Molecularly aware robotics for surgery (MARS)
Molecularly aware robotics for surgery (MARS)
批准号:
EP/W004798/1
负责人:
Zoltan Takats
金额:
$38.52万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2021
资助国家:
英国
项目状态:
已结题
起止时间:
2021 至 --
中文摘要
建议的项目旨在开发一种半自主的手术机器人平台,用于以前所未有的精度切除肿瘤。目前,当外科医生切除肿瘤时,他们使用手术前收集的信息(超声波、X光)来定位肿瘤,并根据他们用指尖看到或感觉到的东西来评估肿瘤的实际范围。不幸的是,通过外观几乎不可能区分健康组织和癌症浸润性组织,这导致了漫长的手术,包括在显微镜下仔细检查切除的组织,以避免留下的癌细胞导致肿瘤的局部再生长。由于手术团队只能检查已经切除的细胞,即使是这种方法也不能完全保证完全切除癌组织。这项拟议的技术提供了另一种选择,将手术工具--在目前的情况下是超细手术激光--与强大的显微镜和分子分析设备相结合。这两个设备结合在一起可以明确地识别癌细胞,然后可以使用外科激光将它们蒸发。虽然逐个细胞切除肿瘤听起来很有吸引力,特别是在保留所有非癌细胞方面,但在实际操作层面上,人类不能进行这样的手术,因为即使我们假设外科医生可以在一秒钟内识别并移除一个细胞,完全消除小肿瘤仍然需要数周的连续工作。然而,如果激光的识别和发射都是由人工智能执行的,这一时间可以减少到几十分钟-这是通常接受的小手术的时间框架。被提议的手术机器人看起来就像在肿瘤上搭起的一个小帐篷。外壳将容纳一个纤维状的探头,其中包括激光、显微镜和分子分析工具。计算机将能够以细胞的精度将探头定向到肿瘤的任何一点,或在一秒钟内扫描数十平方毫米的区域。当设备安装好后,它首先使用显微镜设备定位肿瘤,然后蒸发大量、连续的肿瘤组织,同时使用分子传感工具持续寻找健康细胞的迹象。在肿瘤的边缘,它将使用显微镜发现潜在的癌细胞,并在移除它们之前利用分子信息正确地识别它们。外科医生监督整个过程,并就寻找肿瘤细胞的区域和其他手术步骤(如凝固手术区域上的少量出血)向计算机发出指示。这项技术将显著提高癌症手术的准确性,使目前无法手术的病例成为可手术病例,通过消除局部再生降低再手术率,并将癌症手术的并发症降至最低。此外,它将为医疗保健提供者提供机会,将大多数癌症手术转变为在门诊诊所甚至在全科医生手术中进行的门诊干预。由于该设备本身将提供诊断信息,因此皮肤癌的检测、诊断和移除过程将在全科医生那里花费半个小时,而目前需要几周时间才能多次前往医院就诊。
英文摘要
SummaryThe proposed project is aimed at the development of a semi-autonomous surgical robotics platform for the removal of tumours with unprecedented accuracy. Currently, when surgeons remove tumours, they use information collected before the surgery (ultrasound, X-ray) to locate the tumour and assess its actual extension based on what they see or feel with their fingertips. Unfortunately, it is almost impossible to tell healthy tissue from cancer-infiltrated tissue by its look, which results in lengthy operations including the careful examination of removed tissues under microscope to avoid cancer cells left behind causing local regrowth of the tumour. Since the surgical team can only examine cells which are already removed, even this approach cannot fully guarantee the complete removal of cancerous tissue. The proposed technology offers an alternative, where the surgical tool - in the current case a superfine surgical laser - is combined with a powerful microscope and a molecular analysis device. These two devices together can unambiguously identify cancerous cells and they can subsequently be evaporated using the surgical laser. While the cell-by-cell removal of a tumour may sound attractive, especially in the aspect of sparing all non-cancerous cells, at the practical level human beings cannot perform such operations as even if we assume that a surgeon can identify and remove a cell in a second, the complete elimination of small tumour would still take weeks of continuous work. However, if both the identification and the firing of the laser is performed by an artificial intelligence, this time can be reduced to tens of minutes - a commonly accepted timeframe for minor surgeries. The proposed surgical robot will look like a little tent set up over the tumour. The enclosure will house a fibre-like probe, which contains the laser, the microscope and the molecular analysis tools. The computer will be able to direct the probe at any point of the tumour with cellular precision or scan tens of mm2 area in a second. When the device is set up, it localises the tumour at first using the microscopic device, then evaporates the bulk, continuous tumour tissue, while continuously looking for signs of healthy cells with the molecular sensing tool. At the edge of the tumour it will use the microscope to find potentially cancerous cells and will properly identify them using the molecular information before removing them. The surgeon oversees the process and gives directions to the computer regarding the areas to find tumour cells and other surgical steps e.g. coagulation of minor bleeds on the surgical area. The technology will significantly increase the accuracy of cancer surgery, will make currently inoperable cases operable, decrease reoperation rate by eliminating local regrowth and minimise the complications of cancer surgery. In addition, it will give an opportunity for the healthcare providers to turn most cancer surgeries into outpatient interventions performed at outpatient clinics or even at GP surgeries. As the device will give diagnostic information itself, the detection-diagnostics-removal journey for e.g. a skin cancer will take half an hour at the GP in contrast to the current several weeks involving multiple hospital visits.
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Medical Image Computing and Computer Assisted Intervention - MICCAI 2022 - 25th International Conference, Singapore, September 18-22, 2022, Proceedings, Part VII
医学图像计算和计算机辅助干预 - MICCAI 2022 - 第 25 届国际会议,新加坡,2022 年 9 月 18-22 日,会议记录,第七部分
DOI:
10.1007/978-3-031-16449-1_16
发表时间:
2022
期刊:
影响因子:
--
作者:
[Xu C]
通讯作者:
Xu C
A better way to determine tumour margins intraoperatively, using ambient mass spectrometry (interim report)
使用环境质谱法在术中确定肿瘤边缘的更好方法(中期报告)
DOI:
10.1016/j.bjoms.2021.12.012
发表时间:
2022
期刊:
British Journal of Oral and Maxillofacial Surgery
影响因子:
1.8
作者:
[Higginson J]
通讯作者:
Higginson J
DOI:
10.1021/acs.analchem.1c00270
发表时间:
2021-04-13
期刊:
Analytical chemistry
影响因子:
7.4
作者:
[Manoli E, Mason S, Ford L, Adebesin A, Bodai Z, Darzi A, Kinross J, Takats Z]
通讯作者:
Takats Z
DOI:
10.1109/icra48891.2023.10160287
发表时间:
2023-05
期刊:
2023 IEEE International Conference on Robotics and Automation (ICRA)
影响因子:
--
作者:
[Haozheng Xu;M. Runciman;João Cartucho;Chi Xu;S. Giannarou]
通讯作者:
Haozheng Xu;M. Runciman;João Cartucho;Chi Xu;S. Giannarou
DOI:
10.1016/j.oraloncology.2023.106419
发表时间:
2023-05-12
期刊:
ORAL ONCOLOGY
影响因子:
4.8
作者:
[Higginson,James A., Breik,Omar, Dhanda,Jagtar]
通讯作者:
Dhanda,Jagtar
Imaging of fast-moving single cells with adaptive single pixel detection
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批准号:BB/X004082/1
-
项目类别:Research Grant
-
资助金额:$20.62万
-
财政年份:2023
-
负责人:Zoltan Takats
-
依托单位:
Building research capacity with high-throughput Ultra-performance liquid chromatography high resolution Q-TOF
-
批准号:MR/X013537/1
-
项目类别:Research Grant
-
资助金额:$85.8万
-
财政年份:2022
-
负责人:Zoltan Takats
-
依托单位:
UK Consortium for MetAbolic Phenotyping (MAP UK)
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批准号:MR/S010483/1
-
项目类别:Research Grant
-
资助金额:$272.46万
-
财政年份:2019
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负责人:Zoltan Takats
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依托单位:
Development of a rapid bacterial identification method based on direct mass spectrometric metabolic profiling
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批准号:BB/L020858/1
-
项目类别:Research Grant
-
资助金额:$61.91万
-
财政年份:2014
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负责人:Zoltan Takats
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依托单位:
国内基金
海外基金
动态无线传感器网络弹性化容错组网技术与传输机制研究
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批准号:61001096
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项目类别:青年科学基金项目
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资助金额:20.0万元
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批准年份:2010
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负责人:化存卿
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依托单位:
基于计算和存储感知的运动估计算法与结构研究
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批准号:60803013
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项目类别:青年科学基金项目
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资助金额:18.0万元
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批准年份:2008
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负责人:邓磊
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依托单位: