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 bre...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.展开更多
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 techniq...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.展开更多
We have examined ten human subjects with a previously developed instrument for near-infrared diffuse spectral imaging of the female breast.The instrument is based on a tandem,planar scan of two collinear optical fiber...We have examined ten human subjects with a previously developed instrument for near-infrared diffuse spectral imaging of the female breast.The instrument is based on a tandem,planar scan of two collinear optical fibers(one for illumination and one for collection)to image a gently compressed breast in a transmission geometry.The optical data collection features a spatial sampling of 25 points/cm2 over the whole breast,and a spectral sampling of 2 pointsm in the 650-900nm wavelength range.Of the ten human subjects examined,eight are healthy subjects and two are cancer patients with unilateral invasive ductal carcinoma and ductal carcinoma in situ,respectively.For each subject,we generate second-derivative images that identify a network of highly absorbing structures in the breast that we assign to blood vessels.A previously developed paired-wavelength spectral method assigns oxygenation values to the absorbing structures displayed in the second-derivative images.The resulting oxygenation images feature average values over the whole breast that are significantly lower in cancerous breasts(69±14%,n=2)than in healthy breasts(85±7%,n=18)(p<0.01).Furthermore,in the two patients with breast cancer,the average oxygenation values in the cancerous regions are also significantly lower than in the remainder of the breast(invasive ductal carcinoma:49±11%vs 61±16%,p<0.01;ductal carcinoma in situ:58±8%vs 77±11%,p<0.001).展开更多
本文旨在研究数字乳腺断层合成摄影技术(digital breast tomosynthesis,DBT)联合乳腺能谱成像(contrast-enhanced spectral mammography,CESM)对致密型乳腺内病变患者的诊断价值。通过选取疑似乳腺疾病患者70例,先进行DBT检查再进行CES...本文旨在研究数字乳腺断层合成摄影技术(digital breast tomosynthesis,DBT)联合乳腺能谱成像(contrast-enhanced spectral mammography,CESM)对致密型乳腺内病变患者的诊断价值。通过选取疑似乳腺疾病患者70例,先进行DBT检查再进行CESM检查,结果发现,DBT对致密型乳腺病变BI-RADS分类3~5型检出率为84.29%,低于CESM检查的95.71%(χ2=5.079,P=0.024)。DBT检查以不均匀致密型和高度致密型边缘清晰征象为主,CESM检查以不均匀致密型、高度致密型边缘毛刺征象为主,差异有统计学意义(P<0.05)。DBT与CESM两项联合检查诊断致密型乳腺病变敏感性和准确性较高,与单项结果相比较,差异有统计学意义(P<0.05)。本研究结果提示,DBT联合CESM对致密型乳腺内病变诊断效果显著,两者能实现互补。展开更多
基金supported by the National Natural Science Foundation of China (No.82001775, 82371933)the Natural Science Foundation of Shandong Province of China (No.ZR2021MH120)+1 种基金the Special Fund for Breast Disease Research of Shandong Medical Association (No.YXH2021ZX055)the Taishan Scholar Foundation of Shandong Province of China (No.tsgn202211378)。
摘要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.
摘要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.
基金supported by the National Institutes of Health,Grant CA95885.
摘要We have examined ten human subjects with a previously developed instrument for near-infrared diffuse spectral imaging of the female breast.The instrument is based on a tandem,planar scan of two collinear optical fibers(one for illumination and one for collection)to image a gently compressed breast in a transmission geometry.The optical data collection features a spatial sampling of 25 points/cm2 over the whole breast,and a spectral sampling of 2 pointsm in the 650-900nm wavelength range.Of the ten human subjects examined,eight are healthy subjects and two are cancer patients with unilateral invasive ductal carcinoma and ductal carcinoma in situ,respectively.For each subject,we generate second-derivative images that identify a network of highly absorbing structures in the breast that we assign to blood vessels.A previously developed paired-wavelength spectral method assigns oxygenation values to the absorbing structures displayed in the second-derivative images.The resulting oxygenation images feature average values over the whole breast that are significantly lower in cancerous breasts(69±14%,n=2)than in healthy breasts(85±7%,n=18)(p<0.01).Furthermore,in the two patients with breast cancer,the average oxygenation values in the cancerous regions are also significantly lower than in the remainder of the breast(invasive ductal carcinoma:49±11%vs 61±16%,p<0.01;ductal carcinoma in situ:58±8%vs 77±11%,p<0.001).
摘要本文旨在研究数字乳腺断层合成摄影技术(digital breast tomosynthesis,DBT)联合乳腺能谱成像(contrast-enhanced spectral mammography,CESM)对致密型乳腺内病变患者的诊断价值。通过选取疑似乳腺疾病患者70例,先进行DBT检查再进行CESM检查,结果发现,DBT对致密型乳腺病变BI-RADS分类3~5型检出率为84.29%,低于CESM检查的95.71%(χ2=5.079,P=0.024)。DBT检查以不均匀致密型和高度致密型边缘清晰征象为主,CESM检查以不均匀致密型、高度致密型边缘毛刺征象为主,差异有统计学意义(P<0.05)。DBT与CESM两项联合检查诊断致密型乳腺病变敏感性和准确性较高,与单项结果相比较,差异有统计学意义(P<0.05)。本研究结果提示,DBT联合CESM对致密型乳腺内病变诊断效果显著,两者能实现互补。