Diagnostic accuracy of radiography, digital breast tomosynthesis, micro-CT and ultrasound for margin assessment during breast surgery: A systematic review and meta-analysis

Manhoobi, Irina Palimaru; Bodilsen, Anne; Nijkamp, Jasper; Pareek, Anuj; Tramm, Trine; Redsted, Søren; Christiansen, Peer

doi:10.1016/j.acra.2021.12.006

Cited by 10 publications

(6 citation statements)

References 47 publications

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“…23 AUROC is similarly variable, but low, ranging from 0.60 to 0.73. 23–27 The current models’ accuracy metrics are higher than many of the results published in the literature, demonstrating the potential of this approach.…”

Section: Discussionmentioning

confidence: 72%

Computer Vision Analysis of Specimen Mammography to Predict Margin Status

Chen

Gallagher

Gomez

2023

Preprint

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Intra-operative specimen mammography is a valuable tool in breast cancer surgery, providing immediate assessment of margins for a resected tumor. However, the accuracy of specimen mammography in detecting microscopic margin positivity is low. We sought to develop a deep learning-based model to predict the pathologic margin status of resected breast tumors using specimen mammography. A dataset of specimen mammography images matched with pathology reports describing margin status was collected. Models pre-trained on radiologic images were developed and compared with models pre-trained on non-medical images. Model performance was assessed using sensitivity, specificity, and area under the receiver operating characteristic curve (AUROC). The dataset included 821 images and 53% had positive margins. For three out of four model architectures tested, models pre-trained on radiologic images outperformed domain-agnostic models. The highest performing model, InceptionV3, showed a sensitivity of 84%, a specificity of 42%, and AUROC of 0.71. These results compare favorably with the published literature on surgeon and radiologist interpretation of specimen mammography. With further development, these models could assist clinicians with identifying positive margins intra-operatively and decrease the rate of positive margins and re-operation in breast-conserving surgery.

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Section: Discussionmentioning

confidence: 72%

Computer Vision Analysis of Specimen Mammography to Predict Margin Status

Chen

Gallagher

Gomez

2023

Preprint

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“…Intraoperatively, it is possible to submit the surgical specimen to radiography or ultrasound to confirm the presence of the breast lesion within it [114][115][116][117]. This procedure may be especially helpful in the case of DCIS diagnosed by microcalcifications or in the case of complete regression after neoadjuvant chemotherapy by the presence of a clip, previously placed in the tumor site [118].…”

Section: Preoperative Surgical Planning and Intraoperative Margin Ass...mentioning

confidence: 99%

Updates and Debate Concerning Margin Adequacy and Management following Breast-Conserving Surgery

Bertozzi¹,

Londero²,

Nanez³

et al. 2022

Clin. Exp. Obstet. Gynecol.

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Objective: Breast-conserving surgery (BCS) experienced a significant surge during the last decades due to the increase of early breast cancer detection. Central to the discussion is margin adequacy which represents one of the most significant predictive factors for local relapse. This paper aims to shed light on the problem of margins in breast surgery. Mechanism: We performed a systematic narrative review of the literature by conducting a search using Medline/PubMed, Scopus, and Embase. The following keywords were considered: "breast-conserving surgery" AND "margins"/"margin". Findings in Brief: In the case of invasive breast cancer, "no ink on tumor" can be considered an adequate margin, while for ductal carcinoma in situ (DCIS), a distance of 2 mm from tumor should be obtained. Many novel tools have been developed based both on the latest radiological imaging techniques and on the tissue expression of certain markers, with the aim of precise navigation of tumor excision and intraoperative evaluation of cavity excision margins. Oncoplastic surgery can be considered oncologically safe while improving the cosmetic outcome and patients' quality of life. The appropriate use of adjuvant treatments in the context of a multidisciplinary and personalized management of breast cancer is the only means to omit a second intervention in some carefully selected cases. Conclusions: Debate still exists concerning the definition of adequate clear margin following BCS for DCIS. Further studies are required to better assess multimodal treatment approaches in this condition.

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“…Other studies have found an association between high mammographic breast density and positive margins after BCS [9,12,28]. We hypothesized, that preoperative mammographic breast density might improve the model's predictive accuracy, when added to the model.…”

Section: Introductionmentioning

confidence: 96%

“…A positive histopathological margin is de ned as a 0 mm margin width -'tumor on the inked margin' for invasive cancer , and < 2 mm margin width for ductal carcinoma in situ (DCIS), according to guidelines [5][6][7]. The reported percentages of positive margins following BCS vary from 5-42% according to international reports with varying cohorts of invasive [8,9], combined invasive and in situ breast cancer [10][11][12][13][14][15][16][17][18], using different guidelines for margin positivity [19]. To reduce risk of local recurrence [20], in case of positive margins after BCS, a second surgical procedure is recommended, with increased risk of anxiety for the patients [21], impaired cosmetic outcome [22], prolonged time to systemic treatment [8,23], and with increased health care costs [24].…”

Section: Introductionmentioning

confidence: 99%

External validation of a multivariable prediction model for positive resection margins in breast-conserving surgery

Manhoobi,

Ellbrant,

Bendahl

et al. 2024

Preprint

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Background: Positive resection margins after breast-conserving surgery (BCS) most often demands a repeat surgery. Identifying patients at risk of positive margins allow for surgical techniques using wider resection margins, which may reduce the need of additional surgeries. A prediction model by Ellbrant et al. with seven preoperative clinical-pathological and imaging variables predicts positive margins after BCS with an area under the ROC curve (AUC) of 0.80. The aim of the current study was to externally validate this prediction model and to explore if additional available preoperative variables can further improve the accuracy of the model. Methods: This retrospective cohort study comprises 225 invasive breast cancer patients who underwent BCS and included at Aarhus University Hospital, Aarhus, Denmark during 2020-2022. Receiver operating characteristic (ROC) and calibration analysis were used to validate the multivariable prediction model. Univariable logistic regression was used to evaluate if additional variables available in the validation cohort were associated with positive margins and backward elimination to explore if these variables could further improve the model´s predictive accuracy. Results: The AUC of the model was 0.60 (95% CI: 0.50-0.70) in the validation cohort. High versus low mammographic breast density was associated with positive margins (p=0.009), however the AUC did not further increase, when adding this as an additional variable to the model. Conclusion: The accuracy of the model to predict positive margins after BCS in the validation cohort was lower as compared to in the development cohort, most likely due to differences in patient and tumor characteristics between the sites. High mammographic breast density was found to be associated with positive margins after BCS but did not further improve the model´s predictive accuracy.

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Diagnostic accuracy of radiography, digital breast tomosynthesis, micro-CT and ultrasound for margin assessment during breast surgery: A systematic review and meta-analysis

Cited by 10 publications

References 47 publications

Computer Vision Analysis of Specimen Mammography to Predict Margin Status

Computer Vision Analysis of Specimen Mammography to Predict Margin Status

Updates and Debate Concerning Margin Adequacy and Management following Breast-Conserving Surgery

External validation of a multivariable prediction model for positive resection margins in breast-conserving surgery

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