Contrast-enhanced cone beam breast CT features of breast cancers: correlation with immunohistochemical receptors and molecular subtypes

Ma, Yue; Liu, Aidi; O’Connell, Avice M; Zhu, Yueqiang; Li, Haijie; Han, Peng; Lu, Yin; Lü, Hong; Ye, Zhaoxiang

doi:10.1007/s00330-020-07277-8

Cited by 18 publications

(10 citation statements)

References 35 publications

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“…[22] Quantification of lesion enhancement at CE-CBBCT will be helpful in improving both the sensitivity and specificity of CBBCT. [18,31,[35][36][37] Our study showed excellent interobserver agreement on lesions BI-RADS score for FFDM and moderate interobserver agreement for CBBCT. These results are comparable to previous studies from Wienbeck et al [31,34] within the same study concept.…”

Section: Discussionsupporting

confidence: 51%

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Comparison between cone-beam breast-CT and full-field digital mammography for microcalcification detection depending on breast density

et al. 2023

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The purpose of this study was to evaluate the impact of breast density on the diagnostic performance of cone-beam breast-CT (CBBCT) in comparison to full-field digital mammography (FFDM) for the detection of microcalcifications. This retrospective IRB-approved study was conducted between December 2015 and March 2017 and enrolled 171 women with Breast Imaging Reporting and Data System category 4 or 5 lesions on FFDM and additional CBBCT; 56 of which were ineligible. The inclusion was restricted to 83 women (90 breasts, 90 lesions) with microcalcifications. All lesions underwent histology or were monitored by FFDM and a clinical examination at least 2 years after enrollment. Two breast radiologists independently read each data set twice. Sensitivity, specificity and area under the curve were compared between the modalities. Thirty-two breasts (35.5%) were grouped as non-dense breasts (American College of Radiology types a/b) and 58 breasts (64.5%) as dense breasts (American College of Radiology types c/d). Histopathological assessment was performed in 61 of 90 breast lesions (32 malignant, 1 high-risk and 28 benign). Area under the curve was larger for FFDM than for CBBCT (P = .085). The sensitivity was significantly higher for FFDM compared to CBBCT (P = .009). The specificity showed no significant differences comparing FFDM (both readers: 0.62) versus CBBCT (reader 1: 0.76, reader 2: 0.60; P = .192). Inter-observer-reliability on BI-RADS readings was almost perfect for FFDM and moderate for CBBCT (κ = 0.84, κ = 0.54, respectively). Intra-observer agreement was substantial to almost perfect for both methods and readers. Compared with FFDM, CBBCT demonstrated non-comparable results for microcalcification detection in dense and non-dense breasts.

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Section: Discussionsupporting

confidence: 51%

“…[22] Quantification of lesion enhancement at CE-CBBCT will be helpful in improving both the sensitivity and specificity of CBBCT. [18,31,35–37]…”

Section: Discussionmentioning

confidence: 99%

Comparison between cone-beam breast-CT and full-field digital mammography for microcalcification detection depending on breast density

et al. 2023

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“…This corresponds to better presurgical planning, ability to perform accurate volumetric analysis for treatment response, quantitative estimates of implant rupture, and overall improved diagnostic accuracy. CBBCT has also shown promise in assisting in the evaluation of different breast cancer types based on imaging morphology [40].…”

Section: Cone-beam Breast Computed Tomographymentioning

confidence: 99%

Cone-Beam Breast Computed Tomography: Time for a New Paradigm in Breast Imaging

O’Connell

Marini

Kawakyu-O’Connor

2021

JCM

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It is time to reconsider how we image the breast. Although the breast is a 3D structure, we have traditionally used 2D mammography to perform screening and diagnostic imaging. Mammography has been continuously modified and improved, most recently with tomosynthesis and contrast mammography, but it is still using modifications of compression 2D mammography. It is time to consider 3D imaging for this 3D structure. Cone-beam breast computed tomography (CBBCT) is a revolutionary modality that will assist in overcoming the limitations of current imaging for dense breast tissue and overlapping structures. It also allows easy administration of contrast material for functional imaging. With a radiation dose on par with diagnostic mammography, rapid 10 s acquisition, no breast compression, and true high-resolution isotropic imaging, CBBCT has the potential to usher in a new era in breast imaging. These advantages could translate into lower morbidity and mortality from breast cancer.

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“…It has comparable sensitivity in identifying benign and malignant lesions to magnetic resonance imaging [10,11]. Previous studies have shown that CBBCT is helpful in distinguishing tumor subtypes [12][13][14]. A recent study found a novel approach to lesion classification by developing a convolutional neural network with deep learning [15].…”

Section: Introductionmentioning

confidence: 99%

Assessment of Cone-Beam Breast Computed Tomography for Predicting Pathologic Response to Neoadjuvant Chemotherapy in Breast Cancer: A Prospective Study

Chen

Zhou

et al. 2022

Journal of Oncology

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Background. Response surveillance of neoadjuvant chemotherapy is needed to facilitate treatment decisions. We aimed to assess the imaging features of cone-beam breast computed tomography (CBBCT) for predicting the pathologic response of breast cancer after neoadjuvant chemotherapy. Methods. This prospective study included 81 women with locally advanced breast cancer who underwent neoadjuvant chemotherapy from August 2017 to January 2021. All patients underwent CBBCT before treatment, and 55 and 65 patients underwent CT examinations during the midtreatment (3 cycles) and late-treatment phases (7 cycles), respectively. Clinical information and quantitative parameters such as the diameter, volume, surface area, and CT density were compared between pathologic responders and nonresponders using the T –test and the Mann–Whitney U test. The performance of meaningful parameters was evaluated with the receiver operating characteristic curve, sensitivity, and specificity. Results. The quantitative results for the segmented volume, segmented surface area, segmented volume reduction, maximum enhancement ratio, wash-in rate and two-minute enhancement value in the mid- and late-treatment periods had predictive value for pathologic complete response. The area under the curve for the prediction model after multivariate regression analysis was 0.874. Conclusion. After comparing the outcomes of each timepoint, mid- and late-treatment parameters can be used to predict pathologic outcome. The late-treatment parameters showed significant value with a predictive model.

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Contrast-enhanced cone beam breast CT features of breast cancers: correlation with immunohistochemical receptors and molecular subtypes

Cited by 18 publications

References 35 publications

Comparison between cone-beam breast-CT and full-field digital mammography for microcalcification detection depending on breast density

Comparison between cone-beam breast-CT and full-field digital mammography for microcalcification detection depending on breast density

Cone-Beam Breast Computed Tomography: Time for a New Paradigm in Breast Imaging

Assessment of Cone-Beam Breast Computed Tomography for Predicting Pathologic Response to Neoadjuvant Chemotherapy in Breast Cancer: A Prospective Study

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