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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.

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