Focal Spot, Fall/Winter 1996

https://digitalcommons.wustl.edu/focal_spot_archives/1071/thumbnail.jp

An Optimization-based Approach to Dosimetry Planning for Brachytherapy

Prostate cancer is the second leading cause of death from cancer in North American men, with a reported 32,050 deaths in the U.S. alone for 2010; lung cancer is reported as the number one leading cause of death from cancer in both men and women in North America, its estimated death toll in the U.S. alone in 2010 is over 157,000. One method of treating prostate cancer patients nowadays is by Low Dose Rate Brachytherapy, a process where radioactive seeds are placed in or near the tumor site to kill cancerous cells. For lung cancer, brachytherapy has begun to attract attention due to the advent of robotics assistance and there is increasing research currently in the area. While brachytherapy is gaining popularity as a commonly practiced method for treating cancer patients, the procedure itself has several drawbacks that require further research. One such drawback is that the dosimetry plan created based on the pre-operative imaging may not be accurate due to (a) the change in the tumor’s size as a result of the time elapsed between pre-operative imaging and seed implantation; and (b) movement of the organ under treatment from the position and orientation in pre­ operative imaging; this is particularly important in the case of lung brachytherapy as it would have to take into account lung deflation and respiratory and cardiac motions as well. In addition, seeds may be misplaced during implantation as a result of limitation of the manual or robotic procedures. When this happens, the final dose coverage of the tumor is no longer the same as the intended coverage in the dosimetry plan. In this thesis, the development, implementation and evaluation of two algorithms are presented.The first algorithm is the pre-planning algorithm, which aims to reduce the errors in the dosimetry plan caused by the change in the tumor’s size by providing a mechanism to perform dosimetry planning on-line. By doing this, the first algorithm can also eliminate the need for the patient to be imaged twice, so that the same set of images can be used for dosimetry planning as well as seed implantation. The second algorithm deals with intra-operative dynamic dose optimization, where real­ time seed compensation is performed to compensate for any seed misplacements so that an optimal final coverage can be achieved. The results of the experimental evaluation performed in this project indicate that these algorithms are feasible and have the potential to be applied in the operating room following appropriate animal and clinical validation

Optimizing the Efficiency of the United States Organ Allocation System through Region Reorganization

Allocating organs for transplantation has been controversial in the United States for decades. Two main allocation approaches developed in the past are (1) to allocate organs to patients with higher priority at the same locale; (2) to allocate organs to patients with the greatest medical need regardless of their locations. To balance these two allocation preferences, the U.S. organ transplantation and allocation network has lately implemented a three-tier hierarchical allocation system, dividing the U.S. into 11 regions, composed of 59 Organ Procurement Organizations (OPOs). At present, an procured organ is offered first at the local level, and then regionally and nationally. The purpose of allocating organs at the regional level is to increase the likelihood that a donor-recipient match exists, compared to the former allocation approach, and to increase the quality of the match, compared to the latter approach. However, the question of which regional configuration is the most efficient remains unanswered. This dissertation develops several integer programming models to find the most efficient set of regions. Unlike previous efforts, our model addresses efficient region design for the entire hierarchical system given the existing allocation policy. To measure allocation efficiency, we use the intra-regional transplant cardinality. Two estimates are developed in this dissertation. One is a population-based estimate; the other is an estimate based on the situation where there is only one waiting list nationwide. The latter estimate is a refinement of the former one in that it captures the effect of national-level allocation and heterogeneity of clinical and demographic characteristics among donors and patients. To model national-level allocation, we apply a modeling technique similar to spill-and-recapture in the airline fleet assignment problem. A clinically based simulation model is used in this dissertation to estimate several necessary parameters in the analytic model and to verify the optimal regional configuration obtained from the analytic model. The resulting optimal region design problem is a large-scale set-partitioning problem in whichthere are too many columns to handle explicitly. Given this challenge, we adapt branch and price in this dissertation. We develop a mixed-integer programming pricing problem that is both theoretically and practically hard to solve. To alleviate this existing computational difficulty, we apply geographic decomposition to solve many smaller-scale pricing problems based on pre-specified subsets of OPOs instead of a big pricing problem. When solving each smaller-scale pricing problem, we also generate multiple ``promising' regions that are not necessarily optimal to the pricing problem. In addition, we attempt to develop more efficient solutions for the pricing problem by studying alternative formulations and developing strong valid inequalities. The computational studies in this dissertation use clinical data and show that (1) regional reorganization is beneficial; (2) our branch-and-price application is effective in solving the optimal region design problem

Automatiserad behandlingsplanering inom högintensivt fokuserat ultraljud guidat av magnetresonanstermometri

Högintensivt fokuserat ultraljud guidat av magnetresonanstermometri (MR-HIFU) är en ickeinvasiv medicinsk metod för att åtstadkomma lokal uppvärmning i vävnad, vilket tillämpas främst för behandling av tumörer. Tekniken utnyttjar fokuserat ultraljud för att lokalt höja temperaturen i tumörvävnaden vilket resulterar nekros. För att orsaka ablation i hela tumören krävs det att flera av dessa celler sonikeras. Att manuellt planera hur dessa celler skall placeras, medan behandlingens samtliga säkerhetsaspekter tas i beaktande, är en tidskrävande och monoton process som samtidigt kräver expertis och precision. Dessutom, på grund av behandlingens mångfacetterade karaktär är den svår att optimera manuellt. Syftet med detta arbete var att utforma en algoritm för automatisk behandlingsplanering för MR-HIFU för att förbättra arbetsflödet i planeringsprocessen, samt att producera en prototyp av en dylik algoritm. Den presenterade algoritmen är en stegvis process. Först producerar algoritmen en grupp av positioner som kan sonikeras på ett säkert sätt. Därefter finner algoritmen den optimala undergruppen av dessa positioner. Slutligen optimerar algoritmen resten av de relevanta behandlingsparametrarna. Behandlingen kan optimeras antingen genom att maximera volymen som utsätts för ablation eller genom att minimera tiden som behandlingen kräver. Den presenterade algoritmen är tillräckligt generell för att kunna anpassas till samtliga ablationstillämpningar av MR-HIFU. Den har en modulstruktur vilket förenklar uppgradering, och den kan använda information om hur behandlingen framskrider för att reglera och uppdatera planen. Detta är den första publicerade algoritmen för behandlingsplanering inom MRHIFU som kan optimera behandlingen samt använda återkoppling för att reglera planen. Prototypen testades i två konstgjorda fall samt i ett äkta kliniskt fall vilket dess genomförbarhet.Magnetic Resonance guided High Intensity Focused Ultrasound (MR-HIFU) is a noninvasive medical procedure for localized tissue heating, used mostly in treatment of tumours. The modality utilizes focused ultrasound to raise the temperature of the tumour tissue in small localized volumes, resulting in necrosis. To ablate the whole tumour, several of these sonication cells are need. Planning the positions of the cells, while taking into consideration all safety aspects of the treatment, is a time consuming and monotonous task, but requires at the same time expertise and precision. Furthermore, due to the complex characteristics of a MR-HIFU treatment, it is difficult to optimize manually. The aim of the thesis was to design an outline for an automated treatment planning algorithm for MR-HIFU, and to produce a prototype of such an algorithm. The presented algorithm relies on a step-wise process. First, a set of positions is produced that can be sonicated safely. Then, an optimal subset of those positions is selected. Finally, the remaining treatment parameters are optimized. The treatment can either be optimized for maximum coverage or minimum total treatment time. The proposed algorithm is general enough to be adaptable to all ablation applications of MR-HIFU. It has a modular structure for easy updating, and it is able to improve on the plan during the treatment based on feedback from already delivered cells. This is the first published treatment planning algorithm for MR-HIFU that optimizes the treatment and has the ability to update the plan based on feedback. The prototype was tested in two artificial test cases and one real clinical case, proving its feasibility

Molecular Imaging of Prostate Cancer

Chapter 1 addresses the introduction to the thesis and provides epidemiology, etiology, metastatic spread, current diagnostics and clinical need of new biomarker for risk stratification of prostate cancer. Chapter 2 provides a detailed analysis of the distribution pattern of the three most used choline tracers: 18F-methylcholine, 11C-choline, and 18F-ethylcholine in metabolically and anatomically disease-free patients. The ranges of SUVmax, SUVmean and standard deviations have been presented. Potential pitfalls in evaluation of “non-avid” but clinically significant presentation of different disease entities are also addressed. The chapter provides overview of the variations in choline uptake pattern which is vital for assessment of various organs when imaging is performed for evaluation of metastatic disease. Chapter 3 presents the feasibility of assessing dynamic 18F Ethyl Choline PET with a view to do kinetic modelling in clinical setting of biochemical relapse of Prostate Cancer. This critical piece of work underpins the quantification, tracer kinetics and demonstrates that cancerous tissue shows abnormal perfusion. From these observations I was able to conclude that 18F Choline can act as a biomarker to assess angiogenesis in prostate cancer and introduces 18F Choline as a biomarker for further work presented in chapter 4-8. Chapter 4 addresses the detection of clinically significant and insignificant prostate cancer on 18F-FECH PET/CT and I correlated findings with template guided prostate mapping biopsy (TPM). Sensitivity and Specificity data of 8F-FECH PET/CT has been provided. Chapter 5 addresses the accuracy of 18F Choline PET/MR which is compared to reference standard (template guided prostate mapping biopsy). This work suggests that data obtained from 18F Choline PET/MR can allow detection of clinically significant and insignificant prostate cancer. I noted that multiple previous treatments can give false positive results and 18F Choline PET/MR is the imaging investigation of choice post HIFU. Moreover, false negative results with 18F Choline PET/MR can be due to very small volume (=/<2 mm) disease. Chapter 6 presents the differential diagnosis of abnormal tracer accumulation in the Prostate and periprostatic tissue. Chapter 7 provides spectrum of skeletal findings on dual-phase 18F-fluoroethylcholine (FECH) PET/CT performed during the work-up of patients referred for suspected prostate cancer relapse. I have provided quantification data and explained that SUVmax in isolation cannot be used to characterize these lesions as benign or malignant. Minimal overlap of benign and malignant lesions also exists. Chapter 8 addresses the clinical utility of 18F Choline in the setting of clinical trial in collaboration with Uro-oncology, Nuclear Medicine and Radiology departments. This critical work compares 18F Choline PET-CT and Whole-Body MRI in assessment and decision-making process for salvage treatment of focal radio-recurrent prostate cancer. This chapters concludes that at present WB-MRI cannot be used alone as imaging modality for investigation of biochemical relapse of Prostate Cancer. Chapter 9 is a summary of main findings and discussions from chapters in this thesis. It also highlights the potential applications and future perspectives of novel biomarkers for imaging of prostate cancer

Intensity Modulated Proton Therapy Optimization Under Uncertainty: Field Misalignment and Internal Organ Motion

Intensity modulated proton therapy (IMPT) is one of the most advanced forms of radiation therapy, which can deliver a highly conformal dose to the tumor while sparing the dose in healthy tissues. Compared to conventional photon-based radiation therapy, IMPT is more flexible in delivering radiation dose according to different tumor shapes. However, this flexibility also makes the optimization problems in IMPT harder to solve, e.g., it requires larger memory to store data and longer computational time. Furthermore, proton beams are very sensitive to different uncertainties, such as setup uncertainty, range uncertainty and internal organ motion. These uncertainties can greatly impact the quality of clinical treatment. Therefore, this dissertation aims to investigate different optimization methods for treatment planning and to handle a variety of uncertainties in IMPT. First, to solve the fluence map optimization (FMO) problem in IMPT, we propose a method to formulate the FMO problem into a molecular dynamics model. So that, the FMO problem can be optimized according classical dynamics system. This method combines the advantages of gradient-based algorithms and heuristic search algorithms. Next, we develop and validate a robust optimization method for IMPT treatment plans with multi-isocenter large fields to overcome the dose inhomogeneity problem caused by the setup misalignment in field junctions. Numerical results show that the robust optimized IMPT plans create a low gradient field radiation dose in the junction regions, which can minimize the impact from misalignment uncertainty. Compare to conventional techniques, the robust optimization method leads the whole treatment much more efficient. Lastly, we focus on a two-stage method to solve the beam angle optimization (BAO) problem in IMPT with internal organ motion uncertainty. In the first stage, a $p$-median algorithm is developed for beam angle clustering. In the second stage, a bi-level search algorithm is used to find the final beam angle set for the treatment. Furthermore, Support vector machine (SVM) is used for beam angle classification to reduce the search space and the 4D-CT information is incorporated to handle the internal organ motion uncertainty. Results show that the two-stage BAO method consistently finds a high-quality solution in a short time.Industrial Engineering, Department o

A multi-technique hierarchical X-ray phase-based approach for the characterization and quantification of the effects of novel radiotherapies

Cancer is the first or second leading cause of premature deaths worldwide with an overall rapidly growing burden. Standard cancer therapies include surgery, chemotherapy and radiotherapy (RT) and often a combination of the three is applied to improve the probability of tumour control. Standard therapy protocols have been established for many types of cancers and new approaches are under study especially for treating radio-resistant tumours associated to an overall poor prognosis, as for brain and lung cancers. Follow up techniques able to monitor and investigate the effects of therapies are important for surveying the efficacy of conventionally applied treatments and are key for accessing the curing capabilities and the onset of acute and late adverse effects of new therapies. In this framework, this doctoral Thesis proposes the X-ray Phase Contrast Im-aging - Computed Tomography (XPCI-CT) technique as an imaging-based tool to study and quantify the effects of novel RTs, namely Microbeam and Minibeam Radiation therapy (MRT and MB), and to compare them to the standard Broad Beam (BB) induced effects on brain and lungs. MRT and MB are novel radiotherapies that deliver an array of spatially fractionated X-ray beamlets issued from a synchrotron radiation source, with widths of tens or hundreds of micrometres, respectively. MRT and MB exploit the so-called dose-volume effect: hundreds of Grays are well tolerated by healthy tissues and show a preferential effect on tumour cells and vasculature when delivered in a micrometric sized micro-plane, while induce lethal effects if applied over larger uniform irradiation fields. Such highly collimated X-ray beams need a high-resolution and a full-organ approach that can visualize, with high sensitivity, the effects of the treatment along and outside the beamlets path. XPCI-CT is here suggested and proven as a powerful imaging technique able to determine and quantify the effects of the radiation on normal and tumour-bearing tissues. Moreover, it is shown as an effective technique to complement, with 3D information, the histology findings in the follow-up of the RT treatments. Using a multi-scale and multi-technique X-ray-based approach, I have visualized and analysed the effects of RT delivery on healthy and glioblastoma multiforme (GBM)-bearing rat brains as well as on healthy rat lungs. Ex-vivo XPCI-CT datasets acquired with isotropic voxel sizes in the range 3.253 – 0.653 μm3 could distinguish, with high sensitivity, the idiopathic effects of MRT, MB and BB therapies. Histology, immunohistochemistry, Small- and Wide-Angle X-ray Scattering and X-ray Fluorescence experiments were also carried out to accurately interpret and complement the XPCI-CT findings as well as to obtain a detailed structural and chemical characterization of the detected pathological features. Overall, this multi-technique approach could detect: i) a different radio-sensitivity for the MRT-treated brain areas; ii) Ca and Fe deposits, hydroxyapatite crystals formation; iii) extended and isolated fibrotic contents. Full-organ XPCI-CT datasets allowed for the quantification of tumour and mi-crocalcifications’ volumes in treated brains and the amount of scarring tissue in irradiated lungs. Herein, the role of XPCI-CT as a 3D virtual histology technique for the follow-up of ex-vivo RT effects has been assessed as a complementary method for an accurate volumetric investigation of normal and pathological states in brains and lungs, in a small animal model. Moreover, the technique is proposed as a guidance and auxiliary tool for conventional histology, which is the gold standard for pathological evaluations, owing to its 3D capabilities and the possibility of virtually navigating within samples. This puts a landmark for XPCI-CT inclusion in the pre-clinical studies pipeline and for advancing towards in-vivo XPCI-CT imaging of treated organs.Weltweit gilt Krebs als häufigste bzw. zweithäufigste Ursache eines zu früh erfolgenden Todes, wobei die Zahlen rasch ansteigen. Standardmäßige Krebstherapien umfassen chirurgische Eingriffe, Chemotherapie und Strahlentherapie (radiotherapy, RT); oft kommt eine Kombination daraus zur Anwendung, um die Wahrscheinlichkeit der Tumorkontrolle zu erhöhen. Es wurden Standardtherapieprotokolle für zahlreiche Krebsarten eingerichtet und es wird vor allem in der Behandlung von strahlenresistenten Tumoren mit allgemein schlechter Prognose wie bei Hirn- und Lungentumoren an neuen Ansätzen geforscht. Nachverfolgungstechniken, welche die Auswirkungen von Therapien überwachen und ermitteln, sind zur Überwachung der Wirksamkeit herkömmlich angewandter Behandlungen wichtig und auch maßgeblich am Zugang zu den Fähigkeiten zur Heilung sowie zum Auftreten akuter und verzögerter Nebenwirkungen neuer Therapien beteiligt. In diesem Rahmenwerk unterbreitet diese Doktorarbeit die Technik der Röntgen-Phasenkontrast-Bildgebung über Computertomographie (X-ray Phase Contrast Imaging - Computed Tomography, XPCI‑CT) als bildverarbeitungs-basiertes Tool zur Untersuchung und Quantifizierung der Auswirkungen neuartiger Strahlentherapien, nämlich der Mikrobeam- und Minibeam-Strahlentherapie (MRT und MB), sowie zum Vergleich derselben mit den herkömmlichen durch Breitstrahlen (Broad Beam, BB) erzielten Auswirkungen auf Gehirn und Lunge. MRT und MB sind neuartige Strahlentherapien, die ein Array räumlich aufgeteilter Röntgenstrahlenbeamlets aus einer synchrotronen Strahlenquelle mit einer Breite von Zehnteln bzw. Hundersteln Mikrometern abgeben. MRT und MB nutzen den sogenannten Dosis-Volumen-Effekt: Hunderte Gray werden von gesundem Gewebe gut vertragen und wirken bei der Abgabe in einer Mikroebene im Mikrometerbereich vorrangig auf Tumorzellen und Blutgefäße, während sie bei einer Anwendung über größere gleichförmige Strahlungsfelder letale Auswirkungen aufweisen. Solche hoch kollimierten Röntgenstrahlen erfordern eine hohe Auflösung und einen Zugang zum gesamten Organ, bei dem die Auswirkungen der Behandlung entlang und außerhalb der Beamletpfade mit hoher Empfindlichkeit visualisiert werden können. Hier empfiehlt und bewährt sich die XPCI‑CT als leistungsstarke Bildverarbeitungstechnik, welche die Auswirkungen der Strahlung auf normale und tumortragende Gewebe feststellen und quantifizieren kann. Außerdem hat sich gezeigt, dass sie durch 3‑D-Informationen eine effektive Technik zur Ergänzung der histologischen Erkenntnisse in der Nachverfolgung der Strahlenbehandlung ist. Anhand eines mehrstufigen und multitechnischen röntgenbasierten Ansatzes habe ich die Auswirkungen der Strahlentherapie auf gesunde und von Glioblastomen (GBM) befallene Rattenhirne sowie auf gesunde Rattenlungen visualisiert und analysiert. Mit isotropen Voxelgrößen im Bereich von 3,53 bis 0,653 μm3 erfasste Ex-vivo-XPCI-CT-Datensätze konnten die idiopathischen Auswirkungen der MRT-, MB- und BB‑Behandlung mit hoher Empfindlichkeit unterscheiden. Es wurden auch Experimente zu Histologie, Immunhistochemie, Röntgenklein- und ‑weitwinkelstreuung und Röntgenfluoreszenz durchgeführt, um die XPCI‑CT-Erkenntnisse präzise zu interpretieren und zu ergänzen sowie eine detaillierte strukturelle und chemische Charakterisierung der nachgewiesenen pathologischen Merkmale zu erhalten. Im Allgemeinen wurde durch diesen multitechnischen Ansatz Folgendes ermittelt: i) eine un-terschiedliche Strahlenempfindlichkeit der mit MRT behandelten Gehirnbereiche; ii) Ca- und Fe-Ablagerungen und die Bildung von Hydroxylapatitkristallen; iii) ein ausgedehnter und isolierter Fibrosegehalt. XPCI‑CT-Datensätze des gesamten Organs ermöglichten die Quantifizierung der Volume von Tumoren und Mikroverkalkungen in den behandelten Gehirnen und der Menge des Narbengewebes in bestrahlten Lungen. Dabei wurde die Rolle der XPCI‑CT als virtuelle 3‑D-Histologietechnik für die Nachverfolgung von Ex-vivo-RT‑Auswirkungen als ergänzende Methode für eine präzise volumetrische Untersuchung des normalen und pathologischen Zustands von Gehirnen und Lungen im Kleintiermodell untersucht. Darüber hinaus wird die Technik aufgrund ihrer 3‑D-Fähigkeiten und der Möglichkeit zur virtuellen Navigation in den Proben als Leitfaden und Hilfstool für die herkömmliche Histologie vorgeschlagen, die der Goldstandard für die pathologische Evaluierung ist. Dies markiert einen Meilenstein für die Übernahme der XPCI‑CT in die Pipeline präklinischer Studien und für den Übergang zur In-vivo-XPCI‑CT von behandelten Organen

On the minimum cardinality problem in intensity modulated radiotherapy

The thesis examines an optimisation problem that appears in the treatment planning of intensity modulated radiotherapy. An approach is presented which solved the optimisation problem in question while also extending the approach to execute in a massively parallel environment. The performance of the approach presented is among the fastest available