Veluponnar Dinusha, Dashtbozorg Behdad, Jong Lynn-Jade S, Geldof Freija, Da Silva Guimaraes Marcos, Vrancken Peeters Marie-Jeanne T F D, van Duijnhoven Frederieke, Sterenborg Henricus J C M, Ruers Theo J M, de Boer Lisanne L
Department of Surgery, Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands.
Department of Nanobiophysics, Faculty of Science and Technology, University of Twente, Drienerlolaan 5, 7522 NB Enschede, The Netherlands.
Biomed Opt Express. 2023 Jul 10;14(8):4017-4036. doi: 10.1364/BOE.493179. eCollection 2023 Aug 1.
During breast-conserving surgeries, it remains challenging to accomplish adequate surgical margins. We investigated different numbers of fibers for fiber-optic diffuse reflectance spectroscopy to differentiate tumorous breast tissue from healthy tissue up to 2 mm from the margin. Using a machine-learning classification model, the optimal performance was obtained using at least three emitting fibers (Matthew's correlation coefficient (MCC) of 0.73), which was significantly higher compared to the performance of using a single-emitting fiber (MCC of 0.48). The percentage of correctly classified tumor locations varied from 75% to 100% depending on the tumor percentage, the tumor-margin distance and the number of fibers.
在保乳手术中,实现足够的手术切缘仍然具有挑战性。我们研究了用于光纤漫反射光谱的不同数量的光纤,以区分距切缘2毫米以内的肿瘤性乳腺组织和健康组织。使用机器学习分类模型,使用至少三根发射光纤可获得最佳性能(马修斯相关系数(MCC)为0.73),与使用单根发射光纤的性能(MCC为0.48)相比,该性能显著更高。根据肿瘤百分比、肿瘤与切缘的距离和光纤数量,正确分类的肿瘤位置百分比在75%至100%之间变化。