Predictive factors of upstaging DCIS to invasive carcinoma in BCT vs mastectomy

Sheaffer, William W.; Gray, Richard; Wasif, Nabil; Stucky, Chee Chee H.; Cronin, Patricia A.; Kosiorek, Heidi E.; Basu, Anamika; Pizzitola, Victor; Patel, Bhavika; Giurescu, Marina; Lorans, Roxanne; McCullough, Ann E.; Ocal, Idris Tolgay; Pockaj, Barbara A.

doi:10.1016/j.amjsurg.2018.12.069

Cited by 12 publications

(13 citation statements)

References 18 publications

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“…We found that MRI did not result in higher mastectomy rates, which is in line with some studies that also reported no effect of MRI on mastectomy rates [21,23]. By contrast, the majority of the studies on the effect of MRI on mastectomy rates reported an increased rate [8,20,22,24,26]. Differences between these studies are hard to explain but are probably related to the radiologists' interpretations of the MRI images.…”

Section: Discussionsupporting

confidence: 88%

Preoperative breast MRI in management of patients with needle biopsy-proven ductal carcinoma in situ (DCIS)

Bekkum

Braak

Plaisier

et al. 2020

European Journal of Surgical Oncology

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Background: In 20e25% of patients with biopsy-proven DCIS underestimation occurs. Sentinel lymph node biopsy (SLNB) is offered to patients with biopsy-proven ductal carcinoma in situ (DCIS) and a high risk of occult invasive cancer. However, assessment of high risk is controversial. We aimed to improve selection of patients for SLNB with preoperative breast magnetic resonance imaging (MRI). Methods: In this prospective observational study, MRI was offered to all subsequent patients with a biopsy-proven DCIS admitted to a large Dutch teaching hospital between April 2012 and March 2017. MRI images were analysed for signs of invasive cancer and the results were compared with the pathologic results after surgical treatment. The diagnostic accuracy of additional MRI in detecting occult invasive cancer was determined. Results: Of 211 patients eligible for additional MRI analysis, 149 underwent breast MRI. The majority (67%) received breast-conserving therapy, and the underestimation rate was 20%. Subsequent to MRI analysis, 20 additional invasive diagnostic procedures were performed. Occult invasive cancer was suspected on MRI in 46 patients (31%) and was confirmed in 18 (12%). In this study, breast MRI had a sensitivity of 67%, a specificity of 77%, and a true negative rate of 91%. Conclusion: Preoperative breast MRI cannot reliably predict the presence of invasive cancer in patients with biopsy proven DCIS. Therefore, it cannot be used to in the selection of patients for a SLNB.

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Section: Discussionsupporting

confidence: 88%

Preoperative breast MRI in management of patients with needle biopsy-proven ductal carcinoma in situ (DCIS)

Bekkum

Braak

Plaisier

et al. 2020

European Journal of Surgical Oncology

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“…According to relevant literature, only about 12-32% of pure DCIS diagnosed by CNB before surgery is upstaged to microinvasion or even to invasive cancer in postoperative pathology (3)(4)(5)(6). This would result in an imbalance in the ratio of data between upgraded and pure DCIS, which might make the model's ability to diagnose upgraded DCIS weaker (11).…”

Section: Discussionmentioning

confidence: 99%

“…For optimal performance of the convolution network model, the sample sizes in the two groups (upstaged and pure DCIS) should be equal (11). Previous research has shown a wide variability of the number of cases in the two groups, with an upgrade rate of pure DCIS after surgery of 12-32% (3)(4)(5)(6). Therefore, to balance the number of upstaged and pure DCIS, we retrospectively enrolled 180 upstaged and 180 pure DCIS eligible patients.…”

Section: Patientsmentioning

confidence: 99%

“…However, approximately 12-32% of cases diagnosed by CNB before surgery involve upstaging to a microinvasion; this indicates the invasion of cancer cells beyond the basement membrane into at least 1 mm of the adjacent tissue or the diagnosis of an invasive cancer on postoperative specimen analysis (3)(4)(5)(6). The major cause of upstaging cannot be determined by CNB, and imaging manifestations, biopsy techniques, and the DCIS size could also affect the preoperative diagnosis (3)(4)(5)(6). Therefore, overtreatment and undertreatment may occur in the management of axillary lymph nodes in patients with DCIS.…”

Section: Introductionmentioning

confidence: 99%

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Application of deep learning to predict underestimation in ductal carcinoma in situ of the breast with ultrasound

Qian

Zhang

et al. 2021

Ann Transl Med

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Background: To develop an ultrasound-based deep learning model to predict postoperative upgrading of pure ductal carcinoma in situ (DCIS) diagnosed by core needle biopsy (CNB) before surgery.Methods: Of the 360 patients with DCIS diagnosed by CNB and identified retrospectively, 180 had lesions upstaged to ductal carcinoma in situ with microinvasion (DCISM) or invasive ductal carcinoma (IDC) postoperatively. Ultrasound images obtained from the hospital database were divided into a training set (n=240) and validation set (n=120), with a ratio of 2:1 in chronological order. Four deep learning models, based on the ResNet and VggNet structures, were established to classify the ultrasound images into postoperative upgrade and pure DCIS. We obtained the area under the receiver operating characteristic curve (AUROC), specificity, sensitivity, accuracy, positive predictive value (PPV), and negative predictive value (NPV) to estimate the performance of the predictive models. The robustness of the models was evaluated by a 3-fold cross-validation.Results: Clinical features were not significantly different between the training set and the test set (P value >0.05). The area under the receiver operating characteristic curve of our models ranged from 0.724 to 0.804.The sensitivity, specificity, and accuracy of the optimal model were 0.733, 0.750, and 0.742, respectively. The three-fold cross-validation results showed that the model was very robust. Conclusions:The ultrasound-based deep learning prediction model is effective in predicting DCIS that will be upgraded postoperatively.

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“…As an example, a DCIS diagnosis may entail "radical" treatments including mastectomy, nipple-sparing mastectomy [20,21] or breast-conserving therapy followed by adjuvant radiation in most cases. Finally, in cases of "upstaging" from DCIS to invasive ductal carcinoma [22], the false diagnosis could erroneously alter therapeutic options.…”

Section: Discussionmentioning

confidence: 99%

“Harms” Associated with Breast Cancer Screening and Reliability of Frozen Section in Older Women: In the Case of an 80 Year Old Woman

Antoniou

Zervoudis

Vouxinou

et al. 2020

Reports

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The objective of this paper is to present a rare case with negative final histologic examination despite abnormal findings of all previous exams indicating breast cancer in an 80 year old woman. Mammographic and magnetic resonance imaging findings were concordant with the frozen section biopsy result of DCIS. However, the final histologic diagnosis was radial scar (benign breast lesion that can radiologically mimic malignancy). As a conclusion, abnormal mammographic and magnetic resonance imaging findings with positive for DCIS frozen section reports are not always confirmed in the final histologic examination. Furthermore, considering that screening does not seem to be associated with a reduction in mortality due to breast cancer after the age of 75, breast cancer screening could be individualized in this age group.

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Predictive factors of upstaging DCIS to invasive carcinoma in BCT vs mastectomy

Cited by 12 publications

References 18 publications

Preoperative breast MRI in management of patients with needle biopsy-proven ductal carcinoma in situ (DCIS)

Preoperative breast MRI in management of patients with needle biopsy-proven ductal carcinoma in situ (DCIS)

Application of deep learning to predict underestimation in ductal carcinoma in situ of the breast with ultrasound

“Harms” Associated with Breast Cancer Screening and Reliability of Frozen Section in Older Women: In the Case of an 80 Year Old Woman

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