R Jeraj

A Randomized Trial of Bevacizumab for Newly Diagnosed Glioblastoma

BACKGROUND Concurrent treatment with temozolomide and radiotherapy followed by maintenance temozolomide is the standard of care for patients with newly diagnosed glioblastoma. Bevacizumab, a humanized monoclonal antibody against vascular endothelial growth factor A, is currently approved for recurrent glioblastoma. Whether the addition of bevacizumab would improve survival among patients with newly diagnosed glioblastoma is not known. METHODS In this randomized, double-blind, placebo-controlled trial, we treated adults who had centrally confirmed glioblastoma with radiotherapy (60 Gy) and daily temozolomide. Treatment with bevacizumab or placebo began during week 4 of radiotherapy and was continued for up to 12 cycles of maintenance chemotherapy. At disease progression, the assigned treatment was revealed, and bevacizumab therapy could be initiated or continued. The trial was designed to detect a 25% reduction in the risk of death and a 30% reduction in the risk of progression or death, the two coprimary end points, with the addition of bevacizumab. RESULTS A total of 978 patients were registered, and 637 underwent randomization. There was no significant difference in the duration of overall survival between the bevacizumab group and the placebo group (median, 15.7 and 16.1 months, respectively; hazard ratio for death in the bevacizumab group, 1.13). Progression-free survival was longer in the bevacizumab group (10.7 months vs. 7.3 months; hazard ratio for progression or death, 0.79). There were modest increases in rates of hypertension, thromboembolic events, intestinal perforation, and neutropenia in the bevacizumab group. Over time, an increased symptom burden, a worse quality of life, and a decline in neurocognitive function were more frequent in the bevacizumab group. CONCLUSIONS First-line use of bevacizumab did not improve overall survival in patients with newly diagnosed glioblastoma. Progression-free survival was prolonged but did not reach the prespecified improvement target. (Funded by the National Cancer Institute; ClinicalTrials.gov number, NCT00884741.).

Image guidance for precise conformal radiotherapy

PURPOSE To review the state of the art in image-guided precision conformal radiotherapy and to describe how helical tomotherapy compares with the image-guided practices being developed for conventional radiotherapy. MATERIALS AND METHODS Image guidance is beginning to be the fundamental basis for radiotherapy planning, delivery, and verification. Radiotherapy planning requires more precision in the extension and localization of disease. When greater precision is not possible, conformal avoidance methodology may be indicated whereby the margin of disease extension is generous, except where sensitive normal tissues exist. Radiotherapy delivery requires better precision in the definition of treatment volume, on a daily basis if necessary. Helical tomotherapy has been designed to use CT imaging technology to plan, deliver, and verify that the delivery has been carried out as planned. The image-guided processes of helical tomotherapy that enable this goal are described. RESULTS Examples of the results of helical tomotherapy processes for image-guided intensity-modulated radiotherapy are presented. These processes include megavoltage CT acquisition, automated segmentation of CT images, dose reconstruction using the CT image set, deformable registration of CT images, and reoptimization. CONCLUSIONS Image-guided precision conformal radiotherapy can be used as a tool to treat the tumor yet spare critical structures. Helical tomotherapy has been designed from the ground up as an integrated image-guided intensity-modulated radiotherapy system and allows new verification processes based on megavoltage CT images to be implemented.

Radiation characteristics of helical tomotherapy

Helical tomotherapy is a dedicated intensity modulated radiation therapy (IMRT) system with on-board imaging capability (MVCT) and therefore differs from conventional treatment units. Different design goals resulted in some distinctive radiation field characteristics. The most significant differences in the design are the lack of flattening filter, increased shielding of the collimators, treatment and imaging operation modes and narrow fan beam delivery. Radiation characteristics of the helical tomotherapy system, sensitivity studies of various incident electron beam parameters and radiation safety analyses are presented here. It was determined that the photon beam energy spectrum of helical tomotherapy is similar to that of more conventional radiation treatment units. The two operational modes of the system result in different nominal energies of the incident electron beam with approximately 6 MeV and 3.5 MeV in the treatment and imaging modes, respectively. The off-axis mean energy dependence is much lower than in conventional radiotherapy units with less than 5% variation across the field, which is the consequence of the absent flattening filter. For the same reason the transverse profile exhibits the characteristic conical shape resulting in a 2-fold increase of the beam intensity in the center. The radiation leakage outside the field was found to be negligible at less than 0.05% because of the increased shielding of the collimators. At this level the in-field scattering is a dominant source of the radiation outside the field and thus a narrow field treatment does not result in the increased leakage. The sensitivity studies showed increased sensitivity on the incident electron position because of the narrow fan beam delivery and high sensitivity on the incident electron energy, as common to other treatment systems. All in all, it was determined that helical tomotherapy is a system with some unique radiation characteristics, which have been to a large extent optimized for intensity modulated delivery.

Variability of textural features in FDG PET images due to different acquisition modes and reconstruction parameters

Abstract Background. Characterization of textural features (spatial distributions of image intensity levels) has been considered as a tool for automatic tumor segmentation. The purpose of this work is to study the variability of the textural features in PET images due to different acquisition modes and reconstruction parameters. Material and methods. Twenty patients with solid tumors underwent PET/CT scans on a GE Discovery VCT scanner, 45–60 minutes post-injection of 10 mCi of [18F]FDG. Scans were acquired in both 2D and 3D modes. For each acquisition the raw PET data was reconstructed using five different reconstruction parameters. Lesions were segmented on a default image using the threshold of 40% of maximum SUV. Fifty different texture features were calculated inside the tumors. The range of variations of the features were calculated with respect to the average value. Results. Fifty textural features were classified based on the range of variation in three categories: small, intermediate and large variability. Features with small variability (range ≤ 5%) were entropy-first order, energy, maximal correlation coefficient (second order feature) and low-gray level run emphasis (high-order feature). The features with intermediate variability (10% ≤ range ≤ 25%) were entropy-GLCM, sum entropy, high gray level run emphsis, gray level non-uniformity, small number emphasis, and entropy-NGL. Forty remaining features presented large variations (range > 30%). Conclusion. Textural features such as entropy-first order, energy, maximal correlation coefficient, and low-gray level run emphasis exhibited small variations due to different acquisition modes and reconstruction parameters. Features with low level of variations are better candidates for reproducible tumor segmentation. Even though features such as contrast-NGTD, coarseness, homogeneity, and busyness have been previously used, our data indicated that these features presented large variations, therefore they could not be considered as a good candidates for tumor segmentation.

Re-optimization in adaptive radiotherapy

In routine clinical practice, radiotherapy treatment planning is performed based on the patient CT images obtained during the patient setup procedure. However, the actual delivered dose to the patient might be different from the planned dose because of various reasons such as patient motion. Under such situations, it is desirable to modify the original treatment plan in order to partially remedy the dose delivery errors in the subsequent dose delivery process. Such modification can be implemented by modifying the original treatment plan using re-optimization. In this work, issues such as the re-optimization dose prescription, optimization constraints in re-optimization, re-optimization in multiple fractionation schemes and re-optimization procedure with generalized dose-based objective functions were investigated and corresponding mathematical schemes proposed. The derived results were applied to a clinical case study in which it was shown that the proposed re-optimization method is able to remedy the cold spots in tumour while delivering low dose to normal structures. Thus the potential effectiveness of the method was demonstrated.

Comparisons between MCNP, EGS4 and experiment for clinical electron beams

Understanding the limitations of Monte Carlo codes is essential in order to avoid systematic errors in simulations, and to suggest further improvement of the codes. MCNP and EGS4, Monte Carlo codes commonly used in medical physics, were compared and evaluated against electron depth dose data and experimental backscatter results obtained using clinical radiotherapy beams. Different physical models and algorithms used in the codes give significantly different depth dose curves and electron backscattering factors. The default version of MCNP calculates electron depth dose curves which are too penetrating. The MCNP results agree better with experiment if the ITS-style energy-indexing algorithm is used. EGS4 underpredicts electron backscattering for high-Z materials. The results slightly improve if optimal PRESTA-I parameters are used. MCNP simulates backscattering well even for high-Z materials. To conclude the comparison, a timing study was performed. EGS4 is generally faster than MCNP and use of a large number of scoring voxels dramatically slows down the MCNP calculation. However, use of a large number of geometry voxels in MCNP only slightly affects the speed of the calculation.

The effect of dose calculation accuracy on inverse treatment planning

The effect of dose calculation accuracy during inverse treatment planning for intensity modulated radiotherapy (IMRT) was studied in this work. Three dose calculation methods were compared: Monte Carlo, superposition and pencil beam. These algorithms were used to calculate beamlets. which were subsequently used by a simulated annealing algorithm to determine beamlet weights which comprised the optimal solution to the objective function. Three different cases (lung, prostate and head and neck) were investigated and several different objective functions were tested for their effect on inverse treatment planning. It is shown that the use of inaccurate dose calculation introduces two errors in a treatment plan, a systematic error and a convergence error. The systematic error is present because of the inaccuracy of the dose calculation algorithm. The convergence error appears because the optimal intensity distribution for inaccurate beamlets differs from the optimal solution for the accurate beamlets. While the systematic error for superposition was found to be approximately 1% of Dmax in the tumour and slightly larger outside, the error for the pencil beam method is typically approximately 5% of Dmax and is rather insensitive to the given objectives. On the other hand, the convergence error was found to be very sensitive to the objective function, is only slightly correlated to the systematic error and should be determined for each case individually. Our results suggest that because of the large systematic and convergence errors, inverse treatment planning systems based on pencil beam algorithms alone should be upgraded either to superposition or Monte Carlo based dose calculations.

Impact of the Definition of Peak Standardized Uptake Value on Quantification of Treatment Response

PET-based treatment response assessment typically measures the change in maximum standardized uptake value (SUVmax), which is adversely affected by noise. Peak SUV (SUVpeak) has been recommended as a more robust alternative, but its associated region of interest (ROIpeak) is not uniquely defined. We investigated the impact of different ROIpeak definitions on quantification of SUVpeak and tumor response. Methods: Seventeen patients with solid malignancies were treated with a multitargeted receptor tyrosine kinase inhibitor resulting in a variety of responses. Using the cellular proliferation marker 3′-deoxy-3′-18F-fluorothymidine (18F-FLT), whole-body PET/CT scans were acquired at baseline and during treatment. 18F-FLT–avid lesions (∼2/patient) were segmented on PET images, and tumor response was assessed via the relative change in SUVpeak. For each tumor, 24 different SUVpeaks were determined by changing ROIpeak shape (circles vs. spheres), size (7.5–20 mm), and location (centered on SUVmax vs. placed in highest-uptake region), encompassing different definitions from the literature. Within each tumor, variations in the 24 SUVpeaks and tumor responses were measured using coefficient of variation (CV), standardized deviation (SD), and range. For each ROIpeak definition, a population average SUVpeak and tumor response were determined over all tumors. Results: A substantial variation in both SUVpeak and tumor response resulted from changing the ROIpeak definition. The variable ROIpeak definition led to an intratumor SUVpeak variation ranging from 49% above to 46% below the mean (CV, 17%) and an intratumor SUVpeak response variation ranging from 49% above to 35% below the mean (SD, 9%). The variable ROIpeak definition led to a population average SUVpeak variation ranging from 24% above to 28% below the mean (CV, 14%) and a population average SUVpeak response variation ranging from only 3% above to 3% below the mean (SD, 2%). The size of ROIpeak caused more variation in intratumor response than did the location or shape of ROIpeak. Population average tumor response was independent of size, shape, and location of ROIpeak. Conclusion: Quantification of individual tumor response using SUVpeak is highly sensitive to the ROIpeak definition, which can significantly affect the use of SUVpeak for assessment of treatment response. Clinical trials are necessary to compare the efficacy of SUVpeak and SUVmax for quantification of response to therapy.

Treatment plan optimization incorporating respiratory motion.

Similar to conventional conformal radiotherapy, during lung tomotherapy, a motion margin has to be set for respiratory motion. Consequently, large volume of normal tissue is irradiated by intensive radiation. To solve this problem, we have developed a new motion mitigation method by incorporating target motion into treatment optimization. In this method, the delivery-breathing correlation is determined prior to treatment plan optimization. Beamlets are calculated by using the CT images at the corresponding breathing phases from a dynamic (four-dimensional) image sequence. With the displacement vector fields at different breathing phases, a set of deformed beamlets is obtained by mapping the dose to the primary phase. Optimization incorporating motion is then performed by using the deformed beamlets obtained by dose mapping. During treatment delivery, the same breathing-delivery correlation can be reproduced by instructing the patient to breathe following a visually displayed guiding cycle. This method was tested using a computer-simulated deformable phantom and a real lung case. Results show that treatment optimization incorporating motion achieved similar high dose conformality on a mobile target compared with static delivery. The residual motion effects due to imperfect breathing tracking were also analyzed.

RTOG 0825: Phase III double-blind placebo-controlled trial evaluating bevacizumab (Bev) in patients (Pts) with newly diagnosed glioblastoma (GBM).

1 Background: Chemoradiation (CRT) with temozolomide (TMZ/RT→TMZ) is the standard of care for newly diagnosed GBM. This trial determined if the addition of Bev to standard CRT improves survival (OS) or progression-free survival (PFS) in newly diagnosed GBM. METHODS This phase III trial was conducted by the RTOG, NCCTG, and ECOG. Neurologically stable pts > 18 yrs with KPS ≥ 60, and > 1cm3 tumor tissue block, were randomized to Arm 1: standard CRT + placebo or Arm 2: standard CRT plus Bev (10 mg/kg iv q 2wks). Experimental treatment began at wk 4 of radiation then thru 6-12 cycles of maintenance chemotherapy. Protocol specified co-primary endpoints were OS and PFS, with significance levels of .023 and .002, respectively. At progression, treatment was unblinded and pts allowed to crossover or continue Bev. Symptom, QOL and neurocognitive (NCF) testing was performed in the majority of pts. Secondary analyses evaluated impact of MGMT methylation (meth) and prognostic 9 gene signature status. RESULTS From 978 registered pts, 637 were randomized. Inadequate tissue (n=105) and blood on imaging (n=40) were key reasons for non-randomization. No difference was found between arms for OS (median 16.1 vs. 15.7 mo, p = 0.11). PFS was extended for Arm 2 (7.3 vs. 10.7 mo, p = 0.004). Pts with MGMT meth had superior OS (23.2 vs. 14.3 mo, p < 0.001) and PFS (14.1 vs. 8.2 mo, p < 0.001). Neither the 9 gene signature nor MGMT predicted selective benefit for Bev treatment, but best prognosis pts (MGMT meth, favorable 9-gene), had a worse survival trend with Bev (15.7 vs 25 mo p = 0.08). To date, 128 pts were unblinded on Arm 1 (salvage Bev in 86) and 87 pts on Arm 2 (continued Bev in 39). Increased grade ≥ 3 toxicity was seen with Bev, mostly neutropenia, hypertension, and DVT/PE. CONCLUSIONS The addition of Bev for newly diagnosed GBM did not improve OS, did improve PFS but did not reach the significance criterion. MGMT and 9 gene profile did not identify selective benefit, but risk subset results suggested strongly against the upfront use of Bev in the best prognosis pts. Full interpretation of the PFS results incorporating symptom burden, QOL, and NCF is ongoing. Support: NCI U10 CA 21661, U10 CA37422, and Genentech. CLINICAL TRIAL INFORMATION NCT00884741.