SU-E-J-187: Evaluation of the Effects of Dose on 4DCT-Calculated Lung Ventilation

PURPOSE

To investigate the effects of radiation therapy (RT) treatment dose on ventilation.

METHODS

Optical flow deformable image registration of the normal end-expiration and end-inspiration phases of 4DCT images was used to correlate the voxels between the two phases. 4DCT sets from before and after RT were used to derive ventilation for 3 SBRT lung patients. Planning dose and normalized ventilation were superimposed on the CT volume resulting in each voxel having a volume, a normalized ventilation and a dose. From these values a 3D dose-ventilation-volume surfaces was created. The surface was integrated over dose to reduce the 3D surface to a 2D histogram that is easier to interpret.

RESULTS

For lung tissue regions receiving more than 20 Gy, a decrease in ventilation was observed in the three patients. Patient A (time between scans, T=26 months) showed an increase in ventilation for regions receiving a dose smaller than 20 Gy, whereas patients B (T=3 months) and C (T=6 months) did not show any change for these regions. Mean ventilation within the 20 Gy region for patient A was 0.57 before RT and 0.51 after RT; and 0.54 before and 0.48 after RT for the 30 Gy region. Mean ventilation for the 20 Gy region for patient B was 0.49 before RT and 0.47 after RT, for the 30 Gy region mean ventilation was 0.49 Gy before and 0.45 Gy after RT. Patient C's mean ventilation for the 20 Gy region was 0.54 before RT and 0.50 after RT, for the 30 Gy region mean ventilation was 0.54 before RT and 0.49 after RT.

CONCLUSIONS

Ventilation before and after radiation therapy can be measured using 4DCT and deformable image registration techniques. In a preliminary application of this approach for three patients, changes in ventilation were observed with a weak correlation between ventilation change and dose. Partially supported by a grant from Varian Medical Systems.

SU-E-I-32: Sterile Radiation Reduction Gloves May Be Contraindicated in Fluoroscopically Guided Interventions

PURPOSE

Sterile radiation reduction gloves have been widely used in the past decade to provide modest decreases in operator hand dose when the hands are placed in the field of view (FOV). While multiple publications have quantified the potential dose reduction from the use of such gloves, possible effects on the patient have not yet been assessed. The aim of this study was to determine if radiation reduction gloves can Result in a significant increase in patient dose and increased risk of radiation induced skin injury when used in interventional radiology.

METHODS

The effect of radiation reduction gloves when used in the FOV was determined by measurement of patient entrance exposure rate (EER) for a variety of patient sizes and varying operating and magnification modes. EERs were measured with no glove in the FOV, with one glove and, to replicate the actions of many dose-conscious radiologists, with double gloves in the FOV.

RESULTS

Compared to an ungloved hand, the use of a single radiation reduction glove near the center of the FOV results in a 2-fold average increase in patient EER. The use of double radiation reduction gloves results in a 3-fold average increase in EER. In both cases, this increase was only weakly dependent on the size of the patient and on the operating and magnification modes used. In fact, patient thicknesses ranging from 6-14 inches and operating modes ranging from low-dose fluoroscopy to DSA produced less than a 20% deviation from the increases in EER quoted above.

CONCLUSIONS

When used in the FOV, radiation reduction gloves can substantially increase patient EER. This increase in patient dose, when compared with the relatively small published reduction in extremity dose provided to the operator, may make their use contraindicated in cases where radiation induced skin injury is a possible risk.

SU-E-T-08: Simple Governing Equations for Tumor Growth

PURPOSE

To derive a set of simple differential equations, which can represent temporal growth of typical tumors, by taking into account the effects of the tumor microenvironment on cell proliferation.

METHODS

Cause-effect relationships between cell proliferation and nutrients contained in blood stream, which included oxygen and glucose, were modeled. By formulating a set of rate equations and simplifying those, we finally obtained two differential equations. One equation represents the change of the tumor mass and included time-varying growth rate, which was a solution of another equation relating the growth rate with the blood volume in the tumor. The set of differential equations were numerically solved by varying a parameter, kappa, which represented the growth rate of the blood volume relative to the tumor mass.

RESULTS

Through numerical experiments we showed that the tumor volume increased exponentially if the blood volume increased at the same rate as the tumor. However, the blood volume did not increase rapidly enough as the tumor grew, the tumor showed the saturation in the growth when the tumor grew by 1000-fold. Such a retardation of tumor growth was experimentally observed and the function representing the growth curve is called as Gompertz equation. One of solutions also showed that the tumor stopped growing when the blood supply was shut off (or kappa = 0).

CONCLUSIONS

A solution of simple differential equations derived in this study could reproduce the tumor growth which can be represented by the well known Gompertz equation. Using these equations we were able to theoretically show that the saturation of tumor growth observed often for larger tumors could be explained by a relative lack of blood supply which leads to a decrease in the cell proliferation rate. In a future study the effects of radiation on the tumor growth will be included in the model.

MO-F-BRCD-02: SBRT (Part 2): Physics and Quality Assurance Updates

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 deliver an ablative dose to the target while minimizing the effects of radiation on the surrounding normal tissue. The major advantage of SBRT is the greater biologically effective dose to the target than that permitted by less conformal, fractionated techniques. In this presentation the established recommendations for quality assurance and safety of SBRT from ACR, ASTRO, and AAPM will be reviewed. The recommendations include establishing an SBRT clinic, equipment and imaging considerations, overview of staffing and personnel qualifications, treatment planning considerations, training, acceptance and commissioning practices, and use of safety checklists. Additionally, a Failure Mode and Effect Analysis (FMEA) for Stereotactic Body Radiation Therapy Delivery is presented. References: 1. Timothy D. Solberg PhD, James M. Balter PhD, Stanley H. Benedict PhD, Benedick A. Fraass PhD, Brian Kavanagh MD, Curtis Miyamoto MD, Todd Pawlicki PhD, Louis Potters MD, Yoshiya Yamada MD, "Quality and safety considerations in stereotactic radiosurgery and stereotactic body radiation therapy" Practical Radiation Oncology (2011)2. Benedict SH, Yenice KM, Followill D, et al., "Stereotactic Body Radiation Therapy: The Report of AAPM Task Group 101" Med Phys. 2010;37:4078- 41013. Potters L, Kavanagh B, Galvin JM, et al. American Society for Therapeutic Radiology and Oncology (ASTRO) and American College of Radiology (ACR) practice guideline for the performance of stereotactic body radiation therapy. Int J Radiat Oncol Biol Phys. 2010;76:326-3324. Julian R. Perks PhD, Sinisa Stanic MD, Robin L Stern PhD, Barbara Henk RN MSN, Marsha S Nelson RN MBA, Rick D Harse RTT, Mathew Mathai BS CMD, James A Purdy PhD, Richard K Valicenti MD MA, Allan D Siefkin MD and Allen M Chen MD, "Failure Mode and Effect Analysis for Stereotactic Body Radiation Therapy Delivery" Int J Radiat Oncol Biol Phys. 2012 (in press) Learning Objectives: 1. Review and understand the ASTRO Recommendations for QA and Safety with SBRT 2. Review and understand the AAPM Task Group Recommendations for SBRT 3. Review and understand a FEMA Analysis of SBRT.

SU-E-J-191: A Multivariate Framework for N-Tissue Classification in Treatment Assessment of Glioblastomas

PURPOSE

Glioblastoma is the most common primary brain tumor in adults and is rapidly fatal. Treatment monitoring of these patients has increased awareness that many patients have new areas of contrast enhancement without progressive clinical signs and symptoms. Although the enhancing areas mimic tumor progression, the lesions result from treatment effects and subsequently stabilize or improve without further treatment and are not correlated with poorer outcomes. This phenomenon has been termed pseudoprogression and is hypothesized to occur secondarily to edema and vessel permeability in the tumor area as a result of the combined effects of radiation and chemotherapy. Since the new enhancing lesions of pseudoprogression are indistinguishable from true disease progression, there is a need for a predictive model to distinguish the two phenomena.

METHOD

We developed a classification algorithm that combines perfusion and diffusion MRI imaging to effectively partition the cases as one exhibiting true or pseudo progression based on a vector of features containing T1, rCBV and ADC imaging. The multi-sequence classification algorithm uses an expectation maximization (EM) algorithm that learns from training cases with known clinical outcome to assigns each voxel to a type of tissue.

RESULTS

A training set of 20 where the clinical outcome is known from biopsy or from long-term follow-up was used by EM algorithm to model typical imaging values within tissue of pseudo, tumor, edema, necrosis, vessels or brain anatomy to construct a database of expected values for each tissue type. When presented with a new case, the algorithm automatically classifies voxels by their geographical proximities and Mahalanobis distance to the pre-sampled values.

CONCLUSION

Usage of advanced classification techniques allows automated labeling of voxels into normal, pseudoprogression or tumoral tissue types. The technique allows for early detection of pseudo progression to spare patients from unnecessary surgery or toxic chemotherapy.