Development of a 3D Imaging Diagnostic Tool for the Improved Characterization of Metastatic Melanoma

开发 3D 成像诊断工具以改善转移性黑色素瘤的表征

• 批准号: 10241692
• 负责人: Thomas Steven Villani
• 金额: $ 84.42万
• 依托单位: VISIKOL, INC.
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-05-01 至 2023-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10241692
• 关键词: 3-Dimensional; Address; Adjuvant; Adjuvant Therapy; American Joint Committee on Cancer; Archives; Axillary lymph node group; Biological Assay; Biopsy Specimen; Caring; Cessation of life; Classification; Clinical; Clinical Laboratory Improvement Amendments; Clinical Research; Clinical Treatment; Computer software; Detection; Development; Diagnosis; Diagnostic; Diagnostic Imaging; Disease; Distant; Documentation; Economics; Evaluation; Excision; Guidelines; Histologic; Histopathology; Human Resources; Image; In Situ; Incidence; Label; Laboratories; Malignant Neoplasms; Metastatic Melanoma; Monitor; National Comprehensive Cancer Network; Neoplasm Metastasis; Nivolumab; Nonmetastatic; Operative Surgical Procedures; Outcome; Pathologist; Pathology; Patient-Focused Outcomes; Patients; Phase; Pilot Projects; Population; Primary Neoplasm; Probability; Procedures; Process; Proliferating; Protocols documentation; Quality-Adjusted Life Years; Recurrence; Reporting; Reproducibility; Sampling; Sensitivity and Specificity; Sentinel Lymph Node; Sentinel Lymph Node Biopsy; Skin Cancer; Specificity; Specimen; Statistical Models; Surveys; Testing; Three-Dimensional Imaging; Tissue imaging; Tissues; Translating; Treatment Protocols; Validation; Work; assay development; base; cancer cell; chemotherapy; clinical effect; density; diagnostic assay; diagnostic platform; digital; digital pathology; economic value; experience; follow-up; imager; imaging approach; improved; improved outcome; interest; lymph nodes; malignant breast neoplasm; melanocyte; melanoma; neoplastic cell; software development; tissue processing; tool

Summary The objective of this Phase II project is to improve outcomes and survival for patients with melanoma by reducing the number of false negative sentinel lymph node biopsies wherein metastatic disease is missed through conventional tissue processing and histological characterization. It is estimated that 4,200 patients are misdiagnosed in this manner in the US per year which results in more conservative treatment regimens for these patients than is required to effectively treat their disease. The outcome of patients not receiving the proper treatment regimen is that they experience a three-year reduction in ten-year survival which on a quality adjusted life year basis translates into a $1.2 billion economic loss. To address this problem, we have developed a three-dimensional tissue imaging and digital analysis approach which allows for the complete characterization of sentinel lymph node biopsy tissues and the identification of isolated tumor cells and micro- metastases that are commonly missed with traditional histopathology. We have demonstrated through our preliminary studies that using this approach we can identify these cancer cells in tissues that were previously characterized as node negative and that we can differentiate true negative from false negative samples. The focus of this project is to take this approach and transform it into a CLIA diagnostic assay that can be offered as a laboratory developed test to patients with negative sentinel lymph node biopsies at the conclusion of this Phase II work. Initially, the test will be offered following traditional tissue evaluation but eventually could be used as a primary diagnostic approach for all melanoma sentinel lymph node biopsy tissues. The development of this assay will be completed through conducting a retrospective clinical study in partnership with Cedars-Sinai with archived negative sentinel lymph node biopsy tissue blocks where the approach will be used to characterize these samples in their entirety. Through this study, we will demonstrate the accuracy, specificity and sensitivity of the test and will be able to quantify the extent to which it reduces the incidence of false negatives in the characterization of sentinel lymph node biopsies. Through the execution of this clinical study, we will build a statistical model that will threshold samples based upon their underlying three- dimensional features (e.g. total number of cancer cells, cancer cell aggregate volume, density of cancer cells) and classify them as ‘no metastases present’ (i.e. true negative) or ‘metastases present’ (i.e. true positive). Furthermore, the software we develop will for positive samples describe where a section should be taken from the sample for confirmation by a Visikol pathologist using traditional histopathology such that the report from the assay fits into the traditional classification paradigm. Lastly, we will transform our digital pathology software analysis approach into a 21 CFR part 11 compliant application which will be required at the conclusion of the project to start offering the assay as a CLIA test. To support this approach and to allow for the launch of a laboratory developed test, we will also build the validation documentation package and associated tests required to demonstrate the range, specificity, reproducibility, accuracy and precision of the assay. Therefore, at the conclusion of this project we will have built and validated an assay which can start to be offered to patients following the build-out of a CLIA lab and staffing with clinical personnel.

概括 该二期项目的目标是通过以下方式改善黑色素瘤患者的治疗结果和生存率： 减少漏检转移性疾病的假阴性前哨淋巴结活检数量 通过常规组织处理和组织学表征，估计有 4,200 名患者接受了治疗。 在美国每年都会以这种方式被误诊，这导致了更保守的治疗方案 这些患者比未接受治疗的患者的结果要有效治疗他们的疾病。 正确的治疗方案是，他们的十年生存率会降低三年，而这取决于质量 调整后的生命年基础转化为 12 亿美元的经济损失。 开发了一种三维组织成像和数字分析方法，可以完整地 前哨淋巴结活检组织的表征以及分离的肿瘤细胞和微生物的鉴定 我们已经通过我们的研究证明了传统组织病理学经常遗漏的转移。 初步研究表明，使用这种方法，我们可以在以前发现的组织中识别出这些癌细胞。 表征为节点阴性，我们可以区分真阴性和假阴性样本。 该项目的重点是采用这种方法并将其转化为 CLIA 诊断检测方法，可用于 作为实验室开发的测试，提供给前哨淋巴结活检阴性的患者 最初，该测试将在传统的组织评估之后进行，但最终可能会进行。 可用作所有黑色素瘤前哨淋巴结活检组织的主要诊断方法。 该检测方法的开发将通过合作进行回顾性临床研究来完成 与 Cedars-Sinai 合作，存档阴性前哨淋巴结活检组织块，该方法将在 通过这项研究，我们将证明其准确性， 测试的特异性和敏感性，并将能够量化其降低发病率的程度 通过执行该临床，前哨淋巴结活检的特征出现假阴性。 研究中，我们将建立一个统计模型，该模型将根据样本的潜在三项阈值 维度特征（例如癌细胞总数、癌细胞聚集体积、癌细胞密度） 并将其分类为“不存在转移”（即真阴性）或“存在转移”（即真阳性）。 此外，我们为阳性样本开发的软件将描述应从何处获取切片 样本由 Visikol 病理学家使用传统组织病理学进行确认，以便报告来自 最后，我们将改造我们的数字病理学软件。 分析方法进入符合 21 CFR 第 11 部分要求的应用程序，该应用程序在结束时将需要 项目开始提供该检测作为 CLIA 测试，以支持这种方法并允许启动。 实验室开发的测试，我们还将构建验证文档包和相关测试 需要证明测定的范围、特异性、再现性、准确性和精密度。 在这个项目结束时，我们将建立并验证一种可以开始提供给 CLIA 实验室扩建和临床人员配备后的患者。