Biologically Optimized Radiation Therapy

Anders Brahme

• Publisher: WSPC
• Year: 2014
• ISBN:
  9789814602501
• Topic: Medicine
• Subtopic: Radiology, Radiotherapy & Nuclear Medicine

Radiation therapy has developed and advanced dramatically in the last few decades. However, very little has been published or done in the area of biologically optimized treatment planning. Development of Biologically Optimized Radiation Therapy aims to fill and close an important gap in the literature with a well-focused and in-depth content.

The book covers the biological, physical and clinical background of advanced biologically based radiation therapy optimization with focus on modern radiation therapy modalities such as electron, photon and light ion therapy. Highly recommended for its strong interdisciplinary profile, the book contains a meritorious compilation of previously unpublished materials in many areas of modern science. Undergraduates, researchers and practitioners such as oncologists, medical physicists and radiation biologists alike should find the book immensely informative and comprehensively thorough.

Contents:

• A Brief Introduction to the Development of Radiation Therapy Optimization (Anders Brahme)
• Fundamentals of Clinical Radiation Biology (Anders Brahme, Panayiotis Mavroidis, and Bengt K Lind)
• The Radiation Biological Basis of Radiation Therapy (Anders Brahme, Panayiotis Mavroidis, and Bengt K Lind)
• Development of High Quality Beams for Uniform and Intensity-Modulated Radiation Therapy (Anders Brahme, Roger Svensson, and Bo Nilsson)
• Fundamentals of Physically and Biologically Based Radiation Therapy Optimization (Anders Brahme, Johan Löf, and Bengt K Lind)
• Properties and Clinical Potential of Biologically Based Treatment Plan Optimization (Anders Brahme, Kerash Moaierifar, Panayiotis Mavroidis, and Bengt K Lind)
• BIOART: Biologically Optimized 3D In Vivo Predictive Assay-Based Radiation Therapy (Anders Brahme)
• Physical, Biological, and Clinical Background for the Development of Biologically Optimized Light Ion Therapy (Anders Brahme and Hans Svensson)

Readership: Oncologists, medical physicists, radiation biologists, molecular oncologists, radiation therapists, radiation physicists, undergraduates and graduates studying or doing research on medical imaging.

A Brief Introduction to the Development of Radiation Therapy Optimization

1

Anders Brahme

1.1. Introduction

The first radiation treatments of cancer were started within a year after the discovery of X-rays and it did not take long before successful therapeutic results were achieved. Because all treatments were not successful and some adverse reactions were also seen, especially for deep-seated tumors, various ways to improve the efficacy of the treatment were rapidly developed. To treat deeper tumors higher X-ray energies were used, also multiple collimated fixed or dynamic beam portal irradiations as well as various fractionation schedules were tested. As important as the technical development of methods to quantify the treatment in biological (skin erythema) or physical was the development (air ionization) terms. These methods allowed a more accurately quantified prescription of the radiation dose delivered and observation of the clinical response, leading to the first dose response relations used by Holthusen (1936) to describe a successful treatment in terms of the probability of achieving complication-free cure. The conceptual development of Radiation Therapy Optimization particularly when based on radiation biological objectives as well as its mathematical background and clinical potential and benefits will be discussed in more detail in the following chapters and so will some key algorithms and their clinical applicability. Here we will focus on some of the key developments to get a quick overview of the whole field.

1.2. Treatment Units

The treatments started with low-energy X-rays (30–50 kV), which were suitable for shallow tumors such as basal cell cancers which were probably the first tumor documented to have been successfully treated. Then, higher energy X-rays (50–350 kV) was used for deeper therapy and later Coccroft-Walton and Van der Graaff generators were used to reach the low MV region. In the mid-1930s, neutrons were tested but since their biological effect was far from understood, significant normal tissue damage put too early an end to these trials. To improve the therapeutic efficacy of the high-energy X-rays for deep tumors, different dynamic techniques were rapidly developed such as arc therapy and focused spiral irradiations. At this time just after the war, almost simultaneously, ⁶⁰Co, betatrons, and the first traveling wave linacs appeared in the clinic during the early 1950s, all making improvements for deep-seated tumors with much milder skin reactions. Interestingly, almost at the same time in the mid-to-late 1950s, protons, helium, and later heavy ions such as neon and argon were tested on tumors also with some initial clinical advantages. From the late 1960s, the first high MV betatrons, standing wave linacs and in the 1970s microtrons (10–50 MeV) were used and high-energy electrons became more commonly used mainly to spare tissues downstream of the tumor (cf. Chapter 4, Figs. 4.2 and 4.8). During this period, high-energy π-mesons generated by very high-energy electrons or protons were tested but with minor clinical improvements compared to their high complexity and cost. Finally in the early 1990s, carbon ions was successfully tested in an extensive dual synchrotron facility in Japan with very significant improvements in the clinical results particularly for tumors that are hard to cure by our more common radiation modalities (cf. Chapter 8, Figs. 8.19–8.24). For the further development, see Secs. 1.9 and 1.10 below.

1.3. Radiation Quality

Classical radiation therapy based on X-rays, ⁶⁰Co-γ-rays, or high-energy Bremsstrahlung are by definition associated with a relative biological effectiveness (RBE) of close to unity meaning that a given absorbed dose in Gy or J/kg results in essentially the same cell kill. To be exact, this is only true for quasi-relativistic energies ≳0.5 MeV, since then the slowing down spectrum of low-energy δ-ray-electrons per unit energy delivered is closely energy-independent (cf. Chapter 2, Figs. 2.4 and 2.7 and Chapter 8, Fig. 8.6). This is the main reason why the absorbed dose is a sufficient and very useful quantity for describing the biological effect in high-energy electron and photon beams. However, very low-energy photons and electrons have a much higher fluence of low-energy δ-rays per unit dose and may reach an RBE >3 in the low-to-sub-keV region. High-energy protons are also essentially a low RBE radiation, since the secondary electrons that deliver most of the cell kill are of higher energy (RBE ≈ 1.1–1.2 and partly due to nuclear interactions). Low-energy protons in the low MeV region will also have a high RBE since their secondary electrons again are in the low and sub-keV energy region. Unfortunately, this happens only over a few cell diameters for each proton track, so the net effect is very small for high-energy protons since their range straggling, of about 1% of the range or often a few mm, and thus generally totally dilutes the 50 μm high linear energy transfer (LET) portion very effectively. From lithium and above the RBE of about 2 or more is achieved in the Bragg peak and the multiple scatter penumbra is about one-third or less than that for protons making these beams of considerable clinical value (cf. Chapter 8, Figs. 8.2–8.4 and 8.9).

1.4. Radiation Biology

The development of radiation biology has kept good speed to cope with all the new radiation modalities that have been introduced in the clinical arena. Until the 1990s, most cell survival modeling (Zimmer 1961; Kellerer and Rossi 1972, 1978; Scholtz et al. 1997) was strongly focused simply on cell kill, as this was an obvious cause for loss of cell viability. However, already in the late 1950s, Elkind and Sutton (1959) clearly showed that something is happening between dose fractions, so after a break in the irradiation many cells seemed to be able to recover and reproduce the full shoulder of the cell survival curve after a rest period of approximately 24 hours. Without the break, the quasi-exponential cell survival curve would continue with almost unchanged slope. Elkind and Sutton correctly interpreted this phenomenon as some of the hit cells that where sublethally injured could repair their damage and be recovered for the next treatment fraction. But it took many years until serious cell survival theory took this fact into account. First, Wolfgang Pohlit and following him Cornelius Tobias and Stan Curtis developed theories where the probability to repair or misrepair potentially lethal radiation damage was explicitly accounted for. The resulting formula were quite complex but had under certain conditions some similarity with the commonly used linear quadratic expressions, but the complexity made them less practical for clinical use. About 15 years later, Lind and coworkers (2003), trying to include low dose hypersensitivity in the formalism, developed a very simple model primarily based on Poisson statistics, namely the Repairable–Conditionally Repairable damage or RCR model. The beauty of this model is its simplicity and its ability to separately specify those cells that survive because they are missed (e^−aD) and those that are hit but survive due to the effective cellular repair systems (bDe^−cD) that we know in rather great detail today (cf. Chapter 2, Figs. 2.11 and 2.12 and Chapter 8, Figs. 8.7 and 8.8). Interestingly, this last term gives us a way to account for the key cellular repair pathway of Non-Homologous End Joining (NHEJ) and Homologous Recombination (HR), and the expression is based on the assumption that if NHEJ works, then HR may correct eventual misrepair by NHEJ (that is known to be error prone not least at high dose rates). The total survival is thus, the sum of the above two terms, and for the very simple case, when all single- and double-strand breaks are correctly repaired (this is not far from the truth in normal tissues where close to 99% of the DSBs are repaired), it reduces to e^–D/D₀ + D/D₀e^–D/D₀ = (1 + D/D₀)e^–D/D₀; hence, for this special degenerate case a = b = c = 1/D₀. It is quite clear from this equation, as discussed in more detail in Chapter 8, Section 8.3.6 that this repair capacity explains most of the shoulder of the survival curve as first seen experimentally by Elkind and Sutton in 1959. Interestingly, this simple expression can also be used to describe the LET dependence of effective cross-section of the cell nucleus, the RBE, and the OER, as discussed in further detail in Chapter 8 (cf. Figs. 8.7, 8.8, and 8.5).

1.5. Why Is Radiation Therapy so Curative?

Today, we thus know that around 2 Gy of low LET radiation allow the normal tissue to recover well overnight and that at this common therapeutic dose about 99% of the double-strand breaks in the normal tissues are correctly repaired (cf. Chapter 8, Eqs. (8.5)–(8.7) and Brahme 2011). However, most tumors are genetically instable and practically always have some genes in the growth control and/or DNA damage surveillance pathways mutated (cf. Chapter 8, Fig. 8.25). Therefore, they will not be able to recover their cellular damage as effectively as the normal tissues, particularly when the dose per fractions is the highest in the tumor, for example, using Intensity Modulated Radiation Treatments (IMRT). In fact, the genetic instability characterizing practically all tumors often makes them lack some of the cell cycle blocks essential for high fidelity repair. This is no great surprise since this is probably the principal reason why the tumor was developed in the first place. Most likely it happened after the minor genetic damage that all cells are continuously exposed to, but it was not handled correctly due to possible genetic insufficiencies or predispositions. The tumor cells, therefore, often continue DNA synthesis, and thus instead may accumulate the radiation-induced genomic damage after each treatment fraction. The intact normal tissues, on the other hand, induce well organized and efficient cell cycle blocks that allow high fidelity DNA repair to take place before the S-phase is continued. After each treatment fraction, the tumor cells therefore accumulate more and more damaged DNA in their genome until they lose some essential function and/or cannot divide correctly and reach a state of mitotic catastrophe, apoptosis or senescence. Radiation therapy, therefore, makes optimal use of the genomic instability, the Achilles heal of tumor cells, and hit it repeatedly by multiple treatment fractions that the normal tissues largely tolerate quite well. Instead, they are generating steadily increasing amounts of genetic cellular damage to the tumor clonogens. Radiation therapy, thus, makes efficient use of one of the key biological differences between tumors and normal tissues. Through this mechanism, radiation therapy has an important biological advantage over most other therapies, such as surgery, hyperthermia, or coagulation by heat damaging, electrical or chemical reactions on DC or AC electrodes. This is because it has a significantly higher damaging therapeutic effect on the tumor clonogens than on the surrounding normal tissues that repair mild radiation damage very well between dose fractions.

1.6. Treatment Fractionation

In the early days, a single or a few repeated treatments were generally used when minimal tumor effects were seen. During the first half of the 20th century, multiple fraction schedules were developed generally delivering a few Gy five times per week over 5–7 weeks, largely based on trial and error (cf. Thames and Hendry 1987), not knowing about the just described underlying therapeutic mechanism. Furthermore, for some tumors in organs of parallel organization of their functional subunits such as lung, liver, and kidney, multiple quasi-simultaneous beam portals can effectively treat it, in so-called stereotactic irradiations. Due to the parallel organization surrounding normal tissues, as few as 3 fractions can be used quite efficiently on small tumors (≤5 cm), since the surrounding normal tissue can take over most of the lost function in the irradiated tumor region due to their parallel organization (cf. Chapter 2, Fig. 2.18 and Brahme 2000). More recently, it has been shown that multiple fixed fractionations may not be the most ideal way to treat. On the first day of the week, almost all the sublethal damage in normal tissues from previous treatments are repaired and a higher dose may preferably be delivered. This is similarly the case on the last day of the week when there is a long repair time for sublethal damage over the weekend. Adjustment of the dose fractions is made to maximize the tumor damage and maximize normal tissue recovery between fractions. This may be a very useful approach to compensate for the common absence of treatments during weekends (Chapter 7, Figs. 7.4 and 7.5 and Brahme 2005).

1.7. Diagnostic Tumor Imaging

To optimize a treatment, the best possible diagnostic information about the location of the tumor and the surrounding organs at risk is essential. It is, therefore, interesting to note that the early development of diagnostic and therapeutic radiology largely went hand-in-hand in trying to maximize the diagnostic information and therapeutic effect by optimal X-ray quality selection for each modality. A quantum leap in diagnostic imaging came with the new contrast agents but even more important was the introduction of computed tomography (CT) in the 1970s and magnetic resonance imaging (MRI) in the late 1980s. The arrival of MRI implied a further improvement in diagnostic information with higher tumor-to-normal tissue contrast in soft tissues and less imaging artifacts near bony structures. The ability to make functional MRI was also very valuable. More recently, the developme...

Table of contents

• Cover Page
• Title Page
• Copyright Page
• Contents
• Foreword
• 1. A Brief Introduction to the Development of Radiation Therapy Optimization
• 2. Fundamentals of Clinical Radiation Biology
• 3. The Radiation Biological Basis of Radiation Therapy
• 4. Development of High Quality Beams for Uniform and Intensity-Modulated Radiation Therapy
• 5. Fundamentals of Physically and Biologically Based Radiation Therapy Optimization
• 6. Properties and Clinical Potential of Biologically Based Treatment Plan Optimization
• 7. BIOART: Biologically Optimized 3D In Vivo Predictive Assay-Based Radiation Therapy
• 8. Physical, Biological, and Clinical Background for the Development of Biologically Optimized Light Ion Therapy
• Acknowledgments
• Index