its structure-activity relationship. The structure of curcumin iscomprised of the central 1,6-heptadiene-3,5-dione bearing two terminal phenolic rings. Structural modification of this compound alters its biological activities either by affecting its selectivity, specificity or potency. Understanding of such structure-activity relationship may provide the impetus for further expanding its biological activity repertoire. Although it is an ambitious task to review the current state-of-the-art on the structure-activity relationship of curcumin, it should be mentioned that it is impossible for this chapter to provide a comprehensive account but rather a representative overview is given herein.
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    A patellofemoral chondropathy quantification from vibroarthrography: A preliminary study
    (2021-09-01) Varit Watcharaprechasakul; Kakanand Srungboonmee; Vajira Hospital; Mahidol University
    Objective: To preliminarily investigate if the proposed parameter derived from the knee vibroarthrographic (VAG) signals, namely the VAG score, could potentially be used to quantify the patellofemoral chondropathy. Materials and Methods: Five subjects with meniscus injury as an indication for arthroscopy were recruited for the present preliminary crosssectional study. Prior to the arthroscopy, the Kujala scores were assessed and the knee VAG signals were recorded from all the subjects. Subjects were asked to actively perform the knee flexion-extension for three cycles in the supine position while recording the VAG signal. The proposed VAG score was defined as the power spectral density of the signal in the frequency of 450 to 1,000 Hz. Patellofemoral chondropathy was arthroscopically graded using French Society of Arthroscopy system (SFA) score and SFA category. Results: The SFA score was significantly strongly correlated with the VAG score (r=0.87, p=0.02) but not with the Kujala score (r=-0.79, p=0.11). Likewise, the SFA category was significantly correlated with the VAG score (r=0.98, p<0.01) but not with the Kujala score (r=-0.67, p=0.22). Conclusion: The proposed signal-based VAG score was demonstrated to be preliminarily able to better assess the patellofemoral chondropathy non-invasively, compared to the Kujala score, which is questionnaire-based.
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    Probing the origins of 17β-hydroxysteroid dehydrogenase type 1 inhibitory activity via QSAR and molecular docking
    (2015-05-26) Kakanand Srungboonmee; Napat Songtawee; Teerawat Monnor; Virapong Prachayasittikul; Chanin Nantasenamat; Mahidol University
    © 2015 Elsevier Masson SAS. It is generally known that proliferation of human breast cancer cells is stimulated by excess estrogen namely 17β-estradiol. Therefore, reduction of 17β-estradiol production by inhibiting 17β-hydroxysteroid dehydrogenase type 1 (17β-HSD1) is an interesting route for breast cancer treatment particularly during adjuvant therapy. This study investigated the structure-activity relationship of 17β-HSD1 inhibitors as to gain insights and understanding on the origins of 17β-HSD1 inhibitory activities. To meet this goal, multiple linear regression model was constructed and correspondingly the results revealed good predictivity (N =31, R2= 0.9438, Q2= 0.8530). The model suggested that low molecular weight and energy were preferred as 17β-HSD1 inhibitors. Additionally, high molecular flexibility and high number of hydrogen bond donors were also shown to be important that is in correspondence to previously reported pharmacophore model of 17β-HSD1 inhibitors. Furthermore, molecular docking of inhibitors to 17β-HSD1 followed by anchor analysis suggested that three different pockets comprising of hydrogen bonding sites 1 and 2 as well as van der Waals contacts contributed to protein-ligand interactions. Post-docking analysis of potent compound 9 with 17β-HSD1 suggested that the binding modality was similar to the binding of substrate (i.e. estradiol) and its analog (i.e. equilin). Such information is useful in guiding the further design of novel and robust 17β-HSD1 inhibitors.
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    QSAR study of anti-prion activity of 2-aminothiazoles
    (2012-10-23) Prasit Mandi; Chanin Nantasenamat; Kakanand Srungboonmee; Chartchalerm Isarankura-Na-Ayudhya; Virapong Prachayasittikul; Mahidol University
    2-aminothiazoles is a class of compounds capable of treating life-threatening prion diseases. QSAR studies on a set of forty-seven 2-aminothiazole derivatives possessing anti-prion activity were performed using multivariate analysis, which comprised of multiple linear regression (MLR), artificial neural network (ANN) and support vector machine (SVM). The results indicated that MLR afforded reasonable performance with a correlation coefficient (r) and root mean squared error (RMSE) of 0.9073 and 0.2977, respectively, as obtained from leave-oneout cross-validation (LOO-CV). More sophisticated learning methods such as SVM provided models with the highest accuracy with r and RMSE of 0.9471 and 0.2264, respectively, while ANN gave reasonable performance with r and RMSE of 0.9023 and 0.3043, respectively, as obtained LOO-CV calculations. Descriptor analysis from the regression coefficients of the MLR model suggested that compounds should be asymmetrical molecule with low propensity to form hydrogen bonds and high frequency of N content at topological distance 02 in order to provide good activities. Insights from QSAR studies is anticipated to be useful in the design of novel derivatives based on the 2-aminothiazole scaffold as potent therapeutic agents against prion diseases.
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    Quantitative structure-property relationship study of spectral properties of green fluorescent protein with support vector machine
    (2013-01-05) Chanin Nantasenamat; Kakanand Srungboonmee; Saksiri Jamsak; Natta Tansila; Chartchalerm Isarankura-Na-Ayudhya; Virapong Prachayasittikul; Mahidol University; Prince of Songkla University
    Green fluorescent protein (GFP) is an autofluorescent protein that has been widely used in the biomedical sciences for molecular imaging applications. Computational approach for predicting the spectral properties of GFP offers great benefit for the design and engineering of novel color variants. Herein, we present a quantitative structure-property relationship (QSPR) study to model the spectral properties (e.g. excitation and emission maxima) of GFP chromophores using support vector machine (SVM). The data set is composed of 19 chromophores from GFP color variants and 29 synthetic GFP chromophores based on the imidazolinone scaffold. Quantum chemical descriptors were used to provide information on the physicochemical properties of the chromophores. Such descriptors were mapped onto a higher dimensional space via kernel functions (e.g. linear, polynomial and radial basis function kernels) and learning is then performed using SVM. The predicted spectral properties were well correlated with their experimental values as observed from correlation coefficient in the range of r = 0.953-0.979. Predictive performance of excitation maxima (r = 0.967-0.979) outperformed that of the emission maxima (r = 0.953-0.961). The present strategy holds great promise for expanding the spectral repertoire of GFP by facilitating the rational design of novel color variants. © 2012 Elsevier B.V.
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    Resurfacing in a Posterior-Stabilized Total Knee Arthroplasty Reduces Patellar Crepitus Complication: A Randomized, Controlled Trial
    (2019-09-01) Satit Thiengwittayaporn; Kakanand Srungboonmee; Bhakawat Chiamtrakool; Vajira Hospital; Mahidol University
    © 2019 Elsevier Inc. Background: Patellar crepitus (PC) is a common complication after total knee arthroplasty (TKA) using a posterior-stabilized (PS) prosthesis. While numerous factors have been associated with PC development after PS-TKA, patellar resurfacing (PR) which directly impacts the patellofemoral joint kinematics has been underinvestigated. A prospective, randomized, controlled trial was conducted to (1) compare the PC incidence in PR and non-PR PS-TKA, (2) determine the time of PC presentation in PS-TKA, (3) identify radiographic parameters associated with PC, and (4) compare clinical outcomes of patients with and without PR. Methods: A total of 84 patients who underwent unilateral TKA using the Legion PS Total Knee System were randomized into PR group or non-PR group. PC incidence, time of PC presentation, radiographic parameters associated with PC development, and clinical outcomes were evaluated at 3 months, 6 months, 9 months, and 1 year postoperatively. Results: PC occurred significantly more in the non-PR group (23.1% vs 7.3%, P =.048). Time of PC presentation in both groups was not different. Anterior knee pain was found in 16.7% of crepitus patients, and none required any surgical procedure. The non-PR knees had significant decreases in patellar shift index, patellar displacement, Insall-Salvati ratio, and patellar component height and increase in change in posterior femoral offset. Oxford and patellar scores were significantly better in the PR group at 9 months and 1 year. Conclusion: Given higher PC incidence and several worse clinical outcomes in the non-PR, we recommend resurfacing during PS-TKA with this knee system to avoid PC development.
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    Spectral analysis of knee vibroarthrographic signals in asymptomatic chondromalacia patella
    (2016-01-01) Kulwanee Meedeng; Warakorn Charoensuk; Korakod Panich; Kakanand Srungboonmee; Mahidol University
    © 2016 IEEE. Early stage of chondromalacia patella is usually asymptomatic. Detection of chondromalacia patella sooner can delay further cartilage degeneration by appropriate exercise prescription and behavioral change. The purpose of this study is to preliminary examine asymptomatic subjects and investigate the knee vibroarthrographic (VAG) signals in order to suggest possible parameters to detect chondromalacia patella at the early stage. Frequency characteristics of the signals which include energy and the summing of spectral power in each 500 Hz frequency band were observed. Energy and spectral power of the VAG signals with chondromalacia patella were obviously higher than normal VAG signals, particularly in the high frequency bands (higher than 500 Hz). VAG signal is therefore a promising tool in detection of early stage chondromalacia patella.
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    Spectral analysis on vibroarthrographic signal of total knee arthroplasty
    (2017-02-08) Tanut Aranchayanont; Jitkomut Songsiri; Kakanand Srungboonmee; Chulalongkorn University; Mahidol University
    © 2016 IEEE. Patellar resurfacing during total knee arthroplasty (TKA) depends on surgeon's decisions and has been discussed if resurfacing is better than non-resurfacing. This paper aims to discuss the similarities and differences of the vibroarthrographic (VAG) signal of the knee underwent TKA with either resurfaced or non-resurfaced patella in time-frequency domain. Motion trends and noises were filtered and then processed with Ensemble Empirical Model Decomposition (EEMD) and Detrended Fluctuation Analysis (DFA), which decomposes a non-stationary signal into a set of modes and discards modes that are uncorrelated. However, time-frequency analysis of processed signals suggests no significant differences between both classes and the results rather depend on the individual knee condition.
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    A vibration sensor approach to detect intra-articular needle tip placement in the knee joint: a proof-of-concept study
    (2021-12-01) Rit Apinyankul; Kritsada Siriwattanasit; Kakanand Srungboonmee; Witchaporn Witayakom; Weerachai Kosuwon; Faculty of Medicine, Khon Kaen University; Mahidol University
    Background: Intra-articular injection in the dry knee joint is technically challenging particularly for the beginners. The aim of this study was to investigate the possible use of the vibration sensor to detect if the needle tip was at the knee intra-articular position by characterizing the frequency component of the vibration signal during empty syringe air injection. Methods: Two milliliters of air were injected supero-laterally at extra- and intra-articular positions of a cadaveric knee joint, using needles of size 18, 21 and 24 gauge (G). Ultrasonography was used to confirm the positions of needle tip. A piezoelectric accelerometer was mounted medially on the knee joint to collect the vibration signals which were analyzed to characterize the frequency components of the signals during injections. Results: The vibration frequency band power in the range of 500–1500 Hz was visually observed to potentially localize the needle tip placement during air injection whether they were at the knee extra-articular or intra-articular positions, as demonstrated by the higher band power (over − 40 dB or dB) for all the needle sizes. The differences of frequency band power between extra- and intra-articular positions were 18.1 dB, 26.4 dB and 39.2 dB for the needle size 18G, 21G and 24G respectively. The largest difference in spectral power was found in the smallest needle diameter (24G). Conclusions: A vibration sensor approach was preliminarily proved to distinguish the intra-articular from extra-articular needle placement in the knee joint. This study demonstrated a possible implementation of an alternative electronic device based on this technique to detect the intra-articular knee injection.
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    Vibrational Analysis on Patellofemoral Joint Degradation of Swine's Knee
    (2019-04-09) Nopdanai Ajavakom; Kakanand Srungboonmee; Kocharath Tanadumrongsak; Visarut Limsowan; Chulalongkorn University; Mahidol University
    © Published under licence by IOP Publishing Ltd. Knee's severe patellofemoral joint degeneration gives a lot of people difficulty to endure daily life because walking or any leg movement can cause serious pain. At present, physical examination, x-ray and MRI are often used to diagnose the condition; however, each of the methods has its own disadvantages. For instance, physical examination is highly dependent on the skill of the doctor who practiced the examination, which cannot avoid misdiagnosing the condition. X-ray can detect wounds and tears, but the accuracy is also not top-notch since the result of an x-ray is a 2-dimension picture. MRI is the most reliable method for diagnosing the condition; however, the cost is very high. We propose that other than x-ray and MRI, patellofemoral joint degeneration can be identified by analyzing vibrational signals obtained from an accelerometer attached to the patella while sitting and moving the leg up and down. At the beginning of the study, swine's knees are used to imitate human's knee. Swine's knees with various surface degradation levels are put on a machine that mimics the mechanism of knee motion. An accelerometer is mounted on the patella of the swine's knee while the machine is running to measure the friction and roughness induced vibration of the patella. The vibration results suggest that more surface degradation the higher vibration signal amplitude. Nevertheless, the method still needs a lot more improvement on the database and testing procedures, in order to make it accurate, dependable and affordable. Hence, with further analysis on patient's knees it is highly possible to determine whether patient's knee is degraded or not and at what degradation level.