Optoacoustic Handheld Imaging for Clinical Screening and Intervention
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TECHNISCHE UNIVERSITÄT MÜNCHEN Lehrstuhl für Biologische Bildgebung Optoacoustic handheld imaging for clinical screening and intervention Alexander Dima Vollständiger Abdruck der von der Fakultät für Elektrotechnik und Informationstechnik der Technischen Universität München zur Erlangung des akademischen Grades eines Doktor-Ingenieur (Dr. Ing.) genehmigten Dissertation. Vorsitzender: Univ. - Prof. Dr.-Ing. Martin Buss Prüfer der Dissertation: 1. Univ. - Prof. Vasilis Ntziachristos, Ph. D. 2. Univ. - Prof. Dr.-Ing. Klaus Diepold Die Dissertation wurde am 22.06.2015 bei der Technischen Universität München eingereicht und durch die Fakultät für Elektrotechnik und Informationstechnik am 17.12.2015 angenommen. Abstract Optoacoustic, also known as photoacoustic, imaging is a hybrid imaging modality that combines optical contrast with ultrasound resolution. The method has been studied since the 1990s, yet really took off only in the early 2000s, helped by the sufficient availability of technology components such as nanosecond pulsed lasers in the near- infrared, parallel data acquisition hardware and inversion algorithms. The foremost area of interest during these years has been pre-clinical biomedical imaging of small animals. In mice, reaching tissue diameters of up to 25mm, a number of disease models has been studied ranging from cancers and arthritis to Alzheimer’s. To achieve ever better results a variety of contrast agents has also been applied or newly developed in order to visualize functional and molecular parameters relating to the disease studied. At the same time a desire to increase sensitivity to these agents led to the development of multi-spectral approaches, such as Multi-Spectral Optoacoustic Tomography (MSOT). These techniques also imposed additional requirements in terms of image quality and frame rate that could only be covered by introducing detector arrays and parallel acquisition hardware. As technology improved so did requirements, which at the time of writing reached a peak of 512-element arrays and 512-channel parallel sampling hardware at repetition rates of 10Hz. On the other hand numerous image reconstruction algorithms were developed spanning ultra-fast, yet less accurate, implementations of analytical inversion methods to more demanding methods based on numerical forward models offering higher accuracy and flexibility. Optoacoustic technology has evolved to a stage where translation to clinical problems is not just feasible but highly desirable to bring the benefit of optical contrast at tissue depths and resolutions beyond the scope of purely optical modalities. Therefore in this work we approached clinical translation from the two most common imaging scenarios in patient care. First, we developed a handheld optoacoustic probe for non-invasive diagnostic imaging used in screening and therapy monitoring. Thereby we carefully compared previous illumination and detection patterns and studied achievable imaging depth and quality. To ensure a minimal footprint we devised optimal water coupling for the chosen cylindrically focused curved array and implemented flexible rectangular fiber bundle illumination. Using this handheld probe we were able to perform scans of various body parts. To enable live video feedback we furthermore optimized a simple inversion algorithm in C and parallelized it using first a multi-core CPU and later a consumer graphics card (GPU). Using this prototypical probe we were able to achieve the first ever optoacoustic images of the human carotids and thyroid. In our second approach we targeted a common question posed in every surgical procedure: is this tissue viable? Every cut may disrupt the supply of blood to some tissue part and, if left undetected, can cause severe consequences to the patient. When blood perfusion is too weak for visual and haptic assessment by the surgeon, robust and quantitative assistance is necessary. Optoacoustic imaging is ideally suited to provide such assistance, as it is highly sensitive to vasculature and by means of MSOT can also resolve molecular parameters such as oxygen concentration. In this context we chose to apply optoacoustic imaging to the resection of cancer and subsequent placement of the anastomosis (a suture connecting two tissue parts) in the lower colon. Using excised parts of the porcine lower colon we were able to identify the most suitable and flexible arrangement of detection and illumination. Additionally we devised a method for direct optoacoustic imaging of blood perfusion based on local arterial injection of medical saline. The method allows visual tracking of perfusion pathways and provides sufficient image quality for quantitative assessment of the perfusion rate. Moreover the procedure is clinically approved, highly robust and repeatable as well as risk free to the patient. We demonstrate the achievable contrast cycle on samples of excised porcine colon and on mouse tails in-vivo. Finally, in preparation for future clinical deployment we studied achievable improvements of model-based image reconstruction algorithms in terms of memory consumption and execution speed. While GPU implementations of direct inversion algorithms are sufficient to enable live image feedback, more precise reconstructions can be obtained with model-based methods. Thus, in this work we also propose a paradigm change in numerical modeling. Instead of mixing physical wave propagation and geometric detector positioning, we treat each problem separately and are able to show a proof-of-concept implementation of accurate model-based optoacoustic inversion using only the numerical characteristics of a single detector position. The ultimate goal thereby is to enable inversion on consumer graphics cards that offer faster hardware compared to CPU/mainboard architecture as well as massive parallelization potential. Hence, the algorithm described herein is founded on image transformations – a cornerstone of computer graphics. Contents 1 Abstract ....................................... 3 1 Introduction .................................. 7 1.1 Modern clinical imaging ......................... 7 X-ray/XCT .................................. 7 PET/SPECT ................................. 8 MRI...................................... 9 Ultrasound imaging ............................. 9 1.2 Novel imaging requirements ...................... 10 1.3 Non-invasive clinical optoacoustic imaging ............. 12 1.4 Objectives and outline ......................... 14 2 Optoacoustic imaging: instrumentation and theory ........ 15 2.1 Propagation of light and sound in tissue ............... 17 2.1.1 Light and tissue ........................... 17 2.1.2 Sound and tissue .......................... 21 2.2 The Photoacoustic effect ........................ 24 2.3 Laser excitation and illumination ................... 29 2.4 Ultrasound detection .......................... 32 2.5 Array-based optoacoustic detection geometries ........... 37 2.6 Image reconstruction .......................... 40 2.7 Multi-spectral unmixing ........................ 44 3 Imaging systems .............................. 47 3.1 Data acquisition electronics ...................... 48 3.2 Performance of linear versus curved array .............. 54 3.3 Non-invasive handheld probe ..................... 62 3.4 Intraoperative setup and methodology ................ 66 4 Optimizations for clinical deployability ............... 70 4.1 Improving image reconstruction speed ................. 70 4.2 Transformation-based Optoacoustic Modeling (TOM) ........ 73 4.2.1 Proposed algorithm ......................... 75 4.2.2 Fast inversion ............................ 78 4.2.3 Evaluation using simulated data .................. 79 4.2.4 Evaluation using handheld measurement data ........... 83 4.3 Array density – practical considerations ................ 87 4.3.1 Characterization of arrays ...................... 87 4.3.2 Numerical simulation and experimental setup ........... 90 4.3.3 Numerical and experimental results ................ 92 5 Clinical applications ............................ 99 5.1 Cardio-vascular imaging ......................... 99 5.2 Thyroid imaging ............................ 102 5.3 Tissue viability assessment ...................... 103 6 In vivo imaging results .......................... 105 6.1 Non-invasive imaging ......................... 105 6.2 Towards intraoperative imaging ................... 114 7 Discussion and Conclusion ....................... 121 8 Appendix .................................. 130 8.1 List of figures .............................. 130 8.2 List of tables .............................. 137 8.3 List of publications ........................... 137 8.4 References ............................... 138 1 1 Introduction Modern clinical diagnostic procedures have come to rely to a great extent on medical imaging modalities developed or refined in the course of the last century. The most prominent and common in use can be categorized by the physical quantity employed for sampling: X-rays, γ-rays, ultrasound waves and magnetic fields. The fifth category uses the electromagnetic field at visible wavelengths: optical imaging. To date quantitative optical imaging (as opposed to visual perception) has been used only sparingly in a clinical context and even then it has been mostly limited to microscopy in the process of histological analysis, due to its limited penetration depth and resolution beyond 1-2 mm of tissue depth. Therefore, in this work we strive to bring to the clinics the full force