京都大学 / 0048 / 新制・課程博士 / 博士(医学) / 甲第20986号 / 医博第4332号 / 新制||医||1027(附属図書館) / 京都大学大学院医学研究科医学専攻 / (主査)教授 富樫 かおり, 教授 羽賀 博典, 教授 別所 和久 / 学位規則第4条第1項該当 / Doctor of Medical Science / Kyoto University / DFAM

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Optical coherence imaging, including tomography (OCT) and microscopy (OCM), has been a growing research field in biomedical optical imaging in the last decade. In this imaging modality, a broadband light source, thus of short temporal coherence length, is used to perform imaging via interferometry. A challenge in optical coherence imaging, as in any imaging system towards biomedical diagnosis, is the quantification of image quality and optimization of the system components, both a primary focus of this research. We concentrated our efforts on the optimization of the imaging system from two main standpoints: axial point spread function (PSF) and practical steps towards compact low-cost solutions. Up to recently, the criteria for the quality of a system was based on speed of imaging, sensitivity, and particularly axial resolution estimated solely from the full-width at half-maximum (FWHM) of the axial PSF with the common practice of assuming a Gaussian source power spectrum. As part of our work to quantify axial resolution we first brought forth two more metrics unlike FWHM, which accounted for side lobes in the axial PSF caused by irregularities in the shape of the source power spectrum, such as spectral dips. Subsequently, we presented a method where the axial PSF was significantly optimized by suppressing the side lobes occurring because of the irregular shape of the source power spectrum. The optimization was performed through optically shaping the source power spectrum via a programmable spectral shaper, which consequentially led to suppression of spurious structures in the images of a layered specimen. The superiority of the demonstrated approach was in performing reshaping before imaging, thus eliminating the need for post-data acquisition digital signal processing. Importantly, towards the optimization and objective image quality assessment in optical coherence imaging, the impact of source spectral shaping was further analyzed in a task-based assessment method based on statistical decision theory. Two classification tasks, a signal-detection task and a resolution task, were investigated. Results showed that reshaping the source power spectrum was a benefit essentially to the resolution task, as opposed to both the detection and resolution tasks, and the importance of the specimen local variations in index of refraction on the resolution task was demonstrated. Finally, towards the optimization of OCT and OCM for use in clinical settings, we analyzed the detection electronics stage, which is a crucial component of the system that is designed to capture extremely weak interferometric signals in biomedical and biological imaging applications. We designed and tested detection electronics to achieve a compact and low-cost solution for portable imaging units and demonstrated that the design provided an equivalent performance to the commercial lock-in amplifier considering the system sensitivity obtained with both detection schemes.

Today, medical imaging is playing an important role in medicine as it provides the techniques and processes used to create images of the human body or parts thereof for clinical purposes (medical procedures seeking to reveal, diagnose or examine disease) or medical science (including the study of normal anatomy and function). Modalities are developing over time to achieve the highest possible resolution, speed of image acquisition, sensitivity, and specificity. In the past decade, advances in optics, fiber, as well as laser technology have enabled the development of noninvasive optical biomedical imaging technology that can also be applied to endoscopy to reach deeper locations in the human body. The purpose of this dissertation is to investigate a full system design and optimization of an optical coherence tomography (OCT) system to achieve high axial and lateral resolution together with an extended depth of focus for endoscopic in vivo imaging. In this research aimed at advancing endoscopic OCT imaging, two high axial resolution optical coherence tomography systems were developed: (1) a spectrometer-based frequency-domain (FD) OCT achieving an axial resolution of ~2.5 µm using a Ti:Sa femtosecond laser with a 120nm bandwidth centered at 800nm and (2) a swept-source based FD OCT employing a high speed Fourier domain mode locked (FDML) laser that achieves real time in vivo imaging with ~8 µm axial resolution at an acquisition speed of 90,000 A-scans/sec. A critical prior limitation of FD OCT systems is the presence of mirror images in the image reconstruction algorithm that could only be eliminated at the expense of depth and speed of imaging. A key contribution of this research is the development of a novel FD OCT imager that enables full range depth imaging without a loss in acquisition speed. Furthermore, towards the need for better axial resolution, we developed a mathematical model of the OCT signal that includes the effect on phase modulation of phase delay, group delay, and dispersion. From the mathematical model we saw that a Fourier domain optical delay line (FD ODL) incorporated into the reference arm of the OCT system represented a path to higher performance. Here we then present a method to compensate for overall system dispersion with a FDODL that maintains the axial resolution at the limit determined solely by the coherence length of a broadband source. In the development of OCT for endoscopic applications, the need for long depth of focus imaging is critical to accommodate the placement of the catheter anywhere within a vessel. A potential solution to this challenge is Bessel-beam imaging. In a first step, a Bessel-beam based confocal scanning optical microscopy (BCSOM) using an axicon and single mode fiber was investigated with a mathematical model and simulation. The BCSOM approach was then implemented in a FD OCT system that delivered high lateral resolution over a long depth of focus. We reported on the imaging in biological samples for the first time with a double-pass microoptics axicon that demonstrated clearly invariant SNR and 8 um lateral resolution images across a 4 mm depth of focus. Finally, we describe the design and fabrication of a catheter incorporated in the FD OCT. The design, conceived for a 5 mm outer diameter catheter, allows 360 degree scanning with a lateral resolution of about 5 um across a depth of focus of about 1.6 mm. The dissertation concludes with comments for related future work.

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Paediatric glaucoma leads to a decreased thickness of the peripapillary retinal nerve fibre layer (pRNFL) and of the macula. These changes can be precisely quantified using spectral domain-optical coherence tomography (SD-OCT). Despite abundant reports in adults, studies on the diagnostic capacity of macular SD-OCT in paediatric glaucoma are rare. The aim of this study was to compare the glaucoma discriminative ability of pRNFL and macular segment thickness in paediatric glaucoma patients and healthy children. Data of 72 children aged 5–17 years (glaucoma: 19 (26.4%), healthy: 53 (73.6%)) examined with SD-OCT (SPECTRALIS®, Heidelberg Engineering) were analysed retrospectively. The thickness of pRNFL sectors and of macular segment subfields were compared between diseased and healthy participants. Areas under the receiver-operating characteristic curves (AUC), sensitivity, and specificity from logistic regression were used to evaluate the glaucoma discriminative capacity of single and combined pRNFL and macular segments’ thickness. The results revealed a reduced thickness of the pRNFL and of the three inner macular layers in glaucoma patients, which correlates highly with the presence of glaucoma. The highest glaucoma discriminative ability was observed for the combination of pRNFL sectors or inner macular segments (AUC: 0.83 and 0.85, respectively), although sensitivity remained moderate (both 63% at 95% specificity). In conclusion, while confirmation from investigations in larger cohorts is required, SD-OCT-derived pRNFL and macular thickness measurements seem highly valuable for the diagnosis of paediatric glaucoma.

The aim of this study was to compare the efficacy of trabeculectomy (TE), single XEN microstent implantation (solo XEN) or combined XEN implantation and cataract surgery (combined XEN) in primary open-angle glaucoma cases, naïve to prior surgical treatment, using a monocentric retrospective comparative cohort study. Intraocular pressure (IOP) and the number of IOP-lowering drugs (Meds) were monitored during the first 24 months after surgery. Further disease progression was monitored using peripapillary retinal nerve fiber layer (RNFL) thickness examinations using spectral domain optical coherence tomography (OCT) as well as visual acuity (VA) and visual field (VF) tests. In the TE group (52 eyes), the mean IOP decreased from 24.9 ± 5.9 to 13.9 ± 4.2 mmHg (p < 0.001) and Meds decreased from 3.2 ± 1.2 to 0.5 ± 1.1 (p < 0.001). In the solo XEN (38 eyes) and the combined XEN groups, the mean IOP decreased from 24.1 ± 4.7 to 15.7 ± 3.0 mmHg (p < 0.001) and 25.4 ± 5.6 to 14.7 ± 3.2 mmHg (p < 0.001), while Meds decreased from 3.3 ± 0.8 to 0.8 ± 1.2 (p < 0.001) and 2.7 ± 1.2 to 0.4 ± 1.0 (p < 0.001), respectively. The VF and VA indices showed no sign of further deterioration, the RNFL thickness further decreased in all treatment groups after surgery. TE and XEN led to comparable reductions in IOP and Meds. Although the VA and VF indices remained unaltered, the RNFL thickness continuously decreased in all treatment groups during the 24-month follow-up.

The computer-aided analysis is poised to play an increasingly prominent role in medicine and healthcare. Benefiting from the increasing computing power, various machine learning frameworks have been developed in the biomedical field, bringing significant improvements in real-world clinical applications. However, for many diseases, the development of these life-supporting algorithms is still in its infancy. To bridge this gap: This thesis is dedicated to the development of efficient algorithms for better image intervention and addressing data quality challenges in machine learning algorithms to provide direct guidance for real-world clinical applications. With the above goals, three topics are explored in depth. First, we develop a novel tissue analysis framework for cardiac substrate identification and tissue heterogeneity assessment. In particular, we creatively used model uncertainty to measure tissue structure information, offering a means of extracting the tissue heterogeneity information in a non-invasive way for real-time imaging and processing. The tissue analysis framework in the first aim is based on the fully supervised technique, which relies heavily on the availability of large-scale datasets with accurate annotations. Such high-quality datasets are extremely time-consuming to acquire, especially for biomedical segmentation tasks. To lessen the need for the labeling process, we further develop three weakly supervised learning frameworks to address data and labeling challenges caused by limited data resources. Finally, we develop an in-vivo tissue analysis framework on cardiac datasets, aiming to provide real-time guidance for clinical ablation procedures. Our models could contribute to the improvement of ablation treatment by identifying the ablation targets and avoiding critical structures within the hearts.

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