Journal of Breast Imaging最新文献

{"title":"Posttraumatic Breast Hemorrhage With the Development of Fat Necrosis.","authors":"William Johnson, Cherie Kuzmiak","doi":"10.1093/jbi/wbad086","DOIUrl":"https://doi.org/10.1093/jbi/wbad086","url":null,"abstract":"","PeriodicalId":43134,"journal":{"name":"Journal of Breast Imaging","volume":"6 5","pages":"574-576"},"PeriodicalIF":2.0,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142477145","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Breast Cancer Screening With Automated Breast US and Mammography vs Handheld US and Mammography in Women With Dense Breasts in a Real-World Clinical Setting.","authors":"Andrew J Winkelman, Kassandra Tulenko, Samantha H Epstein, Jonathan V Nguyen, Clay Ford, Matthew M Miller","doi":"10.1093/jbi/wbae039","DOIUrl":"10.1093/jbi/wbae039","url":null,"abstract":"<p><strong>Objective: </strong>We compared the performance of 2 breast cancer screening approaches, automated breast US (ABUS) with same-day mammography (ABUS/MG) and handheld US (HHUS) with same-day mammography (HHUS/MG), in women with dense breasts to better understand the relative usefulness of ABUS and HHUS in a real-world clinical setting.</p><p><strong>Methods: </strong>In this institutional review board-approved, retrospective observational study, we evaluated all ABUS/MG and HHUS/MG screening examinations performed at our institution from May 2013 to September 2021. BI-RADS categories, biopsy pathology results, and diagnostic test characteristics (eg, sensitivity, specificity) were compared between the 2 screening approaches using Fisher's exact test.</p><p><strong>Results: </strong>A total of 1120 women with dense breasts were included in this study, with 852 undergoing ABUS/MG and 268 undergoing HHUS/MG. The sensitivities of ABUS/MG and HHUS/MG were 100% (5/5) and 75.0% (3/4), respectively, which was not a statistically significant difference (P  = .444). The ABUS/MG approach demonstrated a slightly higher specificity (97.4% [825/847] vs 94.3% [249/264]; P = .028), higher accuracy (97.4% [830/852] vs 94.0% [252/268]; P = .011), and lower biopsy recommendation rate (3.2% [27/852] vs 6.7% [18/268]; P = .019) than the HHUS/MG approach in our patient population.</p><p><strong>Conclusion: </strong>Our findings suggest that ABUS/MG performs comparably with HHUS/MG as a breast cancer screening approach in women with dense breasts in a real-world clinical setting, with the ABUS/MG approach demonstrating a similar sensitivity and slightly higher specificity than the HHUS/MG approach. Additional variables, such as patient experience and physician time, may help determine which imaging approach to employ in specific clinical settings.</p>","PeriodicalId":43134,"journal":{"name":"Journal of Breast Imaging","volume":" ","pages":"493-501"},"PeriodicalIF":2.0,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141735335","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dedicated Breast CT: Getting Ready for Prime Time.","authors":"Shadi Aminololama-Shakeri, John M Boone","doi":"10.1093/jbi/wbae043","DOIUrl":"10.1093/jbi/wbae043","url":null,"abstract":"<p><p>Dedicated breast CT is an imaging modality that provides true 3D imaging of the breast with many advantages over current conventional breast imaging modalities. The addition of intravascular contrast increases the sensitivity of breast CT substantially. As such, there are immediate potential applications in the clinical workflow. These include using breast CT to replace much of the traditional diagnostic workup when faced with indeterminate breast lesions. Contrast-enhanced breast CT may be appropriate as a supplemental screening tool for women at high risk of breast cancer, similar to breast MRI. In addition, emerging studies are demonstrating the utility of breast CT in neoadjuvant chemotherapy tumor response monitoring as well as planning for surgical treatment options. While short exam times and fully 3D imaging in a noncompressed position are advantages of this modality, limited coverage of chest wall/axilla due to prone positioning and use of ionizing radiation are drawbacks. To date, several studies have reported on the performance characteristics of this promising modality.</p>","PeriodicalId":43134,"journal":{"name":"Journal of Breast Imaging","volume":" ","pages":"465-475"},"PeriodicalIF":2.0,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142113168","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Utilization of Texture Analysis in Differentiating Benign and Malignant Breast Masses: Comparison of Grayscale Ultrasound, Shear Wave Elastography, and Radiomic Features.","authors":"Daniel Mannina, Ameya Kulkarni, Christian B van der Pol, Reem Al Mazroui, Peri Abdullah, Sayali Joshi, Abdullah Alabousi","doi":"10.1093/jbi/wbae037","DOIUrl":"10.1093/jbi/wbae037","url":null,"abstract":"<p><strong>Objective: </strong>This study aims to determine which qualitative and quantitative US features are independently associated with malignancy, including those derived from grayscale imaging morphology, shear wave elastography (SWE), and texture analysis.</p><p><strong>Methods: </strong>This single-center retrospective study was approved by the institutional research ethics board. Consecutive breast US studies performed between January and December 2020 were included. Images were acquired using a Canon Aplio i800 US unit (Canon Medical Systems, Inc., CA) and i18LX5 wideband linear matrix transducer. Grayscale US features, SWE mean, and median elasticity were obtained. Single representative grayscale images were analyzed using dedicated software (LIFEx, version 6.30). First-order and gray-level co-occurrence matrix second-order texture features were extracted. Multivariate logistic regression was performed to assess for predictors of malignancy (STATA v16.1).</p><p><strong>Results: </strong>One hundred forty-seven cases with complete SWE data were selected for analysis (mean age 54.3, range 21-92). The following variables were found to be independently associated with malignancy: age (P <.001), family history (P = .013), irregular mass shape (P = .024), and stiffness on SWE (mean SWE ≥40 kPa; P <.001). Remaining variables (including texture features) were not found to be independently associated with malignancy (P >.05).</p><p><strong>Conclusion: </strong>US texture analysis features were not associated with malignancy independent of other qualitative and quantitative US characteristics currently utilized in clinical practice. This suggests texture analysis may not be warranted when differentiating benign and malignant breast masses on US. In contrast, irregular mass shape on grayscale imaging and increased stiffness on SWE were found to be independent predictors of malignancy.</p>","PeriodicalId":43134,"journal":{"name":"Journal of Breast Imaging","volume":" ","pages":"513-519"},"PeriodicalIF":2.0,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141724669","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Imaging Features and World Health Organization Classification of Rare Breast Tumors.","authors":"Denas Andrijauskis, Liva Andrejeva-Wright","doi":"10.1093/jbi/wbae047","DOIUrl":"10.1093/jbi/wbae047","url":null,"abstract":"<p><p>Breast radiologists encounter unusual lesions, which may not be well described in the literature. Previously based on histologic and molecular classifications, the World Health Organization (WHO) classification of tumors has become increasingly multidisciplinary. Familiarity with imaging features and basic pathology of infrequent breast lesions, as well as their current classification according to the WHO, may help the radiologist evaluate biopsy results for concordance and help direct the management of uncommon breast lesions. This review article provides a case-based review of imaging features and WHO histologic classification of rare breast tumors.</p>","PeriodicalId":43134,"journal":{"name":"Journal of Breast Imaging","volume":" ","pages":"547-566"},"PeriodicalIF":2.0,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142126895","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Prospective Analysis of Screen-Detected Cancers Recalled and Not Recalled by Artificial Intelligence.","authors":"Samantha J Smith, Sally Anne Bradley, Katie Walker-Stabeler, Michael Siafakas","doi":"10.1093/jbi/wbae027","DOIUrl":"10.1093/jbi/wbae027","url":null,"abstract":"<p><strong>Objective: </strong>The use of artificial intelligence has potential in assisting many aspects of imaging interpretation. We undertook a prospective service evaluation from March to October 2022 of Mammography Intelligent Assessment (MIA) operating \"silently\" within our Breast Screening Service, with a view to establishing its performance in the local population and setting. This evaluation addressed the performance of standalone MIA vs conventional double human reading of mammograms.</p><p><strong>Methods: </strong>MIA analyzed 8779 screening events over an 8-month period. The MIA outcome did not influence the decisions made on the clinical pathway. Cases were reviewed approximately 6 weeks after the screen reading decision when human reading and/or MIA indicated a recall.</p><p><strong>Results: </strong>There were 146 women with positive concordance between human reading and MIA (human reader and MIA recalled) in whom 58 breast cancers were detected. There were 270 women with negative discordance (MIA no recall, human reader recall) for whom 19 breast cancers and 1 breast lymphoma were detected, with 1 cancer being an incidental finding at assessment. Six hundred and four women had positive discordance (MIA recall, human reader no recall) in whom 2 breast cancers were detected at review. The breast cancers demonstrated a wide spectrum of mammographic features, sites, sizes, and pathologies, with no statistically significant difference in features between the negative discordant and positive concordant cases.</p><p><strong>Conclusion: </strong>Of 79 breast cancers identified by human readers, 18 were not identified by MIA, and these had no specific features or site to suggest a systematic error for MIA analysis of 2D screening mammograms.</p>","PeriodicalId":43134,"journal":{"name":"Journal of Breast Imaging","volume":" ","pages":"378-387"},"PeriodicalIF":2.0,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141157168","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Unknown Case: Right Breast Mass With Contralateral Axillary Lymphadenopathy.","authors":"Meng Zhang, Lawrence Lea Gilliland","doi":"10.1093/jbi/wbad097","DOIUrl":"10.1093/jbi/wbad097","url":null,"abstract":"","PeriodicalId":43134,"journal":{"name":"Journal of Breast Imaging","volume":" ","pages":"449-451"},"PeriodicalIF":2.0,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139940872","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Maximizing Mentorship Throughout Your Breast Imaging Career.","authors":"Lisa A Mullen, R Jared Weinfurtner, Kathy M Borovicka, Tamarya L Hoyt, Haley P Letter, Sophia R O'Brien, Nayanatara Swamy, Kerri L Vicenti, Stefanie A Woodard, Brian A Xavier, Kathleen R Gundry, Alex Merkulov, Laurie R Margolies, Priscilla J Slanetz","doi":"10.1093/jbi/wbae009","DOIUrl":"10.1093/jbi/wbae009","url":null,"abstract":"<p><p>Unlike many other subspecialties in radiology, breast radiologists practice in a patient-facing and interdisciplinary environment where team building, communication, and leadership skills are critical. Although breast radiologists can improve these skills over time, strong mentorship can accelerate this process, leading to a more successful and satisfying career. In addition to providing advice, insight, feedback, and encouragement to mentees, mentors help advance the field of breast radiology by contributing to the development of the next generation of leaders. During the mentorship process, mentors continue to hone their listening, problem-solving, and networking skills, which in turn creates a more supportive and nurturing work environment for the entire breast care team. This article reviews important mentorship skills that are essential for all breast radiologists. Although some of the principles apply to all mentoring relationships, ensuring that every breast radiologist has the skills to be both an effective mentor and mentee is key to the future of the profession.</p>","PeriodicalId":43134,"journal":{"name":"Journal of Breast Imaging","volume":" ","pages":"422-429"},"PeriodicalIF":2.0,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11288399/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140330213","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"3D CT Radiomic Analysis Improves Detection of Axillary Lymph Node Metastases Compared to Conventional Features in Patients With Locally Advanced Breast Cancer.","authors":"Mark Barszczyk, Navneet Singh, Afsaneh Alikhassi, Matthew Van Oirschot, Grey Kuling, Alex Kiss, Sonal Gandhi, Sharon Nofech-Mozes, Nicole Look Hong, Alexander Bilbily, Anne Martel, Naomi Matsuura, Belinda Curpen","doi":"10.1093/jbi/wbae022","DOIUrl":"10.1093/jbi/wbae022","url":null,"abstract":"<p><strong>Objective: </strong>Preoperative detection of axillary lymph node metastases (ALNMs) from breast cancer is suboptimal; however, recent work suggests radiomics may improve detection of ALNMs. This study aims to develop a 3D CT radiomics model to improve detection of ALNMs compared to conventional imaging features in patients with locally advanced breast cancer.</p><p><strong>Methods: </strong>Retrospective chart review was performed on patients referred to a specialty breast cancer center between 2015 and 2020 with US-guided biopsy-proven ALNMs and pretreatment chest CT. One hundred and twelve patients (224 lymph nodes) met inclusion and exclusion criteria and were assigned to discovery (n = 150 nodes) and testing (n = 74 nodes) cohorts. US-biopsy images were referenced in identifying ALNMs on CT, with contralateral nodes taken as negative controls. Positive and negative nodes were assessed for conventional features of lymphadenopathy as well as for 107 radiomic features extracted following 3D segmentation. Diagnostic performance of individual and combined radiomic features was evaluated.</p><p><strong>Results: </strong>The strongest conventional imaging feature of ALNMs was short axis diameter ≥ 10 mm with a sensitivity of 64%, specificity of 95%, and area under the curve (AUC) of 0.89 (95% CI, 0.84-0.94). Several radiomic features outperformed conventional features, most notably energy, a measure of voxel density magnitude. This feature demonstrated a sensitivity, specificity, and AUC of 91%, 79%, and 0.94 (95% CI, 0.91-0.98) for the discovery cohort. On the testing cohort, energy scored 92%, 81%, and 0.94 (95% CI, 0.89-0.99) for sensitivity, specificity, and AUC, respectively. Combining radiomic features did not improve AUC compared to energy alone (P = .08).</p><p><strong>Conclusion: </strong>3D radiomic analysis represents a promising approach for noninvasive and accurate detection of ALNMs.</p>","PeriodicalId":43134,"journal":{"name":"Journal of Breast Imaging","volume":" ","pages":"397-406"},"PeriodicalIF":2.0,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140944868","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"USPSTF Recommendations and Overdiagnosis.","authors":"R Edward Hendrick, Debra L Monticciolo","doi":"10.1093/jbi/wbae028","DOIUrl":"10.1093/jbi/wbae028","url":null,"abstract":"<p><p>Overdiagnosis is the concept that some cancers detected at screening would never have become clinically apparent during a woman's lifetime in the absence of screening. This could occur if a woman dies of a cause other than breast cancer in the interval between mammographic detection and clinical detection (obligate overdiagnosis) or if a mammographically detected breast cancer fails to progress to clinical presentation. Overdiagnosis cannot be measured directly. Indirect methods of estimating overdiagnosis include use of data from randomized controlled trials (RCTs) designed to evaluate breast cancer mortality, population-based screening studies, or modeling. In each case, estimates of overdiagnosis must consider lead time, breast cancer incidence trends in the absence of screening, and accurate and predictable rates of tumor progression. Failure to do so has led to widely varying estimates of overdiagnosis. The U.S. Preventive Services Task Force (USPSTF) considers overdiagnosis a major harm of mammography screening. Their 2024 report estimated overdiagnosis using summary evaluations of 3 RCTs that did not provide screening to their control groups at the end of the screening period, along with Cancer Intervention and Surveillance Network modeling. However, there are major flaws in their evidence sources and modeling estimates, limiting the USPSTF assessment. The most plausible estimates remain those based on observational studies that suggest overdiagnosis in breast cancer screening is 10% or less and can be attributed primarily to obligate overdiagnosis and nonprogressive ductal carcinoma in situ.</p>","PeriodicalId":43134,"journal":{"name":"Journal of Breast Imaging","volume":" ","pages":"338-346"},"PeriodicalIF":2.0,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141311930","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}