مهندسی مکانیک مدرس

مهندسی مکانیک مدرس

بررسی اثر جرمی و ترم واکنش در پیش بینی رشد تومور مغزی به کمک مدل ریاضی مبتنی بر تصاویر ام آر

نویسندگان
1 دانشگاه صنعتی سهند، تبریز، ایران
2 دانشگاه صنعتی سهند تبریز
3 دانشگاه صنعتی خواجه نصیرالدین طوسی
چکیده
امروزه سرطان یکی از عوامل اصلی مرگ و میر در جهان محسوب می‌شود و تفاوت بیولوژیکی افراد با یکدیگر موجب می‌شود که استفاده از یک برنامه‌ی درمانیِ واحد برای همه‌ی بیماران نتیجه‌ی مطلوبی نداشته باشد. به‌منظور شخصی‌سازی درمان، لازم است رفتار تومور در هر بیمار مشخص گردد؛ برای این منظور می‌توان از اطلاعات کلینیکی بیماران استفاده نمود. از میان روش‌های مختلف بررسی رشد تومور‌های سرطانی، روش‌های مدل‌سازی به علت انعطاف پذیریِ بیشتر برای بررسی شرایط مختلف، مورد توجه پژوهشگران قرار گرفته‌اند. مطالعات متعددی در زمینه بررسی تومورهای مغزی صورت گرفته است اما تنها مطالعات محدودی از تصاویر پزشکیِ خودِ بیمار برای شخصی‌سازی مدل رشد استفاده کرده‌اند. در مطالعه‌ی حاضر به بررسی رشد تومور مغزی با استفاده از مدل‌سازی ریاضی مبتنی بر تصاویر پزشکی ام آر پرداخته شده و اثر جرمی و ترم-های واکنش مختلف مورد ارزیابی قرار گرفته‌اند؛ هم‌چنین برای اولین بار پارامتر کسر درون سلولی برای ایجاد ارتباط میان مدل و تصاویر مربوط به تومور مغزی، به‌کار رفته است. نتایج پیش‌بینی شده با استفاده از دو معیار خطای جذر میانگین مربعاتِ کسر درون سلولی و ضریب دایس مورد مقایسه قرار گرفته‌اند. طبق این نتایج درنظر گرفتن اثر جرمی در مدل ریاضی رشد تومور مغزی موجب بهبود پیش‌بینی می‌شود. هم‌چنین لازم است به منظور بهبود دقت پیش‌بینی، ترم واکنش مناسب با توجه به اطلاعات پزشکی بیمار در مدل‌سازی درنظر گرفته شود. از روش ارائه شده در این پژوهش می‌توان به‌عنوان مبنایی جهت شخصی‌سازی درمان در بیماران مبتلا به تومور مغزی استفاده نمود.
کلیدواژه‌ها

موضوعات


عنوان مقاله English

Investigation of mass effect and reaction terms on the prediction of brain tumor growth by using mathematical model based on MRIs

نویسندگان English

Nargess Meghdadi 1
Hanieh Niroomand-Oscuii 2
Madjid Soltani 3
1 Sahand University of Technology, PhD student
2 Sahand University of Technology
3 K. N. Toosi University of Technology
چکیده English

Cancer is one of the main causes of mortality and morbidity worldwide. Using a single treatment plan for all of the patients is not efficient due to the biological heterogeneity in the individuals. In order to personalize the therapy plan, tumors behavior in each patient must be understood. For this purpose clinical information of the patients are used. Mathematical modeling has gained significant interest in tumor growth investigations, due to its higher flexibility than the other methods. Mass effect and the reaction terms are the key parameters that are investigated in this paper. This is the first time that the effects of these parameters are considered in brain tumor growth modeling and there are few researches that have used only MR images in this area. The mathematical models are used for predicting the growth of brain tumors based on personal MRIs and introducing intracellular fraction into the model. Results of the comparisons show that considering the mass effect in the growth model would improve the prediction. Furthermore, it is necessary to define the optimum formulation for reaction term according to patients' medical information, to be used in the personalized model of tumor growth prediction. The represented approach can be used as a basis for personalizing the therapy plan in patients with brain tumors.

کلیدواژه‌ها English

Brain Tumor
Mass effect
Reaction term
mathematical modeling
Personalized medicine
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