Automatic Tissue Identification In HIFU Target Areas And Accoustic Passages Based On MRI Images

HIFU (High Intensity Focused Ultrasound) therapy system, is a non-invasive and minimally-invasive device recently developed for clinical treatment of tumors. Ultrasound beams from an extracorporeal transducer penetrates the overlying tussue, and then focuses on and ablates the target tumor within the body. Different from other modern hi-tech therapy system, it's mechanism of action is to focus high-energy ultrasound in the target area so as to induce instant temperature rise which then makes the tumor tissue coagulatively necrozedCompared with other analogous tumor therapeutic tools, radiotherapy technology is the most widely used extracorporeal irradiation technology at present time. Therapeutic effect of radiotherapy is achieved by inducing gradual necrosis of the irradiated tissues, but so gradual that its curative effect only appears several weeks later. Targeting deviation usually does not cause such safety problems as patient death. Therefore, in clinical practice, the irradiated area often exceeds the tumor area for enhancing therapy efficacy. It's determined that a deviation within 3cm is allowed in radiotherapy targeting. However, if this deviation was allowed in HIFU targeting, vital organs or structures would be damaged.To guarantee safety of some special sites or areas, HIFU target areas are smaller than the actual tumor region. This safety concern inevitably is offsetting therapeutic efficacy of HIFU. Under such a background, to improve HIFU treatment accuracy based on targeting accuracy will mean significantly for efficacy enhancement.The study and research into tissue identification based on magnetic resonance imaging (MRI) will shed a light upon accurate targeting and accurate treating in HIFU procedure, and it will also provide HIFU medical personnel with a set of principles as how to identify vital tissues or structures, to calculate accoustic impedance and to chooce the optimal accoustic path. In view of this, we initiate a project to study automatic identification of tissues in the target region and in acoustic path based on MRI images. I did not found similar reports after literature research.Objective: (1) To study common imaging characteristics of human body tissues and to determine its influencing factors through MRI image analysis. (2) To establish a MRI-image-based tissue automatic recognition system. (3) To establish a MRI-and-CT-image-based target region automatic drawing system. The systems established would be helpful to enhance the degree of accuracy during HIFU 3D conformal treatment planning.The research includes two parts as below: Part one MRI Imaging characteristics of human body tissuesObjective: To study common imaging characteristics of human body tissues (including tumors) by analyzing MRI images of hysteromyoma.Methods: A"MRI image analysis software"developed specially for this study under Microsoft Visual C++ 6.0 was used. T2 MRI image data of hysteromyoma were analysed using matched-pair design.Materials: Original image data of hysteromyoma in DICOM format from MRI system (GE) in 2nd Affiliated Hospital of Chongqing Medical University.Results: (1) Under a same imaging condition and from the same patient, hysteromyoma MRI images obtained during different periods had similar MR figs section. (2) Under a same imaging condition, MR figs section from different patients had no significant difference. (3)Under a same MRI imaging condition, MR figs section before HIFU treatment and after HIFU treatment was significantly different. (4) Some principal tissues in acoustic path during hysteromyoma HIFU treatment, such as abdominal wall muscle, turgid bladder, normal hystera tissue, or hysteromyoma, had significantly-different imaging MR figs section.Conclusions: On a same MRI device and under a same MRI imaging condition, the same kind of tissues in different persons have some commonalities, while different tissues have differences. It's these commonalities and differences that provides support to automatic tissue identification, which enables accurate calculation of ultrasound-path acoustic impedance and accurate auto-drawing of the target region. All of the above developments will certainly optimate the HIFU treatment system. In addition, since HIFU treatment will change tissue's MRI charateristics, our study also shows prospects to establish a new standard for therapeutic efficacy evaluation.Part two Establish automatic tissue identification system and automatic target drawing system based on MRI imagesObjective: (1) To analyze the way of automatic tissue recognitio based on MRI images. (2) To establish an automatic target drawing system, and thus to advance the current 3D imaging technology so as to improve accuracy of HIFU treatment. The ultimate objective is to optimate the HIFU treatment system.Methods: We applied current computer recognition techniques in the establishment of automatic tissue identification system based on such images as MRI. The identified tissues were then segmented and further processed to draw a relatively accurate target region. Since a single technology or a single algorithm method was not able to meet requirements of automatic drawing in our study, we applied multiple techniques. After many times of comparative tests, we established an point-and-plane-integrated processing software system, whose core technology lies on the segmentation threshold based on MRI image characteristics, and on image matching technique based on sector accrete algorithm. We also used principles and algorithms such as image segmentation and threshold determination.Results & conclusions: (1) The software system we established is effective in automatic tissue identification. (2) The software system can realize reliable and quick automatic drawing of such target regions whose boundary is clear in medical images (MRI, CT and etc.). Therefore, this study is helpful to realize accurate targeting and accurate treating in HIFU therapy and radiotherapy, which has significant value in clinical practice.Additionally, we applied several image analysis techniques during the establishment of this software system, therefore, it also helps doctors to identify some special tissues , hence improve their medical proficiency. Our study also shed a light on the programming of intelligent diagnosis system. Besides its function in HIFU treatment, the automatic drawing program in the software system can also be used in other therapeutic modalities, such as 3D radiotherapy and super gammaknife therapy, to reduce complication and to protect important adjacent tissues and structures. Therefore, the software system developed in this study may promises to play a significant role in advancing medical technology.