Please use this identifier to cite or link to this item:
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/86462Full metadata record
| ???org.dspace.app.webui.jsptag.ItemTag.dcfield??? | Value | Language |
|---|---|---|
| dc.contributor.advisor | 孫啟光 | zh_TW |
| dc.contributor.advisor | Chi-Kuang Sun | en |
| dc.contributor.author | 曾耀賝 | zh_TW |
| dc.contributor.author | Yao-Chen Tseng | en |
| dc.date.accessioned | 2023-03-19T23:57:14Z | - |
| dc.date.available | 2023-12-29 | - |
| dc.date.copyright | 2022-10-20 | - |
| dc.date.issued | 2022 | - |
| dc.date.submitted | 2002-01-01 | - |
| dc.identifier.citation | [1] McFaline-Figueroa J, Lee E. Brain Tumors.The American Journal of Medicine (2018) 131(8) 874-882
[2] Nabors L, Portnow J, Engh A. NCCN Guidelines Insights: Central Nervous System Cancers, Version 1.2017. Journal of the National Comprehensive Cancer Network (2017) 15(11) 1331-1345 [3] Ostrom Q, Cioffi G, Barnholtz-Sloan J, CBTRUS Statistical Report: Primary Brain and Other Central Nervous System Tumors Diagnosed in the United States in 2014–2018. Neuro-Oncology (2021) 23(Supplement_3) iii1-iii105 [4] Weller M, van den Bent M, Wick W. EANO guidelines on the diagnosis and treatment of diffuse gliomas of adulthood. Nature Reviews Clinical Oncology 2020 18:3 (2020) 18(3) 170-186 [5] Coburger J, Wirtz C. Fluorescence guided surgery by 5-ALA and intraoperative MRI in high grade glioma: a systematic review. Journal of Neuro-Oncology (2019) 141(3) 533-546 [6] Shen B, Zhang Z, Tian J. Real-time intraoperative glioma diagnosis using fluorescence imaging and deep convolutional neural networks. European Journal of Nuclear Medicine and Molecular Imaging (2021) 48(11) 3482-3492 [7] Rajadhyaksha M, Menaker G, González S. Confocal examination of nonmelanoma cancers in thick skin excisions to potentially guide mohs micrographic surgery without frozen histopathology. The Journal of investigative dermatology (2001) 117(5) 1137-1143 [8] Jaafar H. Intra-Operative Frozen Section Consultation: Concepts, Applications and Limitations. The Malaysian Journal of Medical Sciences : MJMS (2006) 13(1) 4 [9] Zanello M, Poulon F, Abi Haidar D. Multimodal optical analysis discriminates freshly extracted human sample of gliomas, metastases and meningiomas from their appropriate controls. Scientific Reports (2017) 7 [10] Lukina M, Yashin K, Shirmanova M. Label-Free Macroscopic Fluorescence Lifetime Imaging of Brain Tumors. Frontiers in Oncology (2021) 11 1781 [11] Kho E, De Boer L, Ruers T. Hyperspectral imaging for resection margin assessment during cancer surgery. Clinical Cancer Research (2019) 25(12) 3572-3580 [12] Jerjes W, Hamdoon Z, Hopper C. Optical coherence tomography in the assessment of cutaneous cancer margins of the face: An immediate ex vivo study. Photodiagnosis and Photodynamic Therapy (2020) 29 101616 [13] Jain M, Robinson B, Mukherjee S. Rapid evaluation of fresh ex vivo kidney tissue with full-field optical coherence tomography. Journal of pathology informatics (2015) 6(1) 53 [14] Shin K, Francis A, Fu D. Intraoperative assessment of skull base tumors using stimulated Raman scattering microscopy. Scientific Reports (2019) 9(1) 1-12 [15] Hollon T, Lewis S, Orringer D. Rapid Intraoperative Diagnosis of Pediatric Brain Tumors Using Stimulated Raman Histology. Cancer research (2018) 78(1) 278-289 [16] Orringer D, Pandian B, Camelo-Piragua S. Rapid intraoperative histology of unprocessed surgical specimens via fibre-laser-based stimulated Raman scattering microscopy. Nature Biomedical Engineering (2017) 1(2) 1-13 [17] Fang N, Wu Z, Chen J. Label-free imaging of collagen as a potential diagnostic marker for detection of gliomas. (2019) 11209 1389-1392 [18] Uckermann O, Galli R, Kirsch M. Label-free multiphoton imaging allows brain tumor recognition based on texture analysis—a study of 382 tumor patients. Neuro-Oncology Advances (2020) 2(1) 1-10 [19] Noske D, Galgano G, Hamer P. Third harmonic generation imaging for fast, label-free pathology of human brain tumors. Biomedical Optics Express, (2016) 7(5) 1889-1904 [20] Zhang Z, de Munck J, Groot M. Quantitative Third Harmonic Generation Microscopy for Assessment of Glioma in Human Brain Tissue. Advanced Science (2019) 6(11) 1900163 [21] Chen D, Nauen D, Mayo Professor C. Label-free imaging of human brain tissue at subcellular resolution for potential rapid intra-operative assessment of glioma surgery. Issue 15 Theranostics (2021) 11(15) 7222-7234 [22] You S, Tu H, Boppart S. Intravital imaging by simultaneous label-free autofluorescence-multiharmonic microscopy. Nature Communications (2018) 9(1) 1-9 [23] Sun Y, You S, Boppart S. Intraoperative visualization of the tumor microenvironment and quantification of extracellular vesicles by label-free nonlinear imaging. Science Advances (2018) 4(12) [24] Karen J, Gareau D, Nehal K. Detection of basal cell carcinomas in Mohs excisions with fluorescence confocal mosaicing microscopy. The British journal of dermatology (2009) 160(6) 1242-1250 [25] Longo C, Pampena R, Ragazzi M. Diagnostic accuracy of ex vivo fluorescence confocal microscopy in Mohs surgery of basal cell carcinomas: a prospective study on 753 margins. British Journal of Dermatology (2019) 180(6) 1473-1480 [26] Snuderl M, Wirth D, Yaroslavsky A. Dye-enhanced multimodal confocal imaging as a novel approach to intraoperative diagnosis of brain tumors. Brain pathology (Zurich, Switzerland) (2013) 23(1) 73-81 [27] Bennàssar A, Vilata A, Malvehy J. Ex vivo fluorescence confocal microscopy for fast evaluation of tumour margins during Mohs surgery. The British journal of dermatology (2014) 170(2) 360-365 [28] Bertoni L, Puliatti S, Montironi R. Ex vivo fluorescence confocal microscopy: prostatic and periprostatic tissues atlas and evaluation of the learning curve. Virchows Archiv : an international journal of pathology (2020) 476(4) 511-520 [29] Tao Y, Shen D, Fujimoto J. Assessment of breast pathologies using nonlinear microscopy. Proceedings of the National Academy of Sciences of the United States of America (2014) [30] Cahill L, Wu Y, Fujimoto J. Nonlinear microscopy for detection of prostate cancer: analysis of sensitivity and specificity in radical prostatectomies. Modern Pathology (2019) 33(5), 916-923 [31] Yoshitake T, Rosen S, Fujimoto J. Rapid histological imaging of bone without microtome sectioning using nonlinear microscopy. Bone (2022) 154 116254 [32] Cahill L, Rosen S, Sun Y. Real-time diagnosis and Gleason grading of prostate core needle biopsies using nonlinear microscopy. Modern Pathology (2021) 35(4) 539-548 [33] Xie W, Glaser A, True L. Diagnosing 12 prostate needle cores within an hour of biopsy via open-top light-sheet microscopy. Journal of Biomedical Optics (2020) 25(12) [34] Wang M, Tulman D, Brown J. Gigapixel surface imaging of radical prostatectomy specimens for comprehensive detection of cancer-positive surgical margins using structured illumination microscopy. Scientific Reports 2016 6:1 (2016) 6(1) 1-16 [35] Wang M, Kimbrell H, Brown J. High-Resolution Rapid Diagnostic Imaging of Whole Prostate Biopsies Using Video-Rate Fluorescence Structured Illumination Microscopy. Cancer research (2015) 75(19) 4032-4041 [36] Liu J, Wang M, Lee B. Nondestructive Diagnosis of Kidney Cancer on 18-gauge Core Needle Renal Biopsy Using Dual-color Fluorescence Structured Illumination Microscopy. Urology (2016) 98 195-199 [37] Lu T, Jorns J, Yu B. Rapid assessment of breast tumor margins using deep ultraviolet fluorescence scanning microscopy. Journal of biomedical optics (2020) 25(12) [38] Yoshitake T, Giacomelli M, Fujimoto J. Rapid histopathological imaging of skin and breast cancer surgical specimens using immersion microscopy with ultraviolet surface excitation. Scientific Reports 2018 8:1 (2018) 8(1) 1-12 [39] Boppart S, You S, Tu H. Simultaneous label-free autofluorescence-multiharmonic microscopy and beyond. APL Photonics (2019) 4(10) 100901 [40] Mehidine H, Jamme F, Abi Haidar D. Discrimination between primary low and high grade tumor and secondary metastasis tumor from deep-UV to NIR.(2019) 10871 27-35 [41] Skala M, Riching K, Ramanujam N. In vivo multiphoton microscopy of NADH and FAD redox states, fluorescence lifetimes, and cellular morphology in precancerous epithelia. Proceedings of the National Academy of Sciences of the United States of America (2007) [42] Poulon F, Mehidine H, Abi Haidar D. Optical properties, spectral, and lifetime measurements of central nervous system tumors in humans. Scientific Reports (2017) 7(1) 1-8 [43] Zhang Y, Huang B, Wong T. Advances in optical microscopy revolutionize the practice of surgical pathology with rapid and non-destructive tissue assessment. The European Physical Journal Special Topics (2022) 231(4) 763-779 [44] Voskuil F, Vonk J, van Dam G. Intraoperative imaging in pathology-assisted surgery. Nature Biomedical Engineering (2021) 6(5) 503-514 [45] Lopez D, Sgroi D, Tearney G. Is Real-Time Microscopy on the Horizon? A Brief Review of the Potential Future Directions in Clinical Breast Tumor Microscopy Implementation. Virchows Archiv : an international journal of pathology (2022) 480(1) 211-227 [46] Liu Y, Levenson R, Jenkins M. Slide Over: Advances in Slide-Free Optical Microscopy as Drivers of Diagnostic Pathology. The American Journal of Pathology (2022) 192(2) 180-194 [47] Sun C, Kao C, Liao Y. Slide‐free imaging of hematoxylin‐eosin stained whole‐mount tissues using combined third‐harmonic generation and three‐photon fluorescence microscopy. Journal of Biophotonics (2019) 12(5) [48] Betts J, Wise J. Anatomy and physiology. OpenStax College [49] Christopher S. Ahuja, Jefferson R. Wilson, Satoshi Nori, Mark R. N. Kotter, Claudia Druschel, Armin Curt & Michael G. Fehlings. Traumatic spinal cord injury. Nature Reviews Disease Primers volume 3, Article number: 17018 (2017) [50] Kleihues P, Louis D, Cavenee W. The WHO Classification of Tumors of the Nervous System. Journal of Neuropathology & Experimental Neurology (2002) 61(3) 215-225 [51] Zong H, Verhaak R, Canolk P. The cellular origin for malignant glioma and prospects for clinical advancements. Expert Review of Molecular Diagnostics (2012) 12(4) 383 [52] Louis D, Perry A, Ellison D. The 2016 World Health Organization Classification of Tumors of the Central Nervous System: a summary. Acta neuropathologica (2016) 131(6) 803-820 [53] Rajeswarie R, Rao S, Santosh V. A simple algorithmic approach using histology and immunohistochemistry for the current classification of adult diffuse glioma in a resource-limited set-up. Journal of Clinical Pathology (2018) 71(4) 323-329 [54] Wesseling P, Kros J, Jeuken J. The pathological diagnosis of diffuse gliomas: towards a smart synthesis of microscopic and molecular information in a multidisciplinary context. Diagnostic Histopathology (2011) 17(11) 486-494 [55] D’Alessio A, Proietti G, Scicchitano B. Pathological and Molecular Features of Glioblastoma and Its Peritumoral Tissue. Cancers (2019) 11(4) [56] J. He, K. Mokhtari, M. Sanson, Y. Marie, M. Kujas, S. Huguet, P. Leuraud, L. Capelle, J. Y. Delattre, J. Poirier, K. Hoang-Xuan. Glioblastomas with an Oligodendroglial Component: A Pathological and Molecular Study. Journal of Neuropathology & Experimental Neurology, (2001)9 863–871 [57] M.D. Rubin, Raphael (Editor), Ph.D. Strayer, David S. Rubin's Pathology: Clinicopathologic Foundations of Medicine (PATHOLOGY (RUBIN)) 6th [58] From the case: Anaplastic astrocytoma IDH wildtype (pineal region). Radiopaedia. [59] Dimitri P. Agamanolis. Neuropathology Chapter 9. https://neuropathology-web.org/ [60] Glioblastoma : Epithelioid type. Webpathology. https://www.webpathology.com/ [61] Ballester L, Fuller G. Intraoperative Consultation and Optimal Processing. Practical Surgical Neuropathology: A Diagnostic Approach (2th edition) [62] Zipfel W, Williams R, Webb W. Nonlinear magic: multiphoton microscopy in the biosciences. Nature Biotechnology 2003 21:11 1369-1377 [63] Squier J, Müller M. High resolution nonlinear microscopy: A review of sources and methods for achieving optimal imaging. Review of Scientific Instruments (2001) 72(7) 2855 [64] Boyd R. Nonlinear Optics, 3rd Edition | Robert Boyd | ISBN 9780123694706.(2008) 640 [65] Kazarine A, Gopal A, Wiseman P. Nonlinear microscopy of common histological stains reveals third harmonic generation harmonophores. Analyst (2019) 144(10) 3239-3249 [66] Wu P, Wu P, Sun C. In vivo harmonic generation microscopy for monitoring the height of basal keratinocytes in solar lentigines after laser depigmentation treatment. Biomedical Optics Express, (2021) 12(10) 6129-6142 [67] Nicolas Olivier, Delphine Débarre, Emmanuel Beaurepaire. THG microscopy of cells and tissues: contrast mechanisms and applications. [68] Tai S, Yu C, Sun C. In vivo molecular-resonant third harmonic generation microscopy of hemoglobin. Conference on Lasers and Electro-Optics, 2007, CLEO 2007 (2007) [69] Boppart S, You S, Tu H. Simultaneous label-free autofluorescence-multiharmonic microscopy and beyond. APL Photonics (2019) 4(10) 100901 [70] Yu C, Sun C, Chan Y. In vivo and ex vivo imaging of intra-tissue elastic fibers using third-harmonic-generation microscopy. Optics Express, (2007) 15(18) 11167-11177 [71] Rehberg M, Krombach F, Dietzel S. Label-Free 3D Visualization of Cellular and Tissue Structures in Intact Muscle with Second and Third Harmonic Generation Microscopy. PLOS ONE (2011) 6(11) e28237 [72] Yu C, Sun C, Chan Y. Molecular third-harmonic-generation microscopy through resonance enhancement with absorbing dye. Optics Letters, Vol. 33, Issue 4, pp. 387-389 (2008) 33(4) [73] Yu C, Sun C, Lee W. In vivo optical biopsy of hamster oral cavity with epi-third-harmonic-generation microscopy. Optics Express, (2006) 14(13) 6178-6187 [74] Chu S, Tai S, Sun C. High-resolution simultaneous three-photon fluorescence and third-harmonic-generation microscopy. Microscopy Research and Technique (2005) 66(4) 193-197 [75] Lee T, Senyuk B, Smalyukh I. Optical Microscopy of Soft Matter Systems.Fluids, Colloids and Soft Materials: An Introduction to Soft Matter Physics (2011) [76] Ulrich Leischner, Walter Zieglga ̈nsberger, Hans-Ulrich Dodt, Resolution of Ultramicroscopy and Field of View Analysis. PLoS ONE 4(6): e5785. https://doi.org/10.1371/journal.pone.0005785 [77] Stelzer E. Contrast, resolution, pixelation, dynamic range and signal-to-noise ratio: fundamental limits to resolution in fluorescence light microscopy. Journal of Microscopy (1998) 189(1) 15-24 [78] Benjamin W. Pearrea, Christos Michasb, Jean-Marc Tsangb, Timothy J. Gardnera,Timothy M. Otchy. Fast micron-scale 3D printing with a resonant-scanning two-photon microscope. Additive Manufacturing 30 (2019) 100887 [79] Bumstead J, Park J, Culver J. Designing a large field-of-view two-photon microscope using optical invariant analysis. (2018) 5(2) 025001 [80] Hess S, Girirajan T, Mason M. Ultra-High Resolution Imaging by Fluorescence Photoactivation Localization Microscopy. Biophysical Journal (2006) 91(11) 4258-4272 [81] COHR_Fidelity-2_DS_0618_4. Coherent instruction. [82] Objective IX71/IX81 Instruction. Olympus instruction. [83] Newton-970-971-EMCCD-Cameras-Andor-Technology-Datasheet. [84] Borah B, Sun C. Construction of a high-NFOM multiphoton microscope with large-angle resonant raster scanning. STAR Protocols (2022) 3(2) 101330 [85] Bhaskar JyotiBorah, Jye-Chang Lee, Han-Hsiung Chi, Yang-Ting Hsiao, Chen-Tung Yen, Chi-Kuang Sun. Nyquist-exceeding high voxel rate acquisition in mesoscopic multiphoton microscopy for full-field submicron resolution resolvability. iScience (2021) 24(9) 103041 [86] Clokey G, Jacobson L. The autofluorescent "lipofuscin granules" in the intestinal cells of Caenorhabditis elegans are secondary lysosomes. Mechanisms of ageing and development (1986) 35(1) 79-94 [87] Kim J, Takahashi M, Miyamoto Y. Effects of a potent antioxidant, platinum nanoparticle, on the lifespan of Caenorhabditis elegans. Mechanisms of ageing and development (2008) 129(6) 322-331 [88] Age-related accumulation and spatial distribution of lipofuscin in RPE of normal subjects – PubMed. [89] Kennedy C, Rakoczy P, Constable I. Lipofuscin of the retinal pigment epithelium: A review. Eye 1995 9:6 (1995) 9(6) 763-771 [90] Gabrielle Alyse Murashova. THE INTEGRATION OF COMPUTATIONAL METHODS AND NONLINEAR MULTIPHOTON MULTIMODAL MICROSCOPY IMAGING FOR THE ANALYSIS OF UNSTAINED HUMAN AND ANIMAL TISSUES. [91] Gibbs S, Genega E, Frangioni J. Near-infrared fluorescent digital pathology for the automation of disease diagnosis and biomarker assessment. Molecular imaging (2015) 14(0) [92] Siddiqui R, Kabir N, Raza Shah M. Characterizing kidney structures in health and diseases using eosin fluorescence from hematoxylin and eosin stained sections. (2016) 39(4) 107-115 [93] Tuer A, Tokarz D, Barzda V. Nonlinear multicontrast microscopy of hematoxylin-and-eosin-stained histological sections. Journal of biomedical optics (2010) 15(2) 026018 [94] Mehidine H, Chalumeau A, Abi Haidar D. Optical Signatures Derived From Deep UV to NIR Excitation Discriminates Healthy Samples From Low and High Grades Glioma. Scientific Reports 2019 9:1 (2019) 9(1) 1-14 [95] Dowson J, Armstrong D, Jolly R. Autofluorescence emission spectra of neuronal lipopigment in animal and human ceroidoses (ceroid-lipofuscinoses). Acta neuropathologica (1982) 58(2) 152-156 [96] Palmer S, Litvinova K, Nabi G. Optical redox ratio and endogenous porphyrins in the detection of urinary bladder cancer: A patient biopsy analysis. Journal of biophotonics (2017) 10(8) 1062-1073 [97] Poulon F, Mehidine H, Abi Haidar D. Optical properties, spectral, and lifetime measurements of central nervous system tumors in humans. Scientific Reports 2017 7:1 (2017) 7(1) 1-8 [98] Boulton M. Studying melanin and lipofuscin in RPE cell culture models. Experimental eye research (2014) 126 61 [99] Sparrow J, Duncker T. Fundus Autofluorescence and RPE Lipofuscin in Age-Related Macular Degeneration. Journal of clinical medicine (2014) 3(4) 1302-1321 [100] Retinal pigment epithelial lipofuscin and melanin and choroidal melanin in human eyes - PubMed | - |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/86462 | - |
| dc.description.abstract | 在癌症的眾多治療方法中,手術為最能完整切除癌化組織的方式,但在有功能保留的組織器官,像是人體中樞神經系統中的腦部,術中能精確並有效率的分辨腫瘤及正常組織,以達到腫瘤完整切除及盡可能保留正常組織的雙重目的,便顯得相當重要。當今腫瘤切除手術的術中黃金標準流程為冷凍病理,其中樣品的製備過程需要花費相當長的處理時間,除有可能將真實的手術邊界於樣品處理流程中切除,也可能因冷凍過程造成假影。術後將會將檢體進行脫水、石蠟包埋等,以製作成術後判讀的黃金標準-石蠟切片,供病理科醫師於術後進行評估,並記錄下詳細的病理記錄。目前國際的眾多研究團隊倡議使用光學新鮮組織切片術來取代冷凍病理,但目前發表之技術除了未能良好地符合與黃金標準-石蠟切片的結果,及國際上對於數位病理影像保存與取樣之大面積高解析度規範,且眾多技術或耗時比目前冷凍病理久,或未能真實使用H&E而造成準確度偏低。
為解決此項迫切需要被改善的問題,本項研究首先透過測試老鼠腦的檢體,並模擬臨床的流程,以達到染色、實驗條件上的優化。而利用其結果,最後開發之the-RFP (true-H&E rapid fresh pathology)技術,透過改良實驗室過去開發之傳統H&E整體組織染色法的快速新鮮樣品染色流程,使非常軟的生物樣品也能進行整體組織的染色,在無需冷凍切片、能保存真實的手術邊緣區域的情況下,直接把術中取下極軟的的腦部檢體進行標準病理染劑的快速染色,再將檢體的最外緣平放於具十億畫素的非線性光學介觀顯微鏡之載物台上進行觀察,並結合以無須任何後處理的光學虛擬切片即時大面積超高解析度成像於螢幕,其檢體染色加上光學切片成像時間小於10分鐘,相當於傳統冷凍切片不到三分之一的時間,即可產生具各種組織病理資訊的大面積高解析度數位影像,以供病理師進行影像判讀。此外該影像在具極高畫素的狀態下,保持了國際數位病理影像所規範之亞微米等級的解析度,能把檢體上的病理細節鉅細靡遺地記錄,也可以提供未來的反覆讀取與後續留存備查。 為證實本技術是否能提供真實H&E、超高解析度、無任何假影且記錄各種組織上的病理特徵之新鮮病理影像,在台大醫院的腦癌手術邊緣臨床試驗中,此研究測試了50個人腦檢體,其中包含了25個經4個患者的腫瘤移除手術而切下的膠質瘤檢體,以及25個經冷凍儲存的正常人腦檢體,並將測試之影像與對應標準病理切片影像提供給台大醫院的病理科醫師進行無訓練的盲測判讀。而病理科醫師不僅能在本項新鮮病理影像技術的影像上快速且準確解讀各種組織病理學上的典型特徵,更在50個檢體的病理判讀上達到了100%的準確率。此項結果驗證了本技術能夠於現今腫瘤手術的術中鑑定過程能提供所急需之快速且準確的病理診斷,若未來使用於臨床,不僅能大幅降低手術時間,提高手術之精準度,更能有效提高醫院手術術中診斷過程之效率,以盡可能地挽救患者們的生命。 | zh_TW |
| dc.description.abstract | Among the multiple treatments for cancer, surgery is the most effective way to remove cancerous tissue completely. However, in some vital organs with preserved functions, such as the brain in the human central nervous system, it is very important to achieve the dual purpose of complete tumor resection and preservation of normal tissue as much as possible. The standard procedure for intraoperative tumor assessment is cryopathology, in which the sample preparation process takes a considerable amount of processing time and manpower. In addition to the possibility of excising the real surgical border in the sample preparation process, it may also cause artifacts due to the freezing process. After surgery, the removed specimen will be dehydrated, embedded in paraffin, etc., to make the gold standard for postoperative specimen assessment – formalin-fixed paraffin-embedded (FFPE) section, for the pathologist to evaluate and record pathological details and interpretion. At present, many international research teams advocate the use of optical microscopy which can do fresh tissue virtual-sectioning to replace cryopathology, but the published technologies are unable to meet the FFPE section results, do sub-micron resolution imaging under the whole-slide imaging guideline to preserve the digital pathological image details. and may take longer than current cryopathology, or fail to reach same contrast as H&E images, resulting in low accuracy.
In order to solve this problem that is urgent to be improved, this study first tested mouse brain samples and tried to simulate the clinical process to achieve the optimization of staining and experimental conditions. Based on those results, we finally develop the-RFP (true-H&E rapid fresh pathology), which include the improvement with the robust fresh sample staining process of traditional H&E whole-mount tissue staining method developed in our laboratory in the past, to enable soft biological samples to be processed. For the preparation of the tissues, it is no need to do microtoming, so the real surgical margin area can be preserved. The extremely soft brain specimens were directly removed from the operation, transferred to laboratory and did true-H&E rapid soft tissue staining with standard clinical dyes, and the superficial surface of the specimens were stained. Later on, the edge was placed on the sample holder of a mesoscale nonlinear optical gigascope for observation, combining with the optical virtual sectioning without any post-processing, so the real-time large-area ultra-high-resolution images were performed on the screen. Besides, the total processing time of staining and imaging was less than 10 minutes, which was equivalent to less than one-third of the time of traditional frozen section, and a large-area high-resolution digital image with various detailed histopathological information can be generated for pathologists to perform pathological interpretation, and can also be repeated reading in the future with digital storage in the computer. To confirm whether this technology can provide true H&E, ultra-high resolution, fresh-tissue-preparation pathological images without any artifacts, and record pathological features on various tissues, this study tested 50 specimens in a clinical trial with National Taiwan University Hospital. The brain specimens included 25 glioma specimens excised from 4 subjects acquired from patients’ tumor removal surgeries, and 25 normal human brain specimens stored in the -80°C refrigerator. The-RFP images and the corresponding FFPE bright field images were provided to pathologists at National Taiwan University Hospital for pathological interpretation as a blind-test. The pathologist can not only quickly and accurately interpret the typical features of various histopathology on the the-RFP images of this new pathological imaging technology, but also achieve 100% accuracy in the pathological assessment of 50 specimens. This result verifies that this technology can provide the fast and accurate pathological procedures in the current intraoperative tumor assessment in tumor removal surgery. If it is conducted in clinical use in the future, it can not only greatly reduce the operation time, improve the accuracy of the operation with more effective preparation to save the lives of patients as much as possible. | en |
| dc.description.provenance | Made available in DSpace on 2023-03-19T23:57:14Z (GMT). No. of bitstreams: 1 U0001-2909202200394500.pdf: 16145575 bytes, checksum: 13cac24700c4d7c2b23df733e0941560 (MD5) Previous issue date: 2022 | en |
| dc.description.tableofcontents | Table of contents
誌謝……………………………………………………………………….I 中文摘要…………………………..…………………………………….II Abstract……………………………… ………………………………..IV List of Figures………………………………………………………...XII List of Tables………………………………………………….……..XXV Chapter 1 Introduction………………………………………………..1 1.1 Motivation……………………………………………………………………1 1.2 Overview of potential optical imaging technologies for rapid intraoperative margin assessment…………………………………………..3 1.3 Thesis scope…………………………………………………………………..6 Chapter 2 Background Knowledge…………………………………..9 2.1 Brief introduction to the central nervous system………………………….9 2.2 What’s “Glioma” ?........................................................................................10 2.3 Intraoperative pathology process………………………………………….16 2.4 Nonlinear optical imaging modalities……………………………………...19 2.4.1 Virtual Sectioning by Femtosecond laser as Excitation Source……..20 2.4.2 Nonlinear Optics……………………………………………………….22 2.4.3 Resolution………………………………………………………………26 2.4.4 Imaging Modalites of NLOM………………………………………….28 Chapter 3 Experimental Setup……………………………………...31 3.1 Ytterbium-doped fiber laser………………………………………………31 3.2 Nonlinear spectroscopy system……………………………………………31 3.3 Nonlinear multimodal microscopy system………………………………..34 3.3.1 System setup……………………………………………………………34 3.3.2 Frame Rate and Image Accumulation………………………………..37 3.3.3 Lateral/Axial Resolution………………………………………………38 Chapter 4 Nonlinear spectroscopy study for fluorophores, dyes, and human brain tissues……………………………………………………40 4.1 Sample Preparation and Spectra Acquisition…………………………….40 4.2 Results and Analysis of Nonlinear Spectra………………………………..42 4.2.1 Hematoxylin & Eosin…………………………………………………..43 4.2.2 Chemical fluorophores in human brain tissue……………………….45 4.2.3 Unstained human brain sectioned tissue……………………………..49 4.2.4 Unstained whole-mount human brain tissue…………………………51 4.2.5 H&E stained human glioblastoma sectioned tissue………………….53 Chapter 5 Developing ing rapid rapid true-H&Efresh pathology...56 5.1 Image processing……………………………………………………………57 5.1.1 Image acquisiton parameters setup………….……………………….57 5.1.2 Three-dimensional Imaging and stacking……………………………60 5.1.3 Real-time color remapping…………………………………………….62 5.1.4 Real-time contrast enhancement and image stitching……………….66 5.2 H&E stained human brain & skin sectioning slides………………………71 5.3 Optimization of the robust H&E staining protocol……………………….78 5.3.1 Tissue Preparation and Staining Reagents…………………………...78 5.3.2 Staining protoocol optimization and comparison……………………82 5.4 H&E stained whole-mount human glioma tissue…………………………90 5.4.1 Tissue Preparation……………………………………………………..90 5.4.2 High cellularity – a obvious feature from macroscopic view………..92 5.4.3 Nuclear atypia –key tumor feature to distinguish abnormality……..96 5.4.4 Microvascular proliferation – abnormal vessels hyperplasia……….98 5.4.5 Necrosis – large area of cell death……………………………………101 5.4.6 Some examples of mesoscale the-RFP images………………………103 5.5 H&E stained whole-mount human normal brain tissue………………..108 5.5.1 Tissue preparation……………………………………………………108 5.5.2 Typical normal brain structures in the-RFP images……………….110 5.6 Blind accuracy test………………………………………………………..115 Chapter 6 Summary and Future work……………………………119 Reference list………………………………………………………….123 | - |
| dc.language.iso | en | - |
| dc.subject | 高解析度病理影像 | zh_TW |
| dc.subject | 快速新鮮樣品染色法 | zh_TW |
| dc.subject | 人體腦部檢體 | zh_TW |
| dc.subject | 具十億畫素之非線性光學介觀顯微鏡 | zh_TW |
| dc.subject | 術中腫瘤評估 | zh_TW |
| dc.subject | ultra-high-resolution pathological image | en |
| dc.subject | intraoperative tumor assessment | en |
| dc.subject | robust fresh whole-mount tissue staining method | en |
| dc.subject | human brain tissue | en |
| dc.subject | mesoscale nonlinear optical gigascope | en |
| dc.title | 以非線性顯微術擷取染色之人腦組織影像:評估膠質瘤手術邊界 | zh_TW |
| dc.title | Nonlinear Microscopy Imaging of Hematoxylin-Eosin Stained Whole-Mount brain Tissues: Assessment of surgical Margins in glioma removal Surgery | en |
| dc.type | Thesis | - |
| dc.date.schoolyear | 110-2 | - |
| dc.description.degree | 碩士 | - |
| dc.contributor.oralexamcommittee | 廖怡華;王奐之 | zh_TW |
| dc.contributor.oralexamcommittee | Yi-Hua Liao;Huan-Chih Wang | en |
| dc.subject.keyword | 術中腫瘤評估,快速新鮮樣品染色法,人體腦部檢體,具十億畫素之非線性光學介觀顯微鏡,高解析度病理影像, | zh_TW |
| dc.subject.keyword | intraoperative tumor assessment,robust fresh whole-mount tissue staining method,human brain tissue,mesoscale nonlinear optical gigascope,ultra-high-resolution pathological image, | en |
| dc.relation.page | 137 | - |
| dc.identifier.doi | 10.6342/NTU202204215 | - |
| dc.rights.note | 同意授權(全球公開) | - |
| dc.date.accepted | 2022-09-30 | - |
| dc.contributor.author-college | 電機資訊學院 | - |
| dc.contributor.author-dept | 光電工程學研究所 | - |
| dc.date.embargo-lift | 2027-09-29 | - |
| Appears in Collections: | 光電工程學研究所 | |
Files in This Item:
| File | Size | Format | |
|---|---|---|---|
| ntu-110-2.pdf Until 2027-09-29 | 15.77 MB | Adobe PDF |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.
