Idiopathic granulomatous mastitis

A case of idiopathic granulomatous mastitis mimicking breast carcinoma clinically and radiographically is reported with mammography, sonography and MR images. Received 18 July 1996; Revision received 2 December 1996; Accepted: 2 January 1996     

Development of a phantom to test fully automated breast density software – A work in progress

ObjectivesMammographic density (MD) is an independent risk factor for breast cancer and may have a future role for stratified screening. Automated software can estimate MD but the relationship between breast thickness reduction and MD is not fully understood. Our aim is to develop a deformable breast phantom to assess automated density software and the impact of breast thickness reduction on MD.MethodsSeveral different configurations of poly vinyl alcohol (PVAL) phantoms were created. Three methods were used to estimate their density. Raw image data of mammographic images were processed using Volpara to estimate volumetric breast density (VBD%); Hounsfield units (HU) were measured on CT images; and physical density (g/cm³) was calculated using a formula involving mass and volume. Phantom volume versus contact area and phantom volume versus phantom thickness was compared to values of real breasts.ResultsVolpara recognized all deformable phantoms as female breasts. However, reducing the phantom thickness caused a change in phantom density and the phantoms were not able to tolerate same level of compression and thickness reduction experienced by female breasts during mammography.ConclusionOur results are promising as all phantoms resulted in valid data for automated breast density measurement. Further work should be conducted on PVAL and other materials to produce deformable phantoms that mimic female breast structure and density with the ability of being compressed to the same level as female breasts.Advances in knowledgeWe are the first group to have produced deformable phantoms that are recognized as breasts by Volpara software.     

The performance of computer-aided detection when analyzing prior mammograms of newly detected breast cancers with special focus on the time interval from initial imaging to detection

Purpose

The clinical role of CAD systems to detect breast cancer, which have not been on cancer containing mammograms not detected by the radiologist was proven retrospectively.

Methods

All patients from 1992 to 2005 with a histologically verified malignant breast lesion and a mammogram at our department, were analyzed in retrospect focussing on the time of detection of the malignant lesion. All prior mammograms were analyzed by CAD (CADx, USA). The resulting CAD printout was matched with the cancer containing images yielding to the radiological diagnosis of breast cancer. CAD performance, sensitivity as well as the association of CAD and radiological features were analyzed.

Results

278 mammograms fulfilled the inclusion criteria. 111 cases showed a retrospectively visible lesion (71 masses, 23 single microcalcification clusters, 16 masses with microcalcifications, in one case two microcalcification clusters). 54/87 masses and 34/41 microcalcifications were detected by CAD.Detection rates varied from 9/20 (ACR 1) to 5/7 (ACR 4) (45% vs. 71%). The detection of microcalcifications was not influenced by breast tissue density.

Conclusion

CAD might be useful in an earlier detection of subtle breast cancer cases, which might remain otherwise undetected.     

Staying abreast of imaging – Current status of breast cancer detection in high density breast

ObjectivesThe aim of this paper is to illustrate the current status of imaging in high breast density as we enter a new decade of advancing medicine and technology to diagnose breast lesions.Key findingsEarly detection of breast cancer has become the chief focus of research from governments to individuals. However, with varying breast densities across the globe, the explosion of breast density information related to imaging, phenotypes, diet, computer aided diagnosis and artificial intelligence has witnessed a dramatic shift in new screening recommendations in mammography, physical examination, screening younger women and women with comorbid conditions, screening women at high risk, and new screening technologies. Breast density is well known to be a risk factor in patients with suspected/known breast neoplasia. Extensive research in the field of qualitative and quantitative analysis on different tissue characteristics of the breast has rapidly become the chief focus of breast imaging. A summary of the available guidelines and modalities of breast imaging, as well as new emerging techniques under study that can potentially provide an augmentation or even a replacement of those currently available.ConclusionDespite all the advances in technology and all the research directed towards breast cancer, detection of breast cancer in dense breasts remains a dilemma.Implications for practiceIt is of utmost importance to develop highly sensitive screening modalities for early detection of breast cancer.     

乳腺计算机X射线摄影自动曝光模式的校正

目的 通过参照乳腺屏-片系统摄影自动曝光控制模式,对乳腺CR摄影自动曝光进行校正,从而实现影像质量与辐射剂量的最优化。方法 应用屏-片组合,28 kV条件下,对40 mm厚的有机玻璃进行自动曝光,以此所得曝光量(mAs)为基准,分10档分别采用±10 mAs的曝光量用CR进行曝光,选取LgM=2.0的曝光量作为基准,对CR的自动曝光模式进行校正。采用经校正后的CR自动曝光模式,分别采用26、28和30 kV对Fluke NA 18-220 乳腺模体进行摄影,模体采用自动曝光控制(AEC)模式进行摄影,记录曝光量数值(mAs),对CR影像进行处理。同时CR采用相同的kV和照射野及不同的曝光量对模体进行摄影,CR影像经后处理后请4位放射医师进行双盲阅片,按照美国放射学会(ACR)的评分标准评价打分。结果 采用稍高于传统屏-片组合的曝光量作为CR自动曝光校正基准值,可实现乳腺CR摄影自动曝光模式的校正,经校正后模体测试影像的评分均高于ACR的评分标准。结论 乳腺CR摄影自动曝光模式可根据CR特点进行校正,经校正后的乳腺CR摄影的自动曝光控制模式应用于临床既可明显降低病人辐射剂量,又可得到满足临床诊断需求的优质乳腺影像。     

全数字化乳腺X线摄影与传统乳腺X线摄影对比分析

目的:探讨全数字化乳腺X线摄影(FFDM)与传统乳腺X线摄影(SFM)的临床应用效果.方法:回顾分析使用传统乳腺X线机及使用全数字化乳腺机摄影各800例的影像及临床资料,分别统计两组病例的平均曝光次数、平均检查时间,同时对乳房各部分细微结构显示率进行评价,并将两组病例中经手术病理证实为乳腺癌病例的病理结果与术前X线诊断作对照.结果:SFM组平均曝光次数5.12次/人,平均检查时间20分钟/人;FFDM组平均曝光次数4.22次/人,平均检查时间6.3分钟/人.同时清晰显示乳房各部分微细结构显示率为SFM组284例(35.5%);FFDM组791例(98.9%).SFM与FFDM诊断乳腺癌的敏感度、特异度、准确度分别为80.2%时87.5%;79.8%对85.2%;81.3%对88.5%.结论:与传统乳腺X线摄影对比,全数字化乳腺X线摄影操作简单,成像快捷,图像质量好,在乳腺癌(尤其是早期乳癌)诊断方面优于传统乳腺X线摄影.     

早期乳腺导管原位癌X线表现与预后生物学标记关系的研究

目的评价乳腺导管原位癌（DCIS）及DCIS伴微浸润的X线片表现，分析X线表现与预后生物学标记的相关性。方法对50例乳腺DCIS及45例DCIS伴微浸润的患者行X线检查，共62例行预后生物学标记，分析影像表现与孕激素受体（PR）、癌基因（C—erbB-2）、抑癌基因（p53）的相关性。用卡方检验进行统计学处理，并对有意义者行优势比（OR值）分析。结果（1）单独1个X线征象表现者62例；合并2个征象26例；阴性7例。（2）各种X线征象单独分析显示，62例有钙化的病灶中恶性钙化占73％（45例），其余为中间性钙化；钙化以簇状分布最为常见（36例），其次为段样分布（18例）。22例有肿块的病灶中，以卵圆形肿块最为常见（13例）；肿块的边缘表现为浸润、小分叶、清晰和模糊各为15、1、4和2例；等密度肿块占的比例较高（55％，12例）。结构扭曲7例，除1例外多与其他征象伴行；局灶性不对称占16％（15／95），可单独发生或与其他征象伴发。（3）将病灶的X线表现分成恶性钙化、中间性钙化和非钙化3组，PR与C-erbB-2在3组中的分布有统计性意义，PR阳性表达者X线上非钙化征象发生率是中间性钙化的11．00倍[χ^2=8．571，P=0．003；95％可信区间（CI）为1．998～60．572]、恶性钙化的8．80倍（χ^2=9．748，P=0．002；95％CI为2．024～38．253）；而C—erbB-2高表达者，恶性钙化是非钙化发生的12．35倍（χ^2=7．353，P=0．007；95％CI为1．447—105．443），中间性钙化的5．74倍（χ^2=4．977，P=0．026；95％CI为1．110～29．645）。结论乳腺DCIS及DCIS伴微浸润X线征象有特征。X线征象可以作为早期乳腺DCIS的一个预后因子。     

群集钙化对鉴别乳腺良恶性病变的意义

目的评价乳腺钼靶片群集钙化对鉴别乳腺良恶性病变的意义。方法分析76例乳腺X线钼靶片群集钙化病例,全部经手术病理证实,其中,乳腺恶性病变52例,良性病变24例。采用下列4项指标分析上述76例群集钙化的特征并进行良恶性对照研究:a)病灶钙化总数;b)每平方厘米钙化数目(N/S);c)钙化灶的大小、形态;d)钙化灶合并肿块。结果76例群集钙化病例中钙化总数大于30个、N/S大于等于10个、钙化灶大小形态不一致、钙化合并肿块,这4项指标诊断恶性钙化的特异性和敏感性分别为83.3%和69.2%,79.2%和76.9%,62.5%和92.3%,62.5%和53.8%。结论N/S大于等于10个、钙化总数大于30个及钙化灶大小、形态不一致这3个特征对恶性钙化最具有诊断价值。     

Screen-Film Mammography and Soft-Copy Full-Field Digital Mammography: Comparison in the Patients with Microcalcifications

Objective

We wanted to compare the ability of screen-film mammography (SFM) and soft-copy full-field digital mammography (s-FFDM) on two different monitors to detect and characterize microcalcifications.

Materials and Methods

The images of 40 patients with microcalcifications (three patients had malignant lesion and 37 patients had benign lesion), who underwent both SFM and FFDM at an interval of less than six months, were independently evaluated by three readers. Three reading sessions were undertaken for SFM and for FFDM on a mammography-dedicated review workstation (RWS, 2K×2.5K), and for FFDM on a high-resolution PACS monitor (1.7K×2.3K). The image quality, breast composition and the number and conspicuity of the microcalcifications were evaluated using a three-point rating method, and the mammographic assessment was classified into 4 categories (normal, benign, low concern and moderate to great concern).

Results

The image quality, the number and conspicuity of the microcalcifications by s-FFDM (on the RWS, PACS and both) were superior to those by SFM in 85.0%, 80.0% and 52.5% of the cases, respectively (p < 0.01), and those by the s-FFDM on the two different monitors were similar in 15.0%, 12.5% and 35.0% of the cases, respectively (p > 0.01). The mammographic assessment category for the microcalcifications in the three reading sessions was similar.

Conclusion

s-FFDM gives a superior image quality to SFM and it is better at evaluating microcalcifications. In addition, s-FFDM with the PACS monitor is comparable to s-FFDM with the RWS for evaluating microcalcifications.