Peksa Janis, Kukharenko Dmytro, Perekrest Andrii, Mamchur Dmytro
Information Technology Faculty, Turiba University, Graudu Street 68, LV-1058 Riga, Latvia.
Institute of Information Technology, Riga Technical University, Kalku Street 1, LV-1658 Riga, Latvia.
Sensors (Basel). 2025 Sep 17;25(18):5781. doi: 10.3390/s25185781.
The advancement of science and technology has elevated the practice of surgery where computer systems now perform the majority of calculations required for successful interventions. This technological progress can be leveraged to foster surgical improvements by developing and implementing novel computer models for the preoperative planning of surgical treatments. Such systems enable surgeons to select optimal treatment tactics and dosages of operative interventions tailored to individual patients. Currently, there is no consensus on the use of expectant management for hemangiomas, as the most effective therapeutic strategy often depends on the tumor's type and location, with early treatment being critical in some cases. Accurate diagnosis and effective treatment necessitate precise determination of the tumor's type, growth characteristics, structure, and location. The use of a surgical method for hemangiomas removal is better for the removal of small formations in places that are not critical from a cosmetic prospective (for example, for males this might be the back and legs). This paper presents a method for creating a three-dimensional (3D) model of hemangioma using polynomial approximation and spline modeling to assist surgeons. The development of the mathematical model, the software implementation, and a comprehensive error analysis are explained in this work. The resulting model demonstrated an average approximation error of 5.6%, and a discriminant analysis confirmed the significance of five key parameters for successful resection. The proposed system offers a robust and economically viable tool for improving the accuracy and outcomes of hemangioma surgery.
科学技术的进步提升了外科手术的水平，如今计算机系统承担了成功干预所需的大部分计算工作。通过开发和实施用于外科治疗术前规划的新型计算机模型，可以利用这一技术进步来促进手术改进。这样的系统使外科医生能够为个体患者选择最佳的治疗策略和手术干预剂量。目前，对于血管瘤的期待性管理的使用尚无共识，因为最有效的治疗策略通常取决于肿瘤的类型和位置，在某些情况下早期治疗至关重要。准确的诊断和有效的治疗需要精确确定肿瘤的类型、生长特征、结构和位置。从美容角度来看，对于非关键部位的小病灶，采用手术方法切除血管瘤更好（例如，对于男性来说，可能是背部和腿部）。本文提出了一种使用多项式逼近和样条建模来创建血管瘤三维（3D）模型的方法，以协助外科医生。这项工作解释了数学模型的开发、软件实现以及全面的误差分析。所得模型的平均逼近误差为5.6%，判别分析证实了五个关键参数对于成功切除的重要性。所提出的系统为提高血管瘤手术的准确性和效果提供了一个强大且经济可行的工具。
