Tsai Hung-Wen, Tsai Hsun-Heng, Kuo Fang-Ying, Chang Kung-Chao
Department of Pathology, National Cheng Kung University, Tainan, Taiwan.
Histopathology. 2009 Feb;54(3):328-36. doi: 10.1111/j.1365-2559.2009.03232.x.
To differentiate hepatoblastoma (HB) from hepatocellular carcinoma (HCC) by computerized image analysis. This is critical for treatment modalities and prognostic stratification but is usually difficult in small biopsy specimens.
Computerized image-processing technology was used to calculate the nuclear-cytoplasmic ratio (N/C), cellularity (CEL) and other cellular and nuclear parameters in HB (n = 18) and paediatric HCC (pHCC, n = 11). The proliferation index (PI) and apoptotic index (AI) were also measured. Fetal type HB (FHB) compared with pHCC had more uniform nuclei (P < or = 0.014), lower PI (P = 0.028) and AI (P = 0.009), whereas the embryonal type HB (EHB) had a higher N/C (P < 0.001), higher CEL (P = 0.043), smaller cells (P = 0.043) and higher PI (P = 0.020) than pHCC. Moreover, EHB had a higher N/C (P < 0.001), higher CEL (P = 0.021), smaller cells (P = 0.021), more nuclear pleomorphism (P < or = 0.036) and higher PI (P < 0.001) than FHB. Multivariate analysis showed that FHB, EHB and pHCC could be classified accurately by a regression model. This logistic model further correctly stratified four additional test cases from biopsy specimens.
These results indicate that computerized morphometric analysis can yield useful criteria to distinguish HB from pHCC in small biopsy specimens, and, compared with FHB, the poorer prognosis of EHB may result from its more undifferentiated (immature) and proliferative phenotype.
通过计算机图像分析鉴别肝母细胞瘤(HB)与肝细胞癌(HCC)。这对于治疗方式及预后分层至关重要,但在小活检标本中通常很难做到。
运用计算机图像处理技术计算18例HB及11例儿童HCC(pHCC)的核质比(N/C)、细胞密度(CEL)及其他细胞和细胞核参数。同时测量增殖指数(PI)和凋亡指数(AI)。胎儿型HB(FHB)与pHCC相比,细胞核更均匀(P≤0.014),PI(P = 0.028)和AI(P = 0.009)更低;而胚胎型HB(EHB)与pHCC相比,N/C更高(P < 0.001),CEL更高(P = 0.043),细胞更小(P = 0.043),PI更高(P = 0.020)。此外,EHB与FHB相比,N/C更高(P < 0.001),CEL更高(P = 0.021),细胞更小(P = 0.021),核异型性更大(P≤0.036),PI更高(P < 0.001)。多因素分析显示,FHB、EHB和pHCC可通过回归模型准确分类。该逻辑模型进一步正确地对另外4例活检标本的测试病例进行了分层。
这些结果表明,计算机形态计量分析能够得出有用的标准,以在小活检标本中区分HB与pHCC,并且与FHB相比,EHB预后较差可能是因其更未分化(不成熟)和增殖的表型所致。