[PitNET (垂体神经内分泌瘤) /腺瘤中Ki-67的量化]
Judith Klein1, Kai Saeger1,2, Wolfgang Saeger3
1Institut für Neuropathologie der Universität Hamburg, UKE, Martinistraße 52, 20246, Hamburg, Deutschland.
Pathologie (Heidelberg, Germany)
|July 11, 2024
概括
数字图像分析准确地确定了垂体神经内分泌瘤 (PitNET) 中的Ki-67指数,减少了观察者变异性. 这种计算机化方法为评估PitNET/垂体腺瘤的增殖率提供了可靠的替代方案.
科学领域:
- 内分泌学 在内分泌学.
- 病理学 病理学 病理学
- 医疗成像医学成像
背景情况:
- 下垂体神经内分泌瘤 (PitNET) /下垂体腺瘤通常表现出低的增殖指数,使得准确的评估具有挑战性.
- 在手动Ki-67指数确定中存在很高的观察者变化,特别是在低百分比的情况下.
- 四眼原则提高了可靠性,但不是持续可行的.
研究的目的:
- 为了比较基于病理学家的Ki-67指数确定与PitNET/垂体腺瘤的计算机数字图像分析方法.
- 在评估PitNET扩散时评估数字图像分析的可靠性和准确性.
主要方法:
- 由两位经验丰富的病理学家进行的Ki-67指数测量与计算机系统 (Cognition MasterSuite,VMScope) 的结果进行比较.
- 利用数字图像分析进行PitNET样本中扩散率的定量评估.
主要成果:
- 经验丰富的病理学家提供的Ki-67估计和数字图像分析系统之间观察到明显的一致性.
- 计算机化方法在确定PitNET/垂体腺瘤的增殖率方面表现出色.
结论:
- 数字图像分析是确定PitNET/垂体腺瘤中的Ki-67指数的可靠和准确工具.
- 这项技术可以作为一个有价值的"第三眼"和"第四眼",提高诊断一致性和减少观察者变化.
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