The many faces of pseudomyxoma peritonei: a radiological review based on 30 cases
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Abstract Objective: To determine the most common imaging features of pseudomyxoma peritonei (PMP), as well as the histologic subtypes of the primary tumors. Materials and Methods: We reviewed 30 cases of women with pathologically confirmed PMP. Only computed tomography scans were available. All cases were retrospectively studied by four radiologists, working independently. We identified the most common imaging findings, the predominant primary site of the disease, and the growth pattern. The most common sites of recurrence were also analyzed. Results: The most common computed tomography finding was peritoneal/omental nodules (including “omental caking”), followed by visceral scalloping and non-mucinous ascites. The most common site of the primary tumor was the appendix (in 63.3%), followed by the ovaries (in 16.6%), and 16.6% of the tumors were of undetermined origin. There was one case of synchronous appendiceal and ovarian tumors. Low-grade mucinous neoplasm was the most common histologic subtype, accounting for 84.2% of the appendiceal tumors and 40% of the ovarian tumors. Conclusion: Although PMP is a relatively rare entity, radiologists must be aware of its possible imaging findings, common locations, and possible patterns of recurrence. The origin of the primary tumor should also be investigated. Future studies are needed in order to determine which preoperative imaging findings predict surgical outcomes and to characterize the main findings of radiological recurrence.
研究目的:明确腹膜假黏液瘤(pseudomyxoma peritonei, PMP)最常见的影像学特征,以及原发肿瘤的组织学亚型。
材料与方法:回顾性分析30例经病理证实的女性腹膜假黏液瘤患者,所有病例仅可获得计算机断层扫描(computed tomography, CT)影像资料。由4名放射科医师独立阅片,对病例进行回顾性分析,总结最常见的影像学表现、疾病主要原发部位及生长模式,并分析最常见的复发部位。
结果:最常见的计算机断层扫描表现为腹膜/大网膜结节(包括"大网膜饼征"),其次为脏器压迹及非黏液性腹水。原发肿瘤最常见的部位为阑尾(占63.3%),其次为卵巢(占16.6%),另有16.6%的肿瘤来源不明。1例患者同时存在阑尾及卵巢肿瘤。低级别黏液性肿瘤是最常见的组织学亚型,在阑尾肿瘤中占比84.2%,在卵巢肿瘤中占比40%。
结论:尽管腹膜假黏液瘤相对少见,但放射科医师需熟悉其可能的影像学表现、好发部位及复发模式。同时需明确原发肿瘤的来源。未来仍需开展相关研究,以明确哪些术前影像学表现可预测手术结局,并表征放射学复发的主要特征。
提供机构:
SciELO journals
创建时间:
2019-11-27



