Volume 34, Issue 6, June 2007
Index of content:
- Therapy Continuing Education Course: Ballroom B
CE‐Therapy: Stereotactic Body Radiation Therapy / SBRT
34(2007); http://dx.doi.org/10.1118/1.2761469View Description Hide Description
Stereotactic body radiation therapy(SBRT) has emerged over the past decade as a safe, efficient, and effective method for eradicating discreet extracranial tumor foci. While the most thoroughly studied indication to date is in the management of early stage lungcancer,SBRT can also be used in the treatment of a variety of other primary cancers as well as certain metastatic malignancies. In this portion of the educational session, SBRT will be defined from an operational perspective, and the clinical rationale for the applicaton of SBRT in the most common indications will be reviewed. Example cases will be shown. Additionally, key published clinical outcomes data (tumor control and toxicity rates) will be presented, with interpretations offered regarding the radiobiological implications.
1. To present the operational definition of SBRT.
2. To present the clinical rationale for the application of SBRT in the most commonly used indications.
3. To review reported clinical outcomes data for SBRT, with discussion of the practical radiobiological ramifications.
WE‐A‐BRB‐02: Stereotactic Body Radiation Therapy: (2) Technical Issues for Clinical Implementation of An SBRT Program34(2007); http://dx.doi.org/10.1118/1.2761470View Description Hide Description
The technical advantage of stereotactic body radiation therapy(SBRT) is based upon the ability to deliver a hypofractionated course of heterogeneous dose to a well‐defined volume with a rapid fall‐off of dose outside the treatment volume. The overall goal is to minimize the direct effects of radiation on the surrounding normal tissue while delivering a dose biologically equivalent (or greater) to several weeks of conventionally fractionated radiation therapy to the treatment volume. Over 4000 publications spanning several decades have affirmed the clinical usefulness of SRT, including hundreds of articles on SBRT in the last decade. The intent of SBRTtreatment has been to deliver noninvasive tumor‐ablative doses to sharply demarcated lesions so that clinical outcomes comparable to surgery could be achieved without surgical complications. The majority of published clinical data describes the treatment of lung,liver and spinal tumors. The radiobiology of short‐course, high‐dose‐per‐fraction regimens suggests that utilizing SBRT, with significant local dose escalation even to curative doses, is feasible. The number of fractions and total doses currently in clinical use varies widely in the literature, typically ranging from 60 Gy delivered in 10 fractions to 30 Gy delivered in a single fraction.
To present the technical issues for clinical implementation of SBRT as reported in the AAPM Task Group No. 101 on Stereotactic Body Radiation Therapy. Including the following topics:
1. Equipment and space considerations.
2. Time and personnel considerations.
3. Acceptance and commissioning requirements.
4. Localization devices.
5. Treatment‐planning systems.
6. Treatment‐delivery and auxiliary systems.
7. Image guidance, patient alignment and verification systems.
8. Quality assurance procedures.
CE‐Therapy: Patient Motion: Adaptive RT
34(2007); http://dx.doi.org/10.1118/1.2761483View Description Hide Description
Patient anatomical variation during the radiotherapy course can be described using a stochastic process. In this process, spatial position of each subvolume in patient organs of interest during the treatment course is represented using a random vector with an intrinsic probability distribution function (pdf). Two main parameters, the mean and the standard deviation, of the pdf have been historically used to characterize patient anatomical variation, the systematic and random variations, during the radiation treatment. It has been demonstrated that treatmentdose distribution in an organ of interest can be evaluated using these two parameters alone, without the full knowledge of organ motion distribution. The approximation is, however, dependent on the size of the motion as well as the number of treatment fractions. It is straightforward to estimate these two parameters if patient anatomical variation process is stationary. In this case, the two parameters are constants or time‐invariance during the treatment course. However, the estimation will be relatively difficult if patient anatomical variation process is non‐stationary.
Patient anatomical variation in radiotherapy can be managed using multiple or 4D image guided or feedback treatment techniques. Among them, adaptive approach is the most effective methodology in utilizing the 4D feedback information. Image guided adaptive radiation therapy is a closed loop treatment process which is designed to include the individual treatment information, such as organdose that has been delivered and/or could be delivered in future, in the treatment evaluation and planning optimization. To include deliveredorgandose in the planning optimization, deformable image registration is necessary. On the other hand, the measured organ variations are used to estimate what may happen in the future treatment. The patient specific information is, then, included in 4D adaptive planning modification or optimization. Based on a pre‐determined control strategy, adaptive planning modification can be performed either offline with signal or multiple modifications, or online. However, selection of control strategy is quite complicated not only depending up on the nature of patient variation process, imaging sampling and estimation methodology, but also the clinical load and practical issues.
The lecture will provide an overview of the model and description of patient anatomical variation process during the radiotherapy. In addition, effect of the variation on treatmentdose, and options of control strategy will be discussed.
1. Understand the characteristics and dynamic model for patient anatomical variation during the course of radiotherapy.
2. Understand the effects of patient anatomical variation on treatmentdose.
3. Understand the options and potentials of control strategy for image guided adaptive radiotherapy.
34(2007); http://dx.doi.org/10.1118/1.2761485View Description Hide Description
Organ motion blurs dose distributions. The blurring can be described in a statistical way by use of a motion probability (density) function (PDF). The motion‐blurred dose distribution is obtained by a convolution of the “sharp” (static case) dose distribution with the motion PDF. This holds true for both inter‐ and intra‐fraction motions. If intra‐fraction motion is present during an IMRT treatment, the dose distribution will also be affected by an “interplay” effect, in addition to the blurring. It has been shown that the interplay effect averages out during the course of a fractionated treatment, and that it is usually negligible after a typical number of fractions. The convolution model relies on the linear superimposition principle, which holds true for dose values but not for the biological effect. This issue has recently been addressed and will be discussed.
Several investigations have now looked at the feasibility of un‐doing the motion blur through the use if intensity‐modulation. In principle it should indeed be possible to de‐convolve the motion PDF from the intensity maps, to compensate for motion effects. This approach has been called 4D optimization or 4D inverse planning. Motion de‐convolution cannot, however, compensate motion effects exactly and it cannot be applied in a naïve straight‐forward way, because that would lead to undeliverable intensity maps with sharp spikes and negative values. The method of choice is rather to include the motion PDF in the IMRToptimization process. It has been shown that this can indeed yield a surprisingly high degree of motion compensation and it can even compete with other motion compensation methods such as gated delivery. However, this is only true if the motion characteristics (the PDF) are known with great precision. If the actually realized motion PDF deviates substantially from the planned PDF, the method becomes less useful and can, in principle, make things worse.
More recently, uncertainties in the knowledge of the motion characteristics have been taken into account by use of robust optimization techniques. With these one can now compensate for motion effects in an approximate way for a large class of motion characteristics. In terms of the sparing of normal structures, the results are in between the use of conventional margins and the idealistic case of perfect motion compensation. The resulting intensity maps exhibit “horns”, which can shave off a few mm from the margins.
1. Understand the concepts of motion blur and PDF.
2. Understand the idea of de‐blurring a dose distribution through “4D” motion optimization.
3. Be able to discuss the relative potential and limitations of 4D motion optimization in comparison with margins and gating.