Department of Laboratory Medicine, NTT Medical Center Tokyo, Tokyo, Japan.
Department of Diagnostic Pathology, NTT Medical Center Tokyo, Tokyo, Japan.
Diagn Cytopathol. 2023 Apr;51(4):230-238. doi: 10.1002/dc.25097. Epub 2023 Jan 3.
Cytological diagnosis using endoscopic ultrasound-guided fine-needle aspiration (EUS-FNA) for gastric submucosal spindle cell tumors, such as gastrointestinal stromal tumors (GISTs), leiomyomas, and schwannomas, is challenging because of their similar morphological characteristics.
To clarify the cytological differential points, we reviewed the EUS-FNA cytology specimens of GISTs (37 cases), leiomyomas (11 cases), and schwannomas (4 cases).
Twelve cytomorphological features were evaluated: lymphocytes, crushed nuclei, naked spindle nuclei, mast cell, length of the streaming arrangement, cellularity, nuclei at the cluster margin (nuclei located at the periphery of the cell cluster), peripheral feathering (loosely aggregated cells at the margin of a cell cluster tended to taper like feathers), metachromasia, wavy nuclei, fishhook-type nuclei, and anisonucleosis.
Among these features, lymphocytes, naked spindle nuclei, length of the streaming arrangement, cellularity, nuclei at the cluster margins, peripheral feathering, and anisonucleosis were statistically significant for differentiation. Based on these findings, we developed an algorithm for cytodiagnosis. The algorithm was taught to four cytologists, and the interobserver agreement and correct diagnosis rates were compared before and after education, which showed a significant improvement.
The histological types of gastric submucosal spindle cell tumors can be estimated using this algorithm for EUS-FNA cytology. Furthermore, this algorithm can be applied for cytological diagnosis at bedside during rapid on-site evaluation.
使用内镜超声引导下细针抽吸（EUS-FNA）对胃黏膜下梭形细胞肿瘤（如胃肠道间质瘤[GIST]、平滑肌瘤和神经鞘瘤）进行细胞学诊断具有挑战性，因为它们具有相似的形态学特征。
为了明确细胞学鉴别点，我们回顾了 GIST（37 例）、平滑肌瘤（11 例）和神经鞘瘤（4 例）的 EUS-FNA 细胞学标本。
评估了 12 种细胞形态学特征：淋巴细胞、压碎核、裸核、肥大细胞、流态排列长度、细胞密度、核位于细胞簇边缘（核位于细胞簇的外周）、周边羽毛状（细胞簇边缘松散聚集的细胞呈羽毛状逐渐变细）、异染性、波浪核、鱼钩状核和核大小不等。
在这些特征中，淋巴细胞、裸核、流态排列长度、细胞密度、核位于细胞簇边缘、周边羽毛状和核大小不等在鉴别诊断中具有统计学意义。基于这些发现，我们开发了一种用于细胞学诊断的算法。该算法被教授给四位细胞学专家，比较了教育前后的观察者间一致性和正确诊断率，结果显示显著提高。
该算法可用于估计胃黏膜下梭形细胞肿瘤的组织学类型。此外，该算法可用于快速现场评估时的床边细胞学诊断。
