Measuring Efficiency of Semi-automated Brain Tumor Segmentation by Simulating User Interaction.

Traditionally, radiologists have crudely quantified tumor extent by measuring the longest and shortest dimension by dragging a cursor between opposite boundary points across a single image rather than full segmentation of the volumetric extent. For algorithmic-based volumetric segmentation, the degree of radiologist experiential involvement varies from confirming a fully automated segmentation, to making a single drag on an image to initiate semi-automated segmentation, to making multiple drags and clicks on multiple images during interactive segmentation. An experiment was designed to test an algorithm that allows various levels of interaction. Given the ground-truth of the BraTS training data, which delimits the brain tumors of 285 patients on multi-spectral MR, a computer simulation mimicked the process that a radiologist would follow to perform segmentation with real-time interaction. Clicks and drags were placed only where needed in response to the deviation between real-time segmentation results and assumed radiologist's goal, as provided by the ground-truth. Results of accuracy for various levels of interaction are presented along with estimated elapsed time, in order to measure efficiency. Average total elapsed time, including loading the study through confirming 3D contours, was 46 s.

Opportunities and challenges to utilization of quantitative imaging: Report of the AAPM practical big data workshop.

BACKGROUND: This article is a summary of the quantitative imaging subgroup of the 2017 AAPM Practical Big Data Workshop (PBDW-2017) on progress and challenges in big data applied to cancer treatment and research supplemented by a draft white paper following an American Association of Physicists in Medicine FOREM meeting on Imaging Genomics in 2014. AIMS: The goal of PBDW-2017 was to close the gap between theoretical vision and practical experience with encountering and solving challenges in curating and analyzing data. CONCLUSIONS: Recommendations based on the meetings are summarized.

Fabrication approaches for the creation of physical models from microscopy data.

BACKGROUND: Three-dimensional (3D) printing has become a useful method of fabrication for many clinical applications. It is also a technique that is becoming increasingly accessible, as the price of the necessary tools and supplies decline. One emerging, and unreported, application for 3D printing is to aid in the visualization of 3D imaging data by creating physical models of select structures of interest. METHODS: Presented here are three physical models that were fabricated from three different 3D microscopy datasets. Different methods of fabrication and imaging techniques were used in each case. RESULTS: Each model is presented in detail. This includes the imaging modality used to capture the raw data, the software used to create any computer models and the 3D printing tools used to create each model. Despite the differences in their creation, these examples follow a simple common workflow that is also detailed. CONCLUSIONS: Following these approaches, one can easily make 3D printed models from 3D microscopy datasets utilizing off the shelf commercially available software and hardware.

The sweet spot: FDG and other 2-carbon glucose analogs for multi-modal metabolic imaging of tumor metabolism.

Multi-modal imaging approaches of tumor metabolism that provide improved specificity, physiological relevance and spatial resolution would improve diagnosing of tumors and evaluation of tumor progression. Currently, the molecular probe FDG, glucose fluorinated with (18)F at the 2-carbon, is the primary metabolic approach for clinical diagnostics with PET imaging. However, PET lacks the resolution necessary to yield intratumoral distributions of deoxyglucose, on the cellular level. Multi-modal imaging could elucidate this problem, but requires the development of new glucose analogs that are better suited for other imaging modalities. Several such analogs have been created and are reviewed here. Also reviewed are several multi-modal imaging studies that have been performed that attempt to shed light on the cellular distribution of glucose analogs within tumors. Some of these studies are performed in vitro, while others are performed in vivo, in an animal model. The results from these studies introduce a visualization gap between the in vitro and in vivo studies that, if solved, could enable the early detection of tumors, the high resolution monitoring of tumors during treatment, and the greater accuracy in assessment of different imaging agents.

Automated quantification of aligned collagen for human breast carcinoma prognosis.

BACKGROUND: Mortality in cancer patients is directly attributable to the ability of cancer cells to metastasize to distant sites from the primary tumor. This migration of tumor cells begins with a remodeling of the local tumor microenvironment, including changes to the extracellular matrix and the recruitment of stromal cells, both of which facilitate invasion of tumor cells into the bloodstream. In breast cancer, it has been proposed that the alignment of collagen fibers surrounding tumor epithelial cells can serve as a quantitative image-based biomarker for survival of invasive ductal carcinoma patients. Specific types of collagen alignment have been identified for their prognostic value and now these tumor associated collagen signatures (TACS) are central to several clinical specimen imaging trials. Here, we implement the semi-automated acquisition and analysis of this TACS candidate biomarker and demonstrate a protocol that will allow consistent scoring to be performed throughout large patient cohorts. METHODS: Using large field of view high resolution microscopy techniques, image processing and supervised learning methods, we are able to quantify and score features of collagen fiber alignment with respect to adjacent tumor-stromal boundaries. RESULTS: Our semi-automated technique produced scores that have statistically significant correlation with scores generated by a panel of three human observers. In addition, our system generated classification scores that accurately predicted survival in a cohort of 196 breast cancer patients. Feature rank analysis reveals that TACS positive fibers are more well-aligned with each other, are of generally lower density, and terminate within or near groups of epithelial cells at larger angles of interaction. CONCLUSION: These results demonstrate the utility of a supervised learning protocol for streamlining the analysis of collagen alignment with respect to tumor stromal boundaries.

Computational segmentation of collagen fibers from second-harmonic generation images of breast cancer.

Second-harmonic generation (SHG) imaging can help reveal interactions between collagen fibers and cancer cells. Quantitative analysis of SHG images of collagen fibers is challenged by the heterogeneity of collagen structures and low signal-to-noise ratio often found while imaging collagen in tissue. The role of collagen in breast cancer progression can be assessed post acquisition via enhanced computation. To facilitate this, we have implemented and evaluated four algorithms for extracting fiber information, such as number, length, and curvature, from a variety of SHG images of collagen in breast tissue. The image-processing algorithms included a Gaussian filter, SPIRAL-TV filter, Tubeness filter, and curvelet-denoising filter. Fibers are then extracted using an automated tracking algorithm called fiber extraction (FIRE). We evaluated the algorithm performance by comparing length, angle and position of the automatically extracted fibers with those of manually extracted fibers in twenty-five SHG images of breast cancer. We found that the curvelet-denoising filter followed by FIRE, a process we call CT-FIRE, outperforms the other algorithms under investigation. CT-FIRE was then successfully applied to track collagen fiber shape changes over time in an in vivo mouse model for breast cancer.

Texture analysis applied to second harmonic generation image data for ovarian cancer classification.

Remodeling of the extracellular matrix has been implicated in ovarian cancer. To quantitate the remodeling, we implement a form of texture analysis to delineate the collagen fibrillar morphology observed in second harmonic generation microscopy images of human normal and high grade malignant ovarian tissues. In the learning stage, a dictionary of "textons"­frequently occurring texture features that are identified by measuring the image response to a filter bank of various shapes, sizes, and orientations­is created. By calculating a representative model based on the texton distribution for each tissue type using a training set of respective second harmonic generation images, we then perform classification between images of normal and high grade malignant ovarian tissues. By optimizing the number of textons and nearest neighbors, we achieved classification accuracy up to 97% based on the area under receiver operating characteristic curves (true positives versus false positives). The local analysis algorithm is a more general method to probe rapidly changing fibrillar morphologies than global analyses such as FFT. It is also more versatile than other texture approaches as the filter bank can be highly tailored to specific applications (e.g., different disease states) by creating customized libraries based on common image features.

A generalized 2D pencil beam scaling algorithm for proton dose calculation in heterogeneous slab geometries.

PURPOSE: Pencil beam algorithms are commonly used for proton therapy dose calculations. Szymanowski and Oelfke ["Two-dimensional pencil beam scaling: An improved proton dose algorithm for heterogeneous media," Phys. Med. Biol. 47, 3313-3330 (2002)] developed a two-dimensional (2D) scaling algorithm which accurately models the radial pencil beam width as a function of depth in heterogeneous slab geometries using a scaled expression for the radial kernel width in water as a function of depth and kinetic energy. However, an assumption made in the derivation of the technique limits its range of validity to cases where the input expression for the radial kernel width in water is derived from a local scattering power model. The goal of this work is to derive a generalized form of 2D pencil beam scaling that is independent of the scattering power model and appropriate for use with any expression for the radial kernel width in water as a function of depth. METHODS: Using Fermi-Eyges transport theory, the authors derive an expression for the radial pencil beam width in heterogeneous slab geometries which is independent of the proton scattering power and related quantities. The authors then perform test calculations in homogeneous and heterogeneous slab phantoms using both the original 2D scaling model and the new model with expressions for the radial kernel width in water computed from both local and nonlocal scattering power models, as well as a nonlocal parameterization of Molière scattering theory. In addition to kernel width calculations, dose calculations are also performed for a narrow Gaussian proton beam. RESULTS: Pencil beam width calculations indicate that both 2D scaling formalisms perform well when the radial kernel width in water is derived from a local scattering power model. Computing the radial kernel width from a nonlocal scattering model results in the local 2D scaling formula under-predicting the pencil beam width by as much as 1.4 mm (21%) at the depth of the Bragg peak for a 220 MeV proton beam in homogeneous water. This translates into a 32% dose discrepancy for a 5 mm Gaussian proton beam. Similar trends were observed for calculations made in heterogeneous slab phantoms where it was also noted that errors tend to increase with greater beam penetration. The generalized 2D scaling model performs well in all situations, with a maximum dose error of 0.3% at the Bragg peak in a heterogeneous phantom containing 3 cm of hard bone. CONCLUSIONS: The authors have derived a generalized form of 2D pencil beam scaling which is independent of the proton scattering power model and robust to the functional form of the radial kernel width in water used for the calculations. Sample calculations made with this model show excellent agreement with expected values in both homogeneous water and heterogeneous phantoms.

Investigation of probabilistic optimization for tomotherapy.

This work builds on a suite of studies related to the 'interplay', or lack thereof, for respiratory motion with helical tomotherapy (HT). It helps explain why HT treatments without active motion management had clinical outcomes that matched positive expectations. An analytical calculation is performed to illuminate the frequency range for which interplay-type dose errors could occur. Then, an experiment is performed which completes a suite of tests. The experiment shows the potential for a stable motion probability distribution function (PDF) with HT and respiratory motion. This PDF enables one to use a motion-robust or probabilistic optimization to intrinsically include respiratory motion into the treatment planning. The reason why HT is robust to respiratory motion is related to the beam modulation sampling of the tumor motion. Because active tracking-based motion management is more complicated for a variety of reasons, HT optimization that is robust to motion is a useful alternative for those many patients that cannot benefit from active motion management.

Maximum kinetic energy considerations in proton stereotactic radiosurgery.

The purpose of this study was to determine the maximum proton kinetic energy required to treat a given percentage of patients eligible for stereotactic radiosurgery (SRS) with coplanar arc-based proton therapy, contingent upon the number and location of gantry angles used. Treatment plans from 100 consecutive patients treated with SRS at the University of Wisconsin Carbone Cancer Center between June of 2007 and March of 2010 were analyzed. For each target volume within each patient, in-house software was used to place proton pencil beam spots over the distal surface of the target volume from 51 equally-spaced gantry angles of up to 360°. For each beam spot, the radiological path length from the surface of the patient to the distal boundary of the target was then calculated along a ray from the gantry location to the location of the beam spot. This data was used to generate a maximum proton energy requirement for each patient as a function of the arc length that would be spanned by the gantry angles used in a given treatment. If only a single treatment angle is required, 100% of the patients included in the study could be treated by a proton beam with a maximum kinetic energy of 118 MeV. As the length of the treatment arc is increased to 90°, 180°, 270°, and 360°, the maximum energy requirement increases to 127, 145, 156, and 179 MeV, respectively. A very high percentage of SRS patients could be treated at relatively low proton energies if the gantry angles used in the treatment plan do not span a large treatment arc. Maximum proton kinetic energy requirements increase linearly with size of the treatment arc.

Estimated radiation pneumonitis risk after photon versus proton therapy alone or combined with chemotherapy for lung cancer.

BACKGROUND: Traditionally, radiation therapy plans are optimized without consideration of chemotherapy. Here, we model the risk of radiation pneumonitis (RP) in the presence of a possible interaction between chemotherapy and radiation dose distribution. MATERIAL AND METHODS: Three alternative treatment plans are compared in 18 non-small cell lung cancer patients previously treated with helical tomotherapy; the tomotherapy plan, an intensity modulated proton therapy plan (IMPT) and a three dimensional conformal radiotherapy (3D-CRT) plan. All plans are optimized without consideration of the chemotherapy effect. The effect of chemotherapy is modeled as an independent cell killing process using a uniform chemotherapy equivalent radiation dose (CERD) added to the entire organ at risk. We estimate the risk of grade 3 or higher RP (G3RP) using the critical volume model. RESULTS: The mean risk of clinical G3RP at zero CERD is 5% for tomotherapy (range: 1-18 %) and 14% for 3D-CRT (range 2-49%). When the CERD exceeds 9 Gy, however, the risk of RP with the tomotherapy plans become higher than the 3D-CRT plans. The IMPT plans are less toxic both at zero CERD (mean 2%, range 1-5%) and at CERD = 10 Gy (mean 7%, range 1-28%). Tomotherapy yields a lower risk of RP than 3D-CRT for 17/18 patients at zero CERD, but only for 7/18 patients at CERD = 10 Gy. IMPT gives the lowest risk of all plans for 17/18 patients at zero CERD and for all patients with CERD = 10 Gy. CONCLUSIONS: The low dose bath from highly conformal photon techniques may become relevant for lung toxicity when radiation is combined with cytotoxic chemotherapy as shown here. Proton therapy allows highly conformal delivery while minimizing the low dose bath potentially interacting with chemotherapy. Thus, intensive drug-radiation combinations could be an interesting indication for selecting patients for proton therapy. It is likely that the IMRT plans would perform better if the CERD was accounted for during optimization, but more clinical data is required to facilitate evidence-based plan optimization in the multi-modality setting.

Intensity-modulated radiotherapy might increase pneumonitis risk relative to three-dimensional conformal radiotherapy in patients receiving combined chemotherapy and radiotherapy: a modeling study of dose dumping.

PURPOSE: To model the possible interaction between cytotoxic chemotherapy and the radiation dose distribution with respect to the risk of radiation pneumonitis. METHODS AND MATERIALS: A total of 18 non-small-cell lung cancer patients previously treated with helical tomotherapy at the University of Wisconsin were selected for the present modeling study. Three treatment plans were considered: the delivered tomotherapy plans; a three-dimensional conformal radiotherapy (3D-CRT) plan; and a fixed-field intensity-modulated radiotherapy (IMRT) plan. The IMRT and 3D-CRT plans were generated specifically for the present study. The plans were optimized without adjusting for the chemotherapy effect. The effect of chemotherapy was modeled as an independent cell killing process by considering a uniform chemotherapy equivalent radiation dose added to all voxels of the organ at risk. The risk of radiation pneumonitis was estimated for all plans using the Lyman and the critical volume models. RESULTS: For radiotherapy alone, the critical volume model predicts that the two IMRT plans are associated with a lower risk of radiation pneumonitis than the 3D-CRT plan. However, when the chemotherapy equivalent radiation dose exceeds a certain threshold, the radiation pneumonitis risk after IMRT is greater than after 3D-CRT. This threshold dose is in the range estimated from clinical chemoradiotherapy data sets. CONCLUSIONS: Cytotoxic chemotherapy might affect the relative merit of competing radiotherapy plans. More work is needed to improve our understanding of the interaction between chemotherapy and the radiation dose distribution in clinical settings.

A phantom model demonstration of tomotherapy dose painting delivery, including managed respiratory motion without motion management.

The aim of the study was to demonstrate a potential alternative scenario for accurate dose-painting (non-homogeneous planned dose) delivery at 1 cm beam width with helical tomotherapy (HT) in the presence of 1 cm, three-dimensional, intra-fraction respiratory motion, but without any active motion management. A model dose-painting experiment was planned and delivered to the average position (proper phase of a 4DCT scan) with three spherical PTV levels to approximate dose painting to compensate for hypothetical hypoxia in a model lung tumor. Realistic but regular motion was produced with the Washington University 4D Motion Phantom. A small spherical Virtual Water phantom was used to simulate a moving lung tumor inside of the LUNGMAN anthropomorphic chest phantom to simulate realistic heterogeneity uncertainties. A piece of 4 cm Gafchromic EBT film was inserted into the 6 cm diameter sphere. TomoTherapy, Inc., DQA software was used to verify the delivery performed on a TomoTherapy Hi-Art II device. The dose uncertainty in the purposeful absence of motion management and in the absence of large, low frequency drifts (periods greater than the beam width divided by the couch velocity) or randomness in the breathing displacement yields very favorable results. Instead of interference effects, only small blurring is observed because of the averaging of many breathing cycles and beamlets and the avoidance of interference. Dose painting during respiration with helical tomotherapy is feasible in certain situations without motion management. A simple recommendation is to make respiration as regular as possible without low frequency drifting. The blurring is just small enough to suggest that it may be acceptable to deliver without motion management if the motion is equal to the beam width or smaller (at respiration frequencies) when registered to the average position.

Dosimetric impact of daily setup variations during treatment of canine nasal tumors using intensity-modulated radiation therapy.

Intensity-modulated radiation therapy (IMRT) can be employed to yield precise dose distributions that tightly conform to targets and reduce high doses to normal structures by generating steep dose gradients. Because of these sharp gradients, daily setup variations may have an adverse effect on clinical outcome such that an adjacent normal structure may be overdosed and/or the target may be underdosed. This study provides a detailed analysis of the impact of daily setup variations on optimized IMRT canine nasal tumor treatment plans when variations are not accounted for due to the lack of image guidance. Setup histories of ten patients with nasal tumors previously treated using helical tomotherapy were replanned retrospectively to study the impact of daily setup variations on IMRT dose distributions. Daily setup shifts were applied to IMRT plans on a fraction-by-fraction basis. Using mattress immobilization and laser alignment, mean setup error magnitude in any single dimension was at least 2.5 mm (0-10.0 mm). With inclusions of all three translational coordinates, mean composite offset vector was 5.9 +/- 3.3 mm. Due to variations, a loss of equivalent uniform dose for target volumes of up to 5.6% was noted which corresponded to a potential loss in tumor control probability of 39.5%. Overdosing of eyes and brain was noted by increases in mean normalized total dose and highest normalized dose given to 2% of the volume. Findings suggest that successful implementation of canine nasal IMRT requires daily image guidance to ensure accurate delivery of precise IMRT distributions when non-rigid immobilization techniques are utilized. Unrecognized geographical misses may result in tumor recurrence and/or radiation toxicities to the eyes and brain.

Monte Carlo-based analytical model for small and variable fields delivered by TomoTherapy.

BACKGROUND AND PURPOSE: Extend to very small fields the validity of a Monte Carlo (MC) based model of TomoTherapy called TomoPen for future implementation of the dynamic jaws feature for helical TomoTherapy. MATERIALS AND METHODS: First, the modelling of the electron source was revisited using a new method to measure source obscuration for very small fields (<1cm). The method consisted in MC simulations simulations and measurements of the central dose in a water phantom for a 10 cm x FW field scanned to deliver a 10 x 10 cm(2) fluence. FW, the longitudinal field width, was varied from 0.4 to 5 cm. The second part of the work consisted of adapting TomoPen to account for any configuration of the jaws in a fast and efficient way by using routinely only the phase-space file of the largest field (5 cm) and interpolated analytical information of phase-space files of smaller field widths. RESULTS: For the electron source fine tuning, it was shown that the best results were obtained for a 1.1mm wide spot. Our single phase-space method showed no significant differences compared to MC simulations of various field widths even though only longitudinal intensity and angular analytical functions were applied to the 5 cm phase-space. CONCLUSION: The designed model is able to simulate all jaw openings from the 5 cm field phase-space file by applying a bi-dimensional analytical function accounting for the fluence and the angular distribution in the longitudinal direction.

Treatment planning to improve delivery accuracy and patient throughput in helical tomotherapy.

PURPOSE: To investigate delivery quality assurance (DQA) discrepancies observed for a subset of helical tomotherapy patients. METHODS AND MATERIALS: Six tomotherapy patient plans were selected for analysis. Three had passing DQA ion chamber (IC) measurements, whereas 3 had measurements deviating from the expected dose by more than 3.0%. All plans used similar parameters, including: 2.5 cm field-width, 15-s gantry period, and pitch values ranging from 0.143 to 0.215. Preliminary analysis suggested discrepancies were associated with plans having predominantly small leaf open times (LOTs). To test this, patients with failing DQA measurements were replanned using an increased pitch of 0.287. New DQA plans were generated and IC measurements performed. Exit fluence data were also collected during DQA delivery for dose reconstruction purposes. RESULTS: Sinogram analysis showed increases in mean LOTs ranging from 29.8% to 83.1% for the increased pitch replans. IC measurements for these plans showed a reduction in dose discrepancies, bringing all measurements within +/-3.0%. The replans were also more efficient to deliver, resulting in reduced treatment times. Dose reconstruction results were in excellent agreement with IC measurements, illustrating the impact of leaf-timing inaccuracies on plans having predominantly small LOTs. CONCLUSIONS: The impact of leaf-timing inaccuracies on plans with small mean LOTs can be considerable. These inaccuracies result from deviations in multileaf collimator latency from the linear approximation used by the treatment planning system and can be important for plans having a 15-s gantry period. The ability to reduce this effect while improving delivery efficiency by increasing the pitch is demonstrated.

A comprehensive assessment by tumor site of patient setup using daily MVCT imaging from more than 3,800 helical tomotherapy treatments.

PURPOSE: To assess patient setup corrections based on daily megavoltage CT (MVCT) imaging for four anatomic treatment sites treated on tomotherapy. METHOD AND MATERIALS: Translational and rotational setup corrections, based on registration of daily MVCT to planning CT images, were analyzed for 1,179 brain and head and neck (H&N), 1,414 lung, and 1,274 prostate treatment fractions. Frequencies of three-dimensional vector lengths, overall distributions of setup corrections, and patient-specific distributions of random and systematic setup errors were analyzed. RESULTS: Brain and H&N had lower magnitude positioning corrections and smaller variations in translational setup errors but were comparable in roll rotations. Three-dimensional vector translational shifts of larger magnitudes occurred more frequently for lung and prostate than for brain and H&N treatments, yet this was not observed for roll rotations. The global systematic error for prostate was 4.7 mm in the vertical direction, most likely due to couch sag caused by large couch extension distances. Variations in systematic errors and magnitudes of random translational errors ranged from 1.6 to 2.6 mm for brain and H&N and 3.2 to 7.2 mm for lung and prostate, whereas roll rotational errors ranged from 0.8 degrees to 1.2 degrees for brain and H&N and 0.5 degrees to 1.0 degrees for lung and prostate. CONCLUSIONS: Differences in setup were observed between brain, H&N, lung, and prostate treatments. Patient setup can be improved if daily imaging is performed. This analysis can assess the utilization of daily image guidance and allows for further investigation into improved anatomic site-specific and patient-specific treatments.

On the impact of longitudinal breathing motion randomness for tomotherapy delivery.

The purpose of this study is to explain the unplanned longitudinal dose modulations that appear in helical tomotherapy (HT) dose distributions in the presence of irregular patient breathing. This explanation is developed by the use of longitudinal (1D) simulations of mock and surrogate data and tested with a fully 4D HT delivered plan. The 1D simulations use a typical mock breathing function which allows more flexibility to adjust various parameters. These simplified simulations are then made more realistic by using 100 surrogate waveforms all similarly scaled to produce longitudinal breathing displacements. The results include the observation that, with many waveforms used simultaneously, a voxel-by-voxel probability of a dose error from breathing is found to be proportional to the realistically random breathing amplitude relative to the beam width if the PTV is larger than the beam width and the breathing displacement amplitude. The 4D experimental test confirms that regular breathing will not result in these modulations because of the insensitivity to leaf motion for low-frequency dynamics such as breathing. These modulations mostly result from a varying average of the breathing displacements along the beam edge gradients. Regular breathing has no displacement variation over many breathing cycles. Some low-frequency interference is also possible in real situations. In the absence of more sophisticated motion management, methods that reduce the breathing amplitude or make the breathing very regular are indicated. However, for typical breathing patterns and magnitudes, motion management techniques may not be required with HT because typical breathing occurs mostly between fundamental HT treatment temporal and spatial scales. A movement beyond only discussing margins is encouraged for intensity modulated radiotherapy such that patient and machine motion interference will be minimized and beneficial averaging maximized. These results are found for homogeneous and longitudinal on-axis delivery for unplanned longitudinal dose modulations.

Radiobiological and treatment planning study of a simultaneously integrated boost for canine nasal tumors using helical tomotherapy.

Feasibility of delivering a simultaneously integrated boost to canine nasal tumors using helical tomotherapy to improve tumor control probability (TCP) via an increase in total biological equivalent uniform dose (EUD) was evaluated. Eight dogs with varying size nasal tumors (5.8-110.9 cc) were replanned to 42 Gy to the nasal cavity and integrated dose boosts to gross disease of 45.2, 48.3, and 51.3 Gy in 10 fractions. EUD values were calculated for tumors and mean normalized total doses (NTD(mean)) for organs at risk (OAR). Normal Tissue Complication Probability (NTCP) values were obtained for OARs, and estimated TCP values were computed using a logistic dose-response model and based on deliverable EUD boost doses. Significant increases in estimated TCP to 54%, 74%, and 86% can be achieved with 10%, 23%, and 37% mean relative EUD boosts to the gross disease, respectively. NTCP values for blindness of either eye and for brain necrosis were < 0.01% for all boosts. Values for cataract development were 31%, 42%, and 46% for studied boost schemas, respectively. Average NTD(mean) to eyes and brain for mean EUD boosts were 10.2, 11.3, and 12.1 Gy3, and 7.5, 7.2, and 7.9 Gy2, respectively. Using helical tomotherapy, simultaneously integrated dose boosts can be delivered to increase the estimated TCP at 1-year without significantly increasing the NTD(mean) to eyes and brain. Delivery of these treatments in a prospective trial may allow quantification of a dose-response relationship in canine nasal tumors.

Whole brain radiotherapy with hippocampal avoidance and simultaneously integrated brain metastases boost: a planning study.

PURPOSE: To evaluate the feasibility of using tomotherapy to deliver whole brain radiotherapy with hippocampal avoidance, hypothesized to reduce the risk of memory function decline, and simultaneously integrated boost to brain metastases to improve intracranial tumor control. METHODS AND MATERIALS: Ten patients treated with radiosurgery and whole brain radiotherapy underwent repeat planning using tomotherapy with the original computed tomography scans and magnetic resonance imaging-computed tomography fusion-defined target and normal structure contours. The individually contoured hippocampus was used as a dose-limiting structure (<6 Gy); the whole brain dose was prescribed at 32.25 Gy to 95% in 15 fractions, and the simultaneous boost doses to individual brain metastases were 63 Gy to lesions >or=2.0 cm in the maximal diameter and 70.8 Gy to lesions <2.0 cm. The plans were generated with a field width (FW) of 2.5 cm and, in 5 patients, with a FW of 1.0 cm. The plans were compared regarding conformation number, prescription isodose/target volume ratio, target coverage, homogeneity index, and mean normalized total dose. RESULTS: A 1.0-cm FW compared with a 2.5-cm FW significantly improved the dose distribution. The mean conformation number improved from 0.55 +/- 0.16 to 0.60 +/- 0.13. Whole brain homogeneity improved by 32% (p <0.001). The mean normalized total dose to the hippocampus was 5.9 +/- 1.3 Gy(2) and 5.8 +/- 1.9 Gy(2) for 2.5- and 1.0-cm FW, respectively. The mean treatment delivery time for the 2.5- and 1.0-cm FW plans was 10.2 +/- 1.0 and 21.8 +/- 1.8 min, respectively. CONCLUSION: Composite tomotherapy plans achieved three objectives: homogeneous whole brain dose distribution equivalent to conventional whole brain radiotherapy; conformal hippocampal avoidance; and radiosurgically equivalent dose distributions to individual metastases.