Treatment Planning Of High Dose Rate Brachytherapy Mathematical Modelling And Optimization
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Treatment Planning Of High Dose Rate Brachytherapy Mathematical Modelling And Optimization
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Author : Björn Morén
language : en
Publisher: Linköping University Electronic Press
Release Date : 2021-01-12
Treatment Planning Of High Dose Rate Brachytherapy Mathematical Modelling And Optimization written by Björn Morén and has been published by Linköping University Electronic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-12 with Electronic books categories.
Cancer is a widespread class of diseases that each year affects millions of people. It is mostly treated with chemotherapy, surgery, radiation therapy, or combinations thereof. High doserate (HDR) brachytherapy (BT) is one modality of radiation therapy, which is used to treat for example prostate cancer and gynecologic cancer. In BT, catheters (i.e., hollow needles) or applicators are used to place a single, small, but highly radioactive source of ionizing radiation close to or within a tumour, at dwell positions. An emerging technique for HDR BT treatment is intensity modulated brachytherapy (IMBT), in which static or dynamic shields are used to further shape the dose distribution, by hindering the radiation in certain directions. The topic of this thesis is the application of mathematical optimization to model and solve the treatment planning problem. The treatment planning includes decisions on catheter placement, that is, how many catheters to use and where to place them, as well as decisions for dwell times. Our focus is on the latter decisions. The primary treatment goals are to give the tumour a sufficiently high radiation dose while limiting the dose to the surrounding healthy organs, to avoid severe side effects. Because these aims are typically in conflict, optimization models of the treatment planning problem are inherently multiobjective. Compared to manual treatment planning, there are several advantages of using mathematical optimization for treatment planning. First, the optimization of treatment plans requires less time, compared to the time-consuming manual planning. Secondly, treatment plan quality can be improved by using optimization models and algorithms. Finally, with the use of sophisticated optimization models and algorithms the requirements of experience and skill level for the planners are lower. The use of optimization for treatment planning of IMBT is especially important because the degrees of freedom are too many for manual planning. The contributions of this thesis include the study of properties of treatment planning models, suggestions for extensions and improvements of proposed models, and the development of new optimization models that take clinically relevant, but uncustomary aspects, into account in the treatment planning. A common theme is the modelling of constraints on dosimetric indices, each of which is a restriction on the portion of a volume that receives at least a specified dose, or on the lowest dose that is received by a portion of a volume. Modelling dosimetric indices explicitly yields mixed-integer programs which are computationally demanding to solve. We have therefore investigated approximations of dosimetric indices, for example using smooth non-linear functions or convex functions. Contributions of this thesis are also a literature review of proposed treatment planning models for HDR BT, including mathematical analyses and comparisons of models, and a study of treatment planning for IMBT, which shows how robust optimization can be used to mitigate the risks from rotational errors in the shield placement. Cancer är en grupp av sjukdomar som varje år drabbar miljontals människor. De vanligaste behandlingsformerna är cellgifter, kirurgi, strålbehandling eller en kombination av dessa. I denna avhandling studeras högdosrat brachyterapi (HDR BT), vilket är en form av strålbehandling som till exempel används vid behandling av prostatacancer och gynekologisk cancer. Vid brachyterapibehandling används ihåliga nålar eller applikatorer för att placera en millimeterstor strålkälla antingen inuti eller intill en tumör. I varje nål finns det ett antal så kallade dröjpositioner där strålkällan kan stanna en viss tid för att bestråla den omkringliggande vävnaden, i alla riktningar. Genom att välja lämpliga tider för dröjpositionerna kan dosfördelningen formas efter patientens anatomi. Utöver HDR BT studeras också den nya tekniken intensitetsmodulerad brachyterapi (IMBT) vilket är en variation på HDR BT där skärmning används för att minska strålningen i vissa riktningar vilket gör det möjligt att forma dosfördelningen bättre. Planeringen av en behandling med HDR BT omfattar hur många nålar som ska användas, var de ska placeras samt hur länge strålkällan ska stanna i de olika dröjpositionerna. För HDR BT kan dessa vara flera hundra stycken medan det för IMBT snarare handlar om tusentals möjliga kombinationer av dröjpositioner och inställningar av skärmarna. Planeringen resulterar i en dosplan som beskriver hur hög stråldos som tumören och intilliggande frisk vävnad och riskorgan utsätts för. Dosplaneringen kan formuleras som ett matematiskt optimeringsproblem vilket är ämnet för avhandlingen. De övergripande målsättningarna för behandlingen är att ge en tillräckligt hög stråldos till tumören, för att döda alla cancerceller, samt att undvika att bestråla riskorgan eftersom det kan ge allvarliga biverkningar. Då alla målsättningarna inte samtidigt kan uppnås fullt ut så fås optimeringsproblem där flera målsättningar behöver prioriteras mot varandra. Utöver att dosplanen uppfyller kliniska behandlingsriktlinjer så är också tidsaspekten av planeringen viktig eftersom det är vanligt att den görs medan patienten är bedövad eller sövd. Vid utvärdering av en dosplan används dos-volymmått. För en tumör anger ett dosvolymmått hur stor andel av tumören som får en stråldos som är högre än en specificerad nivå. Dos-volymmått utgör en viktig del av målen för dosplaner som tas upp i kliniska behandlingsriktlinjer och ett exempel på ett sådant mål vid behandling av prostatacancer är att 95% av prostatans volym ska få en stråldos som är minst den föreskrivna dosen. Dos-volymmått utläses ur de kliniskt betydelsefulla dos-volym histogrammen som för varje stråldosnivå anger motsvarande volym som erhåller den dosen. En fördel med att använda matematisk optimering för dosplanering är att det kan spara tid jämfört med manuell planering. Med väl utvecklade modeller så finns det också möjlighet att skapa bättre dosplaner, till exempel genom att riskorganen nås av en lägre dos men med bibehållen dos till tumören. Vidare så finns det även fördelar med en process som inte är lika personberoende och som inte kräver erfarenhet i lika stor utsträckning som manuell dosplanering i dagsläget gör. Vid IMBT är det dessutom så många frihetsgrader att manuell planering i stort sett blir omöjligt. I avhandlingen ligger fokus på hur dos-volymmått kan användas och modelleras explicit i optimeringsmodeller, så kallade dos-volymmodeller. Detta omfattar såväl analys av egenskaper hos befintliga modeller, utvidgningar av tidigare använda modeller samt utveckling av nya optimeringsmodeller. Eftersom dos-volymmodeller modelleras som heltalsproblem, vilka är beräkningskrävande att lösa, så är det också viktigt att utveckla algoritmer som kan lösa dem tillräckligt snabbt för klinisk användning. Ett annat mål för modellutvecklingen är att kunna ta hänsyn till fler kriterier som är kliniskt relevanta men som inte ingår i dos-volymmodeller. En sådan kategori av mått är hur dosen är fördelad rumsligt, exempelvis att volymen av sammanhängande områden som får en alldeles för hög dos ska vara liten. Sådana områden går dock inte att undvika helt eftersom det är typiskt för dosplaner för brachyterapi att stråldosen fördelar sig ojämnt, med väldigt höga doser till små volymer precis intill strålkällorna. Vidare studeras hur små fel i inställningarna av skärmningen i IMBT påverkar dosplanens kvalitet och de olika utvärderingsmått som används kliniskt. Robust optimering har använts för att säkerställa att en dosplan tas fram som är robust sett till dessa möjliga fel i hur skärmningen är placerad. Slutligen ges en omfattande översikt över optimeringsmodeller för dosplanering av HDR BT och speciellt hur optimeringsmodellerna hanterar de motstridiga målsättningarna.
Mathematical Modelling Of Dose Planning In High Dose Rate Brachytherapy
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Author : Björn Morén
language : en
Publisher: Linköping University Electronic Press
Release Date : 2019-04-24
Mathematical Modelling Of Dose Planning In High Dose Rate Brachytherapy written by Björn Morén and has been published by Linköping University Electronic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-04-24 with categories.
Cancer is a widespread type of diseases that each year affects millions of people. It is mainly treated by chemotherapy, surgery or radiation therapy, or a combination of them. One modality of radiation therapy is high dose-rate brachytherapy, used in treatment of for example prostate cancer and gynecologic cancer. Brachytherapy is an invasive treatment in which catheters (hollow needles) or applicators are used to place the highly active radiation source close to or within a tumour. The treatment planning problem, which can be modelled as a mathematical optimization problem, is the topic of this thesis. The treatment planning includes decisions on how many catheters to use and where to place them as well as the dwell times for the radiation source. There are multiple aims with the treatment and these are primarily to give the tumour a radiation dose that is sufficiently high and to give the surrounding healthy tissue and organs (organs at risk) a dose that is sufficiently low. Because these aims are in conflict, modelling the treatment planning gives optimization problems which essentially are multiobjective. To evaluate treatment plans, a concept called dosimetric indices is commonly used and they constitute an essential part of the clinical treatment guidelines. For the tumour, the portion of the volume that receives at least a specified dose is of interest while for an organ at risk it is rather the portion of the volume that receives at most a specified dose. The dosimetric indices are derived from the dose-volume histogram, which for each dose level shows the corresponding dosimetric index. Dose-volume histograms are commonly used to visualise the three-dimensional dose distribution. The research focus of this thesis is mathematical modelling of the treatment planning and properties of optimization models explicitly including dosimetric indices, which the clinical treatment guidelines are based on. Modelling dosimetric indices explicitly yields mixedinteger programs which are computationally demanding to solve. The computing time of the treatment planning is of clinical relevance as the planning is typically conducted while the patient is under anaesthesia. Research topics in this thesis include both studying properties of models, extending and improving models, and developing new optimization models to be able to take more aspects into account in the treatment planning. There are several advantages of using mathematical optimization for treatment planning in comparison to manual planning. First, the treatment planning phase can be shortened compared to the time consuming manual planning. Secondly, also the quality of treatment plans can be improved by using optimization models and algorithms, for example by considering more of the clinically relevant aspects. Finally, with the use of optimization algorithms the requirements of experience and skill level for the planners are lower. This thesis summary contains a literature review over optimization models for treatment planning, including the catheter placement problem. How optimization models consider the multiobjective nature of the treatment planning problem is also discussed.
Optimization Methods For High Dose Rate Brachytherapy Treatment Planning
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Author : Elodie Rachel Mok Tsze Chung
language : en
Publisher:
Release Date : 2016
Optimization Methods For High Dose Rate Brachytherapy Treatment Planning written by Elodie Rachel Mok Tsze Chung and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with categories.
Optimization approaches for treatment planning in two novel high-dose-rate (HDR) brachytherapy techniques, direction-modulation brachytherapy (DMBT) and energy-modulated brachytherapy (EMBT), are investigated for cervical cancer and prostate cancer. Brachytherapy is a form of radiation therapy where a radioactive source is placed inside the body to irradiate the tumour internally. Conventionally, only one source is used and it is unshielded, thus providing an isotropic dose distribution. DMBT makes use of a new shielded applicator that is capable of delivering highly directional radiation distributions. In EMBT, three HDR sources, 192Ir, 60Co, and 169Yb, are used in combination to provide variety in dose profiles. To investigate the benefit of these two new techniques over conventional brachytherapy, we use an inverse planning approach to generate the treatment plans. We model the treatment planning problem as a quadratic program and use an interior point constraint generation algorithm to generate the treatment plans.
Optimization Of Human Cancer Radiotherapy
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Author : G.W. Swan
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-03-08
Optimization Of Human Cancer Radiotherapy written by G.W. Swan and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-08 with Medical categories.
The mathematical models in this book are concerned with a variety of approaches to the manner in which the clinical radiologic treatment of human neoplasms can be improved. These improvements comprise ways of delivering radiation to the malignan cies so as to create considerable damage to tumor cells while sparing neighboring normal tissues. There is no unique way of dealing with these improvements. Accord ingly, in this book a number of different presentations are given. Each presentation has as its goal some aspect of the improvement, or optimization, of radiotherapy. This book is a collection of current ideas concerned with the optimization of human cancer radiotherapy. It is hoped that readers will build on this collection and develop superior approaches for the understanding of the ways to improve therapy. The author owes a special debt of thanks to Kathy Prindle who breezed through the typing of this book with considerable dexterity. TABLE OF CONTENTS Chapter GENERAL INTRODUCTION 1. 1 Introduction 1 1. 2 History of Cancer and its Treatment by Radiotherapy 8 1. 3 Some Mathematical Models of Tumor Growth 12 1. 4 Spatial Distribution of the Radiation Dose 20 Chapter 2 SURVIVAL CURVES FROM STATISTICAL MODELS 24 2. 1 Introduction 24 2. 2 The Target Model 26 2. 3 Single-hit-to-kill Model 27 2. 4 Multitarget, Single-hit Survival 29 2. 5 Multitarget, Multihit Survival 31 2. 6 Single-target, Multihit Survival 31 2.
Optimization Of Brachytherapy Treatment Planning Using Adjoint Functions
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Author : Sua Yoo
language : en
Publisher:
Release Date : 2003
Optimization Of Brachytherapy Treatment Planning Using Adjoint Functions written by Sua Yoo and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with categories.
Treatment Plan Optimization For Rotating Shield Brachytherapy
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Author : Yunlong Liu
language : en
Publisher:
Release Date : 2014
Treatment Plan Optimization For Rotating Shield Brachytherapy written by Yunlong Liu and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014 with Radioisotope brachytherapy categories.
In this thesis, we aim to develop fundamentally new techniques and algorithms for efficiently computing rotating-shield brachytherapy (RSBT) treatment plans. We propose that these algorithms will pave the way for making RSBT available in clinical practices. RSBT is an intensity modulated high-dose-rate brachytherapy (HDR-BT) technique. Theoretically, RSBT offers advantages over the conventional HDR-BT. Although this technique is promising in theory, its application in practice is still at an early stage. The RSBT technique entails rotating a radiation-attenuating shield about a brachytherapy source to directionally modulate the radiation in an optimized fashion. The unshielded brachytherapy source used in conventional HDR-BT delivers radially symmetric dose distributions, thus the intensity modulation capability of the conventional HDR-BT is limited. With the capability of making anisotropic radiation, RSBT will revolutionize the brachytherapy technique through superior dose conformity, increased flexibility and inherent accuracy. Due to the enhanced power of intensity-modulation, RSBT will also enable dose escalation without increasing toxicity to the organs-at-risk, thus improving quality of life for millions of cancer patients. Although the first conceptual RSBT method was proposed more than ten years ago, there are still tremendous chges for applying it in clinical practices. Creating efficient and automated treatment planning system is one of the major technical obstacles for making RSBT deliverable in the clinic. The time-critical nature of the application significantly increases the difficulty of RSBT treatment planning, demanding innovative techniques for information integration. Therefore, we propose that fundamentally novel technology and algorithms for RSBT treatment planning can make RSBT clinically accessible. The fundamental concept used for this thesis is to decompose the dose optimization step for RSBT treatment planning into two steps, namely anchor plan optimization and optimal sequencing. The degree of freedom in anchor plan optimization is controlled at a low level compared to single-step dose optimization, and the optimal sequencing algorithms can efficiently calculate treatment plans by reusing the solutions from anchor plan optimization. Thus, by decomposing the dose optimization, the computational complexity in the two-step method is greatly reduced compared to the single-step method. In the anchor plan optimization, an abstract RSBT delivery model is assumed. The abstract RSBT delivery model assumes that only beams with fixed small azimuthal emission angle, which are called beamlets, will be used during the delivery. An anchor plan is created based on this assumption that only these beamlets will be used. Generally, an anchor plan will be of high quality in the sense of dose distribution, but of low quality in the sense that it has prohibitory long delivery time. In the optimal sequencing step, beamlets will be superposed into beams to reduce the delivery time. By limiting the delivery time to a clinically acceptable level, the anchor plans turn into deliverable plans. Unlike anchor plan optimization, where an abstract RSBT delivery model is assumed, the optimal sequencing step depends on more concrete RSBT delivery models. Specifically, we will study three methods of RSBT, namely the single rotating-shield brachytherapy (S-RSBT), the dynamic rotating-shield brachytherapy (D-RSBT) and the paddle rotating-shield brachytherapy (P-RSBT). We proposed a novel anchor plan dose optimization method as well as novel optimal sequencing methods for each of the RSBT delivery methods studied in this work. We have implemented all the proposed algorithms and experimented with them using real medical data. With the methods proposed in this thesis, the optimization time for creating delivery plans can be controlled within 15 minutes based on the data from our experiments. Compared to the conventional brachytherapy techniques, the three methods studied in this work can produce more conformal dose distributions at an acceptable level of delivery time increase. With 15 min/fx delivery time, S-RSBT, D-RSBT and P-RSBT averagely increased the D90 (the minimum dose received by the hottest 90% of the tumor) by 17, 9 and 5 Gy compared to conventional interstitial plus intracavitary brachytherapy, whose D90 is 79 Gy. The best choice depends on the specified delivery time or quality requirement, as well as the complexity of building the equipment. Roughly speaking, among the three RSBT methods studied in this thesis, P-RSBT has the most complex applicators as well as the highest plan qualities. S-RSBT has the simplest applicators, and its plan qualities is generally better than D-RSBT with limited delivery time (
Multiobjective Optimization In Imrt Treatment Planning
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Author : Lizhen Shao
language : en
Publisher: LAP Lambert Academic Publishing
Release Date : 2010-07
Multiobjective Optimization In Imrt Treatment Planning written by Lizhen Shao and has been published by LAP Lambert Academic Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-07 with Cancer categories.
The aim of intensity modulated radiation therapy (IMRT) is to kill tumor cells while at the same time protecting the surrounding tissue and organs from the damaging effect of radiation. Given the number of beams and beam directions, beam intensity optimization needs to determine beam intensity profiles that yield the best dose distribution under consideration of clinical and physical constraints. In this book, we first review existing mathematical models and computation methods for the beam intensity optimization problem. Then we formulate the beam intensity optimization problem as a multiobjective linear programme (MOLP) with three objectives. The rest of the book is dedicated to developing methods to solve this large MOLP efficiently and to the application in the beam intensity optimization problem. The book provides the necessary mathmatical foundation of multiobjective optimization to solve multiobjective linear programming problems. It is well suitable to be used as a reference book on multiobjective optimization. Moreover it should also be useful to professionals who may be considering using multiobjective optimization.
Radiobiological Modelling In Radiation Oncology
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Author : Roger G. Dale
language : en
Publisher: British Inst of Radiology
Release Date : 2007
Radiobiological Modelling In Radiation Oncology written by Roger G. Dale and has been published by British Inst of Radiology this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with Medical categories.
The move towards individually-optimised treatments, using knowledge of normal tissue and tumour radiosensitivity, proliferation rates, etc, in combination with three-dimensional planning, will need mathematical modelling to achieve its full potential. This modelling process will also be capable of helping develop a rational and cost-effective use of resources.Amongst radiation oncologists and medical physicists there is a need for a greater understanding of the scope, applications and limitations of radiobiological modelling, particularly in complex situations that include multiple treatment variables, the respective influence of which are difficult to separate out by randomised trials without using radiobiologically-based analysis.In future there will be increasing use of modelling in practical situations, including treatment gap corrections, normal tissue tolerance predictions, optimisation of therapy determined by predictive assays, multi-modality schedule design, the simulation of clinical trials, testing contemporaneous medico-legal problems and teaching general principals of radiotherapy.
The Use Of Machine Learning System In Brachytherapy Treatment Planning
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Author : Ximeng Mao
language : en
Publisher:
Release Date : 2020
The Use Of Machine Learning System In Brachytherapy Treatment Planning written by Ximeng Mao and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with categories.
"High dose rate (HDR) brachytherapy (BT) involves temporarily insertion of a sealed highly radioactive source inside or in close proximity of the target volume, by using catheters and/or applicators. Treatment planning in HDR BT is performed on a 3D set of computerized tomography or magnetic resonance images. The purpose of a treatment plan is to determine where (dwell position) and how long (dwell time) the radiation source should pause to expose its radiation. Each implanted catheter provides a set of possible dwell positions. Combinations of the possible dwell positions and dwell times, as well as utilizing contours of the target volume and organs at risk (OAR), contributes to optimization of treatment plans. The optimal plan has the best possible dose distribution with respect to the target volume and the OAR. Two key questions for treatment planning are how to evaluate a certain plan and how to search for the optimal plan. The traditional solutions to the two questions often lack the capability of fully utilizing previous experience, which result in inefficiency due to long computation times when solving the problems. In this thesis machine learning (ML) algorithms were investigated for evaluation and search for an optimal BT treatment plan. ML-based algorithms are chosen due to their ability to specialize in exploiting previous experience for better future performance. Evaluation of a certain treatment plan in the first problem requires calculation of the radiation dose. Clinical standards for BT dose calculation have traditionally been based on AAPM TG-43 report. In the TG-43 based dose calculation process, the affected malignant tissue, the surrounding radiation sensitive healthy organs, BT seeds, needles and applicators are considered to be water with unit mass density for simplification. This simplification overlooks the alteration of photon fluence and absorption of dose by different tissues, BT seeds, needles or applicators. Model based dose calculation algorithms (MBDCAs) provide a detailed and more accurate method for calculation of absorbed dose in heterogeneous systems such as the human body, with the Monte Carlo (MC) method being the gold standard. Recently, these algorithms have evolved from serving as a research tool into clinical practice in BT. To obtain accurate dose distributions, a correct geometrical description, density and tissue composition of the patient, a model of the BT seed and the implanted applicators with appropriate density and material composition are needed as inputs to these MBDCAs. AAPM TG-186 provides guidance for the use of MBDCAs. Although MC method is the most accurate technique for dose calculations, its use incurs an excessive computational cost and time. To provide a solution for the accuracy-time trade-off, a deep convolutional neural network (CNN) algorithm to predict dose distributions calculated with the MC method has been proposed in this thesis. The developed deep CNN based dose calculation algorithm was shown to be a promising method for accurate patient specific dosimetry in BT, at accuracy arbitrarily close to those of the source MC algorithm but with much faster computation times. Treatment plan optimization is traditionally solved as constrained optimization. Extended from core setup of plan optimization, a related plan analysis problem is formulated to focus on understanding the impacts of individual dwell position to overall plan performance. Derived from linear programming formulation of the optimization problem, reinforcement learning (RL) was applied to solve the plan analysis problem. Relying on the dose distribution at each dwell position, the RL solution showed flexibility in problem formulation as there is no need to enforce linearity. Moreover, when used in a simplified proof-of-concept setup derived from the real clinical case, the fully-trained RL agent showed the capability to reach optimal treatment plan within one step from any random start point"--
Modelling Radiotherapy Side Effects
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Author : Tiziana Rancati
language : en
Publisher: CRC Press
Release Date : 2019-06-11
Modelling Radiotherapy Side Effects written by Tiziana Rancati and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-06-11 with Science categories.
The treatment of a patient with radiation therapy is planned to find the optimal way to treat a tumour while minimizing the dose received by the surrounding normal tissues. In order to better exploit the possibilities of this process, the availability of accurate and quantitative knowledge of the peculiar responses of the different tissues is of paramount importance. This book provides an invaluable tutorial for radiation oncologists, medical physicists, and dosimetrists involved in the planning optimization phase of treatment. It presents a practical, accessible, and comprehensive summary of the field’s current research and knowledge regarding the response of normal tissues to radiation. This is the first comprehensive attempt to do so since the publication of the QUANTEC guidelines in 2010. Features: Addresses the lack of systemization in the field, providing educational materials on predictive models, including methods, tools, and the evaluation of uncertainties Collects the combined effects of features, other than dose, in predicting the risk of toxicity in radiation therapy Edited by two leading experts in the field