Magnetic resonance imaging findings for discriminating clear cell carcinoma and endometrioid carcinoma of the ovary
Magnetic resonance imaging findings for discriminating clear cell carcinoma and endometrioid carcinoma of the ovary
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DOI：
10.1186/s13048-019-0497-1
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发表时间：
2019-02-25
影响因子：
4
通讯作者：
Kobayashi, Hiroshi
中科院分区：
文献类型：
--
作者：
Morioka, Sachiko;Kawaguchi, Ryuji;Kobayashi, Hiroshi
背景与子宫内膜异位症相关的常见癌组织学类型是透明细胞癌（CCC）和子宫内膜样癌（EC）。 CCC 被认为是一种侵袭性、耐药性的组织学亚型。与超声检查或计算机断层扫描相比，磁共振成像 (MRI) 在诊断卵巢肿瘤方面具有一些潜在优势。本研究旨在确定可用于区分 CCC 和 EC 的 MRI 特征。方法我们检索了 2008 年 1 月至 2018 年 9 月期间在奈良医科大学医院接受手术治疗的卵巢癌患者的病历；我们确定了 98 名接受过术前 MRI 的 CCC 或 EC 患者。对比 MRI 扫描是在手术前不到 2 个月进行的。如果患者在研究开始时没有病理学、上皮性卵巢癌的其他病理亚型和/或复发和转移性卵巢癌的挽救治疗，则被排除在研究之外。选择经单因素分析具有统计学意义的临床相关变量进行后续的多因素回归分析，以确定区分CCC和EC的独立因素。结果CCC和EC的MRI显示大的囊性异质混合肿块，附壁结节突出到囊性空间中。单变量逻辑回归分析显示，生长模式（广泛的结节结构[多焦点/同心征]或息肉状结构[焦点/偏心征]）、表面不规则性（光滑/规则表面或粗糙/不规则/分叶状表面）、附壁结节宽度、高宽比（HWR）和术前腹水的存在是CCC和EC之间显着差异的因素。在多变量逻辑回归分析中，壁结节的生长模式（比值比 [OR]=0.69，95% 置信区间 [CI]：0.013-0.273，p=0.0004）和 HWR（OR=3.71，95% CI：1.128-13.438，p=0.036）是区分 CCC 和 CCC 的独立预测因子。 EC. 结论 总之， MRI 数据显示，附壁结节的生长模式和 HWR 是区分 CCC 和 EC 的独立因素。这一发现可能有助于术前预测患者预后。
BackgroundCommon cancerous histological types associated with endometriosis are clear cell carcinoma (CCC) and endometrioid carcinoma (EC). CCC is regarded as an aggressive, chemoresistant histological subtype. Magnetic resonance imaging (MRI) offers some potential advantages to diagnose ovarian tumors compared with ultrasonography or computed tomography. This study aimed to identify MRI features that can be used to differentiate between CCC and EC.MethodsWe searched medical records of patients with ovarian cancers who underwent surgical treatment at Nara Medical University Hospital between January 2008 and September 2018; we identified 98 patients with CCC or EC who had undergone preoperative MRI. Contrasted MRI scans were performed less than 2months before surgery. Patients were excluded from the study if they had no pathology, other pathological subtype of epithelial ovarian cancer, and/or salvage treatment for recurrence and metastatic ovarian cancer at the time of study initiation. Clinically relevant variables that were statistically significant by univariate analysis were selected for subsequent multivariate regression analysis to identify independent factors to distinguish CCC from EC.ResultsMRI of CCC and EC showed a large cystic heterogeneous mixed mass with mural nodules protruding into the cystic space. Univariate logistic regression analysis revealed that the growth pattern (broad-based nodular structures [multifocal/concentric sign] or polypoid structures [focal/eccentric sign]), surface irregularity (a smooth/regular surface or a rough/irregular/lobulated surface), Width of mural nodule, Height-to-Width ratio (HWR), and presence of preoperative ascites were factors that significantly differed between CCC and EC. In the multivariate logistic regression analysis, the growth pattern of the mural nodule (odds ratio [OR]=0.69, 95% confidence interval [CI]: 0.013-0.273, p=0.0004) and the HWR (OR=3.71, 95% CI: 1.128-13.438, p=0.036) were independent predictors to distinguish CCC from EC.ConclusionsIn conclusion, MRI data showed that the growth pattern of mural nodules and the HWR were independent factors that could allow differentiation between CCC and EC. This finding may be helpful to predict patient prognosis before operation.