A world of opportunity …

Although the United States and Europe remain global leaders in medical technology innovation, the story of the medtech sector has become much more diverse in recent years as healthcare has become a global priority. Inventors and companies in countries around the world are playing an increasingly important role in sourcing ideas, designing and developing them into viable products and services, and introducing them into patient care. In parallel, device sales in developing countries are expanding at a rapid pace. As the US and Europe both sustain growth rates in the low single digits, medtech revenues in countries such as India and China are forecast to increase at a compound annual growth rate of 14 percent and 26 percent, respectively.

The global transformation of the medtech sector has been driven by multiple, interrelated factors. In developed markets, health systems are actively seeking to slow health spending associated with medical technologies as they become more cost conscious and attuned to the value these products deliver. Moreover, as the time, expense, and complexity of developing new solutions in environments like the US continues to increase, innovators are moving offshore and creating new innovation hubs in locations around the world.

In developing markets, disease profiles are shifting from infectious to chronic conditions, which makes diagnostic and device solutions a more important part of efforts to meet the healthcare needs of patients. Governments and private healthcare providers alike are increasing health-related spending (see Figure G1). And innovators and companies in low-resource settings are becoming leaders in inventing more affordable solutions that enable care delivery in any setting and reduce (rather than increase) its cost.

Medtech innovators can certainly find compelling opportunities in both environments.

In developing markets, disease profiles are shifting from infectious to chronic conditions, which makes diagnostic and device solutions a more important part of efforts to meet the healthcare needs of patients.

Background

Latin America includes approximately 20 countries in North, South, and Central America and the Caribbean. In contrast to most of the United States and Canada, Latin languages – mainly Spanish and Portuguese – are primarily spoken in the region.

While economic growth varies substantially across Latin America, the gross domestic product (GDP) growth in the region as a whole increased by an average of 5 percent from 2000 to 2008, and decreased to closer to 3 percent subsequently. Brazil and Mexico are the largest economies, accounting for roughly 65 percent of region's combined GDP. Globally, Brazil and Mexico have the 7th and 14th largest GDPs, respectively.

Economic gains have stimulated increases in consumption, population, and longevity, as well as more demand for adequate healthcare by a growing middle class. This, in turn, has led to enhanced opportunities in the public and private healthcare markets and increased investment in healthcare access and infrastructure. Concurrently, Latin America has experienced a rise in the prevalence of chronic diseases across the region. Mortality due to cardiovascular diseases alone is predicted to increase by 145 percent between 1990 and 2020. Healthcare expenditure per capita in the region hovers around US$661, compared to approximately US$8,600 in the United States, suggesting future room for expansion.

As a whole, Latin America has a medical technology industry valued at more than US$8 billion, which makes it one of the larger global markets. Moreover, medical device sales have been expanding at a rate of more than 10 percent per year in the region. Based on their size, Brazil and Mexico comprise the most important medical device markets in Latin America and, accordingly, will be covered in more detail below. However, Colombia has the fastest growing medtech market, with a projected 2013–2018 compound annual growth rate of 13.3 percent. This market is forecast to reach US$2.2 billion in 2018. Chile and Peru are among the region's top economic performers, but both of these countries represent small markets for medical devices. Argentina and Venezuela have demonstrated a higher demand for medical technologies, yet both countries are experiencing serious macroeconomic challenges that are hindering continued medtech expansion.

Background

Europe, in geographic terms, comprises 47 independent countries that jointly can be considered the largest economy on earth. The European Union (EU), as an economically and politically integrated group of member states, includes 28 countries, with 18 of these sharing the euro as their common currency. The EU member states have a total gross domestic product (GDP) of more than US$16 trillion, with a per capita GDP of roughly US$34,000. In terms of medical devices, the EU is often referred to as the “European market” because of its common device regulation under the CE mark. However, innovators should appreciate that the European market extends beyond the EU and includes such non-member states as Switzerland and Norway. Russia, which geographically belongs to both Europe and Asia, is also commonly considered part of the larger European medical device market, as most of its economy and population is located in the western portion of the country.

Europe has a population of nearly 740 million people, approximately 7 percent of the global population (with the current 28 EU member states accounting for 69 percent of the total). Compared to other parts of the world, population growth in Europe is rather slow and the median age comparatively high. Nine of the top 10 countries with the highest median age, worldwide, are European countries, with only Japan having an older population.

Spending on healthcare as a percentage of GDP ranges widely across European countries. France, Germany, the Netherlands, and Denmark commit more than 11 percent of GDP to health, while Romania and Cyprus spend less than 6 percent. In 2010, health expenditures as a percentage of GDP dropped in the EU for the first time since 1975. From an annual average growth rate of 4.6 percent between 2000 and 2009, growth in health spending per capita fell to –0.6 percent in 2010 and has been stagnant in many countries ever since. Among EU member states, those with higher average income levels per person generally spend more on health-related products and services. When considering absolute amounts of healthcare spending per capita, the variation in health-care spending is even more evident, ranging from about US$5,000 in France to merely US$500 in Romania.

Introduction

Unlike a conventional laser which utilizes mirrors or periodic structures to trap light, a random laser relies on the multiple scattering of light in a disordered gain medium for optical feedback and light confinement (see Figure 6.1) [67, 70, 528, 529]. Coherent laser emission has been generated from various random structures ranging from semiconductor nanoparticles and nanorods to polymers and organic materials. Over the past decade, random lasers have generated significant interest among researchers because of their unique applications [67, 529]. For example, specifically designed random lasers combine high radiance with low spatial coherence [357, 403], ideally suited for speckle-free, parallel, high-speed imaging, laser projection and ranging [404]. The sensitivity of the random lasing threshold to the amount of scattering has been explored for cancerous tissue mapping [387, 389]. Moreover, the spectral fingerprint of the random structure [70, 71], the micron size [70], the low fabrication cost, and the robustness against surface roughness and shape deformation point to potential applications in optical tagging and identification [528]. Since random laser cavities are formed by scattering and are much easier to fabricate compared with the mirror-based cavities, they may be applied to lasers at wavelengths where high-reflectivity mirrors are either not available or very expensive, e.g. UV laser, X-ray laser, γ-ray laser. A detailed description of random lasers can be found in Chapter 3.

However, a major limitation to device applications of random lasers is the lack of control and reproducibility of lasing modes. Namely, the frequencies and spatial locations of lasing modes are unpredictable, varying randomly from sample to sample. One way to solve this problem is to utilize pseudo-random structures, or more generally, deterministic aperiodic nanostructures (DANS) [98]. Unlike structures generated by a random process, DANS are generated by the iteration of simple mathematical rules with a controllable degree of spatial complexity that interpolates between periodic and random systems. DANS lasers can combine the advantages of random lasers with the fabrication and design reproducibility required for optoelectronics integration.

This book is the result of our interest in understanding, mastering, and engineering randomness in photonic systems. It is a natural consequence of what we did in the past. In the late 1980s, while Lorenzo Pavesi was working on semiconductor superlattices he noticed that for some energies the vertical transport through the superlattice minibands was inhibited due to disorder (L. Pavesi et al. 1989. Phys. Rev. B, 39, 7788). Then, working on the recombination dynamics of excitons in porous silicon, he further noticed that the random arrangement of silicon quantum dots has a strong influence on the recombination dynamics of excitons(L. Pavesi et al. 1993. Phys. Rev. B, 48, 17625). After Mher Ghulinyan came to Trento in 2002, we developed the techniques to fabricate free-standing porous silicon dielectric multilayers of any stacking sequence (M. Ghulinyan et al. 2003. J. Appl. Phys., 93, 9724). This was the first time that we had the chance to designat will one-dimensional periodic, aperiodic, or random photonic systems. A fascinating new physics opened up for us: that of the analogy of photon propagationin complex dielectric systems with carrier transport in random electronic systems. Our latest results in the field are associated with sequences of ring resonators where randomness causes the formation of resonant coupling between different rings with the possibility of yielding the optical analog of the electromagnetic induced transparency (M. Mancinelli et al. 2011. Opt. Express, 19, 13664), or chaotic photon propagation.

Over all these years, we have had the chance to interact with many researchers active in the field of periodic, quasiperiodic, and random photonic systems. From these interactions the idea of this book was born. We have therefore collected together a series of self-contained chapters to cover the whole field with the specific aim of introducing the different aspects, showing the current status of the research, and envisaging future directions. All invited authors have responded to this challenge with great enthusiasm and professionalism.

The book opens with Chapter 1 by W. L. Vos, A. Lagendijk, and A. P. Mosk, which introduces the field and covers the timeline between the early studies on these systems and the very latest achievements in the field.

Introduction

Optical waveguides are used to transport both phase-insensitive and phase-sensitive information in today's communications networks and signal processing devices. Among applications needing high performance waveguides are delay lines and optical phase-locked loops, generating precise phase offsets for waveform sampling, analog-to-digital conversion, and beam-forming. In fundamental terms, high performance waveguides are based on the ballistic propagation of photons [4, 168], which may be capable of reaching the ultimate limits of computational speed and energy efficiency of interconnects [331, 332], since ballistic propagation of electrons [132] is difficult to achieve in practical chips. Therefore, quantifying the impact of disorder on light propagation, and distinguishing between ballistic and non-ballistic transport, is an important and ongoing research endeavor.

Ballistic transport requires that the phase-breaking length be greater than the device length; which is usually satisfied in optical fibers of short length, and in planar glass lightwave circuits, in which the refractive index difference between core and cladding materials is small [260, 261]. But light propagation in high-index contrast waveguides, e.g. in silicon photonics, can be highly susceptible to the effects of disorder. Here, we will focus on periodically structured nanophotonic waveguides, e.g. coupled microring resonators [188, 392, 548, 555] in which light can accumulate significantly more phase and delay per unit length than in conventional waveguides. Such devices can be valuable for many reasons, among which are the facts that on-chip footprint is a precious commodity in real-world devices, and that our ability to increase, via geometrical patterning of waveguiding structures, the optical phase accumulation per unit (structural) length will considerably benefit nonlinear multiwave interactions. However, such devices may also be more strongly susceptible to the effects of disorder [329], and the issue of whether ballistic propagation can be achieved in coupled-resonator structures is being investigated closely.

From a physics viewpoint, one-dimensional structures are interesting because multiple scattering in transverse dimensions can be restricted, e.g. by using single-transverse-mode waveguides as the constituent building blocks for linear chains of resonators, e.g. microring arrays.

General overview

In many areas in the physical sciences, the propagation of waves in complex mediaplays a central role. Acoustics, applied mathematics, elastics, environmental sciences, mechanics, marine sciences, medical sciences, microwaves, and seismology are just a few examples, and of course nanophotonics [6, 429, 448, 449]. Here, complex media are understood to exhibit a strongly inhomogeneous spatial structure, which determines to a large extent their linear and nonlinear properties. Examples of complex media are random, heterogeneous, porous, and fractal media. The challenges that researchers in these areas must surmount to describe, understand, and ultimately predict wave propagation are formidable. Right from the start of this field – in the early 1900s – it was clear that new concepts and major approximations had to be introduced. Famous examples of such concepts are the effective medium theory [55, 60, 321] and the radiative transport theory [81, 491]. These concepts are very much alive, even today. The fundamental challenge with these approximate concepts is that often the length scales of the inhomogeneities in the complex medium are comparable with the wavelength, whereas the range of validity of these approximations is restricted to situations where these length scales are much larger than the wavelength. Consequently, many relevant situations arise where either the effective medium theory, or radiative transport theory, or both, fail dramatically. Examples of such situations are given in this introduction and throughout this book.

The complexity of the medium that supports wave propagation can be classified in a number of ways. Many different types of spatial inhomogeneities in a host matrix can be envisioned, varying from completely random, via aperiodic and waveguide structures, to quasi-crystalline and even structures with long-range periodic order. The in homogeneities could be of a self-organized form, or the fruit of precise engineering. An additional classification is whether or not the complexity is confined to the surface (in two dimensions (2D)) or is present throughout the volume of the medium (in three dimensions (3D)), as in porous media.