Quantitative Fluorescence Imaging-Guided Detection and Targeted Therapy Monitoring Platform for Ovarian Cancer Micrometastases

卵巢癌微转移定量荧光成像引导检测及靶向治疗监测平台

• 批准号: 10219200
• 负责人: Ulas Sunar
• 金额: $ 33.66万
• 依托单位: WRIGHT STATE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-08-01 至 2025-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10219200
• 关键词: Acids; Address; Adjuvant Chemotherapy; Algorithms; Antineoplastic Agents; Biodistribution; Biopsy; Cancer Patient; Cell Culture Techniques; Cell Line; Clinic; Clinical; Combination Drug Therapy; Data; Detection; Diagnosis; Disease; Dose; Doxorubicin; Drug Targeting; Ensure; Epithelial; Epithelial ovarian cancer; Excision; Exposure to; FOLR1 gene; Feedback; Fluorescence; Folic Acid; Goals; Image; Imaging technology; In Vitro; Kinetics; Laparoscopes; Lead; Lesion; Light; Lighting; Lipids; Liposomal Doxorubicin; Liposomes; Malignant Neoplasms; Malignant neoplasm of gastrointestinal tract; Malignant neoplasm of lung; Malignant neoplasm of ovary; Maps; Metastatic Malignant Neoplasm to the Ovary; Micrometastasis; Microscopic; Modality; Monitor; Neoplasm Metastasis; Nodule; Normal tissue morphology; Operative Surgical Procedures; Ovarian; Ovarian Carcinoma; PUVA Photochemotherapy; Patients; Pharmaceutical Preparations; Phospholipids; Photosensitizing Agents; Phototherapy; Physiological; Platinum; Porphyrins; Protocols documentation; Public Health; Quality of life; Recurrence; Resistance; Resolution; Scheme; Sensitivity and Specificity; Shapes; Signal Transduction; Spatial Frequency Domain Imaging; Structure; Surface; Survival Rate; System; Technology; Therapeutic; Time; Tissues; Toxic effect; Translating; Treatment Efficacy; Treatment-related toxicity; Visualization; absorption; anti-cancer; attenuation; base; cancer cell; cancer diagnosis; cancer therapy; chemotherapy; contrast enhanced; controlled release; deep learning; deep learning algorithm; fluorescence imaging; image guided; image guided therapy; image-guided drug delivery; imaging approach; imaging modality; imaging platform; improved; in vivo; intraperitoneal; liposome vector; malignant mouth neoplasm; nano; nanocarrier; nanomedicine; novel; optical imaging; phantom model; quantitative imaging; side effect; spatiotemporal; targeted treatment; treatment optimization; tumor; tumor specificity; uptake

PROJECT SUMMARY/ABSTRACT A major challenge in the management of advanced ovarian cancer is the presence of disseminated microscopic tumor nodules within the intraperitoneal cavity. Despite surgery and adjuvant chemotherapy, as many as 50% of patients can show occult disseminated disease, with only a 43% survival rate. Furthermore, systemic chemotherapy can have toxic side effects. Thus, recent efforts have aimed at improving detection and treatment of micromets. Chemophototherapy (CPT), the combination of chemotherapy and photodynamic therapy, is an emerging cancer treatment modality that can provide synergistic efficacy of both therapies. The overall goal is to implement a quantitative laparoscopic imaging and treatment approach for advanced detection of micromets and optimization of CPT for targeted destruction of ovarian micromets and reduced toxic side effects. Quantitative fluorescence laparoscopic imaging will provide high sensitivity and resolution for detecting micromets as well as image guided drug delivery. Folate receptor alpha (FA) will be used as a promising target because it is highly specific of epithelial ovarian cancer. The proposed targeted CPT compound has a ~6-fold tumor-specificity providing enhanced fluorescence contrast. These folate-targeted, porphyrin-phospholipid doped liposomes are triggered directly by near infrared (NIR) light. This activates the anti-cancer photosensitizer outer layer and releases the anti-cancer agent Doxorubicin (Dox). While this nanocarrier is expected to improve detection of micromets, tissue absorption and scattering in living tissue can confound fluorescence contrast. Quantitative imaging based on spatial frequency domain imaging can eliminate these confounding effects and provide quantitative contrasts to enable more sensitive detection compared to raw fluorescence or white light visualization. Furthermore, this quantitative capability can function in near-real-time to provide feedback on drug release, thus allowing image-guided optimization of treatment light to ensure full drug release within each tumor. In Aim 1, a wide-field dual-channel laparoscope, fast quantification algorithms and targeted liposomal nano-construct will be implemented and optimized. In Aim 2, the platform will be validated in vivo for improved detection of micromets vs. raw fluorescence and white light. In Aim 3, the platform’s efficacy will be validated in vivo for destroying micromets in targeted tumors while reducing toxicity to surrounding normal tissues. Successful completion of this approach is expected to result in improved detection and treatment of micromets with reduced side effects. This is ultimately expected to lead to reduced recurrence rates and overall improved survival. Although this imaging approach focuses on epithelial ovarian cancer diagnosis and treatment, it can be applicable to a wide range of epithelial diseases, such as oral, lung, and gastrointestinal cancers.

项目概要/摘要 晚期卵巢癌治疗的一个主要挑战是存在播散性卵巢癌 尽管进行了手术和辅助化疗，但腹腔内仍存在显微肿瘤结节。 多达 50% 的患者可表现出隐匿性播散性疾病，存活率仅为 43%。此外， 全身化疗可能会产生毒副作用，因此，最近的努力旨在改善检测。 和化学光疗（CPT）治疗，即化疗和光动力的结合。 疗法，是一种新兴的癌症治疗方式，可以提供两种疗法的协同功效。 总体目标是针对晚期患者实施定量腹腔镜成像和治疗方法 检测 micromets 并优化 CPT，以定向破坏卵巢 micromets 并减少 定量荧光腹腔镜成像将为您提供高灵敏度和分辨率。 检测 micromets 以及图像引导的药物输送将被用作 有希望的目标，因为它对上皮性卵巢癌具有高度特异性。 化合物具有约 6 倍的肿瘤特异性，可增强这些叶酸靶向的荧光对比度。 卟啉磷脂掺杂的脂质体由近红外 (NIR) 光直接触发，从而激活。 抗癌光敏剂外层并释放抗癌剂阿霉素（Dox）。 纳米载体有望改善活体组织中微米、组织吸收和散射的检测 基于空间频域成像的定量成像可以混淆。 消除这些混杂效应并提供定量对比以实现更灵敏的检测 与原始荧光或白光可视化相比，这种定量功能也可以发挥作用。 近乎实时地提供药物释放反馈，从而实现图像引导优化治疗 光确保每个肿瘤内的药物充分释放 In Aim 1，宽视野双通道腹腔镜，快速。 在目标 2 中，将实施和优化量化算法和靶向脂质体纳米结构。 该平台将在体内进行验证，以改进微米计量学与原始荧光和白光的检测。 在目标 3 中，将在体内验证该平台在破坏目标肿瘤中的 micromets 方面的功效，同时 成功完成该方法有望减少对周围正常组织的毒性。 改进微米计量学的检测和治疗并减少副作用，这最终有望实现。 尽管这种成像方法侧重于上皮细胞，但复发率降低并总体提高了生存率。 卵巢癌的诊断和治疗，可适用于多种上皮疾病，如 口腔癌、肺癌和胃肠癌。