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Non-invasive diagnosis of risk in dengue patients using bioelectrical impedance analysis and artificial neural network

Ibrahim F, Faisal T, Salim MI, Taib MN

Med Biol Eng Comput, 2010 Nov;48(11):1141-8.
PMID: 20683676 DOI: 10.1007/s11517-010-0669-z

This paper presents a new approach to diagnose and classify early risk in dengue patients using bioelectrical impedance analysis (BIA) and artificial neural network (ANN). A total of 223 healthy subjects and 207 hospitalized dengue patients were prospectively studied. The dengue risk severity criteria was determined and grouped based on three blood investigations, namely, platelet (PLT) count (less than or equal to 30,000 cells per mm(3)), hematocrit (HCT) (increase by more than or equal to 20%), and either aspartate aminotransferase (AST) level (raised by fivefold the normal upper limit) or alanine aminotransferase (ALT) level (raised by fivefold the normal upper limit). The dengue patients were classified according to their risk groups and the corresponding BIA parameters were subsequently obtained and quantified. Four parameters were used for training and testing the ANN which are day of fever, reactance, gender, and risk group's quantification. Day of fever was defined as the day of fever subsided, i.e., when the body temperature fell below 37.5°C. The blood investigation and the BIA data were taken for 5 days. The ANN was trained via the steepest descent back propagation with momentum algorithm using the log-sigmoid transfer function while the sum-squared error was used as the network's performance indicator. The best ANN architecture of 3-6-1 (3 inputs, 6 neurons in the hidden layer, and 1 output), learning rate of 0.1, momentum constant of 0.2, and iteration rate of 20,000 was pruned using a weight-eliminating method. Eliminating a weight of 0.05 enhances the dengue's prediction risk classification accuracy of 95.88% for high risk and 96.83% for low risk groups. As a result, the system is able to classify and diagnose the risk in the dengue patients with an overall prediction accuracy of 96.27%.
Measurement of bioelectric and acoustic profile of breast tissue using hybrid magnetoacoustic method for cancer detection

Salim MI, Supriyanto E, Haueisen J, Ariffin I, Ahmad AH, Rosidi B

Med Biol Eng Comput, 2013 Apr;51(4):459-66.
PMID: 23238828 DOI: 10.1007/s11517-012-1014-5

This paper proposes a novel hybrid magnetoacoustic measurement (HMM) system aiming at breast cancer detection. HMM combines ultrasound and magnetism for the simultaneous assessment of bioelectric and acoustic profiles of breast tissue. HMM is demonstrated on breast tissue samples, which are exposed to 9.8 MHz ultrasound wave with the presence of a 0.25 Tesla static magnetic field. The interaction between the ultrasound wave and the magnetic field in the breast tissue results in Lorentz Force that produces a magnetoacoustic voltage output, proportional to breast tissue conductivity. Simultaneously, the ultrasound wave is sensed back by the ultrasound receiver for tissue acoustic evaluation. Experiments are performed on gel phantoms and real breast tissue samples harvested from laboratory mice. Ultrasound wave characterization results show that normal breast tissue experiences higher attenuation compared with cancerous tissue. The mean magnetoacoustic voltage results for normal tissue are lower than that for the cancerous tissue group. In conclusion, the combination of acoustic and bioelectric measurements is a promising approach for breast cancer diagnosis.
Fulltext Hyperthermia by near infrared radiation induced immune cells activation and infiltration in breast tumor

Wan Mohd Zawawi WFA, Hibma MH, Salim MI, Jemon K

Sci Rep, 2021 05 13;11(1):10278.
PMID: 33986437 DOI: 10.1038/s41598-021-89740-0

Breast cancer is the most common cancer that causes death in women. Conventional therapies, including surgery and chemotherapy, have different therapeutic effects and are commonly associated with risks and side effects. Near infrared radiation is a technique with few side effects that is used for local hyperthermia, typically as an adjuvant to other cancer therapies. The understanding of the use of near NIR as a monotherapy, and its effects on the immune cells activation and infiltration, are limited. In this study, we investigate the effects of HT treatment using NIR on tumor regression and on the immune cells and molecules in breast tumors. Results from this study demonstrated that local HT by NIR at 43 °C reduced tumor progression and significantly increased the median survival of tumor-bearing mice. Immunohistochemical analysis revealed a significant reduction in cells proliferation in treated tumor, which was accompanied by an abundance of heat shock protein 70 (Hsp70). Increased numbers of activated dendritic cells were observed in the draining lymph nodes of the mice, along with infiltration of T cells, NK cells and B cells into the tumor. In contrast, tumor-infiltrated regulatory T cells were largely diminished from the tumor. In addition, higher IFN-γ and IL-2 secretion was observed in tumor of treated mice. Overall, results from this present study extends the understanding of using local HT by NIR to stimulate a favourable immune response against breast cancer.
Thermal distribution analysis of three-dimensional tumor-embedded breast models with different breast density compositions

Wahab AA, Salim MI, Ahamat MA, Manaf NA, Yunus J, Lai KW

Med Biol Eng Comput, 2016 Sep;54(9):1363-73.
PMID: 26463520 DOI: 10.1007/s11517-015-1403-7

Breast cancer is the most common cancer among women globally, and the number of young women diagnosed with this disease is gradually increasing over the years. Mammography is the current gold-standard technique although it is known to be less sensitive in detecting tumors in woman with dense breast tissue. Detecting an early-stage tumor in young women is very crucial for better survival chance and treatment. The thermography technique has the capability to provide an additional functional information on physiological changes to mammography by describing thermal and vascular properties of the tissues. Studies on breast thermography have been carried out to improve the accuracy level of the thermography technique in various perspectives. However, the limitation of gathering women affected by cancer in different age groups had necessitated this comprehensive study which is aimed to investigate the effect of different density levels on the surface temperature distribution profile of the breast models. These models, namely extremely dense (ED), heterogeneously dense (HD), scattered fibroglandular (SF), and predominantly fatty (PF), with embedded tumors were developed using the finite element method. A conventional Pennes' bioheat model was used to perform the numerical simulation on different case studies, and the results obtained were then compared using a hypothesis statistical analysis method to the reference breast model developed previously. The results obtained show that ED, SF, and PF breast models had significant mean differences in surface temperature profile with a p value <0.025, while HD breast model data pair agreed with the null hypothesis formulated due to the comparable tissue composition percentage to the reference model. The findings suggested that various breast density levels should be considered as a contributing factor to the surface thermal distribution profile alteration in both breast cancer detection and analysis when using the thermography technique.
Speckle Noise Diffusion in Knee Articular Cartilage Ultrasound Images

Shoaib MA, Hossain MB, Hum YC, Chuah JH, Mohd Salim MI, Lai KW

Curr Med Imaging, 2020;16(6):739-751.
PMID: 32723246 DOI: 10.2174/1573405615666190903143330

BACKGROUND: Ultrasound (US) imaging can be a convenient and reliable substitute for magnetic resonance imaging in the investigation or screening of articular cartilage injury. However, US images suffer from two main impediments, i.e., low contrast ratio and presence of speckle noise.
AIMS: A variation of anisotropic diffusion is proposed that can reduce speckle noise without compromising the image quality of the edges and other important details.
METHODS: For this technique, four gradient thresholds were adopted instead of one. A new diffusivity function that preserves the edge of the resultant image is also proposed. To automatically terminate the iterative procedures, the Mean Absolute Error as its stopping criterion was implemented.
RESULTS: Numerical results obtained by simulations unanimously indicate that the proposed method outperforms conventional speckle reduction techniques. Nevertheless, this preliminary study has been conducted based on a small number of asymptomatic subjects.
CONCLUSION: Future work must investigate the feasibility of this method in a large cohort and its clinical validity through testing subjects with a symptomatic cartilage injury.
Feasibility of A-mode ultrasound attenuation as a monitoring method of local hyperthermia treatment

Manaf NA, Aziz MN, Ridzuan DS, Mohamad Salim MI, Wahab AA, Lai KW, et al.

Med Biol Eng Comput, 2016 Jun;54(6):967-81.
PMID: 27039402 DOI: 10.1007/s11517-016-1480-2

Recently, there is an increasing interest in the use of local hyperthermia treatment for a variety of clinical applications. The desired therapeutic outcome in local hyperthermia treatment is achieved by raising the local temperature to surpass the tissue coagulation threshold, resulting in tissue necrosis. In oncology, local hyperthermia is used as an effective way to destroy cancerous tissues and is said to have the potential to replace conventional treatment regime like surgery, chemotherapy or radiotherapy. However, the inability to closely monitor temperature elevations from hyperthermia treatment in real time with high accuracy continues to limit its clinical applicability. Local hyperthermia treatment requires real-time monitoring system to observe the progression of the destroyed tissue during and after the treatment. Ultrasound is one of the modalities that have great potential for local hyperthermia monitoring, as it is non-ionizing, convenient and has relatively simple signal processing requirement compared to magnetic resonance imaging and computed tomography. In a two-dimensional ultrasound imaging system, changes in tissue microstructure during local hyperthermia treatment are observed in terms of pixel value analysis extracted from the ultrasound image itself. Although 2D ultrasound has shown to be the most widely used system for monitoring hyperthermia in ultrasound imaging family, 1D ultrasound on the other hand could offer a real-time monitoring and the method enables quantitative measurement to be conducted faster and with simpler measurement instrument. Therefore, this paper proposes a new local hyperthermia monitoring method that is based on one-dimensional ultrasound. Specifically, the study investigates the effect of ultrasound attenuation in normal and pathological breast tissue when the temperature in tissue is varied between 37 and 65 °C during local hyperthermia treatment. Besides that, the total protein content measurement was also conducted to investigate the relationship between attenuation and tissue denaturation level at different temperature ranges. The tissues were grouped according to their histology results, namely normal tissue with large predominance of cells (NPC), cancer tissue with large predominance of cells (CPC) and cancer with high collagen fiber content (CHF). The result shows that the attenuation coefficient of ultrasound measured following the local hyperthermia treatment increases with the increment of collagen fiber content in tissue as the CHF attenuated ultrasound at the highest rate, followed by NPC and CPC. Additionally, the attenuation increment is more pronounced at the temperature over 55 °C. This describes that the ultrasound wave experienced more energy loss when it propagates through a heated tissue as the tissue structure changes due to protein coagulation effect. Additionally, a significant increase in the sensitivity of attenuation to protein denaturation is also observed with the highest sensitivity obtained in monitoring NPC. Overall, it is concluded that one-dimensional ultrasound can be used as a monitoring method of local hyperthermia since its attenuation is very sensitive to the changes in tissue microstructure during hyperthermia.
Carpal Bone Segmentation Using Fully Convolutional Neural Network

Meng LK, Khalil A, Ahmad Nizar MH, Nisham MK, Pingguan-Murphy B, Hum YC, et al.

Curr Med Imaging Rev, 2019;15(10):983-989.
PMID: 32008525 DOI: 10.2174/1573405615666190724101600

BACKGROUND: Bone Age Assessment (BAA) refers to a clinical procedure that aims to identify a discrepancy between biological and chronological age of an individual by assessing the bone age growth. Currently, there are two main methods of executing BAA which are known as Greulich-Pyle and Tanner-Whitehouse techniques. Both techniques involve a manual and qualitative assessment of hand and wrist radiographs, resulting in intra and inter-operator variability accuracy and time-consuming. An automatic segmentation can be applied to the radiographs, providing the physician with more accurate delineation of the carpal bone and accurate quantitative analysis.
METHODS: In this study, we proposed an image feature extraction technique based on image segmentation with the fully convolutional neural network with eight stride pixel (FCN-8). A total of 290 radiographic images including both female and the male subject of age ranging from 0 to 18 were manually segmented and trained using FCN-8.
RESULTS AND CONCLUSION: The results exhibit a high training accuracy value of 99.68% and a loss rate of 0.008619 for 50 epochs of training. The experiments compared 58 images against the gold standard ground truth images. The accuracy of our fully automated segmentation technique is 0.78 ± 0.06, 1.56 ±0.30 mm and 98.02% in terms of Dice Coefficient, Hausdorff Distance, and overall qualitative carpal recognition accuracy, respectively.
Fulltext Transcranial Electrical Motor Evoked Potential in Predicting Positive Functional Outcome of Patients after Decompressive Spine Surgery: Review on Challenges and Recommendations towards Objective Interpretation

Jamaludin MR, Lai KW, Chuah JH, Zaki MA, Hum YC, Tee YK, et al.

Behav Neurol, 2021;2021:2684855.
PMID: 34777631 DOI: 10.1155/2021/2684855

Spine surgeries impose risk to the spine's surrounding anatomical and physiological structures especially the spinal cord and the nerve roots. Intraoperative neuromonitoring (IONM) is a technology developed to monitor the integrity of the spinal cord and the nerve roots via the surgery. Transcranial motor evoked potential (TcMEP) (one of the IONM modalities) is adopted to monitor the integrity of the motor pathway of the spinal cord and the motor nerve roots. Recent research suggested that the IONM is conducive as a prognostic tool towards the patient's functional outcome. This paper summarizes the researches of IONM being adopted as a prognostic tool. In addition, this paper highlights the problems associated with the signal parameters as the improvement criteria in the previous researches. Lastly, we review the challenges of TcMEP to achieve a prognostic tool focusing on the factors that could interfere with the generation of a stable TcMEP response. The final section will discuss recommendations for IONM technology to achieve an objective prognostic tool.