Clinical Physics Research Articles

Report of the AAPM Task Group No. 105: Issues associated with clinical implementation of Monte Carlo‐based photon and electron external beam treatment planning

The Monte Carlo (MC) method has been shown through many research studies to calculate accurate dose distributions for clinical radiotherapy, particularly in heterogeneous patient tissues where the effects of electron transport cannot be accurately handled with conventional, deterministic dose algorithms. Despite its proven accuracy and the potential for improved dose distributions to influence treatment outcomes, the long calculation times previously associated with MC simulation rendered this method impractical for routine clinical treatment planning. However, the development of faster codes optimized for radiotherapy calculations and improvements in computer processor technology have substantially reduced calculation times to, in some instances, within minutes on a single processor. These advances have motivated several major treatment planning system vendors to embark upon the path of MC techniques. Several commercial vendors have already released or are currently in the process of releasing MC algorithms for photon and/or electron beam treatment planning. Consequently, the accessibility and use of MC treatment planning algorithms may well become widespread in the radiotherapy community. With MC simulation, dose is computed stochastically using first principles; this method is therefore quite different from conventional dose algorithms. Issues such as statistical uncertainties, the use of variance reduction techniques, the ability to account for geometric details in the accelerator treatment head simulation, and other features, are all unique components of a MC treatment planning algorithm. Successful implementation by the clinical physicist of such a system will require an understanding of the basic principles of MC techniques. The purpose of this report, while providing education and review on the use of MC simulation in radiotherapy planning, is to set out, for both users and developers, the salient issues associated with clinical implementation and experimental verification of MC dose algorithms. As the MC method is an emerging technology, this report is not meant to be prescriptive. Rather, it is intended as a preliminary report to review the tenets of the MC method and to provide the framework upon which to build a comprehensive program for commissioning and routine quality assurance of MC-based treatment planning systems.

Radiation Therapy Using A Simultaneously Integrated Boost For Early-Stage Breast Cancer

Evaluation of: van der Laan HP, Dolsma WV, Maduro JH et al.: Three-dimensional conformal simultaneously integrated boost technique for breast-conserving therapy. Int. J. Radiat. Oncol. Biol. Phys. 68(4), 1018–1023 (2007). Radiotherapy of 25 daily fractions of 2 Gy after breast-conserving surgery is effective in reducing the risk of a local recurrence. An extra boost dose of eight daily fractions of 2 Gy reduces this risk even further by a factor of 1.7. However, the extended treatment time is not patient friendly and is more labor intensive. With new, advanced equipment, it is now possible to use a so-called simultaneous integrated boost (SIB) technique to prevent these downsides. With this technique, the boost dose is integrated into the standard dose fractions, thus reducing the number of times a patient has to be irradiated. However, the initial implementation of this technique is very labor intensive and requires profound knowledge of the radiotherapy treatment planning system and treatment unit. In their article, van der Laan and colleagues present an SIB technique which is easier to implement than a sophisticated (inversely planned) SIB technique. Moreover, they are the first authors to present data on acute skin toxicity using this technique and fractionation schedule. Their work contributes significantly to the efforts of clinical physicists, radiation oncologists and radiation therapists worldwide to improve breast cancer patient care by the safe implementation of new, advanced radiotherapy technology. However, one has to realize that implementing such a technique still requires accurate knowledge of the target volume delineation and patient set-up accuracy in each institution. Also, boost volume changes may occur during treatment, which must be taken into account. Data are becoming available on this, and clinical trials investigating even higher boost doses or more conformal treatment techniques are being conducted.

WE‐C‐BRA‐02: Parameters for and Use of NTCP Models in the Clinic

Delivery of adequate tumor dose without causing excessive normal tissue complications is the driving principle of modern radiation therapy. Resulting dose distributions in normal tissues are very different from the “partial organ irradiation” distributions that characterize the simple beam arrangements of earlier days. Further, the growing popularity of hypofractionation drastically widens the range of biological effective doses within organs at risk (OAR). The clinical physicist is faced with uncertainty as to what aspects of an OAR dose distribution require special consideration in treatment plan design and evaluation.Normal tissue complication probability (NTCP) models are one way to account for the full dose distribution. For most serious toxicities, statistical models from various outcomes analyses help direct the planner toward dose‐volume limits. There are also several semi‐mechanistic models, each with a set of parameters that must be adjusted to describe existing data. But for conditions that differ greatly from those under which they were ‘commissioned’, two models for the same endpoint and starting from the same input dose distribution do not necessarily predict the same NTCP. A working group, with joint participation from AAPM, ASTRO and RTOG, is being established to, among other things, reconcile model differences and provide clinical guidelines in the near future.In this presentation, common NTCP models for several major dose‐limiting toxicities will be described, including parameters sets gleaned from literature review. Problems and pitfalls of integrating and interpreting diverse studies and applying them to an individual clinic's practice will be discussed and real‐world examples of application to clinical decisions will be presented.Educational Objectives:1. Understand the important features of the most widely‐used NTCP models.2. Understand how the model parameters affect predictions of normal tissue dose‐volume responses.3. Understand some of the complexities of implementing these models into routine clinical practice.

MO‐A‐BRB‐01: Review of the AAPM TG‐105

Despite its proven accuracy and the potential for improved dose distributions to influence treatment outcomes, the long calculation times previously associated with MC simulation rendered this method impractical for routine clinical treatment planning. However, the development of faster codes optimized for radiotherapy calculations and improvements in computer processor technology have substantially reduced calculation times to, in some instances, within minutes on a single processor. Several commercial vendors have released or are currently in the process of releasing MC algorithms for photon and/or electron beam treatment planning. Consequently, the accessibility and use of MC treatment planning algorithms may well become widespread in the radiotherapy community. With MC simulation, dose is computed stochastically using first principles; this method is therefore quite different from conventional dose algorithms. Issues such as statistical uncertainties, the use of variance reduction techniques, the ability to account for geometric details in the accelerator treatment head simulation, and other features, are all unique components of a MC treatment planning algorithm. Successful implementation by the clinical physicist of such a system will require an understanding of the basic principles of MC techniques.Educational Objectives:1. To provide an educational review of the physics of the MC including discussion of methods used for coupled photon and electron transport.2. To review the methods used to improve the simulation efficiency.3. To briefly review the vendor transport codes currently used for clinical treatment planning.4. To describe the development of treatment head models for clinical treatment planning.5. To discuss the factors associated with MC dose calculation within the patient‐specific geometry, such as statistical uncertainties, CT‐to‐material, and reporting of dose‐to‐medium versus dose‐to‐water.6. To discuss the issues associated with experimental verification of MC algorithms.7. To briefly review the potential clinical implications of MC calculated dose distributions.8. To provide example timing comparisons of the major vendor MC codes in the clinical setting.

TU‐B‐BRB‐02: Monte Carlo — II: Application of Monte Carlo to Clinical IMRT Treatment Planning

The goal of this course is to familiarize participants with the clinical use of Monte Carlo (MC) dose calculation algorithms in IMRT photon‐beam treatment planning. Particular focus will be applied to the actual and potential clinical impact of MC dose calculation algorithms on patient treatments. Following a brief description of the integration of MC algorithms with commercial planning systems, MC dose re‐calculation results will be compared with plans computed using the conventional commercial treatment planning system algorithms. Specific patient examples where MC computed doses differ significantly from those computed with standard treatment planning system algorithms will be presented, with the causes of the dose discrepancies identified. With this background, the roles that MC has played in actual clinical practice will be described: as a QA tool to validate treatment planning system algorithms, as a QA tool to validate individual IMRT plans, and as a treatment planning tool to improve conformity between optimized and delivered IMRT plans. Strategies to minimize MC dose calculation time during IMRT optimization will be described.Educational Objectives:1. To instruct clinical physicists regarding roles of Monte Carlo dose calculations for clinical IMRT patient treatment planning.2. To describe the role of Monte Carlo in IMRT treatment planning system and patient specific quality assurance.3. To describe clinical cases where Monte Carlo dose calculation either resulted —or would have resulted— in a change in the clinical treatment.4. To describe the applications of and impact of Monte Carlo dose calculations for IMRT optimization.5. This work was sponsored in part by Philips Medical Systems and Varian Medical Systems.

TU‐A‐L100F‐01: Quality Assurance Procedures for Digital Radiography

Diagnostic medical physicists have traditionally played a key role in the radiology department's Quality Assurance (QA) program. Procedures for QA of digital radiography (DR) systems are less well‐established than those designed for conventional screen‐film radiography. Some methods that were appropriate for conventional systems do not yield accurate results for digital systems. Methods that rely on images on film cannot be performed in a facility devoid of chemical processing. Methods that do not consider effects of all stages of the digital imaging chain from acquisition to display are likely to provide erroneous results. Digital systems often do not provide data in a convenient form for assessing performance. Nevertheless, medical physicists are responsible for designing and directing efforts to assure the safety and efficacy of DR.Development of standards for performance verification of digital radiographic systems has been outpaced by commercialization of the technology. Practitioners, operators, vendors, and medical physicists are uncertain as to how to configure, calibrate, and verify systems for the best diagnostic quality images at the lowest practical radiation exposure to the patient. Several manufacturers have fielded commercial systems for performance verification, but long term data indicating trends and action limits is rare. Sources of definitive information on practical clinical methods are also scarce in the scientific literature. This has led to the current situation where clinical imaging operations are routinely conducted using systems that are not optimized.The good news is that methods in common practice for conventional radiography can be applied with modification to digital radiography. Some of these methods are described in recent literature. The AAPM has recognized the dilemma and has initiated an effort to provide practical guidance to clinical physicists, i.e. Task Group 150.This lecture will discuss some components of a QA program for DR, including adaptation of conventional QA processes. The lecture will discuss methods of evaluating system performance and provide examples of potential interferences. The lecture will review commercial devices for performance evaluation and their limitations. Finally, some ongoing standardization efforts will be described.Educational Objectives:1. Review components of a QA program and show how they apply to DR.2. Understand how some conventional tests should be modified for a digital radiographic system integrated into an electronic image management system.3. Identify key references and standards that can be useful in QA of DR.

Perioperative medicine and medical care By the Surgical Operations Master (Anesthesiologist)

Knowing of what matters and what matters most, Perioperative medicine matters more than ever (1) There is a growing worldwide awareness of perioperative Medical care (2) Comprehension of perioperative patients safety comfort and well fair, As well as helping surgeons to perform successfully and timely an ever increasing multitude of surgical procedures may necessitate rewriting of Medical texts By contemporary Anaesthesiologists in a purposeful manner that aims specifically at Patients health, safety, and post operative welfare, Why Anaesthesiologists? In contemporary Medical and Surgical practices the Anaesthetist is a clinical Physiologist, Clinical Biochemist a clinical physicist, clinical pharmacologist as well as a competent physician. Anaesthetists have cumulated vast expertise about the patient care minute by minute during the course of operative procedures. They are involved in: appropriate patients placing and locations of equipments, anticipation of possible complications and avoiding it. insuring safety speed and through understanding of what the patient is going through preparing for the post operative demands Post operatively managing pain a resuscitator and a role in early discharge of patients The concern about productivity of operative theatres in sophisticated communities and developed countries alike is the concern of all health care providers. Whether it is Governments, Insurance companies, Private health institutes are undoubtedly under some form of pressure to expand Vertically as well as horizontally, Vertically by continuous process of modernization and rendering new technological facilities for the people they care for. And horizontally by spreading the services to wider sectors of populations in the face the growing demands. The Vertical and Horizontal progresses demands Ideal utilization of surgical operative room's resources Ideal timing for admissions to hospitals Promoting the rates of hospital beds patients turnover Designating responsibilities to the most skilful and who knows how Orienting Health care providers by the role of Anaesthetic practices in contemporary Medical and Surgical practices is a mandatory role of every concerned about the ultimate productivity of HCO (Health care organization) In my article titled taking Anaesthetic practice a few steps higher, My prime concern was about the specialty of Anaesthesia with regards to Maintaining Anaesthetist Cinical medical competence, traditionally the work load on the Anaesthetist had limited his time for maintaining competence in Medical science that undoubtedly reduces the interest of new generations of Perioperative medicine and medical care By the Surgical Operations Master (Anesthesiologist) 2 of 6 physicians from joining this specialty, It would also have negative impacts on the patients under the Anaesthetist care if his tasks shrinks to a physical burden. Providing for patients by the most competent know how in the perioperative settings, Economizing on the perioperative resources I did envision the future arrangements for what modern Operating departments should be like, I simply had the analogy of Labour ward in a modern Obstetric unite, That is intimately linked to Two major departments, An antenatal and a post natal. I am still hoping to see an OR with a preoperative and post operative wards functioning together as a modern Operating department under an Operation master. Patients who are scheduled for surgical procedures would be admitted to the Preoperative wing where the Anesthetist would care from the minute go with a comprehension more than most of what the patient would be going through during surgery. Comparing this speculation to the classic routine of pre operative admission to a surgical ward would expose hundreds of advantages for the patients the surgeon the anesthetist and to the Healthcare providers.

TU‐A‐230A‐01: Monte Carlo II: MC for Source and Machine Characterization

Monte Carlo algorithms have the ability to accurately model dose distributions for arbitrarily complex treatment delivery scenarios and changing patient geometries. These properties make Monte Carlo ideal for clinical planning, or for benchmarking clinical planning systems. Building on the discussion of the role of Monte Carlo in treatment head simulation (from the first course), this second Monte Carlo course will focus on patient planning applications. The goal of the course is to familiarize clinical medical physicists with the use of Monte Carlo in treatment planning, including advanced treatment techniques such as IMRT and motion compensated 4D treatment, and to discuss how Monte Carlo‐based planning differs from planning with conventional algorithms. We will demonstrate the various approaches used in modeling beam modifying devices, such as the multi‐leaf collimator (MLC), including methods to effectively model the dosimetric consequences of the detailed the MLC geometry. We will review methods used to reduce Monte Carlo‐based clinical dose calculation time, such as variance reduction techniques, and discuss how factors specific to the MC method, such as statistical uncertainties, impact dose distributions and clinical decision making. We will illustrate how a properly benchmarked Monte Carlo algorithm can play a unique role in the modeling of complex delivery procedures, such as IMRT and how Monte Carlo fluence prediction can be combined with analytic dose algorithms to estimate patient dose. Finally, we will show how Monte Carlo can include organ motion in 4D dose calculations without an increase in computation time. In addition to illustrating the role of Monte Carlo in complex treatment planning, a focus of this course will also be to review some of the practical issues associated with the implementation, verification and clinical use of Monte Carlo‐based dose calculation algorithms.Educational Objectives:1. To familiarize clinical physicists with some of the issues associated with implementation and experimental verification of Monte Carlo‐based dose algorithms in the clinical setting.2. To understand the factors specific to Monte Carlo‐based dose algorithms, such variance reduction techniques and statistical uncertainties.3. To become familiar with the various approaches used in Monte Carlo‐based modeling of the MLC and the tradeoffs associated with these methods.4. To recognize the potential clinical outcome benefits of Monte Carlo‐based dose distributions.5. To understand the use, benefits and limitations of the Monte Carlo method for IMRT optimization and QA.6. To become familiar with the role of the Monte Carlo method in motion compensated (4D) treatment planning.

TH‐C‐VaIA‐01: Memorial Lecture for Robert Loevinger

How perfectly appropriate is the Symposium: “How accurately can we measure dose clinically?” to memorialize Bob Loevinger. The clear threads in Bob's career and seminal work was his quest for improved accuracy in dosimetry measurements, his organization of calibration networks to transfer traceable measurement standards to the clinical physicist, and his development of protocols and formalisms to implement accurate measurements of dose at the clinical level. In his professional career of some 55 years, his contributions were many and important. Quiet and unassuming, Bob was the supreme dosimetrist: he designed and constructed extrapolation chambers for beta dosimetry in his early career, and then the Wide‐Angle‐Free‐Air‐Chamber (WAFAC) for prostate‐seed dosimetry in his late career; he developed the MIRD schema with Mones Berman for dose calculations in nuclear medicine, and led the development of the TG 21 protocol for the determination of absorbed dose from high‐energy photon and electron beams; at the IAEA in the 1960s he was instrumental in the creation of their Dosimetry Laboratory and the IAEA/WHO Secondary Standards Dosimetry Laboratory Network that serve the mostly developing member states, and initiated their postal dosimetry service to clinics in the member states; then at the NBS in the 1970s he worked with the AAPM (he was a charter member) to create the network of Accredited Calibration Dosimetry Laboratories to better disseminate US radiation measurement standards to the clinical community in North America. Much of his work was recognized during his lifetime by numerous awards given him by many organizations, but I think he would be most honored by this Symposium, which gathers like‐minded scientists to discuss issues on which he spent his career.

TH‐C‐VaIA‐02: In's and Out's of Non‐Equilibrium Dosimetry

Typical procedures for clinical dosimetry are well established for measurements in charged particle equilibrium situations. These situations only form a subset of the measurement challenges of a clinical physicist. Dose measurements in regions of charged particle disequilibrium require special considerations before the measurement can be assumed accurate. These disequilibrium conditions occur in association with measurements performed for standard clinical treatment techniques as well as for special treatment techniques. In the symposium we identified four major areas that complicate accurate clinical dosimetry: (1) the photon build‐up region, (2) narrow photon beams, (3) measurements in heterogeneous phantoms and (4) modulated fields and dynamic measurements.In the present lecture we describe the principles of accurate dose measurements in general in equilibrium and non‐equilibrium situations. Principles of detector response, energy dependence and characteristics of practical detectors are described with emphasis on the understanding of detector behaviour in non‐equilibrium conditions. By way of introduction, practical examples will be provided of non‐equilibrium measurements in the build‐up region, narrow beams, heterogeneous phantoms and IMRT beams. The lecture will provide general guidelines about detector suitability for commercially available devices for the discussed areas of application. Finally, uncertainties of the procedures in a clinical context will be discussed.Educational Objectives:1. To understand the fundamental complications of non‐equilibrium measurements.2. To understand the impact of detector properties on measurement accuracy in non‐equilibrium situations.3. To place measurement uncertainties in non‐equilibrium conditions in a clinical perspective.

SU‐FF‐T‐124: Clinical Evaluation of the Performance of a Fuzzy Logic Guided Parameter Optimization for Inverse Treatment Planning

Purpose: To evaluate the effectiveness of a Fuzzy Logic guided parameter optimization method for inverse treatment planning, in comparison with the results achieved by routine trial‐and‐error method. Method and Materials: The optimization algorithm was developed and integrated into a commercial planning system (Varian Eclipse). 10 prostate IMRT cases previously planned and approved by experienced planners were re‐optimized using this automated method with the same beam geometry. The original dose‐volume histogram (DVH) constraints were used as the initial parameter setup of the automated method. For each organ, the output dose was evaluated based on the percentage of dose received by a specific percentage of volume. The average dose difference between the automated and manual plans was calculated over a set of specified percentage volumes (99%, 80%, 60%, 40%, 20%, 10%, 5%, 1%). In addition, an experienced clinical physicist evaluated the acceptability of the plans generated by the automated method in terms of isodose distributions and DVHs. Results: Adoption of the automated method achieved both a comparable coverage of the planning target volume (PTV) and a substantial dose sparing of organs at risk (OARs). The mean dose was reduced by 30% for bladder, and 25% for rectum. There were few hot spots observed on OARs due to the overemphasis of PTV dose coverage. Conclusion: Preliminary results show that the automated parameter optimization method results in a significant dose reduction of OARs while maintaining a comparable PTV dose coverage. The automated method is able to relieve the burden of routine trial‐and‐error procedures done by planners, and has the potential to improve the resulting plan. However, minor manual intervention is still necessary to incorporate certain case‐specific information, which is beyond the capability of the automated method. This study is partially supported by a research grant from Varian Medical Systems.

AAPM Task Group 103 report on peer review in clinical radiation oncology physics.

This report provides guidelines for a peer review process between two clinical radiation oncology physicists. While the Task Group's work was primarily focused on ensuring timely and productive independent reviews for physicists in solo practice, these guidelines may also be appropriate for physicists in a group setting, particularly when dispersed over multiple separate clinic locations. To ensure that such reviews enable a collegial exchange of professional ideas and productive critique of the entire clinical physics program, the reviews should not be used as an employee evaluation instrument by the employer. Such use is neither intended nor supported by this Task Group. Detailed guidelines are presented on the minimum content of such reviews, as well as a recommended format for reporting the findings of a review. In consideration of the full schedules faced by most clinical physicists, the process outlined herein was designed to be completed in one working day.PACS numbers: 87.53.Xd, 87.90.+y

TH-B-T-6E-01: Monte Carlo Applications in Conformal, IMRT and 4D Clinical Treatment Planning: Pitfalls and Triumphs

Due to its ability to accurately model dose distributions for arbitrarily complex treatment delivery scenarios and patient geometries, it is highly probable that over the next few years the use of Monte Carlo in routine clinical planning will become substantially more widespread. Building on the discussion of the role of Monte Carlo in treatment head simulation (from the first course), this second Monte Carlo course will focus on patient planning applications. The goal of the course is to familiarize clinical medical physicists with the use of Monte Carlo in treatment planning, including advanced treatment techniques such as IMRT and motion compensated 4D treatment, and to discuss how Monte Carlo based planning differs from conventional algorithm based planning. We will demonstrate the utility of Monte Carlo with respect to improved dose calculation accuracy (versus conventional algorithms) in heterogeneous patient tissues, and illustrate how a properly benchmarked Monte Carlo system can play a unique role in the modeling of complex delivery procedures, such as IMRT. In particular, the ability to effectively model the dosimetric consequences of the detailed the multi‐leaf collimator(MLC) geometry with Monte Carlo will be demonstrated. Finally, we will show how Monte Carlo can be applied to compensate for organ motion in 4D treatment planning without an increase in computation time. In addition to illustrating the role of Monte Carlo in complex treatment planning, an important focus of this course will be to provide guidance to clinical physicists on practical issues associated with the implementation, verification and clinical use of Monte Carlo systems. Educational Objectives: 1. To familiarize clinical physicists with Monte Carlo applications for routine clinical treatment planning. 2. To understand the dosimetric influence of Monte Carlo in different anatomical sites and to become familiar with the potential clinical outcome benefits of Monte Carlo. 3. To understand some of the issues that clinical physicists face in the implementation and experimental verification of Monte Carlotreatment planning systems. 4. To understand the use, benefits and limitations of Monte Carlo for IMRT optimization and QA. 5. To become familiar with the role of Monte Carlo in motion compensated (4D) treatment planning.

SU‐FF‐I‐14: New Approaches to Practical CT Dosimetry

Purpose: To outline the basics of conventional CT radiation dosimetry, to discuss difficulties that new cone‐beam and wide‐area detector geometries present to this conventional dosimetry approach, and to illustrate the practical application of recently proposed dosimetry techniques to both multirow and cone‐beam CT configurations. Method and Materials: Traditional CT radiation dosimetry is reviewed and its limitations in cases in which the radiation field is extended in the axial direction are discussed. Comparison is made between this approach, which is based on the use of the standard 100 mm pencil‐type ion chamber, and a recently proposed technique employing a small “point detector” ion chamber (e.g. an RMI type TDC‐100A with 0.1 ml volume)(RL Dixon, A new look at CT dose measurements: beyond CTDI, Med. Phys. 30, 1272–1280 (2003)). The specific corrections for using the small chamber are demonstrated in the case of full cone‐beam CT performed with rotational angiography equipment (Siemens ARTIS BA neuro‐angiographic room). A complete methodology for performing CT dose measurements with small chambers is presented. Results: Good agreement between the point chamber and pencil chamber methods was demonstrated for conventional CT geometries. Direct measurement in cone‐beam geometry is not possible with the pencil chamber, but can be performed with the point chamber. The estimated patient doses for conventional CTA were compared to those delivered by rotational angiographic equipment performing cone‐beam acquisitions and found to be larger by a factor of between 8 and 25, depending on the specific protocol employed. Conclusion: Modern CT equipment employs geometries that make conventional CT dosimetry inapplicable. The clinical physicist should be aware of this and of the necessity for developing new methods to characterize the radiation dose delivered to the patient.

MO-E-T-6C-01: IMRT for Head and Neck Cancer

Clinical physicists have gained considerable experience with IMRTtreatment planning over the past several years. The details of IMRT planning can vary significantly from site to site. The purpose of this presentation is to discuss key issues in IMRTtreatment planning for head and neck cancers. Our main focus will be on details related to the planning process such as, immbolization, imaging,treatment planning, and plan evaluation. The conformal nature of IMRTdose distributions requires additional consideration on the degree of immbolization and expected reproducibility of setup. Custom neck molds, masking systems and additional shoulder constraints are required to maximize reproducibility of the head, chin, and clavicals (supraclavicular nodes). Even with these constraints, daily variability can be expected and the treatment plan should account for those effects. Target and normal tissue segmentation are very important in the planning process and must be considered in detail by the physicist. Various imaging modalities are frequently used. Contrast enhanced CT and MRI‐CT fusion is useful for primary tumor segmentation. Fused 18FDG PET‐CT images can be used to identify positive neck nodes but lack anatomic definition and are not always useful for defining the primary tumor. Before treatment planning begins, a quick but pertinent conversation with the treating physician is necessary to clearly understand the dose/volume tolerances of normal tissues and other patient‐specific issues (e.g., previous treatment, chemotherapy, or already compromised tissues). This dialogue with the physician helps to limit the iterations of optimization and dose evaluation to efficiently arrive at the best IMRT plan. Once treatment planning begins there are many more techniques at the physicist's disposal to develop the best treatment plan compared to conventional planning. Each of these will be discussed. Evaluating IMRT plans is a determination in tradeoffs. An important principle regarding target coverage is the trade‐off between dose conformity and dose heterogeneity across the target. If the plan emphasis is conformity to the target, then one should accept increased dose heterogeneity and vice versa. It is absolutely essential to be realistic in the expectations of IMRT and be prepared to accept some dose to critical structures (but keeping them below tolerance) in order to get better target coverage than a conventional plan would provide. Detailed slice‐by‐slice evaluation of isodose coverage for the location of the hot and cold spots is essential during plan evaluation. Before starting treatment, a set‐up verification step is typically helpful, during which the immobilization system and isocenter location are checked. Orthogonal DRR images of the isocenter(s) location can be reproduced by simulator images for better visualization of bony landmarks. This step may take on a greater importance as kV imaging techniques become more prevalent in the treatment room. For on treatment set‐up verification, utilizing digital images and associated software tools can help to accurately identify isocenter translations and patient rotations (head or shoulder tilt). Educational Objectives: 1. Understand issues related to patient immobilization. 2. Identify normal tissues and know their dose/volume constraints. 3. Describe several planning techniques to achieve the best dose distribution.

Determination of 137Cs dosimetry parameters according to the AAPM TG-43 formalism.

Traditional treatment planning systems calculate dose distributions around 137Cs intracavitary sources by interpolating stored dose rate tables or by Sievert-type integrals. Some of the recently introduced planning systems, such as the Varian BrachyVision and Eclipse (Varian Medical Systems, Palo Alto, CA), have discontinued the use of tables and have implemented instead the AAPM TG-43 formalism as a brachytherapy dosimetry calculation algorithm. In this work we present the dosimetry parameters for 137Cs intracavitary sources as determined according to the TG-43 formalism. With the availability of the TG-43 parameters, the commissioning of a 137Cs source in any current brachytherapy planning system is a straightforward task for a clinical physicist.

The future will not need clinical therapy physicists.

The future will not need clinical therapy physicists.

Entrance dose measurements for in-vivo diode dosimetry: Comparison of correction factors for two types of commercial silicon diode detectors

Silicon diode dosimeters have been used routinely for in-vivo dosimetry. Despite their popularity, an appropriate implementation of an in-vivo dosimetry program using diode detectors remains a challenge for clinical physicists. One common approach is to relate the diode readout to the entrance dose, that is, dose to the reference depth of maximum dose such as for the field. Various correction factors are needed in order to properly infer the entrance dose from the diode readout, depending on field sizes, target-to-surface distances (TSD), and accessories (such as wedges and compensate filters). In some clinical practices, however, no correction factor is used. In this case, a diode-dosimeter-based in-vivo dosimetry program may not serve the purpose effectively; that is, to provide an overall check of the dosimetry procedure. In this paper, we provide a formula to relate the diode readout to the entrance dose. Correction factors for TSD, field size, and wedges used in this formula are also clearly defined. Two types of commercial diode detectors, ISORAD (n-type) and the newly available QED (p-type) (Sun Nuclear Corporation), are studied. We compared correction factors for TSDs, field sizes, and wedges. Our results are consistent with the theory of radiation damage of silicon diodes. Radiation damage has been shown to be more serious for n-type than for p-type detectors. In general, both types of diode dosimeters require correction factors depending on beam energy, TSD, field size, and wedge. The magnitudes of corrections for QED (p-type) diodes are smaller than ISORAD detectors. PACS number(s): 87.66.–a, 87.52.–g

Entrance dose measurements for in‐vivo diode dosimetry: Comparison of correction factors for two types of commercial silicon diode detectors

Silicon diode dosimeters have been used routinely for in‐vivo dosimetry. Despite their popularity, an appropriate implementation of an in‐vivo dosimetry program using diode detectors remains a challenge for clinical physicists. One common approach is to relate the diode readout to the entrance dose, that is, dose to the reference depth of maximum dose such as dmax for the 10×10 cm2 field. Various correction factors are needed in order to properly infer the entrance dose from the diode readout, depending on field sizes, target‐to‐surface distances (TSD), and accessories (such as wedges and compensate filters). In some clinical practices, however, no correction factor is used. In this case, a diode‐dosimeter‐based in‐vivo dosimetry program may not serve the purpose effectively; that is, to provide an overall check of the dosimetry procedure. In this paper, we provide a formula to relate the diode readout to the entrance dose. Correction factors for TSD, field size, and wedges used in this formula are also clearly defined. Two types of commercial diode detectors, ISORAD (n‐type) and the newly available QED (p‐type) (Sun Nuclear Corporation), are studied. We compared correction factors for TSDs, field sizes, and wedges. Our results are consistent with the theory of radiation damage of silicon diodes. Radiation damage has been shown to be more serious for n‐type than for p‐type detectors. In general, both types of diode dosimeters require correction factors depending on beam energy, TSD, field size, and wedge. The magnitudes of corrections for QED (p‐type) diodes are smaller than ISORAD detectors.PACS number(s): 87.66.–a, 87.52.–g

Last ICRU recommendations for the prescription, recording and reporting of external bean therapy

Due to the evolution of radiotherapy techniques and equipment, in 1993 the ICRU decided to modify the guidelines that had been published in the ICRU report 29 (1978) in regard to photon beam therapy and to insert them in Report number 50 (1993). Changes that were introduced mainly concerned the prescription, recording and reporting of external beam therapy with photons. While awaiting for the upcoming publication of the report focusing on external beam therapy with electrons, the ICRU decided to publish a supplement to Report 50, as new insights had been gained after discussions with the Nordic Association of Clinical Physicists (NACP). This supplement includes the following: more accurate definitions of the margins allowing the planned target volume to be derived from the clinical target volume, the internal target volume, the expected volume of organs at-risk and the conformity index. All three points will be included in the report focusing on external beam therapy with electrons as well as extensive discussions relating to the implementation of these new recommendations.