Dataset Information

Association of Magnetic Resonance Imaging and a 12-Gene Expression Assay With Breast Ductal Carcinoma In Situ Treatment.

ABSTRACT: Importance:Advanced diagnostics, such as magnetic resonance imaging (MRI) and gene expression profiles, are potentially useful to guide targeted treatment in patients with ductal carcinoma in situ (DCIS). Objectives:To examine the proportion of patients who converted to mastectomy after MRI and the reasons for those conversions and to measure patient adherence to radiotherapy guided by the 12-gene DCIS score. Design, Setting, and Participants:Analysis of a prospective, cohort, nonrandomized clinical trial that enrolled women with DCIS on core biopsy who were candidates for wide local excision (WLE) from 75 institutions from March 25, 2015, to April 27, 2016, through the Eastern Cooperative Oncology Group-American College of Radiology Imaging Network trial E4112. Interventions:Participants underwent breast MRI before surgery, and subsequent management incorporated MRI findings for choice of surgery. The DCIS score was used to guide radiotherapy recommendations among women with DCIS who had WLE as the final procedure and had tumor-free excision margins of 2 mm or greater. Main Outcomes and Measures:The primary end point was to estimate the conversion rate to mastectomy and the reason for conversion. Results:Of 339 evaluable women (mean [SD] age, 59.1 [10.1] years; 262 [77.3%] of European descent) eligible for WLE before MRI, 65 (19.2%; 95% CI, 15.3%-23.7%) converted to mastectomy. Of these 65 patients, conversion was based on MRI findings in 25 (38.5%), patient preference in 25 (38.5%), positive margins after attempted WLE in 10 (15.4%), positive genetic test results in 3 (4.6%), and contraindication to radiotherapy in 2 (3.1%). Among the 285 who had WLE performed after MRI as the first surgical procedure, 274 (96.1%) achieved successful breast conservation. Of 171 women eligible for radiotherapy guided by DCIS score (clear margins, absence of invasive disease, and score obtained), the score was low (<39) in 82 (48.0%; 95% CI, 40.6%-55.4%) and intermediate-high (?39) in 89 (52.0%; 95% CI, 44.6%-59.4%). Of these 171 patients, 159 (93.0%) were adherent with recommendations. Conclusions and Relevance:Among women with DCIS who were WLE candidates based on conventional imaging, multiple factors were associated with conversion to mastectomy. This study may provide useful preliminary information required for designing a planned randomized clinical trial to determine the effect of MRI and DCIS score on surgical management, radiotherapy, overall resource use, and clinical outcomes, with the ultimate goal of achieving greater therapeutic precision. Trial Registration:ClinicalTrials.gov identifier: NCT02352883.

SUBMITTER: Lehman CD

PROVIDER: S-EPMC6583020 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature

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Association of Magnetic Resonance Imaging and a 12-Gene Expression Assay With Breast Ductal Carcinoma In Situ Treatment.

Lehman Constance D CD Gatsonis Constantine C Romanoff Justin J Khan Seema A SA Carlos Ruth R Solin Lawrence J LJ Badve Sunil S McCaskill-Stevens Worta W Corsetti Ralph L RL Rahbar Habib H Spell Derrick W DW Blankstein Kenneth B KB Han Linda K LK Sabol Jennifer L JL Bumberry John R JR Gareen Ilana I Snyder Bradley S BS Wagner Lynne I LI Miller Kathy D KD Sparano Joseph A JA Comstock Christopher C

JAMA oncology 20190701 7

<h4>Importance</h4>Advanced diagnostics, such as magnetic resonance imaging (MRI) and gene expression profiles, are potentially useful to guide targeted treatment in patients with ductal carcinoma in situ (DCIS).<h4>Objectives</h4>To examine the proportion of patients who converted to mastectomy after MRI and the reasons for those conversions and to measure patient adherence to radiotherapy guided by the 12-gene DCIS score.<h4>Design, setting, and participants</h4>Analysis of a prospective, coho ...[more]

PMID: 30653209

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Project description:ImportanceGuiding treatment decisions for women with ductal carcinoma in situ (DCIS) requires understanding patient preferences and the influence of preoperative magnetic resonance imaging (MRI) and surgeon recommendation.ObjectiveTo identify factors associated with surgery preference and surgery receipt among a prospective cohort of women with newly diagnosed DCIS.Design, setting, and participantsA prospective cohort study was conducted at 75 participating institutions, including community practices and academic centers, across the US between March 25, 2015, and April 27, 2016. Data were analyzed from August 2 to September 24, 2021. This was an ancillary study of the ECOG-ACRIN Cancer Research Group (E4112). Women with recently diagnosed unilateral DCIS who were eligible for wide local excision and had a diagnostic mammogram within 3 months of study registration were included. Participants who had documented surgery and completed the baseline patient-reported outcome questionnaires were included in this substudy.ExposuresWomen received preoperative MRI and surgeon consultation and then underwent wide local excision or mastectomy. Participants will be followed up for recurrence and overall survival for 10 years from the date of surgery.Main outcomes and measuresPatient-reported outcome questionnaires assessed treatment goals and concerns and surgery preference before MRI and after MRI and surgeon consultation.ResultsOf the 368 participants enrolled 316 (86%) were included in this substudy (median [range] age, 59.5 [34-87] years; 45 women [14%] were Black; 245 [78%] were White; and 26 [8%] were of other race). Pre-MRI, age (odds ratio [OR] per 5-year increment, 0.45; 95% CI, 0.26-0.80; P = .007) and the importance of keeping one's breast (OR, 0.48; 95% CI, 0.31-0.72; P < .001) vs removal of the breast for peace of mind (OR, 1.35; 95% CI, 1.04-1.76; P = .03) were associated with surgery preference for mastectomy. After MRI and surgeon consultation, MRI upstaging (48 of 316 [15%]) was associated with patient preference for mastectomy (OR, 8.09; 95% CI, 2.51-26.06; P < .001). The 2 variables with the highest ORs for initial receipt of mastectomy were MRI upstaging (OR, 12.08; 95% CI, 4.34-33.61; P < .001) and surgeon recommendation (OR, 4.85; 95% CI, 1.99-11.83; P < .001).Conclusions and relevanceIn this cohort study, change in patient preference for DCIS surgery and surgery received were responsive to MRI results and surgeon recommendation. These data highlight the importance of ensuring adequate information and ongoing communication about the clinical significance of MRI findings and the benefits and risks of available treatment options.

Project description:BackgroundThe accurate evaluation of favorable response to neoadjuvant chemotherapy (NCT) is critical to determine the extent of surgery. We investigated independent clinicopathological and radiological predictors to discriminate no residual carcinoma (ypT0) from residual ductal carcinoma in situ (ypTis) in breast cancer patients who received NCT.Patients and methodsParameters of 117 patients attaining pathological complete response (CR) in the breast after NCT between January 2010 and December 2013 were retrospectively evaluated by univariate and multivariate analyses. All patients underwent mammography, ultrasound, and magnetic resonance imaging (MRI) before and after NCT.ResultsThere were 67 (57.3%) patients with ypT0. These patients were associated with hormone receptor-negative status, human epidermal growth factor receptor-2 (HER2)-negative tumors, and a higher likelihood of breast-conservation surgery. Baseline mammographic and MRI presentation of the main lesion, absence of associated microcalcifications, shape, posterior features, and absence of calcifications on ultrasound were significantly associated with ypT0. CR in mammography, ultrasound, or MRI after NCT was also related to ypT0. By multivariate analysis, independent predictors of ypT0 were the triple-negative subtype [Odds ratio (OR), 4.23; 95% confidence interval (CI), 1.11-16.09] and CR in MRI after NCT (OR, 5.23; 95% CI, 1.53-17.85). Stratified analysis by breast cancer subtype demonstrated that MRI well predicted ypT0 in all subtypes except the HER2-positive subtype. In particular, of 40 triple-negative subtypes, 22 showed CR in MRI and 21 (95.5%) were ypT0 after NCT.ConclusionAmong imaging modalities, breast MRI can potentially distinguish between ypT0 and ypTis after NCT, especially in patients with triple-negative breast cancer. This information can help clinicians evaluate tumor response to NCT and plan surgery for breast cancer patients of all subtypes except for those with HER2-enriched tumors after NCT.

Project description:BackgroundThe nuclear grading of ductal carcinoma in situ (DCIS) affects its clinical risk. The aim of this study was to investigate the possibility of predicting the nuclear grading of DCIS, by magnetic resonance imaging (MRI)-based radiomics features. And to develop a nomogram combining radiomics features and MRI semantic features to explore the potential role of MRI radiomic features in the assessment of DCIS nuclear grading.MethodsA total of 156 patients (159 lesions) with DCIS and DCIS with microinvasive (DCIS-MI) were enrolled in this retrospective study, with 112 lesions included in the training cohort and 47 lesions included in the validation cohort. Radiomics features were extracted from Dynamic contrast-enhanced MRI (DCE-MRI) phases 1st and 5th. After feature selection, radiomics signature was constructed and radiomics score (Rad-score) was calculated. Multivariate analysis was used to identify MRI semantic features that were significantly associated with DCIS nuclear grading and combined with Rad-score to construct a Nomogram. Receiver operating characteristic curves were used to evaluate the predictive performance of Rad-score and Nomogram, and decision curve analysis (DCA) was used to evaluate the clinical utility.ResultsIn multivariate analyses of MRI semantic features, larger tumor size and heterogeneous enhancement pattern were significantly associated with high-nuclear grade DCIS (HNG DCIS). In the training cohort, Nomogram had an area under curve (AUC) of 0.879 and Rad-score had an AUC of 0.828. Similarly, in the independent validation cohort, Nomogram had an AUC value of 0.828 and Rad-score had an AUC of 0.772. In both the training and validation cohorts, Nomogram had a significantly higher AUC value than Rad-score (P<0.05). DCA confirmed that Nomogram had a higher net clinical benefit.ConclusionsMRI-based radiomic features can be used as potential biomarkers for assessing nuclear grading of DCIS. The nomogram constructed by radiomic features combined with semantic features is feasible in discriminating non-HNG and HNG DCIS.

Project description:ImportanceThe use of magnetic resonance imaging (MRI) in pretreatment planning of ductal carcinoma in situ (DCIS) remains controversial. Understanding changes in short-term health-related quality of life associated with breast MRI would allow for a more complete comparative effectiveness assessment.ObjectiveTo assess whether there are changes in patient-reported quality of life associated with breast MRI among women diagnosed with DCIS.Design, setting, and participantsThis cohort study was a substudy of a nonrandomized clinical trial conducted at 75 participating US institutions from March 2015 to April 2016. Women recently diagnosed with unilateral DCIS who were eligible for wide local excision and had a diagnostic mammogram within 3 months of study registration were included. A total of 355 women met the eligibility criteria and underwent the study MRI. Data analysis was performed from June 3, 2020, to July 1, 2021.ExposuresParticipants underwent bilateral breast MRI within 30 days of study registration and before surgery. Information on patient-reported testing burden for breast MRI was collected after MRI and before surgery.Main outcomes and measuresThe primary outcome of this substudy was the patient-reported testing burden of breast MRI, measured by the Testing Morbidities Index (TMI) summated scale score. The TMI is a 7-item instrument that evaluates the temporary changes in quality of life associated with imaging before, during, and after the test (0 represents the worst possible, 100 the hypothetical ideal test experience).ResultsOf the 355 women who met the eligibility criteria, 244 (69%) completed both questionnaires and were included in this analysis. The median age was 59 years (range, 34-85 years). The mean MRI TMI summated scale score was 85.9 (95% CI, 84.6-87.3). Of the 244 women, 142 (58%) experienced at least some fear and anxiety before the examination, and 120 women (49%) experienced fear and anxiety during the examination. A total of 156 women (64%) experienced pain or discomfort during the examination. In multivariable analyses, greater test-related burden was associated with higher levels of cancer worry (regression coefficient, -2.75; SE, 0.94; P = .004).Conclusions and relevanceIn this cohort study, a clinically meaningful breast MRI testing burden among women with DCIS was revealed that was significantly associated with cancer worry. Understanding the potential quality-of-life reduction associated with MRI, especially when used in combination with mammography, may allow development of targeted interventions to improve the patient experience.

Project description:BackgroundThe following analysis explores clinicopathologic factors and the 12-gene Breast DCIS Score test result in order to better define an appropriate DCIS (ductal carcinoma in situ) population eligible for APBI (accelerated partial breast radiotherapy).MethodsThis exploratory analysis aimed to retrospectively measure the association between the 12-gene Oncotype DX Breast DCIS Score® assay (Redwood City, CA) and relevant clinicopathologic factors with locoregional recurrence in a pooled cohort of women treated with local excision and APBI on prospective phase II (NCT01185145) and phase III (NCT01185132) clinical trials. Univariable Cox proportional hazards regression was used to determine whether there was an association between local recurrence and DCIS Score result risk group (≥ 39 vs < 39) and clinicopathologic factors.ResultsThis analysis included 104 evaluable patients (n = 18 from NCT01185145 and n = 86 from NCT01185132). The median age was 60 years (range: 40-79). Seventy-nine percent of patients were postmenopausal. The median span of DCIS was 10 mm (range 2-45 mm). Two-thirds of the cohort presented with necrosis (71%). The distribution of DCIS Score® results ranged from 0 to 82, with 69% of patients having a DCIS Score result < 39. The median follow-up time was 8.2 years in NCT01185145 versus 3.0 years in NCT01185132. There were 6 local ipsilateral breast recurrences. DCIS Score result was significantly associated with local recurrence in univariable modeling, hazard ratio = 10.3 (95% CI 1.7, 198.4); p = 0.010. None of the clinicopathologic characteristics resulted in any significant association with locoregional recurrence.ConclusionThe Breast DCIS Score assay demonstrated risk stratification in this cohort of patients treated with local excision and APBI pooled from two clinical trials. These results are consistent with those recently published utilizing whole breast radiotherapy. Due to the small number of local recurrence events and limited follow-up time, further investigations are needed to confirm findings.

Project description:ObjectiveTo investigate whether support vector machine (SVM) trained with radiomics features based on breast magnetic resonance imaging (MRI) could predict the upgrade of ductal carcinoma in situ (DCIS) diagnosed by core needle biopsy (CNB) after surgical excision.Materials and methodsThis retrospective study included a total of 349 lesions from 346 female patients (mean age, 54 years) diagnosed with DCIS by CNB between January 2011 and December 2017. Based on histological confirmation after surgery, the patients were divided into pure (n = 198, 56.7%) and upgraded DCIS (n = 151, 43.3%). The entire dataset was randomly split to training (80%) and test sets (20%). Radiomics features were extracted from the intratumor region-of-interest, which was semi-automatically drawn by two radiologists, based on the first subtraction images from dynamic contrast-enhanced T1-weighted MRI. A least absolute shrinkage and selection operator (LASSO) was used for feature selection. A 4-fold cross validation was applied to the training set to determine the combination of features used to train SVM for classification between pure and upgraded DCIS. Sensitivity, specificity, accuracy, and area under the receiver-operating characteristic curve (AUC) were calculated to evaluate the model performance using the hold-out test set.ResultsThe model trained with 9 features (Energy, Skewness, Surface Area to Volume ratio, Gray Level Non Uniformity, Kurtosis, Dependence Variance, Maximum 2D diameter Column, Sphericity, and Large Area Emphasis) demonstrated the highest 4-fold mean validation accuracy and AUC of 0.724 (95% CI, 0.619-0.829) and 0.742 (0.623-0.860), respectively. Sensitivity, specificity, accuracy, and AUC using the test set were 0.733 (0.575-0.892) and 0.7 (0.558-0.842), 0.714 (0.608-0.820) and 0.767 (0.651-0.882), respectively.ConclusionOur study suggested that the combined radiomics and machine learning approach based on preoperative breast MRI may provide an assisting tool to predict the histologic upgrade of DCIS.

Project description:ObjectiveTo investigate the feasibility of radiomics in predicting molecular subtype of breast invasive ductal carcinoma (IDC) based on dynamic contrast enhancement magnetic resonance imaging (DCE-MRI).MethodsA total of 303 cases with pathologically confirmed IDC from January 2018 to March 2021 were enrolled in this study, including 223 cases from Fudan University Shanghai Cancer Center (training/test set) and 80 cases from Shaoxing Central Hospital (validation set). All the cases were classified as HR+/Luminal, HER2-enriched, and TNBC according to immunohistochemistry. DCE-MRI original images were treated by semi-automated segmentation to initially extract original and wavelet-transformed radiomic features. The extended logistic regression with least absolute shrinkage and selection operator (LASSO) penalty was applied to identify the optimal radiomic features, which were then used to establish predictive models combined with significant clinical risk factors. Receiver operating characteristic curve (ROC), calibration curve, and decision curve analysis were adopted to evaluate the effectiveness and clinical benefit of the models established.ResultsOf the 223 cases from Fudan University Shanghai Cancer Center, HR+/Luminal cancers were diagnosed in 116 cases (52.02%), HER2-enriched in 71 cases (31.84%), and TNBC in 36 cases (16.14%). Based on the training set, 788 radiomic features were extracted in total and 8 optimal features were further identified, including 2 first-order features, 1 gray-level run length matrix (GLRLM), 4 gray-level co-occurrence matrices (GLCM), and 1 3D shape feature. Three multi-class classification models were constructed by extended logistic regression: clinical model (age, menopause, tumor location, Ki-67, histological grade, and lymph node metastasis), radiomic model, and combined model. The macro-average areas under the ROC curve (macro-AUC) for the three models were 0.71, 0.81, and 0.84 in the training set, 0.73, 0.81, and 0.84 in the test set, and 0.76, 0.82, and 0.83 in the validation set, respectively.ConclusionThe DCE-MRI-based radiomic features are significant biomarkers for distinguishing molecular subtypes of breast cancer noninvasively. Notably, the classification performance could be improved with the fusion analysis of multi-modal features.

Dataset Information

Association of Magnetic Resonance Imaging and a 12-Gene Expression Assay With Breast Ductal Carcinoma In Situ Treatment.

Publications

Association of Magnetic Resonance Imaging and a 12-Gene Expression Assay With Breast Ductal Carcinoma In Situ Treatment.

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