An integrated spectroscopy-ultrasound surgical navigation system for residual cancer detection in breast surgery.
用于乳腺手术中残留癌症检测的集成光谱超声手术导航系统。
基本信息
- 批准号:538824-2019
- 负责人:
- 金额:$ 9.79万
- 依托单位:
- 依托单位国家:加拿大
- 项目类别:Collaborative Health Research Projects
- 财政年份:2020
- 资助国家:加拿大
- 起止时间:2020-01-01 至 2021-12-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Breast cancer affects 1 in 8 women during their lives and is the second-leading cause of female cancer related deaths. The ideal treatment is breast-conservation surgery , during its early stage, to remove cancer while conserving healthy tissue.
Unfortunately, the current resection methods have high positive margin rates (when cancer cells are found on the edge of the resected specimen) of up to nearly 40%. Positive margins are linked to high probability of recurrence and thus require repeat
surgery. On average, one out of every three women undergoing breast-conservation surgery needs at least one additional surgery due to positive margins. Repeat surgery leads to increased risk of postoperative complications, impaired cosmetics, delayed radiation therapy, increased psychological distress, and increased costs and risks of a
second general anesthesia. Repeat surgery often leads to full mastectomy, which is a traumatic experience for a patient who expected a curative treatment with breastconservation. Through development of a unique surgical navigation system that
integrates intra-operative ultrasound imaging with an acoustic spectroscopy technique, we intend to ensure that the resection cavity is clear of cancer before releasing the patient from the operating table. We take advantage of conventional ultrasound
scanners, while building a unique spectroscopic-ultrasound probe, and thus the resulting system will be affordable and accessible to all care facilities in Canada. The proposed system should enable significant reduction in positive margin rates, thereby reducing the number of repeat surgeries, and yielding significant quality of life benefits to patients and a significant reduction in health care costs.
乳腺癌影响八分之一的女性一生,是女性癌症相关死亡的第二大原因。理想的治疗方法是在早期阶段进行保乳手术,以切除癌症,同时保留健康组织。
不幸的是,目前的切除方法的阳性切缘率(当在切除标本的边缘发现癌细胞时)高达近40%。切缘阳性与复发概率高相关,因此需要重复
外科手术。平均而言,三分之一接受保乳手术的女性由于切缘阳性而需要至少进行一次额外手术。重复手术会导致术后并发症、美容受损、放射治疗延迟、心理困扰增加以及手术费用和风险增加的风险增加。
第二次全身麻醉。重复手术通常会导致全乳房切除术,这对于希望通过保乳进行治愈性治疗的患者来说是一次痛苦的经历。通过开发独特的手术导航系统
将术中超声成像与声学光谱技术相结合,我们打算在将患者从手术台上释放之前确保切除腔内没有癌症。我们利用传统超声波
扫描仪,同时构建独特的光谱超声探头,因此加拿大所有护理机构都可以负担得起并使用由此产生的系统。拟议的系统应能够显着降低正利润率,从而减少重复手术的次数,并为患者带来显着的生活质量效益并显着降低医疗保健成本。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Mousavi, Parvin其他文献
iPINBPA: an integrative network-based functional module discovery tool for genome-wide association studies.
iPINBPA:一种基于网络的综合功能模块发现工具,用于全基因组关联研究。
- DOI:
- 发表时间:
2015 - 期刊:
- 影响因子:0
- 作者:
Wang, Lili;Mousavi, Parvin;Baranzini, Sergio E - 通讯作者:
Baranzini, Sergio E
Transfer learning from RF to B-mode temporal enhanced ultrasound features for prostate cancer detection.
从 RF 到 B 模式时间增强超声特征的迁移学习,用于前列腺癌检测。
- DOI:
- 发表时间:
2017-07 - 期刊:
- 影响因子:0
- 作者:
Azizi, Shekoofeh;Mousavi, Parvin;Yan, Pingkun;Tahmasebi, Amir;Kwak, Jin Tae;Xu, Sheng;Turkbey, Baris;Choyke, Peter;Pinto, Peter;Wood, Bradford;Abolmaesumi, Purang - 通讯作者:
Abolmaesumi, Purang
A user-driven machine learning approach for RNA-based sample discrimination and hierarchical classification
一种用户驱动的机器学习方法,用于基于 RNA 的样本区分和层次分类
- DOI:
10.1016/j.xpro.2023.102661 - 发表时间:
2023-10-31 - 期刊:
- 影响因子:0
- 作者:
Imtiaz, Tashifa;Nanayakkara, Jina;Fang, Alexis;Jomaa, Danny;Mayotte, Harrison;Damiani, Simona;Javed, Fiza;Jones, Tristan;Kaczmarek, Emily;Adebayo, Flourish Omolara;Imtiaz, Uroosa;Li, Yiheng;Zhang, Richard;Mousavi, Parvin;Renwick, Neil;Tyryshkin, Kathrin - 通讯作者:
Tyryshkin, Kathrin
Computer-aided diagnosis of prostate cancer with emphasis on ultrasound-based approaches: A review
- DOI:
10.1016/j.ultrasmedbio.2007.01.008 - 发表时间:
2007-07-01 - 期刊:
- 影响因子:2.9
- 作者:
Moradi, Mehdi;Mousavi, Parvin;Abolmaesumi, Purang - 通讯作者:
Abolmaesumi, Purang
Deep neural maps for unsupervised visualization of high-grade cancer in prostate biopsies.
用于前列腺活检中高级癌症的无监督可视化的深层神经图谱。
- DOI:
- 发表时间:
2019-06 - 期刊:
- 影响因子:0
- 作者:
Sedghi, Alireza;Pesteie, Mehran;Javadi, Golara;Azizi, Shekoofeh;Yan, Pingkun;Kwak, Jin Tae;Xu, Sheng;Turkbey, Baris;Choyke, Peter;Pinto, Peter;Wood, Bradford;Rohling, Robert;Abolmaesumi, Purang;Mousavi, Parvin - 通讯作者:
Mousavi, Parvin
Mousavi, Parvin的其他文献
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{{ truncateString('Mousavi, Parvin', 18)}}的其他基金
Learning Algorithms for Predictive Modeling in Biomedical Computing: Methods and Applications
生物医学计算中预测建模的学习算法:方法与应用
- 批准号:
RGPIN-2020-07117 - 财政年份:2022
- 资助金额:
$ 9.79万 - 项目类别:
Discovery Grants Program - Individual
Learning Algorithms for Predictive Modeling in Biomedical Computing: Methods and Applications
生物医学计算中预测建模的学习算法:方法与应用
- 批准号:
RGPIN-2020-07117 - 财政年份:2022
- 资助金额:
$ 9.79万 - 项目类别:
Discovery Grants Program - Individual
CREATE Training Program in Medical Informatics: Preparing Canada's Workforce for Health Data of Tomorrow
创建医疗信息学培训计划:让加拿大劳动力为明天的健康数据做好准备
- 批准号:
555366-2021 - 财政年份:2021
- 资助金额:
$ 9.79万 - 项目类别:
Collaborative Research and Training Experience
Learning Algorithms for Predictive Modeling in Biomedical Computing: Methods and Applications
生物医学计算中预测建模的学习算法:方法与应用
- 批准号:
RGPIN-2020-07117 - 财政年份:2021
- 资助金额:
$ 9.79万 - 项目类别:
Discovery Grants Program - Individual
Learning Algorithms for Predictive Modeling in Biomedical Computing: Methods and Applications
生物医学计算中预测建模的学习算法:方法与应用
- 批准号:
RGPIN-2020-07117 - 财政年份:2021
- 资助金额:
$ 9.79万 - 项目类别:
Discovery Grants Program - Individual
CREATE Training Program in Medical Informatics: Preparing Canada's Workforce for Health Data of Tomorrow
创建医疗信息学培训计划:让加拿大劳动力为明天的健康数据做好准备
- 批准号:
555366-2021 - 财政年份:2021
- 资助金额:
$ 9.79万 - 项目类别:
Collaborative Research and Training Experience
Learning Algorithms for Predictive Modeling in Biomedical Computing: Methods and Applications
生物医学计算中预测建模的学习算法:方法与应用
- 批准号:
RGPIN-2020-07117 - 财政年份:2020
- 资助金额:
$ 9.79万 - 项目类别:
Discovery Grants Program - Individual
Learning Algorithms for Predictive Modeling in Biomedical Computing: Methods and Applications
生物医学计算中预测建模的学习算法:方法与应用
- 批准号:
RGPIN-2020-07117 - 财政年份:2020
- 资助金额:
$ 9.79万 - 项目类别:
Discovery Grants Program - Individual
An integrated spectroscopy-ultrasound surgical navigation system for residual cancer detection in breast surgery.
用于乳腺手术中残留癌症检测的集成光谱超声手术导航系统。
- 批准号:
538824-2019 - 财政年份:2019
- 资助金额:
$ 9.79万 - 项目类别:
Collaborative Health Research Projects
An integrated spectroscopy-ultrasound surgical navigation system for residual cancer detection in breast surgery.
用于乳腺手术中残留癌症检测的集成光谱超声手术导航系统。
- 批准号:
538824-2019 - 财政年份:2019
- 资助金额:
$ 9.79万 - 项目类别:
Collaborative Health Research Projects
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