Using a Diffuse Reflectance Spectroscopy Probe In-vivo to Identify Tumour and Non-tumour Tissue in the Gastrointestinal Tract to Aid Margin Assessment
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 入组人数
- 20
- 试验地点
- 2
- 主要终点
- Diagnostic accuracy of DRS probe to differentiate normal versus tumour tissue in vivo
研究概览
简要总结
A spectroscopic probe is a sensor designed to illuminate and gather light directly from the tissue while touching it. The probe contains optical fibres, some which illuminate the surface of the tissue with harmless visible (white) light, and others that collects the light that has been reflected from inside the tissue. As the investigators track the position of the probe, they can create spectroscopic images with richer colour information, allowing surgeons to differentiate between different types of tissue, such as normal or cancerous regions.
The spectroscopic probe, either sterilised or covered with a sterile probe cover, will be used on the tissue as part of the patient's operation, inside the body itself. The tissue will be sampled using the spectroscopic probe before the surgeons remove the tissue from the body. The research team will be in the operating theatre. The surgeon or a member of the research team will use the optical probe on the tissue samples. This will involve taking pictures and videos of the sample while the research team scan the samples with the spectroscopic probe.
详细描述
Cancers of the gastrointestinal (GI) tract remain a major contributor to the global cancer risk, with approximately 2.8million cases of colorectal and stomach cancer worldwide. These malignancies continue to pose a major threat to public health. The aim of surgery is for complete resection of tumour with clear margins, whilst preserving as much surrounding tissue as possible. A positive circumferential resection margin (CRM) is associated with local recurrence of the tumour and poorer long-term survival, so it is paramount to establish tissue margins accurately.
Diffuse reflectance spectroscopy (DRS) is a technique that allows discrimination of normal and abnormal tissue and presents a promising advancement in cancer diagnosis. Light emitted using a DRS probe is absorbed and scattered by different structures within tissue and emitted back onto the probe. The wavelength and intensity of this collected light is specific to each tissue type, and in this way, different tissue can be distinguished based on spectral data.
The investigators have developed an optical tracking system to overcome single-point spectral measurements, for use intra-operatively to aid margin assessment. This system is able to process thousands of spectra in a small timeframe, which can be used in real-time to distinguish tumour and non-tumour tissue.
A benchtop ex vivo study on upper GI specimens has successfully tested these approaches.
Participants undergoing elective GI cancer surgery at Imperial NHS trust will be recruited by the clinical care team through clinic. Patients willing to take part in the study will be consented. The study involves a probe emitting harmless visible light being used on the organ that will be removed during the operation just before it is resected. This should not interfere with the operation being carried out and will take 5-15mins in total.
研究设计
- 研究类型
- Interventional
- 分配方式
- Na
- 干预模型
- Single Group
- 主要目的
- Diagnostic
- 盲法
- None
入排标准
- 年龄范围
- 18 Years 至 99 Years（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Patients undergoing primary upper GI cancer resection surgery
- •Patients undergoing primary lower GI (colorectal) cancer resection surgery
- •Patients >18 years of age
- •Patients who consent to take part in the study
排除标准
- •Patients who do not consent to the study or decline to participate
- •Patients who do not meet the inclusion criteria
- •Patients who lack capacity
- •Patients undergoing emergency lower or upper GI cancer surgery
- •Patients undergoing re-operation for cancer surgery
- •Pregnant women
结局指标
主要结局
Diagnostic accuracy of DRS probe to differentiate normal versus tumour tissue in vivo
时间窗: Through study completion - 2 years.
A user interface has been developed using Python 3.6 and Qt5 to integrate the acquisition and processing of the spectral data, as well as the tracking of the DRS fibre probe. Python 3.6 will be used for data processing, visualisation, Machine Learning classification and statistical analysis. A linear Support Vector Machine (SVM) will be used for classification of the spectral data. Machine Learning classifiers will be used for calculating sensitivity, specificity, overall accuracy and the area under the curve (AUC). Receiver-operator characteristics (ROC) curves will be plotted. In addition, one-dimensional convolutional neural networks will be developed and may be used. Real-time tissue classification will be presented on the user interface when using the DRS probe. Real-time tracking at each optical biopsy site coupled with the binary classification probability of each site will be visualised as either normal or tumour tissue using a graduated colour map.
次要结局
- Feasibility of DRS probe to differentiate normal versus tumour tissue in vivo(Over study period - 2 years)