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Objectives: The purpose of our study was to assess the chondrogenic potential and the MR signal effects of GadofluorineM-Cy labeled matrix associated stem cell implants (MASI) in pig knee specimen. Materials and Methods: Human mesenchymal stem cells (hMSCs

BACKGROUND AND RESEARCH OBJECTIVE: The health benefits of cardiac rehabilitation (CR) for women living with heart disease are well documented, yet women remain underrepresented in traditionally structured CR programs. This health service delivery gap has been attributed to a number of sex-related factors experienced by women, including lower rates of physician referral, travel-related barriers, competing work and caregiving responsibilities, greater cardiovascular disease severity, and number of comorbid health conditions. Whether a program specifically designed for women is able to address these barriers and facilitate women's participation is a question that has seldom been explored in the CR literature. As part of a larger study exploring whether 6 predefined principles of women's health (empowerment of women, accessible programs, broad definition of health care, high-quality of care, collaborative planning, and innovative and creative approaches) are reflected in the practices of the Women's Cardiovascular Health Initiative (WCHI) (a comprehensive CR and primary prevention program designed for women), the objective of this analysis was to explore how the principle of 'accessible programs' is experienced by women participating in the WCHI. PARTICIPANTS AND METHOD: Fourteen women previously enrolled in the WCHI program participated in a single, in-person qualitative interview. Transcripts were analyzed using a constant-comparative approach to identify relevant themes related to program accessibility. RESULTS: Key themes identified included participants' experiences with acquiring physician referral, negotiating transportation issues, and navigating program schedules. Women discussed how peer support and staff members' willingness to address their health-related concerns facilitated their participation. CONCLUSION: While a women-centered CR/primary prevention program may facilitate and encourage women's participation by providing flexible program schedules as well as peer and professional support, efforts are still required to address persistent barriers for women related to physician referral and transportation to programs. [ABSTRACT FROM AUTHOR]

Adaptability, sensitivity, resolution and non-invasiveness are the attributes that have contributed to the longstanding use of light as an investigational tool and form the basis of optical imaging (OI). OI, which encompasses numerous techniques and methods, is rapid (<5 min), inexpensive, noninvasive, nontoxic (no radiation) and has molecular (single-cell) sensitivity, which is equal to that of conventional nuclear imaging and several orders of magnitude greater than MRI. This article provides a comprehensive overview of emerging applications of OI-based techniques for in vivo monitoring of new stem cell-based therapies. Different fluorochromes for cell labeling, labeling methods and OI-based cell-tracking techniques will be reviewed with respect to their technical principles, current applications and aims for clinical translation. Advantages and limitations of these new OI-based cell-tracking techniques will be discussed. Non-invasive mapping of cells labeled with fluorochromes or OI marker genes has the potential to evolve further within the clinical realm. [ABSTRACT FROM AUTHOR]

Rationale and Objectives: To develop and evaluate an AI algorithm that detects breast cancer in MRI scans up to one year before radiologists typically identify it, potentially enhancing early detection in high-risk women., Materials and Methods: A convolutional neural network (CNN) AI model, pre-trained on breast MRI data, was fine-tuned using a retrospective dataset of 3029 MRI scans from 910 patients. These contained 115 cancers that were diagnosed within one year of a negative MRI. The model aimed to identify these cancers, with the goal of predicting cancer development up to one year in advance. The network was fine-tuned and tested with 10-fold cross-validation. Mean age of patients was 52 years (range, 18-88 years), with average follow-up of 4.3 years (range 1-12 years)., Results: The AI detected cancers one year earlier with an area under the ROC curve of 0.72 (0.67-0.76). Retrospective analysis by a radiologist of the top 10% highest risk MRIs as ranked by the AI could have increased early detection by up to 30%. (35/115, CI:22.2-39.7%, 30% sensitivity). A radiologist identified a visual correlate to biopsy-proven cancers in 83 of prior-year MRIs (83/115, CI: 62.1-79.4%). The AI algorithm identified the anatomic region where cancer would be detected in 66 cases (66/115, CI:47.8-66.5%); with both agreeing in 54 cases (54/115, CI:%37.5-56.4%)., Conclusion: This novel AI-aided re-evaluation of "benign" breasts shows promise for improving early breast cancer detection with MRI. As datasets grow and image quality improves, this approach is expected to become even more impactful., Competing Interests: Declaration of Competing Interest All authors declare no financial or non-financial competing interests., (Copyright © 2024 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.)

This work aims to perform a cross-site validation of automated segmentation for breast cancers in MRI and to compare the performance to radiologists. A three-dimensional (3D) U-Net was trained to segment cancers in dynamic contrast-enhanced axial MRIs using a large dataset from Site 1 (n = 15,266; 449 malignant and 14,817 benign). Performance was validated on site-specific test data from this and two additional sites, and common publicly available testing data. Four radiologists from each of the three clinical sites provided two-dimensional (2D) segmentations as ground truth. Segmentation performance did not differ between the network and radiologists on the test data from Sites 1 and 2 or the common public data (median Dice score Site 1, network 0.86 vs. radiologist 0.85, n = 114; Site 2, 0.91 vs. 0.91, n = 50; common: 0.93 vs. 0.90). For Site 3, an affine input layer was fine-tuned using segmentation labels, resulting in comparable performance between the network and radiologist (0.88 vs. 0.89, n = 42). Radiologist performance differed on the common test data, and the network numerically outperformed 11 of the 12 radiologists (median Dice: 0.85-0.94, n = 20). In conclusion, a deep network with a novel supervised harmonization technique matches radiologists' performance in MRI tumor segmentation across clinical sites. We make code and weights publicly available to promote reproducible AI in radiology., (© 2024. The Author(s) under exclusive licence to Society for Imaging Informatics in Medicine.)

Rozanolixizumab is a humanized anti-neonatal Fc receptor (FcRn) monoclonal antibody (mAb) of the immunoglobulin G4 (IgG4) sub-class, currently in clinical development for the treatment of IgG autoantibody-driven diseases. This format is frequently used for therapeutic mAbs due to its intrinsic lower affinity for Fc gamma receptors (FcγR) and lack of C1q engagement. However, with growing evidence suggesting that no Fc-containing agent is truly "silent" in this respect, we explored the engagement of FcγRs and potential functional consequences with rozanolixizumab. In the study presented here, rozanolixizumab was shown to bind to FcγRs in both protein-protein and cell-based assays, and the kinetic data were broadly as expected based on published data for an IgG4 mAb. Rozanolixizumab was also able to mediate antibody bipolar bridging (ABB), a phenomenon that led to a reduction of labeled FcγRI from the surface of human macrophages in an FcRn-dependent manner. However, the presence of exogenous human IgG, even at low concentrations, was able to prevent both binding and ABB events. Furthermore, data from in vitro experiments using relevant human cell types that express both FcRn and FcγRI indicated no evidence for functional sequelae in relation to cellular activation events (e.g., intracellular signaling, cytokine production) upon either FcRn or FcγR binding of rozanolixizumab. These data raise important questions about whether therapeutic antagonistic mAbs like rozanolixizumab would necessarily engage FcγRs at doses typically administered to patients in the clinic, and hence challenge the relevance and interpretation of in vitro assays performed in the absence of competing IgG.

Objectives: The aim of the study is to develop and evaluate the performance of a deep learning (DL) model to triage breast magnetic resonance imaging (MRI) findings in high-risk patients without missing any cancers., Materials and Methods: In this retrospective study, 16,535 consecutive contrast-enhanced MRIs performed in 8354 women from January 2013 to January 2019 were collected. From 3 New York imaging sites, 14,768 MRIs were used for the training and validation data set, and 80 randomly selected MRIs were used for a reader study test data set. From 3 New Jersey imaging sites, 1687 MRIs (1441 screening MRIs and 246 MRIs performed in recently diagnosed breast cancer patients) were used for an external validation data set. The DL model was trained to classify maximum intensity projection images as "extremely low suspicion" or "possibly suspicious." Deep learning model evaluation (workload reduction, sensitivity, specificity) was performed on the external validation data set, using a histopathology reference standard. A reader study was performed to compare DL model performance to fellowship-trained breast imaging radiologists., Results: In the external validation data set, the DL model triaged 159/1441 of screening MRIs as "extremely low suspicion" without missing a single cancer, yielding a workload reduction of 11%, a specificity of 11.5%, and a sensitivity of 100%. The model correctly triaged 246/246 (100% sensitivity) of MRIs in recently diagnosed patients as "possibly suspicious." In the reader study, 2 readers classified MRIs with a specificity of 93.62% and 91.49%, respectively, and missed 0 and 1 cancer, respectively. On the other hand, the DL model classified MRIs with a specificity of 19.15% and missed 0 cancers, highlighting its potential use not as an independent reader but as a triage tool., Conclusions: Our automated DL model triages a subset of screening breast MRIs as "extremely low suspicion" without misclassifying any cancer cases. This tool may be used to reduce workload in standalone mode, to shunt low suspicion cases to designated radiologists or to the end of the workday, or to serve as base model for other downstream AI tools., Competing Interests: Conflicts of interest and sources of funding: K.P. received payment for activities not related to the present article including lectures and service on speakers' bureaus and for travel/accommodations/meeting expenses unrelated to activities listed from the European Society of Breast Imaging (MRI educational course, annual scientific meeting), the IDKD 2019 (educational course), GBCC 10, TIBCS 2021, Olea Medical, Vara Merantix Healthcare GmbH, AURA Health Technologies GmbH, and Siemens Healthineers. She is also the Principal Investigator of a research project sponsored by Grail Inc, and a consultant for Merantix Healthcare, Siemens Healthineers, and Genentech, Inc. The other authors of this manuscript declare no conflicts of interest., (Copyright © 2023 Wolters Kluwer Health, Inc. All rights reserved.)

Purpose: Mammography, breast ultrasound (US), and US-guided breast biopsy are essential services for breast cancer early detection and diagnosis. This study undertook a comprehensive evaluation to determine population-level access to these services for breast cancer early detection and diagnosis in Nigeria using a previously validated geographic information system (GIS) model., Methods: A comprehensive list of public and private facilities offering mammography, breast US, and US-guided breast biopsy was compiled using publicly available facility data and a survey administered nationally to Nigerian radiologists. All facilities were geolocated. A cost-distance model using open-source population density (GeoData Institute) and road network data (OpenStreetMap) was used to estimate population-level travel time to the nearest facility for mammography, breast US, and US-guided biopsy using GIS software (ArcMAP)., Results: In total, 1,336 facilities in Nigeria provide breast US, of which 47.8% (639 of 1,336) are public facilities, and 218 provide mammography, of which 45.4% (99 of 218) are public facilities. Of the facilities that provide breast US, only 2.5% (33 of 1,336) also provide US-guided breast biopsy. At the national level, 83.1% have access to either US or mammography and 61.7% have access to US-guided breast biopsy within 120 minutes of a continuous one-way travel. There are differences in access to mammography (64.8% v 80.6% with access at 120 minutes) and US-guided breast biopsy (49.0% v 77.1% with access at 120 minutes) between the northern and southern Nigeria and between geopolitical zones., Conclusion: To our knowledge, this is the first comprehensive evaluation of breast cancer detection and diagnostic services in Nigeria, which demonstrates geospatial inequalities in access to mammography and US-guided biopsy. Targeted investment is needed to improve access to these essential cancer care services in the northern region and the North East geopolitical zone.

Background: In Nigeria, breast cancer incidence is rising, late presentation is common, and outcomes are poor. Patient-related factors such as lack of awareness and misperceptions in addition to health system deficiencies such as lack of a clearly defined framework for breast cancer screening and referral are some of the major drivers of this poor outlook. Guidelines for breast cancer screening in high-income countries have limited applicability in low-middle-income countries, hence the need for innovative, resource-compatible strategies to combat the negative trend. This manuscript presents our study protocol which aims to evaluate the impact of a novel breast cancer early detection program developed to address delayed presentation and lack of access to diagnostic and treatment facilities in South-West Nigeria. This entails the use of mobile technology (innovative handheld iBreast Exam [iBE] device, mobile breast ultrasound, and mobile mammography) and patient navigation as interventions at the community level., Methods: The study (ClinicalTrials.gov identifier: NCT05321823) will adopt a randomized two group clinical trial design with one local government area (LGA) serving as an intervention arm and another serving as the control. Both LGAs will receive breast cancer awareness education but only one will receive the interventions. In the intervention arm, asymptomatic (40-70 years) and symptomatic (30-70 years) women will be invited for breast evaluation which will be performed by trained Community Health Nurses using Clinical Breast Exam (CBE), and iBE. Those with positive findings will proceed to imaging using mobile mammography and ultrasound brought to the LGA every month. Symptomatic women with negative findings on CBE and iBE will be scheduled for repeat clinical evaluation on a short-term basis (one month). The Radiologist will obtain core needle biopsies as indicated and transfer them for prompt pathological assessment. Women presenting to the Primary Healthcare Centers in the control LGA will be referred directly to Obafemi Awolowo University Teaching Hospitals Complex as per the current standard of care. Records of all breast cancer cases seen in the two LGAs during the study period will be obtained. The program metrics will include screening participation rate, cancer detection rate, stage at diagnosis, and timeline from detection to initiation of treatment. The stage at diagnosis and timeline from detection to treatment compared between the two LGAs will be used to assess the impact of the intervention. The study is proposed for 2 years; however, a descriptive analysis will be carried out at 1.5 years to evaluate the retention of the study participants., Study Significance: It is anticipated that this study will provide vital data to support wider breast cancer screening efforts in Nigeria., Competing Interests: The authors have declared that no competing interests exist., (Copyright: This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.)

Despite national and international guidelines, asthma is frequently misdiagnosed, control is poor and unnecessary deaths are far too common. Large scale asthma management programme such as that undertaken in Finland, can improve asthma outcomes. A primary care asthma management quality improvement programme was developed with the support of the British Lung Foundation (now Asthma + Lung UK) and Optimum Patient Care (OPC) Limited. It was delivered and cascaded to all relevant staff at participating practices in three Clinical Commissioning Groups. The programme focussed on improving diagnostic accuracy, management of risk and control, patient self-management and overall asthma control. Patient data were extracted by OPC for the 12 months before (baseline) and after (outcome) the intervention. In the three CCGs, 68 GP practices participated in the programme. Uptake from practices was higher in the CCG that included asthma in its incentivised quality improvement programme. Asthma outcome data were successfully extracted from 64 practices caring for 673,593 patients. Primary outcome (Royal College of Physicians Three Questions [RCP3Q]) data were available in both the baseline and outcome periods for 10,328 patients in whom good asthma control (RCP3Q = 0) increased from 36.0% to 39.2% (p < 0.001) after the intervention. The odds ratio of reporting good asthma control following the intervention was 1.15 (95% CI 1.09-1.22), p < 0.0001. This asthma management programme produced modest but highly statistically significant improvements in asthma outcomes. Key lessons learnt from this small-scale implementation will enable the methodology to be improved to maximise benefit in a larger scale role out., (© 2023. The Author(s).)

Response to immunotherapy across multiple cancer types is approximately 25%, with some tumor types showing increased response rates compared to others (i.e. response rates in melanoma and non-small cell lung cancer (NSCLC) are typically 30-60%). Patients whose tumors are resistant to immunotherapy often lack high levels of pre-existing inflammation in the tumor microenvironment. Increased tumor glycolysis, acting through glucose deprivation and lactic acid accumulation, has been shown to have pleiotropic immune suppressive effects using in-vitro and in-vivo models of disease. To determine whether the immune suppressive effect of tumor glycolysis is observed across human solid tumors, we analyzed glycolytic and immune gene expression patterns in multiple solid malignancies. We found that increased expression of a glycolytic signature was associated with decreased immune infiltration and a more aggressive disease across multiple tumor types. Radiologic and pathologic analysis of untreated estrogen receptor (ER)-negative breast cancers corroborated these observations, and demonstrated that protein expression of glycolytic enzymes correlates positively with glucose uptake and negatively with infiltration of CD3 + and CD8 + lymphocytes. This study reveals an inverse relationship between tumor glycolysis and immune infiltration in a large cohort of multiple solid tumor types., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Cohen, Pareja, Socci, Shen, Doane, Schwartz, Khanin, Morris, Sutton and Blasberg.)

Background: Background parenchymal enhancement (BPE) is assessed on breast MRI reports as mandated by the Breast Imaging Reporting and Data System (BI-RADS) but is prone to inter and intrareader variation. Semiautomated and fully automated BPE assessment tools have been developed but none has surpassed radiologist BPE designations., Purpose: To develop a deep learning model for automated BPE classification and to compare its performance with current standard-of-care radiology report BPE designations., Study Type: Retrospective., Population: Consecutive high-risk patients (i.e. &gt;20% lifetime risk of breast cancer) who underwent contrast-enhanced screening breast MRI from October 2013 to January 2019. The study included 5224 breast MRIs, divided into 3998 training, 444 validation, and 782 testing exams. On radiology reports, 1286 exams were categorized as high BPE (i.e., marked or moderate) and 3938 as low BPE (i.e., mild or minimal)., Field Strength/sequence: A 1.5 T or 3 T system; one precontrast and three postcontrast phases of fat-saturated T1-weighted dynamic contrast-enhanced imaging., Assessment: Breast MRIs were used to develop two deep learning models (Slab artificial intelligence (AI); maximum intensity projection [MIP] AI) for BPE categorization using radiology report BPE labels. Models were tested on a heldout test sets using radiology report BPE and three-reader averaged consensus as the reference standards., Statistical Tests: Model performance was assessed using receiver operating characteristic curve analysis. Associations between high BPE and BI-RADS assessments were evaluated using McNemar's chi-square test (α* = 0.025)., Results: The Slab AI model significantly outperformed the MIP AI model across the full test set (area under the curve of 0.84 vs. 0.79) using the radiology report reference standard. Using three-reader consensus BPE labels reference standard, our AI model significantly outperformed radiology report BPE labels. Finally, the AI model was significantly more likely than the radiologist to assign "high BPE" to suspicious breast MRIs and significantly less likely than the radiologist to assign "high BPE" to negative breast MRIs., Data Conclusion: Fully automated BPE assessments for breast MRIs could be more accurate than BPE assessments from radiology reports., Level of Evidence: 4 TECHNICAL EFFICACY STAGE: 3., (© 2022 International Society for Magnetic Resonance in Medicine.)

Purpose: The Mayo-Baylor RIGHT 10K Study enabled preemptive, sequence-based pharmacogenomics (PGx)-driven drug prescribing practices in routine clinical care within a large cohort. We also generated the tools and resources necessary for clinical PGx implementation and identified challenges that need to be overcome. Furthermore, we measured the frequency of both common genetic variation for which clinical guidelines already exist and rare variation that could be detected by DNA sequencing, rather than genotyping., Methods: Targeted oligonucleotide-capture sequencing of 77 pharmacogenes was performed using DNA from 10,077 consented Mayo Clinic Biobank volunteers. The resulting predicted drug response-related phenotypes for 13 genes, including CYP2D6 and HLA, affecting 21 drug-gene pairs, were deposited preemptively in the Mayo electronic health record., Results: For the 13 pharmacogenes of interest, the genomes of 79% of participants carried clinically actionable variants in 3 or more genes, and DNA sequencing identified an average of 3.3 additional conservatively predicted deleterious variants that would not have been evident using genotyping., Conclusion: Implementation of preemptive rather than reactive and sequence-based rather than genotype-based PGx prescribing revealed nearly universal patient applicability and required integrated institution-wide resources to fully realize individualized drug therapy and to show more efficient use of health care resources., Competing Interests: Conflict of Interest Liewei Wang, John Logan Black III, and Richard M. Weinshilboum are cofounders of and stockholders in OneOme, LLC, which was used only to return results to the study participants. Additionally, John Logan Black III and Mayo Clinic Ventures have applied for a patent on the CNVAR software cited in this study as well as the methodology upon which the software is based. All other authors declare no conflicts of interest., (Copyright © 2022 American College of Medical Genetics and Genomics. Published by Elsevier Inc. All rights reserved.)

Background: Prognostic information is key to shared decision-making, particularly in life-limiting illness like advanced chronic kidney disease (CKD)., Objective: To understand the prognostic information preferences expressed by older patients with CKD., Design and Participants: Qualitative study of 28 consecutively enrolled patients over 65 years of age with non-dialysis dependent CKD stages 3b-5, receiving care in a multi-disciplinary CKD clinic., Approach: Semi-structured telephone or in-person interviews to explore patients' preference for and perceived value of individualized prognostic information. Interviews were analyzed using inductive content analysis., Key Results: We completed interviews with 28 patients (77.7 ± SD 6.8 years, 69% men). Patients varied in their preference for prognostic information and more were interested in their risk of progression to end-stage kidney disease (ESKD) than in life expectancy. Many conflated ESKD risk with risk of death, perceiving a binary choice between dialysis and quick decline and death. Patients expressed that prognostic information would allow them to plan, take care of important business, and think about their treatment options. Patients were accepting of prognostic uncertainty and imagined leveraging it to nurture hope or motivate them to better manage risk factors. They endorsed the desire to receive prognosis of life expectancy even though it may be hard to accept or difficult to talk about but worried it could create helplessness for other patients in their situation., Conclusion: Most, but not all, patients were interested in prognostic information and could see its value in motivating behavior change and allowing planning. Some patients expressed concern that information on life expectancy might cause depression and hopelessness. Therefore, prognostic information is most appropriate as part of a clinical conversation that fosters shared decision-making and helps patients consider treatment risks, benefits, and burdens in context of their lives., (© 2021. Society of General Internal Medicine.)

Purpose: To develop a deep network architecture that would achieve fully automated radiologist-level segmentation of cancers at breast MRI., Materials and Methods: In this retrospective study, 38 229 examinations (composed of 64 063 individual breast scans from 14 475 patients) were performed in female patients (age range, 12-94 years; mean age, 52 years ± 10 [standard deviation]) who presented between 2002 and 2014 at a single clinical site. A total of 2555 breast cancers were selected that had been segmented on two-dimensional (2D) images by radiologists, as well as 60 108 benign breasts that served as examples of noncancerous tissue; all these were used for model training. For testing, an additional 250 breast cancers were segmented independently on 2D images by four radiologists. Authors selected among several three-dimensional (3D) deep convolutional neural network architectures, input modalities, and harmonization methods. The outcome measure was the Dice score for 2D segmentation, which was compared between the network and radiologists by using the Wilcoxon signed rank test and the two one-sided test procedure., Results: The highest-performing network on the training set was a 3D U-Net with dynamic contrast-enhanced MRI as input and with intensity normalized for each examination. In the test set, the median Dice score of this network was 0.77 (interquartile range, 0.26). The performance of the network was equivalent to that of the radiologists (two one-sided test procedures with radiologist performance of 0.69-0.84 as equivalence bounds, P < .001 for both; n = 250)., Conclusion: When trained on a sufficiently large dataset, the developed 3D U-Net performed as well as fellowship-trained radiologists in detailed 2D segmentation of breast cancers at routine clinical MRI. Keywords: MRI, Breast, Segmentation, Supervised Learning, Convolutional Neural Network (CNN), Deep Learning Algorithms, Machine Learning AlgorithmsPublished under a CC BY 4.0 license. Supplemental material is available for this article., Competing Interests: Disclosures of Conflicts of Interest: L.H. Grant from NIBIB and NIMH through the NIH BRAIN Initiative (R01 EB02157); consulting fee from City College of New York. Y.H. Consulting fee from City College of New York. S.L. No relevant relationships. C.R.S. No relevant relationships. R.L.G. No relevant relationships. I.D.N. Grant from Alfonso Martín Escudero Foundation. A.G.V.B. No relevant relationships. N.O. No relevant relationships. E.S.K. No relevant relationships. D.L. No relevant relationships. D.A. Consulting fee AEAD850301RG4. S.E.W. RSNA Research and Education Foundation grant no. RF1905 (content is solely the responsibility of the authors and does not necessarily represent the official views of the RSNA R&E Foundation). M.H. No relevant relationships. D.F.M. No relevant relationships. K.P. Funded in part through the NIH/NCI Cancer Center Support Grant P30 CA008748 and the Breast Cancer Research Foundation; ongoing research grants include Digital Hybrid Breast PET/MRI for Enhanced Diagnosis of Breast Cancer (HYPMED) H2020 - Research and Innovation Framework Programme PHC-11-2015 #667211-2, A Body Scan for Cancer Detection using Quantum Technology (CANCERSCAN) H2020-FETOPEN-2018-2019-2020-01 # 828978, Multiparametric 18F-Fluoroestradiol PET/MRI coupled with Radiomics Analysis and Machine Learning for Prediction and Assessment of Response to Neoadjuvant Endocrine Therapy in Patients with Hormone Receptor+/HER2− Invasive Breast Cancer Jubiläumsfonds of the Austrian National Bank # Nr: 18207, Deciphering breast cancer heterogeneity and tackling the hypoxic tumor microenvironment challenge with PET/MRI, MSI and radiomics The Vienna Science and Technology Fund LS19-046, MSKCC 2020 Molecularly Targeted Intra-Operative Imaging Award 07/2020-06/2021, Breast Cancer Research Foundation 06/2019 - 05/2021 PI Mark Robson Co-I, NIH R01 Breast Cancer Intravoxel-Incoherent-Motion MRI Multisite (BRIMM) 09/01/2020-08/30/2025 PI Eric Sigmund Co-I, NIH R01 subaward: Abbreviated Non-Contrast-Enhanced MRI for Breast Cancer Screening 09/01/2023-08/31/2025 PI Brian Hargreaves; payment for lectures, service on speakers bureaus and for travel/accommodations/meeting expenses from the European Society of Breast Imaging (MRI educational course, annual scientific meeting) and Siemens Healthcare (lectures). K.J. No relevant relationships. A.E.E. No relevant relationships. P.E. No relevant relationships. E.A.M. No relevant relationships. H.A.M. Grant from NIBIB and NIMH through the NIH BRAIN Initiative (R01 EB028157). L.C.P. Grant from NIH (R01CA247910). E.J.S. Grant from National Institutes of Health/National Cancer Institute (P30 CA008748)., (2022 by the Radiological Society of North America, Inc.)

Background: As neoadjuvant chemotherapy (NAC) for breast cancer has become more widely used, so has nipple-sparing mastectomy. A common criterion for eligibility is a 1 cm tumor-to-nipple distance (TND), but its suitability after NAC is unclear. In this study, we examined factors predictive of negative nipple pathologic status (NS-) in women undergoing total mastectomy after NAC., Methods: Women with invasive breast cancer treated with NAC and total mastectomy from August 2014 to April 2018 at our institution were retrospectively identified. Following review of pre- and post-NAC magnetic resonance imaging (MRI) and mammograms, the association of clinicopathologic and imaging variables with NS- was examined and the accuracy of 1 cm TND on imaging for predicting NS- was determined., Results: Among 175 women undergoing 179 mastectomies, 74% of tumors were cT1-T2 and 67% were cN+ on pre-NAC staging; 10% (18/179) had invasive or in situ carcinoma in the nipple on final pathology. On multivariable analysis, after adjusting for age, grade, and tumor stage, three factors, namely number of positive nodes, pre-NAC nipple-areolar complex retraction, and decreasing TND, were significant predictors of nipple involvement (p < 0.05). The likelihood of NS- was higher with increasing TND on pre- and post-NAC imaging (p < 0.05). TND ≥ 1 cm predicted NS- in 97% and 95% of breasts on pre- and post-NAC imaging, respectively., Conclusions: Increasing TND was associated with a higher likelihood of NS-. A TND ≥ 1 cm on pre- or post-NAC imaging is highly predictive of NS- and could be used to determine eligibility for nipple-sparing mastectomy after NAC., (© 2021. Society of Surgical Oncology.)

Background: Female breast cancer is the most commonly diagnosed cancer in the world, with wide variations in reported survival by country. Women in low-income and middle-income countries (LMICs) in particular face several barriers to breast cancer services, including diagnostics and treatment. We aimed to estimate the potential impact of scaling up the availability of treatment and imaging modalities on breast cancer survival globally, together with improvements in quality of care., Methods: For this simulation-based analysis, we used a microsimulation model of global cancer survival, which accounts for the availability and stage-specific survival impact of specific treatment modalities (chemotherapy, radiotherapy, surgery, and targeted therapy), imaging modalities (ultrasound, x-ray, CT, MRI, PET, and single-photon emission computed tomography [SPECT]), and quality of cancer care, to simulate 5-year net survival for women with newly diagnosed breast cancer in 200 countries and territories in 2018. We calibrated the model to empirical data on 5-year net breast cancer survival in 2010-14 from CONCORD-3. We evaluated the potential impact of scaling up specific imaging and treatment modalities and quality of care to the mean level of high-income countries, individually and in combination. We ran 1000 simulations for each policy intervention and report the means and 95% uncertainty intervals (UIs) for all model outcomes., Findings: We estimate that global 5-year net survival for women diagnosed with breast cancer in 2018 was 67·9% (95% UI 62·9-73·4) overall, with an almost 25-times difference between low-income (3·5% [0·4-10·0]) and high-income (87·0% [85·6-88·4]) countries. Among individual treatment modalities, scaling up access to surgery alone was estimated to yield the largest survival gains globally (2·7% [95% UI 0·4-8·3]), and scaling up CT alone would have the largest global impact among imaging modalities (0·5% [0·0-2·0]). Scaling up a package of traditional modalities (surgery, chemotherapy, radiotherapy, ultrasound, and x-ray) could improve global 5-year net survival to 75·6% (95% UI 70·6-79·4), with survival in low-income countries improving from 3·5% (0·4-10·0) to 28·6% (4·9-60·1). Adding concurrent improvements in quality of care could further improve global 5-year net survival to 78·2% (95% UI 74·9-80·4), with a substantial impact in low-income countries, improving net survival to 55·3% (42·2-67·8). Comprehensive scale-up of access to all modalities and improvements in quality of care could improve global 5-year net survival to 82·3% (95% UI 79·3-85·0)., Interpretation: Comprehensive scale-up of treatment and imaging modalities, and improvements in quality of care could improve global 5-year net breast cancer survival by nearly 15 percentage points. Scale-up of traditional modalities and quality-of-care improvements could achieve 70% of these total potential gains, with substantial impact in LMICs, providing a more feasible pathway to improving breast cancer survival in these settings even without the benefits of future investments in targeted therapy and advanced imaging., Funding: Harvard T H Chan School of Public Health, and National Cancer Institute P30 Cancer Center Support Grant to Memorial Sloan Kettering Cancer Center., Competing Interests: Declaration of interests We declare no competing interests., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Purpose: Multiple efforts are underway to increase the inclusion of racial minority participants in genomic research and new forms of individualized medicine. These efforts should include studies that characterize how individuals from minority communities experience genomic medicine in diverse health-care settings and how they integrate genetic knowledge into their understandings of health-care needs., Methods: As part of a large, multisite genomic sequencing study, we surveyed individuals to assess their decision to pursue genomic risk evaluation. Participants included Latino patients recruited at Mountain Park Health Center, a Federally Qualified Health Center in Phoenix, Arizona, and non-Latino patients recruited at a large academic medical center (Mayo Clinic in Rochester, MN). Both groups agreed to receive individualized genomic risk assessments., Results: Comparisons between cohorts showed that Latino respondents had lower levels of decisional conflict about pursuing genomic screening but generally scored lower on genetic knowledge. Latino respondents were also more likely to have concerns about the misuse of genomic information, despite both groups having similar views about the value of genomic risk evaluation., Conclusion: Our results highlight the importance of evaluating sociocultural factors that influence minority patient engagement with genomic medicine in diverse health-care settings.

As genomic sequencing expands to screen larger numbers of individuals, offering genetic counseling to everyone may not be possible. One approach to managing this limitation is for a genetic counselor to communicate clinically actionable results in person or by telephone, but report other results by mail. We employed this approach in a large genomic implementation study. In this paper, we describe participants' experiences receiving genomic screening results by mail. We conducted 50 semi-structured telephone interviews with individuals who received neutral genomic screening results by mail. Most participants were satisfied receiving neutral results by mail. Participants generally had a good understanding of results; however, a few participants had misunderstandings about their genomic screening results, including mistaken beliefs about their disease risk and the comprehensiveness of the test. No one reported plans to alter health behaviors, defer medical evaluations, or take other actions that might be considered medically problematic. Reporting neutral results by mail is unlikely to cause recipients distress or generate misunderstandings that may result in reduced vigilance in following recommended preventive health strategies. Nonetheless, some individuals may benefit from additional genetic counseling support to help situate their results in the context of personal concerns and illness experiences.

Purpose: To assess the feasibility and diagnostic accuracy of multispectral MRI (MSI) in the detection and localization of biopsy markers during MRI-guided breast biopsy., Methods: This prospective study included 20 patients undergoing MR-guided breast biopsy. In 10 patients (Group 1), MSI was acquired following tissue sampling and biopsy marker deployment. In the other 10 patients (Group 2), MSI was acquired following tissue sampling but before biopsy marker deployment (to simulate deployment failure). All patients received post-procedure mammograms. Group 1 and Group 2 designations, in combination with the post-procedure mammogram, served as the reference standard. The diagnostic performance of MSI for biopsy marker identification was independently evaluated by two readers using two-spectral-bin MR and one-spectral-bin MR. The κ statistic was used to assess inter-rater agreement for biopsy marker identification., Results: The sensitivity, specificity, and accuracy of biopsy marker detection for readers 1 and 2 using 2-bin MSI were 90.0% (9/10) and 90.0% (9/10), 100.0% (10/10) and 100.0% (10/10), 95.0% (19/20) and 95.0% (19/20); and using 1-bin MSI were 70.0% (7/10) and 80.0% (8/10), 100.0% (8/8) and 100.0% (10/10), 85.0% (17/20) and 90.0% (18/20). Positive predictive value was 100% for both readers for all numbers of bins. Inter-rater agreement was excellent: κ was 1.0 for 2-bin MSI and 0.81 for 1-bin MSI., Conclusion: MSI is a feasible, diagnostically accurate technique for identifying metallic biopsy markers during MRI-guided breast biopsy and may eliminate the need for a post-procedure mammogram., Competing Interests: YW and PS are inventors on QSM-related patents issued to Cornell University and hold equity in Medimagemetric LLC. KP received payment for activities not related to the present article including lectures including service on speakers bureaus and for travel/accommodations/meeting expenses unrelated to activities listed from the European Society of Breast Imaging (MRI educational course, annual scientific meeting), and the IDKD 2019 (educational course). EM has received a grant from GRAIL, Inc. for research not related to the present article. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Eskreis-Winkler, Simon, Reichman, Spincemaille, Nguyen, Christos, Drotman, Prince, Pinker, Sutton, Morris and Wang.)

Objective: To investigate the feasibility of using deep learning to identify tumor-containing axial slices on breast MRI images., Methods: This IRB-approved retrospective study included consecutive patients with operable invasive breast cancer undergoing pretreatment breast MRI between January 1, 2014, and December 31, 2017. Axial tumor-containing slices from the first postcontrast phase were extracted. Each axial image was subdivided into two subimages: one of the ipsilateral cancer-containing breast and one of the contralateral healthy breast. Cases were randomly divided into training, validation, and testing sets. A convolutional neural network was trained to classify subimages into "cancer" and "no cancer" categories. Accuracy, sensitivity, and specificity of the classification system were determined using pathology as the reference standard. A two-reader study was performed to measure the time savings of the deep learning algorithm using descriptive statistics., Results: Two hundred and seventy-three patients with unilateral breast cancer met study criteria. On the held-out test set, accuracy of the deep learning system for tumor detection was 92.8% (648/706; 95% confidence interval: 89.7%-93.8%). Sensitivity and specificity were 89.5% and 94.3%, respectively. Readers spent 3 to 45 seconds to scroll to the tumor-containing slices without use of the deep learning algorithm., Conclusion: In breast MR exams containing breast cancer, deep learning can be used to identify the tumor-containing slices. This technology may be integrated into the picture archiving and communication system to bypass scrolling when viewing stacked images, which can be helpful during nonsystematic image viewing, such as during interdisciplinary tumor board meetings., (© Society of Breast Imaging 2021. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Purpose: The aim of the study was to characterize experiences of Latino participants receiving genomic screening results., Methods: Participants were recruited at a federally qualified health center in the USA. In-person, semi-structured interviews were conducted in either Spanish or English by a bilingual, bicultural interviewer. Questions focused on motivations for pursuing genomic sequencing, concerns about receiving genomic screening results, and perceived benefits of receiving genomic information. Interviews were audio-recorded, transcribed, and translated., Results: Fifty individuals completed an interview; 39 were conducted in Spanish. Participants described mixed motivations for pursuing genomic screening. Participants viewed the benefits of genomic screening in relation to not only their personal health but to the health of their families and their communities. Participants tended to have few concerns about genomic screening. Those concerns related to potential loss of privacy, misuses of genomic information, and the possibility of receiving distressing results. Some participants had misunderstandings about the scope of the test and the potential implications of their results. Most felt it was better to know about a genetic predisposition to disease than to remain uninformed. Participants felt that genomic screening was worthwhile., Discussion: This is one of the first studies to examine the experiences of Latino individuals receiving genomic screening results. Our results suggest that many Latino patients in the US see value in genomic screening and have limited concerns about its potential to cause harm. These results inform ongoing efforts to increase the availability of genomic medicine to underrepresented populations and add to our understanding of sociocultural drivers in the adoption of precision medicine., (© 2021 S. Karger AG, Basel.)

Purpose: Breast MRI background parenchymal enhancement (BPE) can potentially serve as a prognostic marker, by possible correlation with molecular subtype. Oncotype Dx, a gene assay, is a prognostic and predictive surrogate for tumor aggressiveness and treatment response. The purpose of this study was to investigate the association between contralateral non-tumor breast magnetic resonance imaging (MRI) background parenchymal enhancement and tumor oncotype score., Methods: In this retrospective study, patients with ER+ and HER2- early stage invasive ductal carcinoma who underwent preoperative breast MRI, oncotype risk scoring, and breast conservation surgery from 2008-2010 were identified. After registration, BPE from the pre and three post-contrast phases was automatically extracted using a k-means clustering algorithm. Four metrics were calculated: initial enhancement (IE) relative to the pre-contrast signal, late enhancement, overall enhancement (OE), and area under the enhancement curve (AUC). Histogram analysis was performed to determine first order metrics which were compared to oncotype risk score groups using Mann-Whitney tests and Spearman rank correlation analysis., Results: This study included 80 women (mean age = 51.1 ± 10.3 years); 46 women were categorized as low risk (≤17) and 34 women were categorized as intermediate/high risk (≥18) according to Oncotype Dx. For the mean of the top 10% pixels, significant differences were noted for IE (p = 0.032), OE (p = 0.049), and AUC (p = 0.044). Using the risk score as a continuous variable, correlation analysis revealed a weak but significant correlation with the mean of the top 10% pixels for IE (r = 0.26, p = 0.02), OE (r = 0.25, p = 0.02), and AUC (r = 0.27, p = 0.02)., Conclusion: BPE metrics of enhancement in the non-tumor breast are associated with tumor Oncotype Dx recurrence score, suggesting that the breast microenvironment may relate to likelihood of recurrence and magnitude of chemotherapy benefit., Competing Interests: EM received a grant from GRAIL Inc. for research not related to the present article. MS is currently employed by Promaxo in San Francisco, CA. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Zhang, Sadinski, Haddad, Bae, Martinez, Morris, Gibbs and Sutton.)

Objectives: To assess whether no enhancement on pre-treatment MRI can rule out malignancy of additional US mass(es) initially assessed as BI-RADS 3 or 4 in women with newly diagnosed breast cancer., Methods: This retrospective study included consecutive women from 2010-2018 with newly diagnosed breast cancer; at least one additional breast mass (distinct from index cancer) assigned a BI-RADS 3 or 4 on US; and a bilateral contrast-enhanced breast MRI performed within 90 days of US. All malignant masses were pathologically proven; benign masses were pathologically proven or defined as showing at least 2 years of imaging stability. Incidence of malignant masses and NPV were calculated on a per-patient level using proportions and exact 95% CIs., Results: In 230 patients with 309 additional masses, 140/309 (45%) masses did not enhance while 169/309 (55%) enhanced on MRI. Of the 140 masses seen in 105 women (mean age, 54 years; range 28-82) with no enhancement on MRI, all had adequate follow-up and 140/140 (100%) were benign, of which 89/140 (63.6%) were pathologically proven and 51/140 (36.4%) demonstrated at least 2 years of imaging stability. Pre-treatment MRI demonstrating no enhancement of US mass correlate(s) had an NPV of 100% (95% CI 96.7-100.0)., Conclusions: All BI-RADS 3 and 4 US masses with a non-enhancing correlate on pre-treatment MRI were benign. The incorporation of MRI, when ordered by the referring physician, may decrease unnecessary follow-up imaging and/or biopsy if the initial US BI-RADS assessment and management recommendation were to be retrospectively updated., Key Points: • Of 309 BI-RADS 3 or 4 US masses with a corresponding mass on MRI, 140/309 (45%) demonstrated no enhancement whereas 169/309 (55%) demonstrated enhancement • All masses classified as BI-RADS 3 or 4 on US without enhancement on MRI were benign • MRI can rule out malignancy in non-enhancing US masses with an NPV of 100.

Importance: After neoadjuvant chemotherapy (NAC), pathologic complete response (pCR) is an optimal outcome and a surrogate end point for improved disease-free and overall survival. To date, surgical resection remains the only reliable method for diagnosing pCR., Objective: To evaluate the accuracy of magnetic resonance imaging (MRI)-guided biopsy for diagnosing a pCR after NAC compared with reference-standard surgical resection., Design, Setting, and Participants: Single-arm, phase 1, nonrandomized controlled trial in a single tertiary care cancer center from September 26, 2017, to July 29, 2019. The median follow-up was 1.26 years (interquartile range, 0.85-1.59 years). Data analysis was performed in November 2019. Eligible patients had (1) stage IA to IIIC biopsy-proven operable invasive breast cancer; (2) standard-of-care NAC; (3) MRI before and after NAC, with imaging complete response defined as no residual enhancement on post-NAC MRI; and (4) definitive surgery. Patients were excluded if they were younger than 18 years, had a medical reason precluding study participation, or had a prior history of breast cancer., Interventions: Post-NAC MRI-guided biopsy without the use of intravenous contrast of the tumor bed before definitive surgery., Main Outcomes and Measures: The primary end point was the negative predictive value of MRI-guided biopsy, with true-negative defined as negative results of the biopsy (ie, no residual cancer) corresponding to a surgical pCR. Accuracy, sensitivity, positive predictive value, and specificity were also calculated. Two clinical definitions of pCR were independently evaluated: definition 1 was no residual invasive cancer; definition 2, no residual invasive or in situ cancer., Results: Twenty of 23 patients (87%) had evaluable data (median [interquartile range] age, 51.5 [39.0-57.5] years; 20 women [100%]; 13 White patients [65%]). Of the 20 patients, pre-NAC median tumor size on MRI was 3.0 cm (interquartile range, 2.0-5.0 cm). Nineteen of 20 patients (95%) had invasive ductal carcinoma; 15 of 20 (75%) had stage II cancer; 11 of 20 (55%) had ERBB2 (formerly HER2 or HER2/neu)-positive cancer; and 6 of 20 (30%) had triple-negative cancer. Surgical pathology demonstrated a pCR in 13 of 20 (65%) patients and no pCR in 7 of 20 patients (35%) when pCR definition 1 was used. Results of MRI-guided biopsy had a negative predictive value of 92.8% (95% CI, 66.2%-99.8%), with accuracy of 95% (95% CI, 75.1%-99.9%), sensitivity of 85.8% (95% CI, 42.0%-99.6%), positive predictive value of 100%, and specificity of 100% for pCR definition 1. Only 1 patient had a false-negative MRI-guided biopsy result (surgical pathology showed <0.02 cm of residual invasive cancer)., Conclusions and Relevance: This study's results suggest that the accuracy of MRI-guided biopsy to diagnose a post-NAC pCR approaches that of reference-standard surgical resection. MRI-guided biopsy may be a viable alternative to surgical resection for this population after NAC, which supports the need for further investigation., Trial Registration: ClinicalTrials.gov Identifier: NCT03289195.

Social scientists have advocated for the use of participatory research methods for Global Health project design and planning. However, community-engaged approaches can be time and resource-intensive. This article proposes a feasible framework for conducting a participatory needs assessment in time-limited settings using multiple, triangulated qualitative methods. This framework is outlined through a case study: a participatory needs assessment to inform the design of an ultrasound-guided biopsy training program in Nigeria. Breast cancer is the leading cause of death for Nigerian women and most cases in Nigeria are diagnosed at an advanced stage; timely diagnosis is impeded by fractious referral pathways, costly imaging equipment, and limited access outside urban centers. The project involved participant observation, surveys, and focus groups at the African Research Group for Oncology (ARGO) in Ile-Ife, Nigeria. Through this timely research and engagement, participants spoke about diagnostic challenges, institutional power dynamics, and infrastructure considerations for program implementation.

Introduction: Minority communities have had limited access to advances in genomic medicine. Mayo Clinic and Mountain Park Health Center, a Federally Qualified Health Center in Phoenix, Arizona, partnered to assess the feasibility of offering genomic screening to Latino patients receiving care at a community-based health center. We examined primary care provider (PCP) experiences reporting genomic screening results and integrating those results into patient care., Methods: We conducted open-ended, semi-structured interviews with PCPs and other members of the health care team charged with supporting patients who received positive genomic screening results. Interviews were recorded, transcribed, and analyzed thematically., Results: Of the 500 patients who pursued genomic screening, 10 received results indicating a genetic variant that warranted clinical management. PCPs felt genomic screening was valuable to patients and their families, and that genomic research should strive to include underrepresented minorities. Providers identified multiple challenges integrating genomic sequencing into patient care, including difficulties maintaining patient contact over time; arranging follow-up medical care; and managing results in an environment with limited genetics expertise. Providers also reflected on the ethics of offering genomic sequencing to patients who may not be able to pursue diagnostic testing or follow-up care due to financial constraints., Conclusions: Our results highlight the potential benefits and challenges of bringing advances in precision medicine to community-based health centers serving under-resourced populations. By proactively considering patient support needs, and identifying financial assistance programs and patient-referral mechanisms to support patients who may need specialized medical care, PCPs and other health care providers can help to ensure that precision medicine lives up to its full potential as a tool for improving patient care.

Purpose: The incidence of breast cancer is rising in Nigeria, and one major barrier to care is the lack of affordable and appropriate breast cancer diagnosis by ultrasound (US)-guided biopsy. The prohibitive cost of US devices limits their availability in low- and middle-income countries. The emergence of mobile health (mHealth) imaging devices may offer an acceptable low-cost alternative. The purpose of this research was to perform a comprehensive needs assessment to understand knowledge, use, training needs, and attitudes as regards image-guided biopsy in Nigeria to inform the development of an mHealth-based US-guided biopsy training program., Methods: A multistakeholder needs assessment was conducted at the Sixth Annual African Research Group for Oncology Symposium. Voluntary anonymous surveys were administered to all attendees. A subset of attendees (ie, surgeons, radiologists, pathologists, and nurses) participated in six focus groups. Survey items and interview guides were developed collaboratively with local and international input., Results: Surveys focusing on use, training needs, and attitudes regarding US-guided biopsies were completed with a 55% response rate (n = 54 of 98) among participants from 22 hospitals across Nigeria. Respondents expressed dissatisfaction with the way breast biopsies were currently performed at their hospitals and high interest in having their institution participate in a US-guided biopsy training program. Focus group participants (n = 37) identified challenges to performing US-guided procedures, including equipment functionality and cost, staff training, and access to consumables. Groups brainstormed the design of an mHealth US-guided biopsy training program, preferring a train-the-trainer format combining in-person teaching with independent modules., Conclusion: A multidisciplinary needs assessment of local stakeholders identified a need for and acceptability of an mHealth-based US-guided biopsy training program in Nigeria.

Background: Differences in imaging parameters influence computer-extracted parenchymal enhancement measures from breast MRI., Purpose: To investigate the effect of differences in dynamic contrast-enhanced MRI acquisition parameter settings on quantitative parenchymal enhancement of the breast, and to evaluate harmonization of contrast-enhancement values with respect to flip angle and repetition time., Study Type: Retrospective., Phantom/populations: We modeled parenchymal enhancement using simulations, a phantom, and two cohorts (N = 398 and N = 302) from independent cancer centers., Sequence Field/strength: 1.5T dynamic contrast-enhanced T 1 -weighted spoiled gradient echo MRI. Vendors: Philips, Siemens, General Electric Medical Systems., Assessment: We assessed harmonization of parenchymal enhancement in simulations and phantom by varying the MR parameters that influence the amount of T 1 -weighting: flip angle (8°-25°) and repetition time (4-12 msec). We calculated the median and interquartile range (IQR) of the enhancement values before and after harmonization. In vivo, we assessed overlap of quantitative parenchymal enhancement in the cohorts before and after harmonization using kernel density estimations. Cohort 1 was scanned with flip angle 20° and repetition time 8 msec; cohort 2 with flip angle 10° and repetition time 6 msec., Statistical Tests: Paired Wilcoxon signed-rank-test of bootstrapped kernel density estimations., Results: Before harmonization, simulated enhancement values had a median (IQR) of 0.46 (0.34-0.49). After harmonization, the IQR was reduced: median (IQR): 0.44 (0.44-0.45). In the phantom, the IQR also decreased, median (IQR): 0.96 (0.59-1.22) before harmonization, 0.96 (0.91-1.02) after harmonization. Harmonization yielded significantly (P < 0.001) better overlap in parenchymal enhancement between the cohorts: median (IQR) was 0.46 (0.37-0.58) for cohort 1 vs. 0.37 (0.30-0.44) for cohort 2 before harmonization (57% overlap); and 0.35 (0.28-0.43) vs. .0.37 (0.30-0.44) after harmonization (85% overlap)., Data Conclusion: The proposed practical harmonization method enables an accurate comparison between patients scanned with differences in imaging parameters., Level of Evidence: 3 TECHNICAL EFFICACY STAGE: 4., (© 2020 The Authors. Journal of Magnetic Resonance Imaging published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.)

Importance: Regional nodal irradiation (RNI) for node-positive breast cancer reduces distant metastases and improves survival, albeit with limited reduction in regional nodal recurrences. The mechanism by which RNI robustly reduces distant metastases while modestly influencing nodal recurrences (ie, the presumed target of RNI) remains unclear., Objective: To determine whether some distant metastases putatively arise from occult regional nodal disease and whether regional recurrences otherwise remain largely undetected until an advanced cancer presentation., Design, Setting, and Participants: This cohort study examined patients presenting with de novo stage IV breast cancer to the Memorial Sloan Kettering Cancer Center in New York, New York, from 2006 to 2018. Medical records were reviewed to ascertain clinicopathological parameters, including estrogen receptor status and survival. Pretreatment positron emission tomography-computed tomography (PET-CT) imaging was reviewed to ascertain the extent of regional nodal involvement at metastatic diagnosis using standard nodal assessment criteria. A subset underwent regional lymph node biopsy for diagnostic confirmation and served to validate the radiographic nodal assessment. Data analysis was performed from October 2019 to February 2020., Exposures: Untreated metastatic breast cancer., Main Outcome and Measures: The primary outcome was the likelihood of regional nodal involvement at the time of metastatic breast cancer presentation and was determined by reviewing pretreatment PET-CT imaging and lymph node biopsy findings., Results: Among 597 women (median [interquartile range] age, 53 [44-65] years) with untreated metastatic breast cancer, 512 (85.8%) exhibited regional lymph node involvement by PET-CT or nodal biopsy, 509 (85%) had involvement of axillary level I, 328 (55%) had involvement in axillary level II, 136 (23%) had involvement in axillary level III, 101 (17%) had involvement in the supraclavicular fossa, and 96 (16%) had involvement in the internal mammary chain. Lymph node involvement was more prevalent among estrogen receptor-negative tumors (92.4%) than estrogen receptor-positive tumors (83.6%). Nodal involvement at the time of metastatic diagnosis was not associated with overall survival., Conclusions and Relevance: These findings suggest that a majority of patients with de novo metastatic breast cancer harbor regional lymph node disease at presentation, consistent with the hypothesis that regional involvement may precede metastatic dissemination. This is in alignment with the findings of landmark trials suggesting that RNI reduces distant recurrences. It is possible that this distant effect of RNI may act via eradication of occult regional disease prior to systemic seeding. The challenges inherent in detecting isolated nodal disease (which is typically asymptomatic) may account for the more modest observed benefit of RNI on regional recurrences. Alternative explanations of nodal involvement that arises concurrently or after metastatic dissemination remain possible, but do not otherwise explain the association of RNI with distant recurrence.

As applications of genomic sequencing have expanded, offering genetic counseling support to all patients is arguably no longer practical. Additionally, whether individuals desire and value genetic counseling services for genomic screening is unclear. We offered elective genetic counseling to 5110 individuals prior to undergoing sequencing and 2310 participants who received neutral results to assess demand. A total of 0.2% of the study participants accessed genetic counseling services prior to sequencing, and 0.3% reached out after receiving neutral results. We later conducted 50 interviews with participants to understand why they did not access these services. Many interviewees did not recall the availability of genetic counseling and were unfamiliar with the profession. Interviewees described not needing counseling before sequencing because they understood the study and felt that they could cope with any result. Counseling was considered equally unnecessary after learning neutral results. Although the participants had questions about their results, they did not feel that speaking with a genetic counselor would be helpful. Genomic screening efforts that employ opt-in models of genetic counseling may need to clarify the potential value of genetic counseling support from the outset and feature genetic counseling services more prominently in program materials.

Breast implant-associated anaplastic large cell lymphoma (BIA-ALCL) is a rare but increasingly important diagnosis as the incidence of breast implant placement, both elective and reconstructive, continues to rise. When detected and treated early, this indolent disease carries an excellent prognosis. However, because the clinical presentation is often nonspecific, it is crucial for radiologists to accurately identify the imaging findings associated with BIA-ALCL to facilitate a timely diagnosis. This article will provide radiologists with an overview of the diagnosis, imaging findings, and management of BIA-ALCL., (© Society of Breast Imaging 2020. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background: Ultrafast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI)-derived kinetic parameters have demonstrated at least equivalent accuracy to standard DCE-MRI in differentiating malignant from benign breast lesions. However, it is unclear if they have any efficacy as prognostic imaging markers. The aim of this study was to investigate the relationship between ultrafast DCE-MRI-derived kinetic parameters and breast cancer characteristics., Methods: Consecutive breast MRI examinations between February 2017 and January 2018 were retrospectively reviewed to determine those examinations that meet the following inclusion criteria: (1) BI-RADS 4-6 MRI performed on a 3T scanner with a 16-channel breast coil and (2) a hybrid clinical protocol with 15 phases of ultrafast DCE-MRI (temporal resolution of 2.7-4.6 s) followed by early and delayed phases of standard DCE-MRI. The study included 125 examinations with 142 biopsy-proven breast cancer lesions. Ultrafast DCE-MRI-derived kinetic parameters (maximum slope [MS] and bolus arrival time [BAT]) were calculated for the entire volume of each lesion. Comparisons of these parameters between different cancer characteristics were made using generalized estimating equations, accounting for the presence of multiple lesions per patient. All comparisons were exploratory and adjustment for multiple comparisons was not performed; P values < 0.05 were considered statistically significant., Results: Significantly larger MS and shorter BAT were observed for invasive carcinoma than ductal carcinoma in situ (DCIS) (P < 0.001 and P = 0.008, respectively). Significantly shorter BAT was observed for invasive carcinomas with more aggressive characteristics than those with less aggressive characteristics: grade 3 vs. grades 1-2 (P = 0.025), invasive ductal carcinoma vs. invasive lobular carcinoma (P = 0.002), and triple negative or HER2 type vs. luminal type (P < 0.001)., Conclusions: Ultrafast DCE-MRI-derived parameters showed a strong relationship with some breast cancer characteristics, especially histopathology and molecular subtype.

Background: For breast cancer patients undergoing neoadjuvant chemotherapy (NAC), pathologic complete response (pCR; no invasive or in situ) cannot be assessed non-invasively so all patients undergo surgery. The aim of our study was to develop and validate a radiomics classifier that classifies breast cancer pCR post-NAC on MRI prior to surgery., Methods: This retrospective study included women treated with NAC for breast cancer from 2014 to 2016 with (1) pre- and post-NAC breast MRI and (2) post-NAC surgical pathology report assessing response. Automated radiomics analysis of pre- and post-NAC breast MRI involved image segmentation, radiomics feature extraction, feature pre-filtering, and classifier building through recursive feature elimination random forest (RFE-RF) machine learning. The RFE-RF classifier was trained with nested five-fold cross-validation using (a) radiomics only (model 1) and (b) radiomics and molecular subtype (model 2). Class imbalance was addressed using the synthetic minority oversampling technique., Results: Two hundred seventy-three women with 278 invasive breast cancers were included; the training set consisted of 222 cancers (61 pCR, 161 no-pCR; mean age 51.8 years, SD 11.8), and the independent test set consisted of 56 cancers (13 pCR, 43 no-pCR; mean age 51.3 years, SD 11.8). There was no significant difference in pCR or molecular subtype between the training and test sets. Model 1 achieved a cross-validation AUROC of 0.72 (95% CI 0.64, 0.79) and a similarly accurate (P = 0.1) AUROC of 0.83 (95% CI 0.71, 0.94) in both the training and test sets. Model 2 achieved a cross-validation AUROC of 0.80 (95% CI 0.72, 0.87) and a similar (P = 0.9) AUROC of 0.78 (95% CI 0.62, 0.94) in both the training and test sets., Conclusions: This study validated a radiomics classifier combining radiomics with molecular subtypes that accurately classifies pCR on MRI post-NAC.

Background: To assess the incidence of benign and malignant peri-implant fluid collections and/or masses on magnetic resonance imaging (MRI) in women with silicone implants who are being screened for silent implant rupture., Methods: The institutional review board approved this HIPAA-compliant retrospective study and waived informed consent. Women who underwent silicone implant oncoplastic and/or cosmetic surgery and postoperative implant-protocol MRI from 2000 to 2014 were included. Peri-implant fluid collections and/or masses were measured volumetrically. A benign peri-implant fluid collection and/or mass was pathologically proven or defined as showing 2 years of imaging and/or clinical stability. A malignant peri-implant fluid collection was pathologically proven. Incidence of peri-implant fluid collections and/or masses and positive predictive value (PPV) were calculated on a per-patient level using proportions and exact 95% confidence intervals (CIs). Fisher's exact test was used in the analysis to test statistical significance pre-defined as P-value < 0.05., Results: A total of 1070 women with silicone implants were included (mean age, 50.7 years; range, 40.4-53.8). Median time between reconstructive surgery and first MRI was 88.9 months (range, 0.8-1363.3). Eighteen women (1.7%) had a peri-implant fluid collection and/or mass: 15/18 (83.3%) had adequate follow-up; and only 1/15 was malignant implant associated anaplastic large cell lymphoma, with a PPV of 6.7% (95% CI: 0.003-0.0005). The median peri-implant fluid collection size was 89 mL (range, 18-450 mL)., Conclusion: Peri-implant fluid collections and/or masses identified at silicone implant protocol breast MR imaging are rarely seen 24 months after reconstructive surgery. Image-guided fine-needle aspiration with flow cytometry may be warranted to evaluate for implant-associated lymphoma., (© 2019 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.)

Purpose: To compare annotation segmentation approaches and to assess the value of radiomics analysis applied to diffusion-weighted imaging (DWI) for evaluation of breast cancer receptor status and molecular subtyping., Procedures: In this IRB-approved HIPAA-compliant retrospective study, 91 patients with treatment-naïve breast malignancies proven by image-guided breast biopsy, (luminal A, n = 49; luminal B, n = 8; human epidermal growth factor receptor 2 [HER2]-enriched, n = 11; triple negative [TN], n = 23) underwent multiparametric magnetic resonance imaging (MRI) of the breast at 3 T with dynamic contrast-enhanced MRI, T2-weighted and DW imaging. Lesions were manually segmented on high b-value DW images and segmentation ROIS were propagated to apparent diffusion coefficient (ADC) maps. In addition in a subgroup (n = 79) where lesions were discernable on ADC maps alone, these were also directly segmented there. To derive radiomics signatures, the following features were extracted and analyzed: first-order histogram (HIS), co-occurrence matrix (COM), run-length matrix (RLM), absolute gradient, autoregressive model (ARM), discrete Haar wavelet transform (WAV), and lesion geometry. Fisher, probability of error and average correlation, and mutual information coefficients were used for feature selection. Linear discriminant analysis followed by k-nearest neighbor classification with leave-one-out cross-validation was applied for pairwise differentiation of receptor status and molecular subtyping. Histopathologic results were considered the gold standard., Results: For lesion that were segmented on DWI and segmentation ROIs were propagated to ADC maps the following classification accuracies > 90% were obtained: luminal B vs. HER2-enriched, 94.7 % (based on COM features); luminal B vs. others, 92.3 % (COM, HIS); and HER2-enriched vs. others, 90.1 % (RLM, COM). For lesions that were segmented directly on ADC maps, better results were achieved yielding the following classification accuracies: luminal B vs. HER2-enriched, 100 % (COM, WAV); luminal A vs. luminal B, 91.5 % (COM, WAV); and luminal B vs. others, 91.1 % (WAV, ARM, COM)., Conclusions: Radiomic signatures from DWI with ADC mapping allows evaluation of breast cancer receptor status and molecular subtyping with high diagnostic accuracy. Better classification accuracies were obtained when breast tumor segmentations could be performed on ADC maps.

Objectives: This study aims to evaluate ultrafast DCE-MRI-derived kinetic parameters that reflect contrast agent inflow effects in differentiating between subcentimeter BI-RADS 4-5 breast carcinomas and benign lesions., Methods: We retrospectively reviewed consecutive 3-T MRI performed from February to October 2017, during which ultrafast DCE-MRI was performed as part of a hybrid clinical protocol with conventional DCE-MRI. In total, 301 female patients with 369 biopsy-proven breast lesions were included. Ultrafast DCE-MRI was acquired continuously over approximately 60 s (temporal resolution, 2.7-7.1 s/phase) starting simultaneously with the start of contrast injection. Four ultrafast DCE-MRI-derived kinetic parameters (maximum slope [MS], contrast enhancement ratio [CER], bolus arrival time [BAT], and initial area under gadolinium contrast agent concentration [IAUGC]) and one conventional DCE-MRI-derived kinetic parameter (signal enhancement ratio [SER]) were calculated for each lesion. Wilcoxon rank sum test or Fisher's exact test was performed to compare kinetic parameters, volume, diameter, age, and BI-RADS morphological descriptors between subcentimeter carcinomas and benign lesions. Univariate/multivariate logistic regression analyses were performed to determine predictive parameters for subcentimeter carcinomas., Results: In total, 125 lesions (26 carcinomas and 99 benign lesions) were identified as BI-RADS 4-5 subcentimeter lesions. Subcentimeter carcinomas demonstrated significantly larger MS and SER and shorter BAT than benign lesions (p = 0.0117, 0.0046, and 0.0102, respectively). MS, BAT, and age were determined as significantly predictive for subcentimeter carcinoma (p = 0.0208, 0.0023, and < 0.0001, respectively)., Conclusions: Ultrafast DCE-MRI-derived kinetic parameters may be useful in differentiating subcentimeter BI-RADS 4 and 5 carcinomas from benign lesions., Key Points: • Ultrafast DCE-MRI can generate kinetic parameters, effectively differentiating breast carcinomas from benign lesions. • Subcentimeter carcinomas demonstrated significantly larger maximum slope and shorter bolus arrival time than benign lesions. • Maximum slope and bolus arrival time contribute to better management of suspicious subcentimeter breast lesions.

Objective: To determine survival outcomes in women with breast cancer detected at combined screening with breast MRI and mammography versus screening mammography alone., Methods: This is an institutional review board-approved retrospective study, and the need for informed consent was waived. A total of 3002 women with an increased risk of breast cancer were screened between 2001 and 2004. Of the 3002 women, 1534 (51.1%) had 2780 combined screenings (MRI and mammography) and 1468 (48.9%) had 4811 mammography-only screenings. The Χ 2 test and the Kaplan-Meier method were used to compare cancer detection rates and survival rates., Results: The overall cancer detection rate was significantly higher in the MRI plus mammography group compared with the mammography-only group (1.4% [40 of 2780] vs 0.5% [23 of 4811]; P < 0.001). No interval cancers occurred in the MRI plus mammography group, whereas 9 interval cancers were found in the mammography-only group. During a median follow-up of 10.9 years (range: 0.7 to 15.2), a total of 11 recurrences and 5 deaths occurred. Of the 11 recurrences, 6 were in the MRI plus mammography group and 5 were in the mammography-only group. All five deaths occurred in the mammography-only group. Disease-free survival showed no statistically significant difference between the two groups ( P = 0.32). However, overall survival was significantly improved in the MRI plus mammography group ( P = 0.002)., Conclusion: Combined screening with MRI and mammography in women at elevated risk of breast cancer improves cancer detection and overall survival., (© Society of Breast Imaging 2020. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Introduction: To address ethical concerns about the of future research authorization, biobanks employing a broad model of consent can design ongoing communication with contributors. Notifying contributors at the time of sample distribution provides one form of communication to supplement broad consent. However, little is known about how community-informed governance might anticipate contributor responses and inform communication efforts., Objective: We explored the attitudes of members of a three-site Community Advisory Board (CAB) network. CAB members responded to a hypothetical proposal for notifying biobank contributors at the time of sample distribution to researchers utilizing the biobank., Methods: We used regularly scheduled CAB meetings to facilitate 3 large-group and 6 small-group discussions. Discussions were audio-recorded, transcribed, and analyzed for thematic content using descriptive thematic analysis., Results: The results challenged our expectation of general support for the proposed communications. While CAB members identified some advantages, they were concerned about several potential harms to biobank contributors and the biobank. The CABs understood biobank communication in terms of an ongoing relationship with the biobank and a personal contribution to research., Conclusion: Our findings contribute to the emerging literature on community engagement in biobanking. Additional communication with biobank contributors can serve a variety of value-based objectives to supplement broad consent. Design of communication efforts by biobanks can be improved by CAB members' anticipation of the unintended consequences of additional contact with contributors. CAB members' holistic interpretation of communication efforts suggests that biobank leadership considers all communication options as part of a more comprehensive communications strategy., (© 2020 S. Karger AG, Basel.)

Background: Small breast lesions are difficult to visually categorize due to the inherent lack of morphological and kinetic detail., Purpose: To assess the efficacy of radiomics analysis in discriminating small benign and malignant lesions utilizing model free parameter maps., Study Type: Retrospective, single center., Population: In all, 149 patients, with a total of 165 lesions scored as BI-RADS 4 or 5 on MRI, with an enhancing volume of <0.52 cm 3 ., Field Strength/sequence: Higher spatial resolution T 1 -weighted dynamic contrast-enhanced imaging with a temporal resolution of ~90 seconds performed at 3.0T., Assessment: Parameter maps reflecting initial enhancement, overall enhancement, area under the enhancement curve, and washout were generated. Heterogeneity measures based on first-order statistics, gray level co-occurrence matrices, run length matrices, size zone matrices, and neighborhood gray tone difference matrices were calculated. Data were split into a training dataset (~75% of cases) and a test dataset (~25% of cases)., Statistical Tests: Comparison of medians was assessed using the nonparametric Mann-Whitney U-test. The Spearman rank correlation coefficient was utilized to determine significant correlations between individual features. Finally, a support vector machine was employed to build multiparametric predictive models., Results: Univariate analysis revealed significant differences between benign and malignant lesions for 58/133 calculated features (P < 0.05). Support vector machine analysis resulted in areas under the curve (AUCs) ranging from 0.75-0.81. High negative (>89%) and positive predictive values (>83%) were found for all models., Data Conclusion: Radiomics analysis of small contrast-enhancing breast lesions is of value. Texture features calculated from later timepoints on the enhancement curve appear to offer limited additional value when compared with features determined from initial enhancement for this patient cohort., Level of Evidence: 4 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;50:1468-1477., (© 2019 International Society for Magnetic Resonance in Medicine.)

Purpose: The purpose of this study was to investigate if human-extracted MRI tumor phenotypes of breast cancer could predict receptor status and tumor molecular subtype using MRIs from The Cancer Genome Atlas project., Materials and Methods: Our retrospective interpretation study utilized the analysis of HIPAA-compliant breast MRI data from The Cancer Imaging Archive. One hundred and seven preoperative breast MRIs of biopsy proven invasive breast cancers were analyzed by 3 fellowship-trained breast-imaging radiologists. Each study was scored according to the Breast Imaging Reporting and Data System lexicon for mass and nonmass features. The Spearman rank correlation was used for association analysis of continuous variables; the Kruskal-Wallis test was used for associating continuous outcomes with categorical variables. The Fisher-exact test was used to assess correlations between categorical image-derived features and receptor status. Prediction of estrogen receptor (ER), progesterone receptor, human epidermal growth factor receptor, and molecular subtype were performed using random forest classifiers., Results: ER+ tumors were associated with the absence of rim enhancement (P = 0.019, odds ratio [OR] 5.5), heterogeneous internal enhancement (P = 0.02, OR 6.5), peritumoral edema (P = 0.0001, OR 10.0), and axillary adenopathy (P = 0.04, OR 4.4). ER+ tumors were smaller than ER- tumors (23.7 mm vs 29.2 mm, P = 0.02, OR 8.2). All of these variables except the lack of axillary adenopathy were also associated with progesterone receptor+ status. Luminal A tumors (n = 57) were smaller compared to nonLuminal A (21.8 mm vs 27.5 mm, P = 0.035, OR 7.3) and lacked peritumoral edema (P = 0.001, OR 6.8). Basal like tumors were associated with heterogeneous internal enhancement (P = 0.05, OR 10.1), rim enhancement (P = 0.05, OR6.9), and perituomral edema (P = 0.0001, OR 13.8)., Conclusions: Human extracted MRI tumor phenotypes may be able to differentiate those tumors with a more favorable clinical prognosis from their more aggressive counterparts., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Background: DNA biobanks frequently obtain broad permissions from sample donors, who agree to allow their biospecimens to be used for a variety of future purposes. A limitation of this approach is that it may not be possible to discuss or anticipate all potential uses of biospecimens at the time patient consent is obtained. We surveyed biobank participants to clarify their views regarding the need to be informed about research involving whole genome sequencing (WGS). Methods: We invited 1200 participants in the Mayo Clinic Biobank to complete a survey inquiring about their support for WGS; their interest in being recontacted before WGS of their biospecimens; whether they would consent to WGS if asked; and the acceptability of proceeding with WGS if sample donors could not be reached. Results: Six hundred eighty-seven biobank participants returned completed surveys (57% response). More than 96% of biobank participants were supportive of WGS and would give permission for WGS of their sample, if asked. Nonetheless, 61% of biobank participants felt they should be recontacted before WGS was done. Participants were divided regarding the permissibility of conducting WGS if efforts to recontact sample donors were unsuccessful. Discussion: Our findings highlight a potential discrepancy between the broad permissions granted by biobank participants at the time they donated biospecimens and their views about the application of WGS to their samples. Biobank participants appear to value the ability to confirm their commitment to genetic research when the studies in question involve WGS, a technological capacity they may not have anticipated at the time they donated their biospecimens. Efforts to reevaluate biobank participants' views about the acceptability of new technologies may help to ensure alignment of participants' current beliefs and research applications that would have been difficult to anticipate at the time biospecimens were collected.

Efforts to characterize stakeholder attitudes about the implementation of genomic medicine would benefit from a validated instrument for measuring public views of the potential benefits and harms of genomic technologies, which would facilitate comparison across populations and clinical settings. We sought to develop a scale to evaluate attitudes about the future of genomic medicine. We developed a 21-item scale that examined the likelihood of various outcomes of genomic medicine. The scale was administered to participants in a genomic sequencing study. Exploratory factor analysis was conducted and bivariate correlations were calculated. The genomic orientation (GO) scale was completed by 2895 participants. A two-factor structure was identified, corresponding to an optimism subscale (16 items, α = 0.89) and a pessimism subscale (5 items, α = 0.63). Genomic optimism was positively associated with a perceived value of genetic test results, higher health literacy, and decreased decisional conflict about participation in a genomic research study. Genomic pessimism was associated with concerns about genetic testing, lower health literacy, and increased decisional conflict about the decision to participate in the study. The GO scale is a promising tool for measuring both positive and negative views regarding the future of genomic medicine and deserves further validation., (© 2019 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Purpose: To assess the associations between inter-site texture heterogeneity parameters derived from computed tomography (CT), survival, and BRCA mutation status in women with high-grade serous ovarian cancer (HGSOC)., Materials and Methods: Retrospective study of 88 HGSOC patients undergoing CT and BRCA mutation status testing prior to primary cytoreductive surgery. Associations between texture metrics-namely inter-site cluster variance (SCV), inter-site cluster prominence (SCP), inter-site cluster entropy (SE)-and overall survival (OS), progression-free survival (PFS) as well as BRCA mutation status were assessed., Results: Higher inter-site cluster variance (SCV) was associated with lower PFS (p = 0.006) and OS (p = 0.003). Higher inter-site cluster prominence (SCP) was associated with lower PFS (p = 0.02) and higher inter-site cluster entropy (SE) correlated with lower OS (p = 0.01). Higher values of all three metrics were significantly associated with lower complete surgical resection status in BRCA-negative patients (SE p = 0.039, SCV p = 0.006, SCP p = 0.02), but not in BRCA-positive patients (SE p = 0.7, SCV p = 0.91, SCP p = 0.67). None of the metrics were able to distinguish between BRCA mutation carrier and non-mutation carrier., Conclusion: The assessment of tumoral heterogeneity in the era of personalized medicine is important, as increased heterogeneity has been associated with distinct genomic abnormalities and worse patient outcomes. A radiomics approach using standard-of-care CT scans might have a clinical impact by offering a non-invasive tool to predict outcome and therefore improving treatment effectiveness. However, it was not able to assess BRCA mutation status in women with HGSOC.

Purpose: We assessed the decision-making of individuals pursuing genomic sequencing without a requirement for pretest genetic counselling. We sought to describe the extent to which individuals who decline genetic counselling reported decisional conflict or struggled to make a decision to pursue genomic testing., Methods: We administered a 100-item survey to 3037 individuals who consented to the Return of Actionable Variants Empirical study, a genomic medicine implementation study supported by the National Institutes of Health (USA) eMERGE consortium. The primary outcomes of interest were self-reported decisional conflict about the decision to participate in the study and time required to reach a decision., Results: We received 2895 completed surveys (response rate=95.3%), and of these respondents 97.8% completed the decisional conflict scale in its entirety. A majority of individuals (63%) had minimal or no decisional conflict about the pursuit of genomic sequencing and were able to reach a decision quickly (78%). Multivariable logistic regression analyses identified several characteristics associated with decisional conflict, including lower education, lower health literacy, lower self-efficacy in coping, lack of prior experience with genetic testing, not discussing study participation with a family member or friend, and being male., Conclusion: As genomic sequencing is used more widely, genetic counselling resources may not be sufficient to meet demand. Our results challenge the notion that all individuals need genetic counselling in order to make an informed decision about genomic sequencing., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2019. No commercial re-use. See rights and permissions. Published by BMJ.)