A Cyber-Physical System for Unified Diagnosis and Treatment of Lung Diseases

Lead Research Organisation: University of Edinburgh
Department Name: Sch of Informatics


In this research, I will develop a cyber-physical system (CPS) for the diagnosis and treatment of lung diseases. My project is motivated by three facts:

1) Lung cancer treatment is most successful when it is found at an early stage. Treatment of early-stage cancer offers 73% chance of survival, whereas in late-stage this is reduced to 13%. However, the current methods for early diagnosis of peripheral lung lesions using bronchoscopic biopsy are challenging with varying diagnostic yield. Thus, there is a need to develop new technologies for reliable diagnosis of cancer in the lung periphery.

2) At present, surgical resection of malignant nodules (Tumours<3cm diameter) in the lung is the treatment modality of choice. However, most patients are not suitable surgical candidates, thus prompting the need for other therapeutic options. An emerging less invasive treatment option is bronchoscopic ablation of lung cancer via delivering physical therapy to lesions in the lung (cryotherapy/photonic ablation). Bronchoscopic ablation is not widely used to treat lung cancer, primarily due to the limited depth of penetration and small range of motion of the bronchoscope.

3) The overall in-hospital mortality rate for patients in ICU with ventilator associated events approaches 30%. New pulmonary infiltrates are a diagnostic challenge and due to the poor sampling methods available, patients are often initiated on non-targeted therapies. Bronchoscopy and sampling of the distal lung in diffuse diseases is not standardised and lacks repeatability and requires expert operators. The key aim of this research is to democratise ICU bronchoscopy and develop a platform using vision computing, EMT and external registration to enable non-skilled operators to sense, sample and diagnose pathology in vivo in situ.

To this end, I propose a CPS that addresses the unique issues of bronchoscopic diagnosis and treatment of lung diseases using novel mechatronic systems, control algorithms, and image guidance. The CPS has the potential to deliver unified diagnosis and treatment platform for early-stage lung cancer and on-site differential diagnosis of diffuse lung diseases by enhancing the current bronchoscopic technology in two specific ways:
1) Manipulation augmentation: I will design and develop a mechatronic device comprised of an active mini-bronch and a user interface for steering. The active mini-bronch is made of a flexible robot equipped with an endoscopic camera, fibre-optics for molecular imaging/sensing of tissue. It also provides a working channel that can be used for ablation of cancerous tissue or tissue sampling. The proposed mechatronic device can be used in two scenarios: (1) Autonomous tissue sampling in intensive care units: The mini-bronch uses control algorithms to navigate to lung subsegments and take multiple samples for diagnosis, (2) Semi-autonomous tissue diagnosis/treatment: the operator uses the user interface to navigate the mini-bronch to the periphery of the lung, characterise, sample and detect cancerous tissue, and then ablate . My control algorithms will provide unprecedented capabilities in terms of dexterity, safety, and ease of operation.
2) Visual augmentation: A key goal is to develop algorithms that employ emerging molecular imaging techniques to provide an imaging technology for in-vivo diagnosis of lung diseases.
I postulate that the proposed CPS will enable rapid on-site evaluation of lung diseases and successful bronchoscopic detection and therapy.

Planned Impact

In the past decade, there have been significant advances in technology for pulmonary medicine, including development of imaging technologies (e.g., endobronchial ultrasonography and Cone Beam CT), navigation platforms (e.g., electromagnetic navigation and virtual bronchoscopy), and ablation techniques (e.g., cryoablation, microwave ablation, and photonic ablation). However, the treatment of peripheral lung cancer still faces significant challenges that stem in part from the slow progression and limited capabilities of new bronchoscopic technologies. My proposed fellowship aims to address existing challenges by integrating technologies with a novel mechatronic mini-bronch and image-guided control algorithms.

The population most likely to benefit from the proposed research/innovations are those with suspected lung cancer and in the case of therapy, those who are not candidates for other common treatment options such as surgical removal of tumor or radiotherapy. Lung cancer is an insidious, smoking-related disease, and indeed many patients are not suitable candidates for surgery or radiotherapy, either due to the advanced stage of cancer or because of compromised cardiopulmonary function that precludes the risk of thoracic surgery. An emerging treatment option is a percutaneous ablation in which a needle carrying an ablation probe is inserted through the chest cavity to reach the lesions in the lung for ablation. Percutaneous ablation has a high complication rate, primarily pneumothorax (lung collapse), which makes such a technique difficult to pursue as an alternative treatment. The proposed bronchoscopic ablation methodology is a suitable alternative treatment option for patients with underlying lung disease, as it accesses cancer through the bronchial tree and there is a lower risk of pneumothorax, which is a significant concern in the medically inoperable.

The proposed technology will also make bronchoscopy accessible to new practitioners by offering augmented guidance and mechatronics assistance, allowing them to offer this minimally invasive treatment/diagnosis option to a greater number of patients. A particular target product profile is for the intensive care unit.

The results of this research have the potential for very significant impact on the field of flexible and continuum robotics. I expect the impact of the research/innovations to come directly or indirectly from the project outputs including:
1. Design of a mini-bronch by the integration of continuum robots
2. A mathematical framework for real-time modeling and visualisation of flexible continuum robots.
3. Open source algorithms for autonomous control and operator-in-the-loop control of flexible continuum robots.
These outputs will be of special interest to roboticists as they directly address the three grand challenges that have impeded the application of continuum robots in clinical practice: A) visualisation and integration; B) human-machine interaction; and C) shape sensing.

Another impact of this research will be on the people pipeline and skills base of the UK's healthcare engineering community. The proposed project has significant interdisciplinary aspects, connecting the robotics community and the EPSRC funded CDT in Robotics and Autonomous Systems at the University of Edinburgh to the medical research facilities at the Queen's Medical Research Institute (QMRI) supported by EPSRC IRC grant (PROTEUS project). 3 PDRAs and a Ph.D. student will be trained as independent researchers in the field of medical robotics, who will contribute to the knowledge base of medical robotics in the UK. Also, through the participation in workshops and Edinburgh's science festival we would aim to reach the general public, and in particular secondary school pupils, thereby encouraging them for careers in medical robotics.

Innovation, industrialisation and entrepreneurship are also at the heart of my fellowship proposal.
Description Collaboration between School of Informatics and Queen's Medical Research Institute 
Organisation University of Edinburgh
Department Queen's Medical Research Institute Edinburgh
Country United Kingdom 
Sector Academic/University 
PI Contribution Our research team brings expertise in medical device development and evaluation to the Queen's Medical Research Institute, which didn't exist before. We provide in-house design consultation on developing bespoke biomedical instruments, software development, and experiment design to remove technical barriers that frequently preclude the development and translation of new healthcare technology.
Collaborator Contribution As part of this collaboration, Queen's Medical Research Institute (QMRI) agreed to facilitate our cross-school collaboration through housing our equipment and providing laboratory space and office space in QMRI free of charge. Moreover, the collaboration gave us access to the Healthcare Technology Accelerator Facility (HTAF) (https://proteus.ac.uk/htaf/) at QMRI to help with regulatory pathways and ensure its compatibility with the current clinical workflow. HTAF is a non-profit initiative that provides a unique base for the development of healthcare technology (HT). HTAF has agreed to assist us throughout this award at all the stages of the research by providing professional consultancy from clinical experts and clinical project managers on in-human technology development, trial design, methodology, statistics, commercialization, and legal support.
Impact This is a multidisciplinary collaboration between engineers and computer scientists from the School of Informatics with Clinicians (Pulmonologists) and Photonics experts at the Queen's Medical Research Institute. This collaboration is relatively new and has not resulted in outcomes yet.
Start Year 2020
Description Scientific Workshop on Medical Robotics 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact I co-organised a workshop on "Holistic Integration of Design, Sensing, and Intelligence in Dexterous Surgical Robotic Systems". The workshop was held virtually on June 4, 2021.
Recently, we have seen increasing efforts aimed at implementing Dexterous Surgical Robotic Systems (DSRS) to push the frontiers of medical interventions. However, the deployment and integration of DSRS in real clinical scenarios have been hampered by issues such as limited sensory perception and safety concerns. In the workshop, we invited world-renown researchers and clinicians to discuss several possible avenues to address the challenges in the integration of DSRS, namely, (A) advanced sensing algorithms for robot perception, (B) control architectures and machine intelligence, and (C) novel designs and fabrication methods.
Year(s) Of Engagement Activity 2021
URL https://sites.google.com/view/icra2021workshop