Innovative Practice in Breast Health最新文献

{"title":"Exploring the potential of CRISPR in triple-negative breast cancer treatment","authors":"Lopamudra Chakravarty ,&nbsp;Sk Imtiaz Ahmad ,&nbsp;Afsona Khatun ,&nbsp;Sahabaj Ali Khan","doi":"10.1016/j.ibreh.2024.100028","DOIUrl":"10.1016/j.ibreh.2024.100028","url":null,"abstract":"<div><div>The CRISPR/Cas9 gene editing system, derived from prokaryotic adaptive defense mechanisms, has revolutionized various fields by enabling precise gene editing. Its impact has been particularly significant in cancer research, facilitating improved disease modeling, identification of new cancer-related genes, and more accurate diagnosis, especially for challenging subtypes like triple-negative breast cancer (TNBC). TNBC's resistance to targeted therapies due to the absence of hormone receptors underscores the importance of CRISPR technology. Utilizing guide RNA to direct Cas9 enzyme to specific genomic loci, the CRISPR system induces double-strand breaks, which are repaired by endogenous DNA repair mechanisms, enabling gene insertions, deletions, or modifications. The CRISPR process involves three key steps: guide RNA design and complex formation with Cas9, DNA cleavage at the target site, and cellular repair through non-homologous end joining or homology-directed repair pathways. With its versatility and precision, CRISPR/Cas9 emerges as a potent tool driving innovative cancer research and therapeutic development.</div></div>","PeriodicalId":100675,"journal":{"name":"Innovative Practice in Breast Health","volume":"7 ","pages":"Article 100028"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143154661","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":"Endoscopic mastectomy: quick and fast in 5 steps","authors":"G. Rathat ,&nbsp;C. Vaysse","doi":"10.1016/j.ibreh.2025.100039","DOIUrl":"10.1016/j.ibreh.2025.100039","url":null,"abstract":"","PeriodicalId":100675,"journal":{"name":"Innovative Practice in Breast Health","volume":"7 ","pages":"Article 100039"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144312967","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 detection redefined: Integrating Xception and EfficientNet-B5 for superior mammography imaging","authors":"Niha Talukdar ,&nbsp;Anchita Kakati ,&nbsp;Upasana Barman ,&nbsp;Jyoti Prakash Medhi ,&nbsp;Kandarpa Kumar Sarma ,&nbsp;Geetanjali Barman ,&nbsp;Binoy Kumar Choudhury","doi":"10.1016/j.ibreh.2025.100038","DOIUrl":"10.1016/j.ibreh.2025.100038","url":null,"abstract":"<div><h3>Background and Objective:</h3><div>Breast cancer is a major cause of female mortality, with early detection crucial for effective treatment. This study aims to enhance mammographic breast cancer detection by integrating an autoencoder’s encoder unit with advanced Convolutional Neural Networks (CNNs), incorporating soft attention gates and feature merging for improved accuracy. A custom multi-head attention mechanism is utilized for precise tumor segmentation, with a focus on robust validation across diverse datasets.</div></div><div><h3>Methods:</h3><div>The research involved 3816 mammogram samples (2376 benign, 1440 malignant) and employed deep learning techniques combining model fusion and autoencoders for classification. A custom multi-head attention mechanism was applied for tumor segmentation. The models were validated on publicly available datasets, MIAS and CBIS-DDSM.</div></div><div><h3>Results:</h3><div>On the MIAS dataset, Xception and EfficientNet-B5 CNN models outperformed others, achieving a classification accuracy of 96.88% after autoencoder integration. For segmentation, the model demonstrated strong alignment with tumor regions, achieving a Dice Coefficient of 0.4353, Intersection over Union (IoU) of 0.2998, and F1-Score of 0.4318.</div></div><div><h3>Conclusion:</h3><div>This study developed a robust deep learning approach combining Xception and EfficientNet-B5 for breast cancer diagnosis and segmentation. The fused model demonstrated high classification accuracy and reliable segmentation performance, indicating strong potential for clinical applications in early breast cancer detection and treatment planning.</div></div>","PeriodicalId":100675,"journal":{"name":"Innovative Practice in Breast Health","volume":"7 ","pages":"Article 100038"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144491582","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":"History of breast reconstruction : Towards the era of endoscopic mastectomy ?","authors":"Gauthier Rathat,&nbsp;Martha Duraes","doi":"10.1016/j.ibreh.2025.100035","DOIUrl":"10.1016/j.ibreh.2025.100035","url":null,"abstract":"","PeriodicalId":100675,"journal":{"name":"Innovative Practice in Breast Health","volume":"7 ","pages":"Article 100035"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143681248","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":"Proposed French recommendations for breast cancer screening in the trans population","authors":"Susie Brousse ,&nbsp;Marie-Catherine Morin-Charbonnier ,&nbsp;Sophie Guillermet ,&nbsp;Maïté Briet ,&nbsp;Sophie Harter ,&nbsp;Céline Lescure ,&nbsp;Louise Crivelli ,&nbsp;Jeanne Lemerre-Poincloux ,&nbsp;Bernadette Leproust ,&nbsp;Marine Tas ,&nbsp;Ariane Weyl ,&nbsp;Lucas Freton","doi":"10.1016/j.ibreh.2025.100041","DOIUrl":"10.1016/j.ibreh.2025.100041","url":null,"abstract":"<div><h3>Introduction</h3><div>Transgender patients are increasingly able to assert their gender identity. Nevertheless, their access to care is still limited, mainly due to poorly trained and informed healthcare professionals. Because of a growing incidence of breast cancer (BC) and insufficient screening in France, it is vital to improve access for trans people. Therefore, we aim to produce the first French recommendations adapted to them.</div></div><div><h3>Materials and methods</h3><div>This work is based on the recommendations of the WPATH, the ACR, and a review of the literature.</div></div><div><h3>Results</h3><div>First, there is no excess risk of BC in the trans population. The risk for trans women is 0.3 times that of <em>cis</em> women, 47 times that of <em>cis</em> men, and twice that of trans men. The risk for trans men is 59 times that of <em>cis</em> men, and 0.2 times that of <em>cis</em> women (reduced by the use of testosterone and torsoplasty). The recommendations for BC screening are thus the same for trans men without torsoplasty, and for trans women after 5 years of gender-affirming hormone therapy, as for <em>cis</em> women. These should be adapted to the personal and family histories.</div></div><div><h3>Discussion</h3><div>The lack of inclusion of trans patients in studies makes it impossible to give recommendations that differ from those for <em>cis</em> women. The training of healthcare professionals and the provision of information to patients are vital to the screening and prevention of BC, which are mainly hormone-dependent, thus often contraindicating the gender-affirming hormone therapy essential for trans patients afterwards.</div></div>","PeriodicalId":100675,"journal":{"name":"Innovative Practice in Breast Health","volume":"7 ","pages":"Article 100041"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144548473","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":"Preventive, personalized, and precision medicine and biomarkers for breast cancer diagnosis: Artificial intelligence framework","authors":"Udita J. Monani ,&nbsp;Suchismita Das ,&nbsp;Sanjay Saxena ,&nbsp;Gavino Faa ,&nbsp;Manudeep K. Kalra ,&nbsp;John R. Laird ,&nbsp;Mustafa Al-Maini ,&nbsp;Inder M. Singh ,&nbsp;Laura Mantella ,&nbsp;Narendra N. Khanna ,&nbsp;Rajesh Singh ,&nbsp;Vijay Rathore ,&nbsp;Ekta Tiwari ,&nbsp;Amer M. Johri ,&nbsp;Mostafa M. Fouda ,&nbsp;Esma R. Isenovic ,&nbsp;Mario Scartozzi ,&nbsp;Pankaj Kumar Jain PhD ,&nbsp;Luca Saba ,&nbsp;Jasjit S. Suri","doi":"10.1016/j.ibreh.2025.100045","DOIUrl":"10.1016/j.ibreh.2025.100045","url":null,"abstract":"<div><div>Personalized medicine is needed since standard breast cancer diagnosis and treatment are not always exact or customized. To revolutionize breast cancer diagnosis, this paper examines the clinical utility of artificial intelligence (AI), specifically deep learning (DL). The accuracy with which AI can analyze vast medical databases—genetic data, clinical background, and images— enabling improved accuracy in diagnosis, staging, and treatment planning through integration of multimodal data.</div><div>Recent studies have shown that DL algorithms have already attained 94–98 % diagnostic accuracies in recognizing breast cancer subtypes from histopathological images, against the overall accuracy of approximately 88 % of an average human pathologist. Additionally, CNNs have achieved AUC values of &gt;0.95 in distinguishing between malignant and benign breast lesions based on mammography, substantiating the fact that AI enhances the diagnostic accuracy with a significant improvement.</div><div>The study highlights a few case studies, such as fibroadenoma, invasive lobular carcinoma (ILC), lobular carcinoma in situ (LCIS), and sclerosing adenosis (SAD), to illustrate how DL algorithms outperform human experts in early detection and correct diagnosis. Incorporating DL into personalized medicine not only guarantees more specialized and effective treatment plans but also guarantees a future where every patient with breast cancer will be treated with personalized care. Other than referencing AI's revolutionizing impact on breast cancer screening, this research offers an unassailable case for adopting AI and signals a new epoch of accurate, patient-centered medicine.</div></div>","PeriodicalId":100675,"journal":{"name":"Innovative Practice in Breast Health","volume":"7 ","pages":"Article 100045"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145048125","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 review of the literature: Mammography positioning, body habitus (thorax) and image evaluation system","authors":"Ruth Pape ,&nbsp;Caryn West","doi":"10.1016/j.ibreh.2025.100034","DOIUrl":"10.1016/j.ibreh.2025.100034","url":null,"abstract":"<div><div>The early detection of breast cancer using mammography relies on optimal positioning of the craniocaudal (CC) and the mediolateral oblique (MLO) views to include as much of the breast as possible; and subsequent assessment of image quality using valid image evaluation systems (IES). This review highlights the key positioning literature and IES; and discusses the fundamental issues impacting best practice positioning including body habitus, specifically the thorax. Due to variations in the shape of the thorax and the impact of the linear image receptor (IR) on positioning, the inclusion of all breast tissue may not be possible. Further, body habitus, including the shape of the thorax, is not reflected in any IES. Although used worldwide the lack of consideration given to individual body habitus is a key deficit of all IES. There is no mention in the literature of how to manage thoracic variability to maximise breast tissue inclusion outside of the selection of the angle of the IR in the MLO view. No known studies have investigated the degree to which the oppositional curvilinear thorax and the linear mammography IR impact the amount of breast able to be included in the image. Both issues support the need for future research.</div></div>","PeriodicalId":100675,"journal":{"name":"Innovative Practice in Breast Health","volume":"7 ","pages":"Article 100034"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143512138","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":"Ours","authors":"","doi":"10.1016/S2950-2128(24)00031-9","DOIUrl":"10.1016/S2950-2128(24)00031-9","url":null,"abstract":"","PeriodicalId":100675,"journal":{"name":"Innovative Practice in Breast Health","volume":"5 ","pages":"Article 100031"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143128772","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":"Advancements in managing pure ductal carcinoma in situ: An 18-year artificial intelligence-aided analysis of 998 patients","authors":"Jonathan Sabah ,&nbsp;Charmène Cruchet ,&nbsp;Mousselim Gharbi ,&nbsp;Marie-Pierre Chenard ,&nbsp;Antoine Simoulin ,&nbsp;Nicolas Thiebaut ,&nbsp;Karl Neuberger ,&nbsp;Sébastien Molière ,&nbsp;Carole Mathelin","doi":"10.1016/j.ibreh.2024.100022","DOIUrl":"10.1016/j.ibreh.2024.100022","url":null,"abstract":"<div><h3>Introduction</h3><div>The integration of artificial intelligence (AI) in oncological diseases has opened new avenues for early cancer detection, accurate risk assessments, and personalized treatment protocols. The objective of our study was to describe the shift in the treatment indications and prognosis of ductal carcinoma in situ (DCIS) in a prospective cohort of 998 patients managed over 18 years at a single University Hospital in France.</div></div><div><h3>Methods</h3><div>This analysis included all patients managed for DCIS at the University Hospitals of Strasbourg between January 14, 2002, and December 18, 2019, from the prospective SENOMETRY cohort, which initially included 9599 patients with both in situ and invasive breast cancer. Data were analyzed using Onconum, an AI-based natural language processing tool, to extract structured information from medical records.</div></div><div><h3>Results</h3><div>The incidence of DCIS remained stable at 65 new cases per year. The mean age at diagnosis increased from 55 years in 2002 to 61 years in 2019. There was a significant rise in high-grade DCIS (DIN3) cases from 25% to 35%. The re-excision rate decreased from 57% in 2002 to 18% in 2019. Most DCIS cases were managed with breast-conserving surgeries (682), while total mastectomies accounted for 385 cases. Sentinel lymph node biopsy was performed in 39% of cases, primarily in high-grade and multifocal DCIS. Specific mortality was 0%, with a recurrence rate of 2.2%, predominantly invasive and occurring earlier in high-grade DCIS. Discussion: Over 18 years, there has been a notable shift in the clinicopathological characteristics of DCIS, with an increase in patient age at diagnosis and higher histopathological grades. Therapeutic management evolved significantly, with reduced surgical margins and fewer adjuvant treatments, while maintaining low and stable recurrence rates. AI significantly enhanced data extraction and analysis efficiency, contributing to better clinical decision-making.</div></div><div><h3>Conclusion</h3><div>The study confirms the possibility of therapeutic de-escalation in DCIS, supported by AI-driven data analysis, allowing individualized treatment approaches and leading to optimized patient outcomes.</div></div>","PeriodicalId":100675,"journal":{"name":"Innovative Practice in Breast Health","volume":"5 ","pages":"Article 100022"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142746642","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":"A critical analysis of the potential of formal education programs in breast cancer management in Iran: A Qualitative Content Analysis","authors":"Koosha Rokhzadi ,&nbsp;Saeed Khani ,&nbsp;Kamal Khaleghpanah ,&nbsp;Hossein Daneshmehr ,&nbsp;Kaveh Haji-Allahverdipoor","doi":"10.1016/j.ibreh.2024.100023","DOIUrl":"10.1016/j.ibreh.2024.100023","url":null,"abstract":"<div><h3>Background</h3><div>Education serves as the cornerstone for acquiring essential life skills, yet the conventional structure of academic programs often fails to bridge the gap between theoretical knowledge and its practical application, particularly evident in developing nations. This discrepancy extends to healthcare, notably concerning the challenge of breast cancer on a global scale.</div></div><div><h3>Objectives</h3><div>This study aims to explore the potential of formal biology programs within public education systems to address breast cancer prognosis through qualitative content analysis.</div></div><div><h3>Methods</h3><div>This investigation incorporates qualitative methodologies to elucidate the potential implications of such programs. qualitative content analysis method was conducted by comprehensive examination of formal general Biology programs within the public education sphere worldwide has been undertaken, explicitly emphasizing their relevance to breast cancer prognosis initiatives. Additionally, documentary research and literature reviews have been employed to augment the analytical framework of this study.</div></div><div><h3>Results</h3><div>The analysis uncovers a significant void in current educational frameworks regarding breast cancer awareness and self-examination. With projections indicating a surge in breast cancer cases by 2040, the imperative to address this educational gap becomes increasingly urgent. Integrating breast cancer education into formal schooling emerges as a promising avenue to empower individuals with vital self-healthcare knowledge and early detection skills.</div></div><div><h3>Conclusion</h3><div>By equipping students with life-saving skills, such proactive educational measures hold promise in mitigating the global burden of breast cancer, potentially reducing both mortality rates and incidence worldwide. Our study, through qualitative content analysis, developed a curriculum to enhance students' understanding of breast cancer. In Iran, updating the \"Health and Hygiene\" textbook to include breast cancer information is crucial. This curriculum aims to improve health literacy and proactive healthcare, ultimately contributing to better health outcomes and the global fight against breast cancer.</div></div>","PeriodicalId":100675,"journal":{"name":"Innovative Practice in Breast Health","volume":"5 ","pages":"Article 100023"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142746656","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}