Test-Retest Data for the Assessment of Breast MRI Radiomic Feature Repeatability.

BACKGROUND: Radiomic features extracted from breast MRI have potential for diagnostic, prognostic, and predictive purposes. However, before they can be used as biomarkers in clinical decision support systems, features need to be repeatable and reproducible. OBJECTIVE: Identify repeatable radiomics features within breast tissue on prospectively collected MRI exams through multiple test-retest measurements. STUDY TYPE: Prospective. POPULATION: 11 healthy female volunteers. FIELD STRENGTH/SEQUENCE: 1.5 T; MRI exams, comprising T2-weighted turbo spin-echo (T2W) sequence, native T1-weighted turbo gradient-echo (T1W) sequence, diffusion-weighted imaging (DWI) sequence using b-values 0/150/800, and corresponding derived ADC maps. ASSESSMENT: 18 MRI exams (three test-retest settings, repeated on 2 days) per healthy volunteer were examined on an identical scanner using a fixed clinical breast protocol. For each scan, 91 features were extracted from the 3D manually segmented right breast using Pyradiomics, before and after image preprocessing. Image preprocessing consisted of 1) bias field correction (BFC); 2) z-score normalization with and without BFC; 3) grayscale discretization using 32 and 64 bins with and without BFC; and 4) z-score normalization + grayscale discretization using 32 and 64 bins with and without BFC. STATISTICAL TESTS: Features' repeatability was assessed using concordance correlation coefficient(CCC) for each pair, i.e. each MRI was compared to each of the remaining 17 MRI with a cut-off value of CCC > 0.90. RESULTS: Images without preprocessing produced the highest number of repeatable features for both T1W sequence and ADC maps with 15 of 91 (16.5%) and 8 of 91 (8.8%) repeatable features, respectively. Preprocessed images produced between 4 of 91 (4.4%) and 14 of 91 (15.4%), and 6 of 91 (6.6%) and 7 of 91 (7.7%) repeatable features, respectively for T1W and ADC maps. Z-score normalization produced highest number of repeatable features, 26 of 91 (28.6%) in T2W sequences, in these images, no preprocessing produced 11 of 91 (12.1%) repeatable features. DATA CONCLUSION: Radiomic features extracted from T1W, T2W sequences and ADC maps from breast MRI exams showed a varying number of repeatable features, depending on the sequence. Effects of different preprocessing procedures on repeatability of features were different for each sequence. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY STAGE: 1.

Reducing Seroma Formation and Its Sequelae After Mastectomy by Closure of the Dead Space: A Multi-center, Double-Blind Randomized Controlled Trial (SAM-Trial).

BACKGROUND: Seroma is a common complication after mastectomy, with an incidence of 3% to 85%. Seroma is associated with pain, delayed wound healing, and additional outpatient clinic visits, leading potentially to repeated seroma aspiration or even surgical interventions. This study aimed to assess the effect of flap fixation using sutures or tissue glue in preventing seroma formation and its sequelae. METHODS: Between June 2014 and July 2018, 339 patients with an indication for mastectomy or modified radical mastectomy were enrolled in this randomized controlled trial in the Netherlands. Patients were randomly allocated to one of the three following arms: conventional wound closure (CON, n = 115), flap fixation using sutures (FFS, n = 111) or flap fixation using tissue glue (FFG, n = 113). The primary outcome was the need for seroma aspiration. The secondary outcomes were additional outpatient department visits, surgical-site infection, shoulder function and mobility, cosmesis, skin-dimpling, and postoperative pain scores. RESULTS: Flap fixation after mastectomy leads to fewer seroma aspirations than conventional wound closure (CON 17.5% vs FFS 7.3% vs FFG 10.8%; p = 0.057), with a significant difference between flap fixation with sutures and conventional wound closure (odds ratio [OR], 0.37; 95% confidence interval [CI], 0.16-0.89; p = 0.025). Flap fixation has no significant negative effect on surgical-site infections, shoulder function and mobility, cosmesis, skin-dimpling, or postoperative pain. CONCLUSION: Flap fixation using sutures leads to a significant reduction in aspirations of post-mastectomy seromas. The authors strongly advise surgeons to use sutures for flap fixation in patients undergoing mastectomy. (ClinicalTrials.gov no. NCT03305757). PREREGISTRATION: The trial was registered after enrollment of the first participant. However, no specific explanation exists for this except that through the years more importance has been given to central trial registration. Our research team can ensure that after enrollment of the first participant, no changes were made to the trial, analysis plan, and/or study design.

Risk of Positive Sentinel Lymph Node After Neoadjuvant Systemic Therapy in Clinically Node-Negative Breast Cancer: Implications for Postmastectomy Radiation Therapy and Immediate Breast Reconstruction.

BACKGROUND: Residual axillary lymph node involvement after neoadjuvant systemic therapy (NST) is the determining factor for postmastectomy radiation therapy (PMRT). Preoperative identification of patients needing PMRT is essential to enable shared decision-making when choosing the optimal timing of breast reconstruction. We determined the risk of positive sentinel lymph node (SLN) after NST in clinically node-negative (cN0) breast cancer. METHODS: All cT1-3N0 patients treated with NST followed by mastectomy and SLNB between 2010 and 2016 were identified from the Netherlands Cancer Registry. Rate of positive SLN for different breast cancer subtypes was determined. Logistic regression analysis was performed to determine correlated clinicopathological variables with positive SLN. RESULTS: In total 788 patients were included, of whom 25.0% (197/788) had positive SLN. cT1-3N0 ER+HER2+, cT1-3N0 ER-HER2+ , and cT1-2N0 triple-negative patients had the lowest rate of positive SLN: 7.2-11.5%, 0-6.3%, and 2.9-6.2%, respectively. cT1-3N0 ER+HER2- and cT3N0 triple-negative patients had the highest rate of positive SLN: 23.8-41.7% and 30.4%, respectively. Multivariable regression analysis showed that cT2 (odds ratio [OR] 1.93; 95% confidence interval [CI] 1.01-3.96), cT3 (OR 2.56; 95% CI 1.30-5.38), grade 3 (OR 0.44; 95% CI 0.21-0.91), and ER+HER2- subtype (OR 3.94; 95% CI 1.77-8.74) were correlated with positive SLN. CONCLUSIONS: In cT1-3N0 ER+HER2+, cT1-3N0 ER-HER2+, and cT1-2N0 triple-negative patients treated with NST, immediate reconstruction can be considered an acceptable option due to low risk of positive SLN. In cT1-3N0 ER+HER2- and cT3N0 triple-negative patients treated with NST, risks and benefits of immediate reconstruction should be discussed with patients due to the relatively high risk of positive SLN.

Economic evaluation of flap fixation techniques after mastectomy: Results of a double-blind randomized controlled trial (SAM-trial).

BACKGROUND: An economic evaluation was performed alongside an RCT investigating flap fixation in reducing seroma formation after mastectomy. The evaluation focused on the first year following mastectomy and assessed cost-effectiveness from a health care and societal perspective. METHODS: The economic evaluation was conducted between 2014 and 2018 in four Dutch breast clinics. Patients with an indication for mastectomy or modified radical mastectomy were randomly assigned to: conventional closure (CON), flap fixation with sutures (FFS) or flap fixation with tissue glue (FFG). Health care costs, patient and family costs and costs due to productivity losses were assessed. Outcomes were expressed in incremental cost-effectiveness ratios (ICERs): the incremental cost per quality-adjusted life year (QALY). Bootstrapping techniques, sensitivity and secondary analyses were employed to address uncertainty. RESULTS: The FFS-group yielded most QALYs (0.810; 95%-CI 0.755-0.856), but also incurred the highest mean costs at twelve months (€10.416; 95%-CI 8.231-12.930). CON was the next best alternative with 0.794 QALYs (95%-CI 0.733-0.841) and mean annual costs of €10.051 (95%-CI 8.255-12.044). FFG incurred fewer QALYs and higher costs, when compared to the CON group. The ICER of FFS compared to CON was €22.813/QALY. Applying a willingness to pay threshold in the Netherlands of €20.000/QALY, the probability that FFS was cost-effective was 42%, compared to 37% and 21% for CON and FFG, respectively. CONCLUSION: The cost-effectiveness of FFS following mastectomy, versus CON and FFG, is uncertain from a societal perspective. Yet, from a health care and hospital perspective FFS is likely to be the most cost-effective intervention.

MRI-based radiomics in breast cancer: feature robustness with respect to inter-observer segmentation variability.

Radiomics is an emerging field using the extraction of quantitative features from medical images for tissue characterization. While MRI-based radiomics is still at an early stage, it showed some promising results in studies focusing on breast cancer patients in improving diagnoses and therapy response assessment. Nevertheless, the use of radiomics raises a number of issues regarding feature quantification and robustness. Therefore, our study aim was to determine the robustness of radiomics features extracted by two commonly used radiomics software with respect to variability in manual breast tumor segmentation on MRI. A total of 129 histologically confirmed breast tumors were segmented manually in three dimensions on the first post-contrast T1-weighted MR exam by four observers: a dedicated breast radiologist, a resident, a Ph.D. candidate, and a medical student. Robust features were assessed using the intraclass correlation coefficient (ICC > 0.9). The inter-observer variability was evaluated by the volumetric Dice Similarity Coefficient (DSC). The mean DSC for all tumors was 0.81 (range 0.19-0.96), indicating a good spatial overlap of the segmentations based on observers of varying expertise. In total, 41.6% (552/1328) and 32.8% (273/833) of all RadiomiX and Pyradiomics features, respectively, were identified as robust and were independent of inter-observer manual segmentation variability.

Exploring breast cancer response prediction to neoadjuvant systemic therapy using MRI-based radiomics: A systematic review.

PURPOSE: MRI-based tumor response prediction to neoadjuvant systemic therapy (NST) in breast cancer patients is increasingly being studied using radiomics with outcomes that appear to be promising. The aim of this study is to systematically review the current literature and reflect on its quality. METHODS: PubMed and EMBASE databases were systematically searched for studies investigating MRI-based radiomics for tumor response prediction. Abstracts were screened by two reviewers independently. The quality of the radiomics workflow of eligible studies was assessed using the Radiomics Quality Score (RQS). An overview of the methodologies used in steps of the radiomics workflow and current results are presented. RESULTS: Sixteen studies were included with cohort sizes ranging from 35 to 414 patients. The RQS scores varied from 0 % to 41.2 %. Methodologies in the radiomics workflow varied greatly, especially region of interest segmentation, features selection, and model development with heterogeneous outcomes as a result. Seven studies applied univariate analysis and nine studies applied multivariate analysis. Most studies performed their analysis on the pretreatment dynamic contrast-enhanced T1-weighted sequence. Entropy was the best performing individual feature with AUC values ranging from 0.83 to 0.85. The best performing multivariate prediction model, based on logistic regression analysis, scored a validation AUC of 0.94. CONCLUSION: This systematic review revealed large methodological heterogeneity for each step of the MRI-based radiomics workflow, consequently, the (overall promising) results are difficult to compare. Consensus for standardization of MRI-based radiomics workflow for tumor response prediction to NST in breast cancer patients is needed to further improve research.