Breast-conserving surgery resection margin assessment using optical light active line scanning

使用光学主动线扫描评估保乳手术切除边缘

• 批准号: 10314211
• 负责人: Samuel Stewart Streeter
• 金额: $ 4.6万
• 依托单位: DARTMOUTH COLLEGE
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-07-22 至 2023-07-21
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10314211
• 关键词: 3-Dimensional; Address; Adjuvant Therapy; Assessment tool; Benign; Biomedical Engineering; Bread; Breast-Conserving Surgery; Cancer Patient; Classification; Clinical; Clinical Trials; Code; Collagen; Color; Computer software; Cosmetics; Coupled; Data; Data Analyses; Data Collection; Development; Diffuse; Early treatment; Educational process of instructing; Educational workshop; Epithelial; Excision; Fellowship; Goals; Gold; Grant; Growth; Health; Health Care Costs; Histopathology; Hour; Human Resources; Image; Image-Guided Surgery; Imagery; Imaging Techniques; Individual; Institutional Review Boards; Lasers; Lateral; Lead; Left; Light; Machine Learning; Malignant - descriptor; Malignant Neoplasms; Mammary Gland Parenchyma; Mammary Neoplasms; Manuscripts; Masks; Measures; Medical center; Mentors; Mentorship; Modeling; Monte Carlo Method; Morbidity - disease rate; Morphologic artifacts; Nature; Operative Surgical Procedures; Optical Methods; Optics; Outcome; Pathologic; Pathologist; Pathology; Patients; Performance; Phase; Postoperative Period; Procedures; Property; Protocols documentation; Publishing; Publishing Peer Reviews; Radiation therapy; Radiology Specialty; Research; Research Personnel; Research Project Grants; Residual Tumors; Resolution; Sampling; Scanning; Sensitivity and Specificity; Slice; Slide; Specimen; Speed; Structure; Supervision; Surface; Surgeon; System; Technical Expertise; Technology; Technology Assessment; Testing; Time; Tissues; Training; Translating; Translations; Vision; Work; Writing; anticancer research; application programming interface; bioimaging; breast imaging; breast pathology; cancer invasiveness; cancer subtypes; career; common treatment; design; digital; experience; imaging modality; imaging system; improved; light scattering; malignant breast neoplasm; novel; optical imaging; prospective; radiomics; standard of care; success; tool; tumor; undergraduate student

The rate of re-excision procedures to remove residual tumor left behind after initial resection is high in cancer patients undergoing breast-conserving surgery (BCS) due to the limited intraoperative tools available to the surgeon. The gold standard for BCS specimen margin assessment is histopathological analysis, which is post- operative in nature and can take hours to days to complete. The development of intraoperative margin assessment technology to help the surgeon effectively resect the entire breast tumor during the initial BCS is of paramount importance to reduce patient morbidity, patient disfigurement, and healthcare costs associated with BCS re-excisions. The primary objective of the proposed research project is to further develop a new form of optical imaging, sub-diffuse line scanning (SDLS), to evaluate its value for intraoperative assessment of BCS specimen margins. The first aim is to develop an optimized SDLS system. This aim involves hardware improvements to increase the speed of scanning, enable multi-wavelength acquisition, mitigate specular reflection artifacts, and provide high spatial resolution images. The second aim is to collect SDLS image data of BCS specimens in two phases: first, post-operatively in parallel with standard of care pathological processing, and second, intraoperatively, immediately after excision. In the first phase, line scans will be collected from individual bread loaf slices from each BCS specimen. The image data will be conservatively co-registered with histopathology with guidance from an expert pathologist. In the second phase, line scans of freshly excised, whole specimens will demonstrate the ability to image actual intact BCS specimen margins using SDLS. The third aim is to train a margin classification model using radiomic image features extracted from confirmed tissue subtype regions in the phase 1 bread loaf slice images. The model will be tested on the intraoperative phase 2 images of actual BCS specimen margins. The optimized SDLS system, coupled with the classification model, could eventually be translated into a prospective clinical trial to assess its performance as an intraoperative margin assessment tool. The proposed fellowship training plan involves broadening technical expertise in optical system design, compressive sensing, multivariate data analysis, and machine learning, and includes clinical experiences in breast tissue pathology, radiology, and surgery. Professional development activities include formal presentations to biomedical imaging and clinical audiences, grant writing workshops and R01 grant writing experience, undergraduate mentoring, and teaching. The training plan incorporates publishing peer-reviewed manuscripts from the proposed research. Fellowship sponsors and collaborators are experts with specific expertise in surgery, breast pathology, radiology, biomedical optics, machine learning, and biomedical engineering. The applicant will work closely with the mentoring team to accomplish the aims of the project and to continue developing into an independent, productive, and impactful researcher in biomedical optics and cancer research.

在癌症中，初次切除后残留肿瘤的再次切除率很高 由于术中工具有限， 外科医生BCS标本边缘评估的金标准是组织病理学分析， 操作性质，可能需要数小时至数天才能完成。术中切缘的发展 评估技术，以帮助外科医生有效地切除整个乳房肿瘤在最初的BCS是 最重要的是减少患者发病率，患者毁容，以及与之相关的医疗保健成本。 BCS再切除。 拟议研究项目的主要目标是进一步开发一种新的光学成像形式， 亚弥散线扫描（SDLS），以评价其在术中评估BCS标本边缘的价值。 第一个目标是开发一个优化的SDLS系统。这一目标涉及硬件改进，以增加 扫描速度、实现多波长采集、减轻镜面反射伪影并提供 高空间分辨率图像。第二个目的是分两个阶段收集BCS标本的SDLS图像数据： 第一，术后与标准护理病理处理并行，第二，术中， 切除后立即。在第一阶段，将从单个面包切片中收集线扫描， 每个BCS样本。图像数据将在以下指导下与组织病理学保守共配准： 病理学家专家在第二阶段，对新鲜切除的完整标本进行线扫描， 使用SDLS对实际完整BCS标本边缘成像的能力。第三个目标是训练一个边缘分类 使用从阶段1面包中确认的组织亚型区域提取的放射组学图像特征的模型 切片图像。将在实际BCS标本边缘的术中第2阶段图像上测试该模型。 优化的SDLS系统，加上分类模型，最终可以转化为一个 前瞻性临床试验，以评估其作为术中切缘评估工具的性能。 拟议的研究金培训计划涉及扩大光学系统设计方面的技术专门知识， 压缩传感，多变量数据分析和机器学习，并包括临床经验， 乳腺组织病理学、放射学和外科学。专业发展活动包括正式的演讲 生物医学成像和临床观众，授予写作研讨会和R01授予写作经验， 本科生指导和教学。培训计划包括出版同行评审的手稿 从拟议的研究。研究金赞助者和合作者是在以下方面具有特定专长的专家： 外科、乳腺病理学、放射学、生物医学光学、机器学习和生物医学工程。的 申请人将与指导团队密切合作，以实现项目的目标，并继续 发展成为生物医学光学和癌症研究领域的独立，多产和有影响力的研究人员。