Detection and classification of breast lesions using multiple information on contrast-enhanced mammography by a multiprocess deep-learning system: A multicenter study

Objective: Accurate detection and classification of breast lesions in early stage is crucial to timely formulate effective treatments for patients. We aim to develop a fully automatic system to detect and classify breast lesions using multiple contrast-enhanced mammography(CEM) images.Methods: In this study, a total of 1,903 females who underwent CEM examination from three hospitals were enrolled as the training set, internal testing set, pooled external testing set and prospective testing set. Here we developed a CEM-based multiprocess detection and classification system(MDCS) to perform the task of detection and classification of breast lesions. In this system, we introduced an innovative auxiliary feature fusion(AFF)algorithm that could intelligently incorporates multiple types of information from CEM images. The average freeresponse receiver operating characteristic score(AFROC-Score) was presented to validate system’s detection performance, and the performance of classification was evaluated by area under the receiver operating characteristic curve(AUC). Furthermore, we assessed the diagnostic value of MDCS through visual analysis of disputed cases,comparing its performance and efficiency with that of radiologists and exploring whether it could augment radiologists’ performance.Results: On the pooled external and prospective testing sets, MDCS always maintained a high standalone performance, with AFROC-Scores of 0.953 and 0.963 for detection task, and AUCs for classification were 0.909[95% confidence interval(95% CI): 0.822-0.996] and 0.912(95% CI: 0.840-0.985), respectively. It also achieved higher sensitivity than all senior radiologists and higher specificity than all junior radiologists on pooled external and prospective testing sets. Moreover, MDCS performed superior diagnostic efficiency with an average reading time of 5 seconds, compared to the radiologists’ average reading time of 3.2 min. The average performance of all radiologists was also improved to varying degrees with MDCS assistance.Conclusions: MDCS demonstrated excellent performance in the detection and classification of breast lesions,and greatly enhanced the overall performance of radiologists.

Comparison between Visualization of Microcalcifications by Digital Breast Tomosynthesis and Full-Field Digital Mammography

Objective: To date, few studies have compared the diagnostic performance and visibility of microcalcifications obtained using digital breast tomosynthesis (DBT) with those obtained from full-field digital mammography (FFDM). The visualization and characterization of microcalcifications with DBT remain controversial. The purpose of this study was to compare the visibility of microcalcifications and determine whether DBT exhibits a diagnostic advantage for visualizing microcalcifications over FFDM. Methods: We retrospectively reviewed 120 cases including DBT and FFDM imaging (60 histologically verified as breast cancers and 60 as benign microcalcifications or normal). DBT images with a wide scan-angle of 50° and FFDM images were obtained using a flat-panel system (MAMMOMAT Inspiration, Siemens). Images were independently reviewed by four board-certified radiologists and evaluated for the presence of microcalcifications, probability of malignancy (BI-RADS classification), and visibility. Results: In predicting the malignancy of detected microcalcifications, no significant difference was found between readers’ areas under the receiver operating characteristic curve for DBT and FFDM (p = 0.068). The visibility scores of detected microcalcifications were 3.74 ± 1.06 for DBT and 3.46 ± 0.93 for FFDM, respectively. The visibility of microcalcifications when using DBT was found to be significantly superior to that of FFDM (p < 0.05). Conclusion: Our results suggest that the image quality of DBT with a wide scan-angle is comparable or superior to that obtained with FFDM in terms of both visibility and assessment of microcalcifications.

Combined use of fine needle aspiration cytology and full field digital mammography in preoperative assessment of breast masses

Objective: To evaluate the accuracy of these two methods and focus on the analysis and management of the false-negative cases. Methods: Results of full field digital mammography (FFDM) and fine needle aspiration cytology (FNAC) were obtained and analyzed from a consecutive of 102 women with palpable breast masses, results were correlated with the histopathological findings. Results: Of the 102 cases, malignancy was confirmed in 43 cases (42.16%) by final pathological examination, the sensitivity and specificity of cancer detection with FNA cytology was 90.7% (39/43) and 89.8% (53/59), re- spectively, the whole accuracy was 90.2% (92/102), with a positive predictive value of 86.7% (39/45) and a negative predictive value of 93.0% (53/57). FFDM gave a sensitivity of 88.4% (38/43), specificity of 83.1% (49/59), and whole accuracy 85.3% (87/102), the positive predictive value and negative predictive value was 79.2% (38/48) and 90.7% (49/54), respectively. All the FNAC-negative cancer cases were suggestive of malignancy by FFDM findings, however, the benign cases which present as equivocal finding by FNA cytology, could not be ruled out the presence of malignancy. Conclusion: FNAC and FFDM both are accurate, effective and economical diagnostic modalities, combined use of these two methods can reduced the misdiag- nosis rate of breast masses.

Relationship between Full-Field Digital Mammographic Features and Clinicopathologic Characteristics in 176 Cases with Breast Cancer

OBJECTIVE Different mammographic features are probably predictive of different prognosis. However, ambiguity still exists in understanding the relationship between them. In resent years, digital mammography has been available for clinical use which has led to a revolution in the resolving of images and an increase in early-stage breast cancer detection. Based on the above knowledge, this study was performed to evaluate the relationship between full-field digital mammographic features and clinicopathologic characteristics in breast cancer. METHODS Digital mammograms of 176 patients with pathologically proven breast cancer were reviewed. Also, clinical and pathologic records （histological types and axillary lymph nodes status） were retrospectively examined. RESULTS Most of the patients with a solitary microcalcification were young women under the age of 50（84.4%）, but the majority of the patients with microcalcifications complicated by a mass were elderly women. Microcalcifications detected by mammography occurred frequently in ductal carcinoma in situ （28.1%） and in early invasive carcinoma （15.6%）. Breast cancers with expression of microcalcifications combined with a spiculate mass had a high metastatic rate of axillary lymph nodes （69.4%）. A high metastatic rate of axillary lymph nodes was also found in the patients with solitary worm-like microcalcifications （57.1%）, solitary spiculate mass （53.7%） and solitary non-worm-like microcalcifications （44.4%）. Simple worm-like microcalcifications accompanied with metastasis of 4 to 9 axillary lymph nodes occurred in 42.9% of the（6/14） cases. The patients with microcalcifications combined by a spiculate mass and with metastasis of 4 to 9 axillary lymph nodes accounted for 27.8% （10/36） of the cases, and those with metastases of 10 and over accounted for 16.7% （6/36）. CONCLUSION Solitary microcalcifications occur frequently in young women and are usually associated with early breast cancer. There is a close relationship between worm-like microcalcifications, a spiculate mass and positive metastases of axillary lymph nodes, which are an index of poor prognosis.

Long Term Reproducibility Check of a Full Field Digital Mammography System

In this study different types of customized phantoms were used to examine a long term reproducibility check of a full field digital mammography system. These phantoms can be distinguished into three types： a PMMA （polimethylmethacrylate） object for an easy signal-to-noise ratio measurement in a defined region, a phantom with particular details of various dimensions （TORMAS） and a phantom for a contrast-detail analysis （CDMAM）. In our center the ARTINIS ANALYZER software has been used since 2011 to weekly perform a CDMAM phantom analysis. This soitware is based on the original CDCOM algorithm suggested by the EUREF, the European Reference Organization for assured quality breast screening and diagnostic services. However the CDMAM phantom is a contrast-detail object designed for image quality type tests and not for long term reproducibility control. Since 2013, as suggested by the guidelines of Veneto region, a TORMAS weekly acquisition and analysis of data has also been performed. The purpose of this study is to discuss the data obtained by using the two different detail phantoms, CDMAM and TORMAS. These results can provide some correlations among the analyzed parameters comparing them with the ones emerging from the PMMA phantom analysis. The study reveals that the basic PMMA phantom is the object that provides the necessary information about the stability of the exposure parameters and the reproducibility of a mammographic equipment in terms of image quality indexes.

Efficacy of digital breast tomosynthesis combined with magnetic resonance imaging in the diagnosis of early breast cancer

BACKGROUND The incidence and mortality rate of breast cancer in China rank 120th and 163rd,worldwide,respectively.The incidence of breast cancer is on the rise;the risk increases with age but is slightly reduced after menopause.Early screening,diagnosis,and timely determination of the best treatment plan can ensure clinical efficacy and prognosis.AIM To evaluate the clinical value of magnetic resonance imaging(MRI) combined with digital breast tomosynthesis(DBT) in diagnosing early breast cancer and the effect of breast-conserving surgery by arc incision.METHODS This study was divided into two parts.Firstly,110 patients with early breast cancer confirmed by pathological examination and 110 with benign breast diseases diagnosed simultaneously in Changzhi People’s Hospital of Shanxi Province and Shanxi Dayi Hospital from May 2019 to September 2020 were included in the breast cancer group and the benign group,respectively.Both groups underwent DBT and MRI examination,and the pathological results were used as the gold standard to evaluate the effectiveness of the combined application of DBT and MRI in the diagnosis of early breast cancer.Secondly,according to the operation method,110 patients with breast cancer were divided into either a breast-conserving group(69 patients) or a modified radical mastectomy group(41 patients).The surgical effect,cosmetic effect,and quality of life of the two groups were compared.RESULTS Among the 110 cases of breast cancer,66 were of invasive ductal carcinoma(60.00%),and 22 were of ductal carcinoma in situ(20.00%).Among the 110 cases of benign breast tumors,55 were of breast fibromas(50.00%),and 27 were of breast adenosis(24.55%).The sensitivity,specificity,and area under the curve(AUC) of DBT in the differential diagnosis of benign and malignant breast tumors were 73.64%,84.55%,and 0.791,respectively.The sensitivity,specificity,and AUC of MRI in the differential diagnosis of benign and malignant breast tumors were 84.55%,85.45%,and 0.850,respectively.The sensitivity,specificity,and AUC of DBT combined with MRI in the differential diagnosis of benign and malignant breast tumors were 97.27%,93.64%,and 0.955,respectively.The blood loss,operation time and hospitalization time of the breast-conserving group were significantly lower than those of the modified radical treatment group,and the difference was statistically significant(P < 0.05).After 3 mo of observation,the breast cosmetic effect of the breast-conserving group was better than that of the modified radical group,and the difference was statistically significant(P < 0.05).Before surgery,the quality-of-life scores of the breast-conserving and modified radical mastectomy groups did not differ(P > 0.05).Three months after surgery,the quality-of-life scores in both groups were higher than those before surgery(P < 0.05),and the quality-of-life score of the breast-conserving group was higher than that of the modified radical group(P < 0.05).In the observation of tumor recurrence rate two years after the operation,four patients in the breast-conserving group and one in the modified radical treatment group had a postoperative recurrence.There was no significant difference in the recurrence rate between the two groups(χ2 = 0.668,P = 0.414 > 0.05).CONCLUSION MRI combined with DBT in diagnosing early breast cancer can significantly improve the diagnostic efficacy compared with the two alone.Breast-conserving surgery leads to better cosmetic breast effects and reduces the impact of surgery on postoperative quality of life.

Adaptive segmentation of digital mammograms through reinforcement learning

An approach based on reinfocement learning for the automated segmentation is presented. The approach consists of two modules:segmentation module and learning module. The segmentation module uses the region-growing algorithm combined with the smooth filtering and the morphological filtering to segment mammograms. The learning module uses the segmentation output as the feedback to learn to select the optimal parameter settings of the segmentation algorithm according to the image properties using reinforcement learning techniques. The approach can adapt itself to various kinds of mammograms through training and therefore obviates the tedious and error-prone tuning of parameter settings manually. Quantitative test results show that the approach is accurate for several kinds of mammograms. Compared to previously proposed approaches,the approach is more adaptable to different mammograms.

Contrast-Enhanced Mammogram: A New Game-Changer in Breast Imaging. Indications with Case-Based Experience

Mammograms are the mainstay of diagnostic breast imaging and cancer screening. Despite advances in technology such as Full Field Digital Mammography (FFDM) and Digital Breast Tomosynthesis (DBT), these imaging techniques are purely structural, and are unable to overcome shortcomings in mammography posed by dense breast parenchyma. Magnetic Resonance Imaging (MRI) is the most sensitive modality in breast imaging, due to its functional aspects in addition to structural imaging with this modality. The use of MRI is however constrained by cost and availability. The utilization of intravenous contrast with mammograms introduces a functional element to imaging. This greatly improves the sensitivity of the examination, approaching sensitivity levels of Magnetic Resonance Imaging (MRI) in the detection of primary breast cancer. With increased sensitivity afforded by assessment of tumor neo-vascularity, as well as its low cost, low energy imaging that is more readily available than MRI, Contrast-Enhanced Mammography (CEM) if more readily available than MRI, this imaging modality is a potential game-changer in breast imaging. In this article, we share our experience in the use of CEM, for indications previously reserved for MRI, with the literature review of these indications. In resonance with prior studies, we echo the ease of performing and reporting of CEM as well as greater patient comfort as the distinct advantages of CEM. In spite of slightly higher radiation dose and some risks related to contrast media, functional results at a significantly lower cost may change how we practice breast imaging in the future using CEM.

基于数字化乳腺X线影像组学预测浸润性乳腺癌腋窝淋巴结转移的多中心研究

目的:探讨基于多中心数字化乳腺X线影像组学预测浸润性乳腺癌腋窝淋巴结转移的临床应用价值。方法:回顾性搜集728例经病理证实的浸润性乳腺癌患者,按照7:3的比例将皖南医学院第一附属医院弋矶山医院413例浸润性乳腺癌患者随机拆分为训练组289例(淋巴结转移阴性197例,淋巴结转移阳性92例)和验证组124例(淋巴结转移阴性85例,淋巴结转移阳性39例),将阜阳市人民医院和太和县人民医院浸润性乳腺癌患者共计315例(淋巴结转移阴性221例,淋巴结转移阳性94例)作为外部测试组。对比分析双乳内外斜位(MLO)和头尾位(CC)图像,选取病变面积较大的数字化乳腺X线图像使用深睿医疗多模态科研平台进行图像分割及影像组学特征提取,采用特征间线性相关性分析与最小绝对收缩和选择算法(LASSO)对组学特征进行降维并使用支持向量机(SVM)分类器构建影像组学预测模型。采用受试者工作特征(ROC)曲线和决策曲线分析(DCA)评价模型性能。结果:最终筛选出8个影像组学特征构建预测模型用于预测浸润性乳腺癌腋窝淋巴结转移,该模型的预测效能在训练组、验证组和外部测试组分别为0.807、0.790和0.753,敏感度、特异度分别为84.8%和61.4%、79.5%和69.4%、44.7%和92.8%。决策曲线证实了该模型的临床实用性。结论:基于数字化乳腺X线影像组学对浸润性乳腺癌腋窝淋巴结转移的预测具有较高效能,对患者制定个性化的治疗方案和预后评估有着重要的临床应用价值。

数字乳腺断层摄影评估新辅助化疗后肿瘤大小的价值

目的评估新辅助化疗后数字乳腺断层摄影(DBT)、全数字化乳腺摄影(FFDM)和超声(US)检查预测残留肿瘤大小的能力。方法回顾性分析2020年1月1日至2021年12月31日病理结果确诊为乳腺癌,行新辅助化疗并接受手术治疗患者的临床及影像学资料。所有患者在新辅助化疗后均行乳腺DBT、FFDM及US检查。采用Pearson相关分析计算不同影像检查方法测量残留肿瘤大小与病理测量结果的相关性;以0.5 cm为阈值,分析不同影像检查预测残留肿瘤大小的准确率。结果85例患者,共86个病灶,去除新辅助化疗后无残留癌的病灶,共纳入72个病灶。新辅助化疗后,DBT、FFDM、US测量残留肿瘤大小与病理测量结果均呈中等程度相关。DBT、FFDM、US预测残留肿瘤大小的准确率分别为59.72%(43/72)、43.06%(31/72)、41.67%(30/72)。DBT与FFDM、US预测残留肿瘤大小的准确率比较,差异具有统计学意义(χ^(2)=4.003、4.695,P=0.045、0.030)。结论新辅助化疗后,DBT预测残留肿瘤大小的准确率优于FFDM与US。DBT在新辅助化疗后的术前评估具有良好的应用前景。

基于数字化乳腺X线影像组学列线图预测浸润性乳腺癌组织学分级的多中心研究

目的:探讨基于多中心数字化乳腺X线影像组学列线图预测浸润性乳腺癌组织学分级的价值。方法:以病理诊断为金标准,按照7:3的比例将皖南医学院第一附属医院弋矶山医院437例浸润性乳腺癌患者随机拆分为训练组305例(Ⅰ/Ⅱ级217例,Ⅲ级88例)和验证组132例(Ⅰ/Ⅱ级94例,Ⅲ级38例),将阜阳市人民医院(n=129)和太和县人民医院(n=162)291例浸润性乳腺癌患者(Ⅰ/Ⅱ级203例,Ⅲ级88例)作为外部测试组。对比分析双乳内外斜位(MLO)和头尾位(CC)图像,选取病变面积较大的数字化乳腺X线图像使用深睿医疗多模态科研平台进行图像分割和影像组学特征提取,采用特征间线性相关性分析与最小绝对收缩和选择算法对组学特征进行降维并使用逻辑回归构建影像组学模型。临床指标经单因素及多因素二元Logistic回归分析并构建临床模型。影像组学评分联合临床指标构建列线图。采用受试者工作特征(ROC)曲线和决策曲线分析(DCA)评价模型性能,使用Delong检验比较模型间的预测效能。结果:最终筛选出3个与浸润性乳腺癌组织学分级最相关的影像组学特征。列线图对浸润性乳腺癌组织学分级的预测效能在训练组、验证组和外部测试组分别为0.811、0.825和0.803,诊断效能优于单一模型。DCA显示在概率值为20%~60%时,训练组、验证组及外部测试组列线图预测浸润性乳腺癌组织学分级的净收益高于影像组学模型及临床模型。结论:基于数字乳腺X线影像组学模型对浸润性乳腺癌组织学分级的预测具有较高的效能,对患者制定个性化治疗方案和预后评估有着重要的临床应用价值。

单体位联合双体位DBT与FFDM对乳腺癌的诊断价值

目的 探讨单体位[头尾位(craniocaudal, CC)或内外侧斜位(mediolateral oblique, MLO)]数字化乳腺断层合成技术(digital breast tomosynthesis,DBT)联合全视野数字化乳腺X线摄影(full-fild digital mammography,FFDM)检查对乳腺癌的检出率和诊断效能。方法 选取141例乳腺病变患者影像学资料,患者同时行乳腺DBT和FFDM检查。由2位放射科诊断医师分别对患者DBT图像进行单体位和双体位(CC+MLO)阅片并联合FFDM,以病理结果为金标准。分析单体位和双体位DBT检查联合FFDM检查对患者乳腺良恶性病灶的检出率及诊断效能。结果 141例患者按照ACR2013版BI-RADS系统分类标准:a类3例、b类40例、c类84例、d类14例。根据BI-RADS评级标准,2位放射科诊断医师采用四种诊断方式(DBT-CC,DBT-MLO及双体位DBT分别联合FFDM及单独FFDM)进行诊断。结论 采用DBT+FFDM的阅片方式无论是单体位还是双体位的结果假阳性率及假阴性率均低于FFDM,诊断的准确度、特异度及灵敏度均高于FFDM,对高/低年资诊断医师FFDM+DBT双体位的诊断效能高于单体位,在FFDM+DBT-CC和FFDM+DBT-MLO单体位之间准确度、灵敏度和特异度MLO均高于CC位。

基于深度学习多模态影像学检查对乳腺导管原位癌的诊断效能分析

目的探讨全视野数字乳腺X线摄影(FFDM)、超声(US)及磁共振(MRI)检查在乳腺导管原位癌(DCIS)中的诊断效能,以及乳腺癌智能辅助诊疗系统辅助放射科初级医师阅片的作用。方法选取经手术病理证实为DCIS的患者91例。91例患者均接受FFDM检查,且诊断时分别由放射科高级医师和放射科初级医师结合人工智能系统辅助诊断阅片评估,79例患者接受US检查,49例患者接受MRI检查,其中42例患者联合了FFDM、US及MRI三种检查。所有病灶均采用2013年ACR第五版乳腺影像报告和数据系统(BI-RADS)进行分类,计算其灵敏度和假阴性率,采用卡方检验,评价其各自的诊断效能;分析3种影像学检查方法灵敏度的相关影响因素。91例FFDM图像由2位放射科初级医师借助《乳腺癌智能辅助诊疗系统》(简称:Mammo AI)对病灶进行检出,并对其进行良恶性的评估,亦计算其灵敏度及假阴性率,采用卡方检验,与放射科高级医师独立阅片进行比较,评价其诊断效能。结果FFDM、US及MRI的诊断灵敏度分别为78.0%(71/91)、78.5%(62/79)和95.9%(47/49),差异有统计学意义(χ^(2)=8.132,P<0.05),三种影像学检查方法联合使用时,DCIS的诊断阳性率97.6%(41/42)。放射科高级医师和Mammo AI辅助放射科初级医师对FFDM的诊断灵敏度分别为78.0%(71/91)和75.8%(69/91),差异无统计学意义(χ^(2)=0.124,P>0.05)。FFDM易受致密型腺体及非钙化型病变影响而漏误诊,而非肿块型和钙化型病变是US检查漏误诊的主要原因;MRI检查低估的2例主要受病灶强化情况及弥散受限情况的影响。结论MRI诊断DCIS的灵敏度高于FFDM和US,假阴性率低,漏诊率少,三种影像检查方法联合应用可提高DCIS的诊断准确率,避免漏误诊。Mammo AI降低了放射科医师的阅片时间,提高对乳腺X线摄影检查的诊断效率。

影像组学及深度学习在预测乳腺癌腋窝淋巴结转移中的研究进展

乳腺癌是女性最常见的恶性肿瘤之一,腋窝淋巴结状态对于肿瘤临床分期、治疗决策及预后等起决定性作用。前哨淋巴结活检术和腋窝淋巴结清扫术是当前腋窝淋巴结状态评估的金标准,但其均为有创性检查且存在多种术后并发症。因此,术前无创性评估腋窝淋巴结状态对临床治疗决策至关重要。影像组学和深度学习技术通过高通量地提取影像组学特征来预测肿瘤的生物学行为,具有可重复性、无创性及客观性等特点,现已广泛应用于乳腺癌诊断、淋巴结转移评估及预后评估等方面。本文基于数字乳腺X线成像及MRI的影像组学和深度学习技术在预测乳腺癌腋窝淋巴结转移中的研究进展予以综述,以期为临床个体化精准医疗提供新思路。

基于不同算法的AI技术对乳腺肿瘤诊断效能的对比分析

目的:分析基于全数字化乳腺X线摄影(FD)的全卷积单阶段乳腺AI算法及基于数字乳腺断层摄影(DBT)的三维多影像融合AI算法在乳腺肿瘤影像诊断中的效能。方法:用FD AI算法(AI-FD)及DBT AI算法(AI-DBT)对常州市妇幼保健院乳腺外科2022年经病理证实的469例(515个病灶)乳腺疾病患者的影像数据进行计算。以病理结果为基准,分别采集记录两种算法结果的阳性数及与病理结果符合数,比较两种算法对乳腺癌的诊断灵敏度、特异度、阳性预测值及阴性预测值;以病理诊断为金标准,比较AI算法、超声(US)及钼靶X线人工诊断(MG人工)等诊断方法的受试者工作特征曲线(ROC)和曲线下的面积(AUC)。结果:AI-DBT的诊断阳性率(67.81%)高于AI-FD (49.17%),差异有统计学意义(χ^(2)=35.01,P<0.05);AI-DBT的诊断准确率(44.33%)稍低于AI-FD (46.90%),差异无统计学意义(χ^(2)=0.42,P>0.05)。两种AI算法比较,AI-DBT对乳腺癌的诊断灵敏度高,但特异性较弱,AI-FD的诊断特异性更佳。AUC值方面,MG人工的最高,为0.804,两种AI算法次之,但均略高于US。结论:基于乳腺DBT三维断层图像与FD二维图像的AI算法在乳腺肿瘤尤其是在乳腺癌的诊断方面具有一定的准确性,但其诊断效能与MG人工诊断之间仍有一定的差距,故目前尚不能完全取代人工诊断。

中国肿瘤整合诊治指南(CACA):X线检查(乳腺X线摄影新技术)解读

2023年中国抗癌协会肿瘤影像专业委员会组织专家编写了《中国肿瘤整合诊治指南(CACA)·X线检查》。CACA指南强调了乳腺X线检查是唯一被证明可早期检测乳腺癌、降低患者死亡率的影像学方法。而乳腺X线摄影新技术作为其衍生技术,在一定程度上弥补了传统乳腺X线摄影的不足,特别适用于以致密型乳腺为主的中国女性。本文针对该指南中乳腺X线摄影新技术核心内容进行介绍,为乳腺肿瘤诊断的临床工作提供行之有效的实践指导。

Senographe DS数字乳腺X射线机故障维修2例

介绍了Senographe DS数字乳腺X射线机的结构组成和工作原理,分析了Senographe DS数字乳腺X射线机无法曝光、图像出现伪影2例故障的原因及排除方法,为同行维修类似故障提供了参考。

MRI及钼靶鉴别良恶性乳腺病变的价值分析

目的 探究MRI、钼靶对良恶性乳腺病变的鉴别价值。方法 选取2020年8月至2023年8月我院收治的乳腺包块患者64例,均进行MRI和数字钼靶X线检测,比较两种方法鉴别良性乳腺病变和乳腺癌的检出率和准确性,分析其影像学特征。结果 64例乳腺病变患者中,良性乳腺病变26例(40.63%),以乳腺腺病为主,恶性乳腺病变38例(59.38%),以浸润性导管癌为主;MRI检出64例乳腺病变中的61例,总检出率为95.31%,对乳腺纤维瘤、乳腺囊肿、导管原位癌的检出率均为100.00%,对良性和恶性乳腺疾病的诊断准确率分别为84.62%和78.94%,MRI诊断恶性乳腺疾病的灵敏度为78.9 4%,特异度为84.62%,准确率为81.25%,Kappa值为0.620;钼靶检出64例乳腺病变中的57例,总检出率为89.06%,对良性和恶性乳腺疾病的诊断准确率分别为69.23%和52.63%,钼靶诊断恶性乳腺疾病的灵敏度为53.63%,特异度为69.23%,准确率为59.38%,Kappa值为0.206,钼靶诊断恶性乳腺疾病的准确率低于MRI(P<0.05)。结论 MRI对良恶性乳腺病变的检出率和诊断准确性均优于数字钼靶X线,在鉴别良恶性乳腺病变上具有更高的临床价值。

全数字化乳腺钼靶X线用于乳腺癌的早期诊断价值

目的:分析在乳腺癌早期诊断中,应用全数字化乳腺钼靶X线检查的诊断价值。方法:选取2023年1月至2024年1月于福建医科大学附属三明市第一医院接受检查的疑似乳腺癌患者80例,均应用彩色多普勒超声检查、全数字化乳腺钼靶X线检查,将结果与最终临床确诊结果比较,计算并比较两种检查方法的诊断效能。结果:80例疑似乳腺癌患者中,临床确诊62例;全数字化乳腺钼靶X线对早期乳腺癌的检查灵敏度、特异度及准确度均高于彩色多普勒超声,差异具有统计学意义(P<0.05)。全数字化乳腺钼靶X线对原位癌、黏液腺癌、浸润性导管癌、单纯性乳腺癌的检出数与临床确诊结果的差异均无统计学意义(P>0.05)。结论:在早期乳腺癌诊断中,应用全数字化乳腺钼靶X线检查的诊断效能较高,可为患者后续病情诊断及治疗方案的规划提供可靠参考。

Alternative Exposure Parameters and Post Process Noise Reduction Expect Considerable Dose Reduction in Single Mammography Views—Initial Experience on Mastectomy Specimens

Objective: To experimentally indicate a lower limit of dose in mammographic imaging yielding adequate image quality for complementary diagnostic views, by evaluation of image series with different exposure parameters and additional image processing on mastectomy specimens with diverse pathology. Methods: Image series were obtained on seven specimens with different target-filter combinations at different exposure values. Three experienced radiologists assessed the lowest acceptable dose level per specimen using a relative grading technique. With the standard image as reference, fibroglandular tissue and pathological structures, including microcalcifications, were evaluated. Subsequently, a series of pixel binning processes was tested and subjectively assessed on the selected images. Results: The lowest dose level at which image quality was acceptable, and achieved with a W/Ag target-filter combination at 32 kV and 4 mAs. These images can be acquired with 10.4% to 22.4% of the average glandular dose in standard images. Post process pixel binning added to the interpretability of such low dose images. Conclusion: This specimen study suggests that dose level of mammography images might be reduced substantially by general application of a W/Ag spectrum, particularly when combined with post process noise reduction. Future studies should focus on the feasibility of this technique in clinical mammography.