Breast lesion size assessment in mastectomy specimens

Wienbeck, Susanne; Uhlig, Johannes; Fischer, Uwe; Hellriegel, Martin; Fintel, Eva von; Kulenkampff, D.; Surov, Alexey; Lotz, Joachim; Perske, Christina

doi:10.1097/md.0000000000017082

Cited by 16 publications

(7 citation statements)

References 35 publications

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“…Third, external validation is needed to evaluate its predictive ability and generalizability. Fourth, we used the more CT prediction of axillary lymph node metastasis objective pathological T stage of the primary tumor as a measure to predict metastasis, because CT images sometimes tend to overestimate size relative to histopathological criteria [26]. Finally, there may be concerns about the risk of radiation exposure with the use of chest CT in patients with breast cancer.…”

Section: Discussionmentioning

confidence: 99%

Predictive value of chest computed tomography for axillary lymph node metastasis in patients with breast cancer: A retrospective cohort study

2021

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Purpose: This study aimed to evaluate the predictive value of preoperative chest computed tomography (CT) for axillary lymph node (ALN) metastasis in patients with breast cancer. Methods: CT features of ALNs were retrospectively reviewed in 212 patients with breast cancer who underwent preoperative chest CT examination and ALN dissection. Primary tumor size and CT characteristics of ALNs (cortical thickness, cortical shape, the presence or absence of contrast enhancement of ALNs, and the presence or absence of perinodal infiltration) were recorded and analyzed. A nomogram was developed to visualize the associations between the predictors and each ALN status endpoint. Results: Of 212 patients, 95 (44.8%) had ALN metastasis. Primary tumor size and CT characteristics of ALNs were identified as predictors of ALN metastasis. The nomogram comprising primary tumor size and cortical shape was a good validation model for predicting ALN metastasis. The sensitivity, specificity, and accuracy of the nomogram for predicting ALN metastasis were 88.4%, 79.5%, and 83.5%, respectively. Conclusion: Using preoperative chest CT scans, a nomogram combining the cortical shape of ALNs with the primary tumor size showed good performance in predicting ALN metastasis.

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Section: Discussionmentioning

confidence: 99%

Predictive value of chest computed tomography for axillary lymph node metastasis in patients with breast cancer: A retrospective cohort study

2021

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“…Meta-analysis has shown that the diagnostic sensitivity of CBBCT was higher than that of DM and ultrasound, and CE-CBBCT has comparable sensitivity but slightly lower speci city compared to MRI [17,18]. In addition, CBBCT has shown promise in preoperative assessment, including determining the extent of the primary tumor [19,20] and predicting axillary lymph node metastasis [21,22]. Some studies have also suggested that CE-CBBCT features can assist in characterizing IHC receptor status and distinguishing molecular subtypes of breast cancer [13,23,24].…”

Section: Introductionmentioning

confidence: 99%

Pre-treatment Contrast-enhanced Cone Beam Breast CT Imaging Features Combining with Clinicopathological Characteristics to Predict the Response of Neoadjuvant Chemotherapy: A Preliminary Feasibility Study

Wang,

Ma,

Wang

et al. 2024

Preprint

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Background To explore the association between pre-treatment contrast-enhanced cone beam breast CT (CE-CBBCT) imaging features and pathological complete response (pCR) after neoadjuvant chemotherapy (NAC), and to develop a predictive nomogram combining with clinicopathological characteristics. Methods A total of 183 female patients with stage II or III breast cancer underwent CE-CBBCT before NAC followed by surgery between August 2020 and September 2023 were enrolled, whose CE-CBBCT images and clinicopathological records were reviewed. All patients were randomly divided into the development cohort (n = 128) and the validation cohort (n = 55) at a ratio of 7:3. Univariate and multivariate binary logistic regression analysis were performed to identify the independent factors associated with pCR in the development cohort. A nomogram was developed based on the combined model, the receiver operating characteristic (ROC) curves, calibration curves and decision curve analysis (DCA) curves were used to evaluate and validate the predictive ability of the nomogram in the two cohorts. Results Univariate analysis showed that margin of mass (p = 0.018), distribution (p = 0.046) and morphology (p = 0.014) of calcifications, adjacent vessel sign (AVS, p = 0.001), molecular subtypes (p = 0.000), proportion of tumor-infiltrating lymphocytes (TILs, p = 0.000), and CA125 (p = 0.018) were all associated with pCR. In multivariate analyses, linear or segmental distribution of calcifications (odds ratio, OR = 6.06), AVS-positivity (OR = 0.11), HER2 enriched (OR = 10.34), TILs (OR = 1.06), and CA125 (OR = 0.93) were independent factors in the combined model. The predictive ability of the combined model (area under curve, AUC = 0.886) was superior to the clinicopathological model (AUC = 0.804; p = 0.014) and CE-CBBCT imaging model (AUC = 0.812; p = 0.047). The nomogram based on the combined model showed good discrimination (AUC: 0.886 vs. 0.820; p = 0.333) and calibration abilities (p value: 0.997 vs. 0.147) in the development and the validation cohort. Conclusion A nomogram based on pre-treatment CE-CBBCT features combining with clinicopathological characteristics is feasible and reliable for the prediction of pCR, which could contribute to the realization of clinical individualized therapy.

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“…In several previous studies, CBBCT has shown encouraging results for the diagnosis of suspicious calcifications in the breast ( 16 ), the assessment of background parenchymal enhancement (BPE) ( 17 ), and the prediction of molecular subtypes of breast cancer ( 18 - 20 ). Consequently, the diagnostic capabilities of CBBCT are considered comparable to those of MRI in the preoperative evaluation of breast tumors ( 21 , 22 ). CBBCT may be a reliable alternative for assessing the extent of lesions when patients cannot undergo MRI for reasons such as contraindications.…”

Section: Introductionmentioning

confidence: 99%

Accuracy of cone-beam breast computed tomography for assessing breast cancer tumor size—comparison with breast magnetic resonance imaging

Zhao,

Song,

et al. 2024

Gland Surg

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Background Accurate preoperative assessment of tumor size is important in developing a surgical plan for breast cancer. The purpose of this study was to evaluate the accuracy of cone-beam breast computed tomography (CBBCT) and magnetic resonance imaging (MRI) in the assessment of tumor size and to analyze the factors influencing the discordance. Methods In this retrospective study, patients with breast cancer who underwent preoperative contrast-enhanced CBBCT (CE-CBBCT) and dynamic contrast-enhanced MRI (DCE-MRI) and received a complete pathologic diagnosis from August 2020 to December 2021 were included, using the pathological result as the gold standard. Two radiologists assessed the CBBCT and MRI features and measured the tumor size with a 2-week washout period. Intraclass correlation coefficient (ICC) and Bland-Altman analyses were used to assess inter-observer reproducibility and agreement based on CBBCT, MRI and pathology. Univariate analyses of differences in clinical, pathological and CBBCT/MRI features between the concordant and discordant groups was performed using the t -test, Mann-Whitney U -test, Chi-squared test and Fisher’s exact test. Multivariate analyses were used to identify factors associated with discordance of CBBCT/MRI with pathology. Results A total of 115 female breast cancer patients (115 lesions) were included. All patients had a single malignant tumor of the unilateral breast. The reproducibility and the agreement ranged from moderate to excellent (ICC =0.607–0.983). Receiver operating characteristic (ROC) analyses showed that the cut-off values of CBBCT-pathology and MRI-pathology discordance were 2.25 and 2.65 cm, respectively. CBBCT/MRI-pathology concordance was significantly associated with the extent of pathology, lesion type, presence of calcification, human epidermal growth factor receptor 2 (HER2) status and fatty infiltration (P<0.05). In lesions containing calcification, the difference of CBBCT-pathology was significantly smaller than MRI-pathology (P=0.021). Non-mass enhancement (NME) was the main predictor of CBBCT- or MRI-pathology discordance [odds ratio (OR) =3.293–6.469, P<0.05], and HER2 positivity was a predictor of CBBCT-pathology discordance (OR =3.514, P=0.019). Conclusions CBBCT and MRI have comparable accuracy in measurement of tumor size, and CBBCT is advantageous in assessing the size of calcified lesions. NME and HER2 positivity are significant predictors of CBBCT-pathology discordance. This suggests that CBBCT might serve as an alternative imaging technique to assess tumor size when patients do not tolerate MRI.

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Breast lesion size assessment in mastectomy specimens

Cited by 16 publications

References 35 publications

Predictive value of chest computed tomography for axillary lymph node metastasis in patients with breast cancer: A retrospective cohort study

Predictive value of chest computed tomography for axillary lymph node metastasis in patients with breast cancer: A retrospective cohort study

Pre-treatment Contrast-enhanced Cone Beam Breast CT Imaging Features Combining with Clinicopathological Characteristics to Predict the Response of Neoadjuvant Chemotherapy: A Preliminary Feasibility Study

Accuracy of cone-beam breast computed tomography for assessing breast cancer tumor size—comparison with breast magnetic resonance imaging

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