Design and Use of Anatomical Atlases for Radiotherapy

240 Pages·2010·12.81 MB·English

Improvements on
the Planning and Delivery of
Intensity-Modulated Arc Therapy
Grace Tang B.Sc., M.Sc.
Department of Medical Physics and Bioengineering
UCL
A Thesis Presented as Partial Fulfillment of the Requirements for
the Degree of Doctor of Philosophy in Radiation Physics
April 22, 2010
Primary Supervisor at UCL:
Dr. Ivan Rosenberg
Secondary Supervisor at UCL:
Professor Robert D Speller
Primary Supervisor at University of Maryland:
Professor Cedric X Yu
Secondary Supervisor at University of Maryland:
Dr. Matthew A Earl
I, Grace Tang, confirm that the work presented in this thesis is my own.
Where information has been derived from other sources, I confirm that this
has been indicated in the thesis.
To my Grandpa, Grandma, Mum, Dad and little brother
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Acknowledgments
It is difficult to begin the acknowledgment list. There are too many people to
thank and without whom, this thesis would not be possible.
First, I would like to thank Dr. Rosenberg and Professor Speller for their
noble support. It was an unusual situation when I decided to go to the United
States for the Ph.D. project but both of them were very understanding and
have been very supportive throughout the process. I must also thank them
for their guidance and patience while I was in the US, helping me to stay on
track.
Secondly, I would like to thank Professor Yu for his generous offer and
giving me the opportunity to study in the US. It was very lucky of me to
participate in such an exciting and timely research project. He has been a
selfless teacher and mentor, and was always willing to share his wisdom and
knowledge in medical physics. I feel very grateful for his guidance on the
project while he was also very open to my ideas.
I would also like to thank Dr. Earl, who was my secondary supervisor in
the US. I have learnt a lot from him and received a lot of help from him. In
addition to Dr. Earl, I would like to thank Dr. Shahid Naqvi and Dr. Byong
Yong Yi at the University of Maryland who are very knowledgeable medical
physicists. I thank them for their patience as I asked them questions 10 times
a day, every day, 5 days a week.
There are various components in this project where I have collaborated
with other institutions. I would like to specially thank Dr. Daliang Cao at
Swedish Cancer Institute, Dr. Shuang Luan at the University of New Mexico
and Dr. Chao Wang at the University of Notre Dame for their help on the
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IMAT algorithms. I would also like to thank the physicists, dosimetrists
and physicians at the Department of Radiation Oncology of the University
of Maryland for their help, hospitality and friendship, where some of whom I
have spent many late nights working in the department with.
Last but not least, I would like to thank all the love and support from
my friends and family, especially my grandparents, my parents and my little
brother. I had decided to follow my father’s footstep since I was 6 years
old. By completing a Ph.D. degree, I hope I am a step closer to becoming a
respectable medical physicist like him and help a lot of people.
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Abstract
In the past decade, intensity-modulated radiation therapy (IMRT) has taken
a significant step towards dose conformality and has now become a standard
radiotherapy technique in the clinic. In this era, a rotational IMRT technique
called intensity-modulated arc therapy (IMAT) was also proposed to possibly
further reduce normal tissue toxicity and compete with conventional IMRT.
However, clinical implementation of IMAT had been stagnant primarily due
to the lack of mature planning and delivery systems.
In this study, various aspects of treatment planning and delivery of IMAT
have been investigated and improved. The dosimetric accuracy and compu-
tational efficiency of IMAT planning has been greatly augmented by the use
of Monte Carlo technique which is immune to the large number of discrete
beams in approximating a continuous rotation as compared with traditional
arc calculation methods. An efficient single-arc form of IMAT delivery has
also been explored and extended in contrast to the original multi-arc IMAT.
Here the clinical feasibility of single-arc IMAT was established by comparing
to multi-arc IMAT and conventional IMRT. It was demonstrated that when
using multiple arcs, the requirements on aperture shape connectivity incurred
fewer constraints on the optimisation so that the plan quality became the best
among the three methods studied although the dosimetric differences among
them were generally small and considered clinically insignificant. Neverthe-
less, single-arc IMAT was able to provide a plan quality in between multi-arc
IMAT and fixed-field IMRT with a significant delivery efficiency advantage.
Single-arc IMAT may require dose-rate variation for delivery, which is only
available with the new treatment machines. To expand the clinical utilisa-
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tion, an alternative planning and delivery approach was developed such that
single-arc IMAT can be delivered using constant dose-rate with the existing
machines, sparing the expensive and time-consuming upgrades.
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Clarifications
The works presented in this thesis are based on original ideas. However, there
are a few tools and resources which I have used with permission from the
original owners to support the investigations. These are:
1. Monte Carlo kernel based convolution/superposition dose engine from
Dr. Shahid Naqvi at University of Maryland
2. Continuousintensity-mapoptimisationfromDr. DaliangCaoatSwedish
Cancer Institute
3. K-link IMAT leaf sequencing algorithm from Dr. Shuang Luan at
University of New Mexico
4. Arc-modulated radiation therapy algorithm from Dr. Chao Wang at
University of Notre Dame
Along with other external resources used, the algorithms stated above are
also explicitly identified in the text using footers.
Similarly, the original works and tools developed in this project are differ-
entiated by tagging appendix pointers when they are first introduced in the
text. The appendices give the full description of the computer codes of the
various tools and algorithms that I have written and developed.
Contents
List of Abbreviations 14
List of Tables 17
List of Figures 20
1 Introduction 25
1.1 Cancer and its treatments . . . . . . . . . . . . . . . . . . . . 25
1.2 Radiation in cancer treatments . . . . . . . . . . . . . . . . . 26
1.2.1 Radiobiology of cancer . . . . . . . . . . . . . . . . . . 27
1.3 Overview of external radiotherapy in clinics . . . . . . . . . . 27
1.3.1 Patient simulation . . . . . . . . . . . . . . . . . . . . 28
1.3.2 Treatment planning . . . . . . . . . . . . . . . . . . . . 29
1.3.3 Treatment verification . . . . . . . . . . . . . . . . . . 31
1.3.4 Treatment delivery . . . . . . . . . . . . . . . . . . . . 32
2 Rotational radiotherapy techniques 35
2.1 Rotational therapy . . . . . . . . . . . . . . . . . . . . . . . . 35
2.2 Conformal arc therapy . . . . . . . . . . . . . . . . . . . . . . 36
2.3 Intensity-modulated radiation therapy . . . . . . . . . . . . . 36
2.4 Tomotherapy . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
2.5 Intensity-modulated arc therapy . . . . . . . . . . . . . . . . . 41
3 Treatment planning of IMAT 44
3.1 Forward planning approach . . . . . . . . . . . . . . . . . . . 45
3.2 Inverse planning approach . . . . . . . . . . . . . . . . . . . . 46
Contents 10
3.2.1 Intensity map-based optimisation . . . . . . . . . . . . 49
3.2.2 Aperture-based optimisation . . . . . . . . . . . . . . . 52
3.3 Dose calculation . . . . . . . . . . . . . . . . . . . . . . . . . . 53
4 Improving the accuracy and efficiency of dose calculation for
treatment planning of intensity-modulated arcs 57
4.1 Background and objectives . . . . . . . . . . . . . . . . . . . . 57
4.2 Monte Carlo kernel-based convolution/superposition (MCKS) 59
4.3 Rediscretising the continuous delivery arc for dose calculation 62
4.4 Statisticalcomparisonofstatic-beamcalculationandinterpolated-
static beam calculation . . . . . . . . . . . . . . . . . . . . . . 67
4.4.1 Determine the simulation time of MCKS . . . . . . . . 68
4.4.2 Influence of voxel size in dose computational time . . . 70
4.4.3 Dependence of the number of beams in dose calculation 70
4.5 Planqualitycomparisonofstatic-beamcalculationandinterpolated-
static beam calculation . . . . . . . . . . . . . . . . . . . . . . 72
4.5.1 IMAT planning . . . . . . . . . . . . . . . . . . . . . . 73
4.5.2 Dose differences between 36-beam calculation and 720-
beam calculation . . . . . . . . . . . . . . . . . . . . . 74
4.5.3 Influence of aperture shape variation in dose calculation 79
4.5.4 Influence of MU weighting variation in dose calculation 81
4.5.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . 89
5 Improving the delivery efficiency of IMAT 90
5.1 Background and objectives . . . . . . . . . . . . . . . . . . . . 90
5.2 The development of single-arc IMAT . . . . . . . . . . . . . . 95
5.2.1 Converting multi-arc IMAT into single-arc IMAT . . . 95