Linda J. Brewster
Memorial Sloan Kettering Cancer Center
Network
Latest external collaboration on country level. Dive into details by clicking on the dots.
Publication
Featured researches published by Linda J. Brewster.
International Journal of Radiation Oncology Biology Physics | 1991
G.J. Kutcher; C Burman; Linda J. Brewster; Michael Goitein; Radhe Mohan
New tools are needed to help in evaluating 3-D treatment plans because of the large volume of data. One technique which may prove useful is the application of complication probability calculations. A method of calculating complication probabilities for inhomogeneously irradiated normal tissues is presented in this paper. The method uses clinical estimates of tolerance doses for a few discreet conditions of uniform partial organ irradiation, an empirical fit of a continuous function to these data, and a technique (the effective volume method) for transforming nonuniform dose-volume histograms into equivalent uniform histograms. The behavior of the effective volume histogram reduction method for various boundary conditions is reviewed. The use of complication probabilities in evaluating treatment plans is presented, using examples from an NCI 3-D treatment planning contract.
International Journal of Radiation Oncology Biology Physics | 1991
Robert E. Drzymala; Radhe Mohan; Linda J. Brewster; James C.H. Chu; Michael Goitein; William B. Harms; M. Urie
A plot of a cumulative dose-volume frequency distribution, commonly known as a dose-volume histogram (DVH), graphically summarizes the simulated radiation distribution within a volume of interest of a patient which would result from a proposed radiation treatment plan. DVHs show promise as tools for comparing rival treatment plans for a specific patient by clearly presenting the uniformity of dose in the target volume and any hot spots in adjacent normal organs or tissues. However, because of the loss of positional information in the volume(s) under consideration, it should not be the sole criterion for plan evaluation. DVHs can also be used as input data to estimate tumor control probability (TCP) and normal tissue complication probability (NTCP). The sensitivity of TCP and NTCP calculations to small changes in the DVH shape points to the need for an accurate method for computing DVHs. We present a discussion of the methodology for generating and plotting the DVHs, some caveats, limitations on their use and the general experience of four hospitals using DVHs.
International Journal of Radiation Oncology Biology Physics | 1988
Radhe Mohan; Glenn D. Barest; Linda J. Brewster; Chen S. Chui; Gerald J. Kutcher; John S. Laughlin; Zvi Fuks
A comprehensive software system has been developed to allow 3-dimensional planning of radiation therapy treatments using the extensive anatomical information made available by imaging modalities such as CT and MR. Biological structures of interest and tumor volumes are defined by outlines drawn on a sequence of CT slices. Beam set-ups may then be determined in three dimensions by displaying the structure contours in a beams eye view, or in two dimensions using a single CT cut. Each beam defined may be shaped by the specification of block aperture contours, and its intensity may be modified with the use of planar compensators. 3D dose calculation algorithms are discussed. To evaluate the calculation results, dose volume histograms are provided, as well as various types of displays in two and three dimensions, including dose on arbitrarily oriented planes, dose on the surface of anatomical objects, and isodose surfaces. Computer generated beam films are also available as an aid in patient set-up verification. These tools, and others, provide the basis for a comprehensive 3D system that can be used throughout the treatment planning process.
International Journal of Radiation Oncology Biology Physics | 1991
Steven A. Leibel; Gerald J. Kutcher; Louis B. Harrison; Daniel E. Fass; C Burman; Margie Hunt; Radhe Mohan; Linda J. Brewster; C. Clifton Ling; Zvi Fuks
This study was designed to demonstrate the feasibility of 3-dimensional (3D) treatment planning in patients with carcinoma of the nasopharynx, and to explore its potential therapeutic advantage over the traditional 2-dimensional (2D) approach in this disease. Qualitative and quantitative comparisons between the two techniques were made for the boost portion of the treatment (19.8 Gy of a total 70.2 Gy treatment schedule) in 10 previously untreated patients and for the entire treatment in 5 patients with locally recurrent disease. The 2D and 3D plans were compared in each patient using dose-volume histograms (DVHs), tumor control probabilities (TCPs), normal tissue complication probabilities (NTCPs), and a new biologic figure of merit that describes the probability of uncomplicated control. Although there was no attempt to optimize the 3D treatment approach by using this method throughout the total treatment course (rather than for the boost only), it was still found that for each of the endpoints examined the 3D approach resulted in improved plans. An average of 22% of the target volume was underdosed at the 95% isodose level with the 2D plans compared to 7% with the 3D plans. The improved treatment planning by 3D increased the mean dose to the tumor volume by an average of 13% over 2D planning. The dose to normal structures such as the mandible and parotid glands was reduced with the 3D plans while the brain stem and spinal cord remained within tolerance limits. The probability of uncomplicated tumor control was increased by an average of 15% with 3D treatment planning compared to the 2D approach. Our findings demonstrate the potential of 3D planning for improving the treatment of carcinoma of the nasopharynx, but prospective studies are required to define the true clinical advantages of this methodology.
International Journal of Radiation Oncology Biology Physics | 1991
Lawrence J. Solin; James C.H. Chu; Marc R. Sontag; Linda J. Brewster; E. Cheng; Karen P. Doppke; Robert E. Drzymala; Margie Hunt; Robert R. Kuske; J.M. Manolis; Beryl McCormick; John E. Munzenrider
Three-dimensional treatment planning for the intact breast was performed on two patients who had undergone CT scanning. A total of 38 treatment plans were evaluated. Multiple plans were evaluated for each patient including plans with and without inhomogeneity corrections, plans using varying photon energies of 60Co, 4 MV, 6 MV, 10 MV, and 15 MV, and three-dimensionally unconstrained plans. Increased hot spots were appreciated in the central axis plane when lung inhomogeneity corrections were used. Additional hot spots were appreciated in off-axis planes towards the cephalad and caudad aspects of the target volume because of lung inhomogeneity corrections and changes in the breast contour. The use of 60Co was associated with an increase in the magnitude and volume of hot spots, whereas the use of higher energy photons such as 10 MV and 15 MV was associated with an unacceptable target coverage at shallow depths. Therefore, for the two patients studied, the use of a medium energy photon beam (such as from a 6 MV linear accelerator) appeared to be the energy of choice for treatment of the intact breast. The three-dimensionally unconstrained plans were able to improve slightly upon the standard plans, particularly with relationship of dose to normal tissue structures. Areas for future research were identified, including the use of tissue compensators.
IEEE Computer Graphics and Applications | 1984
Linda J. Brewster; Sushma S. Trivedi; Heang K. Tuy; Jayaram K. Udupa
With this tool for visualizing and manipulating organ images in three dimensions, surgeons can plan and test their strategies before they get to the operating room.
International Journal of Radiation Oncology Biology Physics | 1994
G Mageras; Zvi Fuks; James P. O'Brien; Linda J. Brewster; C Burman; Chen-Shou Chui; Steven A. Leibel; C.C. Ling; M. E. Masterson; Radhe Mohan; G.J. Kutcher
PURPOSE We have described previously a model for delivering computer-controlled radiation treatments. We report here on the implementation and first years clinical experience with such treatments using a 50 MeV medical microtron. METHODS AND MATERIALS The microtron is equipped with a multileaf collimator and is capable of setting up and treating a sequence of fixed fields called segments, under computer control. An external computer derives machine parameters for the segments from a three-dimensional treatment planning system, transfers them to the microtron control computer, checks the machine settings before allowing dose delivery to begin, and records the treatment. We describe the patient treatment methodology, portal film acquisition, electronic portal imaging, and quality assurance. RESULTS Patient treatments began in July 1992, comprising six-segment conformal treatments of the prostate. Using the recorded treatment data, the system performance has been examined and compared to other treatment machines. The average treatment time is 10 min, of which 4 min is for computer-controlled setup and irradiation; the remaining time is for patient positioning and checking of clearances. Long-term reproducibility of computer-controlled setup of the gantry and multileaf position is better than 0.5 degrees and 1 mm, respectively. Termination due to a machine fault has occurred in 5.5% of treatments, improving to 2.5% in recent months. CONCLUSION Our initial experience indicates that computer-controlled segmental therapy can be performed reliably on a routine basis. Treatment times with the microtron are significantly shorter than with conventional linacs, and setup accuracy is consistent with that needed for conformal therapy. We believe that treatment times can be further improved through software upgrades and integration of electronic portal imaging.
Medical Physics | 1993
Linda J. Brewster; G Mageras; Radhe Mohan
In order to specify arbitrarily shaped beam apertures for three-dimensional radiation treatment planning, aperture contours (or outlines) are often manually drawn using a beams eye view display of the target volume and nearby normal structures. This can be a very time consuming process, and can be impractical for multileaf collimation and computer-aided optimization of a large number of fields. A method has been developed that allows automatic generation of aperture shapes that outline the target volume and may spare neighboring structures whenever desired. Margins of user-specified sizes (positive or negative) around the target and normal structures are also incorporated. For a chosen beam orientation, a 3D surface of each anatomic structure of interest is formed and projected onto a plane at the beams isocenter. The outlines of each projected object are detected by an edge following algorithm, and margins are added. The outlines of normal structures are combined with that of the target volume to obtain the final aperture shape. This is done by overlaying filled versions of the outlines in such a way that regions of the target overlapped by normal structures are cut away, leaving only the target volume region to be irradiated. The remaining target volume outline is again detected to produce an aperture contour. Normal structures may split the aperture into several pieces, so this method detects any number of disjoint aperture contours. The results of the algorithm are illustrated with apertures generated for nasopharynx and prostate tumors, including sparing of normal tissues.
International Journal of Radiation Oncology Biology Physics | 1991
Brenda Shank; Thomas LoSasso; Linda J. Brewster; C Burman; E. Cheng; James C.H. Chu; Robert E. Drzymala; J.M. Manolis; Miljenko V. Pilepich; Lawrence J. Solin; Joel E. Tepper; Marcia Urie
The role of three-dimensional (3-D) treatment planning for postoperative radiation therapy was evaluated for rectal carcinoma as part of an NCI contract awarded to four institutions. It was found that the most important contribution of 3-D planning for this site was the ability to plan and localize target and normal tissues at all levels of the treatment volume, rather than using the traditional method of planning with only a single central transverse slice and simulation films. There was also a slight additional improvement when there were no constraints on the types of plans (i.e., when noncoplanar beams were used). Inhomogeneity considerations were not important at this site under the conditions of planning, i.e., with energies greater than 4 MV and multiple fields. Higher beam energies (15-25 MV) were preferred by a small margin over lower energies (down to 4 MV). The beams eye view and dose-volume histograms were found quite useful as planning tools, but it was clear that work should continue on better 3-D displays and improved means of translating such plans to the treatment area.
Medical Physics | 1987
Radhe Mohan; Linda J. Brewster; Glenn D. Barest
Graphical displays of three-dimensional dose distribution data are often too complex to be easily assimilated and interpreted for the evaluation of radiation treatment plans. Histograms showing dose versus volume are convenient and useful tools for summarizing dose distribution information throughout the entire volume of a given anatomic structure. They can quickly highlight characteristics such as dose uniformity and hot and cold spots, and can be used to produce statistics including tumor control and normal tissue complication probabilities. To obtain a dose volume histogram for a given structure, it may be necessary to examine its spatial relationships with neighboring structures. They may overlap, be completely disjoint, or one may be contained within another. To resolve potential ambiguities, a procedure has been developed that assigns hierarchies to anatomical structures for the purpose of histogram calculation. The hierarchy assigned to each structure is used to determine the structure within which a given dose matrix point is considered to lie. In this manner, regions of structure intersection are assigned to one object or another, and dose volume histograms can be calculated for each structure separately. From this framework, addition and subtraction of histograms can also be performed. Details of the algorithm are presented along with an example using patient data.