乳腺病变大小和组织学结果对计算机辅助检测系统肿瘤检出率的影响。

Influence of breast lesion size and histologic findings on tumor detection rate of a computer-aided detection system.

作者信息

Malich Ansgar, Sauner Dieter, Marx Christiane, Facius Mirjam, Boehm Thomas, Pfleiderer Stefan O, Fleck Marlies, Kaiser Werner A

机构信息

Institute of Diagnostic and Interventional Radiology, Friedrich-Schiller-University Jena, Bachstr 18, 07740 Jena, Germany.

出版信息

Radiology. 2003 Sep;228(3):851-6. doi: 10.1148/radiol.2283011906. Epub 2003 Jul 17.

DOI:10.1148/radiol.2283011906

PMID:12869683

Abstract

PURPOSE

To evaluate associations between histopathologic findings, tumor size, and detection rate of malignant mammographic findings by using a computer-aided detection (CAD) system.

MATERIALS AND METHODS

The study included 208 mammographically detected histologically proven malignant breast lesions in 208 women. Findings were 150 masses and 114 microcalcifications; 56 lesions showed both findings; 94 lesions, mass only; and 58 lesions, microcalcification only. CAD was used to evaluate mammograms in two views retrospectively. Also, corresponding histopathologic findings and lesion size were evaluated. CAD marks were considered positive if, on at least one view, they correctly identified the corresponding mammographic lesion location.

RESULTS

Ninety percent (135 of 150) of masses and 93.0% (106 of 114) of microcalcifications were marked correctly by the CAD system. Overall tumor detection rate was 93.8% (195 of 208). Size-related detection rate for masses was 83.3% (25 of 30) for lesions up to 10 mm, 100% (45 of 45) for lesions 11-20 mm, 100% (46 of 46) for lesions 21-30 mm, 83.3% (10 of 12) for lesions 31-40 mm, and 52.9% (nine of 17) for lesions larger than 40 mm. Size-related tumor detection rate for microcalcifications was 92.5% (37 of 40) for microcalcifications up to 10 mm, 93.1% (27 of 29) for lesions 11-20 mm, 100% (20 of 20) for lesions 21-30 mm, 87.5% (seven of eight) for lesions 31-40 mm, and 88.2% (15 of 17) for larger microcalcifications. Detection rates for mammographically visible masses (invasive ductal carcinoma, invasive lobular carcinoma, invasive tubular carcinoma, noninvasive cancers, mucinoid cancers, and others) were 92.3% (84 of 91), 89.3% (25 of 28), 75.0% (six of eight), 100% (15 of 15), 33.3% (one of three), and 80.0% (four of five), respectively. Detectability rates for mammographically visible areas suspicious for microcalcifications (invasive ductal carcinoma, invasive lobular carcinoma, invasive tubular carcinoma, and noninvasive cancers) were 92.3% (60 of 65), 100% (eight of eight), 100% (five of five), and 91.9% (31 of 34), respectively. Highest overall detection rates were observed for invasive ductal carcinomas (96.6% [112 of 116]) and noninvasive cancers (92.9% [39 of 42]).

CONCLUSION

Highest detection rates were observed for 10-30-mm tumor masses and for invasive ductal carcinomas and noninvasive cancers.

摘要

目的

通过使用计算机辅助检测（CAD）系统，评估组织病理学结果、肿瘤大小与乳腺钼靶恶性征象检测率之间的相关性。

材料与方法

本研究纳入了208例经组织学证实的乳腺恶性病变女性患者，她们均经乳腺钼靶检查发现病变。其中有150个肿块和114处微钙化；56个病变同时具有这两种表现；94个病变仅有肿块表现；58个病变仅有微钙化表现。采用CAD对两个投照体位的乳腺钼靶片进行回顾性评估。同时，评估相应的组织病理学结果和病变大小。如果在至少一个投照体位上，CAD标记能正确识别出相应的乳腺钼靶病变位置，则认为该标记为阳性。

结果

CAD系统正确标记了90%（150个中的135个）的肿块和93.0%（114个中的106个）的微钙化。总体肿瘤检测率为93.8%（208个中的195个）。肿块的大小相关检测率为：直径达10 mm的病变为83.3%（30个中的25个），11 - 20 mm的病变为100%（45个中的45个），21 - 30 mm的病变为100%（46个中的46个），31 - 40 mm的病变为83.3%（12个中的10个），大于40 mm的病变为52.9%（17个中的9个）。微钙化的大小相关肿瘤检测率为：直径达10 mm的微钙化为92.5%（40个中的37个），11 - 20 mm的病变为93.1%（29个中的27个），21 - 30 mm的病变为100%（20个中的20个），31 - 40 mm的病变为87.5%（8个中的7个），更大的微钙化为88.2%（17个中的15个）。乳腺钼靶可见肿块（浸润性导管癌、浸润性小叶癌、浸润性管状癌、非浸润性癌、黏液样癌等）的检测率分别为92.3%（91个中的84个）、89.3%（28个中的25个）、75.0%（8个中的6个）、100%（15个中的15个）、33.3%（3个中的1个）和80.0%（5个中的4个）。乳腺钼靶可见可疑微钙化区域（浸润性导管癌、浸润性小叶癌、浸润性管状癌和非浸润性癌）的可检测率分别为92.3%（65个中的60个）、100%（8个中的8个）、100%（5个中的5个）和91.9%（34个中的31个）。浸润性导管癌（96.6% [116个中的112个]）和非浸润性癌（92.9% [42个中的39个]）的总体检测率最高。