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通过红外可视化技术区分孤立肾样本中的恶性和健康区域。

Differentiating Malignant and Healthy Areas in Isolated Kidney Samples Through Infrared Visualization Techniques.

作者信息

Partsvania Besarion, Sulaberidze Tamaz, Khuskivadze Alexandre, Abazadze Sophio, Gogoladze Teimuraz, Khuskivadze Nutsa

机构信息

Department of Bio-Cybernetics, Institute of Cybernetics, Georgian Technical University, Tbilisi, Georgia.

Department of Urology, Georgia-Israel Joint Clinic "Gidmrdi", Tbilisi, Georgia.

出版信息

World J Oncol. 2025 Jun;16(3):311-316. doi: 10.14740/wjon2593. Epub 2025 Jun 14.

Abstract

BACKGROUND

Because partial nephrectomy (PN) may remove malignant tissue while maintaining kidney function, it is currently the gold standard for nephrectomy. However, the blood arteries that supply the kidney are clamped at the start of the procedure. The most common method for evaluating surgical margins during PN is intraoperative frozen section (FS) evaluation. Its long duration and high false-negative rate question its reliability and efficacy. This encouraged us to search for a much quicker and easier method.

METHODS

The infrared (IR) imaging approach uses the differences in optical density between tumor and healthy tissue to create the sharp contrast in the IR images. The cancerous kidneys were examined after a radical nephrectomy. Following the removal of the cancerous tissue and some of the surrounding healthy tissue, the samples were examined using the IR method. For the IR analysis, we created specific software. Following that, tissue samples taken from both healthy and malignant areas were subjected to a histomorphological analysis.

RESULTS

Experiments showed that malignant tissue appeared as areas of high blackness in the IR picture, while healthy tissue appeared as areas of high illumination. Our software highlighted the areas of the IR image that were associated with the healthy and malignant portions, computed their average brightness, and calculated the ratio of the average illumination (RAI) of the malignant area to that of the healthy area. RAI is an interval of numbers obtained as a result of dividing the average brightness of all dark areas in all examined samples by all light areas of all examined samples. The 95% probability interval for RAIs taking place, which ranged from 0.25 to 0.41, was calculated. The location of the malignancy was then identified by a histomorphological examination. The compliance between histomorphological results and the outcomes of IR examination was confirmed in all cases.

CONCLUSIONS

The IR imaging technique offers significant promise for improving the accuracy and efficiency of margin assessment during kidney cancer surgeries. The IR imaging technique can provide immediate feedback on the tumor boundaries, which could potentially reduce the duration of warm ischemia during surgery. Subsequent investigations should be focused on verifying the technology in further clinical trials and investigating its integration into the surgical process, which could result in its acceptance as a standard instrument for intraoperative decision-making in kidney cancer operations.

摘要

背景

由于部分肾切除术(PN)可在保留肾功能的同时切除恶性组织,目前它是肾切除术的金标准。然而,在手术开始时需夹住供应肾脏的血管。PN术中评估手术切缘最常用的方法是术中冰冻切片(FS)评估。其耗时较长且假阴性率高,这对其可靠性和有效性提出了质疑。这促使我们寻找一种更快、更简便的方法。

方法

红外(IR)成像方法利用肿瘤组织与健康组织之间的光密度差异,在红外图像中形成鲜明对比。对根治性肾切除术后的癌肾进行检查。在切除癌组织及部分周围健康组织后,使用IR方法对样本进行检查。为进行IR分析,我们开发了特定软件。随后,对取自健康和恶性区域的组织样本进行组织形态学分析。

结果

实验表明,恶性组织在红外图像中呈现为高黑色区域,而健康组织呈现为高亮度区域。我们的软件突出显示了红外图像中与健康和恶性部分相关的区域,计算其平均亮度,并计算恶性区域与健康区域的平均照度比(RAI)。RAI是通过将所有检查样本中所有暗区的平均亮度除以所有检查样本中所有亮区的平均亮度而得到的数值区间。计算出RAI出现的95%概率区间为0.25至0.41。然后通过组织形态学检查确定恶性肿瘤的位置。在所有病例中均证实了组织形态学结果与IR检查结果的一致性。

结论

红外成像技术在提高肾癌手术中切缘评估的准确性和效率方面具有巨大潜力。红外成像技术可即时反馈肿瘤边界,这有可能缩短手术中的热缺血时间。后续研究应聚焦于在进一步的临床试验中验证该技术,并研究将其整合到手术过程中,这可能会使其被接受为肾癌手术中术中决策的标准工具。

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