Chemical composition of mandibular bone : applications of Fourier transform infrared and narrowband autofluorescence imaging

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DISSERTATIONS | ANNI MARJUKKA PALANDER | CHEMICAL COMPOSITION OF MANDIBULAR BONE | No 641

ANNI MARJUKKA PALANDER

Chemical composition of mandibular bone

Applications of Fourier transform infrared and narrowband autofluorescence imaging

Dissertations in Health Sciences

PUBLICATIONS OF

THE UNIVERSITY OF EASTERN FINLAND

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CHEMICAL COMPOSITION OF MANDIBULAR BONE

APPLICATIONS OF FOURIER TRANSFORM INFRARED AND NARROWBAND AUTOFLUORESCENCE IMAGING

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Anni Marjukka Palander

CHEMICAL COMPOSITION OF MANDIBULAR BONE

APPLICATIONS OF FOURIER TRANSFORM INFRARED AND NARROWBAND AUTOFLUORESCENCE IMAGING

To be presented by permission of the Faculty of Health Sciences,

University of Eastern Finland for public examination in A210-11 auditorium, Tampere on November 26th, 2021, at 12 o’clock noon

Publications of the University of Eastern Finland Dissertations in Health Sciences

No 641

Department of Dentistry/ School of Medicine University of Eastern Finland, Kuopio

2021

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Series Editors

Professor Tomi Laitinen, M.D., Ph.D.

Institute of Clinical Medicine, Clinical Physiology and Nuclear Medicine Faculty of Health Sciences

Professor Ville Leinonen, M.D., Ph.D.

Institute of Clinical Medicine, Neurosurgery Faculty of Health Sciences

Professor Tarja Malm, Ph.D.

A.I. Virtanen Institute for Molecular Sciences Faculty of Health Sciences

Lecturer Veli-Pekka Ranta, Ph.D.

School of Pharmacy Faculty of Health Sciences Lecturer Tarja Välimäki, Ph.D.

Department of Nursing Science Faculty of Health Sciences

Printing office:

PunaMusta Oy 2021 Distributor:

University of Eastern Finland Kuopio Campus Library ISBN: 978-952-61-4301-9 (print/nid.)

ISBN: 978-952-61-4302-6 (PDF) ISSNL: 1798-5706

ISSN: 1798-5706 ISSN: 1798-5714 (PDF)

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Author’s address: Institute of Dentistry University of Eastern Finland KUOPIO

FINLAND

Doctoral programme: Doctoral programme of Clinical Research Supervisors: Professor Arja Kullaa, DDS, Ph.D.

Institute of Dentistry

University of Eastern Finland KUOPIO

FINLAND

Docent Arto Koistinen, Ph.D.

SIB Labs

University of Eastern Finland KUOPIO

FINLAND

Reviewers: Professor Jenneke Klein-Nulend, Ph.D.

Department of Oral Cell Biology, Amsterdam, The Netherlands Academic Centre for Dentistry Amsterdam (ACTA), University of Amsterdam and Vrije Universiteit Amsterdam

AMSTERDAM NEATHERLANDS

Professor György K.B. Sándor, DDS, MD, Ph.D.

Research Unit of Oral Healt Sciences / Department of Oral and Maxillofacial Surgery

University of Oulu OULU

FINLAND

Opponent: Professor Riitta Seppänen-Kaijansinkko, MD, DDS, CVM, PhD, Dr.Tech (h.c.)

Faculty of Medicine / Clinicum

Department of Oral and Maxillofacial Diseases University of Helsinki and Helsinki University Hospital HELSINKI

FINLAND

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7 Palander, Anni

Chemical composition of mandibular bone – applications of Fourier transform infrared and narrowband autofluorescence imaging

Kuopio: University of Eastern Finland

Publications of the University of Eastern Finland Dissertations in Health Sciences 641. 2021, 144 p.

ISBN: 978-952-61-4301-9 (print) ISSNL: 1798-5706

ISSN: 1798-5706

ISBN: 978-952-61-4302-6 (PDF) ISSN: 1798-5714 (PDF)

ABSTRACT

Mandibular bone is unique regarding its embryonic origin, chemical composition, cellular responses, vasculature, and even its characteristic pathologies, i.e osteoradionecrosis and medication-related osteonecrosis of the jaws. These features of mandibular bone highlight the need for targeted research to investigate the composition of mandibular bone and tissue reactions to different exposures (i.e. head and neck cancers, radiotherapy and

chemotherapy). The complex process of new bone formation is of special interest, because of its crucial role in determining the health and biomechanical properties of the newly-formed tissue. The bone’s biomechanical properties are based on a strict hierarchial structure, from the tissue’s chemical composition to the macroscopic orientation of the structures. Ultimately, the tissue’s structure is based on its chemical composition; this can be analyzed with different spectroscopic methods. However, previously none of these methods have been applied to characterize osteoid composition and new mandibular bone formation in detail, perhaps because the specific localization of the spectroscopic data requires a multimodal imaging technique in order to match the spectral data with the histological landmarks.

The main aim of this dissertation was to study mandibular new bone formation and tissue reactions for head and neck cancer treatments with different spectral imaging methods. In order to archieve this aim the following specific objectives were adressed. The first objective was to develop a fast and label-free digital staining technique based on autofluorescence.The new autofluorescence imaging method performed equally or better in tissue feature

recognition than the traditional Masson-Goldner trichrome staining.

The second objective was to couple this new imaging method with high-resolution Fourier Transform Infrared (FTIR) imaging in order to match chemical data from FTIR with digitally stained histologic features of the autofluorescence image. This matching of the two data sets provided two advantages; a chemical explanation for autofluorescent features obtained from FTIR and a specific localization of FTIR data according to histological landmarks. This is the first time that the histologic localization of FTIR data has achieved a specific molecular characterization of the osteoid and new bone formation in mandibular bone. Osteoid deposition starts with collagen matrix secretion and maturation (cross-link formation) in the growth zone of the osteoid. However, the collagen maturation is not completed at the time

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when mineralization begins in the mineralizing front of the osteoid. During mineral maturation, acid phosphate substitution becomes gradually decreased, indicative of its replacement by hydroxyapatite. Furthermore, there is an increased degree of carbonate substitution, leading to a decrease in mineral crystal size and perfection.

The third objective of this dissertation was to evaluate the probable chemical changes in mandibular bone tissue evoked by head and neck cancer, radiotherapy and

chemoradiotherapy. It appeared that combined radiochemotherapy may affect the composition of the bone’s organic component, as revealed from the significantly different amide I region in radiochemotherapy patients compared to healthy controls. Thus, the cumulative effect of cancer and different treatment modalities should be considered in future studies of osteoradionecrosis.

Keywords: mandibular bone, multispectral imaging, autofluorescence, Fourier transform infrared spectroscopy, osteoradionecrosis

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9 Palander, Anni

Chemical composition of mandibular bone – applications of Fourier transform infrared and narrowband autofluorescence imaging

Kuopio: Itä-Suomen yliopisto

Publications of the University of Eastern Finland Dissertations in Health Sciences 641. 2021, 144 p.

ISBN: 978-952-61-4301-9 (print) ISSNL: 1798-5706

ISSN: 1798-5706

ISBN: 978-952-61-4302-6 (PDF) ISSN: 1798-5714 (PDF)

TIIVISTELMÄ

Alaleukaluu eroaa muista luista sikiöaikaisen kehityksen, kemiallisen koostumuksen, soluvasteiden, verisuonituksen ja tyypillisten tautitilojen, kuten osteoradionekroosin sekä lääkkeisiin liittyvän leukaluun osteonekroosin osalta. Näiden erityispiirteiden vuoksi on tärkeää tutkia alaleukaluun koostumusta ja vasteita erilaisille ulkoisille tekijöille, kuten pään ja kaulan alueen syöville, sädehoidolle ja kemoterapialle. Erityisen mielenkiinnon kohteena on luun uudismuodostusprosessi, sillä se määrittää tulevan kudoksen terveyttä ja biomekaanisia ominaisuuksia. Luun biomekaniikan perustana on monitasoinen hierarkinen rakenne, aina kemiallisesta koostumuksesta makroskooppiseen kudosrakenteeseen. Kudosrakenteen perustana olevaa kemiallista koostumusta voidaan tutkia erilaisilla spektroskooppisilla menetelmillä, joita ei kuitenkaan aikaisemmin ole sovellettu leukaluun uudismuodostuksen ja osteoidin kuvantamiseen. Syynä saattaa olla se, että spektridatan tarkka anatominen

asemointi histologisten maamerkkien mukaan vaatii monikuvantamistekniikkaa.

Tämän tutkimuksen päätavoitteena oli tutkia alaleukaluun uudisluun muodostusta ja kudoksen reaktioita pään ja kaulan alueen syöpähoidoille käyttäen spektroskooppisia menetelmiä. Tämän tavoitteen saavuttamiseksi kehitettiin ensimmäisessä osatyössä autofluorsenssiin perustuva, nopea ja kemiallisia leimauksia vaatimaton digitaalinen värjäystekniikka. Tämä uusi autofluoresenssitekniikka pystyi erottelemaan kudoksen komponentteja yhtä hyvin tai paremmin kuin perinteinen histologinen Masson-Goldner värjäys.

Toisessa osatyössä tämä uusi autofluoresenssitekniikka yhdistettiin korkean resoluution Fourier-muunnos infrapunakuvantamisen (FTIR) kanssa, jotta FTIR:n tuottama spektridata saatiin asemoitua autofluoresenssikuvien histologisten komponenttien kanssa. Kahden eri kuvantamismenetelmän datojen kohdistaminen toi kaksi etua; kemiallisen selityksen autofluoresenssikuvissa näkyville kudoksen piirteille, sekä tarkan histologisen sijainnin FTIR kuvantamisen tuottamalle kemialliselle koostumukselle. FTIR-datan histologisen sijainnin

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selvittäminen mahdollisti ensimmäistä kertaa leukaluun uudismuodostuksen arvioimisen.

Osteoidin muodostuminen alkaa kollageenin erityksellä ja kypsymisellä (ristisidosten muodostumisella) osteoidin kasvuvyöhykkeen alueella. Kollageeni ei kuitenkaan ole vielä täysin kypsää ennen kuin se alkaa mineralisoitua osteoidin mineralisaatiovyöhykkeen alueella. Mineraalien kypsymisen aikana niiden fosfaattihapposubstituutio vähenee, mikä viittaa kypsän hydroksiapatiitin muodostumiseen. Lisäksi karbonaattisubstituutio kasvaa, mikä johtaa hydroksiapatiitin ideaalisen kristallirakenteen heikkenemiseen.

Tutkimuksen kolmantena tavoitteena oli tutkia pään ja kaulan alueen syöpien, sädehoidon ja kemoterapian vaikutusta leukaluun kemialliseen rakenteeseen. Kolmannessa osatyössä todettiin, että yhdistetyllä kemosädehoidolla saattaa olla vaikutusta luun orgaanisten

komponenttien koostumukseen, sillä kemosädehoitoa saaneiden potilaiden amidi I alue FTIR- spektroskopiassa oli muuttunut verrattuna terveisiin kontrolleihin. Jatkossa pään ja kaulan alueen syöpien, sädehoidon ja kemoterapian yhteisvaikutukset tulisi huomioida

osteoradionekroositutkimuksissa.

Avainsanat: alaleukaluu, multispektrikuvantaminen, autofluoresenssi, Fourier-muunnos infrapunaspektroskopia, osteoradionekroosi

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ACKNOWLEDGEMENTS

The primary initator of this dissertation was the CSIBIOMED-project (Computational Spectral Imaging for Biological and Biomedical applications), an innovative and multidisciplinary collaboration between The Institute of Dentistry, The Department of Environmental and Biological Sciences and The School of Computing in University of Eastern Finland. The CSIBIOMED-project was funded by Business Finland (former TEKES) and involved collaboration between companies from Finland (PlanMeca Group, OlapCon) and Japan (Olympus Corporation). Bone sample material was provided by Department of Oral and Maxillofacial Surgery, Alrijne Hospital, Leiderdorp in The Netherlands, a long-term international collaboration partner of the Kullaa research group. During this one year CSIBIOMED-project, the preliminary testing of the methods and conceptualization of this thesis were performed. The accredited initiators of this collaboration were Professor Markku Hauta-Kasari, Professor Arja Kullaa, Docent Arto Koistinen and Professor Markku Keinänen. I express my sincerest thanks to every collaboration member for this educative and innovative project, that acted as a promoter for this dissertation.

I want to expess my gratitude to my supervisors Professor Arja Kullaa and Docent Arto Koistinen for their advice, support, patience and flexibility during this project. It has been a pleasure to work in such a warm and open environment. I truly appreciate your expertise, dedication and innovativeness. The multidisciplinary and international collaboration built by Arja and Arto has provided a unique viewpoint in the field of medical spectral research, in which I have been honored to participate.

My sincerest thanks belongs to Laure Fauch Ph.D. for her expertise and altruistic work during this research project. Without her dedication and contribution, I would not have been able to complete this work. I express my thanks to Mikael Turunen Ph.D. for his valuable advice, expertise and flexibility during this project.

My sincere thanks to Professor Riitta Seppänen-Kaijansinkko for accepting the invitation to be the official opponent in the public examination of this thesis. I express my gratitude to Professor Jenneke Klein-Nulend and Professor György Sandor for reviewing this dissertation.

I want to thank laboratory assistant Ritva Savolainen for her precise work with sample preparation. I also owe thanks to Emilia Uurasjärvi, Isa Lyijynen, Lassi Rieppo Ph.D. and Mikko Hyvärinen DDS who have kindly participated in data collection or processing. My sincere thanks to my collaborators in The Netherlands: Hannah Dekker DDS, MD, Professor Engelbert A.J.M. Schulten, Professor Chris Ten Bruggenkate and Professor Nathalie Bravenboer. Special thanks to Ewen MacDonald Ph.D. for lingustic editing.

I want to express my warmest gratitude to my parents and brother and to all of my friends for your love, support and encouragement before, during and after this journey. Reading this, you know you belong to the list of the embraced ones. Most importantly there are no words to thank my beloved husband Johannes. This journey has had its ups and downs, but you

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have guided me through it all, for better or for worse. Finally, the greatest tribute belongs to Aida, you made this and us complete.

Tampereella 26 marraskuuta 2021 Anni Palander

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LIST OF ORIGINAL PUBLICATIONS

This dissertation is based on (data presented in) the following original publications referred to in Chapters 4-6:

Chapter 4: Fauch, L*, Palander A*, Dekker H, Schulten E A J M, Koistinen A, Kullaa A, Keinänen, M. Narrowband-autofluorescence imaging for bone analysis.

Biomedical Optics Express. 2019;10: 2367-2382.

Chapter 5: Palander A*, Fauch L*, Turunen MJ, Dekker H, Schulten EAJM, Koistinen A, Bravenboer N, Kullaa A. Two-dimensional distribution of molecular composition in human mandibular bone osteoid. Submitted.

Chapter 6: Palander A, Dekker H, Hyvärinen M, Rieppo L, Schulten EAJM, Ten Bruggenkate CM, Koistinen A, Kullaa A, Turunen MJ. Long-term changes in mandibular bone microchemical quality after radiation therapy and underlying systemic

malignancy: a pilot study. Journal of Innovative Optical Health Sciences. 2021.

*equal contribution

The publications were adapted with the permission of the copyright owners.

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RADIATION THERAPY AND UNDERLYING SYSTEMIC MALIGNANCY: A PILOT STUDY ... 93 7 GENERAL DISCUSSION ... 109 7.1 Applicability of autofluorescent spectroscopy for bone imaging ... 109 7.2 Applicability of multimodal ftir and autofluorescent imaging of forming mandibular bone and osteoid ... 111 7.3 Process of osteoid and new mandibular bone formation ... 112 7.4 Effects of hnc, rt and radiochemotherapy on mandibular bone chemical composition113 7.5 Future aspects ... 114 8 CONCLUSIONS ... 117 REFERENCES ... 119

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ABBREVIATIONS

ACP Amorphous calcium phosphate

AFM Atomic force microscopy AGEs Advanced glycation end

products

ALP Alkaline phosphatase AMP Adenosine monophosphate APS Acid phosphate substitution APS-index Acid phosphate substitution

index

ASCs Adipose stem cells

ATR-FTIR Attenuated total reflectance Fourier transform infrared spectroscopy

BED Biologically equivalent dose BMD Bone mineral density BMDD Bone mineral density

distribution

BMSCs Bone marrow stem cells BMU Basic multicellular unit BSU Basic structural unit Ca²⁺ Calcium ion

CLSM Confocal laser scanning microscopy

CM Carbonate-to-matrix ratio CM Crystal maturity degree CO32- Carbonate ion

CP Carbonate-to-phosphate ratio

Ct Cortex

CT Computed tomography CT Connective tissue deH-DHLNL Dehydro-dihydroxylysino-

norleucine

deH-HLNL Dehydro-hydroxylysino- norleucine

DMP1 Dentin matrix protein 1 DNA Deoxyribonucleic acid

DPD Deoxy-pyridinolide DPL Deoxy-pyrrololine

DPX Dibutylphthalate polystyrene xylene

DXA Dual x-ray absoptiometry ECM Extracellular matrix FGF Fibroblast growth factor FPA focal-plane-array

FTIR Fourier transform infrared spectroscopy

Gly Glycine

Gy Grey, radiation dose unit

GZ Growth zone

HA Hydroxyapatite HBO Hyperbaric oxygen

HDR Hight dose rate brachytherapy HLKLN Hydroxylysino-5-

ketonorleucine

HNC Head and neck cancers HPO42- Acid phosphate ion HSCs Hematopoietic stem cells Hyl Hydroxylysine

Hyp Hydroxyproline IMRT Intensity-modulated

radiotherapy IQR Interquartile range

Lc Lacuna

LCN Lacuno-canalicular network LCS Lacuno-canalicular system LH Lycine hydroxylase LKLN Lysino-5-ketonorleucine

Lys Lysine

MAR Mineral apposition rate M-CSF Macrophage colony

stimulating factor

MCT Mercury-cadmium-telluride

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MEPE Matrix extracellular phosphoglycoprotein MFr Mineralizing front

MG Masson-Goldner-trichrome MM Minreal-to-matrix ratio MMP Matrix metalloproteinase MRONJ Medication related

osteonecrosis of the jaws NADH Nicotinamide adenine

dinucleotide

NADPH Nicotinamide adenine dinucleotide phosphate NCPs Non-collagenous proteins

O Osteoid

Ob Osteoblast

OCP Octocalciumphosphate OH^- Hydroxyl ion

OPG Osteoprotegerin OPN Osteopontin ORN Osteoradionecrosis

OSCC Oral squamous cell carcinoma

Ot Osteocyte

PCA Principal component analysis PO43- Phosphate ion

pQCT Peripheral quantitative tomography

Pro Proline

PTH Parathyroid hormone Pyl Pyrrololine

Pyr Pyridinolide Raman Raman scattering

spectroscopy RANKL RANK-ligand

RBC Erythrocyte, red blood cell RER Rough endoplasmic reticulum RIF Radiation induced fibrosis RT Radiation therapy,

radiotherapy

SAM Scanning acoustic microscopy SAXS Small angle x-ray

SCC Squamous cell carcinoma SEM Scanning electron microscopy SHG Second harmonic generation SNR Signal-to-noise ratio

TEM Transmission electron microscopy

TGF Transforming growth factor THG Third harmonic generation UV Ultraviolet

XST-index Crystallinity index 3PEF Three-photon excited

fluorescence

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1 INTRODUCTION

Bone quality is defined as “the sum of all characteristics of bone that influence the bone’s resistance to fracture”(1). However, in the jawbone region, the bone tissue is often

predisposed to various disturbances, such as microbial invasion in periodontal conditions or minor surgeries, such as tooth extraction or dental implant placement. The term bone quality in the jaw bone region is hence a wider concept than simply strain resistance. First, it may reflect the tissue responses upon pathogen exposure. Second, the quality of alveolar bone is often considered as its ability to heal after tooth extraction or to provide good stability to a dental implant upon implant insertion surgery and later under prosthetic loading. The third question regarding mandibular bone quality and metabolism is the fact that mandibular bone is especially prone to necrotic conditions, such as medication related osteonecrosis (MRONJ) and osteoradionecrosis (ORN), probably due to its different blood supply or differences in turnover rate and microstructure. As there is no clear consensus on all the parameters of the bone tissue that predicts responses in these processes, there is a demand for new tools to define the composition and quality of mandibular bone (2). A consensus in the debate is that due to its heterogeneous composite nature, a thorough assessment of its quality requires the assessment of macroscopic and microscopic parameters, as well as an evaluation of the bone’s organic and inorganic components. Bone quality research methods should thus aim to adopt multimodal approaches if they are to obtain a reliable assessment of bone properties.

To answer these questions this dissertation describes the development of a new

narrowband ultraviolet autofluorescent imaging method that represents multimodal aspects of tissue chemical (autofluorescent spectral data) and microstructure (digital staining) (Chapter 4). This new method was combined with established high-resolution Fourier transform infrared (FTIR) imaging, an approach that has not been previously applied on human mandibular bone. With these two techniques, an assessment of the formation of new mandibular bone was performed in healthy patients (Chapter 5). Furthermore, the effects of head and neck cancer (HNC), radiotherapy (RT), and radiochemotherapy on bone chemical quality were investigated using FTIR spectroscopy (Chapter 6). Thus, this research presents a new multimodal imaging technique, novel information about mandibular bone normal biology, as well as insights into the potential changes that HNC and its different treatment modalities could exert on mandibular bone tissue.

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2 REVIEW OF THE LITERATURE

2.1 MANDIBULAR BONE

The mandible is a dual-jointed bone that supports the teeth and the masticatory organ. The bone is divided into different anatomical regions (Figure 1). The condylar processes (processus condylaris) articulate with articular fossae of temporal bones on both sides of the skull. The coronoid processes (processus coronoideus) are located anterior to the condyles and serve as insertions for the temporal muscle. The vertical part of the mandible is referred to as the mandibular ramus or branch (ramus mandibulare) and its medial aspect contains mandibular foramen (foramen mandibulare), where the bony mandibular canal (canalis mandibularis) descends inside the mandible. Inside the mandibular canal are blood vessels and nerves that supply the bone and lower teeth. The mandibular angle (angulus mandibulare) is located inferior to ramus and makes an anterior turn towards the body of the mandible (corpus mandibulare). The anterior third of the mandibular body contains the mental foramen (foramen mentale) (3). The most anterior tip of the body is called the mandibular symphysis (symphysis mandibulare). Superior to the mandibular body, the alveolar process (processus alveolaris) supports the arch of lower teeth (4).

Figure 1. Schematic image of mandibular bone anatomy

2.1.1 Mandibular bone embryonic origin

Primary bone formation (bone modeling) arises from mesenchymal stem cells through two different pathways. Most of the long bones in the skeleton are formed by endochondral ossification that takes place in epiphyseal growth plates. Flat bones, such as the maxilla and

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mandible, are formed through intramembranous ossification, where centers of mineralization are located throughout the bone mesenchymal scaffold (5). However, in the condylar regions, the bone growth is achieved through endochondral ossification (6).

During the embryonic mandibular bone development, the mesenchymal stem cells of the neural crest from the mid- and hind-brain neural folds migrate ventrally towards the facial region. At that location, the mesenchymal stem cells differentiate directly into osteoblasts.

The osteoblasts initiate the deposition of collagen matrix and its mineralization, and mandibular bone undergoes an intramembranous ossification. The process is primarily guided by increased expression of RUNX2 and OSX genes and Wnt/β-catenin signalling, which drive osteogenic differentiation of the mesenchymal stem cells. Several other signaling pathways also contribute to the process, including transforming growth factor family (TGF), Notch-pathway, and fibroblast growth factor (FGF) (7).

Meckel’s cartilage is a temporary embryonic structure that supports mandibular bone development. The anterior and posterior parts of the cartilage ossify into the symphyseal bone and bones of the middle ear, respectively. The rest of the cartilage degenerates although part of it forms the sphenomandibular ligament (8).

2.2 BONE EXTRACELLULAR MATRIX

Bone is a heterogeneous composite tissue with multiple hierarchial structural levels (Figure 2).

Macroscopically and microscopically bone consists of dense compact bone and hollow trabecular bone (9-11). In the mandible, the thickness of outer compact or cortical bone can vary between 1-7 mm, depending on the anatomic site, gender, comorbidities and age (12- 14). Cortical bone forms cylindrical shaped units called osteons (11). In the middle of each osteon runs a Haversian canal that supplies the bone with vasculature, lymphatics, and nerves. The interconnecting Volkman canals run perpendicular to the Haversian canals (11).

Each osteon is lined by a cement line (15). Because Haversian systems are constantly

remodeled, some of the osteons remain imperfect. Histologically each bony unit surrounded by a cement line can be called a basic structural unit (BSU), independent from the perfect osteonal structure (16). The cortical bone is surrounded by loose connective tissue called the periosteum that contains periosteal vascular plexus. The periosteum has also its own osteogenic potential. The Volkman canals connect the periosteal vessels to the endosteum that lines the bone trabecles from the inside. Endosteum contains osteoprogenitor cells and is in direct contact with bone marrow (11).

A hollow trabecular bone core is located inside the cortical bone. The trabecular bone is less dense than cortical bone and it makes up the majority of the mandibular bone volume.

Cancellous bone has a higher remodeling rate and load response compared to cortical bone (11). Bone marrow is located in the network that remains between the trabeculae. Bone marrow contains connective tissue, adipose tissue, various cell types, nerves, lymph vessels, and vasculature (Figure 3).

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23 In terms of maturation, the bone types can also be divided into the woven bone and lamellar bone. Woven bone is found in developing bones or healing fracture sites, whereas mature cortical and trabecular bone have organized thin lamellae (17). Based on its chemical composition, bone can be viewed as a composite tissue that mainly consists of type I collagen fibrils mineralized with hydroxyapatite (HA) nanocrystals (18). About 60% of bone matrix is inorganic (mainly HA), 10% water and 30% organic (maily collagen I) (19). The detailed formation of the organic and inorganic matrix will be discussed in Chapter 2.6.

Figure 2. Structural hierarchy of bone tissue from molecular level on the left to microscopic level on the right. Collagen molecules form triple helical tropocollagen structures that further assemble into collagen fibrils and further into collagen fibers. Hydroxyapatite (HA) crystals aggregate on collagen fibrils. This mineralized matrix forms lamellary structures of bone tissue. Highest level in tissue hieararchy in the right separates dense cortical bone and hollow trabecular bone. Modified from (20)

2.3 BONE CELLS 2.3.1 Osteoblasts

Osteoblasts are bone forming cells that account for 4-6% of bone cells (21). They arise from a mesenchymal stem cell subtype, bone marrow stem/stromal cells (BMSCs). The BMCSs in jawbones have shown more rapid cell proliferation, delayed senescence, stronger osteogenic potential as compared to BMSCs in other bones (22,23). However, in contrast to the BMCSs, the mature osteoblasts of rat mandibular bone expressed a lower osteogenic potential than femur osteoblasts, but mandibular osteoblasts promoted more angiogenesis (24). Recent advances in stem cell technology have been able to yield jawbone tissue from another subtype of mesenchymal stem cells, called adipose stem cells (ASCs) (25). The mesenchymal stem cells differentiate into osteoprogenitor cells, referring to any cell type in bone marrow,

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endosteum or periosteum that will become a bone forming cell (11). The most important factors in this differentiation of cells into the osteoblastic direction are the Wnt-signalling pathway that promotes RUNX2 transcription factor (26,27) and osterix (Sp7) transcription factor (21,27). These cascades make the mesenchymal stem cells differentiate first into preosteoblasts and finally to mature osteoblasts which then align on the bone border. They are cuboidal basophilic cells with a round nucleus located basally. The basal border of the cell can also express cytoplasmic processes (21,27). Activated osteoblasts produce new bone; its deposition will be discussed later in detail. After the new bone production, the fate of mature osteoblast is to differentiate into dendritic osteocytes inside the bone matrix, where they either undergo apoptosis or can be converted into flat bone lining cells (28).

2.3.2 Osteocytes

Osteocytes are ellipsoid cells that comprise 90% of the bone tissue cellular volume (29). The transition from osteoblast to osteocyte is called osteocytogenesis (30). In the differentiation process, the osteoblast is first converted into a preosteocyte and then to a mature osteocyte.

During that process, the cell reduces the numbers of cell organelles and it grows dendritic processes that invade into the extracellular matrix (ECM) with the help of different matrix metalloproteinases (30). The dendritic processes connect with gap junctions to adjacent osteocytes and form a complex network of canaliculi (31). During the differentiation process, the cell also expresses different gene and protein characteristics during each development phase (30,32). The osteocyte is considered mature when it expresses the mineralization inhibitor, sclerostin (33). These mature osteocytes are located in lacunae that are gaps in the mineralized matrix. The cell body occupies majority of lacunar volume surrounded by small amount of extracellular fluid. The complex network of lacunae and canaliculi is called the lacuno-canalicular network (LCN) or system (LCS) and it serves as a mechanosensing organ and metabolic pathway for bone tissue (32). The orientation of canaliculi is usually

perpendicular to the lamellae, pointing away from or towards the Haversian canal (31).

Furthermore, the density of osteocyte lacunae is generally greater in those areas that are less porous (34). In the human mandible, the osteocyte density is higher in the alveolar process compared to the inferior basal border (35).

Osteocytes play a crucial role in bone metabolism. They regulate the balance of bone remodeling through mechanosensing transmitted by fluid of the LCN (28,36). This mechanosensing is followed by mechanotransduction and growth factor secretion, that drives either osteoclastogenesis during mechanical underloading or osteoblastogenesis during mechanical overloading (29,36). During the transition from osteoblast to osteocyte, the preosteocytes regulate matrix mineralization and act as mineralization promoters (37).

Sclerostin secreted by mature osteocytes inhibits osteoblast function and mineralization via an inhibition of the Wnt-pathway (29,32). Mechanical loading, instead, inhibits sclerostin production thus allowing mineralization (38). Mature osteocytes may also directly participate

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25 in mineral apposition or degradation of the established mineral cortex adjacent to the lacuna (39) (40). Furthermore, osteocytes are the main drivers of bone resorption. They are a source of RANK-ligands (RANKL), which stimulate osteoclasts and bone resorption (29). In addition, microdamage-derived osteocyte apoptosis can stimulate bone resorption (30). Osteocytes also have systemic endocrine functions on bone metabolism and serum mineral levels through parathyroid hormone (PTH) receptors and fibroblast growth factor 23 (FGF23) (40).

2.3.3 Bone lining cells

Bone lining cells belong to the osteoblast lineage. The osteoblast may terminate as a bone lining cell and vice versa, the bone lining cell can again return to the osteoblastic direction (41). Bone lining cells are flat and a major cellular component of the endosteum (Figure 3).

Bone lining cells may function as bone resorption regulators first by allowing the osteoclast access on the bone surface and covering the bone remodeling pit, called the basic

multicellular unit (BMU) (42). Second, they may secrete osteoclast-activating cytokines (41,43).

However, the exact role of bone lining cells is still unknown.

2.3.4 Osteoclasts

Osteoclasts are bone resorbing cells. Unlike osteoblasts and osteocytes that are of

mesenchymal stem cell origin, osteoblasts stem from hematopoietic stem cells (HSCs). The key promoters of osteoclastogenesis are macrophage colony stimulating factor (M-CSF) and RANK-signalling (44) and RANK signaling is regulated (inhibited) by osteoprotegerin (OPG). The RANK receptor ligands (RANKL) that drive osteoclast activation are derived from the

osteoblasts’ lineage cells, i.e. osteocytes (44) and probably from bone lining cells (43). In cultured mandibular bone cells, the osteoclastic response to M-CSF and RANKL is stronger (45) and the size of the osteoclasts is larger (46) and in vivo, the number of osteoclasts is smaller (47) compared to the long bones, but these features did not affect the resorptive activity of mandibular osteoclasts (46).

Mature osteoclasts are large multinucleated baso- or eosinophilic cells that are located in pits with eroded surfaces called Howship lacunae or cutting cones that later become Haversian canals (11,48) (Figure3). The basal border of osteoclast is called the brush border or ruffled border. This active site of the cell secretes acid and proteolytic enzymes that are able to resorb the bone tissue (11,44).

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26

Figure 3. Histologic bright field images with Masson-Goldner trichrome staining of

mandibular bone cells and tissue components. Osteoblasts (Ob) produce a new mineralizing collagen network called osteoid (O). Some osteoblasts become trapped inside the

mineralizing cortex (Ct) and differentiate into osteocytes (Ot). Some osteoblasts terminate into bone lining cells (BLCs). Osteoclasts (Oc) resorb the bone from eroded surfaces (E) and carve Howship lacunae into the cortex. Bone marrow contains connective tissue (CT), adipose tissue, various cell types, nerves, lymph vessels, and vasculature.

2.4 BONE REMODELING

Bone remodeling is a process where the existing bone is resorbed by osteoclasts and thereafter the lamellary bone is rebuilt by osteoblasts (10). This balance of resorption and formation is dictated primarily by osteocyte mechanosensing that is mediated through LCN (36). The process of bone remodeling is critical for bone health and the disturbances may lead to bone diseases, such as osteoporosis (49) and osteoarthritis (50), where bone resorption dominates over bone formation. As a result of remodeling, the skeleton is slowly renewed. A hypothesis of the difference in this so-called turnover rate or remodeling rate in mandibular bone was initially proposed as an etiologic factor of jaw bone necroses, but there is

contradictory evidence that there are different turnover rates between mandibular and long bones under normal conditions. In the human mandible, the turnover rate is slower than in the human maxilla (51) but, in contrast, in dogs, maxillary turnover was found to be slower (52). Compared to the femur, the turnover of the mandible was lower in dogs (52), but did not differ in breast cancer patients (51) or after antiresorptive treatment (53). In the iliac crest, the number of osteons with bone-forming osteoids is greater than in the mandible, which may indicate differences in remodeling (54).

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27 2.4.1 Interplay between bone cells during bone remodeling

The remodeling takes place on old bone surfaces. The cells can either form so-called cutting cones that later become the Haversian canals of cortical bone, or the remodeling can occur at flat bone surfaces, usually in trabecular bone (55). Remodeling takes place in the functional structure called basic multicellular unit (BMU) also referred to as bone remodeling

compartment (BRC), which is a niche for bone resorption and formation covered by a canopy of cells (Figure 4) (7,56,57). Bone remodeling constitutes of five stages (58,59) In the activation stage, the osteoclasts are recruited at the resorption site by signals from osteoblasts,

osteocytes, and bone lining cells (58). Especially the role of osteocyte mechanosensing in the initiation process is crucial. Lack of mechanical stimuli drives resorption through

osteoclastogenesis, whereas increased mechanical stimuli drives new bone apposition through osteoblastic response (36). The RANK and M-CSF signaling play a key role in the recruitment and differentiation of osteoclasts (60). During three to six weeks of the so-called resorption stage, the osteoclasts produce acid and enzymes that create resorption pits into the old bone cortex (55,60). In the reversal stage, reversal cells cleave the resorbed site from debris (58). Next, during the formation stage, the osteoblasts are recruited into the area and secrete new matrix called the osteoid. First, an organic matrix (growth zone) is secreted that further mineralizes (mineralizing front) into new mature bone (10,61,62). This new bone formation occurs during the following 150 days (55) and is presented in detail in the following chapters. The cycle ends in the termination phase where matrix apposition ends and

osteoblasts become terminated into osteocytes, bone lining cells, or into apoptotic bodies (28).

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28

Figure 4. Schematic image of bone cell differentiation and basic multicellular unit (BMU) or bone remodeling compartment (BRC) with five different stages of bone remodeling cycle. The bone remodeling cycle is initiated by osteocytes in the activation phase (on the left) and terminated in the termination phase (on the right). During the remodeling cycle bone is resorbed by osteoclasts and osteoid is deposited on previously mineralized bone by

osteoblasts. The osteoid gradually mineralizes to form new mineralized bone. Modified from (59)

2.5 NEW BONE FORMATION DURING REMODELING

2.5.1 Organic matrix production

The osteoblasts produce a network of collagen and other non-collagenous proteins. Almost all i.e. 90%, of the organic matrix is composed of collagen type I (63). The jawbone contains significantly more collagen per ash weight than the long bones (64). Collagen is secreted by osteoblasts and provides a scaffold for the future mineral matrix. The protein synthesis in osteoblasts produces a pre-pro-alphapeptide chain, consisting of repetitive amino acid triplets [Glycine (Gly) – X - Y], where X is often proline (Pro) and Y is hydroxyproline (Hyp) (10,18). The chain is transferred to the rough endoplasmic reticulum (RER) based on signal peptide at the end of the alpha chain. Inside the RER, the chain peptidase cleaves off the signal peptide, resulting in the pro-alpha-chain. Inside the RER, the pro-alpha-chain also goes through several post-translational modifications that later affect collagen folding and cross-linking (65).

Hydroxylation of lysine (Lys) by enzyme lycine hydroxylase (LH) results in hydroxylysine (Hyl).

This modification seems to be specific at X-Lys-Gly sequences and requires oxygen and C-

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29 vitamin as a co-factor (66). In the mandible, the amount of Hyl is significantly lower compared to the corresponding amount in long bones (64). The second modification, by enzymes glycosyl- and galactosyltransferases, is the glycosylation of previously formed Hyl with galactose or glucosylgalactose (66,67). Of these two, the resulting galactosyl hydroxylysine is dominant in bone. Sugar groups can also spontaneously aggregate to collagen due to irradiation, aging, diabetes mellitus, or osteoporosis. The end products of these glycation aggregates are referred as advanced glycation end products (AGEs) that form nonenzymatic cross-links between collagen molecules. The aggregation of sugar groups in collagen affects the subsequent collagen cross-linking (67) (68), mechanisms of which are discussed later in this chapter.

Next, the single alpha-chains are united as triple-helical procollagen. The procollagen contains N- and C- terminal domains attached with disulfide bonds and the actual triple- helical collagen in the middle (18). The triple helix structure is reinforced by hydrogen bonds.

This triple-helical procollagen is packed into vesicles within the Golgi apparatus and transported outside the cell. A peptidase enzyme in the cytoplasm cleaves off the N- and C- terminal domains and leaves the triple helix called tropocollagen. Tropocollagen is then assembled into groups forming collagen fibrils (7,69).

The assembly of collagen fibrils is well-defined by inter- and intrafibrillar cross-links. There are seven types of cross-links in collagen (70), but only a few of them are evident in bone (Figure 5) (71). Collagen cross-links in the bone can be divided into lysine hydroxylase or lysyloxidase-mediated enzymatic immature divalent cross-links, their derivates mature into trivalent cross-links, and pathologic non-enzymatic cross-links induced by glycation or oxidation. In the literature, there is a variation in the nomenclature of the cross-links.

Different nomenclatures are presented in Figure 5. In mineralized tissues, the cross-links are predominantly formed of Hyl derivates. The preparatory phase of cross-link production requires the deamination of certain Hyl and Lys residues into aldehydes Hylâld and Lysâld by lysyl oxidase (LOX). In mineralized tissues, the Hylâldpathway predominates in a reaction that requires copper as a co-factor. First, bivalent immature cross-links, are formed between different aldehyde and peptide residues (67). Immature cross-links contribute to fibrillary arrangement by overlapping the terminal ends of collagen fibrils. Second, the mature cross- links are formed from immature cross-links. The mature cross-links can form intra-fibrillary or inter-fibrillary, thus having a major stabilizing effect on collagen structure. Optimally, cross- linked collagen is considered as mature collagen and the correct amount of cross-linking optimizes tissue elasticity versus stiffness. However, excessive cross-linking can increase tissue stiffness and predispose to fractures (72). It seems that the mature collagen scaffold of the mandible contains fewer mature cross-links compared to the long bones. This was proposed to be due to the faster remodeling rate that the mandible has been proposed to have compared to long bones (67). The rate of remodeling, in turn, was speculated to derive from the higher osteogenic potential of jaw mesenchymal stem cells (23). On the other hand,

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30

the contradictory findings of the different remodeling rates in the mandible were discussed earlier in Chapter 2.5.

The non-enzymatic cross-links are a result of pathologic glycation, which results in so-called advanced glycation end products (AGEs) (Figure 5). In bone, one AGE product called

pentosidine has been recognized (73). AGEs may pathologically aggregate to the collagen network and cause this uncontrolled cross-linking that may further deteriorate the tissue properties (74).

Figure 5. Cross-linking mechanisms of collagen in bone. Modified from (67,69,71,75)

2.5.2 Bone mineralization

The non-mineralized matrix, called the osteoid, acts as a scaffold for mineralization. In the first phase of osteoid mineralization osteoblasts produce matrix vesicles from the basal border into this collagen scaffold (62,76,77). These vesicles act as factories for primary mineral formation, analogous to geologic hydroxylapatite [Ca10(PO4)6(OH)2] (78). However, as mature bones are hydroxyl (OH^-) deficient, the bone mineral crystal is referred to as hydroxyapatite (HA) (79). Because HA is formed from calcium-ions (Ca²⁺) and phosphate-ions (PO43-), they must first be provided to the vesicles. Alkaline phosphatase (ALP), adenosine monophosphate (AMP), phosphodiesterase, adenosine triphosphatase, and nucleoside triphosphate

pyrophosphohydrolase hydrolyse PO43- groups, that are transported into vesicles through

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31 NPT3 channels together with sodium. Ca²⁺ is attracted through an ion channel into the vesicles by calbindin D9K, phosphatidyl serine and annexin II, a protein on the inner surface of the vesicle membrane. A transmembrane protein, Annexin A5, acts as a Ca²⁺ channel (80,81).

Inside the vesicle, the Ca²⁺ and PO43- ions mature into HA spindles through precursor phases (80). First, amorphous calcium phosphate (ACP) is provided in the matrix vesicles in the mineralizing front. Some studies suggest the ACP as the only precursor phase of HA (82).

Another precursor phase, octocalciumphosphate (OCP), has also been proposed (83), but the results of its presence are contradictory (84). The complex of osteocalcin and OCP has been suggested to regulate the final crystal size and organization (85). The completed HA templates are then released outside the vesicles as phospholipases and proteases break down the vesicle membrane (76). Next, the matrix metalloproteinases (MMPs) degrade the proteoglycans within the ECM, so that HA crystals can access the final mineralization destination in the collagen scaffold (81).

In the second phase of mineralization, the mineral aggregation onto the collagen scaffold is initiated. Non-collagenous proteins (NCPs) are the primary initiators and regulators of

mineralization, but collagen itself may also have a role (84). The excess of free calcium and phosphate groups acts as a building block for HA crystals. However, the nucleation would be initiated in an uncontrollable maner if the HA were to be mineralized directly from the excess ions. Therefore, there are nucleation inhibitors within the matrix that first need to be down- regulated (80). These inhibitors include proteins of the SIBLING-family, for example,

osteopontin (OPN) and matrix extracellular phosphoglycoprotein (MEPE) (86). Some NCPs, like dentin matrix protein 1 (DMP1) can act as mineralization inhibitors or promoters depending on the mineralization phase (87) (88). It is still a matter of debate where this initiation of nucleation begins. According to the dominant hole zone theory, the minerals first aggregate within gaps between collagen fibrils. Collagen fibrils are about 300 nm long and become aligned, leaving 40 nm gaps after each fibril, known as hole zones or gap zones (84). From the hole zones, the nucleation spreads along the c-axis of collagen fibril (interfibrillar or

extrafibrillar mineralization) and within the collagen fibrils (intrafibrillar mineralization) (10,84). Another theory supports patterned mineralization along with the helical structures, where calcifying nodules initiate the process of mineralization of the collagen scaffold (86).

The formation of crystals occurs in 5-10 days and is called primary mineralization. It is followed by slower secondary mineralization, which includes mineral growth in size and number and mineral maturation(61). Mineralized hydroxyapatite crystals consist of an apatitic core surrounded by a labile hydrated layer of reactive ions. During mineral maturation, the apatitic core grows and the hydrated layer diminishes (61). The perfection of the growing crystals can be disturbed by the carbonation of hydroxyapatite. Carbonate groups (CO32-) can substitute OH-group (type A substitution) or PO43- groups (type B substitution) of

hydroxyapatite lattice. Carbonation disturbs the bone's physical properties and increases the fracture risk (89,90). The final mineral content per ash weight in mandibular bone is greater compared to long bones (64).

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2.6 BONE IMAGING AND DIAGNOSTICS

Because of the composite and heterogenic nature of bone tissue, there are several imaging modalities that focus on different features of the tissue. The tissue hierarchy level of interest determines the selected imaging protocol. Due to the composite and multi-hierarchal nature of the bone tissue, multimodal imaging techniques have recently been recommended (91).

The bone’s macroarchitecture can be estimated noninvasively with magnetic resonance imaging (MRI) (92) or different x-ray techniques, such as native x-ray, computed tomography (CT), dual x-ray absorptiometry (DXA) (93). DXA evaluates the sum of bone micro- and macroarchitecture from the bone mineral density (BMD). BMD is the most widely used parameter for assessing the clinical fracture risk (94). However, the fracture risk is not consistent with BMD alone, which only accounts for the bone mineral mass and does not consider the quality of the organic bone component. Therefore, for example, spectroscopic methods have been shown to predict bone toughness better than BMD (95).

Bone microarchitecture refers to the microscopic features of bone tissue. The evaluation of bone microarchitecture usually requires an invasive bone biopsy. First, the best established of the two-dimensional techniques are traditional histology, polarized light microscopy, and immunohistochemistry, which have an established position in research and clinical practice.

Bone remodeling at the microscopic level is estimated by histomorphometry of traditionally stained and non-stained bone sections. One of the most important dynamic parameters representing bone remodeling is the bone mineral apposition rate (MAR); this can be assessed from two fluorescent labels administered to the patient within a certain time interval before undertaking the bone biopsy (96). Histomorphometry also assesses static parameters that aim to provide a quantitative description of certain histologic features, such as mean osteon perimeter or osteoid thickness. Therefore, microradiographs are used to assess BSU mineralization and age (97). Scanning electron microscopy (SEM) and transmission electron microscopy (TEM) are based on electron beam enabling a higher spatial resolution than can be achieved with light microscopy (98). SEM in a backscattered electron (BSE) mode can also estimate bone mineral density distribution (BMDD) (93). Scanning acoustic

microscopy (SAM) is based on ultrasound backscattering and provides information about the BSU elastic modulus (93). Photon based techniques include confocal laser scanning

microscopy (CLSM) (98), second and third harmonic generation imaging (SHG and THG), and three-photon excited fluorescence (3PEF) (99). A three dimensional description of the microarchitecture can be obtained with Micro-CT, nano-CT, peripheral quantitative

tomography (pQCT), and synchrotron-based x-ray techniques (91,93). Small angle x-ray (SAXS) provides 2D or 3D views of bone microstructure (98). Micro- and nanointendation techniques can be used to determine the microhardness of the bone specimen with a probe that directs force into the tissue. Finite element analysis, which is based on a computed tissue model, is another tool to assess tissue biomechanics (93).

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33 The molecular and atomic level qualities of collagen and hydroxyapatite crystals present in the bone can be evaluated with atomic force microscopy (AFM) (93). Vibrational spectroscopic techniques, such as Fourier-transform infrared (FTIR) spectroscopy and Raman spectroscopy, are convenient tools to analyze the chemical composition of bone (91,93). They provide various descriptive parameters about the organic and inorganic compartments of the bone.

This dissertation focuses on FTIR and autofluorescent imaging of bone tissue.

2.6.1 FTIR spectroscopy

FTIR spectroscopy can be used to characterize the chemical composition and selected structural parameters of bone. Earliest FTIR techniques are based on point measurements to acquire an average spectra of the bone. Current devices also have a high resolution imaging modality to achieve a more precise chemical mapping (100). In brief, a broadband light (with several wavelengths) is directed via a Michelson interferometer onto the sample. The incident light is absorbed by the sample molecules and this evokes a molecular vibration. A

mathematical algorithm Fourier transform is used to convert the detected signal into a spectrum. The peaks in the spectrum (i.e. absorbance vs. wavenumber, see Figure 6) reflect the molecular vibration frequencies; these are affected by the masses of constituting atoms and on the presence of inter-atomic bonds, as well as the geometrical arrangement of atoms in molecules. These molecular features create a characteristic vibrational pattern, that can be detected as absorption peaks in the infrared spectrum (101). The peak intensity of individual peaks is directly proportional to the amount of constituting molecule and thus, FTIR can be used to provide a quantitative molecular analysis. A typical bone spectrum with characteristic absorption peaks is presented in Figure 6. Several compositional indexes/features that describe bone chemical composition can be derived from the spectrum. The spectral analysis consists typically of defining peak intensities and/or integrated peak areas of certain

molecular vibrations (Table 1) and further, calculating their ratios for bone functional information (Table 2) (102-105). More sophisticated analyses include peak-fitting techniques, where underlying peaks are firstly mathematically modelled to match the original data (106- 110). Typical spectral regions and compositional parameters from bone are presented in Table 1.

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Fiqure 6. Schematic image of characteristic FTIR spectrum of mineralized bone and different spectral regions. Peaks at certain wavenumbers of the FTIR spectrum are characteristic to specific tissue molecules. Amide I-III, A and B are descriptive for bone organic components, mostly collagen. Carbonate and phosphate regions are descriptive for bone mineral compartment.

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35 Table 1. Typical FTIR parameters derived from individual peaks of the bone spectra describe the bone tissue composition.

Parameter Wavenumber(s) Definition Ref

Amide I Pyr DPD deH-DHLNL

1720-1595 1660 1680 1690

C=O and C-N stretch Pyr subband DPD subband deH-DHLNL subband

(111-113)

Amide II 1590-1490 N-H bend in plane, C-N stretch and C-C stretch (111,112)

Amide III 1305-1215 N-H bend and C-N stretch (111,112)

Amide A 3500-3185 Fermi resonance of the first overtone of amide II and N-H stretching

(112,114)

Amide B 3080-3000 Fermi resonance of the first overtone of amide II and N-H stretching

(112)

Collagen 1338 Proline side chain (CH2) vibration (115)

Phosphate ν1PO43-

ν₃PO43-

970-950 1200-980

P-O stretch P-O stretch

(116)

Carbonate ν₂CO32-

ν3CO32-

870-850 1485-1355

C-O bend O-C-O stretch

(117)

Acid phosphate ν3HPO42-

ν2HPO42-

ν6HPO42-

ν5HPO42-

875-870 1005-988 1130-1037

1230

P-OH stretch P-O stretch P-O stretch P-O-H bend

(116)

Pyr: Pyridinoline, DPD: Deoxy-pyridinoline, deH-DHLNL: Dehydro-dihydroxylysinonorleucine

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Table 2. Functional parameters of bone tissue defined from FTIR peak ratios

Parameter Ratio Definition Ref

Mineral-to-matrix (MM) ν3PO43-/ Amide I Matrix mineralization degree (70,110) Carbonate-to-phosphate (CP) ν2CO32-/ν3PO43- Total carbonate substitution in HA (110)

Carbonate-to-matrix (CM) ν₂CO32-/ Amide I Total carbonate substitution relative to organic matrix

(110)

Acid phosphate substitution (APS)

1127/1096 cm^-1 Acid phosphate content in HA (118)

Cystallinity 1030/1020cm^-1 Size and perfection of HA crystals (118) Mineral maturity 1030/1010cm^-1 Maturity of HA crystals (118) Collagen maturation/cross-

linking

1660/1690cm^-1 Enzymatic maturation of deH-DHLNL into Pyr

(109) Advanced glycation end

products (AGEs)

1678/1692cm^-1 Non-enzymatic cross-links (73) HA: hydroxyapatite

FTIR parameters for collagen

Different amino acids and the arrangement of their sequences influence the FTIR spectra by creating different subbands that are summarized into characteristic spectra of the tissue. In bone, the organic components are found mainly in different amide regions. Because 90% of the bone’s organic component is type I collagen, most of the subband effect that influences the organic peak intensities is derived from collagen. The most important parameters in bone are amide I and proline side chain vibration. Proline side chain (CH2) vibration at 1338cm^-1 is descriptive to collagen (115). The advantage of utilizing 1338cm^-1 is that the region is not disturbed by water, unlike amide I (119). Furthermore, it is not disturbed by the presence of lipids, DNA, or proteoglycans. The amide I region (1720-1595cm^-1) has been the most prominent and probably also the most widely used amide region in bone FTIR analysis. The amide I band arises from stretching of C=O and N-H bonds, that are found in the collagen backbone. The amide I region is also sensitive to the secondary structure of the protein.

Nonetheless, because the amide I region is disturbed by water, it cannot be used if the amount of collagen is small or nonexistent (119). Thus in the early osteoid region where collagen accumulation is still minimal, amide I is not a reliable parameter. However, in the cortical region, where the collagen content is relatively constant, the parameter can be used.

Other amide regions are also found in the bone spectrum, but their significance in the bone analysis is less important. Amide II (1590-1490cm^-1) reflects an N-H bend in a plane, a C- N stretch, and a C-C stretch. Amide III (1305-1215cm^-1) also rises from an N-H bend in plane and a C-N stretch. Both amide II and III are influenced by the protein’s secondary structure

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37 (115). Amide A and B are derivates of Fermi resonance of the first overtone of amide II and N- H stretching (101).

Mineralization (MM)

The mineral-to-matrix ratio (MM) describes the relation of the bone’s inorganic component (mostly HA) to the organic matrix (mostly collagen). MM is presented as a ratio of phosphate to amide I.

Crystallinity and mineral maturity

Mineral maturity indicates the growth and formation of crystalline hydroxyapatite from the surrounding ions of the hydrated layer that are not involved in the lattice structure (61). With this definition, mineral maturity is determined from the ratio of 1030/1110 cm^-1(120).

Crystallinity or crystallinity index refers to crystal size and perfection and can be deduced from the ratio of 1030/1020cm^-1(120).The terminology of mineral maturity and crystallinity is sometimes complex in the literature. Crystallinity and mineral maturity are sometimes both measured from the same ratio, often thought of as being similar, although the terms are not exact synonyms (100,121). Under normal circumstances, however, the mineral maturity and crystallinity grow synchronously (61) and are therefore sometimes interpreted from the same FTIR ratio and used as synonyms.

Carbonate substitution (CP and CM)

Mineral crystal size and perfection are often disturbed by the presence of different

substituting ions, mostly carbonate (5-6%) (106). Carbonate ions may substitute for OH^- (Type A substitution), phosphate groups (Type B substitution) within the crystal, or be located on the crystal surface (labile carbonate)(122). A type B substitution is predominant in bone (117). The carbonate-to-phosphate ratio (CP) describes the total amount of carbonate in relation to phosphate in HA (123). An increased CP ratio has been linked to increased bone fragility (89).

Sometimes, the carbonate content has been additionally presented as the ratio of carbonate to amide I (carbonate-to-matrix, CM)(124)

Acid phosphate substitution (APS)

Bone tissue is constantly being remodeled, and new bone formation can be assessed in FTIR spectroscopy by the amount of acid phosphate substitution (APS) (118). Free acid phosphate ions (HPO42-) are located in the liquid layer of forming hydroxyapatite and may reversibly be incorporated into the apatitic lattice (61). The substitution of HA with HPO42- is increased in bone forming areas but becomes subsequently decreased with the maturation of the bone (118,125).

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Collagen maturation (cross-linking)

During collagen maturation, different cross-links are formed between single collagen molecules. In mineralized tissues, the Hyl^aldpathways of cross-links predominate (Figure 5) and the evolution of one Hyl^ald derived pathway has been validated by FTIR. This pathway results in the formation of trivalent cross-link hydroxylysyl-pyridinoline (Pyr). Collagen maturation, also known as the cross-linking ratio (1660/1690cm^-1) indicates the ratio of mature trivalent cross-links (Pyr) over immature divalent cross-links (deH-DHLNL) (109).

Glycation and non-enzymatic cross-linking

During certain conditions i.e. diabetes mellitus, osteoporosis, or aging, sugar groups may spontaneously aggregate onto collagen. This aggregation is called glycation and yields so- called advanced glycation end products (AGEs), that form non-enzymatic cross-links between collagen molecules (74). The presence of non-enzymatic pentosidine cross-links cause changes in the tissue’s FTIR vibration properties; these can be estimated from ratio of 1678/1692cm^-1(73).Non-enzymatic cross-linking is considered pathological since it disturbs the tissue's mechanical properties (74).

2.6.2 Autofluorescence spectroscopy

The phenomenon of fluorescence was discovered as early as 1838 and autofluorescence microscopy of biological samples was first established in 1911. Since then, the technique has been primarily applied for monitoring the metabolic functions of cells and tissues or

diagnostics of neoplastic diseases. Hence, autofluorescence is one tool which can be exploited to obtain a so-called optical biopsy. In some imaging applications, autofluorescence has also been considered as a disruptive background noise (126). For example, in Raman

spectroscopy, the autofluorescence of the sample may cause unwanted artefacts (127).

Autofluorescence spectral imaging utilises tissue optical and autofluorescent properties to distinguish between different tissue components. First, the sample is illuminated by a light source. Photons of the light source excite the molecules from an electronic ground state (S0) to upper electronic states (S1 S2). The state of excitation depends on the energy of the

absorbed photon (hνA). Next, the molecule loses energy and reverts to lower electronic states.

During the restoration to lower states, the molecule may emit a photon (hνF) that is detected as fluorescence (128). A schematic image of a molecule’s electronic states is presented in Figure 7A. The optimal excitation/emission wavelengths are characteristic for a substance, and substance recognition can be done, by analysing the detected emission spectrum. Figure 7B presents typical spectral profiles of autofluorescence emission from single endogenous fluorophores (126)

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39 Figure 7A. Schematic image of molecule energy levels and fluorescence phenomena. Exciting photon (hνA) wires the molecule on upper electronic states (S1 S2). During the restoration to lower states, the molecule may emit a photon (hνF) that is detected as fluorescence emission (modified from (128)). B. Schematic image of typical spectral profiles of autofluorescence emission from common single endogenous fluorophores (modified from (126)).

In bone research, the most common application of fluorescence phenomena is labelling of the tissue with fluorescent calcein green tetracycline in order to evaluate the extent of remodeling (129). However, as early as 1965, it was discovered that bone also possesses autofluorescent properties (130,131). Autofluorescence is a potential tool for bone analysis because collagen, a major component of bone tissue, is autofluorescent at 340nm/420nm wavelengths. Other main fluorophores (fluorescent substances) and their characteristic excitation/emission wavelengths in bone are tryptophan residues (291nm/335nm), and coenzymes nicotinamide adenine dinucleotide (NADH) or nicotinamide adenine dinucleotide phosphate (NADPH) (360nm/440nm), representing the bone tissue’s cellular component (132).

Despite the potential and early discovery of bone autofluorescence, the phenomenon has not been widely exploited. It has been recently used for perioperative detection of necrotic bone caused by radiation therapy (133) or MRONJ (134-137) for studying osteoporotic bone (138), bone histomorphometry (139) and archeological samples (140-142). However, the above- mentioned methods excite with a non-specific range of the total tissue fluorescence,

providing less information about individual tissue components. A more precise evaluation of tissue properties can be acquired by collecting multiple spectra with narrow excitation and narrow emission bands (multispectral or hyperspectral imaging). From these spectra, it is possible to form a 3D hypercube of the intensity variation as functions of the excitation- emission wavelengths (Fig 2). The hypercubes provide more specific information about the

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40

spectral and molecular composition of the tissue than can be obtained from single spectra (143). A schematic image of hyperspectral imaging is presented in Figure 8.

Figure 8. Schematic image of hyperspectral autofluorescence imaging. Fluorophores excite the characteristic fluorescence spectrum across certain wavelength range from ultraviolet to near-infrared (on the left). Different excitation-emission wavelength combinations from ultraviolet to near-infrared enable creation of a fluorescence hypercube (on the right).

Modified from (143)

2.7 HEAD AND NECK CANCERS

Head and neck cancers (HNC) comprise the cancers of the oral cavity, larynx, pharynx,

paranasal sinuses, and salivary glands (144). There are several different HNC tumor types, the most common of these is squamous cell carcinoma (SCC). The global incidence of HNCs in the 21^st century is 600 000 new cases that cause 300 000 deaths annually and this value has been predicted to rise (144). Thus, the treatment of HNCs represents an increasing burden for healthcare systems.

2.7.1 Surgical treatment

The primary tumor is fully resected with 1-2cm clinically healthy resection marginals. Wide clinical marginals are used because of microsatellite cells that have invaded into the surrounding tissue without clinical manifestation. In addition to primary tumor resection, neck dissection and removal of affected lymph nodes and submandibular salivary glands can be performed (145).

Chemical composition of mandibular bone : applications of Fourier transform infrared and narrowband autofluorescence imaging

ANNI MARJUKKA PALANDER

Chemical composition of mandibular bone

Dissertations in Health Sciences

PUBLICATIONS OF

THE UNIVERSITY OF EASTERN FINLAND

CHEMICAL COMPOSITION OF MANDIBULAR BONE

CHEMICAL COMPOSITION OF MANDIBULAR BONE

ACKNOWLEDGEMENTS

LIST OF ORIGINAL PUBLICATIONS

CONTENTS

ABBREVIATIONS

1 INTRODUCTION

2 REVIEW OF THE LITERATURE